The human sense of smell serves a variety of important functions in everyday life (Bushdid et al., 2014; Devanand et al., 2015; McGann, 2017). It is used to monitor the safety of inhaled air (Pence et al., 2014) and edibility of food (Yeomans, 2006). It also strongly impacts our social and emotional lives (Durand et al., 2013; Endevelt-Shapira et al., 2018; Frumin et al., 2015; Gelstein et al., 2011; Krusemark et al., 2013; Walla, 2008; Walla et al., 2003). Thus, the brain must extract different types of information from odor stimuli, including information about the identities of objects and foods, environmental hazards, and social and emotional cues. These functions are likely carried out by distinct cortical networks within the olfactory system, yet the organization of these functional networks is not fully understood.

This incomplete understanding is due partly to ambiguity about the anatomical and functional properties of the cortical targets of human olfactory bulb projections. Collectively, these areas are commonly referred to as primary olfactory cortex (Carmichael et al., 1994; Feher and Feher, 2017; Gottfried, 2010; Mai and Paxinos, 2012; Price, 2009) (although see Wilson, 2009; Haberly, 2001; Chapuis and Wilson, 2011 and others for discussions of the accuracy of this definition of the pirmary olfactory cortex). In humans, this includes the anterior olfactory nucleus, the olfactory tubercle, the frontal and temporal piriform cortices, and subregions of both the amygdala and entorhinal cortex (Allison, 1954; Eslinger et al., 1982; Gonçalves Pereira et al., 2005; Insausti et al., 2002; Milardi et al., 2017). The fact that the olfactory bulb simultaneously projects directly to a number of structures suggests parallel functional pathways in the olfactory system (Haberly, 2001; Kauer, 1991), but the distinct roles of these primary olfactory areas and their functional pathways are not fully understood (Bensafi et al., 2007; Gottfried et al., 2006; Gottfried et al., 2004; Gottfried et al., 2002; Howard et al., 2009; Li et al., 2008; Li et al., 2006; Sobel et al., 2000; Sobel et al., 1999; Zelano et al., 2005). Additionally, the olfactory system is organized differently than other sensory systems, which contain pre-cortical thalamic relays, further suggesting a deeper understanding of the organization of olfactory networks in the human brain is warranted.

The vast majority of research on primary olfactory cortex has focused on piriform cortex, which is the largest recipient of bulbar projections. Most of this research has been conducted in rodents, where piriform cortex is divided into anatomically and functionally distinct anterior and posterior subdivisions (Calu et al., 2007; Grau-Perales et al., 2019; Haberly and Price, 1978; Stettler and Axel, 2009; Yang et al., 2017). In humans, the anatomy and functionality of piriform cortex is less understood. Although it can be divided into frontal- and temporal-lobe subregions (Mai et al., 2015; Vaughan and Jackson, 2014; Young et al., 2018; Allison, 1954), whether these correspond to rodent anterior and posterior subdivisions is unclear. While neuroimaging studies have pointed to functional heterogeneity within human piriform cortex (Bensafi, 2012; Fournel et al., 2016; Gottfried et al., 2002; Howard et al., 2009; Howard and Gottfried, 2014; Li et al., 2008; Porter et al., 2005; Seubert et al., 2013; Zelano et al., 2011; Zelano et al., 2005), its anatomical and functional distinctions are still not clearly defined.

While numerous rodent and human studies have focused on piriform cortex, far fewer have examined other primary olfactory structures, such as the anterior olfactory nucleus and the olfactory tubercle. These structures have been anatomically well-defined in rodents (Aqrabawi and Kim, 2018a; Haberly and Price, 1978; Shipley and Adamek, 1984), primates (Carmichael et al., 1994), and humans (Allison, 1954; Eslinger et al., 1982; Mai et al., 2015), but their roles in olfactory processing are not fully understood in any of these species (Gadziola et al., 2015; Wesson and Wilson, 2011). Recent rodent data suggest that the anterior olfactory nucleus may be involved in odor memory (Aqrabawi and Kim, 2018b; Oettl et al., 2016) and localization (Kikuta et al., 2010), and the olfactory tubercle may play an important role in multisensory integration and attention (Wesson and Wilson, 2010; Zelano et al., 2005), although a complete understanding of the functions of these areas is lacking.

Previous studies have used task-related and resting functional magnetic resonance imaging (fMRI) to examine olfactory networks, using primary olfactory and orbitofrontal cortices as seed regions (Banks et al., 2016; Cecchetto et al., 2019; Fjaeldstad et al., 2017; Karunanayaka et al., 2017; Karunanayaka et al., 2014; Kiparizoska and Ikuta, 2017; Kollndorfer et al., 2015; Krusemark and Li, 2012; Nigri et al., 2013; Sreenivasan et al., 2017; Sunwoo et al., 2015). These studies have contributed important broad knowledge of parallel olfactory networks (Karunanayaka et al., 2014), how they compare to trigeminal networks (Karunanayaka et al., 2017), and how they change with age (Wang et al., 2005) and disease (Caffo et al., 2010; Fjaeldstad et al., 2017; Killgore et al., 2013; Sunwoo et al., 2015; Wang et al., 2010; Wang et al., 2015). However, the functional connectivity profiles of the primary olfactory subregions have not been considered separately. This is important because these subregions, which receive direct and parallel input from the bulb, likely form the anatomical substrates of ethological, parallel olfactory networks. Therefore, a quantitative characterization of the distinct functional pathways of human primary olfactory subregions would be an important step toward understanding the large-scale networks that underlie the basic, parallel, purposes of olfactory processing. The discovery of unique whole-brain connectivity profiles for the different primary olfactory subregions could also provide insight into the nature of the distinct functions of these areas in olfactory perception. This information, in turn, could have clinical implications for diseases that impact particular primary olfactory subregions.

Thus, the goals of this study were two-fold: first, to test the hypothesis that primary olfactory subregions form distinct large-scale olfactory processing networks; and second, if so, to characterize these networks across the whole brain. For the first, we used well-established, unsupervised k-means clustering techniques (Eickhoff et al., 2018; Kahnt et al., 2012; Kahnt and Tobler, 2017; Wang et al., 2017), to parcellate primary olfactory cortex into distinct clusters based solely on whole-brain connectivity patterns. We reasoned that if whole-brain functional connectivity patterns alone could be used to accurately parcellate primary olfactory cortex into its established, anatomically-defined subregions, this would suggest that these subregions do in fact form distinct functional pathways. We also reasoned that if these parcellation results were robust, the results should replicate in an independent data set. For the second, we characterized the distinct functional connectivity patterns of each primary olfactory subregion in order to produce a whole-brain map of the networks formed by each area. Our results provide insight into the functional and anatomical organization of the human olfactory system and provide a basis for future investigation into the functions of the distinct cortical targets of the olfactory bulb.

We used resting-state fMRI connectivity to examine the functional pathways of human primary olfactory cortex in two main steps. First, we used k-means clustering techniques to parcellate primary olfactory cortex into distinct clusters. These clusters were based on the group-level, whole-brain functional connectivity of all voxels within primary olfactory cortex, separately for each hemisphere. Second, using the results of the parcellation analysis, we characterized the distinct, large-scale networks of the human olfactory system. To do this, we first determined that there were no hemispheric differences in the connectivity profiles of primary olfactory subregions, suggesting we should combine corresponding clusters across the left and right hemispheres. We then quantified the whole-brain functional networks that were unique to each subdivision, and those that were common to all subdivisions. Finally, as a discussion point, we considered the functional properties of connected brain areas for each primary olfactory subdivision and attempted to form a speculative hypothetical model of human olfactory functional networks.

Parcellation of human primary olfactory cortex

To test the hypothesis that primary olfactory subregions form distinct, large-scale olfactory networks, we tested whether their anatomical boundaries could be accurately delineated based on whole-brain functional connectivity maps. To do this, we conducted a functional-connectivity-based parcellation of human primary olfactory cortex. Twenty-five subjects (average ± standard error age: 25.5 ± 1.2 years; 14 female) underwent a 10 min resting-state fMRI scan. We first outlined the entirety of primary olfactory cortex into a combined region-of-interest (ROI) on which to perform the k-means clustering analysis. This ROI was drawn for the left and right hemispheres separately, according to a human brain atlas which contains detailed demarcation of most primary olfactory areas (Mai et al., 2015; Ongür et al., 2003) (Figure 1A). The ROI included only those subregions with detailed boundaries in the atlas, and consisted of a combination of the anterior olfactory nucleus, olfactory tubercle, and frontal and temporal piriform cortices (Figure 1B), defined based on Mai et al. (2015). Note that additional primary olfactory areas, including amygdala and entorhinal cortex (Allison, 1954; Carmichael et al., 1994; Eslinger et al., 1982; Gonçalves Pereira et al., 2005; Zatorre et al., 1992), were not included in our ROI because the exact location of olfactory afferents into these areas is poorly understood (Gonçalves Pereira et al., 2005). This is an important topic for future investigation of human olfactory networks.

Figure 1

Download asset Open asset

Figure 1—source data 1

Relates to Figure 1.

Atlas and region-of-interest of the human primary olfactory cortex.

https://doi.org/10.7554/eLife.47177.003

Download elife-47177-fig1-data1-v1.zip

We then estimated the whole-brain functional connectivity profile of each voxel within the ROI by computing the Pearson correlation coefficient between the resting-state fMRI time-series of a given voxel and that of every other voxel in the rest of the brain. This resulted in subject-wise connectivity matrices. We then performed a leave-one-out analysis (Kahnt et al., 2012) to estimate the stability of the connectivity profiles of individual primary olfactory cortex voxels across participants, as a prerequisite for averaging the connectivity matrices across subjects (Figure 2A). To examine the similarity between the individual functional connectivity matrices, we computed a histogram of correlation values between individual matrices and the group matrix. The histogram of correlation values showed that the similarity of connectivity patterns was above zero in all voxels in primary olfactory cortex (mean correlation coefficient: 0.19, standard error: 0.0041), justifying averaging across subjects. Note that because they are computed across rest-of-the-brain voxels, R values larger than 0.0088 are statistically significant at p<0.05 (Bonferroni corrected for the number of voxels in primary olfactory cortex). To parcellate within-ROI voxels into subdivisions based on their whole-brain functional connectivity profiles, we applied unsupervised k-means clustering methods to the average connectivity matrix. We used a priori k = 4 based on the fact that our ROI was comprised of four anatomically distinct brain regions. For both the left and right hemispheres, this analysis successfully parcellated the primary olfactory cortex ROI into four distinct brain regions that corresponded anatomically to the anterior olfactory nucleus, olfactory tubercle, and frontal and temporal piriform cortices (Figure 2B).

Figure 2 with 2 supplements see all

Download asset Open asset

Figure 2—source data 1

Relates to Figure 2, panel (A).

Correlation between individual and group-level (leave-one-out) connectivity profiles.

https://doi.org/10.7554/eLife.47177.008

Download elife-47177-fig2-data1-v1.zip

Figure 2—source data 2

Relates to Figure 2, panel (B) and (C).

Manual segmentation and parcellation of the human primary olfactory cortex.

https://doi.org/10.7554/eLife.47177.009

Download elife-47177-fig2-data2-v1.zip

To confirm the correspondence between our parcellation results and the anatomical delineation of primary olfactory subregions in the Atlas of the Human Brain (Mai et al., 2015), we computed the proportion of voxels from each parcellation cluster located within each of the atlas-derived subdivisions, drawn prior to performing the parcellation analysis (Figure 2B). The statistical significance of this proportion was tested using a permutation test. Specifically, for each permutation, we shuffled the labels of the anatomical subdivision and re-calculated the proportion. This procedure was repeated 10,000 times, resulting in a distribution of permuted proportions for each parcellation cluster. A z score of the actual proportion values was computed by subtracting the average and then dividing by the standard deviation, which was obtained by normal distribution fitting of the permuted data (Matlab’s normfit). We found that for each parcellated subdivision, there was one anatomical ROI that contained significantly more voxels than the other anatomical ROIs (Figure 2C, minimal z score = 7.18). Thus, we found that the location of voxels within each parcellated subdivision corresponded to a single anatomically-determined ROI. Specifically, the medial-rostral-most parcellated subdivision corresponded to the anterior olfactory nucleus. The adjacent caudal subdivision corresponded to the olfactory tubercle. Within the frontal lobe, the lateral-rostral subdivision corresponded to the frontal piriform cortex, and within the temporal lobe, the caudal-most subdivision corresponded to temporal piriform cortex.

Parcellation results across hemispheres and k values

Thus far, we demonstrated that both the left and right primary olfactory areas can be accurately subdivided based on their functional connectivity profiles. To further examine differences between the left and right hemispheres and at different k values, we conducted additional parcellation analyses using a single primary olfactory ROI containing all subregions from both hemispheres, at a range of k values. We reasoned that if connectivity patterns were similar across hemispheres for each subregion, then parcellation analysis of this combined ROI should group left and right sides of each primary olfactory subregion, as opposed to grouping, for example, the neighboring subregions on the same hemisphere. We computed this analysis using k values ranging from 3 to 6 (Figure 3). We found that for a k value of 3, the parcellation analysis grouped left and right anterior olfactory nucleus and left tubercle as one cluster, left and right frontal piriform cortex and left temporal piriform cortex as a second cluster, and right temporal piriform cortex alone as the third cluster. For a k value of 4, the analysis successfully grouped left and right hemispheres for both piriform subregions, but it grouped left anterior olfactory nucleus with left olfactory tubercle and right anterior olfactory nucleus with right olfactory tubercle, suggesting these two primary olfactory areas have relatively more lateralized connectivity patterns. A k value of 5 grouped the left and right hemispheres of all subregions, with a fifth cluster consisting of only right temporal piriform cortex. Finally, a k value of 6 grouped all subregions across hemispheres except for the anterior olfactory nucleus. These results indicate a clear separation of frontal and temporal piriform cortex for a wide range of cluster solutions and even across hemispheres (Figure 3A). All parcellation results showed good agreement with the anatomical subregions (Figure 3B,C). Of note, the anterior olfactory nucleus and olfactory tubercle are classified as one subregion for a clustering solution of k = 3. The left and right anterior olfactory nucleus were separated into different subregions for k = 4, 6. These findings suggest stronger lateralization of connectivity patterns for the anterior olfactory nucleus compared to other primary olfactory areas.

Figure 3

Download asset Open asset

Figure 3—source data 1

Relates to Figure 3.

Parcellation result (k = 3 to 6) of left and right hemispheres combined ROI.

https://doi.org/10.7554/eLife.47177.011

Download elife-47177-fig3-data1-v1.zip

Functional connectivity profiles of anterior olfactory nucleus and olfactory tubercle

The brain areas that showed connectivity unique to the anterior olfactory nucleus were largest in the orbitofrontal cortex, with smaller clusters in the left inferior temporal gyrus, bilateral anterior temporal gyri, the bilateral anterior insula and the mammillary bodies and retromammillary commissure (Figure 4A,E). Areas of connectivity in the orbitofrontal cortex were extensive, including the entire gyrus rectus and encompassing parts of the medial, anterior and lateral orbital gyri. Notably, there was a strong cluster of connectivity corresponding to bilateral areas along the medial orbital sulcus, close to its intersection with the transverse orbital sulcus—this is significant because this part of orbitofrontal cortex is sometimes referred to as human secondary olfactory cortex (Gottfried and Zald, 2005). Connectivity with the left inferior temporal gyrus was centered around a posterior region along the established object-recognition pathway. There were also large clusters in the bilateral anterior temporal gyri, and the bilateral anterior insula, in gustatory cortex. Finally, there was a medial cluster centered around the region between the mammillary bodies, the retromammillary commissure and the posterior hypothalamic nucleus.

Figure 4 with 1 supplement see all

Download asset Open asset

Figure 4—source data 1

Relates to Figure 4.

Statistical images of the functional connectivity of human primary olfactory cortex subregions.

https://doi.org/10.7554/eLife.47177.017

Download elife-47177-fig4-data1-v1.zip

The brain areas that exhibited connectivity unique to the olfactory tubercle were largest in the medial prefrontal cortex, with smaller clusters in the perisplenial region, the left temporal fusiform cortex, the red nucleus of the brainstem and the accumbens (Figure 4B,F). Connectivity between the olfactory tubercle and the medial prefrontal cortex was mainly located in the paracingulate gyrus and frontal pole. In the paracingulate, it centered bilaterally around the anterior-most aspect of Brodman’s area 32. Connectivity with the frontal pole was stronger in the left hemisphere, and extended from the dorsal edge of the ventro-medial prefrontal cortex into the medial prefrontal cortex, with a smaller cluster extending even more dorsal, reaching the dorsomedial prefrontal cortex. There was also a cluster of connectivity located bilaterally in the ventral striatum, in the accumbens. There were bilateral clusters of connectivity in both the red nuclei of the brainstem and in the retrosplenial area.

Functional connectivity common to all subregions

Although we have shown that primary olfactory subregions have distinct functional connectivity profiles, they likely also have some functional pathways in common, especially considering the strong reciprocal connectivity between the subregions. To identify the common primary olfactory connectivity network, the connectivity map of each subregion was binarized at a threshold of TFCE corrected p<0.001 to include only those clusters that exhibited connectivity with all subregions. This resulted in a whole-brain connectivity map of areas that are functionally connected to all primary olfactory cortical subregions (Figure 5, Table 1). We found that these areas included large clusters in the bilateral hippocampus, amygdala and subgenual area, with smaller clusters in the anterior insula and posterior orbitofrontal cortex (Figure 5A,B). Connectivity with the hippocampus covered the entire anterior-posterior extent. In the amygdala, connectivity was maximal in the medial subregions and in the central amygdala. Interestingly, for both the right and left primary olfactory cortical subregions, connectivity clusters with the rest of the brain were generally more extensive in the right hemisphere compared to the left hemisphere (Frasnelli et al., 2010; Herz et al., 1999; Royet and Plailly, 2004; Zatorre et al., 1992) (Figure 5A,B). The common connectivity of all primary olfactory subregions with the orbitofrontal cortex could explain why it is so reliably activated even in basic and passive olfactory tasks.

Figure 5

Download asset Open asset

Figure 5—source data 1

Relates to Figure 5.

Functional connectivity patterns common to all human primary olfactory cortex subregions.

https://doi.org/10.7554/eLife.47177.019

Download elife-47177-fig5-data1-v1.zip

In the olfactory system, information flows from the bulb to the cortex in a direct and parallel manner. Similarly, other sensory systems have parallel organization of processing pathways, but these typically occur at a later stage of processing. For example, information from other systems, including somatosensation, gustation, vision and audition, is processed in the thalamus prior to primary sensory cortex, and is parallelized downstream from there. In olfaction, thalamic processing occurs after direct parallel primary cortical processing, and, based on data from this study, may only occur for a subset of olfactory processing streams. From the olfactory bulb, mitral and tufted cells project to several different brain regions which are thought to play unique roles in olfactory processing (Ghosh et al., 2011; Haberly, 2001; Miyamichi et al., 2011; Sosulski et al., 2011). In rodents, the anatomical locations and properties of these regions have been well defined (Igarashi et al., 2012; Nagayama et al., 2010; Vassar et al., 1994). In humans, however, far fewer studies have attempted to identify and define these primary olfactory areas (Crosby and Humphrey, 1939; Eslinger et al., 1982; Allison, 1954; Shipley and Reyes, 1991). Similarly, whereas many studies have begun to outline unique functional properties of primary olfactory areas within the rodent olfactory system (Ikemoto, 2003; Illig, 2005; Lei et al., 2006; Myhrer et al., 2010; Wesson and Wilson, 2010), fewer have done the same in humans. In the current study, we used data-driven connectivity-based parcellation techniques to show that whole-brain functional connectivity patterns alone could be used to parcellate human primary olfactory cortical regions into subregions that anatomically corresponded to the anterior olfactory nucleus, olfactory tubercle and frontal and temporal piriform cortices. Our findings indicate a dissociation in whole-brain functional connectivity patterns across the subregions of human primary olfactory cortex. This suggests that the human olfactory system is comprised of distinct parallel processing pathways (Cecchetto et al., 2019; Savic et al., 2000) that may be related to the different recipients of projections from the olfactory bulb, in line with previous studies in rodents (Geramita et al., 2016; Haberly, 2001; Igarashi et al., 2012; Kauer, 1991; Payton et al., 2012). Our findings provide a detailed description of the particular brain areas that exhibit unique connectivity with each individual primary olfactory subregion. This could be used to gain insight into the specific role that each subregion plays in olfactory perception. We also demonstrate parallel organization of the olfactory system, in which olfactory networks reach a broader set of cortical targets at an earlier stage of processing compared to other sensory systems. This data might have implications for understanding the olfactory decline that appears in early stages of some neurological disease states. For example, olfactory structures that form networks with brain areas implicated in particular pathologies likely perform critical olfactory sensory functions (e.g. the olfactory tubercle is connected to areas involved in depression, see Croy and Hummel, 2017, and the temporal piriform cortex is connected to areas involved in primary progressive aphasia, see Olofsson et al., 2013).

Across species, the most frequently studied primary olfactory area is piriform cortex. In rodents, it has been consistently shown that projections from the bulb to piriform cortex are spatially distributed (Ghosh et al., 2011; Iurilli and Datta, 2017; Miyamichi et al., 2011) and that information about odor identity can be extracted from the spatiotemporal dynamics of these ensemble patterns (Haddad et al., 2013; Illig and Haberly, 2003; Poo and Isaacson, 2009; Rennaker et al., 2007; Stettler and Axel, 2009; Sugai et al., 2005; Zhan and Luo, 2010). At the same time, numerous studies suggest that the function of piriform cortex goes beyond simple odor-identity coding and is strongly impacted by its regional connectivity with other cortical areas (Cleland and Linster, 2003; Sadrian and Wilson, 2015). Numerous studies have implicated posterior piriform cortex in associative functions such as odor learning and memory (Calu et al., 2007; Chen et al., 2014; Choi et al., 2011; Gire et al., 2013; Gottfried and Dolan, 2003; Johnson et al., 2000; Karunanayaka et al., 2015; Martin et al., 2006; Roesch et al., 2007; Sacco and Sacchetti, 2010; Schoenbaum and Eichenbaum, 1995), and also suggest that the region may mediate learned olfactory responses and behaviors (Choi et al., 2011). Moreover, the strength and composition of piriform networks has also been shown to depend on experience and on the state of the organism (Chapuis et al., 2013; Cohen et al., 2015; Cohen et al., 2008; Hasselmo and Barkai, 1995; Kay and Freeman, 1998; Linster and Hasselmo, 2001; Wilson and Sullivan, 2011).

While human studies suggest a role for piriform cortex that goes beyond pure odor-object coding, (Bensafi, 2012; Gottfried, 2010; Porter et al., 2007; Schulze et al., 2017; Zelano et al., 2005), the anatomical and functional properties of human piriform cortex are not well understood compared to rodents. In fact, in some cases, it is not even clear which human bulbar recipients correspond to the well-defined rodent ones. While it has been suggested that the frontal and temporal subdivisions of human piriform may correspond to the anterior and posterior subdivisions of rodent piriform respectively, there is little anatomical or functional evidence to support this. For example, the rodent anterior piriform receives a greater density of bulb projections than the posterior piriform, while the same is not true for human frontal, relative to temporal, piriform. The lack of clear correspondence between human and rodent piriform subdivisions suggest that functional differences in primary olfactory areas across species could be substantial.

In our study, we found a clear differentiation between the functional connectivity patterns of human frontal and temporal piriform subdivisions, suggesting these two areas play different roles in olfactory processing in the human brain (Albrecht et al., 2010; Bao et al., 2016; Bensafi et al., 2007; Howard et al., 2009; Plailly et al., 2012; Porter et al., 2005; Zelano et al., 2005). This distinction between frontal and temporal piriform cortices was robust, surviving across k values and hemispheres. Interestingly, our findings suggest that frontal piriform cortex has strong functional connectivity with motor planning areas, including the caudate/putamen and the primary motor cortex, specifically at the face/nose/jaw section of the motor homunculus (perhaps the facial movement areas include sniffing). Intriguingly, frontal piriform cortex was also connected to the left supramarginal gyrus, an area that has been consistently implicated in tool-grasping in humans (Glover et al., 2012; Johnson-Frey et al., 2005), leading us to the tempting and highly speculative hypothesis that frontal piriform cortex may play a specific role in combining olfactory information with motor planning in order to guide food with the hand to the mouth. In contrast, we found that the temporal piriform cortex was connected to the brainstem raphe magnus and posterior insula, areas implicated in pain processing (Segerdahl et al., 2015; Woo et al., 2009) and respiratory modulations (Ackermann and Riecker, 2010; Evans et al., 2009), as well as the core language network (Ardila et al., 2014; Wible et al., 2005). Interestingly, in the context of olfaction, respiratory modulation and pain mediation are tightly linked, since many olfactory stimuli also activate trigeminal nerve endings that are located inside the nasal cavities. If a painful stimulus enters the nasal cavities (e.g. ammonia), a protective, fast respiratory reduction occurs, to minimize entry of dangerous chemicals into the body. Intriguingly, verbal communication also requires modulations in breathing, and thus, temporal piriform cortex may mediate both olfactory-related verbal communication and protective changes in respiration. These findings may be applicable to the hypothesized neurocognitive limitations of olfactory language (Cain, 1979; Engen and Ross, 1973; Olofsson and Gottfried, 2015), since our data may suggest that the same olfactory subregion exhibiting connectivity with language networks is involved in other critical olfactory functions.

Beyond piriform cortex, other cortical recipients of olfactory bulb output are less explored, including the anterior olfactory nucleus (Brunjes et al., 2005) and olfactory tubercle (Wesson and Wilson, 2011). In rodents, the anterior olfactory nucleus is a true cortical structure that can be divided into two main subdivisions, the pars externa and pars principalis (Pigache, 1970; Valverde et al., 1989). Studies suggest that some of the spatial properties of rodent glomerular activation are preserved in the pars externa, whereas the pars principalis exhibits a spatially distributed activation similar to other primary olfactory areas (Kay et al., 2011; Miyamichi et al., 2011). This suggests functional heterogeneity across the rodent anterior olfactory nucleus. In humans, the anterior olfactory nucleus is also a true cortical structure, but it does not appear to contain an analog to the pars externa (Crosby and Humphrey, 1941). It can be divided anatomically into retrobulbar and cortical anterior and posterior subdivisions (Mai et al., 2015; Ubeda-Bañon et al., 2017; Ongür et al., 2003). That said, only a small number of studies have directly explored the human anterior olfactory nucleus (Ubeda-Bañon et al., 2017), so its functional subdivisions remain unclear. Rodent studies suggest the pars externa is involved in odor localization (Esquivelzeta Rabell et al., 2017; Kikuta et al., 2010) and the pars medialis could be involved in top-down modulation of bulbar responses (Aqrabawi et al., 2016). More broadly, rodent studies suggest a role for the anterior olfactory nucleus in the initial formation of representations of odor objects (gestalts) (Haberly, 2001; Lei et al., 2006), allowing piriform cortex to perform more associative functions, relating information about odor objects to movement and behavior. In our study, we found that whole-brain connectivity of the human anterior olfactory nucleus was maximal in orbitofrontal areas and other regions associated with object recognition. Our findings are in line with rodent studies showing connectivity between anterior olfactory nucleus and orbitofrontal cortex (Illig, 2005), and with the hypothesized role for the anterior olfactory nucleus in the formation of odor-object representations (Haberly, 2001). We also found that connectivity profiles for the anterior olfactory nucleus were more lateralized than those of other primary olfactory subregions. This finding is in line with rodent studies suggesting that anterior olfactory nucleus neurons can distinguish between signals from the ipsilateral and contralateral nostrils, suggesting representation of lateralized inputs in this region (Kikuta et al., 2010).

Similar to the anterior olfactory nucleus, we lack a complete understanding of the function of the olfactory tubercle, especially in humans. The majority of research on the olfactory tubercle has been conducted in rodents and has focused on its relationship with the reward system (Ikemoto, 2007), with far fewer studies considering it as a primary olfactory cortical structure (Wesson and Wilson, 2011). Interestingly, the olfactory tubercle is the main recipient of tufted (as opposed to mitral) cell projections from the rodent olfactory bulb (Scott et al., 1980). Tufted cells show enhanced odor sensitivity, enhanced respiratory entrainment and broader receptive fields compared to mitral cells (Mori and Shepherd, 1994; Shepherd et al., 2004), suggesting that the olfactory tubercle is important for olfactory tasks requiring high sensitivity. Studies suggest potential roles for the rodent olfactory tubercle in odor discrimination (Murakami et al., 2005; Wesson and Wilson, 2010), olfactory multisensory integration (Wang et al., 2010), state-dependent modulation of olfactory bulb activity (Gervais, 1979) and odor reward value (Howard et al., 2016). Studies also suggest a role for the rodent olfactory tubercle in sensory hedonics and social behavior (Gervais, 1979; Hagamen et al., 1977; Hitt et al., 1973). Compared to rodents, much less is known about the human olfactory tubercle. In our study, we found connectivity between the olfactory tubercle and brain areas implicated in emotional processing, depression, and social cognition, including anterior paracingulate cortex and left frontal pole (Bludau et al., 2014; Eskenazi et al., 2015; Fettes et al., 2018; Jackson et al., 2003; Koch et al., 2018; Koechlin, 2011; Papmeyer et al., 2015; Veer et al., 2010). Interestingly, we also found connectivity between the olfactory tubercle and the left fusiform gyrus (fusiform face area), a brain region that is highly responsive to human faces (Çukur et al., 2013; Grill-Spector et al., 2004; Kanwisher et al., 1997; McCarthy et al., 1997). Our findings are consistent with rodent data suggesting a role for the tubercle in emotion and social cognition.

In an attempt to summarize and clarify the basic implications of our findings, we created a simplified, speculative illustrative diagram suggesting potential roles for each of the primary olfactory subdivisions that our study parcellated (Figure 6). One possible interpretation of our data suggests the following basic functions for human primary olfactory cortical subregions: Anterior olfactory nucleus, a cortical structure, may function as a first step in forming olfactory object representations; The olfactory tubercle may function in extracting social and emotional information from olfactory stimuli, mediating olfactory-related social and emotional responses; Frontal piriform cortex may be involved in planning olfactory-related movements, speculatively those involved in eating; Temporal piriform cortex may mediate pain-related (protective) respiratory modulations and verbal communication about olfactory stimuli. Importantly, the functions of primary olfactory areas cannot be determined from resting connectivity networks explored here, and there are numerous alternate interpretations of our data. Future experiments that combine psychophysics with the measurement of neural activity across primary olfactory areas are needed to gain a full understanding of parallel functional olfactory pathways in the human brain.

Figure 6

Download asset Open asset

Figure 6—source data 1

Relates to Figure 6.

Source files for constructing the schematic illustrative model.

https://doi.org/10.7554/eLife.47177.021

Download elife-47177-fig6-data1-v1.zip

Source data have been provided for each figure and table. Source data and code have been made available via GitHub: https://github.com/zelanolab/primaryolfactorycortexparcellation.git (copy archived at https://github.com/elifesciences-publications/primaryolfactorycortexparcellation).

1. 1. Ackermann H
   2. Riecker A

   (2010) The contribution(s) of the insula to speech production: a review of the clinical and functional imaging literature

   Brain Structure and Function 214:419–433.

   https://doi.org/10.1007/s00429-010-0257-x

   • PubMed
   • Google Scholar
2. 1. Albrecht J
   2. Kopietz R
   3. Frasnelli J
   4. Wiesmann M
   5. Hummel T
   6. Lundström JN

   (2010) The neuronal correlates of intranasal trigeminal function-an ALE meta-analysis of human functional brain imaging data

   Brain Research Reviews 62:183–196.

   https://doi.org/10.1016/j.brainresrev.2009.11.001

   • PubMed
   • Google Scholar
3. 1. Allison AC

   (1954)

   The secondary olfactory areas in the human brain

   Journal of Anatomy 88:481–488.

   • PubMed
   • Google Scholar
4. 1. Aqrabawi AJ
   2. Browne CJ
   3. Dargaei Z
   4. Garand D
   5. Khademullah CS
   6. Woodin MA
   7. Kim JC

   (2016) Top-down modulation of olfactory-guided behaviours by the anterior olfactory nucleus pars medialis and ventral Hippocampus

   Nature Communications 7:13721.

   https://doi.org/10.1038/ncomms13721

   • PubMed
   • Google Scholar
5. 1. Aqrabawi AJ
   2. Kim JC

   (2018a) Topographic organization of hippocampal inputs to the anterior olfactory nucleus

   Frontiers in Neuroanatomy 12:12:12.

   https://doi.org/10.3389/fnana.2018.00012

   • Google Scholar
6. 1. Aqrabawi AJ
   2. Kim JC

   (2018b) Hippocampal projections to the anterior olfactory nucleus differentially convey spatiotemporal information during episodic odour memory

   Nature Communications 9:2735.

   https://doi.org/10.1038/s41467-018-05131-6

   • PubMed
   • Google Scholar
7. 1. Ardila A
   2. Bernal B
   3. Rosselli M

   (2014) Participation of the insula in language revisited: a meta-analytic connectivity study

   Journal of Neurolinguistics 29:31–41.

   https://doi.org/10.1016/j.jneuroling.2014.02.001

   • Google Scholar
8. 1. Banks SJ
   2. Sreenivasan KR
   3. Weintraub DM
   4. Baldock D
   5. Noback M
   6. Pierce ME
   7. Frasnelli J
   8. James J
   9. Beall E
   10. Zhuang X
   11. Cordes D
   12. Leger GC

   (2016) Structural and functional MRI differences in master sommeliers: a pilot study on expertise in the brain

   Frontiers in Human Neuroscience 10:414.

   https://doi.org/10.3389/fnhum.2016.00414

   • PubMed
   • Google Scholar
9. 1. Bao X
   2. Raguet LL
   3. Cole SM
   4. Howard JD
   5. Gottfried J

   (2016) The role of piriform associative connections in odor categorization

   eLife 5:e13732.

   https://doi.org/10.7554/eLife.13732

   • PubMed
   • Google Scholar
10. 1. Bensafi M
    2. Sobel N
    3. Khan RM

    (2007) Hedonic-specific activity in piriform cortex during odor imagery mimics that during odor perception

    Journal of Neurophysiology 98:3254–3262.

    https://doi.org/10.1152/jn.00349.2007

    • PubMed
    • Google Scholar
11. 1. Bensafi M

    (2012) The role of the piriform cortex in human olfactory perception: insights from functional neuroimaging studies

    Chemosensory Perception 5:4–10.

    https://doi.org/10.1007/s12078-011-9110-8

    • Google Scholar
12. 1. Bludau S
    2. Eickhoff SB
    3. Mohlberg H
    4. Caspers S
    5. Laird AR
    6. Fox PT
    7. Schleicher A
    8. Zilles K
    9. Amunts K

    (2014) Cytoarchitecture, probability maps and functions of the human frontal pole

    NeuroImage 93 Pt 2:260–275.

    https://doi.org/10.1016/j.neuroimage.2013.05.052

    • PubMed
    • Google Scholar
13. 1. Brunjes PC
    2. Illig KR
    3. Meyer EA

    (2005) A field guide to the anterior olfactory nucleus (cortex)

    Brain Research Reviews 50:305–335.

    https://doi.org/10.1016/j.brainresrev.2005.08.005

    • Google Scholar
14. 1. Bushdid C
    2. Magnasco MO
    3. Vosshall LB
    4. Keller A

    (2014) Humans can discriminate more than 1 trillion olfactory stimuli

    Science 343:1370–1372.

    https://doi.org/10.1126/science.1249168

    • PubMed
    • Google Scholar
15. 1. Caffo BS
    2. Crainiceanu CM
    3. Verduzco G
    4. Joel S
    5. Mostofsky SH
    6. Bassett SS
    7. Pekar JJ

    (2010) Two-stage decompositions for the analysis of functional connectivity for fMRI with application to Alzheimer's disease risk

    NeuroImage 51:1140–1149.

    https://doi.org/10.1016/j.neuroimage.2010.02.081

    • PubMed
    • Google Scholar
16. 1. Cain WS

    (1979) To know with the nose: keys to odor identification

    Science 203:467–470.

    https://doi.org/10.1126/science.760202

    • PubMed
    • Google Scholar
17. 1. Calu DJ
    2. Roesch MR
    3. Stalnaker TA
    4. Schoenbaum G

    (2007) Associative encoding in posterior piriform cortex during odor discrimination and reversal learning

    Cerebral Cortex 17:1342–1349.

    https://doi.org/10.1093/cercor/bhl045

    • PubMed
    • Google Scholar
18. 1. Carmichael ST
    2. Clugnet MC
    3. Price JL

    (1994) Central olfactory connections in the macaque monkey

    The Journal of Comparative Neurology 346:403–434.

    https://doi.org/10.1002/cne.903460306

    • PubMed
    • Google Scholar
19. 1. Cecchetto C
    2. Fischmeister FPS
    3. Reichert JL
    4. Bagga D
    5. Schöpf V

    (2019) When to collect resting-state data: the influence of odor on post-task resting-state connectivity

    NeuroImage 191:361–366.

    https://doi.org/10.1016/j.neuroimage.2019.02.050

    • PubMed
    • Google Scholar
20. 1. Chapuis J
    2. Cohen Y
    3. He X
    4. Zhang Z
    5. Jin S
    6. Xu F
    7. Wilson DA

    (2013) Lateral entorhinal modulation of piriform cortical activity and fine odor discrimination

    Journal of Neuroscience 33:13449–13459.

    https://doi.org/10.1523/JNEUROSCI.1387-13.2013

    • PubMed
    • Google Scholar
21. 1. Chapuis J
    2. Wilson DA

    (2011) Bidirectional plasticity of cortical pattern recognition and behavioral sensory acuity

    Nature Neuroscience 15:155–161.

    https://doi.org/10.1038/nn.2966

    • PubMed
    • Google Scholar
22. 1. Chen CF
    2. Zou DJ
    3. Altomare CG
    4. Xu L
    5. Greer CA
    6. Firestein SJ

    (2014) Nonsensory target-dependent organization of piriform cortex

    PNAS 111:16931–16936.

    https://doi.org/10.1073/pnas.1411266111

    • PubMed
    • Google Scholar
23. 1. Choi GB
    2. Stettler DD
    3. Kallman BR
    4. Bhaskar ST
    5. Fleischmann A
    6. Axel R

    (2011) Driving opposing behaviors with ensembles of piriform neurons

    Cell 146:1004–1015.

    https://doi.org/10.1016/j.cell.2011.07.041

    • PubMed
    • Google Scholar
24. Book

    1. Cleland TA
    2. Linster C

    (2003) Central olfactory processing

    In: Doty R. L, editors. Handbook of Olfaction and Gustation. New York: Marcel Dekker. pp. 165–180.

    https://doi.org/10.1201/9780203911457.ch8

    • Google Scholar
25. 1. Cohen Y
    2. Reuveni I
    3. Barkai E
    4. Maroun M

    (2008) Olfactory learning-induced long-lasting enhancement of descending and ascending synaptic transmission to the piriform cortex

    Journal of Neuroscience 28:6664–6669.

    https://doi.org/10.1523/JNEUROSCI.0178-08.2008

    • PubMed
    • Google Scholar
26. 1. Cohen Y
    2. Putrino D
    3. Wilson DA

    (2015) Dynamic cortical lateralization during olfactory discrimination learning

    The Journal of Physiology 593:1701–1714.

    https://doi.org/10.1113/jphysiol.2014.288381

    • PubMed
    • Google Scholar
27. 1. Cox RW

    (1996) AFNI: software for analysis and visualization of functional magnetic resonance neuroimages

    Computers and Biomedical Research 29:162–173.

    https://doi.org/10.1006/cbmr.1996.0014

    • PubMed
    • Google Scholar
28. 1. Crosby EC
    2. Humphrey T

    (1939)

    Studies of The vertebrate telencephalon. I. the nuclear configuration of the olfactory and accessory olfactory formations and of the nucleus olfactorius anterior of certain reptiles, birds, and mammals

    The Journal of Comparative Neurology 71:121–213.

    • Google Scholar
29. 1. Crosby EC
    2. Humphrey T

    (1941) Studies of the vertebrate telencephalon. II. the nuclear pattern of the anterior olfactory nucleus, tuberculum olfactorium and the amygdaloid complex in adult man

    The Journal of Comparative Neurology 74:309–352.

    https://doi.org/10.1002/cne.900740209

    • Google Scholar
30. 1. Croy I
    2. Hummel T

    (2017) Olfaction as a marker for depression

    Journal of Neurology 264:631–638.

    https://doi.org/10.1007/s00415-016-8227-8

    • PubMed
    • Google Scholar
31. 1. Çukur T
    2. Huth AG
    3. Nishimoto S
    4. Gallant JL

    (2013) Functional subdomains within human FFA

    Journal of Neuroscience 33:16748–16766.

    https://doi.org/10.1523/JNEUROSCI.1259-13.2013

    • PubMed
    • Google Scholar
32. 1. Daniel S
    2. Hawkes C

    (1992) Preliminary diagnosis of Parkinson's disease by olfactory bulb pathology

    The Lancet 340:186.

    https://doi.org/10.1016/0140-6736(92)93275-R

    • Google Scholar
33. 1. Deichmann R
    2. Gottfried JA
    3. Hutton C
    4. Turner R

    (2003) Optimized EPI for fMRI studies of the orbitofrontal cortex

    NeuroImage 19:430–441.

    https://doi.org/10.1016/S1053-8119(03)00073-9

    • PubMed
    • Google Scholar
34. 1. Devanand DP
    2. Lee S
    3. Manly J
    4. Andrews H
    5. Schupf N
    6. Masurkar A
    7. Stern Y
    8. Mayeux R
    9. Doty RL

    (2015) Olfactory identification deficits and increased mortality in the community

    Annals of Neurology 78:401–411.

    https://doi.org/10.1002/ana.24447

    • Google Scholar
35. 1. Durand K
    2. Baudouin JY
    3. Lewkowicz DJ
    4. Goubet N
    5. Schaal B

    (2013) Eye-catching odors: olfaction elicits sustained gazing to faces and eyes in 4-month-old infants

    PLOS ONE 8:e70677.

    https://doi.org/10.1371/journal.pone.0070677

    • PubMed
    • Google Scholar
36. 1. Eickhoff SB
    2. Yeo BTT
    3. Genon S

    (2018) Imaging-based parcellations of the human brain

    Nature Reviews Neuroscience 19:672–686.

    https://doi.org/10.1038/s41583-018-0071-7

    • PubMed
    • Google Scholar
37. 1. Endevelt-Shapira Y
    2. Perl O
    3. Ravia A
    4. Amir D
    5. Eisen A
    6. Bezalel V
    7. Rozenkrantz L
    8. Mishor E
    9. Pinchover L
    10. Soroka T
    11. Honigstein D
    12. Sobel N

    (2018) Altered responses to social chemosignals in autism spectrum disorder

    Nature Neuroscience 21:111–119.

    https://doi.org/10.1038/s41593-017-0024-x

    • PubMed
    • Google Scholar
38. 1. Engen T
    2. Ross BM

    (1973) Long-term memory of odors with and without verbal descriptions

    Journal of Experimental Psychology 100:221–227.

    https://doi.org/10.1037/h0035492

    • PubMed
    • Google Scholar
39. 1. Eskenazi T
    2. Rueschemeyer SA
    3. de Lange FP
    4. Knoblich G
    5. Sebanz N

    (2015) Neural correlates of observing joint actions with shared intentions

    Cortex 70:90–100.

    https://doi.org/10.1016/j.cortex.2015.05.027

    • PubMed
    • Google Scholar
40. 1. Eslinger PJ
    2. Damasio AR
    3. Van Hoesen GW

    (1982) Olfactory dysfunction in man: anatomical and behavioral aspects

    Brain and Cognition 1:259–285.

    https://doi.org/10.1016/0278-2626(82)90028-8

    • PubMed
    • Google Scholar
41. 1. Esquivelzeta Rabell J
    2. Mutlu K
    3. Noutel J
    4. Martin Del Olmo P
    5. Haesler S

    (2017) Spontaneous rapid odor source localization behavior requires interhemispheric communication

    Current Biology 27:1542–1548.

    https://doi.org/10.1016/j.cub.2017.04.027

    • PubMed
    • Google Scholar
42. 1. Evans KC
    2. Dougherty DD
    3. Schmid AM
    4. Scannell E
    5. McCallister A
    6. Benson H
    7. Dusek JA
    8. Lazar SW

    (2009) Modulation of spontaneous breathing via limbic/paralimbic-bulbar circuitry: an event-related fMRI study

    NeuroImage 47:961–971.

    https://doi.org/10.1016/j.neuroimage.2009.05.025

    • PubMed
    • Google Scholar
43. Book

    1. Feher J
    2. Feher J

    (2017) The Chemical senses.Quantitative Human Physiology: An Introduction, 439

    Academic Press.

    https://doi.org/10.1016/B978-0-12-800883-6.00039-2

    • Google Scholar
44. 1. Fettes PW
    2. Moayedi M
    3. Dunlop K
    4. Mansouri F
    5. Vila-Rodriguez F
    6. Giacobbe P
    7. Davis KD
    8. Lam RW
    9. Kennedy SH
    10. Daskalakis ZJ
    11. Blumberger DM
    12. Downar J

    (2018) Abnormal functional connectivity of frontopolar subregions in Treatment-Nonresponsive major depressive disorder

    Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 3:337–347.

    https://doi.org/10.1016/j.bpsc.2017.12.003

    • PubMed
    • Google Scholar
45. 1. Fjaeldstad A
    2. Fernandes HM
    3. Van Hartevelt TJ
    4. Gleesborg C
    5. Møller A
    6. Ovesen T
    7. Kringelbach ML

    (2017) Brain fingerprints of olfaction: a novel structural method for assessing olfactory cortical networks in health and disease

    Scientific Reports 7:42534.

    https://doi.org/10.1038/srep42534

    • PubMed
    • Google Scholar
46. 1. Fournel A
    2. Ferdenzi C
    3. Sezille C
    4. Rouby C
    5. Bensafi M

    (2016) Multidimensional representation of odors in the human olfactory cortex

    Human Brain Mapping 37:2161–2172.

    https://doi.org/10.1002/hbm.23164

    • PubMed
    • Google Scholar
47. 1. Frasnelli J
    2. Lundström JN
    3. Boyle JA
    4. Djordjevic J
    5. Zatorre RJ
    6. Jones-Gotman M

    (2010) Neuroanatomical correlates of olfactory performance

    Experimental Brain Research 201:1–11.

    https://doi.org/10.1007/s00221-009-1999-7

    • PubMed
    • Google Scholar
48. 1. Friederici AD
    2. Rüschemeyer SA
    3. Hahne A
    4. Fiebach CJ

    (2003) The role of left inferior frontal and superior temporal cortex in sentence comprehension: localizing syntactic and semantic processes

    Cerebral Cortex 13:170–177.

    https://doi.org/10.1093/cercor/13.2.170

    • PubMed
    • Google Scholar
49. 1. Frumin I
    2. Perl O
    3. Endevelt-Shapira Y
    4. Eisen A
    5. Eshel N
    6. Heller I
    7. Shemesh M
    8. Ravia A
    9. Sela L
    10. Arzi A
    11. Sobel N

    (2015) A social chemosignaling function for human handshaking

    eLife 4:e05154.

    https://doi.org/10.7554/eLife.05154

    • Google Scholar
50. 1. Gadziola MA
    2. Tylicki KA
    3. Christian DL
    4. Wesson DW

    (2015) The olfactory tubercle encodes odor valence in behaving mice

    Journal of Neuroscience 35:4515–4527.

    https://doi.org/10.1523/JNEUROSCI.4750-14.2015

    • PubMed
    • Google Scholar
51. 1. Gelstein S
    2. Yeshurun Y
    3. Rozenkrantz L
    4. Shushan S
    5. Frumin I
    6. Roth Y
    7. Sobel N

    (2011) Human tears contain a chemosignal

    Science 331:226–230.

    https://doi.org/10.1126/science.1198331

    • PubMed
    • Google Scholar
52. 1. Geramita MA
    2. Burton SD
    3. Urban NN

    (2016) Distinct lateral inhibitory circuits drive parallel processing of sensory information in the mammalian olfactory bulb

    eLife 5:e16039.

    https://doi.org/10.7554/eLife.16039

    • PubMed
    • Google Scholar
53. 1. Gervais R

    (1979) Unilateral lesions of the olfactory tubercle modifying general arousal effects in the rat olfactory bulb

    Electroencephalography and Clinical Neurophysiology 46:665–674.

    https://doi.org/10.1016/0013-4694(79)90104-4

    • PubMed
    • Google Scholar
54. 1. Ghosh S
    2. Larson SD
    3. Hefzi H
    4. Marnoy Z
    5. Cutforth T
    6. Dokka K
    7. Baldwin KK

    (2011) Sensory maps in the olfactory cortex defined by long-range viral tracing of single neurons

    Nature 472:217–220.

    https://doi.org/10.1038/nature09945

    • PubMed
    • Google Scholar
55. 1. Gire DH
    2. Restrepo D
    3. Sejnowski TJ
    4. Greer C
    5. De Carlos JA
    6. Lopez-Mascaraque L

    (2013) Temporal processing in the olfactory system: can we see a smell?

    Neuron 78:416–432.

    https://doi.org/10.1016/j.neuron.2013.04.033

    • PubMed
    • Google Scholar
56. 1. Glover S
    2. Wall MB
    3. Smith AT

    (2012) Distinct cortical networks support the planning and online control of reaching-to-grasp in humans

    European Journal of Neuroscience 35:909–915.

    https://doi.org/10.1111/j.1460-9568.2012.08018.x

    • PubMed
    • Google Scholar
57. 1. Gonçalves Pereira PM
    2. Insausti R
    3. Artacho-Pérula E
    4. Salmenperä T
    5. Kälviäinen R
    6. Pitkänen A

    (2005)

    MR volumetric analysis of the piriform cortex and cortical amygdala in drug-refractory temporal lobe epilepsy

    AJNR. American Journal of Neuroradiology 26:319–332.

    • PubMed
    • Google Scholar
58. 1. Gottfried JA
    2. Deichmann R
    3. Winston JS
    4. Dolan RJ

    (2002) Functional heterogeneity in human olfactory cortex: an event-related functional magnetic resonance imaging study

    The Journal of Neuroscience 22:10819–10828.

    https://doi.org/10.1523/JNEUROSCI.22-24-10819.2002

    • PubMed
    • Google Scholar
59. 1. Gottfried JA
    2. Smith AP
    3. Rugg MD
    4. Dolan RJ

    (2004) Remembrance of odors past: human olfactory cortex in cross-modal recognition memory

    Neuron 42:687–695.

    https://doi.org/10.1016/S0896-6273(04)00270-3

    • PubMed
    • Google Scholar
60. 1. Gottfried JA
    2. Winston JS
    3. Dolan RJ

    (2006) Dissociable codes of odor quality and odorant structure in human piriform cortex

    Neuron 49:467–479.

    https://doi.org/10.1016/j.neuron.2006.01.007

    • PubMed
    • Google Scholar
61. 1. Gottfried JA

    (2010) Central mechanisms of odour object perception

    Nature Reviews Neuroscience 11:628–641.

    https://doi.org/10.1038/nrn2883

    • PubMed
    • Google Scholar
62. 1. Gottfried JA
    2. Dolan RJ

    (2003) The nose smells what the eye sees: crossmodal visual facilitation of human olfactory perception

    Neuron 39:375–386.

    https://doi.org/10.1016/S0896-6273(03)00392-1

    • PubMed
    • Google Scholar
63. 1. Gottfried JA
    2. Zald DH

    (2005) On the scent of human olfactory orbitofrontal cortex: meta-analysis and comparison to non-human primates

    Brain Research Reviews 50:287–304.

    https://doi.org/10.1016/j.brainresrev.2005.08.004

    • PubMed
    • Google Scholar
64. 1. Grau-Perales A
    2. Gómez-Chacón B
    3. Morillas E
    4. Gallo M

    (2019) Flavor recognition memory related activity of the posterior piriform cortex in adult and aged rats

    Behavioural Brain Research 360:196–201.

    https://doi.org/10.1016/j.bbr.2018.12.016

    • PubMed
    • Google Scholar
65. 1. Grill-Spector K
    2. Knouf N
    3. Kanwisher N

    (2004) The fusiform face area subserves face perception, not generic within-category identification

    Nature Neuroscience 7:555–562.

    https://doi.org/10.1038/nn1224

    • PubMed
    • Google Scholar
66. 1. Haberly LB

    (2001) Parallel-distributed processing in olfactory cortex: new insights from morphological and physiological analysis of neuronal circuitry

    Chemical Senses 26:551–576.

    https://doi.org/10.1093/chemse/26.5.551

    • PubMed
    • Google Scholar
67. 1. Haberly LB
    2. Price JL

    (1978) Association and commissural fiber systems of the olfactory cortex of the rat. I. systems originating in the piriform cortex and adjacent Areas

    The Journal of Comparative Neurology 178:711–740.

    https://doi.org/10.1002/cne.901780408

    • Google Scholar
68. 1. Haddad R
    2. Lanjuin A
    3. Madisen L
    4. Zeng H
    5. Murthy VN
    6. Uchida N

    (2013) Olfactory cortical neurons read out a relative time code in the olfactory bulb

    Nature Neuroscience 16:949–957.

    https://doi.org/10.1038/nn.3407

    • PubMed
    • Google Scholar
69. 1. Hagamen TC
    2. Greeley HP
    3. Hagamen WD
    4. Reeves AG

    (1977) Behavioral asymmetries following olfactory tubercle lesions in cats

    Brain, Behavior and Evolution 14:241–250.

    https://doi.org/10.1159/000125664

    • Google Scholar
70. 1. Hasselmo ME
    2. Barkai E

    (1995) Cholinergic modulation of activity-dependent synaptic plasticity in the piriform cortex and associative memory function in a network biophysical simulation

    The Journal of Neuroscience 15:6592–6604.

    https://doi.org/10.1523/JNEUROSCI.15-10-06592.1995

    • Google Scholar
71. 1. Herz RS
    2. McCall C
    3. Cahill L

    (1999) Hemispheric lateralization in the processing of odor pleasantness versus odor names

    Chemical Senses 24:691–695.

    https://doi.org/10.1093/chemse/24.6.691

    • PubMed
    • Google Scholar
72. 1. Hitt JC
    2. Bryon DM
    3. Modianos DT

    (1973) Effects of rostral medial forebrain bundle and olfactory tubercle lesions upon sexual behavior of male rats

    Journal of Comparative and Physiological Psychology 82:30–36.

    https://doi.org/10.1037/h0033797

    • PubMed
    • Google Scholar
73. 1. Howard JD
    2. Plailly J
    3. Grueschow M
    4. Haynes JD
    5. Gottfried JA

    (2009) Odor quality coding and categorization in human posterior piriform cortex

    Nature Neuroscience 12:932–938.

    https://doi.org/10.1038/nn.2324

    • PubMed
    • Google Scholar
74. 1. Howard JD
    2. Kahnt T
    3. Gottfried JA

    (2016) Converging prefrontal pathways support associative and perceptual features of conditioned stimuli

    Nature Communications 7:11546.

    https://doi.org/10.1038/ncomms11546

    • Google Scholar
75. 1. Howard JD
    2. Gottfried JA

    (2014) Configural and elemental coding of natural odor mixture components in the human brain

    Neuron 84:857–869.

    https://doi.org/10.1016/j.neuron.2014.10.012

    • PubMed
    • Google Scholar
76. 1. Hyman BT
    2. Arriagada PV
    3. Van Hoesen GW

    (1991) Pathologic changes in the olfactory system in aging and Alzheimer's disease

    Annals of the New York Academy of Sciences 640:14–19.

    https://doi.org/10.1111/j.1749-6632.1991.tb00184.x

    • PubMed
    • Google Scholar
77. 1. Igarashi KM
    2. Ieki N
    3. An M
    4. Yamaguchi Y
    5. Nagayama S
    6. Kobayakawa K
    7. Kobayakawa R
    8. Tanifuji M
    9. Sakano H
    10. Chen WR
    11. Mori K

    (2012) Parallel mitral and tufted cell pathways route distinct odor information to different targets in the olfactory cortex

    Journal of Neuroscience 32:7970–7985.

    https://doi.org/10.1523/JNEUROSCI.0154-12.2012

    • PubMed
    • Google Scholar
78. 1. Ikemoto S

    (2003) Involvement of the olfactory tubercle in cocaine reward: intracranial self-administration studies

    The Journal of Neuroscience 23:9305–9311.

    https://doi.org/10.1523/JNEUROSCI.23-28-09305.2003

    • PubMed
    • Google Scholar
79. 1. Ikemoto S

    (2007) Dopamine reward circuitry: two projection systems from the ventral midbrain to the nucleus accumbens-olfactory tubercle complex

    Brain Research Reviews 56:27–78.

    https://doi.org/10.1016/j.brainresrev.2007.05.004

    • PubMed
    • Google Scholar
80. 1. Illig KR

    (2005) Projections from orbitofrontal cortex to anterior piriform cortex in the rat suggest a role in olfactory information processing

    The Journal of Comparative Neurology 488:224–231.

    https://doi.org/10.1002/cne.20595

    • PubMed
    • Google Scholar
81. 1. Illig KR
    2. Haberly LB

    (2003) Odor-evoked activity is spatially distributed in piriform cortex

    The Journal of Comparative Neurology 457:361–373.

    https://doi.org/10.1002/cne.10557

    • PubMed
    • Google Scholar
82. 1. Insausti R
    2. Marcos P
    3. Arroyo-Jiménez MM
    4. Blaizot X
    5. Martínez-Marcos A

    (2002) Comparative aspects of the olfactory portion of the entorhinal cortex and its projection to the Hippocampus in rodents, nonhuman primates, and the human brain

    Brain Research Bulletin 57:557–560.

    https://doi.org/10.1016/S0361-9230(01)00684-0

    • PubMed
    • Google Scholar
83. 1. Iurilli G
    2. Datta SR

    (2017) Population coding in an innately relevant olfactory area

    Neuron 93:1180–1197.

    https://doi.org/10.1016/j.neuron.2017.02.010

    • PubMed
    • Google Scholar
84. 1. Jackson DC
    2. Mueller CJ
    3. Dolski I
    4. Dalton KM
    5. Nitschke JB
    6. Urry HL
    7. Rosenkranz MA
    8. Ryff CD
    9. Singer BH
    10. Davidson RJ

    (2003) Now you feel it, now you don't: frontal brain electrical asymmetry and individual differences in emotion regulation

    Psychological Science 14:612–617.

    https://doi.org/10.1046/j.0956-7976.2003.psci_1473.x

    • PubMed
    • Google Scholar
85. 1. Jenkinson M
    2. Beckmann CF
    3. Behrens TE
    4. Woolrich MW
    5. Smith SM

    (2012) FSL

    NeuroImage 62:782–790.

    https://doi.org/10.1016/j.neuroimage.2011.09.015

    • PubMed
    • Google Scholar
86. 1. Johnson DM
    2. Illig KR
    3. Behan M
    4. Haberly LB

    (2000) New features of connectivity in piriform cortex visualized by intracellular injection of pyramidal cells suggest that "primary" olfactory cortex functions like "association" cortex in other sensory systems

    The Journal of Neuroscience 20:6974–6982.

    https://doi.org/10.1523/JNEUROSCI.20-18-06974.2000

    • PubMed
    • Google Scholar
87. 1. Johnson-Frey SH
    2. Newman-Norlund R
    3. Grafton ST

    (2005) A distributed left hemisphere network active during planning of everyday tool use skills

    Cerebral Cortex 15:681–695.

    https://doi.org/10.1093/cercor/bhh169

    • PubMed
    • Google Scholar
88. 1. Kahnt T
    2. Chang LJ
    3. Park SQ
    4. Heinzle J
    5. Haynes JD

    (2012) Connectivity-based parcellation of the human orbitofrontal cortex

    Journal of Neuroscience 32:6240–6250.

    https://doi.org/10.1523/JNEUROSCI.0257-12.2012

    • PubMed
    • Google Scholar
89. 1. Kahnt T
    2. Tobler PN

    (2017) Dopamine modulates the functional organization of the orbitofrontal cortex

    The Journal of Neuroscience 37:1493–1504.

    https://doi.org/10.1523/JNEUROSCI.2827-16.2016

    • PubMed
    • Google Scholar
90. 1. Kanwisher N
    2. McDermott J
    3. Chun MM

    (1997) The fusiform face area: a module in human extrastriate cortex specialized for face perception

    The Journal of Neuroscience 17:4302–4311.

    https://doi.org/10.1523/JNEUROSCI.17-11-04302.1997

    • PubMed
    • Google Scholar
91. 1. Karunanayaka P
    2. Eslinger PJ
    3. Wang JL
    4. Weitekamp CW
    5. Molitoris S
    6. Gates KM
    7. Molenaar PC
    8. Yang QX

    (2014) Networks involved in olfaction and their dynamics using independent component analysis and unified structural equation modeling

    Human Brain Mapping 35:2055–2072.

    https://doi.org/10.1002/hbm.22312

    • PubMed
    • Google Scholar
92. 1. Karunanayaka PR
    2. Wilson DA
    3. Vasavada M
    4. Wang J
    5. Martinez B
    6. Tobia MJ
    7. Kong L
    8. Eslinger P
    9. Yang QX

    (2015) Rapidly acquired multisensory association in the olfactory cortex

    Brain and Behavior 5:e00390.

    https://doi.org/10.1002/brb3.390

    • PubMed
    • Google Scholar
93. 1. Karunanayaka P
    2. Tobia MJ
    3. Yang QX

    (2017) Age-related resting-state functional connectivity in the olfactory and trigeminal networks

    NeuroReport 28:943–948.

    https://doi.org/10.1097/WNR.0000000000000850

    • PubMed
    • Google Scholar
94. 1. Kauer JS

    (1991) Contributions of topography and parallel processing to odor coding in the vertebrate olfactory pathway

    Trends in Neurosciences 14:79–85.

    https://doi.org/10.1016/0166-2236(91)90025-P

    • PubMed
    • Google Scholar
95. 1. Kay RB
    2. Meyer EA
    3. Illig KR
    4. Brunjes PC

    (2011) Spatial distribution of neural activity in the anterior olfactory nucleus evoked by odor and electrical stimulation

    The Journal of Comparative Neurology 519:277–289.

    https://doi.org/10.1002/cne.22519

    • PubMed
    • Google Scholar
96. 1. Kay LM
    2. Freeman WJ

    (1998) Bidirectional processing in the olfactory-limbic Axis during olfactory behavior

    Behavioral Neuroscience 112:541–553.

    https://doi.org/10.1037/0735-7044.112.3.541

    • PubMed
    • Google Scholar
97. 1. Kikuta S
    2. Sato K
    3. Kashiwadani H
    4. Tsunoda K
    5. Yamasoba T
    6. Mori K

    (2010) From the cover: neurons in the anterior olfactory nucleus pars externa detect right or left localization of odor sources

    PNAS 107:12363–12368.

    https://doi.org/10.1073/pnas.1003999107

    • PubMed
    • Google Scholar
98. 1. Killgore WD
    2. Schwab ZJ
    3. Kipman M
    4. Deldonno SR
    5. Weber M

    (2013) Insomnia-related complaints correlate with functional connectivity between sensory-motor regions

    NeuroReport 24:233–240.

    https://doi.org/10.1097/WNR.0b013e32835edbdd

    • PubMed
    • Google Scholar
99. 1. Kiparizoska S
    2. Ikuta T

    (2017) Disrupted olfactory integration in schizophrenia: functional connectivity study

    International Journal of Neuropsychopharmacology 20:740–746.

    https://doi.org/10.1093/ijnp/pyx045

    • PubMed
    • Google Scholar
100. 1. Koch SBJ
     2. Mars RB
     3. Toni I
     4. Roelofs K

     (2018) Emotional control, reappraised

     Neuroscience & Biobehavioral Reviews 95:528–534.

     https://doi.org/10.1016/j.neubiorev.2018.11.003

     • PubMed
     • Google Scholar
101. 1. Koechlin E

     (2011) Frontal pole function: what is specifically human?

     Trends in Cognitive Sciences 15:241.

     https://doi.org/10.1016/j.tics.2011.04.005

     • PubMed
     • Google Scholar
102. 1. Kollndorfer K
     2. Fischmeister FPS
     3. Kowalczyk K
     4. Hoche E
     5. Mueller CA
     6. Trattnig S
     7. Schöpf V

     (2015) Olfactory training induces changes in regional functional connectivity in patients with long-term smell loss

     NeuroImage: Clinical 9:401–410.

     https://doi.org/10.1016/j.nicl.2015.09.004

     • Google Scholar
103. 1. Krusemark EA
     2. Novak LR
     3. Gitelman DR
     4. Li W

     (2013) When the sense of smell meets emotion: anxiety-state-dependent olfactory processing and neural circuitry adaptation

     The Journal of Neuroscience 33:15324–15332.

     https://doi.org/10.1523/JNEUROSCI.1835-13.2013

     • PubMed
     • Google Scholar
104. 1. Krusemark EA
     2. Li W

     (2012) Enhanced olfactory sensory perception of threat in anxiety: an event-related fMRI study

     Chemosensory Perception 5:37–45.

     https://doi.org/10.1007/s12078-011-9111-7

     • PubMed
     • Google Scholar
105. 1. Leff AP
     2. Schofield TM
     3. Crinion JT
     4. Seghier ML
     5. Grogan A
     6. Green DW
     7. Price CJ

     (2009) The left superior temporal gyrus is a shared substrate for auditory short-term memory and speech comprehension: evidence from 210 patients with stroke

     Brain 132:3401–3410.

     https://doi.org/10.1093/brain/awp273

     • PubMed
     • Google Scholar
106. 1. Lei H
     2. Mooney R
     3. Katz LC

     (2006) Synaptic integration of olfactory information in mouse anterior olfactory nucleus

     Journal of Neuroscience 26:12023–12032.

     https://doi.org/10.1523/JNEUROSCI.2598-06.2006

     • PubMed
     • Google Scholar
107. 1. Li W
     2. Luxenberg E
     3. Parrish T
     4. Gottfried JA

     (2006) Learning to smell the roses: experience-dependent neural plasticity in human piriform and orbitofrontal cortices

     Neuron 52:1097–1108.

     https://doi.org/10.1016/j.neuron.2006.10.026

     • PubMed
     • Google Scholar
108. 1. Li W
     2. Howard JD
     3. Parrish TB
     4. Gottfried JA

     (2008) Aversive learning enhances perceptual and cortical discrimination of indiscriminable odor cues

     Science 319:1842–1845.

     https://doi.org/10.1126/science.1152837

     • PubMed
     • Google Scholar
109. 1. Linster C
     2. Hasselmo ME

     (2001) Neuromodulation and the functional dynamics of piriform cortex

     Chemical Senses 26:585–594.

     https://doi.org/10.1093/chemse/26.5.585

     • PubMed
     • Google Scholar
110. Book

     1. Mai JK
     2. Majtanik M
     3. Paxinos G

     (2015)

     Atlas of the Human Brain (Fourth Edition)

     Academic Press.

     • Google Scholar
111. Book

     1. Mai JK
     2. Paxinos G

     (2012)

     The Human Nervous System (Third Edition)

     Elsevier.

     • Google Scholar
112. 1. Martin C
     2. Gervais R
     3. Messaoudi B
     4. Ravel N

     (2006) Learning-induced oscillatory activities correlated to odour recognition: a network activity

     European Journal of Neuroscience 23:1801–1810.

     https://doi.org/10.1111/j.1460-9568.2006.04711.x

     • PubMed
     • Google Scholar
113. 1. McCarthy G
     2. Puce A
     3. Gore JC
     4. Allison T

     (1997) Face-specific processing in the human fusiform gyrus

     Journal of Cognitive Neuroscience 9:605–610.

     https://doi.org/10.1162/jocn.1997.9.5.605

     • PubMed
     • Google Scholar
114. 1. McGann JP

     (2017) Poor human olfaction is a 19th-century myth

     Science 356:eaam7263.

     https://doi.org/10.1126/science.aam7263

     • PubMed
     • Google Scholar
115. 1. Milardi D
     2. Cacciola A
     3. Calamuneri A
     4. Ghilardi MF
     5. Caminiti F
     6. Cascio F
     7. Andronaco V
     8. Anastasi G
     9. Mormina E
     10. Arrigo A
     11. Bruschetta D
     12. Quartarone A

     (2017) The olfactory system revealed: non-invasive mapping by using constrained spherical deconvolution tractography in healthy humans

     Frontiers in Neuroanatomy 11:32.

     https://doi.org/10.3389/fnana.2017.00032

     • PubMed
     • Google Scholar
116. 1. Miyamichi K
     2. Amat F
     3. Moussavi F
     4. Wang C
     5. Wickersham I
     6. Wall NR
     7. Taniguchi H
     8. Tasic B
     9. Huang ZJ
     10. He Z
     11. Callaway EM
     12. Horowitz MA
     13. Luo L

     (2011) Cortical representations of olfactory input by trans-synaptic tracing

     Nature 472:191–196.

     https://doi.org/10.1038/nature09714

     • PubMed
     • Google Scholar
117. 1. Mori K
     2. Shepherd GM

     (1994) Emerging principles of molecular signal processing by mitral/tufted cells in the olfactory bulb

     Seminars in Cell Biology 5:65–74.

     https://doi.org/10.1006/scel.1994.1009

     • PubMed
     • Google Scholar
118. 1. Murakami M
     2. Kashiwadani H
     3. Kirino Y
     4. Mori K

     (2005) State-dependent sensory gating in olfactory cortex

     Neuron 46:285–296.

     https://doi.org/10.1016/j.neuron.2005.02.025

     • PubMed
     • Google Scholar
119. 1. Murphy K
     2. Birn RM
     3. Handwerker DA
     4. Jones TB
     5. Bandettini PA

     (2009) The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

     NeuroImage 44:893–905.

     https://doi.org/10.1016/j.neuroimage.2008.09.036

     • PubMed
     • Google Scholar
120. 1. Myhrer T
     2. Enger S
     3. Aas P

     (2010) Roles of perirhinal and posterior piriform cortices in control and generation of seizures: a microinfusion study in rats exposed to soman

     NeuroToxicology 31:147–153.

     https://doi.org/10.1016/j.neuro.2009.10.002

     • PubMed
     • Google Scholar
121. 1. Nagayama S
     2. Enerva A
     3. Fletcher ML
     4. Masurkar AV
     5. Igarashi KM
     6. Mori K
     7. Chen WR

     (2010) Differential axonal projection of mitral and tufted cells in the mouse main olfactory system

     Frontiers in Neural Circuits 4:.

     https://doi.org/10.3389/fncir.2010.00120

     • PubMed
     • Google Scholar
122. 1. Nigri A
     2. Ferraro S
     3. D'Incerti L
     4. Critchley HD
     5. Bruzzone MG
     6. Minati L

     (2013) Connectivity of the amygdala, piriform, and orbitofrontal cortex during olfactory stimulation: a functional MRI study

     NeuroReport 24:171–175.

     https://doi.org/10.1097/WNR.0b013e32835d5d2b

     • PubMed
     • Google Scholar
123. 1. Oettl LL
     2. Ravi N
     3. Schneider M
     4. Scheller MF
     5. Schneider P
     6. Mitre M
     7. da Silva Gouveia M
     8. Froemke RC
     9. Chao MV
     10. Young WS
     11. Meyer-Lindenberg A
     12. Grinevich V
     13. Shusterman R
     14. Kelsch W

     (2016) Oxytocin enhances social recognition by modulating cortical control of early olfactory processing

     Neuron 90:609–621.

     https://doi.org/10.1016/j.neuron.2016.03.033

     • PubMed
     • Google Scholar
124. 1. Olman CA
     2. Davachi L
     3. Inati S

     (2009) Distortion and signal loss in medial temporal lobe

     PLOS ONE 4:e8160.

     https://doi.org/10.1371/journal.pone.0008160

     • PubMed
     • Google Scholar
125. 1. Olofsson JK
     2. Rogalski E
     3. Harrison T
     4. Mesulam MM
     5. Gottfried JA

     (2013) A cortical pathway to olfactory naming: evidence from primary progressive aphasia

     Brain 136:1245–1259.

     https://doi.org/10.1093/brain/awt019

     • PubMed
     • Google Scholar
126. 1. Olofsson JK
     2. Gottfried JA

     (2015) The muted sense: neurocognitive limitations of olfactory language

     Trends in Cognitive Sciences 19:314–321.

     https://doi.org/10.1016/j.tics.2015.04.007

     • PubMed
     • Google Scholar
127. 1. Ongür D
     2. Ferry AT
     3. Price JL

     (2003) Architectonic subdivision of the human orbital and medial prefrontal cortex

     The Journal of Comparative Neurology 460:425–449.

     https://doi.org/10.1002/cne.10609

     • PubMed
     • Google Scholar
128. 1. Papmeyer M
     2. Giles S
     3. Sussmann JE
     4. Kielty S
     5. Stewart T
     6. Lawrie SM
     7. Whalley HC
     8. McIntosh AM

     (2015) Cortical thickness in individuals at high familial risk of mood disorders as they develop major depressive disorder

     Biological Psychiatry 78:58–66.

     https://doi.org/10.1016/j.biopsych.2014.10.018

     • PubMed
     • Google Scholar
129. 1. Payton CA
     2. Wilson DA
     3. Wesson DW

     (2012) Parallel odor processing by two anatomically distinct olfactory bulb target structures

     PLOS ONE 7:e34926.

     https://doi.org/10.1371/journal.pone.0034926

     • PubMed
     • Google Scholar
130. 1. Pence TS
     2. Reiter ER
     3. DiNardo LJ
     4. Costanzo RM

     (2014) Risk factors for hazardous events in olfactory-impaired patients

     JAMA Otolaryngology–Head & Neck Surgery 140:951–955.

     https://doi.org/10.1001/jamaoto.2014.1675

     • PubMed
     • Google Scholar
131. 1. Pigache RM

     (1970) The anatomy of "paleocortex". A critical review

     Ergebnisse Der Anatomie Und Entwicklungsgeschichte 43:3–62.

     https://doi.org/10.1007/978-3-642-65004-8

     • PubMed
     • Google Scholar
132. 1. Plailly J
     2. Delon-Martin C
     3. Royet JP

     (2012) Experience induces functional reorganization in brain regions involved in odor imagery in perfumers

     Human Brain Mapping 33:224–234.

     https://doi.org/10.1002/hbm.21207

     • PubMed
     • Google Scholar
133. 1. Poo C
     2. Isaacson JS

     (2009) Odor representations in olfactory cortex: "sparse" coding, global inhibition, and oscillations

     Neuron 62:850–861.

     https://doi.org/10.1016/j.neuron.2009.05.022

     • PubMed
     • Google Scholar
134. 1. Porter J
     2. Anand T
     3. Johnson B
     4. Khan RM
     5. Sobel N

     (2005) Brain mechanisms for extracting spatial information from smell

     Neuron 47:581–592.

     https://doi.org/10.1016/j.neuron.2005.06.028

     • PubMed
     • Google Scholar
135. 1. Porter J
     2. Craven B
     3. Khan RM
     4. Chang SJ
     5. Kang I
     6. Judkewitz B
     7. Judkewicz B
     8. Volpe J
     9. Settles G
     10. Sobel N

     (2007) Mechanisms of scent-tracking in humans

     Nature Neuroscience 10:27–29.

     https://doi.org/10.1038/nn1819

     • PubMed
     • Google Scholar
136. Book

     1. Price JL

     (2009)

     Olfactory higher centers anatomy

     In: Squire L. arryR, editors. Encyclopedia Neuroscience. Academic Press. pp. 129–136.

     • Google Scholar
137. 1. Rennaker RL
     2. Chen CF
     3. Ruyle AM
     4. Sloan AM
     5. Wilson DA

     (2007) Spatial and temporal distribution of odorant-evoked activity in the piriform cortex

     Journal of Neuroscience 27:1534–1542.

     https://doi.org/10.1523/JNEUROSCI.4072-06.2007

     • PubMed
     • Google Scholar
138. 1. Roesch MR
     2. Stalnaker TA
     3. Schoenbaum G

     (2007) Associative encoding in anterior piriform cortex versus orbitofrontal cortex during odor discrimination and reversal learning

     Cerebral Cortex 17:643–652.

     https://doi.org/10.1093/cercor/bhk009

     • PubMed
     • Google Scholar
139. 1. Royet JP
     2. Plailly J

     (2004) Lateralization of olfactory processes

     Chemical Senses 29:731–745.

     https://doi.org/10.1093/chemse/bjh067

     • PubMed
     • Google Scholar
140. 1. Sacco T
     2. Sacchetti B

     (2010) Role of secondary sensory cortices in emotional memory storage and retrieval in rats

     Science 329:649–656.

     https://doi.org/10.1126/science.1183165

     • PubMed
     • Google Scholar
141. 1. Sadrian B
     2. Wilson DA

     (2015) Optogenetic stimulation of lateral amygdala input to posterior piriform cortex modulates Single-Unit and ensemble odor processing

     Frontiers in Neural Circuits 9:81.

     https://doi.org/10.3389/fncir.2015.00081

     • PubMed
     • Google Scholar
142. 1. Savic I
     2. Gulyas B
     3. Larsson M
     4. Roland P

     (2000) Olfactory functions are mediated by parallel and hierarchical processing

     Neuron 26:735–745.

     https://doi.org/10.1016/S0896-6273(00)81209-X

     • PubMed
     • Google Scholar
143. 1. Schoenbaum G
     2. Eichenbaum H

     (1995) Information coding in the rodent prefrontal cortex. I. Single-neuron activity in orbitofrontal cortex compared with that in pyriform cortex

     Journal of Neurophysiology 74:733–750.

     https://doi.org/10.1152/jn.1995.74.2.733

     • PubMed
     • Google Scholar
144. 1. Schulze P
     2. Bestgen AK
     3. Lech RK
     4. Kuchinke L
     5. Suchan B

     (2017) Preprocessing of emotional visual information in the human piriform cortex

     Scientific Reports 7:9191.

     https://doi.org/10.1038/s41598-017-09295-x

     • PubMed
     • Google Scholar
145. 1. Scott JW
     2. McBride RL
     3. Schneider SP

     (1980) The organization of projections from the olfactory bulb to the piriform cortex and olfactory tubercle in the rat

     The Journal of Comparative Neurology 194:519–534.

     https://doi.org/10.1002/cne.901940304

     • PubMed
     • Google Scholar
146. 1. Segerdahl AR
     2. Mezue M
     3. Okell TW
     4. Farrar JT
     5. Tracey I

     (2015) The dorsal posterior insula subserves a fundamental role in human pain

     Nature Neuroscience 18:499–500.

     https://doi.org/10.1038/nn.3969

     • PubMed
     • Google Scholar
147. 1. Seubert J
     2. Freiherr J
     3. Djordjevic J
     4. Lundström JN

     (2013) Statistical localization of human olfactory cortex

     NeuroImage 66:333–342.

     https://doi.org/10.1016/j.neuroimage.2012.10.030

     • PubMed
     • Google Scholar
148. Book

     1. Shepherd GM
     2. Chen WR
     3. Greer CA

     (2004) Olfactory bulb.The Synaptic Organization of the Brain

     Oxford University Press.

     https://doi.org/10.1093/acprof:oso/9780195159561.003.0005

     • Google Scholar
149. 1. Shipley MT
     2. Adamek GD

     (1984) The connections of the mouse olfactory bulb: a study using orthograde and retrograde transport of wheat germ agglutinin conjugated to horseradish peroxidase

     Brain Research Bulletin 12:669–688.

     https://doi.org/10.1016/0361-9230(84)90148-5

     • PubMed
     • Google Scholar
150. 1. Shipley M
     2. Reyes P

     (1991)

     Anatomy of the Human Olfactory Bulb and Central Olfactory Pathways

     The Human Sense of Smell, Anatomy of the Human Olfactory Bulb and Central Olfactory Pathways, 60, Berlin, Springer.

     • Google Scholar
151. 1. Smith SM

     (2002) Fast robust automated brain extraction

     Human Brain Mapping 17:143–155.

     https://doi.org/10.1002/hbm.10062

     • PubMed
     • Google Scholar
152. 1. Smith SM
     2. Jenkinson M
     3. Woolrich MW
     4. Beckmann CF
     5. Behrens TE
     6. Johansen-Berg H
     7. Bannister PR
     8. De Luca M
     9. Drobnjak I
     10. Flitney DE
     11. Niazy RK
     12. Saunders J
     13. Vickers J
     14. Zhang Y
     15. De Stefano N
     16. Brady JM
     17. Matthews PM

     (2004) Advances in functional and structural MR image analysis and implementation as FSL

     NeuroImage 23:S208–S219.

     https://doi.org/10.1016/j.neuroimage.2004.07.051

     • PubMed
     • Google Scholar
153. 1. Smith SM
     2. Nichols TE

     (2009) Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference

     NeuroImage 44:83–98.

     https://doi.org/10.1016/j.neuroimage.2008.03.061

     • PubMed
     • Google Scholar
154. 1. Sobel N
     2. Prabhakaran V
     3. Hartley CA
     4. Desmond JE
     5. Glover GH
     6. Sullivan EV
     7. Gabrieli JD

     (1999) Blind smell: brain activation induced by an undetected air-borne chemical

     Brain 122 Pt 2:209–217.

     https://doi.org/10.1093/brain/122.2.209

     • PubMed
     • Google Scholar
155. 1. Sobel N
     2. Prabhakaran V
     3. Zhao Z
     4. Desmond JE
     5. Glover GH
     6. Sullivan EV
     7. Gabrieli JD

     (2000) Time course of odorant-induced activation in the human primary olfactory cortex

     Journal of Neurophysiology 83:537–551.

     https://doi.org/10.1152/jn.2000.83.1.537

     • PubMed
     • Google Scholar
156. 1. Sosulski DL
     2. Bloom ML
     3. Cutforth T
     4. Axel R
     5. Datta SR

     (2011) Distinct representations of olfactory information in different cortical centres

     Nature 472:213–216.

     https://doi.org/10.1038/nature09868

     • Google Scholar
157. 1. Sreenivasan K
     2. Zhuang X
     3. Banks SJ
     4. Mishra V
     5. Yang Z
     6. Deshpande G
     7. Cordes D

     (2017) Olfactory network differences in master sommeliers: connectivity analysis using Granger causality and graph theoretical approach

     Brain Connectivity 7:123–136.

     https://doi.org/10.1089/brain.2016.0458

     • PubMed
     • Google Scholar
158. 1. Stettler DD
     2. Axel R

     (2009) Representations of odor in the piriform cortex

     Neuron 63:854–864.

     https://doi.org/10.1016/j.neuron.2009.09.005

     • PubMed
     • Google Scholar
159. 1. Sugai T
     2. Miyazawa T
     3. Fukuda M
     4. Yoshimura H
     5. Onoda N

     (2005) Odor-concentration coding in the guinea-pig piriform cortex

     Neuroscience 130:769–781.

     https://doi.org/10.1016/j.neuroscience.2004.09.059

     • PubMed
     • Google Scholar
160. 1. Sunwoo MK
     2. Cha J
     3. Ham JH
     4. Song SK
     5. Hong JY
     6. Lee JM
     7. Sohn YH
     8. Lee PH

     (2015) Olfactory performance and resting state functional connectivity in non-demented drug naïve patients with Parkinson's disease

     Human Brain Mapping 36:1716–1727.

     https://doi.org/10.1002/hbm.22732

     • PubMed
     • Google Scholar
161. 1. Todd N
     2. Moeller S
     3. Auerbach EJ
     4. Yacoub E
     5. Flandin G
     6. Weiskopf N

     (2016) Evaluation of 2D multiband EPI imaging for high-resolution, whole-brain, task-based fMRI studies at 3T: sensitivity and slice leakage artifacts

     NeuroImage 124:32–42.

     https://doi.org/10.1016/j.neuroimage.2015.08.056

     • PubMed
     • Google Scholar
162. 1. Ubeda-Bañon I
     2. Flores-Cuadrado A
     3. Saiz-Sanchez D
     4. Martinez-Marcos A

     (2017) Differential effects of Parkinson's disease on interneuron subtypes within the human anterior olfactory nucleus

     Frontiers in Neuroanatomy 11:113.

     https://doi.org/10.3389/fnana.2017.00113

     • PubMed
     • Google Scholar
163. 1. Valverde F
     2. López-Mascaraque L
     3. De Carlos JA

     (1989) Structure of the nucleus olfactorius anterior of the hedgehog (Erinaceus europaeus)

     The Journal of Comparative Neurology 279:581–600.

     https://doi.org/10.1002/cne.902790407

     • PubMed
     • Google Scholar
164. 1. Vassar R
     2. Chao SK
     3. Sitcheran R
     4. Nuñez JM
     5. Vosshall LB
     6. Axel R

     (1994) Topographic organization of sensory projections to the olfactory bulb

     Cell 79:981–991.

     https://doi.org/10.1016/0092-8674(94)90029-9

     • PubMed
     • Google Scholar
165. 1. Vaughan DN
     2. Jackson GD

     (2014) The piriform cortex and human focal epilepsy

     Frontiers in Neurology 5:259.

     https://doi.org/10.3389/fneur.2014.00259

     • PubMed
     • Google Scholar
166. 1. Veer IM
     2. Beckmann CF
     3. van Tol MJ
     4. Ferrarini L
     5. Milles J
     6. Veltman DJ
     7. Aleman A
     8. van Buchem MA
     9. van der Wee NJ
     10. Rombouts SA

     (2010) Whole brain resting-state analysis reveals decreased functional connectivity in major depression

     Frontiers in Systems Neuroscience 4:.

     https://doi.org/10.3389/fnsys.2010.00041

     • PubMed
     • Google Scholar
167. 1. Walla P
     2. Hufnagl B
     3. Lehrner J
     4. Mayer D
     5. Lindinger G
     6. Imhof H
     7. Deecke L
     8. Lang W

     (2003) Olfaction and face encoding in humans: a magnetoencephalographic study

     Cognitive Brain Research 15:105–115.

     https://doi.org/10.1016/S0926-6410(02)00144-1

     • PubMed
     • Google Scholar
168. 1. Walla P

     (2008) Olfaction and its dynamic influence on word and face processing: cross-modal integration

     Progress in Neurobiology 84:192–209.

     https://doi.org/10.1016/j.pneurobio.2007.10.005

     • PubMed
     • Google Scholar
169. 1. Wang J
     2. Eslinger PJ
     3. Smith MB
     4. Yang QX

     (2005) Functional magnetic resonance imaging study of human olfaction and normal aging

     The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 60:510–514.

     https://doi.org/10.1093/gerona/60.4.510

     • PubMed
     • Google Scholar
170. 1. Wang J
     2. Eslinger PJ
     3. Doty RL
     4. Zimmerman EK
     5. Grunfeld R
     6. Sun X
     7. Meadowcroft MD
     8. Connor JR
     9. Price JL
     10. Smith MB
     11. Yang QX

     (2010) Olfactory deficit detected by fMRI in early Alzheimer's disease

     Brain Research 1357:184–194.

     https://doi.org/10.1016/j.brainres.2010.08.018

     • PubMed
     • Google Scholar
171. 1. Wang Z
     2. Wang J
     3. Zhang H
     4. Mchugh R
     5. Sun X
     6. Li K
     7. Yang QX

     (2015) Interhemispheric functional and structural disconnection in Alzheimer's Disease: A Combined Resting-State fMRI and DTI Study

     PLOS ONE 10:e0126310.

     https://doi.org/10.1371/journal.pone.0126310

     • PubMed
     • Google Scholar
172. 1. Wang J
     2. Xie S
     3. Guo X
     4. Becker B
     5. Fox PT
     6. Eickhoff SB
     7. Jiang T

     (2017) Correspondent functional topography of the human left inferior parietal lobule at rest and under task revealed using Resting-State fMRI and coactivation based parcellation

     Human Brain Mapping 38:1659–1675.

     https://doi.org/10.1002/hbm.23488

     • Google Scholar
173. 1. Wesson DW
     2. Wilson DA

     (2010) Smelling sounds: olfactory-auditory sensory convergence in the olfactory tubercle

     Journal of Neuroscience 30:3013–3021.

     https://doi.org/10.1523/JNEUROSCI.6003-09.2010

     • PubMed
     • Google Scholar
174. 1. Wesson DW
     2. Wilson DA

     (2011) Sniffing out the contributions of the olfactory tubercle to the sense of smell: hedonics, sensory integration, and more?

     Neuroscience & Biobehavioral Reviews 35:655–668.

     https://doi.org/10.1016/j.neubiorev.2010.08.004

     • PubMed
     • Google Scholar
175. 1. Wible B
     2. Nicol T
     3. Kraus N

     (2005) Correlation between brainstem and cortical auditory processes in normal and language-impaired children

     Brain 128:417–423.

     https://doi.org/10.1093/brain/awh367

     • PubMed
     • Google Scholar
176. Book

     1. Wilson DA

     (2009) Olfactory cortex physiology

     In: Squire L. R, editors. Encyclopedia of Neuroscience. Academic Press. pp. 95–100.

     https://doi.org/10.1016/B978-008045046-9.01690-9

     • Google Scholar
177. 1. Wilson DA
     2. Sullivan RM

     (2011) Cortical processing of odor objects

     Neuron 72:506–519.

     https://doi.org/10.1016/j.neuron.2011.10.027

     • PubMed
     • Google Scholar
178. 1. Woo MA
     2. Kumar R
     3. Macey PM
     4. Fonarow GC
     5. Harper RM

     (2009) Brain injury in autonomic, emotional, and cognitive regulatory areas in patients with heart failure

     Journal of Cardiac Failure 15:214–223.

     https://doi.org/10.1016/j.cardfail.2008.10.020

     • PubMed
     • Google Scholar
179. 1. Woolrich MW
     2. Jbabdi S
     3. Patenaude B
     4. Chappell M
     5. Makni S
     6. Behrens T
     7. Beckmann C
     8. Jenkinson M
     9. Smith SM

     (2009) Bayesian analysis of neuroimaging data in FSL

     NeuroImage 45:S173–S186.

     https://doi.org/10.1016/j.neuroimage.2008.10.055

     • PubMed
     • Google Scholar
180. 1. Yang J
     2. Litscher G
     3. Sun Z
     4. Tang Q
     5. Kishi K
     6. Oda S
     7. Takayanagi M
     8. Sheng Z
     9. Liu Y
     10. Guo W
     11. Zhang T
     12. Wang L
     13. Gaischek I
     14. Litscher D
     15. Lippe IT
     16. Kuroda M

     (2017) Quantitative analysis of axon collaterals of single pyramidal cells of the anterior piriform cortex of the guinea pig

     BMC Neuroscience 18:25.

     https://doi.org/10.1186/s12868-017-0342-7

     • PubMed
     • Google Scholar
181. 1. Yeomans MR

     (2006) Olfactory influences on appetite and satiety in humans

     Physiology & Behavior 87:800–804.

     https://doi.org/10.1016/j.physbeh.2006.01.029

     • PubMed
     • Google Scholar
182. 1. Young JC
     2. Vaughan DN
     3. Paolini AG
     4. Jackson GD

     (2018) Electrical stimulation of the piriform cortex for the treatment of epilepsy: a review of the supporting evidence

     Epilepsy & Behavior 88:152–161.

     https://doi.org/10.1016/j.yebeh.2018.09.004

     • PubMed
     • Google Scholar
183. 1. Zatorre RJ
     2. Jones-Gotman M
     3. Evans AC
     4. Meyer E

     (1992) Functional localization and lateralization of human olfactory cortex

     Nature 360:339–340.

     https://doi.org/10.1038/360339a0

     • PubMed
     • Google Scholar
184. 1. Zelano C
     2. Bensafi M
     3. Porter J
     4. Mainland J
     5. Johnson B
     6. Bremner E
     7. Telles C
     8. Khan R
     9. Sobel N

     (2005) Attentional modulation in human primary olfactory cortex

     Nature Neuroscience 8:114–120.

     https://doi.org/10.1038/nn1368

     • PubMed
     • Google Scholar
185. 1. Zelano C
     2. Mohanty A
     3. Gottfried JA

     (2011) Olfactory predictive codes and stimulus templates in piriform cortex

     Neuron 72:178–187.

     https://doi.org/10.1016/j.neuron.2011.08.010

     • PubMed
     • Google Scholar
186. Software

     1. Zelano Lab

     (2019) primaryolfactorycortexparcellation, version bee3e9d

     Github.

     https://github.com/zelanolab/primaryolfactorycortexparcellation
187. 1. Zhan C
     2. Luo M

     (2010) Diverse patterns of odor representation by neurons in the anterior piriform cortex of awake mice

     Journal of Neuroscience 30:16662–16672.

     https://doi.org/10.1523/JNEUROSCI.4400-10.2010

     • PubMed
     • Google Scholar
188. 1. Zhang Y
     2. Brady M
     3. Smith S

     (2001) Segmentation of brain MR images through a hidden markov random field model and the expectation-maximization algorithm

     IEEE Transactions on Medical Imaging 20:45–57.

     https://doi.org/10.1109/42.906424

     • PubMed
     • Google Scholar

Thank you for submitting your article "Characterizing functional pathways of the human olfactory system" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a guest Reviewing Editor and Joshua Gold as the Senior Editor. The following individual involved in review of your submission has agreed to reveal his identity: Jonas Olofsson (Reviewer #1).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

The majority of our knowledge regarding primary olfactory cortex anatomy comes from rodents and the field needs more human data. This study uses brain imaging to add additional functional annotation to the human primary olfactory cortex.

Essential revisions:

Several reviewers asked for a more thorough review of the previous literature using fMRI to measure connectivity. Please revise the manuscript to place this study in context of previous work.

Additionally, the reviewers raised concerns and made a number of suggestions regarding technical aspects, lateralization, and addressing individual variability. Please see below for the individual points and address them as much as possible.

Reviewer #1:

The manuscript by Lane et al. describes an experiment whereby functional Magnetic Resonance Imaging connectivity analysis was used to parcellate the human primary olfactory cortex into separate connective pathways. Results suggest four distinct pathways emanating from primary areas (those receiving direct input from the olfactory bulb).

This manuscript is well written, especially considering the rodent neuroanatomical work which is covered in detail, and the results, which are clearly explained. Importantly, the study addresses a key issue in human olfaction, that of the presumed complementary roles of primary olfactory areas and how to define them. Prior work has used seed regions in the piriform, and sometimes even orbitofrontal, cortex to study the connectivity patterns of the olfactory system. The current study provides a more in-depth view, and will facilitate future comparisons within the olfactory network and across sensory systems. The independent validation dataset strengthens the authors' conclusions.

Overall, the study will provide a nice addition to the literature on human olfactory system connectivity, especially since the literature is currently very limited. I have a few issues for the authors to address, these issues are listed below.

The manuscript does not cite the small number of prior studies on fMRI connectivity of the olfactory cortex and it does not adequately describe how the present approach is different from that of prior work of the same kind.

Please motivate your definition of primary olfactory cortex, given the notion that the olfactory bulb is by some considered primary cortex.

Although the methods appear later in the text, there should be an early citation or mentioning of the dataset and its resting-state methodology; only the validation dataset is mentioned in the early stages of the main text.

Discuss the commonly observed problem of poor signal-to-noise ratio in olfactory regions and how the authors avoided the risk of biasing their results due to poor/variable SNR.

You found a mean correlation coefficient of 0.19 (SE 0.0041), how does that compare with prior applications of this method on similar data sets (e.g. Kahnt et al., 2012)? Please provide support for the claim that there is good similarity.

It is interesting to note that AON has a stronger lateralization pattern. Why do you think that is the case, and what are the possible implications? Does it imply a specific functional role or might it be an artifact, or evidence of less well-defined network memberships?

Please provide references for the olfactory interactions with the language regions, as is hypothesized in Discussion.

Regarding the framework, is might be noted that the shared connectivity with the OFC might explain why it is so reliably elicited even in basic/passive olfactory tasks; all primary regions project to it. Furthermore, regarding the connectivity patterns of the frontal piriform to regions responsible for facial movements, might this include sniffing?

It is a bit of a stretch to state that there is a "large body of evidence" suggesting olfaction is lateralized to the right side. The literature is in fact quite inconsistent. I suggest tempering this claim and also adding another more recent supporting citation.

Reviewer #2:

The conclusion appears somewhat weak: "… Our results provide important insight into the functional and anatomical organization of the human olfactory system…" Please be more detailed in terms of the significance of these findings and the consequences of it. Do we have to look at olfactory information processing differently from today on? Please speculate: Does this demonstration of parallel processing of olfactory information explain the vulnerability in aging? Or the decrease of olfactory functioning in depression? Other consequences?

Please compare the parallel processing n the olfactory system to other systems? How is that in taste? Touch?

I was always under the assumption that the AON in humans is part of the olfactory bulb (see Daniel and Hawkes, 1992; Hyman, Arriagada and Van Hoesen, 1991). Maybe you can discuss these discrepancies, too.

The authors talk about the olfactory tubercle. This is despite the anatomical impression that there is no bump in this vicinity. In fact the anterior perforated substance has been proposed as its human homologue (see Freiherr, Wiesmann, Witt in Welge-Luessen, Hummel (eds): 2014, Management of Smell and Taste Disorders; Theme, Stuttgart). Please comment.

It would be extremely valuable for the reader if the authors came up with a sketch that graphically summarizes the results in terms of the strength of the connectivity between the various regions.

Although difficult to do (and although the authors already pay a lot of attention to that), it would be excellent if the authors could try to separate more clearly between research that comes from animals and research on humans.

Reviewer #3:

Odor processing starts with transduction in the olfactory epithelium and continues with treatment in the olfactory bulb and cortical processing in primary and so-called secondary areas. In mammals, we have very good understanding of the anatomy and the functionality of these areas. In contrast, the functional neuroanatomy of human olfaction remains poorly understood. In this paper, Zhou and colleagues provide a significant contribution to this field by highlighting that the human primary olfactory cortex is clustered into sub-regions that anatomically corresponded to the anterior olfactory nucleus, olfactory tubercle and frontal and temporal piriform cortices. Furthermore, a dissociation in the whole-brain functional connectivity patterns was observed across the different sub-areas of the primary olfactory cortex suggesting the existence of distinct parallel processing pathways. The paper is very well written and the method used are innovative in the field of olfaction (data-driven connectivity-based parcellation techniques). My comments are below.

- Subsection “Parcellation results across hemispheres and k values”: Why it is important to combine data from both hemispheres? Asymmetry in human olfactory processing has been documented, especially by the Zatorre group in the early 90's and more recently in different studies. I would like to see how not merging the 2 hemispheres change the findings.

- The authors mentioned “Note that additional primary olfactory areas, including anterior cortical and peri- amygdala areas and entorhinal cortex (Allison, 1954; Carmichael et al., 1994; Eslinger et al., 1982; Gonçalves Pereira et al., 2005; Zatorre et al., 1992), were not included in our ROI because the exact location of olfactory afferents into these areas is poorly understood.”. I am wondering whether some areas included in the ROI (tubercule, AON), are less “poorly understood” than entorhinal cortex or amygdala in humans. Could the authors provide some more rationales for excluding these areas from the ROI?

In the same line, the authors wrote: “Interestingly, connectivity clusters were generally more extensive in the right hemisphere compared to the left hemisphere, supporting a large body of evidence suggesting that olfactory processing is lateralized to the right side (Zatorre et al., 1992).” So, why not considering the primary olfactory cortices separately from the right and the left hemispheres? There is much to gain in showing these data.

- The authors stated that “We then estimated the whole-brain functional connectivity profile of each voxel within the ROI by computing the Pearson correlation coefficient between the resting-state fMRI time-series of a given voxel and that of every other voxel in the rest of the brain. This resulted in subject-wise connectivity matrices, which were then averaged across all subjects.” Does this mean that individual variability is not considered in the rest of the analysis? If yes, how the authors could be sure that the values in the averaged matrix are not due to a sub-sample of subjects?

- In the same line, the authors wrote “To examine the similarity between the individual functional connectivity matrices, we computed a histogram of correlation values between individual matrixes and the groups matrix using a leave-one-out method (Kahnt et al., 2012). The results indicate a good similarity between the group-level and individual functional connectivity patterns (mean correlation coefficient: 0.19, standard error: 0.0041, Figure 2A).”. I can understand that the notion of similarity is relative, but here the averaged r-value is less than 0.20 which means that half of the data fall within a range of 0 to 0.20. I may not understand properly this analysis but to my view it seems that these r-values are low. Could you comment on that? Moreover, the authors must mention the significativity of these correlative analyses. Even if significant, there is a need to detail how many data-points were computed in these analyses and how such low r-values can be interpreted?

- Participants were “instructed to look at a white fixation cross on a black background and breath in-out through their nose.” As the authors know, and they are expert in the field, respiration can alter odor processing. Is there any effect of Nasal breathing on the brain imaging findings? If nasal respiration was measured, in addition to motion correction, the authors should correct for nasal breathing activity.

Reviewer #1:

[…] Overall, the study will provide a nice addition to the literature on human olfactory system connectivity, especially since the literature is currently very limited. I have a few issues for the authors to address, these issues are listed below.

The manuscript does not cite the small number of prior studies on fMRI connectivity of the olfactory cortex and it does not adequately describe how the present approach is different from that of prior work of the same kind.

This is a very important point, and we are grateful for being made aware of having missed important previous work. We have modified the Introduction to include a discussion of the following studies. We would be grateful if you could bring our attention to any additional studies we might have missed.

We now include a discussion of the following:

Banks et al., 2016; Caffo et al., 2010; Cecchetto et al., 2019; Fjaeldstad et al., 2017; Karunanayaka et al., 2014.; Karunanayaka, Tobia and Yang, 2017; Killgore et al., 2013; Kiparizoska and Ikuta2017; Kollndorfer et al., 2015; Krusemark and Li, 2012; Nigri et al., 2013; Sreenivasan et al., 2017; Sunwoo et al., 2015; Wang et al.,2010; Wang et al., 2005.; Wang et al., 2015.

Please motivate your definition of primary olfactory cortex, given the notion that the olfactory bulb is by some considered primary cortex.

We agree with you that the olfactory bulb is considered by some to be “primary olfactory cortex”. However, we feel that the “classic” and dominant terminology in the field still uses the term “primary olfactory cortex” to refer to structures that receive direct input from the olfactory bulb. For example, in Olfactory Cortex: Comparative Anatomy, Illig and Wilson discuss the concept that the olfactory bulb may perform primary sensory cortical functions, but still mention that piriform cortex is typically referred to as primary olfactory cortex. Most book chapters, reviews and studies still refer to primary olfactory cortex as brain areas that receive direct bulb projections. We feel it would be confusing to introduce new terminology in this manuscript, and might take away from the primary goal of our study, which was to provide a quantitative characterization of the parallel processing pathways of the human olfactory system. In humans, these parallel pathways occur downstream of the olfactory bulb. Thus, the important point here is not so much whether we are characterizing primary versus secondary olfactory cortex, but that we are characterizing the parallel pathways, all of which receive direct projections from the olfactory bulb. That said, your point is highly relevant for this paper, and reflects an important emerging movement in the field towards the idea that the classic terminology is flawed. Further, our initial phrasing of this in the Introduction may have mis-characterized the Wilson, 2009 reference. We have clarified these points in the second paragraph of the Introduction. We now initially refer to these areas as the cortical targets of olfactory bulb projections, and we refer readers to papers that discuss the accuracy of their being collectively termed “primary olfactory cortex”.

Although the methods appear later in the text, there should be an early citation or mentioning of the dataset and its resting-state methodology; only the validation dataset is mentioned in the early stages of the main text.

Very good point, thank you. This will make the paper read more clearly. We have added details about the dataset into the beginning of the Results section: “Twenty-five subjects (average ± standard error age: 25.5 ± 1.2 years; 14 female) underwent a 10-minute resting-state fMRI scan.”

Discuss the commonly observed problem of poor signal-to-noise ratio in olfactory regions and how the authors avoided the risk of biasing their results due to poor/variable SNR.

This is a helpful suggestion, and we have added a discussion of this to the Materials and methods as below. We have also added a supplementary figure showing the mean activation map for each subject, in order to show the data transparently.

“To reduce the distortion and improve the signal-to-noise ratio in the primary olfactory and orbitofrontal areas, the slice orientation was set to approximately 30° from AC-PC line (Deichmann et al., 2003). These acquisition parameters resulted in robust signals within orbitofrontal and olfactory areas in each subject (Figure 2—figure supplement 2). Further, our finding of strong connectivity between orbitofrontal cortex and all primary olfactory cortical areas suggests good orbitofrontal coverage.”

You found a mean correlation coefficient of 0.19 (SE 0.0041), how does that compare with prior applications of this method on similar data sets (e.g. Kahnt et al. 2012)? Please provide support for the claim that there is good similarity.

This is an important question, thank you for raising it. One of the other reviewers also asked about this R-value, further confirming that it’s important for us to clarify this analysis. The purpose of this leave-one-out analysis is only to estimate how similar (or stable) connectivity profiles of individual primary olfactory cortex voxels are across participants, as a prerequisite for averaging the connectivity matrices across participants. The overlap observed here was slightly lower than what Kahnt et al., 2012, observed in orbitofrontal cortex (r~0.3) using a different data set. However, this value cannot be reasonably compared across different studies because it depends on many study-specific factors including voxel size, the size of the regions of interest, and the number of data points used to compute the correlations. The important point to note about this histogram is that the similarity of connectivity patterns is above zero in all voxels in primary olfactory cortex. We have clarified this point in the second paragraph of the subsection “Parcellation of human primary olfactory cortex”.

It is interesting to note that AON has a stronger lateralization pattern. Why do you think that is the case, and what are the possible implications? Does it imply a specific functional role or might it be an artifact, or evidence of less well-defined network memberships?

We fully agree, this is a very interesting result and we should provide additional comments on this. We do not believe the finding is an artifact, and we now include, in the Results section, some discussion of this finding that ties it in with existing literature.

There are some interesting rodent findings that support the idea that the functional networks of the AON are more lateralized than other primary olfactory areas. For example, it has also been shown that the AON neurons can distinguish between signals from the ipsilateral and contralateral nostrils, suggesting representation of lateralized inputs in this region.

Please provide references for the olfactory interactions with the language regions, as is hypothesized in Discussion.

Thank you for this point. This comment made us realize that we also left out implications of our data on the neurocognitive limitations of olfactory language. We’ve added a discussion of this, along with references, in the Discussion.

Regarding the framework, is might be noted that the shared connectivity with the OFC might explain why it is so reliably elicited even in basic/passive olfactory tasks; all primary regions project to it. Furthermore, regarding the connectivity patterns of the frontal piriform to regions responsible for facial movements, might this include sniffing?

These are good and insightful points. We have added them to the Discussion.

It is a bit of a stretch to state that there is a "large body of evidence" suggesting olfaction is lateralized to the right side. The literature is in fact quite inconsistent. I suggest tempering this claim and also adding another more recent supporting citation.

We agree. We have toned down this language by removing

“supporting a large body of evidence suggesting that olfactory processing is lateralized to the right side”. We have also added more recent supporting citations.

Reviewer #2:

The conclusion appears somewhat weak: "…Our results provide important insight into the functional and anatomical organization of the human olfactory system..:" Please be more detailed in terms of the significance of these findings and the consequences of it. Do we have to look at olfactory information processing differently from today on?

Thank you for this suggestion, we agree. We have modified the Introduction and Discussion to better distinguish our findings from previous studies, and to clarify the reasons why we believe the study is important. Your suggestion really improved the Introduction, thank you. See the new additions in the fifth paragraph of the Introduction, and in the first paragraph of the Discussion.

Please speculate: Does this demonstration of parallel processing of olfactory information explain the vulnerability in aging? Or the decrease of olfactory functioning in depression? Other consequences?

Great points, thank you. We have added a discussion of these ideas to the Discussion, which has improved this part of the manuscript substantially:

“Our findings provide a detailed description of the particular brain areas which exhibit unique connectivity with each individual primary olfactory subregion. […] For example, olfactory structures that form networks with brain areas that are implicated in particular pathologies likely perform critical olfactory sensory functions (the olfactory tubercle is connected to areas involved in depression, see Croy and Hummel, 2017, and the temporal piriform cortex is connected to areas involved in primary progressive aphasia, see Olofsson et al., 2013).”

Please compare the parallel processing n the olfactory system to other systems? How is that in taste? Touch?

This is a good suggestion. We now highlight that the organization of the olfactory system differs from other sensory modalities. We attempted a detailed review of the organization of other sensory systems, however, in the end we felt that it disrupted the flow of the manuscript and we removed it. If the reviewer feels strongly that it should be included, we will add it back in.

I was always under the assumption that the AON in humans is part of the olfactory bulb (see Daniel and Hawkes, 1992; Hyman, Arriagada and Van Hoesen, 1991). Maybe you can discuss these discrepancies, too.

This is an important point, which we should have discussed more in the manuscript. The human AON certainly seems to differ anatomically from the rodent AON. In humans, it is often referred to as the “retrobulbar region”, but it has been demonstrated to be a true cortical structure, equivalent to paleocortical structures in rodents (Stephan H: Allocortex. In Bargmann W, editor: “Handbuch der mikroskopischen Anatomie des Menschen”, vol 4, Berlin and New York. Part 9, 1975, Springer Verlag, pp 1–998). In fact, the term anterior olfactory nucleus has been suggested to be misleading, given that it is a true cortical structure in humans (Zilles and Amunts, Architecture of the Cerebral Cortex, 3rd Edition, 2012). A recent study by Ongur et al. performed a detailed mapping of the human AON based on data from 5 post-mortem human brains (Ongur, 2003), which was updated in their Atlas of the Human Brain (Mai et al., 2016). Their study showed that the human AON is extensive, extending more than 11mm in the anterior-posterior direction, from MNI position y=14.22mm to MNI position y=2.53mm, as detailed in the 4th Edition of the Atlas of the Human Brain (Mai et al., 2016). Numerous studies (most of which focus on Parkinson’s Disease pathology) have characterized the human anterior olfactory nucleus into several subdivisions other than the bulbar part. Just as one example, a study by Ubeda-Banon et al. in 2010 divided the human AON into the following different parts: bulbar, intrapeduncular, retrobulbar, cortical anterior and cortical posterior subregions. The two cortical subregions could be further divided into medial and lateral components on either side of the olfactory tract. See Author response image 1, taken from this study, which shows the size and extent of the human AON. Some other studies including subdivisions of the AON beyond the olfactory bulb include:

- Pearce, Hawkes and Daniel, 1995, Movement Disorders;

- Price JL (1990) Olfactory system. In: Paxinos G (ed) The human nervous system. Academic Press, San Diego, pp 979–998;

- Hoogland PV, Huisman E (1999) Tyrosine hydroxylase immunoreactive structures in the aged human olfactory bulb and olfactory peduncle. J Chem Neuroanat 17:153–161; -Mai JK, Paxinos G, Voss T (2008) Atlas of the human brain. Elsevier, New York;

- Price JL (1990) Olfactory system. In: Paxinos G (ed) The human nervous system. Academic Press, San Diego, pp 979–998;

- Braak, H., Del Tredici, K., Rüb, U., de Vos, R. A., Jansen Steur, E. N., and Braak, E. (2003a). Staging of brain pathology related to sporadic Parkinson’s disease. Neurobiol. Aging 24, 197–211;

- Sengoku R, Saito Y, Ikemura M, Hatsuta H, Sakiyama Y, Kanemaru K, Arai T, Sawabe M, Tanaka N, Mochizuki H, Inoue K, Murayama S (2008) Incidence and extent of Lewy body-related α-synucleinopathy in aging human olfactory bulb. J Neuropathol Exp Neurol 67:1072–1083;

- Ubeda-Banon et al., 2017.

Author response image 1

Download asset Open asset

In our study, we did not distinguish the subdivisions of the human AON, though this could be of high interest for future studies.

We now include a brief description of these points in the Materials and methods subsection “Functional connectivity-based parcellation”.

The authors talk about the olfactory tubercle. This is despite the anatomical impression that there is no bump in this vicinity. In fact the anterior perforated substance has been proposed as its human homologue (see Freiherr, Wiesmann, Witt in Welge-Luessen, Hummel (eds): 2014, Management of Smell and Taste Disorders; Theme, Stuttgart). Please comment.

We agree that the anatomy of the rodent and human olfactory tubercle differs. Similar to the AON, the human tubercle differs in relative size and shape from the rodent homologue. We followed the definition of the olfactory tubercle used in the Atlas of the Human Brain (Mai et al., 2015; Öngür et al., 2003), as mentioned in our previous response above. The location of the OT in this atlas agrees with previous studies that we cite in the paper (Allison, 1954; Crosby and Humphrey, 1941; Eslinger et al., 1982). It does appear that the currently accepted location of the human olfactory tubercle overlaps with the location of the anterior perforated substance. We have added mention of this to our Materials and methods, and cite the book mentioned.

It would be extremely valuable for the reader if the authors came up with a sketch that graphically summarizes the results in terms of the strength of the connectivity between the various regions.

This is a great point. Our connectivity maps did not contain information about the relative strength of the different connections. We have modified our figures to include t-values rather than simple binarized values. These new maps, that contain information about the strength of the connectivity, have been inserted to replace Figure 4.

Although difficult to do (and although the authors already pay a lot of attention to that), it would be excellent if the authors could try to separate more clearly between research that comes from animals and research on humans.

We agree this is an important point, and a common issue in human olfactory studies/manuscripts, since the vast majority of studies are conducted in rodents. We have made efforts wherever possible to make this distinction more clear.

Reviewer #3:

[…] - Subsection “Parcellation results across hemispheres and k values”: Why it is important to combine data from both hemispheres? Asymmetry in human olfactory processing has been documented, especially by the Zatorre group in the early 90's and more recently in different studies. I would like to see how not merging the 2 hemispheres change the findings.

This is an excellent point. We will clarify our thinking here and in the text.

Not merging the 2 hemispheres does not change the findings in a statistically relevant way.

We merged hemispheres for three main reasons. First, there are no significant differences between hemispheres, based on a statistical comparison of the connectivity maps. Second, given this lack of statistical difference across hemispheres, to show each hemisphere for each subregion would add additional information without additional meaning, to the manuscript, while making it denser and more difficult to interpret for the reader. Third, and most important, to show such data would risk misleading the reader and could lead to misinterpretation of our results.

Because of these concerns, and particularly the concern that readers could mis-cite our paper as showing differences across hemispheres when we found none statistically, we feel strongly that we should not add supplementary figures showing the single hemisphere maps. However, if the reviewer feels very strongly that we should add this figure, we will create a supplementary figure showing these maps.

Based on this helpful comment, we have added clarification of this to the Materials and methods subsection “Functional connectivity-based parcellation”.

- The authors mentioned “Note that additional primary olfactory areas, including anterior cortical and peri- amygdala areas and entorhinal cortex (Allison, 1954; Carmichael et al., 1994; Eslinger et al., 1982; Gonçalves Pereira et al., 2005; Zatorre et al., 1992), were not included in our ROI because the exact location of olfactory afferents into these areas is poorly understood.”. I am wondering whether some areas included in the ROI (tubercule, AON), are less “poorly understood” than entorhinal cortex or amygdala in humans. Could the authors provide some more rationales for excluding these areas from the ROI?

Thank you for this insightful comment. It is a good point, and we did not adequately explain our rationale in the manuscript.

The AON and OT are better understood anatomically (though we agree, not functionally) than the olfactory inputs to the amygdala and entorhinal cortex. For example, a recent histological study by Goncalves et al. found that the borders of the subdivisions of the amygdala and entorhinal cortex that receive direct bulb projections are not discernable in T1 images (Gonçalves Pereira et al., 2005). Furthermore, we were unable to find a human brain atlas that clearly outlines olfactory amygdala and entorhinal areas receiving bulb input, whereas numerous studies and atlases do include delineation of the olfactory tubercle and AON. We have modified the manuscript to include this reference where we discuss this point in the first paragraph of the Results subsection “Parcellation of human primary olfactory cortex”.

In the same line, the authors wrote: “Interestingly, connectivity clusters were generally more extensive in the right hemisphere compared to the left hemisphere, supporting a large body of evidence suggesting that olfactory processing is lateralized to the right side (Zatorre et al., 1992).” So, why not considering the primary olfactory cortices separately from the right and the left hemispheres? There is much to gain in showing these data.

Thank you for this comment. Interestingly, we found that across the whole-brain, connectivity was stronger between all (both left and right) primary olfactory areas and clusters in the right hemisphere. Importantly, this whole-brain hemispheric effect did not differ between primary olfactory cortical hemispheres—that is, both the right and left primary olfactory cortices exhibited increased right-sided whole-brain connectivity. This is a subtle distinction, and is shown in the figure displaying the common connectivity pattern (Figure 5). We clarified this in the subsection “Functional connectivity common to all subregions”.

- The authors stated that “We then estimated the whole-brain functional connectivity profile of each voxel within the ROI by computing the Pearson correlation coefficient between the resting-state fMRI time-series of a given voxel and that of every other voxel in the rest of the brain. This resulted in subject-wise connectivity matrices, which were then averaged across all subjects.” Does this mean that individual variability is not considered in the rest of the analysis? If yes, how the authors could be sure that the values in the averaged matrix are not due to a sub-sample of subjects?

This is a very important point, thank you for bringing this up. We computed the connectivity maps on an individual basis, but averaged the resulting connectivity matrices to obtain a group-connectivity map, as done previously (Kahnt et al., 2012; Kahnt and Tobler, 2017). For this, we first determined whether the connectivity structure of individual primary olfactory cortex voxels was indeed comparable across subjects. This was done using a leave-one-out analysis, which showed that there was substantial overlap, as required for averaging across subjects. We have clarified this in the second paragraph of the subsection “Parcellation of human primary olfactory cortex”, where we mention averaging across subjects.

- In the same line, the authors wrote “To examine the similarity between the individual functional connectivity matrices, we computed a histogram of correlation values between individual matrixes and the groups matrix using a leave-one-out method (Kahnt et al., 2012). The results indicate a good similarity between the group-level and individual functional connectivity patterns (mean correlation coefficient: 0.19, standard error: 0.0041, Figure 2A).”. I can understand that the notion of similarity is relative, but here the averaged r-value is less than 0.20 which means that half of the data fall within a range of 0 to 0.20. I may not understand properly this analysis but to my view it seems that these r-values are low. Could you comment on that? Moreover, the authors must mention the significativity of these correlative analyses. Even if significant, there is a need to detail how many data-points were computed in these analyses and how such low r-values can be interpreted?

These are very important points for our study, thank you for these comments. The purpose of this leave-one-out analysis was solely to determine whether we could reasonably average across the connectivity maps of individual subjects. Similar to previous studies (e.g., Kahnt et al., 2012) we expect this R value to be relatively small. Moreover, this value will likely differ across studies because it depends on study-specific differences in ROI sizes and voxel size. However, as can be seen in the histogram, most of these correlations were above zero, and because they are computed across rest-of-the-brain voxels (N=170,660), also statistically significant (R values larger than 0.0088 are significant at p<0.05, Bonferroni corrected for the number of voxels in the primary olfactory cortex). We have clarified these points in the second paragraph of the subsection “Parcellation of human primary olfactory cortex”.

- Participants were “instructed to look at a white fixation cross on a black background and breath in-out through their nose.” As the authors know, and they are expert in the field, respiration can alter odor processing. Is there any effect of Nasal breathing on the brain imaging findings? If nasal respiration was measured, in addition to motion correction, the authors should correct for nasal breathing activity.

Excellent point. In this study, we focused on low-frequency (< 0.1 Hz) oscillations, which are below the human respiratory frequency (typically from 0.15 – 0.3 Hz). Although there’s increasing interest in studying higher frequency brain activity using fMRI, the resting functional connectivity profile of high frequency oscillations and their relationship with respiration is not well understood. Our previous study has shown that nasal breathing can modulate local brain activity in a way that is different from oral breathing, and it would be interesting to examine whether functional networks are distinct during those two different breathing routines in future studies.

Author details

1. Guangyu Zhou

   Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing

   For correspondence

   guangyu.zhou@northwestern.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-0897-6465

2. Gregory Lane

   Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, United States

   Contribution

   Data curation, Visualization, Writing—original draft, Project administration, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3101-0722

3. Shiloh L Cooper

   Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, United States

   Contribution

   Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0801-6352

4. Thorsten Kahnt

   1. Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, United States
   2. Department of Psychology, Weinberg College of Arts and Sciences, Northwestern University, Evanston, United States

   Contribution

   Resources, Methodology, Writing—review and editing

   Competing interests

   Reviewing editor, eLife

   "This ORCID iD identifies the author of this article:" 0000-0002-3575-2670

5. Christina Zelano

   Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, United States

   Contribution

   Conceptualization, Formal analysis, Supervision, Funding acquisition, Visualization, Methodology, Writing—original draft, Writing—review and editing

   For correspondence

   c-zelano@northwestern.edu

   Competing interests

   No competing interests declared

• 9,593

  Page views

• 905

  Downloads

• 63

  Citations

Article citation count generated by polling the highest count across the following sources: Crossref, Scopus, PubMed Central.