The occipital cortex of early blind (EB) individuals enhances its response to non-visual stimuli (Neville and Bavelier, 2002). For instance, it has been repetitively shown that sound processing triggers enhanced occipital responses in EB people (Van Ackeren et al., 2018; Bedny et al., 2011; Collignon et al., 2011; Dormal et al., 1981; Weeks et al., 2000).

If occipital regions enhance their functional tuning to auditory information in EB, what is the impact of visual deprivation on temporal regions typically coding sounds? Contradictory results emerged from previous literature about the way intramodal plasticity expresses in early blindness. Several studies suggested that visual deprivation elicits enhanced response in the sensory cortices responsible for touch or audition (Elbert et al., 2002; Gougoux et al., 2009; Manjunath et al., 1998; Naveen et al., 1998; Pascual-Leone and Torres, 1993; Rauschecker, 2002; Röder et al., 2002). In contrast, some studies observed a decreased engagement of auditory or tactile sensory cortices during non-visual processing in EB individuals (Bedny et al., 2015; Burton et al., 2002; Pietrini et al., 2004; Ricciardi et al., 2009; Stevens and Weaver, 2009; Striem-Amit et al., 2012; Wallmeier et al., 2015). Those opposing results were, however, both interpreted as showing improved processing in the regions supporting the remaining senses in blind people: more activity means enhanced processing and less activity means lower resources needed to achieve the same process; so, both more and less mean better. In this fallacious interpretational context, the application of multivoxel pattern analysis (MVPA) methods to brain imaging data represents an opportunity to go beyond comparing mere activity level differences between groups by allowing a detailed characterization of the information contained within brain areas (Berlot et al., 2020; Kriegeskorte et al., 2008b). An intriguing possibility, yet to be directly tested, is that early visual deprivation triggers a redeployment mechanism that would reallocate part of the sensory processing typically implemented in the preserved senses (i.e. the temporal cortex for audition) to the occipital cortex deprived of its dominant visual input.

A few studies reported an increased representation of auditory stimuli in the occipital cortex concomitant to a decreased auditory representation in temporal regions in congenitally blind people (Battal et al., 2021; Dormal et al., 2016; Jiang et al., 2016, van den Hurk et al., 2017; Vetter et al., 2020). However, these studies did not focus on the link between intramodal and crossmodal reorganizations in blind individuals. For instance, we do not know, based on this literature, whether this increased/decreased representation is driven by similar or different features of the auditory stimuli in temporal and occipital regions. We have recently demonstrated that categorical membership is the main factor that predicts the representational structure of sounds in ventral occipito-temporal cortex (VOTC) in congenitally blind people (Mattioni et al., 2020), rather than lower-level acoustical attributes of sounds (i.e. pitch). Would the same categorical representation be the one that could be reorganized in the temporal cortex of these blind individuals? If true this would speak up for an interplay between the features that are reorganized in the temporal and occipital cortices of visually deprived people. Alternatively, the intramodal reorganization potentially observed in the temporal region of blind people might be driven by the acoustic properties of sounds, suggesting reorganization of independent auditory features (acoustic vs. categorical) in temporal and occipital regions. Representational similarity analyses (RSA) can reveal whether categorical vs. acoustic representation of the same set of sounds is encoded in a brain region (Giordano et al., 2013). Here, using RSA, we explore for the first time which features of the sounds (acoustic or categorical) are concomitantly reorganized in the temporal or occipital cortex of blind compared to sighted people.

Another unsolved question relates to how the onset of blindness impacts the organization of cortical regions coding for the preserved and deprived senses. We have recently suggested that the increased representation of sound categories in the VOTC of EB people could be an extension of the intrinsic multisensory categorical organization of the VOTC, that is therefore partially independent from vision in sighted as well (Mattioni et al., 2020; see also Amedi et al., 2002; Ricciardi and Pietrini, 2011). According to this view, one should assume that late visual deprivation may extend the non-visual coding that is already implemented in the occipital cortex of sighted people. In contrast with this hypothesis, previous studies suggested that late acquired blindness triggers a reorganization of occipital region that is less functionally organized than the one observed in early blindness (Bedny et al., 2012; Collignon et al., 2013; Kanjlia et al., 2009), promoting the idea that crossmodal plasticity in late blindness is more stochastic and functionally epiphenomenal compared to the one observed in EB people.

The current study aimed to carry out a comprehensive uni- and multivariate characterization of how early and late acquired blindness impact the processing of sounds from various categories (humans, animals, manipulable objects and big objects or scenes, Figure 1 ) in occipital and temporal regions.

Figure 1

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Our study provides a comprehensive exploration of how blindness at different age of acquisition induces large-scale reorganization of the representation of sound categories in the brain. More precisely, compared to our previous paper on which we build on Mattioni et al., 2020, the present study sheds new lights on at least two fundamental issues: (1) How does the reorganization of occipital regions in blind people impact on the response profile of temporal regions typically coding for sounds, and (2) how does the age of blindness onset impact on those large-scale brain (re)organization.

First, we looked whether brain regions show a different level of activation for sounds in blind compared to sighted subjects. We observed that, indeed, a ventral occipital region in the right hemisphere showed enhanced activation for sounds in both EB and LB compared to sighted individuals while some portions of the temporal regions decrease their activation in EB and LB compared to the sighted group (see Figure 2A). However, univariate analyses did not allow to reveal neither if the different categories were discriminated one from each other in these regions, nor if one or multiple categories were more/less represented in those brain regions of blind vs. sighted (see Figure 2B).

To address these questions, we looked more in detail at the patterns of activity generated by the different sound categories in those reorganized occipital and temporal regions that emerged from the univariate group contrasts (EB vs. SC and LB vs. SC). Do these ROIs discriminate the different categories across sensory experiences (i.e. sighted, EB, LB)? If so, could we observe a difference between blind subjects and SC? Results from the eight-way MVP classification analysis show enhanced decoding accuracies in the occipital ROI of EB when compared to SC that was concomitant to reduced decoding accuracy in the temporal cortex of EB people (see Figure 3). Like what was observed in EB, LB also showed enhanced representation of sound categories in the occipital ROI compared to SC while the temporal cortex showed lower decoding in LB.

A dominant view in the field is that the reorganization of occipital regions is less functionally organized in late blindness than the one observed in early blindness (Bedny et al., 2012; Collignon et al., 2013; Kanjlia et al., 2009). Our results overturn this view by showing functionally specific coding of sound categories that is present in LB and increased compared to SC (see Figure 3A and Appendix 1). This has broad implications since it supports the idea that the increased representation of sound categories in the VOTC of EB and LB people could be an extension of the intrinsic multisensory categorical organization of the VOTC, that is therefore partially independent from vision in sighted as well (Mattioni et al., 2020; see also Amedi et al., 2002; Ricciardi and Pietrini, 2011; Striem-Amit and Amedi, 2014). Indeed, for such conceptual view to be true, late visual deprivation should maintain or even extend the non-visual coding that is already implemented in the occipital cortex of sighted people. Our data support this hypothesis, helping to fill this gap in the literature.

Importantly, the eight-way decoding analysis revealed differences in the categorical representation between sighted and blind subjects both in the temporal and in the occipital regions. We observed enhanced decoding accuracies in the occipital ROI of blind subjects when compared to controls and this enhanced representation of sound categories in the occipital cortex was concomitant to reduced decoding accuracy in the temporal cortex of blind people (see Figure 3).

Would this redistribution of computational load across temporal and occipital regions predict a representation of auditory categories in the occipital ROI that is more similar to the representation of the same auditory categories in the temporal regions in blind when compared to sighted? Our results suggest that this is indeed the case. In fact we show that within each blind subject, the correlation between the occipital and the temporal categorical representations is significantly higher compared to the SC (Figure 4A).

Which dimension of our stimuli does determine the response properties of the temporal and occipital regions to sounds? Is one category, among the others, driving these differences between groups? Moreover, is this alteration in the decoding explained by some higher-level representations (e.g. categorical, humanness) or by low-level acoustic features (pitch or HNR) specific to our sounds?

We addressed these questions by looking at which model, among several types based on different categorical (e.g. behavioral similarity judgment, human model, object model, etc.) and acoustic (e.g. harmonicity, pitch) dimensions, would better account for the representation of the auditory categories in the occipital and temporal regions in both sighted and blind subjects (Figure 5). In the temporal cortex, we found that in every group the best model was a ‘human’ model, in which human stimuli were considered similar between themselves and different from all other animate and inanimate stimuli (Figure 5A and C).

Interestingly, we also found that the human model, when compared to other models, showed the highest correlation with the representation of the auditory categories in the occipital ROI of both our blind groups but not of the SC (see Figure 4B and Figure 5D). This finding is well compatible with the spatial location of our ROIs which correspond to regions known to be involved in the processing of faces and voices, respectively (Benetti et al., 2017). Indeed, the two occipital ROIs are located within the fusiform gyrus/infero-temporal cortex, partially overlapping with the fusiform face area (Julian et al., 2009), while the two temporal ROIs are located within the STG, extending over the left and right temporal voice area (Belin et al., 2004).

We also show that it is only the representational structure of our ‘human’ model that is reduced in both LB and EB groups in temporal regions, but not the encoding of other categorical and low-level acoustic features which is similar across groups (Figure 5C). Interestingly, this result relates to the reversed group difference observed in the occipital regions where we find enhanced representation of the ‘human’ model in EB and LB people but no alteration in the representation of other categorical or acoustic features of the sounds (Figure 5D).

Importantly, we additionally show how our stimuli are well suited to address such question (Figure 6) by demonstrating, in all groups, that models of some acoustic features of our sounds (pitch, HNR) correlate more with the representational structure implemented in the Heschl gyrus (pitch) and in a specific portion of the right STS (HNR) while the ‘human’ model correlates more with the representational structure of an extended bilateral portion of STS (see also Giordano et al., 2013).

Why is that important? It shows for the first time that acoustic features of sound processing are not altered in the auditory region and not represented in the occipital cortex of EB and LB people. In contrast, the representation of a higher-level category ‘Human/Voice’ is reduced in temporal regions and enhanced in occipital regions (Figure 4B). Showing that the same feature of our sounds is concomitantly reorganized in temporal and occipital cortices of both blind groups is filling in an important gap in the literature about how changes in the deprived and remaining senses relate to each other in case of early and late visual deprivation, providing a mechanistic view on the way plasticity expresses following blindness.

Could such a difference be driven by general factors like group differences in perceptual abilities, learning, and/or attention? If the different profile of the temporal cortex between blind and sighted individuals was driven by such general factors, one could have expected a difference not only for the representation of the human model but also for other representational models (e.g. sounds of objects or animals or low-level acoustic properties of the sounds). Our results show that this is not the case (see RSA correlations with representational models: Figure 5). Whether such specific alteration in the representation of voices relates to difference in the way blind and sighted people process voices (Bull et al., 1983; Hölig et al., 2014; Klinge et al., 2009) remains to be explored in future studies.

To summarize, we discovered that in both EB and LB the enhanced coding of sound categories in occipital regions is coupled with lower coding in the temporal regions compared to sighted people. The brain representation of the voice category is the one mostly altered in both EB and LB when compared to sighted people. This brain reorganization in blind people is mostly explained by the categorical aspects of the voice category and not by their acoustic features (pitch or harmonicity). An intriguing possibility raised by our results is that visual deprivation may actually trigger a redeployment mechanism that would reallocate part of the processing typically tagging the preserved senses (i.e. the temporal cortex for the auditory stimulation) to the occipital cortex deprived of its most salient visual input.

Since this paper is submitted as a Research Advances format, it represents a substantial development that directly build upon a Research Article published previously by eLife (Mattioni et al., 2020). As for the journal recommendation, no extensive description of material and methods will appear when directly overlapping with our previous publication.

Raw data are not provided as personal consent was not obtained in each participant for their data to be made publicly available. This is especially sensitive as the raw data contain anatomical MRI scans of the participant and therefore full anonymity cannot by default be guaranteed even if we deface those images. Due to those restrictions imposed on data sharing in our ethical approval (anonymity should be fully guaranteed), defaced raw MRI data can only be shared upon request to the corresponding author Olivier Collignon (olivier.collignon@uclouvain.be). Olivier Collignon will evaluate if the request come from an academic team with a specific scientific question in mind. If those criteria are met, the data will be shared. These data cannot be provided for commercial research. Processed data (statistical maps), numerical data and Matlab scripts have been made open on OSF database reachable using this link https://doi.org/10.17605/OSF.IO/FEQA6.

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Author details

1. Stefania Mattioni

   1. Institute for research in Psychology (IPSY) & Neuroscience (IoNS), Louvain Bionics, Crossmodal Perception and Plasticity Laboratory - University of Louvain (UCLouvain), Louvain-la-Neuve, Belgium
   2. Department of Brain and Cognition, KU Leuven, Leuven, Belgium

   Contribution

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

   For correspondence

   stefania.mattioni@uclouvain.be

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8279-6118

2. Mohamed Rezk

   Institute for research in Psychology (IPSY) & Neuroscience (IoNS), Louvain Bionics, Crossmodal Perception and Plasticity Laboratory - University of Louvain (UCLouvain), Louvain-la-Neuve, Belgium

   Contribution

   Data curation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1866-8645

3. Ceren Battal

   Institute for research in Psychology (IPSY) & Neuroscience (IoNS), Louvain Bionics, Crossmodal Perception and Plasticity Laboratory - University of Louvain (UCLouvain), Louvain-la-Neuve, Belgium

   Contribution

   Data curation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-9844-7630

4. Jyothirmayi Vadlamudi

   Institute for research in Psychology (IPSY) & Neuroscience (IoNS), Louvain Bionics, Crossmodal Perception and Plasticity Laboratory - University of Louvain (UCLouvain), Louvain-la-Neuve, Belgium

   Contribution

   Data curation, Writing – review and editing

   Competing interests

   No competing interests declared

5. Olivier Collignon

   1. Institute for research in Psychology (IPSY) & Neuroscience (IoNS), Louvain Bionics, Crossmodal Perception and Plasticity Laboratory - University of Louvain (UCLouvain), Louvain-la-Neuve, Belgium
   2. Center for Mind/Brain Studies, University of Trento, Trento, Italy
   3. School of Health Sciences, HES-SO Valais-Wallis, Sion, Switzerland
   4. The Sense Innovation and Research Center, Lausanne and Sion, Sion, Switzerland

   Contribution

   Conceptualization, Resources, Data curation, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing – original draft, Writing – review and editing

   For correspondence

   olivier.collignon@uclouvain.be

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1882-3550

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