The role of GABA in semantic memory and its neuroplasticity

Understanding how the brain functions to drive flexible human behaviour has been a fundamental challenge in cognitive neuroscience. The ability to (re)shape our behaviours based on our experiences relies on a flexible mechanism in the brain, which is achieved through the regulation of neural excitation and inhibition (Tatti et al., 2017). In particular, an imbalance between excitatory and inhibitory processes has been associated with various cognitive impairments in several psychiatric disorders (Sohal and Rubenstein, 2019) such as autism spectrum disorder (Horder et al., 2018) and schizophrenia (Reddy-Thootkur et al., 2022). Of particular interest is the role of the neurotransmitters, gamma-aminobutyric acid (GABA) and glutamate in coordinating neural functions supporting performance in various cognitive domains. GABA is the primary inhibitory neurotransmitter in the brain, while glutamate is the primary excitatory neurotransmitter. The balance between GABAergic and glutamatergic neurotransmission is crucial for the proper functioning of the brain and the maintenance of optimal behavioural responses in both healthy and diseased states (Duncan et al., 2014; Heaney and Kinney, 2016; Bojesen et al., 2021). While GABA and glutamate are associated with various cognitive processing, the mechanistic link from the neurotransmitters to human cognition is not well understood.

Research has shown that GABAergic inhibition plays a crucial role in various processes, such as sensory processing, attention, memory, and learning (Duncan et al., 2014; Heaney and Kinney, 2016; Jung et al., 2022). Furthermore, GABAergic neurotransmission can regulate synaptic plasticity, leading to long-term potentiation (LTP) and long-term depression (LTD) by modulating the activity of excitatory neurons (Isaacson and Scanziani, 2011; Schmidt-Wilcke et al., 2018; Wolff et al., 1993). Understanding GABAergic inhibition is crucial in uncovering the neurochemical mechanisms underlying human cognition and its neuroplasticity. Research has revealed a link between variability in the levels of GABA in the human brain and individual differences in cognitive behaviour (for a reveiw, see Duncan et al., 2014). Specifically, GABA levels in the sensorimotor cortex were found to predict individual performance in the related tasks: higher GABA levels were correlated with a slower reaction time in simple motor tasks (Stagg et al., 2011a) as well as improved motor control (Boy et al., 2010) and sensory discrimination (Puts et al., 2011; Kolasinski et al., 2017). Visual cortex GABA concentrations were positively correlated with a stronger orientation illusion (Song et al., 2017), a prolonged binocular rivalry (Pitchaimuthu et al., 2017), while displaying a negative correlation with motion suppression (Pitchaimuthu et al., 2017). Individuals with greater frontal GABA concentrations demonstrated enhanced working memory capacity (Yoon et al., 2016; Porges et al., 2017). Studies on learning have reported the importance of GABAergic changes in the motor cortex for motor and perceptual learning: individuals showing bigger decreases in local GABA concentration can facilitate this plasticity more effectively (Stagg et al., 2011a; Floyer-Lea et al., 2006; Kolasinski et al., 2019; Lea-Carnall et al., 2020). However, the relationship between GABAergic inhibition and higher cognition in humans remains unclear. The aim of the study was to investigate the role of GABA in relation to human higher cognition – semantic memory and its neuroplasticity at the individual level.

Semantic memory is a crucial aspect of human cognition, encompassing our knowledge of concepts and meaning, such as words, people, objects, and emotion (Hodges et al., 2000; Lambon Ralph, 2014). Accumulating and converging evidence indicates that the anterior temporal lobe (ATL) is a transmodal and transtemporal hub of semantic memory that generates coherent semantic representations through interactions with modality-specific brain regions and integration over time/episodes (Lambon Ralph, 2014; Ralph et al., 2017; Patterson et al., 2007). The initial and strong evidence supporting this hypothesis comes from semantic dementia patients who show selective semantic degradation in both verbal and non-verbal domains due to progressive ATL-centred atrophy (Hodges et al., 2000; Bozeat et al., 2000; Hodges and Patterson, 2007; Ralph and Patterson, 2008). Recent studies have also supported this hypothesis using intracranial recordings and cortical stimulation (Chen et al., 2016; Shimotake et al., 2015), magnetoencephalography (Clarke et al., 2011; Mollo et al., 2017) and functional magnetic resonance imaging (fMRI; Coutanche and Thompson-Schill, 2015; Murphy et al., 2017; Peelen and Caramazza, 2012; Visser et al., 2012). Transcranial magnetic stimulation (TMS) studies have further established the link between ATL and semantic memory. Perturbing the ATL with inhibitory repetitive TMS (rTMS) and theta burst stimulation (TBS) resulted in healthy individuals showing slower reaction time during semantic processing (Jung and Lambon Ralph, 2016; Pobric et al., 2007; Binney et al., 2010; Pobric et al., 2010, Lambon Ralph et al., 2009; Jung and Lambon Ralph, 2021; Pobric et al., 2009). Our investigations combining rTMS/TBS with fMRI have revealed the critical role of the ATL in the neuroplasticity of the semantic system, demonstrating the flexible and adaptive nature of the neural mechanisms underpinning semantic memory function (Jung and Lambon Ralph, 2016; Binney and Ralph, 2015; Jung et al., 2021). Despite the compelling and consistent findings regarding the involvement of the ATL in semantic memory and its capacity for neuroplasticity, the specific ways in which the underlying neurotransmitter systems influence ATL function in semantic memory and its neuroplasticity remain unclear.

Previously, we explored neurotransmitter systems on the functioning of the ATL in semantic memory using a combination of magnetic resonance spectroscopy (MRS) and fMRI (Jung et al., 2017). By utilising MRS, a non-invasive method for measuring neurometabolites such as GABA and glutamate in vivo, we were able to detect and quantify regional GABA and glutamate concentrations in the ATL (Sanaei Nezhad et al., 2018). The concentration of GABA in the ATL showed a positive correlation with performance in semantic tasks and was negatively associated with blood-oxygen level-dependent (BOLD) signal changes during semantic processing. Our results highlighted the critical involvement of GABAergic inhibition in the modulation of neural activity and behaviour related to semantic processing in the ATL. Subsequently, we explored the relationship between regional GABA levels in the ATL and cTBS-induced plasticity in semantic memory (Jung et al., 2022). To achieve this, we acquired the ATL MRS and fMRI prior to stimulation and then delivered cTBS, an inhibitory protocol (Huang et al., 2005), to the ATL. We examined how baseline GABA levels in the ATL were associated with changes in semantic task performance after cTBS. The results showed that individuals with higher GABA levels in the ATL exhibited stronger cTBS effects on semantic processing, especially those who displayed inhibitory responses after cTBS. These findings suggest that the GABAergic action in the ATL plays a crucial role in cTBS-induced plasticity in semantic memory, predicting inter-individual variability of cTBS responsiveness.

Based on these findings, we hypothesised that GABAergic inhibition in the ATL can affect neural dynamics within the ATL underpinning semantic memory and its neuroplasticity. The study investigated the neural mechanisms underlying cTBS-induced neuroplasticity in the ATL by linking neurochemical profiles, task-induced regional activity, and individual variability in semantic memory performance. We used a combination of cTBS, MRS and fMRI to examine the relationship between changes in GABA levels, cortical activity during a semantic task, and semantic task performance. First, we hypothesised that the inhibitory cTBS would increase GABA concentrations and decrease task-induced BOLD signal changes in the ATL. Second, the effects of cTBS on semantic processing can be attributed to GABAergic action in the ATL at the individual level: greater changes in GABA concentrations would result in increasing changes in task-induced BOLD signal during semantic processing and semantic task performance. Furthermore, to address and explore the relationship between regional GABA levels in the ATL and semantic memory function, we combined data from our previous study (Jung et al., 2017) with the current study’s data. We then explored the function of GABA in the ATL in relation to semantic function. Finally, we extended this GABAergic function to semantic neuroplasticity driven by cTBS.

We acquired resting-state MRS for the left ATL and vertex followed by fMRI before and after cTBS (Figure 1A). During fMRI, participants made semantic association decisions as an active task and pattern matching as a control task (Figure 1B). GABA concentrations were estimated from the ATL with the vertex as a control region (Figure 1C). cTBS with 80% of resting motor threshold (RMT) was delivered outside of scanner at one of the target regions with a week gap between two sessions (Figure 1D).

Figure 1

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cTBS modulates regional GABA concentrations and task-related BOLD signal changes in the ATL

E-field modelling of cTBS showed that, as intended, ATL cTBS stimulated the left ventrolateral ATL (Figure 2A). To investigate how cTBS modulates GABA concentrations, we quantified GABA/NAA and calculated the changes (POST– PRE). A 2×2 repeated measures analysis of variance (ANOVA) with stimulation (ATL vs. vertex) and VOI (ATL vs. vertex) as within subject factor was performed. There was a significant interaction effect between the stimulation and VOI (F_1,16 = 4.57, p=0.048; Figure 2B). There was no significant main effect of the stimulation (F_1,16 = 3.23, p=0.091) and VOI (F_1,16 = 0.64, p=0.435). Planned paired t-tests revealed that ATL stimulation significantly increased GABA concentrations in the ATL compared to the control stimulation (t=1.86, p=0.040) and control site (t=2.07, p=0.027). There were no cTBS effects in the vertex VOI regardless of the stimulation (ps >0.23). It is noted that there was no significant cTBS effect in Glx (Figure 2—figure supplement 1).

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fMRI results demonstrated that the semantic association task evoked increased activation in the ATL, prefrontal and posterior temporal cortex compared to the control task (Figure 2C, Figure 2—figure supplement 2 and Supplementary file 1). To examine the effects of cTBS, we performed ROI analysis using the same VOI in the ATL. Planned paired t-tests revealed that BOLD signal changes during semantic processing were significantly altered after ATL cTBS compared to the pre-stimulation (t=1.78, p=0.046) and the control stimulation (t=–2.11, p=0.025; Figure 2D).

To investigate the effects of ATL cTBS, we conducted a partial correlation analysis between GABA changes (POST–PRE) and BOLD signal changes (POST– PRE), accounting for age and sex. We found a significant correlation between cTBS-induced GABA changes and BOLD signal changes in the ATL (r=–0.86, p<0.001). Individuals with greater increases in ATL GABA levels following ATL cTBS showed greater reductions in task-induced BOLD signal changes in the ATL. These results demonstrate that ATL cTBS modifies regional GABA concentrations, and the cTBS-induced changes in GABA levels are connected to individual-level changes in task-related fMRI signal.

cTBS disrupts semantic task performance, revealing substantial individual variability in responsiveness

Participants’ performance was examined using a 2×2 repeated measures ANOVA with stimulation (ATL vs. vertex) and session (PRE vs. POST) as within-subject factors. There were no significant main effects and interactions on reaction time (RT) in the semantic task (Fs >0.19, ps >0.220). However, we found a significant main effect of session in the control task (F_{1, 15} = 20.21, p<0.001). Post hoc paired t-tests demonstrated that participants performed the task faster in the post-session compared to the pre-session, except in the semantic task after the ATL stimulation. The results showed that ATL cTBS attenuated the practice effects found in the control stimulation and control task. There were no significant effects in accuracy (Fs >0.01, ps >0.073). The results of accuracy and RT for each task were summarised in the Supplementary file 1 and Figure 2—figure supplement 3.

To evaluate the cTBS effects in behaviour, we used the inverse efficiency (IE) score (RT/1-the proportion of error) and calculated IE changes (POST-PRE). The cTBS effects on participants’ performance were examined using a 2×2 repeated measures ANOVA with stimulation (ATL vs. vertex) and task (semantic vs. control) as within-subject factors. There was no significant main effect of stimulation. However, we found a significant main effect of task (F_{1, 15} = 6.66, p=0.021) and a marginally significant interaction between the stimulation and task (F_{1, 15} = 4.06, p=0.061). Post hoc paired t-tests demonstrated that participants performed the semantic task worse (higher IE score) after the ATL stimulation compared to the control task (t=2.81, p=0.006) and vertex stimulation (t=1.91, p=0.038; Figure 2F). The results showed that ATL cTBS induced the task-specific inhibitory effects on semantic task performance. It is noted that a higher IE score indicates poorer performance.

Moreover, we categorised participants based on changes in their semantic task performance following ATL stimulation to examine the relationship between ATL GABA levels and individual behavioural response to cTBS. To account for practice effects (Supplementary file 1), we first adjusted task performance (IE) by normalising ATL stimulation performance relative to with vertex stimulation performance. A 2×2 × 2 ANOVA was conducted with task (semantic vs. control) and session (PRE vs. POST) as within-subject factors, and group (responders vs. non-responders) as a between-subject factor. The analysis revealed a significant interaction between the session and group (F_{1, 15} = 10.367, p=0.006), a marginally significant interaction between the session and task (F_{1, 15} = 4.370, p=0.054), and a significant three-way interaction between the session, task, and group (F_{1, 15} = 7.580, p=0.015). Post hoc tests showed that after ATL stimulation, responders exhibited poorer semantic task performance (higher IE; t=–5.281, p<0.001), whereas non-responders demonstrated paradoxical, facilitatory effects on semantic task performance (lower IE; t=3.206, p=0.007; Figure 3A). Additionally, responders showed poorer semantic task performance compared to non-responders after ATL stimulation (t=2.349, p=0.033; Figure 3A). Notably, no differences were observed between responders and non-responders in the control task performance across pre- and post-stimulation sessions, confirming that the practice effect was successfully controlled (Figure 3B).

Figure 3

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A 2x2 ANOVA with session (PRE vs. POST) as a within- subject factor and with group (responders vs. non-responders) as a between-subject factor was conducted to investigate the effects of individual cTBS responsiveness on ATL GABA levels. The analysis revealed a significant main effect of session (F_{1, 14} = 39.906, p<0.001) and group (F_{1, 14} = 9.677, p=0.008). Post hoc paired t-tests revealed that both responders and non-responders showed increased GABA levels in the ATL following stimulation (responder: t=–3.885, p=0.002, non-responder: t=–4.831, p=0.001; Figure 3C). Post hoc t-tests further revealed a significant difference in ATL GABA levels between responders and non-responders in both pre-stimulation (t=2.816, p=0.007) and post-stimulation session (t=2.555, p=0.011; Figure 3C).

Regional GABA concentrations in the ATL play a crucial role in semantic memory

In our prior study (Jung et al., 2017), ATL GABA levels were significantly and negatively correlated with ATL activity during semantic processing (Figure 4A). Here, we replicated our previous findings in a different cohort with the same research paradigm (pre-stimulation session). We conducted a single-voxel regression analysis with the individual’s GABA concentrations (ATL pre-stimulation session) as the regressor of the fMRI contrast of interest (semantic >control). The BOLD response in the ventral ATL was significantly and negatively correlated with the individual GABA levels in the ATL (MNI –42–6 –33, p _SVC-FWE <0.05), overlapping with the results from our previous study (Jung et al., 2017; Figure 4A). The GABA-related region of the ventral ATL overlapped with the semantic coding hotspot from electrocorticograms (ECoG) data and direct cortical stimulation (Chen et al., 2016; Shimotake et al., 2015; Figure 4A). Furthermore, we found that individual GABA concentrations in the ATL were positively associated with semantic task performance (Figure 4B). We also confirmed this finding, demonstrating that individuals with more GABA in the ATL performed the semantic task better (higher accuracy; r=0.50, p=0.035; Figure 4B). It should be noted that individual GABA levels also significantly correlated with ATL activity and semantic task performance at the vertex stimulation session (Figure 4—figure supplement 1). There was no significant relationship between ATL GABA levels and RT during semantic processing (ps >0.44; Figure 4—figure supplement 2) and between ATL GABA levels and control task performance (Supplementary file 1). These results demonstrate that higher levels of cortical GABA in the ATL are associated with task-related regional activity as well as enhanced semantic function.

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We investigated the role of cortical GABA in the ATL on semantic memory and its neuroplasticity. Our results demonstrated an increase in regional GABA levels following inhibitory cTBS in human associative cortex, specifically in the ATL, a representational semantic hub. Notably, the observed increase was specific to the ATL and semantic processing, as it was not observed in the control region (vertex) and not associated with control processing (visuospatial processing). Our study also found that the magnitude of cTBS-modulated GABA changes at the individual level was associated with their changes in ATL activity during semantic processing. Furthermore, our data confirmed and replicated our previous findings that GABA concentrations in the ATL shape task-related cortical activity and semantic task performance. In other words, individuals with greater semantic performance exhibit selective activity in the ATL due to higher concentrations of inhibitory GABA. GABAergic inhibition could sharpen activated distributed semantic representations through lateral inhibition, leading to improved semantic acuity (Jung et al., 2017), which aligns with theories on representational sharpening in visual perception (Desimone, 1996; Kok et al., 2012). Importantly, our data revealed, for the first time, a non-linear, inverted-U-shape relationship between GABA levels in the ATL and semantic function, by explaining individual differences in semantic task performance and cTBS responsiveness. Understanding the link between neurochemistry and semantic memory is an important step in understanding individual differences in semantic behaviour and could guide therapeutic interventions to restore semantic abilities in clinical settings.

To the best of our knowledge, this is the first study to demonstrate that (1) cTBS modulates both regional GABA concentrations and cortical activity in human higher cognition - semantic memory, and that (2) changes in GABA levels are closely linked to changes in regional activity induced by cTBS. These results suggest that GABAergic activity may be the mechanism by which cTBS induces long-lasting after-effects on cortical excitability, leading to behavioural changes. Previous studies in animals and humans have also suggested that cTBS can induce LTD-like effects on cortical synapses and is associated with the GABAergic system in the cortex (Huang et al., 2011; Funke and Benali, 2011; Huang et al., 2007; Lenz et al., 2016; Romero et al., 2022; Trippe et al., 2009). Another study employing MRS found that cTBS increased regional GABA concentrations at the primary motor cortex in healthy subjects (Stagg et al., 2009). These findings suggest that cTBS activates a population of cortical GABAergic interneurons, leading to the increase in GABAergic activity (Di Lazzaro et al., 2005; Ziemann et al., 1996). As a major inhibitory neurotransmitter, GABA has been shown to have a negative correlation with BOLD signal changes (Duncan et al., 2014; Northoff et al., 2007). Previously, we demonstrated this negative relationship between ATL GABA levels and BOLD signal changes in the ATL during semantic processing (Jung et al., 2017), indicating a potential role of GABA in shaping the functions/computations of the cortex. Here, we further demonstrated that the increase in GABA induced by cTBS was negatively correlated with the reduction of BOLD signal responses in the ATL following cTBS, during semantic processing. Our findings suggest a crucial role for GABAergic inhibition in the ATL shaping the local neural functioning underpinning semantic memory and its neuroplasticity. The GABAergic inhibition confines the propagation of excitatory signalling, thereby maintaining the functional organisation of the cortex (Tremblay et al., 2016), and the modulation of cortical GABAergic inhibition drives experience-dependent plasticity in cognition (Schmidt-Wilcke et al., 2018; Boroojerdi et al., 2001).

GABA exists in two distinct neuronal pools: cytoplasmic GABA, which is involved in metabolism, and vesicular GABA, which plays a role in inhibitory synaptic neurotransmission (Martin and Rimvall, 1993). In addition to intracellular GABA, extracellular GABA exerts tonic inhibition through extra-synaptic GABA_A receptors (Semyanov et al., 2004). MRS is capable of detecting the total concentration of GABA in the voxel of interest, but it cannot differentiate between different pools of GABA (Stagg et al., 2011b; Puts and Edden, 2012). Some studies have suggested that MRS-measured GABA signals reflect GABAergic tonic inhibition rather than synaptic GABA signalling (Stagg et al., 2011c; Mooney et al., 2017), whereas other studies have failed to replicate this relationship (Dyke et al., 2017; Hermans et al., 2018). A recent study has shown a link between MRS-measured GABA and phasic synaptic GABAergic activity (Lea-Carnall et al., 2023). Although findings of previous studies have been mixed, changes in GABA levels observed in this study may reflect cTBS-modulated GABAergic neurotransmission, which encompasses both tonic and synaptic GABAergic activity. This GABAergic activity shapes the selective response profiles of neurons in the cortex (Isaacson and Scanziani, 2011).

Inverted U-shaped models have been previously considered in the field of neuroscience, specifically in terms of the relationship between the concentration of neurotransmitters such as dopamine, acetylcholine and noradrenaline, and the level of neural activity (Aston-Jones and Cohen, 2005; Cools and D’Esposito, 2011; Vijayraghavan et al., 2007; He and Zempel, 2013). Recent studies suggest that this relationship also applies to behaviour, where moderate levels of neural activity are linked to optimal performance (for a review, see Northoff and Tumati, 2019). For example, Ferri et al., 2017 showed an inverted U-shaped relationship between excitation and inhibition balance and multisensory integration, where extreme values impair functionality while intermediate values enhance it, even in healthy individuals. Our findings revealed a non-linear relationship between GABA levels in the ATL and semantic function, indicating that individual variations in semantic task performance can be explained by an inverted-U-shape pattern (Figure 5A). Specifically, for relatively greater levels of GABA in the ATL, with lower task-induced regional activity, were associated with better semantic processing in healthy participants (Jung et al., 2017). That is, individuals with better semantic memory abilities show more specific cortical activity in the ATL, which is linked to higher concentrations of inhibitory GABA. Extreme levels of GABA can be found in studies with dementia patients and pharmacological studies with GABA agonists. Recent studies have reported decreased GABA levels in Alzheimer’s disease (Xu et al., 2020; Jiménez-Balado and Eich, 2021) and frontotemporal dementia (Murley et al., 2020; Perry et al., 2022) in relation to their cognitive impairments such as memory and language. In fact, GABA agonists like midazolam have been found to improve verbal generation in anxiety patients by increasing GABAergic function (Snyder et al., 2010). On the other hand, healthy participants who received GABA supplementation (such as baclofen) have been found to have decreased task performance (Lim and Aquili, 2021). Overall, optimal, elevated levels of GABA in the ATL may aid in refining stimulated widespread semantic representations through local inhibitory processes. However, our findings should be interpreted with caution due to the limitation of having fewer data points in the latter half (right side) of the inverted U-shaped curve. Future studies incorporating GABA agonists could help further validate and refine these findings.

Figure 5

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This inverted U-shaped model could also explain inter-individual variability in cTBS-induced neuroplasticity in the ATL in semantic processing. Our data demonstrated that cTBS over ATL increased regional GABA concentrations, but there was inter-individual variability in GABA level changes in response to cTBS (Figure 2). Our previous investigation (Jung et al., 2022) showed that the pre-interventional neurochemical state was crucial in predicting cTBS-induced changes in semantic memory. Specifically, cTBS over the ATL inhibited the semantic task performance (i.e. reduced accuracy) of individuals with initially higher concentration of GABA in the ATL, linked to better semantic capacity. However, cTBS had a null or even facilitatory effect on individuals with lower semantic ability with relatively lower GABA levels in the ATL. This study suggests that individuals with higher GABA levels in the ATL were more likely to respond to cTBS, exhibiting inhibitory effects on semantic task performance (responders), while individuals with lower GABA concentrations and lower semantic ability were less likely to respond or even showed facilitatory effects after ATL cTBS (non-responders). The current study revealed a non-linear, inverted-U-shape relationship between GABA levels in the ATL and semantic function, by explaining individual differences in semantic task performance and cTBS responsiveness. As regional GABA increases after cTBS, responders with the optimal level of GABA in the ATL would show poorer semantic performance, whereas non-responders could exhibit no changes or even better semantic performance with GABA increase (Figure 5B). This relationship is similar to the inverted U-shaped relationship between dopamine action in the prefrontal cortex (PFC) and cognitive control, whereby moderate levels of dopamine lead to optimal cognitive performance (Cools et al., 2019). The effects of dopaminergic drugs on PFC function also depend on baseline levels of working memory performance (for a review, see Cools and D’Esposito, 2011), explaining the effects of dopaminergic drugs on cognitive performance in individuals with varying working memory capacities (Kimberg et al., 1997; Gibbs and D’esposito, 2005; Frank and O’Reilly, 2006).

Our findings provide novel evidence of a direct link from neurochemical modulations to cortical responses in the brain, highlighting substantial individual variability in semantic memory and plasticity. In addition, the current study represents an important replication and extension of previous findings regarding the role of GABAergic inhibition in semantic memory. These results offer fundamental insights into the mechanisms underlying the maintenance and alteration of functional cortical organisation in response to perturbations. Our study has important implications for the development of personalised therapeutic interventions aimed at modulating neurochemical systems to restore or enhance higher cognitive function in humans.

Data and analysis code are available on OSF (https://doi.org/10.17605/OSF.IO/PMQXH).

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Author details

1. JeYoung Jung

   School of Psychology, University of Nottingham, Nottingham, United Kingdom

   Contribution

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

   For correspondence

   jeyoung.jung@nottingham.ac.uk

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3739-7331

2. Steve Williams

   Division of Informatics, Imaging and Data Science, School of Health Sciences, University of Manchester, Manchester, United Kingdom

   Contribution

   Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

3. Matthew A Lambon Ralph

   MRC Cognition and Brain Sciences Unit (CBU), University of Cambridge, Cambridge, United Kingdom

   Contribution

   Conceptualization, Funding acquisition, Investigation, Writing – original draft, Writing – review and editing

   For correspondence

   Matt.Lambon-Ralph@mrc-cbu.cam.ac.uk

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5907-2488

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