Language in Brains, Minds, and Machines.

It has long been argued that only humans could produce and understand language. But now, for the first time, artificial language models (LMs) achieve this feat. Here we survey the new purchase LMs are providing on the question of how language is implemented in the brain. We discuss why, a priori, LMs might be expected to share similarities with the human language system. We then summarize evidence that LMs represent linguistic information similarly enough to humans to enable relatively accurate brain encoding and decoding during language processing. Finally, we examine which LM properties-their architecture, task performance, or training-are critical for capturing human neural responses to language and review studies using LMs as in silico model organisms for testing hypotheses about language. These ongoing investigations bring us closer to understanding the representations and processes that underlie our ability to comprehend sentences and express thoughts in language.

Functional Ultrasound Neuroimaging.

Functional ultrasound (fUS) is a neuroimaging method that uses ultrasound to track changes in cerebral blood volume as an indirect readout of neuronal activity at high spatiotemporal resolution. fUS is capable of imaging head-fixed or freely behaving rodents and of producing volumetric images of the entire mouse brain. It has been applied to many species, including primates and humans. Now that fUS is reaching maturity, it is being adopted by the neuroscience community. However, the nature of the fUS signal and the different implementations of fUS are not necessarily accessible to nonspecialists. This review aims to introduce these ultrasound concepts to all neuroscientists. We explain the physical basis of the fUS signal and the principles of the method, present the state of the art of its hardware implementation, and give concrete examples of current applications in neuroscience. Finally, we suggest areas for improvement during the next few years.

Inferring Macroscale Brain Dynamics via Fusion of Simultaneous EEG-fMRI.

Advances in the instrumentation and signal processing for simultaneously acquired electroencephalography and functional magnetic resonance imaging (EEG-fMRI) have enabled new ways to observe the spatiotemporal neural dynamics of the human brain. Central to the utility of EEG-fMRI neuroimaging systems are the methods for fusing the two data streams, with machine learning playing a key role. These methods can be dichotomized into those that are symmetric and asymmetric in terms of how the two modalities inform the fusion. Studies using these methods have shown that fusion yields new insights into brain function that are not possible when each modality is acquired separately. As technology improves and methods for fusion become more sophisticated, the future of EEG-fMRI for noninvasive measurement of brain dynamics includes mesoscale mapping at ultrahigh magnetic resonance fields, targeted perturbation-based neuroimaging, and using deep learning to uncover nonlinear representations that link the electrophysiological and hemodynamic measurements.

Translational In Vivo Assays in Behavioral Biology.

The failure of preclinical research to advance successful candidate medications in psychiatry has created a paradigmatic crisis in psychiatry. The Research Domain Criteria (RDoC) initiative was designed to remedy this situation with a neuroscience-based approach that employs multimodal and cross-species in vivo methodology to increase the probability of translational findings and, consequently, drug discovery. The present review underscores the feasibility of this methodological approach by briefly reviewing, first, the use of multidimensional and cross-species methodologies in traditional behavioral pharmacology and, subsequently, the utility of this approach in contemporary neuroimaging and electrophysiology research-with a focus on the value of functionally homologous studies in nonhuman and human subjects. The final section provides a brief review of the RDoC, with a focus on the potential strengths and weaknesses of its domain-based underpinnings. Optimistically, this mechanistic and multidimensional approach in neuropsychiatric research will lead to novel therapeutics for the management of neuropsychiatric disorders.

Genetic architecture of brain morphology and overlap with neuropsychiatric traits.

Uncovering the genetic architectures of brain morphology offers valuable insights into brain development and disease. Genetic association studies of brain morphological phenotypes have discovered thousands of loci. However, interpretation of these loci presents a significant challenge. One potential solution is exploring the genetic overlap between brain morphology and disorders, which can improve our understanding of their complex relationships, ultimately aiding in clinical applications. In this review, we examine current evidence on the genetic associations between brain morphology and neuropsychiatric traits. We discuss the impact of these associations on the diagnosis, prediction, and treatment of neuropsychiatric diseases, along with suggestions for future research directions.

Deciphering the functional specialization of whole-brain spatiomolecular gradients in the adult brain.

Cortical arealization arises during neurodevelopment from the confluence of molecular gradients representing patterned expression of morphogens and transcription factors. However, whether similar gradients are maintained in the adult brain remains unknown. Here, we uncover three axes of topographic variation in gene expression in the adult human brain that specifically capture previously identified rostral-caudal, dorsal-ventral, and medial-lateral axes of early developmental patterning. The interaction of these spatiomolecular gradients i) accurately reconstructs the position of brain tissue samples, ii) delineates known functional territories, and iii) can model the topographical variation of diverse cortical features. The spatiomolecular gradients are distinct from canonical cortical axes differentiating the primary sensory cortex from the association cortex, but radiate in parallel with the axes traversed by local field potentials along the cortex. We replicate all three molecular gradients in three independent human datasets as well as two nonhuman primate datasets and find that each gradient shows a distinct developmental trajectory across the lifespan. The gradients are composed of several well-known transcription factors (e.g., PAX6 and SIX3), and a small set of genes shared across gradients are strongly enriched for multiple diseases. Together, these results provide insight into the developmental sculpting of functionally distinct brain regions, governed by three robust transcriptomic axes embedded within brain parenchyma.

Human adolescent brain similarity development is different for paralimbic versus neocortical zones.

Adolescent development of human brain structural and functional networks is increasingly recognized as fundamental to emergence of typical and atypical adult cognitive and emotional proodal magnetic resonance imaging (MRI) data collected from N [Formula: see text] 300 healthy adolescents (51%; female; 14 to 26 y) each scanned repeatedly in an accelerated longitudinal design, to provide an analyzable dataset of 469 structural scans and 448 functional MRI scans. We estimated the morphometric similarity between each possible pair of 358 cortical areas on a feature vector comprising six macro- and microstructural MRI metrics, resulting in a morphometric similarity network (MSN) for each scan. Over the course of adolescence, we found that morphometric similarity increased in paralimbic cortical areas, e.g., insula and cingulate cortex, but generally decreased in neocortical areas, and these results were replicated in an independent developmental MRI cohort (N [Formula: see text] 304). Increasing hubness of paralimbic nodes in MSNs was associated with increased strength of coupling between their morphometric similarity and functional connectivity. Decreasing hubness of neocortical nodes in MSNs was associated with reduced strength of structure-function coupling and increasingly diverse functional connections in the corresponding fMRI networks. Neocortical areas became more structurally differentiated and more functionally integrative in a metabolically expensive process linked to cortical thinning and myelination, whereas paralimbic areas specialized for affective and interoceptive functions became less differentiated, as hypothetically predicted by a developmental transition from periallocortical to proisocortical organization of the cortex. Cytoarchitectonically distinct zones of the human cortex undergo distinct neurodevelopmental programs during typical adolescence.

High-level cognition is supported by information-rich but compressible brain activity patterns.

To efficiently yet reliably represent and process information, our brains need to produce information-rich signals that differentiate between moments or cognitive states, while also being robust to noise or corruption. For many, though not all, natural systems, these two properties are often inversely related: More information-rich signals are less robust, and vice versa. Here, we examined how these properties change with ongoing cognitive demands. To this end, we applied dimensionality reduction algorithms and pattern classifiers to functional neuroimaging data collected as participants listened to a story, temporally scrambled versions of the story, or underwent a resting state scanning session. We considered two primary aspects of the neural data recorded in these different experimental conditions. First, we treated the maximum achievable decoding accuracy across participants as an indicator of the "informativeness" of the recorded patterns. Second, we treated the number of features (components) required to achieve a threshold decoding accuracy as a proxy for the "compressibility" of the neural patterns (where fewer components indicate greater compression). Overall, we found that the peak decoding accuracy (achievable without restricting the numbers of features) was highest in the intact (unscrambled) story listening condition. However, the number of features required to achieve comparable classification accuracy was also lowest in the intact story listening condition. Taken together, our work suggests that our brain networks flexibly reconfigure according to ongoing task demands and that the activity patterns associated with higher-order cognition and high engagement are both more informative and more compressible than the activity patterns associated with lower-order tasks and lower engagement.

Brain imaging and neuropsychological assessment of individuals recovered from a mild to moderate SARS-CoV-2 infection.

As severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infections have been shown to affect the central nervous system, the investigation of associated alterations of brain structure and neuropsychological sequelae is crucial to help address future health care needs. Therefore, we performed a comprehensive neuroimaging and neuropsychological assessment of 223 nonvaccinated individuals recovered from a mild to moderate SARS-CoV-2 infection (100 female/123 male, age [years], mean ± SD, 55.54 ± 7.07; median 9.7 mo after infection) in comparison with 223 matched controls (93 female/130 male, 55.74 ± 6.60) within the framework of the Hamburg City Health Study. Primary study outcomes were advanced diffusion MRI measures of white matter microstructure, cortical thickness, white matter hyperintensity load, and neuropsychological test scores. Among all 11 MRI markers tested, significant differences were found in global measures of mean diffusivity (MD) and extracellular free water which were elevated in the white matter of post-SARS-CoV-2 individuals compared to matched controls (free water: 0.148 ± 0.018 vs. 0.142 ± 0.017, P < 0.001; MD [10-3 mm2/s]: 0.747 ± 0.021 vs. 0.740 ± 0.020, P < 0.001). Group classification accuracy based on diffusion imaging markers was up to 80%. Neuropsychological test scores did not significantly differ between groups. Collectively, our findings suggest that subtle changes in white matter extracellular water content last beyond the acute infection with SARS-CoV-2. However, in our sample, a mild to moderate SARS-CoV-2 infection was not associated with neuropsychological deficits, significant changes in cortical structure, or vascular lesions several months after recovery. External validation of our findings and longitudinal follow-up investigations are needed.

Identifying causal subsequent memory effects.

Over 40 y of accumulated research has detailed associations between neuroimaging signals measured during a memory encoding task and later memory performance, across a variety of brain regions, measurement tools, statistical approaches, and behavioral tasks. But the interpretation of these subsequent memory effects (SMEs) remains unclear: if the identified signals reflect cognitive and neural mechanisms of memory encoding, then the underlying neural activity must be causally related to future memory. However, almost all previous SME analyses do not control for potential confounders of this causal interpretation, such as serial position and item effects. We collect a large fMRI dataset and use an experimental design and analysis approach that allows us to statistically adjust for nearly all known exogenous confounding variables. We find that, using standard approaches without adjustment, we replicate several univariate and multivariate subsequent memory effects and are able to predict memory performance across people. However, we are unable to identify any signal that reliably predicts subsequent memory after adjusting for confounding variables, bringing into doubt the causal status of these effects. We apply the same approach to subjects' judgments of learning collected following an encoding period and show that these behavioral measures of mnemonic status do predict memory after adjustments, suggesting that it is possible to measure signals near the time of encoding that reflect causal mechanisms but that existing neuroimaging measures, at least in our data, may not have the precision and specificity to do so.

Visual Deprivation during Mouse Critical Period Reorganizes Network-Level Functional Connectivity.

A classic example of experience-dependent plasticity is ocular dominance (OD) shift, in which the responsiveness of neurons in the visual cortex is profoundly altered following monocular deprivation (MD). It has been postulated that OD shifts also modify global neural networks, but such effects have never been demonstrated. Here, we use wide-field fluorescence optical imaging (WFOI) to characterize calcium-based resting-state functional connectivity during acute (3 d) MD in female and male mice with genetically encoded calcium indicators (Thy1-GCaMP6f). We first establish the fundamental performance of WFOI by computing signal to noise properties throughout our data processing pipeline. Following MD, we found that Δ band (0.4-4 Hz) GCaMP6 activity in the deprived visual cortex decreased, suggesting that excitatory activity in this region was reduced by MD. In addition, interhemispheric visual homotopic functional connectivity decreased following MD, which was accompanied by a reduction in parietal and motor homotopic connectivity. Finally, we observed enhanced internetwork connectivity between the visual and parietal cortex that peaked 2 d after MD. Together, these findings support the hypothesis that early MD induces dynamic reorganization of disparate functional networks including the association cortices.

Attention-Driven Modulation of Auditory Cortex Activity during Selective Listening in a Multispeaker Setting.

Real-world listening settings often consist of multiple concurrent sound streams. To limit perceptual interference during selective listening, the auditory system segregates and filters the relevant sensory input. Previous work provided evidence that the auditory cortex is critically involved in this process and selectively gates attended input toward subsequent processing stages. We studied at which level of auditory cortex processing this filtering of attended information occurs using functional magnetic resonance imaging (fMRI) and a naturalistic selective listening task. Forty-five human listeners (of either sex) attended to one of two continuous speech streams, presented either concurrently or in isolation. Functional data were analyzed using an inter-subject analysis to assess stimulus-specific components of ongoing auditory cortex activity. Our results suggest that stimulus-related activity in the primary auditory cortex and the adjacent planum temporale are hardly affected by attention, whereas brain responses at higher stages of the auditory cortex processing hierarchy become progressively more selective for the attended input. Consistent with these findings, a complementary analysis of stimulus-driven functional connectivity further demonstrated that information on the to-be-ignored speech stream is shared between the primary auditory cortex and the planum temporale but largely fails to reach higher processing stages. Our findings suggest that the neural processing of ignored speech cannot be effectively suppressed at the level of early cortical processing of acoustic features but is gradually attenuated once the competing speech streams are fully segregated.

Linking Cognitive Integrity to Working Memory Dynamics in the Aging Human Brain.

Aging is accompanied by a decline of working memory, an important cognitive capacity that involves stimulus-selective neural activity that persists after stimulus presentation. Here, we unraveled working memory dynamics in older human adults (male and female) including those diagnosed with mild cognitive impairment (MCI) using a combination of behavioral modeling, neuropsychological assessment, and MEG recordings of brain activity. Younger adults (male and female) were studied with behavioral modeling only. Participants performed a visuospatial delayed match-to-sample task under systematic manipulation of the delay and distance between sample and test stimuli. Their behavior (match/nonmatch decisions) was fit with a computational model permitting the dissociation of noise in the internal operations underlying the working memory performance from a strategic decision threshold. Task accuracy decreased with delay duration and sample/test proximity. When sample/test distances were small, older adults committed more false alarms than younger adults. The computational model explained the participants' behavior well. The model parameters reflecting internal noise (not decision threshold) correlated with the precision of stimulus-selective cortical activity measured with MEG during the delay interval. The model uncovered an increase specifically in working memory noise in older compared with younger participants. Furthermore, in the MCI group, but not in the older healthy controls, internal noise correlated with the participants' clinically assessed cognitive integrity. Our results are consistent with the idea that the stability of working memory contents deteriorates in aging, in a manner that is specifically linked to the overall cognitive integrity of individuals diagnosed with MCI.

Seven Tesla Evidence for Columnar and Rostral-Caudal Organization of the Human Periaqueductal Gray Response in the Absence of Threat: A Working Memory Study.

The periaqueductal gray (PAG) is a small midbrain structure that surrounds the cerebral aqueduct, regulates brain-body communication, and is often studied for its role in "fight-or-flight" and "freezing" responses to threat. We used ultra-high-field 7 T fMRI to resolve the PAG in humans and distinguish it from the cerebral aqueduct, examining its in vivo function during a working memory task (N = 87). Both mild and moderate cognitive demands elicited spatially similar patterns of whole-brain blood oxygenation level-dependent (BOLD) response, and moderate cognitive demand elicited widespread BOLD increases above baseline in the brainstem. Notably, these brainstem increases were not significantly greater than those in the mild demand condition, suggesting that a subthreshold brainstem BOLD increase occurred for mild cognitive demand as well. Subject-specific masks were group aligned to examine PAG response. In PAG, both mild and moderate demands elicited a well-defined response in ventrolateral PAG, a region thought to be functionally related to anticipated painful threat in humans and nonhuman animals-yet, the present task posed only the most minimal (if any) "threat," with the cognitive tasks used being approximately as challenging as remembering a phone number. These findings suggest that the PAG may play a more general role in visceromotor regulation, even in the absence of threat.

Defining Overlooked Structures Reveals New Associations between the Cortex and Cognition in Aging and Alzheimer's Disease.

Recent work suggests that indentations of the cerebral cortex, or sulci, may be uniquely vulnerable to atrophy in aging and Alzheimer's disease (AD) and that the posteromedial cortex (PMC) is particularly vulnerable to atrophy and pathology accumulation. However, these studies did not consider small, shallow, and variable tertiary sulci that are located in association cortices and are often associated with human-specific aspects of cognition. Here, we manually defined 4,362 PMC sulci in 432 hemispheres in 216 human participants (50.5% female) and found that these smaller putative tertiary sulci showed more age- and AD-related thinning than larger, more consistent sulci, with the strongest effects for two newly uncovered sulci. A model-based approach relating sulcal morphology to cognition identified that a subset of these sulci was most associated with memory and executive function scores in older adults. These findings lend support to the retrogenesis hypothesis linking brain development and aging and provide new neuroanatomical targets for future studies of aging and AD.

Superagers Resist Typical Age-Related White Matter Structural Changes.

Superagers are elderly individuals with the memory ability of people 30 years younger and provide evidence that age-related cognitive decline is not inevitable. In a sample of 64 superagers (mean age, 81.9; 59% women) and 55 typical older adults (mean age, 82.4; 64% women) from the Vallecas Project, we studied, cross-sectionally and longitudinally over 5 years with yearly follow-ups, the global cerebral white matter status as well as region-specific white matter microstructure assessment derived from diffusivity measures. Superagers and typical older adults showed no difference in global white matter health (total white matter volume, Fazekas score, and lesions volume) cross-sectionally or longitudinally. However, analyses of diffusion parameters revealed the better white matter microstructure in superagers than in typical older adults. Cross-sectional differences showed higher fractional anisotropy (FA) in superagers mostly in frontal fibers and lower mean diffusivity (MD) in most white matter tracts, expressed as an anteroposterior gradient with greater group differences in anterior tracts. FA decrease over time is slower in superagers than in typical older adults in all white matter tracts assessed, which is mirrored by MD increases over time being slower in superagers than in typical older adults in all white matter tracts except for the corticospinal tract, the uncinate fasciculus, and the forceps minor. The better preservation of white matter microstructure in superagers relative to typical older adults supports resistance to age-related brain structural changes as a mechanism underpinning the remarkable memory capacity of superagers, while their regional aging pattern is in line with the last-in-first-out hypothesis.

An In Vivo High-Resolution Human Brain Atlas of Synaptic Density.

Synapses are fundamental to the function of the central nervous system and are implicated in a number of brain disorders. Despite their pivotal role, a comprehensive imaging resource detailing the distribution of synapses in the human brain has been lacking until now. Here, we employ high-resolution PET neuroimaging in healthy humans (17F/16M) to create a 3D atlas of the synaptic marker Synaptic Vesicle glycoprotein 2A (SV2A). Calibration to absolute density values (pmol/ml) was achieved by leveraging postmortem human brain autoradiography data. The atlas unveils distinctive cortical and subcortical gradients of synapse density that reflect functional topography and hierarchical order from core sensory to higher-order integrative areas-a distribution that diverges from SV2A mRNA patterns. Furthermore, we found a positive association between IQ and SV2A density in several higher-order cortical areas. This new resource will help advance our understanding of brain physiology and the pathogenesis of brain disorders, serving as a pivotal tool for future neuroscience research.

Deciphering the genetic architecture of human brain structure and function: a brief survey on recent advances of neuroimaging genomics.

Brain imaging genomics is an emerging interdisciplinary field, where integrated analysis of multimodal medical image-derived phenotypes (IDPs) and multi-omics data, bridging the gap between macroscopic brain phenotypes and their cellular and molecular characteristics. This approach aims to better interpret the genetic architecture and molecular mechanisms associated with brain structure, function and clinical outcomes. More recently, the availability of large-scale imaging and multi-omics datasets from the human brain has afforded the opportunity to the discovering of common genetic variants contributing to the structural and functional IDPs of the human brain. By integrative analyses with functional multi-omics data from the human brain, a set of critical genes, functional genomic regions and neuronal cell types have been identified as significantly associated with brain IDPs. Here, we review the recent advances in the methods and applications of multi-omics integration in brain imaging analysis. We highlight the importance of functional genomic datasets in understanding the biological functions of the identified genes and cell types that are associated with brain IDPs. Moreover, we summarize well-known neuroimaging genetics datasets and discuss challenges and future directions in this field.

High-dimensional proteomic analysis for pathophysiological classification of traumatic brain injury.

Pathophysiology and outcomes after Traumatic Brain Injury (TBI) are complex and heterogenous. Current classifications are uninformative about pathophysiology. Proteomic approaches with fluid-based biomarkers are ideal for exploring complex disease mechanisms, as they enable sensitive assessment of an expansive range of processes potentially relevant to TBI pathophysiology. We used novel high-dimensional, multiplex proteomic assays to assess altered plasma protein expression in acute TBI. We analysed samples from 88 participants from the BIO-AX-TBI cohort (n=38 moderate-severe TBI [Mayo Criteria], n=22 non-TBI trauma, n=28 non-injured controls) on two platforms: Alamar NULISA™ CNS Diseases and OLINK® Target 96 Inflammation. Patient participants were enrolled after hospital admission, and samples taken at a single timepoint up to 10 days post-injury. Participants also had neurofilament light, GFAP, total tau, UCH-L1 (all Simoa®) and S100B (Millipore) data. The Alamar panel assesses 120 proteins, most of which were previously unexplored in TBI, plus proteins with known TBI-specificity, such as GFAP. A subset (n=29 TBI, n=24 non-injured controls) also had subacute (10 days to 6 weeks post-injury) 3T MRI measures of lesion volume and white matter injury (fractional anisotropy). Differential Expression analysis identified 16 proteins with TBI-specific significantly different plasma expression. These were neuronal markers (calbindin2, UCH-L1, visinin-like protein1), astroglial markers (S100B, GFAP), neurodegenerative disease proteins (total tau, pTau231, PSEN1, amyloid-beta-42, 14-3-3γ), inflammatory cytokines (IL16, CCL2, ficolin2), cell signalling (SFRP1), cell metabolism (MDH1) and autophagy related (sequestome1) proteins. Acute plasma levels of UCH-L1, PSEN1, total tau and pTau231 correlated with subacute lesion volume. Sequestome1 was positively correlated, whilst CLL2 was inversely correlated, with white matter fractional anisotropy. Neuronal, astroglial, tau and neurodegenerative proteins correlated with each other, IL16, MDH1 and sequestome1. Exploratory clustering (k means) by acute protein expression identified 3 TBI subgroups that differed in injury patterns, but not age or outcome. One TBI cluster had significantly lower white matter fractional anisotropy than control-predominant clusters, but had significantly lower lesion subacute lesions volumes than another TBI cluster. Proteins that overlapped on two platforms had excellent (r>0.8) correlations between values. We identified TBI-specific changes in acute plasma levels of proteins involved in neurodegenerative disease, inflammatory and cellular processes. These changes were related to patterns of injury, thus demonstrating that processes previously only studied in animal models are also relevant in human TBI pathophysiology. Our study highlights how proteomic approaches might improve classification and understanding of TBI pathophysiology, with implications for prognostication and treatment development.

Differential reorganization of episodic and semantic memory systems in epilepsy-related mesiotemporal pathology.

Declarative memory encompasses episodic and semantic divisions. Episodic memory captures singular events with specific spatiotemporal relationships, while semantic memory houses context-independent knowledge. Behavioural and functional neuroimaging studies have revealed common and distinct neural substrates of both memory systems, implicating mesiotemporal lobe (MTL) regions such as the hippocampus and distributed neocortices. Here, we explored declarative memory system reorganization in patients with unilateral temporal lobe epilepsy (TLE) as a human disease model to test the impact of variable degrees of MTL pathology on memory function. Our cohort included 31 patients with TLE as well as 60 age and sex-matched healthy controls, and all participants underwent episodic and semantic retrieval tasks during a multimodal MRI session. The functional MRI tasks were closely matched in terms of stimuli and trial design. Capitalizing on non-linear connectome gradient mapping techniques, we derived task-based functional topographies during episodic and semantic memory states, both in the MTL and in neocortical networks. Comparing neocortical and hippocampal functional gradients between TLE patients and healthy controls, we observed a marked topographic reorganization of both neocortical and MTL systems during episodic memory states. Neocortical alterations were characterized by reduced functional differentiation in TLE across lateral temporal and midline parietal cortices in both hemispheres. In the MTL, on the other hand, patients presented with a more marked functional differentiation of posterior and anterior hippocampal segments ipsilateral to the seizure focus and pathological core, indicating perturbed intrahippocampal connectivity. Semantic memory reorganization was also found in bilateral lateral temporal and ipsilateral angular regions, while hippocampal functional topographies were unaffected. Leveraging MRI proxies of MTL pathology, we furthermore observed alterations in hippocampal microstructure and morphology that were associated with TLE-related functional reorganization during episodic memory. Moreover, correlation analysis and statistical mediation models revealed that these functional alterations contributed to behavioural deficits in episodic, but again not semantic memory in patients. Altogether, our findings suggest that semantic processes rely on distributed neocortical networks, while episodic processes are supported by a network involving both the hippocampus and neocortex. Alterations of such networks can provide a compact signature of state-dependent reorganization in conditions associated with MTL damage, such as TLE.