Contracted functional connectivity profiles in autism.

OBJECTIVE: Autism spectrum disorder (ASD) is a neurodevelopmental condition that is associated with atypical brain network organization, with prior work suggesting differential connectivity alterations with respect to functional connection length. Here, we tested whether functional connectopathy in ASD specifically relates to disruptions in long- relative to short-range functional connections. Our approach combined functional connectomics with geodesic distance mapping, and we studied associations to macroscale networks, microarchitectural patterns, as well as socio-demographic and clinical phenotypes. METHODS: We studied 211 males from three sites of the ABIDE-I dataset comprising 103 participants with an ASD diagnosis (mean ± SD age = 20.8 ± 8.1 years) and 108 neurotypical controls (NT, 19.2 ± 7.2 years). For each participant, we computed cortex-wide connectivity distance (CD) measures by combining geodesic distance mapping with resting-state functional connectivity profiling. We compared CD between ASD and NT participants using surface-based linear models, and studied associations with age, symptom severity, and intelligence scores. We contextualized CD alterations relative to canonical networks and explored spatial associations with functional and microstructural cortical gradients as well as cytoarchitectonic cortical types. RESULTS: Compared to NT, ASD participants presented with widespread reductions in CD, generally indicating shorter average connection length and thus suggesting reduced long-range connectivity but increased short-range connections. Peak reductions were localized in transmodal systems (i.e., heteromodal and paralimbic regions in the prefrontal, temporal, and parietal and temporo-parieto-occipital cortex), and effect sizes correlated with the sensory-transmodal gradient of brain function. ASD-related CD reductions appeared consistent across inter-individual differences in age and symptom severity, and we observed a positive correlation of CD to IQ scores. LIMITATIONS: Despite rigorous harmonization across the three different acquisition sites, heterogeneity in autism poses a potential limitation to the generalizability of our results. Additionally, we focussed male participants, warranting future studies in more balanced cohorts. CONCLUSIONS: Our study showed reductions in CD as a relatively stable imaging phenotype of ASD that preferentially impacted paralimbic and heteromodal association systems. CD reductions in ASD corroborate previous reports of ASD-related imbalance between short-range overconnectivity and long-range underconnectivity.

Brain Networks for Cortical Atrophy and Responsive Neurostimulation in Temporal Lobe Epilepsy.

Importance: Drug-resistant temporal lobe epilepsy (TLE) has been associated with hippocampal pathology. Most surgical treatment strategies, including resection and responsive neurostimulation (RNS), focus on this disease epicenter; however, imaging alterations distant from the hippocampus, as well as emerging data from responsive neurostimulation trials, suggest conceptualizing TLE as a network disorder. Objective: To assess whether brain networks connected to areas of atrophy in the hippocampus align with the topography of distant neuroimaging alterations and RNS response. Design, Setting, and Participants: This retrospective case-control study was conducted between July 2009 and June 2022. Data collection for this multicenter, population-based study took place across 4 tertiary referral centers in Montréal, Canada; Querétaro, México; Nanjing, China; and Salt Lake City, Utah. Eligible patients were diagnosed with TLE according to International League Against Epilepsy criteria and received either neuroimaging or neuroimaging and RNS to the hippocampus. Patients with encephalitis, traumatic brain injury, or bilateral TLE were excluded. Main Outcomes and Measures: Spatial alignment between brain network topographies. Results: Of the 110 eligible patients, 94 individuals diagnosed with TLE were analyzed (51 [54%] female; mean [SD] age, 31.3 [10.9] years). Hippocampal thickness maps in TLE were compared to 120 healthy control individuals (66 [55%] female; mean [SD] age, 29.8 [9.5] years), and areas of atrophy were identified. Using an atlas of normative connectivity (n = 1000), 2 brain networks were identified that were functionally connected to areas of hippocampal atrophy. The first network was defined by positive correlations to temporolimbic, medial prefrontal, and parietal regions, whereas the second network by negative correlations to frontoparietal regions. White matter changes colocalized to the positive network (t93 = -3.82; P = 2.44 × 10-4). In contrast, cortical atrophy localized to the negative network (t93 = 3.54; P = 6.29 × 10-3). In an additional 38 patients (20 [53%] female; mean [SD] age, 35.8 [11.3] years) treated with RNS, connectivity between the stimulation site and atrophied regions within the negative network was associated with seizure reduction (t212 = -2.74; P = .007). Conclusions and Relevance: The findings in this study indicate that distributed pathology in TLE may occur in brain networks connected to the hippocampal epicenter. Connectivity to these same networks was associated with improvement following RNS. A network approach to TLE may reveal therapeutic targets outside the traditional target in the hippocampus.

Region-specific MRI predictors of surgical outcome in temporal lobe epilepsy.

OBJECTIVE: In drug-resistant temporal lobe epilepsy (TLE), it is not well-established in how far surgery should target morphological anomalies to achieve seizure freedom. Here, we assessed interactions between structural brain compromise and surgery to identify region-specific predictors of seizure outcome. METHODS: We obtained pre- and post-operative 3D T1-weighted MRI in 55 TLE patients who underwent selective amygdalo-hippocampectomy (SAH) or anterior temporal lobectomy (ATL) and 40 age and sex-matched healthy subjects. We measured surface-based morphological alterations of the mesiotemporal lobe structures (hippocampus, amygdala, entorhinal and piriform cortices), the neocortex and the thalamus on both pre- and post-operative MRI. Using precise co-registration, in each patient we mapped the surgical cavity onto the MRI acquired before surgery, thereby quantifying the amount of pathological tissue resected; these features, together with the preoperative morphometric data, served as input to a supervised classification algorithm for postsurgical outcome prediction. RESULTS: On pre-operative MRI, patients who became seizure-free (TLE-SF) presented with severe ipsilateral amygdalar and hippocampal atrophy, while not seizure-free patients (TLE-NSF) displayed amygdalar hypertrophy. Stratifying patients based on the surgical approach, post-operative MRI showed similar patterns of mesiotemporal and thalamic changes, but divergent neocortical thinning affecting the parieto-temporo-occipital regions following ATL and the frontal lobes after SAH. Irrespective of the surgical approach, hippocampal atrophy on pre-operative MRI and its extent of resection were the most predictive features of seizure-freedom in 89% of patients (selected 100% across validations). SIGNIFICANCE: Our study indicates a critical role of the extent of resection of MRI-derived hippocampal morphological anomalies on seizure outcome. Precise pre-operative quantification of the mesiotemporal lobe provides non-invasive prognostics for individualized surgery.

ANPHY-Sleep: an Open Sleep Database from Healthy Adults Using High-Density Scalp Electroencephalogram.

Well-documented sleep datasets from healthy adults are important for sleep pattern analysis and comparison with a wide range of neuropsychiatric disorders. Currently, available sleep datasets from healthy adults are acquired using low-density arrays with a minimum of four electrodes in a typical sleep montage. The low spatial resolution is thus prohibitive for the analysis of the spatial structure of sleep. Here we introduce an open-access sleep dataset from 29 healthy adults (13 female, aged 32.17 ± 6.30 years) acquired at the Montreal Neurological Institute. The dataset includes overnight polysomnograms with high-density scalp electroencephalograms incorporating 83 electrodes, electrocardiogram, electromyogram, electrooculogram, and an average of electrode positions using manual co-registrations and sleep scoring annotations. Data characteristics and group-level analysis of sleep properties were assessed. The database can be accessed through ( https://doi.org/10.17605/OSF.IO/R26FH ). This is the first high-density electroencephalogram open sleep database from healthy adults, allowing researchers to investigate sleep physiology at high spatial resolution. We expect that this database will serve as a valuable resource for studying sleep physiology and for benchmarking sleep pathology.

MULTIMODAL NEURAL CORRELATES OF CHILDHOOD PSYCHOPATHOLOGY.

Complex structural and functional changes occurring in typical and atypical development necessitate multidimensional approaches to better understand the risk of developing psychopathology. Here, we simultaneously examined structural and functional brain network patterns in relation to dimensions of psychopathology in the Adolescent Brain Cognitive Development dataset. Several components were identified, recapitulating the psychopathology hierarchy, with the general psychopathology (p) factor explaining most covariance with multimodal imaging features, while the internalizing, externalizing, and neurodevelopmental dimensions were each associated with distinct morphological and functional connectivity signatures. Connectivity signatures associated with the p factor and neurodevelopmental dimensions followed the sensory-to-transmodal axis of cortical organization, which is related to the emergence of complex cognition and risk for psychopathology. Results were consistent in two separate data subsamples, supporting generalizability, and robust to variations in analytical parameters. Our findings help in better understanding biological mechanisms underpinning dimensions of psychopathology, and could provide brain-based vulnerability markers.

Relating sex-bias in human cortical and hippocampal microstructure to sex hormones.

Determining sex-bias in brain structure is of great societal interest to improve diagnostics and treatment of brain-related disorders. So far, studies on sex-bias in brain structure predominantly focus on macro-scale measures, and often ignore factors determining this bias. Here we study sex-bias in cortical and hippocampal microstructure in relation to sex hormones. Investigating quantitative intracortical profiling in-vivo using the T1w/T2w ratio in 1093 healthy females and males of the cross-sectional Human Connectome Project young adult sample, we find that regional cortical and hippocampal microstructure differs between males and females and that the effect size of this sex-bias varies depending on self-reported hormonal status in females. Microstructural sex-bias and expression of sex hormone genes, based on an independent post-mortem sample, are spatially coupled. Lastly, sex-bias is most pronounced in paralimbic areas, with low laminar complexity, which are predicted to be most plastic based on their cytoarchitectural properties. Albeit correlative, our study underscores the importance of incorporating sex hormone variables into the investigation of brain structure and plasticity.

Differential increase of hippocampal subfield volume after socio-affective mental training relates to reductions in diurnal cortisol.

The hippocampus is a central modulator of the HPA-axis, impacting the regulation of stress on brain structure, function, and behavior. The current study assessed whether three different types of 3 months mental Training Modules geared towards nurturing (a) attention-based mindfulness, (b) socio-affective, or (c) socio-cognitive skills may impact hippocampal organization by reducing stress. We evaluated mental training-induced changes in hippocampal subfield volume and intrinsic functional connectivity, by combining longitudinal structural and resting-state fMRI connectivity analysis in 332 healthy adults. We related these changes to changes in diurnal and chronic cortisol levels. We observed increases in bilateral cornu ammonis volume (CA1-3) following the 3 months compassion-based module targeting socio-affective skills (Affect module), as compared to socio-cognitive skills (Perspective module) or a waitlist cohort with no training intervention. Structural changes were paralleled by relative increases in functional connectivity of CA1-3 when fostering socio-affective as compared to socio-cognitive skills. Furthermore, training-induced changes in CA1-3 structure and function consistently correlated with reductions in cortisol output. Notably, using a multivariate approach, we found that other subfields that did not show group-level changes also contributed to changes in cortisol levels. Overall, we provide a link between a socio-emotional behavioural intervention, changes in hippocampal subfield structure and function, and reductions in cortisol in healthy adults.

Too much stress is harmful to the brain and overall health, as it can lead to chronically high levels of the stress hormone cortisol. The part of the brain that regulates memory and emotions, called the hippocampus, is especially sensitive to stress because it has a high number of receptors that bind to cortisol. This connection may explain why stress can lead to memory lapses or strong emotions. Studies have shown that mental training exercises, such as mindfulness and meditation, may change the structure of the brain and reduce stress. However, the results from these experiments have been mixed due to the variation in mental practices used by different programs. Here, Valk, Engert et al. set out to find how distinct types of mental training affect the brain, focusing on the hippocampus and cortisol levels. The team used various magnetic resonance imaging techniques to study the hippocampus of 322 healthy adult volunteers who had undergone three months of mental training. The relationship between mental training, hippocampus size, and stress levels was complex when studying the results of each individual. However, when the results were grouped together, it revealed that volunteers who underwent training to increase empathy and compassion experienced expansion in parts of their hippocampus. As these areas of the brain increased in size, these individuals experienced corresponding reductions in cortisol levels. But volunteers who underwent mental training focused on attention or developing perspective did not experience such increases. These findings suggest that mental training to increase empathy and compassion alters brain structure and lowers cortisol levels. Future studies may explain how this happens, which could lead to improved mental training programs for mitigating stress.

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.

Associations of Cerebral Blood Flow Patterns With Gray and White Matter Structure in Patients With Temporal Lobe Epilepsy.

BACKGROUND AND OBJECTIVES: Neuroimaging studies in patients with temporal lobe epilepsy (TLE) show widespread brain network alterations beyond the mesiotemporal lobe. Despite the critical role of the cerebrovascular system in maintaining whole-brain structure and function, changes in cerebral blood flow (CBF) remain incompletely understood in the disease. Here, we studied whole-brain perfusion and vascular network alterations in TLE and assessed its associations with gray and white matter compromises and various clinical variables. METHODS: We included individuals with and without pharmaco-resistant TLE who underwent multimodal 3T MRI, including arterial spin labelling, structural, and diffusion-weighted imaging. Using surface-based MRI mapping, we generated individualized cortico-subcortical profiles of perfusion, morphology, and microstructure. Linear models compared regional CBF in patients with controls and related alterations to morphological and microstructural metrics. We further probed interregional vascular networks in TLE, using graph theoretical CBF covariance analysis. The effects of disease duration were explored to better understand the progressive changes in perfusion. We assessed the utility of perfusion in separating patients with TLE from controls using supervised machine learning. RESULTS: Compared with control participants (n = 38; mean ± SD age 34.8 ± 9.3 years; 20 females), patients with TLE (n = 24; mean ± SD age 35.8 ± 10.6 years; 12 females) showed widespread CBF reductions predominantly in fronto-temporal regions (Cohen d -0.69, 95% CI -1.21 to -0.16), consistent in a subgroup of patients who remained seizure-free after surgical resection of the seizure focus. Parallel structural profiling and network-based models showed that cerebral hypoperfusion may be partially constrained by gray and white matter changes (8.11% reduction in Cohen d) and topologically segregated from whole-brain perfusion networks (area under the curve -0.17, p < 0.05). Negative effects of progressive disease duration further targeted regional CBF profiles in patients (r = -0.54, 95% CI -0.77 to -0.16). Perfusion-derived classifiers discriminated patients from controls with high accuracy (71% [70%-82%]). Findings were robust when controlling for several methodological confounds. DISCUSSION: Our multimodal findings provide insights into vascular contributions to TLE pathophysiology affecting and extending beyond mesiotemporal structures and highlight their clinical potential in epilepsy diagnosis. As our work was cross-sectional and based on a single site, it motivates future longitudinal studies to confirm progressive effects, ideally in a multicentric setting.

Hippocampal connectivity patterns echo macroscale cortical evolution in the primate brain.

While the hippocampus is key for human cognitive abilities, it is also a phylogenetically old cortex and paradoxically considered evolutionarily preserved. Here, we introduce a comparative framework to quantify preservation and reconfiguration of hippocampal organisation in primate evolution, by analysing the hippocampus as an unfolded cortical surface that is geometrically matched across species. Our findings revealed an overall conservation of hippocampal macro- and micro-structure, which shows anterior-posterior and, perpendicularly, subfield-related organisational axes in both humans and macaques. However, while functional organisation in both species followed an anterior-posterior axis, we observed a marked reconfiguration in the latter across species, which mirrors a rudimentary integration of the default-mode-network in non-human primates. Here we show that microstructurally preserved regions like the hippocampus may still undergo functional reconfiguration in primate evolution, due to their embedding within heteromodal association networks.

Adolescent maturation of cortical excitation-inhibition balance based on individualized biophysical network modeling.

The balance of excitation and inhibition is a key functional property of cortical microcircuits which changes through the lifespan. Adolescence is considered a crucial period for the maturation of excitation-inhibition balance. This has been primarily observed in animal studies, yet human in vivo evidence on adolescent maturation of the excitation-inhibition balance at the individual level is limited. Here, we developed an individualized in vivo marker of regional excitation-inhibition balance in human adolescents, estimated using large-scale simulations of biophysical network models fitted to resting-state functional magnetic resonance imaging data from two independent cross-sectional (N = 752) and longitudinal (N = 149) cohorts. We found a widespread relative increase of inhibition in association cortices paralleled by a relative age-related increase of excitation, or lack of change, in sensorimotor areas across both datasets. This developmental pattern co-aligned with multiscale markers of sensorimotor-association differentiation. The spatial pattern of excitation-inhibition development in adolescence was robust to inter-individual variability of structural connectomes and modeling configurations. Notably, we found that alternative simulation-based markers of excitation-inhibition balance show a variable sensitivity to maturational change. Taken together, our study highlights an increase of inhibition during adolescence in association areas using cross sectional and longitudinal data, and provides a robust computational framework to estimate microcircuit maturation in vivo at the individual level.

MRI-Derived Modeling of Disease Progression Patterns in Patients With Temporal Lobe Epilepsy.

BACKGROUND AND OBJECTIVES: Temporal lobe epilepsy (TLE) is assumed to follow a steady course that is similar across patients. To date, phenotypic and temporal diversities of TLE evolution remain unknown. In this study, we aimed at simultaneously characterizing these sources of variability based on cross-sectional data. METHODS: We studied consecutive patients with TLE referred for evaluation by neurologists to the Montreal Neurological Institute epilepsy clinic, who underwent in-patient video EEG monitoring and multimodal imaging at 3 Tesla, comprising 3D T1 and fluid-attenuated inversion recovery and 2D diffusion-weighted MRI. The cohort included patients with drug-resistant epilepsy and patients with drug-responsive epilepsy. The neuropsychological evaluation included Wechsler Adult Intelligence Scale-III and Leonard tapping task. The control group consisted of participants without TLE recruited through advertisement and who underwent the same MRI acquisition as patients. Based on surface-based analysis of key MRI markers of pathology (gray matter morphology and white matter microstructure), the Subtype and Stage Inference algorithm estimated subtypes and stages of brain pathology to which individual patients were assigned. The number of subtypes was determined by running the algorithm 100 times and estimating mean and SD of disease trajectories and the consistency of patients' assignments based on 1,000 bootstrap samples. Effect of normal aging was subtracted from patients. We examined associations with clinical and cognitive parameters and utility for individualized predictions. RESULTS: We studied 82 patients with TLE (52 female, mean age 35 ± 10 years; 11 drug-responsive) and 41 control participants (23 male, mean age 32 ± 8 years). Among 57 operated, 43/37/20 had Engel-I outcome/hippocampal sclerosis/hippocampal isolated gliosis, respectively. We identified 3 trajectory subtypes: S1 (n = 35), led by ipsilateral hippocampal atrophy and gliosis, followed by white-matter damage; S2 (n = 27), characterized by bilateral neocortical atrophy, followed by ipsilateral hippocampal atrophy and gliosis; and S3 (n = 20), typified by bilateral limbic white-matter damage, followed by bilateral hippocampal gliosis. Patients showed high assignability to their subtypes and stages (>90% bootstrap agreement). S1 had the highest proportions of patients with early disease onset (effect size d = 0.27 vs S2, d = 0.73 vs S3), febrile convulsions (χ2 = 3.70), drug resistance (χ2 = 2.94), a positive MRI (χ2 = 8.42), hippocampal sclerosis (χ2 = 7.57), and Engel-I outcome (χ2 = 1.51), pFDR < 0.05 across all comparisons. S2 and S3 exhibited the intermediate and lowest proportions, respectively. Verbal IQ and digit span were lower in S1 (d = 0.65 and d = 0.50, pFDR < 0.05) and S2 (d = 0.76 and d = 1.09, pFDR < 0.05), compared with S3. We observed progressive decline in sequential motor tapping in S1 and S3 (T = -3.38 and T = -4.94, pFDR = 0.027), compared with S2 (T = 2.14, pFDR = 0.035). S3 showed progressive decline in digit span (T = -5.83, p = 0.021). Supervised classifiers trained on subtype and stage outperformed subtype-only and stage-only models predicting drug response in 73% ± 1.0% (vs 70% ± 1.4% and 63% ± 1.3%) and 76% ± 1.6% for Engel-I outcome (vs 71% ± 0.8% and 72% ± 1.1%), pFDR < 0.05 across all comparisons. DISCUSSION: Cross-sectional MRI-derived models provide reliable prognostic markers of TLE disease evolution, which follows distinct trajectories, each associated with divergent patterns of hippocampal and whole-brain structural alterations, as well as cognitive and clinical profiles.

Cognitive control training with domain-general response inhibition does not change children's brains or behavior.

Cognitive control is required to organize thoughts and actions and is critical for the pursuit of long-term goals. Childhood cognitive control relates to other domains of cognitive functioning and predicts later-life success and well-being. In this study, we used a randomized controlled trial to test whether cognitive control can be improved through a pre-registered 8-week intervention in 235 children aged 6-13 years targeting response inhibition and whether this leads to changes in multiple behavioral and neural outcomes compared to a response speed training. We show long-lasting improvements of closely related measures of cognitive control at the 1-year follow-up; however, training had no impact on any behavioral outcomes (decision-making, academic achievement, mental health, fluid reasoning and creativity) or neural outcomes (task-dependent and intrinsic brain function and gray and white matter structure). Bayesian analyses provide strong evidence of absent training effects. We conclude that targeted training of response inhibition does little to change children's brains or their behavior.

Tau follows principal axes of functional and structural brain organization in Alzheimer's disease.

Alzheimer's disease (AD) is a brain network disorder where pathological proteins accumulate through networks and drive cognitive decline. Yet, the role of network connectivity in facilitating this accumulation remains unclear. Using in-vivo multimodal imaging, we show that the distribution of tau and reactive microglia in humans follows spatial patterns of connectivity variation, the so-called gradients of brain organization. Notably, less distinct connectivity patterns ("gradient contraction") are associated with cognitive decline in regions with greater tau, suggesting an interaction between reduced network differentiation and tau on cognition. Furthermore, by modeling tau in subject-specific gradient space, we demonstrate that tau accumulation in the frontoparietal and temporo-occipital cortices is associated with greater baseline tau within their functionally and structurally connected hubs, respectively. Our work unveils a role for both functional and structural brain organization in pathology accumulation in AD, and supports subject-specific gradient space as a promising tool to map disease progression.

Connectome reorganization associated with temporal lobe pathology and its surgical resection.

Network neuroscience offers a unique framework to understand the organizational principles of the human brain. Despite recent progress, our understanding of how the brain is modulated by focal lesions remains incomplete. Resection of the temporal lobe is the most effective treatment to control seizures in pharmaco-resistant temporal lobe epilepsy (TLE), making this syndrome a powerful model to study lesional effects on network organization in young and middle-aged adults. Here, we assessed the downstream consequences of a focal lesion and its surgical resection on the brain's structural connectome, and explored how this reorganization relates to clinical variables at the individual patient level. We included adults with pharmaco-resistant TLE (n = 37) who underwent anterior temporal lobectomy between two imaging time points, as well as age- and sex-matched healthy controls who underwent comparable imaging (n = 31). Core to our analysis was the projection of high-dimensional structural connectome data-derived from diffusion MRI tractography from each subject-into lower-dimensional gradients. We then compared connectome gradients in patients relative to controls before surgery, tracked surgically-induced connectome reconfiguration from pre- to postoperative time points, and examined associations to patient-specific clinical and imaging phenotypes. Before surgery, individuals with TLE presented with marked connectome changes in bilateral temporo-parietal regions, reflecting an increased segregation of the ipsilateral anterior temporal lobe from the rest of the brain. Surgery-induced connectome reorganization was localized to this temporo-parietal subnetwork, but primarily involved postoperative integration of contralateral regions with the rest of the brain. Using a partial least-squares analysis, we uncovered a latent clinical imaging signature underlying this pre- to postoperative connectome reorganization, showing that patients who displayed postoperative integration in bilateral fronto-occipital cortices also had greater preoperative ipsilateral hippocampal atrophy, lower seizure frequency and secondarily generalized seizures. Our results bridge the effects of focal brain lesions and their surgical resections with large-scale network reorganization and interindividual clinical variability, thus offering new avenues to examine the fundamental malleability of the human brain.

Atypical connectome topography and signal flow in temporal lobe epilepsy.

Temporal lobe epilepsy (TLE) is the most common pharmaco-resistant epilepsy in adults. While primarily associated with mesiotemporal pathology, recent evidence suggests that brain alterations in TLE extend beyond the paralimbic epicenter and impact macroscale function and cognitive functions, particularly memory. Using connectome-wide manifold learning and generative models of effective connectivity, we examined functional topography and directional signal flow patterns between large-scale neural circuits in TLE at rest. Studying a multisite cohort of 95 patients with TLE and 95 healthy controls, we observed atypical functional topographies in the former group, characterized by reduced differentiation between sensory and transmodal association cortices, with most marked effects in bilateral temporo-limbic and ventromedial prefrontal cortices. These findings were consistent across all study sites, present in left and right lateralized patients, and validated in a subgroup of patients with histopathological validation of mesiotemporal sclerosis and post-surgical seizure freedom. Moreover, they were replicated in an independent cohort of 30 TLE patients and 40 healthy controls. Further analyses demonstrated that reduced differentiation related to decreased functional signal flow into and out of temporolimbic cortical systems and other brain networks. Parallel analyses of structural and diffusion-weighted MRI data revealed that topographic alterations were independent of TLE-related cortical thinning but partially mediated by white matter microstructural changes that radiated away from paralimbic circuits. Finally, we found a strong association between the degree of functional alterations and behavioral markers of memory dysfunction. Our work illustrates the complex landscape of macroscale functional imbalances in TLE, which can serve as intermediate markers bridging microstructural changes and cognitive impairment.

Gradients of Brain Organization: Smooth Sailing from Methods Development to User Community.

Multimodal neuroimaging grants a powerful in vivo window into the structure and function of the human brain. Recent methodological and conceptual advances have enabled investigations of the interplay between large-scale spatial trends - or gradients - in brain structure and function, offering a framework to unify principles of brain organization across multiple scales. Strong community enthusiasm for these techniques has been instrumental in their widespread adoption and implementation to answer key questions in neuroscience. Following a brief review of current literature on this framework, this perspective paper will highlight how pragmatic steps aiming to make gradient methods more accessible to the community propelled these techniques to the forefront of neuroscientific inquiry. More specifically, we will emphasize how interest for gradient methods was catalyzed by data sharing, open-source software development, as well as the organization of dedicated workshops led by a diverse team of early career researchers. To this end, we argue that the growing excitement for brain gradients is the result of coordinated and consistent efforts to build an inclusive community and can serve as a case in point for future innovations and conceptual advances in neuroinformatics. We close this perspective paper by discussing challenges for the continuous refinement of neuroscientific theory, methodological innovation, and real-world translation to maintain our collective progress towards integrated models of brain organization.

GAN-MAT: Generative adversarial network-based microstructural profile covariance analysis toolbox.

Multimodal magnetic resonance imaging (MRI) provides complementary information for investigating brain structure and function; for example, an in vivo microstructure-sensitive proxy can be estimated using the ratio between T1- and T2-weighted structural MRI. However, acquiring multiple imaging modalities is challenging in patients with inattentive disorders. In this study, we proposed a comprehensive framework to provide multiple imaging features related to the brain microstructure using only T1-weighted MRI. Our toolbox consists of (i) synthesizing T2-weighted MRI from T1-weighted MRI using a conditional generative adversarial network; (ii) estimating microstructural features, including intracortical covariance and moment features of cortical layer-wise microstructural profiles; and (iii) generating a microstructural gradient, which is a low-dimensional representation of the intracortical microstructure profile. We trained and tested our toolbox using T1- and T2-weighted MRI scans of 1,104 healthy young adults obtained from the Human Connectome Project database. We found that the synthesized T2-weighted MRI was very similar to the actual image and that the synthesized data successfully reproduced the microstructural features. The toolbox was validated using an independent dataset containing healthy controls and patients with episodic migraine as well as the atypical developmental condition of autism spectrum disorder. Our toolbox may provide a new paradigm for analyzing multimodal structural MRI in the neuroscience community and is openly accessible at https://github.com/CAMIN-neuro/GAN-MAT.

The Brain's Topographical Organization Shapes Dynamic Interaction Patterns That Support Flexible Behavior Based on Rules and Long-Term Knowledge.

Adaptive behavior relies both on specific rules that vary across situations and stable long-term knowledge gained from experience. The frontoparietal control network (FPCN) is implicated in the brain's ability to balance these different influences on action. Here, we investigate how the topographical organization of the cortex supports behavioral flexibility within the FPCN. Functional properties of this network might reflect its juxtaposition between the dorsal attention network (DAN) and the default mode network (DMN), two large-scale systems implicated in top-down attention and memory-guided cognition, respectively. Our study tests whether subnetworks of FPCN are topographically proximal to the DAN and the DMN, respectively, and how these topographical differences relate to functional differences: the proximity of each subnetwork is anticipated to play a pivotal role in generating distinct cognitive modes relevant to working memory and long-term memory. We show that FPCN subsystems share multiple anatomical and functional similarities with their neighboring systems (DAN and DMN) and that this topographical architecture supports distinct interaction patterns that give rise to different patterns of functional behavior. The FPCN acts as a unified system when long-term knowledge supports behavior but becomes segregated into discrete subsystems with different patterns of interaction when long-term memory is less relevant. In this way, our study suggests that the topographical organization of the FPCN and the connections it forms with distant regions of cortex are important influences on how this system supports flexible behavior.

Whole-brain structural connectome asymmetry in autism.

Autism spectrum disorder is a common neurodevelopmental condition that manifests as a disruption in sensory and social skills. Although it has been shown that the brain morphology of individuals with autism is asymmetric, how this differentially affects the structural connectome organization of each hemisphere remains under-investigated. We studied whole-brain structural connectivity-based brain asymmetry in individuals with autism using diffusion magnetic resonance imaging obtained from the Autism Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations of structural connectivity and calculated their asymmetry index. Comparing the asymmetry index between individuals with autism and neurotypical controls, we found atypical structural connectome asymmetry in the sensory and default-mode regions, particularly showing weaker asymmetry towards the right hemisphere in autism. Network communication provided topological underpinnings by demonstrating that the inferior temporal cortex and limbic and frontoparietal regions showed reduced global network communication efficiency and decreased send-receive network navigation in the inferior temporal and lateral visual cortices in individuals with autism. Finally, supervised machine learning revealed that structural connectome asymmetry could be used as a measure for predicting communication-related autistic symptoms and nonverbal intelligence. Our findings provide insights into macroscale structural connectome alterations in autism and their topological underpinnings.