AICHA: An atlas of intrinsic connectivity of homotopic areas

EEG Ictal Power Dynamics, Function-Structure Associations, and Epilepsy Surgical Outcomes

BACKGROUND AND OBJECTIVES

Postoperative seizure control in drug-resistant temporal lobe epilepsy (TLE) remains variable, and the causes for this variability are not well understood. One contributing factor could be the extensive spread of synchronized ictal activity across networks. Our study used novel quantifiable assessments from intracranial EEG (iEEG) to test this hypothesis and investigated how the spread of seizures is determined by underlying structural network topological properties.

METHODS

We evaluated iEEG data from 157 seizures in 27 patients with TLE: 100 seizures from 17 patients with postoperative seizure control (Engel score I) vs 57 seizures from 10 patients with unfavorable surgical outcomes (Engel score II-IV). We introduced a quantifiable method to measure seizure power dynamics within anatomical regions, refining existing seizure imaging frameworks and minimizing reliance on subjective human decision-making. Time-frequency power representations were obtained in 6 frequency bands ranging from theta to gamma. Ictal power spectrums were normalized against a baseline clip taken at least 6 hours away from ictal events. Electrodes' time-frequency power spectrums were then mapped onto individual T1-weighted MRIs and grouped based on a standard brain atlas. We compared spatiotemporal dynamics for seizures between groups with favorable and unfavorable surgical outcomes. This comparison included examining the range of activated brain regions and the spreading rate of ictal activities. We then evaluated whether regional iEEG power values were a function of fractional anisotropy (FA) from diffusion tensor imaging across regions over time.

RESULTS

Seizures from patients with unfavorable outcomes exhibited significantly higher maximum activation sizes in various frequency bands. Notably, we provided quantifiable evidence that in seizures associated with unfavorable surgical outcomes, the spread of beta-band power across brain regions is significantly faster, detectable as early as the first second after seizure onset. There was a significant correlation between beta power during seizures and FA in the corresponding areas, particularly in the unfavorable outcome group. Our findings further suggest that integrating structural and functional features could improve the prediction of epilepsy surgical outcomes.

DISCUSSION

Our findings suggest that ictal iEEG power dynamics and the structural-functional relationship are mechanistic factors associated with surgical outcomes in TLE.

Assigning a social status from face adornments: an fMRI study

For at least 150,000 years, the human body has been culturally modified by the wearing of personal ornaments and probably by painting with red pigment. The present study used functional magnetic resonance imaging to explore the brain networks involved in attributing social status from face decorations. Results showed the fusiform gyrus, orbitofrontal cortex, and salience network were involved in social encoding, categorization, and evaluation. The hippocampus and parahippocampus were activated due to the memory and associative skills required for the task, while the inferior frontal gyrus likely interpreted face ornaments as symbols. Resting-state functional connectivity analysis clarified the interaction between these regions. The study highlights the importance of these neural interactions in the symbolic interpretation of social markers on the human face, which were likely active in early Homo species and intensified with Homo sapiens populations as more complex technologies were developed to culturalize the human face.

Optimizing Surgical Planning for Epilepsy Patients With Multimodal Neuroimaging and Neurophysiology Integration: A Case Study

SUMMARY

Current preoperative evaluation of epilepsy can be challenging because of the lack of a comprehensive view of the network's dysfunctions. To demonstrate the utility of our multimodal neurophysiology and neuroimaging integration approach in the presurgical evaluation, we present a proof-of-concept for using this approach in a patient with nonlesional frontal lobe epilepsy who underwent two resective surgeries to achieve seizure control. We conducted a post-hoc investigation using four neuroimaging and neurophysiology modalities: diffusion tensor imaging, resting-state functional MRI, and stereoelectroencephalography at rest and during seizures. We computed region-of-interest-based connectivity for each modality and applied betweenness centrality to identify key network hubs across modalities. Our results revealed that despite seizure semiology and stereoelectroencephalography indicating dysfunction in the right orbitofrontal region, the maximum overlap on the hubs across modalities extended to right temporal areas. Notably, the right middle temporal lobe region served as an overlap hub across diffusion tensor imaging, resting-state functional MRI, and rest stereoelectroencephalography networks and was only included in the resected area in the second surgery, which led to long-term seizure control of this patient. Our findings demonstrated that transmodal hubs could help identify key areas related to epileptogenic network. Therefore, this case presents a promising perspective of using a multimodal approach to improve the presurgical evaluation of patients with epilepsy.

Contributions of the left and right thalami to language: A meta-analytic approach

BACKGROUND

Despite a pervasive cortico-centric view in cognitive neuroscience, subcortical structures including the thalamus have been shown to be increasingly involved in higher cognitive functions. Previous structural and functional imaging studies demonstrated cortico-thalamo-cortical loops which may support various cognitive functions including language. However, large-scale functional connectivity of the thalamus during language tasks has not been examined before.

METHODS

The present study employed meta-analytic connectivity modeling to identify language-related coactivation patterns of the left and right thalami. The left and right thalami were used as regions of interest to search the BrainMap functional database for neuroimaging experiments with healthy participants reporting language-related activations in each region of interest. Activation likelihood estimation analyses were then carried out on the foci extracted from the identified studies to estimate functional convergence for each thalamus. A functional decoding analysis based on the same database was conducted to characterize thalamic contributions to different language functions.

RESULTS

The results revealed bilateral frontotemporal and bilateral subcortical (basal ganglia) coactivation patterns for both the left and right thalami, and also right cerebellar coactivations for the left thalamus, during language processing. In light of previous empirical studies and theoretical frameworks, the present connectivity and functional decoding findings suggest that cortico-subcortical-cerebellar-cortical loops modulate and fine-tune information transfer within the bilateral frontotemporal cortices during language processing, especially during production and semantic operations, but also other language (e.g., syntax, phonology) and cognitive operations (e.g., attention, cognitive control).

CONCLUSION

The current findings show that the language-relevant network extends beyond the classical left perisylvian cortices and spans bilateral cortical, bilateral subcortical (bilateral thalamus, bilateral basal ganglia) and right cerebellar regions.

Modulate the impact of the drowsiness on the resting state functional connectivity

This research explores different methodologies to modulate the effects of drowsiness on functional connectivity (FC) during resting-state functional magnetic resonance imaging (RS-fMRI). The study utilized a cohort of students (MRi-Share) and classified individuals into drowsy, alert, and mixed/undetermined states based on observed respiratory oscillations. We analyzed the FC group difference between drowsy and alert individuals after five different processing methods: the reference method, two based on physiological and a global signal regression of the BOLD time series signal, and two based on Gaussian standardizations of the FC distribution. According to the reference method, drowsy individuals exhibit higher cortico-cortical FC than alert individuals. First, we demonstrated that each method reduced the differences between drowsy and alert states. The second result is that the global signal regression was quantitively the most effective, minimizing significant FC differences to only 3.3% of the total FCs. However, one should consider the risks of overcorrection often associated with this methodology. Therefore, choosing a less aggressive form of regression, such as the physiological method or Gaussian-based approaches, might be a more cautious approach. Third and last, using the Gaussian-based methods, cortico-subcortical and intra-default mode network (DMN) FCs were significantly greater in alert than drowsy subjects. These findings bear resemblance to the anticipated patterns during the onset of sleep, where the cortex isolates itself to assist in transitioning into deeper slow wave sleep phases, simultaneously disconnecting the DMN.

Convolutional neural network-based classification of glaucoma using optic radiation tissue properties

BACKGROUND

Sensory changes due to aging or disease can impact brain tissue. This study aims to investigate the link between glaucoma, a leading cause of blindness, and alterations in brain connections.

METHODS

We analyzed diffusion MRI measurements of white matter tissue in a large group, consisting of 905 glaucoma patients (aged 49-80) and 5292 healthy individuals (aged 45-80) from the UK Biobank. Confounds due to group differences were mitigated by matching a sub-sample of controls to glaucoma subjects. We compared classification of glaucoma using convolutional neural networks (CNNs) focusing on the optic radiations, which are the primary visual connection to the cortex, against those analyzing non-visual brain connections. As a control, we evaluated the performance of regularized linear regression models.

RESULTS

We showed that CNNs using information from the optic radiations exhibited higher accuracy in classifying subjects with glaucoma when contrasted with CNNs relying on information from non-visual brain connections. Regularized linear regression models were also tested, and showed significantly weaker classification performance. Additionally, the CNN was unable to generalize to the classification of age-group or of age-related macular degeneration.

CONCLUSIONS

Our findings indicate a distinct and potentially non-linear signature of glaucoma in the tissue properties of optic radiations. This study enhances our understanding of how glaucoma affects brain tissue and opens avenues for further research into how diseases that affect sensory input may also affect brain aging.

Directed functional connectivity of the default-mode-network of young and older healthy subjects

Alterations in the default mode network (DMN) are associated with aging. We assessed age-dependent changes of DMN interactions and correlations with a battery of neuropsychological tests, to understand the differences of DMN directed connectivity between young and older subjects. Using a novel multivariate analysis method on resting-state functional MRI data from fifty young and thirty-one healthy older subjects, we calculated intra- and inter-DMN 4-nodes directed pathways. For the old subject group, we calculated the partial correlations of inter-DMN pathways with: psychomotor speed and working memory, executive function, language, long-term memory and visuospatial function. Pathways connecting the DMN with visual and limbic regions in older subjects engaged at BOLD low frequency and involved the dorsal posterior cingulate cortex (PCC), whereas in young subjects, they were at high frequency and involved the ventral PCC. Pathways combining the sensorimotor (SM) cortex and the DMN, were SM efferent in the young subjects and SM afferent in the older subjects. Most DMN efferent pathways correlated with reduced speed and working memory. We suggest that the reduced sensorimotor efferent and the increased need to control such activities, cause a higher dependency on external versus internal cues thus suggesting how physical activity might slow aging.

Increased interhemispheric functional connectivity after right anodal tDCS in chronic non-fluent aphasia: preliminary findings

Introduction

Anodal transcranial Direct Current Stimulation (tDCS) is a non-invasive, low-cost and environment-friendly brain neuromodulation technique that increases cortical excitability. In post-stroke aphasia, the role of the right hemisphere in language recovery remains debated. In this preliminary study, we aimed to investigate the efficacy of excitatory tDCS on the right hemisphere in chronic aphasic patients.

Methods

We applied anodal tDCS to the right homologous region of Broca's area in four chronic aphasic patients while performing a one-month naming rehabilitation treatment. Longitudinal data on language assessment and naming performance were collected. Resting-state fMRI images were acquired before and after treatment to measure changes in functional connectivity.

Results

Results showed enhanced positive functional connectivity of the right Broca homologous with the left middle frontal and middle temporal gyri. Every patient showed improvements in language functions, but no major changes in naming performance.

Conclusion

These preliminary findings suggest that tDCS applied over the unaffected hemisphere may result in longitudinal inter-hemispheric functional neuroplastic changes that could specifically improve language recovery and could potentially be included in therapeutic neurorehabilitative plans.

Development of the Alpha Rhythm Is Linked to Visual White Matter Pathways and Visual Detection Performance

Alpha is the strongest electrophysiological rhythm in awake humans at rest. Despite its predominance in the EEG signal, large variations can be observed in alpha properties during development, with an increase in alpha frequency over childhood and adulthood. Here, we tested the hypothesis that these changes in alpha rhythm are related to the maturation of visual white matter pathways. We capitalized on a large diffusion MRI (dMRI)-EEG dataset (dMRI n = 2,747, EEG n = 2,561) of children and adolescents of either sex (age range, 5-21 years old) and showed that maturation of the optic radiation specifically accounts for developmental changes of alpha frequency. Behavioral analyses also confirmed that variations of alpha frequency are related to maturational changes in visual perception. The present findings demonstrate the close link between developmental variations in white matter tissue properties, electrophysiological responses, and behavior.

Hemispheric coupling between structural and functional asymmetries in clinically asymptomatic carotid stenosis with cognitive impairment

Advanced carotid stenosis is a known risk factor for ischemic stroke and vascular dementia, and it is associated with multidomain cognitive impairment as well as asymmetric alterations in hemispheric structure and function. Here we introduced a novel measure-the asymmetry index of amplitude of low-frequency fluctuations (ALFF_AI)-derived from resting-state functional magnetic resonance imaging. This measure captures the hemispheric asymmetry of intrinsic brain activity using high-dimensional registration. We aimed to investigate functional brain asymmetric alterations in patients with severe asymptomatic carotid stenosis (SACS). Furthermore, we extended the analyses of ALFF_AI to different frequencies to detect frequency-specific alterations. Finally, we examined the coupling between hemispheric asymmetric structure and function and the relationship between these results and cognitive tests, as well as the white matter hyperintensity burden. SACS patients presented significantly decreased ALFF_AI in several clusters, including the visual, auditory, parahippocampal, Rolandic, and superior parietal regions. At low frequencies (0.01-0.25 Hz), the ALFF_AI exhibited prominent group differences as frequency increased. Further structure-function coupling analysis indicated that SACS patients had lower coupling in the lateral prefrontal, superior medial frontal, middle temporal, superior parietal, and striatum regions but higher coupling in the lateral occipital regions. These findings suggest that, under potential hemodynamic burden, SACS patients demonstrate asymmetric hemispheric configurations of intrinsic activity patterns and a decoupling between structural and functional asymmetries.

Dissociative Effects of Age on Neural Differentiation at the Category and Item Levels

Increasing age is associated with age-related neural dedifferentiation, a reduction in the selectivity of neural representations, which has been proposed to contribute to cognitive decline in older age. Recent findings indicate that when operationalized in terms of selectivity for different perceptual categories, age-related neural dedifferentiation and the apparent age-invariant association of neural selectivity with cognitive performance are largely restricted to the cortical regions typically recruited during scene processing. It is currently unknown whether this category-level dissociation extends to metrics of neural selectivity defined at the level of individual stimulus items. Here, we examined neural selectivity at the category and item levels using multivoxel pattern similarity analysis (PSA) of fMRI data. Healthy young and older male and female adults viewed images of objects and scenes. Some items were presented singly, while others were either repeated or followed by a "similar lure." In agreement with recent findings, category-level PSA revealed robustly lower differentiation in older than in younger adults in scene-selective, but not object-selective, cortical regions. By contrast, at the item level, robust age-related declines in neural differentiation were evident for both stimulus categories. Additionally, we identified an age-invariant association between category-level scene selectivity in the parahippocampal place area and subsequent memory performance, but no such association was evident for item-level metrics. Lastly, category- and item-level neural metrics were uncorrelated. Thus, the present findings suggest that age-related category- and item-level dedifferentiation depend on distinct neural mechanisms.

Early modulations of neural oscillations during the processing of emotional body language

The processing of threat-related emotional body language (EBL) has been shown to engage sensorimotor cortical areas early on and induce freezing in the observers' motor system, particularly when observing fearful EBL. To provide insights into the interplay between somatosensory and motor areas during observation of EBL, here, we used high-density electroencephalography (hd-EEG) in healthy humans while they observed EBL stimuli involving fearful and neutral expressions. To capture early sensorimotor brain response, we focused on P100 fronto-central event-related potentials (ERPs) and event-related desynchronization/synchronization (ERD/ERS) in the mu-alpha (8-13 Hz) and lower beta (13-20 Hz) bands over the primary motor (M1) and somatosensory (S1) cortices. Source-level ERP and ERD/ERS analyses were conducted using eLORETA. Results revealed higher P100 amplitudes in motor and premotor channels for 'Neutral' compared with 'Fear'. Additionally, analysis of ERD/ERS showed increased beta band desynchronization in M1 for 'Neutral', and the opposite pattern in S1. Source-level estimation showed significant differences between conditions mainly observed in the beta band over sensorimotor areas. These findings provide high-temporal resolution evidence suggesting that seeing fearful EBL induces early activation of somatosensory areas, which in turn could suppress M1 activity. These findings highlight early dynamics within the observer's sensorimotor system and hint at a sensorimotor mechanism supporting freezing during the processing of EBL.

Network-based statistics distinguish anomic and Broca's aphasia

INTRODUCTION

Aphasia is a speech-language impairment commonly caused by damage to the left hemisphere. The neural mechanisms that underpin different types of aphasia and their symptoms are still not fully understood. This study aims to identify differences in resting-state functional connectivity between anomic and Broca's aphasia measured through resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS

We used the network-based statistic (NBS) method, as well as voxel- and connectome-based lesion symptom mapping (V-, CLSM), to identify distinct neural correlates of the anomic and Broca's groups. To control for lesion effect, we included lesion volume as a covariate in both the NBS method and LSM.

RESULTS

NBS identified a subnetwork located in the dorsal language stream bilaterally, including supramarginal gyrus, primary sensory, motor, and auditory cortices, and insula. The connections in the subnetwork were weaker in the Broca's group than the anomic group. The properties of the subnetwork were examined through complex network measures, which indicated that regions in right inferior frontal sulcus, right paracentral lobule, and bilateral superior temporal gyrus exhibit intensive interaction. Left superior temporal gyrus, right postcentral gyrus, and left supramarginal gyrus play an important role in information flow and overall communication efficiency. Disruption of this network underlies the constellation of symptoms associated with Broca's aphasia. Whole-brain CLSM did not detect any significant connections, suggesting an advantage of NBS when thousands of connections are considered. However, CLSM identified connections that differentiated Broca's from anomic aphasia when analysis was restricted to a hypothesized network of interest.

DISCUSSION

We identified novel signatures of resting-state brain network differences between groups of individuals with anomic and Broca's aphasia. We identified a subnetwork of connections that statistically differentiated the resting-state brain networks of the two groups, in comparison with standard CLSM results that yielded isolated connections. Network-level analyses are useful tools for the investigation of the neural correlates of language deficits post-stroke.

When Age Tips the Balance: a Dual Mechanism Affecting Hemispheric Specialization for Language

Aging engenders neuroadaptations, generally reducing specificity and selectivity in functional brain responses. Our investigation delves into the functional specialization of brain hemispheres within language-related networks across adulthood. In a cohort of 728 healthy adults spanning ages 18 to 88, we modeled the trajectories of inter-hemispheric asymmetry concerning the principal functional gradient across 37 homotopic regions of interest (hROIs) of an extensive language network, known as the Language-and-Memory Network. Our findings reveal that over two-thirds of Language-and-Memory Network hROIs undergo asymmetry changes with age, falling into two main clusters. The first cluster evolves from left-sided specialization to right-sided tendencies, while the second cluster transitions from right-sided asymmetry to left-hemisphere dominance. These reversed asymmetry shifts manifest around midlife, occurring after age 50, and are associated with poorer language production performance. Our results provide valuable insights into the influence of functional brain asymmetries on language proficiency and present a dynamic perspective on brain plasticity during the typical aging process.

Identifying canonical and replicable multi-scale intrinsic connectivity networks in 100k+ resting-state fMRI datasets

Despite the known benefits of data-driven approaches, the lack of approaches for identifying functional neuroimaging patterns that capture both individual variations and inter-subject correspondence limits the clinical utility of rsfMRI and its application to single-subject analyses. Here, using rsfMRI data from over 100k individuals across private and public datasets, we identify replicable multi-spatial-scale canonical intrinsic connectivity network (ICN) templates via the use of multi-model-order independent component analysis (ICA). We also study the feasibility of estimating subject-specific ICNs via spatially constrained ICA. The results show that the subject-level ICN estimations vary as a function of the ICN itself, the data length, and the spatial resolution. In general, large-scale ICNs require less data to achieve specific levels of (within- and between-subject) spatial similarity with their templates. Importantly, increasing data length can reduce an ICN's subject-level specificity, suggesting longer scans may not always be desirable. We also find a positive linear relationship between data length and spatial smoothness (possibly due to averaging over intrinsic dynamics), suggesting studies examining optimized data length should consider spatial smoothness. Finally, consistency in spatial similarity between ICNs estimated using the full data and subsets across different data lengths suggests lower within-subject spatial similarity in shorter data is not wholly defined by lower reliability in ICN estimates, but may be an indication of meaningful brain dynamics which average out as data length increases.

Neuroanatomical correlates of cognitive impairment following basal ganglia-thalamic post-hemorrhagic stroke: Uncovering network-wide alterations in hemispheric gray matter asymmetry

Cognitive impairment and recovery are central issues in hemorrhagic stroke. This study aimed to investigate whether post-hemorrhagic stroke cognitive impairment (PhSCI) is associated with cortical gray matter (GM) loss and hemispheric asymmetry changes and whether these changes could predict improvements in cognitive function during the recovery. Nineteen patients with PhSCI, comprising 10 with basal ganglia hemorrhage and 9 with thalamic hemorrhage, were recruited. Among them, 9 completed a course of repetitive transcranial magnetic stimulation (rTMS). Additionally, 19 demographically and comorbidity-matched healthy controls were also included. Structural brain MRI and cognitive assessments were performed. Voxel-wise GM volume and hemispheric asymmetry were analyzed. The PhSCI patients exhibited bilateral, yet asymmetric, GM losses in the hippocampus, fusiform, lateral temporal, prefrontal, somatomotor, and inferior parietal regions. The analysis of GM asymmetry revealed that patients showed rightward GM in the lateral temporal, somatomotor, and inferior parietal regions. Among the 9 PhSCI patients who completed rTMS, there was a marginal trend of regional GM increase and leftward GM, and these changes were in parallel with the improvements in cognitive tests. Further lesion connectivity and metanalytic mapping identified two interconnected systems linked to the lesions, which were anchored in the default mode, somatomotor, and salience/cognitive control networks and in the cognitive domains of memory, language, decision-making, and executive function. In conclusion, PhSCI patients exhibited network-wide cortical GM losses, distal to subcortical hemorrhagic lesions, and hemisphere asymmetry changes. These changes appear to predict rTMS-related cognitive improvements, suggesting that even subcortical focal lesions can lead to alterations in distal cortical neuroanatomical architecture. Our preliminary findings provide new insights into the neuroanatomical basis of PhSCI.

Prospective and Retrospective Metacognitive Abilities and Their Association with Impaired Self-awareness in Patients with Traumatic Brain Injury

Metacognitive impairment often occurs in patients with traumatic brain injury (TBI) and is associated with clinical problems. The aim of this study was to clarify the pathology of metacognitive impairment in TBI patients using a behavioral task, clinical assessment of self-awareness, and lesion-symptom mapping. Metacognitive abilities of TBI patients and healthy controls were assessed using a modified perceptual decision-making task. Self-awareness was assessed using the Patient Competency Rating Scale and the Frontal Systems Behavior Scale. The associations between estimated metacognitive abilities, self-awareness, and neuropsychological test results were examined. The correspondence between metacognitive disabilities and brain lesions was explored by ROI-based lesion-symptom mapping using structural magnetic resonance images. Overall, 25 TBI patients and 95 healthy controls were included in the analyses. Compared with that in healthy controls, the prospective metacognitive ability of TBI patients was lower, with metacognitive evaluations revealing a bias toward overestimating their abilities. Retrospective metacognitive ability showed a negative correlation with self-awareness but not with neuropsychological test results. In the lesion-symptom mapping analysis, the left pFC was associated with lower retrospective metacognitive ability. This study contributes to a better understanding of the pathology of metacognitive and self-awareness deficits in TBI patients and may explain the cause of impaired realistic goal setting and adaptive behavior in these patients.

A personalized cortical atlas for functional regions of interest

Advances in functional MRI (fMRI) allow mapping an individual's brain function in vivo. Task fMRI can localize domain-specific regions of cognitive processing or functional regions of interest (fROIs) within an individual. Moreover, data from resting state (no task) fMRI can be used to define an individual's connectome, which can characterize that individual's functional organization via connectivity-based parcellations. However, can connectivity-based parcellations alone predict an individual's fROIs? Here, we describe an approach to compute individualized rs-fROIs (i.e., regions that correspond to given fROI constructed using only resting state data) for motor control, working memory, high-level vision, and language comprehension. The rs-fROIs were computed and validated using a large sample of young adults (n = 1,018) with resting state and task fMRI from the Human Connectome Project. First, resting state parcellations were defined across a sequence of resolutions from broadscale to fine-grained networks in a training group of 500 individuals. Second, 21 rs-fROIs were defined from the training group by identifying the rs network that most closely matched task-defined fROIs across all individuals. Third, the selectivity of rs-fROIs was investigated in a training set of the remaining 518 individuals. All computed rs-fROIs were indeed selective for their preferred category. Critically, the rs-fROIs had higher selectivity than probabilistic atlas parcels for nearly all fROIs. In conclusion, we present a potential approach to define selective fROIs on an individual-level circumventing the need for multiple task-based localizers.NEW & NOTEWORTHY We compute individualized resting state parcels that identify an individual's own functional regions of interest (fROIs) for high-level vision, language comprehension, motor control, and working memory, using only their functional connectome. This approach demonstrates a rapid and powerful alternative for finding a large set of fROIs in an individual, using only their unique connectivity pattern, which does not require the costly acquisition of multiple fMRI localizer tasks.

The role of functional and structural properties of the nucleus accumbens subregions in eating behavior regulation of bulimia nervosa

OBJECTIVE

Although studies have demonstrated the involvement of the nucleus accumbens (NAc) in the neurobiology of eating disorders, its alterations in bulimia nervosa (BN) remain largely unknown. This study investigated the structural and functional properties of NAc in patients with BN.

METHOD

Based on the resting-state functional MRI and high-resolution anatomical T1-weighted imaging data acquired from 43 right-handed BN patients and 40 sex-, age- and education-matched right-handed healthy controls (HCs), the group differences in gray matter volume (GMV) and fractional amplitude of low-frequency fluctuation (fALFF) in slow-4 and -5 bands and functional connectivity (FC) of NAc subregions (core and shell) were compared. The relationships between MRI and clinical data were explored in the BN group.

RESULTS

Compared with HCs, BN patients showed preserved GMV, decreased fALFF in slow-5 band of the left NAc core and shell, decreased FC between left NAc core and right caudate, and increased FC between all NAc subregions and frontal regions, between all NAc subregions (except the right NAc core) and the supramarginal gyrus (SMG), and between right NAc shell and left middle temporal gyrus. FC between the NAc and SMG was correlated with emotional eating behaviors.

DISCUSSION

Our study revealed preserved GMV, local neuronal activity reduction and functional network reorganization of the NAc in BN. The functional network reorganization of the NAc mainly occurred in the frontal cortex and was correlated with emotional eating behavior. These findings may provide novel insights into the BN using NAc as an entry point.

PUBLIC SIGNIFICANCE

Although studies have demonstrated the involvement of the nucleus accumbens (NAc) in the neurobiology of eating disorders, its alterations in bulimia nervosa (BN) remain largely unknown. We used a multimodal MRI technique to systematically investigate structural and functional alterations in NAc subregions of BN patients and explored the associations between such alterations and maladaptive eating behaviors, hoping to provide novel insights into BN.

Stronger influence of systemic than local hemodynamic-vascular factors on resting-state BOLD functional connectivity

Correlated fluctuations in the blood oxygenation level dependent (BOLD) signal of resting-state functional MRI (i.e., BOLD-functional connectivity, BOLD-FC) reflect a spectrum of neuronal and non-neuronal processes. In particular, there are multiple hemodynamic-vascular influences on BOLD-FC on both systemic (e.g., perfusion delay) and local levels (e.g., neurovascular coupling). While the influence of individual factors has been studied extensively, combined and comparative studies of systemic and local hemodynamic-vascular factors on BOLD-FC are scarce, notably in humans. We employed a multi-modal MRI approach to investigate and compare distinct hemodynamic-vascular processes and their impact on homotopic BOLD-FC in healthy controls and patients with unilateral asymptomatic internal carotid artery stenosis (ICAS). Asymptomatic ICAS is a cerebrovascular disorder, in which neuronal functioning is largely preserved but hemodynamic-vascular processes are impaired, mostly on the side of stenosis. Investigated indicators for local hemodynamic-vascular processes comprise capillary transit time heterogeneity (CTH) and cerebral blood volume (CBV) from dynamic susceptibility contrast (DSC) MRI, and cerebral blood flow (CBF) from pseudo-continuous arterial spin labeling (pCASL). Indicators for systemic processes are time-to-peak (TTP) from DSC MRI and BOLD lags from functional MRI. For each of these parameters, their influence on BOLD-FC was estimated by a comprehensive linear mixed model. Equally across groups, we found that individual mean BOLD-FC, local (CTH, CBV, and CBF) and systemic (TTP and BOLD lag) hemodynamic-vascular factors together explain 40.7% of BOLD-FC variance, with 20% of BOLD-FC variance explained by hemodynamic-vascular factors, with an about two-times larger contribution of systemic versus local factors. We conclude that regional differences in blood supply, i.e., systemic perfusion delays, exert a stronger influence on BOLD-FC than impairments in local neurovascular coupling.

Deep learning distinguishes connectomes from focal epilepsy patients and controls: feasibility and clinical implications

The application of deep learning models to evaluate connectome data is gaining interest in epilepsy research. Deep learning may be a useful initial tool to partition connectome data into network subsets for further analysis. Few prior works have used deep learning to examine structural connectomes from patients with focal epilepsy. We evaluated whether a deep learning model applied to whole-brain connectomes could classify 28 participants with focal epilepsy from 20 controls and identify nodal importance for each group. Participants with epilepsy were further grouped based on whether they had focal seizures that evolved into bilateral tonic-clonic seizures (17 with, 11 without). The trained neural network classified patients from controls with an accuracy of 72.92%, while the seizure subtype groups achieved a classification accuracy of 67.86%. In the patient subgroups, the nodes and edges deemed important for accurate classification were also clinically relevant, indicating the model's interpretability. The current work expands the evidence for the potential of deep learning to extract relevant markers from clinical datasets. Our findings offer a rationale for further research interrogating structural connectomes to obtain features that can be biomarkers and aid the diagnosis of seizure subtypes.

Not all discounts are created equal: Regional activity and brain networks in temporal and effort discounting

Reward outcomes associated with costs like time delay and effort investment are generally discounted in decision-making. Standard economic models predict rewards associated with different types of costs are devalued in a similar manner. However, our review of rodent lesion studies indicated partial dissociations between brain regions supporting temporal- and effort-based decision-making. Another debate is whether options involving low and high costs are processed in different brain substrates (dual-system) or in the same regions (single-system). This research addressed these issues using coordinate-based, connectivity-based, and activation network-based meta-analyses to identify overlapping and separable neural systems supporting temporal (39 studies) and effort (20 studies) discounting. Coordinate-based activation likelihood estimation and resting-state connectivity analyses showed immediate-small reward and delayed-large reward choices engaged distinct regions with unique connectivity profiles, but their activation network mapping was found to engage the default mode network. For effort discounting, salience and sensorimotor networks supported low-effort choices, while the frontoparietal network supported high-effort choices. There was little overlap between the temporal and effort networks. Our findings underscore the importance of differentiating different types of costs in decision-making and understanding discounting at both regional and network levels.

The locations of stroke lesions next to the posterior internal capsule may predict the recovery of the related proprioceptive deficits

Background

Somatosensory deficits after stroke correlate with functional disabilities and impact everyday-life. In particular, the interaction of proprioception and motor dysfunctions affects the recovery. While corticospinal tract (CST) damage is linked to poor motor outcome, much less is known on proprioceptive recovery. Identifying a predictor for such a recovery could help to gain insights in the complex functional recovery processes thereby reshaping rehabilitation strategies.

Methods

50 patients with subacute stroke were tested before and after neurological rehabilitation. Proprioceptive and motor impairments were quantified with three clinical assessments and four hand movement and proprioception measures using a robotic device. Somatosensory evoked potentials (SSEP) to median nerve stimulation and structural imaging data (MRI) were also collected. Voxel-based lesion-symptom mapping (VLSM) along with a region of interest (ROI) analysis were performed for the corticospinal tract (CST) and for cortical areas.

Results

Before rehabilitation, the VLSM revealed lesion correlates for all clinical and three robotic measures. The identified voxels were located in the white matter within or near the CST. These regions associated with proprioception were located posterior compared to those associated with motor performance. After rehabilitation the patients showed an improvement of all clinical and three robotic assessments. Improvement in the box and block test was associated with an area in anterior CST. Poor recovery of proprioception was correlated with a high lesion load in fibers towards primary sensorymotor cortex (S1 and M1 tract). Patients with loss of SSEP showed higher lesion loads in these tracts and somewhat poorer recovery of proprioception. The VSLM analysis for SSEP loss revealed a region within and dorsal of internal capsule next to the posterior part of CST, the posterior part of insula and the rolandic operculum.

Conclusion

Lesions dorsal to internal capsule next to the posterior CST were associated with proprioceptive deficits and may have predictive value. Higher lesion load was correlated with poorer restoration of proprioceptive function. Furthermore, patients with SSEP loss trended towards poor recovery of proprioception, the corresponding lesions were also located in the same location. These findings suggest that structural imaging of the internal capsule and CST could serve as a recovery predictor of proprioceptive function.

Lateralization of the cerebral network of inhibition in children before and after cognitive training

Inhibitory control (IC) plays a critical role in cognitive and socio-emotional development. IC relies on a lateralized cortico-subcortical brain network including the inferior frontal cortex, anterior parts of insula, anterior cingulate cortex, caudate nucleus and putamen. Brain asymmetries play a critical role for IC efficiency. In parallel to age-related changes, IC can be improved following training. The aim of this study was to (1) assess the lateralization of IC network in children (N = 60, 9-10 y.o.) and (2) examine possible changes in neural asymmetry of this network from anatomical (structural MRI) and functional (resting-state fMRI) levels after 5-week computerized IC vs. active control (AC) training. We observed that IC training, but not AC training, led to a leftward lateralization of the putamen anatomy, similarly to what is observed in adults, supporting that training could accelerate the maturation of this structure.

Neural basis of sound-symbolic pseudoword-shape correspondences

Non-arbitrary mapping between the sound of a word and its meaning, termed sound symbolism, is commonly studied through crossmodal correspondences between sounds and visual shapes, e.g., auditory pseudowords, like 'mohloh' and 'kehteh', are matched to rounded and pointed visual shapes, respectively. Here, we used functional magnetic resonance imaging (fMRI) during a crossmodal matching task to investigate the hypotheses that sound symbolism (1) involves language processing; (2) depends on multisensory integration; (3) reflects embodiment of speech in hand movements. These hypotheses lead to corresponding neuroanatomical predictions of crossmodal congruency effects in (1) the language network; (2) areas mediating multisensory processing, including visual and auditory cortex; (3) regions responsible for sensorimotor control of the hand and mouth. Right-handed participants (n = 22) encountered audiovisual stimuli comprising a simultaneously presented visual shape (rounded or pointed) and an auditory pseudoword ('mohloh' or 'kehteh') and indicated via a right-hand keypress whether the stimuli matched or not. Reaction times were faster for congruent than incongruent stimuli. Univariate analysis showed that activity was greater for the congruent compared to the incongruent condition in the left primary and association auditory cortex, and left anterior fusiform/parahippocampal gyri. Multivoxel pattern analysis revealed higher classification accuracy for the audiovisual stimuli when congruent than when incongruent, in the pars opercularis of the left inferior frontal (Broca's area), the left supramarginal, and the right mid-occipital gyri. These findings, considered in relation to the neuroanatomical predictions, support the first two hypotheses and suggest that sound symbolism involves both language processing and multisensory integration.

Task-dependent functional connectivity of pain is associated with the magnitude of placebo analgesia in pain-free individuals

BACKGROUND

Task-based functional connectivity (FC) of pain-related regions resulting from expectancy-based placebo induction has yet to be examined, limiting our understanding of regions and networks associated with placebo analgesia.

METHODS

Fifty-five healthy pain-free adults over 18 (M = 22.8 years, SD = 7.75) were recruited (65.5% women; 63.6% non-Hispanic/Latino/a/x; 58.2% White). Participants completed a baseline followed by a placebo session involving the topical application of an inactive cream in the context of an expectancy-enhancing instruction set. Noxious heat stimuli were applied to the thenar eminence of the right palm using an fMRI-safe thermode. Stimulus intensity was individually calibrated to produce pain ratings of approximately 40 on a 100-point visual analogue scale.

RESULTS

A total of 67.3% of the participants showed a reduction in pain intensity in the placebo condition with an average reduction in pain across the whole sample of 12.7%. Expected pain intensity was associated with reported pain intensity in the placebo session (b = 0.32, p = 0.004, R2  = 0.15). Voxel-wise analyses indicated seven clusters with significant activation during noxious heat stimulation at baseline (pFDR  < 0.05). Generalized psychophysiological interaction analysis suggested that placebo-related FC changes between middle frontal gyrus-superior parietal lobule during noxious stimulation were significantly associated with the magnitude of pain reduction (pFDR  < 0.05).

CONCLUSIONS

Results suggest that stronger expectancy-based placebo responses might be underpinned by greater FC among attentional and somatosensory regions.

SIGNIFICANCE

This article provides support and insight for task-dependent functional connectivity differences related to the magnitude of placebo analgesia. Our findings provide key support that the magnitude of expectation-based placebo response depends on the coupling of regions associated with somatosensory and attentional processing.

Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain

Over the past two decades, the study of resting-state functional magnetic resonance imaging has revealed that functional connectivity within and between networks is linked to cognitive states and pathologies. However, the white matter connections supporting this connectivity remain only partially described. We developed a method to jointly map the white and grey matter contributing to each resting-state network (RSN). Using the Human Connectome Project, we generated an atlas of 30 RSNs. The method also highlighted the overlap between networks, which revealed that most of the brain's white matter (89%) is shared between multiple RSNs, with 16% shared by at least 7 RSNs. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the communication within networks. We provide an atlas and an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage to these networks. In a first application of the software with clinical data, we were able to link stroke patients and impacted RSNs, showing that their symptoms aligned well with the estimated functions of the networks.

Neural Basis Of Sound-Symbolic Pseudoword-Shape Correspondences

Non-arbitrary mapping between the sound of a word and its meaning, termed sound symbolism, is commonly studied through crossmodal correspondences between sounds and visual shapes, e.g., auditory pseudowords, like 'mohloh' and 'kehteh', are matched to rounded and pointed visual shapes, respectively. Here, we used functional magnetic resonance imaging (fMRI) during a crossmodal matching task to investigate the hypotheses that sound symbolism (1) involves language processing; (2) depends on multisensory integration; (3) reflects embodiment of speech in hand movements. These hypotheses lead to corresponding neuroanatomical predictions of crossmodal congruency effects in (1) the language network; (2) areas mediating multisensory processing, including visual and auditory cortex; (3) regions responsible for sensorimotor control of the hand and mouth. Right-handed participants ( n = 22) encountered audiovisual stimuli comprising a simultaneously presented visual shape (rounded or pointed) and an auditory pseudoword ('mohloh' or 'kehteh') and indicated via a right-hand keypress whether the stimuli matched or not. Reaction times were faster for congruent than incongruent stimuli. Univariate analysis showed that activity was greater for the congruent compared to the incongruent condition in the left primary and association auditory cortex, and left anterior fusiform/parahippocampal gyri. Multivoxel pattern analysis revealed higher classification accuracy for the audiovisual stimuli when congruent than when incongruent, in the pars opercularis of the left inferior frontal (Broca's area), the left supramarginal, and the right mid-occipital gyri. These findings, considered in relation to the neuroanatomical predictions, support the first two hypotheses and suggest that sound symbolism involves both language processing and multisensory integration.

HIGHLIGHTS

fMRI investigation of sound-symbolic correspondences between auditory pseudowords and visual shapesFaster reaction times for congruent than incongruent audiovisual stimuliGreater activation in auditory and visual cortices for congruent stimuliHigher classification accuracy for congruent stimuli in language and visual areasSound symbolism involves language processing and multisensory integration.

Diabetes, brain health, and treatment gains in post-stroke aphasia

In post-stroke aphasia, language improvements following speech therapy are variable and can only be partially explained by the lesion. Brain tissue integrity beyond the lesion (brain health) may influence language recovery and can be impacted by cardiovascular risk factors, notably diabetes. We examined the impact of diabetes on structural network integrity and language recovery. Seventy-eight participants with chronic post-stroke aphasia underwent six weeks of semantic and phonological language therapy. To quantify structural network integrity, we evaluated the ratio of long-to-short-range white matter fibers within each participant's whole brain connectome, as long-range fibers are more susceptible to vascular injury and have been linked to high level cognitive processing. We found that diabetes moderated the relationship between structural network integrity and naming improvement at 1 month post treatment. For participants without diabetes (n = 59), there was a positive relationship between structural network integrity and naming improvement (t = 2.19, p = 0.032). Among individuals with diabetes (n = 19), there were fewer treatment gains and virtually no association between structural network integrity and naming improvement. Our results indicate that structural network integrity is associated with treatment gains in aphasia for those without diabetes. These results highlight the importance of post-stroke structural white matter architectural integrity in aphasia recovery.

Language network lateralization is reflected throughout the macroscale functional organization of cortex

Hemispheric specialization is a fundamental feature of human brain organization. However, it is not yet clear to what extent the lateralization of specific cognitive processes may be evident throughout the broad functional architecture of cortex. While the majority of people exhibit left-hemispheric language dominance, a substantial minority of the population shows reverse lateralization. Using twin and family data from the Human Connectome Project, we provide evidence that atypical language dominance is associated with global shifts in cortical organization. Individuals with atypical language organization exhibit corresponding hemispheric differences in the macroscale functional gradients that situate discrete large-scale networks along a continuous spectrum, extending from unimodal through association territories. Analyses reveal that both language lateralization and gradient asymmetries are, in part, driven by genetic factors. These findings pave the way for a deeper understanding of the origins and relationships linking population-level variability in hemispheric specialization and global properties of cortical organization.

The Effect of Physical Exercise on People with Psychosis: A Qualitative Critical Review of Neuroimaging Findings

Recently, genuine motor abnormalities have been recognized as prodromal and predictive signs of psychosis onset and progression. Therefore, physical exercise could represent a potentially relevant clinical tool in promoting the reshaping of neural connections in motor circuitry. The aim of this review is to provide an overview of the literature on neuroimaging findings as a result of physical treatment in psychosis cohorts. Twenty-one studies, all research articles, were included and discussed in this narrative review. Here, we first outlined how the psychotic brain is susceptible to structural plastic changes after aerobic physical training in pathognomic brain areas (i.e., temporal, hippocampal and parahippocampal regions). Secondly, we focused on functional changes, both region-specific and in terms of connections, to gain insights into the involvement of distant but inter-related neural regions in the plastic process occurring after treatment. Third, we attempted to bridge neural plastic changes occurring after physical interventions with clinical and cognitive outcomes of psychotic patients in order to assess the relevance of such neural reshaping in the psychiatric rehabilitation field. In conclusion, we suggest that the current state of the art is presenting physical intervention as effective in promoting neural changes for patients with psychosis; it is not only useful at the onset of the pathology but also in improving the course of the illness and its functional outcome. However, more evidence is needed to improve our knowledge of the efficacy of physical exercise in plastically reorganizing the psychotic brain in the long term, especially within regions lacking specific investigations, such as motor circuitry.

Optic radiations representing different eccentricities age differently

The neural pathways that carry information from the foveal, macular, and peripheral visual fields have distinct biological properties. The optic radiations (OR) carry foveal and peripheral information from the thalamus to the primary visual cortex (V1) through adjacent but separate pathways in the white matter. Here, we perform white matter tractometry using pyAFQ on a large sample of diffusion MRI (dMRI) data from subjects with healthy vision in the U.K. Biobank dataset (UKBB; N = 5382; age 45-81). We use pyAFQ to characterize white matter tissue properties in parts of the OR that transmit information about the foveal, macular, and peripheral visual fields, and to characterize the changes in these tissue properties with age. We find that (1) independent of age there is higher fractional anisotropy, lower mean diffusivity, and higher mean kurtosis in the foveal and macular OR than in peripheral OR, consistent with denser, more organized nerve fiber populations in foveal/parafoveal pathways, and (2) age is associated with increased diffusivity and decreased anisotropy and kurtosis, consistent with decreased density and tissue organization with aging. However, anisotropy in foveal OR decreases faster with age than in peripheral OR, while diffusivity increases faster in peripheral OR, suggesting foveal/peri-foveal OR and peripheral OR differ in how they age.

Homotopic local-global parcellation of the human cerebral cortex from resting-state functional connectivity

Resting-state fMRI is commonly used to derive brain parcellations, which are widely used for dimensionality reduction and interpreting human neuroscience studies. We previously developed a model that integrates local and global approaches for estimating areal-level cortical parcellations. The resulting local-global parcellations are often referred to as the Schaefer parcellations. However, the lack of homotopic correspondence between left and right Schaefer parcels has limited their use for brain lateralization studies. Here, we extend our previous model to derive homotopic areal-level parcellations. Using resting-fMRI and task-fMRI across diverse scanners, acquisition protocols, preprocessing and demographics, we show that the resulting homotopic parcellations are as homogeneous as the Schaefer parcellations, while being more homogeneous than five publicly available parcellations. Furthermore, weaker correlations between homotopic parcels are associated with greater lateralization in resting network organization, as well as lateralization in language and motor task activation. Finally, the homotopic parcellations agree with the boundaries of a number of cortical areas estimated from histology and visuotopic fMRI, while capturing sub-areal (e.g., somatotopic and visuotopic) features. Overall, these results suggest that the homotopic local-global parcellations represent neurobiologically meaningful subdivisions of the human cerebral cortex and will be a useful resource for future studies. Multi-resolution parcellations estimated from 1479 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Yan2023_homotopic).

Dissociative effects of age on neural differentiation at the category and item level

Increasing age is associated with age-related neural dedifferentiation, a reduction in the selectivity of neural representations which has been proposed to contribute to cognitive decline in older age. Recent findings indicate that when operationalized in terms of selectivity for different perceptual categories, age-related neural dedifferentiation, and the apparent age-invariant association of neural selectivity with cognitive performance, are largely restricted to the cortical regions typically recruited during scene processing. It is currently unknown whether this category-level dissociation extends to metrics of neural selectivity defined at the level of individual stimulus items. Here, we examined neural selectivity at the category and item levels using multivoxel pattern similarity analysis (PSA) of fMRI data. Healthy young and older male and female adults viewed images of objects and scenes. Some items were presented singly, while others were either repeated or followed by a 'similar lure'. Consistent with recent findings, category-level PSA revealed robustly lower differentiation in older than younger adults in scene-selective, but not object-selective, cortical regions. By contrast, at the item level, robust age-related declines in neural differentiation were evident for both stimulus categories. Moreover, we identified an age-invariant association between category-level scene-selectivity in the parahippocampal place area and subsequent memory performance, but no such association was evident for item-level metrics. Lastly, category and item-level neural metrics were uncorrelated. Thus, the present findings suggest that age-related category- and item-level dedifferentiation depend on distinct neural mechanisms.

Subjective signal strength distinguishes reality from imagination

Humans are voracious imaginers, with internal simulations supporting memory, planning and decision-making. Because the neural mechanisms supporting imagery overlap with those supporting perception, a foundational question is how reality and imagination are kept apart. One possibility is that the intention to imagine is used to identify and discount self-generated signals during imagery. Alternatively, because internally generated signals are generally weaker, sensory strength is used to index reality. Traditional psychology experiments struggle to investigate this issue as subjects can rapidly learn that real stimuli are in play. Here, we combined one-trial-per-participant psychophysics with computational modelling and neuroimaging to show that imagined and perceived signals are in fact intermixed, with judgments of reality being determined by whether this intermixed signal is strong enough to cross a reality threshold. A consequence of this account is that when virtual or imagined signals are strong enough, they become subjectively indistinguishable from reality.

An fMRI-study of leading and following using rhythmic tapping

Leading and following is about synchronizing and joining actions in accordance with the differences that the leader and follower roles provide. The neural reactivity representing these roles was measured in an explorative fMRI-study, where two persons lead and followed each other in finger tapping using simple, individual, pre-learnt rhythms. All participants acted both as leader and follower. Neural reactivity for both lead and follow related to social awareness and adaptation distributed over the lateral STG, STS and TPJ. Reactivity for follow contrasted with lead mostly reflected sensorimotor and rhythmic processing in cerebellum IV, V, somatosensory cortex and SMA. During leading, as opposed to following, neural reactivity was observed in the insula and bilaterally in the superior temporal gyrus, pointing toward empathy, sharing of feelings, temporal coding and social engagement. Areas for continuous adaptation, in the posterior cerebellum and Rolandic operculum, were activated during both leading and following. This study indicated mutual adaptation of leader and follower during tapping and that the roles gave rise to largely similar neuronal reactivity. The differences between the roles indicated that leading was more socially focused and following had more motoric- and temporally related neural reactivity.

Progressive Voxel-Wise Homotopic Connectivity from childhood to adulthood: Age-related functional asymmetry in resting-state functional magnetic resonance imaging

Homotopic connectivity during resting state has been proposed as a risk marker for neurologic and psychiatric conditions, but a precise characterization of its trajectory through development is currently lacking. Voxel-Mirrored Homotopic Connectivity (VMHC) was evaluated in a sample of 85 neurotypical individuals aged 7-18 years. VMHC associations with age, handedness, sex, and motion were explored at the voxel-wise level. VMHC correlates were also explored within 14 functional networks. Primary and secondary outcomes were repeated in a sample of 107 adults aged 21-50 years. In adults, VMHC was negatively correlated with age only in the posterior insula (false discovery rate p < .05, >30-voxel clusters), while a distributed effect among the medial axis was observed in minors. Four out of 14 considered networks showed significant negative correlations between VMHC and age in minors (basal ganglia r = -.280, p = .010; anterior salience r = -.245, p = .024; language r = -.222, p = .041; primary visual r = -.257, p = .017), but not adults. In minors, a positive effect of motion on VMHC was observed only in the putamen. Sex did not significantly influence age effects on VMHC. The current study showed a specific decrease in VMHC for minors as a function of age, but not adults, supporting the notion that interhemispheric interactions can shape late neurodevelopment.

Brain and behavioral contributions to individual choices in response to affective-cognitive persuasion

Affective and cognitive information conveyed by persuasive stimuli is evaluated and integrated by individuals according to their behavioral predispositions. However, the neurocognitive structure that supports persuasion based on either affective or cognitive content is poorly understood. Here, we examine the neural and behavioral processes supporting choices based on affective and cognitive persuasion by integrating 4 information processing features: intrinsic brain connectivity, stimulus-evoked brain activity, intrinsic affective-cognitive orientation, and explicit target evaluations. We found that the intrinsic cross-network connections of a multimodal fronto-parietal network are associated with individual affective-cognitive orientation. Moreover, using a cross-validated classifier, we found that individuals' intrinsic brain-behavioral dimensions, such as affective-cognitive orientation and intrinsic brain connectivity, can predict individual choices between affective and cognitive targets. Our findings show that affective- and cognitive-based choices rely on multiple sources, including behavioral orientation, stimulus evaluation, and intrinsic functional brain architecture.

Effects of acute ischemic stroke on binaural perception

Stroke-induced lesions at different locations in the brain can affect various aspects of binaural hearing, including spatial perception. Previous studies found impairments in binaural hearing, especially in patients with temporal lobe tumors or lesions, but also resulting from lesions all along the auditory pathway from brainstem nuclei up to the auditory cortex. Currently, structural magnetic resonance imaging (MRI) is used in the clinical treatment routine of stroke patients. In combination with structural imaging, an analysis of binaural hearing enables a better understanding of hearing-related signaling pathways and of clinical disorders of binaural processing after a stroke. However, little data are currently available on binaural hearing in stroke patients, particularly for the acute phase of stroke. Here, we sought to address this gap in an exploratory study of patients in the acute phase of ischemic stroke. We conducted psychoacoustic measurements using two tasks of binaural hearing: binaural tone-in-noise detection, and lateralization of stimuli with interaural time- or level differences. The location of the stroke lesion was established by previously acquired MRI data. An additional general assessment included three-frequency audiometry, cognitive assessments, and depression screening. Fifty-five patients participated in the experiments, on average 5 days after their stroke onset. Patients whose lesions were in different locations were tested, including lesions in brainstem areas, basal ganglia, thalamus, temporal lobe, and other cortical and subcortical areas. Lateralization impairments were found in most patients with lesions within the auditory pathway. Lesioned areas at brainstem levels led to distortions of lateralization in both hemifields, thalamus lesions were correlated with a shift of the whole auditory space, whereas some cortical lesions predominantly affected the lateralization of stimuli contralateral to the lesion and resulted in more variable responses. Lateralization performance was also found to be affected by lesions of the right, but not the left, basal ganglia, as well as by lesions in non-auditory cortical areas. In general, altered lateralization was common in the stroke group. In contrast, deficits in tone-in-noise detection were relatively scarce in our sample of lesion patients, although a significant number of patients with multiple lesion sites were not able to complete the task.

Cross-cohort replicability and generalizability of connectivity-based psychometric prediction patterns

An increasing number of studies have investigated the relationships between inter-individual variability in brain regions' connectivity and behavioral phenotypes, making use of large population neuroimaging datasets. However, the replicability of brain-behavior associations identified by these approaches remains an open question. In this study, we examined the cross-dataset replicability of brain-behavior association patterns for fluid cognition and openness predictions using a previously developed region-wise approach, as well as using a standard whole-brain approach. Overall, we found moderate similarity in patterns for fluid cognition predictions across cohorts, especially in the Human Connectome Project Young Adult, Human Connectome Project Aging, and Enhanced Nathan Kline Institute Rockland Sample cohorts, but low similarity in patterns for openness predictions. In addition, we assessed the generalizability of prediction models in cross-dataset predictions, by training the model in one dataset and testing in another. Making use of the region-wise prediction approach, we showed that first, a moderate extent of generalizability could be achieved with fluid cognition prediction, and that, second, a set of common brain regions related to fluid cognition across cohorts could be identified. Nevertheless, the moderate replicability and generalizability could only be achieved in specific contexts. Thus, we argue that replicability and generalizability in connectivity-based prediction remain limited and deserve greater attention in future studies.

Inter-hemispheric synchronicity and symmetry: The functional connectivity consequences of stroke and neurodegenerative disease

Stroke and neurodegenerative diseases differ along several dimensions, including their temporal trajectories -abrupt onset versus slow disease progression. Despite these differences, they can give rise to very similar cognitive impairments, such as specific forms of aphasia. What has been scarcely investigated, however, is the extent to which the underlying functional neuroplastic consequences are similar or different for these diseases. Here, for the first time, we directly compare changes in the brain's functional network connectivity, measured with resting-state fMRI, in stroke and progressive neurological disease. Specifically, we examined two groups of individuals with chronic post-stroke aphasia or non-fluent primary progressive aphasia, matched for their behavioral profiles and distribution of left-hemisphere damage. Using previous proposals regarding the neural functional connectivity (FC) phenotype of stroke as a starting point, we compared the two diseases in terms of homotopic FC, intra-hemispheric FC changes and also the symmetry of the FC patterns between the two hemispheres. We found, first, that progressive disease showed significantly higher levels of homotopic connectivity than neurotypical controls and, further, that stroke showed the reverse pattern. For both groups these effects were found to be behaviorally relevant. In addition, within the directly impacted left hemisphere, FC changes for the two diseases were significantly correlated. In contrast, in the right hemisphere, the FC changes differed markedly between the two groups, with the progressive disease group exhibiting rather symmetrical FC changes across the hemispheres whereas the post-stroke group showed asymmetrical FC changes across the hemispheres. These findings constitute novel evidence that the functional connectivity consequences of stroke and neurodegenerative disease can be very different despite similar behavioral outcomes and damage foci. Specifically, stroke may lead to greater independence of hemispheric responses, while neurodegenerative disease may produce more symmetrical changes across the hemispheres and more synchronized activity between the two hemispheres.

Activation network mapping for integration of heterogeneous fMRI findings

Functional neuroimaging techniques have been widely used to probe the neural substrates of facial emotion processing in healthy people. However, findings are largely inconsistent across studies. Here, we introduce a new technique termed activation network mapping to examine whether heterogeneous functional magnetic resonance imaging findings localize to a common network for emotion processing. First, using the existing method of activation likelihood estimation meta-analysis, we showed that individual-brain-based reproducibility was low across studies. Second, using activation network mapping, we found that network-based reproducibility across these same studies was higher. Validation analysis indicated that the activation network mapping-localized network aligned with stimulation sites, structural abnormalities and brain lesions that disrupt facial emotion processing. Finally, we verified the generality of the activation network mapping technique by applying it to another cognitive process, that is, rumination. Activation network mapping may potentially be broadly applicable to localize brain networks of cognitive functions.

HomotopicLI: Rationale, characteristics, and implications of a new threshold-free lateralization index of functional magnetic resonance imaging

The reliable preoperative estimation of brain hemispheric asymmetry may be achieved through multiple lateralization indices using functional magnetic resonance imaging. Adding to our previously developed AveLI, we devised a novel threshold-free lateralization index, HomotopicLI, which computes a basic formula, (Left - Right) / (Left + Right), using voxel values of pairs located symmetrically in relation to the midsagittal line as the terms Left and Right, and averages them within the regions-of-interest. The study aimed to evaluate HomotopicLI before clinical applications. Data were collected from 56 healthy participants who performed four language tasks. We compared seven index types, including HomotopicLI, AveLI, and BaseLI; BaseLI was calculated using the sums of voxel values as the terms. Contrary to our expectations, HomotopicLI performed similarly to AveLI but better than BaseLI in detecting right dominance. A detailed analysis of unilaterally activated voxels of the homotopic pairs revealed that unilateral activation occurred more frequently on the right than on the left when HomotopicLI indicated right dominance. The voxel values during right unilateral activation were smaller than those in the left, causing right dominances in the homotopic pairs by HomotopicLI. These unique features provide an advantage in detecting residual, compensative functions spreading weakly in the non-dominant hemisphere.

Neural correlates of perceiving and interpreting engraved prehistoric patterns as human production: Effect of archaeological expertise

It has been suggested that engraved abstract patterns dating from the Middle and Lower Palaeolithic served as means of representation and communication. Identifying the brain regions involved in visual processing of these engravings can provide insights into their function. In this study, brain activity was measured during perception of the earliest known Palaeolithic engraved patterns and compared to natural patterns mimicking human-made engravings. Participants were asked to categorise marks as being intentionally made by humans or due to natural processes (e.g. erosion, root etching). To simulate the putative familiarity of our ancestors with the marks, the responses of expert archaeologists and control participants were compared, allowing characterisation of the effect of previous knowledge on both behaviour and brain activity in perception of the marks. Besides a set of regions common to both groups and involved in visual analysis and decision-making, the experts exhibited greater activity in the inferior part of the lateral occipital cortex, ventral occipitotemporal cortex, and medial thalamic regions. These results are consistent with those reported in visual expertise studies, and confirm the importance of the integrative visual areas in the perception of the earliest abstract engravings. The attribution of a natural rather than human origin to the marks elicited greater activity in the salience network in both groups, reflecting the uncertainty and ambiguity in the perception of, and decision-making for, natural patterns. The activation of the salience network might also be related to the process at work in the attribution of an intention to the marks. The primary visual area was not specifically involved in the visual processing of engravings, which argued against its central role in the emergence of engraving production.

Laterality Hotspots in the Striatum

Striatal loci are connected to both the ipsilateral and contralateral frontal cortex. Normative quantitation of the dissimilarity between striatal loci's hemispheric connection profiles and its spatial variance across the striatum, and assessment of how interindividual differences relate to function, stands to further the understanding of the role of corticostriatal circuits in lateralized functions and the role of abnormal corticostriatal laterality in neurodevelopmental and other neuropsychiatric disorders. A resting-state functional connectivity fingerprinting approach (n = 261) identified "laterality hotspots"-loci whose profiles of connectivity with ipsilateral and contralateral frontal cortex were disproportionately dissimilar-in the right rostral ventral putamen, left rostral central caudate, and bilateral caudal ventral caudate. Findings were replicated in an independent sample and were robust to both preprocessing choices and the choice of cortical atlas used for parcellation definitions. Across subjects, greater rightward connectional laterality at the right ventral putamen hotspot and greater leftward connectional laterality at the left rostral caudate hotspot were associated with higher performance on tasks engaging lateralized functions (i.e., response inhibition and language, respectively). In sum, we find robust and reproducible evidence for striatal loci with disproportionately lateralized connectivity profiles where interindividual differences in laterality magnitude are associated with behavioral capacities on lateralized functions.

Alteration in Asymmetry of White Matter Network of Parkinson’s Disease

Parkinson’s disease (PD) is manifest clinically by an asymmetrical presentation of motor dysfunction. A large number of previous neuroimaging research studies have stated the alteration in the hemispheric asymmetry of morphological features in PD disease. Diffusion Magnetic Resonance Imaging (MRI), which is noninvasive, has been widely used to quantify the white matter network in the human brain of both healthy subjects and patients. Besides, graph theory analysis is widely used to quantify the topological architecture of the human brain network. Lately, researchers have discovered that the topological architecture of the white matter network significantly differs in PD compared with healthy controls (HC). Nevertheless, the asymmetry of the topological architecture of the white matter network for PD patients remains unclear. To clarify this, the diffusion-weighted images and tractography technique were used to reconstruct the hemispherical white matter networks for 22 bilateral PD patients and 18 HC subjects. Network-based statistical analysis and graph theory analysis approaches were employed to estimate the asymmetry at both the connectivity level and the hemispheric topological level for PD patients. We found that the PD group showed atypically right-higher-than-left asymmetry in hemispheric brain global and local efficiencies. The detected right-higher-than-left asymmetry was driven by the atypically topological changes in the left hemispheric brain in the PD group. Findings from these studies might provide new insights into the asymmetric features of hemispheric disconnectivity and emphasize that the topological asymmetry of the hemispheric brain could be used as a biomarker to identify PD individuals.

The Wernicke conundrum revisited: evidence from connectome-based lesion-symptom mapping

Wernicke's area has been assumed since the 1800s to be the primary region supporting word and sentence comprehension. However, in 2015 and 2019, Mesulam and colleagues raised what they termed the 'Wernicke conundrum', noting widespread variability in the anatomical definition of this area and presenting data from primary progressive aphasia that challenged this classical assumption. To resolve the conundrum, they posited a 'double disconnection' hypothesis: that word and sentence comprehension deficits in stroke-based aphasia result from disconnection of anterior temporal and inferior frontal regions from other parts of the brain due to white matter damage, rather than dysfunction of Wernicke's area itself. To test this hypothesis, we performed lesion-deficit correlations, including connectome-based lesion-symptom mapping, in four large, partially overlapping groups of English-speaking chronic left hemisphere stroke survivors. After removing variance due to object recognition and associative semantic processing, the same middle and posterior temporal lobe regions were implicated in both word comprehension deficits and complex noncanonical sentence comprehension deficits. Connectome lesion-symptom mapping revealed similar temporal-occipital white matter disconnections for impaired word and noncanonical sentence comprehension, including the temporal pole. We found an additional significant temporal-parietal disconnection for noncanonical sentence comprehension deficits, which may indicate a role for phonological working memory in processing complex syntax, but no significant frontal disconnections. Moreover, damage to these middle-posterior temporal lobe regions was associated with both word and noncanonical sentence comprehension deficits even when accounting for variance due to the strongest anterior temporal and inferior frontal white matter disconnections, respectively. Our results largely agree with the classical notion that Wernicke's area, defined here as middle superior temporal gyrus and middle-posterior superior temporal sulcus, supports both word and sentence comprehension, suggest a supporting role for temporal pole in both word and sentence comprehension, and speak against the hypothesis that comprehension deficits in Wernicke's aphasia result from double disconnection.

Combined Multi-Atlas and Multi-Layer Perception for Alzheimer's Disease Classification

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. To distinguish the stage of the disease, AD classification technology challenge has been proposed in Pattern Recognition and Computer Vision 2021 (PRCV 2021) which provides the gray volume and average cortical thickness data extracted in multiple atlases from magnetic resonance imaging (MRI). Traditional methods either train with convolutional neural network (CNN) by MRI data to adapt the spatial features of images or train with recurrent neural network (RNN) by temporal features to predict the next stage. However, the morphological features from the challenge have been extracted into discrete values. We present a multi-atlases multi-layer perceptron (MAMLP) approach to deal with the relationship between morphological features and the stage of the disease. The model consists of multiple multi-layer perceptron (MLP) modules, and morphological features extracted from different atlases will be classified by different MLP modules. The final vote of all classification results obtains the predicted disease stage. Firstly, to preserve the diversity of brain features, the most representative atlases are chosen from groups of similar atlases, and one atlas is selected in each group. Secondly, each atlas is fed into one MLP to fetch the score of the classification. Thirdly, to obtain more stable results, scores from different atlases are combined to vote the result of the classification. Based on this approach, we rank 10th among 373 teams in the challenge. The results of the experiment indicate as follows: (1) Group selection of atlas reduces the number of features required without reducing the accuracy of the model; (2) The MLP architecture achieves better performance than CNN and RNN networks in morphological features; and (3) Compared with other networks, the combination of multiple MLP networks has faster convergence of about 40% and makes the classification more stable.

Whole-brain metabolic pattern analysis in patients with anti-LGI1 encephalitis

BACKGROUND AND PURPOSE

Faciobrachial dystonic seizures (FBDS) and hyponatraemia are the distinct clinical features of autoimmune encephalitis (AE) caused by antibodies against leucine-rich glioma-inactivated 1 (LGI1). The pathophysiological pattern and neural mechanisms underlying these symptoms remain largely unexplored.

METHODS

We included 30 patients with anti-LGI1 AE and 30 controls from a retrospective observational cohort. Whole-brain metabolic pattern analysis was performed to assess the pathological network of anti-LGI1 AE, as well as the symptomatic networks of FBDS. Logistic regression was applied to explore independent predictors of FBDS. Finally, we applied multiple regression model to investigate the hyponatraemia-associated brain network and its effect on serum sodium levels.

RESULTS

The pathological network of anti-LGI1 AE involved a hypermetabolism in cerebellum, subcortical structures, and Rolandic area, as well as a hypometabolism in the medial prefrontal cortex. The symptomatic network of FBDS shown a hypometabolism in cerebellum and Rolandic area (P_FDR < 0.05). Hypometabolism in the cerebellum was an independent predictor of FBDS (P < 0.001). Hyponatraemia-associated network highlighted a negative effect on caudate nucleus, frontal and temporal white matter. Serum sodium level had the negative trend with metabolism of hypothalamus (Pearson's R = -0.180, P = 0.342) but the mediation was not detected (path c' = -7.238, 95% CI = -30.947 to 16.472).

CONCLUSIONS

Our results provide insights into the whole-brain metabolic patterns of patients with anti-LGI1 AE, including the symptomatic network FBDS and the hyponatraemia-associated brain network, which is conducive to understanding the neural mechanisms and evaluating disease progress of anti-LGI1 AE.