Psilocybin desynchronizes the human brain.

A single dose of psilocybin, a psychedelic that acutely causes distortions of space-time perception and ego dissolution, produces rapid and persistent therapeutic effects in human clinical trials1-4. In animal models, psilocybin induces neuroplasticity in cortex and hippocampus5-8. It remains unclear how human brain network changes relate to subjective and lasting effects of psychedelics. Here we tracked individual-specific brain changes with longitudinal precision functional mapping (roughly 18 magnetic resonance imaging visits per participant). Healthy adults were tracked before, during and for 3 weeks after high-dose psilocybin (25 mg) and methylphenidate (40 mg), and brought back for an additional psilocybin dose 6-12 months later. Psilocybin massively disrupted functional connectivity (FC) in cortex and subcortex, acutely causing more than threefold greater change than methylphenidate. These FC changes were driven by brain desynchronization across spatial scales (areal, global), which dissolved network distinctions by reducing correlations within and anticorrelations between networks. Psilocybin-driven FC changes were strongest in the default mode network, which is connected to the anterior hippocampus and is thought to create our sense of space, time and self. Individual differences in FC changes were strongly linked to the subjective psychedelic experience. Performing a perceptual task reduced psilocybin-driven FC changes. Psilocybin caused persistent decrease in FC between the anterior hippocampus and default mode network, lasting for weeks. Persistent reduction of hippocampal-default mode network connectivity may represent a neuroanatomical and mechanistic correlate of the proplasticity and therapeutic effects of psychedelics.

Brain aerobic glycolysis and resilience in Alzheimer disease.

The distribution of brain aerobic glycolysis (AG) in normal young adults correlates spatially with amyloid-beta (Aß) deposition in individuals with symptomatic and preclinical Alzheimer disease (AD). Brain AG decreases with age, but the functional significance of this decrease with regard to the development of AD symptomatology is poorly understood. Using PET measurements of regional blood flow, oxygen consumption, and glucose utilization-from which we derive AG-we find that cognitive impairment is strongly associated with loss of the typical youthful pattern of AG. In contrast, amyloid positivity without cognitive impairment was associated with preservation of youthful brain AG, which was even higher than that seen in cognitively unimpaired, amyloid negative adults. Similar findings were not seen for blood flow nor oxygen consumption. Finally, in cognitively unimpaired adults, white matter hyperintensity burden was found to be specifically associated with decreased youthful brain AG. Our results suggest that AG may have a role in the resilience and/or response to early stages of amyloid pathology and that age-related white matter disease may impair this process.

Comparison of Resting State Functional Connectivity in Persons With and Without HIV: A Cross-sectional Study.

BACKGROUND: This study examined the effects of human immunodeficiency virus (HIV) on resting state functional connectivity (RSFC) in a large cohort of people with HIV (PWH) and healthy controls without HIV (PWoH). Within PWH analyses focused on the effects of viral suppression and cognitive impairment on RSFC. METHODS: A total of 316 PWH on stable combination antiretroviral therapy and 209 demographically matched PWoH were scanned at a single institution. Effects of the virus were examined by grouping PWH by detectable (viral load > 20 copies/mL; VLD) and undetectable (VLU) viral loads and as being cognitively impaired (CI) (Global Deficit Score ≥ 0.5) or cognitively normal (CN). Regression analysis, object oriented data analysis, and spring embedded graph models were applied to RSFC measures from 298 established brain regions of interest comprising 13 brain networks to examine group differences. RESULTS: No significant RSFC differences were observed between PWH and PWoH. Within PWH, there were no significant differences in RSFC between VLD and VLU subgroups and CI and CN subgroups. CONCLUSIONS: There were no significant effects of HIV on RSFC in our relatively large cohort of PWH and PWoH. Future studies could increase the sample size and combine with other imaging modalities.

Accelerated Brain Aging and Cerebral Blood Flow Reduction in Persons With Human Immunodeficiency Virus.

BACKGROUND: Persons with human immunodeficiency virus (PWH) are characterized by altered brain structure and function. As they attain normal lifespans, it has become crucial to understand potential interactions between human immunodeficiency virus (HIV) and aging. However, it remains unclear how brain aging varies with viral load (VL). METHODS: In this study, we compare magnetic resonance imaging (MRI) biomarkers among PWH with undetectable VL (UVL; ≤50 genomic copies/mL; n = 230), PWH with detectable VL (DVL; >50 copies/mL; n = 93), and HIV-uninfected (HIV-) controls (n = 206). To quantify gray matter cerebral blood flow (CBF), we utilized arterial spin labeling. To measure structural aging, we used a publicly available deep learning algorithm to estimate brain age from T1-weighted MRI. Cognitive performance was measured using a neuropsychological battery covering 5 domains. RESULTS: Associations between age and CBF varied with VL. Older PWH with DVL had reduced CBF vs PWH with UVL (P = .02). Structurally predicted brain aging was accelerated in PWH vs HIV- controls regardless of VL (P < .001). Overall, PWH had impaired learning, executive function, psychomotor speed, and language compared to HIV- controls. Structural brain aging was associated with reduced psychomotor speed (P < .001). CONCLUSIONS: Brain aging in HIV is multifaceted. CBF depends on age and current VL and is improved by medication adherence. By contrast, structural aging is an indicator of cognitive function and reflects serostatus rather than current VL.

Damage to the shortest structural paths between brain regions is associated with disruptions of resting-state functional connectivity after stroke.

Focal brain lesions disrupt resting-state functional connectivity, but the underlying structural mechanisms are unclear. Here, we examined the direct and indirect effects of structural disconnections on resting-state functional connectivity in a large sample of sub-acute stroke patients with heterogeneous brain lesions. We estimated the impact of each patient's lesion on the structural connectome by embedding the lesion in a diffusion MRI streamline tractography atlas constructed using data from healthy individuals. We defined direct disconnections as the loss of direct structural connections between two regions, and indirect disconnections as increases in the shortest structural path length between two regions that lack direct structural connections. We then tested the hypothesis that functional connectivity disruptions would be more severe for disconnected regions than for regions with spared connections. On average, nearly 20% of all region pairs were estimated to be either directly or indirectly disconnected by the lesions in our sample, and extensive disconnections were associated primarily with damage to deep white matter locations. Importantly, both directly and indirectly disconnected region pairs showed more severe functional connectivity disruptions than region pairs with spared direct and indirect connections, respectively, although functional connectivity disruptions tended to be most severe between region pairs that sustained direct structural disconnections. Together, these results emphasize the widespread impacts of focal brain lesions on the structural connectome and show that these impacts are reflected by disruptions of the functional connectome. Further, they indicate that in addition to direct structural disconnections, lesion-induced increases in the structural shortest path lengths between indirectly structurally connected region pairs provide information about the remote functional disruptions caused by focal brain lesions.

Spontaneously emerging patterns in human visual cortex and their functional connectivity are linked to the patterns evoked by visual stimuli.

The function of spontaneous brain activity is an important issue in neuroscience. Here we test the hypothesis that patterns of spontaneous activity code representational patterns evoked by stimuli. We compared in human visual cortex multivertex patterns of spontaneous activity to patterns evoked by ecological visual stimuli (faces, bodies, scenes) and low-level visual features (e.g., phase-scrambled faces). Specifically, we identified regions that preferred particular stimulus categories during localizer scans (e.g., extrastriate body area for bodies), measured multivertex patterns for each category during event-related task scans, and then correlated over vertices these stimulus-evoked patterns to the pattern measured on each frame of resting-state scans. The mean correlation coefficient was essentially zero for all regions/stimulus categories, indicating that resting multivertex patterns were not biased toward particular stimulus-evoked patterns. However, the spread of correlation coefficients between stimulus-evoked and resting patterns, positive and negative, was significantly greater for the preferred stimulus category of an ROI. The relationship between spontaneous and stimulus-evoked multivertex patterns also governed the temporal correlation or functional connectivity of patterns of spontaneous activity between individual regions (pattern-based functional connectivity). Resting multivertex patterns related to an object category fluctuated preferentially between ROIs preferring the same category, and fluctuations of the pattern for a category (e.g., body) within its preferred ROIs were largely uncorrelated with fluctuations of the pattern for a disparate category (e.g., scene) within its preferred ROIs. These results support the proposal that spontaneous multivertex activity patterns are linked to stimulus-evoked patterns, consistent with a representational function for spontaneous activity.NEW & NOTEWORTHY Spontaneous brain activity was once thought to reflect only noise, but evidence of strong spatiotemporal regularities has motivated a search for functional explanations. Here we show that the spatial pattern of spontaneous activity in human high-level and early visual cortex is related to the spatial patterns evoked by stimuli. Moreover, these patterns partly govern spontaneous spatiotemporal interactions between regions, so-called functional connectivity. These results support the hypothesis that spontaneous activity serves a representational function.

Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke.

Deficits following stroke are classically attributed to focal damage, but recent evidence suggests a key role of distributed brain network disruption. We measured resting functional connectivity (FC), lesion topography, and behavior in multiple domains (attention, visual memory, verbal memory, language, motor, and visual) in a cohort of 132 stroke patients, and used machine-learning models to predict neurological impairment in individual subjects. We found that visual memory and verbal memory were better predicted by FC, whereas visual and motor impairments were better predicted by lesion topography. Attention and language deficits were well predicted by both. Next, we identified a general pattern of physiological network dysfunction consisting of decrease of interhemispheric integration and intrahemispheric segregation, which strongly related to behavioral impairment in multiple domains. Network-specific patterns of dysfunction predicted specific behavioral deficits, and loss of interhemispheric communication across a set of regions was associated with impairment across multiple behavioral domains. These results link key organizational features of brain networks to brain-behavior relationships in stroke.

Distinct phase-amplitude couplings distinguish cognitive processes in human attention.

Spatial attention is the cognitive function that coordinates the selection of visual stimuli with appropriate behavioral responses. Recent studies have reported that phase-amplitude coupling (PAC) of low and high frequencies covaries with spatial attention, but differ on the direction of covariation and the frequency ranges involved. We hypothesized that distinct phase-amplitude frequency pairs have differentiable contributions during tasks that manipulate spatial attention. We investigated this hypothesis with electrocorticography (ECoG) recordings from participants who engaged in a cued spatial attention task. To understand the contribution of PAC to spatial attention we classified cortical sites by their relationship to spatial variables or behavioral performance. Local neural activity in spatial sites was sensitive to spatial variables in the task, while local neural activity in behavioral sites correlated with reaction time. We found two PAC frequency clusters that covaried with different aspects of the task. During a period of cued attention, delta-phase/high-gamma (DH) PAC was sensitive to cue direction in spatial sites. In contrast, theta-alpha-phase/beta-low-gamma-amplitude (TABL) PAC robustly correlated with future reaction times in behavioral sites. Finally, we investigated the origins of TABL PAC and found it corresponded to behaviorally relevant, sharp waveforms, which were also coupled to a low frequency rhythm. We conclude that TABL and DH PAC correspond to distinct mechanisms during spatial attention tasks and that sharp waveforms are elements of a coupled dynamical process.

Normalization of network connectivity in hemispatial neglect recovery.

OBJECTIVE: We recently reported that spatial and nonspatial attention deficits in stroke patients with hemispatial neglect are correlated at 2 weeks postonset with widespread alterations of interhemispheric and intrahemispheric functional connectivity (FC) measured with resting-state functional magnetic resonance imaging across multiple brain networks. The mechanisms underlying neglect recovery are largely unknown. In this study, we test the hypothesis that recovery of hemispatial neglect correlates with a return of network connectivity toward a normal pattern, herein defined as "network normalization." METHODS: We measured attention deficits with a neuropsychological battery and FC in a large cohort of stroke patients at, on average, 2 weeks (n = 99), 3 months (n = 77), and 12 months (n = 64) postonset. The relationship between behavioral improvement and changes in FC was analyzed both in terms of a priori regions and networks known to be abnormal subacutely and in a data-driven manner. RESULTS: Attention deficit recovery was mostly complete by 3 months and was significantly correlated with a normalization of abnormal FC across many networks. Improvement of attention deficits, independent of initial severity, was correlated with improvements of previously depressed interhemispheric FC across attention, sensory, and motor networks, and a restoration of the normal anticorrelation between dorsal attention/motor regions and default-mode/frontoparietal regions, particularly in the damaged hemisphere. INTERPRETATION: These results demonstrate that abnormal network connectivity in hemispatial neglect is behaviorally relevant. A return toward normal network interactions, and presumably optimal information processing, is therefore a systems-level mechanism that is associated with improvements of attention over time after focal injury. Ann Neurol 2016;80:127-141.

Dissociated functional connectivity profiles for motor and attention deficits in acute right-hemisphere stroke.

Strokes often cause multiple behavioural deficits that are correlated at the population level. Here, we show that motor and attention deficits are selectively associated with abnormal patterns of resting state functional connectivity in the dorsal attention and motor networks. We measured attention and motor deficits in 44 right hemisphere-damaged patients with a first-time stroke at 1-2 weeks post-onset. The motor battery included tests that evaluated deficits in both upper and lower extremities. The attention battery assessed both spatial and non-spatial attention deficits. Summary measures for motor and attention deficits were identified through principal component analyses on the raw behavioural scores. Functional connectivity in structurally normal cortex was estimated based on the temporal correlation of blood oxygenation level-dependent signals measured at rest with functional magnetic resonance imaging. Any correlation between motor and attention deficits and between functional connectivity in the dorsal attention network and motor networks that might spuriously affect the relationship between each deficit and functional connectivity was statistically removed. We report a double dissociation between abnormal functional connectivity patterns and attention and motor deficits, respectively. Attention deficits were significantly more correlated with abnormal interhemispheric functional connectivity within the dorsal attention network than motor networks, while motor deficits were significantly more correlated with abnormal interhemispheric functional connectivity patterns within the motor networks than dorsal attention network. These findings indicate that functional connectivity patterns in structurally normal cortex following a stroke link abnormal physiology in brain networks to the corresponding behavioural deficits.

Large-scale changes in network interactions as a physiological signature of spatial neglect.

The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n=84) heterogeneous sample of first-ever stroke patients (within 1-2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization.

Multi-Tracer Studies of Brain Oxygen and Glucose Metabolism Using a Time-of-Flight Positron Emission Tomography - Computed Tomography Scanner.

The authors have developed a paradigm using positron emission tomography (PET) with multiple radiopharmaceutical tracers that combines measurements of cerebral metabolic rate of glucose (CMRGlc), cerebral metabolic rate of oxygen (CMRO2), cerebral blood flow (CBF), and cerebral blood volume (CBV), culminating in estimates of brain aerobic glycolysis (AG). These in vivo estimates of oxidative and non-oxidative glucose metabolism are pertinent to the study of the human brain in health and disease. The latest positron emission tomography-computed tomography (PET-CT) scanners provide time-of-flight (TOF) imaging and critical improvements in spatial resolution and reduction of artifacts. This has led to significantly improved imaging with lower radiotracer doses. Optimized methods for the latest PET-CT scanners involve administering a sequence of inhaled 15O-labeled carbon monoxide (CO) and oxygen (O2), intravenous 15O-labeled water (H2O), and 18F-deoxyglucose (FDG)-all within 2-h or 3-h scan sessions that yield high-resolution, quantitative measurements of CMRGlc, CMRO2, CBF, CBV, and AG. This methods paper describes practical aspects of scanning designed for quantifying brain metabolism with tracer kinetic models and arterial blood samples and provides examples of imaging measurements of human brain metabolism.

Effects of clinical, comorbid, and social determinants of health on brain ageing in people with and without HIV: a retrospective case-control study.

BACKGROUND: Neuroimaging reveals structural brain changes linked with HIV infection and related neurocognitive disorders; however, group-level comparisons between people with HIV and people without HIV do not account for within-group heterogeneity. The aim of this study was to quantify the effects of comorbidities such as cardiovascular disease and adverse social determinants of health on brain ageing in people with HIV and people without HIV. METHODS: In this retrospective case-control study, people with HIV from Washington University in St Louis, MO, USA, and people without HIV identified through community organisations or the Research Participant Registry were clinically characterised and underwent 3-Tesla T1-weighted MRI between Dec 3, 2008, and Oct 4, 2022. Exclusion criteria were established by a combination of self-reports and medical records. DeepBrainNet, a publicly available machine learning algorithm, was applied to estimate brain-predicted age from MRI for people with HIV and people without HIV. The brain-age gap, defined as the difference between brain-predicted age and true chronological age, was modelled as a function of clinical, comorbid, and social factors by use of linear regression. Variables were first examined singly for associations with brain-age gap, then combined into multivariate models with best-subsets variable selection. FINDINGS: In people with HIV (mean age 44·8 years [SD 15·5]; 78% [296 of 379] male; 69% [260] Black; 78% [295] undetectable viral load), brain-age gap was associated with Framingham cardiovascular risk score (p=0·0034), detectable viral load (>50 copies per mL; p=0·0023), and hepatitis C co-infection (p=0·0065). After variable selection, the final model for people with HIV retained Framingham score, hepatitis C, and added unemployment (p=0·0015). Educational achievement assayed by reading proficiency was linked with reduced brain-age gap (p=0·016) for people without HIV but not for people with HIV, indicating a potential resilience factor. When people with HIV and people without HIV were modelled jointly, selection resulted in a model containing cardiovascular risk (p=0·0039), hepatitis C (p=0·037), Area Deprivation Index (p=0·033), and unemployment (p=0·00010). Male sex (p=0·078) and alcohol use history (p=0·090) were also included in the model but were not individually significant. INTERPRETATION: Our findings indicate that comorbid and social determinants of health are associated with brain ageing in people with HIV, alongside traditional HIV metrics such as viral load and CD4 cell count, suggesting the need for a broadened clinical perspective on healthy ageing with HIV, with additional focus on comorbidities, lifestyle changes, and social factors. FUNDING: National Institute of Mental Health, National Institute of Nursing Research, and National Institute of Drug Abuse.

Psilocybin desynchronizes brain networks.

1The relationship between the acute effects of psychedelics and their persisting neurobiological and psychological effects is poorly understood. Here, we tracked brain changes with longitudinal precision functional mapping in healthy adults before, during, and for up to 3 weeks after oral psilocybin and methylphenidate (17 MRI visits per participant) and again 6+ months later. Psilocybin disrupted connectivity across cortical networks and subcortical structures, producing more than 3-fold greater acute changes in functional networks than methylphenidate. These changes were driven by desynchronization of brain activity across spatial scales (area, network, whole brain). Psilocybin-driven desynchronization was observed across association cortex but strongest in the default mode network (DMN), which is connected to the anterior hippocampus and thought to create our sense of self. Performing a perceptual task reduced psilocybin-induced network changes, suggesting a neurobiological basis for grounding, connecting with physical reality during psychedelic therapy. The acute brain effects of psilocybin are consistent with distortions of space-time and the self. Psilocybin induced persistent decrease in functional connectivity between the anterior hippocampus and cortex (and DMN in particular), lasting for weeks but normalizing after 6 months. Persistent suppression of hippocampal-DMN connectivity represents a candidate neuroanatomical and mechanistic correlate for psilocybin's pro-plasticity and anti-depressant effects.

Spontaneous activity patterns in human motor cortex replay evoked activity patterns for hand movements.

Spontaneous brain activity, measured with resting state fMRI (R-fMRI), is correlated among regions that are co-activated by behavioral tasks. It is unclear, however, whether spatial patterns of spontaneous activity within a cortical region correspond to spatial patterns of activity evoked by specific stimuli, actions, or mental states. The current study investigated the hypothesis that spontaneous activity in motor cortex represents motor patterns commonly occurring in daily life. To test this hypothesis 15 healthy participants were scanned while performing four different hand movements. Three movements (Grip, Extend, Pinch) were ecological involving grip and grasp hand movements; one control movement involving the rotation of the wrist was not ecological and infrequent (Shake). They were also scanned at rest before and after the execution of the motor tasks (resting-state scans). Using the task data, we identified movement-specific patterns in the primary motor cortex. These task-defined patterns were compared to resting-state patterns in the same motor region. We also performed a control analysis within the primary visual cortex. We found that spontaneous activity patterns in the primary motor cortex were more like task patterns for ecological than control movements. In contrast, there was no difference between ecological and control hand movements in the primary visual area. These findings provide evidence that spontaneous activity in human motor cortex forms fine-scale, patterned representations associated with behaviors that frequently occur in daily life.

Inferring the dynamical effects of stroke lesions through whole-brain modeling.

Understanding the effect of focal lesions (stroke) on brain structure-function traditionally relies on behavioral analyses and correlation with neuroimaging data. Here we use structural disconnection maps from individual lesions to derive a causal mechanistic generative whole-brain model able to explain both functional connectivity alterations and behavioral deficits induced by stroke. As compared to other models that use only the local lesion information, the similarity to the empirical fMRI connectivity increases when the widespread structural disconnection information is considered. The presented model classifies behavioral impairment severity with higher accuracy than other types of information (e.g.: functional connectivity). We assessed topological measures that characterize the functional effects of damage. With the obtained results, we were able to understand how network dynamics change emerge, in a nontrivial way, after a stroke injury of the underlying complex brain system. This type of modeling, including structural disconnection information, helps to deepen our understanding of the underlying mechanisms of stroke lesions.

Subcortical-cortical dynamical states of the human brain and their breakdown in stroke.

The mechanisms controlling dynamical patterns in spontaneous brain activity are poorly understood. Here, we provide evidence that cortical dynamics in the ultra-slow frequency range (<0.01-0.1 Hz) requires intact cortical-subcortical communication. Using functional magnetic resonance imaging (fMRI) at rest, we identify Dynamic Functional States (DFSs), transient but recurrent clusters of cortical and subcortical regions synchronizing at ultra-slow frequencies. We observe that shifts in cortical clusters are temporally coincident with shifts in subcortical clusters, with cortical regions flexibly synchronizing with either limbic regions (hippocampus/amygdala), or subcortical nuclei (thalamus/basal ganglia). Focal lesions induced by stroke, especially those damaging white matter connections between basal ganglia/thalamus and cortex, provoke anomalies in the fraction times, dwell times, and transitions between DFSs, causing a bias toward abnormal network integration. Dynamical anomalies observed 2 weeks after stroke recover in time and contribute to explaining neurological impairment and long-term outcome.

Naturalistic driving measures of route selection associate with resting state networks in older adults.

Our objective was to identify functional brain changes that associate with driving behaviors in older adults. Within a cohort of 64 cognitively normal adults (age 60+), we compared naturalistic driving behavior with resting state functional connectivity using machine learning. Functional networks associated with the ability to interpret and respond to external sensory stimuli and the ability to multi-task were associated with measures of route selection. Maintenance of these networks may be important for continued preservation of driving abilities.

Stroke-related alterations in inter-areal communication.

Beyond causing local ischemia and cell damage at the site of injury, stroke strongly affects long-range anatomical connections, perturbing the functional organization of brain networks. Several studies reported functional connectivity abnormalities parallelling both behavioral deficits and functional recovery across different cognitive domains. FC alterations suggest that long-range communication in the brain is altered after stroke. However, standard FC analyses cannot reveal the directionality and time scale of inter-areal information transfer. We used resting-state fMRI and covariance-based Granger causality analysis to quantify network-level information transfer and its alteration in stroke. Two main large-scale anomalies were observed in stroke patients. First, inter-hemispheric information transfer was significantly decreased with respect to healthy controls. Second, stroke caused inter-hemispheric asymmetries, as information transfer within the affected hemisphere and from the affected to the intact hemisphere was significantly reduced. Both anomalies were more prominent in resting-state networks related to attention and language, and they correlated with impaired performance in several behavioral domains. Overall, our findings support the hypothesis that stroke provokes asymmetries between the affected and spared hemisphere, with different functional consequences depending on which hemisphere is lesioned.

Lesion Quantification Toolkit: A MATLAB software tool for estimating grey matter damage and white matter disconnections in patients with focal brain lesions.

Lesion studies are an important tool for cognitive neuroscientists and neurologists. However, while brain lesion studies have traditionally aimed to localize neurological symptoms to specific anatomical loci, a growing body of evidence indicates that neurological diseases such as stroke are best conceptualized as brain network disorders. While researchers in the fields of neuroscience and neurology are therefore increasingly interested in quantifying the effects of focal brain lesions on the white matter connections that form the brain's structural connectome, few dedicated tools exist to facilitate this endeavor. Here, we present the Lesion Quantification Toolkit, a publicly available MATLAB software package for quantifying the structural impacts of focal brain lesions. The Lesion Quantification Toolkit uses atlas-based approaches to estimate parcel-level grey matter lesion loads and multiple measures of white matter disconnection severity that include tract-level disconnection measures, voxel-wise disconnection maps, and parcel-wise disconnection matrices. The toolkit also estimates lesion-induced increases in the lengths of the shortest structural paths between parcel pairs, which provide information about changes in higher-order structural network topology. We describe in detail each of the different measures produced by the toolkit, discuss their applications and considerations relevant to their use, and perform example analyses using real behavioral data collected from sub-acute stroke patients. We show that analyses performed using the different measures produced by the toolkit produce results that are highly consistent with results that have been reported in the prior literature, and we demonstrate the consistency of results obtained from analyses conducted using the different disconnection measures produced by the toolkit. We anticipate that the Lesion Quantification Toolkit will empower researchers to address research questions that would be difficult or impossible to address using traditional lesion analyses alone, and ultimately, lead to advances in our understanding of how white matter disconnections contribute to the cognitive, behavioral, and physiological consequences of focal brain lesions.