The brain is not a passive sensory-motor analyzer driven by environmental stimuli, but actively maintains ongoing representations that may be involved in the coding of expected sensory stimuli, prospective motor responses, and prior experience. Spontaneous cortical activity has been proposed to play an important part in maintaining these ongoing, internal representations, although its functional role is not well understood. One spontaneous signal being intensely investigated in the human brain is the interregional temporal correlation of the blood-oxygen level-dependent (BOLD) signal recorded at rest by functional MRI (functional connectivity-by-MRI, fcMRI, or BOLD connectivity). This signal is intrinsic and coherent within a number of distributed networks whose topography closely resembles that of functional networks recruited during tasks. While it is apparent that fcMRI networks reflect anatomical connectivity, it is less clear whether they have any dynamic functional importance. Here, we demonstrate that visual perceptual learning, an example of adult neural plasticity, modifies the resting covariance structure of spontaneous activity between networks engaged by the task. Specifically, after intense training on a shape-identification task constrained to one visual quadrant, resting BOLD functional connectivity and directed mutual interaction between trained visual cortex and frontalparietal areas involved in the control of spatial attention were significantly modified. Critically, these changes correlated with the degree of perceptual learning. We conclude that functional connectivity serves a dynamic role in brain function, supporting the consolidation of previous experience.fMRI ͉ functional connectivity ͉ perceptual learning ͉ resting state S pontaneous neural activity utilizes the majority of the brain's energy budget, but its function remains mysterious (1-8). At the level of single neurons, embedded in the local circuitry of a cortical area, spontaneous activity has been shown to emulate the pattern of activity evoked by the neuron's optimal stimulus, suggesting that at least at this level of description, spontaneous activity is likely to reflect the history of coactivation within local networks (9). At the level of distributed cortical systems, spontaneous activity measured by blood-oxygen level-dependent (BOLD) functional MRI (fMRI) exhibits covariance structures (or functional connectivity) at ultraslow frequencies (Ͻ0.1 Hz) that are stable across a wide range of behavioral states (anesthesia, task performance, resting wakefulness, and sleep) (10, 11). The topography of BOLD functional connectivity is compatible with both the underlying structural connectivity of the cortex and the functional anatomy of systems engaged by a broad range of tasks (12-16).Studies have suggested that BOLD functional connectivity is largely a physiological marker of anatomical connections or a correlate of intrinsic vascular dynamics without functional or behavioral significance (17). This hypothesis is consistent with t...

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 brainbehavior relationships in stroke.stroke | functional connectivity | interhemispheric | memory | language A lthough structural damage from stroke is focal, remote dysfunction can occur in regions of the brain distant from the area of damage (1, 2). The set of regions that are directly damaged or indirectly affected is embedded within a larger functional network that is in dynamic balance with other networks in the brain. This framework posits that a lesion in a single location in the brain has the ability to disrupt brain functions far beyond the lesion boundaries (3-5).Numerous correlates of remote physiological dysfunction have been proposed, including abnormal task recruitment of contralesional brain areas (6-8), disruption of metabolism (9) or regional cerebral blood flow (10, 11), and more recently disruption of signal coherence (12-15).However, there is only a limited understanding of how remote physiological dysfunction is related to lesion topography (14, 16). Moreover, the behavioral relevance of reported physiological changes is unclear. Although some studies have reported significant correlation with behavioral impairment, the total amount of behavioral variance explained is unknown. Finally, because mechanisms of remote dysfunction have typically been examined in relatively small groups of individuals, their generalization at the population level is unknown. As a result, physiological measures of brain function are not used in the evaluation and treatment of stroke victims.More traditional lesion-symptom mapping studies have also used statistical methods to relate lesion topography to the severity of different behavioral deficits (17,18). An implicit assumption of these studies is that the strength of association between structural damage and behavior is the same irrespective of the behavior that is measured. However, it is also possi...

SUMMARY A long-held view is that stroke causes many distinct neurological syndromes due to damage of specialized cortical and subcortical centers. However, it is unknown if a syndrome-based description is helpful in characterizing behavioral deficits across a large number of patients. We studied a large prospective sample of first-time stroke patients with heterogeneous lesions at 1–2 weeks post-stroke. We measured behavior over multiple domains and lesion anatomy with structural MRI and a probabilistic atlas of white matter pathways. Multivariate methods estimated the percentage of behavioral variance explained by structural damage. A few clusters of behavioral deficits spanning multiple functions explained neurological impairment. Stroke topography was predominantly subcortical, and disconnection of white matter tracts critically contributed to behavioral deficits and their correlation. The locus of damage explained more variance for motor and language than memory or attention deficits. Our findings highlight the need for better models of white matter damage on cognition.

Resting-state functional magnetic resonance imaging (fMRI) has been used to study brain networks associated with both normal and pathological cognitive function. The objective of this work is to reliably compute resting state network (RSN) topography in single participants. We trained a supervised classifier (multi-layer perceptron; MLP) to associate blood oxygen level dependent (BOLD) correlation maps corresponding to pre-defined seeds with specific RSN identities. Hard classification of maps obtained from a priori seeds was highly reliable across new participants. Interestingly, continuous estimates of RSN membership retained substantial residual error. This result is consistent with the view that RSNs are hierarchically organized, and therefore not fully separable into spatially independent components. After training on a priori seed-based maps, we propagated voxel-wise correlation maps through the MLP to produce estimates of RSN membership throughout the brain. The MLP generated RSN topography estimates in individuals consistent with previous studies, even in brain regions not represented in the training data. This method could be used in future studies to relate RSN topography to other measures of functional brain organization (e.g., task-evoked responses, stimulation mapping, and deficits associated with lesions) in individuals. The multi-layer perceptron was directly compared to two alternative voxel classification procedures, specifically, dual regression and linear discriminant analysis; the perceptron generated more spatially specific RSN maps than either alternative.

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.

People differ in their ability to perform novel perceptual tasks, both during initial exposure and in the rate of improvement with practice. It is also known that regions of the brain recruited by particular tasks change their activity during learning. Here we investigate neural signals predictive of individual variability in performance. We used resting-state functional MRI to assess functional connectivity before training on a novel visual discrimination task. Subsequent task performance was related to functional connectivity measures within portions of visual cortex and between visual cortex and prefrontal association areas. Our results indicate that individual differences in performing novel perceptual tasks can be related to individual differences in spontaneous cortical activity

Objective We recently reported that spatial and non-spatial attention deficits in stroke patients with hemi-spatial neglect are correlated at 2 weeks post-onset with widespread alterations of inter-hemispheric and intra-hemispheric functional connectivity (FC) measured with resting state fMRI (R-fMRI) across multiple brain networks. The mechanisms underlying neglect recovery are largely unknown. In this study we test the hypothesis that recovery of hemi-spatial 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 (n=64) months post onset. The relationship between behavioral improvement and changes in FC was analyzed both in terms of a priori regions and networks known to be abnormal sub-acutely, 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 inter-hemispheric FC across attention, sensory, and motor networks, and a restoration of the normal anti-correlation between dorsal attention/motor regions and default-mode/frontoparietal regions, particularly in the damaged hemisphere. Interpretation These results demonstrate that abnormal network connectivity in hemi-spatial 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.

Purpose of review An important challenge in neurology is identifying the neural mechanisms underlying behavioral deficits after brain injury. Here, we review recent advances in understanding the effects of focal brain lesions on brain networks and behavior. Recent findings Neuroimaging studies indicate that the human brain is organized in large-scale resting state networks (RSNs) defined via functional connectivity, that is the temporal correlation of spontaneous activity between different areas. Prior studies showed that focal brain lesion induced behaviorally relevant changes of functional connectivity beyond the site of damage. Recent work indicates that across domains, functional connectivity changes largely conform to two patterns: a reduction in interhemispheric functional connectivity and an increase in intrahemispheric functional connectivity between networks that are normally anticorrelated, for example dorsal attention and default networks. Abnormal functional connectivity can exhibit a high degree of behavioral specificity such that deficits in a given behavioral domain are selectively related to functional connectivity of the corresponding RSN, but some functional connectivity changes allow prediction across domains. Finally, as behavioral recovery proceeds, the prestroke pattern of functional connectivity is restored. Summary Investigating changes in RSNs may shed light on the neural mechanisms underlying brain dysfunction after stroke. Therefore, resting state functional connectivity may represent an important tool for clinical diagnosis, tracking recovery and rehabilitation.