Focal brain lesions to critical locations cause widespread disruption of the modular organization of the brain

Early sensory processing in right hemispheric stroke patients with and without extinction

While extinction is most commonly viewed as an attentional disorder and not as a consequence of a failure to process contralesional sensory information, it has been speculated that early sensory processing of contralesional targets in extinction patients might not be fully normal. We used a masked visuo-motor response priming paradigm to study the influence of both contralesional and ipsilesional peripheral subliminal prime stimuli on central target performance, allowing us to compare the strength of the early sensory processing associated with these prime stimuli between right brain damaged patients with and without extinction as well as healthy elderly subjects. We found that the effect of an informative subliminal prime in the left contralesional visual field on central target performance was significantly reduced in both right brain damaged patients with and without extinction. The results suggest that a low-level early sensory deterioration of the neural representation for contralesional prime stimuli is a general consequence of right hemispheric brain damage unrelated to the presence or absence of extinction. This suggests that the presence of a spatial bias against contralesional information is not sufficient to elicit extinction. For extinction to occur, this spatial bias might need to be accompanied by a pathological (non-directional) reduction of attentional capacity.

Functional brain network modularity predicts response to cognitive training after brain injury

OBJECTIVE

We tested the value of measuring modularity, a graph theory metric indexing the relative extent of integration and segregation of distributed functional brain networks, for predicting individual differences in response to cognitive training in patients with brain injury.

METHODS

Patients with acquired brain injury (n = 11) participated in 5 weeks of cognitive training and a comparison condition (brief education) in a crossover intervention study design. We quantified the measure of functional brain network organization, modularity, from functional connectivity networks during a state of tonic attention regulation measured during fMRI scanning before the intervention conditions. We examined the relationship of baseline modularity with pre- to posttraining changes in neuropsychological measures of attention and executive control.

RESULTS

The modularity of brain network organization at baseline predicted improvement in attention and executive function after cognitive training, but not after the comparison intervention. Individuals with higher baseline modularity exhibited greater improvements with cognitive training, suggesting that a more modular baseline network state may contribute to greater adaptation in response to cognitive training.

CONCLUSIONS

Brain network properties such as modularity provide valuable information for understanding mechanisms that influence rehabilitation of cognitive function after brain injury, and may contribute to the discovery of clinically relevant biomarkers that could guide rehabilitation efforts.

The neurobiology of emotion-cognition interactions: fundamental questions and strategies for future research

Recent years have witnessed the emergence of powerful new tools for assaying the brain and a remarkable acceleration of research focused on the interplay of emotion and cognition. This work has begun to yield new insights into fundamental questions about the nature of the mind and important clues about the origins of mental illness. In particular, this research demonstrates that stress, anxiety, and other kinds of emotion can profoundly influence key elements of cognition, including selective attention, working memory, and cognitive control. Often, this influence persists beyond the duration of transient emotional challenges, partially reflecting the slower molecular dynamics of catecholamine and hormonal neurochemistry. In turn, circuits involved in attention, executive control, and working memory contribute to the regulation of emotion. The distinction between the 'emotional' and the 'cognitive' brain is fuzzy and context-dependent. Indeed, there is compelling evidence that brain territories and psychological processes commonly associated with cognition, such as the dorsolateral prefrontal cortex and working memory, play a central role in emotion. Furthermore, putatively emotional and cognitive regions influence one another via a complex web of connections in ways that jointly contribute to adaptive and maladaptive behavior. This work demonstrates that emotion and cognition are deeply interwoven in the fabric of the brain, suggesting that widely held beliefs about the key constituents of 'the emotional brain' and 'the cognitive brain' are fundamentally flawed. We conclude by outlining several strategies for enhancing future research. Developing a deeper understanding of the emotional-cognitive brain is important, not just for understanding the mind but also for elucidating the root causes of its disorders.

Widespread increase of functional connectivity in Parkinson's disease with tremor: a resting-state FMRI study

Parkinson’s disease (PD) is a clinically heterogeneous disease in the symptomatology dominated by tremor, akinesia, or rigidity. Focusing on PD patients with tremor, this study investigated their discoordination patterns of spontaneous brain activity by combining voxel-wise centrality, seed-based functional connectivity, and network efficiency methods. Sixteen patients and 20 matched healthy controls (HCs) were recruited and underwent structural and resting-state functional MRI scan. Compared with the HCs, the patients exhibited increased centrality in the frontal, parietal, and occipital regions while decreased centrality in the cerebellum anterior lobe and thalamus. Seeded at these regions, a distributed network was further identified that encompassed cortical (default mode network, sensorimotor cortex, prefrontal and occipital areas) and subcortical (thalamus and basal ganglia) regions and the cerebellum and brainstem. Graph-based analyses of this network revealed increased information transformation efficiency in the patients. Moreover, the identified network correlated with clinical manifestations in the patients and could distinguish the patients from HCs. Morphometric analyses revealed decreased gray matter volume in multiple regions that largely accounted for the observed functional abnormalities. Together, these findings provide a comprehensive view of network disorganization in PD with tremor and have important implications for understanding neural substrates underlying this specific type of PD.

Studying brain organization via spontaneous fMRI signal

In recent years, some substantial advances in understanding human (and nonhuman) brain organization have emerged from a relatively unusual approach: the observation of spontaneous activity, and correlated patterns in spontaneous activity, in the "resting" brain. Most commonly, spontaneous neural activity is measured indirectly via fMRI signal in subjects who are lying quietly in the scanner, the so-called "resting state." This Primer introduces the fMRI-based study of spontaneous brain activity, some of the methodological issues active in the field, and some ways in which resting-state fMRI has been used to delineate aspects of area-level and supra-areal brain organization.

Decreased segregation of brain systems across the healthy adult lifespan

Healthy aging has been associated with decreased specialization in brain function. This characterization has focused largely on describing age-accompanied differences in specialization at the level of neurons and brain areas. We expand this work to describe systems-level differences in specialization in a healthy adult lifespan sample (n = 210; 20-89 y). A graph-theoretic framework is used to guide analysis of functional MRI resting-state data and describe systems-level differences in connectivity of individual brain networks. Young adults' brain systems exhibit a balance of within- and between-system correlations that is characteristic of segregated and specialized organization. Increasing age is accompanied by decreasing segregation of brain systems. Compared with systems involved in the processing of sensory input and motor output, systems mediating "associative" operations exhibit a distinct pattern of reductions in segregation across the adult lifespan. Of particular importance, the magnitude of association system segregation is predictive of long-term memory function, independent of an individual's age.

Network measures predict neuropsychological outcome after brain injury

Hubs are network components that hold positions of high importance for network function. Previous research has identified hubs in human brain networks derived from neuroimaging data; however, there is little consensus on the localization of such hubs. Moreover, direct evidence regarding the role of various proposed hubs in network function (e.g., cognition) is scarce. Regions of the default mode network (DMN) have been frequently identified as "cortical hubs" of brain networks. On theoretical grounds, we have argued against some of the methods used to identify these hubs and have advocated alternative approaches that identify different regions of cortex as hubs. Our framework predicts that our proposed hub locations may play influential roles in multiple aspects of cognition, and, in contrast, that hubs identified via other methods (including salient regions in the DMN) might not exert such broad influence. Here we used a neuropsychological approach to directly test these predictions by studying long-term cognitive and behavioral outcomes in 30 patients, 19 with focal lesions to six "target" hubs identified by our approaches (high system density and participation coefficient) and 11 with focal lesions to two "control" hubs (high degree centrality). In support of our predictions, we found that damage to target locations produced severe and widespread cognitive deficits, whereas damage to control locations produced more circumscribed deficits. These findings support our interpretation of how neuroimaging-derived network measures relate to cognition and augment classic neuroanatomically based predictions about cognitive and behavioral outcomes after focal brain injury.

A dissociation between stopping and switching actions following a lesion of the pre-supplementary motor area

Introduction

Although the pre-supplementary motor area (pre-SMA) is one of the most frequently reported areas of activation in functional imaging studies, the role of this brain region in cognition is still a matter of intense debate. Here we present a patient with a focal lesion of caudal pre-SMA who displays a selective deficit in updating a response plan to switch actions, but shows no impairment when required to withhold a response – stopping.

Materials & methods

The patient and a control group underwent three tasks designed to measure different aspects of cognitive control and executive function.

Results

The pre-SMA patient displayed no impairment when responding in the face of distracting stimuli (Eriksen flanker paradigm), or when required to halt an on-going response (STOP task). However, a specific deficit was observed when she was required to rapidly switch between response plans (CHANGE task).

Conclusions

These findings suggest that the caudal pre-SMA may have a particularly important role in a network of brain regions required for rapidly updating and implementing response plans. The lack of any significant impairment on other measures of cognitive control suggests that this is not likely due to a global deficit in cognitive control. We discuss the implications of these results in the context of current theories of pre-SMA function.

The hubs of the human connectome are generally implicated in the anatomy of brain disorders

Brain networks or 'connectomes' include a minority of highly connected hub nodes that are functionally valuable, because their topological centrality supports integrative processing and adaptive behaviours. Recent studies also suggest that hubs have higher metabolic demands and longer-distance connections than other brain regions, and therefore could be considered biologically costly. Assuming that hubs thus normally combine both high topological value and high biological cost, we predicted that pathological brain lesions would be concentrated in hub regions. To test this general hypothesis, we first identified the hubs of brain anatomical networks estimated from diffusion tensor imaging data on healthy volunteers (n = 56), and showed that computational attacks targeted on hubs disproportionally degraded the efficiency of brain networks compared to random attacks. We then prepared grey matter lesion maps, based on meta-analyses of published magnetic resonance imaging data on more than 20 000 subjects and 26 different brain disorders. Magnetic resonance imaging lesions that were common across all brain disorders were more likely to be located in hubs of the normal brain connectome (P < 10(-4), permutation test). Specifically, nine brain disorders had lesions that were significantly more likely to be located in hubs (P < 0.05, permutation test), including schizophrenia and Alzheimer's disease. Both these disorders had significantly hub-concentrated lesion distributions, although (almost completely) distinct subsets of cortical hubs were lesioned in each disorder: temporal lobe hubs specifically were associated with higher lesion probability in Alzheimer's disease, whereas in schizophrenia lesions were concentrated in both frontal and temporal cortical hubs. These results linking pathological lesions to the topological centrality of nodes in the normal diffusion tensor imaging connectome were generally replicated when hubs were defined instead by the meta-analysis of more than 1500 task-related functional neuroimaging studies of healthy volunteers to create a normative functional co-activation network. We conclude that the high cost/high value hubs of human brain networks are more likely to be anatomically abnormal than non-hubs in many (if not all) brain disorders.

Network hubs in the human brain

Virtually all domains of cognitive function require the integration of distributed neural activity. Network analysis of human brain connectivity has consistently identified sets of regions that are critically important for enabling efficient neuronal signaling and communication. The central embedding of these candidate 'brain hubs' in anatomical networks supports their diverse functional roles across a broad range of cognitive tasks and widespread dynamic coupling within and across functional networks. The high level of centrality of brain hubs also renders them points of vulnerability that are susceptible to disconnection and dysfunction in brain disorders. Combining data from numerous empirical and computational studies, network approaches strongly suggest that brain hubs play important roles in information integration underpinning numerous aspects of complex cognitive function.

Perfusion MRI indexes variability in the functional brain effects of theta-burst transcranial magnetic stimulation

Transcranial Magnetic Stimulation (TMS) is an important tool for testing causal relationships in cognitive neuroscience research. However, the efficacy of TMS can be variable across individuals and difficult to measure. This variability is especially a challenge when TMS is applied to regions without well-characterized behavioral effects, such as in studies using TMS on multi-modal areas in intrinsic networks. Here, we examined whether perfusion fMRI recordings of Cerebral Blood Flow (CBF), a quantitative measure sensitive to slow functional changes, reliably index variability in the effects of stimulation. Twenty-seven participants each completed four combined TMS-fMRI sessions during which both resting state Blood Oxygen Level Dependent (BOLD) and perfusion Arterial Spin Labeling (ASL) scans were recorded. In each session after the first baseline day, continuous theta-burst TMS (TBS) was applied to one of three locations: left dorsolateral prefrontal cortex (L dlPFC), left anterior insula/frontal operculum (L aI/fO), or left primary somatosensory cortex (L S1). The two frontal targets are components of intrinsic networks and L S1 was used as an experimental control. CBF changes were measured both before and after TMS on each day from a series of interleaved resting state and perfusion scans. Although TBS led to weak selective increases under the coil in CBF measurements across the group, individual subjects showed wide variability in their responses. TBS-induced changes in rCBF were related to TBS-induced changes in functional connectivity of the relevant intrinsic networks measured during separate resting-state BOLD scans. This relationship was selective: CBF and functional connectivity of these networks were not related before TBS or after TBS to the experimental control region (S1). Furthermore, subject groups with different directions of CBF change after TBS showed distinct modulations in the functional interactions of targeted networks. These results suggest that CBF is a marker of individual differences in the effects of TBS.

Diaschisis: past, present, future

After a century of false hopes, recent studies have placed the concept of diaschisis at the centre of the understanding of brain function. Originally, the term 'diaschisis' was coined by von Monakow in 1914 to describe the neurophysiological changes that occur distant to a focal brain lesion. In the following decades, this concept triggered widespread clinical interest in an attempt to describe symptoms and signs that the lesion could not fully explain. However, the first imaging studies, in the late 1970s, only partially confirmed the clinical significance of diaschisis. Focal cortical areas of diaschisis (i.e. focal diaschisis) contributed to the clinical deficits after subcortical but only rarely after cortical lesions. For this reason, the concept of diaschisis progressively disappeared from the mainstream of research in clinical neurosciences. Recent evidence has unexpectedly revitalized the notion. The development of new imaging techniques allows a better understanding of the complexity of brain organization. It is now possible to reliably investigate a new type of diaschisis defined as the changes of structural and functional connectivity between brain areas distant to the lesion (i.e. connectional diaschisis). As opposed to focal diaschisis, connectional diaschisis, focusing on determined networks, seems to relate more consistently to the clinical findings. This is particularly true after stroke in the motor and attentional networks. Furthermore, normalization of remote connectivity changes in these networks relates to a better recovery. In the future, to investigate the clinical role of diaschisis, a systematic approach has to be considered. First, emerging imaging and electrophysiological techniques should be used to precisely map and selectively model brain lesions in human and animals studies. Second, the concept of diaschisis must be applied to determine the impact of a focal lesion on new representations of the complexity of brain organization. As an example, the evaluation of remote changes in the structure of the connectome has so far mainly been tested by modelization of focal brain lesions. These changes could now be assessed in patients suffering from focal brain lesions (i.e. connectomal diaschisis). Finally, and of major significance, focal and non-focal neurophysiological changes distant to the lesion should be the target of therapeutic strategies. Neuromodulation using transcranial magnetic stimulation is one of the most promising techniques. It is when this last step will be successful that the concept of diaschisis will gain all the clinical respectability that could not be obtained in decades of research.

Ischaemic stroke in young adults: risk factors and long-term consequences

Contrary to trends in most other diseases, the average age of ischaemic stroke onset is decreasing, owing to a rise in the incidence of stroke among 'young' individuals (under 50 years of age). This Review provides a critical overview of the risk factors and aetiology of young ischaemic stroke and addresses its long-term prognosis, including cardiovascular risk, functional outcome and psychosocial consequences. We highlight the diminishing role of 'rare' risk factors in the pathophysiology of young stroke in light of the rising prevalence of 'traditional' vascular risk factors in younger age groups. Long-term prognosis is of particular interest to young patients, because of their long life expectancy and major responsibilities during a demanding phase of life. The prognosis of young stroke is not as favourable as previously thought, with respect either to mortality or cardiovascular disease or to psychosocial consequences. Therefore, secondary stroke prevention is probably a life-long endeavour in most young stroke survivors. Due to under-representation of young patients in past trials, new randomized trials focusing on this age group are needed to confirm the benefits of long-term secondary preventive medication. The high prevalence of poor functional outcome and psychosocial problems warrants further study to optimize treatment and rehabilitation for these young patients.

Functional and structural network impairment in childhood frontal lobe epilepsy

In childhood frontal lobe epilepsy (FLE), cognitive impairment and educational underachievement are serious, well-known co-morbidities. The broad scale of affected cognitive domains suggests wide-spread network disturbances that not only involves, but also extends beyond the frontal lobe. In this study we have investigated whole brain connectional properties of children with FLE in relation to their cognitive impairment and compared them with healthy controls. Functional connectivity (FC) of the networks was derived from dynamic fluctuations of resting state fMRI and structural connectivity (SC) was obtained from fiber tractograms of diffusion weighted MRI. The whole brain network was characterized with graph theoretical metrics and decomposed into modules. Subsequently, the graph metrics and the connectivity within and between modules were related to cognitive performance. Functional network disturbances in FLE were related to increased clustering, increased path length, and stronger modularity compared to healthy controls, which was accompanied by stronger within- and weaker between-module functional connectivity. Although structural path length and clustering appeared normal in children with FLE, structural modularity increased with stronger cognitive impairment. It is concluded that decreased coupling between large-scale functional network modules is a hallmark for impaired cognition in childhood FLE.

Altered Cognitive Control Activations after Moderate-to-Severe Traumatic Brain Injury and Their Relationship to Injury Severity and Everyday-Life Function

This study investigated how the neuronal underpinnings of both adaptive and stable cognitive control processes are affected by traumatic brain injury (TBI). Functional magnetic resonance imaging (fMRI) was undertaken in 62 survivors of moderate-to-severe TBI (>1 year after injury) and 68 healthy controls during performance of a continuous performance test adapted for use in a mixed block- and event-related design. Survivors of TBI demonstrated increased reliance on adaptive task control processes within an a priori core region for cognitive control in the medial frontal cortex. TBI survivors also had increased activations related to time-on-task effects during stable task-set maintenance in right inferior parietal and prefrontal cortices. Increased brain activations in TBI survivors had a dose-dependent linear positive relationship to injury severity and were negatively correlated with self-reported cognitive control problems in everyday-life situations. Results were adjusted for age, education, and fMRI task performance. In conclusion, evidence was provided that the neural underpinnings of adaptive and stable control processes are differently affected by TBI. Moreover, it was demonstrated that increased brain activations typically observed in survivors of TBI might represent injury-specific compensatory adaptations also utilized in everyday-life situations.

Systematic network lesioning reveals the core white matter scaffold of the human brain

Brain connectivity loss due to traumatic brain injury, stroke or multiple sclerosis can have serious consequences on life quality and a measurable impact upon neural and cognitive function. Though brain network properties are known to be affected disproportionately by injuries to certain gray matter regions, the manner in which white matter (WM) insults affect such properties remains poorly understood. Here, network-theoretic analysis allows us to identify the existence of a macroscopic neural connectivity core in the adult human brain which is particularly sensitive to network lesioning. The systematic lesion analysis of brain connectivity matrices from diffusion neuroimaging over a large sample (N = 110) reveals that the global vulnerability of brain networks can be predicated upon the extent to which injuries disrupt this connectivity core, which is found to be quite distinct from the set of connections between rich club nodes in the brain. Thus, in addition to connectivity within the rich club, the brain as a network also contains a distinct core scaffold of network edges consisting of WM connections whose damage dramatically lowers the integrative properties of brain networks. This pattern of core WM fasciculi whose injury results in major alterations to overall network integrity presents new avenues for clinical outcome prediction following brain injury by relating lesion locations to connectivity core disruption and implications for recovery. The findings of this study contribute substantially to current understanding of the human WM connectome, its sensitivity to injury, and clarify a long-standing debate regarding the relative prominence of gray vs. WM regions in the context of brain structure and connectomic architecture.

Inferring a dual-stream model of mentalizing from associative white matter fibres disconnection

In the field of cognitive neuroscience, it is increasingly accepted that mentalizing is subserved by a complex frontotemporoparietal cortical network. Some researchers consider that this network can be divided into two distinct but interacting subsystems (the mirror system and the mentalizing system per se), which respectively process low-level, perceptive-based aspects and high-level, inference-based aspects of this sociocognitive function. However, evidence for this type of functional dissociation in a given neuropsychological population is currently lacking and the structural connectivities of the two mentalizing subnetworks have not been established. Here, we studied mentalizing in a large sample of patients (n = 93; 46 females; age range: 18-65 years) who had been resected for diffuse low-grade glioma-a rare tumour that migrates preferentially along associative white matter pathways. This neurological disorder constitutes an ideal pathophysiological model in which to study the functional anatomy of associative pathways. We mapped the location of each patient's resection cavity and residual lesion infiltration onto the Montreal Neurological Institute template brain and then performed multilevel lesion analyses (including conventional voxel-based lesion-symptom mapping and subtraction lesion analyses). Importantly, we estimated each associative pathway's degree of disconnection (i.e. the degree of lesion infiltration) and built specific hypotheses concerning the connective anatomy of the mentalizing subnetworks. As expected, we found that impairments in mentalizing were mainly related to the disruption of right frontoparietal connectivity. More specifically, low-level and high-level mentalizing accuracy were correlated with the degree of disconnection in the arcuate fasciculus and the cingulum, respectively. To the best of our knowledge, our findings constitute the first experimental data on the structural connectivity of the mentalizing network and suggest the existence of a dual-stream hodological system. Our results may lead to a better understanding of disorders that affect social cognition, especially in neuropathological conditions characterized by atypical/aberrant structural connectivity, such as autism spectrum disorders.

The effect of theta-burst TMS on cognitive control networks measured with resting state fMRI

IT HAS BEEN PROPOSED THAT TWO RELATIVELY INDEPENDENT COGNITIVE CONTROL NETWORKS EXIST IN THE BRAIN: the cingulo-opercular network (CO) and the fronto-parietal network (FP). Past work has shown that chronic brain lesions affect these networks independently. It remains unclear, however, how these two networks are affected by acute brain disruptions. To examine this, we conducted a within-subject theta-burst transcranial magnetic stimulation (TBS) experiment in healthy individuals that targeted left anterior insula/frontal operculum (L aI/fO, a region in the CO network), left dorsolateral prefrontal cortex (L dlPFC, a region in the FP network), or left primary somatosensory cortex (L S1, an experimental control region). Functional connectivity (FC) was measured in resting state fMRI scans collected before and after continuous TBS on each day. We found that TBS was accompanied by generalized increases in network connectivity, especially FP network connectivity, after TBS to either region involved in cognitive control. Whole-brain analyses demonstrated that the L dlPFC and L aI/fO showed increased connectivity with regions in frontal, parietal, and cingulate cortex after TBS to either L dlPFC or L aI/fO, but not to L S1. These results suggest that acute disruption by TBS to cognitive control regions causes widespread changes in network connectivity not limited to the targeted networks.

Dissociated repetition deficits in aphasia can reflect flexible interactions between left dorsal and ventral streams and gender-dimorphic architecture of the right dorsal stream

Assessment of brain-damaged subjects presenting with dissociated repetition deficits after selective injury to either the left dorsal or ventral auditory pathways can provide further insight on their respective roles in verbal repetition. We evaluated repetition performance and its neural correlates using multimodal imaging (anatomical MRI, DTI, fMRI, and¹⁸FDG-PET) in a female patient with transcortical motor aphasia (TCMA) and in a male patient with conduction aphasia (CA) who had small contiguous but non-overlapping left perisylvian infarctions. Repetition in the TCMA patient was fully preserved except for a mild impairment in nonwords and digits, whereas the CA patient had impaired repetition of nonwords, digits and word triplet lists. Sentence repetition was impaired, but he repeated novel sentences significantly better than clichés. The TCMA patient had tissue damage and reduced metabolism in the left sensorimotor cortex and insula. DTI showed damage to the left temporo-frontal and parieto-frontal segments of the arcuate fasciculus (AF) and part of the left ventral stream together with well-developed right dorsal and ventral streams, as has been reported in more than one-third of females. The CA patient had tissue damage and reduced metabolic activity in the left temporoparietal cortex with additional metabolic decrements in the left frontal lobe. DTI showed damage to the left temporo-parietal and temporo-frontal segments of the AF, but the ventral stream was spared. The direct segment of the AF in the right hemisphere was also absent with only vestigial remains of the other dorsal subcomponents present, as is often found in males. fMRI during word and nonword repetition revealed bilateral perisylvian activation in the TCMA patient suggesting recruitment of spared segments of the left dorsal stream and right dorsal stream with propagation of signals to temporal lobe structures suggesting a compensatory reallocation of resources via the ventral streams. The CA patient showed a greater activation of these cortical areas than the TCMA patient, but these changes did not result in normal performance. Repetition of word triplet lists activated bilateral perisylvian cortices in both patients, but activation in the CA patient with very poor performance was restricted to small frontal and posterior temporal foci bilaterally. These findings suggest that dissociated repetition deficits in our cases are probably reliant on flexible interactions between left dorsal stream (spared segments, short tracts remains) and left ventral stream and on gender-dimorphic architecture of the right dorsal stream.

Working memory performance of early MS patients correlates inversely with modularity increases in resting state functional connectivity networks

Multiple sclerosis (MS) is an autoimmune inflammatory demyelinating and neurodegenerative disorder of the central nervous system characterized by multifocal white matter brain lesions leading to alterations in connectivity at the subcortical and cortical level. Graph theory, in combination with neuroimaging techniques, has been recently developed into a powerful tool to assess the large-scale structure of brain functional connectivity. Considering the structural damage present in the brain of MS patients, we hypothesized that the topological properties of resting-state functional networks of early MS patients would be re-arranged in order to limit the impact of disease expression. A standardized dual task (Paced Auditory Serial Addition Task simultaneously performed with a paper and pencil task) was administered to study the interactions between behavioral performance and functional network re-organization. We studied a group of 16 early MS patients (35.3±8.3 years, 11 females) and 20 healthy controls (29.9±7.0 years, 10 females) and found that brain resting-state networks of the MS patients displayed increased network modularity, i.e. diminished functional integration between separate functional modules. Modularity correlated negatively with dual task performance in the MS patients. Our results shed light on how localized anatomical connectivity damage can globally impact brain functional connectivity and how these alterations can impair behavioral performance. Finally, given the early stage of the MS patients included in this study, network modularity could be considered a promising biomarker for detection of earliest-stage brain network reorganization, and possibly of disease progression.

Evidence for hubs in human functional brain networks

Hubs integrate and distribute information in powerful ways due to the number and positioning of their contacts in a network. Several resting-state functional connectivity MRI reports have implicated regions of the default mode system as brain hubs; we demonstrate that previous degree-based approaches to hub identification may have identified portions of large brain systems rather than critical nodes of brain networks. We utilize two methods to identify hub-like brain regions: (1) finding network nodes that participate in multiple subnetworks of the brain, and (2) finding spatial locations in which several systems are represented within a small volume. These methods converge on a distributed set of regions that differ from previous reports on hubs. This work identifies regions that support multiple systems, leading to spatially constrained predictions about brain function that may be tested in terms of lesions, evoked responses, and dynamic patterns of activity.

Altered resting state brain networks in Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disorder affecting dopaminergic neurons in the substantia nigra leading to dysfunctional cortico-striato-thalamic-cortical loops. In addition to the characteristic motor symptoms, PD patients often show cognitive impairments, affective changes and other non-motor symptoms, suggesting system-wide effects on brain function. Here, we used functional magnetic resonance imaging and graph-theory based analysis methods to investigate altered whole-brain intrinsic functional connectivity in PD patients (n = 37) compared to healthy controls (n = 20). Global network properties indicated less efficient processing in PD. Analysis of brain network modules pointed to increased connectivity within the sensorimotor network, but decreased interaction of the visual network with other brain modules. We found lower connectivity mainly between the cuneus and the ventral caudate, medial orbitofrontal cortex and the temporal lobe. To identify regions of altered connectivity, we mapped the degree of intrinsic functional connectivity both on ROI- and on voxel-level across the brain. Compared to healthy controls, PD patients showed lower connectedness in the medial and middle orbitofrontal cortex. The degree of connectivity was also decreased in the occipital lobe (cuneus and calcarine), but increased in the superior parietal cortex, posterior cingulate gyrus, supramarginal gyrus and supplementary motor area. Our results on global network and module properties indicated that PD manifests as a disconnection syndrome. This was most apparent in the visual network module. The higher connectedness within the sensorimotor module in PD patients may be related to compensation mechanism in order to overcome the functional deficit of the striato-cortical motor loops or to loss of mutual inhibition between brain networks. Abnormal connectivity in the visual network may be related to adaptation and compensation processes as a consequence of altered motor function. Our analysis approach proved sensitive for detecting disease-related localized effects as well as changes in network functions on intermediate and global scale.

Dissociations between spatial-attentional processes within parietal cortex: insights from hybrid spatial cueing and change detection paradigms

Spatial cueing has been used by many different groups under multiple forms to study spatial attention processes. We will present evidence obtained in brain-damaged patients and healthy volunteers using a variant of this paradigm, the hybrid spatial cueing paradigm, which, besides single-target trials with valid and invalid cues, also contains trials where a target is accompanied by a contralateral competing stimulus (competition trials). This allows one to study invalidity-related processes and selection between competing stimuli within the same paradigm. In brain-damaged patients, lesions confined to the intraparietal sulcus result in contralesional attentional deficits, both during competition and invalid trials, according to a pattern that does not differ from that observed following inferior parietal lesions. In healthy volunteers, however, selection between competing stimuli and invalidity-related processes are partially dissociable, the former relying mainly on cytoarchitectonic areas hIP1-3 in the intraparietal sulcus, the latter on cytoarchitectonic area PF in the right inferior parietal lobule. The activity profile in more posterior inferior parietal areas PFm and PGa, does not distinguish between both types of trials. The functional account for right PF and adjacent areas is further constrained by the activity profile observed during other experimental paradigms. In a change detection task with variable target and distracter set size, for example, these inferior parietal areas show highest activity when the stimulus array consists of only one single target, while the intraparietal sulcus show increased activity as the array contains more targets and distracters. Together, these findings lead us to the hypothesis that right PF functions as a target singleton detector, which is activated when a target stands out from the background, referring both to the temporal background (expectancy) and the momentaneous background (stimulus-driven saliency).

Global increase in task-related fronto-parietal activity after focal frontal lobe lesion

A critical question for neuropsychology is how complex brain networks react to damage. Here, we address this question for the well-known executive control or multiple-demand (MD) system, a fronto-parietal network showing increased activity with many different kinds of cognitive demand, including standard tests of fluid intelligence. Using fMRI, we ask how focal frontal lobe damage affects MD activity during a standard fluid intelligence task. Despite poor behavioral performance, frontal patients showed increased fronto-parietal activity relative to controls. The activation difference was not accounted for by difference in IQ. Moreover, rather than specific focus on perilesional or contralesional cortex, additional recruitment was distributed throughout the MD regions and surrounding cortex and included parietal MD regions distant from the injury. The data suggest that, following local frontal lobe damage, there is a global compensatory recruitment of an adaptive and integrated fronto-parietal network.

Local polymorphic delta activity in cortical lesions causes global decreases in functional connectivity

Increasing evidence from neuroimaging and modeling studies suggests that local lesions can give rise to global network changes in the human brain. These changes are often attributed to the disconnection of the lesioned areas. However, damaged brain areas may still be active, although the activity is altered. Here, we hypothesize that empirically observed global decreases in functional connectivity in patients with brain lesions can be explained by specific alterations of local neural activity that are the result of damaged tissue. We simulated local polymorphic delta activity (PDA), which typically characterizes EEG/MEG recordings of patients with cerebral lesions, in a realistic model of human brain activity. 78 neural masses were coupled according to the human structural brain network. Lesions were created by altering the parameters of individual neural masses in order to create PDA (i.e. simulating acute focal brain damage); combining this PDA with weakening of structural connections (i.e. simulating brain tumors), and fully deleting structural connections (i.e. simulating a full resection). Not only structural disconnection but also PDA in itself caused a global decrease in functional connectivity, similar to the observed alterations in MEG recordings of patients with PDA due to brain lesions. Interestingly, connectivity between regions that were not lesioned directly also changed. The impact of PDA depended on the network characteristics of the lesioned region in the structural connectome. This study shows for the first time that locally disturbed neural activity, i.e. PDA, may explain altered functional connectivity between remote areas, even when structural connections are unaffected. We suggest that focal brain lesions and the corresponding altered neural activity should be considered in the framework of the full functionally interacting brain network, implying that the impact of lesions reaches far beyond focal damage.

Frontoparietal Traffic Signals: A Fast Optical Imaging Study of Preparatory Dynamics in Response Mode Switching

Coordination between networks of brain regions is important for optimal cognitive performance, especially in attention demanding tasks. With the event-related optical signal (a measure of changes in optical scattering because of neuronal activity) we can characterize rapidly evolving network processes by examining the millisecond-scale temporal correlation of activity in distinct regions during the preparatory period of a response mode switching task. Participants received a precue indicating whether to respond vocally or manually. They then saw or heard the letter “L” or “R,” indicating a “left” or “right” response to be implemented with the appropriate response modality. We employed lagged cross-correlations to characterize the dynamic connectivity of preparatory processes. Our results confirmed coupling of frontal and parietal cortices and the trial-dependent relationship of the right frontal cortex with response preparation areas. The frontal-to-modality-specific cortex cross-correlations revealed a pattern in which first irrelevant regions were deactivated, and then relevant regions were activated. These results provide a window into the subsecond scale network interactions that flexibly tune to task demands.

Long-term cognitive impairment after first-ever ischemic stroke in young adults

BACKGROUND AND PURPOSE

Up to 14% of all ischemic strokes occur in young adults (<50 years). Poststroke cognitive performance is a decisive determinant of their quality of life. However, virtually no studies report on cognition after young stroke, especially not on the long term. This long-term perspective is important because young patients have a long life expectancy during which they start forming a family, have an active social life, and make decisive career moves. We aimed to evaluate the long-term cognitive outcome.

METHODS

All consecutive patients between January 1, 1980, and November 1, 2010, with a first-ever young ischemic stroke were recruited for cognitive assessment, using a matched stroke-free population as a reference. Composite Z scores for 7 cognitive domains were calculated and the ANCOVA model was used (Bonferroni correction). A below average performance was defined as >1.0 SD below the age-adjusted mean of the controls and cognitive impairment as >1.5 SD.

RESULTS

Two hundred seventy-seven patients and 146 matched controls completed cognitive assessment (mean follow-up, 11.0 years, SD, 8.2; age, 50.9 years, SD, 10.3). Long-term cognitive outcome after an ischemic stroke was worse in most cognitive domains compared with a nonstroke population. Up to 50% of the patients had a below average performance or cognitive impairment. Deficits in processing speed, working memory, and attention were most common.

CONCLUSIONS

Even 11 years after ischemic stroke in young adults, a substantial proportion of patients must cope with permanent cognitive deficits. These results have implications for information given to patients and rehabilitation services.

Traumatic brain injury impairs small-world topology

OBJECTIVE

We test the hypothesis that brain networks associated with cognitive function shift away from a "small-world" organization following traumatic brain injury (TBI).

METHODS

We investigated 20 TBI patients and 21 age-matched controls. Resting-state functional MRI was used to study functional connectivity. Graph theoretical analysis was then applied to partial correlation matrices derived from these data. The presence of white matter damage was quantified using diffusion tensor imaging.

RESULTS

Patients showed characteristic cognitive impairments as well as evidence of damage to white matter tracts. Compared to controls, the graph analysis showed reduced overall connectivity, longer average path lengths, and reduced network efficiency. A particular impact of TBI is seen on a major network hub, the posterior cingulate cortex. Taken together, these results confirm that a network critical to cognitive function shows a shift away from small-world characteristics.

CONCLUSIONS

We provide evidence that key brain networks involved in supporting cognitive function become less small-world in their organization after TBI. This is likely to be the result of diffuse white matter damage, and may be an important factor in producing cognitive impairment after TBI.

Diffuse reduction of white matter connectivity in cerebral palsy with specific vulnerability of long range fiber tracts

Cerebral palsy (CP) is a heterogeneous group of non-progressive motor disorders caused by injury to the developing fetal or infant brain. Although the defining feature of CP is motor impairment, numerous other neurodevelopmental disabilities are associated with CP and contribute greatly to its morbidity. The relationship between brain structure and neurodevelopmental outcomes in CP is complex, and current evidence suggests that motor and developmental outcomes are related to the spatial pattern and extent of brain injury. Given that multiple disabilities are frequently associated with CP, and that there is increasing burden of neurodevelopmental disability with increasing motor severity, global white matter (WM) connectivity was examined in a cohort of 17 children with bilateral CP to test the hypothesis that increased global WM damage will be seen in the group of severely affected (Gross Motor Function Classification Scale (GMFCS) level of IV) as compared to moderately affected (GMFCS of II or III) individuals. Diffusion tensor tractography was performed and the resulting fibers between anatomically defined brain regions were quantified and analyzed in relation to GMFCS levels. Overall, a reduction in total WM connectivity throughout the brain in severe versus moderate CP was observed, including but not limited to regions associated with the sensorimotor system. Our results also show a diffuse and significant reduction in global inter-regional connectivity between severity groups, represented by inter-regional fiber count, throughout the brain. Furthermore, it was also observed that there is a significant difference (p = 0.02) in long-range connectivity in patients with severe CP as compared to those with moderate CP, whereas short-range connectivity was similar between groups. This new finding, which has not been previously reported in the CP literature, demonstrates that CP may involve distributed, network-level structural disruptions.

Single-subject grey matter graphs in Alzheimer's disease

Coordinated patterns of cortical morphology have been described as structural graphs and previous research has demonstrated that properties of such graphs are altered in Alzheimer's disease (AD). However, it remains unknown how these alterations are related to cognitive deficits in individuals, as such graphs are restricted to group-level analysis. In the present study we investigated this question in single-subject grey matter networks. This new method extracts large-scale structural graphs where nodes represent small cortical regions that are connected by edges when they show statistical similarity. Using this method, unweighted and undirected networks were extracted from T1 weighted structural magnetic resonance imaging scans of 38 AD patients (19 female, average age 72±4 years) and 38 controls (19 females, average age 72±4 years). Group comparisons of standard graph properties were performed after correcting for grey matter volumetric measurements and were correlated to scores of general cognitive functioning. AD networks were characterised by a more random topology as indicated by a decreased small world coefficient (p = 3.53×10(-5)), decreased normalized clustering coefficient (p = 7.25×10(-6)) and decreased normalized path length (p = 1.91×10(-7)). Reduced normalized path length explained significantly (p = 0.004) more variance in measurements of general cognitive decline (32%) in comparison to volumetric measurements (9%). Altered path length of the parahippocampal gyrus, hippocampus, fusiform gyrus and precuneus showed the strongest relationship with cognitive decline. The present results suggest that single-subject grey matter graphs provide a concise quantification of cortical structure that has clinical value, which might be of particular importance for disease prognosis. These findings contribute to a better understanding of structural alterations and cognitive dysfunction in AD.

Network reconfiguration and working memory impairment in mesial temporal lobe epilepsy

Mesial temporal lobe epilepsy (mTLE) is the most prevalent form of focal epilepsy, and hippocampal sclerosis (HS) is considered the most frequent associated pathological finding. Recent connectivity studies have shown that abnormalities, either structural or functional, are not confined to the affected hippocampus, but can be found in other connected structures within the same hemisphere, or even in the contralesional hemisphere. Despite the role of hippocampus in memory functions, most of these studies have explored network properties at resting state, and in some cases compared connectivity values with neuropsychological memory scores. Here, we measured magnetoencephalographic responses during verbal working memory (WM) encoding in left mTLE patients and controls, and compared their effective connectivity within a frontotemporal network using dynamic causal modelling. Bayesian model comparison indicated that the best model included bilateral, forward and backward connections, linking inferior temporal cortex (ITC), inferior frontal cortex (IFC), and the medial temporal lobe (MTL). Test for differences in effective connectivity revealed that patients exhibited decreased ipsilesional MTL-ITC backward connectivity, and increased bidirectional IFC-MTL connectivity in the contralesional hemisphere. Critically, a negative correlation was observed between these changes in patients, with decreases in ipsilesional coupling among temporal sources associated with increases contralesional frontotemporal interactions. Furthermore, contralesional frontotemporal interactions were inversely related to task performance and level of education. The results demonstrate that unilateral sclerosis induced local and remote changes in the dynamic organization of a distributed network supporting verbal WM. Crucially, pre-(peri) morbid factors (educational level) were reflected in both cognitive performance and (putative) compensatory changes in physiological coupling.

The human functional brain network demonstrates structural and dynamical resilience to targeted attack

In recent years, the field of network science has enabled researchers to represent the highly complex interactions in the brain in an approachable yet quantitative manner. One exciting finding since the advent of brain network research was that the brain network can withstand extensive damage, even to highly connected regions. However, these highly connected nodes may not be the most critical regions of the brain network, and it is unclear how the network dynamics are impacted by removal of these key nodes. This work seeks to further investigate the resilience of the human functional brain network. Network attack experiments were conducted on voxel-wise functional brain networks and region-of-interest (ROI) networks of 5 healthy volunteers. Networks were attacked at key nodes using several criteria for assessing node importance, and the impact on network structure and dynamics was evaluated. The findings presented here echo previous findings that the functional human brain network is highly resilient to targeted attacks, both in terms of network structure and dynamics.

Network attributes for segregation and integration in the human brain

Network studies of large-scale brain connectivity have begun to reveal attributes that promote the segregation and integration of neural information: communities and hubs. Network communities are sets of regions that are strongly interconnected among each other while connections between members of different communities are less dense. The clustered connectivity of network communities supports functional segregation and specialization. Network hubs link communities to one another and ensure efficient communication and information integration. This review surveys a number of recent reports on network communities and hubs, and their role in integrative processes. An emerging focus is the shifting balance between segregation and integration over time, which manifest in continuously changing patterns of functional interactions between regions, circuits and systems.

Analyzing complex functional brain networks: Fusing statistics and network science to understand the brain*†

Complex functional brain network analyses have exploded over the last decade, gaining traction due to their profound clinical implications. The application of network science (an interdisciplinary offshoot of graph theory) has facilitated these analyses and enabled examining the brain as an integrated system that produces complex behaviors. While the field of statistics has been integral in advancing activation analyses and some connectivity analyses in functional neuroimaging research, it has yet to play a commensurate role in complex network analyses. Fusing novel statistical methods with network-based functional neuroimage analysis will engender powerful analytical tools that will aid in our understanding of normal brain function as well as alterations due to various brain disorders. Here we survey widely used statistical and network science tools for analyzing fMRI network data and discuss the challenges faced in filling some of the remaining methodological gaps. When applied and interpreted correctly, the fusion of network scientific and statistical methods has a chance to revolutionize the understanding of brain function.

Connectivity in MEG resting-state networks increases after resective surgery for low-grade glioma and correlates with improved cognitive performance

Purpose

Low-grade glioma (LGG) patients often have cognitive deficits. Several disease- and treatment related factors affect cognitive processing. Cognitive outcome of resective surgery is unpredictable, both for improvement and deterioration, especially for complex domains such as attention and executive functioning. MEG analysis of resting-state networks (RSNs) is a good candidate for presurgical prediction of cognitive outcome. In this study, we explore the relation between alterations in connectivity of RSNs and changes in cognitive processing after resective surgery, as a stepping stone to ultimately predict postsurgical cognitive outcome.

Methods

Ten patients with LGG were included, who had no adjuvant therapy. MEG recording and neuropsychological assessment were obtained before and after resective surgery. MEG data were recorded during a no-task eyes-closed condition, and projected to the anatomical space of the AAL atlas. Alterations in functional connectivity, as characterized by the phase lag index (PLI), within the default mode network (DMN), executive control network (ECN), and left- and right-sided frontoparietal networks (FPN) were compared to cognitive changes.

Results

Lower alpha band DMN connectivity was increased after surgery, and this increase was related to improved verbal memory functioning. Similarly, right FPN connectivity was increased after resection in the upper alpha band, which correlated with improved attention, working memory and executive functioning.

Discussion

Increased alpha band RSN functional connectivity in MEG recordings correlates with improved cognitive outcome after resective surgery. The mechanisms resulting in functional connectivity alterations after resection remain to be elucidated. Importantly, our findings indicate that connectivity of MEG RSNs may be used for presurgical prediction of cognitive outcome in future studies.

Intrinsic architecture underlying the relations among the default, dorsal attention, and frontoparietal control networks of the human brain

Human cognition is increasingly characterized as an emergent property of interactions among distributed, functionally specialized brain networks. We recently demonstrated that the antagonistic "default" and "dorsal attention" networks--subserving internally and externally directed cognition, respectively--are modulated by a third "frontoparietal control" network that flexibly couples with either network depending on task domain. However, little is known about the intrinsic functional architecture underlying this relationship. We used graph theory to analyze network properties of intrinsic functional connectivity within and between these three large-scale networks. Task-based activation from three independent studies were used to identify reliable brain regions ("nodes") of each network. We then examined pairwise connections ("edges") between nodes, as defined by resting-state functional connectivity MRI. Importantly, we used a novel bootstrap resampling procedure to determine the reliability of graph edges. Furthermore, we examined both full and partial correlations. As predicted, there was a higher degree of integration within each network than between networks. Critically, whereas the default and dorsal attention networks shared little positive connectivity with one another, the frontoparietal control network showed a high degree of between-network interconnectivity with each of these networks. Furthermore, we identified nodes within the frontoparietal control network of three different types--default-aligned, dorsal attention-aligned, and dual-aligned--that we propose play dissociable roles in mediating internetwork communication. The results provide evidence consistent with the idea that the frontoparietal control network plays a pivotal gate-keeping role in goal-directed cognition, mediating the dynamic balance between default and dorsal attention networks.

Cognitive dysfunction in early multiple sclerosis: altered centrality derived from resting-state functional connectivity using magneto-encephalography

BACKGROUND

Cognitive dysfunction in multiple sclerosis (MS) is frequent. Insight into underlying mechanisms would help to develop therapeutic strategies.

OBJECTIVE

To explore the relationship of cognitive performance to patterns of nodal centrality derived from magneto-encephalography (MEG).

METHODS

34 early relapsing-remitting MS patients (median EDSS 2.0) and 28 age- and gender-matched healthy controls (HC) had a MEG, a neuropsychological assessment and structural MRI. Resting-state functional connectivity was determined by the synchronization likelihood. Eigenvector Centrality (EC) was used to quantify for each sensor its connectivity and importance within the network. A cognition-score was calculated, and normalized grey and white matter volumes were determined. EC was compared per sensor and frequency band between groups using permutation testing, and related to cognition.

RESULTS

Patients had lower grey and white matter volumes than HC, male patients lower cognitive performance than female patients. In HC, EC distribution showed highest nodal centrality over bi-parietal sensors ("hubs"). In patients, nodal centrality was even higher bi-parietally (theta-band) but markedly lower left temporally (upper alpha- and beta-band). Lower cognitive performance correlated to decreased nodal centrality over left temporal (lower alpha-band) and right temporal (beta-band) sensors, and to increased nodal centrality over right parieto-temporal sensors (beta-band). Network changes were most pronounced in male patients.

CONCLUSIONS

Partial functional disconnection of the temporal regions was associated with cognitive dysfunction in MS; increased centrality in parietal hubs may reflect a shift from temporal to possibly less efficient parietal processing. To better understand patterns and dynamics of these network changes, longitudinal studies are warranted, also addressing the influence of gender.