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

Abstract

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...

The canonical semantic network supports residual language function in chronic post‐stroke aphasia

“…This interpretation is consistent with evidence that the abrupt and catastrophic disruption of neural function by stroke leads to widespread disruptions of communication and regulation in distributed brain networks [Baldassarre et al, 2016; Geranmayeh et al, 2016; He et al, 2007; Ovadia-Caro et al, 2013; Siegel et al, 2016], and that the preservation/restoration of typical function in canonical language networks is indicative of successful language recovery [Heiss et al, 1999; Saur et al, 2006]. Indeed, post-stroke deficits in complex cognitive functions [Siegel et al, 2016] that include language [Geranmayeh et al, 2016] and attention [Baldassarre et al, 2016; He et al, 2007] may be conceptualized as behavioral manifestations of dysfunction in large-scale functional brain networks.…”

“…Indeed, post-stroke deficits in complex cognitive functions [Siegel et al, 2016] that include language [Geranmayeh et al, 2016] and attention [Baldassarre et al, 2016; He et al, 2007] may be conceptualized as behavioral manifestations of dysfunction in large-scale functional brain networks. Along these lines, optimal functional recovery after stroke may depend on the preservation/restoration of functional dynamics that most strongly resembles those observed in the pre-stroke brain [Carter et al, 2012].…”

Important considerations in lesion‐symptom mapping: Illustrations from studies of word comprehension

“…A recent study indicates that for mapping language, resting state connectivity between homologous regions can also complement information from the lesion itself in predicting task performance, although the same was not found for mapping motor function [Siegel et al, 2016]. …”

Characterizing Attention with Predictive Network Models

“…Finally, because network models offer objective measures of attention, they may be useful in clinical contexts [82,83]. They could, for example, be used to identify children at risk of developing attention problems for early intervention, match individuals to the most appropriate attention training or treatment, and track changes in attentional state or attention-related symptoms over time (Box 2).…”