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Joseph C. Griffis

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7 papers

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YNICL Journal 2022 Journal Article

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

Sebastian Idesis
Chiara Favaretto
Nicholas V. Metcalf
Joseph C. Griffis
Gordon L. Shulman
Maurizio Corbetta
Gustavo Deco

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.

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YNIMG Journal 2022 Journal Article

Post-stroke reorganization of transient brain activity characterizes deficits and recovery of cognitive functions

Elvira Pirondini
Nawal Kinany
Cécile Le Sueur
Joseph C. Griffis
Gordon L. Shulman
Maurizio Corbetta
Dimitri Van De Ville

Functional magnetic resonance imaging (fMRI) has been widely employed to study stroke pathophysiology. In particular, analyses of fMRI signals at rest were directed at quantifying the impact of stroke on spatial features of brain networks. However, brain networks have intrinsic time features that were, so far, disregarded in these analyses. In consequence, standard fMRI analysis failed to capture temporal imbalance resulting from stroke lesions, hence restricting their ability to reveal the interdependent pathological changes in structural and temporal network features following stroke. Here, we longitudinally analyzed hemodynamic-informed transient activity in a large cohort of stroke patients (n = 103) to assess spatial and temporal changes of brain networks after stroke. Metrics extracted from the hemodynamic-informed transient activity were replicable within- and between-individuals in healthy participants, hence supporting their robustness and their clinical applicability. While large-scale spatial patterns of brain networks were preserved after stroke, their durations were altered, with stroke subjects exhibiting a varied pattern of longer and shorter network activations compared to healthy individuals. Specifically, patients showed a longer duration in the lateral precentral gyrus and anterior cingulum, and a shorter duration in the occipital lobe and in the cerebellum. These temporal alterations were associated with white matter damage in projection and association pathways. Furthermore, they were tied to deficits in specific behavioral domains as restoration of healthy brain dynamics paralleled recovery of cognitive functions (attention, language and spatial memory), but was not significantly correlated to motor recovery. These findings underscore the critical importance of network temporal properties in dissecting the pathophysiology of brain changes after stroke, thus shedding new light on the clinical potential of time-resolved methods for fMRI analysis.

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YNICL Journal 2021 Journal Article

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

Joseph C. Griffis
Nicholas V. Metcalf
Maurizio Corbetta
Gordon L. Shulman

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.

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YNIMG Journal 2020 Journal Article

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

Joseph C. Griffis
Nicholas V. Metcalf
Maurizio Corbetta
Gordon L. Shulman

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.

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YNICL Journal 2017 Journal Article

Damage to white matter bottlenecks contributes to language impairments after left hemispheric stroke

Joseph C. Griffis
Rodolphe Nenert
Jane B. Allendorfer
Jerzy P. Szaflarski

Damage to the white matter underlying the left posterior temporal lobe leads to deficits in multiple language functions. The posterior temporal white matter may correspond to a bottleneck where both dorsal and ventral language pathways are vulnerable to simultaneous damage. Damage to a second putative white matter bottleneck in the left deep prefrontal white matter involving projections associated with ventral language pathways and thalamo-cortical projections has recently been proposed as a source of semantic deficits after stroke. Here, we first used white matter atlases to identify the previously described white matter bottlenecks in the posterior temporal and deep prefrontal white matter. We then assessed the effects of damage to each region on measures of verbal fluency, picture naming, and auditory semantic decision-making in 43 chronic left hemispheric stroke patients. Damage to the posterior temporal bottleneck predicted deficits on all tasks, while damage to the anterior bottleneck only significantly predicted deficits in verbal fluency. Importantly, the effects of damage to the bottleneck regions were not attributable to lesion volume, lesion loads on the tracts traversing the bottlenecks, or damage to nearby cortical language areas. Multivariate lesion-symptom mapping revealed additional lesion predictors of deficits. Post-hoc fiber tracking of the peak white matter lesion predictors using a publicly available tractography atlas revealed evidence consistent with the results of the bottleneck analyses. Together, our results provide support for the proposal that spatially specific white matter damage affecting bottleneck regions, particularly in the posterior temporal lobe, contributes to chronic language deficits after left hemispheric stroke. This may reflect the simultaneous disruption of signaling in dorsal and ventral language processing streams.

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YNIMG Journal 2017 Journal Article

Retinotopic patterns of functional connectivity between V1 and large-scale brain networks during resting fixation

Joseph C. Griffis
Abdurahman S. Elkhetali
Wesley K. Burge
Richard H. Chen
Anthony D. Bowman
Jerzy P. Szaflarski
Kristina M. Visscher

Psychophysical and neurobiological evidence suggests that central and peripheral vision are specialized for different functions. This specialization of function might be expected to lead to differences in the large-scale functional interactions of early cortical areas that represent central and peripheral visual space. Here, we characterize differences in whole-brain functional connectivity among sectors in primary visual cortex (V1) corresponding to central, near-peripheral, and far-peripheral vision during resting fixation. Importantly, our analyses reveal that eccentricity sectors in V1 have different functional connectivity with non-visual areas associated with large-scale brain networks. Regions associated with the fronto-parietal control network are most strongly connected with central sectors of V1, regions associated with the cingulo-opercular control network are most strongly connected with near-peripheral sectors of V1, and regions associated with the default mode and auditory networks are most strongly connected with far-peripheral sectors of V1. Additional analyses suggest that similar patterns are present during eyes-closed rest. These results suggest that different types of visual information may be prioritized by large-scale brain networks with distinct functional profiles, and provide insights into how the small-scale functional specialization within early visual regions such as V1 relates to the large-scale organization of functionally distinct whole-brain networks.

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YNIMG Journal 2015 Journal Article

Distinct effects of trial-driven and task Set-related control in primary visual cortex

Joseph C. Griffis
Abdurahman S. Elkhetali
Ryan J. Vaden
Kristina M. Visscher

Task sets are task-specific configurations of cognitive processes that facilitate task-appropriate reactions to stimuli. While it is established that the trial-by-trial deployment of visual attention to expected stimuli influences neural responses in primary visual cortex (V1) in a retinotopically specific manner, it is not clear whether the mechanisms that help maintain a task set over many trials also operate with similar retinotopic specificity. Here, we address this question by using BOLD fMRI to characterize how portions of V1 that are specialized for different eccentricities respond during distinct components of an attention-demanding discrimination task: cue-driven preparation for a trial, trial-driven processing, task-initiation at the beginning of a block of trials, and task-maintenance throughout a block of trials. Tasks required either unimodal attention to an auditory or a visual stimulus or selective intermodal attention to the visual or auditory component of simultaneously presented visual and auditory stimuli. We found that while the retinotopic patterns of trial-driven and cue-driven activity depended on the attended stimulus, the retinotopic patterns of task-initiation and task-maintenance activity did not. Further, only the retinotopic patterns of trial-driven activity were found to depend on the presence of inter-modal distraction. Participants who performed well on the intermodal selective attention tasks showed strong task-specific modulations of both trial-driven and task-maintenance activity. Importantly, task-related modulations of trial-driven and task-maintenance activity were in opposite directions. Together, these results confirm that there are (at least) two different processes for top-down control of V1: One, working trial-by-trial, differently modulates activity across different eccentricity sectors – portions of V1 corresponding to different visual eccentricities. The second process works across longer epochs of task performance, and does not differ among eccentricity sectors. These results are discussed in the context of previous literature examining top-down control of visual cortical areas.

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