Re-emergence of modular brain networks in stroke recovery

Abstract

Studies of stroke have identified local reorganization in perilesional tissue. However, because the brain is highly networked, strokes also broadly alter the brain's global network organization. Here, we assess brain network structure longitudinally in adult stroke patients using resting state fMRI. The topology and boundaries of cortical regions remain grossly unchanged across recovery. In contrast, the modularity of brain systems i.e. the degree of integration within and segregation between networks, was significantly reduced sub-acutely (n = 107), but partially recovered by 3 months (n = 85), and 1 year (n = 67). Importantly, network recovery correlated with recovery from language, spatial memory, and attention deficits, but not motor or visual deficits. Finally, in-depth single subject analyses were conducted using tools for visualization of changes in brain networks over time. This exploration indicated that changes in modularity during successful recovery reflect specific alterations in the relationships between different networks. For example, in a patient with left temporo-parietal stroke and severe aphasia, sub-acute loss of modularity reflected loss of association between frontal and temporo-parietal regions bi-hemispherically across multiple modules. These long-distance connections then returned over time, paralleling aphasia recovery. This work establishes the potential importance of normalization of large-scale modular brain systems in stroke recovery.

A set of functionally-defined brain regions with improved representation of the subcortex and cerebellum

“…These studies have examined both structural and functional network organization in a wide variety of samples, including healthy young adults (Power et al, 2013;Zanto and Gazzaley, 2013), developmental cohorts (Gu et al, 2015;Nielsen et al, 2018;Rudolph et al, 2017), older adults (Baniqued et al, 2018;Gallen et al, 2016), and a plethora of neurological and psychiatric populations (Gratton et al, 2018a;Greene et al, 2016;Sheffield et al, 2015;Siegel et al, 2018). We have gained a better understanding of typical and atypical human brain organization from these efforts.…”

“…These two ROI sets sample the cortex well, representing a diverse set of brain areas that can be organized into functional networks. Many investigators have used them to describe functional brain organization in a variety of healthy samples (Power et al, 2013;Zanto and Gazzaley, 2013), lifespan cohorts (Baniqued et al, 2018;Gallen et al, 2016;Gu et al, 2015;Nielsen et al, 2018;Rudolph et al, 2017), as well as populations with neurologic and psychiatric diseases (Gratton et al, 2018a;Greene et al, 2016;Sheffield et al, 2015;Siegel et al, 2018). However, the first set (264 volumetric ROIs) under-samples subcortical and cerebellar structures, as only 17 ROIs are non-cortical, and the second set (333 parcels) is restricted to the cortex only, similar to other popular ROI sets, e.g.…”

Structural disconnections explain brain network dysfunction after stroke

“…Focal brain lesions cause dysfunction in distributed brain systems. Functional connectivity (FC), which measures the correlation between spontaneous activity fluctuations in remote brain regions (Biswal et al, 1995), has recently been used to identify several systems-scale abnormalities that predict behavioral impairment after stroke (Baldassarre et al, 2016a;Corbetta et al, 2018): reduced interhemispheric system integration (Bauer et al, 2014;Carter et al, 2010;Golestani et al, 2013;He et al, 2007;Lim et al, 2014;van Meer et al, 2012;New et al, 2015;Park et al, 2011;Siegel et al, 2016;Tang et al, 2016;Wang et al, 2010;Wu et al, 2011), reduced ipsilesional system segregation (Baldassarre et al, 2014;Bauer et al, 2012;Eldaief et al, 2016;Ramsey et al, 2016), reduced system modularity (Gratton et al, 2012;Siegel et al, 2018). An important next step is to characterize how the severity of these FC abnormalities depends on the properties of the focal lesion (Carrera and Tononi, 2014;Corbetta et al, 2018).…”

Alterations in brain network organization in adults with obesity as compared to healthy-weight individuals and seniors

“…This may relate to the well-known increment in the processing times and background noise that elders and subjects with obesity are lean to show in their cognitive performance (Deckers et al, 2017; Sala-Llonch et al, 2014). Also, an escalation in modularity could entail a vulnerability to cardiovascular-related disconnection syndromes (e.g., aphasia) (Siegel et al, 2018). Global and regional mean degree and strength.…”