The Role of Extra-motor Networks in Upper Limb Motor Performance Post-stroke.

BACKGROUND: Motor improvement post-stroke may happen even if resting state functional connectivity between the ipsilesional and contralesional components of the sensorimotor network is not fully recovered. Therefore, we investigated which extra-motor networks might support upper limb motor gains in response to treatment post-stroke. METHODS: Both resting state functional connectivity and upper limb capacity were measured prior to and after an 8-week intervention of task-specific training in 29 human participants [59.24 ± (SD) 10.40 yrs., 12 females and 17 males] with chronic stroke. The sensorimotor and five extra-motor networks were defined: default mode, frontoparietal, cingulo-opercular, dorsal attention network, and salience networks. The Network Level Analysis toolbox was used to identify network pairs whose connectivities were enriched in connectome-behavior relationships. RESULTS: Mean upper limb capacity score increased 5.45 ± (SD) 5.55 following treatment. Baseline connectivity of some motor but mostly extra-motor network interactions of cingulo-opercular and default-mode networks were predictive of upper limb capacity following treatment. Also, changes in connectivity for extra-motor interactions of salience with default mode, cingulo-opercular, and dorsal attention networks were correlated with gains in upper limb capacity. CONCLUSIONS: These connectome-behavior patterns suggest larger involvement of cingulo-opercular networks in prediction of treatment response and of salience networks in maintenance of improved skilled behavior. These results support our hypothesis that cognitive networks may contribute to recovery of motor performance after stroke and provide additional insights into the neural correlates of intensive training.

White matter integrity of contralesional and transcallosal tracts may predict response to upper limb task-specific training in chronic stroke.

OBJECTIVE: To investigate white matter (WM) plasticity induced by intensive upper limb (UL) task specific training (TST) in chronic stroke. METHODS: Diffusion tensor imaging data and UL function measured by the Action Research Arm Test (ARAT) were collected in 30 individuals with chronic stroke prior to and after intensive TST. ANOVAs tested the effects of training on the entire sample and on the Responders [ΔARAT ≥ 5.8, N = 13] and Non-Responders [ΔARAT < 5.8, N = 17] groups. Baseline fractional anisotropy (FA) values were correlated with ARATpost TST controlling for baseline ARAT and age to identify voxels predictive of response to TST. RESULTS: While ARAT scores increased following training (p < 0.0001), FA changes within major WM tracts were not significant at p < 0.05. In the Responder group, larger baseline FA of both contralesional (CL) and transcallosal tracts predicted larger ARAT scores post-TST. Subcortical lesions and more severe damage to transcallosal tracts were more pronounced in the Non-Responder than in the Responder group. CONCLUSIONS: The motor improvements post-TST in the Responder group may reflect the engagement of interhemispheric processes not available to the Non-Responder group. Future studies should clarify differences in the role of CL and transcallosal pathways as biomarkers of recovery in response to training for individuals with cortical and subcortical stroke. This knowledge may help to identify sources of heterogeneity in stroke recovery, which is necessary for the development of customized rehabilitation interventions.

A Novel Gradient Echo Plural Contrast Imaging Method Detects Brain Tissue Abnormalities in Patients With TBI Without Evident Anatomical Changes on Clinical MRI: A Pilot Study.

RESEARCH OBJECTIVES: It is widely accepted that mild traumatic brain injury (mTBI) causes injury to the white matter, but the extent of gray matter (GM) damage in mTBI is less clear. METHODS: We tested 26 civilian healthy controls and 14 civilian adult subacute-chronic mTBI patients using quantitative features of MRI-based Gradient Echo Plural Contrast Imaging (GEPCI) technique. GEPCI data were reconstructed using previously developed algorithms allowing the separation of R2t*, a cellular-specific part of gradient echo MRI relaxation rate constant, from global R2* affected by BOLD effect and background gradients. RESULTS: Single-subject voxel-wise analysis (comparing each mTBI patient to the sample of 26 control subjects) revealed GM abnormalities that were not visible on standard MRI images (T1w and T2w). Analysis of spatial overlap for voxels with low R2t* revealed tissue abnormalities in multiple GM regions, especially in the frontal and temporal regions, that are frequently damaged after mTBI. The left posterior insula was the region with abnormalities found in the highest proportion (50%) of mTBI patients. CONCLUSIONS: Our data suggest that GEPCI quantitative R2t* metric has potential to detect abnormalities in GM cellular integrity in individual TBI patients, including abnormalities that are not detectable by a standard clinical MRI.

Normalization of network connectivity in hemispatial neglect recovery.

OBJECTIVE: We recently reported that spatial and nonspatial attention deficits in stroke patients with hemispatial neglect are correlated at 2 weeks postonset with widespread alterations of interhemispheric and intrahemispheric functional connectivity (FC) measured with resting-state functional magnetic resonance imaging across multiple brain networks. The mechanisms underlying neglect recovery are largely unknown. In this study, we test the hypothesis that recovery of hemispatial 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 months (n = 64) postonset. The relationship between behavioral improvement and changes in FC was analyzed both in terms of a priori regions and networks known to be abnormal subacutely 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 interhemispheric FC across attention, sensory, and motor networks, and a restoration of the normal anticorrelation between dorsal attention/motor regions and default-mode/frontoparietal regions, particularly in the damaged hemisphere. INTERPRETATION: These results demonstrate that abnormal network connectivity in hemispatial 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. Ann Neurol 2016;80:127-141.

Exploring the physiological correlates of chronic mild traumatic brain injury symptoms.

We report on the results of a multimodal imaging study involving behavioral assessments, evoked and resting-state BOLD fMRI, and DTI in chronic mTBI subjects. We found that larger task-evoked BOLD activity in the MT+/LO region in extra-striate visual cortex correlated with mTBI and PTSD symptoms, especially light sensitivity. Moreover, higher FA values near the left optic radiation (OR) were associated with both light sensitivity and higher BOLD activity in the MT+/LO region. The MT+/LO region was localized as a region of abnormal functional connectivity with central white matter regions previously found to have abnormal physiological signals during visual eye movement tracking (Astafiev et al., 2015). We conclude that mTBI symptoms and light sensitivity may be related to excessive responsiveness of visual cortex to sensory stimuli. This abnormal sensitivity may be related to chronic remodeling of white matter visual pathways acutely injured.

Common behavioral clusters and subcortical anatomy in stroke.

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.