Language Recovery after Brain Injury: A Structural Network Control Theory Study.

Aphasia recovery after stroke depends on the condition of the remaining, extralesional brain network. Network control theory (NCT) provides a unique, quantitative approach to assess the interaction between brain networks. In this longitudinal, large-scale, whole-brain connectome study, we evaluated whether controllability measures of language-related regions are associated with treated aphasia recovery. Using probabilistic tractography and controlling for the effects of structural lesions, we reconstructed whole-brain diffusion tensor imaging (DTI) connectomes from 68 individuals (20 female, 48 male) with chronic poststroke aphasia who completed a three-week language therapy. Applying principles of NCT, we computed regional (1) average and (2) modal controllability, which decode the ability of a region to (1) spread control input through the brain network and (2) to facilitate brain state transitions. We tested the relationship between pretreatment controllability measures of 20 language-related left hemisphere regions and improvements in naming six months after language therapy using multiple linear regressions and a parsimonious elastic net regression model with cross-validation. Regional controllability of the inferior frontal gyrus (IFG) pars opercularis, pars orbitalis, and the anterior insula were associated with treatment outcomes independently of baseline aphasia severity, lesion volume, age, education, and network size. Modal controllability of the IFG pars opercularis was the strongest predictor of treated aphasia recovery with cross-validation and outperformed traditional graph theory, lesion load, and demographic measures. Regional NCT measures can reflect the status of the residual language network and its interaction with the remaining brain network, being able to predict language recovery after aphasia treatment.SIGNIFICANCE STATEMENT Predicting and understanding language recovery after brain injury remains a challenging, albeit a fundamental aspect of human neurology and neuroscience. In this study, we applied network control theory (NCT) to fully harness the concept of brain networks as dynamic systems and to evaluate their interaction. We studied 68 stroke survivors with aphasia who underwent imaging and longitudinal behavioral assessments coupled with language therapy. We found that the controllability of the inferior frontal regional network significantly predicted recovery in language production six months after treatment. Importantly, controllability outperformed traditional demographic, lesion, and graph-theoretical measures. Our findings shed light on the neurobiological basis of human language and can be translated into personalized rehabilitation approaches.

Deep Learning for Daily Monitoring of Parkinson's Disease Outside the Clinic Using Wearable Sensors.

Now that wearable sensors have become more commonplace, it is possible to monitor individual healthcare-related activity outside the clinic, unleashing potential for early detection of events in diseases such as Parkinson's disease (PD). However, the unsupervised and "open world" nature of this type of data collection make such applications difficult to develop. In this proof-of-concept study, we used inertial sensor data from Verily Study Watches worn by individuals for up to 23 h per day over several months to distinguish between seven subjects with PD and four without. Since motor-related PD symptoms such as bradykinesia and gait abnormalities typically present when a PD subject is walking, we initially used human activity recognition (HAR) techniques to identify walk-like activity in the unconstrained, unlabeled data. We then used these "walk-like" events to train one-dimensional convolutional neural networks (1D-CNNs) to determine the presence of PD. We report classification accuracies near 90% on single 5-s walk-like events and 100% accuracy when taking the majority vote over single-event classifications that span a duration of one day. Though based on a small cohort, this study shows the feasibility of leveraging unconstrained wearable sensor data to accurately detect the presence or absence of PD.

Long-range fibre damage in small vessel brain disease affects aphasia severity.

We sought to determine the underlying pathophysiology relating white matter hyperintensities to chronic aphasia severity. We hypothesized that: (i) white matter hyperintensities are associated with damage to fibres of any length, but to a higher percentage of long-range compared to mid- and short-range intracerebral white matter fibres; and (ii) the number of long-range fibres mediates the relationship between white matter hyperintensities and chronic post-stroke aphasia severity. We measured the severity of periventricular and deep white matter hyperintensities and calculated the number and percentages of short-, mid- and long-range white matter fibres in 48 individuals with chronic post-stroke aphasia. Correlation and mediation analyses were performed to assess the relationship between white matter hyperintensities, connectome fibre-length measures and aphasia severity as measured with the aphasia quotient of the Western Aphasia Battery-Revised (WAB-AQ). We found that more severe periventricular and deep white matter hyperintensities correlated with a lower proportion of long-range fibres (r = -0.423, P = 0.003 and r = -0.315, P = 0.029, respectively), counterbalanced by a higher proportion of short-range fibres (r = 0.427, P = 0.002 and r = 0.285, P = 0.050, respectively). More severe periventricular white matter hyperintensities also correlated with a lower proportion of mid-range fibres (r = -0.334, P = 0.020), while deep white matter hyperintensities did not correlate with mid-range fibres (r = -0.169, P = 0.250). Mediation analyses revealed: (i) a significant total effect of periventricular white matter hyperintensities on WAB-AQ (standardized beta = -0.348, P = 0.008); (ii) a non-significant direct effect of periventricular white matter hyperintensities on WAB-AQ (P > 0.05); (iii) significant indirect effects of more severe periventricular white matter hyperintensities on worse aphasia severity mediated in parallel by fewer long-range fibres (effect = -6.23, bootstrapping: standard error = 2.64, 95%CI: -11.82 to -1.56) and more short-range fibres (effect = 4.50, bootstrapping: standard error = 2.59, 95%CI: 0.16 to 10.29). We conclude that small vessel brain disease seems to affect chronic aphasia severity through a change of the proportions of long- and short-range fibres. This observation provides insight into the pathophysiology of small vessel brain disease, and its relationship with brain health and chronic aphasia severity.

Different aspects of hand grip performance associated with structural connectivity of distinct sensorimotor networks in chronic stroke.

Knowledge regarding the neural origins of distinct upper extremity impairments may guide the choice of interventions to target neural structures responsible for specific impairments. This cross-sectional pilot study investigated whether different brain networks explain distinct aspects of hand grip performance in stroke survivors. In 22 chronic stroke survivors, hand grip performance was characterized as grip strength, reaction, relaxation times, and control of grip force magnitude and direction. In addition, their brain structural connectomes were constructed from diffusion tensor MRI. Prominent networks were identified based on a two-step factor analysis using the number of streamlines among brain regions relevant to sensorimotor function. We used regression models to estimate the predictive value of sensorimotor network connectivity for hand grip performance measures while controlling for stroke lesion volumes. Each hand grip performance measure correlated with the connectivity of distinct brain sensorimotor networks. These results suggest that different brain networks may be responsible for different aspects of hand grip performance, which leads to varying clinical presentations of upper extremity impairment following stroke. Understanding the brain network correlates for different hand grip performances may facilitate the development of personalized rehabilitation interventions to directly target the responsible brain network for specific impairments in individual patients, thus improving outcomes.

The relationship between motor pathway damage and flexion-extension patterns of muscle co-excitation during walking.

Background: Mass flexion-extension co-excitation patterns during walking are often seen as a consequence of stroke, but there is limited understanding of the specific contributions of different descending motor pathways toward their control. The corticospinal tract is a major descending motor pathway influencing the production of normal sequential muscle coactivation patterns for skilled movements. However, control of walking is also influenced by non-corticospinal pathways such as the corticoreticulospinal pathway that possibly contribute toward mass flexion-extension co-excitation patterns during walking. The current study sought to investigate the associations between damage to corticospinal (CST) and corticoreticular (CRP) motor pathways following stroke and the presence of mass flexion-extension patterns during walking as evaluated using module analysis. Methods: Seventeen healthy controls and 44 stroke survivors were included in the study. We used non-negative matrix factorization for module analysis of paretic leg electromyographic activity. We typically have observed four modules during walking in healthy individuals. Stroke survivors often have less independently timed modules, for example two-modules presented as mass flexion-extension pattern. We used diffusion tensor imaging-based analysis where streamlines connecting regions of interest between the cortex and brainstem were computed to evaluate CST and CRP integrity. We also used a coarse classification tree analysis to evaluate the relative CST and CRP contribution toward module control. Results: Interhemispheric CST asymmetry was associated with worse lower extremity Fugl-Meyer score (p = 0.023), propulsion symmetry (p = 0.016), and fewer modules (p = 0.028). Interhemispheric CRP asymmetry was associated with worse lower extremity Fugl-Meyer score (p = 0.009), Dynamic gait index (p = 0.035), Six-minute walk test (p = 0.020), Berg balance scale (p = 0.048), self-selected walking speed (p = 0.041), and propulsion symmetry (p = 0.001). The classification tree model reveled that substantial ipsilesional CRP or CST damage leads to a two-module pattern and poor walking ability with a trend toward increased compensatory contralesional CRP based control. Conclusion: Both CST and CRP are involved with control of modules during walking and damage to both may lead to greater reliance on the contralesional CRP, which may contribute to a two-module pattern and be associated with worse walking performance.

Indirect White Matter Pathways Are Associated With Treated Naming Improvement in Aphasia.

BACKGROUND: White matter disconnection of language-specific brain regions associates with worse aphasia recovery. Despite a loss of direct connections, many stroke survivors may maintain indirect connections between brain regions. OBJECTIVE: To determine (1) whether preserved direct connections between language-specific brain regions relate to better poststroke naming treatment outcomes compared to no direct connections and (2) whether for individuals with a loss of direct connections, preserved indirect connections are associated with better treatment outcomes compared to individuals with no connections. METHODS: We computed structural whole-brain connectomes from 69 individuals with chronic left-hemisphere stroke and aphasia who completed a 3-week-long language treatment that was supplemented by either anodal transcranial direct current stimulation (A-tDCS) or sham stimulation (S-tDCS). We determined differences in naming improvement between individuals with direct, indirect, and no connections using 1-way analyses of covariance and multivariable linear regressions. RESULTS: Independently of tDCS modality, direct or indirect connections between the inferior frontal gyrus pars opercularis and angular gyrus were both associated with a greater increase in correct naming compared to no connections (P = .027 and P = .039, respectively). Participants with direct connections between the inferior frontal gyrus pars opercularis and middle temporal gyrus who received S-tDCS and participants with indirect connections who received A-tDCS significantly improved in naming accuracy. CONCLUSIONS: Poststroke preservation of indirect white matter connections is associated with better treated naming improvement in aphasia even when direct connections are damaged. This mechanistic information can be used to stratify and predict treated naming recovery in individuals with aphasia.

Individualized Responses to Ipsilesional High-Frequency and Contralesional Low-Frequency rTMS in Chronic Stroke: A Pilot Study to Support the Individualization of Neuromodulation for Rehabilitation.

Background: In this pilot study, we examined the effects of ipsilesional high-frequency rTMS (iHF-rTMS) and contralesional low-frequency rTMS (cLF-rTMS) applied via a double-cone coil on neurophysiological and gait variables in patients with chronic stroke. Objective/Hypothesis: To determine the group and individual level effects of two types of stimulation to better individualize neuromodulation for rehabilitation. Methods: Using a randomized, within-subject, double-blind, sham-controlled trial with 14 chronic stroke participants iHF-rTMS and cLF-rTMS were applied via a double-cone coil to the tibialis anterior cortical representation. Neurophysiological and gait variables were compared pre-post rTMS. Results: A small effect of cLF-rTMS indicated increased MEP amplitudes (Cohen's D; cLF-rTMS, d = -0.30). Group-level analysis via RMANOVA showed no significant group effects of stimulation (P > 0.099). However, secondary analyses of individual data showed a high degree of response variability to rTMS. Individual percent changes in resting motor threshold and normalized MEP latency correlated with changes in gait propulsive forces and walking speed (iHF-rTMS, nLAT:Pp, R = 0.632 P = 0.015; cLF-rTMS, rMT:SSWS, R = -0.557, P = 0.039; rMT:Pp, R = 0.718, P = 0.004). Conclusions: Changes in propulsive forces and walking speed were seen in some individuals that showed neurophysiological changes in response to rTMS. The neurological consequences of stroke are heterogeneous making a "one type fits all" approach to neuromodulation for rehabilitation unlikely. This pilot study suggests that an individual's unique response to rTMS should be considered before the application/selection of neuromodulatory therapies. Before neuromodulatory therapies can be incorporated into standard clinical practice, additional work is needed to identify biomarkers of response and how best to prescribe neuromodulation for rehabilitation for post-stroke gait.

Cardiovascular Risk Factors and Brain Health: Impact on Long-Range Cortical Connections and Cognitive Performance.

Background Cardiovascular risk factor burden in the absence of clinical or radiological "events" is associated with mild cognitive impairment. Magnetic resonance imaging techniques exploring the integrity of neuronal fiber connectivity within white matter networks supporting cognitive processing could be used to measure the impact of cardiovascular disease on brain health and be used beyond bedside neuropsychological tests to detect subclinical changes and select or stratify participants for entry into clinical trials. Methods and Results We assessed the relationship between verbal IQ and brain network integrity and the effect of cardiovascular risk factors on network integrity by constructing whole-brain structural connectomes from magnetic resonance imaging diffusion images (N=60) from people with various degrees of cardiovascular risk factor burden. We measured axonal integrity by calculating network density and determined the effect of fiber loss on network topology and efficiency, using graph theory. Multivariate analyses were used to evaluate the relationship between cardiovascular risk factor burden, physical activity, age, education, white matter integrity, and verbal IQ . Reduced network density, resulting from a disproportionate loss of long-range white matter fibers, was associated with white matter network fragmentation ( r=-0.52, P<10-4), lower global efficiency ( r=0.91, P<10-20), and decreased verbal IQ (adjusted R2=0.23, P<10-4). Conclusions Cardiovascular risk factors may mediate negative effects on brain health via loss of energy-dependent long-range white matter fibers, which in turn leads to disruption of the topological organization of the white matter networks, lowered efficiency, and reduced cognitive function.

Fibroblast growth factor23 is associated with axonal integrity and neural network architecture in the human frontal lobes.

Elevated levels of FGF23 in individuals with chronic kidney disease (CKD) are associated with adverse health outcomes, such as increased mortality, large vessel disease, and reduced white matter volume, cardiovascular and cerebrovascular events. Apart from the well-known link between cardiovascular (CV) risk factors, especially diabetes and hypertension, and cerebrovascular damage, elevated FGF23 is also postulated to be associated with cerebrovascular damage independently of CKD. Elevated FGF23 predisposes to vascular calcification and is associated with vascular stiffness and endothelial dysfunction in the general population with normal renal function. These factors may lead to microangiopathic changes in the brain, cumulative ischemia, and eventually to the loss of white matter fibers. The relationship between FGF23 and brain integrity in individuals without CKD has hitherto not been investigated. In this study, we aimed to determine the association between FGF23, and white matter integrity in a cohort of 50 participants with varying degrees of CV risk burden, using high resolution structural human brain connectomes constructed from MRI diffusion images. We observed that increased FGF23 was associated with axonal loss in the frontal lobe, leading to a fragmentation of white matter network organization. This study provides the first description of the relationship between elevated levels of FGF23, white matter integrity, and brain health. We suggest a synergistic interaction of CV risk factors and FGF23 as a potentially novel determinant of brain health.

Chronic post-stroke aphasia severity is determined by fragmentation of residual white matter networks.

Many stroke survivors with aphasia in the acute period experience spontaneous recovery within the first six months after the stroke. However, approximately 30-40% sustain permanent aphasia and the factors determining incomplete recovery are unclear. Suboptimal recovery may be influenced by disruption of areas seemingly spared by the stroke due to loss of white matter connectivity and network integrity. We reconstructed individual anatomical whole-brain connectomes from 90 left hemisphere stroke survivors using diffusion MR images. We measured the modularity of the residual white matter network organization, the probability of brain regions clustering together, and the degree of fragmentation of left hemisphere networks. Greater post-stroke left hemisphere network fragmentation and higher modularity index were associated with more severe chronic aphasia, controlling for the size of the stroke lesion. Even when the left hemisphere was relatively spared, subjects with disorganized community structure had significantly worse aphasia, particularly when key temporal lobe regions were isolated into segregated modules. These results suggest that white matter integrity and disorganization of neuronal networks could be important determinants of chronic aphasia severity. Connectome white matter organization measured through modularity and other topological features could be used as a personalized variable for clinical staging and aphasia treatment planning.