Association between activity in the ventral premotor cortex and spinal cord activation during force generation-A combined cortico-spinal fMRI study.

Force generation is a crucial element of dexterity and a highly relevant skill of the human motor system. How cerebral and spinal components interact and how spinal activation is associated with the activity in the cerebral primary motor and premotor areas is poorly understood. Here, we conducted combined cortico-spinal functional magnetic resonance imaging during a simple visually guided isometric force generation task in 20 healthy young subjects. Activation was localized in the right cervical spinal cord and left primary motor and premotor areas. The main finding is that spinal activation was negatively correlated with ventral premotor cortex activation. Spinal activation was furthermore significantly correlated with primary motor cortex activation, while increasing target forces led to an increase in the amount of activation. These data indicate that human premotor areas such as the ventral premotor cortex might be functionally connected to the lower cervical spinal cord contributing to distal upper limb functions, a finding that extends our understanding of human motor function beyond the animal literature.

Cortical thickness of contralesional cortices positively relates to future outcome after severe stroke.

Imaging studies have evidenced that contralesional cortices are involved in recovery after motor stroke. Cortical thickness (CT) analysis has proven its potential to capture the changes of cortical anatomy, which have been related to recovery and treatment gains under therapy. An open question is whether CT obtained in the acute phase after stroke might inform correlational models to explain outcome variability. Data of 38 severely impaired (median NIH Stroke Scale 9, interquartile range: 6-13) acute stroke patients of 2 independent cohorts were reanalyzed. Structural imaging data were processed via the FreeSurfer pipeline to quantify regional CT of the contralesional hemisphere. Ordinal logistic regression models were fit to relate CT to modified Rankin Scale as an established measure of global disability after 3-6 months, adjusted for the initial deficit, lesion volume, and age. The data show that CT of contralesional cortices, such as the precentral gyrus, the superior frontal sulcus, and temporal and cingulate cortices, positively relates to the outcome after stroke. This work shows that the baseline cortical anatomy of selected contralesional cortices can explain the outcome variability after severe stroke, which further contributes to the concept of structural brain reserve with respect to contralesional cortices to promote recovery.

Low-Frequency Brain Oscillations Track Motor Recovery in Human Stroke.

OBJECTIVE: The majority of patients with stroke survive the acute episode and live with enduring disability. Effective therapies to support recovery of motor function after stroke are yet to be developed. Key to this development is the identification of neurophysiologic signals that mark recovery and are suitable and susceptible to interventional therapies. Movement preparatory low-frequency oscillations (LFOs) play a key role in cortical control of movement. Recent animal data point to a mechanistic role of motor cortical LFOs in stroke motor deficits and demonstrate neuromodulation intervention with therapeutic benefit. Their relevance in human stroke pathophysiology is unknown. METHODS: We studied the relationship between movement-preparatory LFOs during the performance of a visuomotor grip task and motor function in a longitudinal (<5 days, 1 and 3 months) cohort study of 33 patients with motor stroke and in 19 healthy volunteers. RESULTS: Acute stroke-lesioned brains fail to generate the LFO signal. Whereas in healthy humans, a transient occurrence of LFOs preceded movement onset at predominantly contralateral frontoparietal motor regions, recordings in patients revealed that movement-preparatory LFOs were substantially diminished to a level of 38% after acute stroke. LFOs progressively increased at 1 and 3 months. This re-emergence closely tracked the recovery of motor function across several movement qualities including grip strength, fine motor skills, and synergies and was frequency band specific. INTERPRETATION: Our results provide the first human evidence for a link between movement-preparatory LFOs and functional recovery after stroke, promoting their relevance for movement control. These results suggest that it may be interesting to explore targeted, LFOs-restorative brain stimulation therapy in human stroke patients. ANN NEUROL 2019;86:853-865.

Cortico-Cerebellar Structural Connectivity Is Related to Residual Motor Output in Chronic Stroke.

Functional imaging studies have argued that interactions between cortical motor areas and the cerebellum are relevant for motor output and recovery processes after stroke. However, the impact of the underlying structural connections is poorly understood. To investigate this, diffusion-weighted brain imaging was conducted in 26 well-characterized chronic stroke patients (aged 63 ± 1.9 years, 18 males) with supratentorial ischemic lesions and 26 healthy participants. Probabilistic tractography was used to reconstruct reciprocal cortico-cerebellar tracts and to relate their microstructural integrity to residual motor functioning applying linear regression modeling. The main finding was a significant association between cortico-cerebellar structural connectivity and residual motor function, independent from the level of damage to the cortico-spinal tract. Specifically, white matter integrity of the cerebellar outflow tract, the dentato-thalamo-cortical tract, was positively related to both general motor output and fine motor skills. Additionally, the integrity of the descending cortico-ponto-cerebellar tract contributed to rather fine motor skills. A comparable structure-function relationship was not evident in the controls. The present study provides first tract-related structural data demonstrating a critical importance of distinct cortico-cerebellar connections for motor output after stroke.

Dynamic causal modelling of EEG and fMRI to characterize network architectures in a simple motor task.

Dynamic causal modelling (DCM) has extended the understanding of brain network dynamics in a variety of functional systems. In the motor system, DCM studies based on functional magnetic resonance imaging (fMRI) or on magneto-/electroencephalography (M/EEG) have demonstrated movement-related causal information flow from secondary to primary motor areas and have provided evidence for nonlinear cross-frequency interactions among motor areas. The present study sought to investigate to what extent fMRI- and EEG-based DCM might provide complementary and synergistic insights into neuronal network dynamics. Both modalities share principal similarities in the formulation of the DCM. Thus, we hypothesized that DCM based on induced EEG responses (DCM-IR) and on fMRI would reveal congruent task-dependent network dynamics. Brain electrical (63-channel surface EEG) and Blood Oxygenation Level Dependent (BOLD) signals were recorded in separate sessions from 14 healthy participants performing simple isometric right and left hand grips. DCM-IR and DCM-fMRI were used to estimate coupling parameters modulated by right and left hand grips within a core motor network of six regions comprising bilateral primary motor cortex (M1), ventral premotor cortex (PMv) and supplementary motor area (SMA). We found that DCM-fMRI and DCM-IR similarly revealed significant grip-related increases in facilitatory coupling between SMA and M1 contralateral to the active hand. A grip-dependent interhemispheric reciprocal inhibition between M1 bilaterally was only revealed by DCM-fMRI but not by DCM-IR. Frequency-resolved coupling analysis showed that the information flow from contralateral SMA to M1 was predominantly a linear alpha-to-alpha (9-13Hz) interaction. We also detected some cross-frequency coupling from SMA to contralateral M1, i.e., between lower beta (14-21Hz) at the SMA and higher beta (22-30Hz) at M1 during right hand grip and between alpha (9-13Hz) at SMA and lower beta (14-21Hz) at M1 during left hand grip. In conclusion, the strategy of informing EEG source-space configurations with fMRI-derived coordinates, cross-validating basic connectivity maps and analysing frequency coding allows for deeper insight into the motor network architecture of the human brain. The present results provide evidence for the robustness of non-invasively measured causal information flow from secondary motor areas such as SMA towards M1 and further contribute to the validation of the methodological approach of multimodal DCM to explore human network dynamics.

Action inhibition in Tourette syndrome.

Tourette syndrome is a neuropsychiatric disorder characterized by tics. Tic generation is often linked to dysfunction of inhibitory brain networks. Some previous behavioral studies found deficiencies in inhibitory motor control in Tourette syndrome, but others suggested normal or even better-than-normal performance. Furthermore, neural correlates of action inhibition in these patients are poorly understood. We performed event-related functional magnetic resonance imaging during a stop-signal reaction-time task in 14 uncomplicated adult Tourette patients and 15 healthy controls. In patients, we correlated activations in stop-signal reaction-time task with their individual motor tic frequency. Task performance was similar in both groups. Activation of dorsal premotor cortex was stronger in the StopSuccess than in the Go condition in healthy controls. This pattern was reversed in Tourette patients. A significant positive correlation was present between motor tic frequency and activations in the supplementary motor area during StopSuccess versus Go in patients. Inhibitory brain networks differ between healthy controls and Tourette patients. In the latter the supplementary motor area is probably a key relay of inhibitory processes mediating both suppression of tics and inhibition of voluntary action.

Spatial remapping in the audio-tactile ventriloquism effect: a TMS investigation on the role of the ventral intraparietal area.

Previous studies have suggested that the putative human homologue of the ventral intraparietal area (hVIP) is crucially involved in the remapping of tactile information into external spatial coordinates and in the realignment of tactile and visual maps. It is unclear, however, whether hVIP is critical for the remapping process during audio-tactile cross-modal spatial interactions. The audio-tactile ventriloquism effect, where the perceived location of a sound is shifted toward the location of a synchronous but spatially disparate tactile stimulus, was used to probe spatial interactions in audio-tactile processing. Eighteen healthy volunteers were asked to report the perceived location of brief auditory stimuli presented from three different locations (left, center, and right). Auditory stimuli were presented either alone (unimodal stimuli) or concurrently to a spatially discrepant tactile stimulus applied to the left or right index finger (bimodal stimuli), with the hands adopting either an uncrossed or a crossed posture. Single pulses of TMS were delivered over the hVIP or a control site (primary somatosensory cortex, SI) 80 msec after trial onset. TMS to the hVIP, compared with the control SI-TMS, interfered with the remapping of touch into external space, suggesting that hVIP is crucially involved in transforming spatial reference frames across audition and touch.

Altered microstructure of the contralesional ventral premotor cortex and motor output after stroke.

Cortical thickness analyses have provided valuable insights into changes in cortical brain structure after stroke and their association with recovery. Across studies though, relationships between cortical structure and function show inconsistent results. Recent developments in diffusion-weighted imaging of the cortex have paved the way to uncover hidden aspects of stroke-related alterations in cortical microstructure, going beyond cortical thickness as a surrogate for cortical macrostructure. We re-analysed clinical and imaging data of 42 well-recovered chronic stroke patients from 2 independent cohorts (mean age 64 years, 4 left-handed, 71% male, 16 right-sided strokes) and 33 healthy controls of similar age and gender. Cortical fractional anisotropy and cortical thickness values were obtained for six key sensorimotor areas of the contralesional hemisphere. The regions included the primary motor cortex, dorsal and ventral premotor cortex, supplementary and pre-supplementary motor areas, and primary somatosensory cortex. Linear models were estimated for group comparisons between patients and controls and for correlations between cortical fractional anisotropy and cortical thickness and clinical scores. Compared with controls, stroke patients exhibited a reduction in fractional anisotropy in the contralesional ventral premotor cortex (P = 0.005). Fractional anisotropy of the other regions and cortical thickness did not show a comparable group difference. Higher fractional anisotropy of the ventral premotor cortex, but not cortical thickness, was positively associated with residual grip force in the stroke patients. These data provide novel evidence that the contralesional ventral premotor cortex might constitute a key sensorimotor area particularly susceptible to stroke-related alterations in cortical microstructure as measured by diffusion MRI and they suggest a link between these changes and residual motor output after stroke.

Brain network topology early after stroke relates to recovery.

Analyses of alterations of brain networks have gained an increasing interest in stroke rehabilitation research. Compared with functional networks derived from resting-state analyses, there is limited knowledge of how structural network topology might undergo changes after stroke and, more importantly, if structural network information obtained early after stroke could enhance recovery models to infer later outcomes. The present work re-analysed cross-sectional structural imaging data, obtained within the first 2 weeks, of 45 acute stroke patients (22 females, 24 right-sided strokes, age 68 ± 13 years). Whole-brain tractography was performed to reconstruct structural connectomes and graph-theoretical analyses were employed to quantify global network organization with a focus on parameters of network integration and modular processing. Graph measures were compared between stroke patients and 34 healthy controls (15 females, aged 69 ± 10 years) and they were integrated with four clinical scores of the late subacute stage, covering neurological symptom burden (National Institutes of Health Stroke Scale), global disability (modified Rankin Scale), activity-related disability (Barthel Index) and motor functions (Upper-Extremity Score of the Fugl-Meyer Assessment). The analyses were employed across the complete cohort and, based on clustering analysis, separately within subgroups stratified in mild to moderate (n = 21) and severe (n = 24) initial deficits. The main findings were (i) a significant reduction of network's global efficiency, specifically in patients with severe deficits compared with controls (P = 0.010) and (ii) a significant negative correlation of network efficiency with the extent of persistent functional deficits at follow-up after 3-6 months (P ≤ 0.032). Specifically, regression models revealed that this measure was capable to increase the explained variance in future deficits by 18% for the modified Rankin Scale, up to 24% for National Institutes of Health Stroke Scale, and 16% for Barthel Index when compared with models including the initial deficits and the lesion volume. Patients with mild to moderate deficits did not exhibit a similar impact of network efficiency on outcome inference. Clustering coefficient and modularity, measures of segregation and modular processing, did not exhibit comparable structure-outcome relationships, neither in severely nor in mildly affected patients. This study provides empirical evidence that structural network efficiency as a graph-theoretical marker of large-scale network topology, quantified early after stroke, relates to recovery. Notably, this contribution was only evident in severely but not mildly affected stroke patients. This suggests that the initial clinical deficit might shape the dependency of recovery on global network topology after stroke.

Crossmodal Pattern Discrimination in Humans and Robots: A Visuo-Tactile Case Study.

The quality of crossmodal perception hinges on two factors: The accuracy of the independent unimodal perception and the ability to integrate information from different sensory systems. In humans, the ability for cognitively demanding crossmodal perception diminishes from young to old age. Here, we propose a new approach to research to which degree the different factors contribute to crossmodal processing and the age-related decline by replicating a medical study on visuo-tactile crossmodal pattern discrimination utilizing state-of-the-art tactile sensing technology and artificial neural networks (ANN). We implemented two ANN models to specifically focus on the relevance of early integration of sensory information during the crossmodal processing stream as a mechanism proposed for efficient processing in the human brain. Applying an adaptive staircase procedure, we approached comparable unimodal classification performance for both modalities in the human participants as well as the ANN. This allowed us to compare crossmodal performance between and within the systems, independent of the underlying unimodal processes. Our data show that unimodal classification accuracies of the tactile sensing technology are comparable to humans. For crossmodal discrimination of the ANN the integration of high-level unimodal features on earlier stages of the crossmodal processing stream shows higher accuracies compared to the late integration of independent unimodal classifications. In comparison to humans, the ANN show higher accuracies than older participants in the unimodal as well as the crossmodal condition, but lower accuracies than younger participants in the crossmodal task. Taken together, we can show that state-of-the-art tactile sensing technology is able to perform a complex tactile recognition task at levels comparable to humans. For crossmodal processing, human inspired early sensory integration seems to improve the performance of artificial neural networks. Still, younger participants seem to employ more efficient crossmodal integration mechanisms than modeled in the proposed ANN. Our work demonstrates how collaborative research in neuroscience and embodied artificial neurocognitive models can help to derive models to inform the design of future neurocomputational architectures.

Evolution of brain activation after stroke in a constant-effort versus constant-output motor task.

PURPOSE: Recovery of hand function after stroke has been associated with transient overactivation of the cerebral sensorimotor network. One open question has been as to how much this transient overactivation is related to 'true' reorganisation of the network or reflecting the fact that a simple motor task is difficult to perform for a patient with a motor deficit, i.e. reflecting 'effort'. METHODS: To address this, we combined a constant-output (varying effort) and constant-effort (varying output) task in a longitudinal (T1 = 3-5 days, T2 = 6 weeks, T3 = 3 months after stroke) multimodal (functional magnetic resonance imaging (FMRI), electroencephalography (EEG)) study of 12 (EEG)/8 (FMRI) patients (7 male, age 67 ± 9 years) showing significant recovery from a hand motor deficit. RESULTS: The reduction of sensorimotor activation from T1 to T3 was significant (p = 0.012). But task effort did not exhibit any significant impact on the evolution of task-related brain activation over time. This proved to be equally applicable to FMRI and EEG data. CONCLUSION: We conclude that initial up-regulation of brain activity after stroke is not simply a consequence of enhanced effort early after stroke but rather reflects neural processes involved in reorganisation and recovery of function.

Right Prefrontal TMS Disrupts Interregional Anticipatory EEG Alpha Activity during Shifting of Visuospatial Attention.

Visual attention can be shifted in space without moving the eyes. Amplitude decrease of rhythmical brain activity around 10 Hz (so called alpha activity) at contralateral posterior sites has been reported during covered shifts of visuospatial attention to one visual hemi-field. Alpha amplitude increase, on the other hand, can be found at ipsilateral visual cortex. There is some evidence suggesting an involvement of prefrontal brain areas during the control of attention-related anticipatory alpha amplitude asymmetry. This open question has been studied in detail using a multimodal approach combining transcranial magnetic stimulation (TMS) and multichannel electroencephalography (EEG) in healthy humans. Slow (1 Hz) repetitive TMS leading to reduced excitability of the stimulation site was delivered either to right frontal eye field (FEF) or a control site (vertex). Subsequently, participants had to perform a spatial cuing task in which covert shifts of attention were required to either the left or the right visual hemi-field. After stimulation at the vertex (control condition) a pattern of anticipatory, attention-related ipsilateral alpha increase/contralateral alpha decrease over posterior recording sites could be obtained. Additionally, there was pronounced coupling between (in particular right) FEF and posterior brain sites at EEG alpha frequency. When, however, right prefrontal cortex had been virtually lesioned preceding the task, these EEG correlates of visuospatial attention were attenuated. Notably, the effect of TMS at the right FEF on interregional fronto-parietal alpha coupling predicted the effect of TMS on response times. This suggests that visual attention processes associated with posterior EEG alpha activity are at least partly top-down controlled by the prefrontal cortex.