Targeting Neuroplasticity to Improve Motor Recovery after Stroke

After neurological injury, people develop abnormal patterns of neural activity that limit motor recovery. Traditional rehabilitation, which concentrates on practicing impaired skills, is seldom fully effective. New targeted neuroplasticity (TNP) protocols interact with the CNS to induce beneficial plasticity in key sites and thereby enable wider beneficial plasticity. They can complement traditional therapy and enhance recovery. However, their development and validation is difficult because many different TNP protocols are conceivable, and evaluating even one of them is lengthy, laborious, and expensive. Computational models can address this problem by triaging numerous candidate protocols rapidly and effectively. Animal and human empirical testing can then concentrate on the most promising ones. Here we simulate a neural network of corticospinal neurons that control motoneurons eliciting unilateral finger extension. We use this network to (1) study the mechanisms and patterns of cortical reorganization after a stroke, and (2) identify and parameterize a TNP protocol that improves recovery of extension force. After a simulated stroke, standard training produced abnormal bilateral cortical activation and suboptimal force recovery. To enhance recovery, we interdigitated standard trials with trials in which the teaching signal came from a targeted population of sub-optimized neurons. Targeting neurons in secondary motor areas on 5-20% of the total trials restored lateralized cortical activation and improved recovery of extension force. The results illuminate mechanisms underlying suboptimal cortical activity post-stroke; they enable identification and parameterization of the most promising TNP protocols. By providing initial guidance, computational models could facilitate and accelerate realization of new therapies that improve motor recovery

Targeting Neuroplasticity to Improve Motor Recovery after Stroke

After neurological injury, people develop abnormal patterns of neural activity that limit motor recovery. Traditional rehabilitation, which concentrates on practicing impaired skills, is seldom fully effective. New targeted neuroplasticity (TNP) protocols interact with the CNS to induce beneficial plasticity in key sites and thereby enable wider beneficial plasticity. They can complement traditional therapy and enhance recovery. However, their development and validation is difficult because many different TNP protocols are conceivable, and evaluating even one of them is lengthy, laborious, and expensive. Computational models can address this problem by triaging numerous candidate protocols rapidly and effectively. Animal and human empirical testing can then concentrate on the most promising ones. Here we simulate a neural network of corticospinal neurons that control motoneurons eliciting unilateral finger extension. We use this network to (1) study the mechanisms and patterns of cortical reorganization after a stroke, and (2) identify and parameterize a TNP protocol that improves recovery of extension force. After a simulated stroke, standard training produced abnormal bilateral cortical activation and suboptimal force recovery. To enhance recovery, we interdigitated standard trials with trials in which the teaching signal came from a targeted population of sub-optimized neurons. Targeting neurons in secondary motor areas on 5-20% of the total trials restored lateralized cortical activation and improved recovery of extension force. The results illuminate mechanisms underlying suboptimal cortical activity post-stroke; they enable identification and parameterization of the most promising TNP protocols. By providing initial guidance, computational models could facilitate and accelerate realization of new therapies that improve motor recovery

Single Trial Decoding of Movement Intentions Using Functional Ultrasound Neuroimaging

Brain-machine interfaces (BMI) are powerful devices for restoring function to people living with paralysis. Leveraging significant advances in neurorecording technology, computational power, and understanding of the underlying neural signals, BMI have enabled severely paralyzed patients to control external devices, such as computers and robotic limbs. However, high-performance BMI currently require highly invasive recording techniques, and are thus only available to niche populations. Here, we show that a minimally invasive neuroimaging approach based on functional ultrasound (fUS) imaging can be used to detect and decode movement intention signals usable for BMI. We trained non-human primates to perform memory-guided movements while using epidural fUS imaging to record changes in cerebral blood volume from the posterior parietal cortex, a brain area important for spatial perception, multisensory integration, and movement planning. Using hemodynamic signals acquired during movement planning, we classified left-cued vs. right-cued movements, establishing the feasibility of ultrasonic BMI. These results demonstrate the ability of fUS-based neural interfaces to take advantage of the excellent spatiotemporal resolution, sensitivity, and field of view of ultrasound without breaching the dura or physically penetrating brain tissue

Neural correlates of cognitive motor signals in primary somatosensory cortex

Classical systems neuroscience positions primary sensory areas as early feed-forward processing stations for refining incoming sensory information. This view may oversimplify their role given extensive bi-directional connectivity with multimodal cortical and subcortical regions. Here we show that single units in human primary somatosensory cortex encode imagined reaches centered on imagined limb positions in a cognitive motor task. This result suggests a broader role of primary somatosensory cortex in cortical function than previously demonstrated

Justice and Corporate Governance: New Insights from Rawlsian Social Contract and Sen’s Capabilities Approach

By considering what we identify as a problem inherent in the ‘nature of the firm’—the risk of abuse of authority—we propound the conception of a social contract theory of the firm which is truly Rawlsian in its inspiration. Hence, we link the social contract theory of the firm (justice at firm’s level) with the general theory of justice (justice at society’s level). Through this path, we enter the debate about whether firms can be part of Rawlsian theory of justice showing that corporate governance principles enter the “basic structure.” Finally, we concur with Sen’s aim to broaden the realm of social justice beyond what he calls the ‘transcendental institutional perfectionism’ of Rawls’ theory. We maintain the contractarian approach to justice but introduce Sen’s capability concept as an element of the constitutional and post-constitutional contract model of institutions with special reference to corporate governance. Accordingly, rights over primary goods and capabilities are (constitutionally) granted by the basic institutions of society, but many capabilities have to be turned into the functionings of many stakeholders through the operation of firms understood as post-constitutional institutional domains. The constitutional contract on the distribution of primary goods and capabilities should then shape the principles of corporate governance so that at post-constitutional level anyone may achieve her/his functionings in the corporate domain by exercising such capabilities. In the absence of such a condition, post-constitutional contracts would distort the process that descends from constitutional rights and capabilities toward social outcomes

Adaptation and psychometric properties of the ISPCAN Child Abuse Screening Tool for use in trials (ICAST-Trial) among South African adolescents and their primary caregivers

© 2018 The Authors. Child abuse prevention research has been hampered by a lack of validated multi-dimensional non-proprietary instruments, sensitive enough to measure change in abuse victimization or behavior. This study aimed to adapt the ICAST child abuse self-report measure (parent and child) for use in intervention studies and to investigate the psychometric properties of this substantially modified tool in a South African sample. First, cross-cultural and sensitivity adaptation of the original ICAST tools resulted in two preliminary measures (ICAST-Trial adolescents: 27 items, ICAST-Trial caregivers: 19 items). Second, ICAST-Trial data from a cluster randomized trial of a parenting intervention for families with adolescents (N = 1104, 552 caregiver-adolescent dyads) was analyzed. Confirmatory factor analysis established the hypothesized 6-factor (adolescents) and 4-factor (caregivers) structure. Removal of two items for adolescents and five for caregivers resulted in adequate model fit. Concurrent criterion validity analysis confirmed hypothesized relationships between child abuse and adolescent and caregiver mental health, adolescent behavior, discipline techniques and caregiver childhood abuse history. The resulting ICAST-Trial measures have 25 (adolescent) and 14 (caregiver) items respectively and measure physical, emotional and contact sexual abuse, neglect (both versions), and witnessing intimate partner violence and sexual harassment (adolescent version). The study established that both tools are sensitive to measuring change over time in response to a parenting intervention. The ICAST-Trial should have utility for evaluating the effectiveness of child abuse prevention efforts in similar socioeconomic contexts. Further research is needed to replicate these findings and examine cultural appropriateness, barriers for disclosure, and willingness to engage in child abuse research

International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci

The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5–20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson’s disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations