Involvement of the cortico-basal ganglia-thalamocortical loop in developmental stuttering

Stuttering is a complex neurodevelopmental disorder that has to date eluded a clear explication of its pathophysiological bases. In this review, we utilize the Directions Into Velocities of Articulators (DIVA) neurocomputational modeling framework to mechanistically interpret relevant findings from the behavioral and neurological literatures on stuttering. Within this theoretical framework, we propose that the primary impairment underlying stuttering behavior is malfunction in the cortico-basal ganglia-thalamocortical (hereafter, cortico-BG) loop that is responsible for initiating speech motor programs. This theoretical perspective predicts three possible loci of impaired neural processing within the cortico-BG loop that could lead to stuttering behaviors: impairment within the basal ganglia proper; impairment of axonal projections between cerebral cortex, basal ganglia, and thalamus; and impairment in cortical processing. These theoretical perspectives are presented in detail, followed by a review of empirical data that make reference to these three possibilities. We also highlight any differences that are present in the literature based on examining adults versus children, which give important insights into potential core deficits associated with stuttering versus compensatory changes that occur in the brain as a result of having stuttered for many years in the case of adults who stutter. We conclude with outstanding questions in the field and promising areas for future studies that have the potential to further advance mechanistic understanding of neural deficits underlying persistent developmental stuttering.R01 DC007683 - NIDCD NIH HHS; R01 DC011277 - NIDCD NIH HHSPublished versio

An adaptive 4-week robotic training program of the upper limb for persons with multiple sclerosis

It is suggested that repetitive movements can initiate motor recovery and improve motor learning in populations with neurological impairments and this process can be optimized with robotic devices. The repetitive, reproducible and high dose motor movements that can be delivered by robotics have shown positive results in functional outcomes in stroke patients. However, there is little research on robotic neurorehabilitation for persons with multiple sclerosis (PwMS), more specifically there is lack of literature with focus on the upper extremity. Therefore, the purpose of this work was to use a robotic device to implement an adaptive training program of the forearm and wrist for PwMS. This approach is unique, as it incorporates real time learning from the robotic device to alter the level of assistance/resistance to the individual. This methodology is novel and could prove to be an effective way to properly individualize the therapy process with correct dosage and prescription. 7 individuals with varying levels of MS, placed their most affected limb (forearm) on a robotic device (Wristbot), grasped the handle, and using real-time visual feedback, traced a Lissajous curve allowing the wrist to move in flexion/extension, radial/ulnar directions. Robotic training occurred 3 times per week for 4 consecutive weeks and included 40 minutes of work. Robotic software was adaptive and updated every 3 laps to evaluate the average kinematic performance which modified the robotic assistance/resistance. Outcome measures were taken pre and post intervention. Improvements in performance were quantified by average tracking and figural error, which was significantly reduced from pre – post intervention. Isometric wrist strength and grip force endurance also significantly improved from pre to post intervention. However, maximum grip force, joint position matching, 9-hole peg test, and patient-rated wrist evaluation did not show any significant improvements. To our knowledge, this study was the first adaptive and individualized robotic rehabilitation program providing two opposing forces to the hand/wrist for PwMS. Results of this 4-week training intervention, provide a proof-of-concept that motor control and muscular strength can be improved by this rehabilitation modality. This work acts as a stepping-stone into future investigations of robotic rehabilitation for an MS population

The Purdue Pegboard test : normative data for older adults with low vision

Purpose The usability of assistive technologies depends, in part, on the user’s ability to manipulate the device. In the context of aging and visual impairment, the visibility of any device and its components becomes crucial, and often users rely on tactile information in order to overcome visibility barriers. The purpose of this study was to establish performance norms for older adults with low vision on a common measure of manual dexterity: the Purdue Pegboard Test. Method The Purdue Pegboard was completed visually with the dominant, non-dominant and both hands by 134 older adults (age 60–97) with various levels of low vision, ranging from 20/30 to 20/604 in the better eye. Results Scores decreased significantly as age increased. In addition, performance using the dominant hand was generally best. Compared to previously published values, scores were lower than the norms for healthy older adults as well as those for younger visually impaired individuals. Conclusions The present values for older adults with low vision add to the already existing standards and allow for comparison among future studies with this population. Systematic examination of manual dexterity in low vision clients will enable rehabilitation specialists to make more informed recommendations in terms of usable low-vision devices

White Matter Plasticity in Dancers and Musicians

This dissertation examined training-related brain plasticity by comparing white matter (WM) structure between dancers and musicians and relating the structural changes to dance and music abilities. We focused on the primary motor pathways, to identify potential structural differences between whole-body dance training and specific-effector music training. To this purpose, highly trained dancers and musicians, matched for years of training, were tested on a novel dance imitation task, melody discrimination, and rhythm reproduction. Participants were scanned using magnetic resonance imaging (MRI). WM was analyzed at a whole-brain level in Study 1, using diffusion tensor imaging (DTI). Study 2 used probabilistic tractography to examine the descending motor pathways from the hand, leg, trunk and head regions. In Study 1, dancers showed increased diffusivity and reduced anisotropy in comparison to musicians in regions including the descending motor pathways, the superior longitudinal fasciculus and the corpus callosum, predominantly in the right hemisphere. Consistent with this, in Study 2, dancers had increased diffusivity and greater volume in all portions of the right descending motor pathways, whereas musicians had increased anisotropy, especially in the right hand and trunk/arm tracts. Importantly, in both studies, DTI metrics were positively related with dance and negatively with melody performance. In Study 2, DTI metrics also were negatively associated with age of training start, indicating a direct relation between the structural changes observed and training. Our findings indicate that different types of long-term training have distinct effects on brain structure. In particular, dance training, which engages the whole body, appears to enhance connectivity among a broad range of cortical regions, possibly by increasing axonal diameter and the heterogeneity of fiber orientation. In contrast, music training seems to increase the coherence and packing of the connections linked to the trained effector(s). This dissertation is novel in comparing brain structure between two groups of highly trained performers and in examining multiple DTI metrics concurrently. Further, in Study 2, we developed a novel methodology to segregate the motor cortex into regions corresponding to four main body parts, which could be used by other researchers interested in motor connectivity

Between destiny and disease: genetics and molecular pathways of CNS aging

Human brain aging is associated with robust "normal" functional, structural, and molecular changes that underlie changes in cognition, memory, mood and motor function, amongst other processes. Normal aging is also a requirement for onset of many neurological diseases, ranging from later onset neurodegenerative diseases such as Alzheimer's(AD) and Parkinson's diseases(PD), to earlier onset psychiatric disorders such as bipolar disorder(BPD) and schizophrenia(SCHZ). Understanding the molecular mechanisms and genetic underpinnings of normal age-related brain changes would have profound consequences for prevention and treatment of age-related impairments and disease. Here I introduce current knowledge of these functional changes, their structural and molecular underpinnings, their genetic modulators, and the contribution of normal aging to age-related neurological disease. I then present my contribution to this field in the form of three papers on genetic modulation of mammalian brain molecular aging. These studies demonstrate and investigate mechanisms underlying the causal modulation of molecular brain aging rates by Brain Derived Neurotrophic Factor (BDNF) and Serotonin (5-HT) in knock-out (KO) mice, and associative modulation by the putative longevity gene, Sirtuin 5, in humans (novel low-expressing promoter polymorphism (Sirt5prom2)). In humans we additionally investigate the potential mechanism(s) underlying neurological disease gating by normal aging, providing supporting evidence for molecular aging being a genetically controlled "transcriptional program" that progressively promotes age-regulated neurological diseases. In the discussion, I place these studies in a broader context within the field, detailing their implications and future directions

Brain Imaging Correlates of Developmental Coordination Disorder and Associated Impairments

Developmental Coordination Disorder (DCD) is a common developmental disorder characterised by an inability to learn age appropriate complex motor skills. The first aim of this thesis was to characterise additional cognitive impairments and their relationship with motor difficulties in school aged children with DCD. The second aim was to investigate grey and white matter neuroimaging correlates of motor and cognitive deficits identified. Thirty six children aged 8-10 years who met DSM-5 criteria for DCD and an age-matched typically developing group (N=17) underwent standardised assessments of motor, intellectual, attention, speech and language skills as well as structural and diffusion-weighted MRI scans. Grey matter correlates of impairments were identified using subcortical volumetrics and surface-based analyses of cortical morphology. White matter correlates were examined using tractography and fixel-based fibre morphology of the pyramidal tracts, corpus callosum and cerebellar peduncles. Alongside impaired motor skills, children with DCD performed poorer than controls on several domains of executive function (attention and processing speed) and speech motor control. Motor skills did not correlate with impairments in other domains. Cortical thickness was significantly reduced in the left central sulcus in children with DCD compared to controls. Poor motor skills correlated with measures in left sensorimotor circuitry, posterior cingulate cortex and anterior insula. Poor speech motor control was associated with measures in the thalamus and corticobulbar tract. Poor sustained attention was linked to measures in the right superior cerebellar peduncle. Lower processing speed was associated with reduced mean cortical surface area. Children with DCD show co-occurring impairments in attention and speech motor control. DCD is associated with sensorimotor circuits as well as regions that form part of the default mode and salience networks. Disruption of subcortical circuits may underlie additional impairments. This study provides novel evidence of the neural correlates of DCD

Structure of force as a predictor of oral motor learning in healthy younger and older adults

This study examined the relationship of lingual and labial force structure to learning of oral motor continuous fine force tasks using a pursuit tracking paradigm. It investigated how error and the temporal and frequency structure of force during baseline performance predicted oral motor learning in healthy younger and older adults, drawing on dynamical systems (Bernstein, 1967, as cited in Newell et al., 2003), bidirectional complexity change (Vaillancourt & Newell, 2002) and optimal variability theories (Stergiou, Harbourne, & Cavanaugh, 2006) to explain interacting effects of age and task demand. Right-handed younger (18-28 years of age, N = 20) and older (71-79 years of age, N = 21) adults participated in 2 days’ practice matching constant, 0.75-Hz sinusoidal, and complex periodic (hereafter “multicosine”) visual targets by pursing the lips or elevating the tongue to exert submaximal force whose magnitude controlled the height of a visual trace. Targets were centered at 15% of maximal voluntary force (MVF) determined individually per participant and effector. Over the two days, participants practiced matching each target a total of 35 times with each effector. On the third day, learning was assessed in retention trials (unmodified tasks) and transfer trials (multiple task characteristics individually, systematically modified; only transfer to 10% and 20% MVF target force levels is reported here). Measures of force structure (approximate entropy, ApEn; fuzzy measure entropy, FuzzyMEn; proportion of power, PoP, in 0-1 Hz, 1-2 Hz and 2-3 Hz bands) and error (normalized root mean square error, NRMSE) at baseline (day 1, first trial of each effector x task condition) were related to measurements of reduction in error vs. baseline in retention and transfer trials on the third day ({delta}finalNRMSEret, {delta}finalNRMSEtrn), using primarily linear mixed effects modeling. Results are presented organized by hypotheses within specific aims. Because each hypothesis was assessed using multiple measures, only a selection of the results is covered here for brevity. Specific aim 1. Assess applicability of previous findings on effects of age and task to oral effectors. Hypothesis 1a. Older adults’ force structure will differ task-dependently from younger adults’ (lower entropy and a greater proportion of low-frequency power when the task demands high entropy and reduced low-frequency power, and vice versa). At baseline, task and age group interacted (ApEn: F(2, 205) = 9.555; FuzzyMEn: F(2, 205) = 9.515; both p < 0.0005). Follow-up analysis showed that only younger adults altered entropy across task, (ApEn: F(2, 100) = 17.173; FuzzyMEn, F(2, 100) = 20.492, both p <0.0005). Younger adults produced higher-entropy force than older adults only on the constant task (ApEn: F(1, 41) = 9.407, p = 0.004; FuzzyMEn, F(1, 41) = 10.297, p = 0.003). In retention trials, younger adults’ entropy was higher than older adults’ in the lip x constant force condition (ApEn: t(39) = -4.339, p = 0.002; FuzzyMEn: t(39) = -4.295; p = 0.001) and lower in the tongue x sine condition (ApEn: t(39) = 4.741; FuzzyMEn: t(39) = 4.191; both p = 0.001). These effects suggest younger adults adapted structure of output to task demand more closely than the older adults. Hypothesis 1b. Adaptability (immediate): Older adults will change structure of force to meet task demands less effectively than younger adults, comparing trial 2 to trial 1 on day 1 within each effector x task combination. There was no significant effect of age or age-task interaction with this minimal practice. Hypothesis 1c. Adaptability (after practice): Older adults will change structure of force to meet task demands less effectively than younger adults, comparing day 1 trial 1 to day 3 retention trial 1 within each effector x task combination. Entropy change with practice depended upon an interaction of age group and task (ApEn: F(2, 205) = 5.890, p = 0.003; FuzzyMEn: F(2, 205) = 4.950, p = 0.008). For the multicosine task, younger adults did not change entropy with practice, while older adults increased it (ApEn: t(67.503) = 2.675, p = 0.014; FuzzyMEn: F(1, 41) = 4.559, p = 0.039, NS). For the sine task, younger adults decreased entropy with practice, while older adults increased it (ApEn: t(75.08) = 4.308, p = 0.001; FuzzyMEn: F(1, 41) = 9.657, p = 0.003). Hypothesis 1d. Older adults’ reduction in error vs. baseline on retention and transfer trials after two days’ practice will be less than younger adults’. On retention trials, age group interacted significantly with both effector (F(1, 205) = 5.702, p = 0.018) and task (F(2, 205) = 3.871, p = 0.022). Younger adults showed greater reduction in NRMSE than older adults only with the tongue (F(1, 41) = 7.38, p = 0.009) and on the sine task (F(1, 41) = 11.288, p = 0.002). Hypothesis 1e. Structure of force will differ by task. The constant task will elicit the highest entropy, lowest proportion of low-frequency power, and greatest proportion of higher-frequency power. The sine task will elicit the lowest entropy, greatest proportion of low-frequency power, and lowest proportion of higher-frequency power. The multicosine task will be intermediate. At baseline, both younger and older adults responded to the increased high-frequency content of the multicosine target compared to the sine target by decreasing power in the 0-1 Hz band and increasing it in the 1-2 Hz band (all p ≤ 0.002; see Table 20). On retention trials, entropy had increased with practice to a greater degree for the constant task than for both variable tasks (ApEn, F(2, 205) = 34.918; FuzzyMEn, F(2, 205) = 32.121; main effects and pairwise comparisons of constant to sine and multicosine, all p < 0.0005). Specific aim 2. Assess differences in motor variability between oral effectors. Hypothesis 2a. The tongue will produce less complex force than the lip (lower-entropy, greater dominance of low-frequency power). Hypothesis 2b. The effects of age group and effector on entropy will interact. At baseline, effector and age group interacted (ApEn: F(1, 205) = 10.806, p < 0.0005; FuzzyMEn, F(1, 205) = 9.769, p = 0.002). For older adults only, entropy was higher for the tongue (ApEn: F(1, 105) = 23.591; FuzzyMEn, F(1, 105) = 20.794; both p < 0.0005). On retention trials, older adults still produced higher-entropy force with the tongue (ApEn: F(1, 105) = 22.708; FuzzyMEn, F(1, 105) = 22.767; both p < 0.0005). Younger adults’ force production on retention trials showed higher entropy with the lip for the constant task (which demands high-entropy force; ApEn: F(1, 20) = 11.950, p = 0.002; FuzzyMEn: F(1, 20) = 10.768) and slightly lower entropy with the lip for the more structured variable tasks (significant only for multicosine, ApEn: F(1, 20) = 10.821, p = 0.004; FuzzyMEn: F(1, 20) = 11.775, p = 0.003), suggesting that adaptation to task demand with practice may have been better with the lip. Specific aim 3. Assess utility of baseline performance measures in predicting de novo learning of fine-force pursuit tracking tasks in oral effectors. Hypothesis 3. (a) Error at baseline (NRMSEinitial) and a measure of temporal structure, (b) higher maximal force entropy (maxApEn or maxFuzzyMEn) at baseline or (c) greater adaptability of entropy at baseline, will predict reduction in error vs. baseline on retention and transfer trials ({delta}finalNRMSEret, {delta}finalNRMSEtrn) in pursuit tracking tasks after controlling for age group, effector and task. NRMSEinitial was a significant predictor of reduced error compared to baseline for both retention and transfer trials in all pairings with the various entropy-based predictors (all p < 0.0005). Parameter estimates ranged from -0.89 to -0.91, suggesting that poor initial performance functioned as a marker of greater room for improvement. Maximum entropy also significantly predicted {delta}finalNRMSEret (maxApEn model: F(1, 245.948) = 7.005, p = 0.009; maxFuzzyMEn model: F(1, 245.823) = 5.414, p = 0.021). 1-unit increases in maxApEn and maxFuzzyMEn were estimated to predict changes in {delta}finalNRMSEret of 0.32 and 0.14 respectively (worsening of performance), after controlling for age group, task, effector and NRMSEinitial. The predictive value of initial change in entropy varied by task for retention trials ({delta}initialApEn: F(2, 236.302) = 3.514, p = 0.031; {delta}initialFuzzyMEn: F(2, 236.860) = 5.229, p = 0.006). For the constant task, which demands force output of high entropy, higher entropy on trial 2 than trial 1 on day 1 predicted a decrease in {delta}finalNRMSEret (i.e. a greater reduction in error by day 3). For the sine target, which requires force output of low entropy, higher entropy on trial 2 than trial 1 on day 1 predicted an increase in {delta}finalNRMSEret (i.e. a lesser reduction in error by day 3). Initial change in entropy significantly predicted transfer of learning to tasks with a higher target force level in both models ({delta}initial ApEn model: F(1, 232.077) = 11.853; {delta}initial FuzzyMEn model: F(1, 234.461) = 10.437, both p = 0.001). 1-unit increases in {delta}initial ApEn and {delta}initial FuzzyMEn were estimated to predict changes in {delta}finalNRMSEtrn of -0.17 [-0.27, -0.07] and -0.09 [-0.15, -0.04] respectively (improved transfer), after controlling for age group, task, effector and NRMSEinitial. These and other results from this study suggest that (Aim 1) task-dependent effects on force structure and the bidirectional complexity hypothesis of healthy aging developed in non-oral systems can be applied to fine-force control in pursuit tracking tasks using the lip and tongue; (Aim 2) oral effectors’ structure of force differs, influenced by age, and (Aim 3) baseline behavioral measures can predict learning (measured as reduction in error) after two days’ practice. Initial adaptability of entropy predicted better performance on retention trials if the direction of change was in line with task demand, and worse performance if the direction of change was counter to task demand. This effect comports with the idea of variability in early learning as an exploration of task space (Dhawale, Smith, & Ölveczky, 2017; Stergiou, Harbourne, & Cavanaugh, 2006; Wu, Miyamoto, Gonzalez Castro, Ölveczky, & Smith, 2014) and therefore an active support of learning, rather than a hindrance to be suppressed. Optimal variability in a learning context suggests the ability to shift temporal/frequency structure of force output in the direction demanded by a goal or task. The reduction in adaptability of force structure seen in the older adult participants may play a role in changes in learning with aging. This prediction can be made from a small enough data set to have potential clinical applicability. Older adults remain robustly able to learn and to adjust complexity of oral force output, though with limitations most consistent with the loss of adaptability hypothesis