Konstantinos P. Michmizos

Altered Onset Response Dynamics in Somatosensory Processing in Autism Spectrum Disorder

Abnormalities in cortical connectivity and evoked responses have been extensively documented in autism spectrum disorder (ASD). However, specific signatures of these cortical abnormalities remain elusive, with data pointing toward abnormal patterns of both increased and reduced response amplitudes and functional connectivity. We have previously proposed, using magnetoencephalography (MEG) data, that apparent inconsistencies in prior studies could be reconciled if functional connectivity in ASD was reduced in the feedback (top-down) direction, but increased in the feedforward (bottom-up) direction. Here, we continue this line of investigation by assessing abnormalities restricted to the onset, feedforward inputs driven, component of the response to vibrotactile stimuli in somatosensory cortex in ASD. Using a novel method that measures the spatio-temporal divergence of cortical activation, we found that relative to typically developing participants, the ASD group was characterized by an increase in the initial onset component of the cortical response, and a faster spread of local activity. Given the early time window, the results could be interpreted as increased thalamocortical feedforward connectivity in ASD, and offer a plausible mechanism for the previously observed increased response variability in ASD, as well as for the commonly observed behaviorally measured tactile processing abnormalities associated with the disorder.

Somatosensory cortex functional connectivity abnormalities in autism show opposite trends, depending on direction and spatial scale

Functional connectivity is abnormal in autism, but the nature of these abnormalities remains elusive. Different studies, mostly using functional magnetic resonance imaging, have found increased, decreased, or even mixed pattern functional connectivity abnormalities in autism, but no unifying framework has emerged to date. We measured functional connectivity in individuals with autism and in controls using magnetoencephalography, which allowed us to resolve both the directionality (feedforward versus feedback) and spatial scale (local or long-range) of functional connectivity. Specifically, we measured the cortical response and functional connectivity during a passive 25-Hz vibrotactile stimulation in the somatosensory cortex of 20 typically developing individuals and 15 individuals with autism, all males and right-handed, aged 8-18, and the mu-rhythm during resting state in a subset of these participants (12 per group, same age range). Two major significant group differences emerged in the response to the vibrotactile stimulus. First, the 50-Hz phase locking component of the cortical response, generated locally in the primary (S1) and secondary (S2) somatosensory cortex, was reduced in the autism group (P < 0.003, corrected). Second, feedforward functional connectivity between S1 and S2 was increased in the autism group (P < 0.004, corrected). During resting state, there was no group difference in the mu-α rhythm. In contrast, the mu-β rhythm, which has been associated with feedback connectivity, was significantly reduced in the autism group (P < 0.04, corrected). Furthermore, the strength of the mu-β was correlated to the relative strength of 50 Hz component of the response to the vibrotactile stimulus (r = 0.78, P < 0.00005), indicating a shared aetiology for these seemingly unrelated abnormalities. These magnetoencephalography-derived measures were correlated with two different behavioural sensory processing scores (P < 0.01 and P < 0.02 for the autism group, P < 0.01 and P < 0.0001 for the typical group), with autism severity (P < 0.03), and with diagnosis (89% accuracy). A biophysically realistic computational model using data driven feedforward and feedback parameters replicated the magnetoencephalography data faithfully. The direct observation of both abnormally increased and abnormally decreased functional connectivity in autism occurring simultaneously in different functional connectivity streams, offers a potential unifying framework for the unexplained discrepancies in current findings. Given that cortical feedback, whether local or long-range, is intrinsically non-linear, while cortical feedforward is generally linear relative to the stimulus, the present results suggest decreased non-linearity alongside an increased veridical component of the cortical response in autism.

Robot-Aided Neurorehabilitation: A Pediatric Robot for Ankle Rehabilitation

This paper presents the pediAnklebot, an impedance-controlled low-friction, backdriveable robotic device developed at the Massachusetts Institute of Technology that trains the ankle of neurologically impaired children of ages 6-10 years old. The design attempts to overcome the known limitations of the lower extremity robotics and the unknown difficulties of what constitutes an appropriate therapeutic interaction with children. The robots pilot clinical evaluation is on-going and it incorporates our recent findings on the ankle sensorimotor control in neurologically intact subjects, namely the speed-accuracy tradeoff, the deviation from an ideally smooth ankle trajectory, and the reaction time. We used these concepts to develop the kinematic and kinetic performance metrics that guided the ankle therapy in a similar fashion that we have done for our upper extremity devices. Here we report on the use of the device in at least nine training sessions for three neurologically impaired children. Results demonstrated a statistically significant improvement in the performance metrics assessing explicit and implicit motor learning. Based on these initial results, we are confident that the device will become an effective tool that harnesses plasticity to guide habilitation during childhood.

Pointing with the ankle: the speed-accuracy trade-off.

Abstract This study investigated the trade-off between speed and accuracy in pointing movements with the ankle during goal-directed movements in dorsal–plantar (DP) and inversion–eversion (IE). Nine subjects completed a series of discrete pointing movements with the ankle between spatial targets of varying difficulty. Six different target sets were presented, with a range of task difficulty between 2.2 and 3.8 bits of information. Our results demonstrated that for visually evoked, visually guided discrete DP and IE ankle pointing movements, performance can be described by a linear function, as predicted by Fitts’ law. These results support our ongoing effort to develop an adaptive algorithm employing the speed-accuracy trade-off concept to control our pediatric anklebot while delivering therapy for children with cerebral palsy.

Beta-Band Frequency Peaks Inside the Subthalamic Nucleus as a Biomarker for Motor Improvement After Deep Brain Stimulation in Parkinson's Disease

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) remains an empirical, yet highly effective, surgical treatment for advanced Parkinsons disease (PD). DBS outcome depends on accurate stimulation of the STN sensorimotor area which is a trial-and-error procedure taking place during and after surgery. Pathologically enhanced beta-band (13-35 Hz) oscillatory activity across the cortico-basal ganglia pathways is a prominent neurophysiological phenomenon associated with PD. We hypothesized that weighing together beta-band frequency peaks from simultaneous microelectrode recordings in “off-state” PD patients could map the individual neuroanatomical variability and serve as a biomarker for the location of the STN sensorimotor neurons. We validated our hypothesis with 9 and 11 patients that, respectively, responded well and poorly to bilateral DBS, after at least two years of follow up. We categorized “good” and “poor” DBS responders based on their clinical assessment alongside a > 40% and <;30% change, respectively, in “off” unified PD rating scale motor scores. Good (poor) DBS responders had, in average, 1 mm (3.5 mm) vertical distance between the maximum beta-peak weighted across the parallel microelectrodes and the center of the stimulation area. The distances were statistically different in the two groups (p = 0.0025). Our biomarker could provide personalized intra- and postoperative support in stimulating the STN sensorimotor area associated with optimal long-term clinical benefits.

A comparative analysis of speed profile models for ankle pointing movements: evidence that lower and upper extremity discrete movements are controlled by a single invariant strategy

Little is known about whether our knowledge of how the central nervous system controls the upper extremities (UE), can generalize, and to what extent to the lower limbs. Our continuous efforts to design the ideal adaptive robotic therapy for the lower limbs of stroke patients and children with cerebral palsy highlighted the importance of analyzing and modeling the kinematics of the lower limbs, in general, and those of the ankle joints, in particular. We recruited 15 young healthy adults that performed in total 1,386 visually evoked, visually guided, and target-directed discrete pointing movements with their ankle in dorsal–plantar and inversion–eversion directions. Using a non-linear, least-squares error-minimization procedure, we estimated the parameters for 19 models, which were initially designed to capture the dynamics of upper limb movements of various complexity. We validated our models based on their ability to reconstruct the experimental data. Our results suggest a remarkable similarity between the top-performing models that described the speed profiles of ankle pointing movements and the ones previously found for the UE both during arm reaching and wrist pointing movements. Among the top performers were the support-bounded lognormal and the beta models that have a neurophysiological basis and have been successfully used in upper extremity studies with normal subjects and patients. Our findings suggest that the same model can be applied to different “human” hardware, perhaps revealing a key invariant in human motor control. These findings have a great potential to enhance our rehabilitation efforts in any population with lower extremity deficits by, for example, assessing the level of motor impairment and improvement as well as informing the design of control algorithms for therapeutic ankle robots.

Auditory processing in noise is associated with complex patterns of disrupted functional connectivity in autism spectrum disorder

Autism spectrum disorder (ASD) is associated with difficulty in processing speech in a noisy background, but the neural mechanisms that underlie this deficit have not been mapped. To address this question, we used magnetoencephalography to compare the cortical responses between ASD and typically developing (TD) individuals to a passive mismatch paradigm. We repeated the paradigm twice, once in a quiet background, and once in the presence of background noise. We focused on both the evoked mismatch field (MMF) response in temporal and frontal cortical locations, and functional connectivity with spectral specificity between those locations. In the quiet condition, we found common neural sources of the MMF response in both groups, in the right temporal gyrus and inferior frontal gyrus (IFG). In the noise condition, the MMF response in the right IFG was preserved in the TD group, but reduced relative to the quiet condition in ASD group. The MMF response in the right IFG also correlated with severity of ASD. Moreover, in noise, we found significantly reduced normalized coherence (deviant normalized by standard) in ASD relative to TD, in the beta band (14–25 Hz), between left temporal and left inferior frontal sub‐regions. However, unnormalized coherence (coherence during deviant or standard) was significantly increased in ASD relative to TD, in multiple frequency bands. Our findings suggest increased recruitment of neural resources in ASD irrespective of the task difficulty, alongside a reduction in top‐down modulations, usually mediated by the beta band, needed to mitigate the impact of noise on auditory processing. Autism Res 2016,.

Classification and Prediction of Clinical Improvement in Deep Brain Stimulation From Intraoperative Microelectrode Recordings

We present a random forest (RF) classification and regression technique to predict, intraoperatively, the unified Parkinsons disease rating scale (UPDRS) improvement after deep brain stimulation (DBS). We hypothesized that a data-informed combination of features extracted from intraoperative microelectrode recordings (MERs) can predict the motor improvement of Parkinsons disease patients undergoing DBS surgery. We modified the employed RFs to account for unbalanced datasets and multiple observations per patient, and showed, for the first time, that only five neurophysiologically interpretable MER signal features are sufficient for predicting UPDRS improvement. This finding suggests that subthalamic nucleus (STN) electrophysiological signal characteristics are strongly correlated to the extent of motor behavior improvement observed in STN-DBS.

Modeling reaction time in the ankle

We are examining whether robust behavioral laws, initially designed to describe sensorimotor control of the upper extremities, can also describe lower extremity movements. Herein, we present our initial results of our research on measuring ankle reaction time (RT). We show that RT measured in ankle dorsiflexion (DP) and inversion-eversion (IE) of 7 healthy young subjects followed a γ distribution, a typical finding in the upper limb response modalities. We propose that the low-order statistics (mean and variance) of the best-fit γ function can be used to concatenate RT across subjects with similar performance and create super-subjects (SS). We then show that the most widely used model of RT cognitive processes, the Ratcliff diffusion model, is adequate to describe ankle RT in an SS. The combination of experimental data analysis with diffusion modeling of ankle RT proposed that at least two cognitive components of RT are accounted for a difference in mean RT observed between DP and IE, namely the speed of information accumulation and the non-decision time that includes, among others, the time for motor response encoding and execution. These results show a great potential to inform our adaptive assist-as-needed robotic therapy delivered to the lower limbs of children with Cerebral Palsy.

Pediatric Anklebot: Pilot clinical trial

We are currently examining the therapeutic efficacy of the pediAnklebot, an impedance-controlled low-friction, back-drivable robotic device that trains the ankle of neurologically impaired children of ages 6-10 years old. In this paper, we present the first clinical results from a small feasibility study involving 4 children with Cerebral Palsy. The children used the pediAnklebot in seated position to train their ankle twice per week for a total of 6 weeks (12 sessions). The initial results indicate an improvement of the ankles functions including its pointing abilities and gait speed. The observed clinical outcome reinforces our confidence that the pediAnklebot, driven by our adaptive, assist-as-needed, robotic therapy can harness plasticity to guide habilitation during childhood.