Invariant neural dynamics drive commands to control different movements.

It has been proposed that the nervous system has the capacity to generate a wide variety of movements because it reuses some invariant code. Previous work has identified that dynamics of neural population activity are similar during different movements, where dynamics refer to how the instantaneous spatial pattern of population activity changes in time. Here, we test whether invariant dynamics of neural populations are actually used to issue the commands that direct movement. Using a brain-machine interface (BMI) that transforms rhesus macaques' motor-cortex activity into commands for a neuroprosthetic cursor, we discovered that the same command is issued with different neural-activity patterns in different movements. However, these different patterns were predictable, as we found that the transitions between activity patterns are governed by the same dynamics across movements. These invariant dynamics are low dimensional, and critically, they align with the BMI, so that they predict the specific component of neural activity that actually issues the next command. We introduce a model of optimal feedback control (OFC) that shows that invariant dynamics can help transform movement feedback into commands, reducing the input that the neural population needs to control movement. Altogether our results demonstrate that invariant dynamics drive commands to control a variety of movements and show how feedback can be integrated with invariant dynamics to issue generalizable commands.

Measuring Arm and Hand Joint Kinematics to Estimate Impairment During a Functional Reach and Grasp Task after Stroke.

BACKGROUND: Current approaches to characterizing deficits in upper limb movements after stroke typically focus either on changes in a functional measure, for example, how well a patient can complete a task, or changes in impairment, for example, isolated measurements of joint range of motion. However, there can be notable dissociations between static measures of impairment versus those of function. OBJECTIVE: We develop a method to measure upper limb joint angles during performance of a functional task and use measurements to characterize joint impairment in the context of a functional task. METHODS: We developed a sensorized glove that can precisely measure select finger, hand, and arm joints while participants complete a functional reach-to-grasp task involving manipulation of a sensorized object. RESULTS: We first characterized the accuracy and precision of the glove's joint angle measurements. We then measured joint angles in neurologically intact participants (n = 4 participants, 8 limbs) to define the expected distribution of joint angle variation during task execution. These distributions were used to normalize finger, hand, and arm joint angles in stroke participants (n = 6) as they performed the task. We present a participant-specific visualization of functional joint angle variance which illustrated that stroke participants with nearly identical clinical scores exhibited unique patterns of joint angle variation. CONCLUSIONS: Overall, measuring individual joint angles in the context of a functional task may inform whether changes in functional scores over recovery or rehabilitation are driven by changes in impairment or the development of compensatory strategies, and provide a quantified path toward personalized rehabilitative therapy.

Modulation of neural co-firing to enhance network transmission and improve motor function after stroke.

Stroke is a leading cause of disability. While neurotechnology has shown promise for improving upper limb recovery after stroke, efficacy in clinical trials has been variable. Our central thesis is that to improve clinical translation, we need to develop a common neurophysiological framework for understanding how neurotechnology alters network activity. Our perspective discusses principles for how motor networks, both healthy and those recovering from stroke, subserve reach-to-grasp movements. We focus on neural processing at the resolution of single movements, the timescale at which neurotechnologies are applied, and discuss how this activity might drive long-term plasticity. We propose that future studies should focus on cross-area communication and bridging our understanding of timescales ranging from single trials within a session to across multiple sessions. We hope that this perspective establishes a combined path forward for preclinical and clinical research with the goal of more robust clinical translation of neurotechnology.

Transition from predictable to variable motor cortex and striatal ensemble patterning during behavioral exploration.

Animals can capitalize on invariance in the environment by learning and automating highly consistent actions; however, they must also remain flexible and adapt to environmental changes. It remains unclear how primary motor cortex (M1) can drive precise movements, yet also support behavioral exploration when faced with consistent errors. Using a reach-to-grasp task in rats, along with simultaneous electrophysiological monitoring in M1 and dorsolateral striatum (DLS), we find that behavioral exploration to overcome consistent task errors is closely associated with tandem increases in M1 and DLS neural variability; subsequently, consistent ensemble patterning returns with convergence to a new successful strategy. We also show that compared to reliably patterned intracranial microstimulation in M1, variable stimulation patterns result in significantly greater movement variability. Our results thus indicate that motor and striatal areas can flexibly transition between two modes, reliable neural pattern generation for automatic and precise movements versus variable neural patterning for behavioral exploration.

Low-frequency stimulation enhances ensemble co-firing and dexterity after stroke.

Electrical stimulation is a promising tool for modulating brain networks. However, it is unclear how stimulation interacts with neural patterns underlying behavior. Specifically, how might external stimulation that is not sensitive to the state of ongoing neural dynamics reliably augment neural processing and improve function? Here, we tested how low-frequency epidural alternating current stimulation (ACS) in non-human primates recovering from stroke interacted with task-related activity in perilesional cortex and affected grasping. We found that ACS increased co-firing within task-related ensembles and improved dexterity. Using a neural network model, we found that simulated ACS drove ensemble co-firing and enhanced propagation of neural activity through parts of the network with impaired connectivity, suggesting a mechanism to link increased co-firing to enhanced dexterity. Together, our results demonstrate that ACS restores neural processing in impaired networks and improves dexterity following stroke. More broadly, these results demonstrate approaches to optimize stimulation to target neural dynamics.

Beta band oscillations in motor cortex reflect neural population signals that delay movement onset.

Motor cortical beta oscillations have been reported for decades, yet their behavioral correlates remain unresolved. Some studies link beta oscillations to changes in underlying neural activity, but the specific behavioral manifestations of these reported changes remain elusive. To investigate how changes in population neural activity, beta oscillations, and behavior are linked, we recorded multi-scale neural activity from motor cortex while three macaques performed a novel neurofeedback task. Subjects volitionally brought their beta oscillatory power to an instructed state and subsequently executed an arm reach. Reaches preceded by a reduction in beta power exhibited significantly faster movement onset times than reaches preceded by an increase in beta power. Further, population neural activity was found to shift farther from a movement onset state during beta oscillations that were neurofeedback-induced or naturally occurring during reaching tasks. This finding establishes a population neural basis for slowed movement onset following periods of beta oscillatory activity.

Neurofeedback Control in Parkinsonian Patients Using Electrocorticography Signals Accessed Wirelessly With a Chronic, Fully Implanted Device.

Parkinson's disease (PD) is characterized by motor symptoms such as rigidity and bradykinesia that prevent normal movement. Beta band oscillations (13-30 Hz) in neural local field potentials (LFPs) have been associated with these motor symptoms. Here, three PD patients implanted with a therapeutic deep brain neural stimulator that can also record and wirelessly stream neural data played a neurofeedback game where they modulated their beta band power from sensorimotor cortical areas. Patients' beta band power was streamed in real-time to update the position of a cursor that they tried to drive into a cued target. After playing the game for 1-2 hours each, all three patients exhibited above chance-level performance regardless of subcortical stimulation levels. This study, for the first time, demonstrates using an invasive neural recording system for at-home neurofeedback training. Future work will investigate chronic neurofeedback training as a potentially therapeutic tool for patients with neurological disorders.

Developmental Changes in Skin Barrier and Structure during the First 5 Years of Life.

The structure of the stratum corneum (SC) and the corresponding skin barrier develops from before birth up to about 4 years of age. Large subject-to-subject variability within an age group requires a large population to observe trends in skin barrier properties over time. Barrier function, quantified by transepidermal water loss (TEWL) and SC thickness, was measured on the upper inner arm and dorsal forearm in subjects aged 3 months to 4 years (n = 171) and a subset of mothers (n = 44). The rate of skin surface area expansion as a function of age peaked before birth (∼90 cm2/week) and declined to a steady plateau (∼10 cm2/week) by 1 year of age. SC thickness increased and TEWL decreased, but did not reach adult values until 3-4 years of age. A better understanding of how skin hydration changes after birth suggests that barrier function may be related mechanistically to skin surface area expansion.

Modeling distinct sources of neural variability driving neuroprosthetic control.

Many closed-loop, continuous-control brain-machine interface (BMI) architectures rely on decoding via a linear readout of noisy population neural activity. However, recent work has found that decomposing neural population activity into correlated and uncorrelated variability reveals that improvements in cursor control coincide with the emergence of correlated neural variability. In order to address how correlated and uncorrelated neural variability arises and contributes to BMI cursor control, we simulate a neural population receiving combinations of shared inputs affecting all cells and private inputs affecting only individual cells. When simulating BMI cursor-control with different populations, we find that correlated activity generates faster, straighter cursor trajectories, yet sometimes at the cost of inaccuracies. We also find that correlated variability can be generated from either shared inputs or quickly updated private inputs. Overall, our results suggest a role for both correlated and uncorrelated neural activity in cursor control, and potential mechanisms by which correlated activity may emerge.

Human Cumulative Irritation Tests of Common Preservatives Used in Personal Care Products: A Retrospective Analysis of Over 45 000 Subjects.

The cumulative irritation test (CIT) is an accepted method used to evaluate the skin irritation potential and safety of individual ingredients and formulas of leave-on skin care and cosmetic compounds. Here, we report the results of CITs collected by JOHNSON & JOHNSON Consumer Companies, Inc. (Skillman, NJ), part of an extensive tiered program to evaluate product safety. In the CIT, test formulations were applied to the skin of adults (18-70 years) with no known skin disease or allergies, 3 times per week for 2 weeks using semi-occlusive clinical patches. Preservatives were 1 of up to 16 components of test formulas, and included ethylenediaminetetraacetic acid, diazolidinyl urea, 1,3-Bis(hydroxymethyl)-5,5-dimethylimidazolidine-2,4-dione, parabens, isothiazolinone, phenoxyethanol, sorbates, or benzoates. Skin sites were scored after each patch removal using a 5-point scale, with 0 = no visible reaction and 4 = erythema, marked edema, or substantial vesiculation. Scores were reported as percentage of maximal irritation score. Data were analyzed from 1363 CIT studies (over 45 000 subjects). There were no significant differences in percentage of maximal scores between formulas grouped by preservative types (p > .1). Median score across the entire dataset was 0.44, with most formulas showing none or mild irritation. Although seasonal variations were observed, no correlation was noted between score and preservative concentration. In conclusion, in a large, normal subject dataset, preservatives at typical in-use concentrations did not appear to contribute to skin irritation.

Neural oscillations: beta band activity across motor networks.

Local field potential (LFP) activity in motor cortical and basal ganglia regions exhibits prominent beta (15-40Hz) oscillations during reaching and grasping, muscular contraction, and attention tasks. While in vitro and computational work has revealed specific mechanisms that may give rise to the frequency and duration of this oscillation, there is still controversy about what behavioral processes ultimately drive it. Here, simultaneous behavioral and large-scale neural recording experiments from non-human primate and human subjects are reviewed in the context of specific hypotheses about how beta band activity is generated. Finally, a new experimental paradigm utilizing operant conditioning combined with motor tasks is proposed as a way to further investigate this oscillation.