Repeatability of electromyography recordings and muscle synergies during gait among children with cerebral palsy.

Background: Clinical gait analysis is commonly used in the evaluation and treatment of children with cerebral palsy (CP). While the repeatability of kinematic and kinetic measures of gait has previously been evaluated, the repeatability of electromyography (EMG) recordings or measures calculated from EMG data, such as muscle synergies, remains unclear for this population.

Research Question: Are EMG recordings and muscle synergies from clinical gait analysis repeatable between visits for children with CP?

Methods: We recruited 20 children with bilateral CP who had been referred for clinical gait analysis.

Optogenetic surface stimulation of the rat cervical spinal cord.

Electrical intraspinal microstimulation (ISMS) at various sites along the cervical spinal cord permits forelimb muscle activation, elicits complex limb movements and may enhance functional recovery after spinal cord injury. Here, we explore optogenetic spinal stimulation (OSS) as a less invasive and cell type-specific alternative to ISMS. To map forelimb muscle activation by OSS in rats, adeno-associated viruses (AAV) carrying the blue-light sensitive ion channels channelrhodopsin-2 (ChR2) and Chronos were injected into the cervical spinal cord at different depths and volumes.

Predictive Coding in Area V4: Dynamic Shape Discrimination under Partial Occlusion.

The primate visual system has an exquisite ability to discriminate partially occluded shapes. Recent electrophysiological recordings suggest that response dynamics in intermediate visual cortical area V4, shaped by feedback from prefrontal cortex (PFC), may play a key role. To probe the algorithms that may underlie these findings, we build and test a model of V4 and PFC interactions based on a hierarchical predictive coding framework.

The bilingual language network: Differential involvement of anterior cingulate, basal ganglia and prefrontal cortex in preparation, monitoring, and execution.

Research on the neural bases of bilingual language control has largely overlooked the role of preparatory processes, which are central to cognitive control. Additionally, little is known about how the processes involved in global language selection may differ from those involved in the selection of words and morpho-syntactic rules for manipulating them. These processes were examined separately in an fMRI experiment, with an emphasis on understanding how and when general cognitive control regions become activated.

Non-neural Muscle Weakness Has Limited Influence on Complexity of Motor Control during Gait.

Cerebral palsy (CP) and Duchenne muscular dystrophy (DMD) are neuromuscular disorders characterized by muscle weakness. Weakness in CP has neural and non-neural components, whereas in DMD, weakness can be considered as a predominantly non-neural problem. Despite the different underlying causes, weakness is a constraint for the central nervous system when controlling gait.

Intraspinal microstimulation for respiratory muscle activation.

A complex propriospinal network is synaptically coupled to phrenic and intercostal motoneurons, and this makes it difficult to predict how gray matter intraspinal microstimulation (ISMS) will recruit respiratory motor units. We therefore mapped the cervical and high thoracic gray matter at locations which ISMS activates diaphragm (DIA) and external intercostal (EIC) motor units. Respiratory muscle electromyography (EMG) was recorded in anesthetized female spinally intact adult rats while a stimulating electrode was advanced ventrally into the spinal cord in 600μm increments.

Human aging reduces the neurobehavioral influence of motivation on episodic memory.

The neural circuitry mediating the influence of motivation on long-term declarative or episodic memory formation is delineated in young adults, but its status is unknown in healthy aging. We examined the effect of reward and punishment anticipation on intentional declarative memory formation for words using an event-related functional magnetic resonance imaging (fMRI) monetary incentive encoding task in twenty-one younger and nineteen older adults. At 24-hour memory retrieval testing, younger adults were significantly more likely to remember words associated with motivational cues than neutral cues.

Muscle recruitment and coordination during upper-extremity functional tests.

Performance-based tests, such as the Jebsen Taylor Hand Function Test or Chedoke Arm and Hand Activity Inventory, are commonly used to assess functional performance after neurologic injury. However, the muscle activity required to execute these tasks is not well understood, even for unimpaired individuals. The purpose of this study was to evaluate unimpaired muscle recruitment and coordination of the dominant and non-dominant limbs during common clinical tests.

Dynamic representation of partially occluded objects in primate prefrontal and visual cortex.

Successful recognition of partially occluded objects is presumed to involve dynamic interactions between brain areas responsible for vision and cognition, but neurophysiological evidence for the involvement of feedback signals is lacking. Here, we demonstrate that neurons in the ventrolateral prefrontal cortex (vlPFC) of monkeys performing a shape discrimination task respond more strongly to occluded than unoccluded stimuli. In contrast, neurons in visual area V4 respond more strongly to unoccluded stimuli.

From the statistics of connectivity to the statistics of spike times in neuronal networks.

An essential step toward understanding neural circuits is linking their structure and their dynamics. In general, this relationship can be almost arbitrarily complex. Recent theoretical work has, however, begun to identify some broad principles underlying collective spiking activity in neural circuits.

Honeybees in a virtual reality environment learn unique combinations of colour and shape.

Honeybees are well-known models for the study of visual learning and memory. Whereas most of our knowledge of learned responses comes from experiments using free-flying bees, a tethered preparation would allow fine-scale control of the visual stimuli as well as accurate characterization of the learned responses. Unfortunately, conditioning procedures using visual stimuli in tethered bees have been limited in their efficacy.

Regenerative Rehabilitation: Combining Stem Cell Therapies and Activity-Dependent Stimulation.

The number of clinical trials in regenerative medicine is burgeoning, and stem cell/tissue engineering technologies hold the possibility of becoming the standard of care for a multitude of diseases and injuries. Advances in regenerative biology reveal novel molecular and cellular targets, with potential to optimize tissue healing and functional recovery, thereby refining rehabilitation clinical practice. The purpose of this review is to (1) highlight the potential for synergy between the fields of regenerative medicine and rehabilitation, a convergence of disciplines known as regenerative rehabilitation; (2) provide translational examples of regenerative rehabilitation within the context of neuromuscular injuries and diseases; and (3) offer recommendations for ways to leverage activity dependence via combined therapy and technology, with the goal of enhancing long-term recovery.

Electromyography Data Processing Impacts Muscle Synergies during Gait for Unimpaired Children and Children with Cerebral Palsy.

Muscle synergies calculated from electromyography (EMG) data identify weighted groups of muscles activated together during functional tasks. Research has shown that fewer synergies are required to describe EMG data of individuals with neurologic impairments. When considering potential clinical applications of synergies, understanding how EMG data processing impacts results and clinical interpretation is important.

Learning to see again: biological constraints on cortical plasticity and the implications for sight restoration technologies.

The 'bionic eye'-so long a dream of the future-is finally becoming a reality with retinal prostheses available to patients in both the US and Europe. However, clinical experience with these implants has made it apparent that the visual information provided by these devices differs substantially from normal sight. Consequently, the ability of patients to learn to make use of this abnormal retinal input plays a critical role in whether or not some functional vision is successfully regained.

A Biologically Plausible Action Selection System for Cognitive Architectures: Implications of Basal Ganglia Anatomy for Learning and Decision-Making Models.

Several attempts have been made previously to provide a biological grounding for cognitive architectures by relating their components to the computations of specific brain circuits. Often, the architecture's action selection system is identified with the basal ganglia. However, this identification overlooks one of the most important features of the basal ganglia-the existence of a direct and an indirect pathway that compete against each other.

Dopaminergic modulation of basal ganglia output through coupled excitation-inhibition.

Learning and maintenance of skilled movements require exploration of motor space and selection of appropriate actions. Vocal learning and social context-dependent plasticity in songbirds depend on a basal ganglia circuit, which actively generates vocal variability. Dopamine in the basal ganglia reduces trial-to-trial neural variability when the bird engages in courtship song.

Flexible and stretchable nanowire-coated fibers for optoelectronic probing of spinal cord circuits.

Studies of neural pathways that contribute to loss and recovery of function following paralyzing spinal cord injury require devices for modulating and recording electrophysiological activity in specific neurons. These devices must be sufficiently flexible to match the low elastic modulus of neural tissue and to withstand repeated strains experienced by the spinal cord during normal movement. We report flexible, stretchable probes consisting of thermally drawn polymer fibers coated with micrometer-thick conductive meshes of silver nanowires.

Robust information propagation through noisy neural circuits.

Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in these population responses, leading to insights about the role of covariability among neurons, tuning curve shape, etc. However, the informativeness of neural responses is not the only relevant feature of population codes; of potentially equal importance is how robustly that information propagates to downstream structures.

Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface.

Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites eventually strengthen. It was also found that effective spike-stimulus delays are consistent with experimentally derived spike-timing-dependent plasticity (STDP) rules, suggesting that STDP is key to drive these changes.

Encoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus-Driven Systems.

Highly connected recurrent neural networks often produce chaotic dynamics, meaning their precise activity is sensitive to small perturbations. What are the consequences of chaos for how such networks encode streams of temporal stimuli? On the one hand, chaos is a strong source of randomness, suggesting that small changes in stimuli will be obscured by intrinsically generated variability. On the other hand, recent work shows that the type of chaos that occurs in spiking networks can have a surprisingly low-dimensional structure, suggesting that there may be room for fine stimulus features to be precisely resolved.

Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks.

A large body of experimental and theoretical work on neural coding suggests that the information stored in brain circuits is represented by time-varying patterns of neural activity. Reservoir computing, where the activity of a recurrently connected pool of neurons is read by one or more units that provide an output response, successfully exploits this type of neural activity. However, the question of system robustness to small structural perturbations, such as failing neurons and synapses, has been largely overlooked.

Analysis of Neuronal Spike Trains, Deconstructed.

As information flows through the brain, neuronal firing progresses from encoding the world as sensed by the animal to driving the motor output of subsequent behavior. One of the more tractable goals of quantitative neuroscience is to develop predictive models that relate the sensory or motor streams with neuronal firing. Here we review and contrast analytical tools used to accomplish this task.

Dimensionality reduction in neuroscience.

The nervous system extracts information from its environment and distributes and processes that information to inform and drive behaviour. In this task, the nervous system faces a type of data analysis problem, for, while a visual scene may be overflowing with information, reaching for the television remote before us requires extraction of only a relatively small fraction of that information. We could care about an almost infinite number of visual stimulus patterns, but we don't: we distinguish two actors' faces with ease but two different images of television static with significant difficulty.

Dynamic Signal Tracking in a Simple V1 Spiking Model.

This work is part of an effort to understand the neural basis for our visual system's ability, or failure, to accurately track moving visual signals. We consider here a ring model of spiking neurons, intended as a simplified computational model of a single hypercolumn of the primary visual cortex of primates. Signals that consist of edges with time-varying orientations localized in space are considered.