@article {4453, title = {Heksor: the central nervous system substrate of an adaptive behaviour.}, journal = {J Physiol}, volume = {600}, year = {2022}, month = {08/2022}, pages = {3423-3452}, abstract = {

Over the past half-century, the largely hardwired central nervous system (CNS) of 1970~has become the ubiquitously plastic CNS of today, in which change is the rule not the exception. This transformation complicates a central question in neuroscience: how are adaptive behaviours - behaviours that serve the needs of the individual - acquired and maintained through life? It poses a more basic question: how do many adaptive behaviours share the ubiquitously plastic CNS? This question compels neuroscience to adopt a new paradigm. The core of this paradigm is a CNS entity with unique properties, here given the name heksor from the Greek hexis. A heksor is a distributed network of neurons and synapses that changes itself as needed to maintain the key features of an adaptive behaviour, the features that make the behaviour satisfactory. Through their concurrent changes, the numerous heksors that share the CNS negotiate the properties of the neurons and synapses that they all use. Heksors keep the CNS in a state of negotiated equilibrium that enables each heksor to maintain the key features of its behaviour. The new paradigm based on heksors and the negotiated equilibrium they create is supported by animal and human studies of interactions among new and old adaptive behaviours, explains otherwise inexplicable results, and underlies promising new approaches to restoring behaviours impaired by injury or disease. Furthermore, the paradigm offers new and potentially important answers to extant questions, such as the generation and function of spontaneous neuronal activity, the aetiology of muscle synergies, and the control of homeostatic plasticity.

}, keywords = {Adaptation, Psychological, Animals, central nervous system, Humans, Neuronal Plasticity, Plastics, Synapses}, issn = {1469-7793}, doi = {10.1113/JP283291}, author = {Wolpaw, Jonathan R and Kamesar, Adam} } @article {3389, title = {The simplest motor skill: mechanisms and applications of reflex operant conditioning.}, journal = {Exerc Sport Sci Rev}, volume = {42}, year = {2014}, month = {04/2014}, pages = {82-90}, abstract = {Operant conditioning protocols can change spinal reflexes gradually, which are the simplest behaviors. This article summarizes the evidence supporting two propositions: that these protocols provide excellent models for defining the substrates of learning and that they can induce and guide plasticity to help restore skills, such as locomotion, that have been impaired by spinal cord injury or other disorders.}, keywords = {Animals, Conditioning, Operant, H-Reflex, Humans, Motor Skills, Muscle, Skeletal, Neuronal Plasticity, Reflex, Spinal Cord, Spinal Cord Injuries}, issn = {1538-3008}, doi = {10.1249/JES.0000000000000010}, url = {http://www.ncbi.nlm.nih.gov/pubmed/24508738}, author = {Thompson, Aiko K and Jonathan Wolpaw} } @article {3085, title = {Harnessing neuroplasticity for clinical applications.}, journal = {Brain : a journal of neurology}, volume = {135}, year = {2012}, month = {04/2012}, pages = {e215; author reply e216}, keywords = {Neuronal Plasticity}, issn = {1460-2156}, doi = {10.1093/brain/aws017}, url = {http://www.ncbi.nlm.nih.gov/pubmed/22374936}, author = {Jonathan Wolpaw} } @article {2191, title = {Evolution of brain-computer interfaces: going beyond classic motor physiology.}, journal = {Neurosurg Focus}, volume = {27}, year = {2009}, month = {07/2009}, pages = {E4}, abstract = {

The notion that a computer can decode brain signals to infer the intentions of a human and then enact those intentions directly through a machine is becoming a realistic technical possibility. These types of devices are known as brain-computer interfaces (BCIs). The evolution of these neuroprosthetic technologies could have significant implications for patients with motor disabilities by enhancing their ability to interact and communicate with their environment. The cortical physiology most investigated and used for device control has been brain signals from the primary motor cortex. To date, this classic motor physiology has been an effective substrate for demonstrating the potential efficacy of BCI-based control. However, emerging research now stands to further enhance our understanding of the cortical physiology underpinning human intent and provide further signals for more complex brain-derived control. In this review, the authors report the current status of BCIs and detail the emerging research trends that stand to augment clinical applications in the future.

}, keywords = {Brain, Cerebral Cortex, Humans, Man-Machine Systems, Motor Cortex, Movement, Movement Disorders, Neuronal Plasticity, Prostheses and Implants, Research, Signal Processing, Computer-Assisted, User-Computer Interface}, issn = {1092-0684}, doi = {10.3171/2009.4.FOCUS0979}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19569892}, author = {Leuthardt, E C and Gerwin Schalk and Roland, Jarod and Rouse, Adam and Moran, D} }