Exploring Cognition with Brain–Machine Interfaces

Traditional brain–machine interfaces decode cortical motor commands to control external devices. These commands are the product of higher-level cognitive processes, occurring across a network of brain areas, that integrate sensory information, plan upcoming motor actions, and monitor ongoing movements. We review cognitive signals recently discovered in the human posterior parietal cortex during neuroprosthetic clinical trials. These signals are consistent with small regions of cortex having a diverse role in cognitive aspects of movement control and body monitoring, including sensorimotor integration, planning, trajectory representation, somatosensation, action semantics, learning, and decision making. These variables are encoded within the same population of cells using structured representations that bind related sensory and motor variables, an architecture termed partially mixed selectivity. Diverse cognitive signals provide complementary information to traditional motor commands to enable more natural and intuitive control of external devices.

Improving the means and methods of training of young fencers aged 9-11 years

Background and Study Aim. Training of motor actions of young athletes requires consideration the peculiarities of the sensitive period of their development. An important component of the training program is the use of training tools that do not harm the health of young athletes. The purpose of the study is to identify the dynamics of physical training and provide an assessment of technical and tactical techniques of fencers (sword) aged 9-11 years under the influence of the author's program. Material and methods. The study involved young fencers (n = 20; age 9-11 years). The study lasted one academic year. The training was held in the gym of the children's and youth sports school "Wave" (Kharkiv, Ukraine). Athletes were divided into two uniform groups: control group (n = 10) and experimental group (n = 10). Classes were held according to the author's program 4 times a week for 2 hours. A survey of trainers of trainers (n = 12) and experienced fencers (n = 30) was conducted. Parents of children agreed to participate in the study. The following tests were used: “Standing Long Jump Test (Broad Jump), cm”; “4x9 m Shuttle test, sec.”; "Hits into the target, 30 sec. points"; "Simulation exercises of a simple fencing combination, sec.". The program "Microsoft Excel" Data Analysis, SPSS was used. The level of reliability is selected p <0.05. Results. Significant changes in the indicators of the control group were obtained: “Standing Long Jump Test (Broad Jump), cm”, (p <0.05); in the test "4x9 m Shuttle test, sec." (p <0.05); both tests have assessment of technical and tactical techniques (p <0.01). In the experimental group, all tests showed positive changes (p <0.01). In comparison of two groups with each other in the tests "Standing Long Jump Test (Broad Jump), cm", "4x9 m Shuttle test, sec." and " Hits into the target, 30 sec. points" there were positive statistically significant changes (p <0.05). In the test "Simulation exercises of a simple fencing combination, sec." no significant changes occurred (p˃0.05). Conclusions. It is recommended to take into account the effects of exercise on the health of young athletes when designing a fencing training program.

Cornerstones of teaching tennis for children aged four to six years

The first tennis training stage, which usually takes place between four and six years of age, cannot simply follow an adult training regime with quantitatively reduced loads. Training should account for children’s cognitive, emotional, social, physical and motor development. This article highlights the cornerstones of early tennis teaching, including fundamental motor skills, which help to develop more complex motor actions, and motor abilities, especially strength fitness, which determines posture, jumping, running and throws. This is achieved through fun plays and games, which should include various coordination tasks providing motor experiences and develop more complex actions in future.

Directed motor actions and choice signalling drive cortical acetylcholine dynamics.

Numerous cognitive functions including attention, learning, and plasticity are influenced by the dynamic patterns of acetylcholine release across the brain. How acetylcholine mediates these functions in cortex remains unclear, as the spatiotemporal relationship between cortical acetylcholine and behavioral events has not been precisely measured across task learning. To dissect this relationship, we quantified motor behavior and sub-second acetylcholine dynamics in primary somatosensory cortex during acquisition and performance of a tactile-guided object localization task. We found that acetylcholine dynamics were spatially homogenous and directly attributable to whisker motion and licking, rather than sensory cues or reward delivery. As task performance improved across training, acetylcholine release to the first lick in a trial became dramatically and specifically potentiated, paralleling the emergence of a choice-signalling basis for this motor action. These results show that acetylcholine dynamics in sensory cortex are driven by directed motor actions to gather information and act upon it.

Sensorimotor Self-organization via Circular-Reactions

Newborns demonstrate innate abilities in coordinating their sensory and motor systems through reflexes. One notable characteristic is circular reactions consisting of self-generated motor actions that lead to correlated sensory and motor activities. This paper describes a model for goal-directed reaching based on circular reactions and exocentric reference-frames. The model is built using physiologically plausible visual processing modules and arm-control neural networks. The model incorporates map representations with ego- and exo-centric reference frames for sensory inputs, vector representations for motor systems, as well as local associative learning that result from arm explorations. The integration of these modules is simulated and tested in a three-dimensional spatial environment using Unity3D. The results show that, through self-generated activities, the model self-organizes to generate accurate arm movements that are tolerant with respect to various sources of noise.

Seeing the future: predictive control in neural models of ocular accommodation

Ocular accommodation is the process of adjusting the eye's crystalline lens so as to bring the retinal image into sharp focus. The major stimulus to accommodation is therefore retinal defocus, and in essence, the job of accommodative control is to send a signal to the ciliary muscle which will minimise the magnitude of defocus. In this paper, we first provide a tutorial introduction to control theory to aid vision scientists without this background. We then present a unified model of accommodative control that explains properties of the accommodative response for a wide range of accommodative stimuli. Following previous work, we conclude that most aspects of accommodation are well explained by dual integral control, with a "fast" or "phasic" integrator enabling response to rapid changes in demand, which hands over control to a "slow" or "tonic" integrator which maintains the response to steady demand. Control is complicated by the sensorimotor latencies within the system, which delay both information about defocus and the accommodation changes made in response, and by the sluggish response of the motor plant. These can be overcome by incorporating a Smith predictor, whereby the system predicts the delayed sensory consequences of its own motor actions. For the first time, we show that critically-damped dual integral control with a Smith predictor accounts for adaptation effects as well as for the gain and phase for sinusoidal oscillations in demand. In addition, we propose a novel proportional-control signal to account for the power spectrum of accommodative microfluctuations during steady fixation, which may be important in hunting for optimal focus, and for the nonlinear resonance observed for low-amplitude, high-frequency input. Complete Matlab/Simulink code implementing the model is provided at https://doi.org/10.25405/data.ncl.14945550

An internal model approach for motor behavior

Interacting with the environment requires a remarkable ability to control, learn, and adapt motor skills to ever-changing conditions. The intriguing complexity involved in the process of controlling, learning, and adapting motor skills has led to the development of many theoretical approaches to explain and investigate motor behavior. This paper will present a theoretical approach built upon the top-down mode of motor control that shows substantial internal coherence and has a large and growing body of empirical evidence: The Internal Models. The Internal Models are representations of the external world within the CNS, which learn to predict this external world, simulate behaviors based on sensory inputs, and transform these predictions into motor actions. We present the Internal Models’ background based on two main structures, Inverse and Forward models, explain how they work, and present some applicability.

Respiratory function modulated during execution, observation, and imagination of walking via SII

The Mirror Neurons System (MNS) consists of brain areas active during actions execution, as well as observation-imagination of the same actions. MNS represents a potential mechanism by which we understand other's action goals. We investigated MNS activation for legs actions, and its interaction with the autonomic nervous system. We performed a physiological and fMRI investigation on the common neural structures recruited during the execution, observation, and imagination of walking, and their effects on respiratory activity. Bilateral SMA were activated by all three tasks, suggesting that these areas are responsible for the core of the MNS effect for walking. Moreover, we observed in bilateral parietal opercula (OP1, secondary somatosensory cortex-SII) evidence of an MNS subtending walking execution-observation-imagination that also modulated the respiratory function. We suggest that SII, in modulating the vegetative response during motor activity but also during observation-imagination, consists of a re-enacting function which facilitates the understanding of motor actions.

Higher-Order Conditioning in the Spatial Domain

Spatial learning and memory, the processes through which a wide range of living organisms encode, compute, and retrieve information from their environment to perform goal-directed navigation, has been systematically investigated since the early twentieth century to unravel behavioral and neural mechanisms of learning and memory. Early theories about learning to navigate space considered that animals learn through trial and error and develop responses to stimuli that guide them to a goal place. According to a trial-and error learning view, organisms can learn a sequence of motor actions that lead to a goal place, a strategy referred to as response learning, which contrasts with place learning where animals learn locations with respect to an allocentric framework. Place learning has been proposed to produce a mental representation of the environment and the cartesian relations between stimuli within it—which Tolman coined the cognitive map. We propose to revisit some of the best empirical evidence of spatial inference in animals, and then discuss recent attempts to account for spatial inferences within an associative framework as opposed to the traditional cognitive map framework. We will first show how higher-order conditioning can successfully account for inferential goal-directed navigation in a variety of situations and then how vectors derived from path integration can be integrated via higher-order conditioning, resulting in the generation of higher-order vectors that explain novel route taking. Finally, implications to cognitive map theories will be discussed.

Bimanual Movements and Chronic Stroke Rehabilitation: Looking Back and Looking Forward

Executing voluntary motor actions in the upper extremities after a stroke is frequently challenging and frustrating. Although spontaneous motor recovery can occur, reorganizing the activation of the primary motor cortex and supplementary motor area takes a considerable amount of time involving effective rehabilitation interventions. Based on motor control theory and experience-dependent neural plasticity, stroke protocols centered on bimanual movement coordination are generating considerable evidence in overcoming dysfunctional movements. Looking backward and forward in this comprehensive review, we discuss noteworthy upper extremity improvements reported in bimanual movement coordination studies including force generation. Importantly, the effectiveness of chronic stroke rehabilitation approaches that involve voluntary interlimb coordination principles look promising.