Exploring Cognition with Brain–Machine Interfaces

Abstract

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.

Cognition through internal models: Mirror neurons as one manifestation of a broader mechanism

“…Unlike concept cells, PPC neurons respond to many diverse stimuli in seemingly random ways at an individual cell level. For example, a cell encoding hand movements was as likely as not to encode a shoulder movement ( 20, 47 ). Nonetheless, neurons exhibit clear structure at a population level, forming associations between related variables, consistent with this work.…”

A Multi-Site Accelerator-Rich Processing Fabric for Scalable Brain-Computer Interfacing

“…A growing interest in distributed analyses of the brain [1,13,25,26] has motivated the design of rudimentary multi-site BCIs [31,32,101]. Prior studies [31,32] propose microchips that stream sensor data wirelessly to a central hub outside the skull using back-scattering radio techniques.…”

“…Brain-computer interfaces (BCIs) sense the electrical activity of biological neurons and electrically stimulate them to "rewire" neuronal circuits. By directly connecting brains to computers, BCIs help advance our understanding of the brain and the mind [1,2], offer treatment of neurological disorders [2][3][4][5][6], enable industrial robotics [7], permit novel modes of personal entertainment [8], and more.…”

“…Complicating BCI design further is the emergence of applications that read and process neural activity from many brain sites over time [1,13,25,26]. This is because the brain's functions (and disorders) are ultimately based on physical and functional connectivity between brain regions that evolve over time [1,13,25,26].…”

Preventive Mental Health Care: A Complex Systems Framework for Ambient Smart Environments

“…Conceptualising and describing how human cognition and behaviour entangles and interacts with smart technology has been the topic of a recent work in philosophy of cognitive science (Hansain et al, 2021;Singh et al, 20221;Bruineberg and Fabry, 2022;Andersen et al, 2022), while the topic of subjective wellbeing is now a topic of interest in computational cognitive science (Miller et al, 2021;Smith et al, 2022). Understanding the interaction between the two -between smart technology and wellbeing -has been a driving question behind numerous empirical studies, but as researchers have noted explicitly, the lack of a coherent theoretical framework has proved troubling (Orben, 2020).…”