Work

Making brain–computer interfaces as reliable as muscles

Year: 2025

Type: review

Abstract: Objective. While brain–computer interfaces (BCIs) can restore basic communication to people lacking muscle control, they cannot yet restore actions that require the extremely high reliability of natural (i.e. muscle-based) actions. Most BCI research focuses on neural engineering; it seeks to improve the measurement and analysis of brain signals. But neural engineering alone cannot make BCIs reliable. Approach. A BCI does not simply decode brain activity; it enables its user to acquire a skill that is produced not by nerves and muscles but rather by the BCI. Thus, BCI research should focus also on neuroscience; it should seek to develop BCI skills that emulate natural skills. Main results. A natural skill is produced by a network of neurons and synapses that may extend from cortex to spinal cord. This network has been given the name heksor, from the ancient Greek word hexis. A heksor changes through life; it modifies itself as needed to maintain the key features of its skill, the attributes that make the skill satisfactory. Heksors overlap; they share neurons and synapses. Through their concurrent changes, heksors keep neuronal and synaptic properties in a negotiated equilibrium that enables each to produce its skill satisfactorily. A BCI-based skill is produced by a synthetic heksor, a network of neurons, synapses, and software that produces a BCI-based skill and should change as needed to maintain the skill’s key features. Significance. A synthetic heksor shares neurons and synapses with natural heksors. Like natural heksors, it can benefit from multimodal sensory feedback, using signals from multiple brain areas, and maintaining the skill’s key features rather than all its details. A synthetic heksor also needs successful co-adaptation between its central nervous system and software components and successful integration into the negotiated equilibrium that heksors establish and maintain. With due attention to both neural engineering and neuroscience, BCIs could become as reliable as muscles.

Source: Journal of Neural Engineering

DOI: 10.1088/1741-2552/addd47

Author: Jonathan R Wolpaw

Institutions: State University of New York, University at Albany, State University of New York, Albany Stratton VA Medical Center Albany

Language: English

Topic: EEG and Brain-Computer Interfaces

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $3,325