Favero, P. | Search bioRxiv

bioRxiv2026

Long-term stability of cellular-resolution brain-computer interface recordings after stroke

Implantable brain-computer interfaces (iBCIs) with single-neuron resolution are showing great promise for restoring mobility and communication in individuals with spinal cord injury or motor neuron disease. Stroke is the most common cause of acquired brain injury and a major contributor to long-term disability, making chronic stroke a highly relevant indication for iBCIs. However, whether stable intracortical recordings can be obtained from the structurally lesioned human brain is unknown. We report recordings from four 64-channel microelectrode arrays implanted in a participant with chronic aphasia after a large left-hemispheric stroke. The arrays targeted right-hemispheric frontoparietal regions homotopic to the damaged left-hemispheric language network. Across 111 sessions spanning 1,240 days, unit yield and signal quality remained stable. Waveform-based tracking reliably identified individual units across sessions, including across extended recording gaps. Short- and long-term unit stability was comparable to previous reports from iBCI participants without structural brain lesions, and tracked units showed consistent spiking properties across sessions. Our findings provide the first evidence that single-neuron recordings can remain stable over the long term in the stroke-lesioned human brain. They establish the feasibility of chronic, cellular-resolution iBCIs after stroke and support the development of neurorestorative applications for deficits caused by structural brain injury.

neuroscience↗

bioRxiv2026

A right-hemispheric language network at single-neuron resolution

Human language depends on highly specialized left-hemispheric brain networks. Damage to these networks causes severe language impairments (aphasia), one of the most common, debilitating and costly consequences of left-hemispheric brain injury, especially stroke. The limited recovery of aphasia despite intensive rehabilitation efforts emphasizes the need to understand the basis of residual language abilities at the single-neuron level, which has remained unexplored so far. Here, we report large-scale microelectrode recordings with single-unit resolution over a period of ten months from the right-hemispheric prefrontal and parietal association cortex of an individual with stroke-induced chronic non-fluent aphasia. Single neurons exhibited regionally specific responses during comprehension, retrieval and articulation of words, the core operations of language. Distinct subpopulations encoded linguistic information in a task-specific manner, despite correlated firing patterns across tasks. Both single-neuron activity and temporally coordinated population dynamics were predicted by semantic and phonological embeddings derived from large language models (LLMs), revealing a regional dissociation in which semantic features preferentially accounted for prefrontal activity and phonological features for parietal activity. Our findings suggest that right-hemispheric circuits, homotopic to the left language network, can support language processing through structured, functionally organised activity at the level of single neurons. This study opens an avenue for developing mechanistically specific neurorehabilitation and neurorestorative strategies for aphasia, such as brain-computer interfaces (BCIs), that leverage right-hemispheric language resources.

neuroscience↗