Neural decoding articles from across Nature Portfolio

Recent research has focused on restoring speech in populations with neurological deficits. Chen, Wang et al. develop a framework for decoding speech from neural signals, which could lead to innovative speech prostheses.

Here, using neural activity patterns in the inferior frontal gyrus and large language modeling embeddings, the authors provide evidence for a common neural code for language processing.

Single-neuron and population activity in the macaque prefrontal and temporal cortex robustly encodes 24 species-typical behaviours, reciprocity in social interactions and social support.

Populations of neurons in the mouse hippocampus use distinct representational strategies to encode familiarity and episodic social memory.

A brain–computer interface can decode semantic representations of perceived and imagined stimuli at the level of words and phrases from functional MRI recordings of brain activity.

Using long-term brain recordings in patients with chronic pain, we identified objective biomarkers of real-world subjective pain intensity over many months. Spontaneous chronic pain states were predicted most reliably by sustained changes in the activity of the orbitofrontal cortex, whereas acute pain was most associated with signals from the anterior cingulate cortex.

Bidirectional neuromorphic brain interfaces, based on interconnecting brain networks with artificial spiking neural networks, aim to optimize neural prostheses to help people with paralysis to regain autonomy. Their emergence questions the concept of human subjectivation, the continuous process by which we become and remain the subject of our life.