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Neural encoding is the study of how neurons represent information with electrical activity (action potentials) at the level of individual cells or in networks of neurons. Studies of neural encoding aim to characterize the relationship between sensory stimuli or behavioural output and neural signals.
This study, utilizing deep learning to model semantic saturation, shows its tie to repetitive visual stimuli processing by the primary visual cortex, suggesting a bottom-up neurocognitive process.
The hippocampus maps space, but its role in encoding investigatory intentions is unclear. Here the authors show that certain CA1 neurons encode both spatial information and animals’ intention to explore, depending on input from lateral entorhinal cortex.
How neural ensembles encode information remains poorly understood. Here, the authors identify “offsembles”—neurons that are specifically inactivated by sensory stimuli—which, when combined with “onsemble” neurons that are turned on by the stimulus, provide enhanced encoding power to the cortex.
Understanding the link between multiple movement elements and sequence-related responses in the motor cortex remains elusive. This study reveals a multiplicative joint coding mechanism during motor preparation which transfers to additive during execution, potentially explaining the linear readout of elemental movements.
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.
A new study captures nearly the full repertoire of primate natural behaviour and reveals that highly distributed cortical activity maintains multifaceted dynamic social relationships.
A new study shows that, in a numerical judgement task, individuals show differences in neuronal coding of numbers below and above approximately four in the medial temporal lobe.
Neuronal activity in the secondary motor cortex of mice engaged in a foraging task simultaneously represents multiple alternative decision-making strategies.
Recent work uses a language model to gain insight into how the human brain understands the combined meaning of words in a sentence, and uncovers parts of the brain that contribute to this understanding.
