Feedforward spiking neural networks are not transformers (yet): a learning-theoretic framework for long-range dependencies and biological efficiency, Fishell, William Peter, Fishell, Gord, Honnuraiah, Suraj

Pyramidal neuron-driven mechanisms actively promote the survival and terminal differentiation of their associated interneuron subtypes.

Biological fidelity: The engine driving the neuromorphic renaissance

Advances in spatially resolved transcriptomics provide unprecedented opportunities to characterise intercellular communication pathways. However, robust and computationally efficient incorporation of ...

This week’s AI research highlights how technological innovation and societal responsibility are increasingly intertwined. Studies range from AI-driven advances ...

Spiking Neural Networks (SNNs) have gained increasing attention for their ability to operate on low-power neuromorphic hardware, offering a pathway toward energy-efficient large language models (LLMs)...

Large Language Models (LLMs) are increasingly excelling and outpacing human performance on many tasks. However, to improve LLM reasoning, researchers either rely on ad-hoc generated datasets or formal...

Newly published work funded by the NIH BRAIN Initiative offers a precision toolkit for accessing cells in the brain and spinal cord with unprecedented accuracy. The new delivery tools, about 1,000 in ...

This issue of Neuron, with accompanying papers in Cell, Cell Genomics, Cell Reports, and Cell Reports Methods, contains studies describing methods for access to neuronal and non-neuronal cell types wi...

Johansen et al. report the results of a community challenge to predict functional enhancers targeting specific brain cell types. By comparing multi-omics machine learning approaches using in vivo data...

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The striatum of the mammalian forebrain can be divided into 2 compartments, the patches and the matrix. We have investigated embryonic events involved in the formation of these compartments in rats. E...