Geometric machine learning is applied to decode brain states from invasive intracortical neural recordings, extending Riemannian methods to the invasive regime where data is scarcer and less stationa...

Neural mechanisms underlying flexible learning and decision-making are not fully understood. Using single-cell calcium imaging, authors here found that neurons in orbitofrontal and secondary motor cortex exhibit complementary roles in reward learning, with neurons in the former exerting a sustained role in conditions of uncertainty.

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Biophysical neuron modeling is an indispensable tool in neuroscience research, with the combination of diverse ion channel kinetics and morphologies being used to explain various single-neuron propert...

Intercellular nanotubular networks mediate material exchange, but their existence in neurons remains to be explored in detail. We identified long, thin dendritic filopodia forming direct dendrite–dend...

Cognition is thought to emerge from the flexible organization of neural activity, yet how this organization reconfigures across behaviors varying in cognitive load remains unclear. We investigated how...

To understand the neural basis of behavior, it is essential to sensitively and accurately measure neural activity at single-neuron and single-spike re…