A cortical information bottleneck during decision-making.

Decision-making emerges from distributed computations across multiple brain areas, but it is unclear the brain distributes the computation. In deep learning, artificial neural networks use multiple areas (or layers) to form optimal representations of task inputs. These optimal representations are to perform the task well, but so they are invariant to other irrelevant variables.

WaveMAP for identifying putative cell types from in vivo electrophysiology.

Action potential spike widths are used to classify cell types as either excitatory or inhibitory; however, this approach obscures other differences in waveform shape useful for identifying more fine-grained cell types. Here, we present a protocol for using WaveMAP to generate nuanced average waveform clusters more closely linked to underlying cell types. We describe steps for installing WaveMAP, preprocessing data, and clustering waveform into putative cell types.