Biology subjects

Marius Pachitariu

Publications and source records attributed to Marius Pachitariu.

4 recordsLinked to original sources

bioRxiv2016

Kilosort: realtime spike-sorting for extracellular electrophysiology with hundreds of channels

Advances in silicon probe technology mean that in vivo electrophysiological recordings from hundreds of channels will soon become commonplace. To interpret these recordings we need fast, scalable and accurate methods for spike sorting, whose output requires minimal time for manual curation. Here we introduce Kilosort, a spike sorting framework that meets these criteria, and show that it allows rapid and accurate sorting of large-scale in vivo data. Kilosort models the recorded voltage as a sum of template waveforms triggered on the spike times, allowing overlapping spikes to be identified and resolved. Rapid processing is achieved thanks to a novel low-dimensional approximation for the spatiotemporal distribution of each template, and to batch-based optimization on GPUs. A novel post-clustering merging step based on the continuity of the templates substantially reduces the requirement for subsequent manual curation operations. We compare Kilosort to an established algorithm on data obtained from 384-channel electrodes, and show superior performance, at much reduced processing times. Data from 384-channel electrode arrays can be processed in approximately realtime. Kilosort is an important step towards fully automated spike sorting of multichannel electrode recordings, and is freely available (github.com/cortex-lab/Kilosort).

Neuroscience↗

bioRxiv2016

Suite2p: beyond 10,000 neurons with standard two-photon microscopy

Two-photon microscopy of calcium-dependent sensors has enabled unprecedented recordings from vast populations of neurons. While the sensors and microscopes have matured over several generations of development, computational methods to process the resulting movies remain inefficient and can give results that are hard to interpret. Here we introduce Suite2p: a fast, accurate and complete pipeline that registers raw movies, detects active cells, extracts their calcium traces and infers their spike times. Suite2p runs on standard workstations, operates faster than real time, and recovers ~2 times more cells than the previous state-of-the-art method. Its low computational load allows routine detection of ~10,000 cells simultaneously with standard two-photon resonant-scanning microscopes. Recordings at this scale promise to reveal the fine structure of activity in large populations of neurons or large populations of subcellular structures such as synaptic boutons.

Neuroscience↗

bioRxiv2016

Vision and locomotion shape the interactions between neuron types in mouse visual cortex

In the mouse primary visual cortex (V1), sensory responses are shaped by behavioral factors such as locomotion. These factors are thought to control a disinhibitory circuit, whereby interneurons expressing vasoactive intestinal peptide (Vip) inhibit those expressing somatostatin (Sst), disinhibiting pyramidal cells (Pyr). We measured the effect of locomotion on these neurons and on interneurons expressing parvalbumin (Pvalb) in layer 2/3 of mouse V1, and found in-consistencies with the disinhibitory model. In the presence of large stimuli, locomotion increased Sst cell responses without suppressing Vip cells. In the presence of small stimuli, locomotion increased Vip cell responses without suppressing Sst cells. A circuit model could reproduce each cell types activity from the measured activity of other cell types, but only if we allowed locomotion to increase feedforward synaptic weights while modulating recurrent weights. These results suggest that locomotion alters cortical function by changing effective synaptic connectivity, rather than only through disinhibition.

Neuroscience↗

bioRxiv2016

Inhibitory control of shared variability in cortical networks

Cortical networks exhibit intrinsic dynamics that drive coordinated, large-scale fluctuations across neuronal populations and create noise correlations that impact sensory coding. To investigate the network-level mechanisms that underlie these dynamics, we developed novel computational techniques to fit a deterministic spiking network model directly to multi-neuron recordings from different species, sensory modalities, and behavioral states. The model generated correlated variability without external noise and accurately reproduced the wide variety of activity patterns in our recordings. Analysis of the model parameters suggested that differences in noise correlations across recordings were due primarily to differences in the strength of feedback inhibition. Further analysis of our recordings confirmed that putative inhibitory neurons were indeed more active during desynchronized cortical states with weak noise correlations. Our results demonstrate that network models with intrinsically-generated variability can accurately reproduce the activity patterns observed in multi-neuron recordings and suggest that inhibition modulates the interactions between intrinsic dynamics and sensory inputs to control the strength of noise correlations.

Neuroscience↗