Biology subjects

Seignette, K.

Publications and source records attributed to Seignette, K..

3 recordsLinked to original sources

bioRxiv2023

Visuomotor experience induces functional and structural plasticity of chandelier cells

Detailed characterization of interneuron types in primary visual cortex (V1) has greatly contributed to understanding visual perception, yet the role of chandelier cells (ChCs) in visual processing remains poorly characterized. Using viral tracing we found that V1 ChCs predominantly receive monosynaptic input from local layer 5 pyramidal cells and higher-order cortical regions. Two-photon calcium imaging and convolutional neural network modelling revealed that ChCs are visually responsive but weakly selective for stimulus content. In mice running in a virtual tunnel, ChCs respond strongly to events known to elicit arousal, including locomotion and visuomotor mismatch. Repeated exposure of the mice to the virtual tunnel was accompanied by reduced visual responses of ChCs and structural plasticity of ChC boutons and axon initial segment length. Finally, ChCs only weakly inhibited pyramidal cells. These findings suggest that ChCs provide an arousal-related signal to layer 2/3 pyramidal cells that may modulate their activity and/or gate plasticity of their axon initial segments during behaviorally relevant events.

neuroscience↗

bioRxiv2020

SpecSeg: cross spectral power-based segmentation of neurons and neurites in chronic calcium imaging datasets

Imaging calcium signals in neurons of awake, behaving animals using single- or multi-photon microscopy facilitates the study of coding in large neural populations. Such experiments produce massive datasets requiring powerful methods to extract responses from hundreds of neurons. We present SpecSeg, a new open-source toolbox for 1) segmentation of regions of interest (ROIs) representing neuronal structures, 2) inspection and manual editing of ROIs, 3) neuropil correction and signal extraction and 4) matching of ROIs in sequential recordings. SpecSeg uses a novel method for ROI registration, based on temporal cross-correlations of low-frequency components derived by Fourier analysis, of each pixel with its neighbors. The approach is insightful and enables ROI detection around neurons or neurites. It works for single- (miniscope) and multi-photon microscopy data, eliminating the need for separate toolboxes. SpecSeg thus provides an efficient and user-friendly approach for analyzing calcium responses in neuronal structures imaged over prolonged periods of time.

neuroscience↗

bioRxiv2020

A parameter-free statistical test that improves the detection of neuronal responsiveness

Neurophysiological studies depend on a reliable quantification of whether and when a neuron responds to stimulation. Simple methods to determine responsiveness require arbitrary parameter choices, such as binning size, while more advanced model-based methods require fitting and hyperparameter tuning. These parameter choices can change the results, which invites bad statistical practice and reduces the replicability. New recording techniques that yield increasingly large numbers of cells would benefit from a test for cell-inclusion that requires no manual curation. Here, we present the parameter-free ZETA-test, which outperforms t-tests, ANOVAs, and renewal-process-based methods by including more cells at a similar false-positive rate. We show that our procedure works across brain regions and recording techniques, including calcium imaging and Neuropixels data. Furthermore, in illustration of the method, we show in mouse visual cortex that 1) visuomotor-mismatch and spatial location are encoded by different neuronal subpopulations; and 2) optogenetic stimulation of VIP cells leads to early inhibition and subsequent disinhibition.

neuroscience↗