Cerebellar activity predicts vocalization in fruit bats

Matlab variable with LFP and Spike data recorded from the cerebellum during the production of echolocation and social calls in bats

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README.md

Cerebellum Dataset

% Data Repository related to the paper "Cerebellar activity predicts vocalization in fruit bats" % (currently under minor revision in Current Biology). % % The data is stored in .mat files containing neural recordings from the cerebellum of fruit-eating bats, % captured during the production of both echolocation and social calls.

Data Guide: Cerebellar Activity Predicts Vocalization in Fruit Bats

% % This repository contains data collected from cerebellar recordings in fruit-eating bats during the % production of echolocation and social calls. The data is structured into various .mat files, with details of % each dataset and its specific parameters explained below.

%% 1. *Frequency Tuning LFP % This dataset includes Local Field Potentials (LFP) data captured from 224 channels, organized by stimulus % level and frequency.

*FT_LFP:

* ft: Spike count (224 channels x levels x frequency)
* besterp: Evoked response data across levels (30:15:90) and frequencies (15:5:85)
* bestresponse: Best frequency-band level response (BFBL) for each channel
* cfmt: Characteristic Frequency/Minimum Threshold for each channel (CFMT)

%% 2. *Frequency Tuning Spikes % This dataset contains spike count data from 224 channels, organized similarly by stimulus level and frequency.

*FT_Spikes:

* ft: Spike count (224 channels x levels x frequency)
* N2w: Peri-Stimulus Time Histogram (PSTH) data across levels (30:15:90) and frequencies (15:5:85)
* bestresponse: Best frequency-Best level response (BFBL) for each channel
* cfmt: Characteristic Frequency/Minimum Threshold for each channel (CFMT)

%% 3. *Vocs (Vocalization Data) % This dataset provides information about the call parameters and classification data for both echo and communication calls.

*callparams:

* dur2: Duration of calls, categorized by call type
* pf2: Peak frequency of calls, categorized by call type
* finalMatrix: Cross-correlation matrix of different call types
* newClass: Identifiers for calls used in cross-correlation

*SpikeClassifData:

* Ne: Normalized echo call spike data for training the SVM
* Nc: Normalized communication call spike data for training the SVM
* N2: Spike count data
* N3: Identifiers for spike count data

*LFPClassifData:

* echoData: LFP data during echo calls for training the SVM
* commData: LFP data during communication calls for training the SVM

% --- % This guide outlines the structure of the data, which is organized into several .mat files. % MATLAB version: R2021a.

datacite.yml
Title Cerebellar activity predicts vocalization in fruit bats
Authors Hariharan,Shivani;Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany;ORCID:0009-0000-5467-3858
Palomares,Eugenia González;Institute of Cell Biology and Neuroscience,Goethe University Frankfurt, Frankfurt am Main, Germany;ORCID:0000-0003-3086-7601
Babl,Susanne S.;Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany;ORCID:0000-0003-4818-2782
Jury,Luciana Lopez;Max Planck Institute for Brain Research,Frankfurt am Main, Germany;ORCID:0000-0002-9384-2586
Hechavarria,Julio C.;Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany;ORCID:0000-0001-9277-2339
Description Neural correlate of vocal production within the bat cerebellum: This dataset contains neural recordings from the cerebellum of fruit-eating bats during vocalizations, including both echolocation and social calls. The data is stored in Matlab files and includes Local Field Potentials (LFP) and spike count data from 224 channels, organized by stimulus levels and frequencies. Additionally, the dataset provides vocalization call parameters and classification data for echo and communication calls. The data is structured to support analysis of neural activity associated with vocal production using tools like Support Vector Machines (SVM) for classification of spiking and LFP responses.
License Creative Commons CC0 1.0 Public Domain Dedication (https://creativecommons.org/publicdomain/zero/1.0/)
References Shivani Hariharan, Julio C. Hechavarria: Cerebellar activity predicts vocalization in fruit bats. Current Biology, submitted. [doi:tba] (IsSupplementTo)
Funding DFG, 525183217
Keywords Neuroscience
Electrophysiology
Cerebellum
Vocalisation
Resource Type Dataset