Hariharan_CurrentBio2024_CerebellumDataset/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.