README.md 2.6 KB
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. % % Variables: % - ft-P2P: Local Field Potential data (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. % % Variables: % - 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. % % Variables: % - 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.