xuanma/cage_data

Python codes for loading and managing M1 neural data and EMG data collected in the Miller Lab's plastic telemetry cage

Python codes for loading and managing M1 neural data and EMG data collected in the Miller Lab's plastic telemetry cage

Overview

We are using Blackrock Cerebus for M1 data recording and DSPW RCB module for EMG recording on freely moving monkeys wirelessly. Since data format and recording contexts are very different from those done inside the lab, here we don't use the way for data loading and managing in the cds. Instead, we built a framework for such processing in Python. This repository contains the core codes and some examples. Additionally, for free reaching data recorded in lab, these codes are also useful.

In very early versions of these codes, we tried to directly read Blackrock .nev files in Python, but it would take more than 30 minutes to read a single 15-minute file due to the inefficiency of Blackrock BRPY package. As an altenative solution, we first converted Blackrock .nev files into MATLAB .mat files, then read the .mat file in Python. Fortunately, Blackrock has an updated version of BRPY recently and it works pretty well. Therefore, now we can skip the "MATLAB" step and use BRPY to read the .nev files directly.

The codes also include functions for semi-automatic artifacts rejection based on waveform features. Besides, the codes can read data files with sorted single units.

Details about how to use these codes and designing concerns to be continued, check the examples first if you are interested