This repository contains the supplementary data and source code used in our study. The materials are organized into two main sections: Data and Source Code. Below, you will find detailed information on how the data is structured and how to utilize the provided source code for analysis.

Table of Contents

• Data
  • Directory Structure
  • File Naming Convention
  • Data Format
  • Data Fields
• Source Code
  • Overview
  • Entry Point
  • Data Preprocessing
  • Additional Modules
• Usage Instructions
• Dependencies
• Contact

Data

Directory Structure

The data is organized into folders corresponding to different experiments. Each experiment folder contains subfolders for each patient (P1 and P2). Below is the hierarchical structure:

├── AbstractBodies
│ ├── PatientP1
│ │ └── Session1_MUA.pkl
│ └── PatientP2
│ └── Session1_MUA.pkl
├── BodyParts
│ ├── PatientP1
│ │ ├── Session1_MUA.pkl
│ │ └── Session1_SUA.pkl
│ └── PatientP2
│ ├── Session1_P1_MUA.pkl
│ ├── Session1_P2_MUA.pkl
│ └── Session1_SUA.pkl
├── Categorbodies
│ ├── PatientP1
│ │ ├── Session1_MUA.pkl
│ │ ├── Session_Silhouettes_P1_MUA.pkl
│ │ └── Session_Silhouettes_P2_MUA.pkl
│ └── PatientP2
│ ├── Session1_P1_MUA.pkl
│ └── Session1_P2_MUA.pkl
├── EBALocalizer
│ └── PatientP2
│ └── Session1_P2_MUA.pkl
└── RotationTolerance
├── PatientP1
│ └── Session1_MUA.pkl
└── PatientP2
└── Session1_MUA.pkl

File Naming Convention

Each data file follows the naming pattern:

SessionX_PY_.pkl

• SessionX: Corresponds to the recording session number.
• PY: Indicates the part of the session. Used for large files.
• Resolution: Specifies the data resolution, either MUA (Multi-Unit Activity) or SUA (Single-Unit Activity).

Example: Session1_P1_MUA.pkl

Data Format

All data files are in .pkl format and should be opened using Python. Each .pkl file contains a trials structure with entries corresponding to recorded trials.

Data Fields

Within each trial, the following keys are relevant for analysis:

• answer:
  • 1 if the trial was correct.
  • 0 otherwise.
• MUAA:
  • A dictionary with keys formatted as elecX, where X represents the recording electrode number from the Utah array (total of 96 electrodes).
  • Values are NumPy arrays containing spike times for each electrode.
• current_stimul_name:
  • The name of the stimulus presented during the trial.

Source Code

Overview

The source code provided is used to analyze the dataset. It is organized within the Code folder, which serves as the entry point for various analysis scripts. The analysis is conducted at different levels, including:

• Single Electrodes
• Population Analysis
• Decoding
• V1 Modeling

Entry Point

The primary entry point for the source code is the Code folder. This folder contains scripts tailored to analyze data at multiple levels.

Data Preprocessing

To understand how the data is preprocessed, refer to the analysis_basic.py script of the neurovisual package. This script outlines the fundamental preprocessing steps applied to the raw data before analysis together with single recording site analysis.

Additional Modules

Beyond the basic preprocessing, the source code includes extra modules that perform:

• Population analysis: Multi-electrode interactions and patterns
• Decoding analysis: Neural decoding and classification
• V1 modeling: Primary visual cortex response modeling