PFC_PT_NE_effect

Overview

PFC_PT_NE_effect is a computational neuroscience project investigating the influence of corticospinal (PT) neurons in the prefrontal cortex (PFC) on network dynamics and information processing. The project explores how PT neurons modulate oscillatory behavior in both control and pathological conditions (e.g., Parkinson’s disease).

Research Objectives

• Analyze the role of PT neurons in the PFC.
• Investigate their influence on oscillatory dynamics, and network states.
• Compare computational model results with experimental data.
• Examine the effects of NE on PT activity.
• Tune PT model parameters to match the FI curve for experimental data in:
  • Baseline (no NE applied)
  • NE applied condition

Methodology

This project employs:

• Computational models using neuron and NetPyNE for single cell and network simulations.
• F-I curve tuning to calibrate PT neuron responses to experimental data.
• LFP and spike data analysis to measure power spectral density, modulation index.
• Comparison of control and Parkinsonian conditions to understand how IT neurons contribute to disease-related network changes.

Requirements

To run the simulations and analyses, you need:

• Python 3.8+
• NetPyNE
• NumPy, SciPy, Matplotlib, and Pandas
• Additional libraries for signal processing:

  pip install numpy scipy matplotlib pandas netpyne neo elephant