Skip to content

Zoz-HF/Exploring-Cognitive-Control-through-fMRI-Analysis

Repository files navigation

Exploring-Cognitive-Control-through-fMRI-Analysis: A Comprehensive Data Analysis Report

Abstract

This report presents a thorough examination of the Flanker Dataset using functional magnetic resonance imaging (fMRI) to explore the neural basis of cognitive control. The study investigates differences in the BOLD signal between Congruent and Incongruent Flanker trials. Various analyses, including quality control, preprocessing, statistical modeling, and post-analysis, were conducted using the FSL software. The findings offer valuable insights into the neural mechanisms underlying cognitive control and response inhibition.

Table of Contents

Introduction

This study investigates cognitive control processes, particularly attention and response inhibition, using the Flanker Dataset and fMRI. This report details the experimental design, data collection procedures, and a comprehensive analysis pipeline.

Experimental Design

Flanker Task
Figure 1, Flanker Task Trial

The Flanker task, a well-established paradigm for studying cognitive control, was employed. Participants were presented with Congruent and Incongruent Flanker trials, requiring a button press based on the central arrow's direction.

Data Collection

Twenty-six adult participants underwent 2 fMRI runs while performing the Flanker task. High-resolution anatomical images and functional scans were acquired.

Analysis

Project Workflow
Figure 2, Project Workflow

Quality Control

Quality control procedures identified motion artifacts in specific subjects, addressing potential confounds in the subsequent analysis.

Preprocessing

Anatomical and functional images underwent preprocessing steps, including brain extraction, temporal filtering, motion correction, smoothing, registration of functional to anatomical, and normalization to the MNI152 template.

First-Level Analysis

The first-level analysis included GLM modeling with contrasts for congruent and incongruent conditions. Post-stats analysis identified activated pixels and clusters.

Second-Level Analysis

Different algorithms, including Fixed Effect, Flame 1, and Simple OLS, were applied in the second-level analysis to determine the most effective approach, which was "Fixed Effect".

Third-Level Analysis

Whole-brain analysis was performed using Flame 1 based on the Fixed Effect algorithm.

ROI Analysis

Regions of interest (ROIs) were identified and confirmed using a confirmation test to ensure the significance of the identified clusters.

Results and Interpretation

Lateral Occipital Cortex, Inferior Division

Lateral Occipital Cortex, Inferior Division
Figure 3, Lateral Occipital Cortex, Inferior Division

  • To reduce false positives, Eklund (2016) suggested accepting only P-values < 0.001.
  • Lateral Occipital Cortex, Inferior Division: Associated with visual processing, object recognition, and scene perception.
  • Flanker Task: Although the task focuses on cognitive control, participants still engage early visual areas while processing visual stimuli.

Lateral Occipital Cortex, Superior Division

Lateral Occipital Cortex, Superior Division
Figure 4, Lateral Occipital Cortex, Superior Division

  • Lateral Occipital Cortex, Superior Division: Associated with processing visual motion information.
  • Flanker Task: Focuses on cognitive control, but participants still process visual motion information while viewing stimuli.

Precentral Gyrus

Precentral Gyrus
Figure 5, Precentral Gyrus

  • Precentral Gyrus: Associated with motor control and movement initiation.
  • Flanker Task: Requires cognitive control. Participants inhibit responses, supported by regions like the dorsolateral prefrontal cortex, which communicate with the precentral gyrus for motor execution, emphasizing its role in response control.
  • Acknowledged no direct task link, such as activation of the dorsomedial prefrontal cortex.

Discussion

The results revealed indirect relationships between confirmed clusters and the Flanker task. The discussion interprets these findings in the context of existing literature and theoretical frameworks.

Conclusion

Despite indirect relationships observed, the study provides valuable insights into the neural mechanisms underlying cognitive control and response inhibition during the Flanker task.

References

  • Kelly, A.M., Uddin, L.Q., Biswal, B.B., Castellanos, F.X., Milham, M.P. (2008). Competition between functional brain networks mediates behavioral variability. Neuroimage, 39(1):527-37
  • Soares, J.M., Magalhães, R., Moreira, P.S., Sousa, A., Ganz, E., Sampaio, A., Alves, V., Marques, P., and Sousa, N. (2016). A Hitchhiker’s Guide to Functional Magnetic Resonance Imaging. Front. Neurosci. 10:515. doi: 10.3389/fnins.2016.00515
  • AndysBrainBook website (https://andysbrainbook.readthedocs.io/en/latest/)

Submission

This Report, authored by Ziyad Hossam ElFayoumy, was submitted as the final project for the "fMRI Data Analysis" course, under the guidance of Prof. Meena M. Makary.

Scripts

The repository includes all scripts utilized in the analysis. These scripts, adapted from Andy's Brain Book, proved to be versatile and contributed significantly to achieving similar results.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages