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PSYC 521

Introduction to Functional Magnetic Resonance Imaging

fMRI sits at the intersection of physics, neuroscience, and statistics, and this course treats it as exactly that: you learn why a spinning proton in a magnetic field eventually becomes a colored blob on a brain map, and what that blob actually licenses you to claim. Work runs from the physics of signal generation and the BOLD hemodynamic response through preprocessing, GLM analysis, and connectivity, with Python simulations, weekly quizzes, a midterm, and hands-on time at the campus scanner. It's a methods backbone for anyone planning cognitive neuroscience research at Bilkent, and a prerequisite-in-spirit for reading the fMRI literature without taking its figures on faith.

Credit3ECTS5FacultyFaculty of Economics, Administrative, and Social SciencesBölümPsychology

Değerlendirme 100% — 3 adım

35%
30%
35%
Final:Essay/written Final Exam 35%
Quiz Weekly Quiz 30%
Midterm Midterm 35%

Önerilen kaynaklar 4 kitap

📖
Önerilen
Functional Magnetic Resonance Imaging
Huettel, Song and McCarthy
Sinauer Associates · Inc.
📖
Önerilen
Handbook of Functional MRI Data Analysis
Russell A. Poldrack, Jeanette A. Mumford
Thomas E. Nichols · Cambridge University Press
📖
Önerilen
Statistical Analysis of fMRI Data
Gregory Ashby, The MIT Press
📖
Önerilen
Literature reading posted on Moodle

Haftalık müfredat 14 hafta

Hafta 1
Introduction and basics: *Introduction and class mechanics; *MRI scanners & safety; *Physics of MRI; *Basic principles of signal generation & image formation; *Contrast mechanisms and pulse sequences; *Origins of BOLD response; *Properties of BOLD response
Hafta 2
Hemodynamic Response & Its Characteristics: *From neuronal to BOLD response; *Hemodynamic impulse response function; *Convolution; delta function; linearity; *Empirical estimation, functional models, finite impulse response models, & non-linear models; *Simulation and analysis of BOLD response: deconvolution, maximum likelihood estimation (Python); *Temporal and spatial (in)dependence of BOLD response
Hafta 3
Hemodynamic Response & Its Characteristics (cont.)
Hafta 4
Signal, Noise & Preprocessing of fMRI Data; Analysis Software: *Signal & noise in fMRI data; *Preprocessing steps; *Data file types; *Software packages & analysis pipelines
Hafta 5
Signal, Noise & Preprocessing of fMRI Data; Analysis Software (cont.)
Hafta 6
Review & Midterm exam
Hafta 7
A Broad Overview of Experimental Design & Analysis Strategies: *Block & event related designs; *Hypothesis testing; *Correction for multiple comparisons; *ROI analyses; *FMRI adaptation; *Group analyses; *Displaying results; *Data-driven approaches; *Independent component analyses (ICA); *Connectivity analyses; *Multivariate analyses
Hafta 8
A Broad Overview of Experimental Design & Analysis Strategies (cont.)
Hafta 9
General Linear Model: *GLM theory; *Python simulations
Hafta 10
General Linear Model: *GLM theory; *Python simulations (cont.)
Hafta 11
Connectivity
Hafta 12
Connectivity (cont.)
Hafta 13
Advanced Statistical Analyses & Methods: Multivariate analyses
Hafta 14
Hands-on session

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Geçmiş GPA dağılımı 8 dönem · ort. 3.43

DönemCourse CPA
2025-2026 Fall 3.09 1 sec · 17 öğr
2023-2024 Spring 3.42 1 sec · 12 öğr
2022-2023 Spring 3.16 1 sec · 16 öğr
2020-2021 Fall 3.96 1 sec · 7 öğr
2019-2020 Fall 3.24 1 sec · 10 öğr
2018-2019 Fall 3.62 1 sec · 6 öğr
2017-2018 Fall 3.12 1 sec · 14 öğr
2016-2017 Fall 3.85 1 sec · 11 öğr

Aggregate course GPA — Bilkent STARS'tan public data. Hoca-bazlı per-section detayı için STARS evaluation report →. Öğrenci anket cevapları KVKK kapsamında defter'de tutulmaz.

⚠️ FZ engelleyen şartlar

45 over 100 from the homework assignments and in-class participation

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