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PSYC 405

Introduction to FMRI

PSYC 405 teaches you how to actually do brain imaging research: how the scanner turns hydrogen physics into a BOLD signal, how that signal relates to neural activity, and how you go from a raw 4D dataset to a defensible statistical map. The weekly hands-on sessions at Bilkent's MRI scanner are the core of the course — you'll design small experiments, collect data, and analyze it in Python using GLMs, preprocessing pipelines, and connectivity/multivariate methods, with assessment driven by ten quizzes, a midterm, and a final essay. It's the natural bridge between psychology coursework and cognitive neuroscience research, and effectively a prerequisite for any thesis or lab work that uses neuroimaging.

Credit3ECTS5FacultyFaculty of Economics, Administrative, and Social SciencesBölümPsychologyPrePSYC 200 and PSYC 220

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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PSYC 405 için defter ekibi henüz not yazmadı.

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Geçmiş GPA dağılımı 13 dönem · ort. 3.18

DönemCourse CPA
2025-2026 Fall 2.88 1 sec · 23 öğr
2023-2024 Spring 2.68 1 sec · 19 öğr
2022-2023 Spring 3.45 1 sec · 14 öğr
2020-2021 Fall 2.85 1 sec · 5 öğr
2019-2020 Fall 3.02 1 sec · 9 öğr
2018-2019 Fall 3.57 1 sec · 7 öğr
2017-2018 Fall 3.13 1 sec · 9 öğr
2015-2016 Fall 2.91 1 sec · 13 öğr
2013-2014 Fall 3.85 1 sec · 16 öğr
2012-2013 Fall 3.46 1 sec · 15 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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