Abstract
Functional magnetic resonance imaging (fMRI) methods continue to evolve rapidly. Subtle experimental designs have been joined by more powerful data analysis methods to detect and interpret evoked changes in neural activity. Despite constant development, there are several core principles of fMRI methodology that can be used as a guide to understand the current state of the field and whatever advance awaits tomorrow. This chapter concerns itself primarily with this core understanding but considers several specific aspects of fMRI experiments.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Atlas SW, Howard RS II, Maldjian J, Alsop D, Detre JA, Listerud J, et al. Functional magnetic resonance imaging of regional brain activity in patients with intracerebral gliomas: findings and implications for clinical management. Neurosurgery. 1996;38(2):329–38.
Detre JA, Alsop DC, Aguirre GK, Sperling MR. Coupling of cortical and thalamic ictal activity in human partial epilepsy: demonstration by functional magnetic resonance imaging. Epilepsia. 1996;37(7):657–61.
Esteller R, Echauz J, D’Alessandro M, Worrell G, Cranstoun S, Vachtsevanos G, et al. Continuous energy variation during the seizure cycle: towards an on-line accumulated energy. Clin Neurophysiol. 2005;116:517–26.
Schiff ND, Rodriguez-Moreno D, Kamal A, Kim KH, Giacino JT, Plum F, et al. fMRI reveals large-scale network activation in minimally conscious patients. Neurology. 2005;64(3):514–23.
Haxby JV, Gobbini MI, Furey ML, Ishai A, Schouten JL, Pietrini P. Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science. 2001;293:2425–30.
Fox MD, Raichle ME. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci. 2007;8:700–11.
Buchel C, Friston KJ. Assessing interactions among neuronal systems using functional neuroimaging. Neural Netw. 2000;13:871–82.
Price CJ, Friston KJ. Cognitive conjunctions: a new experimental design for fMRI. NeuroImage. 1997;5:261–70.
Sternberg S. Separate modifiability, mental modules, and the use of pure and composite measures to reveal them. Acta Psychol. 2001;106:147–246.
Aguirre GK, Mattar MG, Magis-Weinberg L. de Bruijn cycles for neural decoding. NeuroImage. 2011;56:1293–300.
Grill-Spector K, Malach R. fMR-adaptation: a tool for studying the functional properties of human cortical neurons. Acta Psychol. 2001;107:293–321.
Aguirre GK, Zarahn E, D’Esposito M. The variability of human BOLD hemodynamic responses. NeuroImage. 1998;8:360–9.
D’Esposito M, Zarahn E, Aguirre GK, Rypma B. The effect of normal aging on coupling of neural activity to the BOLD hemodynamic response. NeuroImage. 1999;10(1):6–14.
Worsley KJ, Friston KJ. The analysis of fMRI time-series revisited again. NeuroImage. 1995;2:173–82.
Detre JA, Alsop DC. Perfusion fMRI with arterial spin labeling. In: Bandettini PA, Moonen C, editors. Functional MRI. Berlin: Springer; 1999. p. 47–62.
Aguirre GK, Detre JA, Zarahn E, Alsop DC. Experimental design and the relative sensitivity of BOLD and perfusion fMRI. NeuroImage. 2002;15:488–500.
Friston KJ, Zarahn E, Josephs O, Henson RN, Dale AM. Stochastic designs in event-related fMRI. NeuroImage. 1999;10:607–19.
Liu T. Efficiency, power, and entropy in event-related fMRI with multiple trial types. Part II: design of experiments. Neuroimage. 2004;21:401–13.
Zarahn E, Aguirre GK, D’Esposito M. A trial-based experimental design for fMRI. Neuroimage. 1997;6(2):122–38.
Menon RS, Luknowsky DC, Gati JS. Mental chronometry using latency-resolved functional MRI. Proc Nat Acad Sci U S A. 1998;95:10902–7.
Henson RNA, Price CJ, Rugg MD, Turner R, Friston KJ. Detecting latency differences in event-related BOLD responses: application to words versus nonwords and initial versus repeated face presentations. Neuroimage. 2002;15:83–97.
Engel SA, Rumelhart DE, Wandell BA, Lee AT, Glover GH, Chichilnisky EJ, et al. fMRI of human visual cortex [letter] [published erratum appears in Nature 1994 Jul 14;370(6485):106]. Nature. 1994;369(6481):525.
Sereno MI, Dale AM, Reppas JB, Kwong KK, Belliveau JW, Brady TJ, et al. Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging [see comments]. Science. 1995;268(5212):889–93.
McIntosh AR, Bookstein FL, Haxby JV, Grady CL, et al. Spatial pattern analysis of functional brain images using partial least squares. NeuroImage. 1996;3:143–57.
Glover GH, Li TQ, Ress D. Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn Reson Med. 2000;44:162–7.
Aguirre GK, Zarahn E, D’Esposito M. The inferential impact of global signal covariates in functional neuroimaging analyses. NeuroImage. 1998;8(3):302–6.
Nichols TE, Holmes AP. Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp. 2002;15:1–25.
Nichols T, Hayasaka K. Controlling the familywise error rate in functional neuroimaging: a comparative review. Stat Methods Med Res. 2003;12(5):419–46.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Aguirre, G.K. (2023). Experimental Design and Data Analysis for fMRI. In: Faro, S.H., Mohamed, F.B. (eds) Functional Neuroradiology. Springer, Cham. https://doi.org/10.1007/978-3-031-10909-6_21
Download citation
DOI: https://doi.org/10.1007/978-3-031-10909-6_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-10908-9
Online ISBN: 978-3-031-10909-6
eBook Packages: MedicineMedicine (R0)