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PhD Ed. Neuroscience: PHDC720-Experimental Methods in Cognitive Neuroscience


This course explores current tools and research protocols that address contemporary issues in cognitive and educational neuroscience to study the human brain and behavior in healthy and clinical populations. To investigate brain function, experimental research methods and neuroimaging tools will be covered in detail and applied; this includes recent emerging tools that offer exciting opportunities to explore brain function under natural conditions. Students will acquire the skills and the in-depth knowledge involved in behavioral testing and brain imaging (e.g. implementation, uses, limitations, design, resolution, sensitivity, equipment, data type, acquisition, reconstruction, inferences) so they will be able to understand what one can (or cannot) do with each tool, and how to use them. Students will develop the skills to help them appreciate the burgeoning literature in applied cognitive neuroscience, along with its methods and protocols. Ultimately, they will be able to identify the right tools, along with testing and designing appropriate procedures for research in the field of brain and behavior.

ejournal articles

Wong, A. L., Goldsmith, J., Forrence, A. D., Haith, A. M., & Krakauer, J. W. (2017). Reaction times can reflect habits rather than computationsELife6, e28075.

Jackson, A. F., & Bolger, D. J. (2014). The neurophysiological bases of EEG and EEG measurement: A review for the rest of us: Neurophysiological bases of EEGPsychophysiology51(11), 1061–1071.

Retter, T. L., & Rossion, B. (2017). Visual adaptation reveals an objective electrophysiological measure of high-level individual face discriminationScientific Reports7(1), 3269.

Schweinberger, S. R., & Neumann, M. F. (2016). Repetition effects in human ERPs to facesCortex80, 141–153.

Khanna, A., Pascual-Leone, A., Michel, C. M., & Farzan, F. (2015). Microstates in resting-state EEG: Current status and future directionsNeuroscience & Biobehavioral Reviews49, 105–113.

Sitaram, R., Ros, T., Stoeckel, L., Haller, S., Scharnowski, F., Lewis-Peacock, J., Weiskopf, N., Blefari, M. L., Rana, M., Oblak, E., Birbaumer, N., & Sulzer, J. (2017). Closed-loop brain training: The science of neurofeedbackNature Reviews Neuroscience18(2), 86–100.

Thibault, R. T., MacPherson, A., Lifshitz, M., Roth, R. R., & Raz, A. (2018). Neurofeedback with fMRI: A critical systematic reviewNeuroImage172, 786–807.

Bates, E., Wilson, S. M., Saygin, A. P., Dick, F., Sereno, M. I., Knight, R. T., & Dronkers, N. F. (2003). Voxel-based lesion–symptom mappingNature Neuroscience6(5), 448–450.

Price, C. J., Hope, T. M., & Seghier, M. L. (2017). Ten problems and solutions when predicting individual outcome from lesion site after strokeNeuroImage145, 200–208.

Wilcox, T., & Biondi, M. (2015). Fnirs in the developmental sciences: Fnirs in the developmental sciencesWiley Interdisciplinary Reviews: Cognitive Science6(3), 263–283.

Logothetis, N. K. (2008). What we can do and what we cannot do with fMRI. Nature453(7197), 869–878.

Thulborn, K. R., & Davis, D. (2001). Quality assurance for clinical fmri. Current Protocols in Magnetic Resonance Imaging00(1), A6.2.1-A6.2.4.

Damoiseaux, J. S., Rombouts, S. A. R. B., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Beckmann, C. F. (2006). Consistent resting-state networks across healthy subjectsProceedings of the National Academy of Sciences103(37), 13848–13853.

Tian, L., Jiang, T., Wang, Y., Zang, Y., He, Y., Liang, M., Sui, M., Cao, Q., Hu, S., Peng, M., & Zhuo, Y. (2006). Altered resting-state functional connectivity patterns of anterior cingulate cortex in adolescents with attention deficit hyperactivity disorderNeuroscience Letters400(1–2), 39–43.

Bassett, D. S., & Bullmore, E. T. (2009). Human brain networks in health and diseaseCurrent Opinion in Neurology22(4), 340–347.

Ashburner, J., & Friston, K. J. (2000). Voxel-based morphometry—the methodsNeuroimage11(6), 805-821.

Weiskopf, N., Mohammadi, S., Lutti, A., & Callaghan, M. F. (2015). Advances in MRI-based computational neuroanatomy: From morphometry to in-vivo histology. Current Opinion in Neurology28(4), 313–322.


Toga, A. W., & Mazziotta, J. C. (Eds.). (2002). Brain mapping: The methods (2nd ed). Academic Press.

Blake, R., & Sekuler, R. (2006). Perception (5. ed., internat. ed). McGraw-Hill.

Huettel, S. A., Song, A. W., & McCarthy, G. (2008). Functional magnetic resonance imaging (2nd ed). Sinauer Associates.