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Methods in neuroscience

Informacje ogólne

Kod przedmiotu: 2500-EN-COG-OB1Z-2 Kod Erasmus / ISCED: 14.4 / (0313) Psychologia
Nazwa przedmiotu: Methods in neuroscience
Jednostka: Wydział Psychologii
Grupy: Cognitive Science
Punkty ECTS i inne: 3.00
Język prowadzenia: angielski
Skrócony opis: (tylko po angielsku)

The aim of the lecture is to introduce students to the wide range of methods which are used in cognitive neuroscience to study brain – behavior relationship. Furthermore, specific applications as well as strengths and limitations of each method will be discussed.

Zajęcia w cyklu "Semestr zimowy 2019/20" (zakończony)

Okres: 2019-10-01 - 2020-01-27
Wybrany podział planu:


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Typ zajęć: Wykład, 30 godzin więcej informacji
Koordynatorzy: (brak danych)
Prowadzący grup: Łukasz Okruszek
Lista studentów: (nie masz dostępu)
Zaliczenie: Egzamin
Pełny opis: (tylko po angielsku)

Cognitive neuroscience is an interdisciplinary field, which aims to investigate neural underpinnings of brain-behavior relationship. To achieve this goal, a wide arrange of methods, ranging from traditional lesion studies to multimodal neuroimaging methods. During the course students will be introduced to the methods used in the cognitive neurosicence research, including behavioral and psychophysics paradigms, neuropsychological lesion studies, psychophysiogical and neurophysiological methods, noninvasive brain stimulation methods, and neuroimaging methods. Both theoretical foundations and practical issues linked to the use of each of the method will be discussed. Furthermore, strengths and shortcomings of each method will be presented to enable students to make informed methodological desciosn while planning their own experiments.

Literatura: (tylko po angielsku)

Kliemann, D., & Adolphs, R. (2018). The social neuroscience of mentalizing: Challenges and recommendations. Current opinion in psychology, 24, 1-6. (T)

Okruszek, Ł., Piejka, A., Wysokiński, A., Szczepocka, E., & Manera, V. (2018). Biological motion sensitivity, but not interpersonal predictive coding is impaired in schizophrenia. (E)

Beadle, J. N., & Tranel, D. (2015). Social Neuroscience: Neuropsychological Perspective. The Oxford Handbook of Social Neuroscience, 49. (ch 5) (T)

Okruszek, Ł., & Rutkowska, A. (2013). Planning disorders in men with schizophrenia and in men with localized frontal lobe lesions. Psychiatria polska, 47, 921-931. (E)

Filmer, H. L., Dux, P. E., & Mattingley, J. B. (2014). Applications of transcranial direct current stimulation for understanding brain function. Trends in neurosciences, 37(12), 742-753.

Marini, M., Banaji, M. R., & Pascual-Leone, A. (2018). Studying implicit social cognition with noninvasive brain stimulation. Trends in cognitive sciences.

van Kemenade, B. M., Muggleton, N., Walsh, V., & Saygin, A. P. (2012). Effects of TMS over premotor and superior temporal cortices on biological motion perception. Journal of Cognitive Neuroscience, 24(4), 896-904.

Ibanez, A., Melloni, M., Huepe, D., Helgiu, E., Rivera-Rei, A., Canales-Johnson, A., ... & Moya, A. (2012). What event-related potentials (ERPs) bring to social neuroscience?. Social neuroscience, 7(6), 632-649. (T)

Okruszek, Ł., Jarkiewicz, M., Gola, M., Cella, M., & Łojek, E. (2018). Using ERPs to explore the impact of affective distraction on working memory stages in schizophrenia. Cognitive, Affective, & Behavioral Neuroscience, 18(3), 437-446. (E)

Shaffer, F., McCraty, R., & Zerr, C. L. (2014). A healthy heart is not a metronome: an integrative review of the heart's anatomy and heart rate variability. Frontiers in psychology, 5, 1040. (T)

Torous, J., Onnela, J. P., & Keshavan, M. (2017). New dimensions and new tools to realize the potential of RDoC: digital phenotyping via smartphones and connected devices. Translational psychiatry, 7(3), e1053. (T)

Okruszek, Ł., Dolan, K., Lawrence, M., & Cella, M. (2017). The beat of social cognition: Exploring the role of heart rate variability as marker of mentalizing abilities. Social neuroscience, 12(5), 489-493. (E)

Kern, R. S., Penn, D. L., Lee, J., Horan, W. P., Reise, S. P., Ochsner, K. N., ... & Green, M. F. (2013). Adapting social neuroscience measures for schizophrenia clinical trials, Part 2: trolling the depths of psychometric properties. Schizophrenia bulletin, 39(6), 1201-1210. (E)

Okruszek, Ł., & Pilecka, I. (2017). Biological motion processing in schizophrenia–Systematic review and meta-analysis. Schizophrenia research, 190, 3-10. (E)

Amaro Jr, E., & Barker, G. J. (2006). Study design in fMRI: basic principles. Brain and cognition, 60(3), 220-232. (T)

Poldrack, R. A. (2012). The future of fMRI in cognitive neuroscience. Neuroimage, 62(2), 1216-1220. (T)

Okruszek, Ł., Wordecha, M., Jarkiewicz, M., Kossowski, B., Lee, J., & Marchewka, A. (2018). Brain correlates of recognition of communicative interactions from biological motion in schizophrenia. Psychological medicine, 48(11), 1862-1871. (E)

Schmälzle, R., O’Donnell, M. B., Garcia, J. O., Cascio, C. N., Bayer, J., Bassett, D. S., ... & Falk, E. B. (2017). Brain connectivity dynamics during social interaction reflect social network structure. Proceedings of the National Academy of Sciences, 114(20), 5153-5158. (E)

Cole, D. M., Smith, S. M., & Beckmann, C. F. (2010). Advances and pitfalls in the analysis and interpretation of resting-state FMRI data. Frontiers in systems neuroscience, 4, 8. (T)

Opisy przedmiotów w USOS i USOSweb są chronione prawem autorskim.
Właścicielem praw autorskich jest Uniwersytet Warszawski.