Psychology 4940, Section 995 – Neurophysiology for Cognitive Researchers Syllabus Spring 2014 What: An online seminar to cultivate your understanding of current and classic neurophysiological studies of attention, priming, memory, affect, and decision-making. Who: Instructor: Teresa Hawkes, Ph.D. Email: [email protected] Office: Skype: teresa.hawkes1 Where: Required Course Websites: Online at D2L OU Psychology Seminar 4940 995 Facebook Page: https://www.facebook.com/pages/OU-Psychology-Seminar-4940-995/211328499042918 When: January 13 – May 2, 2014 Why: “THESE days it is easy to get irritated with the exaggerated interpretations of brain imaging — for example, that a single fMRI scan can reveal our innermost feelings — and with inflated claims about our understanding of the biological basis of our higher mental processes.” --Eric Kandel, NY Times, 9-06-2013 We will learn how to interpret current evidence for the neural correlates of cognitive behaviors. Course Overview: Uses D2L system to deliver lecture material, assignments, discussion board activities, and exams. Instructor will post two example slide presentations. The instructor creates and actively guides the Discussion Board, and creates a Facebook page of anatomical, physiological, and cognitive information drawn from peerreviewed sources. Students will learn to think critically about current studies on the neurophysiological basis of cognition. They will become familiar with some of the methods and statistical tools used at the molecular, cellular, systems, and cognitive levels. Course Materials: Original research and review papers supplied by the Instructor. TEXT: Cognitive Neuroscience, 3rd Edition. Marie T. Banich and Rebecca J. Compton. Wadsworth Cengage Learning. Assignments Students select a primary paper from a list of papers in the five key areas of Attention, Priming, Memory, Affect, and Decision-making to present to the class. Students may present a research or modeling paper. All students will read the methods and review papers. Students then create a powerpoint presentation with substantive presentation notes. Powerpoints and notes are posted to D2L Discussion Board. All students must respond substantively to each presentation. A rubric for the powerpoint, presentation notes, and student responses will be provided the first week of class. There will be two midterm exams covering Chapters from the text and the papers being presented. Final exam is essay. Students select four of eight possible long answer and data analysis questions covering primary paper presentations. Grade Components: 1) Powerpoint presentation (100 points) 2) Presentation notes (includes annotation of five of the research paper’s and review paper’s references). (50 points) 3) Discussion Board Participation (100 points) 4) 2 midterm exams (multiple choice questions) covering neurophysiology of Attention, Priming, Memory, Affect, and Decision-making. (75 points each-150 points total) 5) Final essay exam (100 points) Grading Scale: A is 90-100 B is 80-89 C is 70-79 D is 60-69 F is below 60 Academic Misconduct. Two simple academic misconduct rules to remember: 1. All work must be your own; otherwise it is a violation of the academic conduct code. This means that working with another student or students on your homeworks, quizzes, Excel worksheets, exams or discussion contributions is prohibited. Furthermore, using resources from past sections is also prohibited. All written material will be processed by turnitin plagiarism-checking software. 2. See the OU student academic conduct code for all other rules and regulations at http://www.ou.edu/provost/pronew/content/integritymenu.html Other. When contributing to D2L, be respectful of your fellow students. Maintain a professional demeanor in discussions or chats. Work Schedule Week of 1/13 1/20 1/27 2/10 2/17 Topics/Chapters Methods Papers Attention Attention Attention Priming 2/24 3/10 3/17 3/24 Priming Memory SPRING BREAK Memory 3/31 4/7 4/14 4/21 4/28 Memory Affect Affect Decision-making Decision-making Tests Midterm 1 Midterm 2 5/5 Final Exam Tentative Papers Methods Logothetis, N.K., Pauls, J., Augath, M., Trinath, T., and Oeltermann, A . (2001). Neurophysiological investigation of the basis of the fMRI signal. Nature 412, 150-157. Luck, S.J. (2004). Ten simple rules for designing and interpreting ERP experiments. In Handy, T.C., Eventrelated potentials: a methods handbook. Boston: MIT Press. He, B., Yang, L., Wilke, C., and Yuan, H. (2011). Electrophysiological imaging of brain activity and connectivity – challenges and opportunities. IEEE Trans Biomed Eng, 58, 1918-1931. Frank, M.J. and Fossella, J.A. (2011). Neurogenetics and pharmacology of learning, motivation, and cognition. Neuropsychopharmacology Reviews, 36, 133-152. Thayer, J.F., Ahs, F., Fredrikson, M., Sollers III, J.J. and Wager, T.D. (2012). A meta-analysis of heart rate variability and neuroimaging studies: implications for heart rate variability as a marker of stress and health. Neuroscience and Biobehavioral Reviews 36, 747-756. Attention Reviews Corbetta, M., and Shulman, G.L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 201-215. Posner, M.I. (2012). Imaging Attention Networks. NeuroImage, 61, 450-456. Verhaeghen, P. and Cerella, J. (2002). Aging, executive control, and attention: a review of meta-analyses. Neuroscience and Biobehavioral Reviews, 849-857. Dux, P.E. and Marois, R. (2009). The attentional blink: A review of data and theory. Attention, Perception, & Psychophysics, 1683-1700. Best, J.R. and Miller, P.H. (2010). A developmental perspective on executive function. Child Development, 81, 1641-1660. Luck, S.J., Woodman, G.F. and Vogel, E.K. (2000). Event-related potential studies of attention. Trends in Cognitive Sciences, 4, 432-440. Models: Dehaene, S., Changeux, J-P. (2005). Ongoing spontaneous activity controls access to consciousness: a neuronal model for inattentional blindness. PLOS Biology, 910-927. Frith, C. (2001). A framework for studying the neural basis of attention. Neuropsychologia, 1367-1371. Marcovitch, S. and Zelazo, P.D. (2009). A hierarchical competing systems model of the emergence and early development of executive function. Developmental Science, 12, 1-18. Research: Hopfinger, J.B., Woldorff, M.G., Fletcher, E.M., and Mangun, G.R. (2001). Dissociating top-down attentional control from selective perception and action. Neuropsychologia, 1277-1291. Green, J.J. and McDonald, J.J. (2008). Electrical neuroimaging reveals timing of attentional control activity in human brain. PLOS Biology, 1-9. Grent-‘t-Jong, T. and Woldorff, M.G. (2007). Timing and sequence of brain activity in top-down control of visual-spatial attention. PLOS Biology, 5, 114-1126. Milham, M.P., Banich, M.T., Claus, E.D., and Cohen, N.J. (2003). Practice-related effects demonstrate complementary roles of anterior cingulate and prefrontal cortices in attentional control. NeuroImage, 18, 483493. Chennu, S., Craston, P., Wyble, B., and Bowman, H. (2009). Attention increases the temporal precision of conscious perception: verifying the neural-ST2 model. PlOS Computational Biology, 5, 1-13. Fan, J., Byrne, J., Worden, M.S., Guise, K.G., McCandliss, B.D., Fossela, J. and Posner, M.I. (2007). The relation of brain oscillations to attentional networks. Journal of Neuroscience, 27, 6197-6206. Hopf, J.-M. and Mangun, G.R. (2000). Shifting visual attention in space: an electrophysiological analysis using high spatial resolution mapping. Clinical Neurophysiology, 111, 1241-1257. Dien, J., Spencer, K.M. and Donchin, E. (2004). Parsing the late positive complex: mental chronometry and the ERP components that inhabit the neighborhood of the P300. Psychophysiology, 41, 665-678. Priming Reviews Theeuwes, J. (2013). Feature-based attention: it is all bottom-up priming. Philosophical Transactions of the Royal Society B: Biological Sciences; 368, 1-11. Stevens, W.D., Wig, G.S., and Schacter, D.L. (2008). Implicit memory and priming. Learning and memory: a comprehensive reference, volume 2, 623-644. Model Lavigne, F. and Darmon, N. (2008). Dopaminergic neuromodulation of semantic priming in a cortical network model. Neuropsychologia, 46, 3074-3087. Research Wilcox, T., Hirschkowitz, A., Hawkins, L. and Boas, D.A. (2013). The effect of color priming on infant brain and behavior. NeuroImage, doi: 10.1016/j.neuroimage.2013.08.045. Rossell, S.L., Price, C.J. and Nobre A.C. (2003). The anatomy and time course of semantic priming investigated by fMRI and ERPs. Neurpsychologica, 41, 550-564. Ulrich, M., Hoenig, K., Gron, G., and Kiefer, M. (2013). Brain activation during masked and unmasked semantic priming: commonalities and differences. Journal of Cognitive Neuroscience, doi:10.1162/jocn_a_00449. Gibbons, H., Wiegleb, N. and Stahl, J. (2013). Levels of visuo-spatial selection: an ERP study of negative priming. Brain and Cognition, 83, 203-217. Kaiser, D., Walther, C., Schweinberger, S.R., and Kovacs, G. (2013). Dissociating the neural bases of repetition-priming and adaptation in the human brain for faces. Journal of Neurophysiology, doi:10.1152/jn.00277.2013 Hassler, U., Friese, U., Martens, U., Trujillo-Barreto, N. and Gruber, T. (2013). Repetition priming effects dissociate between miniature eye movements and induced gamma-band responses in the human encephalogram. European Journal of Neuroscience, 38, 2425-2433. Memory Reviews Instructor: Dan, Y. & Poo, M-M. (2004). Spike timing-dependent plasticity of neural circuits. Neuron, 44, 23-30. Lomo, T. (2003). The discovery of long-term potentiation. Philosophical Transactions of the royal Society London B, 358, 617-620. Fretham, S.J.B., Carlson, E.S. and Georgieff, M.K. (). The role of iron in learning and memory. Advances in Nutrition, 2, 112-121. West, R. (2011). The temporal dynamics of prospective memory: a review of the ERP and prospective memory literature. Neuropsychologia, 49, 2233-2245. Gomez-Palacio-Schjetnan, A. & Escobar, M.L. (2013). Neurotrophins and synaptic plasticity. Current Topics in Behavioral Neuroscience, 15, 117-36. Models Baddeley, A. (2012). Working memory: theories, models, and controversies. Annual Reviews of Psychology, 63, 1-29. Wallis, G. (2013). Toward a unified model of face and object recognition in the human visual system. Frontiers in Psychology, doi: 10.3389/fpsyg.2013.00497. Research Bliss, T.V.P. & Lomo, T. (1973). Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. Journal of Physiology, 232, 331-356. Luu, P., Tucker, D.M. and Stripling, R. (2007). Neural mechanisms for learning actions in context. Brain Research, 1179, 89-105. Instructor: Markram, H., Lubke, J., Frotscher, M. & Sakmann, B. (1997). Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs. Science, 275, 213-215. Tran, P.V., Dakoji, S., Reise, K.H., Storey, K.K. and Georgieff, M.K. (2013). Fetal iron deficiency alters proteome of adult rat hippocampal synaptosomes. American Journal of Physiology Regul Integr Comp Physiol, doi:10.1152/ajpregu.00292.2013. Klaver, P. & Talsma, D. (2013). Behind the scenes: how visual memory load biases selective attention during processing of visual streams. Psychophysiology, doi: 10.1111/psyp.12126. Kragel, J.E. & Polyn, S.M. (2013). Functional interactions between large-scale networks during memory search. Cerebral Cortex, doi:10.1093/cercor/bht258. Montalbano, A., Baj, G., Papadia, D., Tongiorgi, E., and Sciancalepore, M. (2013). Blockade of BDNF signaling turns chemically-induced long-term potentiation into long-term depression. Hippocampus, 23, 879889. Affect Reviews Olofsson, J.K., Nordin, S., Sequeira, H., and Polich, J. (2008). Affective picture processing: an integrative review of ERP findings. Biological Psychology, 77, 247-265. Schupp, H.T., Flaisch, T., Stockburger, J., and Junghofer, M. (2006). Emotion and attention: event-related brain potential studies. In Anders, Ende, Junghofer, Kissler & Wildgruber (Eds.), Progress in brain research, vol. 156, Chapter 2. Elsevier. Models Thayer, J.F. and Lane, R.D. (2000). A model of neurovisceral integration in emotion regulation and dysregulation. Journal of Affective Disorders, 61, 201-216. Thayer, J.F. and Lane, R.D. (2009). Claude Bernard and the heart-brain connection: further elaboration of a model of neurovisceral integration. Neuroscience and Biobehavioral Reviews, 33, 81-88. Research Aarts, K., Houwer, J. and Pourtois, G. (2013). Erroneous and correct actions have a different affective valence: evidence from ERPs. Emotion, June, epub. Prochnow, D., Hoing, B., Kleiser, R., Linderberg, R., Wittsack, H.-J., Schafer, R., Franz, M. and Seitz, R.J. (2013). The neural correlates of affect reading: an fMRI study on faces and gestures. Behavioural Brain Research, 237, 270-277. Mothes-Lasch, M., Mentzel, H-J., Miltner, W.H.R., and Straube, T. (2013). Amygdala activation to fearful faces under attentional load. Behavioural Brain Research, 237, 172-175. Lane, R.D., McRae, K., Reiman, E.M., Chen, K., Ahern, G.L. and Thayer, J.F. (2009).Neural correlates of heart rate variability during emotion. NeuroImage, 44, 213-222. Pourtois, G. and Vuilleumier, P. (2006). Dynamics of emotional effects on spatial attention in the human visual cortex. In Anders, Ende, Junghofer, Kissler & Wildgruber (Eds.) Progress in Brain Research Vol 156, Chapter 4. Elsevier. Decision-making Reviews Young, J.J. & Shapiro, M.L. (2011). The orbitofrontal cortex and response selection. Annals of the New York Academy of Sciences, 1239, 25-32. Heekeren, H.R., Marrett, S. and Ungerleider, L.G. (2008). The neural systems that mediate human perceptual decision making. Nature Reviews Neuroscience, 9, 467-479. Models Van Vugt, M.K. Simen, P., Nystrom, L.E. and Cohen, J.D. (2012). EEG oscillations reveal neural correlates of evidence accumulation. Frontiers in Neuroscience, doi: 10.3389/fnins.2012.00106. Mazurek, M.D., Roitman, J.D., Ditterich, J. and Shalden, M.N. (2003). A role for neural integrators in perceptual decision making. Cerebral Cortex, 13, 1257-1269. Research Keiflin, R., Reese, R.M., Woods, C.A. and Janak, P.H. (2013). The orbitofrontal cortext as part of a hierarchical neural system mediating choice between two good options. The Journal of Neuroscience, 33, 1598915998. Meister, M.L.R., Hennig, J. and Huk, A.C. (2013). Signal multiplexing and single-neuron computations in LIP during decision-making. Journal of Neuroscience, 33, 2254-2267. Vilares, I., Howard, J.D., Fernandes, H., Gottfried, J.A. and Kording, K.P. (2012). Differential representations of prior and likelihood uncertainty in the human brain. Current Biology, 22, 1641-1648. Payzan-LeNestour, E., Dunne, S., Bossaerts, P. and O’Doherty, J.P. (2013). The neural representation of unexpected uncertainty during value-based decision making. Neuron, 79, 191-201. Chang, L.J. & Sanfey, A.G. (2013). Great expectations: neural computations underlying the use of social norms in decision-making. Social Cognitive & Affective Neuroscience, 3, 277-284.