Başar Eroğlu, Canan

Demiralp, Tamer

Duru, Adil Deniz

Erdoğdu, Emel

Kurt, Elif

Uslu, Atilla

English

İstanbul Üniversitesi Açık Erişim Sistemi

humanbrainmapping.org/OHBM2014  Celebrating 20 YearsOHBM 2014 Annual Meeting   June 8-12CCH-Congress Center Hamburg          Hamburg, Germanyposter listingsTo view full abstract text and ePosters, visitww4.aievolution.com/hbm14011222177 Effects of the Steady-State Visual Stimuli on the On-Going Alpha Rhythm Elif Kurt1,2, Basri Erdoğan3, Ali Bayram4, Ani Kıçik1, Tamer Demiralp5 1Istanbul University, Institute of Experimental Medicine, Department of Neuroscience, Istanbul, Turkey, 2Istanbul University, Hulusi Behçet Life Sciences Research Laboratory, Istanbul, Turkey, 3Istanbul Kültür University, Department of Electronic Engineering, Istanbul, Turkey, 4Uskudar University, Istanbul, Turkey, 5Istanbul University, Istanbul Faculty of Medicine, Department of Physiology, Istanbul, Turkey 2178 EEG source connectivity analysis: from dense array recordings to brain networks Mahmoud Hassan1, Claude Berrou2, Olivier dufor2, Isabelle Merlet1, Fabrice Wendling1 1Université de Rennes1, Rennes, France, 2Télécom Bretagne (Institut Mines-Télécom), Brest, France 2179 Changes of the coupling of the Broca’s area  and language network following cTBS in  healthy subjects Woo-Kyoung Yoo1, Marine Vernet2, Shahid Bashir3, Anna-Katharine Brem4, Frederick Ifert-Miller5,  Ahn HyunJung6, Chang-Hwan Im7, Mark Eldaief5, Alvaro Pascual-Leone5 1Hallym University, Anyang, Korea, Republic of, 2Harvard Medical School — Berenson-Allen Center for Noninvasive Brain Stimulation, N/A, 3Harvard Medical School — Berenson-Allen Center for Noninvasive Brain Stimulation, Boston, MA, 4Berenson-Allen Center for Noninvasive Brain Stimulation, Harvard Medical School, Boston, United States, 5Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, 6Hallym Institute for Translational Genomics & Bioinformatics, Anyang, Korea, Republic of, 7Department of Biomedical Engineering, Hanyang Universiy, Seoul, Korea, Republic of 2180 CLARA: Classical LORETA Analysis  Recursively Applied Todor Iordanov1, Karsten Hoechstetter2, Patrick Berg1, Isabella Paul-Jordanov1, Michael Scherg1 1BESA GmbH, Gräfelfing, Germany, 2Munich University of Applied Sciences, Munich, Germany 2181 Volume Conduction and Hurst Exponent Estimation for the EEG Duncan Blythe1,2, Stefan Haufe3, Klaus-Robert Müller4,1,5, Vadim Nikulin6,1 1BCCN Berlin, Berlin, Germany, 2TU Berlin, Berlin, Germany, 3City College of New York, New York, United States, 4Technische Universität Berlin, Berlin, Germany, 5Korea University, Seoul, Korea, Republic of, 6Charite, Berlin, Germany 2182 Effect of Handedness on P200 and its Relation  with Change Detection Gökçer Eskikurt1, Numan Ermutlu2,  Ümmühan İşoğlu-Alkaç3 1Istanbul University, Institute of Experimental Medicine, Department of Neuroscience, Istanbul, Turkey, 2Istanbul Bilim University, Faculty of Medicine, Department of Physiology, Istanbul, Turkey, 3Istanbul University, Istanbul Faculty of Medicine, Department  of Physiology, Istanbul, Turkey 2183 Dynamic Changes of Brain Functional Connectivity Petr Klimes1, Jiří Janeček1, Pavel Jurák1,  Josef Halámek1, Jan Chládek1, Milan Brázdil2 1Institute of Scientific Instruments of the ASCR, v.v.i., Brno, Czech Republic, 2Behavioral and Social Neuroscience Research Group, CEITEC-Central European Institute of Technology, Brno,  Czech Republic 2184 Measurement of Cognitive Dynamics during Video Watching Through Event-Related Potentials Emel Erdogdu1, Elif Kurt2,3, Adil Deniz Duru4, Atilla Uslu5, Canan Basar Eroglu6, Tamer Demiralp5 1University of Bremen, Bremen, Germany, 2Istanbul University, Institute of Experimental Medicine, Department of Neuroscience, Istanbul, Turkey, 3Istanbul University, Hulusi Behçet Life Sciences Research Laboratory, Istanbul, Turkey, 4Marmara University, Istanbul, Turkey, 5Istanbul University, Istanbul Faculty of Medicine, Department of Physiology, Istanbul, Turkey, 6Institute of Psychology and Cognition Research, University of Bremen, Bremen, Germany 2185 The complexity of brain dynamics increased with age: an EEG Study Junling Gao1,2, Raymond Cheung3, Jicong Fan1,  Y.S. Hung4, Hinhung Sik5, Albert So6, Zhiguo Zhang7 1Centre of Buddhists Studies, The University of Hong Kong, Hong Kong, Hong Kong, 2Dept. of EEE, The University of Hong Kong, Hong Kong, 3Dept. of Medicine, The University of Hong Kong, Hong Kong, Hong Kong, 4Dept. of EEE, The University of Hong Kong, Hong Kong, Hong Kong, 5Centre of Buddhism Studies, The University of Hong Kong, Hong Kong, Hong Kong, 6The Asian Institute of Built Environment (AIBE), Hong Kong, Hong Kong, 7Department of Electrical and Electronic Engineering, The University of Hong Kong., Hong Kong, China Imaging MethodsEEG continuedMeasurement of Cognitive Dynamics during Video Watching Through Event-Related Potentials Emel Erdogdu1, Elif Kurt2,3, Adil Deniz Duru4, Atilla Uslu5, Canan Basar-Eroglu6, Tamer Demiralp51 University of Bremen, Bremen, Germany 2 Istanbul University, Institute of Experimental Medicine, Department of Neuroscience, Istanbul, Turkey 3 Istanbul University, Hulusi Behçet Life Sciences Research Laboratory, Istanbul, Turkey 4 Marmara University, School of Physical Education and Sports, Istanbul, Turkey 5 Istanbul University, Istanbul Faculty of Medicine, Department of Physiology, Istanbul, Turkey 6 Institute of Psychology and Cognition Research, University of Bremen, Bremen, Germany Introduction The present study aims to develop a method to follow the cognitive dynamics in the electroencephalogram (EEG) during viewing a video. To obtain a high signal/noise (S/N) ratio we aimed to record event related potentials (ERPs) under passive condition by introducing temporal triggers in the visual stream that do not significantly interfere with the real world like dynamic visual experience. The hypothesis was that slight transient changes in short sequences of video frames will produce significant ERP waveforms resembling the P3a wave obtained with the distracters of the novelty paradigm [1, 4, 5], which might be used to follow the dynamics of the attention focused to the content of the video and to measure the changing distractibility of the subject due to the changing engagement [2] to the content of the video.  Methods We chose video segments with strong changes in the emotional valence and arousal level, such that the engagement of the subjects to the video content might be modulated. A transient light intensity effect was introduced in the videos by increasing the luminance through adding a value of 50 to the present RGB values for 150 ms (4 frames) periods with a mean ISI of 3 sec (randomized between 2-4 sec). Behavioral correlates of the engagement to the video content were tested with a long-term memory (LTM) task, where either frames from the viewed or unknown distracting frames were shown in a separate session 30 min after the video presentation. The reaction times of recalled pictures, indicated by a left button press and non-recalled pictures by a right button press were collected. By relating the response accuracy and reaction times to the specific frames of the videos through the ERPs obtained from the triggers of a segment of 30 s surrounding the frame, we tested which ERP features were modulated with the engagement of the subjects to the video content. Results Clear ERPs are generated time-locked to the video frames with increased light intensity. The strongest ERP component was a positive wave around 440 ms followed by two negative peaks around 525 and 710 ms and another positive peak around 610 ms (see figure). We found different ERP patterns at different electrode sites related to the best (short RT & correct responses) and worst (long RT & incorrect response) performances in the memory test. In the worst memory performance condition, the topography of the ERP wave around 440 ms showed a strong, widespread positivity at centro-parietal recording sites resembling the topographical pattern of a P3a wave.  For best memory performance the positivity was smaller especially in posterior channels and the topographies of the two consecutive positive waves around 440 ms and 610 ms were characterized with a left frontal distribution and roughly correspond to a theta oscillation around 5 Hz. 2184Conclusion ERPs were generated by simple passive viewing of the videos without significant disturbance of the visual experience resembling a real-world like scenario. The distractive effect of the introduced changes was not strong enough to produce a clear P3a when the subjects selective attention was focused to the content of the video, while larger P3a responses were obtained when the subjects attention was less engaged, as tested by the LTM task.  The left frontal theta oscillation is compatible with the hemispheric encoding/retrieval asymmetry (HERA) model which describes the stronger involvement of the left prefrontal cortex (PFC) in episodic memory encoding [3], because its’ presence in the ERPs lead to faster and correct responses during the memory test.  Acknowledgements: Emel Erdogdu received a scholarship from the EU Erasmus program as well as the “Deutschland Stipendium” (Germany Scholarship) from Bremen University funded by a public-private-partnership for the study period at Istanbul University.   References: [1]. Courchesne, E., Hillyard, S.A., Galambos, R. (1975), 'Stimulus Novelty, Task Relevance, and the Visual Evoked Potential in Man', Electroencephalography and Clinical Neurophysiology, vol. 39, pp. 131-143. [2]. Donchin, E. (1981), 'Surprise!...Surprise?', Psychophysiology, vol. 18, pp. 493-513. [3]. Habib, R., Nyberg, L., Tulving, E. (2003), 'Hemispheric asymmetries of memory: the HERA model revisited', Trends in Cognitive Science, vol. 7, no. 6, pp. 241–245. [4]. Polich, J. (1999), 'P300 in Clinical Applications: Meaning, Method, and Measurements', In E. Neidermeyer and F. H. Lopes da Silva (Eds), Electroencephalography: Basic Principles, Clinical Applications, and Related Fields, pp. 1073-1091, Baltimore: Williams & Wilkins. [5]. Polich, J. (2007), 'Updating P300: an integrative theory of P3a and P3b', Clinical Neurophysiology, vol.118, no. 10, pp. 2128-2148. 

Measurement of cognitive dynamics during video watching through event-related potentials

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Measurement of cognitive dynamics during video watching through event-related potentials

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