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Visualizing and Manipulating Brain Dynamics


  1. Visualizing and Manipulating Brain Dynamics � ������������������ ����������������� ������������� � �����������������

  2. List of Topics � � � Robots and Brain Machine Interface � � � Brain Decoding and Neurorehabilitation � � � Spontaneous Brain Activity and Neurofeedack � � � Biomarker of Psychiatric Disorder � � � � Ubiquitous Brain Visualization and Control 2 �

  3. � � Humanoid “CB-i”: Computational Brain Interface � � � Human-size robot � – � Height 155cm, Weight 85kg � � � 51 joints � � � Human-like movement range � � � Human comparable power � – � Hydraulic actuation � � � Mechanically compliant � – � Force position control � � � Various sensors � – � Vision, audition, vestibular, proprioception � � � Computers � – � Sensorymotor control; PC � 2 � – � Perception and learning; PC- cluster with wireless �

  4. Hu um ma an noid d P Po ost tu ur re e C Co ontr ro ol o on U Un ns st ta ab ble e T Te err ra ain n - - S Sa ang g- -H Ho o H Hy yo on � Brain-like control without vision or force feedback from foot � Unpredictable Incline � One-foot balance on unknown and unstable object � Base for Christian Ott �

  5. Brain Machine Interface � Compensate, cure and enhance sensory, central and motor ������������������������������������������������������� � ������� � ����� � Artificial sensory BMI � � Artificial cochlear; Cochlear TM ���� � � Artificial vision; Dobelle Institute ���

  6. Brain Machine Interface � Compensate, cure and enhance sensory, central and motor ������������������������������������������������������� � ������� � ����� � Central intervention BMI Deep brain stimulation; Medtronic TM ��

  7. Brain Machine Interface � Compensate, cure and enhance sensory, central and motor ������������������������������������������������������� � ������� � ����� � BMI for motor control compensation � � Silicon electrodes; Cyberkinetics TM ����� � � ECoG � � � EEG � � � NIRS � � � Noninvasive combined � HONDA-ATR-Shimadzu)

  8. List of Topics � � � Robots and Brain Machine Interface � � � Brain Decoding and Neurorehabilitation � � � Spontaneous Brain Activity and Neurofeedack � � � Biomarker of Psychiatric Disorder � � � � Ubiquitous Brain Visualization and Control 9 �

  9. Decoding of Brain/Mind � �� �� �� �� �� �� �� � � �� �� �� �� �� �� �� � � �� �� �� ��� �� �� �� � ��� �� �� �� �� �� �� �� �� �� �� ��� � �� �� �� �� �� �� �� �� �� �� �� � �� �� �� �� �� �� ��� �� �� ��� �� �� �� �� �� �� � � ��������������������������� (modified from http://whatisthematrix.warnerbros.com/) ������������������������������������������ �

  10. Dream Reading � Neural decoding of visual imagery during sleep. T. Horikawa, M. Tamaki, Y. Miyawaki, Y. Kamitani, Science , 340 , 639-642 (2013) � 11 �

  11. EEG-BMI controlled Robot for Neurorehabiliation � Keio University Imagine to extend fingers � rest � Motor Upon successful motor imagery, fingers are imagery � extended by an electrically powered orthosis triggered as a result of the EEG classification. � The position of the cursor reflects the mu rhythm Training protocol � amplitude during motor imagery. � � � Patients imagine to extend their paretic fingers for 5 seconds in every 10 seconds � � 50–100 trials/day, 1-2 weeks � � More than 100 patients treated � � Clinical trials started in 2012 The cursor moves up and down according � � More than 80% curing effect for to the degree of success of motor imagery. � severest patients without EMG

  12. 66 y.o lady with left hemiparetic stroke (right MCA infarction) � � 5 years post onset, no voluntary finger extension � � Anodal t-DCS (10 min, 1mA) � BMI neurofeedback (60 min/d, 5 d/wk for 2wks) � � � % accuracy � 100 patients! RCT � Improvement of BMI classification � More apparent µ-ERD and EMG activities observed � Initial � Final � � � � � ����� ����� �� � �� � � ���� ���� �� �� � �� �� � �� �� � �� �� � � � ���� �� ���� � ��� � ���� ���� �� ���� � ��� � ���� ����������������������������������������������������������������������� ��������������������������������� �� �� ���������������� �

  13. Exoskeleton robot for rehabilitation � ���������������������������������� � ������������������������������������������ � Hybrid actuators composed of air muscles and electric motors are employed 14 � Noda, Hyon, Matsubara, Morimoto

  14. Decoded Neurofeedback Paradigm with XoR and Human in a Loop � decoder � Brain � DecNef � decoded information � Audio-visual stimuli � Rewards Force and Body � position Exoskeleton Humanoid feedback � Robot; XoR � Tactile stimulation � Kawato M: From “understanding the brain by creating the brain” toward manipulative 15 � neuroscience. � Philosophical Transactions of the Royal Society B , � 363 , 2201-2214 (2008) �

  15. List of Topics � � � Robots and Brain Machine Interface � � � Brain Decoding and Neurorehabilitation � � � Spontaneous Brain Activity and Neurofeedack � � � Biomarker of Psychiatric Disorder � � � � Ubiquitous Brain Visualization and Control 16 �

  16. Spontaneous Brain Activity and Intrinsic Functional Connectivity � � � Brain is not a mere input-output transformation system, but a dynamical system generating inherent spatiotemporal patterns even at rest. � � � Correlations of slow fMRI BOLD oscillation (~0.03Hz) between brain regions ���������������� functional connectivity � � � Spontaneous brain activity contains evoked brain activities, and the latter constructs the former. � 17 �

  17. Spontaneous activity in visual cortex wanders over activities induced by different orientation stimuli � � � Arieli & Grinvald, Weizmann Inst., Nature , 954, (2003) � � � Anesthetized cats, voltage sensitive dye, BA18, 4x2 mm � 18 �

  18. Spontaneous activity in the visual cortex represents internal model of visual world and prior provability for Bayesian estimation � � � József Fiser et al. Science , 331 , 83-87 (2011) � � � Wake ferrets, primary visual cortex, 16 multi-elecrodes, 4 young-old stages � � � Natural scene movie, KL-Div � � � Bayes theory, prior P(N) , Posterior P(N|V) , visual stimuls V � P ( N | V ) = P ( V | N ) P ( N ) P ( V ) 19 �

  19. � � Independent Component Analysis of Big Data (30,000 sub., 10,000 exp., and 2,000 papers) � ��������������� ��������������� �������������� �������������� DMN � ���������� ���������������� ��������� �������������� �������������� 20 �

  20. Meta Analysis of Big fMRI Data A r t i f a c t s � BrainMap ICA � Laird et al., 2011, J Cogn Neurosci

  21. ICA from resting state activity of 306 subjects; rs-fcMRI � PDMN � lM 1 � ����������������� ������� ���� �� ���� � 22 �

  22. Orthodox and ROI-based fMRI Real-time Neurofeedback; Pain, Parkinson’s Disease, Anxiety � Weiskopf N, Veit R, Erb M, Mathiak K, Grodd W, Goebel R, Birbaumer N.: Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data. NeuroImage . 2003 Jul; 19(3) :577-86. � ACC for Pain; De Charms RC et al. (2005) PNAS 102 , 18626 � SMA for Parkinson; Subramanian L. et al. (2011) J Neurosci . 31 , 16309 � OFC for OCD; Scheinost D , et al. (2013) Translational psychiatry 3 :e250. �

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