{"id":1076,"date":"2017-10-25T18:17:07","date_gmt":"2017-10-25T09:17:07","guid":{"rendered":"http:\/\/rtfin2017.atr.jp\/?page_id=1076"},"modified":"2017-11-26T13:15:03","modified_gmt":"2017-11-26T04:15:03","slug":"poster-session-schedule","status":"publish","type":"page","link":"https:\/\/rtfin2017.atr.jp\/?page_id=1076","title":{"rendered":"Poster Session Schedule & layout"},"content":{"rendered":"

Schedule<\/span><\/h2>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
POSTER #<\/span><\/strong><\/span><\/td>\nDAY<\/span><\/strong><\/span><\/td>\nNAME<\/span><\/strong><\/span><\/td>\nPRESENTATION TITLE<\/span><\/strong><\/span><\/td>\n<\/tr>\n
CLINICAL<\/span><\/strong><\/span><\/td>\n<\/tr>\n
001<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nZeena-Britt Sanders<\/span><\/td>\nBi-directional modulation of sensorimotor cortex during executed movements<\/span><\/td>\n<\/tr>\n
002<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nYuki Sakai<\/span><\/td>\nPossible Clinical Application of Decoded Neurofeedback to Treatment of Obsessive-compulsive Disorder<\/span><\/td>\n<\/tr>\n
003<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nYujiro Yoshihara<\/span><\/td>\nFunctional connectivity-based neurofeedback for impaired working memory in schizophrenia<\/span><\/td>\n<\/tr>\n
004<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nYu Takagi<\/span><\/td>\nA Neural Marker of Obsessive-Compulsive Disorder from Whole-Brain Functional Connectivity<\/span><\/td>\n<\/tr>\n
005<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nXiaofu He<\/span><\/td>\nConnectivity-based Real-time fMRI Neurofeedback in Youth with a History of Major Depression<\/span><\/td>\n<\/tr>\n
006<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nToshinori Chiba<\/span><\/td>\nThe approach to clinical application of DecNef for PTSD patients<\/span><\/td>\n<\/tr>\n
007<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nDavid Marc Anton Mehler<\/span><\/td>\nTargeting the emotional brain – a Randomized Clinical Trial of realtime fMRI neurofeedback training in patients with depression<\/span><\/td>\n<\/tr>\n
008<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nTomohisa Asai<\/span><\/td>\nNormal aging in resting-state brain networks: Toward a connectivity-neurofeedback for the declined metacognition in elderly people<\/span><\/td>\n<\/tr>\n
009<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nTom Fruchtman<\/span><\/td>\nNeurofeedback intervention for Post Traumatic Stress Disorder (PTSD): Preliminary results from fMRI study of chronic PTSD patients<\/span><\/td>\n<\/tr>\n
010<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nTeiji Kawano<\/span><\/td>\nAssessments of post-stroke aphasia and recovery with the resting state EEG phase synchrony index<\/span><\/td>\n<\/tr>\n
011<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nTakashi Yamada<\/span><\/td>\nThe challenge of ameliorating depressive symptoms using functional connectivity-based neurofeedback (FCNef)<\/span><\/td>\n<\/tr>\n
012<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nTakashi Yamada<\/span><\/td>\nThe search for \u201ctheranostic biomarker\u201d in psychiatric disorders: for more understanding the disease mechanism and for providing tailor-made therapy<\/span><\/td>\n<\/tr>\n
013<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nTakashi Itahashi<\/span><\/td>\nNormalization of altered functional connection by Real-time fMRI neurofeedback on adults with Autism Spectrum Disorder<\/span><\/td>\n<\/tr>\n
014<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nSujesh Sreedharan<\/span><\/td>\nSelf Regulation of Broca\u2019s and Wernicke\u2019s areas using real-time functional MRI\u00a0<\/span>in stroke patients with expressive Aphasia<\/span><\/td>\n<\/tr>\n
015<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nStephen M LaConte<\/span><\/td>\nReal-time fMRI modulation of DMN is enhanced with cognitive behavioral therapy in depression<\/span><\/td>\n<\/tr>\n
016<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nStephen M LaConte<\/span><\/td>\nCognitive improvement in TBI veterans after rtfMRI DMN neurofeedback<\/span><\/td>\n<\/tr>\n
017<\/span><\/strong><\/span><\/td>\n3<\/strong><\/span><\/td>\nMasayuki Hirata<\/span><\/td>\nClinical Application of Implantable Brain Machine Interfaces<\/span><\/td>\n<\/tr>\n
018<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nMikhail Yevgenievitch Melnikov<\/span><\/td>\nTHE REAL TIME FMRI NEUROFEEDBACK FOR DEPRESSED PATIENTS COMPARED TO EEG NEUROFEEDBACK AND COGNITIVE-BEHAVIORAL THERAPY<\/span><\/td>\n<\/tr>\n
019<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nMohit Rana<\/span><\/td>\nSelf-regulation of anterior insular cortex in nicotine addicted smokers<\/span><\/td>\n<\/tr>\n
020<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nNaho Ichikawa<\/span><\/td>\nA classifier of melancholic depression with whole-brain resting-state connectivity.<\/span><\/td>\n<\/tr>\n
021<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nNaho Ichikawa<\/span><\/td>\nDepressive rumination reduced by realtime fMRI neurofeedback of the posterior\u00a0<\/span>cingulate cortex (PCC) activity<\/span><\/td>\n<\/tr>\n
022<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nNana Morita Hayashi<\/span><\/td>\nDecoded neurofeedback training for steady-state visual evoked field in patients with spinal cord injury<\/span><\/td>\n<\/tr>\n
023<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nNoriaki Hattori<\/span><\/td>\nDecoding neurofeedback training to improve hemiparesis after stroke \u2013 a pilot study<\/span><\/td>\n<\/tr>\n
024<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nNoriaki Yahata<\/span><\/td>\nA small number of abnormal functional connections in the brain predicts adult autism spectrum disorder<\/span><\/td>\n<\/tr>\n
025<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nNoriaki Yahata<\/span><\/td>\nIdentification of antidepressant dose-related, resting-state functional connectivity as a novel therapeutic target in neurofeedback: a machine learning-based fMRI study<\/span><\/td>\n<\/tr>\n
026<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nOliver Bichsel<\/span><\/td>\nDeep brain electrode-guided neurofeedback in<\/span>
\n Parkinson’s disease<\/span><\/td>\n<\/tr>\n
027<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nPatricia Vargas<\/span><\/td>\nFunctional Near Infrared Spectroscopy neurofeedback for motor cortical inter-hemispheric inhibition training in stroke patients<\/span><\/td>\n<\/tr>\n
028<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nPatricia Vargas<\/span><\/td>\nSelf-regulation of functional connectivity between cerebellum and primary motor areas\u00a0<\/span>with real-time fMRI neurofeedback: Differential activation and motor performance<\/span><\/td>\n<\/tr>\n
029<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nRyohei Fukuma<\/span><\/td>\nNeurofeedback using DBS electrodes in subthalamic nucleus of patients with Parkinson\u2019s disease<\/span><\/td>\n<\/tr>\n
030<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nShohei Tsuchimoto<\/span><\/td>\nBrain-Machine-Interface changes functional connectivity between sensory and motor\u00a0<\/span>cortices in chronic post-stroke patients with hemiplegia: An interim analysis of\u00a0<\/span>randomized control trial<\/span><\/td>\n<\/tr>\n
031<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nMasaya Misaki<\/span><\/td>\nIndividual difference in the effect of amygdala neurofeedback emotional training in combat-related PTSD<\/span><\/td>\n<\/tr>\n
032<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nMasahiro Yamashita<\/span><\/td>\nA prediction model of working memory based on whole-brain resting-state functional connectivity<\/span><\/td>\n<\/tr>\n
033<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nMarita Mariela Rance<\/span><\/td>\nNeurofeedback produces clinical improvement in obsessive-compulsive disorder that grows over time<\/span><\/td>\n<\/tr>\n
034<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nLeena Subramanian<\/span><\/td>\nBRAINTRAIN consortium: Design principles of randomised controlled trials of real-time fMRI neurofeedback with a focus on alcohol dependence<\/span><\/td>\n<\/tr>\n
035<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nKota Utsumi<\/span><\/td>\nP300-based brain-machine interface applied to patients with Duchenne muscular dystrophy<\/span><\/td>\n<\/tr>\n
036<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nKathryn Dickerson<\/span><\/td>\nUsing real-\u00ad\u2010time fMRI neurofeedback as a tool for demonstrating therapeutic efficacy<\/span><\/td>\n<\/tr>\n
037<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nJinendra\u00a0\u00a0 Ekanayak<\/span><\/td>\nModulation of motor circuits in Parkinson\u2019s disease \u2013 applying realtime fMRI neurofeedback learning in STN-DBS patients<\/span><\/td>\n<\/tr>\n
038<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nJeffrey Eilbott<\/span><\/td>\nResting State Connectivity Predicts Neurofeedback Response in OCD<\/span><\/td>\n<\/tr>\n
039<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nJaime A Pereira<\/span><\/td>\nFunctional connectivity changes with real-time fMRI neurofeedback in Autism<\/span><\/td>\n<\/tr>\n
040<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nHiroaki Fujimoto<\/span><\/td>\nfNIRS-mediated neurofeedback for cerebellar ataxia: potential for augmenting rehabilitation outcome<\/span><\/td>\n<\/tr>\n
041<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nGiuseppe Lisi<\/span><\/td>\nFunctional connectivity rsfMRI as a Biomarker of Mental Disorders<\/span><\/td>\n<\/tr>\n
042<\/span><\/strong><\/span><\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
043<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nDavid Marc Anton Mehler<\/span><\/td>\nSupplementary motor area, but not primary motor cortex \u2013<\/span>
\n Translating graded real-time fMRI neurofeedback training to middle cerebral artery stroke (MCA) patients<\/span><\/td>\n<\/tr>\n
044<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nAndrei Savelov<\/span><\/td>\nRecovery of post stroke wrist function under simultaneous fMRI\/EEG biofeedback<\/span><\/td>\n<\/tr>\n
045<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nAndrea del Pilar Sanchez<\/span><\/td>\nBCI-neurofeedback training for increasing the connectivity of fronto-parietal networks\u00a0<\/span>involved in the conscious perception of emotional stimuli in schizophrenia.<\/span><\/td>\n<\/tr>\n
NEURAL MECHANISM<\/span><\/strong><\/span><\/td>\n<\/tr>\n
046<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nHiroaki Hashimoto<\/span><\/td>\nSwallowing-related oscillatory changes revealed by human electrocorticogram<\/span><\/td>\n<\/tr>\n
047<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nIshani Rajendra Thakkar<\/span><\/td>\nThe effect of reward on brain self-regulation acquired through fNIRS neurofeedback<\/span><\/td>\n<\/tr>\n
048<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nJune Sic Kim<\/span><\/td>\nDiscrimination of kinesthetic and visual motor imagery<\/span><\/td>\n<\/tr>\n
049<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nLeon Skottnik<\/span><\/td>\nInvolvement of the reward system during rtfMRI neurofeedback across various self-regulation tasks<\/span><\/td>\n<\/tr>\n
050<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nMartin Klasen<\/span><\/td>\nfMRI neurofeedback of language networks in auditory verbal hallucinations<\/span><\/td>\n<\/tr>\n
051<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nMasahiro Takamura<\/span><\/td>\nDeactivation of DMN nodes during DLPFC fMRI neurofeedback<\/span><\/td>\n<\/tr>\n
052<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nMeena M. Makary<\/span><\/td>\nDMN Functional Connectivity Modulation after Self-regulation of the Primary Motor Cortex Activity with Motor Imagery: A Real-time fMRI Neurofeedback Study<\/span><\/td>\n<\/tr>\n
053<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nNatalie Ebner<\/span><\/td>\nUse of real-time fMRI in studying the aging brain<\/span><\/td>\n<\/tr>\n
054<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nRanganatha Sitaram<\/span><\/td>\nInvestigating the neural mechanism of brain self-regulation with simultaneous\u00a0<\/span>fMRI-EEG acquisition during rtfMRI neurofeedback<\/span><\/td>\n<\/tr>\n
055<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nWako Yoshida<\/span><\/td>\nClosed-loop pain relief control using fMRI multi-voxel decoder and reinforcement learning<\/span><\/td>\n<\/tr>\n
056<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nSantiago Munoz-Moldes<\/span><\/td>\nSubjective evaluation of real-time fMRI-based neurofeedback performance<\/span><\/td>\n<\/tr>\n
057<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nShabnam Hakimi<\/span><\/td>\nModeling VTA learning from real-time fMRI neurofeedback<\/span><\/td>\n<\/tr>\n
058<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nShingo Tanaka<\/span><\/td>\nElucidating the role of the macaque lateral prefrontal cortex for the value-based decision making using the decoded neurofeeback<\/span><\/td>\n<\/tr>\n
059<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nYuji Mizuno<\/span><\/td>\nChanges of brain activity associated with brain-computer interface learning<\/span><\/td>\n<\/tr>\n
060<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nGuilherme M. de O. Wood<\/span><\/td>\nfMRI neurofeedback training of the left insula mediates the outcome of EEG neurofeedback training of the sensorimotor rhythm (12-15 Hz)<\/span><\/td>\n<\/tr>\n
061<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nGabriele Ende<\/span><\/td>\nThe functional neuroanatomy of neurofeedback control<\/span><\/td>\n<\/tr>\n
062<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nFabien LOTTE<\/span><\/td>\nWhat are the best motor tasks to use and calibrate SensoriMotor Rhythm Neurofeedback and Brain-Computer Interfaces? A preliminary case study<\/span><\/td>\n<\/tr>\n
063<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nCatharina Zich<\/span><\/td>\nDynamic fMRI-based neurofeedback under the microscope \u2013 evidence from the\u00a0<\/span>developing brain<\/span><\/td>\n<\/tr>\n
064<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nRyu Ohata<\/span><\/td>\nDecoding self-other action attribution in the sensorimotor and the parietal cortices<\/span><\/td>\n<\/tr>\n
065<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nAmelie Haugg<\/span><\/td>\nPre-training localizer activity predicts real-time fMRI neurofeedback learning success<\/span><\/td>\n<\/tr>\n
COGNITION AND PERCEPTION<\/span><\/strong><\/span><\/td>\n<\/tr>\n
066<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nTakehito Ito<\/span><\/td>\nThe effect of downregulating the ACC activity on the negativity bias: a preliminary investigation<\/span><\/td>\n<\/tr>\n
067<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nRobert A Backer<\/span><\/td>\nDown-regulating physiological arousal in cognitively demanding\u00a0<\/span>contexts: A real-time neural feedback intervention<\/span><\/td>\n<\/tr>\n
068<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nMegan T deBettencourt<\/span><\/td>\nPredicting memory encoding by tracking attention<\/span><\/td>\n<\/tr>\n
069<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nMegan A. K. Peters<\/span><\/td>\nImproving functional connectivity to prefrontal cortex with decoded neurofeedback<\/span><\/td>\n<\/tr>\n
070<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nKouji Takano<\/span><\/td>\nDecoded neurofeedback training for steady-state visual evoked field<\/span><\/td>\n<\/tr>\n
071<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nJessica Elizabeth Taylor<\/span><\/td>\nAn Investigation into the Ecological Validity of DecNef Fear Memory Counter-Conditioning<\/span><\/td>\n<\/tr>\n
072<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nJessica Elizabeth Taylor<\/span><\/td>\nA DecNef Investigation into the Dissociability of Phenomenal and Access Consciousness<\/span><\/td>\n<\/tr>\n
073<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nJD Knotts<\/span><\/td>\nUsing decoded fMRI neurofeedback to identify multivariate patterns for illusory color perception<\/span><\/td>\n<\/tr>\n
074<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nHannah Boeijkens<\/span><\/td>\nToward improving motor and working memory function through functional near-infrared spectroscopy neurofeedback<\/span><\/td>\n<\/tr>\n
075<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nHyun-Chul Kim<\/span><\/td>\nMediation analysis between triple networks reflects functional connectivity\u00a0<\/span>changes from a mindfulness training in real-time fMRI neurofeedback setting<\/span><\/td>\n<\/tr>\n
076<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nGustavo Pamplona<\/span><\/td>\nImproving attention through network-based neurofeedback training<\/span><\/td>\n<\/tr>\n
077<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nLydia Hellrung<\/span><\/td>\nrtQC: An open-source collaborative framework for quality control methods in real-time\u00a0<\/span>functional magnetic resonance imaging<\/span><\/td>\n<\/tr>\n
078<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nYury Koush<\/span><\/td>\nHippocampal CA1 down-regulation performance as a biomarker of preclinical\u00a0<\/span>Alzheimer\u2019s disease.<\/span><\/td>\n<\/tr>\n
079<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nAi Koizumi<\/span><\/td>\nFear reduction without fear through reinforcement of neural activity that bypasses conscious exposure<\/span><\/td>\n<\/tr>\n
080<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nAnne Mennen<\/span><\/td>\nInhibiting scene memories through closed-loop modulation of retrieval strength<\/span><\/td>\n<\/tr>\n
081<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nAurelio Cortese<\/span><\/td>\nAdaptive significance of consciousness in reinforcement learning<\/span><\/td>\n<\/tr>\n
082<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nAurelio Cortese<\/span><\/td>\nLong-term within-subjects\u2019 bidirectional confidence changes induced by multivoxel pattern manipulation<\/span><\/td>\n<\/tr>\n
083<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nAyako Isato<\/span><\/td>\nPreliminary examination of resting-state functional connectivity associated with the reduction of negativity bias after neurofeedback training<\/span><\/td>\n<\/tr>\n
084<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nBrian Odegaard<\/span><\/td>\nInvestigating the role of prefrontal cortex in conscious perception with decoded\u00a0<\/span>neurofeedback<\/span><\/td>\n<\/tr>\n
085<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nGunda Hanna Johannes<\/span><\/td>\nNeurofeedback-aided regulation of food cue reactivity in the dopaminergic midbrain<\/span><\/td>\n<\/tr>\n
METHOD, THEORY, MATH<\/span><\/strong><\/span><\/td>\n<\/tr>\n
086<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nZhen LIANG<\/span><\/td>\nEEG Alpha Oscillations Reveal Color Contrast: SVR-Based Modelling<\/span><\/td>\n<\/tr>\n
087<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nYusuke Takeda<\/span><\/td>\nEstimating repetitive spatiotemporal patterns from many subjects’ resting-state fMRI data<\/span><\/td>\n<\/tr>\n
088<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nYuto Okada<\/span><\/td>\nSimulation studies of deep-brain activity inference using fMRI-fNIRS<\/span><\/td>\n<\/tr>\n
089<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nYury Koush<\/span><\/td>\nOpenNFT: An open-source Python\/Matlab framework for real-time fMRI neurofeedback training<\/span><\/td>\n<\/tr>\n
090<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nTakeshi Ogawa<\/span><\/td>\nPrediction of resting state fMRI signatures from EEG signal: a study of EEG-fMRI simultaneous recording<\/span><\/td>\n<\/tr>\n
091<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nTabea Kamp<\/span><\/td>\nLocalizing the default mode network for real-time purposes using seed-based analyses<\/span><\/td>\n<\/tr>\n
092<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nShuka Shibusawa<\/span><\/td>\nEstablishing real-time adaptive transcranial alternating current stimulation (tACS) during whole-head magnetoencephalography (MEG)<\/span><\/td>\n<\/tr>\n
093<\/span><\/strong><\/span><\/td>\n\u00a01<\/strong><\/span><\/td>\n\u00a0Lydia Hellrung<\/span><\/td>\nPatterns of successfully regulating the dopaminergic midbrain<\/span><\/td>\n<\/tr>\n
094<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nRick van Hoof<\/span><\/td>\nSingle trial letter imagery decoding in early visual cortex with high-field MRI<\/span><\/td>\n<\/tr>\n
095<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nRahim Malekshahi<\/span><\/td>\nA versatile toolbox for real-time EEG neurofeedback: Emphasis on source activity from auditory cortex in patients with chronic tinnitus<\/span><\/td>\n<\/tr>\n
096<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nMichael Luehrs<\/span><\/td>\nFunctional verification of fNIRS probe locations using a generalized SVM classifier model<\/span><\/td>\n<\/tr>\n
097<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nMichael Luehrs<\/span><\/td>\nRetrieving fMRI data in real-time: difficulties and pitfalls<\/span><\/td>\n<\/tr>\n
098<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nMichael Luehrs<\/span><\/td>\nReal-time MR-Encephalography for BCI\/Neurofeedback applications<\/span><\/td>\n<\/tr>\n
099<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nOkito Yamashita<\/span><\/td>\nVBMEG : Open-source software for MEG\/EEG source localization and dynamics modeling<\/span><\/td>\n<\/tr>\n
100<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nLydia Hellrung<\/span><\/td>\nMotion and physiological noise effects on neurofeedback learning<\/span><\/td>\n<\/tr>\n
101<\/span><\/strong><\/span><\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
102<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nMaro Machizawa<\/span><\/td>\nA simplified multi-axis affective and cognitive decoded neurofeedback system for anticipation of excitement<\/span><\/td>\n<\/tr>\n
103<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nKlaus Mathiak<\/span><\/td>\nIntersubject covariance reveals patterns in neurofeedback dynamics and disturbances in psychiatric disorders<\/span><\/td>\n<\/tr>\n
104<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nKathy Louise Ruddy<\/span><\/td>\nChanging oscillatory brain state using TMS-based neurofeedback<\/span><\/td>\n<\/tr>\n
105<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nAapo Hyvarinen<\/span><\/td>\nTowards a neurofeedback system for mindfulness training based on detecting mind wandering<\/span><\/td>\n<\/tr>\n
106<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nAbhishek Bhutada<\/span><\/td>\nAutomatic digitization and labeling of EEG electrodes from MRI images for rapid coregistration for rtfMRI-EEG neurofeedback.<\/span><\/td>\n<\/tr>\n
107<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nAyumu Yamashita<\/span><\/td>\nFunctional Connectivity Neurofeedback Training Can Differentially Change Functional Connectivity and Cognitive Performance<\/span><\/td>\n<\/tr>\n
108<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nAyumu Yamashita<\/span><\/td>\nQuantitative comparing the magnitude of measurement bias and sampling bias on multi-site resting-state fMRI connectivity with the magnitude of the effects of psychiatric disorders by using traveling subject design<\/span><\/td>\n<\/tr>\n
109<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nAndrea del Pilar Sanchez<\/span><\/td>\nClose-loop training of attention using a low-cost EEG device<\/span><\/td>\n<\/tr>\n
110<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nCaroline Benjamins<\/span><\/td>\nThe (in)consistency among researchers when selecting a neurofeedback target region<\/span><\/td>\n<\/tr>\n
111<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nCatalin Iourdan<\/span><\/td>\nKL-Evidence: A Novel Multivariate Neurofeedback Method for\u00a0<\/span>Differentiating Representations<\/span><\/td>\n<\/tr>\n
112<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nChiara Fioravanti<\/span><\/td>\nEstimation of perceptual thresholds in a neurofeedback paradigm: effects and corrections of observer bias<\/span><\/td>\n<\/tr>\n
113<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nDiletta Rivela<\/span><\/td>\nOn the development of EEG sensorimotor rhythm-based continuous proprioceptive neurofeedback<\/span><\/td>\n<\/tr>\n
114<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nEpifanio Bagarinao<\/span><\/td>\nUse of a small humanoid robot as a neurofeedback system for motor imagery tasks<\/span><\/td>\n<\/tr>\n
115<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nHanna Lu<\/span><\/td>\nIntra-individual variability of head motion (IIV-HM): a novel index of in-scanner head\u00a0<\/span>motion and its associations with cognitive performance<\/span><\/td>\n<\/tr>\n
116<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nHiroki Moriya<\/span><\/td>\nPredictability of amygdala BOLD signal from multiple-electrode EEGs<\/span><\/td>\n<\/tr>\n
117<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nJohan Nicolaas van der Meer<\/span><\/td>\nImage Distortion in 7 Tesla and its significance for high-field Amygdala neurofeedback<\/span><\/td>\n<\/tr>\n
118<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nJudith Eck<\/span><\/td>\nSelf-regulation of a functional network using real-time fMRI<\/span><\/td>\n<\/tr>\n
119<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nJun-ichiro Hirayama<\/span><\/td>\nExploring EEG source resting-state networks by SPLICE: A simultaneous fMRI study<\/span><\/td>\n<\/tr>\n
BRAIN-MACHINE INTERFACE<\/span><\/strong><\/span><\/td>\n<\/tr>\n
120<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nTatsuya Teramae<\/span><\/td>\nA control strategy for physical human-robot interaction using biosignal-based model predictive control<\/span><\/td>\n<\/tr>\n
121<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nTaro Kaiju<\/span><\/td>\nInduction of electrocorticography patterns via operant conditioning using a BMI self-feeding task<\/span><\/td>\n<\/tr>\n
122<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nShinya Chiyohara<\/span><\/td>\nProprioceptive Gain Affects Motor Learning<\/span><\/td>\n<\/tr>\n
123<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nRytoaro Numata<\/span><\/td>\nTowards the development of a co-adaptive brain robot interface<\/span><\/td>\n<\/tr>\n
124<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nJun-ichiro Furukawa<\/span><\/td>\nHuman Movement Estimation from Multiple Biosignal Observations toward Safe Assistive Robot Control<\/span><\/td>\n<\/tr>\n
125<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nBettina Sorger<\/span><\/td>\nAn fNIRS-based brain-machine interface for remote robot control<\/span><\/td>\n<\/tr>\n
126<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nAsuka Takai<\/span><\/td>\nThe differences in motor performances between sensorimotor area activities of pre- and during passive guidance<\/span><\/td>\n<\/tr>\n
EMOTION AND SENSORIMOTOR<\/span><\/strong><\/span><\/td>\n<\/tr>\n
127<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nZhiying Zhao<\/span><\/td>\nTraining the Emotion Regulation Circuit Using Functional Connectivity Based rt-fMRI Neurofeedback: Proof-of-Concept<\/span><\/td>\n<\/tr>\n
128<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nSalim Al-Wasity<\/span><\/td>\nEmpathy and the use of real-time fMRI to learn voluntary regulation of the anterior insula<\/span><\/td>\n<\/tr>\n
129<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nRonald Sladky<\/span><\/td>\nClosed-loop amygdala neurofeedback using emotional faces<\/span><\/td>\n<\/tr>\n
130<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nRonald Sladky<\/span><\/td>\nBrain networks underlying successful emotion regulation with rt-fMRI neurofeedback<\/span><\/td>\n<\/tr>\n
131<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nRenate Schweizer<\/span><\/td>\nExtended rt-fMRI neurofeedback training of the somato-motor cortex reveals different learning outcomes<\/span><\/td>\n<\/tr>\n
132<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nMing Chang<\/span><\/td>\nUnconscious Improvement in Foreign Language Learning Using Mismatch Negativity Neurofeedback<\/span><\/td>\n<\/tr>\n
133<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nMichael Marxen<\/span><\/td>\nThe Influence of Amygdala Regulation on Emotional Reactivity<\/span><\/td>\n<\/tr>\n
134<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nDoron Todder<\/span><\/td>\nDissociating Arithmetic Functions Through Region\u2013Specific EEG Neurofeedback Training: double-blind controlled study<\/span><\/td>\n<\/tr>\n
135<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nEthan Oblak<\/span><\/td>\nMotor sequence skill learning by operant conditioning of cortical activity<\/span><\/td>\n<\/tr>\n
136<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nFrank Pollick<\/span><\/td>\nEnhancing Motor Reaction time using Real-Time Functional MRI Neurofeedback of Supplementary Motor Area (SMA)<\/span><\/td>\n<\/tr>\n
137<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nJackob Nimrod Keynan<\/span><\/td>\nAmygdala-NeuroFeedback improves emotion regulation and reduces vulnerability to mild military stress<\/span><\/td>\n<\/tr>\n
138<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nJana Zweerings<\/span><\/td>\nImpaired voluntary control of the emotion regulation network in PTSD: probing self-regulation with real-time fMRI<\/span><\/td>\n<\/tr>\n
139<\/span><\/strong><\/span><\/td>\n3<\/span><\/strong><\/span><\/td>\nJenny Katharina Zaehringer<\/span><\/td>\nAlterations of Emotion Regulation in Patients with Borderline Personality Disorder through Real-time fMRI Neurofeedback Training<\/span><\/td>\n<\/tr>\n
140<\/span><\/strong><\/span><\/td>\n1<\/span><\/strong><\/span><\/td>\nLulu Wang<\/span><\/td>\nEffects of real-time fMRI neurofeedback on behavioural outcome measures: A\u00a0<\/span>systematic review<\/span><\/td>\n<\/tr>\n
141<\/span><\/strong><\/span><\/td>\n2<\/span><\/strong><\/span><\/td>\nMasaru Tanaka<\/span><\/td>\nSense of agency altered by cognitive intervention affects motor control<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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Layout:
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\"\"<\/a><\/td>\n\"\"<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Day 1 (Nov. 29th): Poster # & layout<\/a>
\n Day 2 (Nov. 30th): Poster # & layout<\/a>
\n Day 3 (Dec. 1st): Poster # & layout<\/a>\u00a0<\/span><\/span><\/span><\/h2>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

Schedule POSTER # DAY NAME PRESENTATION TITLE CLINICAL 001 3 Zeena-Britt Sanders Bi-directional modulation of … \u7d9a\u304d\u3092\u8aad\u3080 Poster Session Schedule & layout<\/span> →<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1076","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/rtfin2017.atr.jp\/index.php?rest_route=\/wp\/v2\/pages\/1076","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rtfin2017.atr.jp\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/rtfin2017.atr.jp\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/rtfin2017.atr.jp\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/rtfin2017.atr.jp\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1076"}],"version-history":[{"count":76,"href":"https:\/\/rtfin2017.atr.jp\/index.php?rest_route=\/wp\/v2\/pages\/1076\/revisions"}],"predecessor-version":[{"id":1477,"href":"https:\/\/rtfin2017.atr.jp\/index.php?rest_route=\/wp\/v2\/pages\/1076\/revisions\/1477"}],"wp:attachment":[{"href":"https:\/\/rtfin2017.atr.jp\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1076"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}