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The strength of our claims and the strength of our data do they always go together? Klaus Kessler Glasgow University, Psychology, Centre for Cognitive Neuroimaging (CCNi) Slide 2 Society Research community Neuroimaging Research and Society Schools of thought/ Paradigms (T. Kuhn) Methods: -fMRI/MRI -MEG/EEG etc. Analysis Publications/ Conferences Peer Review/ Debates Law Business/ Entertainment/ Advertisement Government/ Funding Bodies, etc. Media/P ublic Opinion FUNDING IMPACT POLICIES Slide 3 Re-examining (long) published results in the light of new evidence 1.Kriegeskorte et al. (2009) Nature Neuroscience: Circular analysis in systems neuroscience: the dangers of double dipping = When a preliminary analysis is used to pre-select data (e.g. voxels in the brain) for subsequent statistics circularity between hypotheses/assumption and results. Circularity is therefore the error that beautifies results, rendering them more attractive to authors, reviewers and editors, and thus more competitive for publication. These implicit incentives may create a preference for circular practices so long as the community condones them. (p. 536) Slide 4 Re-examining (long) published results 2.Sirotin and Das (2009) Nature: Anticipatory haemodynamic signals in sensory cortex not predicted by local neuronal activity = BOLD modulations in the absence of a stimulus Debate hosted by CCNi (http://www.ccni.gla.ac.uk/): Does BOLD fMRI reveal Pseudo Neuronal Activity? Slide 5 Re-examining (long) published results 3.Yuval-Greenberg et al. (2008) Neuron: Gamma-Band Response in EEG as a Manifestation of Miniature Saccades = some papers might have reported eye muscle effects and not brain effects Slide 6 Neuroimaging Methods: Time and Space Slide 7 EEG/MEG Three 64 electrode system 4D Neuroimaging 248 channel MEG Cortex Neuron Slide 8 2 sec, occipital Sensors Spontaneous brain activity Slide 9 Slower rate = lower frequency: Theta oscillations (5 8 Hz) Fastest rate = high frequency: Gamma oscillation (30 80 Hz) Brain rhythms/oscillations/frequencies Fast rate = medium frequency: Beta oscillation (12 30 Hz) Slower rate = lower frequency: Alpha oscillation (8 12 Hz) Slide 10 Time-Frequency Time Frequency Colour = Power (Strength) Slide 11 Re-examining (long) published results Yuval-Greenberg et al., 2008, Neuron: Gamma-Band Response in EEG as a Manifestation of Miniature Saccades Recommendation: MEG and/or Eye-tracking for control Slide 12 (Body) Gestalt integration: Theta & Alpha Body Gestalt No Body Gestalt Slide 13 (Body) Gestalt integration: Gamma Body Gestalt No Body Gestalt Slide 14 Cortical Networks of Imitation: Power, Coherence & Synchronization Kessler et al., 2006 Slide 15 Oscillations reflect motor imagination online Motor imagination (as well as observation) suppresses alpha oscillations. Collaboration with Dr. Aleksandra Vuckovic (Clinical Rehabilitation Engineering, CRE) on Brain-Computer Interface with spinal cord injured patients. Slide 16 So? 1.Self-regulation in the scientific process is sometimes delayed some neuroimaging results have to be re-examined in the light of new evidence or new methodological developments = solutions are available but at a delay. 2.Each Methodology (e.g. fMRI, MEG) has its own limitations in space or in time we always look only at one side of the coin 3.The strength of our claims does not always fit the strength of our data: 1.For the methodological reasons listed above 2.Because of Impact, i.e., stronger claims = more influence on public opinion/society = more funding. Regulatory process of society onto science Slide 17 Thank you! Collaborator: Dr Sebastien Miellet Slide 18 SYNCHRONISATION IN THE NETWORK Constant phase-difference over time Constant phase-difference over trials Slide 19 MEG analysis Frequency components (time-frequency representations) Lokalisation with DICS (Kessler al., 2006) Averaging: phase locked responses ERFs Biermann-Ruben et al. (in press)