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Towards an Estimate of the Neural Information of the BOLD Signal
Published on 2012-12-032349 Views
The blood oxygen level dependent (BOLD) signal as measured by functional magnetic resonance imaging (fMRI) has become a standard marker of neural activity. The relationship between neural activity and
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Presentation
Towards an estimate of the neural information of the BOLD signal00:00
How much neural information can we extract from fMRI signals?00:10
Outline01:04
Analysis of Multimodal Neuroimaging Data (1)02:22
Analysis of Multimodal Neuroimaging Data (2)02:23
Standard Model of Neurovascular Coupling03:55
When Canonical HRF Models Fail05:07
A Data-driven Approach to Multimodal Neuroimaging (1)07:05
A Data-driven Approach to Multimodal Neuroimaging (2)07:07
Temporal Kernel Canonical Correlation Analysis07:32
Summary tkCCA10:17
Decoding Neural Information from fMRI Signals (1)10:31
Decoding Neural Information from fMRI Signals (2)10:36
Decoding Neural Information: Workflow11:32
Predicting Neural Amplitude from fMRI12:38
Information Measures13:35
Neural Information in fMRI Signals14:42
Which Neural Features are Reflected in fMRI?15:29
Phase And Amplitude of Neural Oscillations15:30
Neural Frequencies Reflected in fMRI16:04
Is Neural Amplitude Enough?16:35
Phase Synchronization17:30
Phase Synchronization Measures on Real Data18:14
Effect of Phase Synchronization18:53
Which fMRI Features Carry Neural Information?19:11
Beyond Canonical HRF Models19:17
Non-separable and separable HRFs20:07
TkCCA vs Canonical HRF Models22:00
Optimal Preprocessing for fMRI Decoding22:44
Effects of Spatial and Temporal Smoothing23:28
Effect of Searchlight Radius24:54
How Much Neural Information is in fMRI signals?25:55
Mutual Information Estimates26:08
Mutual Information Estimates: EEG-fMRI27:08
Linear and Nonlinear Decoding Models28:03
Summary29:06
Acknowledgements30:52
Thank You31:10