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Frank Leone, Ivan Toni, Pieter Medendorp. Sensorimotor multivariate projects. Sensorimotor multivariate projects. Distributed meeting, 24 November 2011. Two projects. Saccade generation 18 locations Effector specificity Three effectors Repetition suppression General approach:
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Frank Leone, Ivan Toni, Pieter Medendorp Sensorimotor multivariate projects
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Two projects Saccade generation • 18 locations Effector specificity • Three effectors • Repetition suppression General approach: • Have multiple blocks • Fit GLM per block • Have multiple values per voxel (e.g., dir, amp, loc) • Classify t-values (SVM, searchlight)
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Background The domain: saccade generation Both the Frontal Eye Fields (FEF)and Posterior Parietal Cortex (PPC)feature tuning for saccade • Direction • Amplitude? It is unclear why no amplitude selectivity has been found in humans Taking advantage of the increased sensitivity of multivariate analysis, we are busy filling this gap
+ + + Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Standard delayed saccade setup + Serenokinda way
+ + + Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Phase-based mapping a la Sereno • Presentation • Consistent delays • Around the clock • Phase-basedanalysis • Result: nice maps 500 ms. 6 1 6 1 3000 ms. + Amp 750 ms. 5 2 5 2 750 ms. 4 3 4 3 Freq & Phase Sereno et al, 2001
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Background The domain: saccade generation Both the Frontal Eye Fields (FEF)and Posterior Parietal Cortex (PPC)feature tuning for saccade • Direction • Amplitude? It is unclear why no amplitude selectivity has been found in humans Taking advantage of the increased sensitivity of multivariate analysis, we are busy filling this gap
+ + + Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Methods: paradigm 500 ms. 6*500 ms. + 750 ms. 750 ms.
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Methods: Analysis
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 • Stimulus spike
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Fitted per location The classifier actually got: Direction Amplitude Location And was trained to classify location
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Surface based
+ + + Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Methods: Summary Delayed saccade task 18 targets: • 6 directions • 3 amplitudes GLM for all 18 locations to get beta’s/t statistics Move searchlight over the brain, try to distinguish locations Calculate back to direction and amplitude Noting performance, significance, and tuning 500 ms. 6*500 ms. + 750 ms. 750 ms.
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Results: Performance
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Results: Max voxeltuning
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Results: Regional tuning
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 So… Found direction, amplitude, and location information in the expected regions • Can look at this tuning in greater detail than possible before. • Model focused on stimulus • It is actually a regression problem • Participants not perfect But…
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 Effector specificity project SfN 2011 poster
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 So: Specificity as expected, gradients confirmed Interesting similarities and differences between importance and confusion Include sides Include repetition suppression Analyze using RSA (* 2) To do:
Sensorimotor multivariate projects Distributed meeting, 24 November 2011
Sensorimotor multivariate projects Distributed meeting, 24 November 2011
Sensorimotor multivariate projects Distributed meeting, 24 November 2011 General conclusion Multi-valued searchlight Using t-values per block Makes for great performance Confusion matrices For behavior/EMG Is the next step to make