Presentation on theme: "Cross-cortical Coherence during Effector Decision Making Chess Stetson Andersen Laboratory Caltech Sloan-Swartz Meeting 2009/07/28."— Presentation transcript:
Cross-cortical Coherence during Effector Decision Making Chess Stetson Andersen Laboratory Caltech Sloan-Swartz Meeting 2009/07/28
How do different parts of the brain work together? In other words, how do they communicate and form functional networks?
Oscillatory synchrony is a popular answer – different neural populations oscillate at the same phase of a brain rhythm in order to talk. from Womelsdorf et al., Science, 2007 How do different parts of the brain work together?
from Poulet & Petersen, Nature, 2008 How do we look for synchrony? We record single-unit spikes and local field potentials (LFPs), which correlate with subthreshold membrane potential.
Where do we look for synchrony? We are particularly interested in communication between separate cortical areas. Under the theory that LFPs represent input to a region (Mitzdorf, 1982), we might expect the output of one area to synchronize with the input to another.
What measure do we use? FT(x) = the multi-taper Fourier transform of x C(x,y) is a complex number representing the phase of the offset between signals x and y at every frequency We will focus on | |, the epoch-averaged coherence, expressing the consistency in phase-lag between signals, independent of signal power z-transform generates a z-score, according to the # of degrees of freedom, s.t. coherence->0 under the null hypothesis
The common driver problem Apparent communication between two signals could actually result from a 3rd area nefariously driving them both. We would like a measure that isolates the cross- cortical component.
...isolates the coherence between two signals, apart from the influence of a third The partial coherence... Any third party who drives both cortical areas will likely be available in both LFPs. To the extent that we can identify this 3rd party, we can sift it out.
Which brain regions to choose? MIP (medial intraparietal cortex) and PMd (dorsal premotor cortex) are monosynaptically connected parts of the brain MIP is thought of as the final stage of the dorsal pathway of visual processing PMd is thought to be involved in the planning of motor behavior Cortically distant, functionally similar MIP PMd
A typical task for MIP & PMd Delay Reach (600-1000ms)(600 ms) No target or effector cue during the delay period
0.6 Time Into Delay Period (s) Delay Reach 0 80 60 Mean firing rate (Hz) 0
0.6 0 80 60 Time Into Delay Period (s) Mean firing rate (Hz) 0
Visual stimuli exert powerful effects on neural synchrony Decisions are internally generated -- removing visual cues rules out a likely source of common drive Why decision-making?
During effector decision-making, when reward contingencies are near 50/50 ( Barraclough et al., Nat Neuro, 2004 ), information evolves slowly within MIP/PMd. Coherence is often associated with visual attention ( Gregoriou, et al., Science, 2009 ), but cortical communication could be more general. During effector decision-making, are the cells with something to say the ones most likely to communicate? Why effector decision-making?
How do different parts of the brain work together? Between two cortical locations involved in making an effector decision......do cells which show early evidence of the decision have more cross-cortical influence?
Do effector-decision cells show more cross-cortical coherence?
0-.6 0 8 -20 30 Time Into Delay Period (s) Mean firing rate (Hz) z-trans., part. coherence REACH/SACCADE Do effector-decision cells show more cross-cortical coherence? Frequency (Hz) 0 50
0-.6 0 0 60 0 0 100 8 -20 30 Time Into Delay Period (s) Mean firing rate (Hz) z-trans., part. coherence REACH/SACCADE Frequency (Hz) 0 50 0 0 0
Effector decision cells are more cross cortically coherent 0 700 0.5 0.75 time (ms) into memory period % correct Frequency (Hz) avg. z-trans part. coherence MEMORY PERIOD Cells with significant effector tuning during the memory period Cells with non-significant tuning * * * 050100 0 1 Ensemble “effector decode” *, p<.05 Spike-LFP pairs including “effector decision” spikes Spike-LFP pairs without significant tuning during the delay
0 30 Time Into Delay Period (ms) Mean firing rate (Hz) 0-.6 0 Not all coherent cells make effector decisions 14 -2 Frequency (Hz) 0 50 z-trans., part. coherence
Effector decision cells are more cross-cortically coherent during the memory delay 050100 0 1 * * * *, p<.05 Frequency (Hz) z-trans part. coherence
from Pesaran, Nelson and Andersen, Nature, 2009 pre-filtered for significantly coherent cells More fronto-parietal coherence in the WHERE task, as compared to increased parieto- frontal coherence in the HOW task. “WHERE” TO MOVE 060012001800 -0.6 0 1.2 0.6 “HOW” TO MOVE no pre-filtering for significant coherence z-trans part. coherence Time Into Delay Period (ms)
Conclusions Significant, sustained coherence appears in the delay period in an effector choice task. Cells that make effector decisions are more likely to be cross- cortically coherent, supporting the idea that coherence represents influence across cortical regions. The effector decision makes it unlikely that this cross-cortical coherence has exclusively to do with spatial attention. There is an overall increase in parieto-frontal coherence during effector decision-making, potentially suggesting that the type of decision affects the direction of communication.
Thanks The Swartz foundation The Andersen laboratory Richard Andersen, Tessa Yao, Viktor Shcherbatyuk, Xoana Troncoso, Linus Schumacher, and many other talented folks Bijan Pesaran, for many helpful conversations Monkeys L & Z