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2nd TAC Meeting Christian B. Mendl Tim Gollisch Lab Neuronal Coding in the Retina and Fixational Eye Movements April 22, 2010

2nd TAC Meeting

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2nd TAC Meeting. Neuronal Coding in the Retina and Fixational Eye Movements. Christian B. Mendl Tim Gollisch Lab. April 22, 2010. Outline. Review of last TAC meeting Informative spike response features Latency coding by cell pairs Modeling response features Outlook. - PowerPoint PPT Presentation

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Page 1: 2nd TAC Meeting

2nd TAC Meeting

Christian B. MendlTim Gollisch Lab

Neuronal Coding in the Retinaand Fixational Eye Movements

April 22, 2010

Page 2: 2nd TAC Meeting

Outline

• Review of last TAC meeting• Informative spike response

features• Latency coding by cell pairs• Modeling response features• Outlook

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Review of Last TAC Meeting

• Fixational eye movements, microsaccades• Counteract visual perception fading• Enhancement of spatial resolution

• Last TAC meeting: information theory: mutual information, synergy → use as screening tool

• To-do:– stimulus variation: grating instead of border– neuronal model building– decoding strategies

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Informative Spike Response Features

Observed spike responses of a single cell

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Various Response Typesa) b)

d)c)

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Informative Spike Features (cont)Observed spike responses of a single cell

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Informative Spike Responses:Number of Spikes/Trial

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Informative Spike Responses:Internal Structure

ISI (inter-spike-interval)

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Informative Spike Responses:Latency

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Latency Coding by Cell Pairs

• Latency emerges as most informative spike response feature

• Timing reference? (Brain doesn’t know stimulus onset)

• → Need several cells

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Cell Pairs: Experimental Data

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Relative Latencytime intervals accessible to readout by higher brain regions

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Cell Pairs: Latency Scatter Plot

K-means clustering: relative weight of off-diagonal elements:19.1%

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Global Drift Correction

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Drift-Corrected Latency Scatter Plot

K-means clustering:relative weight ofoff-diagonal elements:9.6%

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Latency Correlations

• Observation: global latency drift leads to (artificial) correlations, can correct for that

• Question: cells internally interacting on short-term scale?

• → Compare spikes shuffled by one trial

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Latency Correlations (cont)

shuffled version: no correlations

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Latency Correlation Statistics

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Conclusions Latency Coding

• Use latency instead of spike count and inter-spike-interval

• High information content in latency data from two cells

• Correlations might improve coding

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Comparison with LN Models

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LN Models (cont)

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Conclusions Modeling

• Qualitative agreement• But still much room for

improvement, latency data on 10 ms scale not reproduced

• Gain control might be able to reproduce experimental spike histogram

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Outlook

• Fixational eye movements have been reported in Salamander

• But precise quantification still missing• → Search coil setup