question:

how are neurons in the primary visual cortex encoding the visual scene?

question:

how are neurons in the primary visual cortex encoding the visual scene?

traditional approach:

question:

how are neurons in the primary visual cortex encoding the visual scene?

traditional approach:

• saturation

question:

how are neurons in the primary visual cortex encoding the visual scene?

traditional approach:

• saturation

• cross-orientation suppr

question:

how are neurons in the primary visual cortex encoding the visual scene?

traditional approach:

• saturation

• cross-orientation suppr

• center-surround suppr

question:

how are neurons in the primary visual cortex encoding the visual scene?

traditional approach:

• saturation

• cross-orientation suppr

• center-surround suppr

• luminance, phase, etc

question:

how are neurons in the primary visual cortex encoding the visual scene?

traditional approach:

• saturation

• cross-orientation suppr

• center-surround suppr

• luminance, phase, etc

carandini 2004

question:

how are neurons in the primary visual cortex encoding the visual scene?

traditional approach:

• saturation

• cross-orientation suppr

• center-surround suppr

• luminance, phase, etc

question:

how are neurons in the primary visual cortex encoding the visual scene?

traditional approach:

question:

how are neurons in the primary visual cortex encoding the visual scene?

traditional approach:

• saturation

• cross-orientation suppr

• center-surround suppr

• luminance, phase, etc

gratings

natural images

2 important directions:

• characterize response of neural populations

• use natural stimuli

natural images

Coding of Natural Scenes in Primary Visual Cortex

Weliky, Fiser, Hunt, Wagner

Neuron 37: 703-718, (2003).

population coding, natural image stimulation:

the setup:

• anesthetized ferrets

• multi-electrode cortical surface recorder, ~40 sites

• flashed gratings, white squares, nat images

CRF

tuning curves

white squares, reverse correlation

sine wave gratings

model for single cell response

phase insensitive!

model for single cell response

CRF

tuning curves

white squares, reverse correlation

sine wave gratings

model: band-pass filter, localized to CRF

output

phase insensitive!

output

neurons

correlation across all images, all recording sites

effect of surround modulation on prediction accuracy

no effect on site-specific correlation better predictions of pop response for large-field

restrict stimuli to CRF, compare to large-field

both still badly predicted by local models

in their words,

“...we found no significant differences between recorded activity on the surface compared to activity recorded with penetrating electrodes in layer 2/3.”

“Although the correlation between local contrast structure and cell responses is modest at the level of individual cortical sites, a very simple population code, derived from activity integrated across cortical sites having retinotopically overlapping receptive fields, represents the local contrast structure of natural scenes very well.”

“...our results demonstrate that by integrating across retino topically neighboring recording sites, a significant degree of linearity is restored to the distributed representation of natural scenes in primary visual cortex.”

“...our study is a restoration of this original classical model claiming that relevant information for coding natural scenes is in the classical receptive field.”

problems

• anesthetized ferrets

• surface recording

• flashed images, not movies

• correlation, not percent variance explained

• predict “retinotopic map”, not neural activity or stimulus identity

• neurons coding “local contrast structure”?

• sparseness = efficiency?

• sparseness, efficiency measures for multiple cell recordings

references/future discussions

Vinje and Gallant (2002)

stimulation of nCRF with nat-vis movies makes firing sparse and efficient

David, Vinje, and Gallant (2004)

phase-sep fourier receptive fields are diff for gratings and nat-vis movies

Felsen, Touryan, and Dan (2005)

quad-pair model doesn’t predict response to naturilistic images

Guo, Robertson, Mahmoodi, and Young (2005)

surround of nat images modulates response; phase important

Smyth, Willmore, Baker, Thompson, Tolhurst (2003)

reverse corr invalid for nat stims; reg-inverse more correct, leads to similar receptive fields for gratings and nat images

Kayser, Salazar, and Koenig (2003)

LFP and spiking show diff activity for broad-band stims, motion important

Guo, Robertson, Mahmoodi, Young (2005)

David, Vinje, Gallant (2004)

David, Vinje, Gallant (2004)