Literature DB >> 9705450

Spatial phase and the temporal structure of the response to gratings in V1.

J D Victor1, K P Purpura.   

Abstract

We recorded single-unit activity of 25 units in the parafoveal representation of macaque V1 to transient appearance of sinusoidal gratings. Gratings were systematically varied in spatial phase and in one or two of the following: contrast, spatial frequency, and orientation. Individual responses were compared based on spike counts, and also according to metrics sensitive to spike timing. For each metric, the extent of stimulus-dependent clustering of individual responses was assessed via the transmitted information, H. In nearly all data sets, stimulus-dependent clustering was maximal for metrics sensitive to the temporal pattern of spikes, typically with a precision of 25-50 ms. To focus on the interaction of spatial phase with other stimulus attributes, each data set was analyzed in two ways. In the "pooled phases" approach, the phase of the stimulus was ignored in the assessment of clustering, to yield an index Hpooled. In the "individual phases" approach, clustering was calculated separately for each spatial phase and then averaged across spatial phases to yield an index Hindiv. Hpooled expresses the extent to which a spike train represents contrast, spatial frequency, or orientation in a manner which is not confounded by spatial phase (phase-independent representation), whereas Hindiv expresses the extent to which a spike train represents one of these attributes, provided spatial phase is fixed (phase-dependent representation). Here, representation means that a stimulus attribute has a reproducible and systematic influence on individual responses, not a neural mechanism for decoding this influence. During the initial 100 ms of the response, contrast was represented in a phase-dependent manner by simple cells but primarily in a phase-independent manner by complex cells. As the response evolved, simple cell responses acquired phase-independent contrast information, whereas complex cells acquired phase-dependent contrast information. Simple cells represented orientation and spatial frequency in a primarily phase-dependent manner, but also they contained some phase-independent information in their initial response segment. Complex cells showed primarily phase-independent representation of orientation but primarily phase-dependent representation of spatial frequency. Joint representation of two attributes (contrast and spatial frequency, contrast and orientation, spatial frequency and orientation) was primarily phase dependent for simple cells, and primarily phase independent for complex cells. In simple and complex cells, the variability in the number of spikes elicited on each response was substantially greater than the expectations of a Poisson process. Although some of this variation could be attributed to the dependence of the response on the spatial phase of the grating, variability was still markedly greater than Poisson when the contribution of spatial phase to response variance was removed.

Mesh:

Year:  1998        PMID: 9705450     DOI: 10.1152/jn.1998.80.2.554

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  12 in total

1.  Interspike intervals, receptive fields, and information encoding in primary visual cortex.

Authors:  D S Reich; F Mechler; K P Purpura; J D Victor
Journal:  J Neurosci       Date:  2000-03-01       Impact factor: 6.167

2.  Influence of temporal correlation of synaptic input on the rate and variability of firing in neurons.

Authors:  G Svirskis; J Rinzel
Journal:  Biophys J       Date:  2000-08       Impact factor: 4.033

3.  Nonlinear spectrotemporal sound analysis by neurons in the auditory midbrain.

Authors:  Monty A Escabi; Christoph E Schreiner
Journal:  J Neurosci       Date:  2002-05-15       Impact factor: 6.167

4.  Phosphene threshold as a function of contrast of external visual stimuli.

Authors:  Andreas M Rauschecker; Sven Bestmann; Vincent Walsh; Kai V Thilo
Journal:  Exp Brain Res       Date:  2004-05-26       Impact factor: 1.972

5.  Low error discrimination using a correlated population code.

Authors:  Greg Schwartz; Jakob Macke; Dario Amodei; Hanlin Tang; Michael J Berry
Journal:  J Neurophysiol       Date:  2012-04-25       Impact factor: 2.714

6.  Neural coding of image structure and contrast polarity of Cartesian, hyperbolic, and polar gratings in the primary and secondary visual cortex of the tree shrew.

Authors:  Jordan Poirot; Paolo De Luna; Gregor Rainer
Journal:  J Neurophysiol       Date:  2016-02-03       Impact factor: 2.714

7.  The integration of multiple stimulus features by V1 neurons.

Authors:  Alexander Grunewald; Evelyn K Skoumbourdis
Journal:  J Neurosci       Date:  2004-10-13       Impact factor: 6.167

Review 8.  Computational identification of receptive fields.

Authors:  Tatyana O Sharpee
Journal:  Annu Rev Neurosci       Date:  2013-07-08       Impact factor: 12.449

9.  Low-frequency local field potentials and spikes in primary visual cortex convey independent visual information.

Authors:  Andrei Belitski; Arthur Gretton; Cesare Magri; Yusuke Murayama; Marcelo A Montemurro; Nikos K Logothetis; Stefano Panzeri
Journal:  J Neurosci       Date:  2008-05-28       Impact factor: 6.167

10.  Robust temporal coding of contrast by V1 neurons for transient but not for steady-state stimuli.

Authors:  F Mechler; J D Victor; K P Purpura; R Shapley
Journal:  J Neurosci       Date:  1998-08-15       Impact factor: 6.167

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.