Dynamics of orientation tuning in the cat striate cortex neurons

Shevelev, I. A.; Sharaev, G. A.; Lazareva, N. A.; Novikova, R. V.; Тихомиров, А. С.

doi:10.1016/0306-4522(93)90133-z

Cited by 36 publications

(21 citation statements)

References 51 publications

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“…The ACs have been computed from the activity of the network during 9 set after stimulus on& cortex of behaving monkeys (Celebrini et al, 1993). The experimental situation in cat cortex is not clear (Shevelev et al, 1993).…”

Section: Summary and Discussionmentioning

confidence: 99%

Chaos and synchrony in a model of a hypercolumn in visual cortex

Hansel

Sompolinsky²

1996

J Comput Neurosci

160

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Neurons in cortical slices emit spikes or bursts of spikes regularly in response to a suprathreshold current injection. This behavior is in marked contrast to the behavior of cortical neurons in vivo, whose response to electrical or sensory input displays a strong degree of irregularity. Correlation measurements show a significant degree of synchrony in the temporal fluctuations of neuronal activities in cortex. We explore the hypothesis that these phenomena are the result of the synchronized chaos generated by the deterministic dynamics of local cortical networks. A model of a "hypercolumn" in the visual cortex is studied. It consists of two populations of neurons, one inhibitory and one excitatory. The dynamics of the neurons is based on a Hodgkin-Huxley type model of excitable voltage-clamped cells with several cellular and synaptic conductances. A slow potassium current is included in the dynamics of the excitatory population to reproduce the observed adaptation of the spike trains emitted by these neurons. The pattern of connectivity has a spatial structure which is correlated with the internal organization of hypercolumns in orientation columns. Numerical simulations of the model show that in an appropriate parameter range, the network settles in a synchronous chaotic state, characterized by a strong temporal variability of the neural activity which is correlated across the hypercolumn. Strong inhibitory feedback is essential for the stabilization of this state. These results show that the cooperative dynamics of large neuronal networks are capable of generating variability and synchrony similar to those observed in cortex. Auto-correlation and cross-correlation functions of neuronal spike trains are computed, and their temporal and spatial features are analyzed. In other parameter regimes, the network exhibits two additional states: synchronized oscillations and an asynchronous state. We use our model to study cortical mechanisms for orientation selectivity. It is shown that in a suitable parameter regime, when the input is not oriented, the network has a continuum of states, each representing an inhomogeneous population activity which is peaked at one of the orientation columns. As a result, when a weakly oriented input stimulates the network, it yields a sharp orientation tuning. The properties of the network in this regime, including the appearance of virtual rotations and broad stimulus-dependent cross-correlations, are investigated. The results agree with the predictions of the mean field theory which was previously derived for a simplified model of stochastic, two-state neurons. The relation between the results of the model and experiments in visual cortex are discussed.

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Section: Summary and Discussionmentioning

confidence: 99%

Chaos and synchrony in a model of a hypercolumn in visual cortex

Hansel

Sompolinsky²

1996

J Comput Neurosci

160

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“…This dichotomy between regions having iso-and nonoriented responses suggests that horizontal connections may delimit two specialized regions, corresponding to signals narrowly and broadly tuned for orientation. In addition, the distribution of optical activity in these regions changed dramatically during repetitive stimulation, suggesting that horizontal connections may contribute to the dynamics of receptive field properties in vivo (Celebrini et al 1993;Pei et al 1994;Ringach et al 1997;Shevelev et al 1993). By evoking spatial and temporal dynamics in the distribution of excitatory and inhibitory synaptic potentials, horizontal connections provide a synaptic physiological correlate for the temporal evolution of receptive fields.…”

Section: Role Of the Horizontal Network In Sculpting Population-basedmentioning

confidence: 95%

Spatiotemporal Patterns of Excitation and Inhibition Evoked by the Horizontal Network in Layer 2/3 of Ferret Visual Cortex

Tucker¹,

Katz

2003

Journal of Neurophysiology

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The horizontal network in visual cortex layer 2/3 is implicated in numerous psychophysical and physiological properties. To investigate the spatial and temporal distribution of excitation and inhibition evoked by this network, we used voltage-sensitive dyes to image the responses to focal electrical stimulation in tangential slices of ferret visual cortex layer 2/3. The resulting optical patterns included a diffuse zone of activation near the stimulation site and numerous ovoid domains throughout the slice. In contrast to the fixed anatomy of the horizontal connections, substantial shifts in both space and time were evident in the distribution of population-based neuronal activity during stimulus trains. Both of these shifts relied on inhibitory synaptic potentials, suggesting that inhibition driven by horizontal connections sculpts the distribution of activity in this cortical network.

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“…A difference in phase is responsible for the emergence of spatiotemporally non-separable and hence direction-selective receptive fields, whereas a difference in the preferred orientation of non-lagged and lagged inputs corresponds to a rotation of the preferred orientation in time. Receptive fields with preferred orientation that drifts in time seem to be uncommon [2,3,26], at least in adult animals, although there are some reports of such cells [21,24]. A developmental mechanism that results in this type of receptive field, however, could underlie the earliest development of direction selectivity, after which receptive fields could be modified by vision.…”

Section: Discussionmentioning

confidence: 87%

“…1 may serve as an example of this case. Different orientations of non-lagged and lagged inputs correspond to a rotation of the preferred orientation in time, a feature that is rarely seen in simple cell responses [2,3,26], although some reports support the hypothesis of preferred orientation drifting in time [21,24].…”

Section: Constant Correlations Between Non-lagged and Lagged Inputsmentioning

confidence: 94%

“…However, the preferred orientations of the lagged and non-lagged inputs to a cell are then uncorrelated, resulting in spatiotemporal receptive fields whose preferred orientation changes with time. Experimentally, this feature of a spatiotemporal receptive field appears to be uncommon, at least in adult animals [2,3,26], although some authors report receptive fields with preferred orientations that drift over time [21,24]. If the correlations between lagged and non-lagged inputs are stronger, then the preferred orientations of the two types of input coincide but direction selectivity fails to develop.…”

Section: Introductionmentioning

confidence: 94%

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Development of spatiotemporal receptive fields of simple cells: II. Simulation and analysis

et al. 1997

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In part I of this article a correlation based model for the developmental process of spatiotemporal receptive fields has been introduced. In this model the development is described as an activity-dependent competition between four types of input from the lateral geniculate nucleus onto a cortical cell, viz. non-lagged ON and OFF and lagged ON and OFF inputs. In the present paper simulation results and a first analysis are presented for this model. We study the developmental process both before and after eye-opening and compare the results with experimental data from reverse correlation measurements. The outcome of the developmental process is determined mainly by the spatial and the temporal correlations between the different inputs. In particular, if the mean correlation between non-lagged and lagged inputs is weak, receptive fields with a widely varying degree of direction selectivity emerge. However, spatiotemporal receptive fields may show rotation of their preferred orientation as a function of response delay. Even if the mean correlation between two types of temporal input is not weak, direction-selective receptive fields may emerge because of an intracortical interaction between different cortical maps. In an environment of moving lines or gratings, direction-selective receptive fields develop only if the distribution of the directions of motion presented during development shows some anisotropy. In this case, a continuous map of preferred direction is also shown to develop.

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Dynamics of orientation tuning in the cat striate cortex neurons

Cited by 36 publications

References 51 publications

Chaos and synchrony in a model of a hypercolumn in visual cortex

Chaos and synchrony in a model of a hypercolumn in visual cortex

Spatiotemporal Patterns of Excitation and Inhibition Evoked by the Horizontal Network in Layer 2/3 of Ferret Visual Cortex

Development of spatiotemporal receptive fields of simple cells: II. Simulation and analysis

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