Receptive-field structure in cat striate cortex.

Palmer, Larry A.; Davis, Thomas L.

doi:10.1152/jn.1981.46.2.260

Cited by 181 publications

(128 citation statements)

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“…Figure 2 shows only these two types of balanced excitatory and inhibitory circuits. Other cortical interactions also balance excitation and inhibition, including the interactions that realize monocular simple cell receptive fields in layer 4 (data: Liu et al, 1992;Palmer and Davis, 1981;Pollen and Ronner, 1981;model: Olson and Grossberg, 1998). Balanced excitatory/inhibitory interactions within layer 3B also give rise to binocular simple cells that initiate stereopsis by matching monocular inputs from different eyes (Cao and Grossberg, 2005;Grossberg and Howe, 2003).…”

Section: Balanced Excitatory and Inhibitory Circuits As A Cortical Dementioning

confidence: 99%

Towards a unified theory of neocortex: laminar cortical circuits for vision and cognition

Grossberg¹

2007

Progress in Brain Research

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Section: Balanced Excitatory and Inhibitory Circuits As A Cortical Dementioning

confidence: 99%

Towards a unified theory of neocortex: laminar cortical circuits for vision and cognition

Grossberg¹

2007

Progress in Brain Research

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“…Some studies used only bright stimuli and observed cells that produced excitation or suppression but not both (Toyama and Takeda, 1974;Gilbert, 1977;Palmer and Davis, 1981), but without responses to dark stimuli, it is impossible to know whether these cells were sensitive to only one polarity. In other studies that used bright and dark stimuli to document single-polarity responses, only sustained responses were observed.…”

Section: Relationship To Previous Work On Cells Responsive To a Singlmentioning

confidence: 99%

A Dynamic Nonlinearity and Spatial Phase Specificity in Macaque V1 Neurons

Williams¹,

Shapley²

2007

J. Neurosci.

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While studying the visual response dynamics of neurons in the macaque primary visual cortex (V1), we found a nonlinearity of temporal response that influences the visual functions of V1 neurons. Simple cells were recorded in all layers of V1; the nonlinearity was strongest in neurons located in layer 2/3. We recorded the spike responses to optimal sinusoidal gratings that were displayed for 100 ms, a temporal step response. The step responses were measured at many spatial phases of the grating stimulus. To judge whether simple cell behavior was consistent with linear temporal integration, the decay of the 100 ms step response at the preferred spatial phase was used to predict the step response at the opposite spatial phase. Responses in layers 4B and 4C were mostly consistent with a linear-plus-staticnonlinearity cascade model. However, this was not true in layer 2/3 where most cells had little or no step responses at the opposite spatial phase. Many layer 2/3 cells had transient preferred-phase responses but did not respond at the offset of the opposite-phase stimuli, indicating a dynamic nonlinearity. A different stimulus sequence, rapidly presented random sinusoids, also produced the same effect, with layer 2/3 simple cells exhibiting elevated spike rates in response to stimuli at one spatial phase but not 180°away. The presence of a dynamic nonlinearity in the responses of V1 simple cells indicates that first-order analyses often capture only a fraction of neuronal behavior. The visual implication of our results is that simple cells in layer 2/3 are spatial phase-sensitive detectors that respond to contrast boundaries of one sign but not the opposite.

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“…For instance, there is evidence that directional selectivity is dependent on intracortical inhibitory mechanisms (Tsumoto et al, 1979;Sillito, 1984;Livingstone, 1998). Perhaps the blockage of inhibitory mechanisms reduces directional selectivity by affecting the push-pull mechanisms of simple cells (Hubel and Wiesel, 1962;Palmer and Davis, 1981;Ferster, 1988;Hirsch et al, 1998). Another possibility is that some DS cells might be generated from the difference instead of the sum of two non-DS inputs.…”

Section: Multiple Derivations Of Directional Selectivitymentioning

confidence: 99%

The Derivation of Direction Selectivity in the Striate Cortex

Peterson

Li²,

Freeman³

2004

J. Neurosci.

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In the central visual pathway of binocular animals, the property of directional selectivity (DS) is first exhibited in striate cortex. In this study, we sought to determine the neural circuitry underlying the transformation from non-DS neurons to DS cortical cells. In a well established model, DS receptive fields (RFs) are derived from the sum of two non-DS inputs with 90°(quadrature) spatiotemporal phase differences. We explored possible input sources for this model, which include non-DS simple cells and lateral geniculate nucleus (LGN) neurons, by examination of spatiotemporal RFs of single cells and of pairs of cells. We find that distributions of non-DS simple RFs do not match the temporal predictions of the quadrature model because of a lack of long-latency responses. The long-latency inputs could potentially arise from lagged LGN afferents. However, analysis of cell pairs indicates that DS cells receive cortical input from non-DS simple cells for both short-and long-latency components, with temporal phase differences typically Ͻ90°. Furthermore, the distribution of minimum phase differences needed to generate DS cells overlaps that exhibited by non-DS simple cells. Considered together, these results are consistent with a linear model whereby DS simple cells are formed from simple-cell inputs, with temporal phase differences often less than quadrature.

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Receptive-field structure in cat striate cortex.

Cited by 181 publications

References 0 publications

Towards a unified theory of neocortex: laminar cortical circuits for vision and cognition

Towards a unified theory of neocortex: laminar cortical circuits for vision and cognition

A Dynamic Nonlinearity and Spatial Phase Specificity in Macaque V1 Neurons

The Derivation of Direction Selectivity in the Striate Cortex

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