Identification of complex-cell intensive nonlinearities in a cascade model of cat visual cortex.

Complex cells in the cat's visual cortex show nonlinearities in processing of image luminance and movement. To study mechanisms, initially we have represented the chain of neurons from retina to cortex as a black-box model. Independent information about the visual system has helped us cast this "Wiener-kernel" model into a dynamic-linear/static-nonlinear/dynamic-linear (LNL) cascade. We then use system identification techniques to define the nature of these transformations directly from responses of the neuron to a single presentation of a stimulus composed of a sequence of white-noise-modulated luminance values. The two dynamic linear filters are mainly low-pass, and the static nonlinearity is mainly of even polynomial degree. This approximate squaring function may be effected in the animal by soft-thresholding each of the linear ON- and OFF-channel signals and then summing them, which account for "ON-OFF" responses and for the squaring operation needed for computation of "motion energy", both observed in these neurons.

Nonlinear measurement and classification of receptive fields in cat retinal ganglion cells.

Originally, modeling of ganglion-cell responses in cat was based mainly on linear analysis. This is satisfactory for those cells in which spatial summation of excitation is approximately linear (X-cells) but it fails for Y-cells, where summation has strong nonlinear components. Others have shown the utility of using sinusoidal analysis to study harmonic and intermodulation nonlinearities in the temporal frequency domain. We have used Wiener-kernel analysis to obtain directly both temporal and spatial impulse responses and their nonlinear interactions. From these, we were able to predict accurately the responses that a counterphase modulated grating elicited in both X-cells and Y-cells. In addition, we show that the first-order responses can measure the two-dimensional spatial features of the receptive field with high resolution. Thus, nonlinear analysis of responses to white-noise stimuli may be sufficient to both classify and measure the receptive fields of many different types of ganglion cells.

Nonlinear directionally selective subunits in complex cells of cat striate cortex.

1. We have analyzed receptive fields (RFs) of directionally selective (DS) complex cells in the striate cortex of the cat. We determined the extent to which the DS of a complex cell depends on spatially identifiable subunits within the RF by studying responses to an optimally oriented, three-luminance-valued, gratinglike stimulus that was spatiotemporally randomized. 2. We identified subunits by testing for nonlinear spatial RF interactions. To do this, we calculated Wiener-like kernels in a spatial superposition test that depended on two RF positions at a time. The spatial and temporal separation of light and dark bars at these two positions varied over a spatial range of 8 degrees and a temporal range of +/- 112 ms in increments of 0.5 degree and 16 ms, respectively. 3. DS responses in complex cells cannot be explained by their responses to single light or dark bars because any linear superposition of responses whose time course is uniform across space shows no directional preference. 4. Nonlinear interactions between a flashed reference bar that is fixed in position and a second bar that is flashed at surrounding positions help explain DS by showing multiplicative-type facilitation for bar pairs that mimic motion in the preferred direction and suppression for bar pairs that mimic motion in the null direction. Interactions in the preferred direction have an optimal space/time ratio (velocity), exhibited by elongated, obliquely oriented positive domains in a space-time coordinate frame. This relationship is inseparable in space-time. The slope of the long axis specifies the preferred speed, and its negative agrees with the most strongly suppressed speed in the opposite direction. 5. When the reference bar position is moved across the RF, the spatiotemporal interaction moves with it. This suggests the existence of a family of nearly uniform subunits distributed across the RF. We call the subunit interaction, as averaged across the RF, the "motion kernel" because its spatial and temporal variables are those necessary to specify the velocity, the only parameter that distinguishes a moving image from a temporally modulated stationary image. The nonlinear interaction shows a spatial periodicity, which suggests a mechanism of velocity selectivity for moving extended images.(ABSTRACT TRUNCATED AT 400 WORDS)

Applications of minimum-order Wiener modeling to retinal ganglion cell spatiotemporal dynamics.

In a previous paper (Marmarelis et al. 1986) we presented the concept of minimum-order Wiener (MOW) modeling of continuous-input/spike-output (CISO) systems. The associated MOW methodology aims at obtaining low-order Wiener models for CISO systems of practical interest. The assertion was made that many neurophysiological systems that fall in this class can be studied effectively by the use of this method. We have chosen a sensory system to demonstrate the efficacy of the method with actual experimental data. The response of retinal ganglion cells to spatiotemporal visual stimuli was studied with this approach and a second-order MOW model was obtained. The results appear to corroborate the adequacy of this model in terms of predicting the timing of the output spikes.

Minimum-order Wiener modelling of spike-output systems.

Systems that generate spike outputs in response to continuous inputs abound in neurophysiology. The study of their dynamics with the use of systems analysis methods has been complicated by the difference in modality of the input and output signals. When the problem is placed in the framework of Wiener's theory in discrete time, an infinite functional series is required for the formal representation of the input-output relation. This has given rise to the belief that a large number of Wiener functionals is needed in practice before a model of reasonable accuracy can be obtained. In this paper, we introduce the concept of minimum-order Wiener models for spike-output systems, and we show that a low-order Wiener model is adequate in many cases for predicting fully the timing of the output spikes.

Modification of electroretinograms in dopamine-depleted retinas.

The functional role of dopamine in frog retina was examined in a combined neurochemical, immunohistochemical and electrophysiological study. Dopamine and serotonin are the primary monoamines present in the retina and they are localized to amacrine cells which have distinct morphologies. Intravitreal injection of 6-hydroxydopamine was found to produce a selective depletion of retinal dopamine content and elimination of tyrosine hydroxylase-like immunoreactivity. Electroretinograms from 6-hydroxydopamine-treated retinas demonstrated enhanced oscillatory potentials and a lengthening of the b-wave implicit time compared to vehicle control retinas; both of these changes in the electroretinogram were reversed by the dopamine agonist apomorphine. These observations support earlier suggestions that dopamine-containing amacrine cells are part of a retinal feedback system that generates oscillatory potentials and plays a role in light adaptation.

White noise analysis of cortical directional selectivity in cat.

We studied spatiotemporal interactions in cat cortical receptive fields by presenting a stimulus composed of 16 narrow bars whose luminances were randomly modulated. Conventional stimuli were also presented to classify receptive field properties. A white noise estimate of the cell's response to a stepwise moving bar stimulus was calculated from responses to the spatiotemporal random stimulus. The white noise estimate captured the most important feature of the receptive field demonstrated by conventional stimuli, i.e. directional selectivity. In addition, the white noise analysis; (1) made visible inhibitory response phases that are usually below threshold; (2) subdivided the response into its linear and non-linear estimates; (3) further subdivided the non-linear estimate into spatial and temporal interactions; and (4) allowed estimation of responses to stimuli that were never explicitly presented.

The jet stream microbeveler: an inexpensive way to bevel ultrafine glass micropipettes.

Ultrafine glass micropipettes can be easily beveled in a jet stream of grinding compound suspended in saline. The beveling is gradual and continuous, highly reliable, and can be accomplished with common laboratory apparatus. The beveled electrodes are comparable in performance to those prepared with expensive commercial bevelers.