Spatio-temporal cross-correlation analysis of catfish retinal neurons

State changes rapidly modulate cortical neuronal responsiveness

The responsiveness of cortical neurons is strongly and rapidly influenced by changes in the level of local network activity. In rodent somatosensory cortex, increases in network activity increase neuronal responsiveness to the intracellular injection of brief conductance stimuli but paradoxically decrease responsiveness to brief whisker deflections. However, whisker stimulation frequently evokes long-lasting changes in the level of local circuit activity. The ability of stimuli to successfully evoke prolonged increases in circuit activity is associated with both an increase in the amount of conductance evoked by a whisker stimulus and an increase in action potential responsiveness to whisker stimulation. In addition, brief whisker stimuli presented during periods of high network activity evoke postsynaptic potentials containing a greater proportion of inhibition, consistent with an increased efficiency in the activation of inhibitory mechanisms during the Up state. In contrast, during prolonged and variable whisker stimulation, increased network activity is associated with an increase in overall responsiveness, dynamic range, output gain, and correlation between action potential response and speed of whisker movement. We conclude that stimulus-evoked or spontaneous alterations in cortical state can influence neuronal responsiveness in a complex manner, resulting in large changes in which, and how, sensory stimuli are represented.

Spatio-temporal receptive fields in carp retinal horizontal cells

1. The dynamics of the receptive fields of retinal horizontal cells were examined by applying a spatio-temporal modulated light signal to the retina. 2. The spatio-temporal receptive fields of both cone- and rod-driven horizontal cells, estimated through cross-correlation between the modulated light signal and the cells' responses, showed their receptive fields (the space-dependent component) to be reduced in size with time. 3. In cone-driven horizontal cells, the reduction in receptive field size was initially small but then rapidly became prominent with time. The time to peak of the time-dependent component of spatio-temporal receptive fields did not depend on the distance from the centre. 4. Application of a small amount of Co2+, an agent blocking the cone-driven horizontal cells' feedback action on cones, or GABA, resulted in a reversal of the time-dependent shrinkage of receptive fields to time-dependent expansion. 5. In rod-driven horizontal cells, the receptive field shrinkage was slow. The time to peak of the time-dependent component decreased with the distance from the centre. 6. Image processing experiments examining the response pattern in the horizontal cell layer (neural image) to a moving square of light showed smudging of the neural image when the time-dependent receptive field expansion was present, while there was essentially no smudging under conditions of receptive field shrinkage.

Response dynamics and receptive-field organization of catfish ganglion cells

Responses from catfish retinal ganglion cells were evoked by a spot or an annulus of light and were analyzed by a procedure identical to the one used previously to study catfish amacrine cells (Sakai H. M., and K.-I. Naka, 1992. Journal of Neurophysiology. 67:430-442.). In two-input white-noise experiments, a response evoked by simultaneous stimulation of the center and surround was decomposed into the components generated by the center and surround through a process of cross-correlation. The center and surround responses were also decomposed into their linear and nonlinear components so that the response dynamics of the linear and nonlinear components could be measured. We found that the concentric organization of the receptive field was determined by linear components, i.e., the first-order kernels generated by the center and surround were of opposite polarity. Both the center and surround generated second-order kernels with similar signatures, i.e., the second-order components formed a monotonic receptive field. The peak response time of the first- and second-order kernels from the surround was longer by approximately 20 ms than that of the center. Except for the DC potential present in the intracellular responses, almost identical first- and second-order kernels for the center and surround were obtained from both the intracellular response and spike discharges. Thus, information on concentric organization of a receptive field is translated into spike discharges with little loss of information. A train of spike discharges carries, simultaneously, at least four kinds of information: two linear and two nonlinear components, which originate in the receptive field center and the surround. A spike train is not a simple signaling device but is a carrier of complex and multiple signals. Victor, J. D., and R. M. Shapley (1979. Journal of General Physiology. 74:671-687.) discovered similarly that, in the cat retina, static second-order nonlinearity is encoded into spike trains. Results obtained in this study support the thesis that signals generated by the preganglionic cells are translated into spike discharges without major modification and that those signals can be recovered from the spike trains (Sakuranaga, M., Y. Ando, and K.-I. Naka. 1987. Journal of General Physiology. 90:229-259.; Korenberg, M. J., H. M. Sakai, and K.-I. Naka. 1989. Journal of Neurophysiology. 61:1110-1120.). Current injection studies have shown that such signal transmission is possible (Sakai, H. M., and K.-I. Naka, 1988a. Journal of Neurophysiology. 60:1549-1567.; 1990. Journal of Neurophysiology. 63:105-119.).

White-noise analysis in visual neuroscience

In 1827, plant biologist Robert Brown discovered what is known as Brownian motion, a class of chaos. Formal derivative of Brownian motion is Gaussian white-noise. In 1938, Norbert Wiener proposed to use the Gaussian white-noise as an input probe to identify a system by a series of orthogonal functionals known as the Wiener G-functionals. White-noise analysis is uniquely suited for studying the response dynamics of retinal neurons because (1) white-noise light stimulus is a modulation around a mean luminance, as are the natural photic inputs, and it is a highly efficient input; and (2) the analysis defines the response dynamics and can be extended to spike trains, the final output of the retina. Demonstrated here are typical examples and results from applications of white-noise analysis to a visual system.

Electronic simulation of cones, horizontal cells and bipolar cells of generalized vertebrate cone retina

Electronic analogue of my theoretical model of generalized vertebrate cone retina [Siminoff: J. Theor. Biol. 86, 763 (1980)] is presented. Cone mosaic is simulated by 25 X 21 grid of phototransistors that have colored filters mounted in front of then to produce red-, green-, and blue-sensitive cones arranged in a "trichromatic" retina. Each retinal element is simulated by Summator-Integrator and unit gain voltage invertes are used to give correct polarities to output voltages. Dynamic properties of retinal elements are developed solely by temporal interplay of antagonistic input voltages with differing time courses, and spatial organization of receptive fields is developed by unit hexagons that precisely define cone input voltages to subsequent elements. Electronic model contains both color- and non-color-coded channels. Negative feedback from L-horizontal cells to cones, electrical coupling of like-cones, and electrical coupling of like-horizontal cells are simulated by feedforward circuits. Stray light is present due to light scattering properties of colored filters used to simulate color selectivety of cones. Stationary and moving spots of white and colored lights of varied sizes and intensities are used to study characteristics of electronic analogue. Results demonstrate practicality of electronic simulation to function analogues to real cone retinas to process visual stimuli and give information to higher centers as to size, shape, color and motion of objects in visual world.

A new photographic method for mapping spatio-temporal receptive field using television snow stimulation

A means was devised to measure simultaneously spatial as well as temporal characteristics of visual receptive fields by stimulating the retina with the noise obtained on an unused television channel. The input, television snow, and the output, neural response, were recorded on a video tape. The tape was played back to obtain the (linear) spatio-temporal Wiener kernel by cross-correlating the input with the output. This method can be applied to extract the linear part of the visual responses in time and space.

An analogue model of the luminosity-channel in the vertebrate cone retina. 1. Hardware and responses to square wave voltages

An analogue simulation was built of the vertebrate cone retina based on the model of Siminoff [J. Theor. Biol. 86, 673 (1980)]. Linear operational amplifiers were used for a few simple processes such as summation, integration (for synaptic delay), inversion and gain. Spatial and temporal properties of retinal elements were developed by interaction of simulated retinal neurons. Tonic and phasic ganglion cells were formed from the center-surround antagonistic receptive fields of bipolar cells. Center field input voltages favored the static levels of tonic units, while surround field input voltages favored the phasic units. Properties of receptive fields of retinal neurons could be simulated by the model using 2 antagonistic input voltages, one of which had a longer synaptic delay. Negative feedback from horizontal cells to cones and its potentiation by electrical coupling of horizontal cells reinforced overshoot produced by surround field input voltages with its extra synaptic delay as compared to the center field input voltage. In spite of simplifications, the model was a good representation of some properties of the retina.

A comparison of spatio-temporal receptive fields of ganglion cells in the retinas of the tadpole and adult frog

Receptive fields formed by ganglion cells were measured simultaneously in time and space in the adult and tadpole retinas. The spatio-temporal receptive-fields (STRFs) were measured by cross-correlating the spatio-temporal white-noise stimulus with the cells' spike discharges. Crosscorrelation was made photographically to extract the first order STRF kernel (approximately linear component of the STRFs). The time-course of STRF formed by the frog ganglion cells was twice as fast as that of the tadpole cells. The STRF formed by the tadpole ganglion cells was either a center-brightening or a center-dimming type whereas in the frog there was another class of cells which produced either complex STRFs or did not show any linear component in their STRFs. Size of the STRFs in frog and tadpole was similar in both frog and tadpole retinas.