RD_Exp

iModel

RD_Exp_T
Reichardt Detector, Exponential Temporal Filter

Summary

This is a Reichardt detector (RD) model for direction selectivity (Reichardt, 1957; 1961) with Poisson spike generation. It consists of a set of twenty RD subunits aligned parallel and sequentially along the axis of preferred motion. Each subunit is an opponent mechanism that senses the visual input via a pair of point-like spatial detectors and uses multiplication to combine signals that are processed by either a low-pass filter or a high-pass filter, both implemented with one-sided decaying exponential functions. This form of RD model is similar to that used by Borst et al. (2005).

Results

Please get a Java compatible browser to see this.

References

Borst A, Flanagin VL, Sompolinsky H (2005) Adaptation without parameter change: dynamic gain control in motion detection. PNAS 102:6172--6176.
Reichardt W (1957) Autokorrelationsauswertung als Funktionsprinzip des Zentralnervensystems. Zeitschrift für Naturforschung, Teil B. 12:447--457.
Reichardt W (1961) Autocorrelation, a principle for the evaluation of sensory information by the central nervous system. In: Sensory Communication, Rosenblith WA, ed. pp 303--317. MIT Press, Cambridge, MA.

(A) Each RD subunit processes the signals from two neighboring stimulus pixels (separation dx = 1 pix). The time varying stimulus is convolved with a low-pass (LP) filter that is a one-sided decaying exponential and a high-pass (HP) filter that is a delta-function minus a decaying exponential (see equations, upper right). The LP filter delays the signals in both the left and right branches before it is multiplied to form the preferred, rp and antipreferred ra responses, respectively. The difference of these responses is the final (opponent) response, ropp.

(B) The overall model output is the sum of the ropp signals from multiple subunits aligned along the x-axis, sharing neighboring pixels, as shown.