Related Experiment Video
Updated: Jul 18, 2026

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
Published on: March 10, 2011
Contrast gain control is drift-rate dependent: an informational analysis
M A Hietanen1, N A Crowder, M R Ibbotson
1Visual Sciences, Research School of Biological Sciences, Australian National University, Canberra, ACT, Australia 2601.
Abstract:
Neurons in the visual cortex code relative changes in illumination (contrast) and adapt their sensitivities to the visual scene by centering the steepest regions of their sigmoidal contrast response functions (CRFs: spike rate as a function of contrast) on the prevailing contrast. The influence of this contrast gain control has not been reported at nonoptimal drift rates. We calculated the Fisher information contained in the CRFs of halothane-anesthetized cats. Fisher information gives a measure of the accuracy of contrast representations based on the ratio of the square of the steepness of the CRF and the spike-rate dependency of the spiking variance. Variance increases with spike rate, so Fisher information is maximal where the CRF is steep and spike rates are low. Here, we show that the contrast at which the maximal Fisher information (C(MFI)) occurs for each adapting drift rate is at a fixed level above the adapting contrast. For adapting contrasts of 0 to 0.32 the relationship between C(MFI) and adapting contrast is well described by a straight line with a slope close to 1. The intercept of this line on the C(MFI)-axis is drift-rate dependent, although the slope is not. At high drift rates relative to each cell's peak the C(MFI) offset is higher than that for low drift rates. The results show that the contrast coding strategy in visual cortex maximizes accuracy for contrasts above the prevailing contrast in the environment for all drift rates. We argue that tuning the system for accuracy at contrasts above the prevailing value is optimal for viewing natural scenes.
More Related Videos
09:01Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
Published on: April 4, 2017
07:24Using Eye-tracking to Assess the Relative Importance of Visual and Vestibular Input to Subcortical Motion Processing in the Roll Plane
Published on: August 22, 2025
Related Concept Videos
Effects of feedback
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...
Gain
Gain:
Suppose Vin is the input and Vout is the output signal to a circuit.
Small-Signal Analysis of MOSFET Amplifiers
Control Systems
At the heart...
Time-Domain Interpretation of PD Control
Consider the example of control of motor torque. Initially, a positive...
Feedback control systems
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...