The Operating Point of the Cortex: Neurons as Large Deviation Detectors
By Dario L. Ringach, B. Malone. 2007
63 citations recorded by the source corpus.
Spiking neurons translate analog intracellular variables into a sequence of action potentials. A simplified model of this transformation is one in which an underlying “generator potential,” representing a measure of overall neuronal drive, is passed through a static nonlinearity to produce an instantaneous firing rate. An important question is how adaptive mechanisms adjust the mean and SD of the generator potential to define an “operating point” that controls spike generation. In early sensory pathways adaptation has been shown to rescale the generator potential to maximize the amount of transmitted information. In contrast, we demonstrate that the operating point in the cortex is tuned so that cells respond only when the generator potential executes a large excursion above its mean value. The distance from the mean of the generator potential to spike threshold is, on average, 1 SD of the ongoing activity. Signals above threshold are amplified linearly and do not reach saturation. The operating point is adjusted dynamically so that it remains relatively invariant despite changes in stimulus contrast. We conclude that the operating regimen of the cortex is suitable for the detection of signals in background noise and for enhancing the selectivity of spike responses relative to those of the generator potential (the so-called “iceberg effect”), but not to maximize the transmission of total information.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cellular and Molecular Neuroscience
- David J. Heeger
- Dario L. Ringach
- Matteo Carandini
- Geoffrey E. Hinton
- Xiao-Jing Wang
- D. Ferster
- Nicholas J. Priebe
- Eero P. Simoncelli
In Cognitive Neuroscience
- David J. Heeger
- Matteo Carandini
- Dario L. Ringach
- Xiao-Jing Wang
- Geoffrey E. Hinton
- D. Ferster
- Nicholas J. Priebe
- Fred Henrik Hamker
Citations in the corpus
- Normalization as a canonical neural computation (2011, background): “In neurons such as those in area V1, the resulting fluctuations in membrane potential are essential in making the neuron fire: without them, many stimuli would evoke membrane potential fluctuations that are too small to reach spike threshol”
- Population coding under normalization (2009, background): “…& Sun, 2006), the lateral geniculate nucleus (Bonin, Mante, & Carandini, 2005, 2006), primary visual cortex (Carandini et al., 1997; Heeger, 1992; Ringach & Malone, 2007; Rust, Schwartz, Movshon, & Simoncelli, 2005), area MT (Simoncelli & Heeger, 1998), and area IT (Zoccolan, Cox, & DiCarlo,…”
- Inhibition, spike threshold, and stimulus selectivity in primary visual cortex. (2008, unknown): “…cortical neurons are generally silent in the absence of a stimulus, and the resting membrane potential lies far below threshold, relatively large deviations in the membrane potential are required to generate spikes, and information encoded in small deviations can be lost (Ringach and Malone, 2007).”