Adaptive rescaling maximizes information transmission.

By N. Brenner, William Bialek, R. D. V. Steveninck. Neuron, 2000

667 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/02ac50c1802179a498b8e65e7090c5b422a23bb9

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Citations in the corpus

Noise characteristics and prior expectations in human visual speed perception (2006, background): “Even if such measurements were possible, conditions in the environment change over many timescales, and the observer may thus use a prior that is adapted or even switched abruptly according to sensory context [ 9 ].”
Fractional differentiation by neocortical pyramidal neurons (2008, background): “In general, neural systems adapt to a change in stimulus statistics, which may serve to maintain maximal information transmissio”
Visual adaptation: neural, psychological and computational aspects. (2007, background): “…thus introducing the possibility of a static nonlinear mechanism rather than an active and ongoing process conventionally associated with adaptation (Brenner et al., 2000; Baccus & Meister, 2002; Fairhall et al., 2001; Maravall et al., 2007; McCormick, Connors, Lighthall, & Prince, 1985; Nagel &…”
A Universal Model for Spike-Frequency Adaptation (2003, background): “Note also that subtractive adaptation does not adapt the neuron’s f -I-curve to higher order statistics of the stimulus (Brenner et al., 2000).”
Spatiotemporal elements of macaque v1 receptive fields. (2005, background): “See Experimental Procedures for details. ceding each spike defines the spike-triggered stimulus Steveninck and Bialek, 1988; Brenner et al., 2000; Schwartz et al., 2002; Touryan et al., 2002; Aguera y”
The Operating Point of the Cortex: Neurons as Large Deviation Detectors (2007, background): “” Previous studies have suggested that adaptive mechanisms work primarily to maximize the faithful transmission of information, given the statistics of the underlying signal (Laughlin, 1981; Smirnakis et al., 1997; van Hateren, 1997; Brenner et al., 2000).”
Multiple Time Scales of Adaptation in Auditory Cortex Neurons (2004, methodology): “This sensitivity can also be used for optimizing the coding of sounds by matching the neuronal firing to the stimulus statistics (Brenner et al., 2000; Fairhall et al., 2001) and for forming a sensory memory trace that may capture the complexity of past auditory stimulation (Näätänen et al., 2001).”
The Vulcanization of the Human Brain: A Neural Perspective on Interactions Between Cognition and Emotion (2005, neutral): “It is efficient in the sense that it often produces solutions that effectively (sometimes even optimally) meet the needs of the organism given the resources it has available (for example, Anderson, 1993; Barlow, 1981; Brenner et al., 2000; Hecht et al., 1942; Holmes et al., 2004).”
Efficient coding of natural sounds (2002, background): “Incorporating these factors into a model of auditory periphery would likely increase the efficiency of the sensory cod”
Do We Know What the Early Visual System Does? (2005, methodology): “This method has been used effectively to analyze the nonlinear response properties of fly visual neurons (De Ruyter Van Steveninck and Bialek, 1988; Brenner et al., 2000) and the receptive fields of mammalian V1 complex cells, with either random-bar stimuli aligned to the preferred orientation of th”
Visual adaptation: physiology, mechanisms, and functional benefits. (2007, methodology): “In the fly visual system, Brenner et al. (2000) used this approach to show that the speed tuning of the H1 neuron adjusts to match the range of speeds in a stimulus ensemble.”
Analyzing Neural Responses to Natural Signals: Maximally Informative Dimensions (2002, background): “…adaptive responses that are unlikely to be predicted from a combination of responses to simple stimuli; for example neurons have been shown to adapt to the distribution of sensory inputs, so that any characterization of these responses will depend on context (Smirnakis et al., 1996; Brenner et…”
Dopamine and Cognitive Control in Prefrontal Cortex. (2019, background): “Such a response modulation may improve the ability of cortical networks to detect sensory events [77], causing an adaptive rescaling of its input so as to maximize information transmission [78,79].”
Shunting inhibition modulates neuronal gain during synaptic excitation. (2003, background): “ent systems (Barlow, 1961; Brenner et al., 2000; Fairhall et al., 2001; Laughlin, 1981).”