Sensory adaptation as optimal resource allocation

Gepshtein, Sergei; Lesmes, Luis Andres; Albright, Thomas D.

doi:10.1073/pnas.1204109110

Cited by 48 publications

(47 citation statements)

References 52 publications

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“…Thus, contextual modulation may not necessarily impair all visually guided behavior, even if it alters neural and perceptual selectivity in a way that hinders behavioral performance on very specific and synthetic laboratory tasks. Gepshtein, Lesmes, and Albright (2013) recently demonstrated that adaptation, while detrimental under specific experimental conditions, actually represents an optimal allocation of sensory resources in the general case. Understanding contextual modulation's behavioral effects under naturalistic conditions may similarly prove to be a fruitful avenue for future research.…”

Section: Resultsmentioning

confidence: 99%

Contextual modulation and stimulus selectivity in extrastriate cortex

Krause

Pack

2014

Vision Research

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Contextual modulation is observed throughout the visual system, using techniques ranging from single-neuron recordings to behavioral experiments. Its role in generating feature selectivity within the retina and primary visual cortex has been extensively described in the literature. Here, we describe how similar computations can also elaborate feature selectivity in the extrastriate areas of both the dorsal and ventral streams of the primate visual system. We discuss recent work that makes use of normalization models to test specific roles for contextual modulation in visual cortex function. We suggest that contextual modulation renders neuronal populations more selective for naturalistic stimuli. Specifically, we discuss contextual modulation's role in processing optic flow in areas MT and MST and for representing naturally occurring curvature and contours in areas V4 and IT. We also describe how the circuitry that supports contextual modulation is robust to variations in overall input levels. Finally, we describe how this theory relates to other hypothesized roles for contextual modulation.

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Section: Resultsmentioning

confidence: 99%

Contextual modulation and stimulus selectivity in extrastriate cortex

Krause

Pack

2014

Vision Research

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“…The overall approach of conceptualizing cognitive processes as optimization of neuronal resources has received experimental support and theoretical emphasis in the recent studies of visual perception (Gepshtein et al, 2013) and the analysis of candidate mechanisms in the brain capable of anticipation and long-term planning (“prospective optimization”; Sejnowski et al, 2014). Perhaps, the most compelling argument in favor of the present theory can be garnered from the work reported by Ito (1993, 2008), Salman (2002), Baillieux et al (2008); Ellis and Newton (2010), Murdoch (2010), and Rosenbloom et al (2012) suggesting a possibility that mental activities are controlled by internal models in the cerebellum (Ito, 2008), with movement and thought engaging identical control mechanisms (Ito, 1993).…”

Section: Discussionmentioning

confidence: 99%

Life and Understanding: The Origins of “Understanding” in Self-Organizing Nervous Systems

Yufik¹,

Friston

2016

Front. Syst. Neurosci.

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This article is motivated by a formulation of biotic self-organization in Friston (2013), where the emergence of “life” in coupled material entities (e.g., macromolecules) was predicated on bounded subsets that maintain a degree of statistical independence from the rest of the network. Boundary elements in such systems constitute a Markov blanket; separating the internal states of a system from its surrounding states. In this article, we ask whether Markov blankets operate in the nervous system and underlie the development of intelligence, enabling a progression from the ability to sense the environment to the ability to understand it. Markov blankets have been previously hypothesized to form in neuronal networks as a result of phase transitions that cause network subsets to fold into bounded assemblies, or packets (Yufik and Sheridan, 1997; Yufik, 1998a). The ensuing neuronal packets hypothesis builds on the notion of neuronal assemblies (Hebb, 1949, 1980), treating such assemblies as flexible but stable biophysical structures capable of withstanding entropic erosion. In other words, structures that maintain their integrity under changing conditions. In this treatment, neuronal packets give rise to perception of “objects”; i.e., quasi-stable (stimulus bound) feature groupings that are conserved over multiple presentations (e.g., the experience of perceiving “apple” can be interrupted and resumed many times). Monitoring the variations in such groups enables the apprehension of behavior; i.e., attributing to objects the ability to undergo changes without loss of self-identity. Ultimately, “understanding” involves self-directed composition and manipulation of the ensuing “mental models” that are constituted by neuronal packets, whose dynamics capture relationships among objects: that is, dependencies in the behavior of objects under varying conditions. For example, movement is known to involve rotation of population vectors in the motor cortex (Georgopoulos et al., 1988, 1993). The neuronal packet hypothesis associates “understanding” with the ability to detect and generate coordinated rotation of population vectors—in neuronal packets—in associative cortex and other regions in the brain. The ability to coordinate vector representations in this way is assumed to have developed in conjunction with the ability to postpone overt motor expression of implicit movement, thus creating a mechanism for prediction and behavioral optimization via mental modeling that is unique to higher species. This article advances the notion that Markov blankets—necessary for the emergence of life—have been subsequently exploited by evolution and thus ground the ways that living organisms adapt to their environment, culminating in their ability to understand it.

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“…However, this was famously challenged by Stevens (35), who showed that the logarithmic-like behavior holds only at threshold. Weber-Fechner behavior for sensory attributes is now rarely interpreted to imply logarithmic encoding, usually adaptation or gain control, mechanisms that have been linked to optimal behavior (26,(36)(37)(38). So, the strongest evidence for logarithmic coding was the logarithmic numberline:…”

Section: Discussionmentioning

confidence: 99%

Compressive mapping of number to space reflects dynamic encoding mechanisms, not static logarithmic transform

Cicchini

Anobile

Burr

2014

Proc. Natl. Acad. Sci. U.S.A.

240

329

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The mapping of number onto space is fundamental to measurement and mathematics. However, the mapping of young children, unschooled adults, and adults under attentional load shows strong compressive nonlinearities, thought to reflect intrinsic logarithmic encoding mechanisms, which are later "linearized" by education. Here we advance and test an alternative explanation: that the nonlinearity results from adaptive mechanisms incorporating the statistics of recent stimuli. This theory predicts that the response to the current trial should depend on the magnitude of the previous trial, whereas a static logarithmic nonlinearity predicts trialwise independence. We found a strong and highly significant relationship between numberline mapping of the current trial and the magnitude of the previous trial, in both adults and school children, with the current response influenced by up to 15% of the previous trial value. The dependency is sufficient to account for the shape of the numberline, without requiring logarithmic transform. We show that this dynamic strategy results in a reduction of reproduction error, and hence improvement in accuracy.numerical cognition | predictive coding | approximate number system | Weber-Fechner law | serial dependency H umans have a strong intuition of the spatial nature of numbers, usually (but not always) a horizontal "mental numberline," with numbers increasing from left to right (1-4). However, the nature of number mapping is not identical for all, but changes during development, starting from a nonlinear representation, well characterized as logarithmic (placing, for example, the number 10 near the midpoint of a 1-100 scale), then becoming more linear over the first years of schooling (3,5,6). Similarly, logarithmic-like numberlines have been demonstrated in indigenous Amazonian populations without formal mathematical schooling (4).Several recent studies have shown that under certain circumstances even the math-educated tend to reproduce numbers logarithmically. For example, we showed that depriving attentional resources leads to logarithmic-like numberline responses (7), consistent with the possibility that the native logarithmic encoding emerges when attention is deprived. Other studies have shown that the use of unfamiliar numerical format (such as exponential) can induce a switch from a linear to a logarithmic-like response, even in math-educated adults (7,8). Most recently, Dotan and Dehaene (9) have devised a clever technique to record the whole trajectory of the pointing response (across the face of a touchscreen), rather than just the endpoint: The response begins quite logarithmically, then corrects toward linear mapping by the time contact is made. All these studies have led many to interpret the logarithmic map as the direct reflection of the internal native number representation (4, 10-12) that becomes corrected over time by education but can emerge under special circumstances.Whereas the nonlinear numberline is consistent with intrinsic logarithmic processes, other explanat...

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Sensory adaptation as optimal resource allocation

Cited by 48 publications

References 52 publications

Contextual modulation and stimulus selectivity in extrastriate cortex

Contextual modulation and stimulus selectivity in extrastriate cortex

Life and Understanding: The Origins of “Understanding” in Self-Organizing Nervous Systems

Compressive mapping of number to space reflects dynamic encoding mechanisms, not static logarithmic transform

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