Abstract
It is generally acknowledged that biological vision presents nonlinear characteristics, yet linear filtering accounts of visual processing are ubiquitous. The template-matching operation implemented by the linear-nonlinear cascade (linear filter followed by static nonlinearity) is the most widely adopted computational tool in systems neuroscience. This simple model achieves remarkable explanatory power while retaining analytical tractability, potentially extending its reach to a wide range of systems and levels in sensory processing. The extent of its applicability to human behaviour, however, remains unclear. Because sensory stimuli possess multiple attributes (e.g. position, orientation, size), the issue of applicability may be asked by considering each attribute one at a time in relation to a family of linear-nonlinear models, or by considering all attributes collectively in relation to a specified implementation of the linear-nonlinear cascade. We demonstrate that human visual processing can operate under conditions that are indistinguishable from linear-nonlinear transduction with respect to substantially different stimulus attributes of a uniquely specified target signal with associated behavioural task. However, no specific implementation of a linear-nonlinear cascade is able to account for the entire collection of results across attributes; a satisfactory account at this level requires the introduction of a small gain-control circuit, resulting in a model that no longer belongs to the linear-nonlinear family. Our results inform and constrain efforts at obtaining and interpreting comprehensive characterizations of the human sensory process by demonstrating its inescapably nonlinear nature, even under conditions that have been painstakingly fine-tuned to facilitate template-matching behaviour and to produce results that, at some level of inspection, do conform to linear filtering predictions. They also suggest that compliance with linear transduction may be the targeted outcome of carefully crafted nonlinear circuits, rather than default behaviour exhibited by basic components.
Highlights
Animals constantly submit environmental signals to neural operations designed to extract useful information for guiding behaviour
Any attempt to model human vision must first ask: can it be approximated by a process that linearly matches the visual stimulus with an internal template? We often take this approximation for granted without properly checking its validity
As we demonstrate in this study, a positive answer to the question posed in the previous paragraph does not guarantee a positive answer to this latter question: the system may appear to operate in the manner of the LN cascade with relation to a number of different probes defined within substantially different spaces, yet its behaviour may not be collectively captured by a single LN cascade
Summary
Animals constantly submit environmental signals to neural operations designed to extract useful information for guiding behaviour. Whether their sensory apparatus is considered in its entirety as a behavioural machine or in relation to hardware components like individual nerve cells, it can be described as an input-output transformation that maps external stimuli onto neural representations. W may be the receptive field of a simple cell, and g the nonlinearity that maps membrane voltage onto average spike rate [3] For another example, more relevant to the present study, we can think of w as the perceptual impact associated with different portions of a visual display presented to a human observer, and g the decisional transducer that maps aggregate perceptual impact onto a binary decision of the kind ‘I saw the stimulus’ or ‘I did not see it’ [4]
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