Modeling attention-driven plasticity in auditory cortical receptive fields.

Michael A Carlin,Mounya Elhilali

doi:10.3389/fncom.2015.00106

Michael A Carlin, Mounya Elhilali

Open Access

https://doi.org/10.3389/fncom.2015.00106

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Abstract

To navigate complex acoustic environments, listeners adapt neural processes to focus on behaviorally relevant sounds in the acoustic foreground while minimizing the impact of distractors in the background, an ability referred to as top-down selective attention. Particularly striking examples of attention-driven plasticity have been reported in primary auditory cortex via dynamic reshaping of spectro-temporal receptive fields (STRFs). By enhancing the neural response to features of the foreground while suppressing those to the background, STRFs can act as adaptive contrast matched filters that directly contribute to an improved cognitive segregation between behaviorally relevant and irrelevant sounds. In this study, we propose a novel discriminative framework for modeling attention-driven plasticity of STRFs in primary auditory cortex. The model describes a general strategy for cortical plasticity via an optimization that maximizes discriminability between the foreground and distractors while maintaining a degree of stability in the cortical representation. The first instantiation of the model describes a form of feature-based attention and yields STRF adaptation patterns consistent with a contrast matched filter previously reported in neurophysiological studies. An extension of the model captures a form of object-based attention, where top-down signals act on an abstracted representation of the sensory input characterized in the modulation domain. The object-based model makes explicit predictions in line with limited neurophysiological data currently available but can be readily evaluated experimentally. Finally, we draw parallels between the model and anatomical circuits reported to be engaged during active attention. The proposed model strongly suggests an interpretation of attention-driven plasticity as a discriminative adaptation operating at the level of sensory cortex, in line with similar strategies previously described across different sensory modalities.

Highlights

Plasticity is a ubiquitous property of sensory cortex whereby neural tuning characteristics can be dynamically shaped based on expectations, environmental context, and behavioral demands
By designing and optimizing a suitable objective function, we demonstrate that the model predicts spectro-temporal receptive fields (STRFs) changes that are consistent with the contrast filtering hypothesis, in line with those previously observed in physiological studies, and reflect a form of feature-based attention that enhances and suppresses task-salient acoustic cues
To improve discrimination between target and reference stimuli, we assume that attention acts to vary the shapes of the STRFs in order to maximize the conditional likelihood of the labels

Summary

Introduction

Plasticity is a ubiquitous property of sensory cortex whereby neural tuning characteristics can be dynamically shaped based on expectations, environmental context, and behavioral demands. A important driver of neural plasticity is topdown attention, which acts to adapt cognitive resources to selectively focus on behaviorally relevant sensory input. Such a mechanism helps sensory systems dynamically parse the flood of incoming. A common computational goal can be identified from studies of top-down attention across sensory modalities: that neural tuning characteristics adapt to improve discrimination and separation between the representation of the foreground (i.e., the attended stimuli) and that of the background (i.e., task-irrelevant distractors)

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Results

Conclusion