Predictive feedback to V1 dynamically updates with sensory input

Edwards, Grace; Vetter, Petra; McGruer, Fiona; Petro, Lucy S.; Muckli, Lars

doi:10.1038/s41598-017-16093-y

Cited by 52 publications

(45 citation statements)

References 43 publications

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“…That top-bottom feedback signals are thought to modulate sensory input, providing information about the global scene structure. Recent models of dynamic predictive updating also proposed that these top-down signals could inform about the global structure of the visual scene (Edwards et al 2017). Our results are in line with these studies and demonstrate that neural processing in human primary visual cortex is not purely retinotopic and that it integrates egocentric spatial properties.…”

Section: Discussionsupporting

confidence: 90%

Dynamics of the straight-ahead preference in human visual cortex

et al. 2019

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The objects located straight-ahead of the body are preferentially processed by the visual system. They are more rapidly detected and evoke stronger BOLD responses in early visual areas than elements that are retinotopically identical but located at eccentric spatial positions. To characterize the dynamics of the underlying neural mechanisms, we recorded in 29 subjects the EEG responses to peripheral targets differing solely by their locations with respect to the body. Straight-ahead stimuli led to stronger responses than eccentric stimuli for several components whose latencies ranged between 70 and 350 ms after stimulus onset. The earliest effects were found at 70 ms for a component that originates from occipital areas, the contralateral P1. To determine whether the straight-ahead direction affects primary visual cortex responses, we performed an additional experiment (n = 29) specifically designed to generate two robust components, the C1 and C2, whose cortical origins are constrained within areas V1, V2 and V3. Our analyses confirmed all the results of the first experiment and also revealed that the C2 amplitude between 130 and 160 ms after stimulus onset was significantly stronger for straight-ahead stimuli. A frequency analysis of the pre-stimulus baseline revealed that gaze-driven alterations in the visual hemi-field containing the straight-ahead direction were associated with a decrease in alpha power in the contralateral hemisphere, suggesting the implication of specific neural modulations before stimulus onset. Altogether, our EEG data demonstrate that preferential responses to the straight-ahead direction can be detected in the visual cortex as early as about 70 ms after stimulus onset.

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Section: Discussionsupporting

confidence: 90%

Dynamics of the straight-ahead preference in human visual cortex

et al. 2019

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“…In sum, the ability to predict the sensory consequences of a saccade is crucial when planning sequences of multiple eye movements. Evidence for dynamic updating of predictions has recently been found in primary visual area V1, indicating that CD signals are fed back to the earliest stages of visual cortical processing …”

Section: Function Of Sensory Predictionsmentioning

confidence: 99%

“…Accordingly, in tasks requiring localization across saccades, neural activity related to remapping can be found extending from striate and extrastriate visual cortex to SC, MDN, LIP, and FEF . Recent studies have focused on the microcircuitry in area FEF as a key structure underlying saccadic remapping .…”

Section: Neural Correlates Of Corollary Discharge Function and Failurementioning

confidence: 99%

The function and failure of sensory predictions

Bansal

Ford

Spering

2018

Annals of the New York Academy of Sciences

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Humans and other primates are equipped with neural mechanisms that allow them to automatically make predictions about future events, facilitating processing of expected sensations and actions. Prediction-driven control and monitoring of perceptual and motor acts are vital to normal cognitive functioning. This review provides an overview of corollary discharge mechanisms involved in predictions across sensory modalities and discusses consequences of predictive coding for cognition and behavior. Converging evidence now links impairments in corollary discharge mechanisms to neuropsychiatric symptoms such as hallucinations and delusions. We review studies supporting a prediction-failure hypothesis of perceptual and cognitive disturbances. We also outline neural correlates underlying prediction function and failure, highlighting similarities across the visual, auditory, and somatosensory systems. In linking basic psychophysical and psychophysiological evidence of visual, auditory, and somatosensory prediction failures to neuropsychiatric symptoms, our review furthers our understanding of disease mechanisms.

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“…This internal model is constantly updated by sensory feedback and is used by the central nervous system (CNS) to predict the consequences of its control actions [80]. Edwards et al [81] propose that the brain creates internal models of the environment to predict imminent sensory input. Llinás [82] emphasized that prediction is the prime objective of the brain and is imperative for intelligent motricity.…”

Section: What Is Intelligence?mentioning

confidence: 99%

A Biologically Inspired Framework for the Intelligent Control of Mechatronic Systems and Its Application to a Micro Diving Agent

Bessa

Brinkmann

Duecker

et al. 2018

Mathematical Problems in Engineering

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Mechatronic systems are becoming an intrinsic part of our daily life, and the adopted control approach in turn plays an essential role in the emulation of the intelligent behavior. In this paper, a framework for the development of intelligent controllers is proposed. We highlight that robustness, prediction, adaptation, and learning, which may be considered the most fundamental traits of all intelligent biological systems, should be taken into account within the project of the control scheme. Hence, the proposed framework is based on the fusion of a nonlinear control scheme with computational intelligence and also allows mechatronic systems to be able to make reasonable predictions about its dynamic behavior, adapt itself to changes in the plant, learn by interacting with the environment, and be robust to both structured and unstructured uncertainties. In order to illustrate the implementation of the control law within the proposed framework, a new intelligent depth controller is designed for a microdiving agent. On this basis, sliding mode control is combined with an adaptive neural network to provide the basic intelligent features. Online learning by minimizing a composite error signal, instead of supervised off-line training, is adopted to update the weight vector of the neural network. The boundedness and convergence properties of all closed-loop signals are proved using a Lyapunov-like stability analysis. Numerical simulations and experimental results obtained with the microdiving agent demonstrate the efficacy of the proposed approach and its suitableness for both stabilization and trajectory tracking problems.

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Predictive feedback to V1 dynamically updates with sensory input

Cited by 52 publications

References 43 publications

Dynamics of the straight-ahead preference in human visual cortex

Dynamics of the straight-ahead preference in human visual cortex

The function and failure of sensory predictions

A Biologically Inspired Framework for the Intelligent Control of Mechatronic Systems and Its Application to a Micro Diving Agent

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