Predictive Coding with Neural Transmission Delays: A Real-Time Temporal Alignment Hypothesis

Hogendoorn, Hinze; Burkitt, Anthony N.

doi:10.1523/eneuro.0412-18.2019

Cited by 51 publications

(41 citation statements)

References 96 publications

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“…This shows that successive neural representations that are ordinarily activated sequentially (i.e., on a diagonal in a temporal generalization matrix) are instead activated nearly concurrently, meaning that the corresponding brain areas may have become aligned in time. This would potentially allow the brain to function in close to real time, as has been proposed previously (5). However, a consequence of such a predictive architecture is that, when predicted events are not fulfilled, sensory information about what actually happened arrives too late to prevent the system from temporarily representing the predicted event.…”

Section: Significancementioning

confidence: 95%

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Predictions drive neural representations of visual events ahead of incoming sensory information

Blom

Feuerriegel

Johnson

et al. 2020

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

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The transmission of sensory information through the visual system takes time. As a result of these delays, the visual information available to the brain always lags behind the timing of events in the present moment. Compensating for these delays is crucial for functioning within dynamic environments, since interacting with a moving object (e.g., catching a ball) requires real-time localization of the object. One way the brain might achieve this is via prediction of anticipated events. Using time-resolved decoding of electroencephalographic (EEG) data, we demonstrate that the visual system represents the anticipated future position of a moving object, showing that predictive mechanisms activate the same neural representations as afferent sensory input. Importantly, this activation is evident before sensory input corresponding to the stimulus position is able to arrive. Finally, we demonstrate that, when predicted events do not eventuate, sensory information arrives too late to prevent the visual system from representing what was expected but never presented. Taken together, we demonstrate how the visual system can implement predictive mechanisms to preactivate sensory representations, and argue that this might allow it to compensate for its own temporal constraints, allowing us to interact with dynamic visual environments in real time.

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Section: Significancementioning

confidence: 95%

“…One way the brain might compensate for neural delays is through prediction (3)(4)(5)(6). In support of this idea, predictable visual stimuli have been found to be represented in the visual system with a shorter latency than unpredictable stimuli in cats (7), macaques (8), and humans (9).…”

mentioning

confidence: 89%

Predictions drive neural representations of visual events ahead of incoming sensory information

Blom

Feuerriegel

Johnson

et al. 2020

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

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“…At short inducer durations, the onset of the moving texture rapidly generates a motion signal in the early visual system ( Westheimer & McKee, 1977 ). This accompanies the early afferent position signal, forming a population code that represents both position and velocity, as proposed by previous theoretical ( Hogendoorn & Burkitt, 2019 ) and computational studies ( Khoei, Masson, & Perrinet, 2017 ; Kwon, Tadin, & Knill, 2015 ). These models predict that this visual motion signal causes a shift in the receptive fields of downstream neural populations in the direction opposite to the direction of motion – a prediction consistent with fMRI evidence ( Harvey & Dumoulin, 2016 ; Liu, Ashida, Smith, & Wandell, 2006 ; Maus, Fischer, & Whitney, 2013 ; Schneider et al, 2019 ; Whitney et al, 2003 ).…”

Section: Discussionmentioning

confidence: 80%

Motion extrapolation in the High-Phi illusion: Analogous but dissociable effects on perceived position and perceived motion

2020

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A range of visual illusions, including the much-studied flash-lag effect, demonstrate that neural signals coding for motion and position interact in the visual system. One interpretation of these illusions is that they are the consequence of motion extrapolation mechanisms in the early visual system. Here, we study the recently reported High-Phi illusion to investigate whether it might be caused by the same underlying mechanisms. In the High-Phi illusion, a rotating texture is abruptly replaced by a new, uncorrelated texture. This leads to the percept of a large illusory jump, which can be forward or backward depending on the duration of the initial motion sequence (the inducer). To investigate whether this motion illusion also leads to illusions of perceived position, in three experiments we asked observers to localize briefly flashed targets presented concurrently with the new texture. Our results replicate the original finding of perceived forward and backward jumps, and reveal an illusion of perceived position. Like the observed effects on illusory motion, these position shifts could be forward or backward, depending on the duration of the inducer: brief inducers caused forward mislocalization, and longer inducers caused backward mislocalization. Additionally, we found that both jumps and mislocalizations scaled in magnitude with the speed of the inducer. Interestingly, forward position shifts were observed at shorter inducer durations than forward jumps. We interpret our results as an interaction of extrapolation and correction-for-extrapolation, and discuss possible mechanisms in the early visual system that might carry out these computations.

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“…FEF is considered the primary gaze center, providing top-down information to the afferent region PEF to coordinate visual attention ( 27 , 32 , 33 ). Our results may, therefore, impact on predictive coding models where given two distinct and hierarchical regions, impaired processing of the high-level one ( 34 ) leads to increased activity in the low-level one as a mechanism to optimize and “accumulate evidence.” Our multimodal pattern of putamen-PEF correlations adds a molecular correlate to such predictive coding models ( 35 ).…”

Section: Discussionmentioning

confidence: 98%

A link between synaptic plasticity and reorganization of brain activity in Parkinson's disease

Rebelo

Oliveira

Abrunhosa

et al. 2021

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

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The link between synaptic plasticity and reorganization of brain activity in health and disease remains a scientific challenge. We examined this question in Parkinson’s disease (PD) where functional up-regulation of postsynaptic D2 receptors has been documented while its significance at the neural activity level has never been identified. We investigated cortico-subcortical plasticity in PD using the oculomotor system as a model to study reorganization of dopaminergic networks. This model is ideal because this system reorganizes due to frontal-to-parietal shifts in blood oxygen level–dependent (BOLD) activity. We tested the prediction that functional activation plasticity is associated with postsynaptic dopaminergic modifications by combining positron emission tomography/functional magnetic resonance imaging to investigate striatal postsynaptic reorganization of dopamine D2 receptors (using 11C-raclopride) and neural activation in PD. We used covariance (connectivity) statistics at molecular and functional levels to probe striato-cortical reorganization in PD in on/off medication states to show that functional and molecular forms of reorganization are related. D2 binding across regions defined by prosaccades showed increased molecular connectivity between both caudate/putamen and hyperactive parietal eye fields in PD in contrast with frontal eye fields in controls, in line with the shift model. Concerning antisaccades, parietal-striatal connectivity dominated in again in PD, unlike frontal regions. Concerning molecular–BOLD covariance, a striking sign reversal was observed: PD patients showed negative frontal-putamen functional–molecular associations, consistent with the reorganization shift, in contrast with the positive correlations observed in controls. Follow-up analysis in off-medication PD patients confirmed the negative BOLD–molecular correlation. These results provide a link among BOLD responses, striato-cortical synaptic reorganization, and neural plasticity in PD.

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Predictive Coding with Neural Transmission Delays: A Real-Time Temporal Alignment Hypothesis

Abstract: Visual Abstract

Cited by 51 publications

References 96 publications

Predictions drive neural representations of visual events ahead of incoming sensory information

Predictions drive neural representations of visual events ahead of incoming sensory information

Motion extrapolation in the High-Phi illusion: Analogous but dissociable effects on perceived position and perceived motion

A link between synaptic plasticity and reorganization of brain activity in Parkinson's disease

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