scholarly journals Subjective Duration as a Signature of Coding Efficiency: Emerging Links Among Stimulus Repetition, Predictive Coding, and Cortical GABA Levels

2014 ◽  
Vol 1 (1) ◽  
pp. 1-12 ◽  
Author(s):  
William J. Matthews ◽  
Devin B. Terhune ◽  
Hedderik van Rijn ◽  
David M. Eagleman ◽  
Marc A. Sommer ◽  
...  
2019 ◽  
Author(s):  
Sophie-Marie Rostalski ◽  
Catarina Amado ◽  
Gyula Kovács ◽  
Daniel Feuerriegel

AbstractRepeated presentation of a stimulus leads to reductions in measures of neural responses. This phenomenon, termed repetition suppression (RS), has recently been conceptualized using models based on predictive coding, which describe RS as due to expectations that are weighted toward recently-seen stimuli. To evaluate these models, researchers have manipulated the likelihood of stimulus repetition within experiments. They have reported findings that are inconsistent across hemodynamic and electrophysiological measures, and difficult to interpret as clear support or refutation of predictive coding models. We instead investigated a different type of expectation effect that is apparent in stimulus repetition experiments: the difference in one’s ability to predict the identity of repeated, compared to unrepeated, stimuli. In previous experiments that presented pairs of repeated or alternating images, once participants had seen the first stimulus image in a pair, they could form specific expectations about the repeated stimulus image. However they could not form such expectations for the alternating image, which was often randomly chosen from a large stimulus set. To assess the contribution of stimulus predictability effects to previously observed RS, we measured BOLD signals while presenting pairs of repeated and alternating faces. This was done in contexts whereby stimuli in alternating trials were either i.) predictable through statistically learned associations between pairs of stimuli or ii.) chosen randomly and therefore unpredictable. We found that RS in the right FFA was much larger in trials with unpredictable compared to predictable alternating faces. This was primarily due to unpredictable alternating stimuli evoking larger BOLD signals than predictable alternating stimuli. We show that imbalances in stimulus predictability across repeated and alternating trials can greatly inflate measures of RS, or even mimic RS effects. Our findings also indicate that stimulus-specific expectations, as described by predictive coding models, may account for a sizeable portion of observed RS effects.


Author(s):  
Urvashi Sharma ◽  
Meenakshi Sood ◽  
Emjee Puthooran ◽  
Yugal Kumar

The digitization of human body, especially for treatment of diseases can generate a large volume of data. This generated medical data has a large resolution and bit depth. In the field of medical diagnosis, lossless compression techniques are widely adopted for the efficient archiving and transmission of medical images. This article presents an efficient coding solution based on a predictive coding technique. The proposed technique consists of Resolution Independent Gradient Edge Predictor16 (RIGED16) and Block Based Arithmetic Encoding (BAAE). The objective of this technique is to find universal threshold values for prediction and provide an optimum block size for encoding. The validity of the proposed technique is tested on some real images as well as standard images. The simulation results of the proposed technique are compared with some well-known and existing compression techniques. It is revealed that proposed technique gives a higher coding efficiency rate compared to other techniques.


2016 ◽  
Author(s):  
Biao Han ◽  
Rufin VanRullen

AbstractPredictive coding is an influential model emphasizing interactions between feedforward and feedback signals. Here, we investigated its temporal dynamics. Two gray disks with different versions of the same stimulus, one enabling predictive feedback (a 3D-shape) and one impeding it (random-lines), were simultaneously presented on the left and right of fixation. Human subjects judged the luminance of the two disks while EEG was recorded. Independently of the spatial response (left/right), we found that the choice of 3D-shape or random-lines as the brighter disk (our measure of post-stimulus predictive coding efficiency on each trial) fluctuated along with the pre-stimulus phase of two spontaneous oscillations: a ~5Hz oscillation in contralateral frontal electrodes and a ~16Hz oscillation in contralateral occipital electrodes. This pattern of results demonstrates that predictive coding is a rhythmic process, and suggests that it could take advantage of faster oscillations in low-level areas and slower oscillations in high-level areas.


Author(s):  
Martin Fleury ◽  
Ismail Ali ◽  
Nadia Qadri ◽  
Mohammed Ghanbari

Mobile devices are replacing the desktop computer in most spheres outside the workplace. This development brings a problem to video streaming services, as wireless channels are fundamentally error-prone, whereas video compression depends for most of its gains on predictive coding. The H.264 codec family has included a good number of error resilience facilities to counter-act the spatio-temporal error propagation brought on by packet loss. This chapter outlines these facilities before examining ways in which predictive coding can be temporally restrained. In particular, intra-refresh techniques are the focus, as these bring additional utility to the video stream. For example, the chapter compares periodic and gradual intra-refresh, each of which provides recovery points for the decoder and also allow stream switching or joining at these points. Thus, in intra-coding, the more normal temporal prediction is temporally replaced by spatial prediction, at a cost in coding efficiency but allowing a decoder in a mobile device to reset itself. After a review of research into this area, the chapter provides a case study in non-periodic intra-refresh before considering possible future research directions.


2010 ◽  
Vol 10 (7) ◽  
pp. 1405-1405
Author(s):  
D. Eagleman ◽  
V. Pariyadath

2009 ◽  
Vol 364 (1525) ◽  
pp. 1841-1851 ◽  
Author(s):  
David M. Eagleman ◽  
Vani Pariyadath

Perceived duration is conventionally assumed to correspond with objective duration, but a growing literature suggests a more complex picture. For example, repeated stimuli appear briefer in duration than a novel stimulus of equal physical duration. We suggest that such duration illusions appear to parallel the neural phenomenon of repetition suppression, and we marshal evidence for a new hypothesis: the experience of duration is a signature of the amount of energy expended in representing a stimulus, i.e. the coding efficiency. This novel hypothesis offers a unified explanation for almost a dozen illusions in the literature in which subjective duration is modulated by properties of the stimulus such as size, brightness, motion and rate of flicker.


2020 ◽  
Vol 43 ◽  
Author(s):  
Martina G. Vilas ◽  
Lucia Melloni

Abstract To become a unifying theory of brain function, predictive processing (PP) must accommodate its rich representational diversity. Gilead et al. claim such diversity requires a multi-process theory, and thus is out of reach for PP, which postulates a universal canonical computation. We contend this argument and instead propose that PP fails to account for the experiential level of representations.


2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.


Author(s):  
Roberto Limongi ◽  
Angélica M. Silva

Abstract. The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production – where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.


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