Low‐delay vector backward predictive coding of speech

1992 ◽  
Vol 91 (6) ◽  
pp. 3595-3595
Author(s):  
Vladimir M. Cuperman
Keyword(s):  
Predictive Coding ◽  
Low Delay

scholarly journals Fixed-Lag Smoothing for Low-Delay Predictive Coding with Noise Shaping for Lossy Networks

2010 ◽  
Author(s):  
Thomas Arildsen ◽  
Jan Ostergaard ◽  
Manohar N Murthi ◽  
Soren Vang Andersen ◽  
Soren Holdt Jensen
Keyword(s):  
Predictive Coding ◽  
Noise Shaping ◽  
Lossy Networks ◽  
Low Delay

A challenge for predictive coding: Representational or experiential diversity?

2020 ◽  
Vol 43 ◽  
Author(s):  
Martina G. Vilas ◽  
Lucia Melloni
Keyword(s):  
Brain Function ◽  
Predictive Coding ◽  
Predictive Processing ◽  
Process Theory

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.

Representation, abstraction, and simple-minded sophisticates

2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan
Keyword(s):  
Decision Theory ◽  
Predictive Coding ◽  
Bayesian Decision Theory ◽  
Bayesian Decision ◽  
Model Based ◽  
Model Free

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.

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time

2016 ◽  
Vol 63 (6) ◽  
pp. 333-342
Author(s):  
Roberto Limongi ◽  
Angélica M. Silva
Keyword(s):  
Response Time ◽  
Short Term Memory ◽  
Estimation Error ◽  
Predictive Coding ◽  
Time Estimation ◽  
Prediction Errors ◽  
Memory Scanning ◽  
Short Term ◽  
Term Memory ◽  
Temporal Prediction

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.

Adaptive and Maladaptive Neural Plasticity Due to Facial Nerve Palsy

2016 ◽  
Vol 224 (2) ◽  
pp. 102-111 ◽  
Author(s):  
Carsten M. Klingner ◽  
Stefan Brodoehl ◽  
Gerd F. Volk ◽  
Orlando Guntinas-Lichius ◽  
Otto W. Witte
Keyword(s):  
Facial Nerve ◽  
Neural Plasticity ◽  
Cortical Plasticity ◽  
Brain Plasticity ◽  
Motor Nerve ◽  
Predictive Coding ◽  
Theoretical Framework ◽  
Cortical Reorganization ◽  
Nerve Lesion ◽  
Peripheral Facial Palsy

Abstract. This paper reviews adaptive and maladaptive mechanisms of cortical plasticity in patients suffering from peripheral facial palsy. As the peripheral facial nerve is a pure motor nerve, a facial nerve lesion is causing an exclusive deefferentation without deafferentation. We focus on the question of how the investigation of pure deefferentation adds to our current understanding of brain plasticity which derives from studies on learning and studies on brain lesions. The importance of efference and afference as drivers for cortical plasticity is discussed in addition to the crossmodal influence of different competitive sensory inputs. We make the attempt to integrate the experimental findings of the effects of pure deefferentation within the theoretical framework of cortical responses and predictive coding. We show that the available experimental data can be explained within this theoretical framework which also clarifies the necessity for maladaptive plasticity. Finally, we propose rehabilitation approaches for directing cortical reorganization in the appropriate direction and highlight some challenging questions that are yet unexplored in the field.

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