prediction coding
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2021 ◽  
Author(s):  
Laurens Winkelmeier ◽  
Carla Filosa ◽  
Max Scheller ◽  
Renée Hartig ◽  
Markus Sack ◽  
...  

SUMMARYThe unbiased identification of brain circuits responsible for behavior and their local cellular computations is a challenge for neuroscience. We establish here a hierarchical cross-scale approach from behavioral modeling and fMRI in task-performing mice to cellular network dynamics to identify how reward predictions are represented in the forebrain upon olfactory conditioning. fMRI identified functional segregation in reward prediction and error computations among olfactory cortices and subcortical circuits. Among them, the olfactory tubercle contributed both to dynamic reward predictions and prediction error. In this region, cellular recordings revealed two parallel neuronal populations for prediction coding. One population produced stabilized predictions as distributed stimulus-bound transient network activity; the other evolved during anticipatory waiting and fully reflected predicted value in single-units, dynamically integrating the recent cue-specific history of uncertain outcomes. Thus, the cross-scale approach revealed regional functional differentiation among the distributed forebrain circuits with a limbic hotspot for multiple non-redundant reward prediction coding.


2019 ◽  
Vol 15 (3) ◽  
pp. 1-23
Author(s):  
Zakia Jellali ◽  
Leïla Najjar Atallah ◽  
Sofiane Cherif

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Zhen Ma

An arbitrary-location pulse determination algorithm based on multipulse linear prediction coding (MP-LPC) is presented. This algorithm can determine all the amplitudes of the pulses at a time according to given pulse locations without the use of analysis-by-synthesis. This ensures that the pulses are optimal in a least-square sense, providing the theoretical foundation to improve the quality of synthesized speech. A fixed-location pulse linear prediction coding (FLP-LPC) method is proposed based on the arbitrary-location pulse determination algorithm. Simulation of the algorithm in MATLAB showed the superior quality of the speech synthesized using pulses in different locations and processed using the arbitrary-location pulse determination algorithm. The algorithm improved speech quality without affecting coding time, which was approximately 1.5% of the coding time for MP-LPC. Pulse locations in FLP-LPC are fixed and do not need to be transmitted, with only LSF, gain, and 16 pulse amplitudes requiring coding and transmission. FLP-LPC allows the generation of synthesized speech similar to G.729 coded speech at a rate of 2.5 kbps.


Author(s):  
Cristiano F. Santos ◽  
Fernando Lopes ◽  
Antonio Pinheiro ◽  
Luis A. da Silva Cruz

2018 ◽  
Vol 75 (3) ◽  
pp. 1150-1162 ◽  
Author(s):  
Elena Georgiana Paraschiv ◽  
Damián Ruiz-Coll ◽  
Maria Pantoja ◽  
Gerardo Fernández-Escribano

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