scholarly journals Integrating prediction errors at two time scales permits rapid recalibration of speech sound categories

2018 ◽  
Author(s):  
Itsaso Olasagasti ◽  
Anne-Lise Giraud
Keyword(s):  
Time Scales ◽  
Internal Model ◽  
Speech Sound ◽  
Prediction Errors ◽  
Dependent Manner ◽  
Sensory Cues ◽  
Natural Categories ◽  
Sensory Features ◽  
Old Evidence ◽  
Different Time Scales

AbstractSpeech perception is assumed to arise from internal models of specific sensory features associated speech sounds. When these features change, the listener should recalibrate its internal model by appropriately weighing new versus old evidence in a volatility dependent manner. Models of speech recalibration have classically ignored volatility. Those that explicitly consider volatility have been designed to describe human behavior in tasks where sensory cues are associated with arbitrary experimenter-defined categories or rewards. In such settings, a model that maintains a single representation of the category but continuously adapts the learning rate works well. Using neurocomputational modelling we show that recalibration of existing “natural” categories is better described when sound categories are represented at different time scales. We illustrate our proposal by modeling the rapid recalibration of speech categories (Lüttke et al. 2016).

scholarly journals Integrating prediction errors at two time scales permits rapid recalibration of speech sound categories

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Itsaso Olasagasti ◽  
Anne-Lise Giraud
Keyword(s):  
Time Scales ◽  
Speech Sound ◽  
Internal Models ◽  
Mcgurk Effect ◽  
Long Term Memory ◽  
Prediction Errors ◽  
Speech Sounds ◽  
Sensory Features ◽  
Memory Representations ◽  
Old Evidence

Speech perception presumably arises from internal models of how specific sensory features are associated with speech sounds. These features change constantly (e.g. different speakers, articulation modes etc.), and listeners need to recalibrate their internal models by appropriately weighing new versus old evidence. Models of speech recalibration classically ignore this volatility. The effect of volatility in tasks where sensory cues were associated with arbitrary experimenter-defined categories were well described by models that continuously adapt the learning rate while keeping a single representation of the category. Using neurocomputational modelling we show that recalibration of natural speech sound categories is better described by representing the latter at different time scales. We illustrate our proposal by modeling fast recalibration of speech sounds after experiencing the McGurk effect. We propose that working representations of speech categories are driven both by their current environment and their long-term memory representations.

Agent-Based Computational Model

2017 ◽  
Author(s):  
Joshua M. Epstein
Keyword(s):  
Computational Model ◽  
Bounded Rationality ◽  
Time Scales ◽  
Spatially Explicit ◽  
Agent Based ◽  
Affective Component ◽  
Elementary Type ◽  
Social Component ◽  
Different Time Scales

This part describes the agent-based and computational model for Agent_Zero and demonstrates its capacity for generative minimalism. It first explains the replicability of the model before offering an interpretation of the model by imagining a guerilla war like Vietnam, Afghanistan, or Iraq, where events transpire on a 2-D population of contiguous yellow patches. Each patch is occupied by a single stationary indigenous agent, which has two possible states: inactive and active. The discussion then turns to Agent_Zero's affective component and an elementary type of bounded rationality, as well as its social component, with particular emphasis on disposition, action, and pseudocode. Computational parables are then presented, including a parable relating to the slaughter of innocents through dispositional contagion. This part also shows how the model can capture three spatially explicit examples in which affect and probability change on different time scales.

Green markets integration in different time scales: A regional analysis

2021 ◽  
Vol 98 ◽  
pp. 105254 ◽  
Author(s):  
Christian Urom ◽  
Hela Mzoughi ◽  
Ilyes Abid ◽  
Mariem Brahim
Keyword(s):  
Time Scales ◽  
Regional Analysis ◽  
Different Time Scales

scholarly journals Measuring chromosome dynamics on different time scales using resolvases with varying half-lives

2005 ◽  
Vol 56 (4) ◽  
pp. 1049-1061 ◽  
Author(s):  
Richard A. Stein ◽  
Shuang Deng ◽  
N. Patrick Higgins
Keyword(s):  
Time Scales ◽  
Chromosome Dynamics ◽  
Different Time Scales

scholarly journals Reservoir ecological operation considering outflow variations across different time scales

2021 ◽  
Vol 125 ◽  
pp. 107582 ◽  
Author(s):  
Yibo Wang ◽  
Pan Liu ◽  
Ming Dou ◽  
He Li ◽  
Bo Ming ◽  
...  
Keyword(s):  
Time Scales ◽  
Different Time Scales

scholarly journals Stellar noise and planet detection. I. Oscillations, granulation and sun-like spots

2010 ◽  
Vol 6 (S276) ◽  
pp. 527-529
Author(s):  
Xavier Dumusque ◽  
Nuno C. Santos ◽  
Stéphane Udry ◽  
Cristophe Lovis ◽  
Xavier Bonfils
Keyword(s):  
Radial Velocity ◽  
Time Scales ◽  
High Precision ◽  
Habitable Zone ◽  
Planet Detection ◽  
Solar Type ◽  
Physical Phenomena ◽  
Instrumental Precision ◽  
Observational Strategy ◽  
Different Time Scales

AbstractSpectrographs like HARPS can now reach a sub-ms−1 precision in radial-velocity (RV) (Pepe & Lovis 2008). At this level of accuracy, we start to be confronted with stellar noise produced by 3 different physical phenomena: oscillations, granulation phenomena (granulation, meso- and super-granulation) and activity. On solar type stars, these 3 types of perturbation can induce ms−1 RV variation, but on different time scales: 3 to 15 minutes for oscillations, 15 minutes to 1.5 days for granulation phenomena and 10 to 50 days for activity. The high precision observational strategy used on HARPS, 1 measure per night of 15 minutes, on 10 consecutive days each month, is optimized, due to a long exposure time, to average out the noise coming from oscillations (Dumusque et al. 2011a) but not to reduce the noise coming from granulation and activity (Dumusque et al. 2011a and Dumusque et al. 2011b). The smallest planets found with this strategy (Mayor et al. 2009) seems to be at the limit of the actual observational strategy and not at the limit of the instrumental precision. To be able to find Earth mass planets in the habitable zone of solar-type stars (200 days for a K0 dwarf), new observational strategies, averaging out simultaneously all type of stellar noise, are required.

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