scholarly journals A Philosophical Analysis of the Updating Rule in a Bayesian Perceptual Learning Model

2021 ◽  
Vol 30 (0) ◽  
pp. 85-98
Author(s):  
Yuki OZAKI
Keyword(s):  
Perceptual Learning ◽  
Learning Model ◽  
Philosophical Analysis ◽  
Updating Rule

scholarly journals Can Deep Learning Model Perceptual Learning?

2019 ◽  
Vol 39 (2) ◽  
pp. 194-196 ◽  
Author(s):  
Shahab Bakhtiari
Keyword(s):  
Deep Learning ◽  
Perceptual Learning ◽  
Learning Model ◽  
Deep Learning Model

scholarly journals Pembelajaran Bahasa Arab Dalam Buku Ta’lim Al-‘Arabiyah Bi Thoriqoh Haditsah M. Fethullah Gülen

2020 ◽  
Vol 1 (2) ◽  
pp. 152-174
Author(s):  
Amaliya Sholihah ◽  
Ihadatul Hidayah
Keyword(s):  
Language Learning ◽  
Arabic Language ◽  
Learning Model ◽  
Islamic Education ◽  
Philosophical Analysis ◽  
Model Design ◽  
Library Research ◽  
The World

The focus of this study is to investigate the thinking of Islamic education figures who have an interest in learning Arabic. This study focuses on a work entitled "Ta'lim Al-" Arabiyyah Bi Tariqah Haditsah ". The significance of this study is how the design made by Gülen in his book for learning Arabic and are there implication and integration of his thinking with learning Arabic. Seeing that Gülen is an Islamic education figure who concerns education including Arabic learning. The method of this study is library research, in which the source of the data is taken from several kinds of literature. The approach of this study is the philosophical analysis-thinking of the figure. Gülen’s framework is a form of his concern in the world of education one of which was towards learning Arabic. Gülen designs the Arabic language learning model in a learning book called Ta’lim Al- “Arabiyyah Bi Tariqah Haditsah which contains a (modern) hadith model design. In his book, Gülen divides Arabic language learning into three levels, beginner, intermediate, and advanced.

scholarly journals Neural surprise in somatosensory Bayesian learning

2020 ◽  
Author(s):  
Sam Gijsen ◽  
Miro Grundei ◽  
Robert T. Lange ◽  
Dirk Ostwald ◽  
Felix Blankenburg
Keyword(s):  
Perceptual Learning ◽  
Bayesian Learning ◽  
Model Updating ◽  
Selection Procedure ◽  
Learning Model ◽  
Learning System ◽  
Somatosensory Processing ◽  
Eeg Data ◽  
Statistical Regularities ◽  
The Brain

AbstractTracking statistical regularities of the environment is important for shaping human behavior and perception. Evidence suggests that the brain learns environmental dependencies using Bayesian principles. However, much remains unknown about the employed algorithms, for somesthesis in particular. Here, we describe the cortical dynamics of the somatosensory learning system to investigate both the form of the generative model as well as its neural surprise signatures. Specifically, we recorded EEG data from 40 participants subjected to a somatosensory roving-stimulus paradigm and performed single-trial modeling across peri-stimulus time in both sensor and source space. Our Bayesian model selection procedure indicates that evoked potentials are best described by a non-hierarchical learning model that tracks transitions between observations using leaky integration. From around 70ms post-stimulus onset, secondary somatosensory cortices are found to represent confidence-corrected surprise as a measure of model inadequacy. Primary somatosensory cortex is found to encode Bayesian surprise, reflecting model updating, from around 140ms. As such, this dissociation indicates that early surprise signals may control subsequent model update rates. In sum, our findings support the hypothesis that early somatosensory processing reflects Bayesian perceptual learning and contribute to an understanding of its precise mechanisms.Author summaryOur environment features statistical regularities, such as a drop of rain predicting imminent rainfall. Despite the importance for behavior and survival, much remains unknown about how these dependencies are learned, particularly for somatosensation. As surprise signalling about novel observations indicates a mismatch between one’s beliefs and the world, it has been hypothesized that surprise computation plays an important role in perceptual learning. By analyzing EEG data from human participants receiving sequences of tactile stimulation, we compare different formulations of surprise and investigate the employed underlying learning model. Our results indicate that the brain estimates transitions between observations. Furthermore, we identified different signatures of surprise computation and thereby provide a dissociation of the neural correlates of belief inadequacy and belief updating. Specifically, early surprise responses from around 70ms were found to signal the need for changes to the model, with encoding of its subsequent updating occurring from around 140ms. These results provide insights into how somatosensory surprise signals may contribute to the learning of environmental statistics.

Visual complexity of shapes: a hierarchical perceptual learning model

2021 ◽  
Author(s):  
Lingchen Dai ◽  
Kang Zhang ◽  
Xianjun Sam Zheng ◽  
Ralph R. Martin ◽  
Yina Li ◽  
...  
Keyword(s):  
Perceptual Learning ◽  
Visual Complexity ◽  
Learning Model ◽  
Complexity Of Shapes

Perceptual Learning of Vocoded Speech With and Without Contralateral Hearing: Implications for Cochlear Implant Rehabilitation

2020 ◽  
pp. 1-10
Author(s):  
Martin Chavant ◽  
Alexis Hervais-Adelman ◽  
Olivier Macherey
Keyword(s):  
Cochlear Implant ◽  
Perceptual Learning ◽  
Speech Signal ◽  
Training Phase ◽  
Monosyllabic Words ◽  
Low Pass ◽  
Contralateral Ear ◽  
Number Of Individuals ◽  
Insight Into ◽  
Vocoded Speech

Purpose An increasing number of individuals with residual or even normal contralateral hearing are being considered for cochlear implantation. It remains unknown whether the presence of contralateral hearing is beneficial or detrimental to their perceptual learning of cochlear implant (CI)–processed speech. The aim of this experiment was to provide a first insight into this question using acoustic simulations of CI processing. Method Sixty normal-hearing listeners took part in an auditory perceptual learning experiment. Each subject was randomly assigned to one of three groups of 20 referred to as NORMAL, LOWPASS, and NOTHING. The experiment consisted of two test phases separated by a training phase. In the test phases, all subjects were tested on recognition of monosyllabic words passed through a six-channel “PSHC” vocoder presented to a single ear. In the training phase, which consisted of listening to a 25-min audio book, all subjects were also presented with the same vocoded speech in one ear but the signal they received in their other ear differed across groups. The NORMAL group was presented with the unprocessed speech signal, the LOWPASS group with a low-pass filtered version of the speech signal, and the NOTHING group with no sound at all. Results The improvement in speech scores following training was significantly smaller for the NORMAL than for the LOWPASS and NOTHING groups. Conclusions This study suggests that the presentation of normal speech in the contralateral ear reduces or slows down perceptual learning of vocoded speech but that an unintelligible low-pass filtered contralateral signal does not have this effect. Potential implications for the rehabilitation of CI patients with partial or full contralateral hearing are discussed.

A Philosophical Analysis of Commonplace Morality

1983 ◽  
Vol 28 (6) ◽  
pp. 422-423
Author(s):  
Robert B. Cialdini
Keyword(s):  
Philosophical Analysis

The Philosophical Analysis of a Psychological Stance

PsycCRITIQUES ◽  
2012 ◽  
Vol 57 (29) ◽  
Author(s):  
Charles R. Figley
Keyword(s):  
Philosophical Analysis
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