scholarly journals Decision by sampling implements efficient coding of psychoeconomic functions

2017 ◽  
Author(s):  
Rahul Bhui ◽  
Samuel J. Gershman
Keyword(s):  
Communication Channel ◽  
Frequency Theory ◽  
Noisy Channel ◽  
Response Distribution ◽  
Efficient Coding ◽  
Cognitive Limitations ◽  
Behavioral Observations ◽  
Subjective Value ◽  
Efficient Representation ◽  
Normative Justification

AbstractThe theory of decision by sampling (DbS) proposes that an attribute’s subjective value is its rank within a sample of attribute values retrieved from memory. This can account for instances of context dependence beyond the reach of classic theories which assume stable preferences. In this paper, we provide a normative justification for DbS that is based on the principle of efficient coding. The efficient representation of information in a noiseless communication channel is characterized by a uniform response distribution, which the rank transformation implements. However, cognitive limitations imply that decision samples are finite, introducing noise. Efficient coding in a noisy channel requires smoothing of the signal, a principle that leads to a new generalization of DbS. This generalization is closely connected to range-frequency theory, and helps descriptively account for a wider set of behavioral observations, such as how context sensitivity varies with the number of available response categories.

Depth Image Compression and Error Concealment for 3D Video Communication

2015 ◽  
Vol 764-765 ◽  
pp. 863-867
Author(s):  
Yih Chuan Lin ◽  
Pu Jian Hsu
Keyword(s):  
Neural Network ◽  
Communication Channel ◽  
Error Concealment ◽  
3D Video ◽  
Depth Image ◽  
Noisy Channel ◽  
The Neural Network ◽  
Processing Ability ◽  
Data Volume

In this paper, an error concealment scheme for neural-network based compression of depth image in 3D videos is proposed. In the neural-network based compression, each depth image is represented by one or more neural networks. The advantage of neural-network based compression lies in the parallel processing ability of multiple neurons, which can handle the massive data volume of 3D videos. The similarity of neuron weights of neighboring nodes is exploited to recover the loss neuron weights when transmitting with an error-prone communication channel. With a simulated noisy channel, the quality of compressed 3D video, which is reconstructed undergoing the noisy channel, can be recovered well by the proposed error concealment scheme.

scholarly journals Neural oscillations as a signature of efficient coding in the presence of synaptic delays

2015 ◽  
Author(s):  
Matthew Chalk ◽  
Boris Gutkin ◽  
Sophie Deneve
Keyword(s):  
High Efficiency ◽  
Direct Consequence ◽  
Strongly Correlated ◽  
Cortical Networks ◽  
Efficient Coding ◽  
Gamma Rhythm ◽  
Spiking Networks ◽  
Efficient Representation ◽  
Share Information ◽  
Oscillatory Rhythm

Cortical networks exhibit "global oscillations", in which neural spike times are entrained to an underlying oscillatory rhythm, but where individual neurons fire irregularly, on only a fraction of cycles. While the network dynamics underlying global oscillations have been well characterised, their function is debated. Here, we show that such global oscillations are a direct consequence of optimal efficient coding in spiking networks with synaptic delays. To avoid firing unnecessary spikes, neurons need to share information about the network state. Ideally, membrane potentials should be strongly correlated and reflect a "prediction error" while the spikes themselves are uncorrelated and occur rarely. We show that the most efficient representation is achieved when: (i) spike times are entrained to a global Gamma rhythm (implying a consistent representation of the error); but (ii) few neurons fire on each cycle (implying high efficiency), while (iii) excitation and inhibition are tightly balanced. This suggests that cortical networks exhibiting such dynamics are tuned to achieve a maximally efficient population code.

scholarly journals Efficient coding of subjective value

2018 ◽  
Author(s):  
Rafael Polanía ◽  
Michael Woodford ◽  
Christian C. Ruff
Keyword(s):  
Empirical Data ◽  
Information Structure ◽  
Limited Capacity ◽  
Inference Process ◽  
Efficient Coding ◽  
Mechanistic Explanations ◽  
Level Of Confidence ◽  
Subjective Value ◽  
Subjective Valuation ◽  
Optimal Decoding

AbstractPreference-based decisions are essential for survival, for instance when deciding what we should (not) eat. Despite their importance, choices based on preferences are surprisingly variable and can appear irrational in ways that have defied mechanistic explanations. Here we propose that subjective valuation results from an inference process that accounts for the information structure of values in the environment and that maximizes information in value representations in line with demands imposed by limited coding resources. A model of this inference process explains the variability in both subjective value reports and preference-based choices, and predicts a new preference illusion that we validate with empirical data. Interestingly, the same model also explains the level of confidence associated with these reports. Our results imply that preference-based decisions reflect information-maximizing transmission and statistically optimal decoding of subjective values by a limited-capacity system. These findings provide a unified account of how humans perceive and valuate the environment to optimally guide behavior.

scholarly journals Efficient coding of subjective value

2018 ◽  
Vol 22 (1) ◽  
pp. 134-142 ◽  
Author(s):  
Rafael Polanía ◽  
Michael Woodford ◽  
Christian C. Ruff
Keyword(s):  
Efficient Coding ◽  
Subjective Value

scholarly journals Neural oscillations as a signature of efficient coding in the presence of synaptic delays

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Matthew Chalk ◽  
Boris Gutkin ◽  
Sophie Denève
Keyword(s):  
High Efficiency ◽  
Direct Consequence ◽  
Strongly Correlated ◽  
Cortical Networks ◽  
Efficient Coding ◽  
Gamma Rhythm ◽  
Spiking Networks ◽  
Efficient Representation ◽  
Share Information ◽  
Oscillatory Rhythm

Cortical networks exhibit 'global oscillations', in which neural spike times are entrained to an underlying oscillatory rhythm, but where individual neurons fire irregularly, on only a fraction of cycles. While the network dynamics underlying global oscillations have been well characterised, their function is debated. Here, we show that such global oscillations are a direct consequence of optimal efficient coding in spiking networks with synaptic delays and noise. To avoid firing unnecessary spikes, neurons need to share information about the network state. Ideally, membrane potentials should be strongly correlated and reflect a 'prediction error' while the spikes themselves are uncorrelated and occur rarely. We show that the most efficient representation is when: (i) spike times are entrained to a global Gamma rhythm (implying a consistent representation of the error); but (ii) few neurons fire on each cycle (implying high efficiency), while (iii) excitation and inhibition are tightly balanced. This suggests that cortical networks exhibiting such dynamics are tuned to achieve a maximally efficient population code.

scholarly journals Neural Correlates of Value Are Intrinsically History Dependent

2020 ◽  
Author(s):  
Sangil Lee ◽  
Caryn Lerman ◽  
Joseph W. Kable
Keyword(s):  
Population Level ◽  
Neural Correlates ◽  
Practical Application ◽  
Efficient Coding ◽  
Decision Neuroscience ◽  
History Effects ◽  
Repetition Suppression ◽  
Subjective Value ◽  
Out Of Sample ◽  
Prediction Approach

AbstractA central finding in decision neuroscience is that BOLD activity in several regions, including ventral striatum and ventromedial prefrontal cortex, is correlated with the subjective value of the option being considered, and that BOLD activity in these regions can predict choices out of sample, even at the population-level. Here we show, across two different decision making tasks in a large sample of subjects, that these BOLD value-correlates are intrinsically history dependent. If the subjective value of the previous offer was high, the signal on the current trial will be lower, and vice versa. This kind of history dependency is distinct from previously described adaptation or repetition suppression effects, but instead is of the form predicted by theories of efficient coding such as time-dependent cortical normalization. In terms of practical application, since value-based choice behavior does not exhibit the same history dependence, neural prediction studies may exhibit systematic errors without accounting for history effects. The data-driven, interpretable, whole-brain prediction approach we use to identify history effects also illustrates one way to adjust predictions for neural history dependency.

scholarly journals INFORMATION PARAMETERS OF CODES THAT ARE SYNTHESIZED ON THE BASIS OF ONE MODULE

2020 ◽  
Vol 3 (7) ◽  
pp. 95-102
Author(s):  
Mikola Zaharchenko ◽  
Matin Hadzhyiev ◽  
Nariman Salmanov ◽  
Denis Golev ◽  
Natalya Shvets
Keyword(s):  
Information Transfer ◽  
Communication Channel ◽  
High Accuracy ◽  
Code Word ◽  
Russian Text ◽  
Constant Length ◽  
Efficient Coding ◽  
Digital Methods ◽  
Constant Duration

The advantages of digital methods of processing, displaying, storing and transmitting information. Currently, various conversion methods and efficient coding methods are used to increase the speed of information transfer, maintain high accuracy and provide the required latent accuracy. In particular, timer (temporary) signal constructions, which, in comparison with other coding methods, for example, positional (bitwise) coding, can reduce costs by more than two times. In the work, the information parameters of the code ensembles synthesized at a constant duration "m" are evaluated. Determined the conditions for the formation of a code ensemble and calculate the number of code dictionary implementations on a segment of a nyquist elements.In order to use the communication channel efficiently, the proposed increase in the entropy of the transmitted ensemble is due to the use of code sets with different number of information segments and at a constant length of the code word. A significant increase in the weight of the synthesized ensemble ensured an increase in the value of the module А0 =19 integer times K є 8:18 .The maximum values of the module are calculated in which the greatest number of code words is synthesized: At: КА0 =13, Np=8; КА0 =14, Np=10 КА0 =15, Np=15; КА0 =17, Np=16 КА0 =18, Np=10; КА0 =19, Np=6 КА0 =20, Np=1 For these КА0 values, the entropy value is H=3.269, which is less than the entropy of the Russian text H=4.35. In accordance with code words that satisfy the conditions of the quality equation. The methods and algorithms of reliable reception of code words under the influence of interference in the channel used were analyzed.Studies and calculations have shown that the use of temporary signal structures synthesized on the basis of a onemodule can significantly reduce the value of entropy for the transmission of Russian text.

Ultimate resolution and information in electron microscopy

1991 ◽  
Vol 49 ◽  
pp. 496-497
Author(s):  
D. Van Dyck
Keyword(s):  
Electron Microscopy ◽  
Electron Microscope ◽  
Transfer Function ◽  
Information Transfer ◽  
Communication Channel ◽  
Structural Information ◽  
Information Rate ◽  
Noise Power ◽  
Signal Power ◽  
Imaging Device

An (electron) microscope can be considered as a communication channel that transfers structural information between an object and an observer. In electron microscopy this information is carried by electrons. According to the theory of Shannon the maximal information rate (or capacity) of a communication channel is given by C = B log2 (1 + S/N) bits/sec., where B is the band width, and S and N the average signal power, respectively noise power at the output. We will now apply to study the information transfer in an electron microscope. For simplicity we will assume the object and the image to be onedimensional (the results can straightforwardly be generalized). An imaging device can be characterized by its transfer function, which describes the magnitude with which a spatial frequency g is transferred through the device, n is the noise. Usually, the resolution of the instrument ᑭ is defined from the cut-off 1/ᑭ beyond which no spadal information is transferred.

Stereotype Internalization, Math Perceptions, and Occupational Choices of Women With Counter-Stereotypical University Majors

2007 ◽  
Vol 66 (3) ◽  
pp. 169-178 ◽  
Author(s):  
Virginie Bonnot ◽  
Jean-Claude Croizet
Keyword(s):  
Academic Achievement ◽  
Negative Impact ◽  
Self Concept ◽  
Occupational Choices ◽  
Men And Women ◽  
Performance Expectancies ◽  
Subjective Value ◽  
Stereotype Endorsement

Based on Eccles’ (1987) model of academic achievement-related decisions, we tested whether women, who are engaged in mathematical fields at university, have internalized, to some extent, the stereotype about women’s inferiority in math. The results indicate that men and women do not assess their ability self-concept, subjective value of math, or performance expectancies differently. However, women’s degree of stereotype endorsement has a negative impact on their ability self-concept and their performance expectancies, but does not affect their value of the math domain. Moreover, members of both genders envisage stereotypical careers after university graduation.

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