Back

A digitization theory of the Weber-Fechner law

Choe, H.

2021-03-20 neuroscience
10.1101/2021.03.15.435555 bioRxiv
Show abstract

Ever since the publication of Shannons article about information theory, there have been many attempts to apply information theory to the neuroscience field. Meanwhile, the Weber- Fechner law of psychophysics states that the magnitude of a subjective sensation of a person increases in proportion to the logarithm of the intensity of the external physical-stimulus. It is hardly surprising that we assign the amount of information to the response in the Weber- Fechner law. But, to date no one has succeeded in applying information theory directly to that law: the direct links between information theory and that response in the Weber-Fechner law have not yet been found. The proposed theory unveils a link between information theory and that response, and differs subtly from the field such as neural coding that involves complicated calculations and models. Because my theory targets the Weber-Fechner law which is a macroscopic phenomenon, this theory does not involve complicated calculations. My theory is expected to mark a new era in the fields of sensory perception research. My theory must be studied in parallel with the fields of microscopic scale such as neural coding. This article ultimately aims to provide the fundamental concepts and their applications so that a new field of research on stimuli and responses can be created.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Entropy
20 papers in training set
Top 0.1%
14.3%
2
Chaos, Solitons & Fractals
32 papers in training set
Top 0.1%
14.3%
3
PLOS ONE
4510 papers in training set
Top 20%
9.1%
4
Scientific Reports
3102 papers in training set
Top 18%
6.4%
5
Frontiers in Neuroscience
223 papers in training set
Top 0.5%
6.4%
50% of probability mass above
6
Neural Networks
32 papers in training set
Top 0.1%
4.0%
7
Frontiers in Computational Neuroscience
53 papers in training set
Top 0.6%
4.0%
8
Neuroscience
88 papers in training set
Top 0.3%
3.6%
9
Neurocomputing
13 papers in training set
Top 0.2%
1.7%
10
PLOS Computational Biology
1633 papers in training set
Top 17%
1.7%
11
Neural Computation
36 papers in training set
Top 0.4%
1.5%
12
Heliyon
146 papers in training set
Top 3%
1.3%
13
Journal of Computational Neuroscience
23 papers in training set
Top 0.3%
1.3%
14
Biology
43 papers in training set
Top 1%
1.3%
15
Nonlinear Dynamics
10 papers in training set
Top 0.3%
1.2%
16
Frontiers in Systems Neuroscience
19 papers in training set
Top 0.3%
1.1%
17
Royal Society Open Science
193 papers in training set
Top 3%
1.1%
18
Frontiers in Human Neuroscience
67 papers in training set
Top 2%
0.9%
19
Neuroscience of Consciousness
12 papers in training set
Top 0.3%
0.9%
20
Cognitive Neurodynamics
15 papers in training set
Top 0.4%
0.8%
21
SoftwareX
15 papers in training set
Top 0.4%
0.7%
22
Vision Research
26 papers in training set
Top 0.2%
0.7%
23
eneuro
389 papers in training set
Top 9%
0.7%
24
JMIR Public Health and Surveillance
45 papers in training set
Top 4%
0.7%
25
Epidemiology and Infection
84 papers in training set
Top 3%
0.7%
26
Physical Review E
95 papers in training set
Top 1%
0.7%
27
Consciousness and Cognition
17 papers in training set
Top 0.3%
0.7%
28
Frontiers in Applied Mathematics and Statistics
10 papers in training set
Top 0.5%
0.7%
29
Brain Sciences
52 papers in training set
Top 2%
0.7%