Springer Handbook of Bio-/Neuroinformatics pp 1083-1098 | Cite as
Brain, Gene, and Quantum Inspired Computational Intelligence
Abstract
- 1.
A computational neurogenetic model that in one model combines gene information related to spiking neuronal activities.
- 2.
A general framework of a quantum spiking neural network (SNN) model.
- 3.
A general framework of a quantum computational neurogenetic model (CNGM).
Keywords
Artificial Neural Network Artificial Neural Network Model Gene Regulatory Network Local Field Potential Incremental LearningAbbreviations
- AI
artificial intelligence
- AMPAR
(amino-methylisoxazole-propionic acid) receptor
- ANN
artificial neural network
- BDNF
brain-derived neurotrophic factor
- BGO
brain-gene ontology
- CI
computational intelligence
- CLC
chloride channel
- CNGM
computational neurogenetic model
- DENFIS
dynamic neuro-fuzzy inference system
- DNA
deoxyribonucleic acid
- ECOS
evolving connectionist system
- EEG
electroencephalography
- EFuNN
evolving fuzzy neural network
- FFT
fast Fourier transformation
- FGF
fibroblast growth factor
- GA
genetic algorithm
- GABA
gamma-aminobutyric acid
- GABRA
GABAA receptor
- GABRB
GABAB receptor
- GRN
gene regulatory network
- KCN
kalium (potassium) voltage-gated channel
- LFP
local field potential
- MLP
multilayer perceptron
- NMDA
N-methyl-d-aspartate
- NMDAR
(N-methyl-d-aspartate acid) NMDA receptor
- PS
presenilin
- PSP
post-synaptic potential
- PV
parvalbumin
- QI
quantum inspired
- QIEC
quantum inspired methods of evolutionary computation
- RNA
ribonucleic acid
- SCN
sodium voltage-gated channel
- SNN
spiking neural network
- SOM
self-organizing map
- SRM
spike response model
- SVM
support vector machine
- TWNFI
transductive weighted neuro-fuzzy inference engine
- mRNA
messenger RNA
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