Possible Biological And Cognitive Functions Of Neural Networks Probabilistically Driven By An Influence Of Probabilistic Release Of Synaptic Vesicles

2005 ◽  
Author(s):  
I. Tsuda
Keyword(s):  
Neural Networks ◽  
Cognitive Functions ◽  
Synaptic Vesicles

Neurons versus Networks: The Interplay between Individual Neurons and Neural Networks in Cognitive Functions

2016 ◽  
Vol 23 (4) ◽  
pp. 341-355 ◽  
Author(s):  
Yuri I. Arshavsky
Keyword(s):  
Neural Networks ◽  
Complex Networks ◽  
Cognitive Neuroscience ◽  
Cognitive Functions ◽  
Medial Temporal Lobe ◽  
Nervous Activity ◽  
Intracellular Level ◽  
Abstract Concepts ◽  
Electrical Potentials ◽  
Higher Nervous Activity

The main paradigm of cognitive neuroscience is the connectionist concept postulating that the higher nervous activity is performed through interactions of neurons forming complex networks, whereas the function of individual neurons is restricted to generating electrical potentials and transmitting signals to other cells. In this article, I describe the observations from three fields—neurolinguistics, physiology of memory, and sensory perception—that can hardly be explained within the constraints of a purely connectionist concept. Rather, these examples suggest that cognitive functions are determined by specific properties of individual neurons and, therefore, are likely to be accomplished primarily at the intracellular level. This view is supported by the recent discovery that the brain’s ability to create abstract concepts of particular individuals, animals, or places is performed by neurons (“concept cells”) sparsely distributed in the medial temporal lobe.

Parallel Distributed Processing and Neural Networks: Origins, Methodology and Cognitive Functions

1991 ◽  
Vol 60 (2) ◽  
pp. 195-214 ◽  
Author(s):  
Randolph W. Parks ◽  
Debra L. Long ◽  
Daniel S. Levine ◽  
David J. Crockett ◽  
Edith G. McGeer ◽  
...  
Keyword(s):  
Neural Networks ◽  
Cognitive Functions ◽  
Distributed Processing ◽  
Parallel Distributed Processing

Resetting the brain

2021 ◽  
pp. 110-123
Author(s):  
Chris Letheby
Keyword(s):  
Neural Networks ◽  
Cognitive Functions ◽  
Prediction Error ◽  
Cognitive Process ◽  
Large Scale ◽  
Predictive Processing ◽  
Therapeutic Benefits ◽  
High Level ◽  
The Brain

‘Resetting the brain’ examines the hypothesis that (i) large-scale neural networks become stuck in dysfunctional configurations in pathology, and (ii) psychedelics cause therapeutic benefits by disrupting these configurations, providing an opportunity to ‘reset’ the relevant networks into a healthier state. This chapter argues that this view is correct but limited; per Chapter 5, it needs to be supplemented with an account of these networks’ cognitive functions. To this end, the chapter introduces the predictive processing (PP) theory of cognition, which views the brain as an organ for prediction error minimisation. One PP-based theory of psychedelic action claims that (i) the networks targeted by psychedelics encode high-level beliefs, and (ii) psychedelic disruption of these beliefs provides an opportunity to revise them. This is the cognitive process that corresponds to the ‘resetting’ of neural networks. The chapter concludes by proposing that the beliefs most often revised in successful psychedelic therapy are self-related beliefs.

Homogeneous neural networks cannot provide complex cognitive functions

1999 ◽  
Vol 22 (2) ◽  
pp. 293-293 ◽  
Author(s):  
Alexey M. Ivanitsky ◽  
Andrey R. Nikolaev
Keyword(s):  
Neural Networks ◽  
Cognitive Functions ◽  
Cell Assemblies ◽  
Functional Systems ◽  
The Brain

Within the Hebbian paradigm the mechanism for integrating cell assemblies oscillating with different frequencies remains unclear. We hypothesize that such an integration may occur in cortical “interaction foci” that unite synchronously oscillated assemblies through hard-wired connections, synthesizing the information from various functional systems of the brain.

Parallel Distributed Processing and Neural Networks: Origins, Methodology and Cognitive Functions

1991 ◽  
Vol 60 (3-4) ◽  
pp. 195-214 ◽  
Author(s):  
Randolph W. Parks ◽  
Debra L. Long ◽  
Daniel S. Levine ◽  
David J. Crockett ◽  
Edith G. McGeer ◽  
...  
Keyword(s):  
Neural Networks ◽  
Cognitive Functions ◽  
Distributed Processing ◽  
Parallel Distributed Processing

Language processing is not a race against time

2016 ◽  
Vol 39 ◽  
Author(s):  
Giosuè Baggio ◽  
Carmelo M. Vicario
Keyword(s):  
Information Processing ◽  
Human Brain ◽  
Language Processing ◽  
Cognitive Functions ◽  
Memory Systems ◽  
Language System ◽  
Moderating Factors

AbstractWe agree with Christiansen & Chater (C&C) that language processing and acquisition are tightly constrained by the limits of sensory and memory systems. However, the human brain supports a range of cognitive functions that mitigate the effects of information processing bottlenecks. The language system is partly organised around these moderating factors, not just around restrictions on storage and computation.

The Lateral Giant Fiber to Motor Giant Fiber Synapse in Crayfish

1972 ◽  
Vol 30 ◽  
pp. 170-171
Author(s):  
Charles A. Stirling
Keyword(s):  
Synaptic Vesicles ◽  
Procambarus Clarkii ◽  
Synaptic Contact ◽  
Giant Fiber ◽  
Synaptic Junctions

The lateral giant (LG) to motor giant (MoG) synapses in crayfish (Procambarus clarkii) abdominal ganglia are the classic electrotonic synapses. They have previously been described as having synaptic vesicles and as having them on both the pre- and postsynaptic sides of symmetrical synaptic junctions. This positioning of vesicles would make these very atypical synapses, but in the present work on the crayfish Astacus pallipes the motor giant has never been found to contain any type of vesicle at its synapses with the lateral giant fiber.The lateral to motor giant fiber synapses all occur on short branches off the main giant fibers. Closely associated with these giant fiber synapses are two small presynaptic nerves which make synaptic contact with both of the giant fibers and with their small branches.

Sign in / Sign up

Export Citation Format

Share Document