Information Processing and Collective Behavior in a Model Neuronal System

2014 ◽  
Author(s):  
Daniel B. Forger
Keyword(s):  
Information Processing ◽  
Collective Behavior ◽  
Neuronal System

scholarly journals The Understanding Capacity and Information Dynamics in the Human Brain

Entropy ◽  
2019 ◽  
Vol 21 (3) ◽  
pp. 308 ◽  
Author(s):  
Yan Yufik
Keyword(s):  
Human Brain ◽  
Collective Behavior ◽  
Past History ◽  
Human Cognition ◽  
Emergent Properties ◽  
Neuronal System ◽  
Information Dynamics ◽  
The Past ◽  
Neuronal Processes ◽  
Mental Modeling

This article proposes a theory of neuronal processes underlying cognition, focusing on the mechanisms of understanding in the human brain. Understanding is a product of mental modeling. The paper argues that mental modeling is a form of information production inside the neuronal system extending the reach of human cognition “beyond the information given” (Bruner, J.S., Beyond the Information Given, 1973). Mental modeling enables forms of learning and prediction (learning with understanding and prediction via explanation) that are unique to humans, allowing robust performance under unfamiliar conditions having no precedents in the past history. The proposed theory centers on the notions of self-organization and emergent properties of collective behavior in the neuronal substrate. The theory motivates new approaches in the design of intelligent artifacts (machine understanding) that are complementary to those underlying the technology of machine learning.

Inferring the Logic of Collective Information Processors

2020 ◽  
pp. 81-112
Author(s):  
Bryan C. Daniels
Keyword(s):  
Information Theory ◽  
Information Processing ◽  
Distributed Systems ◽  
Collective Behavior ◽  
Statistical Physics ◽  
Collective Information

From neurons to insects to societies, across biology we see impressive feats of collective information processing. What strategies do these systems use to perform useful computations? Moving toward an answer to this question, this chapter focuses on common challenges in inferring models of complicated distributed systems and how the perspective of information theory and statistical physics is useful for understanding collective behavior.

scholarly journals Diversity improves performance in excitable networks

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1912 ◽  
Author(s):  
Leonardo L. Gollo ◽  
Mauro Copelli ◽  
James A. Roberts
Keyword(s):  
Phase Transition ◽  
Information Processing ◽  
Information Transmission ◽  
Collective Behavior ◽  
General Model ◽  
Heterogeneous Systems ◽  
Optimal Performance ◽  
Excitable Systems ◽  
Neuronal Systems

As few real systems comprise indistinguishable units, diversity is a hallmark of nature. Diversity among interacting units shapes properties of collective behavior such as synchronization and information transmission. However, the benefits of diversity on information processing at the edge of a phase transition, ordinarily assumed to emerge from identical elements, remain largely unexplored. Analyzing a general model of excitable systems with heterogeneous excitability, we find that diversity can greatly enhance optimal performance (by two orders of magnitude) when distinguishing incoming inputs. Heterogeneous systems possess a subset of specialized elements whose capability greatly exceeds that of the nonspecialized elements. We also find that diversity can yield multiple percolation, with performance optimized at tricriticality. Our results are robust in specific and more realistic neuronal systems comprising a combination of excitatory and inhibitory units, and indicate that diversity-induced amplification can be harnessed by neuronal systems for evaluating stimulus intensities.

scholarly journals Outline of a Brain Model for Self-Observing Agents

2021 ◽  
pp. 2150008
Author(s):  
Bernhard J. Mitterauer
Keyword(s):  
Information Processing ◽  
Sensory Information ◽  
Neuronal System ◽  
Qualitative Information ◽  
Machine Consciousness ◽  
Double Structure ◽  
Behavior Intentions ◽  
Elementary Principle ◽  
The Brain

Brain-inspired models for conscious robots should refer to the cellular double structure of the brain, consisting of the neuronal system and the glial system, embodying two ontological realms. Therefore, a purely neurobiological approach to machine consciousness is biased by an ontological fault in exclusively referring to the neuronal system. The brain model for self-observing agents outlined in this paper focuses on the glial-neuronal synaptic units (tripartite synapses). Whereas the neuronal component of the synapse embodies objective subjectivity processing sensory information, the glial component (astrocyte) embodies subjective subjectivity generating subjective behavior (intentions, consciousness) in its interactions with the neuronal part of the synapse. The elementary principle of the implementation of self-observing agents is this: a brain is capable of self-observation, if the concept of intention to observe something and the concept of the observed are located in different places. Based on a formalism of qualitative information processing, the architecture of self-observation is described in increasing complexity, building networks. It is suggested that if a robot brain is equipped with a network of modules for self-observation, the robot may generate subjective perspectives of self-observation indicating self-consciousness.

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.

Attachment and Field Dependence: Individual Differences in Information Processing

2004 ◽  
Vol 9 (1) ◽  
pp. 43-55 ◽  
Author(s):  
Patrizia Vermigli ◽  
Alessandro Toni
Keyword(s):  
Information Processing ◽  
Individual Differences ◽  
Field Dependence ◽  
Attachment Styles ◽  
Close Relationships ◽  
Adult Age ◽  
Males And Females ◽  
Figure Test ◽  
The Relationship ◽  
Measure Field

The present research analyzes the relationship between attachment styles at an adult age and field dependence in order to identify possible individual differences in information processing. The “Experience in Close Relationships” test of Brennan et al. was administered to a sample of 380 individuals (160 males, 220 females), while a subsample of 122 subjects was given the Embedded Figure Test to measure field dependence. Confirming the starting hypothesis, the results have shown that individuals with different attachment styles have a different way of perceiving the figure against the background. Ambivalent and avoidant individuals lie at the two extremes of the same dimension while secure individuals occupy the central part. Significant differences also emerged between males and females.

Hostility and Perceptions of Support in Ambiguous Social Interactions

2006 ◽  
Vol 27 (2) ◽  
pp. 108-115 ◽  
Author(s):  
Ana-Maria Vranceanu ◽  
Linda C. Gallo ◽  
Laura M. Bogart
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Information Processing ◽  
Social Interactions ◽  
Social Information Processing ◽  
Perceived Social Support ◽  
Social Information ◽  
Inverse Association ◽  
Processing Bias ◽  
Information Processing Bias

The present study investigated whether a social information processing bias contributes to the inverse association between trait hostility and perceived social support. A sample of 104 undergraduates (50 men) completed a measure of hostility and rated videotaped interactions in which a speaker disclosed a problem while a listener reacted ambiguously. Results showed that hostile persons rated listeners as less friendly and socially supportive across six conversations, although the nature of the hostility effect varied by sex, target rated, and manner in which support was assessed. Hostility and target interactively impacted ratings of support and affiliation only for men. At least in part, a social information processing bias could contribute to hostile persons' perceptions of their social networks.

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