Internally Organized Cell Assembly Trajectories

2019 ◽  
pp. 165-198
Author(s):  
György Buzsáki
Keyword(s):  
Neuronal Activity ◽  
Initial Conditions ◽  
Cell Assembly ◽  
Self Organized ◽  
Brain Circuits ◽  
Default State ◽  
Neuronal Patterns ◽  
State Of Affairs ◽  
Transfer Of Information ◽  
Enormous Number

Sequences of neuronal patterns are not always imposed on brain circuits in an outside-in manner by the sensory inputs. Internally organized processes can sustain self-organized and coordinated neuronal activity even without external inputs. A prerequisite of cognition is the availability of internally generated neuronal sentences. Self-generated, sequentially evolving activity is the default state of affairs in most neuronal circuits. Neuronal activity moves perpetually, and its trajectory depends only on initial conditions. Large recurrent networks can generate an enormous number of trajectories without prior experience. On the other hand, each is available to be matched by experience to “represent” something useful for the downstream reader mechanisms. The richness of the information depends not on the numbers of generated sequences but on the reader mechanisms. It is typically the reader structure that initiates the transfer of information, coordinating the onset of messages from multiple senders.

Artificial Planning Experience by Means of a Heuristic Cell-Space Model: Simulating International Migration in the Urban Process

1995 ◽  
Vol 27 (10) ◽  
pp. 1647-1665 ◽  
Author(s):  
J Portugali ◽  
I Benenson
Keyword(s):  
Urban Policy ◽  
Initial Conditions ◽  
Point Of View ◽  
Town Planning ◽  
Space Model ◽  
Self Organized ◽  
A Cell ◽  
Policy And Planning ◽  
The City ◽  
Theory And Model

We suggest considering the city as a complex, open, and thus self-organized system, and describing it by means of a cell-space model. A central property of self-organizing systems is that they are not controllable—not by individuals, nor by economic, political, and planning institutions. The city, in this respect, is complex and untamable. Inability to recognize and accept this property is one of the reasons for the difficulties and problems of modernist town planning. The theory and model we present are built to describe the urban process as a historical one in which, given identical initial conditions, each simulation run is unique and never fully repeats itself. From the point of view of urban policy and planning, our heuristic model can guide decisionmakers by answering the following question: ‘given the initial conditions of an inflow of new immigrants (that is, from the ex-USSR), what possible urban scenarios can result, and what are their global structural properties?’.

Boundedness and Other Theories for Complex Systems

2013 ◽  
pp. 108-125
Keyword(s):  
Initial Conditions ◽  
Traditional Approach ◽  
Deterministic Chaos ◽  
Mathematical Object ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Universal Properties ◽  
The One ◽  
Global Invariant ◽  
Sensitivity To Initial Conditions

A comparison between the concept of boundedness on the one hand, and the theory of self-organized criticality (SOC) and the deterministic chaos on the other hand, is made. The focus is put on the methodological importance of the general frame through which an enormous class of empirical observations is viewed. The major difference between the concept of boundedness and the theory of self organized criticality is that under boundedness, the response comprises both specific and universal part, and thus a system has well defined “identity,” while SOC assumes response as a global invariant which has only universal properties. Unlike the deterministic chaos, the boundedness is free to explain the sensitivity to initial conditions independently from the mathematical object that generates them. Alongside, it turns out that the traditional approach to the deterministic chaos has its ample understanding under the concept of boundedness.

scholarly journals Vibration Isolation Critical to Measuring Neuronal Patterns in the Brain

2009 ◽  
Vol 17 (3) ◽  
pp. 12-15
Author(s):  
David L. Platus
Keyword(s):  
Neuronal Activity ◽  
Vibration Isolation ◽  
Medical Center ◽  
Low Frequency ◽  
Vibration Isolators ◽  
Low Frequency Vibration ◽  
Conducting Research ◽  
Neuronal Patterns ◽  
Isolation Systems ◽  
The Brain

Researchers at Georgetown University's Department of Physiology and Biophysics use negative-stiffness vibration isolators to help measure micron-level patterns of neuronal activity in the mammalian neocortex. The research is shedding new light into brain sensory and motor processing functions relating to cardiac fibrillation and epilepsy.Isolating a laboratory's sensitive microscopy equipment against low-frequency vibration has become increasingly more vital to maintaining imaging quality and data integrity for neurobiology researches. Ever more frequently, laboratory researchers are discovering that conventional air tables and the more recent active (electronic) vibration isolation systems are not able to adequately cancel out the lower frequency perturbations derived from air conditioning systems, outside vehicular movements and ambulatory personnel. Such was the case with the Department of Physiology and Biophysics at Georgetown University Medical Center, where Professor Jian-Young Wu has been conducting research on waves of neuronal activity in the neocortex of the brain.

scholarly journals Shared neuronal bases of inhibition and economic choice in orbitofrontal cortex

2020 ◽  
Author(s):  
Pragathi Priyadharsini Balasubramani ◽  
Benjamin Y. Hayden
Keyword(s):  
Neural Network ◽  
Inhibitory Control ◽  
Neuronal Activity ◽  
Orbitofrontal Cortex ◽  
Choice Task ◽  
Stop Signal Task ◽  
Economic Choice ◽  
Brain Circuits ◽  
Neural Processes ◽  
Theoretical Unification

ABSTRACTEconomic choice and inhibition are two important elements of our cognitive repertoires that may be closely related. We and others have noted that during economic choice, options are typically considered serially; this fact provides important constraints on our understanding of choice. Notably, asynchronous contemplation means that each individual option is subject to an accept-reject decision. We have proposed that these component accept-reject decisions may have some kinship with stopping decisions. One prediction of this idea is that stopping and choice may reflect similar neural processes occurring in overlapping brain circuits. To test the idea, we recorded neuronal activity in orbitofrontal cortex (OFC) Area 13 while macaques performed a stop signal task interleaved with a structurally matched choice task. Using neural network decoders, we find that OFC ensembles have overlapping codes for stopping and choice: the decoder that was only trained to identify accept vs. reject trials performed with higher efficiency even when tested on the stop trials. These results provide tentative support for the idea that mechanisms underlying inhibitory control and choice selection may be subject to theoretical unification.

scholarly journals The Evolutionary Dynamics of Cooperation in Collective Search

2019 ◽  
Author(s):  
Alan N. Tump ◽  
Charley M. Wu ◽  
Imen Bouhlel ◽  
Robert L. Goldstone
Keyword(s):  
Selection Pressure ◽  
Evolutionary Dynamics ◽  
Initial Conditions ◽  
Search Efficiency ◽  
Access To Information ◽  
Interaction Structure ◽  
Self Organized ◽  
Shared Information ◽  
Evolutionary Context ◽  
Evolutionary Simulations

AbstractHow does cooperation arise in an evolutionary context? We approach this problem using a collective search paradigm where interactions are dynamic and there is competition for rewards. Using evolutionary simulations, we find that the unconditional sharing of information can be an evolutionary advantageous strategy without the need for conditional strategies or explicit reciprocation. Shared information acts as a recruitment signal and facilitates the formation of a self-organized group. Thus, the improved search efficiency of the collective grants byproduct benefits to the original sharer by altering the interaction structure. A key mechanism is a visibility radius, where individuals have access to information about neighbors within a limited distance. Our results show that for a variety of initial conditions and across both static and dynamic fitness landscapes, there is strong selection pressure for unconditional sharing.

scholarly journals Psychotherapy in the era of artificial intelligence: Therapist Panoptes

2019 ◽  
Vol 2 (1) ◽  
pp. 68 ◽  
Author(s):  
Alexios Brailas
Keyword(s):  
Artificial Intelligence ◽  
Feedback Loop ◽  
Therapeutic Agent ◽  
Initial Conditions ◽  
Social Systems ◽  
Individual Action ◽  
Self Organized ◽  
Sensitive Dependence ◽  
Technological Singularity ◽  
New Perspective

“What will happen when an artificial intelligence entity has access to all the information stored about me online, with the ability to process my information efficiently and flawlessly? Will such an entity not be, in fact, my ideal therapist?” Would there ever come a point at which you would put your trust in an omniscient, apperceptive, and ultra-intelligent robotic therapist? There is a horizon beyond which we can neither see nor even imagine; this is the technological singularity moment for psychotherapy. If human intelligence is capable of creating an artificial intelligence that surpasses its creators, then this intelligence would, in turn, be able to create an even superior next-generation intelligence. An inevitable positive feedback loop would lead to an exponential intelligence growth rate. In the present paper, we introduce the term Therapist Panoptes as a working hypothesis to investigate the implications for psychotherapy of an artificial therapeutic agent: one that is able to access all available data for a potential client and process these with an inconceivably superior intelligence. Although this opens a new perspective on the future of psychotherapy, the sensitive dependence of complex techno-social systems on their initial conditions renders any prediction impossible. Artificial intelligence and humans form a bio-techno-social system, and the evolution of the participating actors in this complex super-organism depends upon their individual action, as well as upon each actor being a coevolving part of a self-organized whole.

Problem Discovery With Many-Objective Visual Analytics

2016 ◽  
Author(s):  
Matthew Woodruff ◽  
Timothy W. Simpson
Keyword(s):  
Visual Analytics ◽  
Design Problem ◽  
Problem Formulation ◽  
Design Problems ◽  
Design Decisions ◽  
Detailed Design ◽  
Default State ◽  
State Of Affairs

Problem discovery is messy. It involves many mistakes, which may be regarded as a failure to address a design problem correctly. Mistakes, however, are inevitable, and misunderstanding the problems we are working on is the natural, default state of affairs. Only through engaging in a series of mistakes can we learn important things about our design problems. This study provides a case study in Many-Objective Visual Analytics (MOVA), as applied to the problem of problem discovery. It demonstrates the process of continually correcting and improving a problem formulation while visualizing its optimization results. This process produces a new, clearer understanding of the problem and puts the designer in a position to proceed with more-detailed design decisions.

scholarly journals The Effect of Brood Quantity on Nest Site Choice in the Temnothorax rugatulus (Hymenoptera: Formicidae)

2020 ◽  
Author(s):  
Takao Sasaki ◽  
Jennifer E Briner ◽  
Stephen C Pratt
Keyword(s):  
Nest Site ◽  
Initial Conditions ◽  
Nest Site Selection ◽  
Self Organized ◽  
Highly Nonlinear ◽  
Nest Site Choice ◽  
Mass Recruitment ◽  
The Difference ◽  
Behavioral Mechanisms ◽  
Brood Item

Abstract Ant colonies are self-organized systems, meaning that complex collective behavior emerges from local interactions among colony members without any central control. Self-organized systems are sensitive to initial conditions, whereby small random effects are amplified through positive feedback and have a large influence on collective outcomes. This sensitivity has been well demonstrated in collective decision-making by ants that use mass recruitment via trail pheromones, where it is attributed to the highly nonlinear relationship between the amount of pheromone on a trail and its effectiveness at attracting recruits. This feature is absent in many species, such as the rock ant Temnothorax rugatulus (Emery) whose tandem run recruitment shows a linear relationship between effort and effectiveness. Thus, these ants may have other behavioral responses that amplify initial differences during collective choices. We investigated this by testing whether nest site selection is influenced by small differences in the amount of brood at competing sites. Our results show that T. rugatulus colonies prefer a nest containing brood items to an empty nest, even when the brood-containing nest has only one brood item. When both nests have brood, colonies prefer the nest that contains more. However, as the numbers of brood items becomes more similar, this preference becomes weaker. Moreover, the smaller the difference in brood number, the more likely are colonies to split between sites. We discuss potential behavioral mechanisms for the observed effect, as well as its implications for number sense in ants.

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