Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Neural Circuits01:25

Neural Circuits

3.2K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
3.2K
Neuroplasticity01:01

Neuroplasticity

2.4K
Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.
2.4K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

502
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
502
Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

2.9K
Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
2.9K
Information Processing Approach01:30

Information Processing Approach

791
The information-processing theory of cognitive development centers on fundamental mental processes, including attention, memory, and problem-solving skills. Researchers in this field examine how cognitive abilities, such as working memory, evolve and influence children's overall development. Studies indicate that children with stronger working memory tend to excel in reading comprehension, math, and problem-solving compared to peers with less efficient memory skills. Low working memory is...
791
Parallel Processing01:20

Parallel Processing

888
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
888

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Donor-derived posttransplant lymphoproliferative disease detection by donor-derived cell-free DNA.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons·2024
Same author

Nuances in the interpretation and utility of donor-derived cell-free DNA in lung transplantation following allogeneic hematopoietic stem cell transplantation - Case report.

Transplant immunology·2024
Same author

Energy-Efficient Neuromorphic Architectures for Nuclear Radiation Detection Applications.

Sensors (Basel, Switzerland)·2024
Same author

¿Notas La Diferencia? [Do You Hear the Difference?]: Perceptual Consequences of Intensive Voice Treatment in Spanish Speakers With Parkinson's Disease.

Journal of speech, language, and hearing research : JSLHR·2024
Same author

Automatic Assessment of Intelligibility in Noise in Parkinson Disease: Validation Study.

Journal of medical Internet research·2022
Same author

Revisiting the edge of chaos: Again?

Bio Systems·2022
Same journal

Erratum: Bacterial Turbulence at Compressible Fluid Interfaces [Phys. Rev. Lett. 136, 138301 (2026)].

Physical review letters·2026
Same journal

Unveiling Light-Quark Yukawa Flavor Structure via Dihadron Fragmentation at Lepton Colliders.

Physical review letters·2026
Same journal

Adaptable Route to Fast Coherent State Transport via Bang-Bang-Bang Protocols.

Physical review letters·2026
Same journal

Topological Transition and Emergence of Elasticity of Dislocation in Skyrmion Lattice: Beyond Kittel's Magnetic-Polar Analogy.

Physical review letters·2026
Same journal

Pound-Drever-Hall Method for Superconducting-Qubit Readout.

Physical review letters·2026
Same journal

Coupling a ^{73}Ge Nuclear Spin to an Electrostatically Defined Quantum Dot in Silicon.

Physical review letters·2026
See all related articles

Related Experiment Video

Updated: Mar 31, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.7K

Emergent criticality through adaptive information processing in boolean networks.

Alireza Goudarzi1, Christof Teuscher, Natali Gulbahce

  • 1Portland State University, 1900 4th SW Avenue, Portland, Oregon 97206, USA.

Physical Review Letters
|May 1, 2012
PubMed
Summary
This summary is machine-generated.

Adaptive information processing in boolean networks drives them to critical connectivity (K(c)=2) for optimal learning and generalization. This critical state, observed in large and finite systems, maximizes topological diversity and fitness variance.

More Related Videos

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

5.3K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

11.0K

Related Experiment Videos

Last Updated: Mar 31, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.7K
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

5.3K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

11.0K

Area of Science:

  • Computational neuroscience
  • Complex systems theory
  • Network science

Background:

  • Boolean networks are models for studying complex systems.
  • Understanding how network properties influence information processing is crucial.
  • The relationship between network connectivity, learning, and robustness remains an open question.

Purpose of the Study:

  • To investigate the interplay between learning capability, robustness, network topology, and task complexity in evolving boolean networks.
  • To determine the critical connectivity value for adaptive information processing in large systems.
  • To explore how network properties optimize learning and generalization.

Main Methods:

  • Computational analysis of boolean networks with evolving connectivity.
  • Systematic exploration of network behavior across varying system sizes and task complexities.
  • Analysis of network topology, learning metrics, and fitness variance near critical points.

Main Results:

  • Adaptive information processing drives large boolean networks to a critical connectivity of K(c)=2.
  • For finite networks, connectivity approaches K(c) via a power law with system size N.
  • Network learning and generalization are optimized near criticality, contingent on task complexity and information thresholds.
  • Maximal topological diversity and fitness variance are observed in critical network populations.

Conclusions:

  • The critical connectivity K(c)=2 is a key feature for optimal information processing in adaptive boolean networks.
  • Network topology near criticality supports efficient exploration and robustness of solutions.
  • Findings provide insights for designing optimal adaptive dynamical networks for computational tasks.