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

Association Areas of the Cortex01:21

Association Areas of the Cortex

9.4K
Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
9.4K
Protein Complex Assembly02:41

Protein Complex Assembly

16.8K
Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
16.8K
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

2.9K
Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order...
2.9K
Complex Numbers01:29

Complex Numbers

317
The real number system cannot represent the square root of a negative number, which restricts solutions for certain equations, such as quadratics with negative discriminants. To address this, the complex number system was developed, introducing the imaginary unit i, where i = √(-1). This extension allows for the representation of all roots, including those involving negative radicands.A complex number is written in the form x + yi, where x and y are real numbers. Here, x represents the...
317
Motor and Sensory Areas of the Cortex01:14

Motor and Sensory Areas of the Cortex

7.6K
The cerebral cortex, the brain's outermost layer, is pivotal in processing complex cognitive tasks, emotions, and various sensory inputs and executing voluntary motor activities. This intricate structure is divided into three primary functional areas: the motor areas, sensory areas, and association areas.
Motor Areas
The motor areas located in the frontal lobe are central to controlling voluntary movements. This region is further subdivided into the primary motor cortex and the premotor cortex....
7.6K
Formation of Complex Ions03:45

Formation of Complex Ions

26.2K
A type of Lewis acid-base chemistry involves the formation of a complex ion (or a coordination complex) comprising a central atom, typically a transition metal cation, surrounded by ions or molecules called ligands. These ligands can be neutral molecules like H2O or NH3, or ions such as CN− or OH−. Often, the ligands act as Lewis bases, donating a pair of electrons to the central atom. These types of Lewis acid-base reactions are examples of a broad subdiscipline called coordination...
26.2K

You might also read

Related Articles

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

Sort by
Same author

Transient plasma p-tau217 elevations after electroconvulsive therapy: A two-case report.

Alzheimer's & dementia (Amsterdam, Netherlands)·2026
Same author

The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing.

Imaging neuroscience (Cambridge, Mass.)·2025
Same author

Biophysical parameters control signal transfer in spiking network.

Frontiers in computational neuroscience·2023
Same author

Resting-state Functional Connectivity After Occipital Stroke.

Neurorehabilitation and neural repair·2021
Same author

Anatomy and Physiology of Macaque Visual Cortical Areas V1, V2, and V5/MT: Bases for Biologically Realistic Models.

Cerebral cortex (New York, N.Y. : 1991)·2020
Same author

Controlling Complexity of Cerebral Cortex Simulations-II: Streamlined Microcircuits.

Neural computation·2019
Same journal

A Model-Free Reinforcement Learning Implementation of Decision Making Under Uncertainty by Sequential Sampling.

Neural computation·2026
Same journal

DROP: Distributional and Regular Optimism and Pessimism for Reinforcement Learning.

Neural computation·2026
Same journal

Hierarchical Active Inference Using Successor Representations.

Neural computation·2026
Same journal

W-Kernel and Its Principal Space for Frequentist Evaluation of Bayesian Estimators.

Neural computation·2026
Same journal

A Hidden Markov Model-Inspired Sequence Classification Method for Hyperdimensional Computing.

Neural computation·2026
Same journal

Sparse Graphical Modeling for Electrophysiological Phase-Based Connectivity Using Circular Statistics.

Neural computation·2026
See all related articles

Related Experiment Video

Updated: Feb 6, 2026

Simulator Training for Endovascular Neurosurgery
08:08

Simulator Training for Endovascular Neurosurgery

Published on: May 6, 2020

4.2K

Controlling Complexity of Cerebral Cortex Simulations-I: CxSystem, a Flexible Cortical Simulation Framework.

Vafa Andalibi1, Henri Hokkanen2, Simo Vanni3

  • 1Clinical Neurosciences, Neurology, University of Helsinki and Helsinki University Hospital, Helsinki 00029, Finland, and School of Informatics, Computing and Engineering, Indiana University Bloomington, IN 47408, U.S.A. vafandal@indiana.edu.

Neural Computation
|August 28, 2018
PubMed
Summary
This summary is machine-generated.

A new framework simplifies complex cerebral cortex simulations on personal computers. CxSystem reduces coding errors and speeds up exploration of neural networks, benefiting researchers without extensive software engineering backgrounds.

More Related Videos

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

1.1K
Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
07:12

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

970

Related Experiment Videos

Last Updated: Feb 6, 2026

Simulator Training for Endovascular Neurosurgery
08:08

Simulator Training for Endovascular Neurosurgery

Published on: May 6, 2020

4.2K
Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

1.1K
Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
07:12

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

970

Area of Science:

  • Computational Neuroscience
  • Systems Neuroscience
  • Neuroscience Software Engineering

Background:

  • Simulating the cerebral cortex demands significant domain knowledge and efficient software.
  • Complexity in biological systems and software increases coding errors, hindering model adjustments.
  • Life scientists often lack software engineering expertise, necessitating simpler modeling approaches.

Purpose of the Study:

  • To develop a scalable cortical simulation framework for personal computers.
  • To abstract biological model parameters for easier use by life scientists.
  • To reduce coding errors and facilitate rapid exploration of complex cortical circuits.

Main Methods:

  • Isolated adjustable domain-specific knowledge from the core software.
  • Designed a framework to read model parameters from CSV files.
  • Generated Brian2 simulation code automatically, supporting Python, C++, and GPU devices.

Main Results:

  • The CxSystem framework efficiently performed simulations across different devices (Python, C++, GPU).
  • Simulation performance was maintained compared to direct Brian2 usage.
  • Device efficiency varied based on hardware, simulation scale, and duration.
  • Python and C++ devices retained Brian2's single-core limitation.

Conclusions:

  • CxSystem enables complex model exploration on personal computers, lowering barriers for neuroscience research.
  • The framework facilitates research on cortical networks and systems by simplifying simulation setup.
  • Separating model parameters from software enhances usability and reduces errors in computational neuroscience.