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

Neuroplasticity01:01

Neuroplasticity

2.3K
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.
2.3K
Plasticity00:58

Plasticity

3.2K
Plasticity is the property where an object loses its elasticity and undergoes irreversible deformation, even after the deformation forces are eliminated. If a material deforms irreversibly without increasing stress or load, then this is called ideal plasticity. For example, when a force is applied to an aluminum rod, it changes its shape, but it does not return to its original shape once the force is removed. Plastic deformation or ductility is thus a permanent deformation or change in the...
3.2K
Somatosensory, Motor, and Association Cortex01:23

Somatosensory, Motor, and Association Cortex

3.7K
The somatosensory cortex in the parietal lobes is crucial for interpreting sensory data such as touch, temperature, and proprioception. The somatosensory cortex, situated in the parietal lobes, plays a vital role in interpreting sensory information like touch, temperature, and proprioception—awareness of body position. This specialized brain region features an organized structure wherein neurons at the top primarily process sensations originating from the lower body. In contrast, those at...
3.7K
Role of Cerebellum and Prefrontal Cortex in Memory01:14

Role of Cerebellum and Prefrontal Cortex in Memory

1.4K
The cerebellum, while traditionally associated with motor control, also plays a crucial role in memory, particularly in procedural memory, which involves learning motor tasks that become automatic through repetition. For example, studies have shown that when the cerebellum is damaged, individuals or animals lose the ability to learn conditioned motor responses, such as the conditioned eye-blink response in classical conditioning experiments with rabbits. This study demonstrates the...
1.4K
Storage01:23

Storage

477
A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
477
Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

2.2K
Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or...
2.2K

You might also read

Related Articles

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

Sort by
Same author

Parallax error indicates simple cue-anchoring in the head-direction system.

bioRxiv : the preprint server for biology·2026
Same author

Deciphering hippocampal place codes in weak theta rhythms.

Nature communications·2026
Same author

Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps.

Advances in neural information processing systems·2025
Same author

Principled neuromorphic reservoir computing.

Nature communications·2025
Same author

Computing With Residue Numbers in High-Dimensional Representation.

Neural computation·2024
Same author

Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps.

ArXiv·2024
Same journal

TC2-Res: a structured fusion of tract-level and connectome-level brain imaging in small-sample cohorts of athletes.

Frontiers in neuroanatomy·2026
Same journal

Revisiting the clastosome: a stress-induced nuclear proteolytic compartment of mammalian cells.

Frontiers in neuroanatomy·2026
Same journal

Intrinsic elaboration of prefrontal modularity: a dual-control model of axon bundling and synaptic docking.

Frontiers in neuroanatomy·2026
Same journal

Selective enrichment of TCF4 in GABAergic neurons during postnatal primate development.

Frontiers in neuroanatomy·2026
Same journal

ATF3-based peripheral neural tract tracing.

Frontiers in neuroanatomy·2026
Same journal

Stereological evaluation of the neuroprotective effects of curcumin on the spinal cord in a streptozotocin-induced diabetic rat model.

Frontiers in neuroanatomy·2026
See all related articles

Related Experiment Video

Updated: Mar 18, 2026

Slice Patch Clamp Technique for Analyzing Learning-Induced Plasticity
11:56

Slice Patch Clamp Technique for Analyzing Learning-Induced Plasticity

Published on: November 11, 2017

16.5K

Structural Plasticity, Effectual Connectivity, and Memory in Cortex.

Andreas Knoblauch1, Friedrich T Sommer2

  • 1Informatics Faculty, Albstadt-Sigmaringen University Albstadt, Germany.

Frontiers in Neuroanatomy
|July 6, 2016
PubMed
Summary
This summary is machine-generated.

Structural plasticity, involving changes in neuronal connections, enhances memory storage capacity in the brain. This study links structural changes to effectual connectivity, improving how neural networks store information and learn.

Keywords:
effective connectivitylearningmemory consolidationpotential synapsespacing effectstorage capacitysynaptic plasticitytransfer entropy

More Related Videos

Investigating Long-term Synaptic Plasticity in Interlamellar Hippocampus CA1 by Electrophysiological Field Recording
14:27

Investigating Long-term Synaptic Plasticity in Interlamellar Hippocampus CA1 by Electrophysiological Field Recording

Published on: August 11, 2019

13.6K
Visualization of Cortical Modules in Flattened Mammalian Cortices
08:49

Visualization of Cortical Modules in Flattened Mammalian Cortices

Published on: January 22, 2018

13.9K

Related Experiment Videos

Last Updated: Mar 18, 2026

Slice Patch Clamp Technique for Analyzing Learning-Induced Plasticity
11:56

Slice Patch Clamp Technique for Analyzing Learning-Induced Plasticity

Published on: November 11, 2017

16.5K
Investigating Long-term Synaptic Plasticity in Interlamellar Hippocampus CA1 by Electrophysiological Field Recording
14:27

Investigating Long-term Synaptic Plasticity in Interlamellar Hippocampus CA1 by Electrophysiological Field Recording

Published on: August 11, 2019

13.6K
Visualization of Cortical Modules in Flattened Mammalian Cortices
08:49

Visualization of Cortical Modules in Flattened Mammalian Cortices

Published on: January 22, 2018

13.9K

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Learning and memory are traditionally linked to synaptic plasticity.
  • Emerging evidence highlights the critical role of structural plasticity in neuronal networks.
  • Structural plasticity encompasses synapse elimination/regeneration and dendritic/axonal remodeling.

Purpose of the Study:

  • To investigate the function of structural plasticity in enhancing memory storage capacity.
  • To define and quantify "effectual connectivity" as a measure of synaptic links within memory representations (Hebbian cell assemblies).
  • To establish the relationship between effectual connectivity, information storage, and effective connectivity used in brain imaging.

Main Methods:

  • Theoretical modeling of neural networks.
  • Numerical simulations to analyze network properties.
  • Application of a novel model to existing memory models and behavioral data.

Main Results:

  • Demonstrated a strong correlation between effectual connectivity and information storage capacity.
  • Showed the link between effectual connectivity and effective connectivity used in functional brain imaging and connectome analysis.
  • Provided improved estimates for memory cell assembly storage in cortical macrocolumns.
  • Linked adult structural plasticity to the spacing effect in learning through a simplified model.

Conclusions:

  • Structural plasticity is crucial for increasing effectual connectivity, thereby enhancing the memory storage capacity of sparsely connected neural networks.
  • The developed model provides a framework for understanding structural plasticity's role in memory and enables large-scale simulations.
  • Findings offer insights into how adult structural plasticity underlies learning phenomena like the spacing effect.