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

Lewis Symbols and the Octet Rule02:36

Lewis Symbols and the Octet Rule

82.6K
Chemical bonds are complex interactions between two or more atoms or ions, which reduce the potential energy of the molecule. Gilbert N. Lewis developed a model called the Lewis model that simplified the depiction of chemical bond formation and provided straightforward explanations for the chemical bonds seen in most common compounds.
82.6K
Exceptions to the Octet Rule02:55

Exceptions to the Octet Rule

37.9K
Many covalent molecules have central atoms that do not have eight electrons in their Lewis structures. These molecules fall into three categories:
37.9K
The Aufbau Principle and Hund's Rule03:02

The Aufbau Principle and Hund's Rule

74.4K
To determine the electron configuration for any particular atom, we can build the structures in the order of atomic numbers. Beginning with hydrogen, and continuing across the periods of the periodic table, we add one proton at a time to the nucleus and one electron to the proper subshell until we have described the electron configurations of all the elements. This procedure is called the aufbau principle, from the German word aufbau (“to build up”). Each added electron occupies the...
74.4K
Protein Networks02:26

Protein Networks

4.6K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.6K
Midpoint Rule01:20

Midpoint Rule

73
Approximating areas under curved boundaries is a common problem in applied mathematics, particularly when an exact calculation is difficult or impractical. One effective numerical method for this purpose is the Midpoint Rule, which provides an estimate of the area under a curve by using rectangular approximations over a specified interval.Description of the Midpoint RuleThe Midpoint Rule begins by dividing the given interval into a number of equal subintervals. For each subinterval, the...
73
Trapezoidal Rule01:26

Trapezoidal Rule

64
Estimating the distance traveled by a vehicle using its recorded velocity over time is a common problem in physics and engineering. When velocity data is available at discrete time intervals, rather than as a continuous function, numerical integration methods such as the trapezoidal rule are often employed to approximate the total displacement.The trapezoidal rule works by dividing the total time interval into several equal segments. Within each segment, the recorded velocities at the endpoints...
64

You might also read

Related Articles

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

Sort by
Same author

The neurovascular impulse response function differentially reflects intrinsic neuromodulation across cortical regions.

Nature neuroscience·2026
Same author

Scientific Histories of Hippocampal Research: Introduction to the Special Issue Part 2.

Hippocampus·2026
Same author

A feature-based generalizable prediction model for both perceptual and abstract reasoning.

Cognitive neuroscience·2025
Same author

Relative phase of membrane potential theta oscillations between individual hippocampal neurons code space.

bioRxiv : the preprint server for biology·2025
Same author

Internal and external codes for location.

Nature neuroscience·2025
Same author

Cortical dissociation of spatial reference frames during place navigation.

bioRxiv : the preprint server for biology·2025
Same journal

The microlandscapes of tree trunks: the effect of lichen and tree-level characteristics on arthropod communities.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2026
Same journal

Centimetre-scale landscapes to assess the motion behaviour and cognition of gastropods and bivalves.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2026
Same journal

Intertidal microcosms of wave-swept rocky shores: ecological and physiological insights from a uniquely stressful environment.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2026
Same journal

Temporal and spatial variation in temperature and oxygen at the microscale: key niche axes for aquatic life.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2026
Same journal

Natural microcosms in ecology: fulfilling the promise of model systems?

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2026
Same journal

Microbe-induced galls and plant defence: metabolite crosstalk in a co-evolutionary battle.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2026
See all related articles

Related Experiment Video

Updated: Feb 14, 2026

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
11:18

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

Published on: June 1, 2015

11.2K

A network model of behavioural performance in a rule learning task.

Michael E Hasselmo1, Chantal E Stern2

  • 1Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Avenue, Boston, MA 02215, USA hasselmo@bu.edu.

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|February 28, 2018
PubMed
Summary
This summary is machine-generated.

This study models how neural circuit activity gating explains individual differences in cognitive rule learning and generalization. Variations in synaptic plasticity and neuromodulation, like acetylcholine, are key factors.

Keywords:
acetylcholinemuscarinic receptorsneocortexrule learning

More Related Videos

Performing Behavioral Tasks in Subjects with Intracranial Electrodes
12:10

Performing Behavioral Tasks in Subjects with Intracranial Electrodes

Published on: October 2, 2014

11.9K
Study Motor Skill Learning by Single-pellet Reaching Tasks in Mice
06:04

Study Motor Skill Learning by Single-pellet Reaching Tasks in Mice

Published on: March 4, 2014

22.3K

Related Experiment Videos

Last Updated: Feb 14, 2026

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
11:18

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

Published on: June 1, 2015

11.2K
Performing Behavioral Tasks in Subjects with Intracranial Electrodes
12:10

Performing Behavioral Tasks in Subjects with Intracranial Electrodes

Published on: October 2, 2014

11.9K
Study Motor Skill Learning by Single-pellet Reaching Tasks in Mice
06:04

Study Motor Skill Learning by Single-pellet Reaching Tasks in Mice

Published on: March 4, 2014

22.3K

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computational Neuroscience

Background:

  • Individual differences in cognitive rule learning exist and may stem from variations in neural circuit properties.
  • Neuromodulatory systems, such as cholinergic pathways, significantly impact cognitive function, yet the underlying mechanisms are not fully understood.

Purpose of the Study:

  • To present a computational model demonstrating how gating of neural activity could explain rule learning and generalization.
  • To analyze how neural circuit parameters, including synaptic modification and presynaptic inhibition, contribute to individual differences in cognitive rule learning.
  • To explore the role of neuromodulatory influences, specifically acetylcholine, in regulating these circuit parameters and their impact on context-dependent rule learning.

Main Methods:

  • Development of a computational model simulating neural circuits with activity-dependent gating.
  • Analysis of network parameters, including synaptic modification rates and presynaptic inhibition levels.
  • Investigation of how variations in these parameters, modulated by acetylcholine, affect rule learning and generalization.

Main Results:

  • The model demonstrates that gating of neural activity can underlie rule learning and generalization to novel stimuli.
  • Identified key network parameters, such as synaptic plasticity and presynaptic inhibition, that correlate with differences in rule learning performance.
  • Highlighted the potential role of acetylcholine in modulating these parameters for context-dependent rule acquisition.

Conclusions:

  • Neural circuit gating provides a plausible mechanism for cognitive rule learning and generalization.
  • Variations in neural circuit properties and neuromodulatory function, particularly acetylcholine, contribute to individual differences in cognitive abilities.
  • The model offers a framework for understanding the biological basis of individual variation in cognitive function.