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

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...
Observational Learning01:12

Observational Learning

Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning because...
Associative Learning01:27

Associative Learning

Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
Brain Imaging01:14

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).
Cognition and Behavior01:23

Cognition and Behavior

Social psychology examines the complex interplay between individual mental processes and social interactions. Historically, the field was divided into two domains: social behavior and social cognition. Researchers focusing on social behavior analyzed actions within social contexts, such as conformity, aggression, or cooperation. Meanwhile, social cognition researchers investigated how people perceive, interpret, and mentally represent their social environments. However, modern perspectives no...
Inductive Reasoning00:59

Inductive Reasoning

Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...

You might also read

Related Articles

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

Sort by
Same author

MASCAF: A Cable Model Fitting Pipeline for Topologically Complex Surface Meshes.

bioRxiv : the preprint server for biology·2026
Same author

A flexible cross-correlation based population model of interaural time difference coding in barn owl's midbrain.

bioRxiv : the preprint server for biology·2026
Same author

Neural Responses Underlying Interaural Time Difference Discrimination as a Function of Sensory Reliability in the Barn Owl.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2025
Same author

Neural responses underlying ITD discrimination as a function of sensory reliability in the barn owl.

bioRxiv : the preprint server for biology·2025
Same author

Auditory Competition and Stimulus Selection across Spatial Locations from Midbrain to Forebrain in Barn Owls.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2024
Same author

Single trial Bayesian inference by population vector readout in the barn owl's sound localization system.

PloS one·2024
Same journal

Neural timescales from a computational perspective.

Nature neuroscience·2026
Same journal

Author Correction: Spinal cord Tau pathology induces tactile deficits and cognitive impairment in Alzheimer's disease via dysregulation of CCK neurons.

Nature neuroscience·2026
Same journal

Hippocampal theta sweeps indicate goal direction during navigation.

Nature neuroscience·2026
Same journal

Just how goal-directed are hippocampal theta sweeps, anyway?

Nature neuroscience·2026
Same journal

Goal-directed hippocampal theta sweeps during memory-guided navigation.

Nature neuroscience·2026
Same journal

Connectomic evidence that ordered activity drives neuromuscular network formation.

Nature neuroscience·2026
See all related articles

Related Experiment Video

Updated: May 31, 2026

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

Owl's behavior and neural representation predicted by Bayesian inference.

Brian J Fischer1, José Luis Peña

  • 1Group for Neural Theory, Département d'Etudes Cognitives, Ecole Normale Supérieure, Paris, France. bfischer.su@gmail.com

Nature Neuroscience
|July 5, 2011
PubMed
Summary
This summary is machine-generated.

Owls use a biased neural map for sound localization, prioritizing central directions for accurate prey capture. This Bayesian model explains why peripheral sound sources are underestimated, optimizing behavior for relevant ranges.

More Related Videos

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants
11:14

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

Published on: October 4, 2015

Related Experiment Videos

Last Updated: May 31, 2026

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants
11:14

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

Published on: October 4, 2015

Area of Science:

  • Neuroscience
  • Animal Behavior
  • Sensory Systems

Background:

  • Owls localize prey using auditory spatial maps.
  • The classical model of auditory space mapping does not fully explain owl behavior.
  • Owls exhibit systematic underestimation of peripheral sound source directions.

Purpose of the Study:

  • To investigate the neural mechanisms underlying owl sound localization.
  • To explain the discrepancy between classical models and observed owl behavior.
  • To propose a probabilistic model for auditory spatial representation in owls.

Main Methods:

  • Development of a Bayesian statistical inference model.
  • Analysis of owl behavior in localizing sound sources.
  • Decoding the owl's auditory spatial map using a population vector.

Main Results:

  • A Bayesian model accurately predicts owl behavior, emphasizing central sound directions.
  • A neural coding bias in auditory space enhances accuracy in the ethologically relevant range.
  • The owl's auditory map, when decoded, aligns with the behavioral model.

Conclusions:

  • Probabilistic models, specifically Bayesian inference, better describe owl sound localization.
  • A bias in neural coding optimizes auditory spatial representation for behavioral relevance.
  • The owl's map of auditory space is behaviorally optimized through a probabilistic approach.