Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Response Surface Methodology

Response Surface Methodology

Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:

Molecular Models

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.

The Bohr Model

The Bohr Model

Following the work of Ernest Rutherford and his colleagues in the early twentieth century, the picture of atoms consisting of tiny dense nuclei surrounded by lighter and even tinier electrons continually moving about the nucleus was well established. This picture was called the planetary model since it pictured the atom as a miniature “solar system” with the electrons orbiting the nucleus like planets orbiting the sun. The simplest atom is hydrogen, consisting of a single proton as the...

The Fluid Mosaic Model

The Fluid Mosaic Model

The fluid mosaic model was first proposed as a visual representation of research observations. The model comprises the composition and dynamics of membranes and serves as a foundation for future membrane-related studies. The model depicts the structure of the plasma membrane with a variety of components, which include phospholipids, proteins, and carbohydrates. These integral molecules are loosely bound, defining the cell’s border and providing fluidity for optimal function.

Responses to Drought and Flooding

Responses to Drought and Flooding

Water plays a significant role in the life cycle of plants. However, insufficient or excess of water can be detrimental and pose a serious threat to plants.

Stereotype Content Model

Stereotype Content Model

The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...

You might also read

Related Articles

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

Sort by

Same author

Bridging Bayesian and representational theories of memory to predict memory bias.

Journal of experimental psychology. General·2026

Same author

The Target Confusability Competition ensemble model predicts full feature distribution reports.

Psychonomic bulletin & review·2026

Same author

Attraction and repulsion in perception and working memory as complementary outcomes of learning.

Current opinion in neurobiology·2026

Same author

Similarity-driven compression during encoding supports biased but more precise working memory.

Journal of vision·2026

Same author

Chunking, Attraction, Repulsion, and Ensemble Effects Are Ubiquitous in Visual Working Memory.

Open mind : discoveries in cognitive science·2026

Same author

Investigating the reproducibility of the social and behavioural sciences.

Nature·2026

Same journal

Another 10 years of PLOS Computational Biology: A data-driven reflection on trends in genomics research.

PLoS computational biology·2026

Same journal

Mobility data resolution needed to inform predictive models of spatial epidemic spread from mobile phone data.

PLoS computational biology·2026

Same journal

DeepMethylation: A deep learning framework for tissue-specific DNA methylation prediction and functional variant annotation.

PLoS computational biology·2026

Same journal

Redefining and estimating the early-phase reproduction ratio for epidemic outbreaks in spatially structured populations.

PLoS computational biology·2026

Same journal

Optimized phenotype definitions boost GWAS power.

PLoS computational biology·2026

Same journal

Detection, communication, and individual identification with deep audio embeddings: A case study with North Atlantic right whales.

PLoS computational biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Feb 4, 2026

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding

Published on: August 22, 2016

A 2D Gabor-wavelet baseline model out-performs a 3D surface model in scene-responsive cortex.

Anna Shafer-Skelton^1,2,3, Timothy F Brady¹, John T Serences^1,4

¹Department of Psychology, University of California, San Diego, La Jolla, California, United States of America.

Plos Computational Biology

|February 2, 2026

Summary

This summary is machine-generated.

A new study found that low-level visual features, like spatial frequency and orientation, better explain brain activity in scene-selective areas than 3D surface models. This challenges previous assumptions about how the brain processes complex spatial information.

More Related Videos

Author Spotlight: Enhancing Skin Model Diversity with Cost-Effective 3D Cellular Models

Author Spotlight: Enhancing Skin Model Diversity with Cost-Effective 3D Cellular Models

Published on: October 20, 2023

2D and 3D Echocardiography in the Axolotl Ambystoma Mexicanum

2D and 3D Echocardiography in the Axolotl Ambystoma Mexicanum

Published on: November 29, 2018

Related Experiment Videos

Last Updated: Feb 4, 2026

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding

Published on: August 22, 2016

Author Spotlight: Enhancing Skin Model Diversity with Cost-Effective 3D Cellular Models

Author Spotlight: Enhancing Skin Model Diversity with Cost-Effective 3D Cellular Models

Published on: October 20, 2023

2D and 3D Echocardiography in the Axolotl Ambystoma Mexicanum

2D and 3D Echocardiography in the Axolotl Ambystoma Mexicanum

Published on: November 29, 2018

Area of Science:

Vision science
Computational neuroscience
Cognitive psychology

Background:

Understanding 3D representations of spatial information in natural scenes is a challenge.
Disentangling high-level 3D information from low-level features like spatial frequency and orientation is difficult.
Model-comparison frameworks are used to analyze visual processing in scene-selective brain regions.

Purpose of the Study:

To test if previous findings on 3D-surface features in scene-selective areas generalize to a new stimulus set.
To investigate whether low-level visual features or 3D-surface features better explain neural responses in OPA, PPA, and MPA/RSC.
To re-evaluate the role of "scene-selective" areas in processing 3D spatial information.

Main Methods:

Used a model-comparison framework with novel stimuli designed to dissociate Gabor-wavelet features from 3D scene-surface features.
Compared the explanatory power of a Gabor-wavelet baseline model against a 3D-surface model for voxel responses in specific visual cortex areas.
Analyzed neural data from human participants viewing naturalistic scene stimuli.

Main Results:

A Gabor-wavelet model (low-level, 2D) provided a better fit to voxel responses in OPA, PPA, and MPA/RSC than a 3D-surface model.
Contrary to prior research, low-level visual features explained more variance in these scene-selective areas.
The findings suggest that spatial frequency and orientation information may be more critical than previously thought for representing 3D scene properties.

Conclusions:

The information processed in scene-selective regions might be predominantly in the form of low-level spatial frequency and orientation.
Differences in baseline models across studies may explain conflicting results regarding 3D-surface representation.
Further research is needed to disentangle low-level and high-level visual information processing and understand how real-world visual properties are cued.