Decyder Analysis
Decyder Analysis - Related Videos
11:46
Decoding Auditory Imagery with Multivoxel Pattern Analysis
0 Views •
2023
Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel—University of Southern California Imagine the sound of a bell ringing. What is happening in the brain when we conjure up a sound like this in the "mind's ear?" There is growing evidence that the brain uses the same mechanisms for imagination that it uses for perception.1 For example, when imagining visual images, the visual cortex becomes activated, and when imagining sounds, the auditory cortex is engaged. However, to what extent are...
08:00
Decoding Natural Behavior from Neuroethological Embedding
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2025
This protocol gives an integrated framework based on advanced computational neuroethological methods to understand brain coding in naturalistic contexts.
11:14
A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants
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Cited by 3 •
2015
This protocol presents a novel methodology for the neural decoding of intent from freely-behaving infants during unscripted social interaction with an actor. Neural activity is acquired using non-invasive high-density active scalp electroencephalography (EEG). Kinematic data is collected with inertial measurement units and supplemented with synchronized video recording.
06:33
Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
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Cited by 10 •
2018
Here we present a protocol for decomposing the variance in reading comprehension into the unique and common effects of language and decoding.
05:36
STFEEG-Tool: A Spatial-Temporal-Frequency EEG Analysis Tool for Motor Imagery Brain-Computer Interfaces
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2026
This study presents a standardized and reproducible protocol for implementing the Spatial-Temporal-Frequency EEG analysis tool (STFEEG) for motor imagery EEG decoding, incorporating configurable spatial-temporal-frequency segmentation, Common Spatial Patterns (CSP)-based feature extraction, multiple classification algorithms, and visualization capabilities.
FAQs
The internal standard supplies a reference for normalizing fluorescent signal intensities across samples and gels. This gives protein abundance measurements a common basis for comparison rather than relying only on raw spot intensity. As a result, researchers can assess relative expression differences more consistently when analyzing biological samples in comparative protein-profiling experiments.
The software detects fluorescent protein spots in the gel images and matches corresponding spots between gels. This matching step links signals that represent the same protein feature across different samples, allowing their abundance values to be compared. Reliable correspondence is essential for interpreting whether an observed difference reflects altered protein expression between biological conditions.
After spot detection, matching, and normalization, DeCyder Analysis applies statistical evaluation to the measured abundance values. This identifies differences considered statistically significant rather than treating every numerical change as meaningful. The resulting comparisons help researchers focus on protein-expression patterns that may be relevant to disease, treatment, or environmental responses.
A typical workflow begins with fluorescent spot detection in 2D-DIGE gel images, followed by matching corresponding spots across gels. Signal intensities are then normalized against an internal standard, and the resulting measurements are evaluated for statistically significant expression differences. This sequence converts image data into quantitative results suitable for comparative protein analysis.
Researchers can apply the method when they need to compare protein abundance across biological samples exposed to different conditions. Supported use cases include examining disease-associated changes, treatment responses, and effects of environmental change. The analysis can also contribute to biomarker discovery by highlighting proteins whose measured expression differs significantly between compared sample groups.
DeCyder Analysis produces quantitative measurements from complex 2D-DIGE gel images, including normalized abundance values and statistically assessed expression differences. These outputs support comparative protein profiling and help investigators interpret cellular responses under contrasting biological conditions. In proteomics research, the results can guide the identification of expression patterns relevant to disease, treatment, or environmental change.