Meal Pattern Analysis
Meal Pattern Analysis - Related Videos
09:05
Meal Duration as a Measure of Orofacial Nociceptive Responses in Rodents
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Cited by 3 •
2014
A lengthening in meal duration represents orofacial nociceptive behavior in rodents similar to the guarding behavior of humans with orofacial pain. Eating is a behavior that requires no training or animal manipulation, requires cortical participation, and is not competing with other experimentally induced behaviors, distinguishing this assay from alternative reflex or operant measurements.
08:09
Preparation and Testing of Plant Seed Meal-based Wood Adhesives
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Cited by 15 •
2015
To facilitate the effort in seeking more economic and environment-friendly formulations of natural product-based wood adhesives, this work demonstrates the preparation and testing of plant seed-based wood adhesives. This protocol allows one to assess plant seed-based agricultural products as suitable candidates for the substitution of synthetic-based wood adhesives.
13:51
Cross-Modal Multivariate Pattern Analysis
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Cited by 5 •
2011
Classical multivariate pattern analysis predicts sensory stimuli a subject perceives from neural activity in the corresponding cortices (e.g. visual stimuli from activity in visual cortex). Here, we apply pattern analysis cross-modally and show that sound- and touch-implying visual stimuli can be predicted from activity in auditory and somatosensory cortices, respectively.
11:46
Decoding Auditory Imagery with Multivoxel Pattern Analysis
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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...
13:44
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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Cited by 13 •
2013
We demonstrate methods for the detection of architectural distortion in prior mammograms. Oriented structures are analyzed using Gabor filters and phase portraits to detect sites of radiating tissue patterns. Each site is characterized and classified using measures to represent spiculating patterns. The methods should assist in the detection of breast cancer.
FAQs
Meal pattern analysis can reveal behavioral drivers that total intake alone may miss. By relating eating episodes to environmental cues, routines, mood, and other behaviors, researchers can examine whether eating occurs in consistent contexts or shifts with changing conditions. This makes timing and context useful variables for studying how behavior influences food choice and appetite-related patterns.
Looking beyond total food intake requires separating several dimensions of eating behavior. Analysts may compare meal timing, eating frequency, episode duration, portion patterns, and regularity rather than treating all intake as one measure. This multidimensional view can distinguish people who consume similar amounts but follow different routines, supporting more precise comparisons between individuals or experimental conditions.
Regularity provides a way to detect whether eating patterns remain stable or vary across observations. Researchers can compare this feature across people, settings, or experimental conditions and examine changes over time. Such comparisons may help identify shifts in eating behavior associated with routines, environmental circumstances, mood, or other behaviors, without assuming that total intake explains the change.
A study may use dietary records, direct observations, surveys, or digital logs, depending on the behavior and setting being examined. These sources can document eating episodes and their surrounding conditions, after which researchers organize the information into comparable pattern features. The resulting data support comparisons across individuals or experimental conditions when the study design permits.
In behavior research, the method helps connect eating patterns with environmental cues, routines, mood, and other behaviors. Researchers can use those links to investigate why food choice changes and how appetite-related patterns may be associated with particular contexts. The resulting behavioral description adds context to intervention studies and comparisons of eating behavior under different experimental conditions.
It is especially useful when a study asks whether eating behavior changes over time or differs after an intervention or between experimental conditions. Repeated pattern information can show changes in timing, frequency, duration, portion patterns, or regularity, while contextual records help interpret those changes. This supports research on appetite regulation, health-related habits, and behavioral interventions.