Behavioral Neuroscience in the Era of Genomics: Tools and Lessons for Analyzing High-Dimensional Datasets

Behavioral neuroscience underwent a technology-driven revolution with the emergence of machine-vision and machine-learning technologies. These technological advances facilitated the generation of high-resolution, high-throughput capture and analysis of complex behaviors. Therefore, behavioral neuros...

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Bibliographic Details
Published in:International journal of molecular sciences 2022-03, Vol.23 (7), p.3811
Main Authors: Bentzur, Assa, Alon, Shahar, Shohat-Ophir, Galit
Format: Article
Language:English
Subjects:
Algorithms
Animals
Behavior
Datasets
Dimensional analysis
Experiments
Genomics
Genomics - methods
Group dynamics
Machine vision
Massive data points
Nervous system
Neurosciences
Proteomics
Review
Social networks
Software
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Summary:Behavioral neuroscience underwent a technology-driven revolution with the emergence of machine-vision and machine-learning technologies. These technological advances facilitated the generation of high-resolution, high-throughput capture and analysis of complex behaviors. Therefore, behavioral neuroscience is becoming a data-rich field. While behavioral researchers use advanced computational tools to analyze the resulting datasets, the search for robust and standardized analysis tools is still ongoing. At the same time, the field of genomics exploded with a plethora of technologies which enabled the generation of massive datasets. This growth of genomics data drove the emergence of powerful computational approaches to analyze these data. Here, we discuss the composition of a large behavioral dataset, and the differences and similarities between behavioral and genomics data. We then give examples of genomics-related tools that might be of use for behavioral analysis and discuss concepts that might emerge when considering the two fields together.
ISSN:1422-0067
1661-6596
1422-0067
DOI:10.3390/ijms23073811