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  Advancing social behavioral neuroscience by integrating ethology and comparative psychology methods through machine learning

Bordes, J., Miranda, L., Mueller-Myhsok, B., & Schmidt, M. V. (2023). Advancing social behavioral neuroscience by integrating ethology and comparative psychology methods through machine learning. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 151: 105243. doi:10.1016/j.neubiorev.2023.105243.

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 Creators:
Bordes, Joeri1, Author           
Miranda, Lucas2, 3, Author           
Mueller-Myhsok, Bertram3, Author           
Schmidt, Mathias V.1, Author           
Affiliations:
1RG Stress Resilience, Max Planck Institute of Psychiatry, Max Planck Society, ou_2040294              
2IMPRS Translational Psychiatry, Max Planck Institute of Psychiatry, Max Planck Society, ou_3318616              
3RG Statistical Genetics, Max Planck Institute of Psychiatry, Max Planck Society, ou_2040288              

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 Abstract: Social behavior is naturally occurring in vertebrate species, which holds a strong evolutionary component and is crucial for the normal development and survival of individuals throughout life. Behavioral neuroscience has seen different influential methods for social behavioral phenotyping. The ethological research approach has extensively investigated social behavior in natural habitats, while the comparative psychology approach was developed utilizing standardized and univariate social behavioral tests. The development of advanced and precise tracking tools, together with post-tracking analysis packages, has recently enabled a novel behavioral phenotyping method, that includes the strengths of both approaches. The implementation of such methods will be beneficial for fundamental social behavioral research but will also enable an increased understanding of the influences of many different factors that can influence social behavior, such as stress exposure. Furthermore, future research will increase the number of data modalities, such as sensory, physiological, and neuronal activity data, and will thereby significantly enhance our understanding of the biological basis of social behavior and guide intervention strategies for behavioral abnormalities in psychiatric disorders.

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 Dates: 2023
 Publication Status: Published online
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Title: NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
Source Genre: Journal
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Pages: - Volume / Issue: 151 Sequence Number: 105243 Start / End Page: - Identifier: ISSN: 0149-7634