Matthew E. Sachs

Brain and Creativity Institute
3620A McClintock Ave
Los Angeles,CA 90089
USA

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Research interests

Real-time emotional and aesthetic experiences in the brain

Human's uniquely experience certain intense emotions, particularly in response to music, films, and narratives. Using neuroimaging, psychophysiological measures, and continuous self-reports, I work to uncover brain networks associated with aesthetic experiences, such as getting "chills" (Sachs et al. 2016), deriving pleasure from sadness (Sachs et al. 2016), and feelings nostalgic. I've also focused on understanding what is different about the patterns and structure of the brain in people who do not or cannot experience emotions, particularly to music (Loui et al. 2017).

 

My dissertation project involves investigating the time-varying patterns of neural activity that are associated with changes in intensity of emotions and enjoyment while listening to full-length pieces of sad music.  

Musical emotions and machine learning

With machine learning algorithms applied to neuroimaging data (multivoxel pattern analysis), we can predict various mental states and decode representational content from patterns of fMRI signal, particularly with regards to emotional experiences in response to music and the human voice (Sachs et al., 2017).

Outside of neuroimaging, I like exploring the large amount of publicly available data on how people consume and respond to music. Scraping information from social media sites like Last.FM and Spotify, acoustical information from music databases like Echonest, and online music reviews from Pitchfork, I can use natural language processing and classification algorithms to predict how listeners respond to certain pieces of music and the emotions that a piece of music is likely to induce. Most of the data are preliminary, but I have made the code I use available on my Github page.

Neurodevelopment of brain networks

How do early childhood experiences influence the structure and function of the human brain? Using longitudinal methods and both resting-state and task-based fMRI, we can asses how particular brain networks related to cognitive and social functioning are enhanced by early childhood training, such as music and sports (Sachs et al. 2017), as well as attenuated by neurodevelopmental disorders, such as autism specturm disorder, ADHD, and adolescent aggression (Saxbe et al. 2017).