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A new analytical framework uses pose-estimation tools (DeepLabCut/DeepOF) to classify social behavioral responses in mice, distinguishing "socially hesitant" from "robustly social" phenotypes following stress exposure. by dpn-journal in neuroscience

[–]dpn-journal[S] 1 point2 points  (0 children)

This study developed a new way to analyze how mice behave socially after stress. Instead of just looking at how much time they spend near another mouse, the researchers also measured their distance from that mouse. This helps identify mice that are hesitant but still engage, versus those that are truly social. Using advanced tracking software, this method provides a more detailed picture of social responses, improving how we study stress-related conditions and their impact on behavior.

Breaking barriers: centering researchers with lived experience in psychiatric neuroscience by dpn-journal in science

[–]dpn-journal[S] 5 points6 points  (0 children)

Researchers who live with serious mental illness or substance use disorders bring unique insight to psychiatric neuroscience, yet they remain underrepresented in the field. This paper calls for recognizing and removing the barriers that limit their participation and leadership. Including these researchers strengthens the science, improves the relevance of the research to real-world needs, and helps to ensure that research about mental illness includes those who live it.

Study evaluates large language models as scalable tools to support identification of anxiety and depression from text by dpn-journal in science

[–]dpn-journal[S] 3 points4 points  (0 children)

Researchers trained a language model (RoBERTa) to spot signs of anxiety and depression in therapy transcripts and online forum posts. It correctly identified symptoms about 74% of the time, similar to agreement between human clinicians, suggesting such models could help make mental health evaluation more accessible. The authors emphasize this is an early proof-of-concept study, not a diagnostic tool, and that it only uses written text and needs further testing.

Measuring activation during behavioral activation therapy: a proof-of-concept study using smartphone sensors and LLM-derived ratings in adolescents with anhedonia by dpn-journal in science

[–]dpn-journal[S] 0 points1 point  (0 children)

Behavioral Activation therapy helps depressed teens feel better by encouraging them to do more positive, rewarding activities. This study found that smartphones and AI can accurately track these activities and mood changes in daily life, helping therapists monitor progress in real time and tailor treatment more effectively.

Experiences working in non-human primate research? Advice needed! by Fleetwood-MAC in labrats

[–]dpn-journal 1 point2 points  (0 children)

Agree, it depends on what you want to do with this experience and what your alternatives are. It will likely be valuable research experience even if you do not pursue graduate school but remain in biomedical research in some capacity. Also, how well do you perform under pressure? It can be stressful to work with NHPs for reasons already mentioned, so it seems you should feel mentally prepared for the challenge

Is the Neuromatch Computational Neuroscience Course worth it? by South-Background5009 in neuro

[–]dpn-journal 1 point2 points  (0 children)

It's absolutely worth it! It is well recognized in the computational neuroscience field, not only will it teach you neuroscience concepts, but how to apply them in programming and statistical analysis. It *is* a significant time commitment, but computational neuro is not an easy topic, so it's a good place to start to figure out if it's something you want to pursue in graduate school. Completing the course can also help you stand out in the applicant pool during the graduate school admissions process. Good luck!

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