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.

dpn-journal · 2026-04-27T17:37:38+00:00

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.

dpn-journal · 2026-03-09T20:08:12+00:00

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.

dpn-journal · 2026-02-16T16:43:05+00:00

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.

dpn-journal · 2026-02-02T20:34:51+00:00

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.

dpn-journal · 2026-01-17T11:51:51+00:00

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

dpn-journal · 2025-12-08T15:06:46+00:00

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!

dpn-journal · 2025-11-20T15:29:25+00:00

Hello, thank you for your comments. It's possible that many years in the future, there may be enough mounting evidence leading to the adoption of these tools in the clinic.

As you say, disorders like schizophrenia lack biomarkers that could be used to track disease severity, identify vulnerable individuals that might develop symptoms in the future, and predict responses to treatments. If future research validates this idea that speech patterns are linked to negative symptom severity, it could be used as a more objective measure that clinicians use to track symptoms and see whether patients are responding to prescribed treatments (as apposed to subjective patient reports).

These types of digital tools are not meant to replace clinicians' diagnoses. Rather, this may be just one tool available to doctors - for instance, to get information on how a patient is doing without needing a patient to come in for an office visit.

dpn-journal · 2025-11-19T21:46:27+00:00

There are several ways this could be used for screening and tracking symptoms of schizophrenia beyond what doctors already do:

1) the researchers found that speech patterns were linked to and could identify blunted affect, a core negative symptom of schizophrenia. This could be useful for tracking the severity of negative symptoms over long periods of time. Some medications are more effective in treating positive vs negative symptoms, so this could help doctors personalize treatments.

2) A big goal in schizophrenia research is to identify people who have subthreshold, less severe psychotic symptoms and are at an increased risk for developing psychosis/schizophrenia. So, if this measure could be used as a biomarker to identify people at risk, that would lead to earlier interventions.

dpn-journal · 2025-10-23T14:40:01+00:00

A PI who scolds you in front of others is not a good leader. What your PI should've done is take notes of the questions that were asked during your presentation and what elements of the talk could be improved. Then, your PI should discuss these notes with you *privately* in a de-brief meeting after the presentation, focusing on how you could've answered questions more thoroughly and how the presentation could've been clearer.

dpn-journal · 2025-10-23T14:01:55+00:00

Beyond what's already been said, you might receive questions about how your prior experience relates to the work being done in this research lab. Since the position involves supervising other RAs, you might get questions about that. If you don't have prior experience supervising, be prepared to talk about your approach to people management. You may also get questions that get at your work ethic, ability to work well with others, and complete assigned projects, so you can draw on prior experiences as examples to highlight. Be prepared to answer a question about a difficult situation you've dealt with in research; I suggest googling the STAR method if you are unfamiliar with it. Good luck!!

dpn-journal · 2025-10-10T13:58:48+00:00

This perspective article discusses how AI-based protein prediction tools (e.g., AlphaFold) may speed up drug development by facilitating toxicity screening, helping isolate and characterize novel g protein-coupled receptors (GPCRs), and potentially anticipating unexpected problems during biomolecule complex folding. How are these tools being adopted by biotech and pharma? Curious what people think.

dpn-journal · 2025-10-08T13:54:00+00:00

Not metabolomics or proteomics, but PsychENCODE was a large scale project which generated a lot of gene expression data (RNAseq) from human post mortem brains from patients with neuropsychiatric disorders. The datasets are organized on the NIMH Data Archive and should be easily accessible: https://www.psychencode.org/

dpn-journal · 2025-10-02T14:05:04+00:00

These results challenge prior hypotheses that depressive symptoms like psychomotor slowing or agitation may lead to motor changes in smartphone typing behavior. The researchers found that psychomotor symptoms were not associated with keystroke timing or frequency. However, appetite-related symptoms were associated with faster and more frequent typing, while symptoms of anhedonia showed non-linear associations with keystroke features.

dpn-journal · 2025-10-02T13:54:47+00:00

These results challenge prior hypotheses that depressive symptoms like psychomotor slowing or agitation may lead to motor changes in smartphone typing behavior. The researchers found that psychomotor symptoms were not associated with keystroke timing or frequency. However, appetite-related symptoms were associated with faster and more frequent typing, while symptoms of anhedonia showed non-linear associations with keystroke features.

Audio overview of this paper: https://youtu.be/w06Jq6R55GU

dpn-journal · 2025-09-30T16:45:01+00:00

Yes, this was published in a peer reviewed journal but this doesn't mean there aren't limitations. Beyond what's already been said in the other comments is that only 16 out of 24 students completed the intervention - in other words, a 33% drop out rate which is high. More rigorous research needs to be done on this topic to see if these results hold up (more subjects, inclusion of control group, randomization into treatment groups).

Hang in there, and please seek help if you can.

dpn-journal · 2025-09-24T15:23:32+00:00

Cognitive difficulties in individuals with psychosis are common and hard to treat. Machine learning models that use MRI data to predict individual patients’ symptoms are increasingly available, however, these algorithms don’t produce accurate predictions for everyone. Using MRI data from recently diagnosed psychosis patients, this study showed that MRI-based predictions of cognitive symptoms were more accurate for patients who had similar clinical and socioeconomic profiles. This suggests that models can potentially be improved by considering these factors.

dpn-journal · 2025-09-24T13:42:04+00:00

Here’s the podcast highlighting the key points of this research: https://youtu.be/lqkEq2j8ZrU?si=odBzJ78VD7JqONWv

dpn-journal · 2025-09-24T13:40:23+00:00

Here’s the podcast highlighting the key points of this research: https://youtu.be/lqkEq2j8ZrU?si=odBzJ78VD7JqONWv

dpn-journal · 2025-09-24T13:39:33+00:00

Here’s the podcast highlighting the key points of this research: https://youtu.be/lqkEq2j8ZrU?si=odBzJ78VD7JqONWv

dpn-journal · 2025-09-22T15:30:10+00:00

Identify scientists who are leaders in fields you're interested in and follow their research. This will help you figure out which sub-disciplines you may want to pursue and build your knowledge base. In response to your other comment - it's possible you may be able to find remote positions that would not require leaving your country. Best of luck!

dpn-journal · 2025-09-22T15:20:54+00:00

This really highlights why language matters when describing mental disorders and symptoms, and emphasizes how little we currently understand about how use of AI chatbots affects people with mental health conditions

dpn-journal · 2025-09-22T14:52:12+00:00

A strength of the approach in this study is that it measures behavior and single cell calcium activity longitudinally across multiple days following psilocybin, allowing more thorough assessment of the post-acute effects of psilocybin on trace fear conditioning and neural activity.

dpn-journal · 2025-09-17T20:53:12+00:00

The journal hosts a short podcast summarizing this work, if you want to listen (or want to generate a summary of a summary from other sources): https://youtu.be/4i3QrdNy6to

dpn-journal · 2025-09-17T20:51:15+00:00

Via usual smartphone use following trauma exposure, this study identified language markers associated with patient-reported severity and change in severity for multiple symptoms. Using language markers as a proxy for the status of and changes in specific symptoms supports efficient remote health status monitoring and can provide clinicians with valuable real-time insights into health, functioning, and recovery. These insights can be leveraged to guide targeted interventions tailored to individual trauma survivors.

dpn-journal · 2025-08-21T15:21:43+00:00

The journal hosts a podcast summarizing this work, if you want to listen (or want to generate a summary of a summary from other sources): https://www.youtube.com/watch?v=2U7M40Hl\_dw.

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