Open Thinking: Big data in Molecular Psychology - F1000
Open Thinking: Big data in Molecular Psychology

Open Thinking: Big data in Molecular Psychology

3 mins

F1000

Molecular Psychology: Brain, Behavior, and Society is an open research publishing Platform for scientists, scholars and clinicians working in biological mechanisms of behavior, offering rapid publication of articles and other research outputs without editorial bias. The latest collections on this Platform cover a diverse range of articles on molecular studies, ranging from behavioural and integrative neuroscience; ethics, science and society; ethology and neurothology; neuroimaging and clinical neuroscience.

We asked Dr Turhan Canli, Chief Editorial Advisor and Professor of Psychology and Psychiatry at Stony Brook University, some questions about his launch editorial, 25 years of molecular psychology, and the innovative aspects of the Molecular Psychology Platform.

You talk about a roadmap for the next decade of work in molecular psychology. What do you predict the direction of travel to be in that map?

I’m thinking South. By that, I mean that most current data in molecular psychology (as well as neuroscience, genetics, and related biological fields) are derived from study populations in high-income countries in the global North. Lower-income countries in the South, such as Africa, have missed out.

You suggest in the editorial a reboot of the candidate gene approach in molecular psychology – what you call CG 2.0. Tell us more.

I imagine a convergence of Big Science and experimental work at cellular and molecular levels of analysis. One identifies reliable associations between behavioral variables and measures of variance in structure and expression of the (epi)genome, the other examines their underlying causal mechanisms.

The editorial highlights the use of novel technologies and computational tools as a catalyst to integrate molecular data across the field. Can you say more about the opportunities and challenges of big data in molecular psychology?

The challenge is to integrate data across multiple levels of analysis, and the fact that each level represents a complex interactive network of variables/nodes/regulators. The opportunity lies in developing new analytical approaches that may interface with other areas of computational neuroscience and AI.

You also underline in the editorial the critical ethical, legal and social implications (ELSI) of molecular psychology. What has been the social impact of molecular psychology to date and where do you see the potential impact in the next decade?

One example is the use of gene-by-environment interaction data in capital murder cases. Defence lawyers have used such data as mitigating evidence (an effort that sometimes back-fired). Unfortunately, more recent data has cast doubt on the validity of these earlier results. The legal system made two errors: first, adapting science that was not yet ready to be used in the courtroom; second, not keeping up with the science that has since followed. Going forward, I hope to see a tighter integration of Neuroscience & Society, in which societal considerations enter the design of neuroscience studies (e.g.,  a concerted effort to reach underserved populations, to address stigma or other social-cultural barriers that prevent their participation into the recruitment plan) and in which training in the ethical, legal, and societal implications of neuroscience is a standard part of neuroscience traineeship.

Browse the Molecular Psychology Platform to learn more.