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A growing number of individuals desire to cut down on meat consumption, yet translating this intention into action poses challenges. Self-control stra…

This genomic study of magnetic resonance imaging-based brain age in 56,348 people identifies 59 genetic loci, links brain aging to mental and physical health, and suggests high blood pressure and type 2 diabetes as causal factors of brain aging.

Longitudinal measurements of brain structure and function are critical for understanding how humans change over time. Traditional longitudinal approaches sample sparsely across large windows of time t...

We read with great interest the recent study by Gilliam-Vigh et al demonstrating significant transcriptomic alterations in the intestinal mucosa of individuals with type 2 diabetes (T2D), particularly...

Connectome-based predictive modeling (CPM) applied to functional MRI connectivity data can identify brain networks that vary with behavioral measures across subjects. The prediction strength also prov...

A 1,024-channel microelectrode array is delivered to the brain cortex via a minimally invasive incision in the skull and dura, and allows recording, stimulation and neural decoding across large portions of the brain in porcine models and human neurosurgical patients.

UCL is consistently ranked as one of the top ten universities in the world (QS World University Rankings 2010-2022) and is No.2 in the UK for research power (Research Excellence Framework 2021).

Wissenschaftlicher Mitarbeiter / Doktorand (gn*) Translationale Psychiatrie

Our Group Our newly established research group at ISTA is seeking a postdoctoral researcher to work on an ERC-funded project- HypoAdapt. We study how the brain controls bodily responses to environm...

Scientific Reports - Transformation starts at the periphery of networks where pushback is less

Neuropsychopharmacology - Dorsomedial striatal neuroinflammation causes excessive goal-directed action control by disrupting astrocyte function

A core strength of computational psychiatry is its focus on theory-driven research, in which cognitive processes are precisely quantified using computational models that formalize specific theoretical mechanisms. However, the data used in these studies often come from traditional laboratory-based cognitive tasks, which have unclear ecological validity. In this review we propose that the same theoretical frameworks and computational models can be applied to real-world data such as experience sampling, passive data, and digital-behavior data (e.g., online activity such as on social media). In turn, modeling real-world data can benefit from a theory-driven computational approach to move from purely predictive to explanatory power. We illustrate these points using emerging studies and discuss the challenges and opportunities of using real-world data in computational psychiatry.