Reading room

A provocative case for treating brain areas as one organizing principle among gradients, distributed networks, layers, columns, and patches—and for rethinking how neuroscience links structure to cognitive function.

Repeated measurement reveals meaningful differences in parameter stability and systematic temporal change—a strong bridge across computational psychiatry, individual differences, and decision science.

A shared vocabulary for latent states, evidence accumulation, neural dynamics, and psychiatric phenotypes.

A clean computational-psychiatry example that separates variability in learning from variability in choice.

An integrative treatment of schemas, latent states, reinforcement learning, memory, and medial prefrontal function.

A cross-species account of information value, reward, uncertainty, exploration, and lateral habenula.

An entry point into richer representations of outcome distributions, risk-sensitive behavior, and individual differences.

A discussion starter for model-based cognition, representation, planning, and when different computational strategies are rational.

A practical anchor for neural model identification, parameter estimation, calibration, recovery, generalization, and failure modes.

Directly relevant background for a hands-on neural and simulation-based inference workshop.

Useful for diagnostics, identifiability, posterior uniqueness, and the broader logic of simulation-based inference.

How formal properties of a decision problem shape effortful deliberation and behavior.

A neuroimaging-focused discussion of valuation, attention, and goal-directed behavior.

Connects decision-making with control, representational geometry, and multivariate fMRI.

A perspective on richer tasks, ecological validity, large-scale behavioral data, and new experimental paradigms.