Recent years have seen a rapid increase in the number of studies using evidence-
accumulation models (such as the drift diffusion model, DDM) in the fields of psychology and …

The last 25 years have shown a steady increase in attention for the Bayes factor as a tool for
hypothesis evaluation and model selection. The present review highlights the potential of …

Inhibitory control is one of the most important control functions in the human brain. Much of
our understanding of its neural basis comes from seminal work showing that lesions to the …

Inferring parameters of computational models that capture experimental data is a central
task in cognitive neuroscience. Bayesian statistical inference methods usually require the …

Evidence accumulation models (EAMs) have been the dominant models of speeded
decision-making for several decades. These models propose that evidence accumulates for …

For many years the Diffusion Decision Model (DDM) has successfully accounted for
behavioral data from a wide range of domains. Important contributors to the DDM's success …

Behavioural disinhibition is a common feature of the syndromes associated with
frontotemporal lobar degeneration (FTLD). It is associated with high morbidity and lacks …

In cognitive neuroscience, computational modeling can formally adjudicate between
theories and affords quantitative fits to behavioral/brain data. Pragmatically, however, the …

Cognitive decline is a common feature of Parkinson's disease, and many of these cognitive
deficits fail to respond to dopaminergic therapy. Therefore, targeting other neuromodulatory …

While decision theories have evolved over the past five decades, their focus has largely
been on choices among a limited number of discrete options, even though many real-world …