Opportunity cost determines free-operant action initiation latency and predicts apathy.

Background: Apathy, a disabling and poorly understood neuropsychiatric symptom, is characterised by impaired self-initiated behaviour. It has been hypothesised that the (OCT) may be a key computational variable linking self-initiated behaviour with motivational status. OCT represents the amount of reward which is foregone per second if no action is taken.

Learning to use past evidence in a sophisticated world model.

Humans and other animals are able to discover underlying statistical structure in their environments and exploit it to achieve efficient and effective performance. However, such structure is often difficult to learn and use because it is obscure, involving long-range temporal dependencies. Here, we analysed behavioural data from an extended experiment with rats, showing that the subjects learned the underlying statistical structure, albeit suffering at times from immediate inferential imperfections as to their current state within it.

Some work and some play: microscopic and macroscopic approaches to labor and leisure.

Given the option, humans and other animals elect to distribute their time between work and leisure, rather than choosing all of one and none of the other. Traditional accounts of partial allocation have characterised behavior on a macroscopic timescale, reporting and studying the mean times spent in work or leisure. However, averaging over the more microscopic processes that govern choices is known to pose tricky theoretical problems, and also eschews any possibility of direct contact with the neural computations involved.

Optimal indolence: a normative microscopic approach to work and leisure.

Dividing limited time between work and leisure when both have their attractions is a common everyday decision. We provide a normative control-theoretic treatment of this decision that bridges economic and psychological accounts. We show how our framework applies to free-operant behavioural experiments in which subjects are required to work (depressing a lever) for sufficient total time (called the price) to receive a reward.

Dynamic excitatory and inhibitory gain modulation can produce flexible, robust and optimal decision-making.

Behavioural and neurophysiological studies in primates have increasingly shown the involvement of urgency signals during the temporal integration of sensory evidence in perceptual decision-making. Neuronal correlates of such signals have been found in the parietal cortex, and in separate studies, demonstrated attention-induced gain modulation of both excitatory and inhibitory neurons. Although previous computational models of decision-making have incorporated gain modulation, their abstract forms do not permit an understanding of the contribution of inhibitory gain modulation.

Acquisition of decision making criteria: reward rate ultimately beats accuracy.

Speed-accuracy trade-offs strongly influence the rate of reward that can be earned in many decision-making tasks. Previous reports suggest that human participants often adopt suboptimal speed-accuracy trade-offs in single session, two-alternative forced-choice tasks. We investigated whether humans acquired optimal speed-accuracy trade-offs when extensively trained with multiple signal qualities.

Learning-rate-dependent clustering and self-development in a network of coupled phase oscillators.

We investigate the role of the learning rate in a Kuramoto Model of coupled phase oscillators in which the coupling coefficients dynamically vary according to a Hebbian learning rule. According to the Hebbian theory, a synapse between two neurons is strengthened if they are simultaneously coactive. Two stable synchronized clusters in antiphase emerge when the learning rate is larger than a critical value.