We offer a formal treatment of choice behavior based on the premise that agents minimize expected free energy future outcomes. Crucially, negative or quality policy can be decomposed into extrinsic and epistemic (or intrinsic) value. Minimizing is therefore equivalent to maximizing value utility (defined in terms prior preferences goals), while information gain intrinsic reducing uncertainty about causes valuable outcomes). The resulting scheme resolves exploration-exploitation dilemma:...

Neural mechanisms for hallucinations Pairing a stimulus in one modality (vision) with another (sound) can lead to task-induced healthy individuals. After many trials, people eventually report perceiving nonexistent contingent on the presence of previously paired stimulus. Powers et al. investigated how different groups volunteers and patients respond this conditioning paradigm. They used behavior, neuroimaging, computational modeling dissect effect perceptual priors versus sensory evidence...

ORIGINAL RESEARCH article Front. Hum. Neurosci., 02 May 2011Sec. Sensory Neuroscience volume 5 - 2011 | https://doi.org/10.3389/fnhum.2011.00039

In its full sense, perception rests on an agent's model of how sensory input comes about and the inferences it draws based this model. These are necessarily uncertain. Here, we illustrate Hierarchical Gaussian Filter (HGF) offers a principled generic way to deal with several forms that uncertainty in takes. The HGF is recent derivation one-step update equations from Bayesian principles hierarchical generative environment (in)stability. It computationally highly efficient, allows for online...

This paper outlines a hierarchical Bayesian framework for interoception, homeostatic/allostatic control, and meta-cognition that connects fatigue depression to the experience of chronic dyshomeostasis. Specifically, viewing interoception as inversion generative model viscerosensory inputs allows formal definition dyshomeostasis (as chronically enhanced surprise about bodily signals, or, equivalently, low evidence brain’s states) allostasis change in prior beliefs or predictions which define...

The effects of stress are frequently studied, yet its proximal causes remain unclear. Here we demonstrate that subjective estimates uncertainty predict the dynamics and physiological responses. Subjects learned a probabilistic mapping between visual stimuli electric shocks. Salivary cortisol confirmed our stressor elicited changes in endocrine activity. Using hierarchical Bayesian learning model, quantified relationship different forms task acute Subjective stress, pupil diameter skin...

This paper revisits the dynamic causal modelling of fMRI timeseries by replacing usual (Taylor) approximation to neuronal dynamics with a neural mass model canonical microcircuit. provides generative or laminar specific responses that can generate haemodynamic and electrophysiological measurements. In principle, this allows fusion (event related induced) responses. Furthermore, it enables Bayesian comparison competing hypotheses about physiologically plausible synaptic effects; for example,...

Dopamine plays a key role in learning; however, its exact function decision making and choice remains unclear. Recently, we proposed generic model based on active (Bayesian) inference wherein dopamine encodes the precision of beliefs about optimal policies. Put simply, discharges reflect confidence that chosen policy will lead to desired outcomes. We designed novel task test this hypothesis, where subjects played "limited offer" game functional magnetic resonance imaging experiment. Subjects...

Inferring on others' (potentially time-varying) intentions is a fundamental problem during many social transactions. To investigate the underlying mechanisms, we applied computational modeling to behavioral data from an economic game in which 16 pairs of volunteers (randomly assigned “player” or “adviser” roles) interacted. The player performed probabilistic reinforcement learning task, receiving information about binary lottery visual pie chart. adviser, who received more predictive...

The COVID-19 pandemic has made the world seem less predictable. Such crises can lead people to feel that others are a threat. Here, we show initial phase of in 2020 increased individuals' paranoia and their belief updating more erratic. A proactive lockdown people's capricious. However, state-mandated mask-wearing induced erratic behaviour. This was most evident states where adherence rules poor but rule following is typically common. Computational analyses participant behaviour suggested...

Attention-deficit/hyperactivity disorder (ADHD) has been associated with deficient decision making and learning. Models of ADHD have suggested that these deficits could be caused by impaired reward prediction errors (RPEs). Reward are signals indicate violations expectations known to encoded the dopaminergic system. However, precise learning decision-making their neurobiological correlates in not well known.To determine mechanisms juvenile using advanced computational models, as related...

This paper describes an active inference scheme for visual searches and the perceptual synthesis entailed by scene construction. Active assumes that perception action minimize variational free energy, where actions are selected to energy expected in future. assumption generalizes risk-sensitive control utility theory include epistemic value; namely, value (or salience) of information inherent resolving uncertainty about causes ambiguous cues or outcomes. Here, we apply saccadic a scene. We...

Inferring the environment's statistical structure and adapting behavior accordingly is a fundamental modus operandi of brain. A simple form this faculty based on spatial attentional orienting can be studied with Posner's location-cueing paradigm in which cue indicates target location known probability. The present study focuses more complex version task, where probabilistic context (percentage validity) changes unpredictably over time, thereby creating volatile environment. Saccadic response...

Successful interaction with the environment requires flexible updating of our beliefs about world. By estimating likelihood future events, it is possible to prepare appropriate actions in advance and execute fast, accurate motor responses. According theoretical proposals, agents track variability arising from changing environments by computing various forms uncertainty. Several neuromodulators have been linked uncertainty signalling, but comprehensive empirical characterisation their...

Social learning is fundamental to human interactions, yet its computational and physiological mechanisms are not well understood. One prominent open question concerns the role of neuromodulatory transmitters. We combined fMRI, modelling genetics address this in two separate samples (N = 35, N 47). Participants played a game requiring inference on an adviser’s intentions whose motivation help or mislead changed over time. Our analyses suggest that hierarchically structured belief updates...

Paranoia is the belief that harm intended by others. It may arise from selective pressures to infer and avoid social threats, particularly in ambiguous or changing circumstances. We propose uncertainty be sufficient elicit learning differences paranoid individuals, without threat. used reversal behavior computational modeling estimate updating across individuals with mental illness, online participants, rats chronically exposed methamphetamine, an elicitor of paranoia humans. associated a...

The deployment of visuospatial attention and the programming saccades are governed by inferred likelihood events. In present study, we combined computational modeling psychophysical data with fMRI to characterize neural mechanisms underlying this flexible attentional control. Sixteen healthy human subjects performed a modified version Posner9s location-cueing paradigm in which percentage cue validity varied time targets required saccadic responses. Trialwise estimates certainty (precision)...

When casting behaviour as active (Bayesian) inference, optimal inference is defined with respect to an agent's beliefs – based on its generative model of the world. This contrasts normative accounts choice behaviour, in which actions are considered relation true structure environment opposed about worldly states (or task). distinction shifts understanding suboptimal or pathological away from aberrant such, prior a subject that cause them behave less 'optimally' than our suggest they should...

Abstract Classical economic models are predicated on the idea that ultimate aim of choice is to maximize utility or reward. In contrast, an alternative perspective highlights fact adaptive behavior requires agents’ model their environment and minimize surprise about states they frequent. We propose can be more accurately accounted for by minimization compared reward maximization alone. Minimizing makes a prediction at variance with expected models; namely, in addition attaining valuable...