Neural signals encoding shifts in beliefs

Dopamine is implicated in a diverse range of cognitive functions including cognitive flexibility, task switching, signalling novel or unexpected stimuli as well as advance information. There is also longstanding line of thought that links dopamine with belief formation and, crucially, aberrant belief formation in psychosis. Integrating these strands of evidence would suggest that dopamine plays a central role in belief updating and more specifically in encoding of meaningful information content in observations. The precise nature of this relationship has remained unclear. To directly address this question we developed a paradigm that allowed us to decompose two distinct types of information content, information-theoretic surprise that reflects the unexpectedness of an observation, and epistemic value that induces shifts in beliefs or, more formally, Bayesian surprise. Using functional magnetic-resonance imaging in humans we show that dopamine-rich midbrain regions encode shifts in beliefs whereas surprise is encoded in prefrontal regions, including the pre-supplementary motor area and dorsal cingulate cortex. By linking putative dopaminergic activity to belief updating these data provide a link to false belief formation that characterises hyperdopaminergic states associated with idiopathic and drug induced psychosis

Density dependent strong coupling constant of QCD derived from compact star data

The present work is an endeavour to connect the properties of tiny nearly massless objects with those of some of the most massive ones, the compact stars. Since 1996 there is major influx of X-ray and $\gamma$ ray data from binary stars, one or both of which are compact objects that are difficult to explain as neutron stars since they contain a mass M in too small a radius R . The suggestion has been put forward that these are strange quark stars (SS) explainable in a simple model with chiral symmetry restoration (CSR) for the quarks and the M, R and other properties like QPOs (quasi periodic oscillations) in their X-ray power spectrum. It would be nice if this astrophysical data could shed some light on fundamental properties of quarks obeying QCD. One can relate the strong coupling constant of QCD, $\alpha_s$ to the quark mass through the Dyson-Schwinger gap equation using the real time formalism of Dolan and Jackiw. This enables us to obtain the density dependence of $\alpha_s$ from the simple CSR referred to above. This way fundamental physics, difficult to extract from other models like for example lattice QCD, can be constrained from present-day compact star data and may be put back to modelling the dense quark phase of early universe.Comment: 7 pages, 4 figure

The Dopaminergic Midbrain Encodes the Expected Certainty about Desired Outcomes

Dopamine plays a key role in learning; however, its exact function in decision making and choice remains unclear. Recently, we proposed a generic model based on active (Bayesian) inference wherein dopamine encodes the precision of beliefs about optimal policies. Put simply, dopamine discharges reflect the confidence that a chosen policy will lead to desired outcomes. We designed a novel task to test this hypothesis, where subjects played a "limited offer" game in a functional magnetic resonance imaging experiment. Subjects had to decide how long to wait for a high offer before accepting a low offer, with the risk of losing everything if they waited too long. Bayesian model comparison showed that behavior strongly supported active inference, based on surprise minimization, over classical utility maximization schemes. Furthermore, midbrain activity, encompassing dopamine projection neurons, was accurately predicted by trial-by-trial variations in model-based estimates of precision. Our findings demonstrate that human subjects infer both optimal policies and the precision of those inferences, and thus support the notion that humans perform hierarchical probabilistic Bayesian inference. In other words, subjects have to infer both what they should do as well as how confident they are in their choices, where confidence may be encoded by dopaminergic firing

Sustained Magnetic Responses in Temporal Cortex Reflect Instantaneous Significance of Approaching and Receding Sounds

Rising sound intensity often signals an approaching sound source and can serve as a powerful warning cue, eliciting phasic attention, perception biases and emotional responses. How the evaluation of approaching sounds unfolds over time remains elusive. Here, we capitalised on the temporal resolution of magnetoencephalograpy (MEG) to investigate in humans a dynamic encoding of perceiving approaching and receding sounds. We compared magnetic responses to intensity envelopes of complex sounds to those of white noise sounds, in which intensity change is not perceived as approaching. Sustained magnetic fields over temporal sensors tracked intensity change in complex sounds in an approximately linear fashion, an effect not seen for intensity change in white noise sounds, or for overall intensity. Hence, these fields are likely to track approach/recession, but not the apparent (instantaneous) distance of the sound source, or its intensity as such. As a likely source of this activity, the bilateral inferior temporal gyrus and right temporo-parietal junction emerged. Our results indicate that discrete temporal cortical areas parametrically encode behavioural significance in moving sound sources where the signal unfolded in a manner reminiscent of evidence accumulation. This may help an understanding of how acoustic percepts are evaluated as behaviourally relevant, where our results highlight a crucial role of cortical areas

Altruistic Learning

The origin of altruism remains one of the most enduring puzzles of human behaviour. Indeed, true altruism is often thought either not to exist, or to arise merely as a miscalculation of otherwise selfish behaviour. In this paper, we argue that altruism emerges directly from the way in which distinct human decision-making systems learn about rewards. Using insights provided by neurobiological accounts of human decision-making, we suggest that reinforcement learning in game-theoretic social interactions (habitisation over either individuals or games) and observational learning (either imitative of inference based) lead to altruistic behaviour. This arises not only as a result of computational efficiency in the face of processing complexity, but as a direct consequence of optimal inference in the face of uncertainty. Critically, we argue that the fact that evolutionary pressure acts not over the object of learning (‘what’ is learned), but over the learning systems themselves (‘how’ things are learned), enables the evolution of altruism despite the direct threat posed by free-riders

Distinct and Convergent Visual Processing of High and Low Spatial Frequency Information in Faces

We tested for differential brain response to distinct spatial frequency (SF) components in faces. During a functional magnetic resonance imaging experiment, participants were presented with "hybrid” faces containing superimposed low and high SF information from different identities. We used a repetition paradigm where faces at either SF range were independently repeated or changed across consecutive trials. In addition, we manipulated which SF band was attended. Our results suggest that repetition and attention affected partly overlapping occipitotemporal regions but did not interact. Changes of high SF faces increased responses of the right inferior occipital gyrus (IOG) and left inferior temporal gyrus (ITG), with the latter response being also modulated additively by attention. In contrast, the bilateral middle occipital gyrus (MOG) responded to repetition and attention manipulations of low SF. A common effect of high and low SF repetition was observed in the right fusiform gyrus (FFG). Follow-up connectivity analyses suggested direct influence of the MOG (low SF), IOG, and ITG (high SF) on the FFG responses. Our results reveal that different regions within occipitotemporal cortex extract distinct visual cues at different SF ranges in faces and that the outputs from these separate processes project forward to the right FFG, where the different visual cues may converg

Dopamine and Effort-Based Decision Making

Motivational theories of choice focus on the influence of goal values and strength of reinforcement to explain behavior. By contrast relatively little is known concerning how the cost of an action, such as effort expended, contributes to a decision to act. Effort-based decision making addresses how we make an action choice based on an integration of action and goal values. Here we review behavioral and neurobiological data regarding the representation of effort as action cost, and how this impacts on decision making. Although organisms expend effort to obtain a desired reward there is a striking sensitivity to the amount of effort required, such that the net preference for an action decreases as effort cost increases. We discuss the contribution of the neurotransmitter dopamine (DA) toward overcoming response costs and in enhancing an animal's motivation toward effortful actions. We also consider the contribution of brain structures, including the basal ganglia and anterior cingulate cortex, in the internal generation of action involving a translation of reward expectation into effortful action

Overcoming status quo bias in the human brain

Humans often accept the status quo when faced with conflicting choice alternatives. However, it is unknown how neural pathways connecting cognition with action modulate this status quo acceptance. Here we developed a visual detection task in which subjects tended to favor the default when making difficult, but not easy, decisions. This bias was suboptimal in that more errors were made when the default was accepted. A selective increase in subthalamic nucleus (STN) activity was found when the status quo was rejected in the face of heightened decision difficulty. Analysis of effective connectivity showed that inferior frontal cortex, a region more active for difficult decisions, exerted an enhanced modulatory influence on the STN during switches away from the status quo. These data suggest that the neural circuits required to initiate controlled, nondefault actions are similar to those previously shown to mediate outright response suppression. We conclude that specific prefrontal-basal ganglia dynamics are involved in rejecting the default, a mechanism that may be important in a range of difficult choice scenarios