Ergodicity-breaking reveals time optimal decision making in humans.

Ergodicity describes an equivalence between the expectation value and the time average of observables. Applied to human behaviour, ergodic theories of decision-making reveal how individuals should tolerate risk in different environments. To optimize wealth over time, agents should adapt their utility function according to the dynamical setting they face. Linear utility is optimal for additive dynamics, whereas logarithmic utility is optimal for multiplicative dynamics. Whether humans approximate time optimal behavior across different dynamics is unknown. Here we compare the effects of additive versus multiplicative gamble dynamics on risky choice. We show that utility functions are modulated by gamble dynamics in ways not explained by prevailing decision theories. Instead, as predicted by time optimality, risk aversion increases under multiplicative dynamics, distributing close to the values that maximize the time average growth of in-game wealth. We suggest that our findings motivate a need for explicitly grounding theories of decision-making on ergodic considerations.

Extending models of "How Foraging Works": Uncertainty, controllability, and survivability.

We argue that How Foraging Works sketches a good foundational model, but it needs expanding to incorporate hierarchical and multiscale conceptions of uncertainty and to incorporate inference of environmental controllability. Most pressingly, its algorithmic implementation needs to be better justified in terms of its functional forms and, ultimately, to be more heavily constrained by survival optimality.

Motivational tuning of fronto-subthalamic connectivity facilitates control of action impulses.

It is critical for survival to quickly respond to environmental stimuli with the most appropriate action. This task becomes most challenging when response tendencies induced by relevant and irrelevant stimulus features are in conflict, and have to be resolved in real time. Inputs from the pre-supplementary motor area (pre-SMA) and inferior frontal gyrus (IFG) to the subthalamic nucleus (STN) are thought to support this function, but the connectivity and causality of these regions in calibrating motor control has not been delineated. In this study, we combined off-line noninvasive brain stimulation and functional magnetic resonance imaging, while young healthy human participants performed a modified version of the Simon task. We show that impairing pre-SMA function by noninvasive brain stimulation improved control over impulsive response tendencies, but only when participants were explicitly rewarded for fast and accurate responses. These effects were mediated by enhanced activation and connectivity of the IFG-STN pathway. These results provide causal evidence for a pivotal role of the IFG-STN pathway during action control. Additionally, they suggest a parallel rather than hierarchical organization of the pre-SMA-STN and IFG-STN pathways, since interruption of pre-SMA function can enhance IFG-STN connectivity and improve control over inappropriate responses.

Levodopa reinstates connectivity from prefrontal to premotor cortex during externally paced movement in Parkinson's disease.

Dopamine deficiency affects functional integration of activity in distributed neural regions. It has been suggested that lack of dopamine induces disruption of neural interactions between prefrontal and premotor areas, which might underlie impairment of motor control observed in patients with Parkinson's disease (PD). In this study we recorded cortical activity with high-density electroencephalography in 11 patients with PD as a pathological model of dopamine deficiency, and 13 healthy control subjects. Participants performed repetitive extension-flexion movements of their right index finger, which were externally paced at a rate of 0.5 Hz. This required participants to align their movement velocity to the slow external pace. Patients were studied after at least 12-hour withdrawal of dopaminergic medication (OFF state) and after intake of the dopamine precursor levodopa (ON state) in order to examine oscillatory coupling between prefrontal and premotor areas during respectively low and high levels of dopamine. In 10 patients and 12 control participants multiple source beamformer analysis yielded task-related activation of a contralateral cortical network comprising prefrontal cortex (PFC), lateral premotor cortex (lPM), supplementary motor area (SMA) and primary motor cortex (M1). Dynamic causal modelling was used to characterize task-related oscillatory coupling between prefrontal and premotor cortical areas. Healthy participants showed task-induced coupling from PFC to SMA, which was modulated within the γ-band. In the OFF state, PD patients did not express any frequency-specific coupling between prefrontal and premotor areas. Application of levodopa reinstated task-related coupling from PFC to SMA, which was expressed as high-ß-γ coupling. Additionally, strong within-frequency γ-coupling as well as cross-frequency θ-γ coupling was observed from PFC to lPM. Enhancement of this cross-frequency θ-γ coupling after application of levodopa was positively correlated with individual improvement in motor function. The results demonstrate that dopamine deficiency impairs the ability to establish oscillatory coupling between prefrontal and premotor areas during an externally paced motor task. Application of extrinsic dopamine in PD patients reinstates physiological prefrontal-premotor coupling and additionally induces within- and cross-frequency coupling from prefrontal to premotor areas, which is not expressed in healthy participants.

Sparse encoding of automatic visual association in hippocampal networks.

Intelligent action entails exploiting predictions about associations between elements of ones environment. The hippocampus and mediotemporal cortex are endowed with the network topology, physiology, and neurochemistry to automatically and sparsely code sensori-cognitive associations that can be reconstructed from single or partial inputs. Whilst acquiring fMRI data and performing an attentional task, participants were incidentally presented with a sequence of cartoon images. By assigning subjects a post-scan free-association task on the same images we assayed the density of associations triggered by these stimuli. Using multivariate Bayesian decoding, we show that human hippocampal and temporal neocortical structures host sparse associative representations that are automatically triggered by visual input. Furthermore, as predicted theoretically, there was a significant increase in sparsity in the Cornu Ammonis subfields, relative to the entorhinal cortex. Remarkably, the sparsity of CA encoding correlated significantly with associative memory performance over subjects; elsewhere within the temporal lobe, entorhinal, parahippocampal, perirhinal and fusiform cortices showed the highest model evidence for the sparse encoding of associative density. In the absence of reportability or attentional confounds, this charts a distribution of visual associative representations within hippocampal populations and their temporal lobe afferent fields, and demonstrates the viability of retrospective associative sampling techniques for assessing the form of reflexive associative encoding.

Attenuated neural response to gamble outcomes in drug-naive patients with Parkinson's disease.

Parkinson's disease results from the degeneration of dopaminergic neurons in the substantia nigra, manifesting as a spectrum of motor, cognitive and affective deficits. Parkinson's disease also affects reward processing, but disease-related deficits in reinforcement learning are thought to emerge at a slower pace than motor symptoms as the degeneration progresses from dorsal to ventral striatum. Dysfunctions in reward processing are difficult to study in Parkinson's disease as most patients have been treated with dopaminergic drugs, which sensitize reward responses in the ventral striatum, commonly resulting in impulse control disorders. To circumvent this treatment confound, we assayed the neural basis of reward processing in a group of newly diagnosed patients with Parkinson's disease that had never been treated with dopaminergic drugs. Thirteen drug-naive patients with Parkinson's disease and 12 healthy age-matched control subjects underwent whole-brain functional magnetic resonance imaging while they performed a simple two-choice gambling task resulting in stochastic and parametrically variable monetary gains and losses. In patients with Parkinson's disease, the neural response to reward outcome (as reflected by the blood oxygen level-dependent signal) was attenuated in a large group of mesolimbic and mesocortical regions, comprising the ventral putamen, ventral tegmental area, thalamus and hippocampus. Although these regions showed a linear response to reward outcome in healthy individuals, this response was either markedly reduced or undetectable in drug-naive patients with Parkinson's disease. The results show that the core regions of the meso-cortico-limbic dopaminergic system, including the ventral tegmental area, ventral striatum, and medial orbitofrontal cortex, are already significantly compromised in the early stages of the disease and that these deficits cannot be attributed to the contaminating effect of dopaminergic treatment.

Does report modality modulate psychophysical sensitivity? The jury remains out.

Scientific studies of perception use motoric reports as the principal means of communicating subjective experience. In such experiments, a widely held and implicit assumption is that the motor action conveys but does not tamper with perceptual experience. We tested nine observers on a luminance detection task in a cross-over repeated measures design. In separate conditions, observers reported their detection via movements of either their hands or eyes. We found only anecdotal evidence for any modality-dependent effect on psychophysical sensitivity. We also reanalyzed an existing dataset from which deployed a similar detection paradigm involving hand and eye reports. In the four paradigm variants tested, we again only found anecdotal evidence for the effect of report modality on psychophysical sensitivity. Both studies reported here provide only anecdotal evidence; thus, whether we can replicate report-dependent perceptual effects still needs to be resolved. We argue why this remains an important question for consciousness research and why it deserves more rigorous and high-powered replication attempts.

Characterising the covariance pattern between lifestyle factors and structural brain measures: a multivariable replication study of two independent ageing cohorts.

Modifiable lifestyle factors have been shown to promote healthy brain ageing. However, studies have typically focused on a single factor at a time. Given that lifestyle factors do not occur in isolation, multivariable analyses provide a more realistic model of the lifestyle-brain relationship. Here, canonical correlation analyses (CCA) examined the relationship between nine lifestyle factors and seven MRI-derived indices of brain structure. The resulting covariance pattern was further explored with Bayesian regressions. CCA analyses were first conducted on a Danish cohort of older adults (n = 251) and then replicated in a British cohort (n = 668). In both cohorts, the latent factors of lifestyle and brain structure were positively correlated (UK: r = .37, p < 0.001; Denmark: r = .27, p < 0.001). In the cross-validation study, the correlation between lifestyle-brain latent factors was r = .10, p = 0.008. However, the pattern of associations differed between datasets. These findings suggest that baseline characterisation and tailoring towards the study sample may be beneficial for achieving targeted lifestyle interventions.

Reward signalling in brainstem nuclei under fluctuating blood glucose.

Phasic dopamine release from mid-brain dopaminergic neurons is thought to signal errors of reward prediction (RPE). If reward maximisation is to maintain homeostasis, then the value of primary rewards should be coupled to the homeostatic errors they remediate. This leads to the prediction that RPE signals should be configured as a function of homeostatic state and thus diminish with the attenuation of homeostatic error. To test this hypothesis, we collected a large volume of functional MRI data from five human volunteers on four separate days. After fasting for 12 hours, subjects consumed preloads that differed in glucose concentration. Participants then underwent a Pavlovian cue-conditioning paradigm in which the colour of a fixation-cross was stochastically associated with the delivery of water or glucose via a gustometer. This design afforded computation of RPE separately for better- and worse-than expected outcomes during ascending and descending trajectories of serum glucose fluctuations. In the parabrachial nuclei, regional activity coding positive RPEs scaled positively with serum glucose for both ascending and descending glucose levels. The ventral tegmental area and substantia nigra became more sensitive to negative RPEs when glucose levels were ascending. Together, the results suggest that RPE signals in key brainstem structures are modulated by homeostatic trajectories of naturally occurring glycaemic flux, revealing a tight interplay between homeostatic state and the neural encoding of primary reward in the human brain.

Spatially distributed encoding of covert attentional shifts in human thalamus.

Spatial attention modulates signal processing within visual nuclei of the thalamus--but do other nuclei govern the locus of attention in top-down mode? We examined functional MRI (fMRI) data from three subjects performing a task requiring covert attention to 1 of 16 positions in a circular array. Target position was cued after stimulus offset, requiring subjects to perform target detection from iconic visual memory. We found positionally specific responses at multiple thalamic sites, with individual voxels activating at more than one direction of attentional shift. Voxel clusters at anatomically equivalent sites across subjects revealed a broad range of directional tuning at each site, with little sign of contralateral bias. By reference to a thalamic atlas, we identified the nuclear correspondence of the four most reliably activated sites across subjects: mediodorsal/central-intralaminar (oculomotor thalamus), caudal intralaminar/parafascicular, suprageniculate/limitans, and medial pulvinar/lateral posterior. Hence, the cortical network generating a top-down control signal for relocating attention acts in concert with a spatially selective thalamic apparatus-the set of active nuclei mirroring the thalamic territory of cortical "eye-field" areas, thus supporting theories which propose the visuomotor origins of covert attentional selection.

Effects of category-specific costs on neural systems for perceptual decision-making.

Perceptual judgments are often biased by prospective losses, leading to changes in decision criteria. Little is known about how and where sensory evidence and cost information interact in the brain to influence perceptual categorization. Here we show that prospective losses systematically bias the perception of noisy face-house images. Asymmetries in category-specific cost were associated with enhanced blood-oxygen-level-dependent signal in a frontoparietal network. We observed selective activation of parahippocampal gyrus for changes in category-specific cost in keeping with the hypothesis that loss functions enact a particular task set that is communicated to visual regions. Across subjects, greater shifts in decision criteria were associated with greater activation of the anterior cingulate cortex (ACC). Our results support a hypothesis that costs bias an intermediate representation between perception and action, expressed via general effects on frontal cortex, and selective effects on extrastriate cortex. These findings indicate that asymmetric costs may affect a neural implementation of perceptual decision making in a similar manner to changes in category expectation, constituting a step toward accounting for how prospective losses are flexibly integrated with sensory evidence in the brain.

Second waves, social distancing, and the spread of COVID-19 across the USA.

We recently described a dynamic causal model of a COVID-19 outbreak within a single region. Here, we combine several of these (epidemic) models to create a (pandemic) model of viral spread among regions. Our focus is on a second wave of new cases that may result from loss of immunity-and the exchange of people between regions-and how mortality rates can be ameliorated under different strategic responses. In particular, we consider hard or soft social distancing strategies predicated on national (Federal) or regional (State) estimates of the prevalence of infection in the population. The modelling is demonstrated using timeseries of new cases and deaths from the United States to estimate the parameters of a factorial (compartmental) epidemiological model of each State and, crucially, coupling between States. Using Bayesian model reduction, we identify the effective connectivity between States that best explains the initial phases of the outbreak in the United States. Using the ensuing posterior parameter estimates, we then evaluate the likely outcomes of different policies in terms of mortality, working days lost due to lockdown and demands upon critical care. The provisional results of this modelling suggest that social distancing and loss of immunity are the two key factors that underwrite a return to endemic equilibrium.

Dopamine agonist treatment increases sensitivity to gamble outcomes in the hippocampus in de novo Parkinson's disease.

BACKGROUND: Parkinson's disease is associated with severe nigro-striatal dopamine depletion, leading to motor dysfunction and altered reward processing. We previously showed that drug-naïve patients with Parkinson's disease had a consistent attenuation of reward signalling in the mesolimbic and mesocortical system. Here, we address the neurobiological effects of dopaminergic therapy on reward sensitivity in the mesolimbic circuitry, and how this may contribute to neuropsychiatric symptoms. OBJECTIVES: We tested the hypothesis that (1) dopaminergic treatment would restore the attenuated, mesolimbic and mesocortical responses to reward; and (2) restoration of reward responsivity by dopaminergic treatment would predict motor performance and the emergence of impulse control symptoms. METHODS: In 11 drug-naïve Parkinson patients, we prospectively assessed treatment-induced changes in reward processing before, and eight weeks after initiation of monotherapy with dopamine agonists. They were compared to 10 non-medicated healthy controls who were also measured longitudinally. We used whole-brain functional magnetic resonance imaging at 3 Tesla to assess the reward responsivity of the brain to monetary gains and losses, while participants performed a simple consequential gambling task. RESULTS: In patients, dopaminergic treatment improved clinical motor symptoms without significantly changing task performance. Dopamine agonist therapy induced a stronger reward responsivity in the right hippocampus with higher doses being less effective. None of the patients developed impulse control disorders in the follow-up period of four years. CONCLUSIONS: Short-term treatment with first-ever dopaminergic medication partially restores deficient reward-related processing in the hippocampus in de novo Parkinson's disease.

Effective immunity and second waves: a dynamic causal modelling study.

This technical report addresses a pressing issue in the trajectory of the coronavirus outbreak; namely, the rate at which effective immunity is lost following the first wave of the pandemic. This is a crucial epidemiological parameter that speaks to both the consequences of relaxing lockdown and the propensity for a second wave of infections. Using a dynamic causal model of reported cases and deaths from multiple countries, we evaluated the evidence models of progressively longer periods of immunity. The results speak to an effective population immunity of about three months that, under the model, defers any second wave for approximately six months in most countries. This may have implications for the window of opportunity for tracking and tracing, as well as for developing vaccination programmes, and other therapeutic interventions.

Neurocomputational theories of homeostatic control.

Homeostasis is a problem for all living agents. It entails predictively regulating internal states within the bounds compatible with survival in order to maximise fitness. This can be achieved physiologically, through complex hierarchies of autonomic regulation, but it must also be achieved via behavioural control, both reactive and proactive. Here we briefly review some of the major theories of homeostatic control and their historical cognates, addressing how they tackle the optimisation of both physiological and behavioural homeostasis. We start with optimal control approaches, setting up key concepts, exploring their strengths and limitations. We then concentrate on contemporary neurocomputational approaches to homeostatic control. We primarily focus on a branch of reinforcement learning known as homeostatic reinforcement learning (HRL). A central premise of HRL is that reward optimisation is directly coupled to homeostatic control. A central construct in this framework is the drive function which maps from homeostatic state to motivational drive, where reductions in drive are operationally defined as reward values. We explain HRL's main advantages, empirical applications, and conceptual insights. Notably, we show how simple constraints on the drive function can yield a normative account of predictive control, as well as account for phenomena such as satiety, risk aversion, and interactions between competing homeostatic needs. We illustrate how HRL agents can learn to avoid hazardous states without any need to experience them, and how HRL can be applied in clinical domains. Finally, we outline several challenges to HRL, and how survival constraints and active inference models could circumvent these problems.

Fairness, fast and slow: A review of dual process models of fairness.

Fairness, the notion that people deserve or have rights to certain resources or kinds of treatment, is a fundamental dimension of moral cognition. Drawing on recent evidence from economics, psychology, and neuroscience, we ask whether self-interest is always intuitive, requiring self-control to override with reasoning-based fairness concerns, or whether fairness itself can be intuitive. While we find strong support for rejecting the notion that self-interest is always intuitive, the literature has reached conflicting conclusions about the neurocognitive systems underpinning fairness. We propose that this disagreement can largely be resolved in light of an extended Social Heuristics Hypothesis. Divergent findings may be attributed to the interpretation of behavioral effects of ego depletion or neurostimulation, reverse inference from brain activity to the underlying psychological process, and insensitivity to social context and inter-individual differences. To better dissect the neurobiological basis of fairness, we outline how future research should embrace cross-disciplinary methods that combine psychological manipulations with neuroimaging, and that can probe inter-individual, and cultural heterogeneities.

Patient profiling for success after weight loss surgery (GO Bypass study): An interdisciplinary study protocol.

Despite substantial research efforts, the mechanisms proposed to explain weight loss after gastric bypass (RYGB) and sleeve gastrectomy (SL) do not explain the large individual variation seen after these treatments. A complex set of factors are involved in the onset and development of obesity and these may also be relevant for the understanding of why success with treatments vary considerably between individuals. This calls for explanatory models that take into account not only biological determinants but also behavioral, affective and contextual factors. In this prospective study, we recruited 47 women and 8 men, aged 25-56 years old, with a BMI of 45.8 ±â€¯7.1 kg/m2 from the waiting list for RYGB and SL at Køge hospital, Denmark. Pre-surgery and 1.5, 6 and 18 months after surgery we assessed various endpoints spanning multiple domains. Endpoints were selected on basis of previous studies and include: physiological measures: anthropometrics, vital signs, biochemical measures and appetite hormones, genetics, gut microbiota, appetite sensation, food and taste preferences, neural sensitivity, sensory perception and movement behaviors; psychological measures: general psychiatric symptom-load, depression, eating disorders, ADHD, personality disorder, impulsivity, emotion regulation, attachment pattern, general self-efficacy, alexithymia, internalization of weight bias, addiction, quality of life and trauma; and sociological and anthropological measures: sociodemographic measures, eating behavior, weight control practices and psycho-social factors.Joining these many endpoints and methodologies from different scientific disciplines and creating a multi-dimensional predictive model has not previously been attempted. Data on the primary endpoint are expected to be published in 2018. TRIAL REGISTRATION: Clinicaltrials. gov ID NCT02070081.

Imaging the Creative Unconscious: Reflexive Neural Responses to Objects in the Visual and Parahippocampal Region Predicts State and Trait Creativity.

What does it take to have a creative mind? Theories of creative cognition assert that the quantity of automatic associations places fundamental constraints on the probability of reaching creative solutions. Due to the difficulties inherent in isolating automated associative responses from cognitive control, the neural basis underlying this faculty remains unknown. Here we acquired fMRI data in an incidental-viewing paradigm in which subjects performed an attention-demanding task whilst viewing task-irrelevant objects. By assigning a standard creativity task on the same objects out of the scanner, as well as a battery of psychometric creativity tests, we could assess whether stimulus-bound neural activity was predictive of state or trait variability in creativity. We found that stimulus-bound responses in superior occipital regions were linearly predictive of trial-by-trial variability in creative performance (state-creativity), and that in more creative individuals (trait-creativity) this response was more strongly expressed in entorhinal cortex. Additionally, the mean response to the onset of objects in parahippocampal gyrus was predictive of trait differences in creativity. This work suggests that, creative individuals are endowed with occipital and medial temporal reflexes that generate a greater fluency in associative representations, making them more accessible for ideation even when no ideation is explicitly called for.

Simultaneous representation of a spectrum of dynamically changing value estimates during decision making.

Decisions are based on value expectations derived from experience. We show that dorsal anterior cingulate cortex and three other brain regions hold multiple representations of choice value based on different timescales of experience organized in terms of systematic gradients across the cortex. Some parts of each area represent value estimates based on recent reward experience while others represent value estimates based on experience over the longer term. The value estimates within these areas interact with one another according to their temporal scaling. Some aspects of the representations change dynamically as the environment changes. The spectrum of value estimates may act as a flexible selection mechanism for combining experience-derived value information with other aspects of value to allow flexible and adaptive decisions in changing environments.

Neural correlates of stimulus reportability.

Most experiments on the "neural correlates of consciousness" employ stimulus reportability as an operational definition of what is consciously perceived. The interpretation of such experiments therefore depends critically on understanding the neural basis of stimulus reportability. Using a high volume of fMRI data, we investigated the neural correlates of stimulus reportability using a partial report object detection paradigm. Subjects were presented with a random array of circularly arranged disc-stimuli and were cued, after variable delays (following stimulus offset), to report the presence or absence of a disc at the cued location, using variable motor actions. By uncoupling stimulus processing, decision, and motor response, we were able to use signal detection theory to deconstruct the neural basis of stimulus reportability. We show that retinotopically specific responses in the early visual cortex correlate with stimulus processing but not decision or report; a network of parietal/temporal regions correlates with decisions but not stimulus presence, whereas classical motor regions correlate with report. These findings provide a basic framework for understanding the neural basis of stimulus reportability without the theoretical burden of presupposing a relationship between reportability and consciousness.