Spin and orbital states in La1.5 Sr0.5 CoO4 studied by electronic structure calculations

Electronic structure of the layered perovskite La1.5Sr0.5CoO4 with a checkerboard Co2+/Co3+ charge order is studied, using the local-spin-density approximation plus Hubbard U calculations including also the spin-orbit coupling and multiplet effect. Our results show that the Co2+ ion is in a high spin state (HS, t(2g)(5)e(g)(2)) and Co3+ low spin state (LS, t(2g)(6)). Due to a small Co2+ t(2g) crystal field splitting, the spin-orbit interaction produces an orbital moment of 0.26 mu(B) and accounts for the observed easy in-plane magnetism. Moreover, we find that the Co3+ intermediate spin state (IS, t(2g)(5)e(g)(1)) has a multiplet splitting of several tenths of eV and the lowest-lying one is still higher than the LS ground state by 120 meV, and that the Co3+ HS state (t(2g)(4)e(g)(2)) is more unstable by 310 meV. Either the IS or HS Co3+ ions would give rise to a wrong magnetic order and anisotropy

A quantitative description of the transition between intuitive altruism and rational deliberation in iterated Prisoner's Dilemma experiments

What is intuitive: pro-social or anti-social behaviour? To answer this fundamental question, recent studies analyse decision times in game theory experiments under the assumption that intuitive decisions are fast and that deliberation is slow. These analyses keep track of the average time taken to make decisions under different conditions. Lacking any knowledge of the underlying dynamics, such simplistic approach might however lead to erroneous interpretations. Here we model the cognitive basis of strategic cooperative decision making using the Drift Diffusion Model to discern between deliberation and intuition and describe the evolution of the decision making in iterated Prisoner's Dilemma experiments. We find that, although initially people's intuitive decision is to cooperate, rational deliberation quickly becomes dominant over an initial intuitive bias towards cooperation, which is fostered by positive interactions as much as frustrated by a negative one. However, this initial pro-social tendency is resilient, as after a pause it resets to the same initial value. These results illustrate the new insight that can be achieved thanks to a quantitative modelling of human behavior

Recognising and reacting to angry and happy facial expressions: a diffusion model analysis.

Researchers have reported two biases in how people recognise and respond to angry and happy facial expressions: (1) a gender-expression bias (Becker et al. in J Pers Soc Psychol, 92(2):179-190, https://doi.org/10.1037/0022-3514.92.2.179 , 2007)-faster identification of male faces as angry and female faces as happy and (2) an approach-avoidance bias-faster avoidance of people who appear angry and faster approach responses people who appear happy (Heuer et al. in Behav Res The, 45(12):2990-3001, https://doi.org/10.1016/j.brat.2007.08.010 2007; Marsh et al. in Emotion, 5(1), 119-124, https://doi.org/10.1037/1528-3542.5.1.119 , 2005; Rotteveel and Phaf in Emotion 4(2):156-172, https://doi.org/10.1037/1528-3542.4.2.156 , 2004). The aim of the current research is to gain insight into the nature of such biases by applying the drift diffusion model to the results of an approach-avoidance task. Sixty-five participants (33 female) identified faces as either happy or angry by pushing and pulling a joystick. In agreement with the original study of this effect (Solarz 1960) there were clear participant gender differences-both the approach avoidance and gender-expression biases were larger in magnitude for female compared to male participants. The diffusion model results extend recent research (Krypotos et al. in Cogn Emot 29(8):1424-1444, https://doi.org/10.1080/02699931.2014.985635 , 2015) by indicating that the gender-expression and approach-avoidance biases are mediated by separate cognitive processes

A computational psychiatry approach identifies how alpha-2A noradrenergic agonist Guanfacine affects feature-based reinforcement learning in the macaque

[EN] Noradrenaline is believed to support cognitive flexibility through the alpha 2A noradrenergic receptor (a2A-NAR) acting in prefrontal cortex. Enhanced flexibility has been inferred from improved working memory with the a2A-NA agonist Guanfacine. But it has been unclear whether Guanfacine improves specific attention and learning mechanisms beyond working memory, and whether the drug effects can be formalized computationally to allow single subject predictions. We tested and confirmed these suggestions in a case study with a healthy nonhuman primate performing a feature-based reversal learning task evaluating performance using Bayesian and Reinforcement learning models. In an initial dose-testing phase we found a Guanfacine dose that increased performance accuracy, decreased distractibility and improved learning. In a second experimental phase using only that dose we examined the faster feature-based reversal learning with Guanfacine with single-subject computational modeling. Parameter estimation suggested that improved learning is not accounted for by varying a single reinforcement learning mechanism, but by changing the set of parameter values to higher learning rates and stronger suppression of non-chosen over chosen feature information. These findings provide an important starting point for developing nonhuman primate models to discern the synaptic mechanisms of attention and learning functions within the context of a computational neuropsychiatry framework.This research was supported by grants from the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Ontario Ministry of Economic Development and Innovation (MEDI). We thank Dr. Hongying Wang for invaluable help with drug administration and animal careHassani, SA.; Oemisch, M.; Balcarras, M.; Westendorff, S.; Ardid-Ramírez, JS.; Van Der Meer, MA.; Tiesinga, P.... (2017). A computational psychiatry approach identifies how alpha-2A noradrenergic agonist Guanfacine affects feature-based reinforcement learning in the macaque. Scientific Reports. 7:1-19. https://doi.org/10.1038/srep40606S1197Arnsten, A. F., Wang, M. J. & Paspalas, C. D. Neuromodulation of thought: flexibilities and vulnerabilities in prefrontal cortical network synapses. Neuron 76, 223–239 (2012).Arnsten, A. F. & Dudley, A. G. Methylphenidate improves prefrontal cortical cognitive function through alpha2 adrenoceptor and dopamine D1 receptor actions: Relevance to therapeutic effects in Attention Deficit Hyperactivity Disorder. Behav Brain Funct 1, 2 (2005).Clark, K. L. & Noudoost, B. The role of prefrontal catecholamines in attention and working memory. Front Neural Circuits 8, 33 (2014).Wang, M. et al. Neuronal basis of age-related working memory decline. Nature 476, 210–213 (2011).Wang, M. et al. Alpha2A-adrenoceptors strengthen working memory networks by inhibiting cAMP-HCN channel signaling in prefrontal cortex. Cell 129, 397–410 (2007).Aston-Jones, G. & Cohen, J. D. An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance. Annu Rev Neurosci 28, 403–450 (2005).Yu, A. J. & Dayan, P. Uncertainty, neuromodulation, and attention. Neuron 46, 681–692 (2005).Mather, M., Clewett, D., Sakaki, M. & Harley, C. W. Norepinephrine ignites local hot spots of neuronal excitation: How arousal amplifies selectivity in perception and memory. Behav Brain Sci, 1–100, doi: 10.1017/S0140525X15000667 (2015).Amemiya, S. & Redish, A. D. Manipulating Decisiveness in Decision Making: Effects of Clonidine on Hippocampal Search Strategies. J Neurosci 36, 814–827 (2016).Doya, K. Metalearning and neuromodulation. Neural Netw 15, 495–506 (2002).Uhlen, S., Muceniece, R., Rangel, N., Tiger, G. & Wikberg, J. E. Comparison of the binding activities of some drugs on alpha 2A, alpha 2B and alpha 2C-adrenoceptors and non-adrenergic imidazoline sites in the guinea pig. Pharmacology & toxicology 76, 353–364 (1995).Mao, Z. M., Arnsten, A. F. & Li, B. M. Local infusion of an alpha-1 adrenergic agonist into the prefrontal cortex impairs spatial working memory performance in monkeys. Biological psychiatry 46, 1259–1265 (1999).Arnsten, A. F. & Goldman-Rakic, P. S. Analysis of alpha-2 adrenergic agonist effects on the delayed nonmatch-to-sample performance of aged rhesus monkeys. Neurobiol Aging 11, 583–590 (1990).Franowicz, J. S. & Arnsten, A. F. The alpha-2a noradrenergic agonist, guanfacine, improves delayed response performance in young adult rhesus monkeys. Psychopharmacology 136, 8–14 (1998).Caetano, M. S. et al. Noradrenergic control of error perseveration in medial prefrontal cortex. Frontiers in Integrative Neuroscience 6, 125 (2012).Kim, S., Bobeica, I., Gamo, N. J., Arnsten, A. F. & Lee, D. Effects of alpha-2A adrenergic receptor agonist on time and risk preference in primates. Psychopharmacology 219, 363–375 (2012).Seu, E., Lang, A., Rivera, R. J. & Jentsch, J. D. Inhibition of the norepinephrine transporter improves behavioral flexibility in rats and monkeys. Psychopharmacology 202, 505–519 (2009).Kawaura, K., Karasawa, J., Chaki, S. & Hikichi, H. Stimulation of postsynapse adrenergic alpha2A receptor improves attention/cognition performance in an animal model of attention deficit hyperactivity disorder. Behav Brain Res 270, 349–356 (2014).Aoki, C., Go, C. G., Venkatesan, C. & Kurose, H. Perikaryal and synaptic localization of alpha 2A-adrenergic receptor-like immunoreactivity. Brain Res 650, 181–204 (1994).Barth, A. M., Vizi, E. S., Zelles, T. & Lendvai, B. Alpha2-adrenergic receptors modify dendritic spike generation via HCN channels in the prefrontal cortex. J Neurophysiol 99, 394–401 (2008).Ji, X. H., Ji, J. Z., Zhang, H. & Li, B. M. Stimulation of alpha2-adrenoceptors suppresses excitatory synaptic transmission in the medial prefrontal cortex of rat. Neuropsychopharmacology 33, 2263–2271 (2008).Yi, F., Liu, S. S., Luo, F., Zhang, X. H. & Li, B. M. Signaling mechanism underlying alpha2A -adrenergic suppression of excitatory synaptic transmission in the medial prefrontal cortex of rats. Eur J Neurosci 38, 2364–2373 (2013).Engberg, G. & Eriksson, E. Effects of alpha 2-adrenoceptor agonists on locus coeruleus firing rate and brain noradrenaline turnover in N-ethoxycarbonyl-2-ethoxy-1,2-dihydroquinoline (EEDQ)-treated rats. Naunyn-Schmiedeberg’s archives of pharmacology 343, 472–477 (1991).Jakala, P. et al. Guanfacine, but not clonidine, improves planning and working memory performance in humans. Neuropsychopharmacology 20, 460–470 (1999).Jakala, P. et al. Guanfacine and clonidine, alpha 2-agonists, improve paired associates learning, but not delayed matching to sample, in humans. Neuropsychopharmacology 20, 119–130 (1999).Muller, U. et al. Lack of effects of guanfacine on executive and memory functions in healthy male volunteers. Psychopharmacology 182, 205–213 (2005).Scahill, L. et al. A placebo-controlled study of guanfacine in the treatment of children with tic disorders and attention deficit hyperactivity disorder. The American journal of psychiatry 158, 1067–1074 (2001).Huys, Q. J. M., Maia, T. V. & Frank, M. J. Computational psychiatry as a bridge from neuroscience to clinical applications. Nat Neurosci 19, 404–413 (2016).Stephan, K. E. et al. Computational neuroimaging strategies for single patient predictions. NeuroImage in press (2015).Arnsten, A. F., Cai, J. X. & Goldman-Rakic, P. S. The alpha-2 adrenergic agonist guanfacine improves memory in aged monkeys without sedative or hypotensive side effects: evidence for alpha-2 receptor subtypes. J Neurosci 8, 4287–4298 (1988).Callado, L. F. & Stamford, J. A. Alpha2A- but not alpha2B/C-adrenoceptors modulate noradrenaline release in rat locus coeruleus: voltammetric data. Eur J Pharmacol 366, 35–39 (1999).Millan, M. J. et al. Cognitive dysfunction in psychiatric disorders: characteristics, causes and the quest for improved therapy. Nature reviews. Drug discovery 11, 141–168 (2012).Niv, Y. et al. Reinforcement learning in multidimensional environments relies on attention mechanisms. J Neurosci 35, 8145–8157 (2015).Balcarras, M., Ardid, S., Kaping, D., Everling, S. & Womelsdorf, T. Attentional Selection Can Be Predicted by Reinforcement Learning of Task-relevant Stimulus Features Weighted by Value-independent Stickiness. J Cogn Neurosci 28, 333–349 (2016).Redish, A. D., Jensen, S., Johnson, A. & Kurth-Nelson, Z. Reconciling reinforcement learning models with behavioral extinction and renewal: implications for addiction, relapse, and problem gambling. Psychol Rev 114, 784–805 (2007).Nassar, M. R. et al. Rational regulation of learning dynamics by pupil-linked arousal systems. Nat Neurosci 15, 1040–1046 (2012).O’Reilly, J. X. et al. Dissociable effects of surprise and model update in parietal and anterior cingulate cortex. Proc Natl Acad Sci USA 110, 3660–3669 (2013).Shenhav, A., Botvinick, M. M. & Cohen, J. D. The expected value of control: an integrative theory of anterior cingulate cortex function. Neuron 79, 217–240 (2013).Womelsdorf, T. & Everling, S. Long-Range Attention Networks: Circuit Motifs Underlying Endogenously Controlled Stimulus Selection. Trends Neurosci 38, 682–700 (2015).Yang, Y. et al. Nicotinic alpha7 receptors enhance NMDA cognitive circuits in dorsolateral prefrontal cortex. Proc Natl Acad Sci USA 110, 12078–12083 (2013).Aston-Jones, G., Rajkowski, J. & Cohen, J. Role of locus coeruleus in attention and behavioral flexibility. Biological psychiatry 46, 1309–1320 (1999).Cole, B. J. & Robbins, T. W. Forebrain norepinephrine: role in controlled information processing in the rat. Neuropsychopharmacology 7, 129–142 (1992).Dalley, J. W., Cardinal, R. N. & Robbins, T. W. Prefrontal executive and cognitive functions in rodents: neural and neurochemical substrates. Neuroscience and biobehavioral reviews 28, 771–784 (2004).Devauges, V. & Sara, S. J. Activation of the noradrenergic system facilitates an attentional shift in the rat. Behav Brain Res 39, 19–28 (1990).Connor, D. F., Arnsten, A. F., Pearson, G. S. & Greco, G. F. Guanfacine extended release for the treatment of attention-deficit/hyperactivity disorder in children and adolescents. Expert opinion on pharmacotherapy 15, 1601–1610 (2014).Sallee, F. R. et al. Guanfacine extended release in children and adolescents with attention-deficit/hyperactivity disorder: a placebo-controlled trial. J Am Acad Child Adolesc Psychiatry 48, 155–165 (2009).Steere, J. C. & Arnsten, A. F. The alpha-2A noradrenergic receptor agonist guanfacine improves visual object discrimination reversal performance in aged rhesus monkeys. Behav Neurosci 111, 883–891 (1997).Doya, K. Modulators of decision making. Nat Neurosci 11, 410–416 (2008).Wang, X. J. & Krystal, J. H. Computational psychiatry. Neuron 84, 638–654 (2014).Wiecki, T. V. et al. A Computational Cognitive Biomarker for Early-Stage Huntington’s Disease. PLoS One 11, e0148409, doi: 10.1371/journal.pone.0148409 (2016).Huys, Q. J., Pizzagalli, D. A., Bogdan, R. & Dayan, P. Mapping anhedonia onto reinforcement learning: a behavioural meta-analysis. Biol Mood Anxiety Disord 3, 12 (2013).Gershman, S. J. & Niv, Y. Learning latent structure: carving nature at its joints. Curr Opin Neurobiol 20, 251–256 (2010).Voon, V. et al. Disorders of compulsivity: a common bias towards learning habits. Mol Psychiatry 20, 345–352 (2015).Maia, T. V. & Frank, M. J. From reinforcement learning models to psychiatric and neurological disorders. Nature Neuroscience 14, 154–162 (2011).Adams, R. A., Huys, Q. J. M. & Roiser, J. P. Computational Psychiatry: towards a mathematically informed understanding of mental illness. Journal of Neurology, Neurosurgery, and Psychiatry 87, 53–63 (2015).Schlagenhauf, F. et al. Striatal dysfunction during reversal learning in unmedicated schizophrenia patients. NeuroImage 89, 171–180 (2014).Harlé, K. M. et al. Bayesian neural adjustment of inhibitory control predicts emergence of problem stimulant use. Brain 138, 3413–3426 (2015).Zhang, J. et al. Different decision deficits impair response inhibition in progressive supranuclear palsy and Parkinson’s disease. Brain 139, 161–173 (2016).Frank, M. J. et al. fMRI and EEG Predictors of Dynamic Decision Parameters during Human Reinforcement Learning. Journal of Neuroscience 35, 485–494 (2015).Smith, A. C. & Brown, E. N. Estimating a state-space model from point process observations. Neural Comput 15, 965–991 (2003).Wilson, R. C. & Niv, Y. Inferring relevance in a changing world. Frontiers in human neuroscience 5, 189 (2011).Rämä, P. et al. Medetomidine, atipamezole, and guanfacine in delayed response performance of aged monkeys. Pharmacology Biochemistry and Behavior 55, 415–422 (1996).Arnsten, A. F. T. & Contant, T. A. Alpha-2 adrenergic agonists decrease distractibility in aged monkeys performing the delayed response task. Psychopharmacology 108, 159–169 (1992).O’Neill, J. et al. Effects of guanfacine on three forms of distraction in the aging macaque. Life Sciences 67, 877–885 (2000).Wang, M., Ji, J.-Z. & Li, B.-M. The α2A-Adrenergic Agonist Guanfacine Improves Visuomotor Associative Learning in Monkeys. Neuropsychopharmacology 29, 86–92 (2004).Witte, E. a. & Marrocco, R. T. Alteration of brain noradrenergic activity in rhesus monkeys affects the alerting component of covert orienting. Psychopharmacology 132, 315–323 (1997).Decamp, E., Clark, K. & Schneider, J. S. Effects of the alpha-2 adrenoceptor agonist guanfacine on attention and working memory in aged non-human primates. European Journal of Neuroscience 34, 1018–1022 (2011)

Adults with autism overestimate the volatility of the sensory environment.

Insistence on sameness and intolerance of change are among the diagnostic criteria for autism spectrum disorder (ASD), but little research has addressed how people with ASD represent and respond to environmental change. Here, behavioral and pupillometric measurements indicated that adults with ASD are less surprised than neurotypical adults when their expectations are violated, and decreased surprise is predictive of greater symptom severity. A hierarchical Bayesian model of learning suggested that in ASD, a tendency to overlearn about volatility in the face of environmental change drives a corresponding reduction in learning about probabilistically aberrant events, thus putatively rendering these events less surprising. Participant-specific modeled estimates of surprise about environmental conditions were linked to pupil size in the ASD group, thus suggesting heightened noradrenergic responsivity in line with compromised neural gain. This study offers insights into the behavioral, algorithmic and physiological mechanisms underlying responses to environmental volatility in ASD

Dopamine, affordance and active inference.

The role of dopamine in behaviour and decision-making is often cast in terms of reinforcement learning and optimal decision theory. Here, we present an alternative view that frames the physiology of dopamine in terms of Bayes-optimal behaviour. In this account, dopamine controls the precision or salience of (external or internal) cues that engender action. In other words, dopamine balances bottom-up sensory information and top-down prior beliefs when making hierarchical inferences (predictions) about cues that have affordance. In this paper, we focus on the consequences of changing tonic levels of dopamine firing using simulations of cued sequential movements. Crucially, the predictions driving movements are based upon a hierarchical generative model that infers the context in which movements are made. This means that we can confuse agents by changing the context (order) in which cues are presented. These simulations provide a (Bayes-optimal) model of contextual uncertainty and set switching that can be quantified in terms of behavioural and electrophysiological responses. Furthermore, one can simulate dopaminergic lesions (by changing the precision of prediction errors) to produce pathological behaviours that are reminiscent of those seen in neurological disorders such as Parkinson's disease. We use these simulations to demonstrate how a single functional role for dopamine at the synaptic level can manifest in different ways at the behavioural level

Conscious perception and the modulatory role of dopamine: no effect of the dopamine D2 agonist cabergoline on visual masking, the attentional blink, and probabilistic discrimination

Rationale Conscious perception is thought to depend on global amplification of sensory input. In recent years, striatal dopamine has been proposed to be involved in gating information and conscious access, due to its modulatory influence on thalamocortical connectivity. Objectives Since much of the evidence that implicates striatal dopamine is correlational, we conducted a double-blind crossover pharmacological study in which we administered cabergoline—a dopamine D2 agonist—and placebo to 30 healthy participants. Under both conditions, we subjected participants to several well-established experimental conscious-perception paradigms, such as backward masking and the attentional blink task. Results We found no evidence in support of an effect of cabergoline on conscious perception: key behavioral and event-related potential (ERP) findings associated with each of these tasks were unaffected by cabergoline. Conclusions Our results cast doubt on a causal role for dopamine in visual perception. It remains an open possibility that dopamine has causal effects in other tasks, perhaps where perceptual uncertainty is more prominent

Auditory information enhances post-sensory visual evidence during rapid multisensory decision-making

Despite recent progress in understanding multisensory decision-making, a conclusive mechanistic account of how the brain translates the relevant evidence into a decision is lacking. Specifically, it remains unclear whether perceptual improvements during rapid multisensory decisions are best explained by sensory (i.e., ‘Early’) processing benefits or post-sensory (i.e., ‘Late’) changes in decision dynamics. Here, we employ a well-established visual object categorisation task in which early sensory and post-sensory decision evidence can be dissociated using multivariate pattern analysis of the electroencephalogram (EEG). We capitalize on these distinct neural components to identify when and how complementary auditory information influences the encoding of decision-relevant visual evidence in a multisensory context. We show that it is primarily the post-sensory, rather than the early sensory, EEG component amplitudes that are being amplified during rapid audiovisual decision-making. Using a neurally informed drift diffusion model we demonstrate that a multisensory behavioral improvement in accuracy arises from an enhanced quality of the relevant decision evidence, as captured by the post-sensory EEG component, consistent with the emergence of multisensory evidence in higher-order brain areas

The default network of the human brain is associated with perceived social isolation

Humans survive and thrive through social exchange. Yet, social dependency also comes at a cost. Perceived social isolation, or loneliness, affects physical and mental health, cognitive performance, overall life expectancy, and increases vulnerability to Alzheimer’s disease-related dementias. Despite severe consequences on behavior and health, the neural basis of loneliness remains elusive. Using the UK Biobank population imaging-genetics cohort (n = ~40,000, aged 40–69 years when recruited, mean age = 54.9), we test for signatures of loneliness in grey matter morphology, intrinsic functional coupling, and fiber tract microstructure. The loneliness-linked neurobiological profiles converge on a collection of brain regions known as the ‘default network’. This higher associative network shows more consistent loneliness associations in grey matter volume than other cortical brain networks. Lonely individuals display stronger functional communication in the default network, and greater microstructural integrity of its fornix pathway. The findings fit with the possibility that the up-regulation of these neural circuits supports mentalizing, reminiscence and imagination to fill the social void