Disrupted habenula function in major depression.

The habenula is a small, evolutionarily conserved brain structure that plays a central role in aversive processing and is hypothesised to be hyperactive in depression, contributing to the generation of symptoms such as anhedonia. However, habenula responses during aversive processing have yet to be reported in individuals with major depressive disorder (MDD). Unmedicated and currently depressed MDD patients (N=25, aged 18-52 years) and healthy volunteers (N=25, aged 19-52 years) completed a passive (Pavlovian) conditioning task with appetitive (monetary gain) and aversive (monetary loss and electric shock) outcomes during high-resolution functional magnetic resonance imaging; data were analysed using computational modelling. Arterial spin labelling was used to index resting-state perfusion and high-resolution anatomical images were used to assess habenula volume. In healthy volunteers, habenula activation increased as conditioned stimuli (CSs) became more strongly associated with electric shocks. This pattern was significantly different in MDD subjects, for whom habenula activation decreased significantly with increasing association between CSs and electric shocks. Individual differences in habenula volume were negatively associated with symptoms of anhedonia across both groups. MDD subjects exhibited abnormal negative task-related (phasic) habenula responses during primary aversive conditioning. The direction of this effect is opposite to that predicted by contemporary theoretical accounts of depression based on findings in animal models. We speculate that the negative habenula responses we observed may result in the loss of the capacity to actively avoid negative cues in MDD, which could lead to excessive negative focus.

The specificity of Pavlovian regulation is associated with recovery from depression.

BACKGROUND: Changes in reflexive emotional responses are hallmarks of depression, but how emotional reflexes make an impact on adaptive decision-making in depression has not been examined formally. Using a Pavlovian-instrumental transfer (PIT) task, we compared the influence of affectively valenced stimuli on decision-making in depression and generalized anxiety disorder compared with healthy controls; and related this to the longitudinal course of the illness. METHOD: A total of 40 subjects with a current DSM-IV-TR diagnosis of major depressive disorder, dysthymia, generalized anxiety disorder, or a combination thereof, and 40 matched healthy controls performed a PIT task that assesses how instrumental approach and withdrawal behaviours are influenced by appetitive and aversive Pavlovian conditioned stimuli (CSs). Patients were followed up after 4-6 months. Analyses focused on patients with depression alone (n = 25). RESULTS: In healthy controls, Pavlovian CSs exerted action-specific effects, with appetitive CSs boosting active approach and aversive CSs active withdrawal. This action-specificity was absent in currently depressed subjects. Greater action-specificity in patients was associated with better recovery over the follow-up period. CONCLUSIONS: Depression is associated with an abnormal influence of emotional reactions on decision-making in a way that may predict recovery.

Disorders of compulsivity: a common bias towards learning habits.

Why do we repeat choices that we know are bad for us? Decision making is characterized by the parallel engagement of two distinct systems, goal-directed and habitual, thought to arise from two computational learning mechanisms, model-based and model-free. The habitual system is a candidate source of pathological fixedness. Using a decision task that measures the contribution to learning of either mechanism, we show a bias towards model-free (habit) acquisition in disorders involving both natural (binge eating) and artificial (methamphetamine) rewards, and obsessive-compulsive disorder. This favoring of model-free learning may underlie the repetitive behaviors that ultimately dominate in these disorders. Further, we show that the habit formation bias is associated with lower gray matter volumes in caudate and medial orbitofrontal cortex. Our findings suggest that the dysfunction in a common neurocomputational mechanism may underlie diverse disorders involving compulsion.

The influence of receptor positioning on chemotactic information.

Chemotaxis, or gradient following, is important in many biological systems, but suffers from noise. How receptors are positioned on the cell or sensing device influences the quality of the inferences they can support about the gradient, suggesting that their configuration might be optimised. We show that for an elliptical sensing device, inhomogeneous receptor placement could be a potential approach for cells to eliminate bias in the posterior distribution of the gradient direction. We use information theory to calculate the mutual information between the gradient and the binding pattern, thus finding the optimal receptor arrangement for gradient sensing.

Acetylcholine contributes through muscarinic receptors to attentional modulation in V1.

Attention exerts a strong influence over neuronal processing in cortical areas. It selectively increases firing rates and affects tuning properties, including changing receptive field locations and sizes. Although these effects are well studied, their cellular mechanisms are poorly understood. To study the cellular mechanisms, we combined iontophoretic pharmacological analysis of cholinergic receptors with single cell recordings in V1 while rhesus macaque monkeys (Macaca mulatta) performed a task that demanded top-down spatial attention. Attending to the receptive field of the V1 neuron under study caused an increase in firing rates. Here we show that this attentional modulation was enhanced by low doses of acetylcholine. Furthermore, applying the muscarinic antagonist scopolamine reduced attentional modulation, whereas the nicotinic antagonist mecamylamine had no systematic effect. These results demonstrate that muscarinic cholinergic mechanisms play a central part in mediating the effects of attention in V1.

Knowing me, knowing you: Interpersonal similarity improves predictive accuracy and reduces attributions of harmful intent.

To benefit from social interactions, people need to predict how their social partners will behave. Such predictions arise through integrating prior expectations with evidence from observations, but where the priors come from and whether they influence the integration into beliefs about a social partner is not clear. Furthermore, this process can be affected by factors such as paranoia, in which the tendency to form biased impressions of others is common. Using a modified social value orientation (SVO) task in a large online sample (n = 697), we showed that participants used a Bayesian inference process to learn about partners, with priors that were based on their own preferences. Paranoia was associated with preferences for earning more than a partner and less flexible beliefs regarding a partner's social preferences. Alignment between the preferences of participants and their partners was associated with better predictions and with reduced attributions of harmful intent to partners. Together, our data and model expand upon theories of interpersonal relationships by demonstrating how dyadic similarity mechanistically influences social interaction by generating more accurate predictions and less threatening impressions.

A neural substrate of prediction and reward.

The capacity to predict future events permits a creature to detect, model, and manipulate the causal structure of its interactions with its environment. Behavioral experiments suggest that learning is driven by changes in the expectations about future salient events such as rewards and punishments. Physiological work has recently complemented these studies by identifying dopaminergic neurons in the primate whose fluctuating output apparently signals changes or errors in the predictions of future salient and rewarding events. Taken together, these findings can be understood through quantitative theories of adaptive optimizing control.

The "wake-sleep" algorithm for unsupervised neural networks.

An unsupervised learning algorithm for a multilayer network of stochastic neurons is described. Bottom-up "recognition" connections convert the input into representations in successive hidden layers, and top-down "generative" connections reconstruct the representation in one layer from the representation in the layer above. In the "wake" phase, neurons are driven by recognition connections, and generative connections are adapted to increase the probability that they would reconstruct the correct activity vector in the layer below. In the "sleep" phase, neurons are driven by generative connections, and recognition connections are adapted to increase the probability that they would produce the correct activity vector in the layer above.

Dopamine, reinforcement learning, and addiction.

Dopamine is intimately linked with the modes of action of drugs of addiction. However, although its role in the initiation of drug abuse seems relatively uncomplicated, its possible involvement in the development of compulsive drug taking, and indeed vulnerability and relapse, is less clear. We first describe a modern reinforcement learning view of affective control, focusing on the roles for dopamine. We then use this as a framework to sketch various notions of the neuromodulator's possible participation in initiation and compulsion. We end with some pointers towards future theoretical developments.

Learning and selective attention.

Selective attention involves the differential processing of different stimuli, and has widespread psychological and neural consequences. Although computational modeling should offer a powerful way of linking observable phenomena at different levels, most work has focused on the relatively narrow issue of constraints on processing resources. By contrast, we consider statistical and informational aspects of selective attention, divorced from resource constraints, which are evident in animal conditioning experiments involving uncertain predictions and unreliable stimuli. Neuromodulatory systems and limbic structures are known to underlie attentional effects in such tasks.

Computational modelling.

Computation modelling is playing an increasingly accepted and important role in neuroscience. It is not a unitary enterprise, though, and the distinction between two different sorts of modelling, one interested in description and the other also in function, is illustrated by their application to activity-dependent developmental plasticity and adult conditioning.

The involvement of recurrent connections in area CA3 in establishing the properties of place fields: a model.

Strong constraints on the neural mechanisms underlying the formation of place fields in the rodent hippocampus come from the systematic changes in spatial activity patterns that are consequent on systematic environmental manipulations. We describe an attractor network model of area CA3 in which local, recurrent, excitatory, and inhibitory interactions generate appropriate place cell representations from location- and direction-specific activity in the entorhinal cortex. In the model, familiarity with the environment, as reflected by activity in neuromodulatory systems, influences the efficacy and plasticity of the recurrent and feedforward inputs to CA3. In unfamiliar, novel, environments, mossy fiber inputs impose activity patterns on CA3, and the recurrent collaterals and the perforant path inputs are subject to graded Hebbian plasticity. This sculpts CA3 attractors and associates them with activity patterns in the entorhinal cortex. In familiar environments, place fields are controlled by the way that perforant path inputs select among the attractors. Depending on the training experience provided, the model generates place fields that are either directional or nondirectional and whose changes when the environment undergoes simple geometric transformations are in accordance with experimental data. Representations of multiple environments can be stored and recalled with little interference, and these have the appropriate degrees of similarity in visually similar environments.

How receptor diffusion influences gradient sensing.

Chemotaxis, or directed motion in chemical gradients, is critical for various biological processes. Many eukaryotic cells perform spatial sensing, i.e. they detect gradients by comparing spatial differences in binding occupancy of chemosensory receptors across their membrane. In many theoretical models of spatial sensing, it is assumed, for the sake of simplicity, that the receptors concerned do not move. However, in reality, receptors undergo diverse modes of diffusion, and can traverse considerable distances in the time it takes such cells to turn in an external gradient. This sets a physical limit on the accuracy of spatial sensing, which we explore using a model in which receptors diffuse freely over the membrane. We find that the Fisher information carried in binding and unbinding events decreases monotonically with the diffusion constant of the receptors.

Memory, modelling and Marr: a commentary on Marr (1971) 'Simple memory: a theory of archicortex'.

David Marr's theory of the archicortex, a brain structure now more commonly known as the hippocampus and hippocampal formation, is an epochal contribution to theoretical neuroscience. Addressing the problem of how information about 10 000 events could be stored in the archicortex during the day so that they can be retrieved using partial information and then transferred to the neocortex overnight, the paper presages a whole wealth of later empirical and theoretical work, proving impressively prescient. Despite this impending success, Marr later apparently grew dissatisfied with this style of modelling, but he went on to make seminal suggestions that continue to resonate loudly throughout the field of theoretical neuroscience. We describe Marr's theory of the archicortex and his theory of theories, setting them into their original and a contemporary context, and assessing their impact. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society.

Development, Evaluation and Implementation of Chief Complaint Groupings to Activate Data Collection: A Multi-Center Study of Clinical Decision Support for Children with Head Trauma.

BACKGROUND: Overuse of cranial computed tomography scans in children with blunt head trauma unnecessarily exposes them to radiation. The Pediatric Emergency Care Applied Research Network (PECARN) blunt head trauma prediction rules identify children who do not require a computed tomography scan. Electronic health record (EHR) based clinical decision support (CDS) may effectively implement these rules but must only be provided for appropriate patients in order to minimize excessive alerts. OBJECTIVES: To develop, implement and evaluate site-specific groupings of chief complaints (CC) that accurately identify children with head trauma, in order to activate data collection in an EHR. METHODS: As part of a 13 site clinical trial comparing cranial computed tomography use before and after implementation of CDS, four PECARN sites centrally developed and locally implemented CC groupings to trigger a clinical trial alert (CTA) to facilitate the completion of an emergency department head trauma data collection template. We tested and chose CC groupings to attain high sensitivity while maintaining at least moderate specificity. RESULTS: Due to variability in CCs available, identical groupings across sites were not possible. We noted substantial variability in the sensitivity and specificity of seemingly similar CC groupings between sites. The implemented CC groupings had sensitivities greater than 90% with specificities between 75-89%. During the trial, formal testing and provider feedback led to tailoring of the CC groupings at some sites. CONCLUSIONS: CC groupings can be successfully developed and implemented across multiple sites to accurately identify patients who should have a CTA triggered to facilitate EHR data collection. However, CC groupings will necessarily vary in order to attain high sensitivity and moderate-to-high specificity. In future trials, the balance between sensitivity and specificity should be considered based on the nature of the clinical condition, including prevalence and morbidity, in addition to the goals of the intervention being considered.

Bayesian retrieval in associative memories with storage errors.

It is well known that for finite-sized networks, onestep retrieval in the autoassociative Willshaw net is a suboptimal way to extract the information stored in the synapses. Iterative retrieval strategies are much better, but have hitherto only had heuristic justification. We show how they emerge naturally from considerations of probabilistic inference under conditions of noisy and partial input and a corrupted weight matrix. We start from the conditional probability distribution over possible patterns for retrieval. This contains all possible information that is available to an observer of the network and the initial input. Since this distribution is over exponentially many patterns, we use it to develop two approximate, but tractable, iterative retrieval methods. One performs maximum likelihood inference to find the single most likely pattern, using the (negative log of the) conditional probability as a Lyapunov function for retrieval. In physics terms, if storage errors are present, then the modified iterative update equations contain an additional antiferromagnetic interaction term and site dependent threshold values. The second method makes a mean field assumption to optimize a tractable estimate of the full conditional probability distribution. This leads to iterative mean field equations which can be interpreted in terms of a network of neurons with sigmoidal responses but with the same interactions and thresholds as in the maximum likelihood update equations. In the absence of storage errors, both models become very similiar to the Willshaw model, where standard retrieval is iterated using a particular form of linear threshold strategy.

Modeling the manifolds of images of handwritten digits.

This paper describes two new methods for modeling the manifolds of digitized images of handwritten digits. The models allow a priori information about the structure of the manifolds to be combined with empirical data. Accurate modeling of the manifolds allows digits to be discriminated using the relative probability densities under the alternative models. One of the methods is grounded in principal components analysis, the other in factor analysis. Both methods are based on locally linear low-dimensional approximations to the underlying data manifold. Links with other methods that model the manifold are discussed.

Idiopathic, bilateral pneumothorax: case report in a young child.

Unilateral, idiopathic pneumothorax (IP) is relatively common and occurs predominantly in males in their teens and twenties, with 85% presenting before age forty. In contrast, bilateral IP occurs rarely, with only three cases reported from 1977-87. To our knowledge, only one case of bilateral IP has been reported in the pediatric population, an adolescent male with likely recurrent disease. We present a case of a 7-year-old child with bilateral IP and discuss the diagnosis, pathophysiology, and treatment of this entity.

Medical causes of pneumomediastinum in children.

The purpose of this study was to determine the possible causes, clinical findings, and associated complications of pneumomediastinum in children. Medical records from January 1985 to December 1994 were retrospectively reviewed at Children's Hospital Medical Center of Akron using International Classification of Diseases, ninth revision, codes to identify cases of pneumomediastinum. The medical causes, nontraumatic and noniatrogenic, of pneumomediastinum were studied; intubated or trauma patients and patients having undergone procedures were excluded. Neonates were also excluded. Twenty-nine cases of pneumomediastinum were identified. Two patients (7%) had recurrent pneumomediastinum. Only the first episode of pneumomediastinum was included in the data analysis. Twenty males (69%) and nine females (31%) were affected. The most common medical causes of pneumomediastinum were asthma exacerbations (17/59%) and infections (8/28%). Over the 10-year period, the prevalence of pneumomediastinum in children with asthma exacerbations was 0.2% (21/10,472); 1% (1/126) in children with airway foreign bodies and 0.2% (1/351) in children with esophageal foreign bodies. The most common signs and symptoms were subcutaneous emphysema (22/76%), sore throat or neck pain (11/38%), and Hamman's crunch (3/10%). The most common complication was pneumothorax with small pneumothoraces in 2 patients (7%) and a tension pneumothorax in 1 asthmatic with recurrent pneumomediastinum. Patients without sore throat or neck pain and patients admitted to the intensive care unit had greater hospital lengths of stay. Pneumomediastinum appears to be uncommon in children. The most common medical causes were asthma and infections. The most common signs and symptoms were subcutaneous emphysema, sore throat or neck pain, and Hamman's crunch. The most common complication was pneumothorax. The clinical significance of pneumomediastinum is its cause and association with significant complications.

Parental attitudes toward BB and pellet guns.

As well as describing our pediatric BB and pellet gun injuries and the circumstances surrounding these injuries, we also evaluated parental perceptions of the dangers of BB and pellet guns. A convenience sample of three groups of parents and their children presenting to a Midwest, urban, children's hospital emergency department was prospectively enrolled. The three groups of parents included the injured group, which consisted of the parents whose children had been injured by BB or pellet guns; the gun group, which consisted of the parents who allowed their children to possess BB or pellet guns but had not sustained injury from these guns; and the no gun group, which consisted of the parents who did not allow their children to have these guns. All parents completed a survey concerning their attitudes toward BB and pellet guns. Twenty-eight parents completed questionnaires in each of the three groups. Most BB and pellet gun injuries occurred in adolescent males at home without adult supervision and were inflicted by a friend or by themselves. The injured group and the no gun group viewed BB and pellet guns as significantly more dangerous than the gun group. Parents who allow their children to have BB or pellet guns appear to misperceive their potential for injury by allowing their children to use these guns in an unsafe manner. Clinicians must educate parents about the significant potential for injury of nonpowdered guns.