'Feedback' for feeding

A new study discovered that ventral pallidal neurons projecting back to the nucleus accumbens promote consumption. The findings call into question the accepted direction of information flow through the ventral basal ganglia and open new avenues for studying how consumption is regulated in proportion to subjective value

Independent circuits in the basal ganglia for the evaluation and selection of actions

The basal ganglia are critical for selecting actions and evaluating their outcome. Although the circuitry for selection is well understood, how these nuclei evaluate the outcome of actions is unknown. Here, we show in lamprey that a separate evaluation circuit, which regulates the habenula-projecting globus pallidus (GPh) neurons, exists within the basal ganglia. The GPh neurons are glutamatergic and can drive the activity of the lateral habenula, which, in turn, provides an indirect inhibitory influence on midbrain dopamine neurons. We show that GPh neurons receive inhibitory input from the striosomal compartment of the striatum. The striosomal input can reduce the excitatory drive to the lateral habenula and, consequently, decrease the inhibition onto the dopaminergic system. Dopaminergic neurons, in turn, provide feedback that inhibits the GPh. In addition, GPh neurons receive direct projections from the pallium (cortex in mammals), which can increase the GPh activity to drive the lateral habenula to increase the inhibition of the neuromodulatory systems. This circuitry, thus, differs markedly from the "direct" and "indirect" pathways that regulate the pallidal (e.g., globus pallidus) output nuclei involved in the control of motion. Our results show that a distinct reward-evaluation circuit exists within the basal ganglia, in parallel to the direct and indirect pathways, which select actions. Our results suggest that these circuits are part of the fundamental blueprint that all vertebrates use to select actions and evaluate their outcome

Neural Networks With Motivation

Animals rely on internal motivational states to make decisions. The role of motivational salience in decision making is in early stages of mathematical understanding. Here, we propose a reinforcement learning framework that relies on neural networks to learn optimal ongoing behavior for dynamically changing motivation values. First, we show that neural networks implementing Q-learning with motivational salience can navigate in environment with dynamic rewards without adjustments in synaptic strengths when the needs of an agent shift. In this setting, our networks may display elements of addictive behaviors. Second, we use a similar framework in hierarchical manager-agent system to implement a reinforcement learning algorithm with motivation that both infers motivational states and behaves. Finally, we show that, when trained in the Pavlovian conditioning setting, the responses of the neurons in our model resemble previously published neuronal recordings in the ventral pallidum, a basal ganglia structure involved in motivated behaviors. We conclude that motivation allows Q-learning networks to quickly adapt their behavior to conditions when expected reward is modulated by agent’s dynamic needs. Our approach addresses the algorithmic rationale of motivation and makes a step toward better interpretability of behavioral data via inference of motivational dynamics in the brain

A Model for the Analysis of Caries Occurrence in Primary Molar Tooth Surfaces

Recently methods of caries quantification in the primary dentition have moved away from summary ‘whole mouth’ measures at the individual level to methods based on generalised linear modelling (GLM) approaches or survival analysis approaches. However, GLM approaches based on logistic transformation fail to take into account the time-dependent process of tooth/surface survival to caries. There may also be practical difficulties associated with casting parametric survival-based approaches in a complex multilevel hierarchy and the selection of an optimal survival distribution, while non-parametric survival methods are not generally suitable for the assessment of supplementary information recorded on study participants. In the current investigation, a hybrid semi-parametric approach comprising elements of survival-based and GLM methodologies suitable for modelling of caries occurrence within fixed time periods is assessed, using an illustrative multilevel data set of caries occurrence in primary molars from a cohort study, with clustering of data assumed to occur at surface and tooth levels. Inferences of parameter significance were found to be consistent with previous parametric survival-based analyses of the same data set, with gender, socio-economic status, fluoridation status, tooth location, surface type and fluoridation status-surface type interaction significantly associated with caries occurrence. The appropriateness of the hierarchical structure facilitated by the hybrid approach was also confirmed. Hence the hybrid approach is proposed as a more appropriate alternative to primary caries modelling than non-parametric survival methods or other GLM-based models, and as a practical alternative to more rigorous survival-based methods unlikely to be fully accessible to most researchers

The Lateral Habenula Circuitry: Reward Processing and Cognitive Control

There has been a growing interest in understanding the role of the lateral habenula (LHb) in reward processing, affect regulation, and goal-directed behaviors. The LHb gets major inputs from the habenula-projecting globus pallidus and the mPFC, sending its efferents to the dopaminergic VTA and SNc, serotonergic dorsal raphe nuclei, and the GABAergic rostromedial tegmental nucleus. Recent studies have made advances in our understanding of the LHb circuit organization, yet the precise mechanisms of its involvement in complex behaviors are largely unknown. To begin to address this unresolved question, we present here emerging cross-species perspectives with a goal to provide a more refined understanding of the role of the LHb circuits in reward and cognition. We begin by highlighting recent findings from rodent experiments using optogenetics, electrophysiology, molecular, pharmacology, and tracing techniques that reveal diverse neural phenotypes in the LHb circuits that may underlie previously undescribed behavioral functions. We then discuss results from electrophysiological studies in macaques that suggest that the LHb cooperates with the anterior cingulate cortex to monitor action outcomes and signal behavioral adjustment. Finally, we provide an integrated summary of cross-species findings and discuss how further research on the connectivity, neural signaling, and physiology of the LHb circuits can deepen our understanding of the role of the LHb in normal and maladaptive behaviors associated with mental illnesses and drug abuse

Population of 13Be in a Nucleon Exchange Reaction

The neutron-unbound nucleus 13Be was populated with a nucleon-exchange reaction from a 71 MeV/u secondary 13B beam. The decay energy spectrum was reconstructed using invariant mass spectroscopy based on 12Be fragments in coincidence with neutrons. The data could be described with an s-wave resonance at E = 0.73(9) MeV with a width of Gamma = 1.98(34) MeV and a d-wave resonance at E = 2.56(13) MeV with a width of Gamma = 2.29(73) MeV. The observed spectral shape is consistent with previous one-proton removal reaction measurements from 14B.Comment: Published in Phys. Rev.

Further Insights into the Reaction Be14(CH2,X)10He

A previously published measurement of the reaction of a 59 MeV/nucleon 14Be beam on a deuterated polyethylene target was further analyzed to search for 12He as well as initial state effects in the population of the 10He ground state. No evidence for either was found. A lower limit of about 1 MeV was determined for a possible resonance in 12He. In addition, the three-body decay energy spectrum of 10He could not be described by a reaction mechanism calculation based on the halo structure of the initial 14Be assuming a direct α-particle removal reaction

Neutron-Unbound Excited States of 23N

Neutron unbound states in 23N were populated via proton knockout from an 83.4 MeV/nucleon 24O beam on a liquid deuterium target. The two-body decay energy displays two peaks at E1∼100keV and E2∼1MeV with respect to the neutron separation energy. The data are consistent with shell model calculations predicting resonances at excitation energies of ∼3.6MeV and ∼4.5MeV. The selectivity of the reaction implies that these states correspond to the first and second 3/2− states. The energy of the first state is about 1.3 MeV lower than the first excited 2+ in 24O. This decrease is largely due to coupling with the πp−13/2 hole along with a small reduction of the N=16 shell gap in 23N