Neural mechanisms and computations underlying stress effects on learning and memory

Stress has complex effects on memory function that can vary depending on the type of information that is learned and in relation to inter-individual characteristics. Recent work has also shown that stress can switch performance between memory systems, biasing it toward habit in detriment of spatial or goal-directed strategies. In addition, novel synaptic mechanisms have been implicated in the effects of stress in plasticity and memory. Computational modeling is emerging as a useful approach to integrate and to ascertain neural and cognitive computations underlying different effects of stress in memory. Having provided novel explanations for the inverted-U-shaped relationship between stress and cognitive performance, model-based analysis studies can improve our understanding of diverse effects of stress in cognition and psychopathology.     

Neural mechanisms underlying the evolvability of behaviour

The complexity of nervous systems alters the evolvability of behaviour. Complex nervous systems are phylogenetically constrained; nevertheless particular species-specific behaviours have repeatedly evolved, suggesting a predisposition towards those behaviours. Independently evolved behaviours in animals that share a common neural architecture are generally produced by homologous neural structures, homologous neural pathways and even in the case of some invertebrates, homologous identified neurons. Such parallel evolution has been documented in the chromatic sensitivity of visual systems, motor behaviours and complex social behaviours such as pair-bonding. The appearance of homoplasious behaviours produced by homologous neural substrates suggests that there might be features of these nervous systems that favoured the repeated evolution of particular behaviours. Neuromodulation may be one such feature because it allows anatomically defined neural circuitry to be re-purposed. The developmental, genetic and physiological mechanisms that contribute to nervous system complexity may also bias the evolution of behaviour, thereby affecting the evolvability of species-specific behaviour.     

A comparison of neural computations underlying stereo vision and sound localization.

Stereo vision and sound localization are behaviors that help organisms to orient in space. Stereo vision provides information about the distance of an object. In sound localization mainly directional signals are analyzed. Two specific cues, binocular disparities underlying stereo vision, and the interaural time difference, suited to represent azimuth in sound localization, have many computational problems in common, although they are generated in two different modalities. The extraction of both cues requires a comparison of signals that arise from two independent sensors, called two-sensor comparison here. This two-sensor comparison is achieved by algorithms similar to summation, half-wave rectification and multiplication. Since the underlying neurons are band-pass filters, the two-sensor comparison results in ambiguities. These are removed in a hierarchical way in several computational steps, involving squaring, inhibition and across-frequency integration.     

ESPD: a pattern detection model underlying gene expression profiles

MOTIVATION: DNA arrays permit rapid, large-scale screening for patterns of gene expression and simultaneously yield the expression levels of thousands of genes for samples. The number of samples is usually limited, and such datasets are very sparse in high-dimensional gene space. Furthermore, most of the genes collected may not necessarily be of interest and uncertainty about which genes are relevant makes it difficult to construct an informative gene space. Unsupervised empirical sample pattern discovery and informative genes identification of such sparse high-dimensional datasets present interesting but challenging problems. RESULTS: A new model called empirical sample pattern detection (ESPD) is proposed to delineate pattern quality with informative genes. By integrating statistical metrics, data mining and machine learning techniques, this model dynamically measures and manipulates the relationship between samples and genes while conducting an iterative detection of informative space and the empirical pattern. The performance of the proposed method with various array datasets is illustrated.     

Neural systems underlying episodic memory: insights from animal research

Two strategies used to uncover neural systems for episodic-like memory in animals are discussed: (i) an attribute of episodic memory (what? when? where?) is examined in order to reveal the neuronal interactions supporting that component of memory; and (ii) the connections of a structure thought to be central to episodic memory in humans are studied at a level of detail not feasible in humans. By focusing on spatial memory (where?) and the hippocampus, it has proved possible to bring the strategies together. A review of lesion, disconnection and immediate early-gene studies in animals reveals the importance of interactions between the hippocampus and specific nuclei in the diencephalon (most notably the anterior thalamic nuclei) for spatial memory. Other parts of this extended hippocampal system include the mammillary bodies and the posterior cingulate (retrosplenial) cortex. Furthermore, by combining lesion and immediate early-gene studies it is possible to show how the loss of one component structure or tract can influence the remaining regions in this group of structures. The validity of this convergent approach is supported by new findings showing that the same set of regions is implicated in anterograde amnesia in humans.     

Neural processes underlying conscious perception: Experimental findings and a global neuronal workspace framework

One striking property of perception is that it can be achieved in two seemingly different ways: either consciously or non-consciously. What distinguishes these two types of processing at the neural level? So far, empirical findings suggest that conscious perception is associated with an increase in activity at the sensory level, the specific involvement of a fronto-parietal network and an increase in long-distance functional connectivity and synchrony within a broad network of areas. We interpret these data in the framework of the global neuronal workspace model which proposes that the neural basis of conscious access is a sudden self-amplifying process leading to a global brain-scale pattern of activity. In contradiction with several theories which assume that there is a continuum of perception, associated with a gradual change in the intensity of brain activation, the model predicts a sharp non-linear transition between non-conscious and conscious processing.     

Analysis of a Schnute postulate-based unified growth model for model selection in evolutionary computations

In order to evaluate the feasibility of a combined evolutionary algorithm-information theoretic approach to select the best model from a set of candidate invasive species models in ecology, and/or to evolve the most parsimonious model from a suite of competing models by comparing their relative performance, it is prudent to use a unified model that covers a myriad of situations. Using Schnute's postulates as a starting point [Schnute, J., 1981. A versatile growth model with statistically stable parameters, Can. J. Fish Aquat. Sci. 38, 1128-1140], we present a single, unified model for growth that can be successfully utilized for model selection in evolutionary computations. Depending on the parameter settings, the unified equation can describe several growth mechanisms. Such a generalized model mechanism, which encompasses a suite of competing models, can be successfully implemented in evolutionary computational algorithms to evolve the most parsimonious model that best fits ground truth data. We have done exactly this by testing the effectiveness of our reaction-diffusion-advection (RDA) model in an evolutionary computation model selection algorithm. The algorithm was validated (with success) against field data sets of the Zebra mussel invasion of Lake Champlain in the United States.     

Effects of pre-motion electromyographic silent period on dynamic force exertion during a rapid ballistic movement in man

The effects of pre-motion silent period (PSP) on dynamic force exertion were studied in ten healthy subjects performing ballistic elbow extensions. The experiments were designed to evaluate the significance of mean differences between the averaged dynamic force curves of two groups: PSP-presence groups and PSP-absence groups. The presence of PSP was judged quantitatively and automatically by means of a newly developed method using statistical analysis. The results indicated that there were two effects of PSP on dynamic force exertion: one was a reducing effect, observed prior to the movement; the other was a reinforcing effect, observed in the first part of the ballistic movement. The duration of the reinforcement was significantly correlated with the duration of the reducing effect of PSP. The findings suggested that the reinforcement of dynamic force may be produced by the pre-stretch of agonistic muscles caused by prior force reduction due to PSP occurrence. The fact that PSP plays an important role in dynamic force exertion suggests that PSP may be incorporated in the central motor control system designed to interrupt the background activity, to stretch the agonist and to reinforce the dynamic force.     

Neural mechanisms underlying motivation of mental versus physical effort

Mental and physical efforts, such as paying attention and lifting weights, have been shown to involve different brain systems. These cognitive and motor systems, respectively, include cortical networks (prefronto-parietal and precentral regions) as well as subregions of the dorsal basal ganglia (caudate and putamen). Both systems appeared sensitive to incentive motivation: their activity increases when we work for higher rewards. Another brain system, including the ventral prefrontal cortex and the ventral basal ganglia, has been implicated in encoding expected rewards. How this motivational system drives the cognitive and motor systems remains poorly understood. More specifically, it is unclear whether cognitive and motor systems can be driven by a common motivational center or if they are driven by distinct, dedicated motivational modules. To address this issue, we used functional MRI to scan healthy participants while performing a task in which incentive motivation, cognitive, and motor demands were varied independently. We reasoned that a common motivational node should (1) represent the reward expected from effort exertion, (2) correlate with the performance attained, and (3) switch effective connectivity between cognitive and motor regions depending on task demand. The ventral striatum fulfilled all three criteria and therefore qualified as a common motivational node capable of driving both cognitive and motor regions of the dorsal striatum. Thus, we suggest that the interaction between a common motivational system and the different task-specific systems underpinning behavioral performance might occur within the basal ganglia.     

Neural mechanisms underlying acoustic behaviour of the frog Pseudophryne semimarmorata (Anura: Leptodactylidae)

Pseudophryne semimarmorata lacks a columella and tympanic membrane. However, at least males are relatively sensitive to sound. The mating call in this species can be inhibited by certain acoustic stimuli. The range of stimuli that inhibited calling was compared with that which evoked neural activity in midbrain auditory units. One of three types of unit which can be distinguished on the basis of best frequency, the high frequency unit, is presumed to be derived from the basilar papilla. High frequency units responded to the same range of sounds that inhibited calling. It is suggested that production of the mating call is initiated by a neural pacemaker, and sufficient neural input to this centre from the basilar papilla inhibits the pacemaker.     

Neural and psychological mechanisms underlying appetitive learning: links to drug addiction

The complexity of drug addiction mirrors the complexity of the psychological processes that motivate animals to work for any reinforcer, be it a natural reward or a drug. Here, we review the role of the nucleus accumbens, together with its dopaminergic and cortical innervation, in responding to reinforcement. One important contribution made by the nucleus accumbens is to the process through which neutral stimuli, once paired with a reinforcer such as a drug, have the capacity to motivate behaviour. This process may be one of several contributing to addiction, and it may be amenable to pharmacological intervention.     

Neural circuitry underlying linear representation of wind information in a nonspiking local interneuron of the cockroach

In the cercal system of the cockroach Periplaneta americana, primary sensory interneurons exhibiting a sharp directional sensitivity respond to wind in a linear manner whereas those exhibiting an omnidirectional sensitivity respond nonlinearly. For example, the wind-evoked response in an identifiable, nonspiking local interneuron, 101, which responds preferentially to wind from the left versus the right, is characterized exclusively by a differential first-order (linear) kernel. However, the slow potential response in a cercal giant interneuron, GI-1, is omnidirectional, and characterized by a second-order (nonlinear) kernel with an elongated depolarizing peak on the diagonal with two off-diagonal valleys. We here examined the neural circuitry underlying the linear and nonlinear representations of wind information by the deprivation of inputs from particular sets of cercal hair afferents. Electrical stimulation of the ipsilateral (related to the soma) cercal nerve elicited a depolarizing potential in 101, which was followed by delayed hyperpolarization. A continuous flow of 10^–4 M picrotoxin, which selectively blocked this delayed hyperpolarization, resulted in a significant change in the 101 response from linear to nonlinear. Because no frequency-doubling response was observed, the nonlinearity is due to signal compression (or rectification) that reflects the mechanical property of cercal afferents. This is consistent with the hypothesis that the linear representation in 101 is based on a subtraction process between two subsets of particular column hairs, whose best optimal directions are opposite to each other.Abbreviations GABA -aminobutyric acid - GI(s) giant interneuron(s) - GI-1, GI-2, GI-3, GI-4 giant interneuron 1,2,3,4 - ipsi ipsilateral - cont contralateral - MSE(s) mean square error(s)     

Neural circuits underlying imitation learning of hand actions: an event-related fMRI study

The neural bases of imitation learning are virtually unknown. In the present study, we addressed this issue using an event-related fMRI paradigm. Musically naive participants were scanned during four events: (1) observation of guitar chords played by a guitarist, (2) a pause following model observation, (3) execution of the observed chords, and (4) rest. The results showed that the basic circuit underlying imitation learning consists of the inferior parietal lobule and the posterior part of the inferior frontal gyrus plus the adjacent premotor cortex (mirror neuron circuit). This circuit, known to be involved in action understanding, starts to be active during the observation of the guitar chords. During pause, the middle frontal gyrus (area 46) plus structures involved in motor preparation (dorsal premotor cortex, superior parietal lobule, rostral mesial areas) also become active. Given the functional properties of area 46, a model of imitation learning is proposed based on interactions between this area and the mirror neuron system.     

Interspecific differences in crustacean homologous behavior: Neural mechanisms underlying the reversal of uropod steering movement

Summary Rolling of the body in the same direction induces an asymmetrical steering movement of uropods in the opposite directions in two closely related species of crayfish. InProcambarus clarkii the uropod on the upper side is spread out and closed on the lower side, whereas inCambaroides japonicus the uropod moves in the opposite direction. The stimulus detector, the statocysts, the effector, the uropod musculature, are neither structurally nor functionally significantly different in the two species. The results indicate that the opposite responses could be ascribed to differences in the interneuronal connections within the central nervous system of these two species.     

Towards a systematic approach to the dynamic adaptation of structured parallel computations using model predictive control

Adaptiveness is an essential feature for distributed parallel applications executed on dynamic environments like Grids and Clouds. Being adaptive means that parallel components can change their configuration at run-time (by modifying their parallelism degree or switching to a different parallel variant) to face irregular workload or to react to uncontrollable changes of the execution platform. A critical problem consists in the definition of adaptation strategies able to select optimal reconfigurations (minimizing operating costs and reconfiguration overhead) and achieve the stability of control decisions (avoiding unnecessary reconfigurations). This paper presents an approach to apply Model Predictive Control (a form of optimal control studied in Control Theory) to adaptive parallel computations expressed according to the Structured Parallel Programming methodology. We show that predictive control is amenable to achieve stability and optimality by relying on the predictability of structured parallelism patterns and the possibility to express analytical cost models of their QoS metrics. The approach has been exemplified on two case-studies, providing a first assessment of its potential and feasibility.     

Neural circuits underlying motor facilitation during observation of implied motion

Abstract

In the present study we used single and paired-pulse Transcranial Magnetic Stimulation (TMS) to evaluate the effect of implied motion on primary motor cortex microcircuits. We found that observation of the implied motion of a static image increases MEP amplitude and reduces short-interval intracortical inhibition (SICI), without significant modulation of intracortical facilitation and sensory-motor integration. Our results add to the existing literature on the activation of the observation-execution matching system and describe a selective modulation of GABAergic cortical microcircuits during observation of implied motion.     

Regressive logistic models for familial diseases: a formulation assuming an underlying liability model

Statistical models have been developed to delineate the major-gene and non-major-gene factors accounting for the familial aggregation of complex diseases. The mixed model assumes an underlying liability to the disease, to which a major gene, a multifactorial component, and random environment contribute independently. Affection is defined by a threshold on the liability scale. The regressive logistic models assume that the logarithm of the odds of being affected is a linear function of major genotype, phenotypes of antecedents and other covariates. An equivalence between these two approaches cannot be derived analytically. I propose a formulation of the regressive logistic models on the supposition of an underlying liability model of disease. Relatives are assumed to have correlated liabilities to the disease; affected persons have liabilities exceeding an estimable threshold. Under the assumption that the correlation structure of the relatives' liabilities follows a regressive model, the regression coefficients on antecedents are expressed in terms of the relevant familial correlations. A parsimonious parameterization is a consequence of the assumed liability model, and a one-to-one correspondence with the parameters of the mixed model can be established. The logits, derived under the class A regressive model and under the class D regressive model, can be extended to include a large variety of patterns of family dependence, as well as gene-environment interactions.