Memory and addiction: shared neural circuitry and molecular mechanisms

An important conceptual advance in the past decade has been the understanding that the process of drug addiction shares striking commonalities with neural plasticity associated with natural reward learning and memory. Basic mechanisms involving dopamine, glutamate, and their intracellular and genomic targets have been the focus of attention in this research area. These two neurotransmitter systems, widely distributed in many regions of cortex, limbic system, and basal ganglia, appear to play a key integrative role in motivation, learning, and memory, thus modulating adaptive behavior. However, many drugs of abuse exert their primary effects precisely on these pathways and are able to induce enduring cellular alterations in motivational networks, thus leading to maladaptive behaviors. Current theories and research on this topic are reviewed from an integrative systems perspective, with special emphasis on cellular, molecular, and behavioral aspects of dopamine D-1 and glutamate NMDA signaling, instrumental learning, and drug cue conditioning.     

Shaping embodied neural networks for adaptive goal-directed behavior

The acts of learning and memory are thought to emerge from the modifications of synaptic connections between neurons, as guided by sensory feedback during behavior. However, much is unknown about how such synaptic processes can sculpt and are sculpted by neuronal population dynamics and an interaction with the environment. Here, we embodied a simulated network, inspired by dissociated cortical neuronal cultures, with an artificial animal (an animat) through a sensory-motor loop consisting of structured stimuli, detailed activity metrics incorporating spatial information, and an adaptive training algorithm that takes advantage of spike timing dependent plasticity. By using our design, we demonstrated that the network was capable of learning associations between multiple sensory inputs and motor outputs, and the animat was able to adapt to a new sensory mapping to restore its goal behavior: move toward and stay within a user-defined area. We further showed that successful learning required proper selections of stimuli to encode sensory inputs and a variety of training stimuli with adaptive selection contingent on the animat's behavior. We also found that an individual network had the flexibility to achieve different multi-task goals, and the same goal behavior could be exhibited with different sets of network synaptic strengths. While lacking the characteristic layered structure of in vivo cortical tissue, the biologically inspired simulated networks could tune their activity in behaviorally relevant manners, demonstrating that leaky integrate-and-fire neural networks have an innate ability to process information. This closed-loop hybrid system is a useful tool to study the network properties intermediating synaptic plasticity and behavioral adaptation. The training algorithm provides a stepping stone towards designing future control systems, whether with artificial neural networks or biological animats themselves.     

Neural mechanisms of reward-related motor learning

The analysis of the neural mechanisms responsible for reward-related learning has benefited from recent studies of the effects of dopamine on synaptic plasticity. Dopamine-dependent synaptic plasticity may lead to strengthening of selected inputs on the basis of an activity-dependent conjunction of sensory afferent activity, motor output activity, and temporally related firing of dopamine cells. Such plasticity may provide a link between the reward-related firing of dopamine cells and the acquisition of changes in striatal cell activity during learning. This learning mechanism may play a special role in the translation of reward signals into context-dependent response probability or directional bias in movement responses.     

Integration of bimodal looming signals through neuronal coherence in the temporal lobe

The ability to integrate information across multiple sensory systems offers several behavioral advantages, from quicker reaction times and more accurate responses to better detection and more robust learning. At the neural level, multisensory integration requires large-scale interactions between different brain regions--the convergence of information from separate sensory modalities, represented by distinct neuronal populations. The interactions between these neuronal populations must be fast and flexible, so that behaviorally relevant signals belonging to the same object or event can be immediately integrated and integration of unrelated signals can be prevented. Looming signals are a particular class of signals that are behaviorally relevant for animals and that occur in both the auditory and visual domain. These signals indicate the rapid approach of objects and provide highly salient warning cues about impending impact. We show here that multisensory integration of auditory and visual looming signals may be mediated by functional interactions between auditory cortex and the superior temporal sulcus, two areas involved in integrating behaviorally relevant auditory-visual signals. Audiovisual looming signals elicited increased gamma-band coherence between these areas, relative to unimodal or receding-motion signals. This suggests that the neocortex uses fast, flexible intercortical interactions to mediate multisensory integration.     

下丘脑-垂体-肾上腺皮质轴应激反应的中枢控制

应激反应是所有生物对紧张性事件的适应性反应,对生物的存活具有十分重要的意义。应激反应的主要特征是下丘脑－垂体－肾上腺皮质（ＨＰＡ）轴激活。ＨＰＨ轴激活的呆区控制十分复杂。海马参与整合感知的信息、解释环境信息的意义及定调行为反应和神经内分泌反应。杏仁核是应激性行为反应以及自主神经和神经内分泌反应的行旅地部位。下丘脑室６ 有直接激活ＨＰＡ轴的作用。负反馈机制、下丘脑局部回路和细胞因子也可能参与了调节Ｈ     

Learning through maps: functional significance of topographic organization in primary sensory cortex.

The presence of "maps" in sensory cortex is a hallmark of the mammalian nervous system, but the functional significance of topographic organization has been called into question by physiological studies claiming that patterns of neural behavioral activity transcend topographic boundaries. This paper discusses recent behavioral and physiological studies suggesting that, when animals or human subjects learn perceptual tasks, the neural modifications associated with the learning are distributed according to the spatial arrangement of the primary sensory cortical map. Topographical cortical representations of sensory events, therefore, appear to constitute a true structural framework for information processing and plasticity.     

Neural systems for behavioral activation and reward.

The circuitry mediating the integration of reward perception and adaptive behavioral responses has been further refined. Recent developments indicate that the nucleus accumbens has a primary role in motivational circuitry, whereas afferents to the nucleus accumbens, in part, subserve distinct functions. Dopaminergic afferents serve to signal changes in rewarding stimuli, whereas glutamatergic input from the amygdala serves to cue behavior to conditioned reward, and afferents from the prefrontal cortex integrate information from short-term memory into behavioral responses.     

Candidate genes for panic disorder: insight from human and mouse genetic studies

Panic disorder is a major cause of medical attention with substantial social and health service cost. Based on pharmacological studies, research on its etiopathogenesis has been focused on the possible dysfunction of specific neurotransmitter systems. However, recent work has related the genes involved in development, synaptic plasticity and synaptic remodeling to anxiety disorders. This implies that learning processes and changes in perception, interpretation and behavioral responses to environmental stimuli are essential for development of complex anxiety responses secondary to the building of specific brain neural circuits and to adult plasticity. The focus of this review is on progress achieved in identifying genes that confer increased risk for panic disorder through genetic epidemiology and the use of genetically modified mouse models. The integration of human and animal studies targeting behavioral, systems-level, cellular and molecular levels will most probably help identify new molecules with potential impact on the pathogenetic aspects of the disease.     

Parallel and interrelated neural systems underlying adaptive navigation

The ability to process in parallel multiple forms of sensoryinformation, and link sensory-sensory associations to behavior,presumably allows for the opportunistic use of the most reliableand predictive sensory modalities in diverse behavioral contexts.Evolutionary considerations indicate that such processing mayrepresent a fundamental operating principle underlying complexsensory associations and sensory-motor integration. Here, wesuggest that animal navigation is a particularly useful modelof such opportunistic use of sensory and motor information becauseit is possible to study directly the effects of memory on neuralsystem functions. First, comparative evidence for parallel processingacross multiple brain structures during navigation is providedfrom the literatures on fish and rodent navigation. Then, basedon neurophysiological evidence of coordinated, multiregionalprocessing, we provide a neurobiological explanation of learningand memory effects on neural circuitry mediating navigation.     

Recording Single Neurons' Action Potentials from Freely Moving Pigeons Across Three Stages of Learning

While the subject of learning has attracted immense interest from both behavioral and neural scientists, only relatively few investigators have observed single-neuron activity while animals are acquiring an operantly conditioned response, or when that response is extinguished. But even in these cases, observation periods usually encompass only a single stage of learning, i.e. acquisition or extinction, but not both (exceptions include protocols employing reversal learning; see Bingman et al.¹ for an example). However, acquisition and extinction entail different learning mechanisms and are therefore expected to be accompanied by different types and/or loci of neural plasticity.Accordingly, we developed a behavioral paradigm which institutes three stages of learning in a single behavioral session and which is well suited for the simultaneous recording of single neurons'' action potentials. Animals are trained on a single-interval forced choice task which requires mapping each of two possible choice responses to the presentation of different novel visual stimuli (acquisition). After having reached a predefined performance criterion, one of the two choice responses is no longer reinforced (extinction). Following a certain decrement in performance level, correct responses are reinforced again (reacquisition). By using a new set of stimuli in every session, animals can undergo the acquisition-extinction-reacquisition process repeatedly. Because all three stages of learning occur in a single behavioral session, the paradigm is ideal for the simultaneous observation of the spiking output of multiple single neurons. We use pigeons as model systems, but the task can easily be adapted to any other species capable of conditioned discrimination learning.     

Information-processing demands in electrosensory and mechanosensory lateral line systems.

The electrosensory and mechanosensory lateral line systems of fish exhibit many common features in their structural and functional organization, both at the sensory periphery as well as in central processing pathways. These two sensory systems also appear to play similar roles in many behavioral tasks such as prey capture, orientation with respect to external environmental cues, navigation in low-light conditions, and mediation of interactions with nearby animals. In this paper, we briefly review key morphological, physiological, and behavioral aspects of these two closely related sensory systems. We present arguments that the information processing demands associated with spatial processing are likely to be quite similar, due largely to the spatial organization of both systems and the predominantly dipolar nature of many electrosensory and mechanosensory stimulus fields. Demands associated with temporal processing may be quite different, however, due primarily to differences in the physical bases of electrosensory and mechanosensory stimuli (e.g. speed of transmission). With a better sense of the information processing requirements, we turn our attention to an analysis of the functional organization of the associated first-order sensory nuclei in the hindbrain, including the medial octavolateral nucleus (MON), dorsal octavolateral nucleus (DON), and electrosensory lateral line lobe (ELL). One common feature of these systems is a set of neural mechanisms for improving signal-to-noise ratios, including mechanisms for adaptive suppression of reafferent signals. This comparative analysis provides new insights into how the nervous system extracts biologically significant information from dipolar stimulus fields in order to solve a variety of behaviorally relevant problems faced by aquatic animals.     

Different neuroplasticity for task targets and distractors

Adult learning-induced sensory cortex plasticity results in enhanced action potential rates in neurons that have the most relevant information for the task, or those that respond strongly to one sensory stimulus but weakly to its comparison stimulus. Current theories suggest this plasticity is caused when target stimulus evoked activity is enhanced by reward signals from neuromodulatory nuclei. Prior work has found evidence suggestive of nonselective enhancement of neural responses, and suppression of responses to task distractors, but the differences in these effects between detection and discrimination have not been directly tested. Using cortical implants, we defined physiological responses in macaque somatosensory cortex during serial, matched, detection and discrimination tasks. Nonselective increases in neural responsiveness were observed during detection learning. Suppression of responses to task distractors was observed during discrimination learning, and this suppression was specific to cortical locations that sampled responses to the task distractor before learning. Changes in receptive field size were measured as the area of skin that had a significant response to a constant magnitude stimulus, and these areal changes paralleled changes in responsiveness. From before detection learning until after discrimination learning, the enduring changes were selective suppression of cortical locations responsive to task distractors, and nonselective enhancement of responsiveness at cortical locations selective for target and control skin sites. A comparison of observations in prior studies with the observed plasticity effects suggests that the non-selective response enhancement and selective suppression suffice to explain known plasticity phenomena in simple spatial tasks. This work suggests that differential responsiveness to task targets and distractors in primary sensory cortex for a simple spatial detection and discrimination task arise from nonselective increases in response over a broad cortical locus that includes the representation of the task target, and selective suppression of responses to the task distractor within this locus.     

Neural mechanisms for filtering self-generated sensory signals in cerebellum-like circuits

This review focuses on recent progress in understanding mechanisms for filtering self-generated sensory signals in cerebellum-like circuits in fish and mammals. Recent in vitro studies in weakly electric gymnotid fish have explored the interplay among anti-Hebbian plasticity, synaptic dynamics, and feedforward inhibition in canceling self-generated electrosensory inputs. Studies of the mammalian dorsal cochlear nucleus have revealed multimodal integration and anti-Hebbian plasticity, suggesting that this circuit may adaptively filter incoming auditory information. In vivo studies in weakly electric mormryid fish suggest a key role for granule cell coding in sensory filtering. The clear links between synaptic plasticity and systems level sensory filtering in cerebellum-like circuits may provide insights into hypothesized adaptive filtering functions of the cerebellum itself.     

昆虫的化学感觉机理

昆虫是通过化学感觉器与其周围环境中的大量化学信息发生联系的。通过特定的化学感觉机制 ,昆虫可感知来自种内和种间 ,以及无机环境中的各种化学信息 ,并由此而作出相应的行为反应 ,从而为其自身寻找适宜的食物、配偶以及生存与繁殖场所 (如躲避天敌、避免或减少竞争等等 ) ,达到最大的繁殖成功。阐明昆虫的化学感觉机理 ,不仅可在理论上进一步加深对昆虫与植物、昆虫与昆虫相互关系的了解 ,而且可在实践上为开发害虫治理的新途径提供理论指导。本文将根据目前的最新研究成果 ,主要就昆虫的化学感觉机理 ,包括嗅觉和味觉机理作一综述 ,以期…     

Persistent sodium current is a nonsynaptic substrate for long-term associative memory

Although synaptic plasticity is widely regarded as the primary mechanism of memory [1], forms of nonsynaptic plasticity, such as increased somal or dendritic excitability or membrane potential depolarization, also have been implicated in learning in both vertebrate and invertebrate experimental systems [2], [3], [4], [5], [6] and [7]. Compared to synaptic plasticity, however, there is much less information available on the mechanisms of specific types of nonsynaptic plasticity involved in well-defined examples of behavioral memory. Recently, we have shown that learning-induced somal depolarization of an identified modulatory cell type (the cerebral giant cells, CGCs) of the snail Lymnaea stagnalis encodes information that enables the expression of long-term associative memory [8]. The Lymnaea CGCs therefore provide a highly suitable experimental system for investigating the ionic mechanisms of nonsynaptic plasticity that can be linked to behavioral learning. Based on a combined behavioral, electrophysiological, immunohistochemical, and computer simulation approach, here we show that an increase of a persistent sodium current of this neuron underlies its delayed and persistent depolarization after behavioral single-trial classical conditioning. Our findings provide new insights into how learning-induced membrane level changes are translated into a form of long-lasting neuronal plasticity already known to contribute to maintained adaptive modifications at the network and behavioral level [8].     

Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making

According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject''s learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations.     

Role of anticipated reward in cognitive behavioral control

The lateral prefrontal cortex (LPFC), which is important for higher cognitive activity, is also concerned with motivational operations; this is exemplified by its activity in relation to expectancy of rewards. In the LPFC, motivational information is integrated with cognitive information, as demonstrated by the enhancement of working-memory-related activity by reward expectancy. Such activity would be expected to induce changes in attention and, subsequently, to modify behavioral performance. Recently, the effects of motivation and emotion on neural activities have been examined in several areas of the brain in relation to cognitive-task performance. Of these areas, the LPFC seems to have the most important role in adaptive goal-directed behavior, by sending top-down attention-control signals to other areas of the brain.     

Multisensory Control of Multimodal Behavior: Do the Legs Know What the Tongue Is Doing?

Understanding of adaptive behavior requires the precisely controlled presentation of multisensory stimuli combined with simultaneous measurement of multiple behavioral modalities. Hence, we developed a virtual reality apparatus that allows for simultaneous measurement of reward checking, a commonly used measure in associative learning paradigms, and navigational behavior, along with precisely controlled presentation of visual, auditory and reward stimuli. Rats performed a virtual spatial navigation task analogous to the Morris maze where only distal visual or auditory cues provided spatial information. Spatial navigation and reward checking maps showed experience-dependent learning and were in register for distal visual cues. However, they showed a dissociation, whereby distal auditory cues failed to support spatial navigation but did support spatially localized reward checking. These findings indicate that rats can navigate in virtual space with only distal visual cues, without significant vestibular or other sensory inputs. Furthermore, they reveal the simultaneous dissociation between two reward-driven behaviors.