Contemporary approaches to neural circuit manipulation and mapping: focus on reward and addiction

Tying complex psychological processes to precisely defined neural circuits is a major goal of systems and behavioural neuroscience. This is critical for understanding adaptive behaviour, and also how neural systems are altered in states of psychopathology, such as addiction. Efforts to relate psychological processes relevant to addiction to activity within defined neural circuits have been complicated by neural heterogeneity. Recent advances in technology allow for manipulation and mapping of genetically and anatomically defined neurons, which when used in concert with sophisticated behavioural models, have the potential to provide great insight into neural circuit bases of behaviour. Here we discuss contemporary approaches for understanding reward and addiction, with a focus on midbrain dopamine and cortico-striato-pallidal circuits.     

Drosophila olfactory memory: single genes to complex neural circuits

A central goal of neuroscience is to understand how neural circuits encode memory and guide behaviour. Studying simple, genetically tractable organisms, such as Drosophila melanogaster, can illuminate principles of neural circuit organization and function. Early genetic dissection of D. melanogaster olfactory memory focused on individual genes and molecules. These molecular tags subsequently revealed key neural circuits for memory. Recent advances in genetic technology have allowed us to manipulate and observe activity in these circuits, and even individual neurons, in live animals. The studies have transformed D. melanogaster from a useful organism for gene discovery to an ideal model to understand neural circuit function in memory.     

Estrogen-responsive neural circuits governing male and female mating behavior in mice

Decades of knockout analyses have highlighted the crucial involvement of estrogen receptors and downstream genes in controlling mating behaviors. More recently, advancements in neural circuit research have unveiled a distributed subcortical network comprising estrogen-receptor or estrogen-synthesis-enzyme-expressing cells that transforms sensory inputs into sex-specific mating actions. This review provides an overview of the latest discoveries on estrogen-responsive neurons in various brain regions and the associated neural circuits that govern different aspects of male and female mating actions in mice. By contextualizing these findings within previous knockout studies of estrogen receptors, we emphasize the emerging field of “circuit genetics”, where identifying mating behavior-related neural circuits may allow for a more precise evaluation of gene functions within these circuits. Such investigations will enable a deeper understanding of how hormone fluctuation, acting through estrogen receptors and downstream genes, influences the connectivity and activity of neural circuits, ultimately impacting the manifestation of innate mating actions.     

Neural integration of reward, arousal, and feeding: Recruitment of VTA, lateral hypothalamus, and ventral striatal neurons

The ability to control neuronal activity using light pulses and optogenetic tools has revealed new properties of neural circuits and established causal relationships between activation of a single genetically defined population of neurons and complex behaviors. Here, we briefly review the causal effect of activity of six genetically defined neural circuits on behavior, including the dopaminergic neurons DA in the ventral tegmental area (VTA); the two main populations of medium-sized spiny neurons (D1- and D2-positive) in the striatum; the giant Cholinergic interneurons in the ventral striatum; and the hypocretin- and MCH- expressing neurons in the lateral hypothalamus. We argue that selective spatiotemporal recruitment and coordinated spiking activity among these cell type-specific neural circuits may underlie the neural integration of reward, learning, arousal and feeding.     

Genetic dissection of neural circuits

Understanding the principles of information processing in neural circuits requires systematic characterization of the participating cell types and their connections, and the ability to measure and perturb their activity. Genetic approaches promise to bring experimental access to complex neural systems, including genetic stalwarts such as the fly and mouse, but also to nongenetic systems such as primates. Together with anatomical and physiological methods, cell-type-specific expression of protein markers and sensors and transducers will be critical to construct circuit diagrams and to measure the activity of genetically defined neurons. Inactivation and activation of genetically defined cell types will establish causal relationships between activity in specific groups of neurons, circuit function, and animal behavior. Genetic analysis thus promises to reveal the logic of the neural circuits in complex brains that guide behaviors. Here we review progress in the genetic analysis of neural circuits and discuss directions for future research and development.     

Dynamics on the manifold: Identifying computational dynamical activity from neural population recordings

The question of how the collective activity of neural populations gives rise to complex behaviour is fundamental to neuroscience. At the core of this question lie considerations about how neural circuits can perform computations that enable sensory perception, decision making, and motor control. It is thought that such computations are implemented through the dynamical evolution of distributed activity in recurrent circuits. Thus, identifying dynamical structure in neural population activity is a key challenge towards a better understanding of neural computation. At the same time, interpreting this structure in light of the computation of interest is essential for linking the time-varying activity patterns of the neural population to ongoing computational processes. Here, we review methods that aim to quantify structure in neural population recordings through a dynamical system defined in a low-dimensional latent variable space. We discuss advantages and limitations of different modelling approaches and address future challenges for the field.     

The classic cadherins in synaptic specificity

During brain development, billions of neurons organize into highly specific circuits. To form specific circuits, neurons must build the appropriate types of synapses with appropriate types of synaptic partners while avoiding incorrect partners in a dense cellular environment. Defining the cellular and molecular rules that govern specific circuit formation has significant scientific and clinical relevance because fine scale connectivity defects are thought to underlie many cognitive and psychiatric disorders. Organizing specific neural circuits is an enormously complicated developmental process that requires the concerted action of many molecules, neural activity, and temporal events. This review focuses on one class of molecules postulated to play an important role in target selection and specific synapse formation: the classic cadherins. Cadherins have a well-established role in epithelial cell adhesion, and although it has long been appreciated that most cadherins are expressed in the brain, their role in synaptic specificity is just beginning to be unraveled. Here, we review past and present studies implicating cadherins as active participants in the formation, function, and dysfunction of specific neural circuits and pose some of the major remaining questions.     

The classic cadherins in synaptic specificity

During brain development, billions of neurons organize into highly specific circuits. To form specific circuits, neurons must build the appropriate types of synapses with appropriate types of synaptic partners while avoiding incorrect partners in a dense cellular environment. Defining the cellular and molecular rules that govern specific circuit formation has significant scientific and clinical relevance because fine scale connectivity defects are thought to underlie many cognitive and psychiatric disorders. Organizing specific neural circuits is an enormously complicated developmental process that requires the concerted action of many molecules, neural activity, and temporal events. This review focuses on one class of molecules postulated to play an important role in target selection and specific synapse formation: the classic cadherins. Cadherins have a well-established role in epithelial cell adhesion, and although it has long been appreciated that most cadherins are expressed in the brain, their role in synaptic specificity is just beginning to be unraveled. Here, we review past and present studies implicating cadherins as active participants in the formation, function, and dysfunction of specific neural circuits and pose some of the major remaining questions.     

幼年斑马鱼的视觉系统与捕食行为

神经环路的研究是揭示动物行为神经机制的关键。斑马鱼作为一种低等脊椎动物, 在神经环路的研究中有着独特优势。文章描述了斑马鱼视觉系统及其下游的神经环路, 重点讨论了它们在捕食行为中的可能作用。斑马鱼捕食行为主要依赖于视觉功能, 该过程涉及到视觉-运动通路各个层次的神经环路, 包括下游的网状脊髓命令神经元、脊髓内部的运动控制环路以及一些亟待研究的功能单元。随着在体记录和操纵神经元活动技术的成熟, 以及行为学范式的完善, 对斑马鱼捕食行为相关神经环路的研究将在未来数年内迅速发展, 同时也将推动神经科学相关研究的进步。     

Elongation factor 2 and fragile X mental retardation protein control the dynamic translation of Arc/Arg3.1 essential for mGluR-LTD

The initiation and coordination of activity in limb muscles are the main functions of neural circuits that control locomotion. Commissural neurons connect locomotor circuits on the two sides of the spinal cord, and represent the known neural substrate for left-right coordination. Here we demonstrate that a group of ipsilateral interneurons, V2a interneurons, plays an essential role in the control of left-right alternation. In the absence of V2a interneurons, the spinal cord fails to exhibit consistent left-right alternation. Locomotor burst activity shows increased variability, but flexor-extensor coordination is unaffected. Anatomical tracing studies reveal a direct excitatory input of V2a interneurons onto commissural interneurons, including a set of molecularly defined V0 neurons that drive left-right alternation. Our findings imply that the neural substrate for left-right coordination consists of at least two components; commissural neurons and a class of ipsilateral interneurons that activate commissural pathways.     

Masseter EMG activity during sleep and sleep bruxism

The masseter muscle is involved in the complex and coordinated oromotor behaviors such as mastication during wakefulness. The masseter electromyographic (EMG) activity decreases but does not disappear completely during sleep: the EMG activity is generally of low level and inhomogeneous for the duration, amplitude and intervals. The decreased excitability of the masseter motoneurons can be determined by neural substrates for NREM and REM sleep. The masseter EMG activity is increased in association with the level of arousal fluctuations within either sleep state. In addition, there are some motor events such as REM twitches, swallowing and rhythmic masticatory muscle activity (RMMA), whose generation might involve the additional activation of specific neural circuits. Sleep bruxism (SB) is characterized by exaggerated occurrence of RMMA. In SB, the rhythmic activation of the masseter muscle can reflect the rhythmic motor inputs to motoneurons through, at least in part, common neural circuits for generating masticatory rhythm under the facilitatory influences of transient arousals. However, it remains elusive as to which neural circuits determine the genesis of sleep bruxism. Based on the available knowledge on the masseter EMG activity during sleep, this review presents that the variety of the masseter EMG phenotypes during sleep can result from the combinations of the quantitative, spatial and temporal neural factors eventually sending net facilitatory inputs to trigeminal motoneurons under sleep regulatory systems.     

Functional organization of a neural network for aversive olfactory learning in Caenorhabditis elegans

Many animals use their olfactory systems to learn to avoid dangers, but how neural circuits encode naive and learned olfactory preferences, and switch between those preferences, is poorly understood. Here, we map an olfactory network, from sensory input to motor output, which regulates the learned olfactory aversion of Caenorhabditis elegans for the smell of pathogenic bacteria. Naive animals prefer smells of pathogens but animals trained with pathogens lose this attraction. We find that two different neural circuits subserve these preferences, with one required for the naive preference and the other specifically for the learned preference. Calcium imaging and behavioral analysis reveal that the naive preference reflects the direct transduction of the activity of olfactory sensory neurons into motor response, whereas the learned preference involves modulations to signal transduction to downstream neurons to alter motor response. Thus, two different neural circuits regulate a behavioral switch between naive and learned olfactory preferences.     

Progress in neural plasticity

The year 2009 marks the tenth anniversary of the founding of Institute of Neuroscience (ION) in the Shanghai campus of Chinese Academy of Sciences.     

Fading memory and kernel properties of generic cortical microcircuit models

It is quite difficult to construct circuits of spiking neurons that can carry out complex computational tasks. On the other hand even randomly connected circuits of spiking neurons can in principle be used for complex computational tasks such as time-warp invariant speech recognition. This is possible because such circuits have an inherent tendency to integrate incoming information in such a way that simple linear readouts can be trained to transform the current circuit activity into the target output for a very large number of computational tasks. Consequently we propose to analyze circuits of spiking neurons in terms of their roles as analog fading memory and non-linear kernels, rather than as implementations of specific computational operations and algorithms. This article is a sequel to [W. Maass, T. Natschl?ger, H. Markram, Real-time computing without stable states: a new framework for neural computation based on perturbations, Neural Comput. 14 (11) (2002) 2531-2560, Online available as #130 from: ], and contains new results about the performance of generic neural microcircuit models for the recognition of speech that is subject to linear and non-linear time-warps, as well as for computations on time-varying firing rates. These computations rely, apart from general properties of generic neural microcircuit models, just on capabilities of simple linear readouts trained by linear regression. This article also provides detailed data on the fading memory property of generic neural microcircuit models, and a quick review of other new results on the computational power of such circuits of spiking neurons.     

An imbalancing act: gap junctions reduce the backward motor circuit activity to bias C. elegans for forward locomotion

A neural network can sustain and switch between different activity patterns to execute multiple behaviors. By monitoring the decision making for directional locomotion through motor circuit calcium imaging in?behaving Caenorhabditis elegans (C.?elegans), we reveal that C.?elegans determines the directionality of movements by establishing an imbalanced output between the forward and backward motor circuits and that it alters directions by switching between these imbalanced states. We further demonstrate that premotor interneurons modulate endogenous motoneuron activity to establish the output imbalance. Specifically, the UNC-7 and UNC-9 innexin-dependent premotor interneuron-motoneuron coupling prevents a balanced output state that leads to movements without directionality. Moreover, they act as shunts to decrease the backward-circuit activity, establishing a persistent bias for the high forward-circuit output state that results in the inherent preference of C.?elegans for forward locomotion. This study demonstrates that imbalanced motoneuron activity underlies directional movement and establishes gap junctions as critical modulators of the properties and outputs of neural circuits.     

Primal-size neural circuits in meta-periodic interaction

Experimental observations of simultaneous activity in large cortical areas have seemed to justify a large network approach in early studies of neural information codes and memory capacity. This approach has overlooked, however, the segregated nature of cortical structure and functionality. Employing graph-theoretic results, we show that, given the estimated number of neurons in the human brain, there are only a few primal sizes that can be attributed to neural circuits under probabilistically sparse connectivity. The significance of this finding is that neural circuits of relatively small primal sizes in cyclic interaction, implied by inhibitory interneuron potentiation and excitatory inter-circuit potentiation, generate relatively long non-repetitious sequences of asynchronous primal-length periods. The meta-periodic nature of such circuit interaction translates into meta-periodic firing-rate dynamics, representing cortical information. It is finally shown that interacting neural circuits of primal sizes 7 or less exhaust most of the capacity of the human brain, with relatively little room to spare for circuits of larger primal sizes. This also appears to ratify experimental findings on the human working memory capacity.     

Developmental regulation of axon branching in the vertebrate nervous system

During nervous system development, axons generate branches to connect with multiple synaptic targets. As with axon growth and guidance, axon branching is tightly controlled in order to establish functional neural circuits, yet the mechanisms that regulate this important process are less well understood. Here, we review recent advances in the study of several common branching processes in the vertebrate nervous system. By focusing on each step in these processes we illustrate how different types of branching are regulated by extracellular cues and neural activity, and highlight some common principles that underlie the establishment of complex neural circuits in vertebrate development.     

Cortical development: the sources of spontaneous patterned activity

A recent study has found that spontaneous neural activity in the developing visual cortex has two distinct origins - local intracortical circuits and spontaneous activity in the retina.     

Illuminating neural circuits and behaviour in Caenorhabditis elegans with optogenetics

The development of optogenetics, a family of methods for using light to control neural activity via light-sensitive proteins, has provided a powerful new set of tools for neurobiology. These techniques have been particularly fruitful for dissecting neural circuits and behaviour in the compact and transparent roundworm Caenorhabditis elegans. Researchers have used optogenetic reagents to manipulate numerous excitable cell types in the worm, from sensory neurons, to interneurons, to motor neurons and muscles. Here, we show how optogenetics applied to this transparent roundworm has contributed to our understanding of neural circuits.     

The role of glial cells in synapse elimination

Excessive synapses generated during early development are eliminated extensively to form functionally mature neural circuits. Synapses in juvenile and mature brains are highly dynamic, and undergo remodeling processes through constant formation and elimination of dendritic spines. Although neural activity has been implicated in initiating the synapse elimination process cell-autonomously, the cellular and molecular mechanisms that transduce changes in correlated neural activity into structural changes in synapses are largely unknown. Recently, however, new findings provide evidence that in different species, glial cells, non-neuronal cell types in the nervous system are crucial in eliminating neural debris and unwanted synapses through phagocytosis. Glial cells not only clear fragmented axons and synaptic debris produced during synapse elimination, but also engulf unwanted synapses thereby actively promoting synapse elimination non-cell autonomously. These new findings support the important role of glial cells in the formation and maintenance of functional neural circuits in development as well as in adult stages and neurodegenerative diseases.