Fear learning and memory across adolescent development: Hormones and Behavior Special Issue: Puberty and Adolescence

Throughout the past several decades, studies have uncovered a wealth of information about the neural circuitry underlying fear learning and extinction that has helped to inform treatments for fear-related disorders such as post-traumatic stress and anxiety. Yet, up to 40% of people do not respond to such treatments. Adolescence, in particular, is a developmental stage during which anxiety disorders peak, yet little is known about the development of fear-related neural circuitry during this period. Moreover, pharmacological and behavioral therapies that have been developed are based on mature circuitry and function. Here, we review neural circuitry implicated in fear learning and data from adolescent mouse and human fear learning studies. In addition, we propose a developmental model of fear neural circuitry that may optimize current treatments and inform when, during development, specific treatments for anxiety may be most effective.     

Contributions of estrogen receptor-α and estrogen receptor-β to the regulation of behavior

Studies of the mechanisms by which estrogens influence brain function and behavior have advanced from the explication of individual hormone receptors, neural circuitry and individual gene expression. Now, we can report patterns of estrogen receptor subtype contributions to patterns of behavior. Moreover, new work demonstrates important contributions of nuclear receptor coactivator expression in the central nervous system. In this paper, our current state of knowledge is reviewed.     

Toward molecular genetic dissection of neural circuits for emotional and motivational behaviors

How does the brain process the emotional meaning of sensory stimuli and in turn drive behavior?Studies in the mammalian systems have identified various brain regions and neurotransmitter systems that are critical for emotional and motivational behaviors and have implicated their involvement in neuropsychiatric disorders including anxiety, depression, schizophrenia, and addiction. Despite these significant advancements, the precise neural circuitry underlying emotional and motivational behaviors remains to be understood at molecular and cellular levels. In this review, we discuss how the vertebrate model organism zebrafish can help us gain insights into the underlying circuitry. We first describe studies of several simple and relevant preference behaviors in this model organism, and then discuss approaches and technologies that can be used to uncover the development and function of neural circuits underlying these behaviors.     

Axonal signals in the assembly of neural circuitry

Recent work in Drosophila and rodents has revealed that proteins transported along axons and delivered to pathway and target cell populations play important roles in the construction of neural circuitry. Interestingly, the parallels between these systems may extend to the identities of some of the molecules involved.     

Sexual Behaviour: Do a Few Dead Neurons Make the Difference?

Why do males and females behave so differently? Sexually dimorphic neural circuitry has just been found in parts of the fly's brain thought to control mating behaviour. Might this explain why males and females have such distinct sexual behaviours?     

Regional brain function, emotion and disorders of emotion.

Significant progress has been made in our understanding of the neural substrates of emotion and its disorders. Neuroimaging methods have been used to characterize the circuitry underlying disorders of emotion. Particular emphasis has been placed on the prefrontal cortex, anterior cingulate, parietal cortex, and the amygdala as critical components of the circuitry that may be dysfunctional in both depression and anxiety.     

Sensitive periods and circuits for learned birdsong

Experience influences the development of certain behaviors and their associated neural circuits during a discrete period after birth. Songbirds, with their highly quantifiable vocal output and well-delineated vocal control circuitry, provide an excellent context in which to examine the neural mechanisms regulating sensitive periods for learning. Recent discoveries indicate that auditory input to the vocal control circuitry in songbirds is dynamically modulated and show that neural circuitry previously thought to be used only in plastic juvenile song may also actively maintain stable adult song. These findings provide important clues to how sensitive periods for auditory feedback and vocal plasticity are regulated during song development.     

Control of male sexual behavior in Drosophila by the sex determination pathway

Understanding how genes influence behavior, including sexuality, is one of biology's greatest challenges. Much of the recent progress in understanding how single genes can influence behavior has come from the study of innate behaviors in the fruit fly Drosophila melanogaster. In particular, the elaborate courtship ritual performed by the male fly has provided remarkable insights into how the neural circuitry underlying sexual behavior--which is largely innate in flies--is built into the nervous system during development, and how this circuitry functions in the adult. In this review we will discuss how genes of the sex determination pathway in Drosophila orchestrate the developmental events necessary for sex-specific behaviors and physiology, and the broader lessons this can teach us about the mechanisms underlying the development of sex-specific neural circuitry.     

Musings on the wanderer: what's new in our understanding of vago-vagal reflexes? V. Remodeling of vagus and enteric neural circuitry after vagal injury

The vago-vagal reflexes mediate a wide range of digestive functions such as motility, secretion, and feeding behavior. Previous articles in this series have discussed the organization and functions of this important neural pathway. The focus of this review will be on some of the events responsible for the adaptive changes of the vagus and the enteric neutral circuitry that occur after vagal injury. The extraordinary plasticity of the neural systems to regain functions when challenged with neural injury will be discussed. In general, neuropeptides and transmitter-related enzymes in the vagal sensory neurons are downregulated after vagal injury to protect against further injury. Conversely, molecules previously absent or present at low levels begin to appear or are upregulated and are available to participate in the survival-regeneration process. Neurotrophins and other related proteins made at the site of the lesion and then retrogradely transported to the soma may play an important role in the regulation of neuropeptide phenotype expression and axonal growth. Vagal injury also triggers adaptive changes within the enteric nervous system to minimize the loss of gastrointestinal functions resulting from the interruption of the vago-vagal pathways. These may include rearrangement of the enteric neural circuitry, changes in the electrophysiological properties of sensory receptors in the intramural neural networks, an increase in receptor numbers, and changes in the affinity states of receptors on enteric neurons.     

Neurobiology of the sleep-wake cycle: sleep architecture, circadian regulation, and regulatory feedback

This mini-review article presents the remarkable progress that has been made in the past decade in our understanding of the neural circuitry underlying the regulation of sleep-wake states and circadian control of behaviors. Following a brief introduction to sleep architecture and physiology, the authors describe the neural circuitry and neurotransmitters that regulate sleep and cortical arousal (i.e., wakefulness). They next examine how sleep and wakefulness are regulated by mutual inhibition between sleep-and arousal-promoting circuitry and how this interaction functions analogously to an electronic "flip-flop" switch that ensures behavioral state stability. The authors then discuss the role of circadian and homeostatic processes in the consolidation of sleep, including the physiologic basis of homeostatic sleep drive (i.e., wake-dependent increase in sleep propensity) and the role of the SCN in the circadian regulation of sleep-wake cycles. Finally, they describe the hypothalamic circuitry for the integration of photic and nonphotic environmental time cues and how this integration allows organisms to sculpt patterns of rest-activity and sleep-wake cycles that are optimally adaptive.     

Knowledge management of the neuroscientific literature: the data model and underlying strategy of the NeuroScholar system.

This paper describes the underlying strategy and system's design of a knowledge management system for the neuroscientific literature called 'NeuroScholar'. The problem that the system is designed to address is to delineate fully the neural circuitry involved in a specific behaviour. The use of this system provides experimental neuroscientists with a new method of building computational models ('knowledge models') of the contents of the published literature. These models may provide input for analysis (conceptual or computational), or be used as constraint sets for conventional neural modelling work. The underlying problems inherent in this approach, the general framework for the proposed solution, the practical issues concerning usage of the system and a detailed, technical account of the system are described. The author uses a widely used software specification language (the Universal Modelling Language) to describe the design of the system and present examples from published work concerned with classical eyeblink conditioning in the rabbit.     

Neural mechanisms of imitation

Recent advances in our knowledge of the neural mechanisms of imitation suggest that there is a core circuitry of imitation comprising the superior temporal sulcus and the 'mirror neuron system', which consists of the posterior inferior frontal gyrus and adjacent ventral premotor cortex, as well as the rostral inferior parietal lobule. This core circuitry communicates with other neural systems according to the type of imitation performed. Imitative learning is supported by interaction of the core circuitry of imitation with the dorsolateral prefrontal cortex and perhaps motor preparation areas--namely, the mesial frontal, dorsal premotor and superior parietal areas. By contrast, imitation as a form of social mirroring is supported by interaction of the core circuitry of imitation with the limbic system.     

A Neural Infrastructure for Rhythmic Motor Patterns

It is possible to work out the neural circuity of many invertebrate central pattern generators (CPGs) thereby providing a basis for linking cellular processes to actual behaviors. This review summarizes the infrastructure of the two CPGs in the lobster stomatogastric ganglion in terms of circuitry, ionic conductances and chemical modulation by amines and peptides. Analysis of the circuit using modeling techniques including the use of electronic neurons closes the chapter.     

Probing neural circuitry and function with electrical microstimulation

Since the discovery of the nervous system's electrical excitability more than 200 years ago, neuroscientists have used electrical stimulation to manipulate brain activity in order to study its function. Microstimulation has been a valuable technique for probing neural circuitry and identifying networks of neurons that underlie perception, movement and cognition. In this review, we focus on the use of stimulation in behaving primates, an experimental system that permits causal inferences to be made about the effect of stimulation-induced activity on the resulting behaviour or neural signals elsewhere in the brain.     

Evolution of motor innervation to vertebrate fins and limbs

The evolution and diversification of vertebrate behaviors associated with locomotion depend highly on the functional transformation of paired appendages. Although the evolution of fins into limbs has long been a focus of interest to scientists, the evolution of neural control during this transition has not received much attention. Recent studies have provided significant progress in the understanding of the genetic and developmental bases of the evolution of fin/limb motor circuitry in vertebrates. Here we compare the organization of the motor neurons in the spinal cord of various vertebrates. We also discuss recent advances in our understanding of these events and how they can provide a mechanistic explanation for the evolution of fin/limb motor circuitry in vertebrates.     

A cortical-hippocampal system for declarative memory

Recent neurobiological studies have begun to reveal the cognitive and neural coding mechanisms that underlie declarative memory--our ability to recollect everyday events and factual knowledge. These studies indicate that the critical circuitry involves bidirectional connections between the neocortex, the parahippocampal region and the hippocampus. Each of these areas makes a unique contribution to memory processing. Widespread high-order neocortical areas provide dedicated processors for perceptual, motor or cognitive information that is influenced by other components of the system. The parahippocampal region mediates convergence of this information and extends the persistence of neocortical memory representations. The hippocampus encodes the sequences of places and events that compose episodic memories, and links them together through their common elements. Here I describe how these mechanisms work together to create and re-create fully networked representations of previous experiences and knowledge about the world.     

Towards neural circuit reconstruction with volume electron microscopy techniques

Electron microscopy is the only currently available technique with a resolution adequate to identify and follow every axon and dendrite in dense neuropil. Reconstructions of large volumes of neural tissue, necessary to reconstruct even local neural circuits, have, however, been inhibited by the daunting task of serially sectioning and reconstructing thousands of sections. Recent technological developments have improved the quality of volume electron microscopy data and automated its acquisition. This opens up the prospect of reconstructing almost complete invertebrate and sizable fractions of vertebrate nervous systems. Such reconstructions of complete neural wiring diagrams could rekindle the tradition of relating neural function to the underlying neuroanatomical circuitry.     

Homeostatic plasticity in the CNS: synaptic and intrinsic forms

The study of experience-dependent plasticity has been dominated by questions of how Hebbian plasticity mechanisms act during learning and development. This is unsurprising as Hebbian plasticity constitutes the most fully developed and influential model of how information is stored in neural circuits and how neural circuitry can develop without extensive genetic instructions. Yet Hebbian plasticity may not be sufficient for understanding either learning or development: the dramatic changes in synapse number and strength that can be produced by this kind of plasticity tend to threaten the stability of neural circuits. Recent work has suggested that, in addition to Hebbian plasticity, homeostatic regulatory mechanisms are active in a variety of preparations. These mechanisms alter both the synaptic connections between neurons and the intrinsic electrical properties of individual neurons, in such a way as to maintain some constancy in neuronal properties despite the changes wrought by Hebbian mechanisms. Here we review the evidence for homeostatic plasticity in the central nervous system, with special emphasis on results from cortical preparations.     

Convergent designs for electrogenesis and electroreception

New- and old-world tropical electric fish lack a common electrical ancestor, suggesting that the mechanisms of signal generation and recognition evolved independently in the two groups. Recent research on convergent designs for electrogenesis and electroreception has focused on the structure of electric organs, the neural circuitry controlling the pacemaker driving the electric organ, and the neural circuitry underlying time coding of electric waveforms.     

Successful Reconstruction of a Physiological Circuit with Known Connectivity from Spiking Activity Alone

Identifying the structure and dynamics of synaptic interactions between neurons is the first step to understanding neural network dynamics. The presence of synaptic connections is traditionally inferred through the use of targeted stimulation and paired recordings or by post-hoc histology. More recently, causal network inference algorithms have been proposed to deduce connectivity directly from electrophysiological signals, such as extracellularly recorded spiking activity. Usually, these algorithms have not been validated on a neurophysiological data set for which the actual circuitry is known. Recent work has shown that traditional network inference algorithms based on linear models typically fail to identify the correct coupling of a small central pattern generating circuit in the stomatogastric ganglion of the crab Cancer borealis. In this work, we show that point process models of observed spike trains can guide inference of relative connectivity estimates that match the known physiological connectivity of the central pattern generator up to a choice of threshold. We elucidate the necessary steps to derive faithful connectivity estimates from a model that incorporates the spike train nature of the data. We then apply the model to measure changes in the effective connectivity pattern in response to two pharmacological interventions, which affect both intrinsic neural dynamics and synaptic transmission. Our results provide the first successful application of a network inference algorithm to a circuit for which the actual physiological synapses between neurons are known. The point process methodology presented here generalizes well to larger networks and can describe the statistics of neural populations. In general we show that advanced statistical models allow for the characterization of effective network structure, deciphering underlying network dynamics and estimating information-processing capabilities.