Synchronized firing in the retina

Synchronized firing in neural populations has been proposed to constitute an elementary aspect of the neural code, but a complete understanding of its origins and significance has been elusive. Synchronized firing has been extensively documented in retinal ganglion cells, the output neurons of the retina. However, differences in synchronized firing across species and cell types have led to varied conclusions about its mechanisms and role in visual signaling. Recent work on two identified cell populations in the primate retina, the ON-parasol and OFF-parasol cells, permits a more unified understanding. Intracellular recordings reveal that synchronized firing in these cell types arises primarily from common synaptic input to adjacent pairs of cells. Statistical analysis indicates that local pairwise interactions can explain the pattern of synchronized firing in the entire parasol cell population. Computational analysis reveals that the aggregate impact of synchronized firing on the visual signal is substantial. Thus, in the parasol cells, the origin and impact of synchronized firing on the neural code may be understood as locally shared input which influences the visual signals transmitted from eye to brain.     

Encoding and processing biologically relevant temporal information in electrosensory systems

Wave-type weakly electric fish are specialists in time-domain processing: behaviors in these animals are often tightly correlated with the temporal structure of electrosensory signals. Behavioral responses in these fish can be dependent on differences in the temporal structure of electrosensory signals alone. This feature has facilitated the study of temporal codes and processing in central nervous system circuits of these animals. The temporal encoding and mechanisms used to transform temporal codes in the brain have been identified and characterized in several species, including South American gymnotid species and in the African mormyrid genus Gymnarchus. These distantly related groups use similar strategies for neural computations of information on the order of microseconds, milliseconds, and seconds. Here, we describe a suite of mechanisms for behaviorally relevant computations of temporal information that have been elucidated in these systems. These results show the critical role that behavioral experiments continue to have in the study of the neural control of behavior and its evolution.     

The role of adherens junctions in the developing neocortex

The disproportional enlargement of the neocortex through evolution has been instrumental in the success of vertebrates, in particular mammals. The neocortex is a multilayered sheet of neurons generated from a simple proliferative neuroepithelium through a myriad of mechanisms with substantial evolutionary conservation. This developing neuroepithelium is populated by progenitors that can generate additional progenitors as well as post-mitotic neurons. Subtle alterations in the production of progenitors vs. differentiated cells during development can result in dramatic differences in neocortical size. This review article will examine how cadherin adhesion proteins, in particular α-catenin and N-cadherin, function in regulating the neural progenitor microenvironment, cell proliferation, and differentiation in cortical development.     

The role of adherens junctions in the developing neocortex

The disproportional enlargement of the neocortex through evolution has been instrumental in the success of vertebrates, in particular mammals. The neocortex is a multilayered sheet of neurons generated from a simple proliferative neuroepithelium through a myriad of mechanisms with substantial evolutionary conservation. This developing neuroepithelium is populated by progenitors that can generate additional progenitors as well as post-mitotic neurons. Subtle alterations in the production of progenitors vs. differentiated cells during development can result in dramatic differences in neocortical size. This review article will examine how cadherin adhesion proteins, in particular α-catenin and N-cadherin, function in regulating the neural progenitor microenvironment, cell proliferation, and differentiation in cortical development.     

Neural sex modifies the function of a C. elegans sensory circuit

Though sex differences in animal behavior are ubiquitous, their neural and genetic underpinnings remain poorly understood. In particular, the role of functional differences in the neural circuitry that is shared by both sexes has not been extensively investigated. We have addressed these issues with C. elegans olfaction, a simple innate behavior mediated by sexually isomorphic neurons. Though males respond to the same olfactory attractants as do hermaphrodites, we find that each sex has a characteristic repertoire of olfactory preferences. These are not secondary to other sex-specific behaviors and do not require signaling from the gonad. Sex-specific olfactory preferences are controlled by tra-1, the master regulator of C. elegans sexual differentiation. Moreover, the genetic masculinization of neurons in an otherwise wild-type hermaphrodite is sufficient to switch the sexual phenotype of olfactory preference behavior. These studies reveal novel and unexpected sex differences in a C. elegans sensory behavior that is exhibited by both sexes. Our results indicate that these differences are a function of the chromosomally determined sexual identity of shared neural 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.     

Transplantation and functional integration of an identified respiratory interneuron in Lymnaea stagnalis.

The possibility that damaged neural circuitries can be repaired through grafting has raised questions regarding the cellular mechanisms required for functional integration of transplanted neurons. Invertebrate models offer the potential to examine such mechanisms at the resolution of single identified neurons within well-characterized neural networks. Here it is reported that a specific deficit in the respiratory behavior of a pulmonate mollusc, caused by the ablation of a solitary interneuron, can be restored by grafting an identical donor interneuron. The transplanted interneuron not only survives and extends neurites within the host nervous system, but under specific conditions forms synapses with appropriate target neurons and is physiologically integrated into the host's circuitry, thereby restoring normal behavior.     

鸣禽鸣叫学习的神经生物学机制

鸣禽鸣叫具有复杂的神经生理和生化基础,表现为一种复杂的学习过程。鸣啭控制系统是研究神经系统与学习、行为和发育关系的重要模型。而鸣禽鸣叫学习行为与鸣啭控制系统内长时程增强效应、神经元超微结构的改变和神经核团内的电活动、激素水平高低及其周期性变化、神经元再生或改变、即早基因的表达等方面密切相关。对鸣禽鸣叫的神经生物学机制进行了综述。     

Mechanisms Explaining Transitions between Tonic and Phasic Firing in Neuronal Populations as Predicted by a Low Dimensional Firing Rate Model

Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.     

Development of neural stem cell in the adult brain

New neurons are continuously generated in the dentate gyrus of the mammalian hippocampus and in the subventricular zone of the lateral ventricles throughout life. The origin of these new neurons is believed to be from multipotent adult neural stem cells. Aided by new methodologies, significant progress has been made in the characterization of neural stem cells and their development in the adult brain. Recent studies have also begun to reveal essential extrinsic and intrinsic molecular mechanisms that govern sequential steps of adult neurogenesis in the hippocampus and subventricular zone/olfactory bulb, from proliferation and fate specification of neural progenitors to maturation, navigation, and synaptic integration of the neuronal progeny. Future identification of molecular mechanisms and physiological functions of adult neurogenesis will provide further insight into the plasticity and regenerative capacity of the mature central nervous system.     

The role of activin in neuropeptide induction and pain sensation

Signals from target tissues play critical roles in the functional differentiation of neuronal cells, and in their subsequent adaptations to peripheral changes in the adult. Sensory neurons in the dorsal root ganglia (DRG) provide an excellent model system for the study of signals that regulate the development of neuronal diversity. DRG have been well characterized and contain both neurons that convey information from muscles about limb position, as well as other neurons that provide sensations from skin about pain information. Sensory neurons involved in pain sensation can be distinguished physiologically and antigenically, and one hallmark characteristic is that these neurons contain neuropeptides important for their functions. The transforming growth factor (TGF) beta family member activin A has recently been implicated in neural development and response to injury. During sensory neuron development, peripheral target tissues containing activin or activin itself can regulate pain neuropeptide expression. Long after development has ceased, skin target tissues retain the capacity to signal neurons about changes or injury, to functionally refine synapses. This review focuses on the role of activin as a target-derived differentiative factor in neural development that has additional roles in response to cutaneous injuries in the adult.     

Emergence of functional hierarchy in a multiple timescale neural network model: a humanoid robot experiment

It is generally thought that skilled behavior in human beings results from a functional hierarchy of the motor control system, within which reusable motor primitives are flexibly integrated into various sensori-motor sequence patterns. The underlying neural mechanisms governing the way in which continuous sensori-motor flows are segmented into primitives and the way in which series of primitives are integrated into various behavior sequences have, however, not yet been clarified. In earlier studies, this functional hierarchy has been realized through the use of explicit hierarchical structure, with local modules representing motor primitives in the lower level and a higher module representing sequences of primitives switched via additional mechanisms such as gate-selecting. When sequences contain similarities and overlap, however, a conflict arises in such earlier models between generalization and segmentation, induced by this separated modular structure. To address this issue, we propose a different type of neural network model. The current model neither makes use of separate local modules to represent primitives nor introduces explicit hierarchical structure. Rather than forcing architectural hierarchy onto the system, functional hierarchy emerges through a form of self-organization that is based on two distinct types of neurons, each with different time properties ("multiple timescales"). Through the introduction of multiple timescales, continuous sequences of behavior are segmented into reusable primitives, and the primitives, in turn, are flexibly integrated into novel sequences. In experiments, the proposed network model, coordinating the physical body of a humanoid robot through high-dimensional sensori-motor control, also successfully situated itself within a physical environment. Our results suggest that it is not only the spatial connections between neurons but also the timescales of neural activity that act as important mechanisms leading to functional hierarchy in neural systems.     

A cultured human neural network operates a robotic actuator

The development of bio-electronic prostheses, hybrid human-electronics devices and bionic robots has been the aim of many researchers. Although neurophysiologic processes have been widely investigated and bio-electronics has developed rapidly, the dynamics of a biological neuronal network that receive sensory inputs, store and control information is not yet understood. Toward this end, we have taken an interdisciplinary approach to study the learning and response of biological neural networks to complex stimulation patterns. This paper describes the design, execution, and results of several experiments performed in order to investigate the behavior of complex interconnected structures found in biological neural networks. The experimental design consisted of biological human neurons stimulated by parallel signal patterns intended to simulate complex perceptions. The response patterns were analyzed with an innovative artificial neural network (ANN), called ITSOM (Inductive Tracing Self Organizing Map). This system allowed us to decode the complex neural responses from a mixture of different stimulations and learned memory patterns inherent in the cell colonies. In the experiment described in this work, neurons derived from human neural stem cells were connected to a robotic actuator through the ANN analyzer to demonstrate our ability to produce useful control from simulated perceptions stimulating the cells. Preliminary results showed that in vitro human neuron colonies can learn to reply selectively to different stimulation patterns and that response signals can effectively be decoded to operate a minirobot. Lastly the fascinating performance of the hybrid system is evaluated quantitatively and potential future work is discussed.     

Sensation in a single neuron pair represses male behavior in hermaphrodites

Pheromones elicit innate sex-specific mating behaviors in many species. We demonstrate that in C.?elegans, male-specific sexual attraction behavior is programmed in both sexes but repressed in hermaphrodites. Repression requires a single sensory neuron pair, the ASIs. To repress attraction in adults, the ASIs must be present, active, and capable of sensing the environment during development. The ASIs release TGF-β, and ASI function can be bypassed by experimental activation of TGF-β signaling. Sexual attraction in derepressed hermaphrodites requires the same sensory neurons as in males. The sexual identity of both these sensory neurons and a distinct subset of interneurons must be male to relieve repression and release attraction. TGF-β may therefore act to change connections between sensory neurons and interneurons during development to engage repression. Thus, sensation in a single sensory neuron pair during development reprograms a common neural circuit from male to female behavior.     

Comparative approaches to avian song system function: insights into auditory and motor processing

Many fundamental advances in our understanding of basic neural function have been made using bird song learning and performance as a model system. These advances have included a greater understanding of higher-order neural processing, developmental and hormonal influences on behavior, and the realization that neurogenesis plays an important role in normal adult brain function. The great diversity of passerine birds and song-related behaviors they exhibit suggest that oscine songbirds are ideally suited for comparative studies. While the comparative approach has been used successfully in the past to study song-related phenomena at anatomical and behavioral levels, it has been underutilized in addressing questions at the neurophysiological level. Most neurophysiological studies of songbird auditory and motor processing have been performed in one species, the zebra finch (Taeniopygia guttata). We present and compare neurophysiological studies we have performed in zebra finches and song sparrows (Melospiza melodia), species that differ markedly in their singing behavior and song repertoire characteristics. Interspecific similarities, and striking differences, in song neural processing are apparent. While preliminary, these data suggest that comparative neurophysiological studies of species carefully chosen for their vocal repertoire and singing behavior will contribute significantly to our understanding of vertebrate sensory and motor neural processing.     

Insights into neural stem cell biology from flies

Drosophila neuroblasts are similar to mammalian neural stem cells in their ability to self-renew and to produce many different types of neurons and glial cells. In the past two decades, great advances have been made in understanding the molecular mechanisms underlying embryonic neuroblast formation, the establishment of cell polarity and the temporal regulation of cell fate. It is now a challenge to connect, at the molecular level, the different cell biological events underlying the transition from neural stem cell maintenance to differentiation. Progress has also been made in understanding the later stages of development, when neuroblasts become mitotically inactive, or quiescent, and are then reactivated postembryonically to generate the neurons that make up the adult nervous system. The ability to manipulate the steps leading from quiescence to proliferation and from proliferation to differentiation will have a major impact on the treatment of neurological injury and neurodegenerative disease.     

A structural and a functional aspect of stable information processing by the brain

Brain is an expert in producing the same output from a particular set of inputs, even from a very noisy environment. In this article a model of neural circuit in the brain has been proposed which is composed of cyclic sub-circuits. A big loop has been defined to be consisting of a feed forward path from the sensory neurons to the highest processing area of the brain and feed back paths from that region back up to close to the same sensory neurons. It has been mathematically shown how some smaller cycles can amplify signal. A big loop processes information by contrast and amplify principle. How a pair of presynaptic and postsynaptic neurons can be identified by an exact synchronization detection method has also been mentioned. It has been assumed that the spike train coming out of a firing neuron encodes all the information produced by it as output. It is possible to extract this information over a period of time by Fourier transforms. The Fourier coefficients arranged in a vector form will uniquely represent the neural spike train over a period of time. The information emanating out of all the neurons in a given neural circuit over a period of time can be represented by a collection of points in a multidimensional vector space. This cluster of points represents the functional or behavioral form of the neural circuit. It has been proposed that a particular cluster of vectors as the representation of a new behavior is chosen by the brain interactively with respect to the memory stored in that circuit and the amount of emotion involved. It has been proposed that in this situation a Coulomb force like expression governs the dynamics of functioning of the circuit and stability of the system is reached at the minimum of all the minima of a potential function derived from the force like expression. The calculations have been done with respect to a pseudometric defined in a multidimensional vector space.