Combinations of active striatal neurons connected selectively with certain behavioral actions of the monkey Macaca mulatta

At present there is widely spread concept of populational coding of information by brain neurons; it is based first of all on results of comparison of neuronal activity with parameters of the used stimulus. Relation between the neuronal activity coding and the observed behavioral actions has been practically not studied. In the present work, neuronal impulse activity has been studied in groups of 6 neurons recorded in parallel. Distribution of frequencies of the presence of cases of excitation of one or several cells has been established to differ statistically significantly form the theoretical distribution of the same values; this indicates that under real conditions, the appearance of individual combinations of active neurons is not random, but is connected to a certain degree with conditions of experiment. The selective combinations of neuronal activity have revealed to be different at stages of program. This indicates that organization of different behavioral actions is associated with activities of certain combinations of neurons.     

Combinations of active striatal neurons connected selectively with certain behavioral actions of the monkey <Emphasis Type="Italic">Macaca mulatta</Emphasis>

At present there is widely spread concept of populational coding of information by brain neurons; it is based first of all on results of comparison of neuronal activity with parameters of the used stimulus. Relation between the neuronal activity coding and the observed behavioral actions has been practically not studied. In the present work, neuronal impulse activity has been studied in groups of 6 neurons recorded in parallel. Distribution of frequencies of the presence of cases of excitation of one or several cells has been established to differ statistically significantly from the theoretical distribution of the same values; this indicates that under real conditions, the appearance of individual combinations of active neurons is not random, but is connected to a certain degree with conditions of experiment. The selective combinations of neuronal activity have been revealed to be different at stages of program. This indicates that organization of different behavioral actions is associated with activities of certain combinations of neurons.     

Neuronal basis of Hammel's model for set-point thermoregulation.

In 1965, H. T. Hammel proposed a neuronal model to explain set-point thermoregulation. His model was based on a synaptic network encompassing four different types of hypothalamic neurons: i.e., warm-sensitive and temperature-insensitive neurons and heat loss and heat production effector neurons. Although some modifications to this model are suggested, recent electrophysiological and morphological studies support many of the model's major tenets. Hypothalamic warm-sensitive neurons integrate core and peripheral thermal information. These neurons sense changes in hypothalamic temperature, and they orient their dendrites medially and laterally to receive ascending afferent input from cutaneous thermoreceptors. Temperature-insensitive neurons have a different dendritic orientation and may provide constant reference signals, which are important in determining thermoregulatory set points. In Hammel's model, temperature-sensitive and -insensitive neurons send mutually antagonistic synaptic inputs to effector neurons controlling various thermoregulatory responses. The model predicts that warm-sensitive neurons synaptically excite heat loss effector neurons and inhibit heat production effector neurons. In recent studies, one counterpart of these effector neurons may be "excitatory postsynaptic potential-driven neurons," the activity of which is dependent on synaptic excitation from nearby cells. Excitatory postsynaptic potential-driven neurons have sparse dendrites that appear to be specifically oriented, either medially or laterally, presumably to receive selective synaptic input from a discrete source. Another counterpart of effector neurons may be "silent neurons," which have extensive dendritic branches that may receive synaptic excitation from remote sources. Because some silent neurons receive synaptic inhibition from nearby warm-sensitive neurons, Hammel's model would predict that they have a role in heat production or heat retention responses.     

Rearrangement of the Prefrontal Cortex Neural Activity in Both Hemispheres during Learning

Neuronal activity of both right and left hemispheres of the rat prefrontal brain cortex was recorded in the two-ring maze during animal learning to operate in response to signals. At the beginning of learning, pairwise comparison of neural activity that accompanied correct and incorrect choice of the right and left sides showed significant differences in the left hemisphere and the lack of differences in the right one. With increasing percentage of correct choices during a session of learning, the differences in neuronal responses appeared in the right hemispheres and were reduced in the left one. The opposite trends in rearrangement of the total impulse activity are believed to be related to different roles of hemispheres in the construction of the internal behavioral model.     

Shaping Neuronal Network Activity by Presynaptic Mechanisms

Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model''s primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level.     

Neuronal population activity and functional imaging.

Human functional brain imaging detects blood flow changes that are thought to reflect the activity of neuronal populations and, thus, the responses of neurons that carry behaviourally relevant information. Since this relationship is poorly understood, we explored the link between the activity of single neurons and their neuronal population. The functional imaging results were in good agreement with levels of population activation predicted from the known effects of sensory stimulation, learning and attention on single cortical neurons. However, the nature of the relationship between population activation and single neuron firing was very surprising. Population activation was strongly influenced by those neurons firing at low rates and so was very sensitive to the baseline or 'spontaneous' firing rate. When neural representations were sparse and neurons were tuned to several stimulus dimensions, population activation was hardly influenced by the few neurons whose firing was most strongly modulated by the task or stimulus. Measures of population activation could miss changes in information processing given simultaneous changes in neurons' baseline firing, response modulation or tuning width. Factors that can modulate baseline firing, such as attention, may have a particularly large influence on population activation. The results have implications for the interpretation of functional imaging signals and for cross-calibration between different methods for measuring neuronal activity.     

The Correlation Structure of Local Neuronal Networks Intrinsically Results from Recurrent Dynamics

Correlated neuronal activity is a natural consequence of network connectivity and shared inputs to pairs of neurons, but the task-dependent modulation of correlations in relation to behavior also hints at a functional role. Correlations influence the gain of postsynaptic neurons, the amount of information encoded in the population activity and decoded by readout neurons, and synaptic plasticity. Further, it affects the power and spatial reach of extracellular signals like the local-field potential. A theory of correlated neuronal activity accounting for recurrent connectivity as well as fluctuating external sources is currently lacking. In particular, it is unclear how the recently found mechanism of active decorrelation by negative feedback on the population level affects the network response to externally applied correlated stimuli. Here, we present such an extension of the theory of correlations in stochastic binary networks. We show that (1) for homogeneous external input, the structure of correlations is mainly determined by the local recurrent connectivity, (2) homogeneous external inputs provide an additive, unspecific contribution to the correlations, (3) inhibitory feedback effectively decorrelates neuronal activity, even if neurons receive identical external inputs, and (4) identical synaptic input statistics to excitatory and to inhibitory cells increases intrinsically generated fluctuations and pairwise correlations. We further demonstrate how the accuracy of mean-field predictions can be improved by self-consistently including correlations. As a byproduct, we show that the cancellation of correlations between the summed inputs to pairs of neurons does not originate from the fast tracking of external input, but from the suppression of fluctuations on the population level by the local network. This suppression is a necessary constraint, but not sufficient to determine the structure of correlations; specifically, the structure observed at finite network size differs from the prediction based on perfect tracking, even though perfect tracking implies suppression of population fluctuations.     

Neuronal correlates of the activation of the brain-reinforcing system in dogs

In analysis of neuronal activity of g. proreus of dogs brain in response to positive and differentiation conditioned cutaneous stimuli, in 44% of 78 studied neurons "late responses" appeared in the form of impulse activity intensification elicited by a positive conditioned stimulus after the end of eating and by a differentiation one--during conditioned signal action; it persisted in different neurones for 30--60 s. By means of various functional tests it has been shown that these reactions are a neurophysiological correlate of animals emotional state gradient.     

Intrinsic Neuronal Properties Switch the Mode of Information Transmission in Networks

Diverse ion channels and their dynamics endow single neurons with complex biophysical properties. These properties determine the heterogeneity of cell types that make up the brain, as constituents of neural circuits tuned to perform highly specific computations. How do biophysical properties of single neurons impact network function? We study a set of biophysical properties that emerge in cortical neurons during the first week of development, eventually allowing these neurons to adaptively scale the gain of their response to the amplitude of the fluctuations they encounter. During the same time period, these same neurons participate in large-scale waves of spontaneously generated electrical activity. We investigate the potential role of experimentally observed changes in intrinsic neuronal properties in determining the ability of cortical networks to propagate waves of activity. We show that such changes can strongly affect the ability of multi-layered feedforward networks to represent and transmit information on multiple timescales. With properties modeled on those observed at early stages of development, neurons are relatively insensitive to rapid fluctuations and tend to fire synchronously in response to wave-like events of large amplitude. Following developmental changes in voltage-dependent conductances, these same neurons become efficient encoders of fast input fluctuations over few layers, but lose the ability to transmit slower, population-wide input variations across many layers. Depending on the neurons'' intrinsic properties, noise plays different roles in modulating neuronal input-output curves, which can dramatically impact network transmission. The developmental change in intrinsic properties supports a transformation of a networks function from the propagation of network-wide information to one in which computations are scaled to local activity. This work underscores the significance of simple changes in conductance parameters in governing how neurons represent and propagate information, and suggests a role for background synaptic noise in switching the mode of information transmission.     

Neural network mosaic model for pupillary responses to spatial stimuli

A neural network mosaic model was developed to investigate the spatial-temporal properties of the human pupillary control system. It was based on the double-layer neural network model developed by Cannon and Robinson and the pupillary dual-path model developed by Sun and Stark. The neural network portion of the model received its input from a sensor array and consisted of a retina-like two-dimensional neuronal layer. The dual-path portion of the model was composed of interconnections of the neurons that formed a mosaic of AC transient and DC sustained paths. The spatial aggregates of the AC and DC signals were input to the AC and DC summing neurons, respectively. Finally, the weighted sum of the aggregate AC and DC signals provided the output for driving the pupillary response. An important property of the model was that it could adaptively learn from training samples by adjustment of the weights. The neural network mosaic model showed excellent performance in simulating both the traditional pupillary phenomena and the new spatial stimulation findings such as responses to change in stimulus pattern and shift of light spot. Moreover, the model could also be used for the diagnosis of clinical deficits and image processing in machine vision. Received: 12 December 1997 / Accepted in revised form: 22 April 1998     

Behavior-related neuronal reactions and dynamics of neuronal activity

Functionally, behavior-related discharges of associative neurons are an efferent flow of pulses continuously generated over the course of each behavioral act of an animal. However, predominant research approaches are based on the "stimulus - reaction" principle. Analysis of the dynamics of unit activity in monkeys during performance of a multi-step behavioral complex showed that differences related to different behavioral acts consist in composition changes in the active neurons (or their recombination) rather than in a number of responsive cells or involvement of action-specific neurons. Each combination of active neurons ensures the distribution of efferent signals characteristic of the given combination. These findings suggest the addressing coding of the efferent neuronal signals.     

Neural pattern dynamics in an oscillator model of the thalamo-reticular system.

One of development issues for information processing with synchronous oscillations in the brain is how new information is coded and how a comparison with already existing information is performed. In the present work we study a simple neural network model of the thalamo-reticular system based on the Wilson-Cowan model of neuronal oscillatory behavior. Our results show that both cortical control over the thalamus and external sensory input are essential in coordinating and generating spatio-temporal patterns of synchronous activity. A main finding of the numerical simulations is that the network connectivity and the intrinsic oscillatory properties of the neurons result in distinct collective behaviors within the network. By varying the connectivity schemes comparable with lesionated or damaged brain regions our results are in good agreement with in vivo experimental results. Suppressing the sensory input results in temporal oscillatory activity in the beta and gamma range and a strong spatial dependence of the network activity.     

Pharmacological Characterization of Cultivated Neuronal Networks: Relevance to Synaptogenesis and Synaptic Connectivity

Mental disorders, such as schizophrenia or Alzheimer’s disease, are associated with impaired synaptogenesis and/or synaptic communication. During development, neurons assemble into neuronal networks, the primary supracellular mediators of information processing. In addition to the orchestrated activation of genetic programs, spontaneous electrical activity and associated calcium signaling have been shown to be critically involved in the maturation of such neuronal networks. We established an in vitro model that recapitulates the maturation of neuronal networks, including spontaneous electrical activity. Upon plating, mouse primary hippocampal neurons grow neurites and interconnect via synapses to form a dish-wide neuronal network. Via live cell calcium imaging, we identified a limited period of time in which the spontaneous activity synchronizes across neurons, indicative of the formation of a functional network. After establishment of network activity, the neurons grow dendritic spines, the density of which was used as a morphological readout for neuronal maturity and connectivity. Hence, quantification of neurite outgrowth, synapse density, spontaneous neuronal activity, and dendritic spine density allowed to study neuronal network maturation from the day of plating until the presence of mature neuronal networks. Via acute pharmacological intervention, we show that synchronized network activity is mediated by the NMDA-R. The balance between kynurenic and quinolinic acid, both neuro-active intermediates in the tryptophan/kynurenine pathway, was shown to be decisive for the maintenance of network activity. Chronic modulation of the neurotrophic support influenced the network formation and revealed the extreme sensitivity of calcium imaging to detect subtle alterations in neuronal physiology. Given the reproducible cultivation in a 96-well setup in combination with fully automated analysis of the calcium recordings, this approach can be used to build a high-content screening assay usable for neurotoxicity screening, target identification/validation, or phenotypic drug screening.     

Conceptual approaches to revealing the function of the structural organization of a neuronal network

Brain is an unexcelled instrument of perception and analysis of intensive information flows and decision making. Joint achievements of neurophysiology and morphology highlight the pathways between neuronal formations of different brain regions and their functions and fine organization of relationships within these formations. However, the principles of information transmission and signal processing in such structures remain hypothetical. The structure of the network executing the function of extrapolation or prediction of input signal values is discussed. Organization of neurons in this network is compared with relationships of neurons in the cerebellar cortex. It is suggested that the considered organization of neuronal relationships and the functions executed by the network are inherent for all brain formations including the brain cortex.     

Self-Initiated Motor Behavioral Act-Related Neuronal Activity in the Cat Locus Coeruleus

In experiments on awake cats, we recorded the activity of 61 putative noradrenergic neurons localized within the region of the locus coeruleus (LC) of the brainstem. The animals were trained to perform a self-initiated (voluntary) motor act aimed at obtaining a food reward by pushing a pedal by the forelimb. The intervals between pushings (stay of the limb on a platform before initiation of the movement) should not be shorter than 4 sec, and the duration of the movement itself should not exceed 1 sec. The following impulse reactions were most clearly manifested (i) related to the pre-starting events and performance of the voluntary movement, (ii) related to the presentations of the conditioning stimuli, which predicted giving out the food reward (a positive signal) or the absence of the latter (a negative signal) and (iii) related to the reward presentation. About 50% of the LC units under study had changed their activities before the movement was initiated. These reactions can be related to a cognitive component (determination of the movement initiation(, which is present in the experimental task. Most neurons responded by phasic activation to presentation of the conditioning signals, and this activation was more pronounced in the case of negative signals. Responses of the studied nerve cells are probably indicative of the involvement of the LC neuronal systems in the perception of the emotiogenic stimuli, as well as in the processes providing the maintenance of selective attention within different stages of targeted behavioral acts.     

The Role of the Neuronal Network in Functional Evolution of the Mammalian Telencephalon

During evolution of the vertebrate telencephalon the analyzing-synthesizing function was divided between two structures: the screen one, optimal for mechanisms of discrete analysis of information, and the neuronal network, in which cortical, functionally specialized modules can create the generalized equivalent of their activity. In the screen and reticular structures, each of these mechanisms got a possibility of developing independently without restricting functional capabilities of the other one. This resulted in formation of two telencephalon structures developing in parallel and functionally related, the cortex and the neostriatum. Experimental data indicate that the neuronal network of neostriatum is a field for interaction of corticofugal signals. These signals form neuronal mosaics reflecting the dynamics of cortical activity as combination patterns. Thereby, in neostriatum, corticofugal signals spread over a large surface of the cortex are transformed into their three-dimensional equivalent similar to population coding of information that takes place in the brain sensory structures. The established system of interrelationships between the cortex and the neostriatum turned out to be rather universal and economic. As a result, a broad spectrum of functional brain capabilities that we can see in various representatives of mammals was formed during a relatively short time with the minimum of structural changes, mainly quantitative in character.     

Neuronal control of energy homeostasis

Neuronal control of body energy homeostasis is the key mechanism by which animals and humans regulate their long-term energy balance. Various hypothalamic neuronal circuits (which include the hypothalamic melanocortin, midbrain dopamine reward and caudal brainstem autonomic feeding systems) control energy intake and expenditure to maintain body weight within a narrow range for long periods of a life span. Numerous peripheral metabolic hormones and nutrients target these structures providing feedback signals that modify the default "settings" of neuronal activity to accomplish this balance. A number of molecular genetic tools for manipulating individual components of brain energy homeostatic machineries, in combination with anatomical, electrophysiological, pharmacological and behavioral techniques, have been developed, which provide a means for elucidating the complex molecular and cellular mechanisms of feeding behavior and metabolism. This review will highlight some of these advancements and focus on the neuronal circuitries of energy homeostasis.     

The roles of calcium/calmodulin-dependent and Ras/mitogen-activated protein kinases in the development of psychostimulant-induced behavioral sensitization

Although the development of behavioral sensitization to psychostimulants such as cocaine and amphetamine is confined mainly to one nucleus in the brain, the ventral tegmental area (VTA), this process is nonetheless complex, involving a complicated interplay between neurotransmitters, neuropeptides and trophic factors. In the present review we present the hypothesis that calcium-stimulated second messengers, including the calcium/calmodulin-dependent protein kinases and the Ras/mitogen-activated protein kinases, represent the major biochemical pathways whereby converging extracellular signals are integrated and amplified, resulting in the biochemical and molecular changes in dopaminergic neurons in the VTA that represent the critical neuronal correlates of the development of behavioral sensitization to psychostimulants. Moreover, given the important role of calcium-stimulated second messengers in the expression of behavioral sensitization, these signal transduction systems may represent the biochemical substrate through which the transient neurochemical changes associated with the development of behavioral sensitization are translated into the persistent neurochemical, biochemical and molecular alterations in neuronal function that underlie the long-term expression of psychostimulant-induced behavioral sensitization.     

Analysis of the Neuronal Background Impulse Activity in the Rat Locus Coeruleus

Using several techniques of statistical analysis, we studied in detail the extracellularly recorded background impulse activity (BA) of neuronal elements of the rat locus coeruleus (LC). Impulse trains generated by most LC neurons were stationary and demonstrated different levels of regularity; a nonstationary type of BA was observed in 17% of the neurons under study. Statistical parameters of the BA generated by LC neurons showed a wide variability. Distributions of the BA interspike intervals (ISI) of most LC neurons were characterized by more or less expressed bimodality or polymodality. Serial correlation analysis of the ISI durations both in stationary and nonstationary spike trains allowed us to differentiate five main types of the dynamics of ISI successions in the BA of LC neurons.     

Reflexogenic changes in the spontaneous and evoked activity of the parafascicular neurons in the rat thalamus during electroacupuncture stimulation

Acute experiments on cats were made to study the electroacupuncture (EAP) effect on neuronal impulse activity in the parafascicular complex (PFC) of the thalamus in response to solitary peripheral nociceptive and non-nociceptive stimuli. EAP stimulation affects the pattern of spontaneous and evoked activity of PFC neurons and forms their new functional status. It is suggested that the analgetic effect is brought about by the changes in neuronal activity in subcortical structures of the brain including the thalamic nuclei which transmit the ascending nociceptive input.