Monosynaptic rabies virus reveals premotor network organization and synaptic specificity of cholinergic partition cells

Movement is the behavioral output of neuronal activity in the spinal cord. Motor neurons are grouped into motor neuron pools, the functional units innervating individual muscles. Here we establish an anatomical rabies virus-based connectivity assay in early postnatal mice. We employ it to study the connectivity scheme of premotor neurons, the neuronal cohorts monosynaptically connected to motor neurons, unveiling three aspects of organization. First, motor neuron pools are connected to segmentally widely distributed yet stereotypic interneuron populations, differing for pools innervating functionally distinct muscles. Second, depending on subpopulation identity, interneurons take on local or segmentally distributed positions. Third, cholinergic partition cells involved in the regulation of motor neuron excitability segregate into ipsilaterally and bilaterally projecting populations, the latter exhibiting preferential connections to functionally equivalent motor neuron pools bilaterally. Our study visualizes the widespread yet precise nature of the connectivity matrix for premotor interneurons and reveals exquisite synaptic specificity for bilaterally projecting cholinergic partition cells.     

Postvibration changes in the spontaneous activity of neurons in the medial vestibular nucleus

The method of computer analyses was used for the research of the spectral changes of spontaneous neuronal activity of the medial vestibular nucleus ander vibration action (5, 10 and 15 daily). On the basis of neurons activity analyses it is possible to conclude that the majority of investigated units of flow and instability figured on different levels. The findings are discussed in respect to special points of functional meaning.     

Glutamate release from astrocytes as a non-synaptic mechanism for neuronal synchronization in the hippocampus.

Synchronization of activity of anatomically distributed groups of neurons represents a fundamental event in the processing of information in the brain. While this phenomenon is believed to result from dynamic interactions within the neuronal circuitry, how exactly populations of neurons become synchronized remains largely to be clarified. We propose that astrocytes are directly involved in the generation of neuronal synchrony in the hippocampus. By using a combination of experimental approaches in hippocampal slice preparations, including patch-clamp recordings and confocal microscopy calcium imaging, we studied the effect on CA1 pyramidal neurons of glutamate released from astrocytes upon various stimuli that trigger Ca2+ elevations in these glial cells, including Schaffer collateral stimulation. We found that astrocytic glutamate evokes synchronous, slow inward currents (SICs) and Ca2+ elevations in CA1 pyramidal neurons by acting preferentially, if not exclusively, on extrasynaptic NMDA receptors. Due to desensitization, AMPA receptors were not activated by astrocytic glutamate unless cyclothiazide was present. In the virtual absence of extracellular Mg2+, glutamate released from astrocytes was found to evoke, in paired recordings, highly synchronous SICs from two CA1 pyramidal neurons and, in Ca2+ imaging experiments, Ca2+ elevations that occurred synchronously in domains composed of 2-12 CA1 neurons. In the presence of extracellular Mg2+ (1 mM), synchronous SICs in two neurons as well as synchronous Ca2+ elevations in neuronal domains were still observed, although with a reduced frequency. Our results reveal a functional link between astrocytic glutamate and extrasynaptic NMDA receptors that contributes to the overall dynamics of neuronal synchrony. Our observations also raise a series of questions on possible roles of this astrocyte-to-neuron signaling in pathological changes in the hippocampus such as excitotoxic neuronal damage or the generation of epileptiform activity.     

Stochastic models of neuronal dynamics

Cortical activity is the product of interactions among neuronal populations. Macroscopic electrophysiological phenomena are generated by these interactions. In principle, the mechanisms of these interactions afford constraints on biologically plausible models of electrophysiological responses. In other words, the macroscopic features of cortical activity can be modelled in terms of the microscopic behaviour of neurons. An evoked response potential (ERP) is the mean electrical potential measured from an electrode on the scalp, in response to some event. The purpose of this paper is to outline a population density approach to modelling ERPs.We propose a biologically plausible model of neuronal activity that enables the estimation of physiologically meaningful parameters from electrophysiological data. The model encompasses four basic characteristics of neuronal activity and organization: (i) neurons are dynamic units, (ii) driven by stochastic forces, (iii) organized into populations with similar biophysical properties and response characteristics and (iv) multiple populations interact to form functional networks. This leads to a formulation of population dynamics in terms of the Fokker-Planck equation. The solution of this equation is the temporal evolution of a probability density over state-space, representing the distribution of an ensemble of trajectories. Each trajectory corresponds to the changing state of a neuron. Measurements can be modelled by taking expectations over this density, e.g. mean membrane potential, firing rate or energy consumption per neuron. The key motivation behind our approach is that ERPs represent an average response over many neurons. This means it is sufficient to model the probability density over neurons, because this implicitly models their average state. Although the dynamics of each neuron can be highly stochastic, the dynamics of the density is not. This means we can use Bayesian inference and estimation tools that have already been established for deterministic systems. The potential importance of modelling density dynamics (as opposed to more conventional neural mass models) is that they include interactions among the moments of neuronal states (e.g. the mean depolarization may depend on the variance of synaptic currents through nonlinear mechanisms).Here, we formulate a population model, based on biologically informed model-neurons with spike-rate adaptation and synaptic dynamics. Neuronal sub-populations are coupled to form an observation model, with the aim of estimating and making inferences about coupling among sub-populations using real data. We approximate the time-dependent solution of the system using a bi-orthogonal set and first-order perturbation expansion. For didactic purposes, the model is developed first in the context of deterministic input, and then extended to include stochastic effects. The approach is demonstrated using synthetic data, where model parameters are identified using a Bayesian estimation scheme we have described previously.     

Structure and development of the insect antennodeutocerebral system

The structure and postembryonic development of antennae and deutocerebrum in various insect orders are reviewed. First, the number and/or size of system components, i.e. antennal sensilla, neuroreceptors, deutocerebral neurons and synaptic complexes (glomeruli), are compared in adult insects. Second, the neuronal organization of the system is examined. Evidence of projection of the neuroreceptors from the 2 basal antennal segments (scape and pedicel) in the antennal mechanosensory and motor center and from the distal segments (flagellum) in the antennal lobe is discussed. Third, the types of cerebral neurons found in the antennal lobe are described. Fourth, all synaptic contacts between neurons in the antennal lobe take place in discrete glomeruli whose ultrastructure and neurotransmitters are examined. Evidence of individual identifiability of glomeruli is given. Fifth, various sexual dimorphisms present in the antenna and antennal lobe, related or not to sex pheromone perception, are described at sensillar, neuronal, and glomerular levels. Sixth, the postembryonic development of neurons and glomeruli is analyzed in holo- and hemimetabolous insects. In conclusion, the columnar organization of the system is emphasized, alternative models of antennal-neuron projection into glomeruli are considered, and the functional significance of identified glomeruli is discussed.     

NAD causes dissociation of neural networks into subpopulations of neurons by inhibiting the network synchronous hyperactivity evoked by ammonium ions

The mechanisms of hyperexcitability of neuronal networks by ammonium ions and inhibition of this activity by coenzyme NAD were investigated on mixed neuro-glial cultures of rat hippocampus. Ammonium ions cause activation of silent or spontaneously active neuronal networks inducing a bursting electrical activity of neurons and high-frequency synchronous calcium oscillations. In control conditions NAD completely inhibits spontaneous activity of the neuronal network. NAD added after NH₄Cl disrupts synchronous oscillation in neurons and splits the network into five populations of neurons. In 4% of cells NAD decreased the amplitude of Ca²⁺ oscillations, preserving initial mode of oscillations. In 32% of cells, a transient suppression of the neuronal oscillations was observed: inhibition was followed by restoration of the synchronous periodic activity. In 10% of cells, NAD produced a gradual decrease of Ca²⁺ oscillations down to a complete termination of the initial periodic activity induced by ammonium. Fast and total inhibition of Ca²⁺ oscillations by NAD was observed in two small groups of neurons. First group (A) participated in the initial spontaneous network activity (5% of cells) with a period of 66–100 s. Second group (B), on the contrary, did not participate in the spontaneous activity. This group of neurons began to pulse with a high frequency (with a period of 6–8 s) synchronously with other neurons in the network after the addition of NH₄Cl. Based on the comparison of calcium responses of different cell groups to the depolarization caused by KCl and NH₄Cl and to the application of domoic acid, as well as on the results obtained in experiments with fluorescent antibodies against GAD 65/67, parvalbumin, calretinin, and calbindin, we propose that neurons of populations (A) and (B) may belong to GABAergic neurons containing calbindin and parvalbumin, respectively. Further analysis of specificity of the NAD effect on these neuronal groups may allow identification of the main targets of the ammonium toxic action in the brain. Thus, we have shown that NAD selectively inhibits neuronal activity and high-frequency synchronous Ca²⁺ oscillations in GABAergic neurons containing calcium-binding proteins. The inhibition is accompanied by desynchronization of oscillations and dissociation of neuronal network into several populations.     

Maximization of learning speed in the motor cortex due to neuronal redundancy

Many redundancies play functional roles in motor control and motor learning. For example, kinematic and muscle redundancies contribute to stabilizing posture and impedance control, respectively. Another redundancy is the number of neurons themselves; there are overwhelmingly more neurons than muscles, and many combinations of neural activation can generate identical muscle activity. The functional roles of this neuronal redundancy remains unknown. Analysis of a redundant neural network model makes it possible to investigate these functional roles while varying the number of model neurons and holding constant the number of output units. Our analysis reveals that learning speed reaches its maximum value if and only if the model includes sufficient neuronal redundancy. This analytical result does not depend on whether the distribution of the preferred direction is uniform or a skewed bimodal, both of which have been reported in neurophysiological studies. Neuronal redundancy maximizes learning speed, even if the neural network model includes recurrent connections, a nonlinear activation function, or nonlinear muscle units. Furthermore, our results do not rely on the shape of the generalization function. The results of this study suggest that one of the functional roles of neuronal redundancy is to maximize learning speed.     

Responses of neurons of the extrastriate cortex of the cat brain to moving stimuli of different forms

We examined responses of neurons of the field 21b of the cat brain cortex to presentation of moving visual stimuli of different forms. Characteristics of the responses of about 54% of the studied neurons showed that in these cases configurations of the contours of moving stimuli were to a certain extent discriminated. Most neurons selectively reacting to changes in the form of the stimulus were dark-sensitive units (they generated optimum responses to presentation of dark visual stimuli on the light background). Detailed examination of the spatial infrastructure of receptive fields (RFs) of the neurons and comparison of this structure with the selectivity of neuronal responses showed that there is no significant correlation between static organization of the RF and responses of the neuron to the movements of stimuli of different forms. We hypothesize that the dynamic infrastructure of the RF and the combined activity of functional groups of neurons, whose RFs spatially overlap the RF of the neuron under study, play a definite role in the mechanisms responsible for neuronal discrimination of the form of the visual stimulus. Neirofiziologiya/Neurophysiology, Vol. 38, No. 1, pp. 61–71, January–February, 2006.     

Scale-Free Topology of the CA3 Hippocampal Network: A Novel Method to Analyze Functional Neuronal Assemblies

Cognitive mapping functions of the hippocampus critically depend on the recurrent network of the CA3 pyramidal cells. However, it is still not known in detail how network activity patterns emerge, or how they encode information. By using functional multineuron calcium imaging, we simultaneously recorded the activity of >100 neurons in the CA3 region of hippocampal slice cultures. We utilized a novel computational method to analyze the multichannel spike trains and to depict functional neuronal assemblies. By means of event synchronization and the correlation matrix analysis method, we found that: 1), the average functional neuronal cluster consists of 23 neurons, and neurons could be part of multiple assemblies; 2), the clustering strength, size, and mean distance among cells in neuronal assemblies follow a power-law-like distribution; 3), the clustering strength and size of neuronal assemblies are not correlated with the total number of neurons and their physical distance; and 4), the clustering distance of neuronal assemblies is weakly correlated with the total number of neurons and their physical distance. These findings suggest that the functional organization of the spontaneously firing CA3 hippocampal network is a scale-free structure in slice culture.     

Activity Correlation Imaging: Visualizing Function and Structure of Neuronal Populations

For the analysis of neuronal networks it is an important yet unresolved task to relate the neurons' activities to their morphology. Here we introduce activity correlation imaging to simultaneously visualize the activity and morphology of populations of neurons. To this end we first stain the network's neurons using a membrane-permeable [Ca²⁺] indicator (e.g., Fluo-4/AM) and record their activities. We then exploit the recorded temporal activity patterns as a means of intrinsic contrast to visualize individual neurons' dendritic morphology. The result is a high-contrast, multicolor visualization of the neuronal network. Taking the Xenopus olfactory bulb as an example we show the activities of the mitral/tufted cells of the olfactory bulb as well as their projections into the olfactory glomeruli. This method, yielding both functional and structural information of neuronal populations, will open up unprecedented possibilities for the investigation of neuronal networks.     

Dissecting cascade computational components in spiking neural networks

Finding out the physical structure of neuronal circuits that governs neuronal responses is an important goal for brain research. With fast advances for large-scale recording techniques, identification of a neuronal circuit with multiple neurons and stages or layers becomes possible and highly demanding. Although methods for mapping the connection structure of circuits have been greatly developed in recent years, they are mostly limited to simple scenarios of a few neurons in a pairwise fashion; and dissecting dynamical circuits, particularly mapping out a complete functional circuit that converges to a single neuron, is still a challenging question. Here, we show that a recent method, termed spike-triggered non-negative matrix factorization (STNMF), can address these issues. By simulating different scenarios of spiking neural networks with various connections between neurons and stages, we demonstrate that STNMF is a persuasive method to dissect functional connections within a circuit. Using spiking activities recorded at neurons of the output layer, STNMF can obtain a complete circuit consisting of all cascade computational components of presynaptic neurons, as well as their spiking activities. For simulated simple and complex cells of the primary visual cortex, STNMF allows us to dissect the pathway of visual computation. Taken together, these results suggest that STNMF could provide a useful approach for investigating neuronal systems leveraging recorded functional neuronal activity.     

X inactivation of the OCNC1 channel gene reveals a role for activity-dependent competition in the olfactory system

The organization of neuronal systems is often dependent on activity and competition between cells. In olfaction, the X-linked OCNC1 channel subunit is subject to random inactivation and is essential for odorant-evoked activity. Reporter-tagged OCNC1 mutant mice permit the visualization of OCNC1-deficient olfactory neurons and their projections. In heterozygous females, X inactivation creates a mosaic with two populations of genetically distinct neurons. OCNC1-deficient neurons are slowly and specifically depleted from the olfactory epithelium and display unusual patterns of projection to the olfactory bulb. Remarkably, this depletion is dependent on odorant exposure and is reversed by odorant deprivation. This suggests that odorants and the activity they evoke are critical for neuronal survival in a competitive environment and implicate evoked activity in the organization and maintenance of the olfactory system.     

Bradykinin microinjection in the paratrigeminal nucleus triggers neuronal discharge in the rat rostroventrolateral reticular nucleus

A small collection of neurons in the dorsal lateral medulla, the paratrigeminal nucleus (Pa5), projects directly to the rostroventrolateral reticular nucleus (RVL). Bradykinin (BK) microinjections in the Pa5 produce marked pressor responses. Also, the Pa5 is believed to be a component of the neuronal substrates of the somatosensory response and the baroreflex arc. Considering the developing interest in the functional physiology of the Pa5, the present study was designed to characterize RVL neuronal activity in response to BK microinjections in the Pa5 as well as to phenylephrine-induced blood pressure increases in freely behaving rats. Of the 46 discriminated RVL neurons, 82% responded with a 180% mean increase in firing rate after BK application to the paratrigeminal nucleus, before the onset of the blood pressure increase. Thirty (79%) of the RVL BK-excited neurons were baroreceptor-inhibited units that responded with a 30% decrease in firing rate in response to a phenylephrine-produced increase of blood pressure. Twenty-seven (71%) units of the latter population displayed cardiac-cycle-locked rhythmic activity. The findings demonstrate a BK-stimulated functional connection between the Pa5 and RVL that may represent the neural pathway in the BK-mediated pressor response. This pathway may be relevant to baroreflex mechanisms since it relates to cardiovascular pressure-sensitive neurons.     

The neuronal basis of behavior in Tritonia. III. Neuronal mechanism of a fixed action pattern

We have investigated the roles played by numerous identified brain cells in initiating and controlling the coordinated sequence of movements of an instinctive escape-swimming sequence in an intact animal preparation of the nudibranch mollusc Tritonia diomedia. Intracellular electrical activity in different neurons has been correlated with the various phases of the behavior. We recognized four major stages in the response: (1) reflex local withdrawal; (2) preparation for swimming; (3) swimming; and (4) termination. We have located and studied brain cells whose activity is associated with the following aspects of swimming: withdrawal; elongation; triggering behavior; dorsal flexion; ventral flexion; and neurons which excite both dorsal and ventral flexor neurons simulataneously. We find that specific neurons play clearly defined and invariant roles in control of escape-swimming and that the neuronal circuitry underlying the coordination of the sequence is the same in different individuals of the species. Details of the neuronal circuitry and a number of the general functional attributes of interacting cell groups have been determined directly or inferred from observations of cell to cell interactions. A preliminary model of the neuronal apparatus which controls this behavior is discussed. The principal findings are: (1) a discrete group of electrically coupled neurons determines, by its output, whether or not escapeswimming will be executed; (2) the neuronal elements responsible for execution of the swimming stages of the sequence are maintained in an excited state for the required period, in part by a regenerative feedback system; (3) alternating bursts of impulses in functional antagonists are co-ordinated in part by reciprocal inhibition between them; and (4) termination of the sequence occurs abruptly at a particular phase in the swimming cycle and appears to be an active neural process, rather than a simple running-down.     

What image characteristics are selected by neurons in the cat primary visual cortex?]

About 40% of neurons (114/289) studied in the cat area 17 gave a larger (by 3.06 +/- 0.32 times on average) response to a flashed cross, corner or y-like figures centered in the RF than to an optimal single bar. Most such neurons (72%) were found to be highly selective both to shape (angle between the lines) and to orientation of these figures. In the studied neuronal selection we have also found all possible types of invariance of sensitivity to orientation and/or shape of these figures. Separated and combined stimulation of RF center and surrounding area revealed in 44 units summation, antagonism or absence of interaction of these zones by the selectivity index (cross/bar response ratio). Cross-sensitivity was investigated in 85 V1 neurons before, during and after local blockade of GABAA ergic inhibition by microiontophoretical application of bicuculline. Inhibition either emerged or increased cross-sensitivity (32% of cells), or depressed it (36% of cases), while in some neurons it does not influenced the function. Possible mechanisms of the described effects are discussed as well as their functional implication for second-order feature extraction in the visual cortex: selective or invariant sensitivity of neurons to the shape and orientation of the line-crossings.     

Reorganization of Receptive Fields of Cortical Field 21a Neurons and Formation of Responses to Moving Visual Stimuli

Using extracellular recording of spike activity from single neurons of field 21a of the cat neocortex, we examined in detail the spatial organization of receptive fields (RFs) of such cells after conditions of presentation of an immobile blinking light spot (a static RF) and moving visual stimuli (dynamic RFs). As was shown, the excitability of different RF subfields of a group of neurons possessing homogeneous on–off organization of the static RF changes significantly depended on the contrast, shape, dimension, orientation, and direction of movement of the applied mobile visual stimulus. This is manifested in changes in the number of discharge centers and shifts of their spatial localization. A hypothesis on the possible role of synchronous activation of the neurons neighboring the cell under study in the formation of an additional neuronal mechanism providing specialization of neuronal responses is proposed.     

The local and non-local components of the local field potential in awake primate visual cortex

The Local Field Potential (LFP) is the analog signal recorded from a microelectrode inserted into cortex, typically in the frequency band of approximately 1 to 200 Hz. Here visual stimuli were flashed on in the receptive fields of primary visual cortical neurons in awake behaving macaques, and both isolated single units (neurons) and the LFP signal were recorded from the same unipolar microelectrode. The fall-off of single unit activity as a visual stimulus was moved from near the center to near the edge of the receptive field paralleled the fall-off of the stimulus-locked (evoked) LFP response. This suggests that the evoked LFP strongly reflects local neuronal activity. However, the evoked LFP could be significant even when the visual stimulus was completely outside the receptive field and the single unit response had fallen to zero, although this phenomenon was variable. Some of the non-local components of the LFP may be related to the slow distributed, or non-retinotopic, LFP signal previously observed in anesthetized animals. The induced (not time-locked to stimulus onset) component of the LFP showed significant increases only for stimuli within the receptive field of the single units. While the LFP primarily reflects local neuronal activity, it can also reflect neuronal activity at more distant sites, although these non-local components are typically more variable, slower, and weaker than the local components.     

The functional role of different neural activation profiles during precision grip: An artificial neural network approach

A dynamic and recurrent artificial neural network was used to investigate the functional properties of firing patterns observed in the primary motor (M1) and the primary somatosensory (S1) cortex of the behaving monkey during control of precision grip force. In the behaving monkey it was found that neurons in M1 and in S1 increase their firing activity with increasing grip force, as do the intrinsic and extrinsic hand muscles implicated in the task. However, some neurons also decreased their activity as a function of increasing force. The functional implication of these latter neurons is not clear and has not been elucidated so far. In order to explore their functional implication, we therefore simulated patterns of neural activity in artificial neural networks that represent cortical, spinal and afferent neural populations and tested whether particular activity profiles would emerge as a function of the input and of the connectivity of these networks. The functional implication of units with emergent or imposed decreasing activity was then explored.Decreasing patterns of activity in M1 units did not emerge from the networks. However, the same networks generated decreasing activity if imposed as target patterns. As indicated by the emerging weight space, M1 projection units with decreasing patterns are functionally less involved in driving alpha motoneurons than units with increasing profiles. Furthermore, these units did not provide significant fusimotor drive, whereas those with increasing profiles did. Fusimotor drive was a function of the (imposed) form of muscle spindle afferent activity: with gamma (fusimotor) drive, muscle spindle afferents provided signals other than muscle length (as observed experimentally). The network solutions thus predict a functional dichotomy between increasing and decreasing M1 neurons: the former primarily drive alpha and gamma motoneurons, the latter only weakly alpha motoneurons.     

Neuronal assembly detection and cell membership specification by principal component analysis

In 1949, Donald Hebb postulated that assemblies of synchronously activated neurons are the elementary units of information processing in the brain. Despite being one of the most influential theories in neuroscience, Hebb's cell assembly hypothesis only started to become testable in the past two decades due to technological advances. However, while the technology for the simultaneous recording of large neuronal populations undergoes fast development, there is still a paucity of analytical methods that can properly detect and track the activity of cell assemblies. Here we describe a principal component-based method that is able to (1) identify all cell assemblies present in the neuronal population investigated, (2) determine the number of neurons involved in ensemble activity, (3) specify the precise identity of the neurons pertaining to each cell assembly, and (4) unravel the time course of the individual activity of multiple assemblies. Application of the method to multielectrode recordings of awake and behaving rats revealed that assemblies detected in the cerebral cortex and hippocampus typically contain overlapping neurons. The results indicate that the PCA method presented here is able to properly detect, track and specify neuronal assemblies, irrespective of overlapping membership.