The structure of dependent relationship between neurons in the sensorimotor cortex of the left and right hemisphere in rabbits during immobilizing catatonia

Relations between activities of neurons simultaneously recorded in the left and right sensorimotor brain cortices of rabbits were analyzed in a series of experiments before the induction of the immobilization state ("animal hypnosis"), in the state of immobilization, and after its termination. The total baseline percent of significant correlations between activities of neighboring (within 50 microns) neurons in the left hemisphere was significantly lower than in the right hemisphere. This characteristic of the left hemisphere changed neither in the immobilization state nor after its termination. In the right-hemisphere cortex, the total percent of correlations between neighboring neurons significantly decreased during immobilization and returned to the baseline level after the termination of this state. In contrast, percent of correlations between the activities of remote (within 500 microns) neurons in the right-hemisphere did not change during immobilization, whereas in the left cortex it changed significantly and reached its baseline level after the normalization of rabbit's state. Further analysis showed that the revealed cortical interhemispheric asymmetry is underlain by asymmetric activities of individual neurons and small neuronal populations. Thus, for example, changes in the structure of interneuronal correlations in cortical microareas of the left and macroareas of the right hemispheres could be of different directions, whereas correlated activities in microareas of the right and macroareas of the left-hemispheres could change synergetically. In other words, asymmetry was revealed at different levels of neuronal integration (neuronal pairs, micro- or macrogroups of neurons). This finding testifies to a mosaic character of neuronal activity, which finally results in the general functional asymmetry during the "animal hypnosis". Certain changes in the structure of functional relations between neurons of the sensorimotor cortex that developed in the state of "animal hypnosis" persisted and even augmented after the termination of this state.     

Comparative analysis of discharge frequency of right and left sensorimotor cortical neurons in rabbits during tonic immobility

Multiunit activity was recorded in left and right sensorimotor cortex of rabbits in the state of tonic immobility. After the first immobilization session, the discharge frequency changed in 47% cells in the right hemisphere: 30% decreased their frequency, and 17% increased. In the left hemisphere, only 18% cells changed their discharge frequency (13% decreased and 5% increased). Reciprocal changes in discharge frequency could be observed in the neighboring neurons (recorded by the same electrode). Several days later, after the second immobilization session, the interhemispheric difference in the number of neurons, whose activity changed, almost disappeared (21% neurons in the right and 24% neurons in the left hemispheres). The relationship between the number of cortical neurons, which increased and decreased their activities in the state of "hypnosis" also became similar in the right and left hemispheres. A suggestion about the involvement of cortical neurons in organization of the state of "animal hypnosis" was made.     

Correlated activity of neurons in the sensorimotor cortex of rabbits in the state of defensive dominanta and "animal hypnosis"

A hidden excitation focus (dominanta focus) was produced in the rabbit's CNS by threshold electrical stimulation of the left forelimb with the frequency of 0.5 Hz. As a rule, after the formation of the focus, pairs of neurons with prevailing two-second rhythm in their correlated activity were revealed both in the left and right sensorimotor cortices (with equal probabilities 29.3 and 32.4%, respectively). After "animal hypnosis" induction, the total percent of neuronal pairs with the prevalent dominanta-induced rhythm decreased significantly only in the right hemisphere (21%). After the termination of the "animal hypnosis" state, percent of neuronal pairs in the right cortex with prevailing two-second rhythm significantly increasead if the neurons in a pair were neighboring and decreased if they were remote from each other. Similar changes after the hypnotization were not found in the left cortex. Analysis of correlated activity of neuronal pairs with regard to amplitude characteristics showed that for both the right and left hemispheres, the prevalence of the two-second rhythm was more frequently observed in crosscorrelation histograms constructed regarding discharges of neurons with the lowest spike amplitude (in the right hemisphere) or the lowest and mean amplitudes (in the left hemisphere) selected from multiunit records.     

Unilateral Left-Hand Contractions Produce Widespread Depression of Cortical Activity after Their Execution

The execution of unilateral hand contractions before performance has been reported to produce behavioral aftereffects in various tasks. These effects have been regularly attributed to an induced shift in activation asymmetry to the contralateral hemisphere produced by the contractions. An alternative explanation proposes a generalized state of reduced bilateral cortical activity following unilateral hand contractions. The current experiment contrasted the above explanation models and tested the state of cortical activity after the termination of unilateral hand contractions. Twenty right-handed participants performed hand contractions in two blocks, one for each hand. Using electroencephalogram (EEG), the broad alpha band and its asymmetry between hemispheres before, during, and after hand contractions were analyzed. During contractions, significant bilateral decrease in alpha amplitudes (indicating cortical activation) emerged for both hands around sensory-motor regions. After contractions, alpha amplitudes increased significantly over the whole scalp when compared to baseline, but only for the left hand. No modulation of hemispheric asymmetry was observed at any phase. The results suggest that unilateral hand contractions produce a state of reduced cortical activity after their termination, which is more pronounced if the left hand was used. Consequently, we propose that the reduced cortical activity (and not the persistent activation asymmetry) may facilitate engagement in subsequent behavior, probably due to preventing interference from other, nonessential cortical regions.     

Partial correlation analysis for the identification of synaptic connections

In this paper, we investigate the use of partial correlation analysis for the identification of functional neural connectivity from simultaneously recorded neural spike trains. Partial correlation analysis allows one to distinguish between direct and indirect connectivities by removing the portion of the relationship between two neural spike trains that can be attributed to linear relationships with recorded spike trains from other neurons. As an alternative to the common frequency domain approach based on the partial spectral coherence we propose a new statistic in the time domain. The new scaled partial covariance density provides additional information on the direction and the type, excitatory or inhibitory, of the connectivities. In simulation studies, we investigated the power and limitations of the new statistic. The simulations show that the detectability of various connectivity patterns depends on various parameters such as connectivity strength and background activity. In particular, the detectability decreases with the number of neurons included in the analysis and increases with the recording time. Further, we show that the method can also be used to detect multiple direct connectivities between two neurons. Finally, the methods of this paper are illustrated by an application to neurophysiological data from spinal dorsal horn neurons.     

Neuronal activity in the prefrontal cortex in rats with various typological features during emotional affect

Unit activity in the right and left prefrontal cortex was recorded in male Wistar rats after testing by the emotional resonance technique. Rats were divided in two groups by their reaction to the suffering cry of a partner. Rats from the group A ("altruists") escaped partner's crying, and those from the group E ("egoists") did not. Activity of neurons was analyzed in hungry rats, after feeding, during intracranial emotionally positive and negative stimulation, and during crying of the rat partner. Some differences in neural activity between A and E groups were revealed. In the hungry state the rate of neuronal discharges was higher in the A group. In both groups of animals the positive emotional stimulation was accompanied by more intensive neuronal reaction that the negative stimulation, but in the E group increase in the rate of neuronal discharges in both hemispheres was significantly more pronounced. Negative stimulation produced in both groups a significantly greater activation in the left hemisphere than in the right one while during the positive stimulation the neural activity was more intensive in the left hemisphere. The neuronal reaction to partner's crying was significantly higher in the A group in both hemispheres, while the neuronal activity in E group did not significantly change.     

Effects of Immobilization Stress on the Background Impulse Activity of Locus Coeruleus Neurons

We studied in rats changes in the impulse background activity (BA) of locus coeruleus (LC) neurons after short- and long-term immobilization stress; distributions of LC neurons by the level of regularity of their BA, dynamics of spike trains, and pattern of histograms of interspike intervals (ISI) were taken into account. We also calculated the means of the main BA statistical indices. Both short- and long-lasting immobilizations resulted in drops in the mean frequency of background discharges of LC neurons to about half of the initial value. Two-hour-long immobilization evoked statistically significant shifts in the distribution of LC neurons by the level of regularity of their BA, while after longer (15 h) immobilization this distribution nearly returned to the initial pattern. Short-lasting immobilization exerted no significant effect on the dynamic characteristics of BA; statistically significant changes in this respect developed only after longer stress. After 15-h-long immobilization, we also observed a noticeable increase in the number of neurons with polymodal ISI distributions. Therefore, stress results in significant modifications of the temporal parameters of the BA of LC neurons; characteristics of the BA of these neurons should be considered neuronal correlates of the stress state.     

Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex

The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC) of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70–200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys’ behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators.     

Neuronal spike trains and stochastic point processes. II. Simultaneous spike trains

The statistical analysis of two simultaneously observed trains of neuronal spikes is described, using as a conceptual framework the theory of stochastic point processes.The first statistical question that arises is whether the observed trains are independent; statistical techniques for testing independence are developed around the notion that, under the null hypothesis, the times of spike occurrence in one train represent random instants in time with respect to the other. If the null hypothesis is rejected—if dependence is attributed to the trains—the problem then becomes that of characterizing the nature and source of the observed dependencies. Statistical signs of various classes of dependencies, including direct interaction and shared input, are discussed and illustrated through computer simulations of interacting neurons. The effects of nonstationarities on the statistical measures for simultaneous spike trains are also discussed. For two-train comparisons of irregularly discharging nerve cells, moderate nonstationarities are shown to have little effect on the detection of interactions.Combining repetitive stimulation and simultaneous recording of spike trains from two (or more) neurons yields additional clues as to possible modes of interaction among the monitored neurons; the theory presented is illustrated by an application to experimentally obtained data from auditory neurons.A companion paper covers the analysis of single spike trains.     

Critical parameters of the spike trains in a cell assembly: coding of turn direction by the giant interneurons of the cockroach

Cockroaches (Periplaneta americana) respond to air displacement produced by an approaching predator by turning and running away. A set of 4 bilateral pairs of ventral giant interneurons is important in determining turn direction. Wind from a given side is known to produce more spikes, an earlier onset of the spike trains, and different fine temporal patterning, in the ipsilateral vs the contralateral set of these interneurons. Here we investigate which of these spike train parameters the cockroach actually uses to determine the direction it will turn.We delivered controlled wind puffs from the right front, together with intracellular injection of spike trains in a left ventral giant interneuron, under conditions where the animal could make normally directed turning movements of the legs and body. In trials where our stimuli caused the left side to give both the first spike and more total spikes than the right, but where our injected spike train included none of the normal fine temporal patterning, 92% of the evoked turns were to the rightopposite of normal (Figs. 4–6). In trials where the left side gave the first spike, but the right side gave more spikes, 100% of the turns were to the left-the normal direction (Figs. 8, 9). Comparable results were obtained when each of the left giant interneurons 1, 2 or 3 were electrically stimulated, and when either weak or stronger wind puffs were used. Stimulating a left giant interneuron electrically in the absence of a wind puff evoked an escape-like turn on 9% of the trials, and these were all to the right (Fig. 9).These results indicate that fine temporal patterning in the spike trains is not necessary, and information about which side gives the first spike is not sufficient, to determine turn direction. Rather, the key parameter appears to be relative numbers of action potentials in the left vs the right group of cells. These conclusions were supported by similar experiments in which extracellular stimulation of several left giant interneurons was paired with right wind (Figs. 11, 12).Abbreviations GI giant interneuron - vGI ventral giant interneuron - dGI dorsal giant interneuron - LY Lucifer yellow - CF carboxyfluorescein     

Analyzing multiple spike trains with nonparametric granger causality

Simultaneous recordings of spike trains from multiple single neurons are becoming commonplace. Understanding the interaction patterns among these spike trains remains a key research area. A question of interest is the evaluation of information flow between neurons through the analysis of whether one spike train exerts causal influence on another. For continuous-valued time series data, Granger causality has proven an effective method for this purpose. However, the basis for Granger causality estimation is autoregressive data modeling, which is not directly applicable to spike trains. Various filtering options distort the properties of spike trains as point processes. Here we propose a new nonparametric approach to estimate Granger causality directly from the Fourier transforms of spike train data. We validate the method on synthetic spike trains generated by model networks of neurons with known connectivity patterns and then apply it to neurons simultaneously recorded from the thalamus and the primary somatosensory cortex of a squirrel monkey undergoing tactile stimulation.     

STOCHASTIC RESONANCE MEASURED BY THEMUTUAL INFORMATION IN THE NEURONSTHAT TRANSMIT CHAOTIC SPIKE TRAINS

The spike trains generated by a neuron model are studied by the methods of nonlinear time series analysis. The results show that the spike trains are chaotic. To investigate effect of noise on transmission of chaotic spike trains, this chaotic spike trains are used as a discrete subthreshold input signal to the integrate-and-fire neuronal model and the FitzHugh-Nagumo(FHN) neuronal model working in noisy environment. The mutual information between the input spike trains and the output spike trains is calculated, the result shows that the transformation of information encoded by the chaotic spike trains is optimized by some level of noise, and stochastic resonance(SR) measured by mutual information is a property available for neurons to transmit chaotic spike trains.     

Conjugation of the neuronal impulse activity in the rabbit neocortex during self stimulation of the lateral hypothalamus

Correlation of impulse activity of visual and sensorimotor neurons of both hemispheres in 10-s interval after self-stimulation of the right and left lateral hypothalamus was studied by plotting cross- and autocorrelation histograms. The number of cell pairs, in which sensorimotor neurons discharged after visual ones, increased after self-stimulation (from 24 +/- 6 to 44 +/- 7%). Frequencies of the alpha- and theta-range in crosscorrelograms increased; the alpha frequency increased mainly in the right hemisphere, while the theta frequency increased in the left hemisphere. The interhemispheric asymmetry in the interaction between cortical neurons was not associated with the side of hypothalamic stimulation.     

STOCHASTIC RESONANCE MEASURED BY THEMUTUAL INFORMATION IN THE NEURONSTHAT TRANSMIT CHAOTIC SPIKE TRAINS

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A model for the neuronal implementation of selective visual attention based on temporal correlation among neurons

We propose a model for the neuronal implementation of selective visual attention based on temporal correlation among groups of neurons. Neurons in primary visual cortex respond to visual stimuli with a Poisson distributed spike train with an appropriate, stimulus-dependent mean firing rate. The spike trains of neurons whose receptive fields donot overlap with the focus of attention are distributed according to homogeneous (time-independent) Poisson process with no correlation between action potentials of different neurons. In contrast, spike trains of neurons with receptive fields within the focus of attention are distributed according to non-homogeneous (time-dependent) Poisson processes. Since the short-term average spike rates of all neurons with receptive fields in the focus of attention covary, correlations between these spike trains are introduced which are detected by inhibitory interneurons in V4. These cells, modeled as modified integrate-and-fire neurons, function as coincidence detectors and suppress the response of V4 cells associated with non-attended visual stimuli. The model reproduces quantitatively experimental data obtained in cortical area V4 of monkey by Moran and Desimone (1985).     

Quantification of Clustering in Joint Interspike Interval Scattergrams of Spike Trains

Joint interval scattergrams are usually employed in determining serial correlations between events of spike trains. However, any inherent structures in such scattergrams that are often seen in experimental records are not quantifiable by serial correlation coefficients. Here, we develop a method to quantify clustered structures in any two-dimensional scattergram of pairs of interspike intervals. The method gives a cluster coefficient as well as clustering density function that could be used to quantify clustering in scattergrams obtained from first- or higher-order interval return maps of single spike trains, or interspike interval pairs drawn from simultaneously recorded spike trains. The method is illustrated using numerical spike trains as well as in vitro pairwise recordings of rat striatal tonically active neurons.     

A cross-interval spike train analysis: the correlation between spike generation and temporal integration of doublets

A stochastic spike train analysis technique is introduced to reveal the correlation between the firing of the next spike and the temporal integration period of two consecutive spikes (i.e., a doublet). Statistics of spike firing times between neurons are established to obtain the conditional probability of spike firing in relation to the integration period. The existence of a temporal integration period is deduced from the time interval between two consecutive spikes fired in a reference neuron as a precondition to the generation of the next spike in a compared neuron. This analysis can show whether the coupled spike firing in the compared neuron is correlated with the last or the second-to-last spike in the reference neuron. Analysis of simulated and experimentally recorded biological spike trains shows that the effects of excitatory and inhibitory temporal integration are extracted by this method without relying on any subthreshold potential recordings. The analysis also shows that, with temporal integration, a neuron driven by random firing patterns can produce fairly regular firing patterns under appropriate conditions. This regularity in firing can be enhanced by temporal integration of spikes in a chain of polysynaptically connected neurons. The bandpass filtering of spike firings by temporal integration is discussed. The results also reveal that signal transmission delays may be attributed not just to conduction and synaptic delays, but also to the delay time needed for temporal integration. Received: 3 March 1997 / Accepted in revised form: 6 November 1997     

Testing of information condensation in a model reverberating spiking neural network

Information about external world is delivered to the brain in the form of structured in time spike trains. During further processing in higher areas, information is subjected to a certain condensation process, which results in formation of abstract conceptual images of external world, apparently, represented as certain uniform spiking activity partially independent on the input spike trains details. Possible physical mechanism of condensation at the level of individual neuron was discussed recently. In a reverberating spiking neural network, due to this mechanism the dynamics should settle down to the same uniform/ periodic activity in response to a set of various inputs. Since the same periodic activity may correspond to different input spike trains, we interpret this as possible candidate for information condensation mechanism in a network. Our purpose is to test this possibility in a network model consisting of five fully connected neurons, particularly, the influence of geometric size of the network, on its ability to condense information. Dynamics of 20 spiking neural networks of different geometric sizes are modelled by means of computer simulation. Each network was propelled into reverberating dynamics by applying various initial input spike trains. We run the dynamics until it becomes periodic. The Shannon's formula is used to calculate the amount of information in any input spike train and in any periodic state found. As a result, we obtain explicit estimate of the degree of information condensation in the networks, and conclude that it depends strongly on the net's geometric size.     

Neural coding properties based on spike timing and pattern correlation of retinal ganglion cells

Correlation between spike trains or neurons sometimes indicates certain neural coding rules in the visual system. In this paper, the relationship between spike timing correlation and pattern correlation is discussed, and their ability to represent stimulus features is compared to examine their coding strategies not only in individual neurons but also in population. Two kinds of stimuli, natural movies and checkerboard, are used to arouse firing activities in chicken retinal ganglion cells. The spike timing correlation and pattern correlation are calculated by cross-correlation function and Lempel–Ziv distance respectively. According to the correlation values, it is demonstrated that spike trains with similar spike patterns are not necessarily concerted in firing time. Moreover, spike pattern correlation values between individual neurons’ responses reflect the difference of natural movies and checkerboard; neurons cooperate with each other with higher pattern correlation values which represent spatiotemporal correlations during response to natural movies. Spike timing does not reflect stimulus features as obvious as spike patterns, caused by their particular coding properties or physiological foundation. As a result, separating the pattern correlation out of traditional timing correlation concept uncover additional insight in neural coding.     

Significance of the corpus callosum in the paired activity of the respiratory center

The asymmetrical reactions of respiratory neurons of the right and left halves of the respiratory center and varied changes in bioelectrical activity of external intercostal muscles on both sides of the chest were discovered in experiments on anesthetized cats in response to successive electrical stimulation of the symmetrical cortical areas of the right and left cerebral hemispheres before and after callosotomy. It was demonstrated that callosotomy increased on both sides of the respiratory center the quantity of neurons responsive to ipsilateral cortical stimulation and determined the character of the asymmetrical reactions of right and left respiratory neurons and intercostal muscles. On the basis of the data obtained it is concluded that the corpus callosum contributes to the functional integration of both halves of the respiratory center.