Dependence of cortical plasticity on correlated activity of single neurons and on behavioral context.

It has not been possible to analyze the cellular mechanisms underlying learning in behaving mammals because of the difficulties in recording intracellularly from awake animals. Therefore, in the present study of neuronal plasticity in behaving monkeys, the net effect of a single neuron on another neuron (the "functional connection") was evaluated by cross-correlating the times of firing of the two neurons. When two neurons were induced to fire together within a short time window, the functional connection between them was potentiated, and when simultaneous firing was prevented, the connection was depressed. These modifications were strongly dependent on the behavioral context of the stimuli that induced them. The results indicate that changes in the temporal contingency between neurons are often necessary, but not sufficient, for cortical plasticity in the adult monkey: behavioral relevance is required.

Physiological aspects of information processing in the basal ganglia of normal and parkinsonian primates.

There are two views as to the character of basal-ganglia processing - processing by segregated parallel circuits or by information sharing. To distinguish between these views, we studied the simultaneous activity of neurons in the output stage of the basal ganglia with cross-correlation techniques. The firing of neurons in the globus pallidus of normal monkeys is almost always uncorrelated. However, after dopamine depletion and induction of parkinsonism by treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), oscillatory activity appeared and the firing of many neurons became correlated. We conclude that the normal dopaminergic system supports segregation of the functional subcircuits of the basal ganglia, and that a breakdown of this independent processing is a hallmark of Parkinson's disease.

Firing patterns and correlations of spontaneous discharge of pallidal neurons in the normal and the tremulous 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine vervet model of parkinsonism.

To investigate the role of the basal ganglia in parkinsonian tremor, we recorded hand tremor and simultaneous activity of several neurons in the external and internal segments of the globus pallidus (GPe and GPi) in two vervet monkeys, before and after systemic treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and development of parkinsonism with tremor of 5 and 11 Hz. In healthy monkeys, only 11% (20/174) of the GPe cells and 3% (1/29) of the GPi cells displayed significant 3-19 Hz oscillations. After MPTP treatment, 39% (107/271) of the GPe cells and 43% (26/61) of the GPi cells developed significant oscillations. Oscillation frequencies of single cells after MPTP treatment were bimodally distributed around 7 and 13 Hz. For 10% of the oscillatory cells that were recorded during tremor periods, there was a significant tendency for the tremor and neuronal oscillations to appear simultaneously. Cross-correlation analysis revealed a very low level of correlated activity between pallidal neurons in the normal state; 95.6% (477/499) of the pairs were not correlated, and oscillatory cross-correlograms were found in only 1% (5/499) of the pairs. After MPTP treatment, the correlations increased dramatically, and 40% (432/1080) of the cross-correlograms had significant oscillations, centered around 13-14 Hz. Phase shifts of the cross-correlograms of GPe pairs, but not of GPi, were clustered around 0 degrees. The results illustrate that MPTP treatment changes the pattern of activity and synchronization in the GPe and GPi. These changes are related to the symptoms of Parkinson's disease and especially to the parkinsonian tremor.

Activity of pallidal and striatal tonically active neurons is correlated in mptp-treated monkeys but not in normal monkeys.

The goal of this study is to assess the function of tonically active neurons (TANs) of the striatum and their malfunction in the parkinsonian state. We recorded multiple spike trains of striatal TANs and pallidal neurons, which are the main target of striatal projections. Recordings were performed in two vervet monkeys before and after the induction of tremulous parkinsonism by systemic injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine hydrochloride (MPTP). We then calculated cross-correlograms between TANs and pallidal neurons to evaluate the interactions between them. In the normal monkeys, only 1.3% (2/152) of the cross-correlograms displayed significant peaks, and 8.6% (13/152) displayed significant oscillations. After MPTP treatment, 42.8% (83/194) of the cross-correlograms displayed significant peaks or troughs, or both, and 58.8% (114/194) displayed significant 3-19 Hz periodic oscillations. The frequency content of the coherent oscillations matched the frequency content of the activity of individual TANs, but was only weakly related to that of individual pallidal cells. These results confirm the notion that in the normal state neurons in the basal ganglia tend to fire independently, whereas in the parkinsonian state they exhibit synchronized oscillatory activity. The low level of correlated activity in the normal state demonstrates that TANs have only a slight effect on pallidal activity during execution of familiar behavior. The high level of oscillatory correlated activity in the parkinsonian state further suggests that coherent oscillations of the whole basal ganglia circuitry underlie the clinical features of Parkinson's disease.

Hebbian-like functional plasticity in the auditory cortex of the behaving monkey.

In this study, the necessary conditions, including those related to behavior, for lasting modifications to occur in correlated activity ('functional plasticity') were examined in the behaving monkey. Previously, in-vitro studies of neuronal plasticity yielded important information about possible mechanisms of synaptic plasticity, but could not be used to test their functionality in the intact, behaving brain. In-vivo studies usually focused on analysis of the responsiveness of single cells, but did not examine interactions between pairs of neurons. In this study, we combined the two approaches. This was achieved by recording extracellularly and simultaneously the spike activity of several single cells in the auditory cortex of the behaving monkey. The efficacy of neuronal interactions was estimated by measuring the correlation between firing times of pairs of single neurons. Using acoustic stimuli, a version of cellular conditioning was applied when the monkey performed an auditory discrimination task and when it did not. We found that: (i) functional plasticity is a function of the change in correlation, and not of the correlation or covariance per se, and (ii) functional plasticity depends critically on behavior. During behavior, an increase in the correlation caused a short-lasting strengthening of the neuronal coupling efficacy, and a decrease caused a short-lasting weakening. These findings indicate that neuronal plasticity in the auditory cortex obeys a version of Hebb's associative rule under strong behavioral control, as predicted by Thorndike's "Law of Effect".

'Dynamics of neuronal interactions' cannot be explained by 'neuronal transients'.

In a recent paper, Vaadia et al. demonstrated that patterns of firing correlation between single neurons in the cortex of behaving monkeys can be modified within a fraction of a second. These changes occur in relation to sensory stimuli and behavioral events, and even without modulations of the neurons' firing rates. These findings call for a revision of prevailing models of neural coding that solely rely on single neuron firing rates. In a defense of these models, Friston put forward an alternative explanation, proposing that the observed correlation dynamics emerge solely from co-modulations of the firing rates of each of the neurons, while the strength of their interaction remains constant. To test this possibility we re-examined the data, adopting Friston's 'neuronal transients' model, and the associated equations and procedures. We found that, to explain the dynamic correlation between a pair of neurons, the alternative interpretation requires that each neuron's response to a single stimulus is composed of a relatively large number of independent components, which co-vary with their counterparts in the companion neuron. This large number of components and their shapes lead us to conclude that, although in principle possible, the neuronal transients model: (i) does not provide a simpler explanation of the experimental results; and (ii) cannot explain these results without itself deviating significantly from most rate code models.

Failure in identification of overlapping spikes from multiple neuron activity causes artificial correlations.

Recording of multiple neurons from a single electrode is common practice during extra-cellular recordings. Separation and sorting of spikes originating from the different neurons can be performed either on-line or off-line using multiple methods for pattern matching. However, all spike sorting techniques fail either fully or partially in identifying spikes from multiple neurons when they overlap due to occurrence within a short time interval. This failure, that we termed the 'shadowing effect', causes the well-known phenomenon of decreased cross-correlation at zero offset. However, the shadowing effect also causes other artifacts in the auto and cross-correlation of the recorded neurons. These artifacts are significant mainly in brain areas with high firing rate or increased firing synchrony leading to a high probability of spike overlap. Cross correlation of cells recorded from the same electrodes tends to reflect the autocorrelation functions of the two cells, even when there are no functional interactions between the cells. Therefore, the cross-correlation function tends to have a short-term (about the length of the refractory period) peak. A long-term (hundreds of milliseconds to a few seconds) trough in the cross-correlation can be seen in cells with bursting and pausing activities recorded from the same electrode. Even the autocorrelation functions of the recorded neurons feature firing properties of other neurons recorded from the same electrode. Examples of these effects are given from our recordings in the globus pallidus of behaving primates and from the literature. Results of simulations of independent simple model neurons exhibit the same properties as the recorded neurons. The effect is analyzed and can be estimated to enable better evaluation of the underlying firing patterns and the actual synchronization of neighboring neurons recorded by a single electrode.

The effects of stimuli on the activity and functional connectivity of local neuronal groups in the cat auditory cortex.

Simultaneous extracellular recordings from one electrode of 'local' groups of 3-6 neurons were obtained from the auditory cortex of unanesthetized, paralyzed cats. The activity and functional connectivity of local microenvironments were examined under various auditory stimuli. Single cell response patterns were examined using peri-stimulus (PST) histograms and functional connectivity among neighboring cells by the cross renewal density (CRD) histograms. Analysis of the PST histograms suggested that a high percentage of single cells demonstrated different response patterns to different stimuli. Analysis of the CRD histograms suggested, on the one hand, that only small numbers of neighboring cells behaved as if there were direct connections from one cell to another, and that these direct connections appeared to be excitatory. On the other hand, many cell pairs shared input from shared sources which lay outside the local groups. The majority of functional connections were altered by at least one of the stimuli delivered, thus demonstrating the system's plasticity. It is suggested that long-term gates at the synaptic level are responsible for this phenomenon.

Population responses to multifrequency sounds in the cat auditory cortex: one- and two-parameter families of sounds.

Population responses to multi-frequency sounds were recorded in primary auditory cortex of anesthetized cats. The sounds consisted of single-tone stimuli; two-tone stimuli; and nine-tone stimuli, with the tones evenly spaced on a linear frequency scale. The stimuli were presented through a sealed, calibrated sound delivery system. Single units, cluster activity (CA) and the short-time mean absolute value of the envelope of the neural signal (MABS) were recorded extracellularly from six microelectrodes simultaneously. The CA and MABS were interpreted as measures of the activity of large populations of neurons, in contrast with the single unit activity which is presumably recorded from single neurons. The responses of the MABS signal to simple stimuli were generally similar to those of the CA, but were more stable statistically. Thus, the MABS is better suited for studying the activity of populations of neurons. The responses to tones near the best frequency were strongly influenced by a second tone, even when the second tone was outside the single-tone response area. These influences could be both facilitatory and suppressory. They could not be predicted from the responses to single tones. The responses to the nine-tone stimuli could be explained qualitatively by the responses to the two-tone stimuli. It is concluded that the population responses in primary auditory cortex are shaped by the contributions of the individual frequencies appearing in the stimulus and by the interactions between pairs of frequencies. Interactions between stimulus components are therefore a necessary component of any attempt to explain the processing of complex sounds in the auditory cortex. They may play a role in a global representation of the stimulus spectrum in the primary auditory cortex. The presence of higher-order interactions cannot be excluded by the results presented here.

In search of the best stimulus: an optimization procedure for finding efficient stimuli in the cat auditory cortex.

Units in the auditory cortex of cats respond to a large variety of stimuli: pure tones, AM- and FM-modulated signals, clicks, wideband noise, natural sounds, and more. However, no single family of sounds was found to be optimal (in the sense that oriented lines are optimal in the visual cortex). The search for optimal complex sounds is hard because of the high dimensionality of the space of interesting sounds. In an effort to overcome this problem, an automatic search procedure for finding efficient stimuli in high-dimensional sound spaces was developed. This procedure chooses the stimuli to be presented according to the responses to past stimuli, trying to increase the strength of the response. The results of applying this method to recordings of population activity in the primary auditory cortex of cats are described. The search was applied to single tones, two-tone stimuli, four-tone stimuli and to a two-dimensional subset of nine-tone stimuli, parametrized by the center frequency and the fixed difference between adjacent frequencies. The method was able to find efficient stimuli, and its performance improved with the dimension of the sound spaces. Efficient stimuli, found in different optimization runs using population activity recorded from the same electrode, often shared similar frequencies and pairs of frequencies, and tended to evoke similar levels of activity. This result indicates that a global analysis of the location of spectral peaks is performed at the level of the auditory cortex.

Neuronal activities related to higher brain functions--theoretical and experimental implications.

The activities of several single units (6-10) were recorded simultaneously in the auditory cortex and in frontal cortical areas of cats and monkeys. The response properties of the single units and the interaction between them were studied. It is shown that single units in both areas may participate in prolonged processes and be involved in more than one process. Adjacent neurons need not function in unison; while some neurons are activated, others may stay inactive. The interactions among adjacent neurons are weak, and can be modulated by sensory stimulation, and by arousal and behavioral states. These properties lead us to hypothesize that information is represented in the cortex by coactivation of sets of neurons rather than by independent modulation of the single-unit firing rate. A single unit may be a member of several representing sets. Thus, each neuron may participate in more than one function and each small cortical area may contain members of several functional sets. A mechanism for computing and transmitting information, based on converging-diverging links, between neuronal sets is described and tested by simulations and analysis of experimental data.

Emergence of spatio-temporal patterns in neuronal activity.

This paper explores if dynamic modulation of coherent firing serves cortical functions. We recorded neuronal activity in the frontal cortex of behaving monkeys and found that temporal coincidences of spikes firing of different neurons can emerge within a fraction of a second in relation to the animal behavior. The temporal patterns of the correlation could not be predicted from the modulations of the neurons firing rate and finally, the patterns of correlation depend on the distance between neurons. These findings call for a revision of prevailing models of neural coding that solely rely on firing rates. The findings suggest that modification of neuronal interactions can serve as a mechanism by which neurons associate rapidly into a functional group in order to perform a specific computational task. Increased correlation between members of the groups, and decreased or negative correlation with others, enhance the ability to dissociate one group from concurrently activated competing groups. Such modulation of neuronal interactions allows each neuron to become a member of several different groups and participate in different computational tasks.

Single-unit activity related to active localization of acoustic and visual stimuli in the frontal cortex of the rhesus monkey.

Single-unit recordings were made in monkey periarcuate regions during the performance of limb movement tasks. A large class of neurons is described that appear to be involved in active localization of both acoustic and visual stimuli. These neurons failed to respond to stimuli of either modalities except in tasks where the location of the stimulus served as the cue for direction of movement.

Temporal firing patterns of single units, pairs and triplets of units in the auditory cortex.

The spontaneous and acoustically driven activities of single units, pairs and triplets of units in the auditory cortex were analyzed. Data were obtained in two sets of experiments from nonbehaving awake cats and from a behaving monkey. The results of the two sets of experiments indicated that neighboring neurons usually fire independently. The weak correlations found between pairs of adjacent neurons were mostly indicative of a common input driving both units. In some cases, signs of synaptic interaction between the neurons were found. When triplets of units were considered, it was found that several independent inputs exist, even within a small group of adjacent neurons. When such small groups of neurons were studied in the behaving monkey, it was found that the temporal firing pattern of single neurons and the interactions between pairs of neurons were in some cases dependent on the behavioral state and on the sensorimotor association.

Dynamics of neuronal interactions: relation to behavior, firing rates, and distance between neurons.

This report describes exploration of the hypothesis that cortical function is mediated by dynamic modulation of coherent firing in groups of neurons. We recorded neuronal activity in the frontal cortex of behaving monkeys and found that correlation between neurons changed frequently within a fraction of a second and in relation to behavior. Those modulations can happen without modulation of firing rates. When firing rates are modulated, the modulation of correlation is not related to it in a simple way. Moreover, the dynamic patterns of correlation depend on the distance between neurons. These findings support the notion that, in order to perform a computational task, neurons can associate rapidly into a functional group, while dissociating from concurrently activated competing groups.

A sensitive estimator for crosscorrelograms.

The best established method for finding interactions between extracellularly recorded neurons is the crosscorrelation technique. The method is simple and useful, but it has some drawbacks. One of them is its limited sensitivity to weak interactions, which are common in the mammalian cerebral cortex. In the present paper a new method for the estimation of interaction strength is presented. This method is based on the intensity representation of point processes, and provides an optimal estimator for the intensity of the postsynaptic spike train. The estimator is complicated to use, but it can be approximated by a simple estimator, similar to ordinary measures of synaptic efficacy like the area under the crosscorrelogram peak. Simulation results, showing the advantage of the new estimator over the commonly used efficacy estimators and some measure of its robustness to deviations from model assumptions, are presented. Finally, application of the estimator to the analysis of simultaneous recordings of physiological single units is demonstrated.

Oscillatory activity of single units in a somatosensory cortex of an awake monkey and their possible role in texture analysis.

Neuronal activity was extracellularly recorded in the cortex of an awake monkey (Macaca fascicularis). Single units displaying oscillatory firing patterns were found in the upper bank of the lateral sulcus in a region where most of the neurons responded to somatosensory stimuli. The spectral energies of the oscillating activity were distributed in a trimodal fashion--0-15, 15-50, and 80-250 Hz--with the most common frequencies around 30 Hz. The oscillatory activity was not affected by anesthesia, but it was often reduced by tactile stimulation or self-initiated movements. Analysis of the spike trains suggests that the majority of oscillatory activity was intrinsically generated by the neurons. A neural model of texture analysis is offered based on a corticothalamic phase-locked loop. The newly identified oscillators play a key role in this model. The relevance of the model to physiological, anatomical, and psychophysical data, as well as testable predictions, are discussed.