Statistical signs of synaptic interaction in neurons

Statistically rigorous calculations do not support common input and long-term synchronization of motor-unit firings

Over the past four decades, various methods have been implemented to measure synchronization of motor-unit firings. In this work, we provide evidence that prior reports of the existence of universal common inputs to all motoneurons and the presence of long-term synchronization are misleading, because they did not use sufficiently rigorous statistical tests to detect synchronization. We developed a statistically based method (SigMax) for computing synchronization and tested it with data from 17,736 motor-unit pairs containing 1,035,225 firing instances from the first dorsal interosseous and vastus lateralis muscles--a data set one order of magnitude greater than that reported in previous studies. Only firing data, obtained from surface electromyographic signal decomposition with >95% accuracy, were used in the study. The data were not subjectively selected in any manner. Because of the size of our data set and the statistical rigor inherent to SigMax, we have confidence that the synchronization values that we calculated provide an improved estimate of physiologically driven synchronization. Compared with three other commonly used techniques, ours revealed three types of discrepancies that result from failing to use sufficient statistical tests necessary to detect synchronization. 1) On average, the z-score method falsely detected synchronization at 16 separate latencies in each motor-unit pair. 2) The cumulative sum method missed one out of every four synchronization identifications found by SigMax. 3) The common input assumption method identified synchronization from 100% of motor-unit pairs studied. SigMax revealed that only 50% of motor-unit pairs actually manifested synchronization.

Joint cross-correlation analysis reveals complex, time-dependent functional relationship between cortical neurons and arm electromyograms

Correlation between cortical activity and electromyographic (EMG) activity of limb muscles has long been a subject of neurophysiological studies, especially in terms of corticospinal connectivity. Interest in this issue has recently increased due to the development of brain-machine interfaces with output signals that mimic muscle force. For this study, three monkeys were implanted with multielectrode arrays in multiple cortical areas. One monkey performed self-timed touch pad presses, whereas the other two executed arm reaching movements. We analyzed the dynamic relationship between cortical neuronal activity and arm EMGs using a joint cross-correlation (JCC) analysis that evaluated trial-by-trial correlation as a function of time intervals within a trial. JCCs revealed transient correlations between the EMGs of multiple muscles and neural activity in motor, premotor and somatosensory cortical areas. Matching results were obtained using spike-triggered averages corrected by subtracting trial-shuffled data. Compared with spike-triggered averages, JCCs more readily revealed dynamic changes in cortico-EMG correlations. JCCs showed that correlation peaks often sharpened around movement times and broadened during delay intervals. Furthermore, JCC patterns were directionally selective for the arm-reaching task. We propose that such highly dynamic, task-dependent and distributed relationships between cortical activity and EMGs should be taken into consideration for future brain-machine interfaces that generate EMG-like signals.

Quantification of pairwise neuronal interactions: going beyond the significance lines

BACKGROUND

Normal brain function depends on intact interactions between multiple neuronal ensembles. Interactions within and between local networks comprising multiple neuronal types may occur on a range of time scales thus affecting the estimation of interaction strength. A common technique to investigate functional interactions within neuronal ensembles is pairwise cross-correlation analysis. However, conventional cross-correlation methods address the question of whether an observed peak in the cross-correlation is statistically significant relative to the null hypothesis which assumes a lack of correlation. Ultimately, these methods were not designed to evaluate the strength of the observed interactions.

NEW METHOD

We devised four complementary measures - Triplets, Bin crossing, Bin height and Entropy - for assessing the strength of neuronal interactions; each is sensitive to different features of the cross-correlogram peak such as height, width and smoothness.

RESULTS

First, a comparison of five prevalent methods for evaluating whether an observed peak in neuronal cross-correlogram is significant allowed their ranking from the most conservative to the more sensitive for purposes of selecting the appropriate method based on the data structure and preferred strategy. Second, the performance of the four measures we derived improved with interaction strength and the number of spikes in the cross-correlogram. The four measures also enabled the reconstruction of interaction parameters of simulated networks including the detection of time-dependent alterations.

CONCLUSIONS

We suggest that the combination of several measures of peak characteristics helps rectify the individual shortcomings of specific measures and can yield a broad coverage of interaction strengths and widths.

Elevated correlations in neuronal ensembles of mouse auditory cortex following parturition

The auditory cortex is malleable by experience. Previous studies of auditory plasticity have described experience-dependent changes in response profiles of single neurons or changes in global tonotopic organization. However, experience-dependent changes in the dynamics of local neural populations have remained unexplored. In this study, we examined the influence of a dramatic yet natural experience in the life of female mice, giving birth and becoming a mother on single neurons and neuronal ensembles in the primary auditory cortex (A1). Using in vivo two-photon calcium imaging and electrophysiological recordings from layer 2/3 in A1 of mothers and age-matched virgin mice, we monitored changes in the responses to a set of artificial and natural sounds. Population dynamics underwent large changes as measured by pairwise and higher-order correlations, with noise correlations increasing as much as twofold in lactating mothers. Concomitantly, changes in response properties of single neurons were modest and selective. Remarkably, despite the large changes in correlations, information about stimulus identity remained essentially the same in the two groups. Our results demonstrate changes in the correlation structure of neuronal activity as a result of a natural life event.

Active decorrelation in the basal ganglia

The cytoarchitecturally-homogeneous appearance of the globus pallidus, subthalamic nucleus and substantia nigra has long been said to imply a high degree of afferent convergence and sharing of inputs by nearby neurons. Moreover, axon collaterals of neurons in the external segment of the globus pallidus and the substantia nigra pars reticulata arborize locally and make inhibitory synapses on other cells of the same type. These features suggest that the connectivity of the basal ganglia may impose spike-time correlations among the cells, and it has been puzzling that experimental studies have failed to demonstrate such correlations. One possible solution arises from studies of firing patterns in basal ganglia cells, which reveal that they are nearly all pacemaker cells. Their high rate of firing does not depend on synaptic excitation, but they fire irregularly because a dense barrage of synaptic inputs normally perturbs the timing of their autonomous activity. Theoretical and computational studies show that the responses of repetitively-firing neurons to shared input or mutual synaptic coupling often defy classical intuitions about temporal synaptic integration. The patterns of spike-timing among such neurons depend on the ionic mechanism of pacemaking, the level of background uncorrelated cellular and synaptic noise, and the firing rates of the neurons, as well as the properties of their synaptic connections. Application of these concepts to the basal ganglia circuitry suggests that the connectivity and physiology of these nuclei may be configured to prevent the establishment of permanent spike-timing relationships between neurons. The development of highly synchronous oscillatory patterns of activity in Parkinson's disease may result from the loss of pacemaking by some basal ganglia neurons, and accompanying breakdown of the mechanisms responsible for active decorrelation.

The representation of egocentric space in the posterior parietal cortex

The posterior parietal cortex (PPC) is the most likely site where egocentric spatial relationships are represented in the brain. PPC cells receive visual, auditory, somaesthetic, and vestibular sensory inputs; oculomotor, head, limb, and body motor signals; and strong motivational projections from the limbic system. Their discharge increases not only when an animal moves towards a sensory target, but also when it directs its attention to it. PPC lesions have the opposite effect: sensory inattention and neglect. The PPC does not seem to contain a "map" of the location of objects in space but a distributed neural network for transforming one set of sensory vectors into other sensory reference frames or into various motor coordinate systems. Which set of transformation rules is used probably depends on attention, which selectively enhances the synapses needed for making a particular sensory comparison or aiming a particular movement.

Differences in intrinsic functional organization between dorsolateral prefrontal and posterior parietal cortex

The dorsolateral prefrontal and posterior parietal cortex are 2 components of the cortical network controlling attention, working memory, and executive function. Little is known about how the anatomical organization of the 2 areas accounts for their functional specialization. In order to address this question, we examined the strength of intrinsic functional connectivity between neurons sampled in each area by means of cross-correlation analyses of simultaneous recordings from monkeys trained to perform working memory tasks. In both areas, effective connectivity declined as a function of distance between neurons. However, the strength of effective connectivity was higher overall and more localized over short distances in the posterior parietal than the prefrontal cortex. The difference in connectivity strength between the 2 areas could not be explained by differences in firing rate or selectivity for the stimuli and task events, it was present when the fixation period alone was analyzed, and according to simulation results, was consistent with a systematic difference either in the strength or in the relative numbers of shared inputs between neurons. Our results indicate that the 2 areas are characterized by unique intrinsic functional organization, consistent with known differences in their response patterns during working memory.

Connections between expiratory bulbospinal neurons and expiratory motoneurons in thoracic and upper lumbar segments of the spinal cord

Cross-correlation of neural discharges was used to investigate the connections between expiratory bulbospinal neurons (EBSNs) in the caudal medulla and expiratory motoneurons innervating thoracic and abdominal muscles in anesthetized cats. Peaks were seen in the cross-correlation histograms for around half of the EBSN-nerve pairs for the following: at T8, the nerve branches innervating internal intercostal muscle and external abdominal oblique muscle and a more distal branch of the internal intercostal nerve; and at L1, a nerve branch innervating internal abdominal oblique muscle and a more distal branch of the ventral ramus. Fewer peaks were seen for the L1 nerve innervating external abdominal oblique, but a paucity of presumed α-motoneuron discharges could explain the rarity of the peaks in this instance. Taking into account individual EBSN conduction times to T8 and to L1, as well as peripheral conduction times, nearly all of the peaks were interpreted as representing monosynaptic connections. Individual EBSNs showed connections at both T8 and L1, but without any discernible pattern. The overall strength of the monosynaptic connection from EBSNs at L1 was found to be very similar to that at T8, which was previously argued to be substantial and responsible for the temporal patterns of expiratory motoneuron discharges. However, we argue that other inputs are required to create the stereotyped spatial patterns of discharges in the thoracic and abdominal musculature.

A simple method of cross-correlating spike trains demonstrated on primary muscle spindle ending discharges

A simple method is shown by which spike trains can be correlated. It is based on the Parzen convolution estimation and can easily be implemented with some electronic hardware and an averaging computer. The method is demonstrated on spike trains from primary muscle spindling endinga. Advantages and drawbacks are discussed.

Brain state-dependent neuronal computation

Neuronal firing pattern, which includes both the frequency and the timing of action potentials, is a key component of information processing in the brain. Although the relationship between neuronal output (the firing pattern) and function (during a task/behavior) is not fully understood, there is now considerable evidence that a given neuron can show very different firing patterns according to brain state. Thus, such neurons assembled into neuronal networks generate different rhythms (e.g., theta, gamma and sharp wave ripples), which sign specific brain states (e.g., learning, sleep). This implies that a given neuronal network, defined by its hard-wired physical connectivity, can support different brain state-dependent activities through the modulation of its functional connectivity. Here, we review data demonstrating that not only the firing pattern, but also the functional connections between neurons, can change dynamically. We then explore the possible mechanisms of such versatility, focusing on the intrinsic properties of neurons and the properties of the synapses they establish, and how they can be modified by neuromodulators, i.e., the different ways that neurons can use to switch from one mode of communication to the other.

Short-term synchrony in diverse motor nuclei presumed to receive different extents of direct cortical input

Motor units within human muscles usually exhibit a significant degree of short-term synchronization. Such coincident spiking typically has been attributed to last-order projections that provide common synaptic input across motor neurons. The extent of branched input arising directly from cortical neurons has often been suggested as a critical factor determining the magnitude of short-term synchrony. The purpose of this study, therefore, was to quantify motor unit synchrony in a variety of human muscles differing in the presumed extent of cortical input to their respective motor nuclei. Cross-correlation histograms were generated from the firing times of 551 pairs of motor units in 16 human muscles. Motor unit synchrony tended to be weakest for proximal muscles and strongest for more distal muscles. Previous work in monkeys and humans has shown that the strength of cortical inputs to motor neurons also exhibits a similar proximal-to-distal gradient. However, in the present study, proximal-distal location was not an exclusive predictor of synchrony magnitude. The muscle that exhibited the least synchrony was an elbow flexor, whereas the greatest synchrony was most often found in intrinsic foot muscles. Furthermore, the strength of corticospinal inputs to the abductor hallucis muscle, an intrinsic foot muscle, as assessed through transcranial magnetic stimulation, was weaker than that projecting to the tibialis anterior muscle, even though the abductor hallucis muscle had higher synchrony values compared with the tibialis anterior muscle. We argue, therefore, that factors other than the potency of cortical inputs to motor neurons, such as the number of motor neurons innervating a muscle, significantly affects motor unit synchrony.

Inter-neuronal correlation distinguishes mechanisms of direction selectivity in cortical circuit models

Direction selectivity is a fundamental physiological property that arises from primary visual cortex (V1) circuitry, yet basic questions of how direction-selective (DS) receptive fields are constructed remain unanswered. We built a set of simple, plausible neuronal circuits that produce DS cells via different mechanisms and tested these circuits to determine how they can be distinguished experimentally. Our models consisted of populations of spiking units representing physiological cell classes ranging from LGN cells to V1 complex DS cells. They differed in network architecture and DS mechanism, including linear summation of non-DS simple-cell inputs or nonlinear pairwise combinations of non-DS inputs. The circuits also varied in the location of the DS time delay and whether the DS interaction was facilitatory or suppressive. We tested the models with visual stimuli often used experimentally, including sinusoidal gratings and flashed bars, and computed shuffle-corrected cross-correlograms (CCGs) of spike trains from pairs of units that would be accessible to extracellular recording. We found that CCGs revealed fundamental features of the DS models, including the location of signal delays in the DS circuit and the sign (facilitatory or suppressive) of DS interactions. We also found that correlation was strongly stimulus-dependent, changing with direction and temporal frequency in a manner that generalized across model architectures. Our models make specific predictions for designing, optimizing, and interpreting electrophysiology experiments aimed at resolving DS circuitry and provide new insights into mechanisms that could underlie stimulus-dependent correlation. The models are available and easy to explore at www.imodel.org.

Brain state dependent postinhibitory rebound in entorhinal cortex interneurons

Postinhibitory rebound (PIR) is believed to play an important role in the genesis and maintenance of biological rhythms. While it has been demonstrated during several in vitro studies, in vivo evidence for PIR remains scarce. Here, we report that PIR can be observed in the dorsomedial entorhinal cortex of anesthetized rats, mostly between putatively connected GABAergic interneurons, and that it is more prevalent during the theta (4-6 Hz) oscillation state than the slow (0.5-2 Hz) oscillation state. Functional inhibition was also found to be brain state and postsynaptic cell type dependent but that alone could not explain this brain state dependence of PIR. A theoretical analysis, using two Fitzhugh-Nagumo neurons coupled to an external periodic drive, predicted that the modulation of a faster spiking rate by the slower periodic drive could account for the brain state dependence of PIR. Model predictions were verified experimentally. We conclude that PIR is cell type and brain state dependent and propose that this could impact network synchrony and rhythmogenesis.

Analysis of motoneuron responses to composite synaptic volleys (computer simulation study)

This paper deals with the analysis of changes in motoneuron (MN) firing evoked by repetitively applied stimuli aimed toward extracting information about the underlying synaptic volleys. Spike trains were obtained from computer simulations based on a threshold-crossing model of tonically firing MN, subjected to stimulation producing postsynaptic potentials (PSPs) of various parameters. These trains were analyzed as experimental results, using the output measures that were previously shown to be most effective for this purpose: peristimulus time histogram, raster plot and peristimulus time intervalgram. The analysis started from the effects of single excitatory and inhibitory PSPs (EPSPs and IPSPs). The conclusions drawn from this analysis allowed the explanation of the results of more complex synaptic volleys, i.e., combinations of EPSPs and IPSPs, and the formulation of directions for decoding the results of human neurophysiological experiments in which the responses of tonically firing MNs to nerve stimulation are analyzed.

Disentangling the functional consequences of the connectivity between optic-flow processing neurons

Typically, neurons in sensory areas are highly interconnected. Coupling two neurons can synchronize their activity and affect a variety of single-cell properties, such as their stimulus tuning, firing rate or gain. All of these factors must be considered to understand how two neurons should be coupled to optimally process stimuli. We quantified the functional effect of an interaction between two optic-flow processing neurons (Vi and H1) in the fly (Lucilia sericata). Using a generative model, we estimated a uni-directional coupling from H1 to Vi. Especially at a low signal-to-noise ratio (SNR), the coupling strongly improved the information about optic-flow in Vi. We identified two constraints confining the strength of the interaction. First, for weak couplings, Vi benefited from inputs by H1 without a concomitant shift of its stimulus tuning. Second, at both low and high SNR, the coupling strength lay in a range in which the information carried by single spikes is optimal.

Extending transfer entropy improves identification of effective connectivity in a spiking cortical network model

Transfer entropy (TE) is an information-theoretic measure which has received recent attention in neuroscience for its potential to identify effective connectivity between neurons. Calculating TE for large ensembles of spiking neurons is computationally intensive, and has caused most investigators to probe neural interactions at only a single time delay and at a message length of only a single time bin. This is problematic, as synaptic delays between cortical neurons, for example, range from one to tens of milliseconds. In addition, neurons produce bursts of spikes spanning multiple time bins. To address these issues, here we introduce a free software package that allows TE to be measured at multiple delays and message lengths. To assess performance, we applied these extensions of TE to a spiking cortical network model (Izhikevich, 2006) with known connectivity and a range of synaptic delays. For comparison, we also investigated single-delay TE, at a message length of one bin (D1TE), and cross-correlation (CC) methods. We found that D1TE could identify 36% of true connections when evaluated at a false positive rate of 1%. For extended versions of TE, this dramatically improved to 73% of true connections. In addition, the connections correctly identified by extended versions of TE accounted for 85% of the total synaptic weight in the network. Cross correlation methods generally performed more poorly than extended TE, but were useful when data length was short. A computational performance analysis demonstrated that the algorithm for extended TE, when used on currently available desktop computers, could extract effective connectivity from 1 hr recordings containing 200 neurons in ∼5 min. We conclude that extending TE to multiple delays and message lengths improves its ability to assess effective connectivity between spiking neurons. These extensions to TE soon could become practical tools for experimentalists who record hundreds of spiking neurons.

Frequency-dependent tuning of the human motor system induced by transcranial oscillatory potentials

Different corticothalamic brain modules intrinsically oscillate at a "natural frequency" in a topographically organized manner. In "quiescent" human sensorimotor regions, the main detectable oscillatory activity peaks at ∼20 Hz, and partly contributes to determine the state of corticospinal excitability. Here, we showed that the transcranial application of an imperceptible, short-lasting (90 s) electric field oscillating at a physiological range increases corticospinal excitability online, with well defined frequency dependence and regional specificity. Indeed, the size of motor evoked potentials (MEPs) induced by navigated single-pulse TMS over the motor cortex significantly increased only during the local application of transcranial alternating current stimulation (tACS) at 20 Hz (β range). Other tACS frequencies (5, 10, and 40 Hz) applied on the motor cortex did not impact MEPs' size. Moreover, tACS applied on a control site (parietal cortex) and on a peripheral site (ulnar nerve) also failed to modulate MEPs. These results help clarifying the functional significance of the 20 Hz idling β rhythm of sensorimotor regions and suggest potential clinical applications of this approach.

Central chemoreceptor modulation of breathing via multipath tuning in medullary ventrolateral respiratory column circuits

Ventrolateral respiratory column (VRC) circuits that modulate breathing in response to changes in central chemoreceptor drive are incompletely understood. We employed multielectrode arrays and spike train correlation methods to test predictions of the hypothesis that pre-Bötzinger complex (pre-BötC) and retrotrapezoid nucleus/parafacial (RTN-pF) circuits cooperate in chemoreceptor-evoked tuning of ventral respiratory group (VRG) inspiratory neurons. Central chemoreceptors were selectively stimulated by injections of CO(2)-saturated saline into the vertebral artery in seven decerebrate, vagotomized, neuromuscularly blocked, and artificially ventilated cats. Among sampled neurons in the Bötzinger complex (BötC)-to-VRG region, 70% (161 of 231) had a significant change in firing rate after chemoreceptor stimulation, as did 70% (101 of 144) of the RTN-pF neurons. Other responsive neurons (24 BötC-VRG; 11 RTN-pF) had a change in the depth of respiratory modulation without a significant change in average firing rate. Seventy BötC-VRG chemoresponsive neurons triggered 189 offset-feature correlograms (96 peaks; 93 troughs) with at least one responsive BötC-VRG cell. Functional input from at least one RTN-pF cell could be inferred for 45 BötC-VRG neurons (19%). Eleven RTN-pF cells were correlated with more than one BötC-VRG target neuron, providing evidence for divergent connectivity. Thirty-seven RTN-pF neurons, 24 of which were chemoresponsive, were correlated with at least one chemoresponsive BötC-VRG neuron. Correlation linkage maps and spike-triggered averages of phrenic nerve signals suggest transmission of chemoreceptor drive via a multipath network architecture: RTN-pF modulation of pre-BötC-VRG rostral-to-caudal excitatory inspiratory neuron chains is tuned by feedforward and recurrent inhibition from other inspiratory neurons and from "tonic" expiratory neurons.

Cortical state and attention

The brain continuously adapts its processing machinery to behavioural demands. To achieve this, it rapidly modulates the operating mode of cortical circuits, controlling the way that information is transformed and routed. This article will focus on two experimental approaches by which the control of cortical information processing has been investigated: the study of state-dependent cortical processing in rodents and attention in the primate visual system. Both processes involve a modulation of low-frequency activity fluctuations and spiking correlation, and are mediated by common receptor systems. We suggest that selective attention involves processes that are similar to state change, and that operate at a local columnar level to enhance the representation of otherwise non-salient features while suppressing internally generated activity patterns.

Acute in vivo nicotine administration enhances synchrony among dopamine neurons

Altered functional interactions among midbrain dopamine (DA) neurons contribute to the reinforcing properties of environmental stimuli and addictive drugs. To examine correlations among DA neurons, acute nicotine was administrated to rats via an intraperitoneal catheter and unit activity was measured using multi-tetrode in vivo recordings. Nicotine administration enhanced the correlated activity of simultaneously recorded DA neurons from the ventral tegmental area (VTA). The strength of the correlations between DA neuron pairs, as measured by cross covariance among two spike trains, showed dynamic changes over time. Nicotine produced a gradual rise in firing rate and burst activity that reached a stable plateau approximately 20 min after the intraperitoneal nicotine infusion. Shortly after that time the cross correlations measured using 5-ms bins increased significantly above baseline. In addition, nicotine increased the firing rates of DA neurons in the posterior VTA more than in the anterior VTA. Unlike nicotine, eticlopride administration also boosted DA neuron firing activity but did not enhance synchronization, indicating that the cross correlations induced by nicotine were not due to a non-specific increase in firing rate. The overall results show that nicotine induces nearly synchronous firing by a subset of DA neurons, and those changes in correlative firing will enhance the DA signal that contributes to nicotine-induced behavioral reinforcement.

Does the nervous system depend on kinesthetic information to control natural limb movements?

This target article draws together two groups of experimental studies on the control of human movement through peripheral feedback and centrally generated signals of motor commands. First, during natural movement, feedback from muscle, joint, and cutaneous afferents changes; in human subjects these changes have reflex and kinesthetic consequences. Recent psychophysical and microneurographic evidence suggests that joint and even cutaneous afferents may have a proprioceptive role. Second, the role of centrally generated motor commands in the control of normal movements and movements following acute and chronic deafferentation is reviewed. There is increasing evidence that subjects can perceive their motor commands under various conditions, but that this is inadequate for normal movement; deficits in motor performance arise when the reliance on proprioceptive feedback is abolished either experimentally or because of pathology. During natural movement, the CNS appears to have access to functionally useful input from a range of peripheral receptors as well as from internally generated command signals. The unanswered questions that remain suggest a number of avenues for further research.

Implications of neural networks for how we think about brain function

Engineers use neural networks to control systems too complex for conventional engineering solutions. To examine the behavior of individual hidden units would defeat the purpose of this approach because it would be largely uninterpretable. Yet neurophysiologists spend their careers doing just that! Hidden units contain bits and scraps of signals that yield only arcane hints about network function and no information about how its individual units process signals. Most literature on single-unit recordings attests to this grim fact. On the other hand, knowing a system's function and describing it with elegant mathematics tell one very little about what to expect of interneuronal behavior. Examples of simple networks based on neurophysiology are taken from the oculomotor literature to suggest how single-unit interpretability might decrease with increasing task complexity. It is argued that trying to explain how any real neural network works on a cell-by-cell, reductionist basis is futile and we may have to be content with trying to understand the brain at higher levels of organization.

Submillisecond firing synchrony between different subtypes of cortical interneurons connected chemically but not electrically

Synchronous firing is commonly observed in the brain, but its underlying mechanisms and neurobiological meaning remain debated. Most commonly, synchrony is attributed either to electrical coupling by gap junctions or to shared excitatory inputs. In the cerebral cortex and hippocampus, fast-spiking (FS) or somatostatin-containing (SOM) inhibitory interneurons are electrically coupled to same-type neighbors, and each subtype-specific network tends to fire in synchrony. Electrical coupling across subtypes is weak or absent, but SOM-FS and FS-FS pairs are often connected by inhibitory synapses. Theoretical studies suggest that purely inhibitory coupling can also promote synchrony; however, this has not been confirmed experimentally. We recorded from 74 pairs of electrically noncoupled layer 4 interneurons in mouse somatosensory cortex in vitro, and found that tonically depolarized FS-FS and SOM-FS pairs connected by unidirectional or bidirectional inhibitory synapses often fired within 1 ms of each other. Using a novel, jitter-based measure of synchrony, we found that synchrony correlated with inhibitory coupling strength. Importantly, synchrony was resistant to ionotropic glutamate receptors antagonists but was strongly reduced when GABA(A) receptors were blocked, confirming that in our experimental system IPSPs were both necessary and sufficient for synchrony. Submillisecond firing lags emerged in a computer simulation of pairs of spiking neurons, in which the only assumed interaction between neurons was by inhibitory synapses. We conclude that cortical interneurons are capable of synchronizing both within and across subtypes, and that submillisecond coordination of firing can arise by mutual synaptic inhibition alone, with neither shared inputs nor electrical coupling.

Ventrolateral medullary functional connectivity and the respiratory and central chemoreceptor-evoked modulation of retrotrapezoid-parafacial neurons

The medullary ventral respiratory column (VRC) of neurons is essential for respiratory motor pattern generation; however, the functional connections among these cells are not well understood. A rostral extension of the VRC, including the retrotrapezoid nucleus/parafacial region (RTN-pF), contains neurons responsive to local perturbations of CO(2)/pH. We addressed the hypothesis that both local RTN-pF interactions and functional connections from more caudal VRC compartments--extending from the Bötzinger and pre-Bötzinger complexes to the ventral respiratory group (Böt-VRG)--influence the respiratory modulation of RTN-pF neurons and their responses to central chemoreceptor and baroreflex activation. Spike trains from 294 RTN-pF and 490 Böt-VRG neurons were monitored with multielectrode arrays along with phrenic nerve activity in 14 decerebrate, vagotomized cats. Overall, 214 RTN-pF and 398 Böt-VRG neurons were respiratory modulated; 124 and 95, respectively, were cardiac modulated. Subsets of these neurons were tested with sequential, selective, transient stimulation of central chemoreceptors and arterial baroreceptors; each cell's response was evaluated and categorized according to the change in firing rate (if any) following the stimulus. Cross-correlation analysis was applied to 2,884 RTN-pF↔RTN-pF and 8,490 Böt-VRG↔RTN-pF neuron pairs. In total, 174 RTN-pF neurons (59.5%) had significant features in short-time scale correlations with other RTN-pF neurons. Of these, 49 neurons triggered cross-correlograms with offset peaks or troughs (n = 99) indicative of paucisynaptic excitation or inhibition of the target. Forty-nine Böt-VRG neurons (10.0%) were triggers in 74 Böt-VRG→RTN-pF correlograms with offset features, suggesting that Böt-VRG trigger neurons influence RTN-pF target neurons. The results support the hypothesis that local RTN-pF neuron interactions and inputs from Böt-VRG neurons jointly contribute to respiratory modulation of RTN-pF neuronal discharge patterns and promotion or limitation of their responses to central chemoreceptor and baroreceptor stimulation.

Assessment of across-muscle coherence using multi-unit vs. single-unit recordings

Coherence between electromyographic (EMG) signals has been used to identify correlated neural inputs to motor units (MUs) innervating different muscles. Simulations using a motor-unit model (Fuglevand et al. 1992) were performed to determine the ability of coherence between two multi-unit EMGs (mEMG) to detect correlated MU activity and the range of correlation strengths in which mEMG coherence can be usefully employed. Coherence between motor-unit and mEMG activities in two muscles was determined as we varied the strength of a 30-Hz periodic common input, the number of correlated MU pairs and variability of MU discharge relative to the common input. Pooled and mEMG coherence amplitudes positively and negatively accelerated, respectively, toward the strongest and most widespread correlating inputs. Furthermore, the relation between pooled and mEMG coherence was also nonlinear and was essentially the same whether correlation strength varied by changing common input strength or its distribution. However, the most important finding is that while the mEMG coherence saturates at the strongest common input strengths, this occurs at common input strengths greater than found in most physiological studies. Thus, we conclude that mEMG coherence would be a useful measure in many experimental conditions and our simulation results suggest further guidelines for using and interpreting coherence between mEMG signals.

Triphasic dynamics of stimulus-dependent information flow between single neurons in macaque inferior temporal cortex

The functional connectivity between cortical neurons is not static and is known to exhibit contextual modulations in terms of the coupling strength. Here we hypothesized that the information flow in a cortical local circuit exhibits complex forward-and-back dynamics, and conducted Granger causality analysis between the neuronal spike trains that were simultaneously recorded from macaque inferior temporal (IT) cortex while the animals performed a visual object discrimination task. Spikes from neuron pairs with a displaced peak on the cross-correlogram (CCG) showed Granger causality in the gamma-frequency range (30-80 Hz) with the dominance in the direction consistent with the CCG peak (forward direction). Although, in a classical view, the displaced CCG peak has been interpreted as an indicative of a pauci-synaptic serial linkage, temporal dynamics of the gamma Granger causality after stimulus onset exhibited a more complex triphasic pattern, with a transient forward component followed by a slowly developing backward component and subsequent reappearance of the forward component. These triphasic dynamics of causality were not explained by the firing rate dynamics and were not observed for cell pairs that exhibited a center peak on the CCG. Furthermore, temporal dynamics of Granger causality depended on the feature configuration within the presented object. Together, these results demonstrate that the classical view of functional connectivity could be expanded to incorporate more complex forward-and-back dynamics and also imply that multistage processing in the recognition of visual objects might be implemented by multiphasic dynamics of directional information flow between single neurons in a local circuit in the IT cortex.

Differential involvement of excitatory and inhibitory neurons of cat motor cortex in coincident spike activity related to behavioral context

To assess temporal associations in spike activity between pairs of neurons in the primary motor cortex (MI) related to different behaviors, we compared the incidence of coincident spiking activity of task-related (TR) and non-task-related (NTR) neurons during a skilled motor task and sitting quietly in adult cats (Felis domestica). Chronically implanted microwires were used to record spike activity of MI neurons in four animals (two male and two female) trained to perform a skilled reaching task or sit quietly. Neurons were identified as TR if spike activity was modulated during the task (and NTR if not). Based on spike characteristics, they were also classified as either regular-spiking (RS, putatively excitatory) or fast-spiking (FS, putatively inhibitory) neurons. Temporal associations in the activities of simultaneously recorded neurons were evaluated using shuffle-corrected cross-correlograms. Pairs of NTR and TR neurons showed associations in their firing patterns over wide areas of MI (representing forelimb and hindlimb movements) during quiet sitting, more commonly involving RS neurons. During skilled task performance, however, significantly coincident firing was seen almost exclusively between TR neurons in a smaller part of MI (representing forelimb movements), involving mainly FS neurons. The findings of this study show evidence for widespread interactions in MI when the animal sits quietly, which changes to a more specific and restricted pattern of interactions during task performance. Different populations of excitatory and inhibitory neurons appear to be synchronized during skilled movement and quiet sitting.

Functional properties of putative pyramidal neurons and inhibitory interneurons in the rat gustatory cortex

In order to address how taste information is modulated by inhibitory neuronal interactions in the rat gustatory cortex, we examined putative pyramidal neurons (PY units) and putative inhibitory interneurons (fast spiking [FS] units) that were distinguished by their spike waveforms and discharge rates. FS units were strikingly different from PY units in that the majority of FS units were N- or NH-best neurons and narrowly tuned to 1 or 2 tastant(s), whereas PY units were broadly tuned to plural tastants. Compared with PY units, FS units were characterized by a shorter response latency and/or a longer response duration. These results suggest that inhibitory modulations in the gustatory cortex are carried out in a taste specific and tonic manner. Sensitivity to tastant concentrations in PY units was similar to that in FS units for NaCl but higher for HCl. FS units may act to enhance concentration sensitivity in PY units by reducing PY units' response activity. High density of FS and PY units was observed in the superficial and middle layers (mainly layers III and IV). Responses in N-best FS units in these layers were significantly larger than those in the deep layers, suggesting the existence of layer-specific inhibitory interactions.

An uncorrelated state for the cortex?

The spike trains of nearby neurons in the sensory cortex are typically thought to be correlated due to mutual connections and common input. Multiple studies have measured these correlations and found them to be substantial (in the range of 10-40%). Two recent papers, however, reported that average correlations can be an order of magnitude smaller. Such low correlations could indicate an ‘uncorrelated state’ for the cortex, where cortical neurons act independently even in the face of strong common input.

Deciphering the contribution of intrinsic and synaptic currents to the effects of transient synaptic inputs on human motor unit discharge

The amplitude and time course of synaptic potentials in human motoneurons can be estimated in tonically discharging motor units by measuring stimulus-evoked changes in the rate and probability of motor unit action potentials. However, in spite of the fact that some of these techniques have been used for over 30 years, there is still no consensus on the best way to estimate the characteristics of synaptic potentials or on the accuracy of these estimates. In this review, we compare different techniques for estimating synaptic potentials from human motor unit discharge and also discuss relevant animal models in which estimated synaptic potentials can be compared to those directly measured from intracellular recordings. We also review the experimental evidence on how synaptic noise and intrinsic motoneuron properties influence their responses to synaptic inputs. Finally, we consider to what extent recordings of single motor unit discharge in humans can be used to distinguish the contribution of changes in synaptic inputs versus changes in intrinsic motoneuron properties to altered motoneuron responses following CNS injury.

Respiratory and Mayer wave-related discharge patterns of raphé and pontine neurons change with vagotomy

Previous models have attributed changes in respiratory modulation of pontine neurons after vagotomy to a loss of pulmonary stretch receptor "gating" of an efference copy of inspiratory drive. Recently, our group confirmed that pontine neurons change firing patterns and become more respiratory modulated after vagotomy, although average peak and mean firing rates of the sample did not increase (Dick et al., J Physiol 586: 4265-4282, 2008). Because raphé neurons are also elements of the brain stem respiratory network, we tested the hypotheses that after vagotomy raphé neurons have increased respiratory modulation and that alterations in their firing patterns are similar to those seen for pontine neurons during withheld lung inflation. Raphé and pontine neurons were recorded simultaneously before and after vagotomy in decerebrated cats. Before vagotomy, 14% of 95 raphé neurons had increased activity during single respiratory cycles prolonged by withholding lung inflation; 13% exhibited decreased activity. After vagotomy, the average index of respiratory modulation (eta(2)) increased (0.05 +/- 0.10 to 0.12 +/- 0.18 SD; Student's paired t-test, P < 0.01). Time series and frequency domain analyses identified pontine and raphé neuron firing rate modulations with a 0.1-Hz rhythm coherent with blood pressure Mayer waves. These "Mayer wave-related oscillations" (MWROs) were coupled with central respiratory drive and became synchronized with the central respiratory rhythm after vagotomy (7 of 10 animals). Cross-correlation analysis identified functional connectivity in 52 of 360 pairs of neurons with MWROs. Collectively, the results suggest that a distributed network participates in the generation of MWROs and in the coordination of respiratory and vasomotor rhythms.

Interaction of hippocampal and neocortical neurons in emotionally negative situations in active and passive rabbits

Cross-correlation histograms were used to compare the interaction of close-lying cells in the hippocampus (field CA1) and the parietal-temporal areas of the neocortex in active and passive rabbits during exposure to emotionally significant stimuli. Interaction of hippocampal neurons depended on the type of the behavioral response to the stimulus. The greatest changes from baseline were seen in active rabbits in orientational-investigative and active defensive reactions, while the greatest changes in passive animals were in freezing. In all states, cases of common inputs to hippocampal neurons were found more frequently in passive rabbits and excitatory links between neurons with short delays (up to 40 msec) were more frequent in active rabbits. Interaction of neocortical neurons, in contrast with hippocampal neurons, was less dependent on the type of behavioral response to the stimulus and the animal's behavioral strategy. These results provide evidence of individual-typological features in information processing in hippocampal field CA1 in active and passive animals in emotionally negative situations.

Cooperative and competitive interactions facilitate stereo computations in macaque primary visual cortex

Inferring depth from binocular disparities is a difficult problem for the visual system because local features in the left- and right-eye images must be matched correctly to solve this "stereo correspondence problem." Cortical architecture and computational studies suggest that lateral interactions among neurons could help resolve local uncertainty about disparity encoded in individual neurons by incorporating contextual constraints. We found that correlated activity among pairs of neurons in primary visual cortex depended both on disparity-tuning relationships and the stimuli displayed within the receptive fields of the neurons. Nearby pairs of neurons with distinct disparity tuning exhibited a decrease in spike correlation at competing disparities soon after response onset. Distant neuronal pairs of similar disparity tuning exhibited an increase in spike correlation at mutually preferred disparities. The observed correlated activity and response dynamics suggests that local competitive and distant cooperative interactions improve disparity tuning of individual neurons over time. Such interactions could represent a neural substrate for the principal constraints underlying cooperative stereo algorithms.

Spatial attention decorrelates intrinsic activity fluctuations in macaque area V4

Attention typically amplifies neuronal responses evoked by task-relevant stimuli while attenuating responses to task-irrelevant distracters. In this context, visual distracters constitute an external source of noise that is diminished to improve attended signal quality. Activity that is internal to the cortex itself, stimulus-independent ongoing correlated fluctuations in firing, might also act as task-irrelevant noise. To examine this, we recorded from area V4 of macaques performing an attention-demanding task. The firing of neurons to identically repeated stimuli was highly variable. Much of this variability originates from ongoing low-frequency (<5 Hz) fluctuations in rate correlated across the neuronal population. When attention is directed to a stimulus inside a neuron's receptive field, these correlated fluctuations in rate are reduced. This attention-dependent reduction of ongoing cortical activity improves the signal-to-noise ratio of pooled neural signals substantially more than attention-dependent increases in firing rate.

Patterns of spatio-temporal correlations in the neural activity of the cat motor cortex during trained forelimb movements

In order to study how neurons in the primary motor cortex (MI) are dynamically linked together during skilled movement, we recorded simultaneously from many cortical neurons in cats trained to perform a reaching and retrieval task using their forelimbs. Analysis of task-related spike activity in the MI of the hemisphere contralateral to the reaching forelimb (in identified forelimb or hindlimb representations) recorded through chronically implanted microwires, was followed by pairwise evaluation of temporally correlated activity in these neurons during task performance using shuffle corrected cross-correlograms. Over many months of recording, a variety of task-related modulations of neural activities were observed in individual efferent zones. Positively correlated activity (mainly narrow peaks at zero or short latencies) was seen during task performance frequently between neurons recorded within the forelimb representation of MI, rarely within the hindlimb area of MI, and never between forelimb and hindlimb areas. Correlated activity was frequently observed between neurons with different patterns of task-related activity or preferential activity during different task elements (reaching, feeding, etc.), and located in efferent zones with dissimilar representation as defined by intracortical microstimulation. The observed synchronization of action potentials among selected but functionally varied groups of MI neurons possibly reflects dynamic recruitment of network connections between efferent zones during skilled movement.

Central and peripheral chemoreceptors evoke distinct responses in simultaneously recorded neurons of the raphé-pontomedullary respiratory network

The brainstem network for generating and modulating the respiratory motor pattern includes neurons of the medullary ventrolateral respiratory column (VRC), dorsolateral pons (PRG) and raphé nuclei. Midline raphé neurons are proposed to be elements of a distributed brainstem system of central chemoreceptors, as well as modulators of central chemoreceptors at other sites, including the retrotrapezoid nucleus. Stimulation of the raphé system or peripheral chemoreceptors can induce a long-term facilitation of phrenic nerve activity; central chemoreceptor stimulation does not. The network mechanisms through which each class of chemoreceptor differentially influences breathing are poorly understood. Microelectrode arrays were used to monitor sets of spike trains from 114 PRG, 198 VRC and 166 midline neurons in six decerebrate vagotomized cats; 356 were recorded during sequential stimulation of both receptor classes via brief CO(2)-saturated saline injections in vertebral (central) and carotid arteries (peripheral). Seventy neurons responded to both stimuli. More neurons were responsive only to peripheral challenges than those responsive only to central chemoreceptor stimulation (PRG, 20 : 4; VRC, 41 : 10; midline, 25 : 13). Of 16 474 pairs of neurons evaluated for short-time scale correlations, similar percentages of reference neurons in each brain region had correlation features indicative of a specific interaction with at least one target neuron: PRG (59.6%), VRC (51.0%) and raphé nuclei (45.8%). The results suggest a brainstem network architecture with connectivity that shapes the respiratory motor pattern via overlapping circuits that modulate central and peripheral chemoreceptor-mediated influences on breathing.

How connectivity, background activity, and synaptic properties shape the cross-correlation between spike trains

Functional interactions between neurons in vivo are often quantified by cross-correlation functions (CCFs) between their spike trains. It is therefore essential to understand quantitatively how CCFs are shaped by different factors, such as connectivity, synaptic parameters, and background activity. Here, we study the CCF between two neurons using analytical calculations and numerical simulations. We quantify the role of synaptic parameters, such as peak conductance, decay time, and reversal potential, and analyze how various patterns of connectivity influence CCF shapes. In particular, we find that the symmetry of the CCF distinguishes in general, but not always, the case of shared inputs between two neurons from the case in which they are directly synaptically connected. We systematically examine the influence of background synaptic inputs from the surrounding network that set the baseline firing statistics of the neurons and modulate their response properties. We find that variations in the background noise modify the amplitude of the cross-correlation function as strongly as variations of synaptic strength. In particular, we show that the postsynaptic neuron spiking regularity has a pronounced influence on CCF amplitude. This suggests an efficient and flexible mechanism for modulating functional interactions.