Effects of cholinergic modulation on responses of neocortical neurons to fluctuating input

Acetylcholine Mediates Dynamic Switching Between Information Coding Schemes in Neuronal Networks

Rate coding and phase coding are the two major coding modes seen in the brain. For these two modes, network dynamics must either have a wide distribution of frequencies for rate coding, or a narrow one to achieve stability in phase dynamics for phase coding. Acetylcholine (ACh) is a potent regulator of neural excitability. Acting through the muscarinic receptor, ACh reduces the magnitude of the potassium M-current, a hyperpolarizing current that builds up as neurons fire. The M-current contributes to several excitability features of neurons, becoming a major player in facilitating the transition between Type 1 (integrator) and Type 2 (resonator) excitability. In this paper we argue that this transition enables a dynamic switch between rate coding and phase coding as levels of ACh release change. When a network is in a high ACh state variations in synaptic inputs will lead to a wider distribution of firing rates across the network and this distribution will reflect the network structure or pattern of external input to the network. When ACh is low, network frequencies become narrowly distributed and the structure of a network or pattern of external inputs will be represented through phase relationships between firing neurons. This work provides insights into how modulation of neuronal features influences network dynamics and information processing across brain states.

A network model of behavioural performance in a rule learning task

Humans demonstrate differences in performance on cognitive rule learning tasks which could involve differences in properties of neural circuits. An example model is presented to show how gating of the spread of neural activity could underlie rule learning and the generalization of rules to previously unseen stimuli. This model uses the activity of gating units to regulate the pattern of connectivity between neurons responding to sensory input and subsequent gating units or output units. This model allows analysis of network parameters that could contribute to differences in cognitive rule learning. These network parameters include differences in the parameters of synaptic modification and presynaptic inhibition of synaptic transmission that could be regulated by neuromodulatory influences on neural circuits. Neuromodulatory receptors play an important role in cognitive function, as demonstrated by the fact that drugs that block cholinergic muscarinic receptors can cause cognitive impairments. In discussions of the links between neuromodulatory systems and biologically based traits, the issue of mechanisms through which these linkages are realized is often missing. This model demonstrates potential roles of neural circuit parameters regulated by acetylcholine in learning context-dependent rules, and demonstrates the potential contribution of variation in neural circuit properties and neuromodulatory function to individual differences in cognitive function.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'.

A computational model for how the fast afterhyperpolarization paradoxically increases gain in regularly firing neurons

The gain of a neuron, the number and frequency of action potentials triggered in response to a given amount of depolarizing injection, is an important behavior underlying a neuron's function. Variations in action potential waveform can influence neuronal discharges by the differential activation of voltage- and ion-gated channels long after the end of a spike. One component of the action potential waveform, the afterhyperpolarization (AHP), is generally considered an inhibitory mechanism for limiting firing rates. In dentate gyrus granule cells (DGCs) expressing fast-gated BK channels, large fast AHPs (fAHP) are paradoxically associated with increased gain. In this article, we describe a mechanism for this behavior using a computational model. Hyperpolarization provided by the fAHP enhances activation of a dendritic inward current (a T-type Ca²⁺ channel is suggested) that, in turn, boosts rebound depolarization at the soma. The model suggests that the fAHP may both reduce Ca²⁺ channel inactivation and, counterintuitively, enhance its activation. The magnitude of the rebound depolarization, in turn, determines the activation of a subsequent, slower inward current (a persistent Na⁺ current is suggested) limiting the interspike interval. Simulations also show that the effect of AHP on gain is also effective for physiologically relevant stimulation; varying AHP amplitude affects interspike interval across a range of "noisy" stimulus frequency and amplitudes. The mechanism proposed suggests that small fAHPs in DGCs may contribute to their limited excitability. NEW & NOTEWORTHY The afterhyperpolarization (AHP) is canonically viewed as a major factor underlying the refractory period, serving to limit neuronal firing rate. We recently reported that enhancing the amplitude of the fast AHP (fAHP) in a relatively slowly firing neuron (vs. fast spiking neurons) expressing fast-gated BK channels augments neuronal excitability. In this computational study, we present a novel, quantitative hypothesis for how varying the amplitude of the fAHP can, paradoxically, influence a subsequent spike tens of milliseconds later.

Memory recall and spike-frequency adaptation

The brain can reproduce memories from partial data; this ability is critical for memory recall. The process of memory recall has been studied using autoassociative networks such as the Hopfield model. This kind of model reliably converges to stored patterns that contain the memory. However, it is unclear how the behavior is controlled by the brain so that after convergence to one configuration, it can proceed with recognition of another one. In the Hopfield model, this happens only through unrealistic changes of an effective global temperature that destabilizes all stored configurations. Here we show that spike-frequency adaptation (SFA), a common mechanism affecting neuron activation in the brain, can provide state-dependent control of pattern retrieval. We demonstrate this in a Hopfield network modified to include SFA, and also in a model network of biophysical neurons. In both cases, SFA allows for selective stabilization of attractors with different basins of attraction, and also for temporal dynamics of attractor switching that is not possible in standard autoassociative schemes. The dynamics of our models give a plausible account of different sorts of memory retrieval.

Influence of developmental nicotine exposure on spike-timing precision and reliability in hypoglossal motoneurons

Smoothly graded muscle contractions depend in part on the precision and reliability of motoneuron action potential generation. Whether or not a motoneuron generates spikes precisely and reliably depends on both its intrinsic membrane properties and the nature of the synaptic input that it receives. Factors that perturb neuronal intrinsic properties and/or synaptic drive may compromise the temporal precision and the reliability of action potential generation. We have previously shown that developmental nicotine exposure (DNE) alters intrinsic properties and synaptic transmission in hypoglossal motoneurons (XIIMNs). Here we show that the effects of DNE also include alterations in spike-timing precision and reliability, and spike-frequency adaptation, in response to sinusoidal current injection. Current-clamp experiments in brainstem slices from neonatal rats show that DNE lowers the threshold for spike generation but increases the variability of spike-timing mechanisms. DNE is also associated with an increase in spike-frequency adaptation and reductions in both peak and steady-state firing rate in response to brief, square wave current injections. Taken together, our data indicate that DNE causes significant alterations in the input-output efficiency of XIIMNs. These alterations may play a role in the increased frequency of obstructive apneas and altered suckling strength and coordination observed in nicotine-exposed neonatal humans.

Gamma oscillations in the midbrain spatial attention network: linking circuits to function

Gamma-band (25-140Hz) oscillations are ubiquitous in mammalian forebrain structures involved in sensory processing, attention, learning and memory. The optic tectum (OT) is the central structure in a midbrain network that participates critically in controlling spatial attention. In this review, we summarize recent advances in characterizing a neural circuit in this midbrain network that generates large amplitude, space-specific, gamma oscillations in the avian OT, both in vivo and in vitro. We describe key physiological and pharmacological mechanisms that produce and regulate the structure of these oscillations. The extensive similarities between midbrain gamma oscillations in birds and those in the neocortex and hippocampus of mammals, offer important insights into the functional significance of a midbrain gamma oscillatory code.

Cholinergic modulation of neuronal excitability and recurrent excitation-inhibition in prefrontal cortex circuits: implications for gamma oscillations

Cholinergic neuromodulation in neocortical networks is required for gamma oscillatory activity associated with working memory and other cognitive processes. Importantly, the cholinergic agonist carbachol (CCh) induces gamma oscillations in vitro, via mechanisms that may be shared with in vivo gamma oscillations and that are consistent with the pyramidal interneuron network gamma (PING) model. In PING oscillations, pyramidal cells (PCs), driven by asynchronous excitatory input, recruit parvalbumin-positive fast-spiking interneurons (FSNs), which then synchronize the PCs via feedback inhibition. Whereas the PING model is favoured by current data, how cholinergic neuromodulation contributes to gamma oscillation production is poorly understood. We thus studied the effects of cholinergic modulation on circuit components of the PING model in mouse medial prefrontal cortex (mPFC) brain slices. CCh depolarized and evoked action potential firing in a fraction of PCs and increased excitatory synaptic input onto FSNs. In synaptically connected pairs, CCh reduced the short-term depression at FSN-PC and PC-FSN synapses, equalizing synaptic strength during repetitive presynaptic firing while simultaneously increasing the failure probability. Interestingly, when PCs or FSNs fired in response to gamma frequency oscillatory inputs, CCh increased the firing probability per cycle. Combined with the equalization of synaptic strength, an increase by CCh in the fraction of neurons recruited per oscillation cycle may support oscillatory synchrony of similar strength during relatively long oscillation episodes such as those observed during working memory tasks, suggesting a significant functional impact of cholinergic modulation of mPFC circuit components crucial for the PING model.

Modifying spiking precision in conductance-based neuronal models

The temporal precision of a neuron's spiking can be characterized by calculating its "jitter," defined as the standard deviation of the timing of individual spikes in response to repeated presentations of a stimulus. Sub-millisecond jitters have been measured for neurons in a variety of experimental systems and appear to be functionally important in some instances. We have investigated how modifying a neuron's maximal conductances affects jitter using the leaky integrate-and-fire (LIF) model and an eight-conductance Hodgkin-Huxley type (HH8) model. We observed that jitter can be largely understood in the LIF model in terms of the neuron's filtering properties. In the HH8 model we found the role of individual conductances in determining jitter to be complicated and dependent on the model's spiking properties. Distinct behaviors were observed for populations with slow (<11.5 Hz) and fast (>11.5 Hz) spike rates and appear to be related to differences in a particular channel's activity at times just before spiking occurs.

Inhibition of adult rat retinal ganglion cells by D1-type dopamine receptor activation

The spike output of neural pathways can be regulated by modulating output neuron excitability and/or their synaptic inputs. Dopaminergic interneurons synapse onto cells that route signals to mammalian retinal ganglion cells, but it is unknown whether dopamine can activate receptors in these ganglion cells and, if it does, how this affects their excitability. Here, we show D(1a) receptor-like immunoreactivity in ganglion cells identified in adult rats by retrogradely transported dextran, and that dopamine, D(1)-type receptor agonists, and cAMP analogs inhibit spiking in ganglion cells dissociated from adult rats. These ligands curtailed repetitive spiking during constant current injections and reduced the number and rate of rise of spikes elicited by fluctuating current injections without significantly altering the timing of the remaining spikes. Consistent with mediation by D(1)-type receptors, SCH-23390 [R-(+)-7-chloro-8-hydroxy-3-methyl-1-phenyl-2,3,4,5-tetrahydro-1H-3-benzazepine] reversed the effects of dopamine on spikes. Contrary to a recent report, spike inhibition by dopamine was not precluded by blocking I(h). Consistent with the reduced rate of spike rise, dopamine reduced voltage-gated Na(+) current (I(Na)) amplitude, and tetrodotoxin, at doses that reduced I(Na) as moderately as dopamine, also inhibited spiking. These results provide the first direct evidence that D(1)-type dopamine receptor activation can alter mammalian retinal ganglion cell excitability and demonstrate that dopamine can modulate spikes in these cells by a mechanism different from the presynaptic and postsynaptic means proposed by previous studies. To our knowledge, our results also provide the first evidence that dopamine receptor activation can reduce excitability without altering the temporal precision of spike firing.

M1 receptors mediate cholinergic modulation of excitability in neocortical pyramidal neurons

ACh release into the rodent prefrontal cortex is predictive of successful performance of cue detection tasks, yet the cellular mechanisms underlying cholinergic modulation of cortical function are not fully understood. Prolonged ("tonic") muscarinic ACh receptor (mAChR) activation increases the excitability of cortical pyramidal neurons, whereas transient ("phasic") mAChR activation generates inhibitory and/or excitatory responses, depending on neuron subtype. These cholinergic effects result from activation of "M1-like" mAChRs (M1, M3, and M5 receptors), but the specific receptor subtypes involved are not known. We recorded from cortical pyramidal neurons from wild-type mice and mice lacking M1, M3, and/or M5 receptors to determine the relative contribution of M1-like mAChRs to cholinergic signaling in the mouse prefrontal cortex. Wild-type neurons in layer 5 were excited by tonic mAChR stimulation, and had biphasic inhibitory followed by excitatory, responses to phasic ACh application. Pyramidal neurons in layer 2/3 were substantially less responsive to tonic and phasic cholinergic input. Cholinergic effects were largely absent in neurons from mice lacking M1 receptors, but most were robust in neurons lacking M3, M5, or both M3 and M5 receptors. The exception was tonic cholinergic suppression of the afterhyperpolarization in layer 5 neurons, which was absent in cells lacking either M1 or M3 receptors. Finally, we confirm a role for M1 receptors in behavior by demonstrating cue detection deficits in M1-lacking mice. Together, our results demonstrate that M1 receptors facilitate cue detection behaviors and are both necessary and sufficient for most direct effects of ACh on pyramidal neuron excitability.

Adaptation of firing rate and spike-timing precision in the avian cochlear nucleus

Adaptation is commonly defined as a decrease in response to a constant stimulus. In the auditory system such adaptation is seen at multiple levels. However, the first-order central neurons of the interaural time difference detection circuit encode information in the timing of spikes rather than the overall firing rate. We investigated adaptation during in vitro whole-cell recordings from chick nucleus magnocellularis neurons. Injection of noisy, depolarizing current caused an increase in firing rate and a decrease in spike time precision that developed over approximately 20 s. This adaptation depends on sustained depolarization, is independent of firing, and is eliminated by alpha-dendrotoxin (0.1 microM), implicating slow inactivation of low-threshold voltage-activated K+ channels as its mechanism. This process may alter both firing rate and spike-timing precision of phase-locked inputs to coincidence detector neurons in nucleus laminaris and thereby adjust the precision of sound localization.

Dopamine Increases the Gain of the Input-Output Response of Rat Prefrontal Pyramidal Neurons

Dopaminergic modulation of prefrontal cortical activity is known to affect cognitive functions like working memory. Little consensus on the role of dopamine modulation has been achieved, however, in part because quantities directly relating to the neuronal substrate of working memory are difficult to measure. Here we show that dopamine increases the gain of the frequency-current relationship of layer 5 pyramidal neurons in vitro in response to noisy input currents. The gain increase could be attributed to a reduction of the slow afterhyperpolarization by dopamine. Dopamine also increases neuronal excitability by shifting the input-output functions to lower inputs. The modulation of these response properties is mainly mediated by D1 receptors. Integrate-and-fire neurons were fitted to the experimentally recorded input-output functions and recurrently connected in a model network. The gain increase induced by dopamine application facilitated and stabilized persistent activity in this network. The results support the hypothesis that catecholamines increase the neuronal gain and suggest that dopamine improves working memory via gain modulation.

Intrinsic mechanisms for adaptive gain rescaling in barrel cortex

Barrel cortex neuronal responses adapt to changes in the statistics of complex whisker stimuli. This form of adaptation involves an adjustment in the input-output tuning functions of the neurons, such that their gain rescales depending on the range of the current stimulus distribution. Similar phenomena have been observed in other sensory systems, suggesting that adaptive adjustment of responses to ongoing stimulus statistics is an important principle of sensory function. In other systems, adaptation and gain rescaling can depend on intrinsic properties; however, in barrel cortex, whether intrinsic mechanisms can contribute to adaptation to stimulus statistics is unknown. To examine this, we performed whole-cell patch-clamp recordings of pyramidal cells in acute slices while injecting stochastic current stimuli. We induced changes in statistical context by switching across stimulus distributions. The firing rates of neurons adapted in response to changes in stimulus statistics. Adaptation depended on the form of the changes in stimulus distribution: in vivo-like adaptation occurred only for rectified stimuli that maintained neurons in a persistent state of net depolarization. Under these conditions, neurons rescaled the gain of their input-output functions according to the scale of the stimulus distribution, as observed in vivo. This stimulus-specific adaptation was caused by intrinsic properties and correlated strongly with the amplitude of calcium-dependent slow afterhyperpolarizations. Our results suggest that widely expressed intrinsic mechanisms participate in barrel cortex adaptation but that their recruitment is highly stimulus specific.

The impact of input fluctuations on the frequency-current relationships of layer 5 pyramidal neurons in the rat medial prefrontal cortex

The role of irregular cortical firing in neuronal computation is still debated, and it is unclear how signals carried by fluctuating synaptic potentials are decoded by downstream neurons. We examined in vitro frequency versus current (f-I) relationships of layer 5 (L5) pyramidal cells of the rat medial prefrontal cortex (mPFC) using fluctuating stimuli. Studies in the somatosensory cortex show that L5 neurons become insensitive to input fluctuations as input mean increases and that their f-I response becomes linear. In contrast, our results show that mPFC L5 pyramidal neurons retain an increased sensitivity to input fluctuations, whereas their sensitivity to the input mean diminishes to near zero. This implies that the discharge properties of L5 mPFC neurons are well suited to encode input fluctuations rather than input mean in their firing rates, with important consequences for information processing and stability of persistent activity at the network level.

Diversity of gain modulation by noise in neocortical neurons: regulation by the slow afterhyperpolarization conductance

Neuronal firing is known to depend on the variance of synaptic input as well as the mean input current. Several studies suggest that input variance, or "noise," has a divisive effect, reducing the slope or gain of the firing frequency-current (f-I) relationship. We measured the effects of current noise on f-I relationships in pyramidal neurons and fast-spiking (FS) interneurons in slices of rat sensorimotor cortex. In most pyramidal neurons, noise had a multiplicative effect on the steady-state f-I relationship, increasing gain. In contrast, noise reduced gain in FS interneurons. Gain enhancement in pyramidal neurons increased with stimulus duration and was correlated with the amplitude of the slow afterhyperpolarization (sAHP), a major mechanism of spike-frequency adaptation. The 5-HT2 receptor agonist alpha-methyl-5-HT reduced the sAHP and eliminated gain increases, whereas augmenting the sAHP conductance by spike-triggered dynamic-current clamp enhanced the gain increase. These results indicate that the effects of noise differ fundamentally between classes of neocortical neurons, depending on specific biophysical properties including the sAHP conductance. Thus, noise from background synaptic input may enhance network excitability by increasing gain in pyramidal neurons with large sAHPs and reducing gain in inhibitory FS interneurons.

Nonlinear interaction between shunting and adaptation controls a switch between integration and coincidence detection in pyramidal neurons

The membrane conductance of a pyramidal neuron in vivo is substantially increased by background synaptic input. Increased membrane conductance, or shunting, does not simply reduce neuronal excitability. Recordings from hippocampal pyramidal neurons using dynamic clamp revealed that adaptation caused complete cessation of spiking in the high conductance state, whereas repetitive spiking could persist despite adaptation in the low conductance state. This behavior was reproduced in a phase plane model and was explained by a shunting-induced increase in voltage threshold. The increase in threshold allows greater activation of the M current (I(M)) at subthreshold potentials and reduces the minimum adaptation required to stabilize the system; in contrast, activation of the afterhyperpolarization current is unaffected by the increase in threshold and therefore remains unable to stop repetitive spiking. The nonlinear interaction between shunting and I(M) has other important consequences. First, timing of spikes elicited by brief stimuli is more precise when background spikes elicited by sustained input are prohibited, as occurs exclusively with I(M)-mediated adaptation in the high conductance state. Second, activation of I(M) at subthreshold potentials, which is increased in the high conductance state, hyperpolarizes average membrane potential away from voltage threshold, allowing only large, rapid fluctuations to reach threshold and elicit spikes. These results suggest that the shift from a low to high conductance state in a pyramidal neuron is accompanied by a switch from encoding time-averaged input with firing rate to encoding transient inputs with precisely timed spikes, in effect, switching the operational mode from integration to coincidence detection.

Rate coding and spike-time variability in cortical neurons with two types of threshold dynamics

Neurons and dynamical models of spike generation display two different classes of threshold behavior: type 1 [firing frequency vs. current (f-I) relationship is continuous at threshold] and type 2 (discontinuous f-I). With steady current or conductance stimulation, regular-spiking (RS) pyramidal neurons and fast-spiking (FS) inhibitory interneurons in layer 2/3 of somatosensory cortex exhibit type 1 and type 2 threshold behaviors, respectively. We compared the postsynaptic firing variability of type 1 RS and type 2 FS cells, during naturalistic, fluctuating conductance input. In RS neurons, increasing the level of independently random, shunting inhibition caused a monotonic increase in spike reliability, whereas in FS interneurons, there was an optimum level of shunting inhibition for achieving the most reliable spike generation and the most precise spike-time encoding. This was observed over a range of different degrees of synchrony, or correlation, in the input. RS cells displayed a progressive rise in spike jitter during natural-like transient burst inputs, whereas for FS cells, jitter was mostly kept low. Furthermore, RS cells showed encoding of the input level in the spike shape, whereas FS cells did not. These differences between the two cell types are consistent with a role of RS neurons as rate-coding integrators, and a role of FS neurons as resonators controlling the coherence of synchronous firing.

Cholinergic modulation of response properties and orientation tuning of neurons in primary visual cortex of anaesthetized Marmoset monkeys

Cortical processing is strongly influenced by the actions of neuromodulators such as acetylcholine (ACh). Early studies in anaesthetized cats argued that acetylcholine can cause a sharpening of orientation tuning functions and an improvement of the signal-to-noise ratio (SNR) of neuronal responses in primary visual cortex (V1). Recent in vitro studies have demonstrated that acetylcholine reduces the efficacy of feedback and intracortical connections via the activation of muscarinic receptors, and increases the efficacy of feed-forward connections via the activation of nicotinic receptors. If orientation tuning is mediated or enhanced by intracortical connections, high levels of acetylcholine should diminish orientation tuning. Here we investigate the effects of acetylcholine on orientation tuning and neuronal responsiveness in anaesthetized marmoset monkeys. We found that acetylcholine caused a broadening of the orientation tuning in the majority of cells, while tuning functions became sharper in only a minority of cells. Moreover, acetylcholine generally facilitated neuronal responses, but neither improved signal-to-noise ratio, nor reduced trial-to-trial firing rate variance systematically. Acetylcholine did however, reduce variability of spike occurrences within spike trains. We discuss these findings in the context of dynamic control of feed-forward and lateral/feedback connectivity by acetylcholine.

Multiple time scales of temporal response in pyramidal and fast spiking cortical neurons

Neural dynamic processes correlated over several time scales are found in vivo, in stimulus-evoked as well as spontaneous activity, and are thought to affect the way sensory stimulation is processed. Despite their potential computational consequences, a systematic description of the presence of multiple time scales in single cortical neurons is lacking. In this study, we injected fast spiking and pyramidal (PYR) neurons in vitro with long-lasting episodes of step-like and noisy, in-vivo-like current. Several processes shaped the time course of the instantaneous spike frequency, which could be reduced to a small number (1-4) of phenomenological mechanisms, either reducing (adapting) or increasing (facilitating) the neuron's firing rate over time. The different adaptation/facilitation processes cover a wide range of time scales, ranging from initial adaptation (<10 ms, PYR neurons only), to fast adaptation (<300 ms), early facilitation (0.5-1 s, PYR only), and slow (or late) adaptation (order of seconds). These processes are characterized by broad distributions of their magnitudes and time constants across cells, showing that multiple time scales are at play in cortical neurons, even in response to stationary stimuli and in the presence of input fluctuations. These processes might be part of a cascade of processes responsible for the power-law behavior of adaptation observed in several preparations, and may have far-reaching computational consequences that have been recently described.

Synaptic bombardment modulates muscarinic effects in forelimb motor cortex

Neocortical neurons in vivo exist in an environment of continuous synaptic bombardment, receiving a complex barrage of excitatory and inhibitory inputs. This background activity (by depolarizing neurons, increasing membrane conductance, and introducing fluctuations) strongly alters many aspects of neuronal responsiveness. In this study, we asked how it shapes neuromodulation of postsynaptic responses. Specifically, we examined muscarinic modulation of forelimb motor cortex, a brain area in which cholinergic stimulation is known to be necessary for modifications during motor skill learning. Using a dynamic clamp system to inject simulated conductances into pyramidal neurons in motor cortical slices, we mimicked in vivo-like activity by introducing a random background of excitatory and inhibitory inputs. When muscarinic receptors were stimulated with the agonist oxotremorine-M, several previously described currents were modified, and excitability was increased. However, the presence of the background conductances strongly attenuated most muscarinic agonist effects, with the notable exception that sustained firing responses to trains of inputs were well preserved. This may be important for promoting plasticity in vivo.

Unraveling the attentional functions of cortical cholinergic inputs: interactions between signal-driven and cognitive modulation of signal detection

Neurophysiological studies demonstrated that increases in cholinergic transmission in sensory areas enhance the cortical processing of thalamic inputs. Cholinergic activity also suppresses the retrieval of internal associations, thereby further promoting sensory input processing. Behavioral studies documented the role of cortical cholinergic inputs in attentional functions and capacities by demonstrating, for example, that the integrity of the cortical cholinergic input system is necessary for attentional performance, and that the activity of cortical cholinergic inputs is selectively enhanced during attentional performance. This review aims at integrating the neurophysiological and behavioral evidence on the functions of cortical cholinergic inputs and hypothesizes that the cortical cholinergic input system generally acts to optimize the processing of signals in attention-demanding contexts. Such signals 'recruit', via activation of basal forebrain corticopetal cholinergic projections, the cortical attention systems and thereby amplify the processing of attention-demanding signals (termed 'signal-driven cholinergic modulation of detection'). The activity of corticopetal cholinergic projections is also modulated by direct prefrontal projections to the basal forebrain and, indirectly, to cholinergic terminals elsewhere in the cortex; thus, cortical cholinergic inputs are also involved in the mediation of top-down effects, such as the knowledge-based augmentation of detection (see Footnote 1) of signals and the filtering of irrelevant information (termed 'cognitive cholinergic modulation of detection'). Thus, depending on the quality of signals and task characteristics, cortical cholinergic activity reflects the combined effects of signal-driven and cognitive modulation of detection. This hypothesis begins to explain signal intensity or duration-dependent performance in attention tasks, the distinct effects of cortex-wide versus prefrontal cholinergic deafferentation on attention performance, and it generates specific predictions concerning cortical acetylcholine (ACh) release in attention task-performing animals. Finally, the consequences of abnormalities in the regulation of cortical cholinergic inputs for the manifestation of the symptoms of major neuropsychiatric disorders are conceptualized in terms of dysregulation in the signal-driven and cognitive cholinergic modulation of detection processes.

Phase-response curves give the responses of neurons to transient inputs

Neuronal firing is determined largely by incoming barrages of excitatory postsynaptic potentials (EPSPs), each of which produce a transient increase in firing probability. To measure the effects of weak transient inputs on firing probability of cortical neurons, we compute phase-response curves (PRCs). PRCs, whose shape can be related to the dynamics of spike generation, document the changes in timing of spikes caused by an EPSP in a repetitively firing neuron as a function of when it arrives in the interspike interval (ISI). The PRC can be exactly related to the poststimulus time histogram (PSTH) so that knowledge of one uniquely determines the other. Typically, PRCs have zero values at the start and end of the ISI, where EPSPs have minimal effects and a peak in the middle. Where the peak occurs depends in part on the firing properties of neurons. The PRC can have regions of positivity and negativity corresponding respectively to speeding up and slowing down the time of the next spike. A simple canonical model for spike generation is introduced that shows how both the background firing rate and the degree of postspike afterhyperpolarization contribute to the shape of the PRC and thus to the PSTH. PRCs in strongly adapting neurons are highly skewed to the right (indicating a higher change in probability when the EPSPs appear late in the ISI) and can have negative regions (indicating a decrease in firing probability) early in the ISI. The PRC becomes more skewed to the right as the firing rate decreases. Thus at low firing rates, the spikes are triggered preferentially by inputs that occur only during a small time interval late in the ISI. This implies that the neuron is more of a coincidence detector at low firing frequencies and more of an integrator at high frequencies. The steady-state theory is shown to also hold for slowly varying inputs.

Robustness of the noise-induced phase synchronization in a general class of limit cycle oscillators

We show that a wide class of uncoupled limit-cycle oscillators can be in-phase synchronized by common weak additive noise. An expression of the Lyapunov exponent is analytically derived to study the stability of the noise-driven synchronizing state. The result shows that such a synchronization can be achieved in a broad class of oscillators with little constraint on their intrinsic property. On the other hand, the leaky integrate-and-fire neuron oscillators do not belong to this class, generating intermittent phase slips according to a power law distribution of their intervals.

Predicting spike timings of current-injected neurons

Typical neurospiking models were examined on the ability to reproduce and predict the spike sequences of a biological neuron for a variety of fluctuating currents, using a fixed set of parameter values. The predicting accuracy was found to be particularly good for the Hodgkin-Huxley models augmented with the Ca(2+)-dependent potassium current generating slow afterhyper-polarization and/or the muscarine-sensitive potassium current. In the successful parameter determination method, the effective membrane time constant is estimated very short, typically about 5 ms. The biological neurons we examined were distinctly classified into two types according to the estimated percent contents of those ionic channels.

Noise-induced enhancement of fluctuation and spurious synchronization in uncoupled type-I intermittent chaotic systems

We study the dynamics of a pair of two uncoupled identical type-I intermittent chaotic systems driven by common random forcing. We first observe that the degree of the fluctuation of the local expansion rate of orbits to perturbations of a single system as a function of the noise intensity shows a convex curve and takes its maximum value at a certain noise intensity, whereas the Liapunov exponent itself monotonically increases in this range. Furthermore, it is numerically demonstrated that this nontrivial enhancement of fluctuation causes that two orbits with different initial conditions may synchronize each other after a finite interval of time. As pointed out by Pikovsky [Phys. Lett. A 165, 33 (1992)], since the Liapunov exponent of the present system is positive, the synchronization that we observed is a numerical artifact due to the finite precision of calculations. The spurious noise-induced synchronization in an ensemble of uncoupled type-I intermittent chaotic systems are numerically characterized and the relations between these features and the fluctuation properties of the local expansion rate are also discussed.

A computer model of neural processes observed in the cat motor cortex during performance of an operant movement

This report describes a computer model of a "column" in the cat motor cortex. The model includes two layers of two-segment pyramidal neurons with two groups of inhibitory interneurons in each layer, which selectively control the somatic and dendritic segments of the pyramidal cells. In this model, neurons include active sodium, calcium, and several types of potassium currents. Excitatory connections between neurons are of the AMPA and NMDA types, while collateral connections between neurons of the upper layer are mainly of the NMDA type; connections between neurons in the lower layer are of the AMPA type. All inhibitory connections are of the GABA(A) type. The model reproduces the main neuronal processes seen in the cat motor cortex during performance of an operant movement. Pyramidal neurons of the upper layer generate primary and secondary responses to external stimuli. As in real experiments, secondary NMDA-dependent responses appear when GABA(A) inhibition is weakened and disappear when stimulation is increased; these properties of secondary responses are only reproduced when NMDA receptors are located in the terminals of collateral connections. Using only rapid NMDA-independent connections, neurons in the lower layer generate a slow bell-shaped wave of excitation (a "motor command"), which is formed by sequential activation of neurons with dendritic trees of different sizes.

Spike-frequency adaptation in the inferior colliculus

We investigated spike-frequency adaptation of neurons sensitive to interaural phase disparities (IPDs) in the inferior colliculus (IC) of urethane-anesthetized guinea pigs using a stimulus paradigm designed to exclude the influence of adaptation below the level of binaural integration. The IPD-step stimulus consists of a binaural 3,000-ms tone, in which the first 1,000 ms is held at a neuron's least favorable ("worst") IPD, adapting out monaural components, before being stepped rapidly to a neuron's most favorable ("best") IPD for 300 ms. After some variable interval (1-1,000 ms), IPD is again stepped to the best IPD for 300 ms, before being returned to a neuron's worst IPD for the remainder of the stimulus. Exponential decay functions fitted to the response to best-IPD steps revealed an average adaptation time constant of 52.9 +/- 26.4 ms. Recovery from adaptation to best IPD steps showed an average time constant of 225.5 +/- 210.2 ms. Recovery time constants were not correlated with adaptation time constants. During the recovery period, adaptation to a 2nd best-IPD step followed similar kinetics to adaptation during the 1st best-IPD step. The mean adaptation time constant at stimulus onset (at worst IPD) was 34.8 +/- 19.7 ms, similar to the 38.4 +/- 22.1 ms recorded to contralateral stimulation alone. Individual time constants after stimulus onset were correlated with each other but not with time constants during the best-IPD step. We conclude that such binaurally derived measures of adaptation reflect processes that occur above the level of exclusively monaural pathways, and subsequent to the site of primary binaural interaction.

Oscillations in endogenous inputs to neurons affect excitability and signal processing

Synchrony and oscillations in neuronal firing play important roles in information processing in the mammalian brain. Here, we evaluate their role in controlling neuronal output in a well defined motor behavior, breathing, using an in vitro preparation from neonatal rat that generates respiratory-related motor output. In this preparation, phrenic motoneurons (PMNs) receive endogenous rhythmic inspiratory currents with prominent oscillations in the 20-50 Hz range. We recorded these inspiratory currents in individual PMNs and used them as test inputs for the same motoneuron (MN) during the normally silent expiratory periods. The impact of the oscillations on MN output was evaluated by filtering the currents before injection. Responses to unfiltered inspiratory currents were indistinguishable from voltage changes during spontaneous inspiratory periods. More than 90% of action potentials occurred within milliseconds [-2 to +4] of the oscillation peaks. The timing of action potentials was highly reproducible in response to unfiltered currents. Attenuation of the oscillations by low-pass filtering (<50 Hz) decreased the precision in action potential timing and significantly reduced the number of action potentials by approximately 35%. The adrenergic agonist phenylephrine increased instantaneous firing frequency in responses evoked by square-wave or low-pass filtered inspiratory currents but had no effect on firing frequency evoked by unfiltered currents. We conclude that oscillations control the precise timing of action potentials, help to maximize synaptic drive efficiency, and constrain MN firing frequencies to those optimal for muscle contraction.

Spike generating dynamics and the conditions for spike-time precision in cortical neurons

Temporal precision of spiking response in cortical neurons has been a subject of intense debate. Using a canonical model of spike generation, we explore the conditions for precise and reliable spike timing in the presence of Gaussian white noise. In agreement with previous results we find that constant stimuli lead to imprecise timing, while aperiodic stimuli yield precise spike timing. Under constant stimulus the neuron is a noise perturbed oscillator, the spike times follow renewal statistics and are imprecise. Under an aperiodic stimulus sequence, the neuron acts as a threshold element; the firing times are precisely determined by the dynamics of the stimulus. We further study the dependence of spike-time precision on the input stimulus frequency and find a non-linear tuning whose width can be related to the locking modes of the neuron. We conclude that viewing the neuron as a non-linear oscillator is the key for understanding spike-time precision.

Constructive effects of noise in homoclinic chaotic systems

Many chaotic oscillators have coherent phase dynamics but strong fluctuations in the amplitudes. At variance with such a behavior, homoclinic chaos is characterized by quite regular spikes but strong fluctuation in their time intervals due to the chaotic recurrence to a saddle point. We study influences of noise on homoclinic chaos. We demonstrate both numerically and experimentally on a CO2 laser various constructive effects of noise, including coherence resonance, noise-induced synchronization in uncoupled systems and noise-enhanced phase synchronization, deterministic resonance with respect to signal frequency, and stochastic resonance versus noise intensity in response to weak signals. The peculiar sensitivity of the system along the weak unstable manifold of the saddle point underlines the unified mechanism of these nontrivial and constructive noise-induced phenomena.

Noise-induced synchronization and coherence resonance of a Hodgkin-Huxley model of thermally sensitive neurons

We study nontrivial effects of noise on synchronization and coherence of a chaotic Hodgkin-Huxley model of thermally sensitive neurons. We demonstrate that identical neurons which are not coupled but subjected to a common fluctuating input (Gaussian noise) can achieve complete synchronization when the noise amplitude is larger than a threshold. For nonidentical neurons, noise can induce phase synchronization. Noise enhances synchronization of weakly coupled neurons. We also find that noise enhances the coherence of the spike trains. A saddle point embedded in the chaotic attractor is responsible for these nontrivial noise-induced effects. Relevance of our results to biological information processing is discussed.

Noise enhanced phase synchronization and coherence resonance in sets of chaotic oscillators with weak global coupling

The effect of noise on phase synchronization in small sets and larger populations of weakly coupled chaotic oscillators is explored. Both independent and correlated noise are found to enhance phase synchronization of two coupled chaotic oscillators below the synchronization threshold; this is in contrast to the behavior of two coupled periodic oscillators. This constructive effect of noise results from the interplay between noise and the locking features of unstable periodic orbits. We show that in a population of nonidentical chaotic oscillators, correlated noise enhances synchronization in the weak coupling region. The interplay between noise and weak coupling induces a collective motion in which the coherence is maximal at an optimal noise intensity. Both the noise-enhanced phase synchronization and the coherence resonance numerically observed in coupled chaotic Rössler oscillators are verified experimentally with an array of chaotic electrochemical oscillators.

Fine gating properties of channels responsible for persistent sodium current generation in entorhinal cortex neurons

The gating properties of channels responsible for the generation of persistent Na(+) current (I(NaP)) in entorhinal cortex layer II principal neurons were investigated by performing cell-attached, patch-clamp experiments in acutely isolated cells. Voltage-gated Na(+)-channel activity was routinely elicited by applying 500-ms depolarizing test pulses positive to -60 mV from a holding potential of -100 mV. The channel activity underlying I(NaP) consisted of prolonged and frequently delayed bursts during which repetitive openings were separated by short closings. The mean duration of openings within bursts was strongly voltage dependent, and increased by e times per every approximately 12 mV of depolarization. On the other hand, intraburst closed times showed no major voltage dependence. The mean duration of burst events was also relatively voltage insensitive. The analysis of burst-duration frequency distribution returned two major, relatively voltage-independent time constants of approximately 28 and approximately 190 ms. The probability of burst openings to occur also appeared largely voltage independent. Because of the above "persistent" Na(+)-channel properties, the voltage dependence of the conductance underlying whole-cell I(NaP) turned out to be largely the consequence of the pronounced voltage dependence of intraburst open times. On the other hand, some kinetic properties of the macroscopic I(NaP), and in particular the fast and intermediate I(NaP)-decay components observed during step depolarizations, were found to largely reflect mean burst duration of the underlying channel openings. A further I(NaP) decay process, namely slow inactivation, was paralleled instead by a progressive increase of interburst closed times during the application of long-lasting (i.e., 20 s) depolarizing pulses. In addition, long-lasting depolarizations also promoted a channel gating modality characterized by shorter burst durations than normally seen using 500-ms test pulses, with a predominant burst-duration time constant of approximately 5-6 ms. The above data, therefore, provide a detailed picture of the single-channel bases of I(NaP) voltage-dependent and kinetic properties in entorhinal cortex layer II neurons.

Muscarinic activation of a cation current and associated current noise in entorhinal-cortex layer-II neurons

The effects of muscarinic stimulation on the membrane potential and current of in situ rat entorhinal-cortex layer-II principal neurons were analyzed using the whole cell, patch-clamp technique. In current-clamp experiments, application of carbachol (CCh) induced a slowly developing, prolonged depolarization initially accompanied by a slight decrease or no significant change in input resistance. By contrast, in a later phase of the depolarization input resistance appeared consistently increased. To elucidate the ionic bases of these effects, voltage-clamp experiments were then carried out. In recordings performed in nearly physiological ionic conditions at the holding potential of -60 mV, CCh application promoted the slow development of an inward current deflection consistently associated with a prominent increase in current noise. Similarly to voltage responses to CCh, this inward-current induction was abolished by the muscarinic antagonist, atropine. Current-voltage relationships derived by applying ramp voltage protocols during the different phases of the CCh-induced inward-current deflection revealed the early induction of an inward current that manifested a linear current/voltage relationship in the subthreshold range and the longer-lasting block of an outward K(+) current. The latter current could be blocked by 1 mM extracellular Ba(2+), which allowed us to study the CCh-induced inward current (I(CCh)) in isolation. The extrapolated reversal potential of the isolated I(CCh) was approximately 0 mV and was not modified by complete substitution of intrapipette K(+) with Cs(+). Moreover, the extrapolated I(CCh) reversal shifted to approximately -20 mV on removal of 50% extracellular Na(+). These results are consistent with I(CCh) being a nonspecific cation current. Finally, noise analysis of I(CCh) returned an estimated conductance of the underlying channels of approximately 13.5 pS. We conclude that the depolarizing effect of muscarinic stimuli on entorhinal-cortex layer-II principal neurons depends on both the block of a K(+) conductance and the activation of a "noisy" nonspecific cation current. We suggest that the membrane current fluctuations brought about by I(CCh) channel noise may facilitate the "theta" oscillatory dynamics of these neurons and enhance firing reliability and synchronization.

Noradrenergic modulation of functional selectivity in the cat visual cortex: an in vivo extracellular and intracellular study

In vitro intracellular studies have shown that norepinephrine modulates cellular excitability and synaptic transmission in the cortex. Based on these effects, norepinephrine has been proposed to enhance the signal-to-noise ratio and to improve functional selectivity by potentiating strong synaptic responses and reducing weak ones. Here we have studied the functional effects of iontophoretic applications of norepinephrine during in vivo extracellular and intracellular recordings from neurons of the primary visual cortex of kittens and adult cats. Analysis of extracellular data concentrated on norepinephrine-induced changes in spontaneous and evoked activities, in signal-to-noise ratio, and in orientation and direction selectivity. Analysis of the intracellular data concentrated on actions of norepinephrine on spike firing accommodation, which has been shown to be reduced by norepinephrine in vitro, and on synaptic responses. Application of norepinephrine resulted in a depression of both spontaneous and evoked spiking activity. However, no systematic change in signal-to-noise ratio was observed. The suppressive effect of norepinephrine was exerted with no significant sharpening of direction or orientation selectivity tuning. The overall reduction in visual activity by norepinephrine affected the orientation tuning curves in a way compatible with a divisive effect, that is a normalization or gain control with no change in tuning width. Norepinephrine applied during intracellular recordings reduced the visually evoked depolarizing potentials whereas no change in the responsiveness of the cell to current-induced depolarizations was observed. In conditions of optimal visual stimulation which produced large depolarizations of several hundreds of milliseconds and sustained repetitive firing comparable to that obtained by direct current injection, we were unable to observe a facilitation of the evoked responses by norepinephrine as it would be expected from the well-documented increase in excitability induced by norepinephrine in vitro. In conclusion, from these results we suggest that norepinephrine released in the primary visual cortex primarily reduces the level of cortical activation by afferent signals, without affecting the cortical functional selectivity nor increasing the signal-to-noise ratio.

Spike frequency adaptation and neocortical rhythms

Spike-frequency adaptation in neocortical pyramidal neurons was examined using the whole cell patch-clamp technique and a phenomenological model of neuronal activity. Noisy current was injected to reproduce the irregular firing typically observed under in vivo conditions. The response was quantified by computing the poststimulus histogram (PSTH). To simulate the spiking activity of a pyramidal neuron, we considered an integrate-and-fire model to which an adaptation current was added. A simplified model for the mean firing rate of an adapting neuron under noisy conditions is also presented. The mean firing rate model provides a good fit to both experimental and simulation PSTHs and may therefore be used to study the response characteristics of adapting neurons to various input currents. The models enable identification of the relevant parameters of adaptation that determine the shape of the PSTH and allow the computation of the response to any change in injected current. The results suggest that spike frequency adaptation determines a preferred frequency of stimulation for which the phase delay of a neuron's activity relative to an oscillatory input is zero. Simulations show that the preferred frequency of single neurons dictates the frequency of emergent population rhythms in large networks of adapting neurons. Adaptation could therefore be one of the crucial factors in setting the frequency of population rhythms in the neocortex.

Noise-enhanced phase synchronization of chaotic oscillators

The effects of noise on phase synchronization (PS) of coupled chaotic oscillators are explored. In contrast to coupled periodic oscillators, noise is found to enhance phase synchronization significantly below the threshold of PS. This constructive role of noise has been verified experimentally with chaotic electrochemical oscillators of the electrodissolution of Ni in sulfuric acid solution.

High frequency oscillations in respiratory networks: functionally significant or phenomenological?

Inspiratory activities, whether recorded from medullary neurons, motoneurons or motor nerves, feature prominent oscillations in high (50-120 Hz) and medium (15-50 Hz) frequency ranges. These oscillations have been extensively characterized and are considered signatures of respiratory network activity. Their functional significance, however, if any, remains unknown. Here we review the literature describing the nature and origin of these oscillations as well as their modulation during development and by mechanoreceptive and chemoreceptive feedback, respiratory- and non-respiratory-related behaviors, temperature and anesthesia. We then consider the potential significance of these oscillations for respiratory network function by drawing on analyses of distributed motor and sensory networks of the cortex where current interest in oscillatory activity, and the synchronization of neural discharge that can result, is based on the increased efficacy with which synchronous inputs influence neuronal output, and the role that synchronous activity may play in information coding. We speculate that synchronized oscillations at the network level help coordinate activity in distributed rhythm and pattern generating systems and at the muscle level enhance force development. Data most strongly support that oscillatory synaptic inputs play an important role in controlling timing and pattern of action potential output.

Attractor reliability reveals deterministic structure in neuronal spike trains

When periodic current is injected into an integrate-and-fire model neuron, the voltage as a function of time converges from different initial conditions to an attractor that produces reproducible sequences of spikes. The attractor reliability is a measure of the stability of spike trains against intrinsic noise and is quantified here as the inverse of the number of distinct spike trains obtained in response to repeated presentations of the same stimulus. High reliability characterizes neurons that can support a spike-time code, unlike neurons with discharges forming a renewal process (such as a Poisson process). These two classes of responses cannot be distinguished using measures based on the spike-time histogram, but they can be identified by the attractor dynamics of spike trains, as shown here using a new method for calculating the attractor reliability. We applied these methods to spike trains obtained from current injection into cortical neurons recorded in vitro. These spike trains did not form a renewal process and had a higher reliability compared to renewal-like processes with the same spike-time histogram.

Noise-induced phase synchronization and synchronization transitions in chaotic oscillators

Whether common noise can induce complete synchronization in chaotic systems has been a topic of great relevance and long-standing controversy. We first clarify the mechanism of this phenomenon and show that the existence of a significant contraction region, where nearby trajectories converge, plays a decisive role. Second, we demonstrate that, more generally, common noise can induce phase synchronization in nonidentical chaotic systems. Such a noise-induced synchronization and synchronization transitions are of special significance for understanding neuron encoding in neurobiology.

Precision and reliability of periodically and quasiperiodically driven integrate-and-fire neurons

Neurons in the brain communicate via trains of all-or-none electric events known as spikes. How the brain encodes information using spikes-the neural code-remains elusive. Here the robustness against noise of stimulus-induced neural spike trains is studied in terms of attractors and bifurcations. The dynamics of model neurons converges after a transient onto an attractor yielding a reproducible sequence of spike times. At a bifurcation point the spike times on the attractor change discontinuously when a parameter is varied. Reliability, the stability of the attractor against noise, is reduced when the neuron operates close to a bifurcation point. We determined using analytical spike-time maps the attractor and bifurcation structure of an integrate-and-fire model neuron driven by a periodic or a quasiperiodic piecewise constant current and investigated the stability of attractors against noise. The integrate-and-fire model neuron became mode locked to the periodic current with a rational winding number p/q and produced p spikes per q cycles. There were q attractors. p:q mode-locking regions formed Arnold tongues. In the model, reliability was the highest during 1:1 mode locking when there was only one attractor, as was also observed in recent experiments. The quasiperiodically driven neuron mode locked to either one of the two drive periods, or to a linear combination of both of them. Mode-locking regions were organized in Arnold tongues and reliability was again highest when there was only one attractor. These results show that neuronal reliability in response to the rhythmic drive generated by synchronized networks of neurons is profoundly influenced by the location of the Arnold tongues in parameter space.

Information transfer in entrained cortical neurons

Cortical interneurons connected by gap junctions can provide a synchronized inhibitory drive that can entrain pyramidal cells. This was studied in a single-compartment Hodgkin-Huxley-type model neuron that was entrained by periodic inhibitory inputs with low jitter in the input spike times (i.e. high precision), and a variable but large number of presynaptic spikes on each cycle. During entrainment the Shannon entropy of the output spike times was reduced sharply compared with its value outside entrainment. Surprisingly, however, the information transfer as measured by the mutual information between the number of inhibitory inputs in a cycle and the phase lag of the subsequent output spike was significantly increased during entrainment. This increase was due to the reduced contribution of the internal correlations to the output variability. These theoretical predictions were supported by experimental recordings from the rat neocortex and hippocampus in vitro.

Characterization of reliability of spike timing in spinal interneurons during oscillating inputs

The spike timing in rhythmically active interneurons in the mammalian spinal locomotor network varies from cycle to cycle. We tested the contribution from passive membrane properties to this variable firing pattern, by measuring the reliability of spike timing, P, in interneurons in the isolated neonatal rat spinal cord, using intracellular injection of sinusoidal command currents of different frequencies (0.325-31.25 Hz). P is a measure of the precision of spike timing. In general, P was low at low frequencies and amplitudes (P = 0-0.6; 0-1.875 Hz; 0-30 pA), and high at high frequencies and amplitudes (P = 0.8-1; 3.125-31.25 Hz; 30-200 pA). The exact relationship between P and amplitude was difficult to describe because of the well-known low-pass properties of the membrane, which resulted in amplitude attenuation of high-frequency compared with low-frequency command currents. To formalize the analysis we used a leaky integrate and fire (LIF) model with a noise term added. The LIF model was able to reproduce the experimentally observed properties of P as well as the low-pass properties of the membrane. The LIF model enabled us to use the mathematical theory of nonlinear oscillators to analyze the relationship between amplitude, frequency, and P. This was done by systematically calculating the rotational number, N, defined as the number of spikes divided by the number of periods of the command current, for a large number of frequencies and amplitudes. These calculations led to a phase portrait based on the amplitude of the command current versus the frequency-containing areas [Arnold tongues (ATs)] with the same rotational number. The largest ATs in the phase portrait were those where N was a whole integer, and the largest areas in the ATs were seen for middle to high (>3 Hz) frequencies and middle to high amplitudes (50-120 pA). This corresponded to the amplitude- and frequency-evoked increase in P. The model predicted that P would be high when a cell responded with an integer and constant N. This prediction was confirmed by comparing N and P in real experiments. Fitting the result of the LIF model to the experimental data enabled us to estimate the standard deviation of the internal neuronal noise and to use these data to simulate the relationship between N and P in the model. This simulation demonstrated a good correspondence between the theoretical and experimental values. Our data demonstrate that interneurons can respond with a high reliability of spike timing, but only by combining fast and slow oscillations is it possible to obtain a high reliability of firing during rhythmic locomotor movements. Theoretical analysis of the rotation number provided new insights into the mechanism for obtaining reliable spike timing.

Contrast-dependent nonlinearities arise locally in a model of contrast-invariant orientation tuning

We study a recently proposed "correlation-based," push-pull model of the circuitry of layer 4 of cat visual cortex. This model was previously shown to explain the contrast-invariance of cortical orientation tuning. Here we show that it can simultaneously account for several contrast-dependent (c-d) "nonlinearities" in cortical responses. These include an advance with increasing contrast in the temporal phase of response to a sinusoidally modulated stimulus; a change in shape of the temporal frequency tuning curve, so that higher temporal frequencies may give little or no response at low contrast but reasonable responses at high contrast; and contrast saturation that occurs at lower contrasts in cortex than in the lateral geniculate nucleus (LGN). In the context of the model circuit, these properties arise from a mixture of nonlinear cellular and synaptic mechanisms: short-term synaptic depression, spike-rate adaptation, contrast-induced changes in cellular conductance, and the nonzero spike threshold. The former three mechanisms are sufficient to explain the experimentally observed increase in c-d phase advance in cortex relative to LGN. The c-d changes in temporal frequency tuning arise as a threshold effect: voltage modulations in response to higher-frequency inputs are only slightly above threshold at lower contrast, but become robustly suprathreshold at higher contrast. The other three nonlinear mechanisms also play a crucial role in this result, allowing contrast dependence of temporal frequency tuning to coexist with contrast-invariance of orientation tuning. Contrast saturation, and the observation that responses to stimuli of increasing temporal frequency saturate at increasingly high contrasts, can be induced both by the model's push-pull inhibition and by synaptic depression. Previous proposals explained these nonlinear response properties by assuming contrast-invariant orientation tuning as a starting point, and adding normalization by shunting inhibition derived equally from cells of all preferred orientations. The present proposal simultaneously explains both contrast-invariant orientation tuning and these contrast-dependent nonlinearities and requires only processing that is local in orientation, in agreement with intracellular measurements.

Modulation of hypoglossal motoneuron excitability by NK1 receptor activation in neonatal mice in vitro

1. The effects of substance P (SP), acting at NK1 receptors, on the excitability and inspiratory activity of hypoglossal (XII) motoneurons (MNs) were investigated using rhythmically active medullary-slice preparations from neonatal mice (postnatal day 0-3). 2. Local application of the NK1 agonist [SAR(9),Met (O(2))(11)]-SP (SP(NK1)) produced a dose-dependent, spantide- (a non-specific NK receptor antagonist) and GR82334-(an NK1 antagonist) sensitive increase in inspiratory burst amplitude recorded from XII nerves. 3. Under current clamp, SP(NK1) significantly depolarized XII MNs, potentiated repetitive firing responses to injected currents and produced a leftward shift in the firing frequency-current relationships without affecting slope. 4. Under voltage clamp, SP(NK1) evoked an inward current and increased input resistance, but had no effect on inspiratory synaptic currents. SP(NK1) currents persisted in the presence of TTX, were GR82334 sensitive, were reduced with hyperpolarization and reversed near the expected E(K). 5. Effects of the alpha(1)-noradrenergic receptor agonist phenylephrine (PE) on repetitive firing behaviour were virtually identical to those of SP(NK1). Moreover, SP(NK1) currents were completely occluded by PE, suggesting that common intracellular pathways mediate the actions of NK1 and alpha(1)-noradrenergic receptors. In spite of the similar actions of SP(NK1) and PE on XII MN responses to somally injected current, alpha(1)-noradrenergic receptor activation potentiated inspiratory synaptic currents and was more than twice as effective in potentiating XII nerve inspiratory burst amplitude. 6. GR82334 reduced XII nerve inspiratory burst amplitude and generated a small outward current in XII MNs. These observations, together with the first immunohistochemical evidence in the newborn for SP immunopositive terminals in the vicinity of SP(NK1)-sensitive inspiratory XII MNs, support the endogenous modulation of XII MN excitability by SP. 7. In contrast to phrenic MNs (Ptak et al. 2000), blocking NMDA receptors with AP5 had no effect on the modulation of XII nerve activity by SP(NK1). 8. In conclusion, SP(NK1) modulates XII motoneuron responses to inspiratory drive primarily through inhibition of a resting, postsynaptic K+ leak conductance. The results establish the functional significance of SP in controlling upper airway tone during early postnatal life and indicate differential modulation of motoneurons controlling airway and pump muscles by SP.

Corticothalamic resonance, states of vigilance and mentation

During various states of vigilance, brain oscillations are grouped together through reciprocal connections between the neocortex and thalamus. The coherent activity in corticothalamic networks, under the control of brainstem and forebrain modulatory systems, requires investigations in intact-brain animals. During behavioral states associated with brain disconnection from the external world, the large-scale synchronization of low-frequency oscillations is accompanied by the inhibition of synaptic transmission through thalamocortical neurons. Despite the coherent oscillatory activity, on the functional side there is dissociation between the thalamus and neocortex during slow-wave sleep. While dorsal thalamic neurons undergo inhibitory processes due to the prolonged spike-bursts of thalamic reticular neurons, the cortex displays, periodically, a rich spontaneous activity and preserves the capacity to process internally generated signals that dominate the state of sleep. In vivo experiments using simultaneous intracellular recordings from thalamic and cortical neurons show that short-term plasticity processes occur after prolonged and rhythmic spike-bursts fired by thalamic and cortical neurons during slow-wave sleep oscillations. This may serve to support resonant phenomena and reorganize corticothalamic circuitry, determine which synaptic modifications, formed during the waking state, are to be consolidated and generate a peculiar kind of dreaming mentation. In contrast to the long-range coherent oscillations that occur at low frequencies during slow-wave sleep, the sustained fast oscillations that characterize alert states are synchronized over restricted territories and are associated with discrete and differentiated patterns of conscious events.

Resonance effect for neural spike time reliability

The spike timing reliability of Aplysia motoneurons stimulated by repeated presentation of periodic or aperiodic input currents is investigated. Two properties of the input are varied, the frequency content and the relative amplitude of the fluctuations to the mean (expressed as the coefficient of variation: CV). It is shown that, for small relative amplitude fluctuations (CV approximately 0.05-0.15), the reliability of spike timing is enhanced if the input contains a resonant frequency equal to the firing rate of the neuron in response to the DC component of the input. This resonance-related enhancement in reliability decreases as the relative amplitude of the fluctuations increases (CV-->1). Similar results were obtained for a leaky integrate-and-fire neuronal model, suggesting that these effects are a general property of encoders that combine a threshold with a leaky integrator. These observations suggest that, when the magnitude of input fluctuations is small, changes in the power spectrum of the current fluctuations or in the spike discharge rate can have a pronounced effect on the ability of the neuron to encode a time-varying input with reliably timed spikes.