Abstract: When recording the membrane potential, V, of a neuron it is desirable to be able to extract the synaptic input. Critically, the synaptic input is stochastic and nonreproducible so one is therefore often restricted to single-trial data. Here, we introduce means of estimating the inhibition and excitation and their confidence limits from single sweep trials. The estimates are based on the mean membrane potential, V, and the membrane time constant, Ï„. The time constant provides the total conductance (G = capacitance/Ï„) and is extracted from the autocorrelation of V. The synaptic conductances can then be inferred from V when approximating the neuron as a single compartment. We further employ a stochastic model to establish limits of confidence. The method is verified on models and experimental data, where the synaptic input is manipulated pharmacologically or estimated by an alternative method. The method gives best results if the synaptic input is large compared with other conductances, the intrinsic conductances have little or no time dependence or are comparably small, the ligand-gated kinetics is faster than the membrane time constant, and the majority of synaptic contacts are electrotonically close to soma (recording site). Although our data are in current clamp, the method also works in V-clamp recordings, with some minor adaptations. All custom made procedures are provided in Matlab.
Abstract: Neurons often receive massive concurrent bombardment of synaptic inhibition and excitation during functional network activity. This increases membrane conductance and causes fluctuations in membrane potential (V(m)) and spike timing. The conductance increase is commonly attributed to synaptic conductance, but also includes the intrinsic conductances recruited during network activity. These two sources of conductance have contrasting dynamic properties at sub-threshold membrane potentials. Synaptic transmitter gated conductance changes abruptly and briefly with each presynaptic action potential. If the spikes arrive at random times the changes in synaptic conductance are therefore stochastic and rapid during intense network activity. In comparison, sub-threshold intrinsic conductances vary smoothly in time. In the present study this discrepancy is investigated using two conductance-based models: a (1) compartment model and a (2) compartment with realistic slow intrinsic conductances. We examine the effects of varying the relative contributions of non-fluctuating intrinsic conductance with fluctuating concurrent inhibitory and excitatory synaptic conductance. For given levels of correlation in the synaptic input we find that the magnitude of the membrane fluctuations uniquely determines the relative contribution of synaptic and intrinsic conductance. We also quantify how V(m)-fluctuations vary with synaptic correlations for fixed ratios of synaptic and intrinsic conductance. Interestingly, the levels of V(m) -fluctuations and conductance observed experimentally during functional network activity leave little room for intrinsic conductance to contribute. Even without intrinsic conductances the variance in V(m) -fluctuations can only be explained by a high degree of correlated firing among presynaptic neurons.
Abstract: The red-eared turtle is an important animal model for investigating the neural activity in the spinal circuit that generates motor behavior. However, basic anatomical features, including the number of neurons in the spinal segments involved, are unknown. In the present study, we estimate the total number of neurons in segment D9 of the spinal cord in the red-eared turtle (Trachemys scripta elegans) using stereological cell counting methods. In transverse spinal cord sections stained with modified Giemsa, motoneurons (MNs), interneurons (INs), and non-neuronal cells were distinguished according to location and morphology. Each cell type was then counted separately using an optical disector with the cell nucleus as counting item. The number of cells in segment D9 was as follows (mean ± SE): MNs, 2049 ± 74; INs, 16,135 ± 316; non-neuronal cells, 47,504 ± 478 (n = 6). These results provide the first estimate of the total number of neurons in a spinal segment in a terrestrial vertebrate based on unbiased stereological methods and an upper bound on the number of neurons involved in segmental sensorimotor activity. These findings also form a crucial quantitative foundation for integrating electrophysiological data into mathematical circuit models.
Abstract: Stochastic leaky integrate-and-fire models are popular due to their simplicity and statistical tractability. They have been widely applied to gain understanding of the underlying mechanisms for spike timing in neurons, and have served as building blocks for more elaborate models. Especially the Ornstein-Uhlenbeck process is popular to describe the stochastic fluctuations in the membrane potential of a neuron, but also other models like the square-root model or models with a non-linear drift are sometimes applied. Data that can be described by such models have to be stationary and thus, the simple models can only be applied over short time windows. However, experimental data show varying time constants, state dependent noise, a graded firing threshold and time-inhomogeneous input. In the present study we build a jump diffusion model that incorporates these features, and introduce a firing mechanism with a state dependent intensity. In addition, we suggest statistical methods to estimate all unknown quantities and apply these to analyze turtle motoneuron membrane potentials. Finally, simulated and real data are compared and discussed. We find that a square-root diffusion describes the data much better than an Ornstein-Uhlenbeck process with constant diffusion coefficient. Further, the membrane time constant decreases with increasing depolarization, as expected from the increase in synaptic conductance. The network activity, which the neuron is exposed to, can be reasonably estimated to be a threshold version of the nerve output from the network. Moreover, the spiking characteristics are well described by a Poisson spike train with an intensity depending exponentially on the membrane potential.
Abstract: Tonic and phasic dopamine release is implicated in learning, motivation, and motor functions. However, the relationship between spike patterns in dopaminergic neurons, the extracellular concentration of dopamine, and activation of dopamine receptors remains unresolved. In the present study, we develop a computational model of dopamine signaling that give insight into the relationship between the dynamics of release and occupancy of D(1) and D(2) receptors. The model is derived from first principles using experimental data. It has no free parameters and offers unbiased estimation of the boundaries of dopaminergic volume transmission. Bursts primarily increase occupancy of D(1) receptors, whereas pauses translate into low occupancy of D(1) and D(2) receptors. Phasic firing patterns, composed of bursts and pauses, reduce the average D(2) receptor occupancy and increase average D(1) receptor occupancy compared with equivalent tonic firing. Receptor occupancy is crucially dependent on synchrony and the balance between tonic and phasic firing modes. Our results provide quantitative insight in the dynamics of volume transmission and complement experimental data obtained with electrophysiology, positron emission tomography, microdialysis, amperometry, and voltammetry.
Abstract: We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages of this metabolically costly organization are analyzed by comparing with synaptically less intense networks driven by the intrinsic response properties of the network neurons.
Abstract: Extracellular recordings from single units in the brain, for example the neocortex, have proven feasible in moving, awake rats, but have not yet been possible in the spinal cord. Single-unit activity during locomotor-like activity in reduced preparations from adult cats and rats have provided valuable insights for the development of hypotheses about the organization of functional networks in the spinal cord. However, since reduced preparations could result in spurious conclusions, it is crucial to test these hypotheses in animals that are awake and behaving. Furthermore, unresolved issues such as how muscle force precision is achieved by motoneurons as well as how spinal neurons are spatio-temporally correlated are better to investigate in the conscious and behaving animal. We have therefore developed procedures to implant arrays of extracellular recording electrodes in the lumbar spinal cord of the adult rat for long-term studies. In addition, we implanted pairs of electromyographic electrodes in the hindlimbs for the purpose of monitoring locomotion. With our technique, we obtained stable long-term recordings of spinal units, even during locomotion. We suggest this as a novel method for investigating motor pattern-generating circuitry in the spinal cord.
Abstract: In neurons, spike timing is determined by integration of synaptic potentials in delicate concert with intrinsic properties. Although the integration time is functionally crucial, it remains elusive during network activity. While mechanisms of rapid processing are well documented in sensory systems, agility in motor systems has received little attention. Here we analyze how intense synaptic activity affects integration time in spinal motoneurons during functional motor activity and report a 10-fold decrease. As a result, action potentials can only be predicted from the membrane potential within 10 ms of their occurrence and detected for less than 10 ms after their occurrence. Being shorter than the average inter-spike interval, the AHP has little effect on integration time and spike timing, which instead is entirely determined by fluctuations in membrane potential caused by the barrage of inhibitory and excitatory synaptic activity. By shortening the effective integration time, this intense synaptic input may serve to facilitate the generation of rapid changes in movements.
Abstract: Many limb movements are composed of alternating flexions and extensions. However, the underlying spinal network mechanisms remain poorly defined. Here, we show that the intensity of synaptic excitation and inhibition in limb motoneurons varies in phase rather than out of phase during rhythmic scratchlike network activity in the turtle. Inhibition and excitation peak with the total neuron conductance during the depolarizing waves of scratch episodes. Furthermore, spike activity is driven by depolarizing synaptic transients rather than pacemaker properties. These findings show that balanced excitation and inhibition and irregular firing are fundamental motifs in certain spinal network functions.
Abstract: The rat has a strong 6-9 Hz rhythm of electrical activity in the hippocampus, known as the theta rhythm. Exploratory whisking, i.e., the rhythmic movement of the rat's vibrissas to acquire tactile information, occurs within the same frequency range as the theta rhythm and provides a model system to examine the relationship between theta rhythm and active sensory movements. In particular, it has been postulated that these two rhythms are phase locked as a means to synchronize sensory and hippocampal processing. We tested this hypothesis in rats trained to whisk in air. Theta activity was measured via field electrodes in the hippocampus, and whisking was measured via the mystacial electromyogram. We calculated the spectral coherence between these two signals as a means to quantify the extent of phase locking. First, we found that the fraction of epochs with high coherence is not significantly greater than that expected by chance (seven of eight animals and as a population average). Second, we found that the trial-averaged coherence is low (coherence, < 0.1) and, as an average across all animals, statistically insignificant. We further asked whether the strength of the theta rhythm correlated with that of whisking, independent of the lack of cycle-by-cycle coherence. We observe that the correlation is weak and insignificant (six of eight animals and as a population average). We conclude that there is no relationship between the whisking and theta rhythms, at least when animals whisk in air.
Abstract: We tested the hypothesis that activation of nucleus basalis magnocellularis (NBM), which provides cholinergic input to cortex, facilitates motor control. Our measures of facilitation were changes in the direction and time-course of vibrissa movements that are elicited by microstimulation of vibrissa motor (M1) cortex. In particular, microstimulation led solely to a transient retraction of the vibrissae in the sessile animal but to a full motion sequence of protraction followed by retraction in the aroused animal. We observed that activation of NBM, as assayed by cortical desynchronization, induced a transition from microstimulation-evoked retraction to full sweep sequences. This dramatic change in the vibrissa response to microstimulation was blocked by systemic delivery of atropine and, in anesthetized animals, an analogous change was blocked by the topical administration of atropine to M1 cortex. We conclude that NBM significantly facilitates the ability of M1 cortex to control movements. Our results bear on the importance of cholinergic activation in schemes for neuroprosthetic control of movement.
Abstract: The rhythmic motor activity of the vibrissae that rodents use for the tactile localization of objects provides a model system for understanding patterned motor activity in mammals. The muscles that drive this whisking are only partially fixed relative to bony attachments and thus shift their position along with the movement. As a means to characterize the pattern of muscular dynamics during different patterns of whisking, we recorded electromyogram (EMG) activity from the muscles that propel individual follicles, as well as EMG activity from a muscle group that moves the mystacial pad. The dominant pattern of whisking in our behavioral paradigm, referred to as exploratory whisking, consisted of large amplitude sweeps in the frequency range of 5-15 Hz. The frequency remained remarkably constant within a bout of whisking but changed values between bouts. The extrinsic musculature, which shifts the surface of the pad backwards, was found to be activated in approximate antiphase to that of the intrinsic muscles, which rotate individual vibrissae forward. Thus retraction of the vibrissae was driven by a backward shift in the attachment point of the follicles to the mystacial pad. In a less frequent pattern of whisking, referred to as foveal whisking, the vibrissae are thrust forward and palpate objects with low-amplitude movements that are in the higher frequency range of 15-25 Hz. Protraction of the vibrissae remains driven by the intrinsic muscles, while retraction in this pattern is largely passive. Interestingly, a mechanical argument suggests that activation of the extrinsic muscles during foveal whisking is not expected to affect the angle of the vibrissae. As a means to establish if the phasic control of the intrinsic versus extrinsic muscles depended on sensory feedback, we characterized whisking before and after bilateral transections of the infraorbital branch of the trigeminal sensory nerve. The loss of sensory feedback had no net effect on the antiphase relation between activation of the intrinsic versus extrinsic muscles over the full frequency range for exploratory whisking. These data point to the existence of a dual-phase central pattern generator that drives the vibrissae.
Abstract: The rhythmic motor activity of the vibrissae that rodents use for the tactile localization of objects provides a model system for understanding patterned motor activity in mammals. Evidence suggests that neural circuitry in the brain stem provides rhythmic drive to the vibrissae. Yet multiple brain structures at higher levels of organization, including vibrissa primary motor cortex (M1), have direct projections to brain stem nuclei that are implicated in whisking. We thus asked whether output from M1 can control vibrissa movement on the approximately 10-Hz scale of the natural rhythmic movement of the vibrissae. Our assay of cortical control made use of periodic intracortical microstimulation (ICMS) to excite a region of vibrissa M1 cortex in awake, behaving animals and measurements of the stimulus-locked electromyogram (EMG) in both the intrinsic and extrinsic muscles that drive the vibrissae. We observed that ICMS evoked a prompt activation of the extrinsic muscles and a delayed and prolonged response in the intrinsic muscles. The relative timing and shape of these waveforms approximates the EMG waveforms seen during natural exploratory whisking. We further observed prompt activation of the intrinsic muscles, an occurrence not seen during exploratory whisking. Despite the latter difference in muscular activation, the motion of the vibrissae evoked by periodic ICMS strongly resembled the motion during natural, exploratory whisking. Interestingly, the extent of the movement was proportional to the level of arousal, as quantified by the amplitude of hippocampal activity in the theta frequency band. We interpret these data as demonstrating that M1 cortex can, in principle, initiate the full pattern of whisking on a cycle-by-cycle basis in aroused animals. Beyond issues of natural motor control, our result may bear on the design of algorithms for neuroprosthetic control of motor output.
Abstract: Electromyographic recordings from the mystacial pad of rats were used to assess the effect of unilateral vibrissa contact on the bilateral movement of the vibrissae. A first group of animals was trained to whisk freely in air and served to establish the baseline variability in bilateral symmetry. We observed that the electromyogram (EMG) activity across the two mystacial pads was rhythmic and synchronous to within 2 ms on a whisk-by-whisk basis; this value is small in comparison with the approximately 50 ms required for protraction during the whisk cycle. A second group of animals was trained to use their vibrissae to contact a sensor that was located on one side of the head. The average EMG activity across the two pads was synchronous at the time of vibrissa contact, albeit with higher variability than for the case of free whisking. In contrast, the average amplitude of the activity on the contact vs noncontact side of the face was transiently greater, by 25% or approximately 10 degrees, at the time of contact. These data show that the amplitude of the vibrissae on the two sides of the face can be controlled independently, while the timing of vibrissa movement is largely synchronous.
Abstract: We tested if coherent signaling between the sensory vibrissa areas of cerebellum and neocortex in rats was enhanced as they whisked in air. Whisking was accompanied by 5- to 15-Hz oscillations in the mystatial electromyogram, a measure of vibrissa position, and by 5- to 20-Hz oscillations in the differentially recorded local field potential (nablaLFP) within the vibrissa area of cerebellum and within the nablaLFP of primary sensory cortex. We observed that only 10% of the activity in either cerebellum or sensory neocortex was significantly phase-locked to rhythmic motion of the vibrissae; the extent of this modulation is in agreement with the results from previous single-unit measurements in sensory neocortex. In addition, we found that 40% of the activity in the vibrissa areas of cerebellum and neocortex was significantly coherent during periods of whisking. The relatively high level of coherence between these two brain areas, in comparison with their relatively low coherence with whisking per se, implies that the vibrissa areas of cerebellum and neocortex communicate in a manner that is incommensurate with whisking. To the extent that the vibrissa areas of cerebellum and neocortex communicate over the same frequency band as that used by whisking, these areas must multiplex electrical activity that is internal to the brain with activity that is that phase-locked to vibrissa sensory input.
Abstract: An accumulation of anatomical, behavioral, and electrophysiological evidence allows us to identify the neuronal circuitry that is involved with vibrissa-mediated sensation and the control of rhythmic vibrissa movement. Anatomical evidence points to a multiplicity of closed sensorimotor loops, while electrophysiological data delineate the flow of electrical signals in these pathways. These loops process sensory input from the vibrissae and send projections to direct vibrissa movement, starting at the level of the hindbrain and proceeding toward loops that involve multiple structures in the forebrain. The nature of the vibrissa-related electrical signals in behaving animals has been studied extensively at the level of neocortical loops. Two types of spike signal are observed that serve as a reference of vibrissa motion: a fast signal that correlates with the relative phase of the vibrissae within a whisk cycle and a slow signal that correlates with the amplitude, and possibly the set-point, of the vibrissae during a whisk. Both signals are observed in vibrissa primary sensory (S1) cortex, and in some cases they are sufficiently robust to allow vibrissa position to be accurately estimated from the spike train of a single neuron. Unlike the case for S1 cortex, only the slow signal has been observed in vibrissa primary motor (M1) cortex. The control capabilities of M1 cortex were estimated from experiments with anesthetized animals in which progressive areas along the vibrissa motor branch were microstimulated with rhythmically applied currents. The motion of the vibrissae followed stimulation of M1 cortex only for rates that were well below the frequency of rhythmic whisking; in contrast, the vibrissae followed stimulation of the facial nucleus, whose cells directly drive the vibrissae, for rates above that of whisking. In toto, the evidence implies that there is fast signaling from the facial nucleus, through the mystacial pad and the vibrissae and up through sensory cortex, but only slow signaling at the level of the motor cortex and down through the superior colliculus to the facial nucleus. The transformation from fast sensory signals to slow motor control is an unresolved issue. On the other hand, there is a candidate scheme to understand how the fast reference of vibrissa motion in the whisk cycle may be used to decode the angle of the vibrissae upon their contact with an object. We discuss a circuit in which servo mechanisms are used to determine the angle of contact relative to the preferred phase of the fast reference signals. Support for this scheme comes from results with anesthetized animals on the frequency and phase entrainment of intrinsic neuronal oscillators in S1 cortex. A prediction based on this scheme is that the output from a decoder circuit is maximal when the angle of contact differs from the preferred phase of a fast regerence signal. In contrast, for correlation-based schemes the output is maximal when the angle of contact equals the preferred phase.
