Analysis of Drosophila motor neuron activity patterns with neural analogs

A network of reciprocally inhibitory motorneurons has been previously postulated to account for the firing patterns of motor units during dipteran flight. Possible activity patterns of such a network were analyzed by means of appropriately interconnected neuromimes. This theoretical analysis showed that the proposed network can account for many aspects of dipteran motor unit activity patterns including firing in specific sequences, stability, and resetting of the firing pattern by antidromic spikes. In addition, the analysis showed that one aspect of physiological activity, motor unit phase locking, can not be explained simply on the basis of network properties alone; evidently specific membrane properties of the dipteran motor units also play an essential role in establishing the activity pattern.     

Neural Mechanisms Underlying Stop-and-Restart Difficulties: Involvement of the Motor and Perceptual Systems

The ability to suddenly stop a planned movement or a movement being performed and restart it after a short interval is an important mechanism that allows appropriate behavior in response to contextual or environmental changes. However, performing such stop-and-restart movements smoothly is difficult at times. We investigated performance (response time) of stop-and-restart movements using a go/stop/re-go task and found consistent stop-and-restart difficulties after short (∼100 ms) stop-to-restart intervals (SRSI), and an increased probability of difficulties after longer (>200 ms) SRSIs, suggesting that two different mechanisms underlie stop-and-restart difficulties. Next, we investigated motor evoked potentials (MEPs) in a moving muscle induced by transcranial magnetic stimulation during a go/stop/re-go task. In re-go trials with a short SRSI (100 ms), the MEP amplitude continued to decrease after the re-go-signal onset, indicating that stop-and-restart difficulties with short SRSIs might be associated with a neural mechanism in the human motor system, namely, stop-related suppression of corticomotor (CM) excitability. Finally, we recorded electroencephalogram (EEG) activity during a go/stop/re-go task and performed a single-trial-based EEG power and phase time-frequency analysis. Alpha-band EEG phase locking to re-go-signal, which was only observed in re-go trials with long SRSI (250 ms), weakened in the delayed re-go response trials. These EEG phase dynamics indicate an association between stop-and-restart difficulties with long SRSIs and a neural mechanism in the human perception system, namely, decreased probability of EEG phase locking to visual stimuli. In contrast, smooth stop-and-restart human movement can be achieved in re-go trials with sufficient SRSI (150–200 ms), because release of stop-related suppression and simultaneous counter-activation of CM excitability may occur as a single task without second re-go-signal perception. These results suggest that skilled motor behavior is subject to various constraints in not only motor, but also perceptual (and attentional), systems.     

Alteration of phase–phase coupling between theta and gamma rhythms in a depression-model of rats

Alterations in oscillatory brain activity are strongly correlated with cognitive performance in various physiological rhythms, especially the theta and gamma rhythms. In this study, we investigated the coupling relationship of neural activities between thalamus and medial prefrontal cortex (mPFC) by measuring the phase interactions between theta and gamma oscillations in a depression model of rats. The phase synchronization analysis showed that the phase locking at theta rhythm was weakened in depression. Furthermore, theta-gamma phase locking at n:m (1:6) ratio was found between thalamus and mPFC, while it was diminished in depression state. In addition, the analysis of coupling direction based on phase dynamics showed that the unidirectional influence from thalamus to mPFC was diminished in depression state only in theta rhythm, while it was partly recovered after the memantine treatment in a depression model of rats. The results suggest that the effects of depression on cognitive deficits are modulated via profound alterations in phase information transformation of theta rhythm and theta-gamma phase coupling.     

Information transmission in oscillatory neural activity

Periodic neural activity not locked to the stimulus or to motor responses is usually ignored. Here, we present new tools for modeling and quantifying the information transmission based on periodic neural activity that occurs with quasi-random phase relative to the stimulus. We propose a model to reproduce characteristic features of oscillatory spike trains, such as histograms of inter-spike intervals and phase locking of spikes to an oscillatory influence. The proposed model is based on an inhomogeneous Gamma process governed by a density function that is a product of the usual stimulus-dependent rate and a quasi-periodic function. Further, we present an analysis method generalizing the direct method (Rieke et al. in Spikes: exploring the neural code. MIT Press, Cambridge, 1999; Brenner et al. in Neural Comput 12(7):1531-1552, 2000) to assess the information content in such data. We demonstrate these tools on recordings from relay cells in the lateral geniculate nucleus of the cat.     

Phase-locked responses in the Limulus lateral eye. Theoretical and experimental investigation.

The 1:1 phase locking of the neural discharge to sinusoidally modulated stimuli was investigated both theoretically and experimentally. On the theoretical side, a neural encoder model, the self-inhibited leaky integrator, was considered, and the phase of the locked impulse was computed for each frequency in the locking range by imposing the condition that the "leaky integral" u(t) of the driving signal should reach the threshold for the first time one stimulus period after the preceding impulse. As u(t) can be a nonmonotonic function, this approach leads to results that sometimes differ from those reported in the literature. It turns out that the phase excursion is often much smaller than the values of about 180 degrees predicted from previous analysis. Moreover, our analysis shows a peculiar effect; the phase locking frequency range narrows when the input modulation depth increases. The theoretical predictions are then compared with phase-locked discharge patterns recorded from visual cells of the Limulus lateral eye, stimulated by sinusoidally modulated light or depolarizing current. The phases of the locked spikes at each of a number of modulation frequencies have been measured. The predictions offered by the model fit the experimental data, although there are some difficulties in determining the effective driving signal.     

Estimating the contribution of assembly activity to cortical dynamics from spike and population measures

The hypothesis that cortical networks employ the coordinated activity of groups of neurons, termed assemblies, to process information is debated. Results from multiple single-unit recordings are not conclusive because of the dramatic undersampling of the system. However, the local field potential (LFP) is a mesoscopic signal reflecting synchronized network activity. This raises the question whether the LFP can be employed to overcome the problem of undersampling. In a recent study in the motor cortex of the awake behaving monkey based on the locking of coincidences to the LFP we determined a lower bound for the fraction of spike coincidences originating from assembly activation. This quantity together with the locking of single spikes leads to a lower bound for the fraction of spikes originating from any assembly activity. Here we derive a statistical method to estimate the fraction of spike synchrony caused by assemblies—not its lower bound—from the spike data alone. A joint spike and LFP surrogate data model demonstrates consistency of results and the sensitivity of the method. Combining spike and LFP signals, we obtain an estimate of the fraction of spikes resulting from assemblies in the experimental data.     

Automatic classification of interference patterns in driven event series: application to single sympathetic neuron discharge forced by mechanical ventilation

This study proposes a method for the automatic classification of nonlinear interactions between a strictly periodical event series modelling the activity of an exogenous oscillator working at a fixed and well-known rate and an event series modelling the activity of a self-sustained oscillator forced by the exogenous one. The method is based on a combination of several well-known tools (probability density function of the cyclic relative phase, probability density function of the count of forced events per forcing cycle, conditional entropy of the cyclic relative phase sequence and a surrogate data approach). Classification is reached via a sequence of easily applicable decision rules, thus rendering classification virtually user-independent and fully reproducible. The method classifies four types of dynamics: full uncoupling, quasiperiodicity, phase locking and aperiodicity. In the case of phase locking, the coupling ratio (i.e. n:m) and the strength of the coupling are calculated. The method, validated on simulations of simple and complex phase-locking dynamics corrupted by different levels of noise, is applied to data derived from one anesthetized and artificially ventilated rat to classify the nonlinear interactions between mechanical ventilation and: (1) the discharges of two (contemporaneously recorded) single postganglionic sympathetic neurons innervating the caudal ventral artery in the tail and (2) arterial blood pressure. Under central apnea, the activity of the underlying sympathetic oscillators is perturbed by means of five different lung inflation rates (0.58, 0.64, 0.76, 0.95, 1.99 Hz). While ventilation and arterial pressure are fully uncoupled, ventilation is capable of phase locking sympathetic discharges, thus producing 40% of phase-locked patterns (one case of 2:5, 1:1, 3:2 and 2:2) and 40% of aperiodic dynamics. In the case of phase-locked patterns, the coupling strength is low, thus demonstrating that this pattern is sliding. Non-stationary interactions are observed in 20% of cases. The two discharges behave differently, suggesting the presence of a population of sympathetic oscillators working at different frequencies.     

Impact of adaptation currents on synchronization of coupled exponential integrate-and-fire neurons

The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF) neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency oscillations in local excitatory networks, but indicate that inhibition rather than excitation generates coherent rhythms at higher frequencies.     

Feeding-related motor patterns of the locust suboesophageal ganglion induced by pilocarpine and IBMX

The mandibular motor pattern induced by the phosphodiesterase inhibitor 3-isobutyl-1-methylxanthine (IBMX) in isolated locust suboesophageal ganglia (SOG) was investigated and compared with the motor pattern induced by pilocarpine in an already established preparation of the SOG. Motor patterns occurring after bath application of IBMX or pilocarpine were recorded extracellularly from suitable nerves of isolated SOG. For a quantitative evaluation of long (15 min) sequences of rhythmic neural activity containing several hundred cycles, spectral analysis of spike trains was applied. Using a set of characteristic parameters extracted from spectra computed for each individual preparation, quantitative comparisons of the rhythms induced by IBMX and pilocarpine were made. Significant differences in regularity, frequency of oscillation, and intra-burst frequency were found whereas the phase relationships of different motor pools were similar. Differences in the effect of the drugs on the activity recorded extracellularly from mandibular closer motoneurones were investigated further using intracellular recordings. Our findings imply that the IBMX-induced motor pattern is a suitable in vitro model of mandibular central motor control like the pilocarpine induced pattern. The better regularity is an advantageous feature for further experiments on central pattern generation. Information on second messengers involved in central pattern generation provided by the pharmacological profile of IBMX forms a basis for pharmacological and histological investigations on the mandibular central pattern generating network.     

The analysis of the unstable tibia fracture treatment applying internal stabilization method

The study included 51 patients with tibia fractures, who underwent percutaneous bone reposition and stabilization with unrimed tibial locking nail. The results obtained using this method were compared with those obtained by standard fracture treatment where flat and anatomic plates were applied (n = 64). In patients who had osteosynthetic material implanted percutaneously (using unrimed tibial locking nail) there was no incidence of post surgical osteitis or any pseudarthrosis. The healing callus of the fracture was of lesser quality and spindle shaped, suggesting that fracture stabilization using this method was less efficient. In patients with fractures stabilized by the open method using flat and anatomic plates (n = 64), we noticed 3.1% (n = 2) cases of osteitis and 4.7% (n = 3) cases of pseudarthrosis. Due to lesser incidence of postoperative osteitis, our method of choice in tibia fractures would be percutaneous stabilization with unrimed tibial locking nail. However, this treatment method has its disadvantages, too. Fracture callus is of lesser quality and it is spindle shaped. Furthermore, there are problems with adequate percutaneous reposition in some cases, as well as necessity for radiological checking.     

Analysis of point process signals applied to motor unit firing patterns: I. Superposition of independent spike trains

The aim of the present study was to examine whether statistical methods common for the analysis of point process signals could be applied to the electromyogram, in order to extract information concerning the physiological mechanisms involved. This was carried out on the assumption that the electromyogram can be treated as the superposition result of a number of point process signals, each representing the firing pattern of one motor unit. No correlated activity between the different spike trains was assumed at this stage. A digital model for the superposition of event sequences was constructed, assigning to the individual sequences a Gaussian interval distribution. The effects of varying the number of spike trains participating in the superposition process, and changing the mean rates of firing were explored. The statistical methods used in the analysis were serial correlation, event autocorrelation, and power spectrum studies. It has been found that serial correlograms of the superimposed processes may be helpful in detecting the number of spike trains involved in the superposition, whereas power spectrum studies are useful in determining the mean rates of firing of the individual sequences.     

Fluorescent protein-based detection of φC31 integrase activity in mammalian cells

The enzyme φC31 integrase from Streptomyces phage has been documented as functional in mammalian cells and, therefore, has the potential to be a powerful gene manipulation tool. However, the activity of this enzyme is cell-type dependent. The more active mutant forms of φC31 integrase are required. Therefore, a rapid and effective method should be developed to detect the intracellular activity of φC31 integrase. We devised in this study an integrase-inversion cassette that contains the enhanced green fluorescent protein (EGFP) gene and the reverse complementary DsRed gene, which are flanked by attB and reverse complementary attP. This cassette can be inverted by φC31 integrase, thereby altering the fluorescent protein expression. Thus, φC31 integrase activity can be qualitatively or quantitatively evaluated based on the detected fluorescence. Furthermore, this cassette-based method was applied to several cell types, demonstrating that it is an efficient and reliable tool for measuring φC31 integrase activity in mammalian cells.     

A simple model for phase locking of biological oscillators

Summary A mathematical model is presented for phase locking of a biological oscillator to a sinusoidal stimulus. Analytical, numerical and topological considerations are used to discuss the patterns of phase locking as a function of the amplitude of the sinusoidal stimulus and the relative frequencies of the oscillator and the sinusoidal stimulus. The sorts of experimental data which are needed to make comparisons between theory and experiment are discussed.     

Stimulus Phase Locking of Cortical Oscillation for Auditory Stream Segregation in Rats

The phase of cortical oscillations contains rich information and is valuable for encoding sound stimuli. Here we hypothesized that oscillatory phase modulation, instead of amplitude modulation, is a neural correlate of auditory streaming. Our behavioral evaluation provided compelling evidences for the first time that rats are able to organize auditory stream. Local field potentials (LFPs) were investigated in the cortical layer IV or deeper in the primary auditory cortex of anesthetized rats. In response to ABA- sequences with different inter-tone intervals and frequency differences, neurometric functions were characterized with phase locking as well as the band-specific amplitude evoked by test tones. Our results demonstrated that under large frequency differences and short inter-tone intervals, the neurometric function based on stimulus phase locking in higher frequency bands, particularly the gamma band, could better describe van Noorden’s perceptual boundary than the LFP amplitude. Furthermore, the gamma-band neurometric function showed a build-up-like effect within around 3 seconds from sequence onset. These findings suggest that phase locking and amplitude have different roles in neural computation, and support our hypothesis that temporal modulation of cortical oscillations should be considered to be neurophysiological mechanisms of auditory streaming, in addition to forward suppression, tonotopic separation, and multi-second adaptation.     

Characterization of Bacillus subtilis uracil-DNA glycosylase and its inhibition by phage φ29 protein p56

Uracil-DNA glycosylase (UDG) is a conserved DNA repair enzyme involved in uracil excision from DNA. Here, we report the biochemical characterization of UDG encoded by Bacillus subtilis, a model low G+C Gram-positive organism. The purified enzyme removes uracil preferentially from single-stranded DNA over double-stranded DNA, exhibiting higher preference for U:G than U:A mismatches. Furthermore, we have identified key amino acids necessary for B. subtilis UDG activity. Our results showed that Asp-65 and His-187 are catalytic residues involved in glycosidic bond cleavage, whereas Phe-78 would participate in DNA recognition. Recently, it has been reported that B. subtilis phage φ29 encodes an inhibitor of the UDG enzyme, named protein p56, whose role has been proposed to ensure an efficient viral DNA replication, preventing the deleterious effect caused by UDG when it eliminates uracils present in the φ29 genome. In this work, we also show that a φ29-related phage, GA-1, encodes a p56-like protein with UDG inhibition activity. In addition, mutagenesis analysis revealed that residue Phe-191 of B. subtilis UDG is critical for the interaction with φ29 and GA-1 p56 proteins, suggesting that both proteins have similar mechanism of inhibition.     

A postmitotic role for Isl-class LIM homeodomain proteins in the assignment of visceral spinal motor neuron identity

LIM homeobox genes have a prominent role in the regulation of neuronal subtype identity and distinguish motor neuron subclasses in the embryonic spinal cord. We have investigated the role of Isl-class LIM homeodomain proteins in motor neuron diversification using mouse genetic methods. All spinal motor neuron subtypes initially express both Isl1 and Isl2, but Isl2 is rapidly downregulated by visceral motor neurons. Mouse embryos lacking Isl2 function exhibit defects in the migration and axonal projections of thoracic level motor neurons that appear to reflect a cell-autonomous switch from visceral to somatic motor neuron character. Additional genetic mutations that reduce or eliminate both Isl1 and Isl2 activity result in more pronounced defects in visceral motor neuron generation and erode somatic motor neuron character. Thus, an early phase of high Isl expression and activity in newly generated motor neurons permits the diversification of visceral and somatic motor neuron subtypes in the developing spinal cord.     

Roles of dynamic and stationary components of a motor command in establishing the equilibrium state at simplest targeted movements

We studied in humans interrelations between the kinematic characteristics of targeted movements of the arm and current levels of EMG of the muscles providing these movements; the movements were relatively slow, and the attained joint angle was held for a time. The EMG level was considered a correlate of the level of integral motor commands (efferent activity of the respective motoneuronal pools). Application of low-amplitude non-inertial loadings, directed against the forces developed by one or another muscle group, allowed us to provide realization of targeted movements exclusively by the activity of this muscle group, without Involvement of the antagonists. It was demonstrated that the target equilibrium joint angle is reached synchronously with the dynamic phase of EMG activity, before the latter reaches a stationary level. The structure of the dynamic EMG phase itself is complex; in most cases it is split into several components. The dependence between the joint angle and amplitude of the EMG stationary phase is rather complex and variable, and usually it is difficult to predict the characteristics of this phase based on simple biomechanical considerations. There are proofs that at the performance of the studied movements and maintaining a target position there are some components in the mechanical muscle activity, which are not controlled by the motor commands. Thus, the stationary level of a motor command represents only one of several factors responsible for attaining and maintaining a target equilibrium position. Establishing this position is provided, first of all, by interaction of dynamic components of the motor commands to different muscles. Our results show that the attempts to interpret the processes of control of targeted movements on the basis of modifications of the equilibrium point hypothesis are inadequate; these data are in better compliance with the concept of impulse-temporal control; at their interpretation it is also necessary to take more thoroughly into account nonlinear properties of the muscle reactions.     

Synchronization of pacemaker cell firing by weak ELF fields: Simulation by a circuit model

Entrainment of output action potentials from repetitively firing pacemaker cells, brought about by regularly spaced excitatory or inhibitory postsynaptic inputs, is a well-known phenomenon. Synchronization of neural firing patterns by extremely low frequency (ELF) external electric fields has also been observed. Whereas current densities of ≈10 A-m⁻² are required for direct excitation of otherwise quiescent neural tissue, much lower peak current densities (≈10⁻² A-m²) have been reported to entrain spontaneously firing molluscan pacemaker cells. We have developed a neural spike generator circuit model that simulates repetitive spike generation by a space clamped patch (area ≈ 10⁻⁷ m²) of excitable membrane subjected to depolarizing current. Picoampere (pA) range variation of DC depolarizing current causes a corresponding smooth variation of neural spike frequency, producing a physiologically realistic stimulus-response (S-R) characteristic. When lower pA range 60 Hz AC current is superposed upon the DC depolarizing current, smooth variation of the S-R characteristic is distorted by subharmonic locking of the spike generator at 30, 20, 15, 12, 10 Hz, and higher order subharmonic frequencies. Although the additional superposition of a physiologically realistic level of “white” current noise, covering the bandwidth 4–200 Hz, suffices to obscure higher order subharmonic locking, locking at 30, 20, and 15 Hz is still clearly evident in the presence of noise. Subharmonic locking is observed at a root mean square AC simulated tissue current density of ≈10⁻⁵ A-m⁻². Bioelectromagnetics 19:92–97, 1998. © 1998 Wiley-Liss, Inc.     

Phase locking in integrate-and-fire models with refractory periods and modulation

It is known [8, 11, 16, 26] that phase locking can entrain frequency information when the leaky integrate-and-fire (IF) model of a neuron is forced by a periodic function. We show that this is still the case when the IF model is made more biologically realistic. We incorporate into our model spike dependent threshold modulation and refractory periods. Consecutive firing times from this model and their respective interspike intervals are related by an annulus map. We prove a general theorem concerning orientation reversing annulus twist homeomorphisms, which shows that our map admits a unique rotation number. This implies, in particular, that chaotic behaviour is not possible in our model and phase locking is predicted.This research was partially supported by NSF EIA-BITS grant 426411This research was partially supported by the Summer Undergraduate Research Program sponsored by IGERT grant NSF-DGE 9972824 and the Undergraduate Scholars Program at MSU-BozemanAcknowledgement The authors would like to thank Marcy Barge for discussions of prime ends and Sherry Heis for formatting the diagrams.     

Neural network simulations of coupled locomotor oscillators in the lamprey spinal cord

The segmental locomotor network in the lamprey spinal cord was simulated on a computer using a connectionist-type neural network. The cells of the network were identical except for their excitatory levels and their synaptic connections. The synaptic connections used were based on previous experimental work. It was demonstrated that the connectivity of the circuit is capable of generating oscillatory activity with the appropriate phase relations among the cells. Intersegmental coordination was explored by coupling two identical segmental networks using only the cells of the network. Each of the possible couplings of a bilateral pair of cells in one oscillator with a bilateral pair of cells in the other oscillator produced stable phase locking of the two oscillators. The degree of phase difference was dependent upon synaptic weight, and the operating range of synaptic weights varied among the pairs of connections. The coupling was tested using several criteria from experimental work on the lamprey spinal cord. Coupling schemes involving several pairs of connecting cells were found which 1) achieved steadystate phase locking within a single cycle, 2) exhibited constant phase differences over a wide range of cycle periods, and 3) maintained stable phase locking in spite of large differences in the intrinsic frequencies of the two oscillators. It is concluded that the synaptic connectivity plays a large role in producing oscillations in this network and that it is not necessary to postulate a separate set of coordinating neurons between oscillators in order to achieve appropriate phase coupling.