Microcircuits in action – from CPGs to neocortex

A central pattern generator producing alternative outputs: phase relations of leech heart motor neurons with respect to premotor synaptic input

The central pattern generator (CPG) for heartbeat in leeches consists of seven identified pairs of segmental heart interneurons and one unidentified pair. Four of the identified pairs and the unidentified pair of interneurons make inhibitory synaptic connections with segmental heart motor neurons. The CPG produces a side-to-side asymmetric pattern of intersegmental coordination among ipsilateral premotor interneurons corresponding to a similarly asymmetric fictive motor pattern in heart motor neurons, and asymmetric constriction pattern of the two tubular hearts: synchronous and peristaltic. Using extracellular techniques, we recorded, in 61 isolated nerve cords, the activity of motor neurons in conjunction with the phase reference premotor heart interneuron, HN(4), and another premotor interneuron that allowed us to assess the coordination mode. These data were then coupled with a previous description of the temporal pattern of premotor interneuron activity in the two coordination modes to synthesize a global phase diagram for the known elements of the CPG and the entire motor neuron ensemble. These average data reveal the stereotypical side-to-side asymmetric patterns of intersegmental coordination among the motor neurons and show how this pattern meshes with the activity pattern of premotor interneurons. Analysis of animal-to-animal variability in this coordination indicates that the intersegmental phase progression of motor neuron activity in the midbody in the peristaltic coordination mode is the most stereotypical feature of the fictive motor pattern. Bilateral recordings from motor neurons corroborate the main features of the asymmetric motor pattern.

Bursting in substantia nigra pars reticulata neurons in vitro: possible relevance for Parkinson disease

Projection neurons of the substantia nigra reticulata (SNr) convey basal ganglia (BG) processing to thalamocortical and brain stem circuits responsible for movement. Two models try to explain pathological BG performance during Parkinson disease (PD): the rate model, which posits an overexcitation of SNr neurons due to hyperactivity in the indirect pathway and hypoactivity of the direct pathway, and the oscillatory model, which explains PD as the product of pathological pattern generators disclosed by dopamine reduction. These models are, apparently, incompatible. We tested the predictions of the rate model by increasing the excitatory drive and reducing the inhibition on SNr neurons in vitro. This was done pharmacologically with bath application of glutamate agonist N-methyl-d-aspartate and GABA(A) receptor blockers, respectively. Both maneuvers induced bursting behavior in SNr neurons. Therefore synaptic changes forecasted by the rate model induce the electrical behavior predicted by the oscillatory model. In addition, we found evidence that Ca(V)3.2 Ca(2+) channels are a critical step in generating the bursting firing pattern in SNr neurons. Other ion channels involved are: hyperpolarization-activated cation channels, high-voltage-activated Ca(2+) channels, and Ca(2+)-activated K(+) channels. However, although these channels shape the temporal structure of bursting, only Ca(V)3.2 Ca(2+) channels are indispensable for the initiation of the bursting pattern.

Neural bases of goal-directed locomotion in vertebrates--an overview

The different neural control systems involved in goal-directed vertebrate locomotion are reviewed. They include not only the central pattern generator networks in the spinal cord that generate the basic locomotor synergy and the brainstem command systems for locomotion but also the control systems for steering and control of body orientation (posture) and finally the neural structures responsible for determining which motor programs should be turned on in a given instant. The role of the basal ganglia is considered in this context. The review summarizes the available information from a general vertebrate perspective, but specific examples are often derived from the lamprey, which provides the most detailed information when considering cellular and network perspectives.

Vagal nerve stimulation improves cerebellar tremor and dysphagia in multiple sclerosis

Vagus nerve stimulation (VNS), an adjunctive approach for the treatment of epilepsy, was performed in three multiple sclerosis (MS) patients displaying postural cerebellar tremor (PCT) and dysphagia. Following VNS, improvement of PCT and dysphagia was manifested over a period of two and three months, respectively. In view of the involvement of the main brainstem visceral component of the vagus, the nucleus tractus solitarius (NTS), in modulating central pattern generators (CPGs) linked to both olive complex pathway and swallowing, improvement is likely to be VNS related. The results obtained suggest an additional therapeutic application for VNS and may represent a novel form of treatment in patients with severe MS.

Muscle proprioceptive feedback and spinal networks

This review revolves primarily around segmental feedback systems established by muscle spindle and Golgi tendon organ afferents, as well as spinal recurrent inhibition via Renshaw cells. These networks are considered as to their potential contributions to the following functions: (i) generation of anti-gravity thrust during quiet upright stance and the stance phase of locomotion; (ii) timing of locomotor phases; (iii) linearization and correction for muscle nonlinearities; (iv) compensation for muscle lever-arm variations; (v) stabilization of inherently unstable systems; (vi) compensation for muscle fatigue; (vii) synergy formation; (viii) selection of appropriate responses to perturbations; (ix) correction for intersegmental interaction forces; (x) sensory-motor transformations; (xi) plasticity and motor learning. The scope will at times extend beyond the narrow confines of spinal circuits in order to integrate them into wider contexts and concepts.

Stochastic description of complex and simple spike firing in cerebellar Purkinje cells

Cerebellar Purkinje cells generate two distinct types of spikes, complex and simple spikes, both of which have conventionally been considered to be highly irregular, suggestive of certain types of stochastic processes as underlying mechanisms. Interestingly, however, the interspike interval structures of complex spikes have not been carefully studied so far. We showed in a previous study that simple spike trains are actually composed of regular patterns and single interspike intervals, a mixture that could not be explained by a simple rate-modulated Poisson process. In the present study, we systematically investigated the interspike interval structures of separated complex and simple spike trains recorded in anaesthetized rats, and derived an appropriate stochastic model. We found that: (i) complex spike trains do not exhibit any serial correlations, so they can effectively be generated by a renewal process, (ii) the distribution of intervals between complex spikes exhibits two narrow bands, possibly caused by two oscillatory bands (0.5-1 and 4-8 Hz) in the input to Purkinje cells and (iii) the regularity of regular patterns and single interspike intervals in simple spike trains can be represented by gamma processes of orders, which themselves are drawn from gamma distributions, suggesting that multiple sources modulate the regularity of simple spike trains.

Capturing the bursting dynamics of a two-cell inhibitory network using a one-dimensional map

Out-of-phase bursting is a functionally important behavior displayed by central pattern generators and other neural circuits. Understanding this complex activity requires the knowledge of the interplay between the intrinsic cell properties and the properties of synaptic coupling between the cells. Here we describe a simple method that allows us to investigate the existence and stability of anti-phase bursting solutions in a network of two spiking neurons, each possessing a T-type calcium current and coupled by reciprocal inhibition. We derive a one-dimensional map which fully characterizes the genesis and regulation of anti-phase bursting arising from the interaction of the T-current properties with the properties of synaptic inhibition. This map is the burst length return map formed as the composition of two distinct one-dimensional maps that are each regulated by a different set of model parameters. Although each map is constructed using the properties of a single isolated model neuron, the composition of the two maps accurately captures the behavior of the full network. We analyze the parameter sensitivity of these maps to determine the influence of both the intrinsic cell properties and the synaptic properties on the burst length, and to find the conditions under which multistability of several bursting solutions is achieved. Although the derivation of the map relies on a number of simplifying assumptions, we discuss how the principle features of this dimensional reduction method could be extended to more realistic model networks.

Patterns in inhibitory networks of simple map neurons

We study the dynamics of networks of inhibitory map-based bursting neurons. Linear analysis allows us to understand how the patterns of bursting are determined by network topology and how they depend on the strength of synaptic connections, when inhibition is balanced. Two kinds of patterns are found depending on the symmetry of the network: slow cyclic patterns riding on subthreshold oscillations where almost all neurons contribute bursts in a sparse manner and fast patterns of bursts in which only one of two mutually exclusive groups of neurons take part. We also discuss the properties of the neuron model that underlie the described phenomena, comment on the limitations of the technique of analysis, and point to some possible ways to overcome them.

Invertebrate preparations and their contribution to neurobiology in the second half of the 20th century

This review summarized the contribution to neurobiology achieved through the use of invertebrate preparations in the second half of the 20th century. This fascinating period was preceded by pioneers who explored a wide variety of invertebrate phyla and developed various preparations appropriate for electrophysiological studies. Their work advanced general knowledge about neuronal properties (dendritic, somatic, and axonal excitability; pre- and postsynaptic mechanisms). The study of invertebrates made it possible to identify cell bodies in different ganglia, and monitor their operation in the course of behavior. In the 1970s, the details of central neural circuits in worms, molluscs, insects, and crustaceans were characterized for the first time and well before equivalent findings were made in vertebrate preparations. The concept and nature of a central pattern generator (CPG) have been studied in detail, and the stomatogastric nervous system (STNS) is a fine example, having led to many major developments since it was first examined. The final part of the review is a discussion of recent neuroethological studies that have addressed simple cognitive functions and confirmed the utility of invertebrate models. After presenting our invertebrate "mice," the worm Caenorhabditis elegans and the fruit fly Drosophila melanogaster, our conclusion, based on arguments very different from those used fifty years ago, is that invertebrate models are still essential for acquiring insight into the complexity of the brain.

Resonance or Integration? Self-Sustained Dynamics and Excitability of Neural Microcircuits

We investigated spontaneous activity and excitability in large networks of artificial spiking neurons. We compared three different spiking neuron models: integrate-and-fire (IF), regular-spiking (RS), and resonator (RES). First, we show that different models have different frequency-dependent response properties, yielding large differences in excitability. Then, we investigate the responsiveness of these models to a single afferent inhibitory/excitatory spike and calibrate the total synaptic drive such that they would exhibit similar peaks of the postsynaptic potentials (PSP). Based on the synaptic calibration, we build large microcircuits of IF, RS, and RES neurons and show that the resonance property favors homeostasis and self-sustainability of the network activity. On the other hand, integration produces instability while it endows the network with other useful properties, such as responsiveness to external inputs. We also investigate other potential sources of stable self-sustained activity and their relation to the membrane properties of neurons. We conclude that resonance and integration at the neuron level might interact in the brain to promote stability as well as flexibility and responsiveness to external input and that membrane properties, in general, are essential for determining the behavior of large networks of neurons.

Phase resetting curves and oscillatory stability in interneurons of rat somatosensory cortex

Synchronous oscillations in neural activity are found over wide areas of the cortex. Specific populations of interneurons are believed to play a significant role in generating these synchronized oscillations through mutual synaptic and gap-junctional interactions. Little is known, though, about the mechanism of how oscillations are maintained stably by particular types of interneurons and by their local networks. To obtain more insight into this, we measured membrane-potential responses to small current-pulse perturbations during regular firing, to construct phase resetting curves (PRCs) for three types of interneurons: nonpyramidal regular-spiking (NPRS), low-threshold spiking (LTS), and fast-spiking (FS) cells. Within each cell type, both monophasic and biphasic PRCs were observed, but the proportions and sensitivities to perturbation amplitude were clearly correlated to cell type. We then analyzed the experimentally measured PRCs to predict oscillation stability, or firing reliability, of cells for a complex stochastic input, as occurs in vivo. To do this, we used a method from random dynamical system theory to estimate Lyapunov exponents of the simplified phase model on the circle. The results indicated that LTS and NPRS cells have greater oscillatory stability (are more reliably entrained) in small noisy inputs than FS cells, which is consistent with their distinct types of threshold dynamics.

Biological pattern generation: the cellular and computational logic of networks in motion

In 1900, Ramón y Cajal advanced the neuron doctrine, defining the neuron as the fundamental signaling unit of the nervous system. Over a century later, neurobiologists address the circuit doctrine: the logic of the core units of neuronal circuitry that control animal behavior. These are circuits that can be called into action for perceptual, conceptual, and motor tasks, and we now need to understand whether there are coherent and overriding principles that govern the design and function of these modules. The discovery of central motor programs has provided crucial insight into the logic of one prototypic set of neural circuits: those that generate motor patterns. In this review, I discuss the mode of operation of these pattern generator networks and consider the neural mechanisms through which they are selected and activated. In addition, I will outline the utility of computational models in analysis of the dynamic actions of these motor networks.

Abstracts of the 15th Annual Meeting of the Israel Society for Neuroscience (Eilat, Israel, December 3–5, 2006)

The Israel Society for Neuroscience (ISFN) was founded in 1993 by a group of Israeli leading scientists conducting research in the area of neurobiology. The primary goal of the society was to promote and disseminate the knowledge and understanding acquired by its members, and to strengthen interactions between them. Since then, the society holds its annual meeting every year in Eilat during the month of December. At these annual meetings the senior Israeli neurobiologists, their teams, and their graduate students, as well as foreign scientists and students, present their recent research findings in platform and poster presentations. The meeting also offers the opportunity for the researchers to exchange information with each other, often leading to the initiation of collaborative studies. Both the number of members of the society and of those participating in the annual meeting is constantly increasing, and it is anticipated that this year about 600 scientists will convene at the Princess Hotel in Eilat, Israel.

Further information concerning the Israel Society for Neuroscience can be found at http://www.isfn.org.il.

Committee:

Zvi Wollberg (President) Tel Aviv University

Edi Barkai University of Haifa

Etti Grauer Israel Institute for Biological Research, Ness Ziona

Yoram Rami Grossman Ben Gurion University of the Negev

Yoel Yaari Hebrew University of Jerusalem

Gal Yadid Bar-Ilan University

Shlomo Rotshenker (President Elect) Hebrew University of Jerusalem

Ettie Grauer (Treasurer) Israel Institute for Biological Research, Ness Ziona

Michal Gilady (Administrator) Rishon Le Zion

Serotonin and Dopamine Interactions in Rodents and Primates: Implications for Psychosis and Antipsychotic Drug Development

Since the late 1950s, appreciation of dopamine receptor blockade has played a primary role in understanding the mechanism underlying the therapeutic effects of antipsychotic drugs in schizophrenic patients in treating the positive symptoms of schizophrenia (e.g., delusions and hallucinations). Development of the second generation of antipsychotic drugs, otherwise known as atypical antipsychotic drugs, has resulted in treatments with improved subjective tolerability but relatively modest improvements in the negative symptoms of schizophrenia such as avolition, flat affect, and anhedonia. The major current challenge is to develop medications which can further improve negative symptoms treatment and also tackle the intractable clinical problems of cognitive impairment associated with schizophrenia. Further advances along these lines with respect to the dopaminergic and serotonergic neurostransmitter systems will be aided by an appreciation of the interaction between dopamine and serotonin receptor subtypes in a range of key brain structures, such as the prefrontal cortex, thalamus, striatum, amygdala, hippocampus, and the brain stem nuclei, from which the cell bodies of monoaminergic-containing neurons originate. Increasing emphasis on the use of animal models which are homologous to critical aspects of the pathophysiology in the brains of schizophrenic patients will also be required, especially as negative symptoms and cognitive impairment become an important focus for generating novel therapeutics.

Cortical network modeling: analytical methods for firing rates and some properties of networks of LIF neurons

The circuitry of cortical networks involves interacting populations of excitatory (E) and inhibitory (I) neurons whose relationships are now known to a large extent. Inputs to E- and I-cells may have their origins in remote or local cortical areas. We consider a rudimentary model involving E- and I-cells. One of our goals is to test an analytic approach to finding firing rates in neural networks without using a diffusion approximation and to this end we consider in detail networks of excitatory neurons with leaky integrate-and-fire (LIF) dynamics. A simple measure of synchronization, denoted by S(q), where q is between 0 and 100 is introduced. Fully connected E-networks have a large tendency to become dominated by synchronously firing groups of cells, except when inputs are relatively weak. We observed random or asynchronous firing in such networks with diverse sets of parameter values. When such firing patterns were found, the analytical approach was often able to accurately predict average neuronal firing rates. We also considered several properties of E-E networks, distinguishing several kinds of firing pattern. Included were those with silences before or after periods of intense activity or with periodic synchronization. We investigated the occurrence of synchronized firing with respect to changes in the internal excitatory postsynaptic potential (EPSP) magnitude in a network of 100 neurons with fixed values of the remaining parameters. When the internal EPSP size was less than a certain value, synchronization was absent. The amount of synchronization then increased slowly as the EPSP amplitude increased until at a particular EPSP size the amount of synchronization abruptly increased, with S(5) attaining the maximum value of 100%. We also found network frequency transfer characteristics for various network sizes and found a linear dependence of firing frequency over wide ranges of the external afferent frequency, with non-linear effects at lower input frequencies. The theory may also be applied to sparsely connected networks, whose firing behaviour was found to change abruptly as the probability of a connection passed through a critical value. The analytical method was also found to be useful for a feed-forward excitatory network and a network of excitatory and inhibitory neurons.

Slow-waves in the olfactory system: an olfactory perspective on cortical rhythms

Over the past few years, it has become clear that oscillatory dynamics of cortical networks are closely involved in sensory coding, attention, memory and sleep. Although most experimental and theoretical studies have focused on the neocortex, we believe that progress in understanding cortical oscillations can be advanced by also considering the olfactory system--which shares many basic properties with the neocortex and shows similar oscillatory patterns. Besides offering the advantage of a greater experimental tractability, the olfactory cortex might prove to be instrumental in uncovering general functional principles of neocortical oscillations, by virtue of the potentially important role of olfaction during neocortical evolution. In this article, we illustrate how such an evolution-based comparative approach can provide novel insights into neocortical slow-wave sleep oscillations and their relationship to respiration.

Conditional rhythmicity and synchrony in a bilateral pair of bursting motor neurons in Aplysia

This investigation examined the activity of a bilateral pair of motor neurons (B67) in the feeding system of Aplysia californica. In isolated ganglia, B67 firing exhibited a highly stereotyped bursting pattern that could be attributed to an underlying TTX-resistant driver potential (DP). Under control conditions, this bursting in the two B67 neurons was infrequent, irregular, and asynchronous. However, bath application of the neuromodulator dopamine (DA) increased the duration, frequency, rhythmicity, and synchrony of B67 bursts. In the absence of DA, depolarization of B67 with injected current produced rhythmic bursting. Such depolarization-induced rhythmic burst activity in one B67, however, did not entrain its contralateral counterpart. Moreover, when both B67s were depolarized to potentials that produced rhythmic bursting, their synchrony was significantly lower than that produced by DA. In TTX, dopamine increased the DP duration, enhanced the amplitude of slow signaling between the two B67s, and increased DP synchrony. A potential source of dopaminergic signaling to B67 was identified as B65, an influential interneuron with bilateral buccal projections. Firing B65 produced bursts in the ipsilateral and contralateral B67s. Under conditions that attenuated polysynaptic activity, firing B65 evoked rapid excitatory postsynaptic potentials in B67 that were blocked by sulpiride, an antagonist of synaptic DA receptors in this system. Finally, firing a single B65 was capable of producing a prolonged period of rhythmic synchronous bursting of the paired B67s. It is proposed that modulatory dopaminergic signaling originating from B65 during consummatory behaviors can promote rhythmicity and bilateral synchrony in the paired B67 motor neurons.

Sodium channel-mediated intrinsic mechanisms underlying the differences of spike programming among GABAergic neurons

Neural codes to guide well-organized behavior are thought to be the programmed patterns of sequential spikes at central neurons, in which the coordinative activities of voltage-gated ion channels are involved. The attention has been paid to study the role of potassium channels in spike pattern; but it is not clear how the intrinsic mechanism mediated by voltage-gated sodium channels (VGSC) influences the programming of sequential spikes, which we investigated at GABAergic cerebellar Purkinje cells and hippocampal interneurons by patch-clamp recording in brain slices. Spike capacity is higher at Purkinje cells than interneurons in response to the given intensities of inputs, and is dependent on input intensity. Compared to interneurons, Purkinje cells express the lower threshold potentials and the shorter refractory periods of sequential spikes. The increases of input intensities shorten spike refractory periods significantly. The threshold potentials for VGSC activation and the refractory periods for its reactivation are lower at Purkinje cells, and are reduced by the strong depolarization. We suggest that the VGSC-mediated threshold potentials and refractory periods are regulated by synaptic inputs, and navigate the programming of sequential spikes at the neurons.

Differential effects of a selective dopamine D1-like receptor agonist on motor activity and c-fos expression in the frontal-striatal circuitry of SHR and Wistar-Kyoto rats

BACKGROUND

Molecular genetic studies suggest the dopamine D1 receptor (D1R) may be implicated in attention-deficit/hyperactivity disorder (ADHD). As little is known about the potential motor role of D1R in ADHD, animal models may provide important insights into this issue.

METHODS

We investigated the effects of a full and selective D1R agonist, SKF-81297 (0.3, 3 and 10 mg/kg), on motor behaviour and expression of the plasticity-associated gene, c-fos, in habituated young adult male Spontaneously Hypertensive Rats (SHR), the most commonly used animal model of ADHD, and Wistar-Kyoto (WKY; the strain from which SHR were derived).

RESULTS

SHR rats were more behaviourally active than WKY rats after injection with vehicle. The 0.3 mg/kg dose of SKF-81297 increased motor behaviour (locomotion, sifting, rearing, and sniffing) in both SHR and WKY rats. Total grooming was also stimulated, but only in WKY rats. The same dose increased c-fos mRNA expression in the piriform cortex of both strains. The 3 mg/kg dose increased sifting and sniffing in both strains. Locomotion was also stimulated towards the end of the testing period. The intermediate dose decreased total rearing in both strains, and produced a significant increase in c-fos mRNA in the striatum, nucleus accumbens, olfactory tuberculum, and in the cingulate, agranular insular and piriform cortices. The 10 mg/kg dose of SKF-81297 produced a biphasic effect on locomotion, which was characterized by an initial decrease followed by later stimulation. The latter stimulatory effect was more pronounced in SHR than in WKY rats when compared to their respective vehicle-injected groups. The 10 mg/kg dose also stimulated sifting and sniffing in both strains. Both the 3 and 10 mg/kg doses had no effect on total grooming. The 10 mg/kg dose induced significantly higher levels of c-fos mRNA expression in the nucleus accumbens and adjacent cortical regions (but not striatum) of SHR when compared to WKY rats.

CONCLUSION

The present results suggest a potential alteration in D1R neurotransmission within the frontal-striatal circuitry of SHR involved in motor control. These findings extend our understanding of the molecular alterations in SHR, a heuristically useful model of ADHD.

A central pattern generator producing alternative outputs: temporal pattern of premotor activity

The central pattern generator for heartbeat in medicinal leeches constitutes seven identified pairs of segmental heart interneurons. Four identified pairs of heart interneurons make a staggered pattern of inhibitory synaptic connections with segmental heart motor neurons. Using extracellular recording from multiple interneurons in the network in 56 isolated nerve cords, we show that this pattern generator produces a side-to-side asymmetric pattern of intersegmental coordination among ipsilateral premotor interneurons. This pattern corresponds to a similarly asymmetric fictive motor pattern in heart motor neurons and asymmetric constriction pattern of the two tubular hearts, synchronous and peristaltic. We provide a quantitative description of the firing pattern of all the premotor interneurons, including phase, duty cycle, and intraburst frequency of this premotor activity pattern. This analysis identifies two stereotypical coordination modes corresponding to synchronous and peristaltic, which show phase constancy over a broad range of periods as do the fictive motor pattern and the heart constriction pattern. Coordination mode is controlled through one segmental pair of heart interneurons (switch interneurons). Side-to-side switches in coordination mode are a regular feature of this pattern generator and occur with changes in activity state of these switch interneurons. Associated with synchronous coordination of premotor interneurons, the ipsilateral switch interneuron is in an active state, during which it produces rhythmic bursts, whereas associated with peristaltic coordination, the ipsilateral switch interneuron is largely silent. We argue that timing and pattern elaboration are separate functions produced by overlapping subnetworks in the heartbeat central pattern generator.

Complexities and uncertainties of neuronal network function

The nervous system generates behaviours through the activity in groups of neurons assembled into networks. Understanding these networks is thus essential to our understanding of nervous system function. Understanding a network requires information on its component cells, their interactions and their functional properties. Few networks come close to providing complete information on these aspects. However, even if complete information were available it would still only provide limited insight into network function. This is because the functional and structural properties of a network are not fixed but are plastic and can change over time. The number of interacting network components, their (variable) functional properties, and various plasticity mechanisms endows networks with considerable flexibility, but these features inevitably complicate network analyses. This review will initially discuss the general approaches and problems of network analyses. It will then examine the success of these analyses in a model spinal cord locomotor network in the lamprey, to determine to what extent in this relatively simple vertebrate system it is possible to claim detailed understanding of network function and plasticity.

The education and re-education of the spinal cord

In normal life, activity-dependent plasticity occurs in the spinal cord as well as in the brain. Like CNS plasticity elsewhere, this spinal cord plasticity can occur at many neuronal and synaptic sites and by a variety of mechanisms. Spinal cord plasticity is prominent in postnatal development and contributes to acquisition of standard behaviors such as locomotion and rapid withdrawal from pain. Later on in life, spinal cord plasticity contributes to acquisition and maintenance of specialized motor skills, and to compensation for the peripheral and central changes associated with aging, disease, and trauma. Mastery of even the simplest behaviors is accompanied by complex spinal and supraspinal plasticity. This complexity is necessary, to preserve the full roster of behaviors, and is also inevitable, due to the ubiquity of activity-dependent plasticity in the CNS. Careful investigation of spinal cord plasticity is essential for understanding motor skills; and, because of the relative simplicity and accessibility of the spinal cord, is a logical and convenient starting point for exploring skill acquisition. Appropriate induction and guidance of activity-dependent plasticity in the spinal cord is likely to be a key part of the realization of effective new rehabilitation methods for spinal cord injuries, cerebral palsy, and other chronic motor disorders.

The refractory periods and threshold potentials of sequential spikes measured by whole-cell recording

Neurons in the central nervous system are thought to program neural language via firing sequential spikes for guiding animal behaviors. The quantitative profiles of spike intrinsic properties are critically important to understand spike programming. We developed approaches with whole-cell recordings to measure the threshold potentials and refractory periods (RPs) of sequential spikes, and to analyze the relationships of these factors with spike timing precision and capacity at the regular-spiking and fast-spiking neurons in cortical slice. The RPs and threshold potentials of sequential spikes at these two groups of neurons are different and are linearly correlated with spike timing precision and capacity. These data suggest that RPs and threshold potentials essentially navigate the spike programming for the precise and loyal encoding of meaningful neural signals. Our study provides the avenues for decoding the spectrum of the neural signals quantitatively.

Integrative neuroscience: linking levels of analyses

If we are to understand how the brain performs different integrated functions in cellular terms, we need both to understand all relevant levels of analysis from the molecular to the behavioural and cognitive levels and to realize an integration of such levels. This is currently a major challenge for neuroscience. Most research, whether dealing with perception, action or learning, focuses on a few levels of organization, for instance the molecular level and brain imaging, and leaves other crucial areas practically untouched. To reach the level of understanding that we desire, a multi-level approach is required in which the different levels link into each other. It is possible to bridge across the different levels for one system, and this has been demonstrated, for example, in the lamprey in generation of goal-directed locomotion. It can be argued that an integrated analysis of any neural system cannot be performed without the aid of a close interaction between experiments and modelling. The dynamic processing within any neural system is such that an intuitive interpretation is rarely sufficient.