Induction of myelination in the central nervous system by electrical activity.

The oligodendrocyte is the myelin-forming cell in the central nervous system. Despite the close interaction between axons and oligodendrocytes, there is little evidence that neurons influence myelinogenesis. On the contrary, newly differentiated oligodendrocytes, which mature in culture in the total absence of neurons, synthesize the myelin-specific constituents of oligodendrocytes differentiated in vivo and even form myelin-like figures. Neuronal electrical activity may be required, however, for the appropriate formation of the myelin sheath. To investigate the role of electrical activity on myelin formation, we have used highly specific neurotoxins, which can either block (tetrodotoxin) or increase (alpha-scorpion toxin) the firing of neurons. We show that myelination can be inhibited by blocking the action potential of neighboring axons or enhanced by increasing their electrical activity, clearly linking neuronal electrical activity to myelinogenesis.

Self-organized phase transitions in neural networks as a neural mechanism of information processing.

Transitions between dynamically stable activity patterns imposed on an associative neural network are shown to be induced by self-organized infinitesimal changes in synaptic connection strength and to be a kind of phase transition. A key event for the neural process of information processing in a population coding scheme is transition between the activity patterns encoding usual entities. We propose that the infinitesimal and short-term synaptic changes based on the Hebbian learning rule are the driving force for the transition. The phase transition between the following two dynamical stable states is studied in detail, the state where the firing pattern is changed temporally so as to itinerate among several patterns and the state where the firing pattern is fixed to one of several patterns. The phase transition from the pattern itinerant state to a pattern fixed state may be induced by the Hebbian learning process under a weak input relevant to the fixed pattern. The reverse transition may be induced by the Hebbian unlearning process without input. The former transition is considered as recognition of the input stimulus, while the latter is considered as clearing of the used input data to get ready for new input. To ensure that information processing based on the phase transition can be made by the infinitesimal and short-term synaptic changes, it is absolutely necessary that the network always stays near the critical state corresponding to the phase transition point.

Origin and evolution of circular waves and spirals in Dictyostelium discoideum territories.

Randomly distributed Dictyostelium discoideum cells form cooperative territories by signaling to each other with cAMP. Cells initiate the process by sending out pulsatile signals, which propagate as waves. With time, circular and spiral patterns form. We show that by adding spatial and temporal noise to the levels of an important regulator of external cAMP levels, the cAMP phosphodiesterase inhibitor, we can explain the natural progression of the system from randomly firing cells to circular waves whose symmetries break to form double- and single- or multi-armed spirals. When phosphodiesterase inhibitor is increased with time, mimicking experimental data, the wavelength of the spirals shortens, and a proportion of them evolve into pairs of connected spirals. We compare these results to recent experiments, finding that the temporal and spatial correspondence between experiment and model is very close.

Multineuronal codes in retinal signaling.

The visual world is presented to the brain through patterns of action potentials in the population of optic nerve fibers. Single-neuron recordings show that each retinal ganglion cell has a spatially restricted receptive field, a limited integration time, and a characteristic spectral sensitivity. Collectively, these response properties define the visual message conveyed by that neuron's action potentials. Since the size of the optic nerve is strictly constrained, one expects the retina to generate a highly efficient representation of the visual scene. By contrast, the receptive fields of nearby ganglion cells often overlap, suggesting great redundancy among the retinal output signals. Recent multineuron recordings may help resolve this paradox. They reveal concerted firing patterns among ganglion cells, in which small groups of nearby neurons fire synchronously with delays of only a few milliseconds. As there are many more such firing patterns than ganglion cells, such a distributed code might allow the retina to compress a large number of distinct visual messages into a small number of optic nerve fibers. This paper will review the evidence for a distributed coding scheme in the retinal output. The performance limits of such codes are analyzed with simple examples, illustrating that they allow a powerful trade-off between spatial and temporal resolution.

Cortical activity flips among quasi-stationary states.

Parallel recordings of spike trains of several single cortical neurons in behaving monkeys were analyzed as a hidden Markov process. The parallel spike trains were considered as a multivariate Poisson process whose vector firing rates change with time. As a consequence of this approach, the complete recording can be segmented into a sequence of a few statistically discriminated hidden states, whose dynamics are modeled as a first-order Markov chain. The biological validity and benefits of this approach were examined in several independent ways: (i) the statistical consistency of the segmentation and its correspondence to the behavior of the animals; (ii) direct measurement of the collective flips of activity, obtained by the model; and (iii) the relation between the segmentation and the pair-wise short-term cross-correlations between the recorded spike trains. Comparison with surrogate data was also carried out for each of the above examinations to assure their significance. Our results indicated the existence of well-separated states of activity, within which the firing rates were approximately stationary. With our present data we could reliably discriminate six to eight such states. The transitions between states were fast and were associated with concomitant changes of firing rates of several neurons. Different behavioral modes and stimuli were consistently reflected by different states of neural activity. Moreover, the pair-wise correlations between neurons varied considerably between the different states, supporting the hypothesis that these distinct states were brought about by the cooperative action of many neurons.

Mathematical analysis of activation thresholds in enzyme-catalyzed positive feedbacks: application to the feedbacks of blood coagulation.

A hierarchy of enzyme-catalyzed positive feedback loops is examined by mathematical and numerical analysis. Four systems are described, from the simplest, in which an enzyme catalyzes its own formation from an inactive precursor, to the most complex, in which two sequential feedback loops act in a cascade. In the latter we also examine the function of a long-range feedback, in which the final enzyme produced in the second loop activates the initial step in the first loop. When the enzymes generated are subject to inhibition or inactivation, all four systems exhibit threshold properties akin to excitable systems like neuron firing. For those that are amenable to mathematical analysis, expressions are derived that relate the excitation threshold to the kinetics of enzyme generation and inhibition and the initial conditions. For the most complex system, it was expedient to employ numerical simulation to demonstrate threshold behavior, and in this case long-range feedback was seen to have two distinct effects. At sufficiently high catalytic rates, this feedback is capable of exciting an otherwise subthreshold system. At lower catalytic rates, where the long-range feedback does not significantly affect the threshold, it nonetheless has a major effect in potentiating the response above the threshold. In particular, oscillatory behavior observed in simulations of sequential feedback loops is abolished when a long-range feedback is present.

Brain-derived neurotrophic factor rapidly enhances synaptic transmission in hippocampal neurons via postsynaptic tyrosine kinase receptors.

Although neurotrophins are primarily associated with long-term effects on neuronal survival and differentiation, recent studies have shown that acute changes in synaptic transmission can also be produced. In the hippocampus, an area critically involved in learning and memory, we have found that brain-derived neurotrophic factor (BDNF) rapidly enhanced synaptic efficacy through a previously unreported mechanism--increased postsynaptic responsiveness via a phosphorylation-dependent pathway. Within minutes of BDNF application to cultured hippocampal neurons, spontaneous firing rate was dramatically increased, as were the frequency and amplitude of excitatory postsynaptic currents. The increased frequency of postsynaptic currents resulted from the change in presynaptic firing. However, the increased amplitude was postsynaptic in origin because it was selectively blocked by intracellular injection of the tyrosine kinase receptor (Ntrk2/TrkB) inhibitor K-252a and potentiated by injection of the phosphatase inhibitor okadaic acid. These results suggest a role for BDNF in the modulation of synaptic transmission in the hippocampus.

Rapid local synchronization of action potentials: toward computation with coupled integrate-and-fire neurons.

The collective behavior of interconnected spiking nerve cells is investigated. It is shown that a variety of model systems exhibit the same short-time behavior and rapidly converge to (approximately) periodic firing patterns with locally synchronized action potentials. The dynamics of one model can be described by a downhill motion on an abstract energy landscape. Since an energy landscape makes it possible to understand and program computation done by an attractor network, the results will extend our understanding of collective computation from models based on a firing-rate description to biologically more realistic systems with integrate-and-fire neurons.

Presynaptic modulation of cortical synaptic activity by calcineurin.

Synaptic plasticity is modulated by Ca(2+)-induced alterations in the balance between phosphorylation and dephosphorylation. Recent evidence suggests that calcineurin, the Ca(2+)-calmodulin-dependent phosphatase (2B), modulates the activity of postsynaptic glutamate receptors. However, in rat cortex, calcineurin is enriched mainly in presynaptic, not postsynaptic, fractions. To determine if calcineurin modulates glutamatergic neurotransmission through a presynaptic mechanism, we used whole-cell patch clamp experiments to test effects of two specific calcineurin inhibitors, cyclosporin A (CsA) and FK506, on synaptic activity in fetal rat cortical neurons. The rate of spontaneous action-potential firing was markedly increased by either CsA or FK506 but was unaffected by rapamycin, a structural analog of FK506 which has no effect on calcineurin. In voltage-clamp experiments, CsA increased the rate but not the amplitude of glutamate receptor-mediated, excitatory postsynaptic currents, suggesting an increased rate of glutamate release. CsA had no effect on the amplitude of currents evoked by brief bath application of selective glutamate receptor agonists, providing further evidence for a pre- rather than postsynaptic site of action. In conclusion, these data indicate that calcineurin modulates glutamatergic neurotransmission in rat cortical neurons through a presynaptic mechanism.

Estradiol and the inhibition of hypothalamic gonadotropin-releasing hormone pulse generator activity in the rhesus monkey.

In mammals, gonadal function is controlled by a hypothalamic signal generator that directs the pulsatile release of gonadotropin-releasing hormone (GnRH) and the consequent pulsatile secretion of luteinizing hormone. In female rhesus monkeys, the electrophysiological correlates of GnRH pulse generator activity are abrupt, rhythmic increases in hypothalamic multiunit activity (MUA volleys), which represent the simultaneous increase in firing rate of individual neurons. MUA volleys are arrested by estradiol, either spontaneously at midcycle or after the administration of the steroid. Multiunit recordings, however, provide only a measure of total neuronal activity, leaving the behavior of the individual cells obscure. This study was conducted to determine the mode of action of estradiol at the level of single neurons associated with the GnRH pulse generator. Twenty-three such single units were identified by cluster analysis of multiunit recordings obtained from a total of six electrodes implanted in the mediobasal hypothalamus of three ovariectomized rhesus monkeys, and their activity was monitored before and after estradiol administration. The bursting of all 23 units was arrested within 4 h of estradiol administration although their baseline activity was maintained. The bursts of most units reappeared at the same time as the MUA volleys, the recovery of some was delayed, and one remained inhibited for the duration of the study (43 days). The results indicate that estradiol does not desynchronize the bursting of single units associated with the GnRH pulse generator but that it inhibits this phenomenon. The site and mechanism of action of estradiol in this regard remain to be determined.

Inhibitory influence of frontal cortex on locus coeruleus neurons.

The functional influence of the frontal cortex (FC) on the noradrenergic nucleus locus coeruleus (LC) was studied in the rat under ketamine anesthesia. The FC was inactivated by local infusion of lidocaine or ice-cold Ringer's solution while recording neuronal activity simultaneously in FC and LC. Lidocaine produced a transient increase in activity in FC, accompanied by a decrease in LC unit and multiunit activity. This was followed by a total inactivation of FC and a sustained increase in firing rate of LC neurons. Subsequent experiments revealed antidromic responses in the FC when stimulation was applied to the LC region. The antidromic responses in FC were found in a population of neurons (about 8%) restricted to the dorsomedial area, FR2. The results indicate that there is a strong inhibitory influence of FC on the tonic activity of LC neurons. The antidromic responses in FC to stimulation of the LC region suggest that this influence is locally mediated, perhaps through interneurons within the nucleus or neighboring the LC.

Mechanisms underlying the sensitivity of songbird forebrain neurons to temporal order.

Neurons in the songbird forebrain area HVc (hyperstriatum ventrale pars caudale or high vocal center) are sensitive to the temporal structure of the bird's own song and are capable of integrating auditory information over a period of several hundred milliseconds. Extracellular studies have shown that the responses of some HVc neurons depend on the combination and temporal order of syllables from the bird's own song, but little is known about the mechanisms underlying these response properties. To investigate these mechanisms, we recorded intracellular responses to a set of auditory stimuli designed to assess the degree of dependence of the responses on temporal context. This report provides evidence that HVc neurons encode information about temporal structure by using a variety of mechanisms including syllable-specific inhibition, excitatory postsynaptic potentials with a range of different time courses, and burst-firing nonlinearity. The data suggest that the sensitivity of HVc neurons to temporal combinations of syllables results from the interactions of several cells and does not arise in a single step from afferent inputs alone.

Role of the monkey ventrolateral prefrontal cortex in the integration of contextual information for the selection and understanding of goal-directed actions

Action selection and organization are very complex processes that need to exploit contextual information and the retrieval of previously memorized information, as well as the integration of these different types of data. On the basis of anatomical connection with premotor and parietal areas involved in action goal coding, and on the data about the literature it seems appropriate to suppose that one of the most candidate involved in the selection of neuronal pools for the selection and organization of intentional actions is the prefrontal cortex. We recorded single ventrolateral prefrontal (VLPF) neurons activity while monkeys performed simple and complex manipulative actions aimed at distinct final goals, by employing a modified and more strictly controlled version of the grasp-to-eat(a food pellet)/grasp-to-place(an object) paradigm used in previous studies on parietal (Fogassi et al., 2005) and premotor neurons (Bonini et al., 2010). With this task we have been able both to evaluate the processing and integration of distinct (visual and auditory) contextual sequentially presented information in order to select the forthcoming action to perform and to examine the possible presence of goal-related activity in this portion of cortex. Moreover, we performed an observation task to clarify the possible contribution of VLPF neurons to the understanding of others’ goal-directed actions. Simple Visuo Motor Task (sVMT). We found four main types of neurons: unimodal sensory-driven, motor-related, unimodal sensory-and-motor, and multisensory neurons. We found a substantial number of VLPF neurons showing both a motor-related discharge and a visual presentation response (sensory-and-motor neurons), with remarkable visuo-motor congruence for the preferred target. Interestingly the discharge of multisensory neurons reflected a behavioural decision independently from the sensory modality of the stimulus allowing the monkey to make it: some encoded a decision to act/refraining from acting (the majority), while others specified one among the four behavioural alternatives. Complex Visuo Motor Task (cVMT). The cVMT was similar to the sVMT, but included a further grasping motor act (grasping a lid in order to remove it, before grasping the target) and was run in two modalities: randomized and in blocks. Substantially, motor-related and sensory-and-motor neurons tested in the cVMTrandomized were activated already during the first grasping motor act, but the selectivity for one of the two graspable targets emerged only during the execution of the second grasping. In contrast, when the cVMT was run in block, almost all these neurons not only discharged during the first grasping motor act, but also displayed the same target selectivity showed in correspondence of the hand contact with the target. Observation Task (OT). A great part of the neurons active during the OT showed a firing rate modulation in correspondence with the action performed by the experimenter. Among them, we found neurons significantly activated during the observation of the experimenter’s action (action observation-related neurons) and neurons responding not only to the action observation, but also to the presented cue stimuli (sensory-and-action observation-related neurons. Among the neurons of the first set, almost the half displayed a target selectivity, with a not clear difference between the two presented targets; Concerning to the second neuronal set, sensory-and-action related neurons, we found a low target selectivity and a not strictly congruence between the selectivity exhibited in the visual response and in the action observation.

Modelagem de sinais neuronais utilizando filtros lineares de tempo discreto.

A aquisição experimental de sinais neuronais é um dos principais avanços da neurociência. Por meio de observações da corrente e do potencial elétricos em uma região cerebral, é possível entender os processos fisiológicos envolvidos na geração do potencial de ação, e produzir modelos matemáticos capazes de simular o comportamento de uma célula neuronal. Uma prática comum nesse tipo de experimento é obter leituras a partir de um arranjo de eletrodos posicionado em um meio compartilhado por diversos neurônios, o que resulta em uma mistura de sinais neuronais em uma mesma série temporal. Este trabalho propõe um modelo linear de tempo discreto para o sinal produzido durante o disparo do neurônio. Os coeficientes desse modelo são calculados utilizando-se amostras reais dos sinais neuronais obtidas in vivo. O processo de modelagem concebido emprega técnicas de identificação de sistemas e processamento de sinais, e é dissociado de considerações sobre o funcionamento biofísico da célula, fornecendo uma alternativa de baixa complexidade para a modelagem do disparo neuronal. Além disso, a representação por meio de sistemas lineares permite idealizar um sistema inverso, cuja função é recuperar o sinal original de cada neurônio ativo em uma mistura extracelular. Nesse contexto, são discutidas algumas soluções baseadas em filtros adaptativos para a simulação do sistema inverso, introduzindo uma nova abordagem para o problema de separação de spikes neuronais.