Death and rebirth of neural activity in sparse inhibitory networks

In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of the neural activity, as expected, but it can also promote neural reactivation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition (neurons' death). However, the random pruning of the connections is able to reverse the action of inhibition, i.e. in a sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of the neurons (neurons' rebirth). Thus the number of firing neurons reveals a minimum at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by the neurons with higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving an analytic mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, the system passes from a perfectly regular evolution to an irregular bursting dynamics. In this latter regime the model provides predictions consistent with experimental findings for a specific class of neurons, namely the medium spiny neurons in the striatum.Comment: 19 pages, 10 figures, submitted to NJ

Cell assembly dynamics of sparsely-connected inhibitory networks: a simple model for the collective activity of striatal projection neurons

Striatal projection neurons form a sparsely-connected inhibitory network, and this arrangement may be essential for the appropriate temporal organization of behavior. Here we show that a simplified, sparse inhibitory network of Leaky-Integrate-and-Fire neurons can reproduce some key features of striatal population activity, as observed in brain slices [Carrillo-Reid et al., J. Neurophysiology 99 (2008) 1435{1450]. In particular we develop a new metric to determine the conditions under which sparse inhibitory networks form anti-correlated cell assemblies with time-varying activity of individual cells. We found that under these conditions the network displays an input-specific sequence of cell assembly switching, that effectively discriminates similar inputs. Our results support the proposal [Ponzi and Wickens, PLoS Comp Biol 9 (2013) e1002954] that GABAergic connections between striatal projection neurons allow stimulus-selective, temporally-extended sequential activation of cell assemblies. Furthermore, we help to show how altered intrastriatal GABAergic signaling may produce aberrant network-level information processing in disorders such as Parkinson's and Huntington's diseases.Comment: 22 pages, 9 figure

Inhibitory synchrony as a mechanism for attentional gain modulation

Recordings from area V4 of monkeys have revealed that when the focus of attention is on a visual stimulus within the receptive field of a cortical neuron, two distinct changes can occur: The firing rate of the neuron can change and there can be an increase in the coherence between spikes and the local field potential in the gamma-frequency range (30-50 Hz). The hypothesis explored here is that these observed effects of attention could be a consequence of changes in the synchrony of local interneuron networks. We performed computer simulations of a Hodgkin-Huxley type neuron driven by a constant depolarizing current, I, representing visual stimulation and a modulatory inhibitory input representing the effects of attention via local interneuron networks. We observed that the neuron's firing rate and the coherence of its output spike train with the synaptic inputs was modulated by the degree of synchrony of the inhibitory inputs. The model suggest that the observed changes in firing rate and coherence of neurons in the visual cortex could be controlled by top-down inputs that regulated the coherence in the activity of a local inhibitory network discharging at gamma frequencies.Comment: J.Physiology (Paris) in press, 11 figure

Static and dynamic properties of synaptic transmission at the cyto-neural junction of frog labyrinth posterior canal

The properties of synaptic transmission have been studied at the cyto-neural junction of the frog labyrinth posterior canal by examining excitatory postsynaptic potential (EPSP) activity recorded intraaxonally from the afferent nerve after abolishing spike firing by tetrodotoxin. The waveform, amplitude, and rate of occurrence of the EPSPs have been evaluated by means of a procedure of fluctuation analysis devised to continuously monitor these parameters, at rest as well as during stimulation of the semicircular canal by sinusoidal rotation at 0.1 Hz, with peak accelerations ranging from 8 to 87 deg.s-2. Responses to excitatory and inhibitory accelerations were quantified in terms of maximum and minimum EPSP rates, respectively, as well as total numbers of EPSPs occurring during the excitatory and inhibitory half cycles. Excitatory responses were systematically larger than inhibitory ones (asymmetry). Excitatory responses were linearly related either to peak acceleration or to its logarithm, and the same occurred for inhibitory responses. In all units examined, the asymmetry of the response yielded nonlinear two-sided input-output intensity functions. Silencing of EPSPs during inhibition (rectification) was never observed. Comparison of activity during the first cycle of rotation with the average response over several cycles indicated that variable degrees of adaptation (up to 48%) characterize the excitatory response, whereas no consistent adaptation was observed in the inhibitory response. All fibers appeared to give responses nearly in phase with angular velocity, at 0.1 Hz, although the peak rates generally anticipated by a few degrees the peak angular velocity. From the data presented it appears that asymmetry, adaptation, and at least part of the phase lead in afferent nerve response are of presynaptic origin, whereas rectification and possible further phase lead arise at the encoder. To confirm these conclusions a simultaneous though limited study of spike firing and EPSP activity has been attempted in a few fibers

Decorrelation of neural-network activity by inhibitory feedback

Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural networks is common presynaptic input to pairs of neurons. Recent theoretical and experimental studies demonstrate that spike correlations in recurrent neural networks are considerably smaller than expected based on the amount of shared presynaptic input. By means of a linear network model and simulations of networks of leaky integrate-and-fire neurons, we show that shared-input correlations are efficiently suppressed by inhibitory feedback. To elucidate the effect of feedback, we compare the responses of the intact recurrent network and systems where the statistics of the feedback channel is perturbed. The suppression of spike-train correlations and population-rate fluctuations by inhibitory feedback can be observed both in purely inhibitory and in excitatory-inhibitory networks. The effect is fully understood by a linear theory and becomes already apparent at the macroscopic level of the population averaged activity. At the microscopic level, shared-input correlations are suppressed by spike-train correlations: In purely inhibitory networks, they are canceled by negative spike-train correlations. In excitatory-inhibitory networks, spike-train correlations are typically positive. Here, the suppression of input correlations is not a result of the mere existence of correlations between excitatory (E) and inhibitory (I) neurons, but a consequence of a particular structure of correlations among the three possible pairings (EE, EI, II)

Physiological sharp wave-ripples and interictal events in vitro: What’s the difference?

Sharp wave-ripples and interictal events are physiological and pathological forms of transient high activity in the hippocampus with similar features. Sharp wave-ripples have been shown to be essential in memory consolidation, while epileptiform (interictal) events are thought to be damaging. It is essential to grasp the difference between physiological sharp wave-ripples and pathological interictal events in order to understand the failure of control mechanisms in the latter case. We investigated the dynamics of activity generated intrinsically in the CA3 region of the mouse hippocampus in vitro, using four different types of intervention to induce epiletiform activity. As a result, sharp wave-ripples spontaneously occurring in CA3 disappeared, and following an asynchronous transitory phase, activity reorganized into a new form of pathological synchrony. During epileptiform events, all neurons increased their firing rate compared to sharp wave-ripples. Different cell types showed complementary firing: parvalbumin-positive basket cells and some axo-axonic cells stopped firing due to a depolarization block at the climax of the events in high potassium, 4-aminopyridine and zero magnesium models, but not in the gabazine model. In contrast, pyramidal cells started firing maximally at this stage. To understand the underlying mechanism we measured changes of intrinsic neuronal and transmission parameters in the high potassium model. We found that the cellular excitability increased and excitatory transmission was enhanced, whereas inhibitory transmission was compromised. We observed a strong short-term depression in parvalbumin-positive basket cell to pyramidal cell transmission. Thus, the collapse of pyramidal cell perisomatic inhibition appears to be a crucial factor in the emergence of epileptiform events

Phase transitions in single neurons and neural populations: Critical slowing, anesthesia, and sleep cycles

The firing of an action potential by a biological neuron represents a dramatic transition from small-scale linear stochastics (subthreshold voltage fluctuations) to gross-scale nonlinear dynamics (birth of a 1-ms voltage spike). In populations of neurons we see similar, but slower, switch-like there-and-back transitions between low-firing background states and high-firing activated states. These state transitions are controlled by varying levels of input current (single neuron), varying amounts of GABAergic drug (anesthesia), or varying concentrations of neuromodulators and neurotransmitters (natural sleep), and all occur within a milieu of unrelenting biological noise. By tracking the altering responsiveness of the excitable membrane to noisy stimulus, we can infer how close the neuronal system (single unit or entire population) is to switching threshold. We can quantify this “nearness to switching” in terms of the altering eigenvalue structure: the dominant eigenvalue approaches zero, leading to a growth in correlated, low-frequency power, with exaggerated responsiveness to small perturbations, the responses becoming larger and slower as the neural population approaches its critical point–-this is critical slowing. In this chapter we discuss phase-transition predictions for both single-neuron and neural-population models, comparing theory with laboratory and clinical measurement

ATP-Sensitive Potassium Channel-Mediated Lactate Effect on Orexin Neurons: Implications for Brain Energetics during Arousal

Active neurons have a high demand for energy substrate, which is thought to be mainly supplied as lactate by astrocytes. Heavy lactate dependence of neuronal activity suggests that there may be a mechanism that detects and controls lactate levels and/or gates brain activation accordingly. Here, we demonstrate that orexin neurons can behave as such lactate sensors. Using acute brain slice preparations and patch-clamp techniques, we show that the monocarboxylate transporter blocker α-cyano-4-hydroxycinnamate (4-CIN) inhibits the spontaneous activity of orexin neurons despite the presence of extracellular glucose. Furthermore, fluoroacetate, a glial toxin, inhibits orexin neurons in the presence of glucose but not lactate. Thus, orexin neurons specifically use astrocyte-derived lactate. The effect of lactate on firing activity is concentration dependent, an essential characteristic of lactate sensors. Furthermore, lactate disinhibits and sensitizes these neurons for subsequent excitation. 4-CIN has no effect on the activity of some arcuate neurons, indicating that lactate dependency is not universal. Orexin neurons show an indirect concentration-dependent sensitivity to glucose below 1mM, responding by hyperpolarization, which is mediated by ATP-sensitive potassium channels composed of Kir6.1 and SUR1 subunits. In conclusion, our study suggests that lactate is a critical energy substrate and a regulator of the orexin system. Together with the known effects of orexins in inducing arousal, food intake, and hepatic glucose production, as well as lactate release from astrocytes in response to neuronal activity, our study suggests that orexin neurons play an integral part in balancing brain activity and energy supply