Lévy noise-induced inverse stochastic resonance on Newman–Watts networks of Hodgkin–Huxley neurons

This paper primarily investigates the inverse stochastic resonance (ISR) of neuron network driven by Lévy noise with electrical autapse and chemical autapse, respectively. Firstly, the discharge of Hodgkin–Huxley (HH) neuron network under different noise parameters, autapse parameters and network coupling strength is shown. Then, the variation of average firing rate with Lévy noise in the case of electrical autapse and chemical autapse is presented. We find that there exists a minimum value of the average firing rate curve caused by stability index and noise intensity of Lévy noise across the whole network, which is the phenomenon of ISR. With the increase of autaptic intensity and coupling strength, the ISR inhibitory effect of neuron discharge is weakened. In addition, with the increase of coupling strength, the neuron discharge of neural network is more intense and regular. As a consequence, our work suggests that autaptic intensity and coupling efficient of neuronal network can regulate the neuronal firing activities and suppress the effect of ISR, and Lévy noise can induce ISR phenomenon in Newman–Watts neuronal network.

Hidden Markov Models Predict the Future Choice Better Than a PSTH-Based Method

Beyond average firing rate, other measurable signals of neuronal activity are fundamental to an understanding of behavior. Recently, hidden Markov models (HMMs) have been applied to neural recordings and have described how neuronal ensembles process information by going through sequences of different states. Such collective dynamics are impossible to capture by just looking at the average firing rate. To estimate how well HMMs can decode information contained in single trials, we compared HMMs with a recently developed classification method based on the peristimulus time histogram (PSTH). The accuracy of the two methods was tested by using the activity of prefrontal neurons recorded while two monkeys were engaged in a strategy task. In this task, the monkeys had to select one of three spatial targets based on an instruction cue and on their previous choice. We show that by using the single trial's neural activity in a period preceding action execution, both models were able to classify the monkeys' choice with an accuracy higher than by chance. Moreover, the HMM was significantly more accurate than the PSTH-based method, even in cases in which the HMM performance was low, although always above chance. Furthermore, the accuracy of both methods was related to the number of neurons exhibiting spatial selectivity within an experimental session. Overall, our study shows that neural activity is better described when not only the mean activity of individual neurons is considered and that therefore, the study of other signals rather than only the average firing rate is fundamental to an understanding of the dynamics of neuronal ensembles.

The superior colliculus and the steering of saccades toward a moving visual target

ABSTRACTFollowing the suggestion that a command encoding the expected here-and-now target location feeds the oculomotor system during interceptive saccades, we tested whether this command originates in the deep superior colliculus (SC). Monkeys generated saccades to targets that were static or moving along the preferred axis, away from (outward) or toward a fixated target (inward) with a constant speed (20°/s). Vertical and horizontal motions were also tested. Extracellular activity of 57 saccade-related neurons was recorded in 3 monkeys. The movement field (MF) parameters (boundaries, center and firing rate) were estimated after spline fitting the relation between the saccade amplitude and the average firing rate of the motor burst. During radial motion, the inner MF boundary shifted in the same direction as the target motion for some neurons, not all. During vertical motion, both lower and upper boundaries were shifted upward during upward motion whereas the upper boundary only shifted during downward motions. For horizontal motions, the medial boundaries were not changed. The MF center was shifted only for outward motion. Regardless of the motion direction, the average firing rate was consistently reduced during interceptive saccades. Our study shows an involvement of the saccade-related burst of SC neurons in steering the gaze toward a moving target. When observed, the shifts of MF boundary in the direction of target motion correspond to commands related to antecedent target locations. The absence of shift in the opposite direction shows that SC activity does not issue predictive commands related to the future target location.SIGNIFICANCE STATEMENTBy comparing the movement field (MF) of saccade-related neurons between saccades toward static and moving targets, we show that the motor burst issued by neurons in the superior colliculus does not convey commands related to the future location of a moving target. During interceptive saccades, the active population consists of a continuum of neurons, ranging from cells exhibiting a shift in the center or boundary of their MF to cells which exhibit no change. The shifts correspond to residual activity related to the fact that the active population does not change as fast as the target in the visual field. By contrast, the absence of shift indicates commands related to the current target location, as if it were static.

Neural Ensemble Coding during Working Memory Task in Rat Prefrontal Cortex

Working memory is one of important cognitive functions and recent studies demonstrate that prefrontal cortex plays an important role in working memory. But the issue that how neural activity encodes during working memory task is still a question that lies at the heart of cognitive neuroscience. The aim of this study is to investigate neural ensemble coding mechanism via average firing rate during working memory task. Neural population activity was measured simultaneously from multiple electrodes placed in prefrontal cortex while rats were performing a working memory task in Y-maze. Then the original data was filtered by a high-pass filtering, spike detection and spike sorting, spatio-temporal trains of neural population were ultimately obtained. Then, the average firing rates were computed in a selected window (500ms) with a moving step (125ms). The results showed that the average firing rate were higher during workinig memory task, along with obvious ensemble activity. Conclusion: The results indicate that the working memory information is encoded with neural ensemble activity.

Role of the Primate Superior Colliculus in the Control of Head Movements

One important behavioral role for head movements is to assist in the redirection of gaze. However, primates also frequently make head movements that do not involve changes in the line of sight. Virtually nothing is known about the neural basis of these head-only movements. In the present study, single-unit extracellular activity was recorded from the superior colliculus while monkeys performed behavioral tasks that permit the temporal dissociation of gaze shifts and head movements. We sought to determine whether superior colliculus contains neurons that modulate their activity in association with head movements in the absence of gaze shifts and whether classic gaze-related burst neurons also discharge for head-only movements. For 26% of the neurons in our sample, significant changes in average firing rate could be attributed to head-only movements. Most of these increased their firing rate immediately prior to the onset of a head movement and continued to discharge at elevated frequency until the offset of the movement. Others discharged at a tonic rate when the head was stable and decreased their activity, or paused, during head movements. For many putative head cells, average firing rate was found to be predictive of head displacement. Some neurons exhibited significant changes in activity associated with gaze, eye-only, and head-only movements, although none of the gaze-related burst neurons significantly modulated its activity in association with head-only movements. These results suggest the possibility that the superior colliculus plays a role in the control of head movements independent of gaze shifts.

Temporal Damping in Response to Broadband Noise. I. Inferior Colliculus

Many cells in the inferior colliculus (IC) are sensitive to interaural time differences (ITDs), in the form of an oscillatory dependency of average firing rate on ITD. We studied the degree of damping in such binaural responses, recording from neurons in the inferior colliculus of pentobarbital-anesthetized cats to binaural broadband noise and tones. Noise-delay functions and composite curves were characterized by computing the difference between responses to correlated and anticorrelated stimuli. We use a new metric, based on the envelope of this difference, to quantify damping. There is a clear relationship between damping and characteristic frequency (CF), but even neurons of the same CF can differ in their damping. For individual cells, damping can be stronger to tones or to noise; at the population level the two are positively correlated and are scarcely affected by SPL. The frequencies that dominate ITD sensitivity are near the CF in response to noise, but are often below CF in response to tones. These findings qualify conclusions from earlier reports but overall they support the conclusion that, at a population level, basic aspects of binaural responses to wideband noise are consistent with summed responses to pure tones.

Integrate-and-Fire Neurons Driven by Correlated Stochastic Input

Neurons are sensitive to correlations among synaptic inputs. However, analytical models that explicitly include correlations are hard to solve analytically, so their influence on a neuron's response has been difficult to ascertain. To gain some intuition on this problem, we studied the firing times of two simple integrate-and-fire model neurons driven by a correlated binary variable that represents the total input current. Analytic expressions were obtained for the average firing rate and coefficient of variation (a measure of spike-train variability) as functions of the mean, variance, and correlation time of the stochastic input. The results of computer simulations were in excellent agreement with these expressions. In these models, an increase in correlation time in general produces an increase in both the average firing rate and the variability of the output spike trains. However, the magnitude of the changes depends differentially on the relative values of the input mean and variance: the increase in firing rate is higher when the variance is large relative to the mean, whereas the increase in variability is higher when the variance is relatively small. In addition, the firing rate always tends to a finite limit value as the correlation time increases toward infinity, whereas the coefficient of variation typically diverges. These results suggest that temporal correlations may play a major role in determining the variability as well as the intensity of neuronal spike trains.

Synchrony in Heterogeneous Networks of Spiking Neurons

The emergence of synchrony in the activity of large, heterogeneous networks of spiking neurons is investigated. We define the robustness of synchrony by the critical disorder at which the asynchronous state becomes linearly unstable. We show that at low firing rates, synchrony is more robust in excitatory networks than in inhibitory networks, but excitatory networks cannot display any synchrony when the average firing rate becomes too high. We introduce a new regime where all inputs, external and internal, are strong and have opposite effects that cancel each other when averaged. In this regime, the robustness of synchrony is strongly enhanced, and robust synchrony can be achieved at a high firing rate in inhibitory networks. On the other hand, in excitatory networks, synchrony remains limited in frequency due to the intrinsic instability of strong recurrent excitation.