Propagation Of Neural Activity Research Articles

Neural activity propagation in an unfolded hippocampal preparation with a penetrating micro-electrode array.

This protocol describes a method for preparing a new in vitro flat hippocampus preparation combined with a micro-machined array to map neural activity in the hippocampus. The transverse hippocampal slice preparation is the most common tissue preparation to study hippocampus electrophysiology. A longitudinal hippocampal slice was also developed in order to investigate longitudinal connections in the hippocampus. The intact mouse hippocampus can also be maintained in vitro because its thickness allows adequate oxygen diffusion. However, these three preparations do not provide direct access to neural propagation since some of the tissue is either missing or folded. The unfolded intact hippocampus provides both transverse and longitudinal connections in a flat configuration for direct access to the tissue to analyze the full extent of signal propagation in the hippocampus in vitro. In order to effectively monitor the neural activity from the cell layer, a custom made penetrating micro-electrode array (PMEA) was fabricated and applied to the unfolded hippocampus. The PMEA with 64 electrodes of 200 µm in height could record neural activity deep inside the mouse hippocampus. The unique combination of an unfolded hippocampal preparation and the PMEA provides a new in-vitro tool to study the speed and direction of propagation of neural activity in the two-dimensional CA1-CA3 regions of the hippocampus with a high signal to noise ratio.

Activity Propagation in a Network of Coincidence-Detecting Neurons

This paper presents a formal analytical description of activity propagation in a simple multilayer network of coincidence-detecting neuron models receiving and generating Poisson spike trains. Simulations are also presented. In feedforward networks of coincidence-detecting neurons, the average firing rate decreases layer by layer, until information disappears. To prevent this, the model assumes that all neurons exhibit self-sustained firing, at a preset rate, initiated by the recognition of local features of the stimulus. Such firing can be interpreted as a form of local short-term memory. Inhibitory feedback signals from higher layers are then included in the model to minimize the duration of sustained firing, while ensuring information propagation. The theory predicts the time-dependent firing probability in successive layers and can be used to fit experimental data. The analyzed multilayer neural network exhibits stochastic propagation of neural activity. Such propagation has interesting features, such as information delocalization, that could explain backward masking. Stochastic propagation is normally observed in simulations of networks of spiking neurons. One of the contributions of this paper is to offer a method for formalizing and quantifying such effects, albeit in a simplified system. The mathematical analysis produces expressions for latencies in successive layers in dependence of the number of inputs of a neuron, the level of sustained firing, and the onset time jitter in the first layer of the network. In this model, latencies are not caused by the neuronal integration time, but by the waiting time before a coincidence of input spikes occurs. Numerical evaluation indicates that the retinal jitter may make a major contribution to inter-layer visual latencies. This could be confirmed experimentally. An interesting feature of the model is its potential to describe, within a single framework, a number of apparently unrelated characteristics of visual information processing, such as latencies, backward masking, synchronization, and temporal pattern of post-stimulus histograms. Due to its simplicity, the model can easily be understood, refined, and extended. This work has its origins in the nineties, but modeling latencies and firing probabilities in realistic biological systems is still an unsolved problem.

Long-range neural activity evoked by premotor cortex stimulation: a TMS/EEG co-registration study

The premotor cortex is one of the fundamental structures composing the neural networks of the human brain. It is implicated in many behaviors and cognitive tasks, ranging from movement to attention and eye-related activity. Therefore, neural circuits that are related to premotor cortex have been studied to clarify their connectivity and/or role in different tasks. In the present work, we aimed to investigate the propagation of the neural activity evoked in the dorsal premotor cortex using transcranial magnetic stimulation/electroencephalography (TMS/EEG). Toward this end, interest was focused on the neural dynamics elicited in long-ranging temporal and spatial networks. Twelve healthy volunteers underwent a single-pulse TMS protocol in a resting condition with eyes closed, and the evoked activity, measured by EEG, was compared to a sham condition in a time window ranging from 45 ms to about 200 ms after TMS. Spatial and temporal investigations were carried out with sLORETA. TMS was found to induce propagation of neural activity mainly in the contralateral sensorimotor and frontal cortices, at about 130 ms after delivery of the stimulus. Different types of analyses showed propagated activity also in posterior, mainly visual, regions, in a time window between 70 and 130 ms. Finally, a likely “rebounding” activation of the sensorimotor and frontal regions, was observed in various time ranges. Taken together, the present findings further characterize the neural circuits that are driven by dorsal premotor cortex activation in healthy humans.

Neuronal avalanches, epileptic quakes and other transient forms of neurodynamics

Power-law behaviors in brain activity in healthy animals, in the form of neuronal avalanches, potentially benefit the computational activities of the brain, including information storage, transmission and processing. In contrast, power-law behaviors associated with seizures, in the form of epileptic quakes, potentially interfere with the brain's computational activities. This review draws attention to the potential roles played by homeostatic mechanisms and multistable time-delayed recurrent inhibitory loops in the generation of power-law phenomena. Moreover, it is suggested that distinctions between health and disease are scale-dependent. In other words, what is abnormal and defines disease it is not the propagation of neural activity but the propagation of activity in a neural population that is large enough to interfere with the normal activities of the brain. From this point of view, epilepsy is a disease that results from a failure of mechanisms, possibly located in part in the cortex itself or in the deep brain nuclei and brainstem, which truncate or otherwise confine the spatiotemporal scales of these power-law phenomena.

Neural mechanism of activity spread in the cat motor cortex and its relation to the intrinsic connectivity

Motor cortical points are linked by intrinsic horizontal connections having a recurrent network topology. However, it is not known whether neural activity can propagate over the area covered by these intrinsic connections and whether there are spatial anisotropies of synaptic strength, as opposed to synaptic density. Moreover, the mechanisms by which activity spreads have yet to be determined. To address these issues, an 8 × 8 microelectrode array was inserted in the forelimb area of the cat motor cortex (MCx). The centre of the array had a laser etched hole ∼500 μm in diameter. A microiontophoretic pipette, with a tip diameter of 2-3 μm, containing bicuculline methiodide (BIC) was inserted in the hole and driven to a depth of 1200-1400 μm from the cortical surface. BIC was ejected for ∼2min from the tip of the micropipette with positive direct current ranging between 20 and 40 nA in different experiments. This produced spontaneous nearly periodic bursts (0.2-1.0 Hz) of multi-unit activity in a radius of about 400 μm from the tip of the micropipette. The bursts of neural activity spread at a velocity of 0.11-0.24 ms⁻¹ (mean=0.14 mm ms⁻¹, SD=0.05)with decreasing amplitude.The area activated was on average 7.22 mm² (SD=0.91 mm²), or ∼92% of the area covered by the recording array. The mode of propagation was determined to occur by progressive recruitment of cortical territory, driven by a central locus of activity of some 400 μm in radius. Thus, activity did not propagate as a wave. Transection of the connections between the thalamus and MCx did not significantly alter the propagation velocity or the size of the recruited area, demonstrating that the bursts spread along the routes of intrinsic cortical connectivity. These experiments demonstrate that neural activity initiated within a small motor cortical locus (≤ 400 μm in radius) can recruit a relatively large neighbourhood in which a variety of muscles acting at several forelimb joints are represented. These results support the hypothesis that the MCx controls the forelimb musculature in an integrated and anticipatory manner based on a recurrent network topology

Signal propagation in feedforward neuronal networks with unreliable synapses

In this paper, we systematically investigate both the synfire propagation and firing rate propagation in feedforward neuronal network coupled in an all-to-all fashion. In contrast to most earlier work, where only reliable synaptic connections are considered, we mainly examine the effects of unreliable synapses on both types of neural activity propagation in this work. We first study networks composed of purely excitatory neurons. Our results show that both the successful transmission probability and excitatory synaptic strength largely influence the propagation of these two types of neural activities, and better tuning of these synaptic parameters makes the considered network support stable signal propagation. It is also found that noise has significant but different impacts on these two types of propagation. The additive Gaussian white noise has the tendency to reduce the precision of the synfire activity, whereas noise with appropriate intensity can enhance the performance of firing rate propagation. Further simulations indicate that the propagation dynamics of the considered neuronal network is not simply determined by the average amount of received neurotransmitter for each neuron in a time instant, but also largely influenced by the stochastic effect of neurotransmitter release. Second, we compare our results with those obtained in corresponding feedforward neuronal networks connected with reliable synapses but in a random coupling fashion. We confirm that some differences can be observed in these two different feedforward neuronal network models. Finally, we study the signal propagation in feedforward neuronal networks consisting of both excitatory and inhibitory neurons, and demonstrate that inhibition also plays an important role in signal propagation in the considered networks.

Potassium diffusive coupling in neural networks

Conventional neural networks are characterized by many neurons coupled together through synapses. The activity, synchronization, plasticity and excitability of the network are then controlled by its synaptic connectivity. Neurons are surrounded by an extracellular space whereby fluctuations in specific ionic concentration can modulate neuronal excitability. Extracellular concentrations of potassium ([K(+)](o)) can generate neuronal hyperexcitability. Yet, after many years of research, it is still unknown whether an elevation of potassium is the cause or the result of the generation, propagation and synchronization of epileptiform activity. An elevation of potassium in neural tissue can be characterized by dispersion (global elevation of potassium) and lateral diffusion (local spatial gradients). Both experimental and computational studies have shown that lateral diffusion is involved in the generation and the propagation of neural activity in diffusively coupled networks. Therefore, diffusion-based coupling by potassium can play an important role in neural networks and it is reviewed in four sections. Section 2 shows that potassium diffusion is responsible for the synchronization of activity across a mechanical cut in the tissue. A computer model of diffusive coupling shows that potassium diffusion can mediate communication between cells and generate abnormal and/or periodic activity in small (section sign 3) and in large networks of cells (section sign 4). Finally, in section sign 5, a study of the role of extracellular potassium in the propagation of axonal signals shows that elevated potassium concentration can block the propagation of neural activity in axonal pathways. Taken together, these results indicate that potassium accumulation and diffusion can interfere with normal activity and generate abnormal activity in neural networks.

Cortical Dynamics of Anticipatory Mechanisms in Interception: A Neuromagnetic Study

Humans demonstrate an amazing ability for intercepting and catching moving targets, most noticeably in fast-speed ball games. However, the few studies exploring the neural bases of interception in humans and the classical studies on visual motion processing and visuomotor interactions have reported rather long latencies of cortical activations that cannot explain the performances observed in most natural interceptive actions. The aim of our experiment was twofold: (1) describe the spatio-temporal unfolding of cortical activations involved in catching a moving target and (2) provide evidence that fast cortical responses can be elicited by a visuomotor task with high temporal constraints and decide if these responses are task or stimulus dependent. Neuromagnetic brain activity was recorded with whole-head coverage while subjects were asked to catch a free-falling ball or simply pay attention to the ball trajectory. A fast, likely stimulus-dependent, propagation of neural activity was observed along the dorsal visual pathway in both tasks. Evaluation of latencies of activations in the main cortical regions involved in the tasks revealed that this entire network of regions was activated within 40 msec. Moreover, comparison of experimental conditions revealed similar patterns of activation except in contralateral sensorimotor regions where common and catch-specific activations were differentiated.

Combined EEG-fMRI and tractography to visualise propagation of epileptic activity

In a patient with refractory temporal lobe epilepsy, EEG-fMRI showed activation in association with left anterior temporal interictal discharges, in the left temporal, parietal and occipital lobes. Dynamic causal modelling...

Variability and Corresponding Amplitude–Velocity Relation of Activity Propagating in One-Dimensional Neural Cultures

We investigate the propagation of neural activity along one-dimensional rat hippocampal cultures patterned in lines over multielectrode arrays. Activity occurs spontaneously or is evoked by local electrical or chemical stimuli, with different resulting propagation velocities and firing rate amplitudes. A variability of an order of magnitude in velocity and amplitude is observed in spontaneous activity. A linear relation between velocity and amplitude is identified. We define a measure for neuron activation synchrony and find that it correlates with front velocity and is higher for electrically evoked fronts. We present a model that explains the linear relation between amplitude and velocity, which highlights the role of synchrony. The relation to current models for signal propagation in neural media is discussed.

Lagged covariance structure models for studying functional connectivity in the brain

Most cognitive processes are supported by large networks of brain regions. To describe the operation of these networks, it is critical to understand how individual areas are functionally connected. Here, we establish a statistical framework for studying effective and functional brain connectivity, using data obtained with a relatively new neuroimaging method, the event-related optical signal (EROS). The novelty of our approach is the use of timing information (in the form of lagged cross-correlations) in interpreting the connections between areas. Interpretation of lagged cross-correlations exploits the combination of spatial and temporal resolution provided by EROS. In this paper, we apply dynamic factor analysis as a method for testing various structural models on the lagged covariance matrices derived from the EROS data. We first illustrate the approach by testing a simple path model of neural activity propagation from area V1 to V3 in a visual stimulation task. We then build more complex structural equation models with latent variables, describing both within-hemisphere integrity, and interactions between the two hemispheres, to interpret data from a second task involving inter-hemispheric competition. The results demonstrate how the integrity of anatomical connections between the two hemispheres explains different patterns of cross-hemispheric interactions. This approach allows for fitting brain imaging data to complex models that capture dynamic cognitive processes as they rapidly evolve over time.

A Biological Inspired Approach to Collision-Free Path Planning and Tracking Control of a Mobile Robot

In this paper, a novel biologically inspired neural network approach is proposed for real-time collision-free path planning and tracking control of a nonholonomic mobile robot in a dynamic environment. The real-time collision-free robot trajectory is generated by a topologically organized neural network, where the dynamics of each neuron is characterized by a shunting equation derived from Hodgkin and Huxley’s biological membrane equation. The dynamically changing environment is represented by the dynamic activity landscape of the neural network, where the neural activity propagation is subject to the nonholonomic kinematic constraint of the mobile robot. The tracking velocities for the mobile robot are generated by a novel neural dynamics based controller, which is based on two shunting equations and the conventional backstepping technique. Unlike the conventional backstepping controllers suffer from sharp jumps, the proposed tracking controller can generate smooth and continuous commands. The effectiveness and efficiency of the proposed approach are demonstrated through simulation and comparison studies.

Fast Propagation of Firing Rates through Layered Networks of Noisy Neurons

We model the propagation of neural activity through a feedforward network consisting of layers of integrate-and-fire neurons. In the presence of a noisy background current and spontaneous background firing, firing rate modulations are transmitted linearly through many layers, with a delay proportional to the synaptic time constant and with little distortion. Single neuron properties and firing statistics are in agreement with physiological data. The proposed mode of propagation allows for fast computation with population coding based on firing rates, as is demonstrated with a local motion detector.

An experimental study on the course of trans-synaptic propagation of neural activity and plasticity in the hippocampus in kainate-induced epilepsy

To investigate the course of trans-synaptic propagation of neural activity and plasticity in temporal lobe epilepsy, time-dependent changes in the level of synapsin I, a synaptic vesicle protein that is a marker of enhanced synaptic activity and synaptogenesis, were examined following kainate-induced epileptic status in rats. Compared with the control, the level of synapsin I protein increased in the bilateral stratum oriens of CA3 (28.8–40.2%) and CA1 (28.0–34.6%), and the stratum radiatum of CA1 (34.0%) ipsilateral to the injection site at 8 h after intra-amygdala administration of kainate. At 24 h, and 2 and 4 weeks after the kainate treatment, however, synapsin I levels returned to normal levels in most of the regions studied in spite of the extended neural loss in the hippocampus, which suggested the axonal sprouting on the remaining cells. The synapsin I mRNA levels time-dependently decreased bilaterally in CA1–CA3 and the hilus, while no significant changes were observed in the dentate gyrus. These results suggest that the synaptic input to CA3 and CA1 through the stratum oriens was enhanced in this model. A different mode of hippocampal neural activity and plasticity between kainate and kindling models of epilepsy may be stressed.

Beta-frequency (15–35 Hz) electroencephalogram activities elicited by toluene and electrical stimulation in the behaving rat

Bursts of beta-frequency (15–35 Hz) electroencephalogram activity occur in the olfactory system during odour sampling, but their mode of propagation within the olfactory system and potential contribution to the mechanisms of learning and memory are unclear. We have elicited large-amplitude beta activity in the rat olfactory system by applying noxious olfactory stimuli (toluene), and have monitored the bursts via chronically-implanted electrodes. Following exposure to toluene, coherent bursts with a peak frequency of 19.8±0.9 Hz were observed in the olfactory bulb, piriform cortex, entorhinal cortex and dentate gyrus. The timing of the bursts and the phases of electroencephalogram cross-spectra indicate that beta bursts propagate in a caudal direction from the olfactory bulb to the entorhinal cortex. The time delays between peaks of bursts in these structures were similar to latency differences for field potentials evoked by olfactory bulb or piriform cortex test-pulses. Peaks of burst cycles in the dentate region, however, were observed just prior to those in the entorhinal cortex. Surprisingly, power in toluene-induced beta-frequency oscillations was not increased following long-term potentiation induced by tetanic stimulation of the olfactory bulb, piriform cortex and entorhinal cortex. The activity of local inhibitory mechanisms may therefore counteract the effects of synaptic enhancements in afferent pathways during beta bursts. Low-frequency electrical stimulation of the piriform cortex was most effective in inducing coherent oscillatory responses in the entorhinal cortex and dentate gyrus at stimulation frequencies between 12 and 16 Hz. The results show that repetitive polysynaptic volleys at frequencies in the beta band induced by either toluene or electrical stimulation are transmitted readily within the olfactory system. The propagation of neural activity within this frequency range may therefore contribute to the transmission of olfactory signals to the hippocampal formation, particularly for those odours which induce high-amplitude bursts of beta activity.

A neural network predicting posterior parietal cortex function in the control of goal-directed arm movements

A neural network is developed to explain the intriguing pattern of pointing movement deficits observed previously in monkeys after small cortical parietal Area 7 lesions. It postulates the existence of major routes for neural activity propagation from the sensory to the motor cortex, and of separate routes for “intention-coding” activity which controls the sensory-motor propagation. The postulated network is held against a variety of neuroanatomical, electrophysiological, and lesion studies of Area 7, and its compliance with those data supports its validity.