Stimulation with a low-amplitude, digitized synaptic signal to invoke robust activity within neuronal networks on multielectrode arrays

Multielectrode arrays (MEAs) are used for analysis of neuronal activity. Here we report two variations on commonly accepted techniques that increase the precision of extracellular electrical stimulation: (i) the use of a low-amplitude recorded spontaneous synaptic signal as a stimulus waveform and (ii) the use of a specific electrode within the array adjacent to the stimulus electrode as a hard-grounded stimulus signal return path. Both modifications remained compatible with manipulation of neuronal networks. In addition, localized stimulation with the low-amplitude synaptic signal allowed selective stimulation or inhibition of otherwise spontaneous signals. These findings indicate that minimizing the area of the culture impacted by external stimulation allows modulation of signaling patterns within subpopulations of neurons in culture. The simple modifications described herein may be useful for precise monitoring and manipulation of neuronal networks.     

Orienting reflex: "targeting reaction" and "searchlight of attention"

The concept of orienting reflex based on the principle of vector coding of cognitive and executive processes is proposed. The orienting reflex to non-signal and signal stimuli is a set of orienting reactions: motor, autonomic, neuronal, and subjective emphasizing new and significant stimuli. Two basic mechanisms can be identified within the orienting reflex: a "targeting reaction" and a "searchlight of attention". In the visual system the first one consists in a foveation of a target stimulus. The foveation is performed with participation of premotor neurons excited by saccadic command neurons of the superior colliculi. The "searchlight of attention" is based on the resonance of gamma-oscillations in the reticular thalamus selectively enhancing responses of cortical neurons (involuntary attention). The novelty signal is generated in novelty neurons of the hippocampus, which are selectively tuned to a repeatedly presented standard stimulus. The selective tuning is caused by the depression of plastic synapses representing a "neuronal model" of the standard stimulus. A mismatch of the novel stimulus with the established neuronal model gives rise to a "novelty signal" enhancing the novel input. The novelty signal inhibits current conditioned reflexes (external inhibition) contributing to redirecting the behavior. By triggering the expression of early genes the novelty signal initiates the formation of the long-term memory connected with neoneurogenesis.     

关于耦合神经元活动时的能量原理

最近美国耶鲁大学的神经科学家们用实验数据表明,哺乳动物大脑皮层中神经信号的传递是一个代价昂贵的能量支出过程,而神经信号的编码是与能量代谢紧密地耦合在一起的,但是到目前为止还无法定量给出神经元活动时的能量函数。在这篇文章中,能量原理被用于神经活动和神经信息处理机制的研究,在电生理实验数据的基础上,建立神经元活动的用能量函数表示的运动方程。结果表明用能量函数表达耦合神经元的阈下电活动和动作电位,数值计算结果与用Hodgkin-Huxley方程所描述的动作电位一致。从而有可能依据能量原理从脑信息处理的角度揭示和理解大脑神经网络系统的信息表现规律。     

蜚蠊单个棘—钟形感器冲动发放的特性

本文分析了蜚镰后胸足单个棘一钟形感器对机械位移刺激的反应模式以及冲动发放的特性.结果证明该感器是一种适应较慢的相位性触觉感受器,对触刺激有相当稳定的反应.     

Exploring how extracellular electric field modulates neuron activity through dynamical analysis of a two-compartment neuron model

To investigate how extracellular electric field modulates neuron activity, a reduced two-compartment neuron model in the presence of electric field is introduced in this study. Depending on neuronal geometric and internal coupling parameters, the behaviors of the model have been studied extensively. The neuron model can exist in quiescent state or repetitive spiking state in response to electric field stimulus. Negative electric field mainly acts as inhibitory stimulus to the neuron, positive weak electric field could modulate spiking frequency and spike timing when the neuron is already active, and positive electric fields with sufficient intensity could directly trigger neuronal spiking in the absence of other stimulations. By bifurcation analysis, it is observed that there is saddle-node on invariant circle bifurcation, supercritical Hopf bifurcation and subcritical Hopf bifurcation appearing in the obtained two parameter bifurcation diagrams. The bifurcation structures and electric field thresholds for triggering neuron firing are determined by neuronal geometric and coupling parameters. The model predicts that the neurons with a nonsymmetric morphology between soma and dendrite, are more sensitive to electric field stimulus than those with the spherical structure. These findings suggest that neuronal geometric features play a crucial role in electric field effects on the polarization of neuronal compartments. Moreover, by determining the electric field threshold of our biophysical model, we could accurately distinguish between suprathreshold and subthreshold electric fields. Our study highlights the effects of extracellular electric field on neuronal activity from the biophysical modeling point of view. These insights into the dynamical mechanism of electric field may contribute to the investigation and development of electromagnetic therapies, and the model in our study could be further extended to a neuronal network in which the effects of electric fields on network activity may be investigated.     

Electrodynamic eigenmodes in cellular morphology

Eigenmodes of the spherical and ellipsoidal dielectric electromagnetic resonator have been analysed. The sizes and shape of the resonators have been chosen to represent the shape of the interphase and dividing animal cell. Electromagnetic modes that have shape exactly suitable for positioning of the sufficiently large organelles in cell (centrosome, nucleus) have been identified. We analysed direction and magnitude of dielectrophoretic force exerted on large organelles by electric field of the modes. We found that the TM(1m1) mode in spherical resonator acts by centripetal force which drags the large organelles which have higher permittivity than the cytosol to the center of the cell. TM-kind of mode in the ellipsoidal resonator acts by force on large polarizable organelles in a direction that corresponds to the movement of the centrosomes (also nucleus) observed during the cell division, i.e. to the foci of the ellipsoidal cell. Minimal required force (10(-16)N), gradient of squared electric field and corresponding energy (10(-16)J) of the mode have been calculated to have biological significance within the periods on the order of time required for cell division. Minimal required energy of the mode, in order to have biological significance, can be lower in the case of resonance of organelle with the field of the cellular resonator mode. In case of sufficient energy in the biologically relevant mode, electromagnetic field of the mode will act as a positioning or steering mechanism for centrosome and nucleus in the cell, thus contribute to the spatial and dynamical self-organization in biological systems.     

Microgravity dependence of excitable biological and physicochemical media

Neuronal tissue and especially the central nervous system (CNS) is an excitable medium. Self-organisation, pattern formation, and propagating excitation waves as typical characteristics in excitable media consequently have been found in neuronal tissue. The properties of such phenomena in excitable media do critically depend on the parameters (i.e., electromagnetic fields, temperature, chemical drugs) of the system and on small external forces to which gravity belongs. The spreading depression, a propagating excitation depression wave of neuronal activity, is one of the best described of the those wave phenomena in the CNS. Especially in the retina as a true part of the CNS it can be easily observed with optical techniques due to the high intrinsic optical signal of this tissue. Another of such waves in neuronal tissue is the propagating action potential in nerve fibres. In this paper, data from our laboratories concerning the influence of gravity on the velocity of propagating waves in excitable media are summarized mainly in terms of the retinal spreading depression and propagating action potentials. Additionally, we have used waves in gels of the Belousov-Zhabotinsky reaction as the physicochemical model system of biological activity as the properties of these waves follow the same theories as the spreading depression and action potentials and they have some striking similarities in wave behavior. Thus propagating Belousov-Zhabotinsky waves are described by their gravity dependence.     

The principle of coherence in multi-level brain information processing

Synchronisation has become one of the major scientific tools to explain biological order at many levels of organisation. In systems neuroscience, synchronised subthreshold and suprathreshold oscillatory neuronal activity within and between distributed neuronal assemblies is acknowledged as a fundamental mode of neuronal information processing. Coherent neuronal oscillations correlate with all basic cognitive functions, mediate local and long-range neuronal communication and affect synaptic plasticity. However, it remains unclear how the very fast and complex changes of functional neuronal connectivity necessary for cognition, as mediated by dynamic patterns of neuronal synchrony, could be explained exclusively based on the well-established synaptic mechanisms. A growing body of research indicates that the intraneuronal matrix, composed of cytoskeletal elements and their binding proteins, structurally and functionally connects the synapses within a neuron, modulates neurotransmission and memory consolidation, and is hypothesised to be involved in signal integration via electric signalling due to its charged surface. Theoretical modelling, as well as emerging experimental evidence indicate that neuronal cytoskeleton supports highly cooperative energy transport and information processing based on molecular coherence. We suggest that long-range coherent dynamics within the intra- and extracellular filamentous matrices could establish dynamic ordered states, capable of rapid modulations of functional neuronal connectivity via their interactions with neuronal membranes and synapses. Coherence may thus represent a common denominator of neurophysiological and biophysical approaches to brain information processing, operating at multiple levels of neuronal organisation, from which cognition may emerge as its cardinal manifestation.     

Modeling electromagnetic fields detectability in a HH-like neuronal system: stochastic resonance and window behavior

Noise has already been shown to play a constructive role in neuronal processing and reliability, according to stochastic resonance (SR). Here another issue is addressed, concerning noise role in the detectability of an exogenous signal, here representing an electromagnetic (EM) field. A Hodgkin–Huxley like neuronal model describing a myelinated nerve fiber is proposed and validated, excited with a suprathreshold stimulation. EM field is introduced as an additive voltage input and its detectability in neuronal response is evaluated in terms of the output signal-to-noise ratio. Noise intensities maximizing spiking activity coherence with the exogenous EM signal are clearly shown, indicating a stochastic resonant behavior, strictly connected to the model frequency sensitivity. In this study SR exhibits a window of occurrence in the values of field frequency and intensity, which is a kind of effect long reported in bioelectromagnetic experimental studies. The spatial distribution of the modeled structure also allows to investigate possible effects on action potentials saltatory propagation, which results to be reliable and robust over the presence of an exogenous EM field and biological noise. The proposed approach can be seen as assessing biophysical bases of medical applications funded on electric and magnetic stimulation where the role of noise as a cooperative factor has recently gained growing attention. This work investigates the role of noise as a cooperative factor for the detection of an exogenous electromagnetic field in a compartimental model of a myelinated nerve fiber. The occurrence of stochastic resonance is discussed in relation to neuronal frequency sensitivity.     

Fluorescent and dispersion experiments on biological membranes under micro-gravity

Almost all biological processes, especially those involved in signal reception and signal transduction, depend on the physical and physiological properties of biological membranes. It has been shown, that neuronal tissue and the speed of the action potential (AP) which is the basic neuronal unit of all nervous activity, is sensitive to changes in gravity as well as to other weak external forces. We strongly suppose the membrane to be the most important factor in gravitational responses although it is very difficult to observe the effects of gravity changes on these fragile thermodynamic systems. Therefore we developed two different experiments to measure the structural changes and the lateral membrane tension of spheroid cells under microgravity.     

Defining the V5/MT neuronal pool for perceptual decisions in a visual stereo-motion task

In the primate visual cortex, neurons signal differences in the appearance of objects with high precision. However, not all activated neurons contribute directly to perception. We defined the perceptual pool in extrastriate visual area V5/MT for a stereo-motion task, based on trial-by-trial co-variation between perceptual decisions and neuronal firing (choice probability (CP)). Macaque monkeys were trained to discriminate the direction of rotation of a cylinder, using the binocular depth between the moving dots that form its front and rear surfaces. We manipulated the activity of single neurons trial-to-trial by introducing task-irrelevant stimulus changes: dot motion in cylinders was aligned with neuronal preference on only half the trials, so that neurons were strongly activated with high firing rates on some trials and considerably less activated on others. We show that single neurons maintain high neurometric sensitivity for binocular depth in the face of substantial changes in firing rate. CP was correlated with neurometric sensitivity, not level of activation. In contrast, for individual neurons, the correlation between perceptual choice and neuronal activity may be fundamentally different when responding to different stimulus versions. Therefore, neuronal pools supporting sensory discrimination must be structured flexibly and independently for each stimulus configuration to be discriminated.This article is part of the themed issue ‘Vision in our three-dimensional world''.     

Sensitivity of different stimulus-timing strategies for the detection of small excitations in noisy spike train data

There are several different strategies to control the timing of a stimulus with respect to the ongoing discharge during the recording of neuronal stimulus-response characteristics. One possible strategy consists of delivering stimuli in such a way that a constant pre-stimulus spike density is reached. Another strategy enforces spike application with a constant stimulus latency after a spontaneous discharge. In this paper the sensitivity of these different strategies for statistical verification of small excitatory response components was investigated. It was found that the difference between observed poststimulus spike distribution and expected spike distribution under the null hypothesis of no stimulus effect was larger using a constant-stimulus-latency (CSL) strategy with an appropriate value for the stimulus latency. Thus, the statistical verification of neuronal response components is clearly facilitated if a CSL strategy is used. This superiority of the CSL strategy is marked, especially for small excitations at neurons discharging slowly with low discharge variability.     

Real time computation: zooming in on population codes

Information processing in nervous systems intricately combines computation at the neuronal and network levels. Many computations may be envisioned as sequences of signal processing steps along some pathway. How can information encoded by single cells be mapped onto network population codes, and how do different modules or layers in the computation synchronize their communication and computation? These fundamental questions are particularly severe when dealing with real time streams of inputs. Here we study this problem within the context of a minimal signal perception task. In particular, we encode neuronal information by externally applying a space- and time-localized stimulus to individual neurons within a network. We show that a pulse-coupled recurrent neural network can successfully handle this task in real time, and obeys three key requirements: (i) stimulus dependence, (ii) initial-conditions independence, and (iii) accessibility by a readout mechanism. In particular, we suggest that the network's overall level of activity can be used as a temporal cue for a robust readout mechanism. Within this framework, the network can rapidly map a local stimulus onto a population code that can then be reliably read out during some narrow but well defined window of time.     

Review of possible modulation-dependent biological effects of radiofrequency fields

The biological effects of modulated radiofrequency (RF) electromagnetic fields have been a subject of debate since early publications more than 30 years ago, suggesting that relatively weak amplitude-modulated RF electromagnetic fields have specific biological effects different from the well-known thermal effects of RF energy. This discussion has been recently activated by the increasing human exposure to RF fields from wireless communication systems. Modulation is used in all wireless communication systems to enable the signal to carry information. A previous review in 1998 indicated that experimental evidence for modulation-specific effects of RF energy is weak. This article reviews recent studies (published after 1998) on the biological effects of modulated RF fields. The focus is on studies that have compared the effects of modulated and unmodulated (continuous wave) RF fields, or compared the effects of different kinds of modulations; studies that used only one type of signal are not included. While the majority of recent studies have reported no modulation-specific effects, there are a few interesting exceptions indicating that there may be specific effects from amplitude-modulated RF fields on the human central nervous system. These findings warrant follow-up studies.     

Modeling of biological doses and mechanical effects on bone transduction

Shear stress, hormones like parathyroid and mineral elements like calcium mediate the amplitude of stimulus signal, which affects the rate of bone remodeling. The current study investigates the theoretical effects of different metabolic doses in stimulus signal level on bone. The model was built considering the osteocyte as the sensing center mediated by coupled mechanical shear stress and some biological factors. The proposed enhanced model was developed based on previously published works dealing with different aspects of bone transduction. It describes the effects of physiological doses variations of calcium, parathyroid hormone, nitric oxide and prostaglandin E2 on the stimulus level sensed by osteocytes in response to applied shear stress generated by interstitial fluid flow. We retained the metabolic factors (parathyroid hormone, nitric oxide and prostaglandin E2) as parameters of bone cell mechanosensitivity because stimulation/inhibition of induced pathways stimulates osteogenic response in vivo. We then tested the model response in terms of stimulus signal variation versus the biological factors doses to external mechanical stimuli. Despite the limitations of the model, it is consistent and has physiological bases. Biological inputs are histologically measurable. This makes the model amenable to experimental verification.     

Evidence concerning how neurons of the perirhinal cortex may effect familiarity discrimination

Many studies indicate that recognition memory involves at least two separable processes, familiarity discrimination and recollection. Aspects of what is known of potential neuronal substrates of familiarity discrimination are reviewed. Lesion studies have established that familiarity discrimination for individual visual stimuli is effected by a system centred on the perirhinal cortex of the temporal lobe. The fundamental change that encodes prior occurrence of such stimuli appears to be a reduction in the response of neurons in anterior inferior temporal (including perirhinal) cortex when a stimulus is repeated. The neuronal responses rapidly signal the presence of a novel stimulus, and are evidence of long-lasting learning after a single exposure. Computational modelling indicates that a neuronal network based on such a change in responsiveness is potentially highly efficient in information theoretic terms. Processes that occur in long-term depression within the perirhinal cortex provide candidate synaptic plastic mechanisms for that underlying the change, but such linkage remains to be experimentally established.     

Switching neuronal state: optimal stimuli revealed using a stochastically-seeded gradient algorithm

Inducing a switch in neuronal state using energy optimal stimuli is relevant to a variety of problems in neuroscience. Analytical techniques from optimal control theory can identify such stimuli; however, solutions to the optimization problem using indirect variational approaches can be elusive in models that describe neuronal behavior. Here we develop and apply a direct gradient-based optimization algorithm to find stimulus waveforms that elicit a change in neuronal state while minimizing energy usage. We analyze standard models of neuronal behavior, the Hodgkin-Huxley and FitzHugh-Nagumo models, to show that the gradient-based algorithm: 1) enables automated exploration of a wide solution space, using stochastically generated initial waveforms that converge to multiple locally optimal solutions; and 2) finds optimal stimulus waveforms that achieve a physiological outcome condition, without a priori knowledge of the optimal terminal condition of all state variables. Analysis of biological systems using stochastically-seeded gradient methods can reveal salient dynamical mechanisms underlying the optimal control of system behavior. The gradient algorithm may also have practical applications in future work, for example, finding energy optimal waveforms for therapeutic neural stimulation that minimizes power usage and diminishes off-target effects and damage to neighboring tissue.     

Model analysis of the effect of modulated electromagnetic fields with various parameters of modulating signals in cells

A theoretical analysis of the dependence of cell response to modulated electromagnetic fields on the parameters of modulating signals was performed on the basis of the model for calcium-dependent membrane-associated intracellular signaling systems. Expressed amplitude-frequency "windows" in the response of the nonlinear system to external influence were shown to depend on the effective time during which the amplitude of the influencing signal exceeded some threshold value, which is determined by the properties of the system. The presence of negative values in the influencing signal, i.e. the variations in the rate of some process around the inherent value, played an important role for the effect characteristics. The response of the nonlinear system to external influence strongly depended on the waveform of the modulating signal which is determined not only by frequency spectrum, but also by the initial phase of each frequency component. To ensure a regime for the optimal effect, the rates of increase and drop in the modulating signal amplitude should be synchronized with dynamic processes in the biological object being exposed.