Dynamics of spontaneous activity in random networks with multiple neuron subtypes and synaptic noise

During slow-wave sleep, brain electrical activity is dominated by the slow (< 1 Hz) electroencephalogram (EEG) oscillations characterized by the periodic transitions between active (or Up) and silent (or Down) states in the membrane voltage of the cortical and thalamic neurons. Sleep slow oscillation is believed to play critical role in consolidation of recent memories. Past computational studies, based on the Hodgkin-Huxley type neuronal models, revealed possible intracellular and network mechanisms of the neuronal activity during sleep, however, they failed to explore the large-scale cortical network dynamics depending on collective behavior in the large populations of neurons. In this new study, we developed a novel class of reduced discrete time spiking neuron models for large-scale network simulations of wake and sleep dynamics. In addition to the spiking mechanism, the new model implemented nonlinearities capturing effects of the leak current, the Ca²⁺ dependent K⁺ current and the persistent Na⁺ current that were found to be critical for transitions between Up and Down states of the slow oscillation. We applied the new model to study large-scale two-dimensional cortical network activity during slow-wave sleep. Our study explained traveling wave dynamics and characteristic synchronization properties of transitions between Up and Down states of the slow oscillation as observed in vivo in recordings from cats. We further predict a critical role of synaptic noise and slow adaptive currents for spike sequence replay as found during sleep related memory consolidation.     

In vivo visualization of individual neurons in arthropod ganglia facilitates intracellular neuropil recording

Summary A simple method for the in vivo visualization of dye filled cells by laser illumination is used to characterize neurons in situ in the segmentai ganglia of the locust and the crayfish (Fig. 1). Neuron visualization provides the structural information necessary for identification of cells during an ongoing physiological experiment (Figs. 2, 3). Sequential penetrations of soma and neuropil as well as simultaneous double neuropil penetrations of spiking and nonspiking cells are facilitated by the visual control afforded by neuron visualization (Figs. 4, 5, 6). Furthermore, neuron visualization allows the sampling of cellular properties at multiple, predetermined sites in the dendritic and axonal arbors of identified neurons (Fig. 7) and aids in establishing synaptic connectivity through double neuropil recordings (Fig. 8).     

Manufacturing and Using Piggy-back Multibarrel Electrodes for In vivo Pharmacological Manipulations of Neural Responses

In vivo recordings from single neurons allow an investigator to examine the firing properties of neurons, for example in response to sensory stimuli. Neurons typically receive multiple excitatory and inhibitory afferent and/or efferent inputs that integrate with each other, and the ultimate measured response properties of the neuron are driven by the neural integrations of these inputs. To study information processing in neural systems, it is necessary to understand the various inputs to a neuron or neural system, and the specific properties of these inputs. A powerful and technically relatively simple method to assess the functional role of certain inputs that a given neuron is receiving is to dynamically and reversibly suppress or eliminate these inputs, and measure the changes in the neuron''s output caused by this manipulation. This can be accomplished by pharmacologically altering the neuron''s immediate environment with piggy-back multibarrel electrodes. These electrodes consist of a single barrel recording electrode and a multibarrel drug electrode that can carry up to 4 different synaptic agonists or antagonists. The pharmacological agents can be applied iontophoretically at desired times during the experiment, allowing for time-controlled delivery and reversible reconfiguration of synaptic inputs. As such, pharmacological manipulation of the microenvironment represents a powerful and unparalleled method to test specific hypotheses about neural circuit function.Here we describe how piggy-back electrodes are manufactured, and how they are used during in vivo experiments. The piggy-back system allows an investigator to combine a single barrel recording electrode of any arbitrary property (resistance, tip size, shape etc) with a multibarrel drug electrode. This is a major advantage over standard multi-electrodes, where all barrels have more or less similar shapes and properties. Multibarrel electrodes were first introduced over 40 years ago ^1-3, and have undergone a number of design improvements ^2,3 until the piggy-back type was introduced in the 1980s ^4,5. Here we present a set of important improvements in the laboratory production of piggy-back electrodes that allow for deep brain penetration in intact in vivo animal preparations due to a relatively thin electrode shaft that causes minimal damage. Furthermore these electrodes are characterized by low noise recordings, and have low resistance drug barrels for very effective iontophoresis of the desired pharmacological agents.     

Preparation of an Awake Mouse for Recording Neural Responses and Injecting Tracers

It is well known that anesthesia alters neural response properties in various regions of the brain.¹³. In the auditory system, fundamental response properties of brainstem neurons including threshold, frequency specificity, and inhibitory sidebands are altered in significant ways under anesthesia^1-2. These observations prompted physiologists to seek ways to record from single neurons without the contaminating effects of anesthesia. One result was a decerebrate preparation, where the brainstem was completely transected at the level of the midbrain⁴. The drawbacks of this preparation are a formidable surgery, the elimination of descending projections from the forebrain, and an inability to use sensory stimulation to examine structures above the midbrain. A different strategy has been to implant electrode arrays chronically to record from single neurons and multiunit clusters while the animal is awake and/or behaving^5,6. These techniques however are not compatible with injecting tracer dyes after first electrophysiologically characterizing a brain structure. To avoid altering neural response properties with anesthetics while recording electrophysiological response properties from single neurons, we have adapted a head restraint technique long used in bats^7-9 to mouse^10-12. Using this method, we are able to conduct electrophysiological recordings over several days in the unanesthetized mouse. At the end of the recording sessions, we can then inject a dye to reconstruct electrode positions and recording sites or inject a tracer so that pathways to and from the recording loci can be determined. This method allows for well isolated single neuron recordings over multiple days without the use anesthetics.     

Voltage-sensitive Dye Recording from Axons,Dendrites and Dendritic Spines of Individual Neurons in Brain Slices

Understanding the biophysical properties and functional organization of single neurons and how they process information is fundamental for understanding how the brain works. The primary function of any nerve cell is to process electrical signals, usually from multiple sources. Electrical properties of neuronal processes are extraordinarily complex, dynamic, and, in the general case, impossible to predict in the absence of detailed measurements. To obtain such a measurement one would, ideally, like to be able to monitor, at multiple sites, subthreshold events as they travel from the sites of origin on neuronal processes and summate at particular locations to influence action potential initiation. This goal has not been achieved in any neuron due to technical limitations of measurements that employ electrodes. To overcome this drawback, it is highly desirable to complement the patch-electrode approach with imaging techniques that permit extensive parallel recordings from all parts of a neuron. Here, we describe such a technique - optical recording of membrane potential transients with organic voltage-sensitive dyes (V_m-imaging) - characterized by sub-millisecond and sub-micrometer resolution. Our method is based on pioneering work on voltage-sensitive molecular probes ². Many aspects of the initial technology have been continuously improved over several decades ^{3, 5, 11}. Additionally, previous work documented two essential characteristics of V_m-imaging. Firstly, fluorescence signals are linearly proportional to membrane potential over the entire physiological range (-100 mV to +100 mV; ^{10, 14, 16}). Secondly, loading neurons with the voltage-sensitive dye used here (JPW 3028) does not have detectable pharmacological effects. The recorded broadening of the spike during dye loading is completely reversible ^{4, 7}. Additionally, experimental evidence shows that it is possible to obtain a significant number (up to hundreds) of recordings prior to any detectable phototoxic effects ^{4, 6, 12, 13}. At present, we take advantage of the superb brightness and stability of a laser light source at near-optimal wavelength to maximize the sensitivity of the V_m-imaging technique. The current sensitivity permits multiple site optical recordings of V_m transients from all parts of a neuron, including axons and axon collaterals, terminal dendritic branches, and individual dendritic spines. The acquired information on signal interactions can be analyzed quantitatively as well as directly visualized in the form of a movie.     

视觉编码的快速学习

活动依赖的神经可塑性在视觉皮层信息处理过程中起着很重要的作用。该文将讲述几个关于视觉刺激引起皮层反应发生快速变化的研究工作。在体膜片钳的实验结果表明,将视觉刺激与能够诱发孽个视皮层神经元发放动作电位的电刺激相偶联可以改变神经元的感受野特性。单电极和多电极胞外记录的实验结果显示,反复地给予自然图形电影刺激,不仅能增加视皮层神经元反应的可靠性,而且能造成之后的自发活动中存在“记忆的痕迹”。最后,用电压敏感染料成像的方法对群体细胞活动进行考察,结果提示视觉活动之后的皮层回放可能是由皮层波介导的。     

Targeted patch-clamp recordings and single-cell electroporation of unlabeled neurons in vivo

Here we describe an approach for making targeted patch-clamp recordings from single neurons in vivo, visualized by two-photon microscopy. A patch electrode is used to perfuse the extracellular space surrounding the neuron of interest with a fluorescent dye, thus enabling the neuron to be visualized as a negative image ('shadow') and identified on the basis of its somatodendritic structure. The same electrode is then placed on the neuron under visual control to allow formation of a gigaseal ('shadowpatching'). We demonstrate the reliability and versatility of shadowpatching by performing whole-cell recordings from visually identified neurons in the neocortex and cerebellum of rat and mouse. We also show that the method can be used for targeted in vivo single-cell electroporation of plasmid DNA into identified cell types, leading to stable transgene expression. This approach facilitates the recording, labeling and genetic manipulation of single neurons in the intact native mammalian brain without the need to pre-label neuronal populations.     

Optical recording of the electrical activity of synaptically interacting Aplysia neurons in culture using potentiometric probes.

We used multiple-site optical recording methods, in conjunction with impermeant molecular probes of the cell membrane potential, to record the electrical activity of model neural circuits in vitro. Our system consisted of co-cultured pairs of left upper quadrant neurons from the abdominal ganglion of the marine gastropod Aplysia. These neurons interact via inhibitory synapses in vitro. Photodynamic damage to the neurons was essentially eliminated over the time course of the measurements, approximately less than 30 s, by removing oxygen from the recording solution and replacing it with argon. This procedure did not affect the synaptic interactions. We observed repetitive spiking activity in single-trace optical recordings with a maximum signal-to-noise ratio per detector of approximately 50. Individual optical signals that corresponded to either the activity of the presynaptic neuron or that of the postsynaptic neuron were clearly identified. This allowed us to monitor the activity of synaptically interacting neurons, observed as a reduction of the firing rate of the postsynaptic cell after activity of the presynaptic cell. Our results demonstrate that optical methods are appropriate for recording prolonged, asynchronous activity from synaptically interacting neurons in culture.     

Analysing neuronal correlates of the comparison of two sequentially presented sensory stimuli

In a typical sequential sensory discrimination task, subjects are required to make a decision based on comparing a sensory stimulus against the memory trace left by a previous stimulus. What is the neuronal substrate for such comparisons and the resulting decisions? This question was studied by recording neuronal responses in a variety of cortical areas of awake monkeys (Macaca mulatta), trained to carry out a vibrotactile sequential discrimination task. We describe methods to analyse responses obtained during the comparison and decision phases of the task, and describe the resulting findings from recordings in secondary somatosensory cortical area (S2). A subset of neurons in S2 become highly correlated with the monkey''s decision in the task.     

The Possible Role of Spike Patterns in Cortical Information Processing

When the same visual stimulus is presented across many trials, neurons in the visual cortex receive stimulus-related synaptic inputs that are reproducible across trials (S) and inputs that are not (N). The variability of spike trains recorded in the visual cortex and their apparent lack of spike-to-spike correlations beyond that implied by firing rate fluctuations, has been taken as evidence for a low S/N ratio. A recent re-analysis of in vivo cortical data revealed evidence for spike-to-spike correlations in the form of spike patterns. We examine neural dynamics at a higher S/N in order to determine what possible role spike patterns could play in cortical information processing. In vivo-like spike patterns were obtained in model simulations. Superpositions of multiple sinusoidal driving currents were especially effective in producing stable long-lasting patterns. By applying current pulses that were either short and strong or long and weak, neurons could be made to switch from one pattern to another. Cortical neurons with similar stimulus preferences are located near each other, have similar biophysical properties and receive a large number of common synaptic inputs. Hence, recordings of a single neuron across multiple trials are usually interpreted as the response of an ensemble of these neurons during one trial. In the presence of distinct spike patterns across trials there is ambiguity in what would be the corresponding ensemble, it could consist of the same spike pattern for each neuron or a set of patterns across neurons. We found that the spiking response of a neuron receiving these ensemble inputs was determined by the spike-pattern composition, which, in turn, could be modulated dynamically as a means for cortical information processing.     

Noise Normalizes Firing Output of Mouse Lateral Geniculate Nucleus Neurons

The output of individual neurons is dependent on both synaptic and intrinsic membrane properties. While it is clear that the response of an individual neuron can be facilitated or inhibited based on the summation of its constituent synaptic inputs, it is not clear whether subthreshold activity, (e.g. synaptic “noise”- fluctuations that do not change the mean membrane potential) also serve a function in the control of neuronal output. Here we studied this by making whole-cell patch-clamp recordings from 29 mouse thalamocortical relay (TC) neurons. For each neuron we measured neuronal gain in response to either injection of current noise, or activation of the metabotropic glutamate receptor-mediated cortical feedback network (synaptic noise). As expected, injection of current noise via the recording pipette induces shifts in neuronal gain that are dependent on the amplitude of current noise, such that larger shifts in gain are observed in response to larger amplitude noise injections. Importantly we show that shifts in neuronal gain are also dependent on the intrinsic sensitivity of the neuron tested, such that the gain of intrinsically sensitive neurons is attenuated divisively in response to current noise, while the gain of insensitive neurons is facilitated multiplicatively by injection of current noise- effectively normalizing the output of the dLGN as a whole. In contrast, when the cortical feedback network was activated, only multiplicative gain changes were observed. These network activation-dependent changes were associated with reductions in the slow afterhyperpolarization (sAHP), and were mediated at least in part, by T-type calcium channels. Together, this suggests that TC neurons have the machinery necessary to compute multiple output solutions to a given set of stimuli depending on the current level of network stimulation.     

The Limited Utility of Multiunit Data in Differentiating Neuronal Population Activity

To date, single neuron recordings remain the gold standard for monitoring the activity of neuronal populations. Since obtaining single neuron recordings is not always possible, high frequency or ‘multiunit activity’ (MUA) is often used as a surrogate. Although MUA recordings allow one to monitor the activity of a large number of neurons, they do not allow identification of specific neuronal subtypes, the knowledge of which is often critical for understanding electrophysiological processes. Here, we explored whether prior knowledge of the single unit waveform of specific neuron types is sufficient to permit the use of MUA to monitor and distinguish differential activity of individual neuron types. We used an experimental and modeling approach to determine if components of the MUA can monitor medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) in the mouse dorsal striatum. We demonstrate that when well-isolated spikes are recorded, the MUA at frequencies greater than 100Hz is correlated with single unit spiking, highly dependent on the waveform of each neuron type, and accurately reflects the timing and spectral signature of each neuron. However, in the absence of well-isolated spikes (the norm in most MUA recordings), the MUA did not typically contain sufficient information to permit accurate prediction of the respective population activity of MSNs and FSIs. Thus, even under ideal conditions for the MUA to reliably predict the moment-to-moment activity of specific local neuronal ensembles, knowledge of the spike waveform of the underlying neuronal populations is necessary, but not sufficient.     

Optimal signal filtering parameters for tetrode recording of neuronal activity

Extracellular recording of neuronal spiking is the main method of investigation of involvement of neurons in behavioral tasks. Development of multichannel electrodes made it possible to simultaneously record activity of the same group of neurons from different locations in the brain tissue. That method allows the researches to distinguish spiking of simultaneously recorded neurons by individual set of projection coefficients of amplitude parameters on axes corresponding to different channels of the multichannel electrode. We tested the possibility of effective separation of single unit spiking streams from multiunit activity recorded by tetrode and subjected to different filtering. We described the main limitations for effective spike identification and determined the optimal band of signal filtering for tetrode recording.     

Firing patterns in the adaptive exponential integrate-and-fire model

For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations.     

Functional organization and structure of the serotonergic neuronal network of terrestrial snail

The extension of knowledge how the brain works requires permanent improvement of methods of recording of neuronal activity and increase in the number of neurons recorded simultaneously to better understand the collective work of neuronal networks and assemblies. Conventional methods allow simultaneous intracellular recording up to 2-5 neurons and their membrane potentials, currents or monosynaptic connections or observation of spiking of neuronal groups with subsequent discrimination of individual spikes with loss of details of the dynamics of membrane potential. We recorded activity of a compact group of serotonergic neurons (up to 56 simultaneously) in the ganglion of a terrestrial mollusk using the method of optical recording of membrane potential that allowed to record individual action potentials in details with action potential parameters and to reveal morphology of the neurons rcorded. We demonstrated clear clustering in the group in relation with the dynamics of action potentials and phasic or tonic components in the neuronal responses to external electrophysiological and tactile stimuli. Also, we showed that identified neuron Pd2 could induce activation of a significant number of neurons in the group whereas neuron Pd4 did not induce any activation. However, its activation is delayed with regard to activation of the reacting group of neurons. Our data strongly support the concept of possible delegation of the integrative function by the network to a single neuron.     

A novel silicon patch‐clamp chip permits high‐fidelity recording of ion channel activity from functionally defined neurons

We report on a simple and high‐yield manufacturing process for silicon planar patch‐clamp chips, which allow low capacitance and series resistance from individually identified cultured neurons. Apertures are etched in a high‐quality silicon nitride film on a silicon wafer; wells are opened on the backside of the wafer by wet etching and passivated by a thick deposited silicon dioxide film to reduce the capacitance of the chip and to facilitate the formation of a high‐impedance cell to aperture seal. The chip surface is suitable for culture of neurons over a small orifice in the substrate with minimal leak current. Collectively, these features enable high‐fidelity electrophysiological recording of transmembrane currents resulting from ion channel activity in cultured neurons. Using cultured Lymnaea neurons we demonstrate whole‐cell current recordings obtained from a voltage‐clamp stimulation protocol, and in current‐clamp mode we report action potentials stimulated by membrane depolarization steps. Despite the relatively large size of these neurons, good temporal and spatial control of cell membrane voltage was evident. To our knowledge this is the first report of recording of ion channel activity and action potentials from neurons cultured directly on a planar patch‐clamp chip. This interrogation platform has enormous potential as a novel tool to readily provide high‐information content during pharmaceutical assays to investigate in vitro models of disease, as well as neuronal physiology and synaptic plasticity. Biotechnol. Bioeng. 2010;107:593–600. © 2010 Wiley Periodicals, Inc.     

What single-cell stimulation has told us about neural coding

In recent years, single-cell stimulation experiments have resulted in substantial progress towards directly linking single-cell activity to movement and sensation. Recent advances in electrical recording and stimulation techniques have enabled control of single neuron spiking in vivo and have contributed to our understanding of neuronal coding schemes in the brain. Here, we review single neuron stimulation effects in different brain structures and how they vary with artificially inserted spike patterns. We briefly compare single neuron stimulation with other brain stimulation techniques. A key advantage of single neuron stimulation is the precise control of the evoked spiking patterns. Systematically varying spike patterns and measuring evoked movements and sensations enables ‘decoding’ of the single-cell spike patterns and provides insights into the readout mechanisms of sensory and motor cortical spikes.     

Supervised learning with decision margins in pools of spiking neurons

Learning to categorise sensory inputs by generalising from a few examples whose category is precisely known is a crucial step for the brain to produce appropriate behavioural responses. At the neuronal level, this may be performed by adaptation of synaptic weights under the influence of a training signal, in order to group spiking patterns impinging on the neuron. Here we describe a framework that allows spiking neurons to perform such “supervised learning”, using principles similar to the Support Vector Machine, a well-established and robust classifier. Using a hinge-loss error function, we show that requesting a margin similar to that of the SVM improves performance on linearly non-separable problems. Moreover, we show that using pools of neurons to discriminate categories can also increase the performance by sharing the load among neurons.