An olfactory bulb slice-based biosensor for multi-site extracellular recording of neural networks

Multi-site recording is the important component for studies of the neural networks. In order to investigate the electrophysiological properties of the olfactory bulb neural networks, we developed a novel slice-based biosensor for synchronous measurement with multi-sites. In the present study, the horizontal olfactory bulb slices with legible layered structures were prepared as the sensing element to construct a tissue-based biosensor with the microelectrode array. This olfactory bulb slice-based biosensor was used to simultaneously record the extracellular potentials from multi-positions. Spike detection and cross-correlation analysis were applied to evaluate the electrophysiological activities. The spontaneous potentials as well as the induced responses by glutamic acid took on different electrophysiological characteristics and firing patterns at the different sites of the olfactory bulb slice. This slice-based biosensor can realize multi-site synchronous monitoring and is advantageous for searching after the firing patterns and synaptic connections in the olfactory bulb neural networks. It is also helpful for further probing into olfactory information encoding of the olfactory neural networks.     

Negative relationship between odor-induced spike activity and spontaneous oscillations in the primary olfactory system of the terrestrial slug Limax marginatus

Although primary olfactory systems in various animals display spontaneous oscillatory activity, its functional significance in olfactory processing has not been elucidated. The tentacular ganglion, the primary olfactory system of the terrestrial slug Limax marginatus, also displays spontaneous oscillatory activity at 1-2 Hz. In the present study, we examined the relationship between odor-evoked spike activity and spontaneous field potential oscillations in the tentacular nerve, representing the pathway from the primary olfactory system to the olfactory center. Neural activity was recorded from the tentacular nerve before, during and after application of various odors (garlic, carrot, and rat chow) to the sensory epithelium and the changes in firing rate and spontaneous oscillations were analyzed. We detected the baseline amplitude of the oscillations and baseline spike activity before stimulation. Odor stimulations for 20 s or 60 s evoked a transient increase in the firing rate followed by a decrease in the amplitude of spontaneous oscillations. The decrease in the amplitude was larger in the first 8 s of stimulation and subsequently showed recovery during stimulation. The amplitude of the recovered oscillations often fluctuated. Odor-evoked spikes appeared when the amplitude of the recovered oscillations was transiently small. These results suggest that the large oscillations could inhibit spike activity whereas the first transient increase in spike activity was followed by the decrease in the oscillation amplitude. Our results indicate that there is a significant negative correlation between spontaneous oscillations and odor-evoked spike activity, suggesting that the spontaneous oscillations contribute to the olfactory processing in slugs.     

Specific Entrainment of Mitral Cells during Gamma Oscillation in the Rat Olfactory Bulb

Local field potential (LFP) oscillations are often accompanied by synchronization of activity within a widespread cerebral area. Thus, the LFP and neuronal coherence appear to be the result of a common mechanism that underlies neuronal assembly formation. We used the olfactory bulb as a model to investigate: (1) the extent to which unitary dynamics and LFP oscillations can be correlated and (2) the precision with which a model of the hypothesized underlying mechanisms can accurately explain the experimental data. For this purpose, we analyzed simultaneous recordings of mitral cell (MC) activity and LFPs in anesthetized and freely breathing rats in response to odorant stimulation. Spike trains were found to be phase-locked to the gamma oscillation at specific firing rates and to form odor-specific temporal patterns. The use of a conductance-based MC model driven by an approximately balanced excitatory-inhibitory input conductance and a relatively small inhibitory conductance that oscillated at the gamma frequency allowed us to provide one explanation of the experimental data via a mode-locking mechanism. This work sheds light on the way network and intrinsic MC properties participate in the locking of MCs to the gamma oscillation in a realistic physiological context and may result in a particular time-locked assembly. Finally, we discuss how a self-synchronization process with such entrainment properties can explain, under experimental conditions: (1) why the gamma bursts emerge transiently with a maximal amplitude position relative to the stimulus time course; (2) why the oscillations are prominent at a specific gamma frequency; and (3) why the oscillation amplitude depends on specific stimulus properties. We also discuss information processing and functional consequences derived from this mechanism.     

Olfactory cell-based biosensor: a first step towards a neurochip of bioelectronic nose

Human olfactory system can distinguish thousands of odors. In order to realize the biomimetic design of electronic nose on the principle of mammalian olfactory system, this article reports an olfactory cell-based biosensor as a real bionic technique for odorants detection. Effective cultures of olfactory receptor neurons and olfactory bulb cells have been achieved on the semiconductor chip. Using light-addressable potentiometric sensor (LAPS) as sensing chip to monitor extracellular potential of the neurons, the response under stimulations of the odorants or neurotransmitters, such as acetic acid and glutamic acid, was tested. The results demonstrate that this kind of hybrid system of LAPS and olfactory neurons, which is sensitive to odorous changes, has great potential and is promising to be used as a novel neurochip of bioelectronic nose for detecting odors.     

Taste receptor cell-based biosensor for taste specific recognition based on temporal firing

Taste receptor cells are the taste sensation elements expressing sour, salty, sweet, bitter and umami receptors, respectively. There are cell-to-cell communications between different types of cells. Nevertheless, the mechanism of taste sensation and taste information coded by taste receptor cell is not well understood at present and it is a long-standing issue. In order to explore taste sensation and analyze taste-firing responses from another point of view, we present a promising biomimetic taste receptor cell-based biosensor. The temporal firing responses to different tastants are recorded. Meanwhile, we investigate the firing rate and temporal firing of taste receptor cells. The experimental results are consistent with that from patch clamp and molecular biology experiment. Firing rate is dependent on the concentration of stimulus. PCA analysis (principal component analysis) of the temporal firing responses shows that the responses from different types of taste receptor cells can be distinguished. Furthermore, exogenous ATP is applied to mimic the effects of transmitter ATP (adenosine triphosphate) released from type II cells onto type III cells. Both enhanced and inhibitory effects on spontaneous firing are observed. This novel biomimetic hybrid biosensor provides a potential solution to investigate the taste sensation and coding mechanisms in a non-invasive way.     

神经元群简化模型的动态特性的研究

神经发放率的振荡和同步现象是视觉神经生理学的最新实验发现,也是Ｍａｌｓｂｕｒｇ等人关于物体感知的时间相关性神经群理论的重要假设。本文在神经元群简化模型动力学方程的基础上加以改进,研究了噪声对振荡的相关性和独立性的影响,取得与生物实验相似的结果;发现在具有时间结构的输入刺激下单个神经元群发放的锁频现象,进一步讨论了两个神经元群之间的同步现象及其机理。     

Simultaneous single unit recording in the mitral cell layer of the rat olfactory bulb under nasal and tracheal breathing

Odor perception depends on the odorant-evoked changes on Mitral/Tufted cell firing pattern within the olfactory bulb (OB). The OB exhibits a significant "ongoing" or spontaneous activity in the absence of sensory stimulation. We characterized this ongoing activity by simultaneously recording several single neurons in the mitral cell layer (MCL) of anesthetized rats and determined the extent of synchrony and oscillations under nasal and tracheal breathing. We recorded 115 neurons and found no significant differences in the mean firing rates between both breathing conditions. Surprisingly, nearly all single units exhibited a long refractory period averaging 14.4 ms during nasal respiration that was not different under tracheal breathing. We found a small incidence (2% of neurons) of gamma band oscillations and a low incidence (8.1%) of correlated firing between adjacent MCL cells. During nasal respiration, a significant oscillation at the respiratory rate was observed in 12% of cells that disappeared during tracheal breathing. Thus, in the absence of odorants, MCL cells exhibit a long refractory period, probably reflecting the intrinsic OB network properties. Furthermore, in the absence of sensory stimulation, MCL cell discharge does not oscillate in the gamma band and the respiratory cycle can modulate the firing of these cells.     

Encoding odorant identity by spiking packets of rate-invariant neurons in awake mice

Background

How do neural networks encode sensory information? Following sensory stimulation, neural coding is commonly assumed to be based on neurons changing their firing rate. In contrast, both theoretical works and experiments in several sensory systems showed that neurons could encode information as coordinated cell assemblies by adjusting their spike timing and without changing their firing rate. Nevertheless, in the olfactory system, there is little experimental evidence supporting such model.

Methodology/Principal Findings

To study these issues, we implanted tetrodes in the olfactory bulb of awake mice to record the odorant-evoked activity of mitral/tufted (M/T) cells. We showed that following odorant presentation, most M/T neurons do not significantly change their firing rate over a breathing cycle but rather respond to odorant stimulation by redistributing their firing activity within respiratory cycles. In addition, we showed that sensory information can be encoded by cell assemblies composed of such neurons, thus supporting the idea that coordinated populations of globally rate-invariant neurons could be efficiently used to convey information about the odorant identity. We showed that different coding schemes can convey high amount of odorant information for specific read-out time window. Finally we showed that the optimal readout time window corresponds to the duration of gamma oscillations cycles.

Conclusion

We propose that odorant can be encoded by population of cells that exhibit fine temporal tuning of spiking activity while displaying weak or no firing rate change. These cell assemblies may transfer sensory information in spiking packets sequence using the gamma oscillations as a clock. This would allow the system to reach a tradeoff between rapid and accurate odorant discrimination.     

Oscillation and coding in a formal neural network considered as a guide for plausible simulations of the insect olfactory system

For the analysis of coding mechanisms in the insect olfactory system, a fully connected network of synchronously updated McCulloch and Pitts neurons (MC-P type) was developed [Quenet, B., Horn, D., 2003. The dynamic neural filter: a binary model of spatio-temporal coding. Neural Comput. 15 (2), 309-329]. Considering the update time as an intrinsic clock, this "Dynamic Neural Filter" (DNF), which maps regions of input space into spatio-temporal sequences of neuronal activity, is able to produce exact binary codes extracted from the synchronized activities recorded at the level of projection neurons (PN) in the locust antennal lobe (AL) in response to different odors [Wehr, M., Laurent, G., 1996. Odor encoding by temporal sequences of firing in oscillating neural assemblies. Nature 384, 162-166]. Here, in a first step, we separate the populations of PN and local inhibitory neurons (LN) and use the DNF as a guide for simulations based on biological plausible neurons (Hodgkin-Huxley: H-H type). We show that a parsimonious network of 10 H-H neurons generates action potentials whose timing represents the required codes. In a second step, we construct a new type of DNF in order to study the population dynamics when different delays are taken into account. We find synaptic matrices which lead to both the emergence of robust oscillations and spatio-temporal patterns, using a formal criterion, based on a Normalized Euclidian Distance (NED), in order to measure the use of the temporal dimension as a coding dimension by the DNF. Similarly to biological PN, the activity of excitatory neurons in the model can be both phase-locked to different cycles of oscillations which remind local field potential (LFP), and nevertheless exhibit dynamic behavior complex enough to be the basis of spatio-temporal codes.     

Dendritic synchrony and transient dynamics in a coupled oscillator model of the dopaminergic neuron

Transient increases in spontaneous firing rate of mesencephalic dopaminergic neurons have been suggested to act as a reward prediction error signal. A mechanism previously proposed involves subthreshold calcium-dependent oscillations in all parts of the neuron. In that mechanism, the natural frequency of oscillation varies with diameter of cell processes, so there is a wide variation of natural frequencies on the cell, but strong voltage coupling enforces a single frequency of oscillation under resting conditions. In previous work, mathematical analysis of a simpler system of oscillators showed that the chain of oscillators could produce transient dynamics in which the frequency of the coupled system increased temporarily, as seen in a biophysical model of the dopaminergic neuron. The transient dynamics was shown to be consequence of a slow drift along an invariant subset of phase space, with rate of drift given by a Lyapunov function. In this paper, we show that the same mathematical structure exists for the full biophysical model, giving physiological meaning to the slow drift and the Lyapunov function, which is shown to describe differences in intracellular calcium concentration in different parts of the cell. The duration of transients was long, being comparable to the time constant of calcium disposition. These results indicate that brief changes in input to the dopaminergic neuron can produce long lasting firing rate transients whose form is determined by intrinsic cell properties.     

Regional slow waves and spindles in human sleep

The most prominent EEG events in sleep are slow waves, reflecting a slow (<1 Hz) oscillation between up and down states in cortical neurons. It is unknown whether slow oscillations are synchronous across the majority or the minority of brain regions--are they a global or local phenomenon? To examine this, we recorded simultaneously scalp EEG, intracerebral EEG, and unit firing in multiple brain regions of neurosurgical patients. We find that most sleep slow waves and the underlying active and inactive neuronal states occur locally. Thus, especially in late sleep, some regions can be active while others are silent. We also find that slow waves can propagate, usually from medial prefrontal cortex to the medial temporal lobe and hippocampus. Sleep spindles, the other hallmark of NREM sleep EEG, are likewise predominantly local. Thus, intracerebral communication during sleep is constrained because slow and spindle oscillations often occur out-of-phase in different brain regions.     

Firing pattern and synchronization property analysis in a network model of the olfactory bulb

In the olfactory system, both the temporal spike structure and spatial distribution of neuronal activity are important for processing odor information. In this paper, a biophysically-detailed, spiking neuronal model is used to simulate the activity of olfactory bulb. It is shown that by varying some key parameters such as maximal conductances of Ks and Nap the spike train of single neuron can exhibit various firing patterns. Synchronization in coupled neurons is also investigated as the coupling strength varying in the situation of two neurons and network. It is illustrated that the coupled neurons can exhibit different types of pattern when the coupling strength varies. These results may be instructive to understand information transmission in olfactory system.     

Information processing in the olfactory systems of insects and vertebrates

Insects and vertebrates separately evolved remarkably similar mechanisms to process olfactory information. Odors are sampled by huge numbers of receptor neurons, which converge type-wise upon a much smaller number of principal neurons within glomeruli. There, odor information is transformed by inhibitory interneuron-mediated, cross-glomerular circuit interactions that impose slow temporal structures and fast oscillations onto the firing patterns of principal neurons. The transformations appear to improve signal-to-noise characteristics, define odor categories, achieve precise odor identification, extract invariant features, and begin the process of sparsening the neural representations of odors for efficient discrimination, memorization, and recognition.     

Membrane Potential Oscillations Produced by Excitatory Amino Acids in Isolated Spinal Neurons of the Lamprey Lampetra fluviatilis

Membrane potential (MP) oscillations produced by excitatory amino acids (EAA) have been studied in branching neurons isolated by an enzymatic-mechanical method from the lamprey spinal cord. It was shown that (1) all studied EAA (glutamate, kainate, NMDA, aspartate, and quisqualate) evoke an ion current and a short-term reversible depolarization in studied cells; (2) EAA added to perfusion solution may produce MP oscillations, with kinetic parameters and duration of the oscillation depending on the amino acid used (the most effective are kainate and NMDA, the least effective, quisqualate); (3) oscillations can be irregular (of the type of a synaptic noise or of a long-term plateau of depolarization with action potentials—AP) or regular, with frequency of 0.5–1.5 Hz. Amplitude of both oscillation types depends on MP level, frequency is more steady for each cell and less depends on MP. In 68 out of 128 studied cells, oscillations could be evoked, which indicates that a significant part of lamprey spinal neurons have intrinsic capability for MP oscillations and probably pacemaker properties. The functional role of oscillations can be different. They can take cells out from the profound inhibition state, synchronize activity of rhythm generation neurons and/or be the base for trigger signals (AP firing) sent by locomotor neuronal circuits to trunk muscles.     

A basic biophysical model for bursting neurons

Presented here is a basic biophysical cell model for bursting, an extension of our previous model (Av-Ron et al. 1991) for excitability and oscillations. By changing a limited set of model parameters, one can describe different patterns of bursting behavior in terms of the burst cycle, the durations of oscillation and quiescence, and firing frequency.     

Computational Models Describing Possible Mechanisms for Generation of Excessive Beta Oscillations in Parkinson’s Disease

In Parkinson’s disease, an increase in beta oscillations within the basal ganglia nuclei has been shown to be associated with difficulty in movement initiation. An important role in the generation of these oscillations is thought to be played by the motor cortex and by a network composed of the subthalamic nucleus (STN) and the external segment of globus pallidus (GPe). Several alternative models have been proposed to describe the mechanisms for generation of the Parkinsonian beta oscillations. However, a recent experimental study of Tachibana and colleagues yielded results which are challenging for all published computational models of beta generation. That study investigated how the presence of beta oscillations in a primate model of Parkinson’s disease is affected by blocking different connections of the STN-GPe circuit. Due to a large number of experimental conditions, the study provides strong constraints that any mechanistic model of beta generation should satisfy. In this paper we present two models consistent with the data of Tachibana et al. The first model assumes that Parkinsonian beta oscillation are generated in the cortex and the STN-GPe circuits resonates at this frequency. The second model additionally assumes that the feedback from STN-GPe circuit to cortex is important for maintaining the oscillations in the network. Predictions are made about experimental evidence that is required to differentiate between the two models, both of which are able to reproduce firing rates, oscillation frequency and effects of lesions carried out by Tachibana and colleagues. Furthermore, an analysis of the models reveals how the amplitude and frequency of the generated oscillations depend on parameters.     

High-frequency organization and synchrony of activity in the purkinje cell layer of the cerebellum

The cerebellum controls complex, coordinated, and rapid movements, a function requiring precise timing abilities. However, the network mechanisms that underlie the temporal organization of activity in the cerebellum are largely unexplored, because in vivo recordings have usually targeted single units. Here, we use tetrode and multisite recordings to demonstrate that Purkinje cell activity is synchronized by a high-frequency (approximately 200 Hz) population oscillation. We combine pharmacological experiments and modeling to show how the recurrent inhibitory connections between Purkinje cells are sufficient to generate these oscillations. A key feature of these oscillations is a fixed population frequency that is independent of the firing rates of the individual cells. Convergence in the deep cerebellar nuclei of Purkinje cell activity, synchronized by these oscillations, likely organizes temporally the cerebellar output.     

Recent advances in the development of bioelectronic nose

The olfactory system has the ability to discriminate and identify thousands of odorant compounds at very low concentrations. Recently, many researchers have been trying to develop artificial sensing devices that are based on the olfactory system. A bioelectronic nose, which uses olfactory receptors (ORs) as sensing elements, would benefit naturally optimized molecular recognition. Accordingly, ORs can be effectively used as a biological element in bioelectronic noses. Bioelectronic nose can be classified into cell-based and protein-based biosensors. The cell-based biosensor uses living cells that express olfactory receptors as the biological sensing elements and the protein-based biosensor uses the olfactory receptor protein. The binding of odorant molecules to the ORs can be measured using various methods such as piezoelectric, optic, and electric devices. Thus, bioelectronic nose can be developed by combining the biological sensing elements with these non-biological devices. The application of bioelectronic nose in a wide range of different scientific and medical fields is essentially dependent on the development of highly sensitive and selective biosensors. These sensor systems for the rapid detection of specific odorants are crucial for environmental monitoring, anti-bioterrorism, disease diagnostics, and food safety. In this article, we reviewed recent advances in the development of bioelectronic nose.     

Oscillatory current responses of olfactory receptor neurons to odorants and computer simulation based on a cyclic AMP transduction model

Neural oscillatory activities triggered by odorant stimulation have been often reported at various levels of olfactory nervous systems in vertebrates. To elucidate the origin of neural oscillations, we studied first the oscillatory properties of current responses of isolated olfactory receptor neurons (ORNs) of the rainbow trout to amino acid odorants, using a whole-cell voltage-clamp technique and found that the damped current oscillations were intrinsic in both ciliated and microvillous ORNs and occurred when ORNs were stimulated by odorants at high intensities. Continuous wavelet analysis using the Gabor function revealed that the dominant frequency of oscillations was 1.89 +/- 0.50 Hz (mean +/- SD, n = 92). There was no significant difference in oscillation frequency between the two types of ORNs and between different perfusion conditions with standard and Na(+)-free (choline) Ringer's solutions, but there was a slight difference in oscillation frequency between different holding potential conditions of negative and positive potentials. We then performed a computer simulation of the current responses with a cAMP olfactory transduction model. The model was based on the assumption that the current responses of ORNs were linearly related to the sum of concentrations of active cyclic-nucleotide-gated channels and Ca(2+)-activated Cl(-) channels, and was expressed by 12 differential equations with 44 different parameters. The simulation revealed that the oscillations of current responses of ORNs were mainly due to the oscillatory properties of intracellular cAMP and Ca(2+) concentrations. The necessary reaction component for the oscillations in the transduction model was direct inhibition of adenylate cyclase activity by Ca(2+). High Ca(2+) efflux by the Na(+)-Ca(2+) exchanger and cAMP-phosphodiesterase activity were most influential on the oscillations. The simulation completely represented the characteristics of current responses of ORNs: odorant-intensity-dependent response, intensity-dependent latency and adaptation. Thus, the simulation is generally applicable to current and voltage responses of ORNs equipped with cAMP olfactory transduction pathway in other vertebrate species. The simulation programs for Macintosh (cAMP 9.2.7 and 9.2.8 for MacOS 8.1 or later) and cAMP JAVA applet versions based on cAMP 9.2.8 have been published on the world wide web (http://bio2.sci.hokudai.ac.jp/bio/chinou1/noriyo_home.html).     

Brain stimulation competes with ongoing oscillations for control of spike timing in the primate brain

Transcranial alternating current stimulation (tACS) is a popular method for modulating brain activity noninvasively. In particular, tACS is often used as a targeted intervention that enhances a neural oscillation at a specific frequency to affect a particular behavior. However, these interventions often yield highly variable results. Here, we provide a potential explanation for this variability: tACS competes with the brain’s ongoing oscillations. Using neural recordings from alert nonhuman primates, we find that when neural firing is independent of ongoing brain oscillations, tACS readily entrains spiking activity, but when neurons are strongly entrained to ongoing oscillations, tACS often causes a decrease in entrainment instead. Consequently, tACS can yield categorically different results on neural activity, even when the stimulation protocol is fixed. Mathematical analysis suggests that this competition is likely to occur under many experimental conditions. Attempting to impose an external rhythm on the brain may therefore often yield precisely the opposite effect.

Transcranial alternating current stimulation (tACS) is a popular method for modulating brain activity noninvasively; however, tACS can often yield highly variable results. This study shows that when neurons are strongly entrained to ongoing oscillations, tACS often causes a decrease in entrainment instead of the expected enhancement.