Encoding mechanisms based on fast oscillations in the retina of the cat and their dependencies on anesthesia

Processing in the visual system starts in the retina. Its complex network of cells with different properties enables for parallel encoding and transmission of visual information to the lateral geniculate nucleus (LGN) and to the cortex. In the retina, it has been shown that responses are often accompanied by fast synchronous oscillations (30 - 90 Hz) in a stimulus-dependent manner. Studies in the frog, rabbit, cat and monkey, have shown strong oscillatory responses to large stimuli which probably encode global stimulus properties, such as size and continuity (Neuenschwander and Singer, 1996; Ishikane et al., 2005). Moreover, simultaneous recordings from different levels in the visual system have demonstrated that the oscillatory patterning of retinal ganglion cell responses are transmitted to the cortex via the LGN (Castelo-Branco et al., 1998). Overall these results suggest that feedforward synchronous oscillations contribute to visual encoding. In the present study on the LGN of the anesthetized cat, we further investigate the role of retinal oscillations in visual processing by applying complex stimuli, such as natural visual scenes, light spots of varying size and contrast, and flickering checkerboards. This is a necessary step for understanding encoding mechanisms in more naturalistic conditions, as currently most data on retinal oscillations have been limited to simple, flashed and stationary stimuli. Correlation analysis of spiking responses confirmed previous results showing that oscillatory responses in the retina (observed here from the LGN responses) largely depend on the size and stationarity of the stimulus. For natural scenes (gray-level and binary movies) oscillations appeared only for brief moments probably when receptive fields were dominated by large continuous, flat-contrast surfaces. Moreover, oscillatory responses to a circle stimulus could be broken with an annular mask indicating that synchronization arises from relatively local interactions among populations of activated cells in the retina. A surprising finding in this study was that retinal oscillations are highly dependent on halothane anesthesia levels. In the absence of halothane, oscillatory activity vanished independent of the characteristics of the stimuli. The same results were obtained for isoflurane, which has similar pharmacological properties. These new and unexpected findings question whether feedfoward oscillations in the early visual system are simply due to an imbalance between excitation and inhibition in the retinal networks generated by the halogenated anesthetics. Further studies in awake behaving animals are necessary to extend these conclusions

Recurrent excitatory postsynaptic potentials induced by synchronized fast cortical oscillations

Gamma frequency (about 20–70 Hz) oscillations occur during novel sensory stimulation, with tight synchrony over distances of at least 7 mm. Synchronization in the visual system has been proposed to reflect coactivation of different parts of the visual field by a single spatially extended object. We have shown that intracortical mechanisms, including spike doublet firing by interneurons, can account for tight long-range synchrony. Here we show that synchronous gamma oscillations in two sites also can cause long-lasting (>1 hr) potentiation of recurrent excitatory synapses. Synchronous oscillations lasting >400 ms in hippocampal area CA1 are associated with an increase in both excitatory postsynaptic potential (EPSP) amplitude and action potential afterhyperpolarization size. The resulting EPSPs stabilize and synchronize a prolonged beta frequency (about 10–25 Hz) oscillation. The changes in EPSP size are not expressed during non-oscillatory behavior but reappear during subsequent gamma-oscillatory events. We propose that oscillation-induced EPSPs serve as a substrate for memory, whose expression either enhances or blocks synchronization of spatially separated sites. This phenomenon thus provides a dynamical mechanism for storage and retrieval of stimulus-specific neuronal assemblies.

Emergent spindle oscillations and intermittent burst firing in a thalamic model: specific neuronal mechanisms.

The rhythmogenesis of 10-Hz sleep spindles is studied in a large-scale thalamic network model with two cell populations: the excitatory thalamocortical (TC) relay neurons and the inhibitory nucleus reticularis thalami (RE) neurons. Spindle-like bursting oscillations emerge naturally from reciprocal interactions between TC and RE neurons. We find that the network oscillations can be synchronized coherently, even though the RE-TC connections are random and sparse, and even though individual neurons fire rebound bursts intermittently in time. When the fast gamma-aminobutyrate type A synaptic inhibition is blocked, synchronous slow oscillations resembling absence seizures are observed. Near-maximal network synchrony is established with even modest convergence in the RE-to-TC projection (as few as 5-10 RE inputs per TC cell suffice). The hyperpolarization-activated cation current (Ih) is found to provide a cellular basis for the intermittency of rebound bursting that is commonly observed in TC neurons during spindles. Such synchronous oscillations with intermittency can be maintained only with a significant degree of convergence for the TC-to-RE projection.

Detection and description of non-linear interdependence in normal multichannel human EEG data

Objectives: This study examines human scalp electroencephalographic (EEG) data for evidence of non-linear interdependence between posterior channels. The spectral and phase properties of those epochs of EEG exhibiting non-linear interdependence are studied. Methods: Scalp EEG data was collected from 40 healthy subjects. A technique for the detection of non-linear interdependence was applied to 2.048 s segments of posterior bipolar electrode data. Amplitude-adjusted phase-randomized surrogate data was used to statistically determine which EEG epochs exhibited non-linear interdependence. Results: Statistically significant evidence of non-linear interactions were evident in 2.9% (eyes open) to 4.8% (eyes closed) of the epochs. In the eyes-open recordings, these epochs exhibited a peak in the spectral and cross-spectral density functions at about 10 Hz. Two types of EEG epochs are evident in the eyes-closed recordings; one type exhibits a peak in the spectral density and cross-spectrum at 8 Hz. The other type has increased spectral and cross-spectral power across faster frequencies. Epochs identified as exhibiting non-linear interdependence display a tendency towards phase interdependencies across and between a broad range of frequencies. Conclusions: Non-linear interdependence is detectable in a small number of multichannel EEG epochs, and makes a contribution to the alpha rhythm. Non-linear interdependence produces spatially distributed activity that exhibits phase synchronization between oscillations present at different frequencies. The possible physiological significance of these findings are discussed with reference to the dynamical properties of neural systems and the role of synchronous activity in the neocortex. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures

Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures

Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

Time-of-flight two-photon photoemission spectromicroscopy with femtosecond laser radiation

Time-of-flight photoemission spectromicroscopy was used to measure and compare the two-photon photoemission (2PPE) spectra of Cu and Ag nanoparticles with linear dimensions ranging between 40 nm and several 100 nm, with those of the corresponding homogeneous surfaces. 2PPE was induced employing femtosecond laser radiation from a frequency-doubled Ti:sapphire laser in the spectral range between 375 nm and 425 nm with a pulse width of 200 fs and a repetition rate of 80 MHz. The use of a pulsed radiation source allowed us to use a high-resolution photoemission electron microscope as imaging time-of-flight spectrometer, and thus to obtain spectroscopic information about the laterally resolved electron signal. Ag nanoparticle films have been deposited on Si(111) by electron-beam evaporation, a technique leading to hemispherically-shaped Ag clusters. Isolated Cu nanoparticles have been generated by prolonged heating of a polycrystalline Cu sample. If compared to the spectra of the corresponding homogeneous surfaces, the Cu and Ag nanoparticle spectra are characterized by a strongly enhanced total 2PPE yield (enhancement factor up to 70), by a shift (about 0.1 eV) of the Fermi level onset towards lower final state energies, by a reduction of the work function (typically by 0.2 eV) and by a much steeper increase of the 2PPE yield towards lower final state energies. The shift of the Fermi level onset in the nanoparticle spectra has been explained by a positive unit charge (localized photohole) residing on the particle during the time-scale relevant for the 2PPE process (few femtoseconds). The total 2PPE yield enhancement and the different overall shape of the spectra have been explained by considering that the laser frequency was close to the localized surface plasmon resonance of the Cu and Ag nanoparticles. The synchronous oscillations induced by the laser in the metal electrons enhance the near-zone (NZ) field, defined as the linear superposition of the laser field and the field produced in the vicinity of the particles by the forced charge oscillations. From the present measurements it is clear that the NZ field behavior is responsible for the 2PPE enhancement and affects the 2PPE spatial and energy distribution and its dynamics. In particular, its strong spatial dependence allows indirect transitions through real intermediate states to take place in the metal clusters. Such transitions are forbidden by momentum conservation arguments and are thus experimentally much less probable on homogeneous surfaces. Further, we investigated specially tailored moon-shaped small metal nanostructures, whose NZ field was theoretically predicted, and compared the calculation with the laterally resolved 2PPE signal. We could show that the 2PPE signal gives a clear fingerprint of the theoretically predicted spatial dependence of the NZ field. This potential of our method is highly attractive in the novel field of plasmonics.

BOLD correlates of EEG alpha phase-locking and the fMRI default mode network

Phase locking or synchronization of brain areas is a key concept of information processing in the brain. Synchronous oscillations have been observed and investigated extensively in EEG during the past decades. EEG oscillations occur over a wide frequency range. In EEG, a prominent type of oscillations is alpha-band activity, present typically when a subject is awake, but at rest with closed eyes. The spectral power of alpha rhythms has recently been investigated in simultaneous EEG/fMRI recordings, establishing a wide-range cortico-thalamic network. However, spectral power and synchronization are different measures and little is known about the correlations between BOLD effects and EEG synchronization. Interestingly, the fMRI BOLD signal also displays synchronous oscillations across different brain regions. These oscillations delineate so-called resting state networks (RSNs) that resemble the correlation patterns of simultaneous EEG/fMRI recordings. However, the nature of these BOLD oscillations and their relations to EEG activity is still poorly understood. One hypothesis is that the subunits constituting a specific RSN may be coordinated by different EEG rhythms. In this study we report on evidence for this hypothesis. The BOLD correlates of global EEG synchronization (GFS) in the alpha frequency band are located in brain areas involved in specific RSNs, e.g. the 'default mode network'. Furthermore, our results confirm the hypothesis that specific RSNs are organized by long-range synchronization at least in the alpha frequency band. Finally, we could localize specific areas where the GFS BOLD correlates and the associated RSN overlap. Thus, we claim that not only the spectral dynamics of EEG are important, but also their spatio-temporal organization.

Speleothem U-series dating of semi-synchronous climate oscillations during the last deglaciation

Evidence for nearly synchronous climate oscillations during the last deglaciation has been found throughout the Northern Hemisphere but few records are based on independent time scales of calendar years. We present a rare uranium-series dated oxygen-carbon isotope record for a speleothem from Tangshan Cave, China, which demonstrates that abrupt deglacial climatic oscillations from 16 800 to 10 500 yr BP are semi-synchronous with those found in Greenland ice core records. Relatively rapid shifts in speleothem oxygen isotope ratios demonstrate that the intensity of the East Asian monsoon switched in parallel with the abrupt transitions separating the Bolling-Allerod, Younger Dryas, and pre-Boreal climatic reversals. However, the dated isotopic transitions appear to have lasted longer. Our results demonstrate the dominant role of atmospheric teleconnections in the rapid propagation of deglacial climatic signals on a hemispheric scale, and highlight the importance of U-series dated speleothems in the timing and characterization of abrupt climate change. (C) 2003 Elsevier B.V. All rights reserved.

Synchronous and baroceptor-sensitive oscillations in skin microcirculation: evidence for central autonomic control.

To determine whether skin blood flow is local or takes part in general regulatory mechanisms, we recorded laser-Doppler flowmetry (LDF; left and right index fingers), blood pressure, muscle sympathetic nerve activity (MSNA), R-R interval, and respiration in 10 healthy volunteers and 3 subjects after sympathectomy. We evaluated 1) the synchronism of LDF fluctuations in two index fingers, 2) the relationship with autonomically mediated fluctuations in other signals, and 3) the LDF ability to respond to arterial baroreflex stimulation (by neck suction at frequencies from 0.02 to 0.20 Hz), using spectral analysis (autoregressive uni- and bivariate, time-variant algorithms). Synchronous LDF fluctuations were observed in the index fingers of healthy subjects but not in sympathectomized patients. LDF fluctuations were coherent with those obtained for blood pressure, MSNA, and R-R interval. LDF fluctuations were leading blood pressure in the low-frequency (LF; 0.1 Hz) band and lagging in the respiratory, high-frequency (HF; approximately 0.25 Hz) band, suggesting passive "downstream" transmission only for HF and "upstream" transmission for LF from the microvessels. LDF fluctuations were responsive to sinusoidal neck suction up to 0.1 Hz, indicating response to sympathetic modulation. Skin blood flow thus reflects modifications determined by autonomic activity, detectable by frequency analysis of spontaneous fluctuations.

Synchronous Holocene climatic oscillations recorded on the Swiss Plateau and at timberline in the Alps

Eight synchronous pre-Roman cold phases were found at 9600–9200, 8600–8150, 7550–6900, 6600– 6200, 5350–4900, 4600–4400, 3500–3200 and 2600–2350 radiocarbon years BP by reconstructing past climate at two sites on the Swiss Plateau and at timberline in the Alps. The cooling events during the early-and mid-Holocene represent temperature values similar to today, and apparently the onset of cooling events represents a deviation from today's mean annual temperature of about 1°C and is triggered at a 1000-year periodicity. At Wallisellen-Langachermoos (440 m), a former oligotrophic lake near Zürich, the correlation between sum mertime lake levels and the seed production of the amphi-Atlantic aquatic plantNajas flexilis was used to reconstruct lake levels over a 3000-year period during the first part of the Holocene. At Lake Seedorf on the western Swiss Plateau (609 m) the sedimentological, palynological and macrofossil record revealed fluctuations of lake levels for the complete Holocene. From Lago Basso in the southern Alps (2250 m, Val San Giacomo near Splügen Pass, Northern Italy) the terrestrial plant macrofossils – especiallyPinus cembra andLarix – allowed the reconstruction of timberline fluctuations controlled by climate. A similar climatic pattern was found at Gouillé Rion pond in the central Swiss Alps (2343 m, Val d'Hérémence) with plant macrofossils and pollen concentrations and percentages. We postulate that these climatic events are detectable throughout central Europe by independent methods in combination with precise AMS-radiocarbon datings on terrestrial plant remains. Our data fit other proxy records of regional climatic change, such as cool intervals from Greenland ice cores, glacier movements in the Swiss and Austrian Alps, and dendro-densitometry on subfossil wood, as well as the palaeoclimatic data from the Jura Mountains of France obtained by sedimentological analyses. Thus our data indicate that the Northern Hemisphere climate was less stable during the Holocene than previously believed.

Effect of dopamine on synchronous neuronal oscillations in the globus pallidus-subthalamic nucleus network

Changes in the pattern of activity of neurones within the basal ganglia are relevant in the pathophysiology and symptoms of Parkinson’s disease. The globus pallidus (GP) – subthalamic nucleus (STN) network has been proposed to form a pacemaker driving regenerative synchronous bursting activity. In order to test whether this activity can be sustained in vitro a 20o parasagittal slice of mouse midbrain was developed which preserved functional connectivity between the STN and GP. Mouse STN and GP cells were characterised electrophysiologically by the presence or absence of a voltage sag in response to hyperpolarising current steps indicative of Ih and the presence of rebound depolarisations. The presence of evoked and spontaneous post-synaptic GABA and glutamatergic currents indicated functional connectivity between the STN and GP. In control slices, STN cells fired action potentials at a regular rate, activity which was unaffected by bath application of the GABAA receptor antagonist picrotoxin (50 μM) or the glutamate receptor antagonist CNQX (10 μM). Paired extracellular recordings of STN cells showed uncorrelated firing. Oscillatory burst activity was induced pharmacologically using the glutamate receptor agonist, NMDA (20 μM), in combination with the potassium channel blocker apamin (50 -100 nM). The burst activity was unaffected by bath application of picrotoxin or CNQX while paired STN recordings showed uncorrelated activity indicating that the activity is not produced by the neuronal network. Thus, no regenerative activity is evident in this mouse brain preparation, either in control slices or when bursting is pharmacologically induced, suggesting the requirement of other afferent inputs that are not present in the slice. Using single-unit extracellular recording, dopamine (30 μM) produced an excitation of STN cells. This excitation was independent of synaptic transmission and was mimicked by both the Dl-like receptor agonist SKF38393 (10 μM) and the D2-like receptor agonist quinpirole (10 μM). However, the excitation was partially reduced by the D1-like antagonist SCH23390 (2 μM) but not by the D2-like antagonists sulpiride (10 μM) and eticlopride (10 μM). Using whole-recordings, dopamine was shown to induce membrane depolarisation. This depolarisation was caused either by a D1-like receptor mediated increase in a conductance which reversed at -34 mV, consistent with a non-specific cation conductance, or a D2-like receptor mediated decrease in conductance which reversed around -100 mV, consistent with a potassium conductance. Bath application of dopamine altered the pattern of the burst-firing produced by NMDA an apamin towards a more regular pattern. This effect was associated with a decrease in amplitude and ll1crease in frequency of TTX-resistant plateau potentials which underlie the burst activity.

Stimulus statistics shape oscillations in nonlinear recurrent neural networks.

Rhythmic activity plays a central role in neural computations and brain functions ranging from homeostasis to attention, as well as in neurological and neuropsychiatric disorders. Despite this pervasiveness, little is known about the mechanisms whereby the frequency and power of oscillatory activity are modulated, and how they reflect the inputs received by neurons. Numerous studies have reported input-dependent fluctuations in peak frequency and power (as well as couplings across these features). However, it remains unresolved what mediates these spectral shifts among neural populations. Extending previous findings regarding stochastic nonlinear systems and experimental observations, we provide analytical insights regarding oscillatory responses of neural populations to stimulation from either endogenous or exogenous origins. Using a deceptively simple yet sparse and randomly connected network of neurons, we show how spiking inputs can reliably modulate the peak frequency and power expressed by synchronous neural populations without any changes in circuitry. Our results reveal that a generic, non-nonlinear and input-induced mechanism can robustly mediate these spectral fluctuations, and thus provide a framework in which inputs to the neurons bidirectionally regulate both the frequency and power expressed by synchronous populations. Theoretical and computational analysis of the ensuing spectral fluctuations was found to reflect the underlying dynamics of the input stimuli driving the neurons. Our results provide insights regarding a generic mechanism supporting spectral transitions observed across cortical networks and spanning multiple frequency bands.

On the Analysis and Control of a Linear Synchronous Servomotor with a Flexible Load

Industry's growing need for higher productivity is placing new demands on mechanisms connected with electrical motors, because these can easily lead to vibration problems due to fast dynamics. Furthermore, the nonlinear effects caused by a motor frequently reduce servo stability, which diminishes the controller's ability to predict and maintain speed. Hence, the flexibility of a mechanism and its control has become an important area of research. The basic approach in control system engineering is to assume that the mechanism connected to a motor is rigid, so that vibrations in the tool mechanism, reel, gripper or any apparatus connected to the motor are not taken into account. This might reduce the ability of the machine system to carry out its assignment and shorten the lifetime of the equipment. Nonetheless, it is usually more important to know how the mechanism, or in other words the load on the motor, behaves. A nonlinear load control method for a permanent magnet linear synchronous motor is developed and implemented in the thesis. The purpose of the controller is to track a flexible load to the desired velocity reference as fast as possible and without awkward oscillations. The control method is based on an adaptive backstepping algorithm with its stability ensured by the Lyapunov stability theorem. As a reference controller for the backstepping method, a hybrid neural controller is introduced in which the linear motor itself is controlled by a conventional PI velocity controller and the vibration of the associated flexible mechanism is suppressed from an outer control loop using a compensation signal from a multilayer perceptron network. To avoid the local minimum problem entailed in neural networks, the initial weights are searched for offline by means of a differential evolution algorithm. The states of a mechanical system for controllers are estimated using the Kalman filter. The theoretical results obtained from the control design are validated with the lumped mass model for a mechanism. Generalization of the mechanism allows the methods derived here to be widely implemented in machine automation. The control algorithms are first designed in a specially introduced nonlinear simulation model and then implemented in the physical linear motor using a DSP (Digital Signal Processor) application. The measurements prove that both controllers are capable of suppressing vibration, but that the backstepping method is superior to others due to its accuracy of response and stability properties.

Comparison of FACTS STATCOM models for damping oscillations in power system due to small perturbations

This paper presents small-signal stability studies of a multimachine power system, considering Static Synchronous Compensators (STATCOM)and discussed control modes of the STATCOM. The Power Sensitivity Model(PSM)is used to represent the electric power system. The study is based on modal analysis and time domain simulations. The results obtained allow concluding that the STATCOM improves the stabilization in the electric power system. © 2011 IEEE.