Perception-related modulations of local field potential power and coherence in primary visual cortex of awake monkey during binocular rivalry

Cortical synchronization at γ-frequencies (35–90 Hz) has been proposed to define the connectedness among the local parts of a perceived visual object. This hypothesis is still under debate. We tested it under conditions of binocular rivalry (BR), where a monkey perceived alternations among conflicting gratings presented singly to each eye at orthogonal orientations. We made multi-channel microelectrode recordings of multi-unit activity (MUA) and local field potentials (LFP) from striate cortex (V1) during BR while the monkey indicated his perception by pushing a lever. We analyzed spectral power and coherence of MUA and LFP over 4–90 Hz. As in previous work, coherence of γ-signals in most pairs of recording locations strongly depended on grating orientation when stimuli were presented congruently in both eyes. With incongruent (rivalrous) stimulation LFP power was often consistently modulated in consonance with the perceptual state. This was not visible in MUA. These perception-related modulations of LFP occurred at low and medium frequencies (<30 Hz), but not at γ-frequencies. Perception-related modulations of LFP coherence were also restricted to the low–medium range. In conclusion, our results do not support the expectation that γ-synchronization in V1 is related to the perceptual state during BR, but instead suggest a perception-related role of synchrony at low and medium frequencies

Spatiotemporal receptive field properties of epiretinally recorded spikes and local electroretinograms in cats

BACKGROUND: Receptive fields of retinal neural signals of different origin can be determined from extracellular microelectrode recordings at the inner retinal surface. However, locations and types of neural processes generating the different signal components are difficult to separate and identify. We here report epiretinal receptive fields (RFs) from simultaneously recorded spikes and local electroretinograms (LERGs) using a semi-chronic multi-electrode in vivo recording technique in cats. Broadband recordings were filtered to yield LERG and multi unit as well as single unit spike signals. RFs were calculated from responses to multifocal pseudo-random spatiotemporal visual stimuli registered at the retinal surface by a 7-electrode array. RESULTS: LERGs exhibit spatially unimodal RFs always centered at the location of the electrode tip. Spike-RFs are either congruent with LERG-RFs (N = 26/61) or shifted distally (N = 35/61) but never proximally with respect to the optic disk. LERG-RFs appear at shorter latencies (11.9 ms ± 0.5 ms, N = 18) than those of spikes (18.6 ms ± 0.4 ms, N = 53). Furthermore, OFF-center spike-RFs precede and have shorter response rise times than ON-center spike-RFs. Our results indicate that displaced spike-RFs result from action potentials of ganglion cell axons passing the recording electrode en route to the optic disk while LERG-RFs are related to superimposed postsynaptic potentials of cells near the electrode tip. CONCLUSION: Besides contributing to the understanding of retinal function we demonstrate the caveats that come with recordings from the retinal surface, i.e., the likelihood of recordings from mixed sets of retinal neurons. Implications for the design of an epiretinal visual implant are discussed

Konzeptionelle Modellierung geometrischer Invarianzen in der visuellen Wahrnehmung von Primaten - Situativ gesteuerte Complex-Bildung als Grundlage invarianter Zellantworten

Unser Sehsinn vermittelt uns eine stabile Wahrnehmung der Umwelt. Objekte darin erkennen wir unabhängig von der Position, die wir ihnen gegenüber einnehmen. Diese invariante Wahrnehmung ist im Rahmen der verfügbaren neuronalen Modelle nur mit Einschränkungen zu erklären. Die Standardmodelle basieren auf einer hierarchischen Anordnung von Nervenzellen, deren Ziel es ist, spezifische neuronale Antworten für komplexe visuelle Reize aus Antworten auf einfache Reizkomponenten zu konstruieren. Ein wesentliches Konzept ist dabei die neuronale Oder-Bildung (Complex-Bildung) durch konvergente Verschaltung. Die Generierung von Invarianz für bestimmte Reizvariationen läuft hierbei der Formierung reizspezifischer Antworten entgegen -- auf Ebene des Signalflusses im Netzwerk, wie auch als Denkmodell. Die klassischen Modelle zur invarianten visuellen Formerkennung weisen daher Schwächen auf, etwa das Binde-Problem oder die Ununterscheidbarkeit von Objekten mit überlappenden Repräsentantenmengen. Die vorliegende Arbeit nähert sich dieser Problematik vom Blickwinkel der konzeptionellen Modellierung. Ein lebendiges Individuum erfährt seine Umwelt aktiv: Äußere physikalisch-körperliche Umstände beeinflussen die Verarbeitung im visuellen System. Ich formuliere hier das Konzept der situativ gesteuerten Complex-Bildung, das auf einer Steuerung der Übertragungseigenschaften einzelner Neuronen durch externe Parameter beruht. Seine Leistungsfähigkeit demonstriere ich in zwei Modellen zur invarianten visuellen Verarbeitung, der neuronalen retinalen Schlupfkorrektur und der entfernungsinvarianten Objektrepräsentation. Die Modelle überwinden entscheidende Probleme der klassischen Modellierung, erfordern jedoch einen erhöhten neuronalen Aufwand. Im Falle des Entfernungsinvarianzmodells führt der Einsatz der situativ gesteuerten Complex-Bildung zur Vorhersage einer neuartigen Zellklasse, den Entfernungs-Complex-Zellen. Neuronen mit teilweise ähnlichen Codierungseigenschaften wurden in jüngster Zeit experimentell nachgewiesen. In beiden Modellen wird durch die situativ gesteuerte Complex-Bildung eine Szenenrepräsentation generiert, die vom verwendeten Steuerparameter unabhängig ist. Es ist zu erwarten, daß auf gleiche Weise Invarianz auch gegenüber anderen äußeren Bedingungen erzeugt werden kann. Die situativ gesteuerte Complex-Bildung erweist sich so als universell einsetzbares Werkzeug zur konzeptionellen Modellierung neuronaler Invarianzen. Damit liefert sie auch ein effektives Denkmodell für das weitere Verständnis kortikaler Verarbeitung

Neural models of learning and visual grouping in the presence of finite conduction velocities

The hypothesis of object binding-by-synchronization in the visual cortex has been supported by recent experiments in awake monkeys. They demonstrated coherence among gamma-activities (30–90 Hz) of local neural groups and its perceptual modulation according to the rules of figure-ground segregation. Interactions within and between these neural groups are based on axonal spike conduction with finite velocities. Physiological studies confirmed that the majority of transmission delays is comparable to the temporal scale defined by gamma-activity (11–33 ms). How do these finite velocities influence the development of synaptic connections within and between visual areas? What is the relationship between the range of gamma-coherence and the velocity of signal transmission? Are these large temporal delays compatible with recently discovered phenomenon of gamma-waves traveling across larger parts of the primary visual cortex? The refinement of connections in the immature visual cortex depends on temporal Hebbian learning to adjust synaptic efficacies between spiking neurons. The impact of constant, finite, axonal spike conduction velocities on this process was investigated using a set of topographic network models. Random spike trains with a confined temporal correlation width mimicked cortical activity before visual experience. After learning, the lateral connectivity within one network layer became spatially restricted, the width of the connection profile being directly proportional to the lateral conduction velocity. Furthermore, restricted feedforward divergence developed between neurons of two successive layers. The size of this connection profile matched the lateral connection profile of the lower layer neuron. The mechanism in this network model is suitable to explain the emergence of larger receptive fields at higher visual areas while preserving a retinotopic mapping. The influence of finite conduction velocities on the local generation of gamma-activities and their spatial synchronization was investigated in a model of a mature visual area. Sustained input and local inhibitory feedback was sufficient for the emergence of coherent gamma-activity that extended across few millimeters. Conduction velocities had a direct impact on the frequency of gamma-oscillations, but did neither affect gamma-power nor the spatial extent of gamma-coherence. Adding long-range horizontal connections between excitatory neurons, as found in layer 2/3 of the primary visual cortex, increased the spatial range of gamma-coherence. The range was maximal for zero transmission delays, and for all distances attenuated with finite, decreasing lateral conduction velocities. Below a velocity of 0.5 m/s, gamma-power and gamma-coherence were even smaller than without these connections at all, i.e., slow horizontal connections actively desynchronized neural populations. In conclusion, the enhancement of gamma-coherence by horizontal excitatory connections critically depends on fast conduction velocities. Coherent gamma-activity in the primary visual cortex and the accompanying models was found to only cover small regions of the visual field. This challenges the role of gamma-synchronization to solve the binding problem for larger object representations. Further analysis of the previous model revealed that the patches of coherent gamma-activity (1.8 mm half-height decline) were part of more globally occurring gamma-waves, which coupled over much larger distances (6.3 mm half-height decline). The model gamma-waves observed here are very similar to those found in the primary visual cortex of awake monkeys, indicating that local recurrent inhibition and restricted horizontal connections with finite axonal velocities are sufficient requirements for their emergence. In conclusion, since the model is in accordance with the connectivity and gamma-processes in the primary visual cortex, the results support the hypothesis that gamma-waves provide a generalized concept for object binding in the visual cortex

Scale-invariance of receptive field properties in primary visual cortex

<p>Abstract</p> <p>Background</p> <p>Our visual system enables us to recognize visual objects across a wide range of spatial scales. The neural mechanisms underlying these abilities are still poorly understood. Size- or scale-independent representation of visual objects might be supported by processing in primary visual cortex (V1). Neurons in V1 are selective for spatial frequency and thus represent visual information in specific spatial wavebands. We tested whether different receptive field properties of neurons in V1 scale with preferred spatial wavelength. Specifically, we investigated the size of the area that enhances responses, i.e., the grating summation field, the size of the inhibitory surround, and the distance dependence of signal coupling, i.e., the linking field.</p> <p>Results</p> <p>We found that the sizes of both grating summation field and inhibitory surround increase with preferred spatial wavelength. For the summation field this increase, however, is not strictly linear. No evidence was found that size of the linking field depends on preferred spatial wavelength.</p> <p>Conclusion</p> <p>Our data show that some receptive field properties are related to preferred spatial wavelength. This speaks in favor of the hypothesis that processing in V1 supports scale-invariant aspects of visual performance. However, not all properties of receptive fields in V1 scale with preferred spatial wavelength. Spatial-wavelength independence of the linking field implies a constant spatial range of signal coupling between neurons with different preferred spatial wavelengths. This might be important for encoding extended broad-band visual features such as edges.</p

A Robust Method for Detecting Interdependences: Application to Intracranially Recorded EEG

We present a measure for characterizing statistical relationships between two time sequences. In contrast to commonly used measures like cross-correlations, coherence and mutual information, the proposed measure is non-symmetric and provides information about the direction of interdependence. It is closely related to recent attempts to detect generalized synchronization. However, we do not assume a strict functional relationship between the two time sequences and try to define the measure so as to be robust against noise, and to detect also weak interdependences. We apply our measure to intracranially recorded electroencephalograms of patients suffering from severe epilepsies.Comment: 29 pages, 5 figures, paper accepted for publication in Physica

Relevance of Dynamic Clustering to Biological Networks

Network of nonlinear dynamical elements often show clustering of synchronization by chaotic instability. Relevance of the clustering to ecological, immune, neural, and cellular networks is discussed, with the emphasis of partially ordered states with chaotic itinerancy. First, clustering with bit structures in a hypercubic lattice is studied. Spontaneous formation and destruction of relevant bits are found, which give self-organizing, and chaotic genetic algorithms. When spontaneous changes of effective couplings are introduced, chaotic itinerancy of clusterings is widely seen through a feedback mechanism, which supports dynamic stability allowing for complexity and diversity, known as homeochaos. Second, synaptic dynamics of couplings is studied in relation with neural dynamics. The clustering structure is formed with a balance between external inputs and internal dynamics. Last, an extension allowing for the growth of the number of elements is given, in connection with cell differentiation. Effective time sharing system of resources is formed in partially ordered states.Comment: submitted to Physica D, no figures include

Topological Speed Limits to Network Synchronization

We study collective synchronization of pulse-coupled oscillators interacting on asymmetric random networks. We demonstrate that random matrix theory can be used to accurately predict the speed of synchronization in such networks in dependence on the dynamical and network parameters. Furthermore, we show that the speed of synchronization is limited by the network connectivity and stays finite, even if the coupling strength becomes infinite. In addition, our results indicate that synchrony is robust under structural perturbations of the network dynamics.Comment: 5 pages, 3 figure

Sporadicity and synchronization in one-dimensional asymmetrically coupled maps

A one-dimensional chain of sporadic maps with asymmetric nearest neighbour couplings is numerically studied. It is shown that in the region of strong asymmetry the system becomes spatially fully synchronized, even in the thermodinamic limit, while the Lyapunov exponent is zero. For weak asymmetry the synchronization is no more complete, and the Lyapunov exponent becomes positive. In addition one has a clear relation between temporal and spatial chaos, {\it i.e.}: a positive effective Lyapunov exponent corresponds to a lack of synchronization and {\it vice versa}Comment: 9 pages + 3 figures (postscript appended uuencoded tar), IOP style (appended uuencoded compress

A statistical mechanics of an oscillator associative memory with scattered natural frequencies

Analytic treatment of a non-equilibrium random system with large degrees of freedoms is one of most important problems of physics. However, little research has been done on this problem as far as we know. In this paper, we propose a new mean field theory that can treat a general class of a non-equilibrium random system. We apply the present theory to an analysis for an associative memory with oscillatory elements, which is a well-known typical random system with large degrees of freedoms.Comment: 8 pages, 4 figure