Sscillatory Cortical Activity during Visual Hallucinations

From a theoretical point of view we investigate cortical activity patterns causing dynamic visual hallucinations. For this reason we analyze an oscillatory instability of the dynamics ofthe activator-inhibitor model of Ermentrout and Cowan.Such an oscillatory instability occurs as a result of several disease mechanisms.We explicitly derive the order parameter equation. By means of the averaging theorem, we obtain the averaged order parameter equation.The latter enables us to determine stable and unstable bifurcating cortical activity patterns analytically in lowest order.Depending on model parameters as well as on initial conditions two types of cortical activity patterns occur: travelling waves and blinking rolls, i.e.standing waves oscillating with the same frequency and with a phase shift of /2. In contrast to cortical activitypatterns caused by non-oscillatory instabilitiesanalyzed by Ermentrout and Cowan and by the author the travelling waves and the blinking rolls lead to a variety of dynamic visual hallucinations which are discussed indetail.     

Peripheral and central inputs shape network dynamics in the developing visual cortex in vivo

Spontaneous network activity constitutes a central theme during the development of neuronal circuitry [1, 2]. Before the onset of vision, retinal neurons generate waves of spontaneous activity that are relayed along the ascending visual pathway [3, 4] and shape activity patterns in these regions [5, 6]. The spatiotemporal nature of retinal waves is required to establish precise functional maps in higher visual areas, and their disruption results in enlarged axonal projection areas (e.g., [7-10]). However, how retinal inputs shape network dynamics in the visual cortex on the cellular level is unknown. Using in vivo two-photon calcium imaging, we identified two independently occurring patterns of network activity in the mouse primary visual cortex (V1) before and at the onset of vision. Acute manipulations of spontaneous retinal activity revealed that one type of network activity largely originated in the retina and was characterized by low synchronicity (L-) events. In addition, we identified a type of high synchronicity (H-) events that required gap junction signaling but were independent of retinal input. Moreover, the patterns differed in wave progression and developmental profile. Our data suggest that different activity patterns have complementary functions during the formation of synaptic circuits in the developing visual cortex.     

Order of function of the budding-yeast mitotic exit-network proteins Tem1, Cdc15, Mob1, Dbf2, and Cdc5

The Dbf2 protein kinase functions as part of the mitotic-exit network (MEN), which controls the inactivation of the Cdc28-Clb2 kinase in late mitosis [1]. The MEN includes the Tem1 GTP binding protein; the kinases Cdc15 and Cdc5; Mob1, a protein of unknown function; and the phosphatase Cdc14 [2]. Here we have used Dbf2 kinase activity to investigate the regulation and order of function of the MEN. We find that Tem1 acts at the top of the pathway, upstream of Cdc15, which in turn functions upstream of Mob1 and Dbf2. The Cdc5 Polo-like kinase impinges at least twice on the MEN since it negatively regulates the network, probably upstream of Tem1, and is also required again for Dbf2 kinase activation. Furthermore, we find that regulation of Dbf2 kinase activity and actin ring formation at the bud neck are causally linked. In metaphase-arrested cells, the MEN inhibitor Bub2 restrains both Dbf2 kinase activity [3] and actin ring formation [4]. We find that the MEN proteins that are required for Dbf2 kinase activity are also required for actin ring formation. Thus, the MEN is crucial for the regulation of cytokinesis, as well as mitotic exit.     

Self-organization phenomena resulting from cell-cell contact

Self-organization phenomena in an ensemble of cells in contact is considered. By a simple and general argument it is shown that in order to have pattern formation or spatio-temporal organization in these systems it is not necessary that chemicals move throughout the field. The influence of one cell on its neighbour can be transmitted by surface contact interactions in which molecules in the surface of one cell influence the rates of reactions in neighbouring cells without the actual passage of molecules from one cell to the other. It is shown that these systems present all the self-organizing properties seen in reaction diffusion systems. The possible biological applications and the role of first bifurcating solution out of the homogeneous state to provide “positional information” in morphogenesis is discussed.     

Bifurcating spatially heterogeneous solutions in a chemotaxis model for biological pattern generation

We consider a simple cell-chemotaxis model for spatial pattern formation on two-dimensional domains proposed by Oster and Murray (1989,J. exp. Zool. 251, 186–202). We determine finite-amplitude, steady-state, spatially heterogeneous solutions and study the effect of domain growth on the resulting patterns. We also investigate in-depth bifurcating solutions as the chemotactic parameter varies. This numerical study shows that this deceptively simple-chemotaxis model can produce a surprisingly rich spectrum of complex spatial patterns.     

Synchronized oscillations in the visual cortex — a synergetic model

We present an oscillator network model for the synchronization of oscillatory neuronal activity underlying visual processing. The single neuron is modeled by means of a limit cycle oscillator with an eigenfrequency corresponding to visual stimulation. The eigenfrequency may be time dependent. The mutual coupling strengths are unsymmetrical and activity dependent, and they scatter within the network. Synchronized clusters (groups) of neurons emerge in the network due to the visual stimulation. The different clusters correspond to different visual stimuli. There is no limitation of the number of stimuli. Distinct clusters do not perturb each other, although the coupling strength between all model neurons is of the same order of magnitude. Our analysis is not restricted to weak coupling strength. The scatter of the couplings causes shifts of the cluster frequencies. The model's behavior is compared with the experimental findings. The coupling mechanism is extended in order to model the influence of bicucullin upon the neural network. We additionally investigate repulsive couplings, which lead to constant phase differences between clusters of the same frequency. Finally, we consider the problem of selective attention from the viewpoint of our model.     

Formation of band-type electric patterns in Characean cells

It is observed by experiments that band patterns of alternating acid and alkaline zones are formed on the surface of Characean cells under illumination. In order to understand theoretically such pattern formation, we employ a reaction-diffusion equation model with activator-inhibitor interaction. We study the existence problem of band patterns and hysteresis phenomena such as patterns appearing and disappearing with changing light intensity by using singular perturbation methods.     

Sense Production in Reading Fiction

If we want to know more about the process of becoming a person, we should investigate the psychological mechanisms in the formation of value and sense (meaning) [33]. Art is one of the existing forms of developing values, making sense of the world and giving meaning to social life. It is well known that art possesses the capacity to influence the process of human growth [11]. But the psychological mechanisms in understanding such influences have remained elusive.     

Stimulus timing-dependent plasticity in high-level vision

Humans are able to efficiently learn and remember complex visual patterns after only a few seconds of exposure [1]. At a cellular level, such learning is thought to involve changes in synaptic efficacy, which have been linked to the precise timing of action potentials relative to synaptic inputs [2-4]. Previous experiments have tapped into the timing of neural spiking events by using repeated asynchronous presentation of visual stimuli to induce changes in both the tuning properties of visual neurons and the perception of simple stimulus attributes [5, 6]. Here we used a similar approach to investigate potential mechanisms underlying the perceptual learning of face identity, a high-level stimulus property based on the spatial configuration of local features. Periods of stimulus pairing induced a systematic bias in face-identity perception in a manner consistent with the predictions of spike timing-dependent plasticity. The perceptual shifts induced for face identity were tolerant to a 2-fold change in stimulus size, suggesting that they reflected neuronal changes in nonretinotopic areas, and were more than twice as strong as the perceptual shifts induced for low-level visual features. These results support the idea that spike timing-dependent plasticity can rapidly adjust the neural encoding of high-level stimulus attributes [7-11].     

Myoblast fusion in Drosophila

The body wall musculature of a Drosophila larva is composed of an intricate pattern of 30 segmentally repeated muscle fibers in each abdominal hemisegment. Each muscle fiber has unique spatial and behavioral characteristics that include its location, orientation, epidermal attachment, size and pattern of innervation. Many, if not all, of these properties are dictated by founder cells, which determine the muscle pattern and seed the fusion process. Myofibers are then derived from fusion between a specific founder cell and several fusion competent myoblasts (FCMs) fusing with as few as 3-5 FCMs in the small muscles on the most ventral side of the embryo and as many as 30 FCMs in the larger muscles on the dorsal side of the embryo. The focus of the present review is the formation of the larval muscles in the developing embryo, summarizing the major issues and players in this process. We have attempted to emphasize experimentally-validated details of the mechanism of myoblast fusion and distinguish these from the theoretically possible details that have not yet been confirmed experimentally. We also direct the interested reader to other recent reviews that discuss myoblast fusion in Drosophila, each with their own perspective on the process [1], [2], [3] and [4]. With apologies, we use gene nomenclature as specified by Flybase (http://flybase.org) but provide Table 1 with alternative names and references.     

Synchronized oscillations in the visual cortex — a synergetic model

 We present an oscillator network model for the synchronization of oscillatory neuronal activity underlying visual processing. The single neuron is modeled by means of a limit cycle oscillator with an eigenfrequency corresponding to visual stimulation. The eigenfrequency may be time dependent. The mutual coupling strengths are unsymmetrical and activity dependent, and they scatter within the network. Synchronized clusters (groups) of neurons emerge in the network due to the visual stimulation. The different clusters correspond to different visual stimuli. There is no limitation of the number of stimuli. Distinct clusters do not perturb each other, although the coupling strength between all model neurons is of the same order of magnitude. Our analysis is not restricted to weak coupling strength. The scatter of the couplings causes shifts of the cluster frequencies. The model’s behavior is compared with the experimental findings. The coupling mechanism is extended in order to model the influence of bicucullin upon the neural network. We additionally investigate repulsive couplings, which lead to constant phase differences between clusters of the same frequency. Finally, we consider the problem of selective attention from the viewpoint of our model. Received: 15 February 1995/Accepted in revised form: 18 July 1995     

Disorders of agency in schizophrenia correlate with an inability to compensate for the sensory consequences of actions

Psychopathological symptoms in schizophrenia patients suggest that the concept of self might be disturbed in these individuals [1]. Delusions of influence make them feel that someone else is guiding their actions, and certain kinds of their hallucinations seem to be misinterpretations of their own inner voice as an external voice, the common denominator being that self-produced information is perceived as if coming from outside. If this interpretation were correct, we might expect that schizophrenia patients might also attribute the sensory consequences of their own eye movements to the environment rather than to themselves, challenging the percept of a stable world. Indeed, this seems to be the case because we found a clear correlation between the strength of delusions of influence and the ability of schizophrenia patients to cancel out such self-induced retinal information in motion perception. This correlation reflects direct experimental evidence supporting the view that delusions of influence in schizophrenia might be due to a specific deficit in the perceptual compensation of the sensory consequences of one's own actions [1, 2, 3, 4, 5 and 6].     

Stability switches,oscillatory multistability,and spatio-temporal patterns of nonlinear oscillations in recurrently delay coupled neural networks

A model of time-delay recurrently coupled spatially segregated neural assemblies is here proposed. We show that it operates like some of the hierarchical architectures of the brain. Each assembly is a neural network with no delay in the local couplings between the units. The delay appears in the long range feedforward and feedback inter-assemblies communications. Bifurcation analysis of a simple four-units system in the autonomous case shows the richness of the dynamical behaviors in a biophysically plausible parameter region. We find oscillatory multistability, hysteresis, and stability switches of the rest state provoked by the time delay. Then we investigate the spatio-temporal patterns of bifurcating periodic solutions by using the symmetric local Hopf bifurcation theory of delay differential equations and derive the equation describing the flow on the center manifold that enables us determining the direction of Hopf bifurcations and stability of the bifurcating periodic orbits. We also discuss computational properties of the system due to the delay when an external drive of the network mimicks external sensory input.     

Attention-dependent representation of a size illusion in human V1

One of the most fundamental properties of human primary visual cortex (V1) is its retinotopic organization, which makes it an ideal candidate for encoding spatial properties, such as size, of objects. However, three-dimensional (3D) contextual information can lead to size illusions that are reflected in the spatial pattern of activity in V1 [1]. A critical question is how complex 3D contextual information can influence spatial activity patterns in V1. Here, we assessed whether changes in the spatial distribution of activity in V1 depend on the focus of attention, which would be suggestive of feedback of 3D contextual information from higher visual areas. We presented two 3D rings at close and far apparent depths in a 3D scene. When subjects fixated its center, the far ring appeared to be larger and occupy a more eccentric portion of the visual field, relative to the close ring. Using functional magnetic resonance imaging, we found that the spatial distribution of V1 activity induced by the far ring was also shifted toward a more eccentric representation of the visual field, whereas that induced by the close ring was shifted toward the foveal representation, consistent with their perceptual appearances. This effect was significantly reduced when the focus of spatial attention was narrowed with a demanding central fixation task. We reason that focusing attention on the fixation task resulted in reduced activity in--and therefore reduced feedback from--higher visual areas that process the 3D depth cues.     

Optic flow cues guide flight in birds

Although considerable effort has been devoted to investigating how birds migrate over large distances, surprisingly little is known about how they tackle so successfully the moment-to-moment challenges of rapid flight through cluttered environments [1]. It has been suggested that birds detect and avoid obstacles [2] and control landing maneuvers [3-5] by using cues derived from the image motion that is generated in the eyes during flight. Here we investigate the ability of budgerigars to fly through narrow passages in a collision-free manner, by filming their trajectories during flight in a corridor where the walls are decorated with various visual patterns. The results demonstrate, unequivocally and for the first time, that birds negotiate narrow gaps safely by balancing the speeds of image motion that are experienced by the two eyes and that the speed of flight is regulated by monitoring the speed of image motion that is experienced by the two eyes. These findings have close parallels with those previously reported for flying insects [6-13], suggesting that some principles of visual guidance may be shared by all diurnal, flying animals.     

Reconstructing visual experiences from brain activity evoked by natural movies

Quantitative modeling of human brain activity can provide crucial insights about cortical representations [1, 2] and can form the basis for brain decoding devices [3-5]. Recent functional magnetic resonance imaging (fMRI) studies have modeled brain activity elicited by static visual patterns and have reconstructed these patterns from brain activity [6-8]. However, blood oxygen level-dependent (BOLD) signals measured via fMRI are very slow [9], so it has been difficult to model brain activity elicited by dynamic stimuli such as natural movies. Here we present a new motion-energy [10, 11] encoding model that largely overcomes this limitation. The model describes fast visual information and slow hemodynamics by separate components. We recorded BOLD signals in occipitotemporal visual cortex of human subjects who watched natural movies and fit the model separately to individual voxels. Visualization of the fit models reveals how early visual areas represent the information in movies. To demonstrate the power of our approach, we also constructed a Bayesian decoder [8] by combining estimated encoding models with a sampled natural movie prior. The decoder provides remarkable reconstructions of the viewed movies. These results demonstrate that dynamic brain activity measured under naturalistic conditions can be decoded using current fMRI technology.