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Biomedical subjects

O Sporns

Publications and source records attributed to O Sporns.

8 recordsLinked to original sources

PubMed1992

Synthetic neural modeling applied to a real-world artifact.

We describe the general design, operating principles, and performance of a neurally organized, multiply adaptive device (NOMAD) under control of a nervous system simulated in a computer. The complete system, Darwin IV, is the latest in a series of models based on the theory of neuronal group selection, which postulates that adaptive behavior is the result of selection in somatic time among synaptic populations. The simulated brain of Darwin IV includes visual and motor areas that are connected with NOMAD by telemetry. Under suitable conditions, Darwin IV can be trained to track a light moving in a random path. After such training, it can approach colored blocks and collect them to a home position. Following a series of contacts with such blocks, value signals received through a "snout" that senses conductivity allow it to sort these blocks on the basis of differences in color associated with differences in their conductivity. Darwin IV represents a new approach to synthetic neural modeling (SNM), a technique in which large-scale computer simulations are employed to analyze the interactions among the nervous system, the phenotype, and the environment of a designed organism as behavior develops. Darwin IV retains the advantages of SNM while avoiding the difficulties and pitfalls of attempting to simulate a rich environment in addition to a brain.

Behavior↗

PubMed1991

Modeling perceptual grouping and figure-ground segregation by means of active reentrant connections.

The segmentation of visual scenes is a fundamental process of early vision, but the underlying neural mechanisms are still largely unknown. Theoretical considerations as well as neurophysiological findings point to the importance in such processes of temporal correlations in neuronal activity. In a previous model, we showed that reentrant signaling among rhythmically active neuronal groups can correlate responses along spatially extended contours. We now have modified and extended this model to address the problems of perceptual grouping and figure-ground segregation in vision. A novel feature is that the efficacy of the connections is allowed to change on a fast time scale. This results in active reentrant connections that amplify the correlations among neuronal groups. The responses of the model are able to link the elements corresponding to a coherent figure and to segregate them from the background or from another figure in a way that is consistent with the so-called Gestalt laws.

Animals↗

PubMed1989

Reentrant signaling among simulated neuronal groups leads to coherency in their oscillatory activity.

Recent experiments have revealed tightly synchronized oscillatory discharges in local assemblies of cortical neurons as well as phase coherency of oscillations at distant cortical sites. These findings are consistent with the theory of neuronal group selection, a population theory of brain function that is based on the properties of local groups of neurons. A set of computer simulations shows that cooperative interactions within and among neuronal groups can generate the observed phenomena. In the simulations, oscillations within neuronal groups are generated through local excitatory and inhibitory interactions. Different groups in general oscillate in an uncorrelated fashion. Coherency of the oscillatory activity of different neuronal groups depends crucially on reciprocal reentrant signaling and can reflect the spatial continuity of a stimulus. Separated or discontinuous features of a given stimulus can be transiently associated in a temporally coherent pattern through reentrant signaling between groups in networks responding to different aspects of that stimulus. A simulation of reentrant activity between arrays of neuronal groups selective for oriented lines and pattern motion displays cross-correlations between groups that are responsive to different parts of a stimulus contour if these parts move together. Such coherency among neuronal groups might be used in the discrimination of a stimulus from other stationary or differentially moving elements in a visual scene.

Animals↗

PubMed1987

Spatiotemporal relationship of embryonic cholinesterases with cell proliferation in chicken brain and eye.

Close relationships between acetylcholinesterase (AcChoEase; acetylcholine acetylhydrolase, true cholinesterase, EC, 3.1.1.7) and butyrylcholinesterase (BtChoEase, acylcholine acylhydrolase, pseudocholinesterase, EC, 3.1.1.8) with cell proliferation were observed in the early chicken brain. These include the following: BtChoEase is transiently accumulating in patchy fashion on the ventricular side of the neuroepithelium shortly before AcChoEase appears in cell bodies along the opposing mantle layer. The amount of BtChoEase in retina and brain is greatest in the early phase (E3-E5, or incubation periods of 3-5 days); in retina it decreases about 2 days later than in brain. However, AcChoEase expression increases with time, in inverse order to that of BtChoEase. In both tissues decrease of cell proliferation is closely followed by decrease in BtChoEase. A double-labeling technique of cholinesterase staining together with [3H]thymidine autoradiography reveals proliferation zones that are diffusely stained by BtChoEase but not by AcChoEase. Patches intensely stained for BtChoEase accompany clusters of cells in final stages of mitosis on their way to the differentiation zone, where they begin expressing AcChoEase. By applying different thymidine pulses, we identify an 11-hr lag from the last thymidine-uptake to full AcChoEase expression. (iv) These findings are confirmed by studying lens development, where areas of proliferation and differentiation are well separated. The spatiotemporal pattern of the transition of neuroblasts from a proliferating into a differentiating state correlates with the expression of BtChoEase just before and during mitosis and that of AcChoEase about 11 hr after mitosis. Thus cholinesterases could be involved in the regulation of this transition.

Acetylcholinesterase↗

PubMed1987

Quantitative development and molecular forms of acetyl- and butyrylcholinesterase during morphogenesis and synaptogenesis of chick brain and retina.

The embryonic development of total specific activities as well as of molecular forms of acetylcholinesterase (AChE, EC 3.1.1.7) and of butyrylcholinesterase (BChE, EC 3.1.1.8) have been studied in the chick brain. A comparison of the development in different brain parts shows that cholinesterases first develop in diencephalon, then in tectum and telencephalon; cholinesterase development in retina is delayed by about 2-3 days; and the development in rhombencephalon [not studied until embryonic day 6 (E6)] and cerebellum is last. Both enzymes show complex and independent developmental patterns. During the early period (E3-E7) first BChE expresses high specific activities that decline rapidly, but in contrast AChE increases more or less constantly with a short temporal delay. Thereafter the developmental courses approach a late phase (E14-E20), during which AChE reaches very high specific activities and BChE follows at much lower but about parallel levels. By extraction of tissues from brain and retina in high salt plus 1% Triton X-100, we find that both cholinesterases are present in two major molecular forms, AChE sedimenting at 5.9S and 11.6S (corresponding to G2 and G4 globular forms) and BChE at 2.9S and 10.3S (G1 and G4, globular). During development there is a continuous increase of G4 over G2 AChE, the G4 form reaching 80% in brain but only 30% in retina. The proportion of G1 BChE in brain remains almost constant at 55%, but in retina there is a drastic shift from 65% G1 before E5 to 70% G4 form at E7.(ABSTRACT TRUNCATED AT 250 WORDS)

Acetylcholinesterase↗

PubMed1986

Oscillations in theoretical models of induction.

A two-variable model for the genetic regulatory mechanism of induction is proposed. In a feedforward step an autocatalytically accumulated substrate induces the transcription of its own degrading enzyme. The differential equations for enzyme and substrate are treated analytically and it is found that in a defined parameter range the system becomes unstable and shows structurally stable limit cycle oscillations. The system behaves like an activator-inhibitor model and instability is likely to arise if the transcription process is slow. In a slightly modified system oscillations inside a cell are generated if an external parameter (extracellular substrate concentration) exceeds a certain threshold and all other parameters are unchanged. Possible biological implications of these results are destabilization of metabolic units by transport processes and feedforward catalysis.

Biological Transport, Active↗

PubMed1986

Turing structures in an enzyme-induction system with gap junction-mediated non-linear diffusion.

Two cells, each containing a reaction system modeling genetic induction, are coupled by diffusion. The substrate is moving through gap junctions, the number of which is regulated by the adjacent cells. This leads to a non-linear substrate diffusion term in the rate equations. Stability analysis reveals the conditions for the emergence of stable asymmetric solutions (dissipative structures). Due to non-linear diffusion rigid restrictions on the ratio of the two diffusion constants no longer exist. We demonstrate that substances operating as regulators of intercellular communication and participating in cellular metabolism may exhibit morphogenetic functions.

Animals↗

PubMedDate not supplied

Reentry and the problem of integrating multiple cortical areas: simulation of dynamic integration in the visual system.

Studies of the cerebral cortex, particularly those of the visual system, demonstrate the existence of multiple, anatomically segregated and functionally specialized cortical areas. There is no evidence that these areas, which are linked by a network of reciprocal connections, are coordinated by a higher-order center. The visual image that we perceive, however, seems to be unified and coherent. In this article, we address the problem of integration posed by these observations. In an extension of our previous work, we develop a dynamic model of reentry. Reentry is a process of parallel and recursive signaling along ordered anatomical connections that achieves integration by giving rise to constructive and correlative properties within and among maps. We present and test a computer model simulating nine functionally segregated visual areas organized into three streams for form, color, and motion. The model receives visual input consisting of camera images of objects of different shapes and colors. We show the specialized response properties of the areas in the three streams. A computational strategy involving a phase variable is introduced to represent explicitly the dynamics of short-term temporal correlations among thousands of units distributed across different areas. We then illustrate constructive and correlative consequences of reentry within a system of reciprocal intra- and interareal connections by two examples taken from psychophysics: generation of form from motion and motion capture. The model solves the so-called "binding problem" through short-term correlations, which serve to link similar object features within a simulated cortical area and to bind multiple attributes of one or more objects across several areas, including a nontopographic one. Integration emerges from cooperative effects within and among the specialized areas. These effects lead to a simple output, a simulated foveation response, that is used as a basis for conditioning. Reward is mediated by the activation of a saliency system that is modeled on diffuse projection systems in the brain. As a result, the visual cortical model carries out foveation responses to input stimuli that require the dynamic conjunction and discrimination of form, color, and location for successful performance.

Animals↗