PubMed Health⌕ Search

PubMed · 15460513

Visual neuroscience before the neuron.

Abstract

Visual neuroscience is considered to be a contemporary concern, based in large part on relating characteristics of neural functioning to visual experience. It presupposes a detailed knowledge of neural activity for which the neuron doctrine is a fundamental tenet. However, long before either the neuron doctrine had been advanced or the nerve cell had been described, attempts were made to estimate the dimensions of nerve fibres from measures of visual resolution. In the seventeenth century, the microscopes of Hooke and van Leeuwenhoek were unable to resolve structures as small as nerves adequately. However, it was not Hooke's microscope that led to an estimate of the dimensions of nerve fibres but his experiments on the limits of visual resolution. Hooke determined that a separation of one minute of arc was the minimum that could normally be seen. Descartes had earlier speculated that the retina consisted of the terminations of fibres of the optic nerve, and that their size defined the limits of what could be seen. Estimates of the diameters of nerve fibres were made on the basis of human visual acuity by Porterfield in 1738; he calculated the diameters of nerve fibres in the retina as one 7200th part of an inch (0.0035 mm), based on the resolution of one minute of arc as the minimum visible. In the same year, Jurin questioned the reliability of such estimates because of variations in visual resolution with different stimuli. The measurement of visual acuity was refined by Mayer in 1755, with dots, gratings, and grids used as stimuli. In the 1830s, Treviranus fused the microscopic and acuity approaches to determine the dimensions of nerve fibres. His indirect estimates of the dimensions of retinal fibres were close to those derived from microscopic observation. However, the suggestion that the retina consisted of terminations of nerve fibres influenced his detailed illustrations of its microscopic structure. Contrary to the situation that obtained after the microscopic structure of the retina had been established, a function of vision (acuity) was used to determine the dimensions of the structures (retinal elements) that were thought to mediate it.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Nicholas J Wade. 2004. Visual neuroscience before the neuron.. https://doi.org/10.1068/p5153

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Neutral fitness landscapes in signalling networks.

Biological and technological systems process information by means of cascades of signals. Be they interacting genes, spiking neurons or electronic transistors, information travels across these systems, producing, for each set of external conditions, an appropriate response. In technology, circuits performing specific complex tasks are designed by humans. In biology, however, design has to be ruled out, confronting us with the question of how these systems could have arisen by accumulation of small changes. The key factor is the genotype-phenotype map. With the exception of RNA folding, not much is known about the exact nature of this mapping. Here, we show that structure of the genotype-phenotype map of simple feed-forward circuits is very close to the ones found in RNA; they have a large degree of neutrality, by which a circuit can be completely rewired keeping its input-output function intact, and there is a relatively small neighbourhood of a given circuit containing almost all the phenotypes.

Cell Physiological Phenomena↗

Directed cell migration in the presence of obstacles.

BACKGROUND: Chemotactic movement is a common feature of many cells and microscopic organisms. In vivo, chemotactic cells have to follow a chemotactic gradient and simultaneously avoid the numerous obstacles present in their migratory path towards the chemotactic source. It is not clear how cells detect and avoid obstacles, in particular whether they need a specialized biological mechanism to do so. RESULTS: We propose that cells can sense the presence of obstacles and avoid them because obstacles interfere with the chemical field. We build a model to test this hypothesis and find that this naturally enables efficient at-a-distance sensing to be achieved with no need for a specific and active obstacle-sensing mechanism. We find that (i) the efficiency of obstacle avoidance depends strongly on whether the chemotactic chemical reacts or remains unabsorbed at the obstacle surface. In particular, it is found that chemotactic cells generally avoid absorbing barriers much more easily than non-absorbing ones. (ii) The typically low noise in a cell's motion hinders the ability to avoid obstacles. We also derive an expression estimating the typical distance traveled by chemotactic cells in a 3D random distribution of obstacles before capture; this is a measure of the distance over which chemotaxis is viable as a means of directing cells from one point to another in vivo. CONCLUSION: Chemotactic cells, in many cases, can avoid obstacles by simply following the spatially perturbed chemical gradients around obstacles. It is thus unlikely that they have developed specialized mechanisms to cope with environments having low to moderate concentrations of obstacles.

Cell Physiological Phenomena↗

Thermodynamically feasible kinetic models of reaction networks.

The dynamics of biological reaction networks are strongly constrained by thermodynamics. An holistic understanding of their behavior and regulation requires mathematical models that observe these constraints. However, kinetic models may easily violate the constraints imposed by the principle of detailed balance, if no special care is taken. Detailed balance demands that in thermodynamic equilibrium all fluxes vanish. We introduce a thermodynamic-kinetic modeling (TKM) formalism that adapts the concepts of potentials and forces from irreversible thermodynamics to kinetic modeling. In the proposed formalism, the thermokinetic potential of a compound is proportional to its concentration. The proportionality factor is a compound-specific parameter called capacity. The thermokinetic force of a reaction is a function of the potentials. Every reaction has a resistance that is the ratio of thermokinetic force and reaction rate. For mass-action type kinetics, the resistances are constant. Since it relies on the thermodynamic concept of potentials and forces, the TKM formalism structurally observes detailed balance for all values of capacities and resistances. Thus, it provides an easy way to formulate physically feasible, kinetic models of biological reaction networks. The TKM formalism is useful for modeling large biological networks that are subject to many detailed balance relations.

Cell Physiological Phenomena↗