PubMed · 770182
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1976. Editorial: Dendrites--the second coming.. https://pubmed.ncbi.nlm.nih.gov/770182/
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The single neurone stands in the midst of a controversy among modelers. Some believe that its details are functionally superfluous when the neurone operates in a large network, and very simple models can be used to represent the input/output characteristics of neurones. Others claim that the unique morphology and electrical properties of neurones do play an important role. Complicated models of neurones are developed to reveal how the various kinds of 'neurone-ware' (dendrites, spines, axons, membrane channels and synapses) create a computationally powerful unit. Various models are discussed, including new carefully reduced models that retain essential features of more complex models. Such intermediate models will play a central role in our efforts to understand information processing in large neuronal networks.
A modified Golgi method (Vaisamruat and Hess, '53) was found to give satisfactory impregnation of cell bodies and dendrites, but not of dendritic spines and axons, in adult human material fixed by immersion in formalin. Examination of the motor columns in the spinal cord intumescences and of the third and twelfth cranial nerve nuclei revealed four neuron types, based on dendritic field size and dendritic branching pattern. Two of these were recognized as alpha-motoneurons; one of them was seen only in the medial motor column of the spinal ventral horn, while the other was observed in the cranial motor nuclei as well as the spinal lateral motor column. Differences in somadendritic dimensions in this neuron type were thought to reflect motor unit size, and thus terminal axon field dimensions. Of the two types of gamma-motoneurons recognized in the spinal cord and oculomotor nucleus, one was a miniature version of the commoner type of alpha-motoneuron. On this basis, it is proposed that it may give rise to fusimotor axons with plate endings. The second type of gamma-motoneuron does not resemble any of the other motoneuron types, and its axons may therefore be thought to terminate in trail endings.
Mean and variance of the first passage time through a constant boundary for the Ornstein-Uhlenbeck process are determined by a straight-forward differentiation of the Laplace transform of the first passage time probability density function. The results of some numerical computations are discussed to shed some light on the input-output behavior of a formal neuron whose dynamics is modeled by a diffusion process of Ornstein-Uhlenbeck type.