The richness and complexity of data sets acquired from positron emission tomography or functional magnetic resonance imaging studies of human cognition have not been exploited until recently by computational neural modeling methods. Two neural modeling approaches for use with functional brain imaging data will be described. One, which uses structural equation modeling, estimates the functional strengths of the anatomical connections between various brain regions during specific cognitive tasks. An application to Alzheimer's disease will be provided.
Various hypotheses regard spines as possible loci for synaptic plasticity.
We present a new variation of this model to investigate spatially clustered synaptic inputs in both nerve and muscle fibers. We show how the type of bifurcation affects the neuro-computational properties of the cells. Increasing the input frequency may actually delay or terminate its firing. Derivation of Second-Order 'Excess Buffer,' 'Rapid Buffer,' and 'Nearly Immobile Buffer' Approximations. Gases introduced into the respiratory cycle are absorbed in the alveolar region of the lungs.