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Brain magnetic resonance imaging with contrast dependent on blood oxygenation.
- S. Ogawa, T. Lee, A. Kay, D. Tank
- Medicine, BiologyProceedings of the National Academy of Sciences…
- 1 December 1990
It is demonstrated that in vivo images of brain microvasculature with image contrast reflecting the blood oxygen level can be used to provide in vivo real-time maps of blood oxygenation in the brain under normal physiological conditions.
“Neural” computation of decisions in optimization problems
Results of computer simulations of a network designed to solve a difficult but well-defined optimization problem-the Traveling-Salesman Problem-are presented and used to illustrate the computational power of the networks.
Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging.
We report that visual stimulation produces an easily detectable (5-20%) transient increase in the intensity of water proton magnetic resonance signals in human primary visual cortex in gradient echo…
Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model.
Probing the Limits to Positional Information
Stability and Nuclear Dynamics of the Bicoid Morphogen Gradient
Choice-specific sequences in parietal cortex during a virtual-navigation decision task
Optically imaged the spatial and temporal activity patterns of neuronal populations in mice performing a PPC-dependent task that combined a perceptual decision and memory-guided navigation in a virtual environment.
Imaging Large-Scale Neural Activity with Cellular Resolution in Awake, Mobile Mice
Intracellular dynamics of hippocampal place cells during virtual navigation
The intracellular dynamics of place cells are measured by combining in vivo whole-cell recordings with a virtual-reality system to examine the mechanisms underlying hippocampal coding and to enable new experimental approaches to study the neural circuits underlying navigation.
Simple 'neural' optimization networks: An A/D converter, signal decision circuit, and a linear programming circuit
It is described how several optimization problems can be rapidly solved by highly interconnected networks of simple analog processors, and it is shown that a network which solves linear programming Problems can be understood from the same concepts.