5 results on '"Hines, Michael L."'
Search Results
2. Sparse coding and lateral inhibition arising from balanced and unbalanced dendrodendritic excitation and inhibition.
- Author
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Yu Y, Migliore M, Hines ML, and Shepherd GM
- Subjects
- Animals, Learning physiology, Models, Neurological, Neural Inhibition physiology, Neural Networks, Computer, Neural Pathways physiology, Neuronal Plasticity physiology, Olfactory Bulb cytology, Rats, Smell physiology, Dendrites physiology, Olfactory Bulb physiology, Synapses physiology
- Abstract
The precise mechanism by which synaptic excitation and inhibition interact with each other in odor coding through the unique dendrodendritic synaptic microcircuits present in olfactory bulb is unknown. Here a scaled-up model of the mitral-granule cell network in the rodent olfactory bulb is used to analyze dendrodendritic processing of experimentally determined odor patterns. We found that the interaction between excitation and inhibition is responsible for two fundamental computational mechanisms: (1) a balanced excitation/inhibition in strongly activated mitral cells, leading to a sparse representation of odorant input, and (2) an unbalanced excitation/inhibition (inhibition dominated) in surrounding weakly activated mitral cells, leading to lateral inhibition. These results suggest how both mechanisms can carry information about the input patterns, with optimal level of synaptic excitation and inhibition producing the highest level of sparseness and decorrelation in the network response. The results suggest how the learning process, through the emergent development of these mechanisms, can enhance odor representation of olfactory bulb., (Copyright © 2014 the authors 0270-6474/14/3413701-13$15.00/0.)
- Published
- 2014
- Full Text
- View/download PDF
3. Multiple modes of action potential initiation and propagation in mitral cell primary dendrite.
- Author
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Chen WR, Shen GY, Shepherd GM, Hines ML, and Midtgaard J
- Subjects
- Animals, Axons physiology, Computer Simulation, Dendrites ultrastructure, Electrophysiology, Electroshock, Microscopy, Video, Models, Neurological, Neurons ultrastructure, Olfactory Bulb cytology, Olfactory Bulb physiology, Olfactory Nerve cytology, Olfactory Nerve physiology, Olfactory Pathways cytology, Olfactory Pathways physiology, Rats, Rats, Sprague-Dawley, Smell physiology, Synapses physiology, Action Potentials physiology, Dendrites physiology, Neurons physiology
- Abstract
The mitral cell primary dendrite plays an important role in transmitting distal olfactory nerve input from olfactory glomerulus to the soma-axon initial segment. To understand how dendritic active properties are involved in this transmission, we have combined dual soma and dendritic patch recordings with computational modeling to analyze action-potential initiation and propagation in the primary dendrite. In response to depolarizing current injection or distal olfactory nerve input, fast Na(+) action potentials were recorded along the entire length of the primary dendritic trunk. With weak-to-moderate olfactory nerve input, an action potential was initiated near the soma and then back-propagated into the primary dendrite. As olfactory nerve input increased, the initiation site suddenly shifted to the distal primary dendrite. Multi-compartmental modeling indicated that this abrupt shift of the spike-initiation site reflected an independent thresholding mechanism in the distal dendrite. When strong olfactory nerve excitation was paired with strong inhibition to the mitral cell basal secondary dendrites, a small fast prepotential was recorded at the soma, which indicated that an action potential was initiated in the distal primary dendrite but failed to propagate to the soma. As the inhibition became weaker, a "double-spike" was often observed at the dendritic recording site, corresponding to a single action potential at the soma. Simulation demonstrated that, in the course of forward propagation of the first dendritic spike, the action potential suddenly jumps from the middle of the dendrite to the axonal spike-initiation site, leaving the proximal part of primary dendrite unexcited by this initial dendritic spike. As Na(+) conductances in the proximal dendrite are not activated, they become available to support the back-propagation of the evoked somatic action potential to produce the second dendritic spike. In summary, the balance of spatially distributed excitatory and inhibitory inputs can dynamically switch the mitral cell firing among four different modes: axo-somatic initiation with back-propagation, dendritic initiation either with no forward propagation, forward propagation alone, or forward propagation followed by back-propagation.
- Published
- 2002
- Full Text
- View/download PDF
4. Neuron Names: A Gene- and Property-Based Name Format, With Special Reference to Cortical Neurons.
- Author
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Shepherd, Gordon M., Marenco, Luis, Hines, Michael L., Migliore, Michele, McDougal, Robert A., Carnevale, Nicholas T., Newton, Adam J. H., Surles-Zeigler, Monique, and Ascoli, Giorgio A.
- Subjects
NEURONS ,PARENT-child relationships ,NEUROTRANSMITTER receptors ,CEREBRAL cortex ,PROOF of concept ,GENE expression - Abstract
Precision in neuron names is increasingly needed. We are entering a new era in which classical anatomical criteria are only the beginning toward defining the identity of a neuron as carried in its name. New criteria include patterns of gene expression, membrane properties of channels and receptors, pharmacology of neurotransmitters and neuropeptides, physiological properties of impulse firing, and state-dependent variations in expression of characteristic genes and proteins. These gene and functional properties are increasingly defining neuron types and subtypes. Clarity will therefore be enhanced by conveying as much as possible the genes and properties in the neuron name. Using a tested format of parent-child relations for the region and subregion for naming a neuron, we show how the format can be extended so that these additional properties can become an explicit part of a neuron's identity and name, or archived in a linked properties database. Based on the mouse, examples are provided for neurons in several brain regions as proof of principle, with extension to the complexities of neuron names in the cerebral cortex. The format has dual advantages, of ensuring order in archiving the hundreds of neuron types across all brain regions, as well as facilitating investigation of a given neuron type or given gene or property in the context of all its properties. In particular, we show how the format is extensible to the variety of neuron types and subtypes being revealed by RNA-seq and optogenetics. As current research reveals increasingly complex properties, the proposed approach can facilitate a consensus that goes beyond traditional neuron types. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
5. Sparse Coding and Lateral Inhibition Arising from Balanced and Unbalanced Dendrodendritic Excitation and Inhibition.
- Author
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Yuguo Yu, Migliore, Michele, Hines, Michael L., and Shepherd, Gordon M.
- Subjects
CEREBRAL dominance ,DENDRITES ,OLFACTORY bulb ,NEURAL codes ,HUMAN information processing - Abstract
The precise mechanism by which synaptic excitation and inhibition interact with each other in odor coding through the unique dendrodendritic synaptic microcircuits present in olfactory bulb is unknown. Here a scaled-up model of the mitral- granule cell network in the rodent olfactory bulb is used to analyze dendrodendritic processing of experimentally determined odor patterns. We found that the interaction between excitation and inhibition is responsible for two fundamental computational mechanisms: (1) a balanced excitation/ inhibition in strongly activated mitral cells, leading to a sparse representation of odorant input, and (2) an unbalanced excitation/ inhibition (inhibition dominated) in surrounding weakly activated mitral cells, leading to lateral inhibition. These results suggest how both mechanisms can carry information about the input patterns, with optimal level of synaptic excitation and inhibition producing the highest level of sparseness and decorrelation in the network response. The results suggest how the learningprocess, through the emergent development of these mechanisms, can enhance odor representation of olfactory bulb. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
- View/download PDF
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