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Biomedical subjects

Kevin Staley

Publications and source records attributed to Kevin Staley.

7 recordsLinked to original sources
PubMed2006

The use of radiotelemetry to evaluate electrographic seizures in rats with kainate-induced epilepsy.

Temporal lobe epilepsy in humans is a chronic condition with a highly variable temporal evolution. Animal models of this disorder have been developed to recapitulate many of the characteristics seen in humans with temporal lobe epilepsy. These animal models generate chronic spontaneous electrographic and motor seizures with a progressive increase in frequency over many months. In order to understand the underlying cellular and molecular mechanisms driving epileptogenesis, a practical means for accurately assessing seizure progression over this extended time period must be devised. In this report, we describe the use of a three-channel radiotelemetry system to record spontaneous electrographic interictal "spikes" and seizure activity from the cortical surface and the two hippocampi. This approach has allowed continuous recording before, during, and several months after kainate-induced status epilepticus. The important advantages of this approach are the potential for long-term continuous electrographic recording with comparatively unrestricted behavior; the disadvantages include increased cost, surgical difficulty and lower frequency-response in the recordings.

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PubMed2006

A new synaptic plasticity rule for networks of spiking neurons.

In this paper, we describe a new Synaptic Plasticity Activity Rule (SAPR) developed for use in networks of spiking neurons. Such networks can be used for simulations of physiological experiments as well as for other computations like image analysis. Most synaptic plasticity rules use artificially defined functions to modify synaptic connection strengths. In contrast, our rule makes use of the existing postsynaptic potential values to compute the value of adjustment. The network of spiking neurons we consider consists of excitatory and inhibitory neurons. Each neuron is implemented as an integrate-and-fire model that accurately mimics the behavior of biological neurons. To test performance of our new plasticity rule we designed a model of a biologically-inspired signal processing system, and used it for object detection in eye images of diabetic retinopathy patients, and lung images of cystic fibrosis patients. The results show that the network detects the edges of objects within an image, essentially segmenting it. Our ultimate goal, however, is not the development of an image segmentation tool that would be more efficient than nonbiological algorithms, but developing a physiologically correct neural network model that could be applied to a wide range of neurological experiments. We decided to validate the SAPR by using it in a network of spiking neurons for image segmentation because it is easy to visually assess the results. An important thing is that image segmentation is done in an entirely unsupervised way.

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PubMed2005

Do interictal spikes drive epileptogenesis?

Interictal spikes are periodic, very brief bursts of neuronal activity that are observed in the electroencephalogram of patients with chronic epilepsy. These spikes are useful diagnostically, but we do not know why they are so strongly associated with the spontaneous seizures that characterize chronic epilepsy. Interictal spikes appear before the first spontaneous seizures in animal models of acquired epilepsy, and spikes are sufficient to induce long-term changes in synaptic connections between neurons. Thus, spikes may guide the development of the neuronal circuits that initiate spontaneous seizures. If so, then attempts to prevent or cure epilepsy may best be directed at spikes rather than seizures.

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