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Articles 1 - 4 of 4
Full-Text Articles in Computational Neuroscience
Theoretical Analysis Of Cnns For Automatic Seizure Detection In Eeg Signals, Jackson T. Small
Theoretical Analysis Of Cnns For Automatic Seizure Detection In Eeg Signals, Jackson T. Small
Honors Undergraduate Theses
Epilepsy is a common brain disorder where neurons in the brain rapidly fire, causing recurring seizures. The brain activity during a seizure can be detected by electroencephalogram (EEG) signals; however, this process is not only labor-intensive and time-consuming but is also subject to inter-rater variability, with a study showing only moderate agreement when diagnosing patients, even among experts. Convolutional Neural Networks (CNNs) are often proposed to detect seizures automatically, achieving high performance. The focus on performance comes at a cost of losing interpretability, leaving the model as effective but seen as a ’black box’. This thesis confronts the interpretability knowledge …
Accelerated Forgetting In People With Epilepsy: Pathologic Memory Loss, Its Neural Basis, And Potential Therapies, Sarah Ashley Steimel Phd
Accelerated Forgetting In People With Epilepsy: Pathologic Memory Loss, Its Neural Basis, And Potential Therapies, Sarah Ashley Steimel Phd
Dartmouth College Ph.D Dissertations
While forgetting is vital to human functioning, delineating between normative and disordered forgetting can become incredibly complex. This thesis characterizes a pathologic form of forgetting in epilepsy, identifies a neural basis, and investigates the potential of stimulation as a therapeutic tool. Chapter 2 presents a behavioral characterization of the time course of Accelerated Long-Term Forgetting (ALF) in people with epilepsy (PWE). This chapter shows evidence of ALF on a shorter time scale than previous studies, with a differential impact on recall and recognition. Chapter 3 builds upon the work in Chapter 2 by extending ALF time points and investigating the …
Energy As A Limiting Factor In Neuronal Seizure Control: A Mathematical Model, Sophia E. Epstein
Energy As A Limiting Factor In Neuronal Seizure Control: A Mathematical Model, Sophia E. Epstein
CMC Senior Theses
The majority of seizures are self-limiting. Within a few minutes, the observed neuronal synchrony and deviant dynamics of a tonic-clonic or generalized seizure often terminate. However, a small epilesia partialis continua can occur for years. The mechanisms that regulate subcortical activity of neuronal firing and seizure control are poorly understood. Published studies, however, through PET scans, ketogenic treatments, and in vivo mouse experiments, observe hypermetabolism followed by metabolic suppression. These observations indicate that energy can play a key role in mediating seizure dynamics. In this research, I seek to explore this hypothesis and propose a mathematical framework to model how …
Field Effects And Ictal Synchronization: Insights From In Homine Observations, Shennan A. Weiss, Guy Mckhann Jr., Robert Goodman, Ronald G. Emerson, Andrew Trevelyan, Marom Bikson, Catherine A. Schevon
Field Effects And Ictal Synchronization: Insights From In Homine Observations, Shennan A. Weiss, Guy Mckhann Jr., Robert Goodman, Ronald G. Emerson, Andrew Trevelyan, Marom Bikson, Catherine A. Schevon
Publications and Research
It has been well established in animal models that electrical fields generated during inter-ictal and ictal discharges are strong enough in intensity to influence action potential firing threshold and synchronization. We discuss recently published data from microelectrode array recordings of human neocortical seizures and speculate about the possible role of field effects in neuronal synchronization. We have identified two distinct seizure territories that cannot be easily distinguished by traditional EEG analysis. The ictal core exhibits synchronized neuronal burst firing, while the surrounding ictal penumbra exhibits asynchronous and relatively sparse neuronal activity. In the ictal core large amplitude rhythmic ictal discharges …