Applying a Machine Learning Method to Detect Changing Neuronal Activity in Seizure Disorders
This study aims to use machine learning to find miniature excitatory postsynaptic currents (EPSCs) in neurons of a Drosophila to find behavior markers of a seizure. Using MATLAB, we are training a machine learning model on electrophysiological data to recognize patterns of post-synaptic events that...
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| Format: | Article |
| Language: | English |
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LibraryPress@UF
2025-05-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
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| Online Access: | https://journals.flvc.org/FLAIRS/article/view/138939 |
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| author | Cengiz Gunay Krishan Bhalsod |
| author_facet | Cengiz Gunay Krishan Bhalsod |
| author_sort | Cengiz Gunay |
| collection | DOAJ |
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This study aims to use machine learning to find miniature excitatory postsynaptic currents (EPSCs) in neurons of a Drosophila to find behavior markers of a seizure. Using MATLAB, we are training a machine learning model on electrophysiological data to recognize patterns of post-synaptic events that show potential seizure activity. We have faced challenges applying this method and we are planning to present these in our poster. The results of this research may help develop a further understanding of seizure mechanisms in Drosophila that could translate into a more in-depth understanding for neurological disorders in humans.
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| format | Article |
| id | doaj-art-2836218f14fe47409f404c4bb2d24d4e |
| institution | OA Journals |
| issn | 2334-0754 2334-0762 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | LibraryPress@UF |
| record_format | Article |
| series | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| spelling | doaj-art-2836218f14fe47409f404c4bb2d24d4e2025-08-20T02:30:39ZengLibraryPress@UFProceedings of the International Florida Artificial Intelligence Research Society Conference2334-07542334-07622025-05-0138110.32473/flairs.38.1.138939Applying a Machine Learning Method to Detect Changing Neuronal Activity in Seizure DisordersCengiz Gunay0Krishan Bhalsod1https://orcid.org/0009-0007-1338-054XGeorgia Gwinnett CollegeGeorgia Gwinnett College This study aims to use machine learning to find miniature excitatory postsynaptic currents (EPSCs) in neurons of a Drosophila to find behavior markers of a seizure. Using MATLAB, we are training a machine learning model on electrophysiological data to recognize patterns of post-synaptic events that show potential seizure activity. We have faced challenges applying this method and we are planning to present these in our poster. The results of this research may help develop a further understanding of seizure mechanisms in Drosophila that could translate into a more in-depth understanding for neurological disorders in humans. https://journals.flvc.org/FLAIRS/article/view/138939time series analysisevent detectionMODoptimal filterneuronsynapse |
| spellingShingle | Cengiz Gunay Krishan Bhalsod Applying a Machine Learning Method to Detect Changing Neuronal Activity in Seizure Disorders Proceedings of the International Florida Artificial Intelligence Research Society Conference time series analysis event detection MOD optimal filter neuron synapse |
| title | Applying a Machine Learning Method to Detect Changing Neuronal Activity in Seizure Disorders |
| title_full | Applying a Machine Learning Method to Detect Changing Neuronal Activity in Seizure Disorders |
| title_fullStr | Applying a Machine Learning Method to Detect Changing Neuronal Activity in Seizure Disorders |
| title_full_unstemmed | Applying a Machine Learning Method to Detect Changing Neuronal Activity in Seizure Disorders |
| title_short | Applying a Machine Learning Method to Detect Changing Neuronal Activity in Seizure Disorders |
| title_sort | applying a machine learning method to detect changing neuronal activity in seizure disorders |
| topic | time series analysis event detection MOD optimal filter neuron synapse |
| url | https://journals.flvc.org/FLAIRS/article/view/138939 |
| work_keys_str_mv | AT cengizgunay applyingamachinelearningmethodtodetectchangingneuronalactivityinseizuredisorders AT krishanbhalsod applyingamachinelearningmethodtodetectchangingneuronalactivityinseizuredisorders |