Introduction: The unpredictability of epileptic seizures is considered an important threat to the quality of life of a person with epilepsy. Currently, however, there are no tools for seizure prediction that can be applied to the domestic setting. Although the information about seizure-alert dogs - dogs that display changes in behavior before a seizure that are interpreted by the owner as an alert - is mostly anecdotal; living with an alerting dog (AD) has been reported to improve quality of life of the owner by reducing the stress originating from the unpredictability of epileptic seizures and, sometimes, diminishing the seizure frequency.
Aim Of The Study: The aim of the study was to investigate, at an international level, the behaviors displayed by trained and untrained dogs that are able to anticipate seizures and to identify patient- and dog-related factors associated with the presence or absence of alerting behavior.
Methodology: An online questionnaire for dog owners with seizures was designed. Information about the participants (demographics, seizure type, presence of preictal symptoms) and their dogs (demographics, behavior around the time of seizures) was collected. In addition, two validated scales were included to measure the human-dog relationship (Monash Dog-Owner Relationship scale (MDORS)) and five different traits of the dogs' personality (Monash Canine Personality Questionnaire refined (MCPQ-R)).
Results: Two hundred and twenty-seven responses of people experiencing seizures were received from six participant countries: 132 from people with dogs that had started alerting spontaneously, 10 from owners of trained AD, and the rest from owners of dogs that did not display any alerting behavior (nonalerting dog (NAD)). Individuals' gender, age, or seizure type did not predict the presence of alerting behavior in their dogs. People who indicated that they experience preictal symptoms were more likely to have a spontaneously AD. The owner-dog bond was significantly higher with ADs compared with NADs, and ADs scored significantly higher than NADs in the personality traits "Amicability", "Motivation", and "Training focus".
Conclusion: This study collected a large group of dog owners with seizures reporting behavioral changes in their dogs before their seizures occurred. This was associated with the presence of preictal symptoms. The seizure-alerting behavior of the dog may have a positive influence on the bond between the owner and the dog.
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http://dx.doi.org/10.1016/j.yebeh.2019.02.001 | DOI Listing |
J Neural Eng
December 2024
Muir Maxwell Epilepsy Centre, University of Edinburgh, Edinburgh, United Kingdom.
. Accurate seizure prediction could prove critical for improving patient safety and quality of life in drug-resistant epilepsy. While deep learning-based approaches have shown promising performance using scalp electroencephalogram (EEG) signals, the incomplete understanding and variability of the preictal state imposes challenges in identifying the optimal preictal period (OPP) for labeling the EEG segments.
View Article and Find Full Text PDFRev Prat
November 2024
Service de psychiatrie, université de Lorraine et service de neurologie, hôpital central de Nancy, Nancy, France.
EPILEPSY AND PSYCHIATRIC DISORDERS (EPI-PSY). Epilepsy is not only a brain pathology characterized by a lasting predisposition to generate seizures, it is also associated with cognitive, behavioral, psychological, and social disorders. The interaction between psychiatric pathologies and epilepsy is bidirectional and complex.
View Article and Find Full Text PDFEur J Pain
January 2025
Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Background: Functional neuroimaging studies indicate that central transmission of trigeminal pain may commence up to 48 h prior to the onset of headache. Whether these cyclic changes are associated with somatosensory alteration remains incompletely understood.
Methods: The present study aimed to investigate the temporal progression of somatosensory alterations preceding the onset of a migraine attack.
Biomed Phys Eng Express
November 2024
Edmond and Lily Safra International Institute of Neurosciences, Santos Dumont Institute, 59288-899 Macaiba, Brazil.
This study proposes a closed-loop brain-machine interface (BMI) based on spinal cord stimulation to inhibit epileptic seizures, applying a semi-supervised machine learning approach that learns from Local Field Potential (LFP) patterns acquired on the pre-ictal (preceding the seizure) condition.LFP epochs from the hippocampus and motor cortex are band-pass filtered from 1 to 13 Hz, to obtain the time-frequency representation using the continuous Wavelet transform, and successively calculate the phase lock values (PLV). As a novelty, the-score-based PLV normalization using both modified-means and Davies-Bouldin's measure for clustering is proposed here.
View Article and Find Full Text PDFEpilepsia
December 2024
INSERM, LTSI U1099, Université de Rennes, Rennes, France.
Objective: For the pre-surgical evaluation of patients with drug-resistant focal epilepsy, stereo-electroencephalographic (SEEG) signals are routinely recorded to identify the epileptogenic zone network (EZN). This network consists of remote brain regions involved in seizure initiation. However, the pathophysiological mechanisms underlying typical SEEG patterns that occur during the transition from interictal to ictal activity in distant brain nodes of the EZN remain poorly understood.
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