Objective: Seizures of frontal or temporal lobe origin can associate with vocalizations in humans. Our objective was to assess whether rats emit specific seizure-related patterns of ultrasonic vocalizations (USVs) during seizures and epileptiform activity.
Methods: Adult male Sprague-Dawley rats were treated with a single administration of pentylenetetrazol (PTZ, 50 mg/kg, i.p.) and monitored with simultaneous USV and video-electroencephalogram recordings for up to 15 min. USVs were detected using a deep learning algorithm (DeepSqueak-Screener) and manually annotated into the 15 previously described subcategories. The number, frequency, duration, sonographic structure, and temporal relationship of the USVs to seizures and epileptiform activity were assessed.
Results: A total of 2147 USVs were recorded in 12 rats that expressed a total of 22 PTZ-induced seizures. Of the USVs, 77% were in the 50-kHz range (i.e., appetitive state) and 23% in the 22-kHz ( i.e., aversive state) range. More than a third (37%) of the USVs could be classified into 1 of the 15 call subcategories; the remaining 63% belonged to a novel "multiform" USV category with a complex sonographic structure. Of the 2147 USVs, 23% occurred during the PTZ-induced seizures and 77% during other types of PTZ-induced epileptiform activity. Almost all (19/22) of seizures were associated with USVs. In each rat, the first seizure was always associated with a USV. The shorter the latency to the first USV, the shorter the latency to the onset of the first electrographic seizure (r = 0.995, p < 0.001). The greater the number of USVs, the greater the number of seizures (r = 0.916, p < 0.001) and the longer the total seizure duration in a given rat (r = 0.750, p < 0.05).
Significance: Like in humans, vocalizations are a seizure-related behavioral feature in rats and recording USVs provides a novel noninvasive tool for detecting experimental seizures. Further studies are needed to explore USV occurrence during spontaneous seizures and their potential for screening novel anti-seizure drugs.
Keywords: Deep learning; Epileptiform activity; Pentylenetetrazol; Seizure; Ultrasonic vocalizations; Video-EEG.
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