Abstract
We present an electrophysiological dataset collected from the amygdalae of nine participants attending a visual dynamic stimulation of emotional aversive content. The participants were patients affected by epilepsy who underwent preoperative invasive monitoring in the mesial temporal lobe. Participants were presented with dynamic visual sequences of fearful faces (aversive condition), interleaved with sequences of neutral landscapes (neutral condition). The dataset contains the simultaneous recording of intracranial EEG (iEEG) and neuronal spike times and waveforms, and localization information for iEEG electrodes. Participant characteristics and trial information are provided. We technically validated this dataset and provide here the spike sorting quality metrics and the spectra of iEEG signals. This dataset allows the investigation of amygdalar response to dynamic aversive stimuli at multiple spatial scales, from the macroscopic EEG to the neuronal firing in the human brain.
Highlights
Background & SummarySeveral aspects of perception and cognition involve the amygdala
Electrophysiological oscillatory responses in the human amygdala are mostly explored in patients with refractory epilepsy who are undergoing pre-surgical monitoring[11,12]
The intracranial electroencephalography records local field potentials that result from the activity of thousands of neurons[13]
Summary
Several aspects of perception and cognition involve the amygdala. Neural activity within the amygdala is implied in novelty detection[1], perception of faces[2], emotions[3] and aversive learning[4]. Electrophysiological oscillatory responses in the human amygdala are mostly explored in patients with refractory epilepsy who are undergoing pre-surgical monitoring[11,12] In these patients, the intracranial electroencephalography (iEEG) records local field potentials that result from the activity of thousands of neurons[13]. Along with the iEEG traces and neuronal recordings, we here provide the technical validation of the quality of the isolated neurons, the localization information for iEEG electrodes, and the task video[19] This dataset represents a unique opportunity for further investigation of the cross-scale dynamics that define the relation between macroscopic oscillatory activity in the iEEG and the neuronal firing in the human amygdala
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