Nejvíce citovaný článek - PubMed ID 29410414
Temporal lobe epilepsy is a common neurological disease characterized by recurrent seizures that often originate within limbic networks involving amygdala and hippocampus. The limbic network is involved in crucial physiologic functions involving memory, emotion and sleep. Temporal lobe epilepsy is frequently drug-resistant, and people often experience comorbidities related to memory, mood and sleep. Deep brain stimulation targeting the anterior nucleus of the thalamus (ANT-DBS) is an established therapy for temporal lobe epilepsy. However, the optimal stimulation parameters and their impact on memory, mood and sleep comorbidities remain unclear. We used an investigational brain sensing-stimulation implanted device to accurately track seizures, interictal epileptiform spikes (IES), and memory, mood and sleep comorbidities in five ambulatory subjects. Wireless streaming of limbic network local field potentials (LFPs) and subject behaviour were captured on a mobile device integrated with a cloud environment. Automated algorithms applied to the continuous LFPs were used to accurately cataloged seizures, IES and sleep-wake brain state. Memory and mood assessments were remotely administered to densely sample cognitive and behavioural response during ANT-DBS in ambulatory subjects living in their natural home environment. We evaluated the effect of continuous low-frequency and duty cycle high-frequency ANT-DBS on epileptiform activity and memory, mood and sleep comorbidities. Both low-frequency and high-frequency ANT-DBS paradigms reduced seizures. However, continuous low-frequency ANT-DBS showed greater reductions in IES, electrographic seizures and better sleep and memory outcomes. These results highlight the potential of synchronized brain sensing and dense behavioural tracking during ANT-DBS for optimizing neuromodulation therapy. While studies with larger patient numbers are needed to validate the benefits of low-frequency ANT-DBS, these findings are potentially translatable to individuals currently implanted with ANT-DBS systems.
- Klíčová slova
- artificial intelligence and machine learning, electrical brain stimulation, epilepsy comorbidities, intracranial EEG,
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Treating memory and cognitive deficits requires knowledge about anatomical sites and neural activities to be targeted with particular therapies. Emerging technologies for local brain stimulation offer attractive therapeutic options but need to be applied to target specific neural activities, at distinct times, and in specific brain regions that are critical for memory formation. METHODS: The areas that are critical for successful encoding of verbal memory as well as the underlying neural activities were determined directly in the human brain with intracranial electrophysiological recordings in epilepsy patients. We recorded a broad range of spectral activities across the cortex of 135 patients as they memorised word lists for subsequent free recall. FINDINGS: The greatest differences in the spectral power between encoding subsequently recalled and forgotten words were found in low theta frequency (3-5 Hz) activities of the left anterior prefrontal cortex. This subsequent memory effect was proportionally greater in the lower frequency bands and in the more anterior cortical regions. We found the peak of this memory signal in a distinct part of the prefrontal cortex at the junction between the Broca's area and the frontal pole. The memory effect in this confined area was significantly higher (Tukey-Kramer test, p<0.05) than in other anatomically distinct areas. INTERPRETATION: Our results suggest a focal hotspot of human verbal memory encoding located in the higher-order processing region of the prefrontal cortex, which presents a prospective target for modulating cognitive functions in the human patients. The memory effect provides an electrophysiological biomarker of low frequency neural activities, at distinct times of memory encoding, and in one hotspot location in the human brain. FUNDING: Open-access datasets were originally collected as part of a BRAIN Initiative project called Restoring Active Memory (RAM) funded by the Defence Advanced Research Project Agency (DARPA). CT, ML, MTK and this research were supported from the First Team grant of the Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund.
- Klíčová slova
- Anterior prefrontal cortex, Frontal pole, Human verbal memory, Intracranial recordings, Memory encoding,
- MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- mapování mozku MeSH
- mozek fyziologie MeSH
- paměť * fyziologie MeSH
- prefrontální mozková kůra * fyziologie MeSH
- rozpomínání fyziologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Data comprise intracranial EEG (iEEG) brain activity represented by stereo EEG (sEEG) signals, recorded from over 100 electrode channels implanted in any one patient across various brain regions. The iEEG signals were recorded in epilepsy patients (N = 10) undergoing invasive monitoring and localization of seizures when they were performing a battery of four memory tasks lasting approx. 1 hour in total. Gaze tracking on the task computer screen with estimating the pupil size was also recorded together with behavioral performance. Each dataset comes from one patient with anatomical localization of each electrode contact. Metadata contains labels for the recording channels with behavioral events marked from all tasks, including timing of correct and incorrect vocalization of the remembered stimuli. The iEEG and the pupillometric signals are saved in BIDS data structure to facilitate efficient data sharing and analysis.
- MeSH
- elektrody MeSH
- elektrokortikografie * MeSH
- epilepsie patofyziologie MeSH
- lidé MeSH
- mozek fyziologie MeSH
- oční fixace MeSH
- paměť fyziologie MeSH
- pupila MeSH
- technologie sledování pohybu očí MeSH
- záchvaty patofyziologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- dataset MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH