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Related Concept Videos

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Electroconvulsive therapy (ECT), or shock therapy, remains a critical biomedical intervention for severe, treatment-resistant depression. While its origins can be traced back to Hippocrates' observations that malaria-induced convulsions alleviated mental illness, modern ECT has evolved significantly from its earlier, more primitive applications. First introduced in 1938 by Ugo Cerletti and his colleagues, ECT involves inducing controlled seizures using electrical currents. In its early...
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Epilepsy is a chronic neurological disease marked by recurrent, unpredictable seizures. These seizures are caused by abnormal electrical discharges in the brain, leading to behavior, sensation, or consciousness alterations. They can also cause transient impairment of awareness, interfering with daily activities.
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Related Experiment Video

Updated: Jul 9, 2025

Investigating the Function of Deep Cortical and Subcortical Structures Using Stereotactic Electroencephalography: Lessons from the Anterior Cingulate Cortex
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Electroencephalography in encephalopathy and encephalitis.

Hollie Morris1, Peter W Kaplan2, Nick Kane3

  • 1Grey Walter Dept of Clinical Neurophysiology, North Bristol NHS Trust, Bristol, UK.

Practical Neurology
|December 5, 2023
PubMed
Summary

Electroencephalography (EEG) aids neurological exams by detecting subtle brain dysfunction and monitoring activity. Advanced EEG analysis can identify real-time changes, improving patient outcomes in various neurological conditions.

Keywords:
CLINICAL NEUROLOGYCOMACREUTZFELDT-JAKOB DISEASEEEGNEUROPHYSIOLOGY

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Area of Science:

  • Neurology
  • Neurophysiology

Background:

  • Electroencephalography (EEG) is a valuable tool for assessing cerebral function.
  • It detects subclinical disturbances and allows for longitudinal monitoring of brain activity.

Purpose of the Study:

  • To highlight the utility of continuous EEG with quantitative analysis and machine learning for real-time detection of neurological changes.
  • To emphasize EEG's role in diagnosing specific encephalopathies and its inclusion in clinical guidelines.

Main Methods:

  • Continuous EEG monitoring.
  • Quantitative EEG analysis.
  • Machine learning algorithms for real-time change detection.

Main Results:

  • EEG can identify subtle or subclinical cerebral dysfunction.
  • Specific EEG patterns can suggest particular pathologies (e.g., HSV-1 encephalitis, Creutzfeldt-Jakob disease, autoimmune encephalitis).
  • EEG is crucial for diagnosing non-convulsive seizures and status epilepticus, especially in critical care.

Conclusions:

  • EEG is an indispensable tool for neurological assessment, monitoring, and prognostication.
  • Advanced EEG techniques enhance early detection and understanding of neurological conditions.
  • EEG aids in managing critical neurological states and understanding concepts like epileptic encephalopathy.