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Neuronal complexity tracks changes of epileptic activity and identifies epilepsy patients independent of interictal epileptiform discharges.

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Title: Neuronal complexity tracks changes of epileptic activity and identifies epilepsy patients independent of interictal epileptiform discharges.
Authors: Kienitz, Ricardo (AUTHOR), Strüber, Michael (AUTHOR), Merkel, Nina (AUTHOR), Süß, Annika (AUTHOR), Spyrantis, Andrea (AUTHOR), Strzelczyk, Adam (AUTHOR), Rosenow, Felix (AUTHOR)
Source: Epilepsia (Series 4). Mar2025, Vol. 66 Issue 3, p790-801. 12p.
Subjects: Temporal lobe epilepsy, Biomarkers, Anticonvulsants, Electroencephalography, People with epilepsy, Diagnosis
Abstract: Objective: To date, the identification of objective biomarkers of neural epileptic activity (EA) remains challenging. We therefore investigated whether neuronal complexity could serve as an interictal electroencephalographic measure of EA, independent of interictal epileptiform discharges (IEDs). By tapering anti‐seizure medication (ASM) during video‐EEG (electroencephalography) monitoring (VEM), we studied whether changes in neuronal complexity could reliably indicate the increase in EA and identify patients with epilepsy. Methods: The study included 27 patients with unilateral mesial temporal lobe epilepsy (TLE) and 24 control patients with non‐epileptic episodes (NEEs) only, each undergoing ASM reduction during VEM. Thirteen additional patients undergoing intracranial recordings during VEM were included to study the relation of surface EEG complexity to intracranial IED. Neuronal complexity was quantified using sample entropy. Delta power served as a control parameter. Receiver‐operating characteristic (ROC) analysis was used to evaluate diagnostic performance. Results: As ASM was reduced, patients with epilepsy showed a significant decrease in neuronal complexity over consecutive days (p =.0008). In contrast, patients with NEE showed no significant change in neuronal complexity (p =.78). Delta power in contrast increased and did not differ significantly between patients with TLE and patients with NEE (p = 1). ROC analysis demonstrated that neuronal complexity effectively distinguished between patients with epilepsy and patients with NEE (area under the curve [AUC] =.76), whereas delta power performed at chance level (AUC =.5). Analysis of simultaneously recorded surface and intracranial EEG showed that hippocampal IEDs are followed by an increase in surface EEG delta power (p = 1.8 × 10−18) without any significant change in complexity (p =.39). Significance: An increase in EA caused by ASM reduction resulted in a loss of neuronal complexity in surface EEG recordings of patients with epilepsy, independent of IEDs. These findings suggest that neuronal complexity could serve as a potential biomarker to differentiate between epilepsy patients and those with NEEs only. This holds promise for improving the clinical evaluation of EA in epilepsy, addressing the limitations of seizure frequency and IED identification. [ABSTRACT FROM AUTHOR]
Copyright of Epilepsia (Series 4) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Neuronal complexity tracks changes of epileptic activity and identifies epilepsy patients independent of interictal epileptiform discharges.
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  Data: <searchLink fieldCode="AR" term="%22Kienitz%2C+Ricardo%22">Kienitz, Ricardo</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Strüber%2C+Michael%22">Strüber, Michael</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Merkel%2C+Nina%22">Merkel, Nina</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Süß%2C+Annika%22">Süß, Annika</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Spyrantis%2C+Andrea%22">Spyrantis, Andrea</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Strzelczyk%2C+Adam%22">Strzelczyk, Adam</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rosenow%2C+Felix%22">Rosenow, Felix</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Epilepsia+%28Series+4%29%22">Epilepsia (Series 4)</searchLink>. Mar2025, Vol. 66 Issue 3, p790-801. 12p.
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  Data: <searchLink fieldCode="DE" term="%22Temporal+lobe+epilepsy%22">Temporal lobe epilepsy</searchLink><br /><searchLink fieldCode="DE" term="%22Biomarkers%22">Biomarkers</searchLink><br /><searchLink fieldCode="DE" term="%22Anticonvulsants%22">Anticonvulsants</searchLink><br /><searchLink fieldCode="DE" term="%22Electroencephalography%22">Electroencephalography</searchLink><br /><searchLink fieldCode="DE" term="%22People+with+epilepsy%22">People with epilepsy</searchLink><br /><searchLink fieldCode="DE" term="%22Diagnosis%22">Diagnosis</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Objective: To date, the identification of objective biomarkers of neural epileptic activity (EA) remains challenging. We therefore investigated whether neuronal complexity could serve as an interictal electroencephalographic measure of EA, independent of interictal epileptiform discharges (IEDs). By tapering anti‐seizure medication (ASM) during video‐EEG (electroencephalography) monitoring (VEM), we studied whether changes in neuronal complexity could reliably indicate the increase in EA and identify patients with epilepsy. Methods: The study included 27 patients with unilateral mesial temporal lobe epilepsy (TLE) and 24 control patients with non‐epileptic episodes (NEEs) only, each undergoing ASM reduction during VEM. Thirteen additional patients undergoing intracranial recordings during VEM were included to study the relation of surface EEG complexity to intracranial IED. Neuronal complexity was quantified using sample entropy. Delta power served as a control parameter. Receiver‐operating characteristic (ROC) analysis was used to evaluate diagnostic performance. Results: As ASM was reduced, patients with epilepsy showed a significant decrease in neuronal complexity over consecutive days (p =.0008). In contrast, patients with NEE showed no significant change in neuronal complexity (p =.78). Delta power in contrast increased and did not differ significantly between patients with TLE and patients with NEE (p = 1). ROC analysis demonstrated that neuronal complexity effectively distinguished between patients with epilepsy and patients with NEE (area under the curve [AUC] =.76), whereas delta power performed at chance level (AUC =.5). Analysis of simultaneously recorded surface and intracranial EEG showed that hippocampal IEDs are followed by an increase in surface EEG delta power (p = 1.8 × 10−18) without any significant change in complexity (p =.39). Significance: An increase in EA caused by ASM reduction resulted in a loss of neuronal complexity in surface EEG recordings of patients with epilepsy, independent of IEDs. These findings suggest that neuronal complexity could serve as a potential biomarker to differentiate between epilepsy patients and those with NEEs only. This holds promise for improving the clinical evaluation of EA in epilepsy, addressing the limitations of seizure frequency and IED identification. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Epilepsia (Series 4) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1111/epi.18218
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      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 790
    Subjects:
      – SubjectFull: Temporal lobe epilepsy
        Type: general
      – SubjectFull: Biomarkers
        Type: general
      – SubjectFull: Anticonvulsants
        Type: general
      – SubjectFull: Electroencephalography
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      – SubjectFull: People with epilepsy
        Type: general
      – SubjectFull: Diagnosis
        Type: general
    Titles:
      – TitleFull: Neuronal complexity tracks changes of epileptic activity and identifies epilepsy patients independent of interictal epileptiform discharges.
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              M: 03
              Text: Mar2025
              Type: published
              Y: 2025
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