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Benoit J, Martin F, Thomas P. Disconjugate paroxysmal oculomotor movements in psychogenic nonepileptic seizures: A video-EEG study of three patients. Epileptic Disord 2024; 26:533-535. [PMID: 38808527 DOI: 10.1002/epd2.20232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 03/24/2024] [Accepted: 04/15/2024] [Indexed: 05/30/2024]
Abstract
Content available: Video
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Affiliation(s)
- Jeanne Benoit
- UF EEG-Épileptologie, Service de Neurologie, University Hospitals of Nice, Nice, France
- Université Côte d'Azur, CHU Nice, UR2CA-URRIS, Nice, France
| | - Florence Martin
- UF EEG-Épileptologie, Service de Neurologie, University Hospitals of Nice, Nice, France
| | - Pierre Thomas
- UF EEG-Épileptologie, Service de Neurologie, University Hospitals of Nice, Nice, France
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Hadzic A, Andersson S. Non-ictal, interictal and ictal déjà vu: a systematic review and meta-analysis. Front Neurol 2024; 15:1406889. [PMID: 38966090 PMCID: PMC11223632 DOI: 10.3389/fneur.2024.1406889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 05/27/2024] [Indexed: 07/06/2024] Open
Abstract
Background Déjà vu, French for "already seen," is a phenomenon most people will experience at least once in their lifetime. Emerging evidence suggests that déjà vu occurs in healthy individuals (as "non-ictal déjà vu") and in epilepsy patients during seizures (as "ictal déjà vu") and between seizures (as "interictal déjà vu"). Although the ILAE has recognized déjà vu as a feature of epileptic seizures, it is notably absent from the ICD-11. A lack of evidence-based research may account for this omission. To our knowledge, this study represents the first systematic review and meta-analysis on déjà vu experiences. Through detailed examinations of non-ictal, interictal and ictal déjà vu, we seek to highlight possible clinical implications. Rethinking the status quo of ictal déjà vu could potentially lead to earlier interventions and improve outcomes for epilepsy patients. Methods This study was registered in PROSPERO (ID: CRD42023394239) on 5 February 2023. Systematic searches were conducted across four databases: EMBASE, MEDLINE, PsycINFO, and PubMed, from inception to 1 February 2023, limited to English language and human participants. Studies were included/excluded based on predefined criteria. Data was extracted according to the PICO framework and synthesized through a thematic approach. Meta-analyses were performed to estimate prevalence's of the phenomena. Study quality, heterogeneity, and publication bias were assessed. Results Database searching identified 1,677 records, of which 46 studies were included. Meta-analyses of prevalence showed that non-ictal déjà vu was experienced by 0.74 (95% CI [0.67, 0.79], p < 0.001) of healthy individuals, whereas interictal déjà vu was experienced by 0.62 (95% CI [0.48, 0.75], p = 0.099) and ictal déjà vu by 0.22 (95% CI [0.15, 0.32], p = 0.001) of epilepsy patients. Examinations of phenomenological (sex, age, frequency, duration, emotional valence, and dissociative symptoms) and neuroscientific (brain structures and functions) data revealed significant variations between non-ictal, interictal and ictal déjà vu on several domains. Conclusion This systematic review and meta-analysis do not support the notion that non-ictal, interictal and ictal déjà vu are homogenous experiences. Instead, it provides insight into ictal déjà vu as a symptom of epilepsy that should be considered included in future revisions of the ICD-11. Systematic Review Registration https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=394239, CRD42023394239.
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Affiliation(s)
- Alena Hadzic
- Section for Clinical and Cognitive Neuroscience, Department of Psychology, University of Oslo, Oslo, Norway
- Section for Pharmacology and Pharmaceutical Biosciences, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Stein Andersson
- Section for Clinical and Cognitive Neuroscience, Department of Psychology, University of Oslo, Oslo, Norway
- Psychosomatic Medicine and CL Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
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Vijay M, Reuber M. An update on psychogenic nonepileptic seizures. Curr Opin Neurol 2024; 37:121-126. [PMID: 38235768 DOI: 10.1097/wco.0000000000001245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
PURPOSE OF REVIEW The understanding of psychogenic nonepileptic seizures (PNES) has advanced steadily over recent decades. This update summarizes new insights from the last three years. RECENT FINDINGS The process of diagnosing PNES has shifted from the exclusion of epilepsy to one based on the recognition of typical clinical features. While the diagnosis cannot rely on any single feature in isolation, a range of semiological features characterising PNES are now recognised and a number of studies hint at the potential for machine learning and AI to improve the diagnostic process. Advances in data processing and analysis may also help to make sense of the heterogeneity of PNES populations demonstrated by recent studies focussing on aetiology and patient subgroups. It is now clear that PNES are associated with high rates of mental and physical comorbidities and premature death, highlighting that they are only one manifestation of a complex disorder extending beyond the nervous system and the seizures themselves. SUMMARY PNES are now understood as a manifestation of dysfunction in interacting brain networks. This understanding provides an explanation for the psychopathological and semiological heterogeneity of PNES patient populations. New insights into medical comorbidities and increased rates of premature death call for more research into associated pathological processes outside the nervous system.
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Affiliation(s)
| | - Markus Reuber
- Department of Neurology
- Academic Neurology Unit, University of Sheffield, Royal Hallamshire Hospital, Sheffield, United Kingdom
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Kerr WT, McFarlane KN. Machine Learning and Artificial Intelligence Applications to Epilepsy: a Review for the Practicing Epileptologist. Curr Neurol Neurosci Rep 2023; 23:869-879. [PMID: 38060133 DOI: 10.1007/s11910-023-01318-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/24/2023] [Indexed: 12/08/2023]
Abstract
PURPOSE OF REVIEW Machine Learning (ML) and Artificial Intelligence (AI) are data-driven techniques to translate raw data into applicable and interpretable insights that can assist in clinical decision making. Some of these tools have extremely promising initial results, earning both great excitement and creating hype. This non-technical article reviews recent developments in ML/AI in epilepsy to assist the current practicing epileptologist in understanding both the benefits and limitations of integrating ML/AI tools into their clinical practice. RECENT FINDINGS ML/AI tools have been developed to assist clinicians in almost every clinical decision including (1) predicting future epilepsy in people at risk, (2) detecting and monitoring for seizures, (3) differentiating epilepsy from mimics, (4) using data to improve neuroanatomic localization and lateralization, and (5) tracking and predicting response to medical and surgical treatments. We also discuss practical, ethical, and equity considerations in the development and application of ML/AI tools including chatbots based on Large Language Models (e.g., ChatGPT). ML/AI tools will change how clinical medicine is practiced, but, with rare exceptions, the transferability to other centers, effectiveness, and safety of these approaches have not yet been established rigorously. In the future, ML/AI will not replace epileptologists, but epileptologists with ML/AI will replace epileptologists without ML/AI.
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Affiliation(s)
- Wesley T Kerr
- Department of Neurology, University of Pittsburgh, 3471 Fifth Ave, Kaufmann 811.22, Pittsburgh, PA, 15213, USA.
- Department of Biomedical Informatics, University of Pittsburgh, 3471 Fifth Ave, Kaufmann 811.22, Pittsburgh, PA, 15213, USA.
- Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA.
| | - Katherine N McFarlane
- Department of Neurology, University of Pittsburgh, 3471 Fifth Ave, Kaufmann 811.22, Pittsburgh, PA, 15213, USA
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Kerr WT. Using Verbally-Reported and Video-Observed Semiology to Identify Functional Seizures. Neurol Clin 2023; 41:605-617. [PMID: 37775193 DOI: 10.1016/j.ncl.2023.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/01/2023]
Abstract
Diagnosis of functional seizures, also known as psychogenic nonepileptic seizures, starts with a clinical interview and description of the seizures. A targeted approach to this evaluation can provide valuable information to gauge the likelihood of functional seizures as compared with other similar conditions including but not limited to epileptic seizures. This review focuses on the use of patient and witness descriptions and seizure videos to identify patients with probable functional seizures. Particular emphasis is given to recognizing the limitations of the available data and the influence of health-care provider expertise on diagnostic accuracy.
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Affiliation(s)
- Wesley T Kerr
- Department of Neurology, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI 48109, USA.
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Kerr WT, Tatekawa H, Lee JK, Karimi AH, Sreenivasan SS, O'Neill J, Smith JM, Hickman LB, Savic I, Nasrullah N, Espinoza R, Narr K, Salamon N, Beimer NJ, Hadjiiski LM, Eliashiv DS, Stacey WC, Engel J, Feusner JD, Stern JM. Clinical MRI morphological analysis of functional seizures compared to seizure-naïve and psychiatric controls. Epilepsy Behav 2022; 134:108858. [PMID: 35933959 DOI: 10.1016/j.yebeh.2022.108858] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 06/26/2022] [Accepted: 07/15/2022] [Indexed: 11/15/2022]
Abstract
PURPOSE Functional seizures (FS), also known as psychogenic nonepileptic seizures (PNES), are physical manifestations of acute or chronic psychological distress. Functional and structural neuroimaging have identified objective signs of this disorder. We evaluated whether magnetic resonance imaging (MRI) morphometry differed between patients with FS and clinically relevant comparison populations. METHODS Quality-screened clinical-grade MRIs were acquired from 666 patients from 2006 to 2020. Morphometric features were quantified with FreeSurfer v6. Mixed-effects linear regression compared the volume, thickness, and surface area within 201 regions-of-interest for 90 patients with FS, compared to seizure-naïve patients with depression (n = 243), anxiety (n = 68), and obsessive-compulsive disorder (OCD, n = 41), respectively, and to other seizure-naïve controls with similar quality MRIs, accounting for the influence of multiple confounds including depression and anxiety based on chart review. These comparison populations were obtained through review of clinical records plus research studies obtained on similar scanners. RESULTS After Bonferroni-Holm correction, patients with FS compared with seizure-naïve controls exhibited thinner bilateral superior temporal cortex (left 0.053 mm, p = 0.014; right 0.071 mm, p = 0.00006), thicker left lateral occipital cortex (0.052 mm, p = 0.0035), and greater left cerebellar white-matter volume (1085 mm3, p = 0.0065). These findings were not accounted for by lower MRI quality in patients with FS. CONCLUSIONS These results reinforce prior indications of structural neuroimaging correlates of FS and, in particular, distinguish brain morphology in FS from that in depression, anxiety, and OCD. Future work may entail comparisons with other psychiatric disorders including bipolar and schizophrenia, as well as exploration of brain structural heterogeneity within FS.
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Affiliation(s)
- Wesley T Kerr
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA.
| | - Hiroyuki Tatekawa
- Department of Radiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - John K Lee
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Amir H Karimi
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Siddhika S Sreenivasan
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Joseph O'Neill
- Division of Child & Adolescent Psychiatry, Jane & Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA; Brain Research Institute, University of California Los Angeles, Los Angeles, CA, USA
| | - Jena M Smith
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - L Brian Hickman
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Ivanka Savic
- Department of Women's and Children's Health, Karolinska Institute and Neurology Clinic, Karolinksa University Hospital, Karolinska Universitetssjukhuset, Stockholm, Sweden
| | - Nilab Nasrullah
- Department of Women's and Children's Health, Karolinska Institute and Neurology Clinic, Karolinksa University Hospital, Karolinska Universitetssjukhuset, Stockholm, Sweden
| | - Randall Espinoza
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Katherine Narr
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Department of Radiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Nicholas J Beimer
- Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Psychiatry, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Lubomir M Hadjiiski
- Department of Radiology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Dawn S Eliashiv
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - William C Stacey
- Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Jerome Engel
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA; Brain Research Institute, University of California Los Angeles, Los Angeles, CA, USA; Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Jamie D Feusner
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA; Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada; Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - John M Stern
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
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Subjective distinguishability of seizure and non-seizure Déjà Vu: A case report, brief literature review, and research prospects. Epilepsy Behav 2021; 125:108373. [PMID: 34735965 PMCID: PMC8639800 DOI: 10.1016/j.yebeh.2021.108373] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 09/24/2021] [Accepted: 09/25/2021] [Indexed: 11/24/2022]
Abstract
Roughly two-thirds of all people report having experienced déjà vu-the odd feeling that a current experience is both novel and a repeat or replay of a previous, unrecalled experience. Reports of an association between déjà vu and seizure aura symptomatology have accumulated for over a century, and frequent déjà vu is also now known to be associated with focal seizures, particularly those of a medial temporal lobe (MTL) origin. A longstanding question is whether seizure-related déjà vu has the same basis and is the same subjective experience as non-seizure déjà vu. Survey research suggests that people who experience both seizure-related and non-seizure déjà vu can often subjectively distinguish between the two. We present a case of a person with a history of focal MTL seizures who reports having experienced both seizure-related and non-seizure common déjà vu, though the non-seizure type was more frequent during this person's youth than it is currently. The patient was studied with a virtual tour paradigm that has previously been shown to elicit déjà vu among non-clinical, young adult participants. The patient reported experiencing déjà vu of the common non-seizure type during the virtual tour paradigm, without associated abnormalities of the intracranial EEG. We situate this work in the context of broader ongoing projects examining the subjective correlates of seizures. The importance for memory research of virtual scenes, spatial tasks, virtual reality (VR), and this paradigm for isolating familiarity in the context of recall failure are discussed.
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Kerr WT, Zhang X, Hill CE, Janio EA, Chau AM, Braesch CT, Le JM, Hori JM, Patel AB, Allas CH, Karimi AH, Dubey I, Sreenivasan SS, Gallardo NL, Bauirjan J, Hwang ES, Davis EC, D'Ambrosio SR, Al Banna M, Cho AY, Dewar SR, Engel J, Feusner JD, Stern JM. Epilepsy, dissociative seizures, and mixed: Associations with time to video-EEG. Seizure 2021; 86:116-122. [PMID: 33601302 PMCID: PMC7979505 DOI: 10.1016/j.seizure.2021.02.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 01/23/2021] [Accepted: 02/02/2021] [Indexed: 12/12/2022] Open
Abstract
PURPOSE Video-electroencephalographic monitoring (VEM) is a core component to the diagnosis and evaluation of epilepsy and dissociative seizures (DS)-also known as functional or psychogenic seizures-but VEM evaluation often occurs later than recommended. To understand why delays occur, we compared how patient-reported clinical factors were associated with time from first seizure to VEM (TVEM) in patients with epilepsy, DS or mixed. METHODS We acquired data from 1245 consecutive patients with epilepsy, VEM-documented DS or mixed epilepsy and DS. We used multivariate log-normal regression with recursive feature elimination (RFE) to evaluate which of 76 clinical factors interacting with patients' diagnoses were associated with TVEM. RESULTS The mean and median TVEM were 14.6 years and 10 years, respectively (IQR 3-23 years). In the multivariate RFE model, the factors associated with longer TVEM in all patients included unemployment and not student status, more antiseizure medications (current and past), concussion, and ictal behavior suggestive of temporal lobe epilepsy. Average TVEM was shorter for DS than epilepsy, particularly for patients with depression, anxiety, migraines, and eye closure. Average TVEM was longer specifically for patients with DS taking more medications, more seizure types, non-metastatic cancer, and with other psychiatric comorbidities. CONCLUSIONS In all patients with seizures, trials of numerous antiseizure medications, unemployment and non-student status was associated with longer TVEM. These associations highlight a disconnect between International League Against Epilepsy practice parameters and observed referral patterns in epilepsy. In patients with dissociative seizures, some but not all factors classically associated with DS reduced TVEM.
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Affiliation(s)
- Wesley T Kerr
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
| | - Xingruo Zhang
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Chloe E Hill
- Department of Neurology, University of Michigan, Ann Arbor, MI, United States
| | - Emily A Janio
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Andrea M Chau
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Chelsea T Braesch
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Justine M Le
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Jessica M Hori
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Akash B Patel
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Corinne H Allas
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Amir H Karimi
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Ishita Dubey
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Siddhika S Sreenivasan
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Norma L Gallardo
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Janar Bauirjan
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Eric S Hwang
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Emily C Davis
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Shannon R D'Ambrosio
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Mona Al Banna
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Andrew Y Cho
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - Sandra R Dewar
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Jerome Engel
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States; Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States; Brain Research Institute, University of California Los Angeles, Los Angeles, CA, United States
| | - Jamie D Feusner
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States
| | - John M Stern
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
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