1
|
Tomlinson SB, Baumgartner ME, Darlington TR, Marsh ED, Kennedy BC. Mapping the Epileptogenic Brain Using Low-Frequency Stimulation: Two Decades of Advances and Uncertainties. J Clin Med 2025; 14:1956. [PMID: 40142764 PMCID: PMC11943392 DOI: 10.3390/jcm14061956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2025] [Revised: 03/03/2025] [Accepted: 03/11/2025] [Indexed: 03/28/2025] Open
Abstract
Cortical stimulation is the process of delivering brief pulses of electrical current and visualizing the distributed pattern of evoked responses across the brain. Compared to high-frequency stimulation, which has long been used for seizure provocation and functional mapping, low-frequency stimulation (<1-2 Hz) is rarely incorporated into the epilepsy surgery evaluation. Increasingly, researchers have demonstrated that various cortico-cortical evoked potential (CCEP) features, including early and delayed responses, evoked high-frequency oscillations, and derived network metrics, may be useful biomarkers of tissue excitability and abnormal connectivity. Emerging evidence also highlights a potential role of CCEPs in guiding neuromodulatory therapies like responsive neurostimulation. In this review, we examine the past two decades of innovation in low-frequency stimulation as it pertains to pre-surgical evaluation. We begin with a basic overview of single-pulse electrical stimulation and CCEPs, including definitions, methodology, physiology, and traditional interpretation. We then explore the literature examining CCEPs as markers of cortical excitability, seizure onset, and network-level dysfunction. Finally, the relationship between stimulation-induced and spontaneous seizures is considered. By examining these questions, we identify both opportunities and pitfalls along the path towards integrating low-frequency stimulation into clinical practice.
Collapse
Affiliation(s)
- Samuel B. Tomlinson
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA 19104, USA
| | | | | | - Eric D. Marsh
- Division of Child Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Departments of Neurology and Pediatrics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Benjamin C. Kennedy
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA 19104, USA
- Division of Neurosurgery, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| |
Collapse
|
2
|
Johnson GW, Doss DJ, Morgan VL, Paulo DL, Cai LY, Shless JS, Negi AS, Gummadavelli A, Kang H, Reddy SB, Naftel RP, Bick SK, Williams Roberson S, Dawant BM, Wallace MT, Englot DJ. The Interictal Suppression Hypothesis in focal epilepsy: network-level supporting evidence. Brain 2023; 146:2828-2845. [PMID: 36722219 PMCID: PMC10316780 DOI: 10.1093/brain/awad016] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 12/24/2022] [Accepted: 01/08/2023] [Indexed: 02/02/2023] Open
Abstract
Why are people with focal epilepsy not continuously having seizures? Previous neuronal signalling work has implicated gamma-aminobutyric acid balance as integral to seizure generation and termination, but is a high-level distributed brain network involved in suppressing seizures? Recent intracranial electrographic evidence has suggested that seizure-onset zones have increased inward connectivity that could be associated with interictal suppression of seizure activity. Accordingly, we hypothesize that seizure-onset zones are actively suppressed by the rest of the brain network during interictal states. Full testing of this hypothesis would require collaboration across multiple domains of neuroscience. We focused on partially testing this hypothesis at the electrographic network level within 81 individuals with drug-resistant focal epilepsy undergoing presurgical evaluation. We used intracranial electrographic resting-state and neurostimulation recordings to evaluate the network connectivity of seizure onset, early propagation and non-involved zones. We then used diffusion imaging to acquire estimates of white-matter connectivity to evaluate structure-function coupling effects on connectivity findings. Finally, we generated a resting-state classification model to assist clinicians in detecting seizure-onset and propagation zones without the need for multiple ictal recordings. Our findings indicate that seizure onset and early propagation zones demonstrate markedly increased inwards connectivity and decreased outwards connectivity using both resting-state (one-way ANOVA, P-value = 3.13 × 10-13) and neurostimulation analyses to evaluate evoked responses (one-way ANOVA, P-value = 2.5 × 10-3). When controlling for the distance between regions, the difference between inwards and outwards connectivity remained stable up to 80 mm between brain connections (two-way repeated measures ANOVA, group effect P-value of 2.6 × 10-12). Structure-function coupling analyses revealed that seizure-onset zones exhibit abnormally enhanced coupling (hypercoupling) of surrounding regions compared to presumably healthy tissue (two-way repeated measures ANOVA, interaction effect P-value of 9.76 × 10-21). Using these observations, our support vector classification models achieved a maximum held-out testing set accuracy of 92.0 ± 2.2% to classify early propagation and seizure-onset zones. These results suggest that seizure-onset zones are actively segregated and suppressed by a widespread brain network. Furthermore, this electrographically observed functional suppression is disproportionate to any observed structural connectivity alterations of the seizure-onset zones. These findings have implications for the identification of seizure-onset zones using only brief electrographic recordings to reduce patient morbidity and augment the presurgical evaluation of drug-resistant epilepsy. Further testing of the interictal suppression hypothesis can provide insight into potential new resective, ablative and neuromodulation approaches to improve surgical success rates in those suffering from drug-resistant focal epilepsy.
Collapse
Affiliation(s)
- Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
| | - Derek J Doss
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Danika L Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Leon Y Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
| | - Jared S Shless
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Aarushi S Negi
- Department of Neuroscience, Vanderbilt University, Nashville, TN 37232, USA
| | - Abhijeet Gummadavelli
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA
| | - Shilpa B Reddy
- Department of Pediatrics, Vanderbilt Children’s Hospital, Nashville, TN 37232, USA
| | - Robert P Naftel
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Sarah K Bick
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | | | - Benoit M Dawant
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
| | - Mark T Wallace
- Department of Hearing and Speech Sciences, Vanderbilt University, Nashville, TN 37232, USA
- Department of Psychology, Vanderbilt University, Nashville, TN 37232, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
| |
Collapse
|
3
|
Mo J, Zhang J, Hu W, Shao X, Sang L, Zheng Z, Zhang C, Wang Y, Wang X, Liu C, Zhao B, Zhang K. Neuroimaging gradient alterations and epileptogenic prediction in focal cortical dysplasia Ⅲa. J Neural Eng 2022; 19. [PMID: 35405671 DOI: 10.1088/1741-2552/ac6628] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 04/10/2022] [Indexed: 11/12/2022]
Abstract
INTRODUCTION Focal cortical dysplasia Type Ⅲa (FCD Ⅲa) is a highly prevalent temporal lobe epilepsy but the seizure outcomes are not satisfactory after epilepsy surgery. Hence, quantitative neuroimaging, epileptogenic alterations, as well as their values in guiding surgery are worth exploring. METHODS We examined 69 patients with pathologically verified FCD Ⅲa using multimodal neuroimaging and stereoelectroencephalography (SEEG). Among them, 18 received postoperative imaging which showed the extent of surgical resection and 9 underwent SEEG implantation. We also explored neuroimaging gradient alterations along with the distance to the temporal pole. Subsequently, the machine learning regression model was employed to predict whole-brain epileptogenicity. Lastly, the correlation between neuroimaging or epileptogenicity and surgical cavities was assessed. RESULTS FCD Ⅲa displayed neuroimaging gradient alterations on the temporal neocortex, morphology-signal intensity decoupling, low similarity of intra-morphological features and high similarity of intra-signal intensity features. The support vector regression model was successfully applied at the whole-brain level to calculate the continuous epileptogenic value at each vertex (mean-squared error = 13.8 ± 9.8). CONCLUSION Our study investigated the neuroimaging gradient alterations and epileptogenicity of FCD Ⅲa, along with their potential values in guiding suitable resection range and in predicting postoperative seizure outcomes. The conclusions from this study may facilitate an accurate presurgical examination of FCD Ⅲa. However, further investigation including a larger cohort is necessary to confirm the results.
Collapse
Affiliation(s)
- Jiajie Mo
- Beijing Tiantan Hospital, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, CHINA
| | - Jianguo Zhang
- Beijing Tiantan Hospital, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, CHINA
| | - Wenhan Hu
- Beijing Tiantan Hospital, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, CHINA
| | - Xiaoqiu Shao
- Beijing Tiantan Hospital, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, CHINA
| | - Lin Sang
- Peking University First Hospital Fengtai Hospital, No. 99 South 4th Fengtai Road, Fengtai District, Beijing, 100070, CHINA
| | - Zhong Zheng
- Peking University First Hospital Fengtai Hospital, No. 99 South 4th Fengtai Road, Fengtai District, Beijing, 100070, CHINA
| | - Chao Zhang
- Beijing Tiantan Hospital, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, CHINA
| | - Yao Wang
- Beijing Tiantan Hospital, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, CHINA
| | - Xiu Wang
- Beijing Tiantan Hospital, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, CHINA
| | - Chang Liu
- Beijing Tiantan Hospital, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, CHINA
| | - Baotian Zhao
- Beijing Tiantan Hospital, , Beijing, 100070, CHINA
| | - Kai Zhang
- Beijing Tiantan Hospital, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, CHINA
| |
Collapse
|
5
|
Garcia-Cairasco N, Podolsky-Gondim G, Tejada J. Searching for a paradigm shift in the research on the epilepsies and associated neuropsychiatric comorbidities. From ancient historical knowledge to the challenge of contemporary systems complexity and emergent functions. Epilepsy Behav 2021; 121:107930. [PMID: 33836959 DOI: 10.1016/j.yebeh.2021.107930] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 03/06/2021] [Indexed: 10/21/2022]
Abstract
In this review, we will discuss in four scenarios our challenges to offer possible solutions for the puzzle associated with the epilepsies and neuropsychiatric comorbidities. We need to recognize that (1) since quite old times, human wisdom was linked to the plural (distinct global places/cultures) perception of the Universe we are in, with deep respect for earth and nature. Plural ancestral knowledge was added with the scientific methods; however, their joint efforts are the ideal scenario; (2) human behavior is not different than animal behavior, in essence the product of Darwinian natural selection; knowledge of animal and human behavior are complementary; (3) the expression of human behavior follows the same rules that complex systems with emergent properties, therefore, we can measure events in human, clinical, neurobiological situations with complexity systems' tools; (4) we can use the semiology of epilepsies and comorbidities, their neural substrates, and potential treatments (including experimental/computational modeling, neurosurgical interventions), as a source and collection of integrated big data to predict with them (e.g.: machine/deep learning) diagnosis/prognosis, individualized solutions (precision medicine), basic underlying mechanisms and molecular targets. Once the group of symptoms/signals (with a myriad of changing definitions and interpretations over time) and their specific sequences are determined, in epileptology research and clinical settings, the use of modern and contemporary techniques such as neuroanatomical maps, surface electroencephalogram and stereoelectroencephalography (SEEG) and imaging (MRI, BOLD, DTI, SPECT/PET), neuropsychological testing, among others, are auxiliary in the determination of the best electroclinical hypothesis, and help design a specific treatment, usually as the first attempt, with available pharmacological resources. On top of ancient knowledge, currently known and potentially new antiepileptic drugs, alternative treatments and mechanisms are usually produced as a consequence of the hard, multidisciplinary, and integrated studies of clinicians, surgeons, and basic scientists, all over the world. The existence of pharmacoresistant patients, calls for search of other solutions, being along the decades the surgeries the most common interventions, such as resective procedures (i.e., selective or standard lobectomy, lesionectomy), callosotomy, hemispherectomy and hemispherotomy, added by vagus nerve stimulation (VNS), deep brain stimulation (DBS), neuromodulation, and more recently focal minimal or noninvasive ablation. What is critical when we consider the pharmacoresistance aspect with the potential solution through surgery, is still the pursuit of localization-dependent regions (e.g.: epileptogenic zone (EZ)), in order to decide, no matter how sophisticated are the brain mapping tools (EEG and MRI), the size and location of the tissue to be removed. Mimicking the semiology and studying potential neural mechanisms and molecular targets - by means of experimental and computational modeling - are fundamental steps of the whole process. Concluding, with the conjunction of ancient knowledge, coupled to critical and creative contemporary, scientific (not dogmatic) clinical/surgical, and experimental/computational contributions, a better world and of improved quality of life can be offered to the people with epilepsy and neuropsychiatric comorbidities, who are still waiting (as well as the scientists) for a paradigm shift in epileptology, both in the Basic Science, Computational, Clinical, and Neurosurgical Arenas. This article is part of the Special Issue "NEWroscience 2018".
Collapse
Affiliation(s)
- Norberto Garcia-Cairasco
- Laboratório de Neurofisiologia e Neuroetologia Experimental, Departmento de Fisiologia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto. Brazil; Departamento de Neurociências e Ciências do Comportamento, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil.
| | - Guilherme Podolsky-Gondim
- Departamento de Neurociências e Ciências do Comportamento, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil.
| | - Julian Tejada
- Departamento de Psicologia, Universidade Federal de Sergipe, Brazil.
| |
Collapse
|