1
|
Lastilla M, Carbone F. Commentary on "Cortical stimulation depth of nTMS investigated in a cohort of convexity meningiomas above the primary motor cortex". J Neurosci Methods 2024; 409:110208. [PMID: 38914375 DOI: 10.1016/j.jneumeth.2024.110208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2024] [Revised: 06/14/2024] [Accepted: 06/21/2024] [Indexed: 06/26/2024]
Affiliation(s)
- Michele Lastilla
- Division of Neurosurgery, Policlinico Riuniti Foggia, University of Catania, Italy.
| | - Francesco Carbone
- Department of Neurosurgery, Städtisches Klinikum Karlsruhe - Karlsruher Neurozentrum, Karlsruhe 76133, Germany; Division of Neurosurgery, Policlinico Riuniti Foggia - University of Foggia, Foggia 71122, Italy
| |
Collapse
|
2
|
Coletta L, Avesani P, Zigiotto L, Venturini M, Annicchiarico L, Vavassori L, Ng S, Duffau H, Sarubbo S. Integrating direct electrical brain stimulation with the human connectome. Brain 2024; 147:1100-1111. [PMID: 38048613 PMCID: PMC10907080 DOI: 10.1093/brain/awad402] [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] [Received: 06/27/2023] [Revised: 10/20/2023] [Accepted: 11/18/2023] [Indexed: 12/06/2023] Open
Abstract
Neurological and neurodevelopmental conditions are a major public health concern for which new therapies are urgently needed. The development of effective therapies relies on the precise mapping of the neural substrates causally involved in behaviour generation. Direct electrical stimulation (DES) performed during cognitive and neurological monitoring in awake surgery is currently considered the gold standard for the causal mapping of brain functions. However, DES is limited by the focal nature of the stimulation sites, hampering a real holistic exploration of human brain functions at the network level. We used 4137 DES points derived from 612 glioma patients in combination with human connectome data-resting-state functional MRI, n = 1000 and diffusion weighted imaging, n = 284-to provide a multimodal description of the causal macroscale functional networks subtending 12 distinct behavioural domains. To probe the validity of our procedure, we (i) compared the network topographies of healthy and clinical populations; (ii) tested the predictive capacity of DES-derived networks; (iii) quantified the coupling between structural and functional connectivity; and (iv) built a multivariate model able to quantify single subject deviations from a normative population. Lastly, we probed the translational potential of DES-derived functional networks by testing their specificity and sensitivity in identifying critical neuromodulation targets and neural substrates associated with postoperative language deficits. The combination of DES and human connectome data resulted in an average 29.4-fold increase in whole brain coverage compared to DES alone. DES-derived functional networks are predictive of future stimulation points (97.8% accuracy) and strongly supported by the anatomical connectivity of subcortical stimulations. We did not observe any significant topographical differences between the patients and the healthy population at both group and single subject level. Showcasing concrete clinical applications, we found that DES-derived functional networks overlap with effective neuromodulation targets across several functional domains, show a high degree of specificity when tested with the intracranial stimulation points of a different stimulation technique and can be used effectively to characterize postoperative behavioural deficits. The integration of DES with the human connectome fundamentally advances the quality of the functional mapping provided by DES or functional imaging alone. DES-derived functional networks can reliably predict future stimulation points, have a strong correspondence with the underlying white matter and can be used for patient specific functional mapping. Possible applications range from psychiatry and neurology to neuropsychology, neurosurgery and neurorehabilitation.
Collapse
Affiliation(s)
- Ludovico Coletta
- Neuroinformatics Laboratory (NiLab), Bruno Kessler Foundation (FBK), Trento 38123, Italy
- Center for Mind/Brain Sciences – CIMeC, University of Trento, Rovereto 38068, Italy
| | - Paolo Avesani
- Neuroinformatics Laboratory (NiLab), Bruno Kessler Foundation (FBK), Trento 38123, Italy
- Center for Mind/Brain Sciences – CIMeC, University of Trento, Rovereto 38068, Italy
| | - Luca Zigiotto
- Department of Neurosurgery, S. Chiara Hospital, Trento 38122, Italy
- Structural and Functional Connectivity Lab Project, S. Chiara Hospital, Trento 38122, Italy
- Department of Psychology, S. Chiara Hospital, Trento 38122, Italy
| | - Martina Venturini
- Department of Biotechnology and Life Sciences, Division of Neurosurgery, University of Insubria, Ospedale di Circolo e Fondazione Macchi, Varese 21100, Italy
| | - Luciano Annicchiarico
- Department of Neurosurgery, S. Chiara Hospital, Trento 38122, Italy
- Structural and Functional Connectivity Lab Project, S. Chiara Hospital, Trento 38122, Italy
| | - Laura Vavassori
- Center for Mind/Brain Sciences – CIMeC, University of Trento, Rovereto 38068, Italy
- Department of Neurosurgery, S. Chiara Hospital, Trento 38122, Italy
- Structural and Functional Connectivity Lab Project, S. Chiara Hospital, Trento 38122, Italy
| | - Sam Ng
- Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier 34094, France
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier 34295, France
| | - Hugues Duffau
- Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier 34094, France
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier 34295, France
| | - Silvio Sarubbo
- Department of Neurosurgery, S. Chiara Hospital, Trento 38122, Italy
- Structural and Functional Connectivity Lab Project, S. Chiara Hospital, Trento 38122, Italy
| |
Collapse
|
3
|
Bao Z, Zhang T, Pan T, Zhang W, Zhao S, Liu H, Nie B. Automatic method for individual parcellation of manganese-enhanced magnetic resonance imaging of rat brain. Front Neurosci 2022; 16:954237. [PMID: 35968388 PMCID: PMC9365988 DOI: 10.3389/fnins.2022.954237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 07/05/2022] [Indexed: 11/25/2022] Open
Abstract
Aims To construct an automatic method for individual parcellation of manganese-enhanced magnetic resonance imaging (MEMRI) of rat brain with high accuracy, which could preserve the inherent voxel intensity and Regions of interest (ROI) morphological characteristics simultaneously. Methods and results The transformation relationship from standardized space to individual space was obtained by firstly normalizing individual image to the Paxinos space and then inversely transformed. On the other hand, all the regions defined in the atlas image were separated and resaved as binary mask images. Then, transforming the mask images into individual space via the inverse transformations and reslicing using the 4th B-spline interpolation algorithm. The boundary of these transformed regions was further refined by image erosion and expansion operator, and finally combined together to generate the individual parcellations. Moreover, two groups of MEMRI images were used for evaluation. We found that the individual parcellations were satisfied, and the inherent image intensity was preserved. The statistical significance of case-control comparisons was further optimized. Conclusions We have constructed a new automatic method for individual parcellation of rat brain MEMRI images, which could preserve the inherent voxel intensity and further be beneficial in case-control statistical analyses. This method could also be extended to other imaging modalities, even other experiments species. It would facilitate the accuracy and significance of ROI-based imaging analyses.
Collapse
Affiliation(s)
- Zhiguo Bao
- First Affiliated Hospital of Henan University, Kaifeng, China
| | - Tianhao Zhang
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
- School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Tingting Pan
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
- Physical Science and Technology College, Zhengzhou University, Zhengzhou, China
| | - Wei Zhang
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
- School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Shilun Zhao
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
- School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Hua Liu
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
- School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Binbin Nie
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
- School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
- *Correspondence: Binbin Nie
| |
Collapse
|
4
|
Lioumis P, Rosanova M. The role of neuronavigation in TMS-EEG studies: current applications and future perspectives. J Neurosci Methods 2022; 380:109677. [PMID: 35872153 DOI: 10.1016/j.jneumeth.2022.109677] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 07/12/2022] [Accepted: 07/19/2022] [Indexed: 11/28/2022]
Abstract
Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) allows measuring non-invasively the electrical response of the human cerebral cortex to a direct perturbation. Complementing TMS-EEG with a structural neuronavigation tool (nTMS-EEG) is key for accurately selecting cortical areas, targeting them, and adjusting the stimulation parameters based on some relevant anatomical priors. This step, together with the employment of visualization tools designed to perform a quality check of TMS-evoked potentials (TEPs) in real-time during acquisition, is key for maximizing the impact of the TMS pulse on the cortex and in ensuring highly reproducible measurements within sessions and across subjects. Moreover, storing stimulation parameters in the neuronavigation system can help in reproducing the stimulation parameters within and across experimental sessions and sharing them across research centers. Finally, the systematic employment of neuronavigation in TMS-EEG studies is also key to standardize measurements in clinical populations in search for reliable diagnostic and prognostic TMS-EEG-based biomarkers for neurological and psychiatric disorders.
Collapse
Affiliation(s)
- Pantelis Lioumis
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Diagnostic Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, Italy
| |
Collapse
|
5
|
Bridging the gap: TMS-EEG from Lab to Clinic. J Neurosci Methods 2022; 369:109482. [PMID: 35041855 DOI: 10.1016/j.jneumeth.2022.109482] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 01/09/2022] [Accepted: 01/13/2022] [Indexed: 01/06/2023]
Abstract
The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has reached technological maturity and has been an object of significant scientific interest for over two decades. Ιn parallel, accumulating evidence highlights the potential of TMS-EEG as a useful tool in the field of clinical neurosciences. Nevertheless, its clinical utility has not yet been established, partly because technical and methodological limitations have created a gap between an evolving scientific tool and standard clinical practice. Here we review some of the identified gaps that still prevent TMS-EEG moving from science laboratories to clinical practice. The principal and partly overlapping gaps include: 1) complex and laborious application, 2) difficulty in obtaining high-quality signals, 3) suboptimal accuracy and reliability, and 4) insufficient understanding of the neurobiological substrate of the responses. All these four aspects need to be satisfactorily addressed for the method to become clinically applicable and enter the diagnostic and therapeutic arena. In the current review, we identify steps that might be taken to address these issues and discuss promising recent studies providing tools to aid bridging the gaps.
Collapse
|