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Pan LLH, Chen SP, Ling YH, Wang YF, Lai KL, Liu HY, Chen WT, Huang WJ, Coppola G, Treede RD, Wang SJ. Salivary Testosterone Levels and Pain Perception Exhibit Sex-Specific Association in Healthy Adults But Not in Patients With Migraine. THE JOURNAL OF PAIN 2024; 25:104575. [PMID: 38788888 DOI: 10.1016/j.jpain.2024.104575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 04/30/2024] [Accepted: 05/16/2024] [Indexed: 05/26/2024]
Abstract
This study investigated the sex-specific associations between pain perception and testosterone levels in healthy controls (HCs) and patients with migraine. Male and female HCs and migraine patients were recruited. A series of questionnaires were completed by the participants to evaluate their psychosocial profiles, which included data on mood, stress, and sleep quality. Heat pain thresholds and suprathreshold pain ratings at 45 °C (referred to as the pain perception score [PPS]) were assessed using the Thermode system. Salivary testosterone levels were analyzed using a commercial enzyme-linked immunosorbent assay kit. A total of 88 HCs (men/women: 41/47, age: 29.9 ± 7.7 years) and 75 migraine patients (men/women: 30/45, age: 31.1 ± 7.7 years) completed all assessments. No significant differences were observed in either the psychosocial profiles or heat pain thresholds and PPSs between the sexes in the control and migraine groups. A positive correlation between testosterone levels and PPSs was identified in the male controls (r = .341, P = .029), whereas a negative correlation was identified in the female controls (r = -.407, P = .005). No such correlations were identified in the migraine group. This study confirms that a negative association is present between PPSs and testosterone levels in female controls, which is in line with the findings that testosterone is associated with reduced pain perception. Our study is the first to demonstrate a sex-specific association between PPSs and testosterone levels in HCs. Moreover, this study also revealed that the presence of migraine appears to disrupt this association. PERSPECTIVE: This study revealed that testosterone levels demonstrate opposite associations with pain perception in healthy men and women. However, the presence of migraine appears to disrupt this sex-specific association.
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Affiliation(s)
- Li-Ling Hope Pan
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan.
| | - Shih-Pin Chen
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan; College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yu-Hsiang Ling
- College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yen-Feng Wang
- College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Kuan-Lin Lai
- College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Hung-Yu Liu
- College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Wei-Ta Chen
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan; College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; Department of Neurology, Keelung Hospital, Ministry of Health and Welfare, Keelung, Taiwan
| | - William J Huang
- College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Urology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Gianluca Coppola
- Department of Medico‑Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino, Latina, Italy
| | - Rolf-Detlef Treede
- Mannheim Center for Translational Neurosciences, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Shuu-Jiun Wang
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan; College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
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Porcaro C, Diciotti S, Madan CR, Marzi C. Editorial: Methods and application in fractal analysis of neuroimaging data. Front Hum Neurosci 2024; 18:1453284. [PMID: 39050380 PMCID: PMC11266171 DOI: 10.3389/fnhum.2024.1453284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2024] [Accepted: 06/26/2024] [Indexed: 07/27/2024] Open
Affiliation(s)
- Camillo Porcaro
- Department of Neuroscience and Padova Neuroscience Center, University of Padua, Padua, Italy
- Institute of Cognitive Sciences and Technologies—National Research Council, Rome, Italy
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, United Kingdom
| | - Stefano Diciotti
- Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi” – DEI, University of Bologna, Cesena, Italy
- Alma Mater Research Institute for Human-Centered Artificial Intelligence, University of Bologna, Bologna, Italy
| | | | - Chiara Marzi
- Department of Statistics, Computer Science and Applications “Giuseppe Parenti,” University of Florence, Florence, Italy
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Porcaro C, Seppi D, Pellegrino G, Dainese F, Kassabian B, Pellegrino L, De Nardi G, Grego A, Corbetta M, Ferreri F. Characterization of antiseizure medications effects on the EEG neurodynamic by fractal dimension. Front Neurosci 2024; 18:1401068. [PMID: 38911599 PMCID: PMC11192015 DOI: 10.3389/fnins.2024.1401068] [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: 03/14/2024] [Accepted: 05/20/2024] [Indexed: 06/25/2024] Open
Abstract
Objectives An important challenge in epilepsy is to define biomarkers of response to treatment. Many electroencephalography (EEG) methods and indices have been developed mainly using linear methods, e.g., spectral power and individual alpha frequency peak (IAF). However, brain activity is complex and non-linear, hence there is a need to explore EEG neurodynamics using nonlinear approaches. Here, we use the Fractal Dimension (FD), a measure of whole brain signal complexity, to measure the response to anti-seizure therapy in patients with Focal Epilepsy (FE) and compare it with linear methods. Materials Twenty-five drug-responder (DR) patients with focal epilepsy were studied before (t1, named DR-t1) and after (t2, named DR-t2) the introduction of the anti-seizure medications (ASMs). DR-t1 and DR-t2 EEG results were compared against 40 age-matched healthy controls (HC). Methods EEG data were investigated from two different angles: frequency domain-spectral properties in δ, θ, α, β, and γ bands and the IAF peak, and time-domain-FD as a signature of the nonlinear complexity of the EEG signals. Those features were compared among the three groups. Results The δ power differed between DR patients pre and post-ASM and HC (DR-t1 vs. HC, p < 0.01 and DR-t2 vs. HC, p < 0.01). The θ power differed between DR-t1 and DR-t2 (p = 0.015) and between DR-t1 and HC (p = 0.01). The α power, similar to the δ, differed between DR patients pre and post-ASM and HC (DR-t1 vs. HC, p < 0.01 and DR-t2 vs. HC, p < 0.01). The IAF value was lower for DR-t1 than DR-t2 (p = 0.048) and HC (p = 0.042). The FD value was lower in DR-t1 than in DR-t2 (p = 0.015) and HC (p = 0.011). Finally, Bayes Factor analysis showed that FD was 195 times more likely to separate DR-t1 from DR-t2 than IAF and 231 times than θ. Discussion FD measured in baseline EEG signals is a non-linear brain measure of complexity more sensitive than EEG power or IAF in detecting a response to ASMs. This likely reflects the non-oscillatory nature of neural activity, which FD better describes. Conclusion Our work suggests that FD is a promising measure to monitor the response to ASMs in FE.
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Affiliation(s)
- Camillo Porcaro
- Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy
- Institute of Cognitive Sciences and Technologies (ISTC) – National Research Council (CNR), Rome, Italy
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, United Kingdom
| | - Dario Seppi
- Neurology Clinics, Azienda Ospedale Università, Padua, Italy
- Unit of Clinical Neurophysiology, Azienda Ospedale Università, Padua, Italy
| | - Giovanni Pellegrino
- Epilepsy Program, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Filippo Dainese
- Neurology Clinics, Azienda Ospedale Università, Padua, Italy
- Unit of Clinical Neurophysiology, Azienda Ospedale Università, Padua, Italy
| | - Benedetta Kassabian
- Neurology Clinics, Azienda Ospedale Università, Padua, Italy
- Unit of Clinical Neurophysiology, Azienda Ospedale Università, Padua, Italy
| | - Luciano Pellegrino
- Neurology Clinics, Azienda Ospedale Università, Padua, Italy
- Unit of Clinical Neurophysiology, Azienda Ospedale Università, Padua, Italy
| | - Gianluigi De Nardi
- Neurology Clinics, Azienda Ospedale Università, Padua, Italy
- Unit of Clinical Neurophysiology, Azienda Ospedale Università, Padua, Italy
| | - Alberto Grego
- Neurology Clinics, Azienda Ospedale Università, Padua, Italy
- Unit of Clinical Neurophysiology, Azienda Ospedale Università, Padua, Italy
| | - Maurizio Corbetta
- Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy
- Neurology Clinics, Azienda Ospedale Università, Padua, Italy
- Veneto Institute of Molecular Medicine (VIMM), Fondazione Biomedica, Padua, Italy
| | - Florinda Ferreri
- Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy
- Neurology Clinics, Azienda Ospedale Università, Padua, Italy
- Unit of Clinical Neurophysiology, Azienda Ospedale Università, Padua, Italy
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Fiorenzato E, Moaveninejad S, Weis L, Biundo R, Antonini A, Porcaro C. Brain Dynamics Complexity as a Signature of Cognitive Decline in Parkinson's Disease. Mov Disord 2024; 39:305-317. [PMID: 38054573 DOI: 10.1002/mds.29678] [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: 07/26/2023] [Revised: 11/13/2023] [Accepted: 11/17/2023] [Indexed: 12/07/2023] Open
Abstract
BACKGROUND Higuchi's fractal dimension (FD) captures brain dynamics complexity and may be a promising method to analyze resting-state functional magnetic resonance imaging (fMRI) data and detect the neuronal interaction complexity underlying Parkinson's disease (PD) cognitive decline. OBJECTIVES The aim was to compare FD with a more established index of spontaneous neural activity, the fractional amplitude of low-frequency fluctuations (fALFF), and identify through machine learning (ML) models which method could best distinguish across PD-cognitive states, ranging from normal cognition (PD-NC), mild cognitive impairment (PD-MCI) to dementia (PDD). Finally, the aim was to explore correlations between fALFF and FD with clinical and cognitive PD features. METHODS Among 118 PD patients age-, sex-, and education matched with 35 healthy controls, 52 were classified with PD-NC, 46 with PD-MCI, and 20 with PDD based on an extensive cognitive and clinical evaluation. fALFF and FD metrics were computed on rs-fMRI data and used to train ML models. RESULTS FD outperformed fALFF metrics in differentiating between PD-cognitive states, reaching an overall accuracy of 78% (vs. 62%). PD showed increased neuronal dynamics complexity within the sensorimotor network, central executive network (CEN), and default mode network (DMN), paralleled by a reduction in spontaneous neuronal activity within the CEN and DMN, whose increased complexity was strongly linked to the presence of dementia. Further, we found that some DMN critical hubs correlated with worse cognitive performance and disease severity. CONCLUSIONS Our study indicates that PD-cognitive decline is characterized by an altered spontaneous neuronal activity and increased temporal complexity, involving the CEN and DMN, possibly reflecting an increased segregation of these networks. Therefore, we propose FD as a prognostic biomarker of PD-cognitive decline. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Eleonora Fiorenzato
- Parkinson's Disease and Movement Disorders Unit, Department of Neuroscience, Centre for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
| | - Sadaf Moaveninejad
- Department of Neuroscience and Padova Neuroscience Center, University of Padua, Padua, Italy
| | - Luca Weis
- Parkinson's Disease and Movement Disorders Unit, Department of Neuroscience, Centre for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
- IRCCS, San Camillo Hospital, Venice, Italy
| | - Roberta Biundo
- Parkinson's Disease and Movement Disorders Unit, Department of Neuroscience, Centre for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
- Department of Neuroscience, Center for Neurodegenerative Disease Research (CESNE), University of Padova, Padova, Italy
- Department of General Psychology, University of Padua, Padua, Italy
| | - Angelo Antonini
- Parkinson's Disease and Movement Disorders Unit, Department of Neuroscience, Centre for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
- Department of Neuroscience and Padova Neuroscience Center, University of Padua, Padua, Italy
- Department of Neuroscience, Center for Neurodegenerative Disease Research (CESNE), University of Padova, Padova, Italy
| | - Camillo Porcaro
- Department of Neuroscience and Padova Neuroscience Center, University of Padua, Padua, Italy
- Institute of Cognitive Sciences and Technologies-National Research Council, Rome, Italy
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, United Kingdom
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Porcaro C, Moaveninejad S, D'Onofrio V, DiIeva A. Fractal Time Series: Background, Estimation Methods, and Performances. ADVANCES IN NEUROBIOLOGY 2024; 36:95-137. [PMID: 38468029 DOI: 10.1007/978-3-031-47606-8_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Over the past 40 years, from its classical application in the characterization of geometrical objects, fractal analysis has been progressively applied to study time series in several different disciplines. In neuroscience, starting from identifying the fractal properties of neuronal and brain architecture, attention has shifted to evaluating brain signals in the time domain. Classical linear methods applied to analyzing neurophysiological signals can lead to classifying irregular components as noise, with a potential loss of information. Thus, characterizing fractal properties, namely, self-similarity, scale invariance, and fractal dimension (FD), can provide relevant information on these signals in physiological and pathological conditions. Several methods have been proposed to estimate the fractal properties of these neurophysiological signals. However, the effects of signal characteristics (e.g., its stationarity) and other signal parameters, such as sampling frequency, amplitude, and noise level, have partially been tested. In this chapter, we first outline the main properties of fractals in the domain of space (fractal geometry) and time (fractal time series). Then, after providing an overview of the available methods to estimate the FD, we test them on synthetic time series (STS) with different sampling frequencies, signal amplitudes, and noise levels. Finally, we describe and discuss the performances of each method and the effect of signal parameters on the accuracy of FD estimation.
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Affiliation(s)
- Camillo Porcaro
- Department of Neuroscience (DNS) and Padova Neuroscience Center (PNC), University of Padova, Padua, Italy.
- Institute of Cognitive Sciences and Technologies (ISTC) National Research Council (CNR), Rome, Italy.
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK.
| | | | | | - Antonio DiIeva
- Computational NeuroSurgery (CNS) Lab & Macquarie Neurosurgery, Macquarie Medical School, Faculty of Medicine, Human and Health Sciences, Macquarie University, Sydney, NSW, Australia
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Messina R, Rocca MA, Goadsby PJ, Filippi M. Insights into migraine attacks from neuroimaging. Lancet Neurol 2023; 22:834-846. [PMID: 37478888 DOI: 10.1016/s1474-4422(23)00152-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 03/15/2023] [Accepted: 04/12/2023] [Indexed: 07/23/2023]
Abstract
Migraine is one of the most common neurological diseases and it has a huge social and personal impact. Although head pain is the core symptom, individuals with migraine can have a plethora of non-headache symptoms that precede, accompany, or follow the pain. Neuroimaging studies have shown that the involvement of specific brain areas can explain many of the symptoms reported during the different phases of migraine. Recruitment of the hypothalamus, pons, spinal trigeminal nucleus, thalamus, and visual and pain-processing cortical areas starts during the premonitory phase and persists through the headache phase, contributing to the onset of pain and associated symptoms. Once the pain stops, the involvement of most brain areas ends, although the pons, hypothalamus, and visual cortex remain active after acute treatment intake and resolution of migraine symptoms. A better understanding of the correlations between imaging findings and migraine symptomatology can provide new insight into migraine pathophysiology and the mechanisms of novel migraine-specific treatments.
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Affiliation(s)
- Roberta Messina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Peter J Goadsby
- NIHR King's Clinical Research Facility, King's College, London, UK; Department of Neurology, University of California, Los Angeles, CA, USA
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy; Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.
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Zhou Y, Gong L, Yang Y, Tan L, Ruan L, Chen X, Luo H, Ruan J. Spatio-temporal dynamics of resting-state brain networks are associated with migraine disability. J Headache Pain 2023; 24:13. [PMID: 36800935 PMCID: PMC9940435 DOI: 10.1186/s10194-023-01551-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 02/13/2023] [Indexed: 02/21/2023] Open
Abstract
OBJECTIVE The changes in resting-state functional networks and their correlations with clinical traits remain to be clarified in migraine. Here we aim to investigate the brain spatio-temporal dynamics of resting-state networks and their possible correlations with the clinical traits in migraine. METHODS Twenty Four migraine patients without aura and 26 healthy controls (HC) were enrolled. Each included subject underwent a resting-state EEG and echo planar imaging examination. The disability of migraine patients was evaluated by Migraine Disability Assessment (MIDAS). After data acquisition, EEG microstates (Ms) combining functional connectivity (FC) analysis based on Schafer 400-seven network atlas were performed. Then, the correlation between obtained parameters and clinical traits was investigated. RESULTS Compared with HC group, the brain temporal dynamics depicted by microstates showed significantly increased activity in functional networks involving MsB and decreased activity in functional networks involving MsD; The spatial dynamics were featured by decreased intra-network FC within the executive control network( ECN) and inter-network FC between dorsal attention network (DAN) and ECN (P < 0.05); Moreover, correlation analysis showed that the MIDAS score was positively correlated with the coverage and duration of MsC, and negatively correlated with the occurrence of MsA; The FC within default mode network (DMN), and the inter-FC of ECN- visual network (VN), ECN- limbic network, VN-limbic network was negatively correlated with MIDAS. However, the FC of DMN-ECN was positively correlated with MIDAS; Furthermore, significant interactions between the temporal and spatial dynamics were also obtained. CONCLUSIONS Our study confirmed the notion that altered spatio-temporal dynamics exist in migraine patients during resting-state. And the temporal dynamics, the spatial changes and the clinical traits such as migraine disability interact with each other. The spatio-temporal dynamics obtained from EEG microstate and fMRI FC analyses may be potential biomarkers for migraine and with a huge potential to change future clinical practice in migraine.
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Affiliation(s)
- Yan Zhou
- Department of Neurology, Jianyang People's Hospital, Jianyang, 641400, China
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, China
| | - Liusheng Gong
- Department of Neurology, Jianyang People's Hospital, Jianyang, 641400, China
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China
| | - Yushu Yang
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, China
| | - Linjie Tan
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, China
| | - Lili Ruan
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, China
| | - Xiu Chen
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, China
| | - Hua Luo
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, China
| | - Jianghai Ruan
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China.
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, China.
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Porcaro C, Di Renzo A, Tinelli E, Parisi V, Di Lorenzo C, Caramia F, Fiorelli M, Giuliani G, Cioffi E, Seri S, Di Piero V, Pierelli F, Di Lorenzo G, Coppola G. A Hypothalamic Mechanism Regulates the Duration of a Migraine Attack: Insights from Microstructural and Temporal Complexity of Cortical Functional Networks Analysis. Int J Mol Sci 2022; 23:13238. [PMID: 36362026 PMCID: PMC9658908 DOI: 10.3390/ijms232113238] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 10/21/2022] [Accepted: 10/27/2022] [Indexed: 07/23/2023] Open
Abstract
The role of the hypothalamus and the limbic system at the onset of a migraine attack has recently received significant interest. We analyzed diffusion tensor imaging (DTI) parameters of the entire hypothalamus and its subregions in 15 patients during a spontaneous migraine attack and in 20 control subjects. We also estimated the non-linear measure resting-state functional MRI BOLD signal's complexity using Higuchi fractal dimension (FD) and correlated DTI/fMRI findings with patients' clinical characteristics. In comparison with healthy controls, patients had significantly altered diffusivity metrics within the hypothalamus, mainly in posterior ROIs, and higher FD values in the salience network (SN). We observed a positive correlation of the hypothalamic axial diffusivity with migraine severity and FD of SN. DTI metrics of bilateral anterior hypothalamus positively correlated with the mean attack duration. Our results show plastic structural changes in the hypothalamus related to the attacks severity and the functional connectivity of the SN involved in the multidimensional neurocognitive processing of pain. Plastic changes to the hypothalamus may play a role in modulating the duration of the attack.
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Affiliation(s)
- Camillo Porcaro
- Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, 35128 Padova, Italy
- Institute of Cognitive Sciences and Technologies (ISTC)—National Research Council (CNR), 00185 Rome, Italy
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham B15 2TT, UK
| | | | - Emanuele Tinelli
- Unit of Neuroradiology, Department of Medical and Surgical Sciences, Magna Græcia University, 88100 Catanzaro, Italy
| | | | - Cherubino Di Lorenzo
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino—I.C.O.T., 04100 Latina, Italy
| | - Francesca Caramia
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Marco Fiorelli
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Giada Giuliani
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Ettore Cioffi
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino—I.C.O.T., 04100 Latina, Italy
| | - Stefano Seri
- Aston Institute of Health and Neurodevelopment, College of Health and Life Sciences, Aston University, Birmingham B4 7ET, UK
- Department of Clinical Neurophysiology, Birmingham Women’s and Children’s NHS Foundation Trust, Birmingham B4 6NH, UK
| | - Vittorio Di Piero
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Francesco Pierelli
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino—I.C.O.T., 04100 Latina, Italy
| | - Giorgio Di Lorenzo
- Laboratory of Psychophysiology and Cognitive Neuroscience, Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy
- IRCCS—Fondazione Santa Lucia, 00179 Rome, Italy
| | - Gianluca Coppola
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino—I.C.O.T., 04100 Latina, Italy
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The Patent Foramen Ovale and Migraine: Associated Mechanisms and Perspectives from MRI Evidence. Brain Sci 2022; 12:brainsci12070941. [PMID: 35884747 PMCID: PMC9313384 DOI: 10.3390/brainsci12070941] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/10/2022] [Accepted: 07/15/2022] [Indexed: 02/04/2023] Open
Abstract
Migraine is a common neurological disease with a still-unclear etiology and pathogenesis. Patent foramen ovale (PFO) is a kind of congenital heart disease that leads to a right-to-left shunt (RLS). Although previous studies have shown that PFO has an effect on migraine, a clear conclusion about the link between PFO and migraine is lacking. We first summarized the PFO potential mechanisms associated with migraine, including microembolus-triggered cortical spreading depression (CSD), the vasoactive substance hypothesis, impaired cerebral autoregulation (CA), and a common genetic basis. Further, we analyzed the changes in brain structure and function in migraine patients and migraine patients with PFO. We found that in migraine patients with PFO, the presence of PFO may affect the structure of the cerebral cortex and the integrity of white matter, which is mainly locked in subcortical, deep white matter, and posterior circulation, and may lead to changes in brain function, such as cerebellum and colliculus, which are involved in the processing and transmission of pain. In summary, this paper provides neuroimaging evidence and new insights into the correlation between PFO and migraine, which will help to clarify the etiology and pathogenesis of migraine, and aid in the diagnosis and treatment of migraine in the future.
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Noseda R. Cerebro-Cerebellar Networks in Migraine Symptoms and Headache. FRONTIERS IN PAIN RESEARCH 2022; 3:940923. [PMID: 35910262 PMCID: PMC9326053 DOI: 10.3389/fpain.2022.940923] [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: 05/10/2022] [Accepted: 06/13/2022] [Indexed: 11/13/2022] Open
Abstract
The cerebellum is associated with the biology of migraine in a variety of ways. Clinically, symptoms such as fatigue, motor weakness, vertigo, dizziness, difficulty concentrating and finding words, nausea, and visual disturbances are common in different types of migraine. The neural basis of these symptoms is complex, not completely known, and likely involve activation of both specific and shared circuits throughout the brain. Posterior circulation stroke, or neurosurgical removal of posterior fossa tumors, as well as anatomical tract tracing in animals, provided the first insights to theorize about cerebellar functions. Nowadays, with the addition of functional imaging, much progress has been done on cerebellar structure and function in health and disease, and, as a consequence, the theories refined. Accordingly, the cerebellum may be useful but not necessary for the execution of motor, sensory or cognitive tasks, but, rather, would participate as an efficiency facilitator of neurologic functions by improving speed and skill in performance of tasks produced by the cerebral area to which it is reciprocally connected. At the subcortical level, critical regions in these processes are the basal ganglia and thalamic nuclei. Altogether, a modulatory role of the cerebellum over multiple brain regions appears compelling, mainly by considering the complexity of its reciprocal connections to common neural networks involved in motor, vestibular, cognitive, affective, sensory, and autonomic processing—all functions affected at different phases and degrees across the migraine spectrum. Despite the many associations between cerebellum and migraine, it is not known whether this structure contributes to migraine initiation, symptoms generation or headache. Specific cerebellar dysfunction via genetically driven excitatory/inhibitory imbalances, oligemia and/or increased risk to white matter lesions has been proposed as a critical contributor to migraine pathogenesis. Therefore, given that neural projections and functions of many brainstem, midbrain and forebrain areas are shared between the cerebellum and migraine trigeminovascular pathways, this review will provide a synopsis on cerebellar structure and function, its role in trigeminal pain, and an updated overview of relevant clinical and preclinical literature on the potential role of cerebellar networks in migraine pathophysiology.
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Affiliation(s)
- Rodrigo Noseda
- Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
- *Correspondence: Rodrigo Noseda
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Suzuki K. Microstructural changes in the basal ganglia in restless legs syndrome and migraine. Sleep Biol Rhythms 2022; 20:323-324. [PMID: 38469418 PMCID: PMC10899921 DOI: 10.1007/s41105-022-00393-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Keisuke Suzuki
- Department of Neurology, Dokkyo Medical University, 880 KitakobayashiShimotsuga, Mibu, Tochigi 321-0293 Japan
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Borri A, Cerasa A, Tonin P, Citrigno L, Porcaro C. Characterizing Fractal Genetic Variation in the Human Genome from the Hapmap Project. Int J Neural Syst 2022; 32:2250028. [PMID: 35579974 DOI: 10.1142/s0129065722500289] [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] [Indexed: 11/18/2022]
Abstract
Over the last decades, the exuberant development of next-generation sequencing has revolutionized gene discovery. These technologies have boosted the mapping of single nucleotide polymorphisms (SNPs) across the human genome, providing a complex universe of heterogeneity characterizing individuals worldwide. Fractal dimension (FD) measures the degree of geometric irregularity, quantifying how "complex" a self-similar natural phenomenon is. We compared two FD algorithms, box-counting dimension (BCD) and Higuchi's fractal dimension (HFD), to characterize genome-wide patterns of SNPs extracted from the HapMap data set, which includes data from 1184 healthy subjects of eleven populations. In addition, we have used cluster and classification analysis to relate the genetic distances within chromosomes based on FD similarities to the geographical distances among the 11 global populations. We found that HFD outperformed BCD at both grand average clusterization analysis by the cophenetic correlation coefficient, in which the closest value to 1 represents the most accurate clustering solution (0.981 for the HFD and 0.956 for the BCD) and classification (79.0% accuracy, 61.7% sensitivity, and 96.4% specificity for the HFD with respect to 69.1% accuracy, 43.2% sensitivity, and 94.9% specificity for the BCD) of the 11 populations present in the HapMap data set. These results support the evidence that HFD is a reliable measure helpful in representing individual variations within all chromosomes and categorizing individuals and global populations.
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Affiliation(s)
- Alessandro Borri
- CNR-IASI Biomathematics Laboratory, (BioMatLab), Rome, Italy.,Centre of Excellence for Research DEWS, University of L'Aquila, L'Aquila, Italy
| | - Antonio Cerasa
- Institute for Biomedical Research and Innovation, National Research Council, IRIB-CNR, 98164 Messina, Italy.,S. Anna Institute, 88900 Crotone, Italy.,Pharmacotechnology Documentation and Transfer Unit, Preclinical and Translational Pharmacology, Department of Pharmacy, Health Science and Nutrition, University of Calabria, 87036 Arcavacata, Italy
| | | | - Luigi Citrigno
- Institute for Biomedical Research and Innovation, National Research Council, IRIB-CNR, 87050 Mangone CS, Italy
| | - Camillo Porcaro
- Department of Neuroscience and Padova Neuroscience, Center (PNC), University of Padova, Padova, Italy.,Institute of Cognitive Sciences and Technologies, (ISTC) - National Research Council (CNR), Rome, Italy.,Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK
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Porcaro C, Marino M, Carozzo S, Russo M, Ursino M, Valentinaruggiero, Ragno C, Proto S, Tonin P. Fractal Dimension Feature as a Signature of Severity in Disorders of Consciousness: An EEG Study. Int J Neural Syst 2022; 32:2250031. [DOI: 10.1142/s0129065722500319] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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