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Tscherpel C, Mustin M, Massimini M, Paul T, Ziemann U, Fink GR, Grefkes C. Local neuronal sleep after stroke: The role of cortical bistability in brain reorganization. Brain Stimul 2024; 17:836-846. [PMID: 39019396 DOI: 10.1016/j.brs.2024.07.008] [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: 10/07/2023] [Revised: 06/30/2024] [Accepted: 07/12/2024] [Indexed: 07/19/2024] Open
Abstract
BACKGROUND Acute cerebral ischemia triggers a number of cellular mechanisms not only leading to excitotoxic cell death but also to enhanced neuroplasticity, facilitating neuronal reorganization and functional recovery. OBJECTIVE Transferring these cellular mechanisms to neurophysiological correlates adaptable to patients is crucial to promote recovery post-stroke. The combination of TMS and EEG constitutes a promising readout of neuronal network activity in stroke patients. METHODS We used the combination of TMS and EEG to investigate the development of local signal processing and global network alterations in 40 stroke patients with motor deficits alongside neural reorganization from the acute to the chronic phase. RESULTS We show that the TMS-EEG response reflects information about reorganization and signal alterations associated with persistent motor deficits throughout the entire post-stroke period. In the early post-stroke phase and in a subgroup of patients with severe motor deficits, TMS applied to the lesioned motor cortex evoked a sleep-like slow wave response associated with a cortical off-period, a manifestation of cortical bistability, as well as a rapid disruption of the TMS-induced formation of causal network effects. Mechanistically, these phenomena were linked to lesions affecting ascending activating brainstem fibers. Of note, slow waves invariably vanished in the chronic phase, but were highly indicative of a poor functional outcome. CONCLUSION In summary, we found evidence that transient effects of sleep-like slow waves and cortical bistability within ipsilesional M1 resulting in excessive inhibition may interfere with functional reorganization, leading to a less favorable functional outcome post-stroke, pointing to a new therapeutic target to improve recovery of function.
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Affiliation(s)
- Caroline Tscherpel
- Department of Neurology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany; Medical Faculty, University of Cologne, and Department of Neurology, University Hospital Cologne, Cologne, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Jülich, Jülich, Germany
| | - Maike Mustin
- Medical Faculty, University of Cologne, and Department of Neurology, University Hospital Cologne, Cologne, Germany
| | - Marcello Massimini
- Department of Biomedical and Clinical Science 'L. Sacco', University Milan, Milan, Italy; IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Theresa Paul
- Medical Faculty, University of Cologne, and Department of Neurology, University Hospital Cologne, Cologne, Germany
| | - Ulf Ziemann
- Department of Neurology & Stroke and Hertie Institute for Clinical Brain Research, Eberhard-Karls-University Tübingen, Tübingen, Germany
| | - Gereon R Fink
- Medical Faculty, University of Cologne, and Department of Neurology, University Hospital Cologne, Cologne, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Jülich, Jülich, Germany
| | - Christian Grefkes
- Department of Neurology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany; Medical Faculty, University of Cologne, and Department of Neurology, University Hospital Cologne, Cologne, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Jülich, Jülich, Germany.
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Liuzzi P, Grippo A, Sodero A, Castagnoli C, Pellegrini I, Burali R, Toci T, Barretta T, Mannini A, Hakiki B, Macchi C, Lolli F, Cecchi F. Quantitative EEG and prognosis for recovery in post-stroke patients: The effect of lesion laterality. Neurophysiol Clin 2024; 54:102952. [PMID: 38422721 DOI: 10.1016/j.neucli.2024.102952] [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: 07/18/2023] [Revised: 01/23/2024] [Accepted: 01/24/2024] [Indexed: 03/02/2024] Open
Abstract
OBJECTIVE There is emerging confidence that quantitative EEG (qEEG) has the potential to inform clinical decision-making and guide individualized rehabilitation after stroke, but consensus on the best EEG biomarkers is needed for translation to clinical practice. This study investigates the spatial qEEG spectral and symmetry distribution in patients with a left/right hemispheric stroke, to evaluate their side-specific prognostic power in post-acute rehabilitation outcome. METHODS Resting-state 19-channel EEG recordings were collected with clinical information on admission to intensive inpatient rehabilitation (within 30 days post stroke), and six months post stroke. After preprocessing, spectral (Delta-to-Alpha Ratio, DAR) and symmetry (pairwise and hemispheric Brain Symmetry Index) features were extracted. Patients were divided into Affected Right and Left (AR/AL) groups, according to the location of their lesion. Within each group, DAR was compared between homologous electrode pairs and the pairwise difference between pairs was compared across pairs in the scalp. Then, the prognostic power of qEEG admission metrics was evaluated by performing correlations between admission metrics and discharge mBI values. RESULTS Fifty-two patients with hemorrhagic or ischemic stroke (20 females, 38.5 %, median age 76 years [IQR = 22]) were included in the study. DAR was significantly higher in the affected hemisphere for both AR and AL groups, and, a higher frontal (to posterior) asymmetry was found independent of the side of the lesion. DAR was found to be a prognostic marker of 6-months modified Barthel Index (mBI) only for the AL group, while hemispheric asymmetry did not correlate with follow-up outcomes in either group. DISCUSSION While the presence of EEG abnormalities in the affected hemisphere of a stroke is well recognized, we have shown that the extent of DAR abnormalities seen correlates with disability at 6 months post stroke, but only for left hemispheric lesions. Routine prognostic evaluation, in addition to motor and functional scales, can add information concerning neuro-prognostication and reveal neurophysiological abnormalities to be assessed during rehabilitation.
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Affiliation(s)
- Piergiuseppe Liuzzi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Di Scandicci 269, Firenze, Italy; Scuola Superiore Sant'Anna, Istituto di BioRobotica, Viale Rinaldo Piaggio 34, Pontedera, Italy.
| | - Antonello Grippo
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Di Scandicci 269, Firenze, Italy
| | - Alessandro Sodero
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Di Scandicci 269, Firenze, Italy
| | - Chiara Castagnoli
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Di Scandicci 269, Firenze, Italy
| | - Ilaria Pellegrini
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Di Scandicci 269, Firenze, Italy
| | - Rachele Burali
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Di Scandicci 269, Firenze, Italy
| | - Tanita Toci
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Di Scandicci 269, Firenze, Italy
| | - Teresa Barretta
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Di Scandicci 269, Firenze, Italy
| | - Andrea Mannini
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Di Scandicci 269, Firenze, Italy
| | - Bahia Hakiki
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Di Scandicci 269, Firenze, Italy
| | - Claudio Macchi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Di Scandicci 269, Firenze, Italy; Università di Firenze, Dipartimento di Medicina Sperimentale e Clinica, Largo Brambilla 3, Firenze, Italy
| | - Francesco Lolli
- Università degli Studi di Firenze, Dipartimento di Scienze Biomediche Sperimentali e Cliniche, Viale Morgagni 50, Firenze, Italy
| | - Francesca Cecchi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via Di Scandicci 269, Firenze, Italy; Università degli Studi di Firenze, Dipartimento di Scienze Biomediche Sperimentali e Cliniche, Viale Morgagni 50, Firenze, Italy
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Hencz AJ, Magony A, Thomas C, Kovacs K, Szilagyi G, Pal J, Sik A. Short-term hyperoxia-induced functional and morphological changes in rat hippocampus. Front Cell Neurosci 2024; 18:1376577. [PMID: 38686017 PMCID: PMC11057248 DOI: 10.3389/fncel.2024.1376577] [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: 01/25/2024] [Accepted: 03/27/2024] [Indexed: 05/02/2024] Open
Abstract
Excess oxygen (O2) levels may have a stimulating effect, but in the long term, and at high concentrations of O2, it is harmful to the nervous system. The hippocampus is very sensitive to pathophysiological changes and altered O2 concentrations can interfere with hippocampus-dependent learning and memory functions. In this study, we investigated the hyperoxia-induced changes in the rat hippocampus to evaluate the short-term effect of mild and severe hyperoxia. Wistar male rats were randomly divided into control (21% O2), mild hyperoxia (30% O2), and severe hyperoxia groups (100% O2). The O2 exposure lasted for 60 min. Multi-channel silicon probes were used to study network oscillations and firing properties of hippocampal putative inhibitory and excitatory neurons. Neural damage was assessed using the Gallyas silver impregnation method. Mild hyperoxia (30% O2) led to the formation of moderate numbers of silver-impregnated "dark" neurons in the hippocampus. On the other hand, exposure to 100% O2 was associated with a significant increase in the number of "dark" neurons located mostly in the hilus. The peak frequency of the delta oscillation decreased significantly in both mild and severe hyperoxia in urethane anesthetized rats. Compared to normoxia, the firing activity of pyramidal neurons under hyperoxia increased while it was more heterogeneous in putative interneurons in the cornu ammonis area 1 (CA1) and area 3 (CA3). These results indicate that short-term hyperoxia can change the firing properties of hippocampal neurons and network oscillations and damage neurons. Therefore, the use of elevated O2 concentration inhalation in hospitals (i.e., COVID treatment and surgery) and in various non-medical scenarios (i.e., airplane emergency O2 masks, fire-fighters, and high altitude trekkers) must be used with extreme caution.
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Affiliation(s)
| | - Andor Magony
- Institute of Physiology, Medical School, University of Pécs, Pécs, Hungary
| | - Chloe Thomas
- Institute of Clinical Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Krisztina Kovacs
- Institute of Clinical Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Gabor Szilagyi
- Institute of Biochemistry and Medical Chemistry, Medical School, University of Pécs, Pécs, Hungary
| | - Jozsef Pal
- Institute of Physiology, Medical School, University of Pécs, Pécs, Hungary
| | - Attila Sik
- Institute of Physiology, Medical School, University of Pécs, Pécs, Hungary
- Institute of Clinical Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
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Lanzone J, Zulueta A, Boscarino M, Gallotta M, Argentieri MR, Viganò A, Sarasso S, Colombo MA, D’Ambrosio S, Lunetta C, Parati E. Spectral exponent assessment and neurofilament light chain: a comprehensive approach to describe recovery patterns in stroke. Front Neurol 2024; 15:1329044. [PMID: 38562428 PMCID: PMC10982436 DOI: 10.3389/fneur.2024.1329044] [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: 10/27/2023] [Accepted: 02/29/2024] [Indexed: 04/04/2024] Open
Abstract
Introduction Understanding the residual recovery potential in stroke patients is crucial for tailoring effective neurorehabilitation programs. We propose using EEG and plasmatic Neurofilament light chain (NfL) levels as a model to depict longitudinal patterns of stroke recovery. Methods We enrolled 13 patients (4 female, mean age 74.7 ± 8.8) who underwent stroke in the previous month and were hospitalized for 2-months rehabilitation. Patients underwent blood withdrawal, clinical evaluation and high-definition EEG at T1 (first week of rehabilitation) and at T2 (53 ± 10 days after). We assessed the levels of NfL and we analyzed the EEG signal extracting Spectral Exponent (SE) values. We compared our variables between the two timepoint and between cortical and non-cortical strokes. Results We found a significant difference in the symmetry of SE values between cortical and non-cortical stroke at both T1 (p = 0.005) and T2 (p = 0.01). SE in the affected hemisphere showed significantly steeper values at T1 when compared with T2 (p = 0.001). EEG measures were consistently related to clinical scores, while NfL at T1 was related to the volume of ischemic lesions (r = 0.75; p = 0.003). Additionally, the combined use of NfL and SE indicated varying trends in longitudinal clinical recovery. Conclusion We present proof of concept of a promising approach for the characterization of different recovery patterns in stroke patients.
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Affiliation(s)
- Jacopo Lanzone
- Istituti Clinici Scientifici Maugeri IRCCS, Neurorehabilitation Department of the Milano Institute, Milan, Italy
| | - Aida Zulueta
- Istituti Clinici Scientifici Maugeri IRCCS, Neurorehabilitation Department of the Milano Institute, Milan, Italy
| | - Marilisa Boscarino
- Istituti Clinici Scientifici Maugeri IRCCS, Neurorehabilitation Department of the Milano Institute, Milan, Italy
| | - Matteo Gallotta
- Istituti Clinici Scientifici Maugeri IRCCS, Neurorehabilitation Department of the Milano Institute, Milan, Italy
| | - Maria Rosaria Argentieri
- Istituti Clinici Scientifici Maugeri IRCCS, Neurorehabilitation Department of the Milano Institute, Milan, Italy
| | | | - Simone Sarasso
- Department of Biomedical and Clinical Sciences, Università Degli Studi di Milano, Milan, Italy
| | - Michele A. Colombo
- Department of Biomedical and Clinical Sciences, Università Degli Studi di Milano, Milan, Italy
| | - Sasha D’Ambrosio
- IRCCS Fondazione Don Carlo Gnocchi, ONLUS, Milan, Italy
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
- Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom
| | - Christian Lunetta
- Istituti Clinici Scientifici Maugeri IRCCS, Neurorehabilitation Department of the Milano Institute, Milan, Italy
| | - Eugenio Parati
- Istituti Clinici Scientifici Maugeri IRCCS, Neurorehabilitation Department of the Milano Institute, Milan, Italy
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Zhang JJ, Bai Z, Fong KNK. Resting-state cortical electroencephalogram rhythms and network in patients after chronic stroke. J Neuroeng Rehabil 2024; 21:32. [PMID: 38424592 PMCID: PMC10902978 DOI: 10.1186/s12984-024-01328-7] [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] [Received: 10/09/2023] [Accepted: 02/22/2024] [Indexed: 03/02/2024] Open
Abstract
OBJECTIVE To investigate the resting-state cortical electroencephalogram (EEG) rhythms and networks in patients with chronic stroke and examine their correlation with motor functions of the hemiplegic upper limb. METHODS Resting-state EEG data from 22 chronic stroke patients were compared to EEG data from 19 age-matched and 16 younger-age healthy controls. The EEG rhythmic powers and network metrics were analyzed. Upper limb motor functions were evaluated using the Fugl-Meyer assessment-upper extremity scores and action research arm test. RESULTS Compared with healthy controls, patients with chronic stroke showed hemispheric asymmetry, with increased low-frequency activity and decreased high-frequency activity. The ipsilesional hemisphere of stroke patients exhibited reduced alpha and low beta band node strength and clustering coefficient compared to the contralesional side. Low beta power and node strength in the delta band correlated with motor functions of the hemiplegic arm. CONCLUSION The stroke-affected hemisphere showed low-frequency oscillations and decreased influence and functional segregation in the brain network. Low beta activity and redistribution of delta band network between hemispheres were correlated with motor functions of hemiplegic upper limb, suggesting a compensatory mechanism involving both hemispheres post-stroke.
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Affiliation(s)
- Jack Jiaqi Zhang
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China.
| | - Zhongfei Bai
- Department of Rehabilitation, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai, China.
| | - Kenneth N K Fong
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
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Shamsi F, Aligholi H, Karimi MT, Borhani-Haghighi A, Nami M. Quantitative EEG for the Monitoring of Walking Recovery in Chronic Stroke Patients Receiving Action Observation Training. J Mot Behav 2024; 56:428-438. [PMID: 38408745 DOI: 10.1080/00222895.2024.2320904] [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: 04/13/2023] [Accepted: 02/14/2024] [Indexed: 02/28/2024]
Abstract
The current study aimed to evaluate the effects of action observation on the walking ability and oscillatory brain activity of chronic stroke patients. Fourteen chronic stroke patients were allocated randomly to the action observation (AO) or sham observation (SO) groups. Both groups received 12 sessions of intervention. Each session composed of 12 min of observational training, which depicted exercises for the experimental group but nature pictures for the sham group and 40 min of occupational therapy, which was the same for the both groups. Walking ability was assessed by a motion analysis system and brain activity was monitored using quantitative electroencephalography (QEEG) before and after the intervention. Brain asymmetry at alpha frequency, the percentage of stance phase, and step length showed significant changes in the AO group. Only the change in global alpha power was significantly correlated with the change in velocity after the intervention in AO group. Despite more improvements in walking and brain activity of patients in the AO group, our study failed to show significant correlations between the brain activity changes and functional improvements after the intervention, which might be mainly due to the small sample size in our study. Trial registration: IRCT20181014041333N1.
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Affiliation(s)
- Fatemeh Shamsi
- Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Neuroscience Laboratory (Brain, Cognition and Behavior), Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Hadi Aligholi
- Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Neuroscience Laboratory (Brain, Cognition and Behavior), Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mohammad Taghi Karimi
- Rehabilitation Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | | | - Mohammad Nami
- Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Neuroscience Laboratory (Brain, Cognition and Behavior), Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Neuroscience Center, Instituto de Investigaciones Científicas Servicios de Alta Tecnología (INDICASAT AIP), City of Knowledge, Panama City, Panama
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Bernardes TS, Santos KCS, Nascimento MR, Filho CANES, Bazan R, Pereira JM, de Souza LAPS, Luvizutto GJ. Effects of anodal transcranial direct current stimulation over motor cortex on resting-state brain activity in the early subacute stroke phase: A power spectral density analysis. Clin Neurol Neurosurg 2024; 237:108134. [PMID: 38335706 DOI: 10.1016/j.clineuro.2024.108134] [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: 09/27/2023] [Revised: 01/06/2024] [Accepted: 01/24/2024] [Indexed: 02/12/2024]
Abstract
INTRODUCTION Despite promising results, the effects of transcranial direct current stimulation (tDCS) in the early stages of stroke and its impact on brain activity have been poorly studied. Therefore, this study aimed to investigate the effect of tDCS applied over the ipsilesional motor cortex on resting-state brain activity in the early subacute phase of stroke. METHODS This is a pilot, randomized, double-blind, proof-of-concept study. The patients with stroke were randomly assigned into two groups: anodal tDCS (A-tDCS) or sham tDCS (S-tDCS). For A-tDCS, the anode was placed over the ipsilesional motor cortex, while the cathode was placed over the left or right supraorbital area (Fp2 for left stroke or Fp1 for right stroke). For the real stimulation, a constant current of 1.0 mA was delivered for 20 min and then ramped down linearly for 30 s, maintaining a resistance below 10 kΩ. For the sham stimulation, the stimulator was turned on, and the current intensity was gradually increased for 30 s, tapered off over 30 s, and maintained for 30 min without stimulation. Each stimulation was performed for three consecutive sessions with an interval of 1 h between them. The primary outcome was spectral electroencephalography (EEG) analysis based on the Power Spectral Density (PSD) determined by EEG records of areas F3, F4, C3, C4, P3, and P4. Brain Vision Analyzer software processed the signals, EEG power spectral density (PSD) was calculated before and after stimulation, and alpha, beta, delta, and theta power were analyzed. The secondary outcomes included hemodynamic variables based on the difference between baseline (D0) and post-intervention session (D1) values of systolic (SBP) and diastolic (DBP) blood pressure, heart rate (HR), respiratory rate (RR) and peripheral oxygen saturation (SPO2). Mann-Whitney test was used to compare position measurements of two independent samples; Fisher's exact test was used to compare two proportions; paired Wilcoxon signed-rank test was used to compare the median differences in the within-group comparison, and Spearman correlations matrix among spectral power analysis between EEG bands was performed to verify consistency of occurrence of oscillations. Statistical significance was set at P < 0.05. RESULTS An increase in PSD in the alpha frequency in the P4 region was observed after the intervention in the A-tDCS group, as compared to the placebo group (before = 6.13; after = 10.45; p < 0.05). In the beta frequency, an increase in PSD was observed in P4 (before = 4.40; after = 6.79; p < 0.05) and C4 (before = 4.43; after = 6.94; p < 0.05) after intervention in the A-tDCS group. There was a reduction in PSD at delta frequency in C3 (before = 293.8; after = 58.6; p < 0.05) after intervention in the A-tDCS group. In addition, it was observed a strong relationship between alpha and theta power in the A-tDCS group before and after intervention. However, the sham group showed correlations between more power bands (alpha and theta, alpha and delta, and delta and theta) after intervention. There was no difference in hemodynamic variables between the intra- (before and after stimulation) and inter-groups (mean difference). CONCLUSION Anodal tDCS over the ipsilesional motor cortex had significant effects on the brain electrical activity in the early subacute stroke phase, increasing alpha and beta wave activities in sensorimotor regions while reducing slow delta wave activity in motor regions. These findings highlight the potential of anodal tDCS as a therapeutic intervention in the early stroke phase.
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Affiliation(s)
- Tiago Soares Bernardes
- Department of Medicine, Universidade Federal do Triângulo Mineiro (UFTM), Uberaba, Minas Gerais, Brazil
| | - Kelly Cristina Sousa Santos
- Department of Applied Physical Therapy, Universidade Federal do Triângulo Mineiro (UFTM), Uberaba, Minas Gerais, Brazil
| | - Monalisa Resende Nascimento
- Department of Applied Physical Therapy, Universidade Federal do Triângulo Mineiro (UFTM), Uberaba, Minas Gerais, Brazil
| | | | - Rodrigo Bazan
- Department of Neurology, Psychology, and Psychiatry, Botucatu Medical School (UNESP), Botucatu, SP, Brazil
| | - Janser Moura Pereira
- Statistical Department, Universidade Federal de Uberlândia (UFU), Uberlândia, MG, Brazil
| | | | - Gustavo José Luvizutto
- Department of Applied Physical Therapy, Universidade Federal do Triângulo Mineiro (UFTM), Uberaba, Minas Gerais, Brazil.
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Lassi M, Dalise S, Bandini A, Spina V, Azzollini V, Vissani M, Micera S, Mazzoni A, Chisari C. Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients. Eur J Phys Rehabil Med 2024; 60:13-26. [PMID: 37987741 DOI: 10.23736/s1973-9087.23.07922-4] [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: 11/22/2023]
Abstract
BACKGROUND Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanisms depend on the time after stroke is yet to be assessed. AIM We investigated the response to an intensive protocol of robot-assisted rehabilitation in sub-acute and chronic stroke patients, by analyzing the underlying changes in clinical scores, electroencephalography (EEG) and end-effector kinematics. We aimed at identifying neural correlates of the participants' upper limb motor function recovery, following an intensive 2-week rehabilitation protocol. DESIGN Prospective cohort study. SETTING Inpatients and outpatients from the Neurorehabilitation Unit of Pisa University Hospital, Italy. POPULATION Sub-acute and chronic stroke survivors. METHODS Thirty-one stroke survivors (14 sub-acute, 17 chronic) with mild-to-moderate UL paresis were enrolled. All participants underwent ten rehabilitative sessions of task-oriented exercises with a planar end-effector robotic device. All patients were evaluated with the Fugl-Meyer Assessment Scale and the Wolf Motor Function Test, at recruitment (T0), end-of-treatment (T1), and one-month follow-up (T2). Along with clinical scales, kinematic parameters and quantitative EEG were collected for each patient. Kinematics metrics were related to velocity, acceleration and smoothness of the movement. Relative power in four frequency bands was extracted from the EEG signals. The evolution over time of kinematic and EEG features was analyzed, in correlation with motor recovery. RESULTS Both groups displayed significant gains in motility after treatment. Sub-acute patients displayed more pronounced clinical improvements, significant changes in kinematic parameters, and a larger increase in Beta-band in the motor area of the affected hemisphere. In both groups these improvements were associated to a decrease in the Delta-band of both hemispheres. Improvements were retained at T2. CONCLUSIONS The intensive two-week rehabilitation protocol was effective in both chronic and sub-acute patients, and improvements in the two groups shared similar dynamics. However, stronger cortical and behavioral changes were observed in sub-acute patients suggesting different reorganizational patterns. CLINICAL REHABILITATION IMPACT This study paves the way to personalized approaches to UL motor rehabilitation after stroke, as highlighted by different neurophysiological modifications following recovery in subacute and chronic stroke patients.
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Affiliation(s)
- Michael Lassi
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Stefania Dalise
- Neurorehabilitation Unit, Pisa University Hospital, Pisa, Italy
| | - Andrea Bandini
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
- Health Science Interdisciplinary Research Center, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Vincenzo Spina
- Neurorehabilitation Unit, Pisa University Hospital, Pisa, Italy
| | | | - Matteo Vissani
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
- Harvard Medical School, Boston, MA, USA
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Silvestro Micera
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
- Bertarelli Foundation Chair in Translational Neural Engineering, Center for Neuroprosthetics and Institute of Bioengineering, École Polytechnique Fèdèrale de Lausanne, Lausanne, Switzerland
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Carmelo Chisari
- Neurorehabilitation Unit, Pisa University Hospital, Pisa, Italy -
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Lanzone J, Motolese F, Ricci L, Tecchio F, Tombini M, Zappasodi F, Cruciani A, Capone F, Di Lazzaro V, Assenza G. Quantitative measures of the resting EEG in stroke: a systematic review on clinical correlation and prognostic value. Neurol Sci 2023; 44:4247-4261. [PMID: 37542545 DOI: 10.1007/s10072-023-06981-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 07/26/2023] [Indexed: 08/07/2023]
Abstract
OBJECT Quantitative electroencephalography (qEEG) has shown promising results as a predictor of clinical impairment in stroke. We systematically reviewed published papers that focus on qEEG metrics in the resting EEG of patients with mono-hemispheric stroke, to summarize current knowledge and pave the way for future research. METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched the literature for papers that fitted our inclusion criteria. Rayyan QCRR was used to allow deduplication and collaborative blinded paper review. Due to multiple outcomes and non-homogeneous literature, a scoping review approach was used to address the topic. RESULTS Or initial search (PubMed, Embase, Google scholar) yielded 3200 papers. After proper screening, we selected 71 papers that fitted our inclusion criteria and we developed a scoping review thar describes the current state of the art of qEEG in stroke. Notably, among selected papers 53 (74.3%) focused on spectral power; 11 (15.7%) focused on symmetry indexes, 17 (24.3%) on connectivity metrics, while 5 (7.1%) were about other metrics (e.g. detrended fluctuation analysis). Moreover, 42 (58.6%) studies were performed with standard 19 electrodes EEG caps and only a minority used high-definition EEG. CONCLUSIONS We systematically assessed major findings on qEEG and stroke, evidencing strengths and potential pitfalls of this promising branch of research.
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Affiliation(s)
- J Lanzone
- Istituti Clinici Scientifici Maugeri IRCCS, Neurorehabilitation Department of the Milano Institute, Milan, Italy.
| | - F Motolese
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
| | - L Ricci
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
| | - F Tecchio
- Laboratory of Electrophysiology for Translational Neuroscience LET'S, Institute of Cognitive Sciences and Technologies ISTC, Consiglio Nazionale Delle Ricerche CNR, Rome, Italy
| | - M Tombini
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
| | - F Zappasodi
- Department of Neuroscience, Imaging and Clinical Sciences and Institute for Advanced Biomedical Technologies, 'Gabriele D'Annunzio' University, Chieti, Italy
| | - A Cruciani
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
| | - F Capone
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
| | - V Di Lazzaro
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
| | - G Assenza
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128, Roma, Italy
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10
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Raposo I, Szczepanski SM, Haaland K, Endestad T, Solbakk AK, Knight RT, Helfrich RF. Periodic attention deficits after frontoparietal lesions provide causal evidence for rhythmic attentional sampling. Curr Biol 2023; 33:4893-4904.e3. [PMID: 37852264 PMCID: PMC10842514 DOI: 10.1016/j.cub.2023.09.065] [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: 05/23/2023] [Revised: 08/08/2023] [Accepted: 09/26/2023] [Indexed: 10/20/2023]
Abstract
Contemporary models conceptualize spatial attention as a blinking spotlight that sequentially samples visual space. Hence, behavior fluctuates over time, even in states of presumed "sustained" attention. Recent evidence has suggested that rhythmic neural activity in the frontoparietal network constitutes the functional basis of rhythmic attentional sampling. However, causal evidence to support this notion remains absent. Using a lateralized spatial attention task, we addressed this issue in patients with focal lesions in the frontoparietal attention network. Our results revealed that frontoparietal lesions introduce periodic attention deficits, i.e., temporally specific behavioral deficits that are aligned with the underlying neural oscillations. Attention-guided perceptual sensitivity was on par with that of healthy controls during optimal phases but was attenuated during the less excitable sub-cycles. Theta-dependent sampling (3-8 Hz) was causally dependent on the prefrontal cortex, while high-alpha/low-beta sampling (8-14 Hz) emerged from parietal areas. Collectively, our findings reveal that lesion-induced high-amplitude, low-frequency brain activity is not epiphenomenal but has immediate behavioral consequences. More generally, these results provide causal evidence for the hypothesis that the functional architecture of attention is inherently rhythmic.
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Affiliation(s)
- Isabel Raposo
- Hertie Institute for Clinical Brain Research, University Medical Center Tübingen, 72076 Tübingen, Germany; International Max Planck Research School for the Mechanisms of Mental Function and Dysfunction, University of Tübingen, Tübingen, Germany
| | - Sara M Szczepanski
- Department of Psychology and the Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, CA 94720, USA
| | - Kathleen Haaland
- Department of Psychiatry and Behavioral Sciences, University of New Mexico Health Sciences, Albuquerque, NM 87102, USA
| | - Tor Endestad
- Department of Psychology, University of Oslo, 0373 Oslo, Norway; RITMO Centre for Interdisciplinary Studies in Rhythm, Time, and Motion, University of Oslo, 0371 Oslo, Norway
| | - Anne-Kristin Solbakk
- Department of Psychology, University of Oslo, 0373 Oslo, Norway; RITMO Centre for Interdisciplinary Studies in Rhythm, Time, and Motion, University of Oslo, 0371 Oslo, Norway; Department of Neurosurgery, Oslo University Hospital, 0372 Oslo, Norway; Department of Neuropsychology, Helgeland Hospital, 8656 Mosjøen, Norway
| | - Robert T Knight
- Department of Psychology and the Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, CA 94720, USA
| | - Randolph F Helfrich
- Hertie Institute for Clinical Brain Research, University Medical Center Tübingen, 72076 Tübingen, Germany.
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11
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Hencz A, Magony A, Thomas C, Kovacs K, Szilagyi G, Pal J, Sik A. Mild hypoxia-induced structural and functional changes of the hippocampal network. Front Cell Neurosci 2023; 17:1277375. [PMID: 37841285 PMCID: PMC10576450 DOI: 10.3389/fncel.2023.1277375] [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: 08/14/2023] [Accepted: 09/15/2023] [Indexed: 10/17/2023] Open
Abstract
Hypoxia causes structural and functional changes in several brain regions, including the oxygen-concentration-sensitive hippocampus. We investigated the consequences of mild short-term hypoxia on rat hippocampus in vivo. The hypoxic group was treated with 16% O2 for 1 h, and the control group with 21% O2. Using a combination of Gallyas silver impregnation histochemistry revealing damaged neurons and interneuron-specific immunohistochemistry, we found that somatostatin-expressing inhibitory neurons in the hilus were injured. We used 32-channel silicon probe arrays to record network oscillations and unit activity from the hippocampal layers under anaesthesia. There were no changes in the frequency power of slow, theta, beta, or gamma bands, but we found a significant increase in the frequency of slow oscillation (2.1-2.2 Hz) at 16% O2 compared to 21% O2. In the hilus region, the firing frequency of unidentified interneurons decreased. In the CA3 region, the firing frequency of some unidentified interneurons decreased while the activity of other interneurons increased. The activity of pyramidal cells increased both in the CA1 and CA3 regions. In addition, the regularity of CA1, CA3 pyramidal cells' and CA3 type II and hilar interneuron activity has significantly changed in hypoxic conditions. In summary, a low O2 environment caused profound changes in the state of hippocampal excitatory and inhibitory neurons and network activity, indicating potential changes in information processing caused by mild short-term hypoxia.
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Affiliation(s)
- Alexandra Hencz
- Institute of Physiology, Medical School, University of Pecs, Pecs, Hungary
| | - Andor Magony
- Institute of Physiology, Medical School, University of Pecs, Pecs, Hungary
- Institute of Transdisciplinary Discoveries, Medical School, University of Pecs, Pecs, Hungary
| | - Chloe Thomas
- Institute of Clinical Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Krisztina Kovacs
- Institute of Clinical Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Gabor Szilagyi
- Institute of Biochemistry and Medical Chemistry, Medical School, University of Pecs, Pecs, Hungary
| | - Jozsef Pal
- Institute of Physiology, Medical School, University of Pecs, Pecs, Hungary
| | - Attila Sik
- Institute of Physiology, Medical School, University of Pecs, Pecs, Hungary
- Institute of Transdisciplinary Discoveries, Medical School, University of Pecs, Pecs, Hungary
- Institute of Clinical Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
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12
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Ferreira LO, de Souza RD, Teixeira LL, Pinto LC, Rodrigues JCM, Martins-Filho AJ, da Costa ET, Hamoy M, Lopes DCF. The GPER1 agonist G1 reduces brain injury and improves the qEEG and behavioral outcome of experimental ischemic stroke. J Neuropathol Exp Neurol 2023; 82:787-797. [PMID: 37558387 DOI: 10.1093/jnen/nlad061] [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] [Indexed: 08/11/2023] Open
Abstract
Stroke is one of the principal cerebrovascular diseases in human populations and contributes to a majority of the functional impairments in the elderly. Recent discoveries have led to the inclusion of electroencephalography (EEG) in the complementary prognostic evaluation of patients. The present study describes the EEG, behavioral, and histological changes that occur following cerebral ischemia associated with treatment by G1, a potent and selective G protein-coupled estrogen receptor 1 (GPER1) agonist in a rat model. Treatment with G1 attenuated the neurological deficits induced by ischemic stroke from the second day onward, and reduced areas of infarction. Treatment with G1 also improved the total brainwave power, as well as the theta and alpha wave activity, specifically, and restored the delta band power to levels similar to those observed in the controls. Treatment with G1 also attenuated the peaks of harmful activity observed in the EEG indices. These improvements in brainwave activity indicate that GPER1 plays a fundamental role in the mediation of cerebral injury and in the behavioral outcome of ischemic brain injuries, which points to treatment with G1 as a potential pharmacological strategy for the therapy of stroke.
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Affiliation(s)
- Luan Oliveira Ferreira
- Laboratory of Experimental Neuropathology, Joao de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | - Rafael Dias de Souza
- Laboratory of Experimental Neuropathology, Joao de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | - Leonan Lima Teixeira
- Laboratory of Experimental Neuropathology, Joao de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | - Laine Celestino Pinto
- Laboratory of Experimental Neuropathology, Joao de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | - Joao Cleiton Martins Rodrigues
- Laboratory of Experimental Neuropathology, Joao de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | | | - Edmar Tavares da Costa
- Laboratory of Experimental Neuropathology, Joao de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | - Moisés Hamoy
- Laboratory of Pharmacology and Toxicology of Natural Products, Biological Sciences Institute, Federal University of Pará, Belém, Brazil
| | - Dielly Catrina Favacho Lopes
- Laboratory of Experimental Neuropathology, Joao de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
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13
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Agner SC, Brier LM, Hill J, Liu E, Bice A, Rahn RM, Culver JP, Klein RS. Myeloid cell activation during Zika virus encephalitis predicts recovery of functional cortical connectivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.06.547991. [PMID: 37461558 PMCID: PMC10350085 DOI: 10.1101/2023.07.06.547991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
Neurologic complications of Zika virus (ZIKV) infection across the lifespan have been described during outbreaks in Southeast Asia, South America, and Central America since 2016. In the adult CNS ZIKV tropism for neurons is tightly linked to its effects, with neuronal loss within the hippocampus during acute infection and protracted synapse loss during recovery, which is associated with cognitive deficits. The effects of ZIKV on cortical networks have not been evaluated. Although animal behavior assays have been used previously to model cognitive impairment, in vivo brain imaging can provide orthogonal information regarding the health of brain networks in real time, providing a tool to translate findings in animal models to humans. In this study, we use widefield optical imaging to measure cortical functional connectivity (FC) in mice during acute infection with, and recovery from, intracranial infection with a mouse-adapted strain of ZIKV. Acute ZIKV infection leads to high levels of myeloid cell activation, with loss of neurons and presynaptic termini in the cerebral cortex and associated loss of FC primarily within the somatosensory cortex. During recovery, neuron numbers, synapses and FC recover to levels near those of healthy mice. However, hippocampal injury and impaired spatial cognition persist. The magnitude of activated myeloid cells during acute infection predicted both recovery of synapses and the degree of FC recovery after recovery from ZIKV infection. These findings suggest that a robust inflammatory response may contribute to the health of functional brain networks after recovery from infection.
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Affiliation(s)
- Shannon C. Agner
- Center for Neuroimmunology and Neuroinfectious Diseases, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Lindsey M. Brier
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Jeremy Hill
- Center for Neuroimmunology and Neuroinfectious Diseases, Washington University School of Medicine, St. Louis, MO, USA
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Ethan Liu
- Center for Neuroimmunology and Neuroinfectious Diseases, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Annie Bice
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Rachel M. Rahn
- Departments of Physics, Biomedical Engineering, and Electrical and Systems Engineering, Washington University School of Medicine, St. Louis, MO, USA
| | - Joseph P. Culver
- Departments of Physics, Biomedical Engineering, and Electrical and Systems Engineering, Washington University School of Medicine, St. Louis, MO, USA
| | - Robyn S. Klein
- Center for Neuroimmunology and Neuroinfectious Diseases, Washington University School of Medicine, St. Louis, MO, USA
- Departments of Medicine, Pathology & Immunology, and Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
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14
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Lassi M, Fabbiani C, Mazzeo S, Burali R, Vergani AA, Giacomucci G, Moschini V, Morinelli C, Emiliani F, Scarpino M, Bagnoli S, Ingannato A, Nacmias B, Padiglioni S, Micera S, Sorbi S, Grippo A, Bessi V, Mazzoni A. Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum? Neuroimage Clin 2023; 38:103407. [PMID: 37094437 PMCID: PMC10149415 DOI: 10.1016/j.nicl.2023.103407] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 03/29/2023] [Accepted: 04/14/2023] [Indexed: 04/26/2023]
Abstract
Alzheimer's disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by mild cognitive impairment (MCI), the initial stage of clinical cognitive decline. However, the neural correlates of these prodromic stages are not completely clear yet. Recent studies suggest that EEG analysis tools characterizing the cortical activity as a whole, such as microstates and cortical regions connectivity, might support a characterization of SCD and MCI conditions. Here we test this approach by performing a broad set of analyses to identify the prominent EEG markers differentiating SCD (n = 57), MCI (n = 46) and healthy control subjects (HC, n = 19). We found that the salient differences were in the temporal structure of the microstates patterns, with MCI being associated with less complex sequences due to the altered transition probability, frequency and duration of canonic microstate C. Spectral content of EEG, network connectivity, and spatial arrangement of microstates were instead largely similar in the three groups. Interestingly, comparing properties of EEG microstates in different cerebrospinal fluid (CSF) biomarkers profiles, we found that canonic microstate C displayed significant differences in topography in AD-like profile. These results show that the progression of dementia might be associated with a degradation of the cortical organization captured by microstates analysis, and that this leads to altered transitions between cortical states. Overall, our approach paves the way for the use of non-invasive EEG recordings in the identification of possible biomarkers of progression to AD from its prodromal states.
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Affiliation(s)
- Michael Lassi
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy
| | - Carlo Fabbiani
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Salvatore Mazzeo
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Rachele Burali
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Alberto Arturo Vergani
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy
| | - Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Valentina Moschini
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Carmen Morinelli
- Dipartimento Neuromuscolo-scheletrico e degli organi di senso, Careggi University Hospital, 50134 Florence, Italy
| | - Filippo Emiliani
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Maenia Scarpino
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Benedetta Nacmias
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Sonia Padiglioni
- Regional Referral Centre for Relational Criticalities - Tuscany Region, 50139 Florence, Italy
| | - Silvestro Micera
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy; Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Sandro Sorbi
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Antonello Grippo
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Alberto Mazzoni
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy.
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15
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Zhang JJ, Sánchez Vidaña DI, Chan JNM, Hui ESK, Lau KK, Wang X, Lau BWM, Fong KNK. Biomarkers for prognostic functional recovery poststroke: A narrative review. Front Cell Dev Biol 2023; 10:1062807. [PMID: 36699006 PMCID: PMC9868572 DOI: 10.3389/fcell.2022.1062807] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 12/19/2022] [Indexed: 01/11/2023] Open
Abstract
Background and objective: Prediction of poststroke recovery can be expressed by prognostic biomarkers that are related to the pathophysiology of stroke at the cellular and molecular level as well as to the brain structural and functional reserve after stroke at the systems neuroscience level. This study aimed to review potential biomarkers that can predict poststroke functional recovery. Methods: A narrative review was conducted to qualitatively summarize the current evidence on biomarkers used to predict poststroke functional recovery. Results: Neurophysiological measurements and neuroimaging of the brain and a wide diversity of molecules had been used as prognostic biomarkers to predict stroke recovery. Neurophysiological studies using resting-state electroencephalography (EEG) revealed an interhemispheric asymmetry, driven by an increase in low-frequency oscillation and a decrease in high-frequency oscillation in the ipsilesional hemisphere relative to the contralesional side, which was indicative of individual recovery potential. The magnitude of somatosensory evoked potentials and event-related desynchronization elicited by movement in task-related EEG was positively associated with the quantity of recovery. Besides, transcranial magnetic stimulation (TMS) studies revealed the potential values of using motor-evoked potentials (MEP) and TMS-evoked EEG potentials from the ipsilesional motor cortex as prognostic biomarkers. Brain structures measured using magnetic resonance imaging (MRI) have been implicated in stroke outcome prediction. Specifically, the damage to the corticospinal tract (CST) and anatomical motor connections disrupted by stroke lesion predicted motor recovery. In addition, a wide variety of molecular, genetic, and epigenetic biomarkers, including hemostasis, inflammation, tissue remodeling, apoptosis, oxidative stress, infection, metabolism, brain-derived, neuroendocrine, and cardiac biomarkers, etc., were associated with poor functional outcomes after stroke. However, challenges such as mixed evidence and analytical concerns such as specificity and sensitivity have to be addressed before including molecular biomarkers in routine clinical practice. Conclusion: Potential biomarkers with prognostic values for the prediction of functional recovery after stroke have been identified; however, a multimodal approach of biomarkers for prognostic prediction has rarely been studied in the literature. Future studies may incorporate a combination of multiple biomarkers from big data and develop algorithms using data mining methods to predict the recovery potential of patients after stroke in a more precise way.
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Affiliation(s)
- Jack Jiaqi Zhang
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | | | - Jackie Ngai-Man Chan
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Edward S. K. Hui
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
- Department of Psychiatry, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Kui Kai Lau
- Division of Neurology, Department of Medicine, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Xin Wang
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Benson W. M. Lau
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Kenneth N. K. Fong
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
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16
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Corsi L, Liuzzi P, Ballanti S, Scarpino M, Maiorelli A, Sterpu R, Macchi C, Cecchi F, Hakiki B, Grippo A, Lanatà A, Carrozza MC, Bocchi L, Mannini A. EEG asymmetry detection in patients with severe acquired brain injuries via machine learning methods. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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17
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Padawer-Curry JA, Bowen RM, Jarang A, Wang X, Lee JM, Bauer AQ. Wide-Field Optical Imaging in Mouse Models of Ischemic Stroke. Methods Mol Biol 2023; 2616:113-151. [PMID: 36715932 DOI: 10.1007/978-1-0716-2926-0_11] [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] [Indexed: 01/31/2023]
Abstract
Functional neuroimaging is a powerful tool for evaluating how local and global brain circuits evolve after focal ischemia and how these changes relate to functional recovery. For example, acutely after stroke, changes in functional brain organization relate to initial deficit and are predictive of recovery potential. During recovery, the reemergence and restoration of connections lost due to stroke correlate with recovery of function. Thus, information gleaned from functional neuroimaging can be used as a proxy for behavior and inform on the efficacy of interventional strategies designed to affect plasticity mechanisms after injury. And because these findings are consistently observed across species, bridge measurements can be made in animal models to enrich findings in human stroke populations. In mice, genetic engineering techniques have provided several new opportunities for extending optical neuroimaging methods to more direct measures of neuronal activity. These developments are especially useful in the context of stroke where neurovascular coupling can be altered, potentially limiting imaging measures based on hemodynamic activity alone. This chapter is designed to give an overview of functional wide-field optical imaging (WFOI) for applications in rodent models of stroke, primarily in the mouse. The goal is to provide a protocol for laboratories that want to incorporate an affordable functional neuroimaging assay into their current research thrusts, but perhaps lack the background knowledge or equipment for developing a new arm of research in their lab. Within, we offer a comprehensive guide developing and applying WFOI technology with the hope of facilitating accessibility of neuroimaging technology to other researchers in the stroke field.
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Affiliation(s)
- Jonah A Padawer-Curry
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Imaging Science PhD Program, Washington University in St. Louis, St. Louis, MO, USA
| | - Ryan M Bowen
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Anmol Jarang
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Xiaodan Wang
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Jin-Moo Lee
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Adam Q Bauer
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA.
- Imaging Science PhD Program, Washington University in St. Louis, St. Louis, MO, USA.
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA.
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18
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An IoMT-Based Approach for Real-Time Monitoring Using Wearable Neuro-Sensors. JOURNAL OF HEALTHCARE ENGINEERING 2023; 2023:1066547. [PMID: 36814546 PMCID: PMC9940964 DOI: 10.1155/2023/1066547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 08/15/2022] [Accepted: 01/28/2023] [Indexed: 02/15/2023]
Abstract
The Internet of Things (IoT) has demonstrated over the past few decades to be a powerful tool for connecting various medical equipment with in-built sensors and healthcare professionals to deliver superior health services that also reach remote areas. In addition to reducing healthcare costs, increasing access to clinical services, and enhancing operational effectiveness in the healthcare industry, it has also enhanced patient health safety. Recent research has focused on using EEG to assist and comprehend brain changes in rehabilitation facilities. These technologies can spot fluctuations in EEG constraints during treatment, which could result in more effective therapy and better functional outcomes. As a result, we have tried to use an IoT-based system for real-time monitoring of the constraints. Another unknown patient who is suffering from acute ischemic stroke may experience stroke-in-evolution or an early worsening of neurological symptoms, which is frequently associated with poor clinical outcomes. Because of this, managing an acute stroke requires early detection of these indications. The present investigation work will act as a standard reference for academic researchers, medical professionals, and everyone else involved in the use of IoMT. This study aims to anticipate strokes sooner and prevent their consequences by early intervention using an Internet of Things (IoT)-based system. Also, this study proposes usage of wearable equipment that can monitor and analyze brain signals for improved treatment and the prevention of stroke-related complications.
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19
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Islam MS, Hussain I, Rahman MM, Park SJ, Hossain MA. Explainable Artificial Intelligence Model for Stroke Prediction Using EEG Signal. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22249859. [PMID: 36560227 PMCID: PMC9782764 DOI: 10.3390/s22249859] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 11/30/2022] [Accepted: 12/14/2022] [Indexed: 05/07/2023]
Abstract
State-of-the-art healthcare technologies are incorporating advanced Artificial Intelligence (AI) models, allowing for rapid and easy disease diagnosis. However, most AI models are considered "black boxes," because there is no explanation for the decisions made by these models. Users may find it challenging to comprehend and interpret the results. Explainable AI (XAI) can explain the machine learning (ML) outputs and contribution of features in disease prediction models. Electroencephalography (EEG) is a potential predictive tool for understanding cortical impairment caused by an ischemic stroke and can be utilized for acute stroke prediction, neurologic prognosis, and post-stroke treatment. This study aims to utilize ML models to classify the ischemic stroke group and the healthy control group for acute stroke prediction in active states. Moreover, XAI tools (Eli5 and LIME) were utilized to explain the behavior of the model and determine the significant features that contribute to stroke prediction models. In this work, we studied 48 patients admitted to a hospital with acute ischemic stroke and 75 healthy adults who had no history of identified other neurological illnesses. EEG was obtained within three months following the onset of ischemic stroke symptoms using frontal, central, temporal, and occipital cortical electrodes (Fz, C1, T7, Oz). EEG data were collected in an active state (walking, working, and reading tasks). In the results of the ML approach, the Adaptive Gradient Boosting models showed around 80% accuracy for the classification of the control group and the stroke group. Eli5 and LIME were utilized to explain the behavior of the stroke prediction model and interpret the model locally around the prediction. The Eli5 and LIME interpretable models emphasized the spectral delta and theta features as local contributors to stroke prediction. From the findings of this explainable AI research, it is expected that the stroke-prediction XAI model will help with post-stroke treatment and recovery, as well as help healthcare professionals, make their diagnostic decisions more explainable.
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Affiliation(s)
- Mohammed Saidul Islam
- Network and Data Analysis Group, Department of Computer Science and Engineering, Islamic University and Technology (IUT), Gazipur 1704, Bangladesh
| | - Iqram Hussain
- Department of Biomedical Engineering, Medical Research Center, College of Medicine, Seoul National University, Seoul 03080, Republic of Korea
- Data Mind Ltd., Dhaka 1230, Bangladesh
- Correspondence: or (I.H.); (M.A.H.)
| | - Md Mezbaur Rahman
- Network and Data Analysis Group, Department of Computer Science and Engineering, Islamic University and Technology (IUT), Gazipur 1704, Bangladesh
| | - Se Jin Park
- AI-Based Healthcare Research Group, Sewon Intelligence Ltd., Seoul 04512, Republic of Korea
| | - Md Azam Hossain
- Network and Data Analysis Group, Department of Computer Science and Engineering, Islamic University and Technology (IUT), Gazipur 1704, Bangladesh
- Correspondence: or (I.H.); (M.A.H.)
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20
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Biskamp J, Isla Cainzos S, Higgen FL, Gerloff C, Magnus T. Normalization of Aperiodic Electrocorticography Components Indicates Fine Motor Recovery After Sensory Cortical Stroke in Mice. Stroke 2022; 53:2945-2953. [PMID: 35770668 DOI: 10.1161/strokeaha.122.039335] [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: 11/16/2022]
Abstract
BACKGROUND Electrophysiological signatures of ischemic stroke might help to develop a deeper understanding of the mechanisms of recovery. However, to identify critical windows for novel treatment approaches, suitable readout parameters in vivo with the potential to close the gap between functional modifications within the peri-infarct cortex and behavioral outcome on the systems-level are still lacking. METHODS Wild-type mice were trained in a skilled reaching task and underwent permanent distal medial cerebral artery occlusion or sham intervention. Functional deficits and their recovery were monitored both behaviorally and electrophysiologically recording multichannel electrocorticography from both hemispheres. RESULTS Ischemic strokes are located in sensory cortical areas. Affected mice presented fine motor deficits of their contralateral forepaw. Analyses of electrocorticography signals from awake animals demonstrated a modulation of the shape of power spectral density in the vicinity of the infarct. While power spectral density consists of both rhythmic oscillatory and nonrhythmic, aperiodic components, the alteration of spectrum shape was reflected in a transient increase of aperiodic exponents in the peri-infarct cortex. The relative power and frequency of slow oscillations remained unchanged. Exponents derived from motor areas significantly correlated with fine motor recovery, thus indicating functional modifications of neuronal activity. CONCLUSIONS Aperiodic spectral exponents exhibited a unique spatiotemporal profile in the mouse cortex after stroke and might complement future translational studies providing a dynamic link from pathophysiology to behavior.
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Affiliation(s)
- Jonatan Biskamp
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Germany
| | - Sara Isla Cainzos
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Germany
| | - Focko L Higgen
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Germany
| | - Tim Magnus
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Germany
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21
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Luppi AI, Mediano PAM, Rosas FE, Allanson J, Pickard JD, Williams GB, Craig MM, Finoia P, Peattie ARD, Coppola P, Owen AM, Naci L, Menon DK, Bor D, Stamatakis EA. Whole-brain modelling identifies distinct but convergent paths to unconsciousness in anaesthesia and disorders of consciousness. Commun Biol 2022; 5:384. [PMID: 35444252 PMCID: PMC9021270 DOI: 10.1038/s42003-022-03330-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Accepted: 03/30/2022] [Indexed: 12/02/2022] Open
Abstract
The human brain entertains rich spatiotemporal dynamics, which are drastically reconfigured when consciousness is lost due to anaesthesia or disorders of consciousness (DOC). Here, we sought to identify the neurobiological mechanisms that explain how transient pharmacological intervention and chronic neuroanatomical injury can lead to common reconfigurations of neural activity. We developed and systematically perturbed a neurobiologically realistic model of whole-brain haemodynamic signals. By incorporating PET data about the cortical distribution of GABA receptors, our computational model reveals a key role of spatially-specific local inhibition for reproducing the functional MRI activity observed during anaesthesia with the GABA-ergic agent propofol. Additionally, incorporating diffusion MRI data obtained from DOC patients reveals that the dynamics that characterise loss of consciousness can also emerge from randomised neuroanatomical connectivity. Our results generalise between anaesthesia and DOC datasets, demonstrating how increased inhibition and connectome perturbation represent distinct neurobiological paths towards the characteristic activity of the unconscious brain.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
- Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, UK.
- The Alan Turing Institute, London, UK.
| | - Pedro A M Mediano
- Department of Psychology, University of Cambridge, Cambridge, UK
- Department of Psychology, Queen Mary University of London, London, UK
| | - Fernando E Rosas
- Center for Psychedelic Research, Department of Brain Science, Imperial College London, London, UK
- Data Science Institute, Imperial College London, London, UK
- Centre for Complexity Science, Imperial College London, London, UK
| | - Judith Allanson
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Department of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke's Hospital, Cambridge, UK
| | - John D Pickard
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Guy B Williams
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Michael M Craig
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Paola Finoia
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Alexander R D Peattie
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Peter Coppola
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Adrian M Owen
- The Brain and Mind Institute, University of Western Ontario, London, ON, Canada
| | - Lorina Naci
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Daniel Bor
- Department of Psychology, University of Cambridge, Cambridge, UK
- Department of Psychology, Queen Mary University of London, London, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
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22
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EEG spectral exponent as a synthetic index for the longitudinal assessment of stroke recovery. Clin Neurophysiol 2022; 137:92-101. [PMID: 35303540 PMCID: PMC9038588 DOI: 10.1016/j.clinph.2022.02.022] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 01/02/2022] [Accepted: 02/22/2022] [Indexed: 12/20/2022]
Abstract
The Spectral Exponent (SE) indexes power-law features of the resting EEG in stroke patients. SE is consistently steeper in the affected hemisphere of patients after middle cerebral artery stroke. SE is linked to clinical status and seems to be a good predictor of clinical outcome.
Objective Quantitative Electroencephalography (qEEG) can capture changes in brain activity following stroke. qEEG metrics traditionally focus on oscillatory activity, however recent findings highlight the importance of aperiodic (power-law) structure in characterizing pathological brain states. We assessed neurophysiological alterations and recovery after mono-hemispheric stroke by means of the Spectral Exponent (SE), a metric that reflects EEG slowing and quantifies the power-law decay of the EEG Power Spectral Density (PSD). Methods Eighteen patients (n = 18) with mild to moderate mono-hemispheric Middle Cerebral Artery (MCA) ischaemic stroke were retrospectively enrolled for this study. Patients underwent EEG recording in the sub-acute phase (T0) and after 2 months of physical rehabilitation (T1). Sixteen healthy controls (HC; n = 16) matched by age and sex were enrolled as a normative group. SE values and narrow-band PSD were estimated for each recording. We compared SE and band-power between patients and HC, and between the affected (AH) and unaffected hemisphere (UH) at T0 and T1 in patients. Results At T0, stroke patients showed significantly more negative SE values than HC (p = 0.003), reflecting broad-band EEG slowing. Most important, in patients SE over the AH was consistently more negative compared to the UH and showed a renormalization at T1. This SE renormalization significantly correlated with National Institute of Health Stroke Scale (NIHSS) improvement (R = 0.63, p = 0.005). Conclusions SE is a reliable readout of the neurophysiological and clinical alterations occurring after an ischaemic cortical lesion. Significance SE promise to be a robust method to monitor and predict patients’ functional outcome.
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23
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Keser Z, Buchl SC, Seven NA, Markota M, Clark HM, Jones DT, Lanzino G, Brown RD, Worrell GA, Lundstrom BN. Electroencephalogram (EEG) With or Without Transcranial Magnetic Stimulation (TMS) as Biomarkers for Post-stroke Recovery: A Narrative Review. Front Neurol 2022; 13:827866. [PMID: 35273559 PMCID: PMC8902309 DOI: 10.3389/fneur.2022.827866] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 01/31/2022] [Indexed: 01/20/2023] Open
Abstract
Stroke is one of the leading causes of death and disability. Despite the high prevalence of stroke, characterizing the acute neural recovery patterns that follow stroke and predicting long-term recovery remains challenging. Objective methods to quantify and characterize neural injury are still lacking. Since neuroimaging methods have a poor temporal resolution, EEG has been used as a method for characterizing post-stroke recovery mechanisms for various deficits including motor, language, and cognition as well as predicting treatment response to experimental therapies. In addition, transcranial magnetic stimulation (TMS), a form of non-invasive brain stimulation, has been used in conjunction with EEG (TMS-EEG) to evaluate neurophysiology for a variety of indications. TMS-EEG has significant potential for exploring brain connectivity using focal TMS-evoked potentials and oscillations, which may allow for the system-specific delineation of recovery patterns after stroke. In this review, we summarize the use of EEG alone or in combination with TMS in post-stroke motor, language, cognition, and functional/global recovery. Overall, stroke leads to a reduction in higher frequency activity (≥8 Hz) and intra-hemispheric connectivity in the lesioned hemisphere, which creates an activity imbalance between non-lesioned and lesioned hemispheres. Compensatory activity in the non-lesioned hemisphere leads mostly to unfavorable outcomes and further aggravated interhemispheric imbalance. Balanced interhemispheric activity with increased intrahemispheric coherence in the lesioned networks correlates with improved post-stroke recovery. TMS-EEG studies reveal the clinical importance of cortical reactivity and functional connectivity within the sensorimotor cortex for motor recovery after stroke. Although post-stroke motor studies support the prognostic value of TMS-EEG, more studies are needed to determine its utility as a biomarker for recovery across domains including language, cognition, and hemispatial neglect. As a complement to MRI-based technologies, EEG-based technologies are accessible and valuable non-invasive clinical tools in stroke neurology.
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Affiliation(s)
- Zafer Keser
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Samuel C. Buchl
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Nathan A. Seven
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Matej Markota
- Department of Psychiatry, Mayo Clinic, Rochester, MN, United States
| | - Heather M. Clark
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - David T. Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - Giuseppe Lanzino
- Department of Neurosurgery, Mayo Clinic, Rochester, MN, United States
| | - Robert D. Brown
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
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24
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Mirror Therapy Rehabilitation in Stroke: A Scoping Review of Upper Limb Recovery and Brain Activities. Rehabil Res Pract 2022; 2021:9487319. [PMID: 35003808 PMCID: PMC8741383 DOI: 10.1155/2021/9487319] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 12/10/2021] [Indexed: 11/17/2022] Open
Abstract
Background Mirror therapy (MT) has been used as a treatment for various neurological disorders. Recent application of electroencephalogram (EEG) to the MT study allows researchers to gain insight into the changes in brain activity during the therapy. Objective This scoping review is aimed at mapping existing evidence and identifying knowledge gaps about the effects of MT on upper limb recovery and its application for individuals with chronic stroke. Methods and Materials A scoping review through a systematic literature search was conducted using PubMed, CINAHL, PsycINFO, and Scopus databases. Twenty articles published between 2010 and 2020 met the inclusion criteria. The efficacy of MT on upper limb recovery and brain activity during MT were discussed according to the International Classification of Functioning, Disability and Health (ICF). Results A majority of the studies indicated positive effects of MT on upper limb recovery from the body structure/functional domain. All studies used EEG to indicate brain activation during MT. Conclusion MT is a promising intervention for improving upper limb function for individuals with chronic stroke. This review also highlights the need to incorporate EEG into the MT study to capture brain activity and understand the mechanism underlying the therapy.
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25
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Garro F, Chiappalone M, Buccelli S, De Michieli L, Semprini M. Neuromechanical Biomarkers for Robotic Neurorehabilitation. Front Neurorobot 2021; 15:742163. [PMID: 34776920 PMCID: PMC8579108 DOI: 10.3389/fnbot.2021.742163] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 09/22/2021] [Indexed: 02/06/2023] Open
Abstract
One of the current challenges for translational rehabilitation research is to develop the strategies to deliver accurate evaluation, prediction, patient selection, and decision-making in the clinical practice. In this regard, the robot-assisted interventions have gained popularity as they can provide the objective and quantifiable assessment of the motor performance by taking the kinematics parameters into the account. Neurophysiological parameters have also been proposed for this purpose due to the novel advances in the non-invasive signal processing techniques. In addition, other parameters linked to the motor learning and brain plasticity occurring during the rehabilitation have been explored, looking for a more holistic rehabilitation approach. However, the majority of the research done in this area is still exploratory. These parameters have shown the capability to become the “biomarkers” that are defined as the quantifiable indicators of the physiological/pathological processes and the responses to the therapeutical interventions. In this view, they could be finally used for enhancing the robot-assisted treatments. While the research on the biomarkers has been growing in the last years, there is a current need for a better comprehension and quantification of the neuromechanical processes involved in the rehabilitation. In particular, there is a lack of operationalization of the potential neuromechanical biomarkers into the clinical algorithms. In this scenario, a new framework called the “Rehabilomics” has been proposed to account for the rehabilitation research that exploits the biomarkers in its design. This study provides an overview of the state-of-the-art of the biomarkers related to the robotic neurorehabilitation, focusing on the translational studies, and underlying the need to create the comprehensive approaches that have the potential to take the research on the biomarkers into the clinical practice. We then summarize some promising biomarkers that are being under investigation in the current literature and provide some examples of their current and/or potential applications in the neurorehabilitation. Finally, we outline the main challenges and future directions in the field, briefly discussing their potential evolution and prospective.
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Affiliation(s)
- Florencia Garro
- Rehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.,Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy
| | - Michela Chiappalone
- Rehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.,Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy
| | - Stefano Buccelli
- Rehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy
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26
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Almarzouki HZ, Alsulami H, Rizwan A, Basingab MS, Bukhari H, Shabaz M. An Internet of Medical Things-Based Model for Real-Time Monitoring and Averting Stroke Sensors. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:1233166. [PMID: 34745488 PMCID: PMC8566034 DOI: 10.1155/2021/1233166] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 10/09/2021] [Accepted: 10/12/2021] [Indexed: 02/07/2023]
Abstract
In recent years, neurological diseases have become a standout amongst all the other diseases and are the most important reasons for mortality and morbidity all over the world. The current study's aim is to conduct a pilot study for testing the prototype of the designed glove-wearable technology that could detect and analyze the heart rate and EEG for better management and avoiding stroke consequences. The qualitative, clinical experimental method of assessment was explored by incorporating use of an IoT-based real-time assessing medical glove that was designed using heart rate-based and EEG-based sensors. We conducted structured interviews with 90 patients, and the results of the interviews were analyzed by using the Barthel index and were grouped accordingly. Overall, the proportion of patients who followed proper daily heart rate recording behavior went from 46.9% in the first month of the trial to 78.2% after 3-10 months of the interventions. Meanwhile, the percentage of individuals having an irregular heart rate fell from 19.5% in the first month of the trial to 9.1% after 3-10 months of intervention research. In T5, we found that delta relative power decreased by 12.1% and 5.8% compared with baseline at 3 and at 6 months and an average increase was 24.3 ± 0.08. Beta-1 remained relatively steady, while theta relative power grew by 7% and alpha relative power increased by 31%. The T1 hemisphere had greater mean values of delta and theta relative power than the T5 hemisphere. For alpha (p < 0.05) and beta relative power, the opposite pattern was seen. The distinction was statistically significant for delta (p < 0.001), alpha (p < 0.01), and beta-1 (p < 0.05) among T1 and T5 patient groups. In conclusion, our single center-based study found that such IoT-based real-time medical monitoring devices significantly reduce the complexity of real-time monitoring and data acquisition processes for a healthcare provider and thus provide better healthcare management. The emergence of significant risks and controlling mechanisms can be improved by boosting the awareness. Furthermore, it identifies the high-risk factors besides facilitating the prevention of strokes. The EEG-based brain-computer interface has a promising future in upcoming years to avert DALY.
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Affiliation(s)
- Hatim Z. Almarzouki
- Department of Radiology, Faculty of Medicine, King Abdulaziz University Hospital, Jeddah, Saudi Arabia
| | - Hemaid Alsulami
- Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Ali Rizwan
- Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Mohammed S. Basingab
- Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Hatim Bukhari
- Department of Industrial and Systems Engineering, College of Engineering, University of Jeddah, Jeddah, Saudi Arabia
| | - Mohammad Shabaz
- Arba Minch University, Arba Minch, Ethiopia
- Department of Computer Science Engineering, Chandigarh University, Punjab, Ajitgarh, India
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27
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Intrahemispheric EEG: A New Perspective for Quantitative EEG Assessment in Poststroke Individuals. Neural Plast 2021; 2021:5664647. [PMID: 34603441 PMCID: PMC8481048 DOI: 10.1155/2021/5664647] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 08/18/2021] [Accepted: 09/06/2021] [Indexed: 11/17/2022] Open
Abstract
The ratio between slower and faster frequencies of brain activity may change after stroke. However, few studies have used quantitative electroencephalography (qEEG) index of ratios between slower and faster frequencies such as the delta/alpha ratio (DAR) and the power ratio index (PRI; delta + theta/alpha + beta) for investigating the difference between the affected and unaffected hemisphere poststroke. Here, we proposed a new perspective for analyzing DAR and PRI within each hemisphere and investigated the motor impairment-related interhemispheric frequency oscillations. Forty-seven poststroke subjects and twelve healthy controls were included in the study. Severity of upper limb motor impairment was classified according to the Fugl-Meyer assessment in mild/moderate (n = 25) and severe (n = 22). The qEEG indexes (PRI and DAR) were computed for each hemisphere (intrahemispheric index) and for both hemispheres (cerebral index). Considering the cerebral index (DAR and PRI), our results showed a slowing in brain activity in poststroke patients when compared to healthy controls. Only the intrahemispheric PRI index was able to find significant interhemispheric differences of frequency oscillations. Despite being unable to detect interhemispheric differences, the DAR index seems to be more sensitive to detect motor impairment-related frequency oscillations. The intrahemispheric PRI index may provide insights into therapeutic approaches for interhemispheric asymmetry after stroke.
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28
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Hussain I, Park SJ. Quantitative Evaluation of Task-Induced Neurological Outcome after Stroke. Brain Sci 2021; 11:brainsci11070900. [PMID: 34356134 PMCID: PMC8307254 DOI: 10.3390/brainsci11070900] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 07/05/2021] [Accepted: 07/06/2021] [Indexed: 11/16/2022] Open
Abstract
Electroencephalography (EEG) can access ischemic stroke-derived cortical impairment and is believed to be a prospective predictive method for acute stroke prognostics, neurological outcome, and post-stroke rehabilitation management. This study aims to quantify EEG features to understand task-induced neurological declines due to stroke and evaluate the biomarkers to distinguish the ischemic stroke group and the healthy adult group. We investigated forty-eight stroke patients (average age 72.2 years, 62% male) admitted to the rehabilitation center and seventy-five healthy adults (average age 77 years, 31% male) with no history of known neurological diseases. EEG was recorded through frontal, central, temporal, and occipital cortical electrodes (Fz, C1, C2, T7, T8, Oz) using wireless EEG devices and a newly developed data acquisition platform within three months after the appearance of symptoms of ischemic stroke (clinically confirmed). Continuous EEG data were recorded during the consecutive resting, motor (walking and working activities), and cognitive reading tasks. The statistical results showed that alpha, theta, and delta activities are biomarkers classifying the stroke patients and the healthy adults in the motor and cognitive states. DAR and DTR of the stroke group differed significantly from those of the healthy control group during the resting, motor, and cognitive tasks. Using the machine-learning approach, the C5.0 model showed 78% accuracy for the resting state, 89% accuracy in the functional motor walking condition, 84% accuracy in the working condition, and 85% accuracy in the cognitive reading state for classification the stroke group and the control group. This study is expected to be helpful for post-stroke treatment and post-stroke recovery.
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Affiliation(s)
- Iqram Hussain
- Center for Medical Convergence Metrology, Korea Research Institute of Standards and Science, Daejeon 34113, Korea;
- Department of KSB (Knowledge-Converged Super Brain) Convergence Research, Electronics and Telecommunication Research Institute, Daejeon 34129, Korea
- Department of Medical Physics, University of Science & Technology, Daejeon 34113, Korea
| | - Se-Jin Park
- Center for Medical Convergence Metrology, Korea Research Institute of Standards and Science, Daejeon 34113, Korea;
- Department of KSB (Knowledge-Converged Super Brain) Convergence Research, Electronics and Telecommunication Research Institute, Daejeon 34129, Korea
- Department of Medical Physics, University of Science & Technology, Daejeon 34113, Korea
- AI Research Group, Sewon Intelligence, Ltd., Seoul 04512, Korea
- Correspondence:
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Fanciullacci C, Panarese A, Spina V, Lassi M, Mazzoni A, Artoni F, Micera S, Chisari C. Connectivity Measures Differentiate Cortical and Subcortical Sub-Acute Ischemic Stroke Patients. Front Hum Neurosci 2021; 15:669915. [PMID: 34276326 PMCID: PMC8281978 DOI: 10.3389/fnhum.2021.669915] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 06/08/2021] [Indexed: 01/14/2023] Open
Abstract
Brain lesions caused by cerebral ischemia lead to network disturbances in both hemispheres, causing a subsequent reorganization of functional connectivity both locally and remotely with respect to the injury. Quantitative electroencephalography (qEEG) methods have long been used for exploring brain electrical activity and functional connectivity modifications after stroke. However, results obtained so far are not univocal. Here, we used basic and advanced EEG methods to characterize how brain activity and functional connectivity change after stroke. Thirty-three unilateral post stroke patients in the sub-acute phase and ten neurologically intact age-matched right-handed subjects were enrolled. Patients were subdivided into two groups based on lesion location: cortico-subcortical (CS, n = 18) and subcortical (S, n = 15), respectively. Stroke patients were evaluated in the period ranging from 45 days since the acute event (T0) up to 3 months after stroke (T1) with both neurophysiological (resting state EEG) and clinical assessment (Barthel Index, BI) measures, while healthy subjects were evaluated once. Brain power at T0 was similar between the two groups of patients in all frequency bands considered (δ, θ, α, and β). However, evolution of θ-band power over time was different, with a normalization only in the CS group. Instead, average connectivity and specific network measures (Integration, Segregation, and Small-worldness) in the β-band at T0 were significantly different between the two groups. The connectivity and network measures at T0 also appear to have a predictive role in functional recovery (BI T1-T0), again group-dependent. The results obtained in this study showed that connectivity measures and correlations between EEG features and recovery depend on lesion location. These data, if confirmed in further studies, on the one hand could explain the heterogeneity of results so far observed in previous studies, on the other hand they could be used by researchers as biomarkers predicting spontaneous recovery, to select homogenous groups of patients for the inclusion in clinical trials.
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Affiliation(s)
- Chiara Fanciullacci
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.,Unit of Neurorehabilitation, Department of Medical Specialties, University Hospital of Pisa, Pisa, Italy
| | | | - Vincenzo Spina
- Unit of Neurorehabilitation, Department of Medical Specialties, University Hospital of Pisa, Pisa, Italy
| | - Michael Lassi
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Alberto Mazzoni
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Fiorenzo Artoni
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.,Translational Neural Engineering Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Silvestro Micera
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.,Translational Neural Engineering Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Carmelo Chisari
- Unit of Neurorehabilitation, Department of Medical Specialties, University Hospital of Pisa, Pisa, Italy
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30
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Ferreira LO, Mattos BG, Jóia de Mello V, Martins-Filho AJ, da Costa ET, Yamada ES, Hamoy M, Lopes DCF. Increased Relative Delta Bandpower and Delta Indices Revealed by Continuous qEEG Monitoring in a Rat Model of Ischemia-Reperfusion. Front Neurol 2021; 12:645138. [PMID: 33897602 PMCID: PMC8058376 DOI: 10.3389/fneur.2021.645138] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 03/11/2021] [Indexed: 01/14/2023] Open
Abstract
The present study describes the electroencephalographic changes that occur during cerebral ischemia and reperfusion in animals submitted to transient focal cerebral ischemia by middle cerebral artery occlusion (MCAO) for 30 min. For this, male Wistar rats were divided into two groups (n = 6 animals/group): (1) sham (control) group, and (2) ischemic/reperfusion group. The quantitative electroencephalography (qEEG) was recorded during the ischemic and immediate reperfusion (acute) phases, and then once a day for 7 days after the MCAO (subacute phase). The acute phase was characterized by a marked increase in the relative delta wave band power (p < 0.001), with a smaller, but significant increase in the relative alpha wave bandpower in the ischemic stroke phase, in comparison with the control group (p = 0.0054). In the immediate reperfusion phase, however, there was an increase in the theta, alpha, and beta waves bandpower (p < 0.001), but no alteration in the delta waves (p = 0.9984), in comparison with the control group. We also observed high values in the delta/theta ratio (DTR), the delta/alpha ratio (DAR), and the (delta+theta)/(alpha+beta) ratio (DTABR) indices during the ischemia (p < 0.05), with a major reduction in the reperfusion phase. In the subacute phase, the activity of all the waves was lower than that of the control group (p < 0.05), although the DTR, DAR, and DTABR indices remained relatively high. In conclusion, early and accurate identification of decreased delta wave bandpower, DTR, DAR, and DTABR indices, and an increase in the activity of other waves in the immediate reperfusion phase may represent an important advance for the recognition of the effectiveness of reperfusion therapy.
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Affiliation(s)
- Luan Oliveira Ferreira
- Laboratory of Experimental Neuropathology, João de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | - Bruna Gerrits Mattos
- Laboratory of Experimental Neuropathology, João de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | - Vanessa Jóia de Mello
- Laboratory of Pharmacology and Toxicology of Natural Products, Institute Biological Science, Federal University of Pará, Belém, Brazil
| | | | - Edmar Tavares da Costa
- Laboratory of Experimental Neuropathology, João de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | - Elizabeth Sumi Yamada
- Laboratory of Experimental Neuropathology, João de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | - Moisés Hamoy
- Laboratory of Pharmacology and Toxicology of Natural Products, Institute Biological Science, Federal University of Pará, Belém, Brazil
| | - Dielly Catrina Favacho Lopes
- Laboratory of Experimental Neuropathology, João de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
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31
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Predicting stroke severity with a 3-min recording from the Muse portable EEG system for rapid diagnosis of stroke. Sci Rep 2020; 10:18465. [PMID: 33116187 PMCID: PMC7595199 DOI: 10.1038/s41598-020-75379-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 10/09/2020] [Indexed: 12/13/2022] Open
Abstract
In this study, we demonstrated the use of low-cost portable electroencephalography (EEG) as a method for prehospital stroke diagnosis. We used a portable EEG system to record data from 25 participants, 16 had acute ischemic stroke events, and compared the results to age-matched controls that included stroke mimics. Delta/alpha ratio (DAR), (delta + theta)/(alpha + beta) ratio (DBATR) and pairwise-derived Brain Symmetry Index (pdBSI) were investigated, as well as head movement using the on-board accelerometer and gyroscope. We then used machine learning to distinguish between different subgroups. DAR and DBATR increased in ischemic stroke patients with increasing stroke severity (p = 0.0021, partial η2 = 0.293; p = 0.01, partial η2 = 0.234). Also, pdBSI decreased in low frequencies and increased in high frequencies in patients who had a stroke (p = 0.036, partial η2 = 0.177). Using classification trees, we were able to distinguish moderate to severe stroke patients and from minor stroke and controls, with a 63% sensitivity, 86% specificity and accuracy of 76%. There are significant differences in DAR, DBATR, and pdBSI between patients with ischemic stroke when compared to controls, and these effects scale with severity. We have shown the utility of a low-cost portable EEG system to aid in patient triage and diagnosis as an early detection tool.
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32
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Tscherpel C, Dern S, Hensel L, Ziemann U, Fink GR, Grefkes C. Brain responsivity provides an individual readout for motor recovery after stroke. Brain 2020; 143:1873-1888. [PMID: 32375172 PMCID: PMC7296846 DOI: 10.1093/brain/awaa127] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 01/30/2020] [Accepted: 03/01/2020] [Indexed: 12/17/2022] Open
Abstract
Promoting the recovery of motor function and optimizing rehabilitation strategies for stroke patients is closely associated with the challenge of individual prediction. To date, stroke research has identified critical pathophysiological neural underpinnings at the cellular level as well as with regard to network reorganization. However, in order to generate reliable readouts at the level of individual patients and thereby realize translation from bench to bedside, we are still in a need for innovative methods. The combined use of transcranial magnetic stimulation (TMS) and EEG has proven powerful to record both local and network responses at an individual's level. To elucidate the potential of TMS-EEG to assess motor recovery after stroke, we used neuronavigated TMS-EEG over ipsilesional primary motor cortex (M1) in 28 stroke patients in the first days after stroke. Twenty-five of these patients were reassessed after >3 months post-stroke. In the early post-stroke phase (6.7 ± 2.5 days), the TMS-evoked EEG responses featured two markedly different response morphologies upon TMS to ipsilesional M1. In the first group of patients, TMS elicited a differentiated and sustained EEG response with a series of deflections sequentially involving both hemispheres. This response type resembled the patterns of bilateral activation as observed in the healthy comparison group. By contrast, in a subgroup of severely affected patients, TMS evoked a slow and simplified local response. Quantifying the TMS-EEG responses in the time and time-frequency domain revealed that stroke patients exhibited slower and simple responses with higher amplitudes compared to healthy controls. Importantly, these patterns of activity changes after stroke were not only linked to the initial motor deficit, but also to motor recovery after >3 months post-stroke. Thus, the data revealed a substantial impairment of local effects as well as causal interactions within the motor network early after stroke. Additionally, for severely affected patients with absent motor evoked potentials and identical clinical phenotype, TMS-EEG provided differential response patterns indicative of the individual potential for recovery of function. Thereby, TMS-EEG extends the methodological repertoire in stroke research by allowing the assessment of individual response profiles.
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Affiliation(s)
- Caroline Tscherpel
- Medical Faculty, University of Cologne, and Department of Neurology, University Hospital Cologne, Cologne, Germany
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Jülich, Jülich, Germany
| | - Sebastian Dern
- Medical Faculty, University of Cologne, and Department of Neurology, University Hospital Cologne, Cologne, Germany
| | - Lukas Hensel
- Medical Faculty, University of Cologne, and Department of Neurology, University Hospital Cologne, Cologne, Germany
| | - Ulf Ziemann
- Department of Neurology and Stroke, and Hertie Institute for Clinical Brain Research, Eberhard-Karls-University Tübingen, Tübingen, Germany
| | - Gereon R Fink
- Medical Faculty, University of Cologne, and Department of Neurology, University Hospital Cologne, Cologne, Germany
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Jülich, Jülich, Germany
| | - Christian Grefkes
- Medical Faculty, University of Cologne, and Department of Neurology, University Hospital Cologne, Cologne, Germany
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Jülich, Jülich, Germany
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33
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Cassidy JM, Wodeyar A, Wu J, Kaur K, Masuda AK, Srinivasan R, Cramer SC. Low-Frequency Oscillations Are a Biomarker of Injury and Recovery After Stroke. Stroke 2020; 51:1442-1450. [PMID: 32299324 DOI: 10.1161/strokeaha.120.028932] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Background and Purpose- Low-frequency oscillations reflect brain injury but also contribute to normal behaviors. We examined hypotheses relating electroencephalography measures, including low-frequency oscillations, to injury and motor recovery poststroke. Methods- Patients with stroke completed structural neuroimaging, a resting-state electroencephalography recording and clinical testing. A subset admitted to an inpatient rehabilitation facility also underwent serial electroencephalography recordings. The relationship that electroencephalography measures (power and coherence with leads overlying ipsilesional primary motor cortex [iM1]) had with injury and motor status was assessed, focusing on delta (1-3 Hz) and high-beta (20-30 Hz) bands. Results- Across all patients (n=62), larger infarct volume was related to higher delta band power in bilateral hemispheres and to higher delta band coherence between iM1 and bilateral regions. In chronic stroke, higher delta power bilaterally correlated with better motor status. In subacute stroke, higher delta coherence between iM1 and bilateral areas correlated with poorer motor status. These coherence findings were confirmed in serial recordings from 18 patients in an inpatient rehabilitation facility. Here, interhemispheric coherence between leads overlying iM1 and contralesional M1 was elevated at inpatient rehabilitation facility admission compared with healthy controls (n=22), declining to control levels over time. Decreases in interhemispheric coherence between iM1 and contralesional M1 correlated with better motor recovery. Conclusions- Delta band coherence with iM1 related to greater injury and poorer motor status subacutely, while delta band power related to greater injury and better motor status chronically. Low-frequency oscillations reflect both injury and recovery after stroke and may be useful biomarkers in stroke recovery and rehabilitation.
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Affiliation(s)
- Jessica M Cassidy
- From the Department of Allied Health Sciences, University of North Carolina, Chapel Hill (J.M.C.)
| | - Anirudh Wodeyar
- Department of Cognitive Sciences (A.W., R.S.), University of California, Irvine
| | - Jennifer Wu
- Department of Neurology (J.W., K.K., A.K.M.), University of California, Irvine.,Department of Physical Medicine & Rehabilitation (J.W.), University of California, Irvine
| | - Kiranjot Kaur
- Department of Neurology (J.W., K.K., A.K.M.), University of California, Irvine
| | - Ashley K Masuda
- Department of Neurology (J.W., K.K., A.K.M.), University of California, Irvine
| | - Ramesh Srinivasan
- Department of Cognitive Sciences (A.W., R.S.), University of California, Irvine.,Department of Biomedical Engineering, University of California, Irvine (R.S.)
| | - Steven C Cramer
- Department of Neurology, University of California, Los Angeles (S.C.C.).,California Rehabilitation Institute, Los Angeles (S.C.C.)
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34
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Saes M, Zandvliet SB, Andringa AS, Daffertshofer A, Twisk JWR, Meskers CGM, van Wegen EEH, Kwakkel G. Is Resting-State EEG Longitudinally Associated With Recovery of Clinical Neurological Impairments Early Poststroke? A Prospective Cohort Study. Neurorehabil Neural Repair 2020; 34:389-402. [PMID: 32249674 DOI: 10.1177/1545968320905797] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Background. The time course of cortical activation and its relation with clinical measures may elucidate mechanisms underlying spontaneous neurobiological recovery after stroke. Objective. We aimed to investigate (1) the time course of cortical activation as revealed by EEG-based spectral characteristics during awake rest and (2) the development of these spectral characteristics in relation to global neurological and upper-limb motor recovery in the first 6 months poststroke. Methods. Resting-state EEG was measured serially in 41 patients after a first-ever ischemic stroke, within 3 and at 5, 12, and 26 weeks poststroke. We computed the brain symmetry index (BSI) and directional BSI (BSIdir) over different frequency bands (1-25 Hz, delta, theta) and delta/alpha ratio (DAR). The National Institutes of Health Stroke Scale (NIHSS) and Fugl-Meyer motor assessment of the upper extremity (FM-UE) were determined as clinical reflections of spontaneous neurobiological recovery. Longitudinal changes in spectral characteristics and within- and between-subject associations with NIHSS and FM-UE were analyzed with linear mixed models. Results. Spectral characteristics showed a gradual normalization over time, within and beyond 12 weeks poststroke. Significant within- and between-subject associations with NIHSS were found for DAR of the affected hemisphere (DARAH) and BSIdirdelta. BSIdirdelta also demonstrated significant within- and between-subject associations with FM-UE. Conclusions. Changes in spectral characteristics are not restricted to the time window of recovery of clinical neurological impairments. The present study suggests that decreasing DARAH and BSIdirdelta reflect improvement of global neurological impairments, whereas BSIdirdelta was also specifically associated with upper-limb motor recovery early poststroke.
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Affiliation(s)
- Mique Saes
- Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,These authors are members of The American Society of Neurorehabilitation
| | | | - Aukje S Andringa
- Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Andreas Daffertshofer
- Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam, Netherlands
| | - Jos W R Twisk
- Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Carel G M Meskers
- Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | - Gert Kwakkel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.,Amsterdam Rehabilitation Research Centre, Reade, Amsterdam, Netherlands.,These authors are members of The American Society of Neurorehabilitation
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35
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Micera S, Caleo M, Chisari C, Hummel FC, Pedrocchi A. Advanced Neurotechnologies for the Restoration of Motor Function. Neuron 2020; 105:604-620. [PMID: 32078796 DOI: 10.1016/j.neuron.2020.01.039] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 11/15/2019] [Accepted: 01/27/2020] [Indexed: 01/23/2023]
Abstract
Stroke is one of the leading causes of long-term disability. Advanced technological solutions ("neurotechnologies") exploiting robotic systems and electrodes that stimulate the nervous system can increase the efficacy of stroke rehabilitation. Recent studies on these approaches have shown promising results. However, a paradigm shift in the development of new approaches must be made to significantly improve the clinical outcomes of neurotechnologies compared with those of traditional therapies. An "evolutionary" change can occur only by understanding in great detail the basic mechanisms of natural stroke recovery and technology-assisted neurorehabilitation. In this review, we first describe the results achieved by existing neurotechnologies and highlight their current limitations. In parallel, we summarize the data available on the mechanisms of recovery from electrophysiological, behavioral, and anatomical studies in humans and rodent models. Finally, we propose new approaches for the effective use of neurotechnologies in stroke survivors, as well as in people with other neurological disorders.
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Affiliation(s)
- Silvestro Micera
- The Biorobotics Institute and Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa, Italy; Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
| | - Matteo Caleo
- Department of Biomedical Sciences, University of Padova, Padova, Italy; Institute of Neuroscience, National Research Council (CNR), Pisa, Italy
| | - Carmelo Chisari
- Neurorehabilitation Section, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Friedhelm C Hummel
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland; Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, 1951 Sion, Switzerland; Clinical Neuroscience, University of Geneva Medical School, 1202 Geneva, Switzerland
| | - Alessandra Pedrocchi
- Neuroengineering and Medical Robotics Laboratory NearLab, Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
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36
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Acute Phase Neuronal Activity for the Prognosis of Stroke Recovery. Neural Plast 2019; 2019:1971875. [PMID: 31611914 PMCID: PMC6755296 DOI: 10.1155/2019/1971875] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Revised: 05/17/2019] [Accepted: 06/24/2019] [Indexed: 11/17/2022] Open
Abstract
Strokes causing similar lesions and clinical states can be followed by diverse regains of neurological functions, indicating that the clinical recovery can depend on individual modulating factors. A promising line to disclose these factors, to finally open new therapeutic strategies, is to search for individual indices of recovery prognosis. Here, we pursued on strengthening the value of acute phase electrophysiological biomarkers for poststroke functional recovery in a wide group of patients. We enrolled 120 patients affected by a monohemispheric stroke within the middle cerebral artery territory (70 left and 50 right damages) and collected the NIH stroke scale (NIHSS) score in the acute phase (T0, median 4 days) and chronic follow-up (T1, median 6 months). At T0, we executed electrophysiological noninvasive assessment (19-channel electroencephalography (EEG) or 28 channels per side magnetoencephalography (MEG)) of brain activity at rest by means of band powers in the contra- and ipsilesional hemispheres (CLH, ILH) or the homologous area symmetry (HArS). Low-band (2-6 Hz) HArS entered the regression model for predicting the stabilized clinical state (p < 0.001), with bilateral impairment correlated with a poor outcome. Present data strengthen the fact that low-band impairment of homologous ipsi- and contralesional hemispheric regions in the acute stroke indicate a negative prognosis of clinical recovery.
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37
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Leemburg S, Gao B, Cam E, Sarnthein J, Bassetti CL. Power spectrum slope is related to motor function after focal cerebral ischemia in the rat. Sleep 2019; 41:5079131. [PMID: 30165388 DOI: 10.1093/sleep/zsy132] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Indexed: 11/14/2022] Open
Abstract
Electroencephalography (EEG) changes across vigilance states have been observed after ischemic stroke in patients and experimental stroke models, but their relation to functional recovery remains unclear. Here, we evaluate motor function, as measured by single pellet reaching (SPR), as well as local EEG changes in nonrapid eye movement (NREM), rapid eye movement (REM), and wakefulness during a 30 day recovery period after middle cerebral artery occlusion or sham surgery in rats. Small cortical infarcts resulted in poor SPR performance and induced widespread changes in EEG spectra in the ipsilesional hemisphere in all vigilance states, without causing major changes in sleep-wake architecture. Ipsilesional 1-4 Hz power was increased after stroke, whereas power in higher frequencies was reduced, resulting in a steeper slope of the power spectrum. Microelectrode array analysis of ipsilesional M1 showed that these spectral changes were present on the microelectrode level throughout M1 and were not related to increased synchronization between electrodes. Spectrum slope was significantly correlated with poststroke motor function and may thus be a useful readout of recovery-related plasticity.
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Affiliation(s)
- Susan Leemburg
- Department of Neurology, University Hospital Zurich, Zürich, Switzerland
| | - Bo Gao
- Department of Neurology, University Hospital Zurich, Zürich, Switzerland.,Department of Neurology, Inselspital, University Hospital, Bern, Switzerland
| | - Ertugrul Cam
- Department of Neurology, University Hospital Zurich, Zürich, Switzerland.,Department of Neurology, Inselspital, University Hospital, Bern, Switzerland
| | - Johannes Sarnthein
- Department of Neurology, University Hospital Zurich, Zürich, Switzerland
| | - Claudio L Bassetti
- Department of Neurology, University Hospital Zurich, Zürich, Switzerland.,Department of Neurology, Inselspital, University Hospital, Bern, Switzerland
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38
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Slowing is slowing: Delayed neural responses to words are linked to abnormally slow resting state activity in primary progressive aphasia. Neuropsychologia 2019; 129:331-347. [PMID: 31029594 DOI: 10.1016/j.neuropsychologia.2019.04.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2018] [Revised: 04/12/2019] [Accepted: 04/13/2019] [Indexed: 11/22/2022]
Abstract
Neurodegenerative disorders are often characterized by neuronal "slowing," which may be assessed in different ways. In the present study, we examined the latency of neural responses to linguistic stimuli in participants diagnosed with primary progressive aphasia (PPA), as well as changes in the power spectra of resting state activity, both measured with MEG. Compared to both age-matched and younger controls, patients with PPA showed a delayed latency of 8-30 Hz event-related desynchronization (ERD) in response to semantic anomalies. In addition, resting-state MEG revealed increased power in the lower frequency delta and theta bands, but decreased activity in the higher alpha and beta bands. The task-induced and spontaneous measures of neural dynamics were related, such that increased peak latencies in response to words were correlated with a shift of spontaneous oscillatory dynamics towards lower frequencies. In contrast, older controls showed similar task related ERD latencies as younger controls, but also "speeding" of spontaneous activity, i.e. a shift towards faster frequencies. In PPA patients both increased peak latencies on task and increased slow oscillations at rest were associated with less accurate performance on the language task and poorer performance on offline cognitive measures, beyond variance accounted for by structural atrophy. A mediation analysis indicated that increased theta power accounted for the relationship between delayed electrophysiological responses and reduced accuracy in PPA patients. These results indicate that the neuropathological changes in PPA result in slowing of both task-related and spontaneous neuronal activity, linked to functional decline, whereas the speeding of spontaneous activity in healthy aging seems to have a protective or compensatory effect.
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39
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Comparison of electroencephalogram (EEG) response to MDPV versus the hallucinogenic drugs MK-801 and ketamine in rats. Exp Neurol 2019; 313:26-36. [DOI: 10.1016/j.expneurol.2018.12.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2018] [Revised: 11/22/2018] [Accepted: 12/02/2018] [Indexed: 12/20/2022]
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40
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Zappasodi F, Tecchio F, Marzetti L, Pizzella V, Di Lazzaro V, Assenza G. Longitudinal quantitative electroencephalographic study in mono-hemispheric stroke patients. Neural Regen Res 2019; 14:1237-1246. [PMID: 30804255 PMCID: PMC6425833 DOI: 10.4103/1673-5374.251331] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The identification of individual factors modulating clinical recovery after a stroke is fundamental to personalize the therapeutic intervention to enhance the final clinical outcome. In this framework, electrophysiological factors are promising since are more directly related to neuroplasticity, which supports recovery in stroke patients, than neurovascular factors. In this retrospective observational study, we investigated brain neuronal activity assessed via spectral features and Higuchi’s fractal dimension (HFD) of electroencephalographic signals in acute phase (2–10 days from symptom onset, T0) and sub-acute phase (2.5 months, T1) in 24 patients affected by unilateral middle cerebral artery stroke. Longitudinal assessment of the clinical deficits was performed using the National Institutes of Health Stroke Scale (NIHSS), together with the effective recovery calculated as the ratio between difference of NIHSS at T0 and T1 over the NIHSS value at T0. We observed that delta and alpha band electroencephalographic signal power changed between the two phases in both the hemispheres ipsilateral (ILH) and contralateral (CHL) to the lesion. Moreover, at T0, bilateral higher delta band power correlated with worse clinical conditions (Spearman’s rs = 0.460, P = 0.027 for ILH and rs = 0.508, P = 0.013 for CLH), whereas at T1 this occurred only for delta power in ILH (rs = 0.411, P = 0.046) and not for CHL. Inter-hemispheric difference (ILH vs. CLH) of alpha power in patients was lower at T0 than at T1 (P = 0.020). HFD at T0 was lower than at T1 (P = 0.005), and at both phases, ILH HFD was lower than CLH HFD (P = 0.020). These data suggest that inter-hemispheric low band asymmetry and fractal dimension changes from the acute to the sub-acute phase are sensitive to neuroplasticity processes which subtend clinical recovery. The study protocol was approved by the Bioethical Committee of Ospedale San Giovanni Calibita Fatebenefretelli (No. 40/2011) on July 14, 2011.
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Affiliation(s)
- Filippo Zappasodi
- Department of Neuroscience, Imaging and Clinical Sciences and Institute for Advanced Biomedical Imaging, "G. D'Annunzio" University, Chieti, Italy
| | - Franca Tecchio
- Laboratory of Electrophysiology for Translational NeuroScience (LET'S), ISTC-CNR, and Fondazione Policlinico Gemelli IRCCS, Rome, Italy
| | - Laura Marzetti
- Department of Neuroscience, Imaging and Clinical Sciences and Institute for Advanced Biomedical Imaging, "G. D'Annunzio" University, Chieti, Italy
| | - Vittorio Pizzella
- Department of Neuroscience, Imaging and Clinical Sciences and Institute for Advanced Biomedical Imaging, "G. D'Annunzio" University, Chieti, Italy
| | - Vincenzo Di Lazzaro
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Giovanni Assenza
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, Università Campus Bio-Medico di Roma, Rome, Italy
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41
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Compressibility of High-Density EEG Signals in Stroke Patients. SENSORS 2018; 18:s18124107. [PMID: 30477168 PMCID: PMC6308673 DOI: 10.3390/s18124107] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Revised: 11/15/2018] [Accepted: 11/18/2018] [Indexed: 02/05/2023]
Abstract
Stroke is a critical event that causes the disruption of neural connections. There is increasing evidence that the brain tries to reorganize itself and to replace the damaged circuits, by establishing compensatory pathways. Intra- and extra-cellular currents are involved in the communication between neurons and the macroscopic effects of such currents can be detected at the scalp through electroencephalographic (EEG) sensors. EEG can be used to study the lesions in the brain indirectly, by studying their effects on the brain electrical activity. The primary goal of the present work was to investigate possible asymmetries in the activity of the two hemispheres, in the case one of them is affected by a lesion due to stroke. In particular, the compressibility of High-Density-EEG (HD-EEG) recorded at the two hemispheres was investigated since the presence of the lesion is expected to impact on the regularity of EEG signals. The secondary objective was to evaluate if standard low density EEG is able to provide such information. Eighteen patients with unilateral stroke were recruited and underwent HD-EEG recording. Each EEG signal was compressively sensed, using Block Sparse Bayesian Learning, at increasing compression rate. The two hemispheres showed significant differences in the compressibility of EEG. Signals acquired at the electrode locations of the affected hemisphere showed a better reconstruction quality, quantified by the Structural SIMilarity index (SSIM), than the EEG signals recorded at the healthy hemisphere (p < 0.05), for each compression rate value. The presence of the lesion seems to induce an increased regularity in the electrical activity of the brain, thus an increased compressibility.
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42
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Rosanova M, Fecchio M, Casarotto S, Sarasso S, Casali AG, Pigorini A, Comanducci A, Seregni F, Devalle G, Citerio G, Bodart O, Boly M, Gosseries O, Laureys S, Massimini M. Sleep-like cortical OFF-periods disrupt causality and complexity in the brain of unresponsive wakefulness syndrome patients. Nat Commun 2018; 9:4427. [PMID: 30356042 PMCID: PMC6200777 DOI: 10.1038/s41467-018-06871-1] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 10/01/2018] [Indexed: 12/21/2022] Open
Abstract
Unresponsive wakefulness syndrome (UWS) patients may retain intact portions of the thalamocortical system that are spontaneously active and reactive to sensory stimuli but fail to engage in complex causal interactions, resulting in loss of consciousness. Here, we show that loss of brain complexity after severe injuries is due to a pathological tendency of cortical circuits to fall into silence (OFF-period) upon receiving an input, a behavior typically observed during sleep. Spectral and phase domain analysis of EEG responses to transcranial magnetic stimulation reveals the occurrence of OFF-periods in the cortex of UWS patients (N = 16); these events never occur in healthy awake individuals (N = 20) but are similar to those detected in healthy sleeping subjects (N = 8). Crucially, OFF-periods impair local causal interactions, and prevent the build-up of global complexity in UWS. Our findings link potentially reversible local events to global brain dynamics that are relevant for pathological loss and recovery of consciousness. Many brain-injured patients retain large cortical islands that are intact, active and reactive but blocked in a state of low complexity, leading to unconsciousness. Here, the authors show that this loss of complexity is due to the pathological engagement of sleep-like neuronal mechanisms.
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Affiliation(s)
- M Rosanova
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, 20157, Italy.,Fondazione Europea per la Ricerca Biomedica Onlus, Milan, 20063, Italy.,Neurointensive Care Unit, ASTT Grande Ospedale Metropolitano Niguarda, Milan, 20162, Italy
| | - M Fecchio
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, 20157, Italy
| | - S Casarotto
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, 20157, Italy.,IRCCS Fondazione Don Gnocchi, Milan, 20149, Italy
| | - S Sarasso
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, 20157, Italy
| | - A G Casali
- Instituto de Ciência e Tecnologia, Universidade Federal de São Paulo, Sao Jose dos Campos, 12231-280, Brazil
| | - A Pigorini
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, 20157, Italy
| | - A Comanducci
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, 20157, Italy
| | - F Seregni
- Department of Paediatrics, Cambridge University Hospital NHS Foundation Trust, Cambridge, CB2 0QQ, UK
| | - G Devalle
- IRCCS Fondazione Don Gnocchi, Milan, 20149, Italy
| | - G Citerio
- Scuola di Medicina e Chirurgia, University of Milan Bicocca, Milan, 20126, Italy
| | - O Bodart
- GIGA-consciousness, Coma Science Group, University and University Hospital of Liège, Liège, 4000, Belgium
| | - M Boly
- Department of Neurology, University of Wisconsin, Madison, WI, 53705, USA.,Department of Psychiatry, University of Wisconsin, Madison, WI, 53719, USA
| | - O Gosseries
- GIGA-consciousness, Coma Science Group, University and University Hospital of Liège, Liège, 4000, Belgium
| | - S Laureys
- GIGA-consciousness, Coma Science Group, University and University Hospital of Liège, Liège, 4000, Belgium
| | - M Massimini
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, 20157, Italy. .,IRCCS Fondazione Don Gnocchi, Milan, 20149, Italy.
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43
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Sun C, Yang F, Wang C, Wang Z, Zhang Y, Ming D, Du J. Mutual Information-Based Brain Network Analysis in Post-stroke Patients With Different Levels of Depression. Front Hum Neurosci 2018; 12:285. [PMID: 30065639 PMCID: PMC6056615 DOI: 10.3389/fnhum.2018.00285] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Accepted: 06/25/2018] [Indexed: 11/15/2022] Open
Abstract
Post-stroke depression (PSD) is the most common stroke-related emotional disorder, and it severely affects the recovery process. However, more than half cases are not correctly diagnosed. This study was designed to develop a new method to assess PSD using EEG signal to analyze the specificity of PSD patients' brain network. We have 107 subjects attended in this study (72 stabilized stroke survivors and 35 non-depressed healthy subjects). A Hamilton Depression Rating Scale (HDRS) score was determined for all subjects before EEG data collection. According to HDRS score, the 72 patients were divided into 3 groups: post-stroke non-depression (PSND), post-stroke mild depression (PSMD) and post-stroke depression (PSD). Mutual information (MI)-based graph theory was used to analyze brain network connectivity. Statistical analysis of brain network characteristics was made with a threshold of 10-30% of the strongest MIs. The results showed significant weakened interhemispheric connections and lower clustering coefficient in post-stroke depressed patients compared to those in healthy controls. Stroke patients showed a decreasing trend in the connection between the parietal-occipital and the frontal area as the severity of the depression increased. PSD subjects showed abnormal brain network connectivity and network features based on EEG, suggesting that MI-based brain network may have the potential to assess the severity of depression post stroke.
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Affiliation(s)
- Changcheng Sun
- Rehabilitation Medical Department, Tianjin Union Medical Centre, Tianjin, China
| | - Fei Yang
- Department of Health and Exercise Science, Tianjin University of Sport, Tianjin, China
| | - Chunfang Wang
- Rehabilitation Medical Department, Tianjin Union Medical Centre, Tianjin, China
| | - Zhonghan Wang
- Rehabilitation Medical Department, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Ying Zhang
- Rehabilitation Medical Department, Tianjin Union Medical Centre, Tianjin, China
| | - Dong Ming
- Department of Biomedical Engineering, College of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin, China
| | - Jingang Du
- Rehabilitation Medical Department, Tianjin Union Medical Centre, Tianjin, China
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