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Rubega M, Facca M, Curci V, Sparacino G, Molteni F, Guanziroli E, Masiero S, Formaggio E, Del Felice A. EEG Microstates as a Signature of Hemispheric Lateralization in Stroke. Brain Topogr 2024; 37:475-478. [PMID: 37195492 PMCID: PMC10191079 DOI: 10.1007/s10548-023-00967-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 04/23/2023] [Indexed: 05/18/2023]
Abstract
Stroke recovery trajectories vary substantially. The need for tracking and prognostic biomarkers in stroke is utmost for prognostic and rehabilitative goals: electroencephalography (EEG) advanced signal analysis may provide useful tools toward this aim. EEG microstates quantify changes in configuration of neuronal generators of short-lasting periods of coordinated synchronized communication within large-scale brain networks: this feature is expected to be impaired in stroke. To characterize the spatio-temporal signatures of EEG microstates in stroke survivors in the acute/subacute phase, EEG microstate analysis was performed in 51 first-ever ischemic stroke survivors [(28-82) years, 24 with right hemisphere (RH) lesion] who underwent a resting-state EEG recording in the acute and subacute phase (from 48 h up to 42 days after the event). Microstates were characterized based on 4 parameters: global explained variance (GEV), mean duration, occurrences per second, and percentage of coverage. Wilcoxon Rank Sum tests were performed to compare features of each microstate across the two groups [i.e., left hemisphere (LH) and right hemisphere (RH) stroke survivors]. The canonical microstate map D, characterized by a mostly frontal topography, displayed greater GEV, occurrence per second, and percentage of coverage in LH than in RH stroke survivors (p < 0.05). The EEG microstate map B, with a left-frontal to right-posterior topography, and F, with an occipital-to-frontal topography, exhibited a greater GEV in RH than in LH stroke survivors (p = 0.015). EEG microstates identified specific topographic maps which characterize stroke survivors' lesioned hemisphere in the acute and early subacute phase. Microstate features offer an additional tool to identify different neural reorganization.
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Affiliation(s)
- Maria Rubega
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128, Padova, Italy
| | - Massimiliano Facca
- Padova Neuroscience Center, University of Padova, Via Orus 2, 35131, Padova, Italy
| | - Vittorio Curci
- Department of Information Engineering, University of Padova, via Gradenigo 6/b, 35128, Padova, Italy
| | - Giovanni Sparacino
- Department of Information Engineering, University of Padova, via Gradenigo 6/b, 35128, Padova, Italy
| | - Franco Molteni
- Villa Beretta Rehabilitation Center, Valduce Hospital, Via Sauro 17, 23845, Costa Masnaga, Lecco, Italy
| | - Eleonora Guanziroli
- Villa Beretta Rehabilitation Center, Valduce Hospital, Via Sauro 17, 23845, Costa Masnaga, Lecco, Italy
| | - Stefano Masiero
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128, Padova, Italy
- Padova Neuroscience Center, University of Padova, Via Orus 2, 35131, Padova, Italy
| | - Emanuela Formaggio
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128, Padova, Italy
- Padova Neuroscience Center, University of Padova, Via Orus 2, 35131, Padova, Italy
| | - Alessandra Del Felice
- Padova Neuroscience Center, University of Padova, Via Orus 2, 35131, Padova, Italy.
- Department of Neuroscience, Section of Neurology, University of Padova, Via Giustiniani 3, 35128, Padova, Italy.
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Paramento M, Rubega M, Di Marco R, Contessa P, Agostini M, Cantele F, Masiero S, Formaggio E. Experimental protocol to investigate cortical, muscular and body representation alterations in adolescents with idiopathic scoliosis. PLoS One 2023; 18:e0292864. [PMID: 37824513 PMCID: PMC10569634 DOI: 10.1371/journal.pone.0292864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 10/02/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND Adolescent idiopathic scoliosis (AIS) is the most common form of scoliosis. AIS is a three-dimensional morphological spinal deformity that affects approximately 1-3% of adolescents. Not all factors related to the etiology of AIS have yet been identified. OBJECTIVE The primary aim of this experimental protocol is to quantitatively investigate alterations in body representation in AIS, and to quantitatively and objectively track the changes in body sensorimotor representation due to treatment. METHODS Adolescent girls with a confirmed diagnosis of mild (Cobb angle: 10°-20°) or moderate (21°-35°) scoliosis as well as age and sex-matched controls will be recruited. Participants will be asked to perform a 6-min upright standing and two tasks-named target reaching and forearm bisection task. Eventually, subjects will fill in a self-report questionnaire and a computer-based test to assess body image. This evaluation will be repeated after 6 and 12 months of treatment (i.e., partial or full-time brace and physiotherapy corrective postural exercises). RESULTS We expect that theta brain rhythm in the central brain areas, alpha brain rhythm lateralization and body representation will change over time depending on treatment and scoliosis progression as a compensatory strategy to overcome a sensorimotor dysfunction. We also expect asymmetric activation of the trunk muscle during reaching tasks and decreased postural stability in AIS. CONCLUSIONS Quantitatively assess the body representation at different time points during AIS treatment may provide new insights on the pathophysiology and etiology of scoliosis.
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Affiliation(s)
- Matilde Paramento
- Department of Neurosciences, Section of Rehabilitation, University of Padova, Padova, Italy
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Maria Rubega
- Department of Neurosciences, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Roberto Di Marco
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | - Paola Contessa
- Orthopedic Rehabilitation Unit, Padova University Hospital, Padova, Italy
| | - Michela Agostini
- Department of Neurosciences, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Francesca Cantele
- Department of Neurosciences, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Stefano Masiero
- Department of Neurosciences, Section of Rehabilitation, University of Padova, Padova, Italy
- Orthopedic Rehabilitation Unit, Padova University Hospital, Padova, Italy
- Ospedale Riabilitativo di Alta Specializzazione di Motta di Livenza, Motta di Livenza, Treviso, Italy
| | - Emanuela Formaggio
- Department of Neurosciences, Section of Rehabilitation, University of Padova, Padova, Italy
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Bertuccelli M, Rubega M, Cantele F, Favero C, Ermolao A, Formaggio E, Masiero S. Body-Related Attentional Bias in Adolescents Affected by Idiopathic Scoliosis. Eur J Investig Health Psychol Educ 2023; 13:1909-1919. [PMID: 37754477 PMCID: PMC10527921 DOI: 10.3390/ejihpe13090138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 09/04/2023] [Accepted: 09/14/2023] [Indexed: 09/28/2023] Open
Abstract
Attentional biases toward body-related information increase body dissatisfaction. This can lead at-risk populations to develop psychopathologies. This phenomenon has not been extensively studied in girls affected by idiopathic scoliosis. This work aimed to study the cognitive processes that could contribute to the worsening and maintaining of body image disorders in adolescent idiopathic scoliosis. Twenty-eight girls were recruited and tested for body image dissatisfaction through the Scoliosis-Research-Society-22-revised (SRS-22r) questionnaire. Attentional biases towards disease-related body parts were assessed using a computerized visual match-to-sample task: girls were asked to answer as fast and accurately as possible to find the picture matching a target by pressing a button on a computer keyboard. Reaction times (RTs) and accuracy were collected as outcome variables and compared within and between groups and conditions. Lower scores in SRS-22r self-image, function, and total score were observed in scoliosis compared to the control group (p-value < 0.01). Faster response times (p-value = 0.02) and higher accuracy (p-value = 0.02) were detected in the scoliosis group when processing shoulders and backs (i.e., disease-relevant body parts). A self-body advantage effect emerged in the scoliosis group, showing higher accuracy when answering self-body stimuli compared to others' bodies stimuli (p-value = 0.04). These results provide evidence of body image dissatisfaction and attentional bias towards disease-relevant body parts in girls with scoliosis, requiring clinical attention as highly predisposing to psychopathologies.
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Affiliation(s)
- Margherita Bertuccelli
- Padova Neuroscience Center, University of Padova, 35131 Padova, Italy;
- Department of Neuroscience, Section of Neurology, University of Padova, 35128 Padova, Italy
| | - Maria Rubega
- Department of Neuroscience, Section of Rehabilitation, University of Padova, 35128 Padova, Italy; (M.R.); (F.C.); (E.F.)
| | - Francesca Cantele
- Department of Neuroscience, Section of Rehabilitation, University of Padova, 35128 Padova, Italy; (M.R.); (F.C.); (E.F.)
| | - Claudia Favero
- Clinical Network of Sports and Exercise Medicine of the Veneto Region, 35131 Padova, Italy; (C.F.); (A.E.)
| | - Andrea Ermolao
- Clinical Network of Sports and Exercise Medicine of the Veneto Region, 35131 Padova, Italy; (C.F.); (A.E.)
- Sport and Exercise Medicine Division, Department of Medicine, University of Padova, 35128 Padova, Italy
| | - Emanuela Formaggio
- Department of Neuroscience, Section of Rehabilitation, University of Padova, 35128 Padova, Italy; (M.R.); (F.C.); (E.F.)
| | - Stefano Masiero
- Padova Neuroscience Center, University of Padova, 35131 Padova, Italy;
- Department of Neuroscience, Section of Rehabilitation, University of Padova, 35128 Padova, Italy; (M.R.); (F.C.); (E.F.)
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Rubega M, Storti SF, Pascucci D. Editorial: Chasing brain dynamics at their speed: what can time-varying functional connectivity tell us about brain function? Front Neurosci 2023; 17:1223955. [PMID: 37389369 PMCID: PMC10299920 DOI: 10.3389/fnins.2023.1223955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 05/30/2023] [Indexed: 07/01/2023] Open
Affiliation(s)
- Maria Rubega
- Section of Rehabilitation, Department of Neuroscience, University of Padua, Padua, Italy
| | | | - David Pascucci
- Laboratory of Psychophysics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Di Marco R, Rubega M, Lennon O, Vianello A, Masiero S, Formaggio E, Del Felice A. Exoskeleton Training Modulates Complexity in Movement Patterns and Cortical Activity in Able-Bodied Volunteers. IEEE Trans Neural Syst Rehabil Eng 2023; 31:2381-2390. [PMID: 37155402 DOI: 10.1109/tnsre.2023.3273819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Robot-aided gait training (RAGT) plays a crucial role in providing high-dose and high-intensity task-oriented physical therapy. The human-robot interaction during RAGT remains technically challenging. To achieve this aim, it is necessary to quantify how RAGT impacts brain activity and motor learning. This work quantifies the neuromuscular effect induced by a single RAGT session in healthy middle-aged individuals. Electromyographic (EMG) and motion (IMU) data were recorded and processed during walking trials before and after RAGT. Electroencephalographic (EEG) data were recorded during rest before and after the entire walking session. Linear and nonlinear analyses detected changes in the walking pattern, paralleled by a modulation of cortical activity in the motor, attentive, and visual cortices immediately after RAGT. Increases in alpha and beta EEG spectral power and pattern regularity of the EEG match the increased regularity of body oscillations in the frontal plane, and the loss of alternating muscle activation during the gait cycle, when walking after a RAGT session. These preliminary results improve the understanding of human-machine interaction mechanisms and motor learning and may contribute to more efficient exoskeleton development for assisted walking.
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Formaggio E, Bertuccelli M, Rubega M, Di Marco R, Cantele F, Gottardello F, De Giuseppe M, Masiero S. Brain oscillatory activity in adolescent idiopathic scoliosis. Sci Rep 2022; 12:17266. [PMID: 36241666 PMCID: PMC9568615 DOI: 10.1038/s41598-022-19449-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 08/29/2022] [Indexed: 01/06/2023] Open
Abstract
Pathophysiology of Adolescent Idiopathic Scoliosis (AIS) is not yet completely understood. This exploratory study aims to investigate two aspects neglected in clinical practice: a defective postural central nervous system control in AIS, and alterations of body schema due to scoliosis spinal deformities. We recorded EEG data and balance data in four different standing positions in 14 adolescents with AIS and in 14 controls. A re-adaptation of the Image Marking Procedure (IMP) assessed body schema alterations on the horizontal (Body Perception Indices (BPIs)) and vertical direction (interacromial and bisiliac axes inclinations). Our results revealed no differences in balance control between groups; higher EEG alpha relative power over sensorimotor areas ipsilateral to the side of the curve and a significant increase of theta relative power localized over the central areas in adolescents with AIS. The difference in BPI shoulder and BPI waist significantly differed between the two groups. The inclinations of the perceived interacromial axes in adolescents with AIS was opposite to the real inclination. Increased theta activity and alpha lateralization observed may be a compensatory strategy to overcome sensorimotor dysfunction mirrored by altered body schema. Scoliosis onset might be preceded by sensorimotor control impairments that last during curve progression.
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Affiliation(s)
- Emanuela Formaggio
- grid.5608.b0000 0004 1757 3470Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy
| | - Margherita Bertuccelli
- grid.5608.b0000 0004 1757 3470Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy ,grid.5608.b0000 0004 1757 3470Padova Neuroscience Center, University of Padova, Via Orus 2/B, 35129 Padova, Italy
| | - Maria Rubega
- grid.5608.b0000 0004 1757 3470Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy
| | - Roberto Di Marco
- grid.5608.b0000 0004 1757 3470Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy ,grid.5611.30000 0004 1763 1124Present Address: Department of Computer Science, University of Verona, Strada le Grazie 15, 37134 Verona, Italy
| | - Francesca Cantele
- grid.5608.b0000 0004 1757 3470Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy
| | - Federica Gottardello
- grid.5608.b0000 0004 1757 3470Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy
| | - Michela De Giuseppe
- grid.5608.b0000 0004 1757 3470Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy
| | - Stefano Masiero
- grid.5608.b0000 0004 1757 3470Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy ,grid.5608.b0000 0004 1757 3470Padova Neuroscience Center, University of Padova, Via Orus 2/B, 35129 Padova, Italy
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Rubega M, Facca M, Curci V, Sparacino G, Masiero S, Formaggio E, Del Felice A. TH-162. EEG microstates as a signature of hemispheric lateralization in stroke. Clin Neurophysiol 2022. [DOI: 10.1016/j.clinph.2022.07.342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Zoghi M, Rubega M, Fung J. Editorial: Women in science: Interventions for rehabilitation. Front Rehabilit Sci 2022; 3:1008741. [PMID: 36188927 PMCID: PMC9452839 DOI: 10.3389/fresc.2022.1008741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 08/09/2022] [Indexed: 11/21/2022]
Affiliation(s)
- Maryam Zoghi
- Discipline of Physiotherapy, Institute of Health and Wellbeing, Federation University, VIC, Australia
- Correspondence: Maryam Zoghi
| | - Maria Rubega
- Section of Rehabilitation, Department of Neuroscience, University of Padova, Padova, Italy
| | - Joyce Fung
- School of Physical and Occupational Therapy, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada
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Rubega M, Ciringione L, Bertuccelli M, Paramento M, Sparacino G, Vianello A, Masiero S, Vallesi A, Formaggio E, Del Felice A. High-density EEG sleep correlates of cognitive and affective impairment at 12-month follow-up after COVID-19. Clin Neurophysiol 2022; 140:126-135. [PMID: 35763985 PMCID: PMC9292469 DOI: 10.1016/j.clinph.2022.05.017] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/17/2022] [Accepted: 05/31/2022] [Indexed: 11/29/2022]
Abstract
Objective To disentangle the pathophysiology of cognitive/affective impairment in Coronavirus Disease-2019 (COVID-19), we studied long-term cognitive and affective sequelae and sleep high-density electroencephalography (EEG) at 12-month follow-up in people with a previous hospital admission for acute COVID-19. Methods People discharged from an intensive care unit (ICU) and a sub-intensive ward (nonICU) between March and May 2020 were contacted between March and June 2021. Participants underwent cognitive, psychological, and sleep assessment. High-density EEG recording was acquired during a nap. Slow and fast spindles density/amplitude/frequency and source reconstruction in brain gray matter were extracted. The relationship between psychological and cognitive findings was explored with Pearson correlation. Results We enrolled 33 participants ( 17 nonICU) and 12 controls. We observed a lower Physical Quality of Life index, higher post-traumatic stress disorder (PTSD) score, and a worse executive function performance in nonICU participants. Higher PTSD and Beck Depression Inventory scores correlated with lower executive performance. The same group showed a reorganization of spindle cortical generators. Conclusions Our results show executive and psycho-affective deficits and spindle alterations in COVID-19 survivors – especially in nonICU participants – after 12 months from discharge. Significance These findings may be suggestive of a crucial contribution of stress experienced during hospital admission on long-term cognitive functioning.
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Affiliation(s)
- Maria Rubega
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani, 3, Padova 35128, Italy.
| | - Luciana Ciringione
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani, 3, Padova 35128, Italy.
| | - Margherita Bertuccelli
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani, 3, Padova 35128, Italy; Padova Neuroscience Center, University of Padova, via Orus 2/B, Padova 35129, Italy.
| | - Matilde Paramento
- Department of Information Engineering, University of Padova, via Gradenigo 6/B, Padova 35131, Italy.
| | - Giovanni Sparacino
- Department of Information Engineering, University of Padova, via Gradenigo 6/B, Padova 35131, Italy.
| | - Andrea Vianello
- Department of Cardio-Thoraco-Vascular Sciences and Public Health, University of Padova, via Giustiniani, 2, Padova 35128, Italy.
| | - Stefano Masiero
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani, 3, Padova 35128, Italy; Padova Neuroscience Center, University of Padova, via Orus 2/B, Padova 35129, Italy.
| | - Antonino Vallesi
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani, 3, Padova 35128, Italy; Padova Neuroscience Center, University of Padova, via Orus 2/B, Padova 35129, Italy.
| | - Emanuela Formaggio
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani, 3, Padova 35128, Italy; Padova Neuroscience Center, University of Padova, via Orus 2/B, Padova 35129, Italy.
| | - Alessandra Del Felice
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani, 3, Padova 35128, Italy; Padova Neuroscience Center, University of Padova, via Orus 2/B, Padova 35129, Italy.
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Tortora S, Beraldo G, Bettella F, Formaggio E, Rubega M, Del Felice A, Masiero S, Carli R, Petrone N, Menegatti E, Tonin L. Neural correlates of user learning during long-term BCI training for the Cybathlon competition. J Neuroeng Rehabil 2022; 19:69. [PMID: 35790978 PMCID: PMC9254548 DOI: 10.1186/s12984-022-01047-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 06/22/2022] [Indexed: 11/15/2022] Open
Abstract
Background Brain-computer interfaces (BCIs) are systems capable of translating human brain patterns, measured through electroencephalography (EEG), into commands for an external device. Despite the great advances in machine learning solutions to enhance the performance of BCI decoders, the translational impact of this technology remains elusive. The reliability of BCIs is often unsatisfactory for end-users, limiting their application outside a laboratory environment. Methods We present the analysis on the data acquired from an end-user during the preparation for two Cybathlon competitions, where our pilot won the gold medal twice in a row. These data are of particular interest given the mutual learning approach adopted during the longitudinal training phase (8 months), the long training break in between the two events (1 year) and the demanding evaluation scenario. A multifaceted perspective on long-term user learning is proposed: we enriched the information gathered through conventional metrics (e.g., accuracy, application performances) by investigating novel neural correlates of learning in different neural domains. Results First, we showed that by focusing the training on user learning, the pilot was capable of significantly improving his performance over time even with infrequent decoder re-calibrations. Second, we revealed that the analysis of the within-class modifications of the pilot’s neural patterns in the Riemannian domain is more effective in tracking the acquisition and the stabilization of BCI skills, especially after the 1-year break. These results further confirmed the key role of mutual learning in the acquisition of BCI skills, and particularly highlighted the importance of user learning as a key to enhance BCI reliability. Conclusion We firmly believe that our work may open new perspectives and fuel discussions in the BCI field to shift the focus of future research: not only to the machine learning of the decoder, but also in investigating novel training procedures to boost the user learning and the stability of the BCI skills in the long-term. To this end, the analyses and the metrics proposed could be used to monitor the user learning during training and provide a marker guiding the decoder re-calibration to maximize the mutual adaptation of the user to the BCI system. Supplementary Information The online version contains supplementary material available at 10.1186/s12984-022-01047-x.
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Rubega M, Formaggio E, Ciringione L, Bertuccelli M, Paramento M, Sparacino G, Vianello A, Masiero S, Del Felice A. Sleep spindles changes in people with previous COVID-19 infection. Annu Int Conf IEEE Eng Med Biol Soc 2022; 2022:4135-4138. [PMID: 36086492 DOI: 10.1109/embc48229.2022.9871679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Stage 2 sleep spindles are considered useful biomarkers for the integrity of the central nervous system and for cognitive and memory skills. We investigated sleep spindles patterns in subjects after 12 months of their hospitalization in the intensive care unit (ICU) of the Padova Teaching Hospital due to COVID-19 between March and November 2020. Before the nap, participants (13 hospitalized in ICU - ICU; 9 hospitalized who received noninvasive ventilation - nonlCU; 9 age and sex-matched healthy controls - CTRL, i.e., not infected by COVID-19) underwent a cognitive and psychological as-sessment. During the nap, high-density electroencephalography (EEG) recordings were acquired. Slow (i.e., [9]-[12] Hz) and fast (i.e.,]12-16] Hz) spindles were automatically detected. Spindle density and spindle source reconstruction in brain grey matter were extracted. The psychological assessment revealed a statistical difference comparing CTRL and nonlCU in Beck Depression Inventory score and in the Physical Quality of Life index (pvalue = 0.03). The cognitive assessment revealed a trend of worsening results in executive functions in COVID-19 survivors. Slow spindle density significantly decreased comparing CTRL to COVID-19 survivors (pvalue= 0.001). There were statistically significant differences in EEG source-waveforms fast spindle amplitude onset among the three groups, mainly between CTRL and nonlCU. Clinical Relevance- Our results suggest that nonlCU were more susceptible to the hospitalization experience than ICU participants with a slight effect on cognitive tests. This impacted the spindle generation revealing a decreased density of slow spindles and affecting the generators of fast spindles in COVID-19 survivors especially in nonlCU.
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Bertuccelli M, Ciringione L, Rubega M, Bisiacchi P, Masiero S, Del Felice A. Cognitive impairment in people with previous COVID-19 infection: A scoping review. Cortex 2022; 154:212-230. [PMID: 35780756 PMCID: PMC9187867 DOI: 10.1016/j.cortex.2022.06.002] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 04/15/2022] [Accepted: 06/02/2022] [Indexed: 11/28/2022]
Abstract
Severe acute respiratory syndrome coronavirus 2 is a worldwide public health issue. Almost 2 years into the pandemic, the persistence of symptoms after the acute phase is a well-recognized phenomenon. We conducted a scoping review to map cognitive domain impairments, their frequency, and associated psycho-affective disorders in people with a previous COVID-19 infection. We searched PubMed/MEDLINE, Scopus, and PsycInfo to identify relevant reports published between December 1, 2019 and February 21, 2022. We followed the PRISMA (Preferred-Reporting-Items-for-Systematic-Reviews-and-Meta-Analyses) extension for scoping review guidelines. Three independent reviewers selected and charted 25 records out of 922. Memory, attention, and executive functions appeared to be the most affected domains. Delayed recall and learning were the most impaired domains of memory. Among the executive functions, abstraction, inhibition, set shifting, and sustained and selective attention were most commonly impaired. Language and visuo-spatial abilities were rarely affected, although this finding might be biased by the scarcity of reports. Neurological and respiratory conditions were often reported in association with cognitive deficits. Results on psycho-affective conditions were inconclusive due to the low frequency of reported data. Admission to an intensive care unit is not related to cognitive deficits. This review highlighted a potential effect of a previous post-COVID-19 infection on a pattern of memory, attention, and executive functions impairments. These findings need to be confirmed on larger cohorts with comprehensive neuropsychological batteries and correlated to neurophysiological and neurobiological substrates.
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Affiliation(s)
- Margherita Bertuccelli
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy; Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
| | - Luciana Ciringione
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy
| | - Maria Rubega
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy
| | - Patrizia Bisiacchi
- Padova Neuroscience Center, University of Padova, 35131 Padova, Italy; Department of General Psychology, University of Padova, Padova, Italy
| | - Stefano Masiero
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy; Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
| | - Alessandra Del Felice
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, Italy; Padova Neuroscience Center, University of Padova, 35131 Padova, Italy.
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Del Felice A, Bertuccelli M, Rubega M, Cattelan M, Masiero S. Reply to Letter "Transcranial alternating current stimulation (tACS) as a treatment for fibromyalgia syndrome?" by Fröhlich and Riddle. Eur Arch Psychiatry Clin Neurosci 2022; 272:351-353. [PMID: 34002242 DOI: 10.1007/s00406-021-01271-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 04/22/2021] [Indexed: 11/26/2022]
Affiliation(s)
- Alessandra Del Felice
- Section of Rehabilitation, Department of Neuroscience, University of Padova, Via Giustiniani, 3, 35128, Padua, Italy.
- Padova Neuroscience Center, University of Padova, 35131, Padua, Italy.
| | - Margherita Bertuccelli
- Section of Rehabilitation, Department of Neuroscience, University of Padova, Via Giustiniani, 3, 35128, Padua, Italy
- Padova Neuroscience Center, University of Padova, 35131, Padua, Italy
| | - Maria Rubega
- Section of Rehabilitation, Department of Neuroscience, University of Padova, Via Giustiniani, 3, 35128, Padua, Italy
| | - Manuela Cattelan
- Department of Statistical Sciences, University of Padova, via C. Battisti 241, 35121, Padua, Italy
| | - Stefano Masiero
- Section of Rehabilitation, Department of Neuroscience, University of Padova, Via Giustiniani, 3, 35128, Padua, Italy
- Padova Neuroscience Center, University of Padova, 35131, Padua, Italy
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Pascucci D, Rubega M, Rué-Queralt J, Tourbier S, Hagmann P, Plomp G. Structure supports function: Informing directed and dynamic functional connectivity with anatomical priors. Netw Neurosci 2022; 6:401-419. [PMID: 35733424 PMCID: PMC9205420 DOI: 10.1162/netn_a_00218] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 11/23/2021] [Indexed: 12/03/2022] Open
Abstract
The dynamic repertoire of functional brain networks is constrained by the underlying topology of structural connections. Despite this intrinsic relationship between structural connectivity (SC) and functional connectivity (FC), integrative and multimodal approaches to combine the two remain limited. Here, we propose a new adaptive filter for estimating dynamic and directed FC using structural connectivity information as priors. We tested the filter in rat epicranial recordings and human event-related EEG data, using SC priors from a meta-analysis of tracer studies and diffusion tensor imaging metrics, respectively. We show that, particularly under conditions of low signal-to-noise ratio, SC priors can help to refine estimates of directed FC, promoting sparse functional networks that combine information from structure and function. In addition, the proposed filter provides intrinsic protection against SC-related false negatives, as well as robustness against false positives, representing a valuable new tool for multimodal imaging in the context of dynamic and directed FC analysis.
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Affiliation(s)
- David Pascucci
- Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Perceptual Networks Group, University of Fribourg, Fribourg, Switzerland
| | - Maria Rubega
- Department of Neurosciences, University of Padova, Padova, Italy
| | - Joan Rué-Queralt
- Perceptual Networks Group, University of Fribourg, Fribourg, Switzerland
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne and University of Lausanne (CHUV-SUNIL), Lausanne, Switzerland
| | - Sebastien Tourbier
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne and University of Lausanne (CHUV-SUNIL), Lausanne, Switzerland
| | - Patric Hagmann
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne and University of Lausanne (CHUV-SUNIL), Lausanne, Switzerland
| | - Gijs Plomp
- Perceptual Networks Group, University of Fribourg, Fribourg, Switzerland
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15
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Di Marco R, Rubega M, Antonini A, Formaggio E, Masiero S, Del Felice A. Fractal Analysis of Lower Back Acceleration Profiles in balance tasks. Annu Int Conf IEEE Eng Med Biol Soc 2021; 2021:7381-7384. [PMID: 34892803 DOI: 10.1109/embc46164.2021.9629870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The body sway during standing displays fractal properties that can possibly describe motion complexity. This study aimed to use the Higuchi's fractal dimension (HFD) and Tortuosity on lower back accelerations recorded on younger (< 35 y) and older adults (> 64 y). One wearable sensor was secured on participants lower back (i.e., fifth lumbar vertebra), which were asked to perform three different postural tasks while standing barefoot as still as possible with and without performing a visual oddball task. Results of HFD and Tortuosity, applied to global anterior-posterior and medial-lateral accelerations of the body, were not dependent from signal amplitude, nor from any parametrization and allowed distinguishing between different postural tasks (p < 0.001). The proposed fractal analysis is promising to describe the complexity of postural control in both younger and older adults, paving the way to a wider use in pathological populations.
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Tortora S, Rubega M, Formaggio E, Marco RD, Masiero S, Menegatti E, Tonin L, Felice AD. Age-related differences in visual P300 ERP during dual-task postural balance. Annu Int Conf IEEE Eng Med Biol Soc 2021; 2021:6511-6514. [PMID: 34892601 DOI: 10.1109/embc46164.2021.9630088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Standing and concurrently performing a cognitive task is a very common situation in everyday life. It is associated with a higher risk of falling in the elderly. Here, we aim at evaluating the differences of the P300 evoked potential elicited by a visual oddball paradigm between healthy younger (< 35 y) and older (> 64 y) adults during a simultaneous postural task. We found that P300 latency increases significantly (p < 0.001) when the elderly are engaged in more challenging postural tasks; younger adults show no effect of balance condition. Our results demonstrate that, even if the elderly have the same accuracy in odd stimuli detection as younger adults do, they require a longer processing time for stimulus discrimination. This finding suggests an increased attentional load which engages additional cerebral reserves.
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Formaggio E, Rubega M, Rupil J, Antonini A, Masiero S, Toffolo GM, Del Felice A. Reduced Effective Connectivity in the Motor Cortex in Parkinson's Disease. Brain Sci 2021; 11:brainsci11091200. [PMID: 34573222 PMCID: PMC8466840 DOI: 10.3390/brainsci11091200] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 09/06/2021] [Accepted: 09/09/2021] [Indexed: 11/16/2022] Open
Abstract
Fast rhythms excess is a hallmark of Parkinson’s Disease (PD). To implement innovative, non-pharmacological, neurostimulation interventions to restore cortical-cortical interactions, we need to understand the neurophysiological mechanisms underlying these phenomena. Here, we investigated effective connectivity on source-level resting-state electroencephalography (EEG) signals in 15 PD participants and 10 healthy controls. First, we fitted multivariate auto-regressive models to the EEG source waveforms. Second, we estimated causal connections using Granger Causality, which provide information on connections’ strength and directionality. Lastly, we sought significant differences connectivity patterns between the two populations characterizing the network graph features—i.e., global efficiency and node strength. Causal brain networks in PD show overall poorer and weaker connections compared to controls quantified as a reduction of global efficiency. Motor areas appear almost isolated, with a strongly impoverished information flow particularly from parietal and occipital cortices. This striking isolation of motor areas may reflect an impaired sensory-motor integration in PD. The identification of defective nodes/edges in PD network may be a biomarker of disease and a potential target for future interventional trials.
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Affiliation(s)
- Emanuela Formaggio
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Gustiniani 3, 35128 Padova, Italy; (E.F.); (S.M.); (A.D.F.)
| | - Maria Rubega
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Gustiniani 3, 35128 Padova, Italy; (E.F.); (S.M.); (A.D.F.)
- Correspondence:
| | - Jessica Rupil
- Department of Information Engineering, University of Padova, Via Gradenigo 6/A, 35131 Padova, Italy; (J.R.); (G.M.T.)
| | - Angelo Antonini
- Parkinson and Movement Disorders Unit, Study Centre on Neurodegeneration (CESNE), Department of Neuroscience, University of Padova, Via Giustiniani 5, 35121 Padova, Italy;
- Padova Neuroscience Center, University of Padova, Via Orus, 35128 Padova, Italy
| | - Stefano Masiero
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Gustiniani 3, 35128 Padova, Italy; (E.F.); (S.M.); (A.D.F.)
- Padova Neuroscience Center, University of Padova, Via Orus, 35128 Padova, Italy
| | - Gianna Maria Toffolo
- Department of Information Engineering, University of Padova, Via Gradenigo 6/A, 35131 Padova, Italy; (J.R.); (G.M.T.)
| | - Alessandra Del Felice
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Gustiniani 3, 35128 Padova, Italy; (E.F.); (S.M.); (A.D.F.)
- Padova Neuroscience Center, University of Padova, Via Orus, 35128 Padova, Italy
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18
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Di Marco R, Rubega M, Lennon O, Formaggio E, Sutaj N, Dazzi G, Venturin C, Bonini I, Ortner R, Cerrel Bazo HA, Tonin L, Tortora S, Masiero S, Del Felice A. Experimental Protocol to Assess Neuromuscular Plasticity Induced by an Exoskeleton Training Session. Methods Protoc 2021; 4:48. [PMID: 34287357 PMCID: PMC8293335 DOI: 10.3390/mps4030048] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 07/01/2021] [Accepted: 07/07/2021] [Indexed: 12/13/2022] Open
Abstract
Exoskeleton gait rehabilitation is an emerging area of research, with potential applications in the elderly and in people with central nervous system lesions, e.g., stroke, traumatic brain/spinal cord injury. However, adaptability of such technologies to the user is still an unmet goal. Despite important technological advances, these robotic systems still lack the fine tuning necessary to adapt to the physiological modification of the user and are not yet capable of a proper human-machine interaction. Interfaces based on physiological signals, e.g., recorded by electroencephalography (EEG) and/or electromyography (EMG), could contribute to solving this technological challenge. This protocol aims to: (1) quantify neuro-muscular plasticity induced by a single training session with a robotic exoskeleton on post-stroke people and on a group of age and sex-matched controls; (2) test the feasibility of predicting lower limb motor trajectory from physiological signals for future use as control signal for the robot. An active exoskeleton that can be set in full mode (i.e., the robot fully replaces and drives the user motion), adaptive mode (i.e., assistance to the user can be tuned according to his/her needs), and free mode (i.e., the robot completely follows the user movements) will be used. Participants will undergo a preparation session, i.e., EMG sensors and EEG cap placement and inertial sensors attachment to measure, respectively, muscular and cortical activity, and motion. They will then be asked to walk in a 15 m corridor: (i) self-paced without the exoskeleton (pre-training session); (ii) wearing the exoskeleton and walking with the three modes of use; (iii) self-paced without the exoskeleton (post-training session). From this dataset, we will: (1) quantitatively estimate short-term neuroplasticity of brain connectivity in chronic stroke survivors after a single session of gait training; (2) compare muscle activation patterns during exoskeleton-gait between stroke survivors and age and sex-matched controls; and (3) perform a feasibility analysis on the use of physiological signals to decode gait intentions.
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Affiliation(s)
- Roberto Di Marco
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Belzoni, 160, 35121 Padova, Italy; (E.F.); (G.D.); (C.V.); (S.M.); (A.D.F.)
| | - Maria Rubega
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Belzoni, 160, 35121 Padova, Italy; (E.F.); (G.D.); (C.V.); (S.M.); (A.D.F.)
| | - Olive Lennon
- School of Public Health, Physiotherapy and Sports Science, University College Dublin, 4 Dublin, Ireland;
| | - Emanuela Formaggio
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Belzoni, 160, 35121 Padova, Italy; (E.F.); (G.D.); (C.V.); (S.M.); (A.D.F.)
| | - Ngadhnjim Sutaj
- g.tec Medical Engineering GmbH, 4521 Schiedlberg, Austria; (N.S.); (R.O.)
| | - Giacomo Dazzi
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Belzoni, 160, 35121 Padova, Italy; (E.F.); (G.D.); (C.V.); (S.M.); (A.D.F.)
| | - Chiara Venturin
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Belzoni, 160, 35121 Padova, Italy; (E.F.); (G.D.); (C.V.); (S.M.); (A.D.F.)
| | - Ilenia Bonini
- Ospedale Riabilitativo di Alta Specializzazione di Motta di Livenza, 31045 Treviso, Italy; (I.B.); (H.A.C.B.)
| | - Rupert Ortner
- g.tec Medical Engineering GmbH, 4521 Schiedlberg, Austria; (N.S.); (R.O.)
| | | | - Luca Tonin
- Department of Information Engineering, University of Padova, 35131 Padova, Italy; (L.T.); (S.T.)
| | - Stefano Tortora
- Department of Information Engineering, University of Padova, 35131 Padova, Italy; (L.T.); (S.T.)
| | - Stefano Masiero
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Belzoni, 160, 35121 Padova, Italy; (E.F.); (G.D.); (C.V.); (S.M.); (A.D.F.)
- Padova Neuroscience Center, University of Padova, 35129 Padova, Italy
| | - Alessandra Del Felice
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Belzoni, 160, 35121 Padova, Italy; (E.F.); (G.D.); (C.V.); (S.M.); (A.D.F.)
- Padova Neuroscience Center, University of Padova, 35129 Padova, Italy
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Rubega M, Formaggio E, Di Marco R, Bertuccelli M, Tortora S, Menegatti E, Cattelan M, Bonato P, Masiero S, Del Felice A. Cortical correlates in upright dynamic and static balance in the elderly. Sci Rep 2021; 11:14132. [PMID: 34238987 PMCID: PMC8266885 DOI: 10.1038/s41598-021-93556-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 06/24/2021] [Indexed: 02/06/2023] Open
Abstract
Falls are the second most frequent cause of injury in the elderly. Physiological processes associated with aging affect the elderly's ability to respond to unexpected balance perturbations, leading to increased fall risk. Every year, approximately 30% of adults, 65 years and older, experiences at least one fall. Investigating the neurophysiological mechanisms underlying the control of static and dynamic balance in the elderly is an emerging research area. The study aimed to identify cortical and muscular correlates during static and dynamic balance tests in a cohort of young and old healthy adults. We recorded cortical and muscular activity in nine elderly and eight younger healthy participants during an upright stance task in static and dynamic (core board) conditions. To simulate real-life dual-task postural control conditions, the second set of experiments incorporated an oddball visual task. We observed higher electroencephalographic (EEG) delta rhythm over the anterior cortex in the elderly and more diffused fast rhythms (i.e., alpha, beta, gamma) in younger participants during the static balance tests. When adding a visual oddball, the elderly displayed an increase in theta activation over the sensorimotor and occipital cortices. During the dynamic balance tests, the elderly showed the recruitment of sensorimotor areas and increased muscle activity level, suggesting a preferential motor strategy for postural control. This strategy was even more prominent during the oddball task. Younger participants showed reduced cortical and muscular activity compared to the elderly, with the noteworthy difference of a preferential activation of occipital areas that increased during the oddball task. These results support the hypothesis that different strategies are used by the elderly compared to younger adults during postural tasks, particularly when postural and cognitive tasks are combined. The knowledge gained in this study could inform the development of age-specific rehabilitative and assistive interventions.
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Affiliation(s)
- Maria Rubega
- Department of Neuroscience, Section of Rehabilitation, University of Padua, Padova, 35128, Italy
| | - Emanuela Formaggio
- Department of Neuroscience, Section of Rehabilitation, University of Padua, Padova, 35128, Italy
| | - Roberto Di Marco
- Department of Neuroscience, Section of Rehabilitation, University of Padua, Padova, 35128, Italy
| | - Margherita Bertuccelli
- Department of Neuroscience, Section of Rehabilitation, University of Padua, Padova, 35128, Italy
| | - Stefano Tortora
- Department of Information Engineering, University of Padua, Padova, Italy, 35131
| | - Emanuele Menegatti
- Department of Information Engineering, University of Padua, Padova, Italy, 35131
| | - Manuela Cattelan
- Department of Statistical Sciences, University of Padua, Padova, 35121, Italy
| | - Paolo Bonato
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital, Charlestown, Boston, MA, 02129, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, 02115, USA
| | - Stefano Masiero
- Department of Neuroscience, Section of Rehabilitation, University of Padua, Padova, 35128, Italy
- Padova Neuroscience Center, Padova, 35128, Italy
| | - Alessandra Del Felice
- Department of Neuroscience, Section of Rehabilitation, University of Padua, Padova, 35128, Italy.
- Padova Neuroscience Center, Padova, 35128, Italy.
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Rubega M, Formaggio E, Molteni F, Guanziroli E, Di Marco R, Baracchini C, Ermani M, Ward NS, Masiero S, Del Felice A. EEG Fractal Analysis Reflects Brain Impairment after Stroke. Entropy (Basel) 2021; 23:592. [PMID: 34064732 PMCID: PMC8150817 DOI: 10.3390/e23050592] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 04/30/2021] [Accepted: 05/07/2021] [Indexed: 12/12/2022]
Abstract
Stroke is the commonest cause of disability. Novel treatments require an improved understanding of the underlying mechanisms of recovery. Fractal approaches have demonstrated that a single metric can describe the complexity of seemingly random fluctuations of physiological signals. We hypothesize that fractal algorithms applied to electroencephalographic (EEG) signals may track brain impairment after stroke. Sixteen stroke survivors were studied in the hyperacute (<48 h) and in the acute phase (∼1 week after stroke), and 35 stroke survivors during the early subacute phase (from 8 days to 32 days and after ∼2 months after stroke): We compared resting-state EEG fractal changes using fractal measures (i.e., Higuchi Index, Tortuosity) with 11 healthy controls. Both Higuchi index and Tortuosity values were significantly lower after a stroke throughout the acute and early subacute stage compared to healthy subjects, reflecting a brain activity which is significantly less complex. These indices may be promising metrics to track behavioral changes in the very early stage after stroke. Our findings might contribute to the neurorehabilitation quest in identifying reliable biomarkers for a better tailoring of rehabilitation pathways.
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Affiliation(s)
- Maria Rubega
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, PD, Italy; (E.F.); (R.D.M.); (S.M.); (A.D.F.)
| | - Emanuela Formaggio
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, PD, Italy; (E.F.); (R.D.M.); (S.M.); (A.D.F.)
| | - Franco Molteni
- Villa Beretta Rehabilitation Center, Valduce Hospital, Via N. Sauro 17, 23845 Costa Masnaga, LC, Italy; (F.M.); (E.G.)
| | - Eleonora Guanziroli
- Villa Beretta Rehabilitation Center, Valduce Hospital, Via N. Sauro 17, 23845 Costa Masnaga, LC, Italy; (F.M.); (E.G.)
| | - Roberto Di Marco
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, PD, Italy; (E.F.); (R.D.M.); (S.M.); (A.D.F.)
| | - Claudio Baracchini
- Stroke Unit and Neurosonology Laboratory, Padova University Hospital, Via Giustiniani 3, 35128 Padova, PD, Italy; (C.B.); (M.E.)
| | - Mario Ermani
- Stroke Unit and Neurosonology Laboratory, Padova University Hospital, Via Giustiniani 3, 35128 Padova, PD, Italy; (C.B.); (M.E.)
| | - Nick S. Ward
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK;
| | - Stefano Masiero
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, PD, Italy; (E.F.); (R.D.M.); (S.M.); (A.D.F.)
- Padova Neuroscience Center, University of Padova, Via Orus, 35128 Padova, PD, Italy
| | - Alessandra Del Felice
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128 Padova, PD, Italy; (E.F.); (R.D.M.); (S.M.); (A.D.F.)
- Padova Neuroscience Center, University of Padova, Via Orus, 35128 Padova, PD, Italy
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Bernardi L, Bertuccelli M, Formaggio E, Rubega M, Bosco G, Tenconi E, Cattelan M, Masiero S, Del Felice A. Beyond physiotherapy and pharmacological treatment for fibromyalgia syndrome: tailored tACS as a new therapeutic tool. Eur Arch Psychiatry Clin Neurosci 2021; 271:199-210. [PMID: 33237361 PMCID: PMC7867558 DOI: 10.1007/s00406-020-01214-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 11/07/2020] [Indexed: 12/17/2022]
Abstract
Fibromyalgia syndrome (FMS) is a complex pain disorder, characterized by diffuse pain and cognitive disturbances. Abnormal cortical oscillatory activity may be a promising biomarker, encouraging non-invasive neurostimulation techniques as a treatment. We aimed to modulate abnormal slow cortical oscillations by delivering transcranial alternating current stimulation (tACS) and physiotherapy to reduce pain and cognitive symptoms. This was a double-blinded, randomized, crossover trial conducted between February and September 2018 at the Rehabilitation Unit of a teaching Hospital (NCT03221413). Participants were randomly assigned to tACS or random noise stimulation (RNS), 5 days/week for 2 weeks followed by ad hoc physiotherapy. Clinical and cognitive assessments were performed at T0 (baseline), T1 (after stimulation), T2 (1 month after stimulation). Electroencephalogram (EEG) spectral topographies recorded from 15 participants confirmed slow-rhythm prevalence and provided tACS tailored stimulation parameters and electrode sites. Following tACS, EEG alpha1 ([8-10] Hz) activity increased at T1 (p = 0.024) compared to RNS, pain symptoms assessed by Visual Analog Scale decreased at T1 (T1 vs T0 p = 0.010), self-reported cognitive skills and neuropsychological scores improved both at T1 and T2 (Patient-Reported Outcomes in Cognitive Impairment, T0-T2, p = 0.024; Everyday memory questionnaire, T1 compared to RNS, p = 0.012; Montréal Cognitive Assessment, T0 vs T1, p = 0.048 and T0 vs T2, p = 0.009; Trail Making Test B T0-T2, p = 0.034). Psychopathological scales and other neuropsychological scores (Trail Making Test-A; Total Phonemic Fluency; Hopkins Verbal Learning Test-Revised; Rey-Osterrieth Complex Figure) improved both after tACS and RNS but earlier improvements (T1) were registered only after tACS. These results support tACS coupled with physiotherapy in treating FMS cognitive symptoms, pain and subclinical psychopathology.
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Affiliation(s)
- Laura Bernardi
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani 3, 35128 Paduas, Italy
| | - Margherita Bertuccelli
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani 3, 35128, Paduas, Italy. .,Department of Neurosciencse and Padova Neuroscience Center, University of Padova, 35131, Padua, Italy.
| | - Emanuela Formaggio
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani 3, 35128 Paduas, Italy
| | - Maria Rubega
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani 3, 35128 Paduas, Italy
| | - Gerardo Bosco
- Department of Biomedical Sciences, University of Padova, Via Marzolo 3, 35031 Padua, Italy
| | - Elena Tenconi
- Department of Neuroscience and Padova Neuroscience Center, Psychiatric Clinic, University of Padova, Via Giustiniani 3, 35128 Padua, Italy
| | - Manuela Cattelan
- Department of Statistical Sciences, University of Padova, via C. Battisti 241, 35121 Padua, Italy
| | - Stefano Masiero
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani 3, 35128 Paduas, Italy ,Department of Neurosciencse and Padova Neuroscience Center, University of Padova, 35131 Padua, Italy
| | - Alessandra Del Felice
- Department of Neuroscience, Section of Rehabilitation, University of Padova, via Giustiniani 3, 35128 Paduas, Italy ,Department of Neurosciencse and Padova Neuroscience Center, University of Padova, 35131 Padua, Italy
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22
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Rubega M, Di Marco R, Zampini M, Formaggio E, Menegatti E, Bonato P, Masiero S, Del Felice A. Muscular and cortical activation during dynamic and static balance in the elderly: A scoping review. Aging Brain 2021; 1:100013. [PMID: 36911521 PMCID: PMC9997172 DOI: 10.1016/j.nbas.2021.100013] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 03/17/2021] [Accepted: 03/18/2021] [Indexed: 12/28/2022] Open
Abstract
Falls due to balance impairment are a major cause of injury and disability in the elderly. The study of neurophysiological correlates during static and dynamic balance tasks is an emerging area of research that could lead to novel rehabilitation strategies and reduce fall risk. This review aims to highlight key concepts and identify gaps in the current knowledge of balance control in the elderly that could be addressed by relying on surface electromyographic (EMG) and electroencephalographic (EEG) recordings. The neurophysiological hypotheses underlying balance studies in the elderly as well as the methodologies, findings, and limitations of prior work are herein addressed. The literature shows: 1) a wide heterogeneity in the experimental procedures, protocols, and analyses; 2) a paucity of studies involving the investigation of cortical activity; 3) aging-related alterations of cortical activation during balance tasks characterized by lower cortico-muscular coherence and increased allocation of attentional control to postural tasks in the elderly; and 4) EMG patterns characterized by delayed onset after perturbations, increased levels of activity, and greater levels of muscle co-activation in the elderly compared to younger adults. EMG and EEG recordings are valuable tools to monitor muscular and cortical activity during the performance of balance tasks. However, standardized protocols and analysis techniques should be agreed upon and shared by the scientific community to provide reliable and reproducible results. This will allow researchers to gain a comprehensive knowledge on the neurophysiological changes affecting static and dynamic balance in the elderly and will inform the design of rehabilitative and preventive interventions.
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Affiliation(s)
- Maria Rubega
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Giustiniani 5, 35128 Padova, IT, Italy
| | - Roberto Di Marco
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Giustiniani 5, 35128 Padova, IT, Italy
| | - Marianna Zampini
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Giustiniani 5, 35128 Padova, IT, Italy
| | - Emanuela Formaggio
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Giustiniani 5, 35128 Padova, IT, Italy
| | - Emanuele Menegatti
- Department of Information Engineering, University of Padova, Padova, IT, Italy
| | - Paolo Bonato
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, USA
| | - Stefano Masiero
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Giustiniani 5, 35128 Padova, IT, Italy.,Padova Neuroscience Center, University of Padova, Padova, IT, Italy
| | - Alessandra Del Felice
- Department of Neurosciences, Section of Rehabilitation, University of Padova, via Giustiniani 5, 35128 Padova, IT, Italy.,Padova Neuroscience Center, University of Padova, Padova, IT, Italy
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Pascucci D, Rubega M, Plomp G. Modeling time-varying brain networks with a self-tuning optimized Kalman filter. PLoS Comput Biol 2020; 16:e1007566. [PMID: 32804971 PMCID: PMC7451990 DOI: 10.1371/journal.pcbi.1007566] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 08/27/2020] [Accepted: 07/03/2020] [Indexed: 12/14/2022] Open
Abstract
Brain networks are complex dynamical systems in which directed interactions between different areas evolve at the sub-second scale of sensory, cognitive and motor processes. Due to the highly non-stationary nature of neural signals and their unknown noise components, however, modeling dynamic brain networks has remained one of the major challenges in contemporary neuroscience. Here, we present a new algorithm based on an innovative formulation of the Kalman filter that is optimized for tracking rapidly evolving patterns of directed functional connectivity under unknown noise conditions. The Self-Tuning Optimized Kalman filter (STOK) is a novel adaptive filter that embeds a self-tuning memory decay and a recursive regularization to guarantee high network tracking accuracy, temporal precision and robustness to noise. To validate the proposed algorithm, we performed an extensive comparison against the classical Kalman filter, in both realistic surrogate networks and real electroencephalography (EEG) data. In both simulations and real data, we show that the STOK filter estimates time-frequency patterns of directed connectivity with significantly superior performance. The advantages of the STOK filter were even clearer in real EEG data, where the algorithm recovered latent structures of dynamic connectivity from epicranial EEG recordings in rats and human visual evoked potentials, in excellent agreement with known physiology. These results establish the STOK filter as a powerful tool for modeling dynamic network structures in biological systems, with the potential to yield new insights into the rapid evolution of network states from which brain functions emerge. During normal behavior, brains transition between functional network states several times per second. This allows humans to quickly read a sentence, and a frog to catch a fly. Understanding these fast network dynamics is fundamental to understanding how brains work, but up to now it has proven very difficult to model fast brain dynamics for various methodological reasons. To overcome these difficulties, we designed a new Kalman filter (STOK) by innovating on previous solutions from control theory and state-space modelling. We show that STOK accurately models fast network changes in simulations and real neural data, making it an essential new tool for modelling fast brain networks in the time and frequency domain.
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Affiliation(s)
- D Pascucci
- Perceptual Networks Group, University of Fribourg, Fribourg, Switzerland.,Laboratory of Psychophysics, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - M Rubega
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland.,Department of Neurosciences, University of Padova, Padova, Italy
| | - G Plomp
- Perceptual Networks Group, University of Fribourg, Fribourg, Switzerland
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Glomb K, Mullier E, Carboni M, Rubega M, Iannotti G, Tourbier S, Seeber M, Vulliemoz S, Hagmann P. Using structural connectivity to augment community structure in EEG functional connectivity. Netw Neurosci 2020; 4:761-787. [PMID: 32885125 PMCID: PMC7462431 DOI: 10.1162/netn_a_00147] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Accepted: 05/12/2020] [Indexed: 11/17/2022] Open
Abstract
Recently, EEG recording techniques and source analysis have improved, making it feasible to tap into fast network dynamics. Yet, analyzing whole-cortex EEG signals in source space is not standard, partly because EEG suffers from volume conduction: Functional connectivity (FC) reflecting genuine functional relationships is impossible to disentangle from spurious FC introduced by volume conduction. Here, we investigate the relationship between white matter structural connectivity (SC) and large-scale network structure encoded in EEG-FC. We start by confirming that FC (power envelope correlations) is predicted by SC beyond the impact of Euclidean distance, in line with the assumption that SC mediates genuine FC. We then use information from white matter structural connectivity in order to smooth the EEG signal in the space spanned by graphs derived from SC. Thereby, FC between nearby, structurally connected brain regions increases while FC between nonconnected regions remains unchanged, resulting in an increase in genuine, SC-mediated FC. We analyze the induced changes in FC, assessing the resemblance between EEG-FC and volume-conduction- free fMRI-FC, and find that smoothing increases resemblance in terms of overall correlation and community structure. This result suggests that our method boosts genuine FC, an outcome that is of interest for many EEG network neuroscience questions.
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Affiliation(s)
- Katharina Glomb
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne and University of Lausanne, Lausanne (CHUV-UNIL), Vaud, Switzerland
| | - Emeline Mullier
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne and University of Lausanne, Lausanne (CHUV-UNIL), Vaud, Switzerland
| | - Margherita Carboni
- EEG and Epilepsy, Neurology, University Hospitals of Geneva and University of Geneva, Geneva, Switzerland
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Maria Rubega
- Department of Neurosciences, University of Padova, Padova, Italy
| | - Giannarita Iannotti
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Sebastien Tourbier
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne and University of Lausanne, Lausanne (CHUV-UNIL), Vaud, Switzerland
| | - Martin Seeber
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy, Neurology, University Hospitals of Geneva and University of Geneva, Geneva, Switzerland
| | - Patric Hagmann
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne and University of Lausanne, Lausanne (CHUV-UNIL), Vaud, Switzerland
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Carboni M, De Stefano P, Vorderwülbecke BJ, Tourbier S, Mullier E, Rubega M, Momjian S, Schaller K, Hagmann P, Seeck M, Michel CM, van Mierlo P, Vulliemoz S. Abnormal directed connectivity of resting state networks in focal epilepsy. Neuroimage Clin 2020; 27:102336. [PMID: 32679553 PMCID: PMC7363703 DOI: 10.1016/j.nicl.2020.102336] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2020] [Revised: 06/30/2020] [Accepted: 07/01/2020] [Indexed: 11/03/2022]
Abstract
OBJECTIVE Epilepsy diagnosis can be difficult in the absence of interictal epileptic discharges (IED) on scalp EEG. We used high-density EEG to measure connectivity in large-scale functional networks of patients with focal epilepsy (Temporal and Extratemporal Lobe Epilepsy, TLE and ETLE) and tested for network alterations during resting wakefulness without IEDs, compared to healthy controls. We measured global efficiency as a marker of integration within networks. METHODS We analysed 49 adult patients with focal epilepsy and 16 healthy subjects who underwent high-density-EEG and structural MRI. We estimated cortical activity using electric source analysis in 82 atlas-based cortical regions based on the individual MRI. We applied directed connectivity analysis (Partial Directed Coherence) on these sources and performed graph analysis: we computed the Global Efficiency on the whole brain and on each resting state network. We tested these features in different group of patients. RESULTS Compared to controls, efficiency was increased in both TLE and ETLE (p < 0.05). The somato-motor-network, the ventral-attention-network and the default-mode-network had a significantly increased efficiency (p < 0.05) in both TLE and ETLE as well as TLE with hippocampal sclerosis. SIGNIFICANCE During interictal scalp EEG epochs without IED, patients with focal epilepsy show brain functional connectivity alterations in the whole brain and in specific resting-state-networks. This higher integration reflects a chronic effect of pathological activity within these structures and complement previous work on altered information outflow. These findings could increase the diagnostic sensitivity of scalp EEG to identify epileptic activity in the absence of IED.
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Affiliation(s)
- Margherita Carboni
- EEG and Epilepsy Unit, Clinical Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland.
| | - Pia De Stefano
- EEG and Epilepsy Unit, Clinical Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Bernd J Vorderwülbecke
- EEG and Epilepsy Unit, Clinical Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Epilepsy-Center Berlin-Brandenburg, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Sebastien Tourbier
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - Emeline Mullier
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - Maria Rubega
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland; Department of Neurosciences, University of Padova, Padova, Italy
| | - Shahan Momjian
- Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Karl Schaller
- Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Patric Hagmann
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Clinical Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Pieter van Mierlo
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Clinical Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
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26
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Rubega M, Pascucci D, Queralt JR, Van Mierlo P, Hagmann P, Plomp G, Michel CM. Time-varying effective EEG source connectivity: the optimization of model parameters .. Annu Int Conf IEEE Eng Med Biol Soc 2020; 2019:6438-6441. [PMID: 31947316 DOI: 10.1109/embc.2019.8856890] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Adaptive estimation methods based on general Kalman filter are powerful tools to investigate brain networks dynamics given the non-stationary nature of neural signals. These methods rely on two parameters, the model order p and adaptation constant c, which determine the resolution and smoothness of the time-varying multivariate autoregressive estimates. A sub-optimal filtering may present consistent biases in the frequency domain and temporal distortions, leading to fallacious interpretations. Thus, the performance of these methods heavily depends on the accurate choice of these two parameters in the filter design. In this work, we sought to define an objective criterion for the optimal choice of these parameters. Since residual- and information-based criteria are not guaranteed to reach an absolute minimum, we propose to study the partial derivatives of these functions to guide the choice of p and c. To validate the performance of our method, we used a dataset of human visual evoked potentials during face perception where the generation and propagation of information in the brain is well understood and a set of simulated data where the ground truth is available.
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Toscano G, Carboni M, Rubega M, Spinelli L, Pittau F, Bartoli A, Momjian S, Manni R, Terzaghi M, Vulliemoz S, Seeck M. Visual analysis of high density EEG: As good as electrical source imaging? Clin Neurophysiol Pract 2019; 5:16-22. [PMID: 31909306 PMCID: PMC6939057 DOI: 10.1016/j.cnp.2019.09.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2019] [Revised: 09/19/2019] [Accepted: 09/29/2019] [Indexed: 11/29/2022] Open
Abstract
Visual analysis of HD-EEG is an excellent tool to explore the epileptogenic focus. ESI remains the gold standard for presurgical evaluation of the cortical source. ESI at 50% slope/ESI at peak discordance could predict worse surgical outcome.
Objective In this study, we sought to determine whether visual analysis of high density EEG (HD-EEG) would provide similar localizing information comparable to electrical source imaging (ESI). Methods HD-EEG (256 electrodes) recordings from 20 patients suffering from unifocal, drug-resistant epilepsy (13 women, mean age 29.1 ± 2.62 years, 11 with temporal lobe epilepsy) were examined. In the visual analysis condition, we identified the 5 contacts with maximal spike amplitude and determined their localization with respect to the underlying cortex. ESI was computed using the LAURA algorithm of the averaged spikes in the patient’s individual MRI. We considered the localization “correct” if all 5 contacts were concordant with the resection volume underneath or if ESI was located within the resection as determined by the postoperative MRI. Results Twelve patients were postoperatively seizure-free (Engel Class IA), while the remaining eight were in class IB to IV. Visual analysis and ESI showed sensitivity of 58% and 75%, specificity of 75% and 87%, and accuracy of 65% and 80%, respectively. In 70% of cases, visual analysis and ESI provided concordant results. Conclusions Localization of the electrodes with maximal spike amplitude provides very good estimation of the localization of the underlying source. However, ESI has a higher accuracy and adds 3D information; therefore, it should remain the tool of choice for presurgical evaluation. Significance The present study proposes the possibility to analyze HD-EEG visually, in tandem with ESI or alone, if ESI is not accessible.
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Affiliation(s)
- Gianpaolo Toscano
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland.,Unit of Sleep Medicine and Epilepsy, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioural Sciences, University of Pavia, Italy
| | - Margherita Carboni
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland.,Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Maria Rubega
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Laurent Spinelli
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - Francesca Pittau
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - Andrea Bartoli
- Department of Neurosurgery, University Hospital of Geneva, Geneva, Switzerland
| | - Shahan Momjian
- Department of Neurosurgery, University Hospital of Geneva, Geneva, Switzerland
| | - Raffaele Manni
- Unit of Sleep Medicine and Epilepsy, IRCCS Mondino Foundation, Pavia, Italy
| | - Michele Terzaghi
- Unit of Sleep Medicine and Epilepsy, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioural Sciences, University of Pavia, Italy
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
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Carboni M, Rubega M, Iannotti GR, De Stefano P, Toscano G, Tourbier S, Pittau F, Hagmann P, Momjian S, Schaller K, Seeck M, Michel CM, van Mierlo P, Vulliemoz S. The network integration of epileptic activity in relation to surgical outcome. Clin Neurophysiol 2019; 130:2193-2202. [PMID: 31669753 DOI: 10.1016/j.clinph.2019.09.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 08/21/2019] [Accepted: 09/12/2019] [Indexed: 11/24/2022]
Abstract
OBJECTIVE Epilepsy is a network disease with epileptic activity and cognitive impairment involving large-scale brain networks. A complex network is involved in the seizure and in the interictal epileptiform discharges (IEDs). Directed connectivity analysis, describing the information transfer between brain regions, and graph analysis are applied to high-density EEG to characterise networks. METHODS We analysed 19 patients with focal epilepsy who had high-density EEG containing IED and underwent surgery. We estimated cortical activity during IED using electric source analysis in 72 atlas-based cortical regions of the individual brain MRI. We applied directed connectivity analysis (information Partial Directed Coherence) and graph analysis on these sources and compared patients with good vs poor post-operative outcome at global, hemispheric and lobar level. RESULTS We found lower network integration reflected by global, hemispheric, lobar efficiency during the IED (p < 0.05) in patients with good post-surgical outcome, compared to patients with poor outcome. Prediction was better than using the IED field or the localisation obtained by electric source imaging. CONCLUSIONS Abnormal network patterns in epilepsy are related to seizure outcome after surgery. SIGNIFICANCE Our finding may help understand networks related to a more "isolated" epileptic activity, limiting the extent of the epileptic network in patients with subsequent good post-operative outcome.
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Affiliation(s)
- M Carboni
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland.
| | - M Rubega
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - G R Iannotti
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland; Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - P De Stefano
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - G Toscano
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Unit of Sleep Medicine and Epilepsy, C. Mondino National Neurological Institute, Pavia, Italy
| | - S Tourbier
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - F Pittau
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - P Hagmann
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - S Momjian
- Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - K Schaller
- Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - M Seeck
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - C M Michel
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - P van Mierlo
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - S Vulliemoz
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland.
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Rubega M, Carboni M, Seeber M, Pascucci D, Tourbier S, Toscano G, Van Mierlo P, Hagmann P, Plomp G, Vulliemoz S, Michel CM. Estimating EEG Source Dipole Orientation Based on Singular-value Decomposition for Connectivity Analysis. Brain Topogr 2018; 32:704-719. [PMID: 30511174 DOI: 10.1007/s10548-018-0691-2] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Accepted: 11/29/2018] [Indexed: 12/14/2022]
Abstract
In the last decade, the use of high-density electrode arrays for EEG recordings combined with the improvements of source reconstruction algorithms has allowed the investigation of brain networks dynamics at a sub-second scale. One powerful tool for investigating large-scale functional brain networks with EEG is time-varying effective connectivity applied to source signals obtained from electric source imaging. Due to computational and interpretation limitations, the brain is usually parcelled into a limited number of regions of interests (ROIs) before computing EEG connectivity. One specific need and still open problem is how to represent the time- and frequency-content carried by hundreds of dipoles with diverging orientation in each ROI with one unique representative time-series. The main aim of this paper is to provide a method to compute a signal that explains most of the variability of the data contained in each ROI before computing, for instance, time-varying connectivity. As the representative time-series for a ROI, we propose to use the first singular vector computed by a singular-value decomposition of all dipoles belonging to the same ROI. We applied this method to two real datasets (visual evoked potentials and epileptic spikes) and evaluated the time-course and the frequency content of the obtained signals. For each ROI, both the time-course and the frequency content of the proposed method reflected the expected time-course and the scalp-EEG frequency content, representing most of the variability of the sources (~ 80%) and improving connectivity results in comparison to other procedures used so far. We also confirm these results in a simulated dataset with a known ground truth.
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Affiliation(s)
- M Rubega
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202, Geneva, Switzerland.
| | - M Carboni
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202, Geneva, Switzerland.,EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - M Seeber
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202, Geneva, Switzerland
| | - D Pascucci
- Perceptual Networks Group, Department of Psychology, University of Fribourg, Fribourg, Switzerland
| | - S Tourbier
- Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - G Toscano
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland.,Unit of Sleep Medicine and Epilepsy, C. Mondino National Neurological Institute, Pavia, Italy
| | - P Van Mierlo
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland.,Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - P Hagmann
- Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - G Plomp
- Perceptual Networks Group, Department of Psychology, University of Fribourg, Fribourg, Switzerland
| | - S Vulliemoz
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - C M Michel
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202, Geneva, Switzerland.,Lemanic Biomedical Imaging Centre (CIBM), Lausanne, Geneva, Switzerland
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Toscano G, Carboni M, Rubega M, Manni R, Vulliémoz S, Seeck M. F180. The effectiveness of high-density EEG visual analysis and electrical source imaging in detecting the epileptogenic zone in focal epilepsy. Clin Neurophysiol 2018. [DOI: 10.1016/j.clinph.2018.04.343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Scarpa F, Rubega M, Zanon M, Finotello F, Sejling AS, Sparacino G. Hypoglycemia-induced EEG complexity changes in Type 1 diabetes assessed by fractal analysis algorithm. Biomed Signal Process Control 2017. [DOI: 10.1016/j.bspc.2017.06.004] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Rubega M, Cecchetto C, Vassanelli S, Sparacino G. Algorithm and software to automatically identify latency and amplitude features of local field potentials recorded in electrophysiological investigation. Source Code Biol Med 2017; 12:3. [PMID: 28191033 PMCID: PMC5297145 DOI: 10.1186/s13029-017-0062-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2015] [Accepted: 01/28/2017] [Indexed: 11/10/2022]
Abstract
BACKGROUND Local field potentials (LFPs) evoked by sensory stimulation are particularly useful in electrophysiological research. For instance, spike timing and current transmembrane current flow estimated from LFPs recorded in the barrel cortex in rats and mice are exploited to investigate how the brain represents sensory stimuli. Recent improvements in microelectrodes technology enable neuroscientists to acquire a great amount of LFPs during the same experimental session, calling for algorithms for their quantitative automatic analysis. Several computer tools were proposed for LFP analysis, but many of them incorporate algorithms that are not open to inspection or modification/personalization. We present a MATLAB software to automatically detect some important LFP features (latency, amplitude, time-derivative value in the inflection-point) for a quantitative analysis. The software features can be customized by the user according to his/her personal research needs. The incorporated algorithm is based on Phillips-Tikhonov regularization to deal with noise amplification due to ill-conditioning. In particular, its accuracy in the estimation of the features of interest is assessed in a Monte Carlo simulation mimicking the acquisition of LFPs in different SNR (signal-to-noise-ratio) conditions. Then, the algorithm is tested by analyzing a real set of 2500 LFPs recorded in rat after whisker stimulation at different depths in the primary somatosensory (S1) cortex, i.e., the region involved in the cortical representation of touch in mammals. RESULTS Automatic identification of LFP features by the presented software is easy and fast. As far as accuracy is concerned, error indices from simulated data suggest that the algorithm provides reliable estimates . Indeed, results obtained from LFPs recorded in rat after whisker stimulation are in line with the known sequential activation of the microcircuits of the S1 cortex. CONCLUSION A MATLAB software implementing an algorithm to automatically detect the main LFPs features was presented. Simulated and real case studies showed that the employed algorithm is accurate and robust against measurement noise. The available code can be used as it is, but the reported description of the algorithms allows users to easily modify the code to cope with specific requirements.
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Affiliation(s)
- Maria Rubega
- Department of Information Engineering, University of Padova, Padova, 35131 Italy
| | - Claudia Cecchetto
- Department of Information Engineering, University of Padova, Padova, 35131 Italy.,Department of Biomedical Sciences, University of Padova, Padova, 35131 Italy
| | - Stefano Vassanelli
- Department of Biomedical Sciences, University of Padova, Padova, 35131 Italy
| | - Giovanni Sparacino
- Department of Information Engineering, University of Padova, Padova, 35131 Italy
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Affiliation(s)
- Maria Rubega
- Department of Information Engineering, University of Padova , Padova, Italy
| | - Giovanni Sparacino
- Department of Information Engineering, University of Padova , Padova, Italy
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Fontana R, Agostini M, Murana E, Mahmud M, Scremin E, Rubega M, Sparacino G, Vassanelli S, Fasolato C. Early hippocampal hyperexcitability in PS2APP mice: role of mutant PS2 and APP. Neurobiol Aging 2016; 50:64-76. [PMID: 27889678 DOI: 10.1016/j.neurobiolaging.2016.10.027] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2016] [Revised: 10/17/2016] [Accepted: 10/28/2016] [Indexed: 12/27/2022]
Abstract
Alterations of brain network activity are observable in Alzheimer's disease (AD) together with the occurrence of mild cognitive impairment, before overt pathology. However, in humans as well in AD mouse models, identification of early biomarkers of network dysfunction is still at its beginning. We performed in vivo recordings of local field potential activity in the dentate gyrus of PS2APP mice expressing the human amyloid precursor protein (APP) Swedish mutation and the presenilin-2 (PS2) N141I. From a frequency-domain analysis, we uncovered network hyper-synchronicity as early as 3 months, when intracellular accumulation of amyloid beta was also observable. In addition, at 6 months of age, we identified network hyperactivity in the beta/gamma frequency bands, along with increased theta-beta and theta-gamma phase-amplitude cross-frequency coupling, in coincidence with the histopathological traits of the disease. Although hyperactivity and hypersynchronicity were respectively detected in mice expressing the PS2-N141I or the APP Swedish mutant alone, the increase in cross-frequency coupling specifically characterized the 6-month-old PS2APP mice, just before the surge of the cognitive decline.
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Affiliation(s)
- Roberto Fontana
- Department of Biomedical Sciences, University of Padova, Padova, Italy
| | - Mario Agostini
- Department of Biomedical Sciences, University of Padova, Padova, Italy
| | - Emanuele Murana
- Department of Biomedical Sciences, University of Padova, Padova, Italy
| | - Mufti Mahmud
- Department of Biomedical Sciences, University of Padova, Padova, Italy
| | - Elena Scremin
- Department of Biomedical Sciences, University of Padova, Padova, Italy
| | - Maria Rubega
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Giovanni Sparacino
- Department of Information Engineering, University of Padova, Padova, Italy
| | | | - Cristina Fasolato
- Department of Biomedical Sciences, University of Padova, Padova, Italy.
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Rubega M, Fontana R, Vassanelli S, Sparacino G. A tunable local field potentials computer simulator to assess minimal requirements for phase-amplitude cross-frequency-coupling estimation. Network 2016; 27:268-288. [PMID: 27715367 DOI: 10.1080/0954898x.2016.1213440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
The quantitative study of cross-frequency coupling (CFC) is a relevant issue in neuroscience. In local field potentials (LFPs), measured either in the cortex or in the hippocampus, how γ-oscillation amplitude is modulated by changes in θ-rhythms-phase is thought to be important in memory formation. Several methods were proposed to quantify CFC, but reported evidence suggests that experimental parameters affect the results. Therefore, a simulation tool to support the determination of minimal requirements for CFC estimation in order to obtain reliable results is particularly useful. An approach to generate computer-simulated signals having CFC intensity, sweep duration, signal-to-noise ratio (SNR), and multiphasic-coupling tunable by the user has been developed. Its utility has been proved by a study evaluating minimal sweep duration and SNR required for reliable θ-γ CFC estimation from signals simulating LFP measured in the mouse hippocampus. A MATLAB® software was made available to facilitate methodology reproducibility. The analysis of the synthetic LFPs created by the simulator shows how the minimal sweep duration for achieving accurate θ-γ CFC estimates increases as SNR decreases and the number of CFC levels to discriminate increases. In particular, a sufficient reliability in discriminating five different predetermined CFC levels is reached with 35-s sweep with SNR = 20, while SNR = 5 requires at least 140-s sweep.
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Affiliation(s)
- Maria Rubega
- a Department of Information Engineering , University of Padova , Padova , Italy
| | - Roberto Fontana
- b NeuroChip Laboratory, Department of Biomedical Sciences , University of Padova , Padova , Italy
| | - Stefano Vassanelli
- b NeuroChip Laboratory, Department of Biomedical Sciences , University of Padova , Padova , Italy
| | - Giovanni Sparacino
- a Department of Information Engineering , University of Padova , Padova , Italy
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Abstract
BACKGROUND Hypoglycemic events in patients with type 1 diabetes (T1D) are associated with measurable electroencephalography (EEG) changes. Previous studies have, however, evaluated these changes on a single EEG channel level, whereas multivariate analysis of several EEG channels has been scarcely investigated. The aim of the present work is to use a coherence approach to quantitatively assess how hypoglycemia affects mutual connectivity of different brain areas. MATERIALS AND METHODS EEG multichannel data were obtained from 19 patients with T1D (58% males; mean age, 55 ± 2.4 years; diabetes duration, 28.5 ± 2.6 years; glycated hemoglobin, 8.0 ± 0.2%) who underwent a hyperinsulinemic-hypoglycemic clamp study. The information partial directed coherence (iPDC) function was computed through multivariate autoregressive models during eu- and hypoglycemia in the theta and alpha bands. RESULTS In passing from eu- to hypoglycemia, absolute values of the iPDC function tend to decrease in both bands in all combinations of the considered channels. In particular, the scalar indicator [Formula: see text], which summarizes iPDC information, significantly decreased (P < 0.01) in 17 of 19 subjects: from T5-A1A2 to C3-A1A2 from O1-A1A2 to C4-A1A2 and from O2-A1A2 to Cz-A1A2 in the theta band and from O1-A1A2 to T4-A1A2 and from O1-A1A2 to C4-A1A2 in the alpha band. CONCLUSIONS The coherence decrease measured by iPDC in passing from eu- to hypoglycemia is likely related to the progressive loss of cognitive function and altered cerebral activity in hypoglycemia. This result encourages further quantitative investigation of EEG changes in hypoglycemia and of how EEG acquisition and real-time processing can support hypoglycemia alert systems.
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Affiliation(s)
- Maria Rubega
- 1 Department of Information Engineering, University of Padova , Padova, Italy
| | - Giovanni Sparacino
- 1 Department of Information Engineering, University of Padova , Padova, Italy
| | - Anne S Sejling
- 2 Department of Cardiology, Nephrology and Endocrinology, Nordsjællands University Hospital , Hillerød, Denmark
| | - Claus B Juhl
- 3 Hyposafe , Lyngsby, Denmark
- 4 Hospital of South West Jutland , Department of Medicine, Esbjerg, Denmark
| | - Claudio Cobelli
- 1 Department of Information Engineering, University of Padova , Padova, Italy
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Rubega M, Cecchetto C, Vassanelli S, Sparacino G. Automated analysis of local field potentials evoked by mechanical whisker stimulation in rat barrel cortex. Annu Int Conf IEEE Eng Med Biol Soc 2015; 2015:1520-1523. [PMID: 26736560 DOI: 10.1109/embc.2015.7318660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Local field potentials (LFPs) recorded in the barrel cortex in rats and mice are important to investigate somatosensory systems, the final aim being to start to understand mechanisms of brain representation of sensory stimuli in humans. Parameters extracted from LFP of particular interest include spike timing and transmembrane current flow. Recent improvements in microelectrodes technology have enabled neuroscientists to acquire a great amount of LFP signals during the same experimental session, calling for the development of algorithms for their quantitative automatic analysis. In the present work, an algorithm based on Phillips-Tikhonov regularization is presented to automatically detect the main features (in terms of amplitude and latency) of LFP waveforms recorded after whisker stimulation in rat. The accuracy of the algorithm is first assessed in a Monte Carlo simulation mimicking the acquisition of LFP in three different conditions of SNR. Then, the algorithm is tested by analyzing a set of 100 LFP recorded in the primary somatosensory (S1) cortex, i.e., the region involved in the cortical representation of touch in mammals.
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Rubega M, Sparacino G, Sejling AS, Juhl CB, Cobelli C. Decrease of EEG Coherence during hypoglycemia in type 1 diabetic subjects. Annu Int Conf IEEE Eng Med Biol Soc 2015; 2015:2375-2378. [PMID: 26736771 DOI: 10.1109/embc.2015.7318871] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Hypoglycemic events have been proven to be associated with measurable EEG changes. Several works in the literature have evaluated these changes by considering approaches at the single EEG channel level, but multivariate analyses have been scarcely investigated in Type 1 diabetes (T1D) subjects. The aim of the present work is to assess if and how hypoglycemia affects EEG coherence in a subset of EEG channels acquired in a hospital setting where eye- and muscle activation-induced artifacts are virtually absent. In particular, EEG multichannel data, acquired in 19 T1D hospitalized subjects undertaken to an insulin-induced hypoglycemia experiment, are considered. Computation of Partial Directed Coherence (PDC) through multivariate autoregressive models of P3-A1A2, P4-A1A2, C3-A1A2 and C4-A1A2 EEG channels shows that a decrease in the value of coherence, most likely related to the progressive loss of cognitive function and altered cerebral activity, occurs when passing from eu- to hypoglycemia, in both theta ([4, 8] Hz) and alpha ([8, 13] Hz) bands.
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