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Liuzzi P, Cassioli T, Secci S, Hakiki B, Scarpino M, Burali R, di Palma A, Toci T, Grippo A, Cecchi F, Frosini A, Mannini A. A neurophysiological profiling of the heartbeat-evoked potential in severe acquired brain injuries: A focus on unconsciousness. Eur J Neurosci 2024. [PMID: 38797841 DOI: 10.1111/ejn.16394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 04/26/2024] [Accepted: 05/01/2024] [Indexed: 05/29/2024]
Abstract
Unconsciousness in severe acquired brain injury (sABI) patients occurs with different cognitive and neural profiles. Perturbational approaches, which enable the estimation of proxies for brain reorganization, have added a new avenue for investigating the non-behavioural diagnosis of consciousness. In this prospective observational study, we conducted a comparative analysis of the topological patterns of heartbeat-evoked potentials (HEP) between patients experiencing a prolonged disorder of consciousness (pDoC) and patients emerging from a minimally consciousness state (eMCS). A total of 219 sABI patients were enrolled, each undergoing a synchronous EEG-ECG resting-state recording, together with a standardized consciousness diagnosis. A number of graph metrics were computed before/after the HEP (Before/After) using the R-peak on the ECG signal. The peak value of the global field power of the HEP was found to be significantly higher in eMCS patients with no difference in latency. Power spectrum was not able to discriminate consciousness neither Before nor After. Node assortativity and global efficiency were found to vary with different trends at unconsciousness. Lastly, the Perturbational Complexity Index of the HEP was found to be significantly higher in eMCS patients compared with pDoC. Given that cortical elaboration of peripheral inputs may serve as a non-behavioural determinant of consciousness, we have devised a low-cost and translatable technique capable of estimating causal proxies of brain functionality with an endogenous, non-invasive stimulus. Thus, we present an effective means to enhance consciousness assessment by incorporating the interaction between the autonomic nervous system (ANS) and central nervous system (CNS) into the loop.
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Affiliation(s)
- Piergiuseppe Liuzzi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
- Istituto di BioRobotica, Scuola Superiore Sant'Anna, Pisa, Italy
| | | | - Sara Secci
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
| | - Bahia Hakiki
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
- Dipartimento di Medicina Sperimentale e Clinica, Università di Firenze, Florence, Italy
| | | | - Rachele Burali
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
| | | | - Tanita Toci
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
| | | | - Francesca Cecchi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
- Dipartimento di Medicina Sperimentale e Clinica, Università di Firenze, Florence, Italy
| | - Andrea Frosini
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
- Dipartimento di Matematica Ulisse Dini, Università di Firenze, Florence, Italy
| | - Andrea Mannini
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
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Hermann B, Candia‐Rivera D, Sharshar T, Gavaret M, Diehl J, Cariou A, Benghanem S. Aberrant brain-heart coupling is associated with the severity of post cardiac arrest brain injury. Ann Clin Transl Neurol 2024; 11:866-882. [PMID: 38243640 PMCID: PMC11021613 DOI: 10.1002/acn3.52000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 12/24/2023] [Indexed: 01/21/2024] Open
Abstract
OBJECTIVE To investigate autonomic nervous system activity measured by brain-heart interactions in comatose patients after cardiac arrest in relation to the severity and prognosis of hypoxic-ischemic brain injury. METHODS Strength and complexity of bidirectional interactions between EEG frequency bands (delta, theta, and alpha) and ECG heart rate variability frequency bands (low frequency, LF and high frequency, HF) were computed using a synthetic data generation model. Primary outcome was the severity of brain injury, assessed by (i) standardized qualitative EEG classification, (ii) somatosensory evoked potentials (N20), and (iii) neuron-specific enolase levels. Secondary outcome was the 3-month neurological status, assessed by the Cerebral Performance Category score [good (1-2) vs. poor outcome (3-4-5)]. RESULTS Between January 2007 and July 2021, 181 patients were admitted to ICU for a resuscitated cardiac arrest. Poor neurological outcome was observed in 134 patients (74%). Qualitative EEG patterns suggesting high severity were associated with decreased LF/HF. Severity of EEG changes were proportional to higher absolute values of brain-to-heart coupling strength (p < 0.02 for all brain-to-heart frequencies) and lower values of alpha-to-HF complexity (p = 0.049). Brain-to-heart coupling strength was significantly higher in patients with bilateral absent N20 and correlated with neuron-specific enolase levels at Day 3. This aberrant brain-to-heart coupling (increased strength and decreased complexity) was also associated with 3-month poor neurological outcome. INTERPRETATION Our results suggest that autonomic dysfunctions may well represent hypoxic-ischemic brain injury post cardiac arrest pathophysiology. These results open avenues for integrative monitoring of autonomic functioning in critical care patients.
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Affiliation(s)
- Bertrand Hermann
- Faculté de MédecineUniversité Paris CitéParisFrance
- Medical Intensive Care UnitHEGP Hospital, Assistance Publique ‐ Hôpitaux de Paris‐Centre (APHP.Centre)ParisFrance
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris (IPNP)Université Paris CitéParisFrance
| | - Diego Candia‐Rivera
- Sorbonne Université, Paris Brain Institute (ICM), INRIA, CNRS UMR 722, INSERM U1127, AP‐HP Hôpital Pitié‐SalpêtrièreParisFrance
| | - Tarek Sharshar
- Faculté de MédecineUniversité Paris CitéParisFrance
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris (IPNP)Université Paris CitéParisFrance
- GHU Paris Psychiatrie Neurosciences, Service hospitalo‐universitaire de Neuro‐anesthésie réanimationParisFrance
| | - Martine Gavaret
- Faculté de MédecineUniversité Paris CitéParisFrance
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris (IPNP)Université Paris CitéParisFrance
- Neurophysiology and Epileptology DepartmentGHU Paris Psychiatrie et NeurosciencesParisFrance
| | - Jean‐Luc Diehl
- Faculté de MédecineUniversité Paris CitéParisFrance
- Medical Intensive Care UnitHEGP Hospital, Assistance Publique ‐ Hôpitaux de Paris‐Centre (APHP.Centre)ParisFrance
- Université Paris Cité, INSERM, Innovative Therapies in HaemostasisParisFrance
- Biosurgical Research Lab (Carpentier Foundation)ParisFrance
| | - Alain Cariou
- Faculté de MédecineUniversité Paris CitéParisFrance
- Medical Intensive Care UnitCochin Hospital, Assistance Publique ‐ Hôpitaux de Paris‐Centre (APHP‐Centre)ParisFrance
- Paris‐Cardiovascular‐Research‐CenterINSERM U970ParisFrance
| | - Sarah Benghanem
- Faculté de MédecineUniversité Paris CitéParisFrance
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris (IPNP)Université Paris CitéParisFrance
- Medical Intensive Care UnitCochin Hospital, Assistance Publique ‐ Hôpitaux de Paris‐Centre (APHP‐Centre)ParisFrance
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Riganello F, Vatrano M, Cortese MD, Tonin P, Soddu A. Central autonomic network and early prognosis in patients with disorders of consciousness. Sci Rep 2024; 14:1610. [PMID: 38238457 PMCID: PMC10796939 DOI: 10.1038/s41598-024-51457-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 01/05/2024] [Indexed: 01/22/2024] Open
Abstract
The central autonomic network (CAN) plays a crucial role in modulating the autonomic nervous system. Heart rate variability (HRV) is a valuable marker for assessing CAN function in disorders of consciousness (DOC) patients. We used HRV analysis for early prognosis in 58 DOC patients enrolled within ten days of hospitalization. They underwent a five-minute electrocardiogram during baseline and acoustic/visual stimulation. The coma recovery scale-revised (CRS-R) was used to define the patient's consciousness level and categorize the good/bad outcome at three months. The high-frequency Power Spectrum Density and the standard deviation of normal-to-normal peaks in baseline, the sample entropy during the stimulation, and the time from injury features were used in the support vector machine analysis (SVM) for outcome prediction. The SVM predicted the patients' outcome with an accuracy of 96% in the training test and 100% in the validation test, underscoring its potential to provide crucial clinical information about prognosis.
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Affiliation(s)
- Francesco Riganello
- Reseach in Advanced Neurorehabilitation, S. Anna Institute, 88900, Crotone, Italy.
| | - Martina Vatrano
- Reseach in Advanced Neurorehabilitation, S. Anna Institute, 88900, Crotone, Italy
| | | | - Paolo Tonin
- Reseach in Advanced Neurorehabilitation, S. Anna Institute, 88900, Crotone, Italy
| | - Andrea Soddu
- Physics & Astronomy Department and Western Institute for Neuroscience, University of Western Ontario, London, ON, Canada
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Kwon SB, Megjhani M, Nametz D, Agarwal S, Park S. Heart rate and heart rate variability as a prognosticating feature for functional outcome after cardiac arrest: A scoping review. Resusc Plus 2023; 15:100450. [PMID: 37645619 PMCID: PMC10461016 DOI: 10.1016/j.resplu.2023.100450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 07/19/2023] [Accepted: 07/31/2023] [Indexed: 08/31/2023] Open
Abstract
Background Despite significant progress in cardiopulmonary resuscitation and post-cardiac arrest care, favorable outcome in out-of hospital sudden cardiac arrest patients remains low. One of the main reasons for mortality in these patients is withdrawal of life-sustaining treatment. There is a need for precise and equitable prognostication tools to support families in avoiding premature or inappropriate WLST. Heart rate (HR) and heart rate variability (HRV) have been noted for their association with outcome, and are positioned to be a useful modality for prognostication. Objectives The aim of this scoping review is to rigorously explore which electrocardiography features have been shown to predict functional outcome in post-cardiac arrest patients. Methods The search was performed in Pubmed, EMBASE, and SCOPUS for studies published from January 1, 2011, to September 29, 2022, including papers in English or Korean. Results Seven studies were included with a total of 1359 patients. Four studies evaluated HR, one study evaluated RR inverval, and two studies evaluated HRV. All studies were retrospective, with 3 multi-center and 4 single-center studies. All seven studies were inclusive of patients who underwent targeted temperature management (TTM) after cardiac arrest, and two studies included patients without TTM. Five studies used cerebral performance category to assess functional outcome, two studies used Glasgow outcome score, and one study used modified Rankin scale. Three studies measured outcome at hospital discharge, one study measured outcome at 14 days after return of spontaneous circulation, two studies measured outcome after 3 months, and one after 1 year. In all studies that evaluated HR, lower HR was associated with favorable functional outcome. Two studies found that higher complexity of HRV was associated with favorable functional outcome. Conclusion HR and HRV showed clear associations with functional outcome in patients after CA, but cinilcial utility for prognostication is uncertain.
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Affiliation(s)
- Soon Bin Kwon
- Program for Hospital and Intensive Care Informatics, Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons, USA
| | - Murad Megjhani
- Program for Hospital and Intensive Care Informatics, Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons, USA
| | - Daniel Nametz
- Program for Hospital and Intensive Care Informatics, Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons, USA
| | - Sachin Agarwal
- Division of Critical Care and Hospitalist Neurology, Department of Neurology, Columbia University Irving Medical Center, NewYork-Presbyterian Hospital, USA
| | - Soojin Park
- Program for Hospital and Intensive Care Informatics, Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons, USA
- Division of Critical Care and Hospitalist Neurology, Department of Neurology, Columbia University Irving Medical Center, NewYork-Presbyterian Hospital, USA
- Department of Biomedical Informatics, Columbia University, USA
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Liuzzi P, Hakiki B, Scarpino M, Burali R, Maiorelli A, Draghi F, Romoli AM, Grippo A, Cecchi F, Mannini A. Neural coding of autonomic functions in different states of consciousness. J Neuroeng Rehabil 2023; 20:96. [PMID: 37491259 PMCID: PMC10369699 DOI: 10.1186/s12984-023-01216-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 07/10/2023] [Indexed: 07/27/2023] Open
Abstract
Detecting signs of residual neural activity in patients with altered states of consciousness is a crucial issue for the customization of neurorehabilitation treatments and clinical decision-making. With this large observational prospective study, we propose an innovative approach to detect residual signs of consciousness via the assessment of the amount of autonomic information coded within the brain. The latter was estimated by computing the mutual information (MI) between preprocessed EEG and ECG signals, to be then compared across consciousness groups, together with the absolute power and an international qualitative labeling. One-hundred seventy-four patients (73 females, 42%) were included in the study (median age of 65 years [IQR = 20], MCS +: 29, MCS -: 23, UWS: 29). Electroencephalography (EEG) information content was found to be mostly related to the coding of electrocardiography (ECG) activity, i.e., with higher MI (p < 0.05), in Unresponsive Wakefulness Syndrome and Minimally Consciousness State minus (MCS -). EEG-ECG MI, besides clearly discriminating patients in an MCS - and +, significantly differed between lesioned areas (sides) in a subgroup of unilateral hemorrhagic patients. Crucially, such an accessible and non-invasive measure of residual consciousness signs was robust across electrodes and patient groups. Consequently, exiting from a strictly neuro-centric consciousness detection approach may be the key to provide complementary insights for the objective assessment of patients' consciousness levels and for the patient-specific planning of rehabilitative interventions.
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Affiliation(s)
- Piergiuseppe Liuzzi
- Sant’Anna School of Advanced Studies, The BioRobotics Institute, Viale Rinaldo Piaggio 69, 56025 Pontedera, PI Italy
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI 50143 Florence, Italy
| | - Bahia Hakiki
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI 50143 Florence, Italy
| | - Maenia Scarpino
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI 50143 Florence, Italy
| | - Rachele Burali
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI 50143 Florence, Italy
| | - Antonio Maiorelli
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI 50143 Florence, Italy
| | - Francesca Draghi
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI 50143 Florence, Italy
| | - Anna Maria Romoli
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI 50143 Florence, Italy
| | - Antonello Grippo
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI 50143 Florence, Italy
| | - Francesca Cecchi
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI 50143 Florence, Italy
- Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, 50143 Florence, FI Italy
| | - Andrea Mannini
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI 50143 Florence, Italy
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Liuzzi P, Campagnini S, Hakiki B, Burali R, Scarpino M, Macchi C, Cecchi F, Mannini A, Grippo A. Heart rate variability for the evaluation of patients with disorders of consciousness. Clin Neurophysiol 2023; 150:31-39. [PMID: 37002978 DOI: 10.1016/j.clinph.2023.03.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 12/12/2022] [Accepted: 03/03/2023] [Indexed: 04/03/2023]
Abstract
OBJECTIVE Clinical responsiveness of patients with a Disorder of Consciousness (DoC) correlates to sympathetic/parasympathetic homeostatic balance. Heart Rate Variability (HRV) metrics result in non-invasive proxies of modulation capabilities of visceral states. In this work, our aim was to evaluate whether HRV measures could improve the differential diagnosis between Unresponsive Wakefulness Syndrome (UWS) and Minimally Conscious State (MCS) with respect to multivariate models based on standard clinical electroencephalography (EEG) labeling only in a rehabilitation setting. METHODS A prospective observational study was performed consecutively enrolling 82 DoC patients. Polygraphic recordings were performed. HRV-metrics and EEG descriptors derived from the American Clinical Neurophysiology Society's Standardized Critical Care terminology were included. Descriptors entered univariate and then multivariate logistic regressions with the target set to the UWS/MCS diagnosis. RESULTS HRV measures resulted significantly different between UWS and MCS patients, with higher values being associated with better consciousness levels. Specifically, adding HRV-related metrics to ACNS EEG descriptors increased the Nagelkerke R2 from 0.350 (only EEG descriptors) to 0.565 (HRV-EEG combination) with the outcome set to the consciousness diagnosis. CONCLUSIONS HRV changes across the lowest states of consciousness. Rapid changes in heart rate, occurring in better consciousness levels, confirm the mutual correlation between visceral state functioning patterns and consciousness alterations. SIGNIFICANCE Quantitative analysis of heart rate in patients with a DoC paves the way for the implementation of low-cost pipelines supporting medical decisions within multimodal consciousness assessments.
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Affiliation(s)
- Piergiuseppe Liuzzi
- IRCCS Fondazione Don Carlo Gnocchi, Firenze, Via di Scandicci 269, Italy; Scuola Superiore Sant'Anna, Istituto di BioRobotica, Pontedera, Viale Rinaldo Piaggio 34, Italy
| | - Silvia Campagnini
- IRCCS Fondazione Don Carlo Gnocchi, Firenze, Via di Scandicci 269, Italy; Scuola Superiore Sant'Anna, Istituto di BioRobotica, Pontedera, Viale Rinaldo Piaggio 34, Italy
| | - Bahia Hakiki
- IRCCS Fondazione Don Carlo Gnocchi, Firenze, Via di Scandicci 269, Italy.
| | - Rachele Burali
- IRCCS Fondazione Don Carlo Gnocchi, Firenze, Via di Scandicci 269, Italy
| | - Maenia Scarpino
- IRCCS Fondazione Don Carlo Gnocchi, Firenze, Via di Scandicci 269, Italy
| | - Claudio Macchi
- IRCCS Fondazione Don Carlo Gnocchi, Firenze, Via di Scandicci 269, Italy; Università di Firenze, Dipartimento di Medicina Sperimentale e Clinica, Firenze, Largo Brambilla 3, Italy
| | - Francesca Cecchi
- IRCCS Fondazione Don Carlo Gnocchi, Firenze, Via di Scandicci 269, Italy; Università di Firenze, Dipartimento di Medicina Sperimentale e Clinica, Firenze, Largo Brambilla 3, Italy
| | - Andrea Mannini
- IRCCS Fondazione Don Carlo Gnocchi, Firenze, Via di Scandicci 269, Italy
| | - Antonello Grippo
- IRCCS Fondazione Don Carlo Gnocchi, Firenze, Via di Scandicci 269, Italy
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Liuzzi P, Grippo A, Draghi F, Hakiki B, Macchi C, Cecchi F, Mannini A. Can Respiration Complexity Help the Diagnosis of Disorders of Consciousness in Rehabilitation? Diagnostics (Basel) 2023; 13:diagnostics13030507. [PMID: 36766612 PMCID: PMC9914359 DOI: 10.3390/diagnostics13030507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/23/2023] [Accepted: 01/27/2023] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Autonomic Nervous System (ANS) activity, as cardiac, respiratory and electrodermal activity, has been shown to provide specific information on different consciousness states. Respiration rates (RRs) are considered indicators of ANS activity and breathing patterns are currently already included in the evaluation of patients in critical care. OBJECTIVE The aim of this work was to derive a proxy of autonomic functions via the RR variability and compare its diagnostic capability with known neurophysiological biomarkers of consciousness. METHODS In a cohort of sub-acute patients with brain injury during post-acute rehabilitation, polygraphy (ECG, EEG) recordings were collected. The EEG was labeled via descriptors based on American Clinical Neurophysiology Society terminology and the respiration variability was extracted by computing the Approximate Entropy (ApEN) of the ECG-derived respiration signal. Competing logistic regressions were applied to evaluate the improvement in model performances introduced by the RR ApEN. RESULTS Higher RR complexity was significantly associated with higher consciousness levels and improved diagnostic models' performances in contrast to the ones built with only electroencephalographic descriptors. CONCLUSIONS Adding a quantitative, instrumentally based complexity measure of RR variability to multimodal consciousness assessment protocols may improve diagnostic accuracy based only on electroencephalographic descriptors. Overall, this study promotes the integration of biomarkers derived from the central and the autonomous nervous system for the most comprehensive diagnosis of consciousness in a rehabilitation setting.
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Affiliation(s)
- Piergiuseppe Liuzzi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, 50143 Firenze, Italy
- Istituto di BioRobotica, Scuola Superiore Sant’Anna, Viale Rinaldo Piaggio 34, 56025 Pontedera, Italy
| | - Antonello Grippo
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, 50143 Firenze, Italy
| | - Francesca Draghi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, 50143 Firenze, Italy
| | - Bahia Hakiki
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, 50143 Firenze, Italy
- Correspondence: ; Tel.: +39-333-401-8388
| | - Claudio Macchi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, 50143 Firenze, Italy
- Dipartimento di Medicina Sperimentale e Clinica, Universita di Firenze, Largo Brambilla 3, 50134 Firenze, Italy
| | - Francesca Cecchi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, 50143 Firenze, Italy
- Istituto di BioRobotica, Scuola Superiore Sant’Anna, Viale Rinaldo Piaggio 34, 56025 Pontedera, Italy
- Dipartimento di Medicina Sperimentale e Clinica, Universita di Firenze, Largo Brambilla 3, 50134 Firenze, Italy
| | - Andrea Mannini
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, 50143 Firenze, Italy
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Inhibitory Control and Brain–Heart Interaction: An HRV-EEG Study. Brain Sci 2022; 12:brainsci12060740. [PMID: 35741625 PMCID: PMC9221218 DOI: 10.3390/brainsci12060740] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/01/2022] [Accepted: 06/02/2022] [Indexed: 12/10/2022] Open
Abstract
Background: Motor inhibition is a complex cognitive function regulated by specific brain regions and influenced by the activity of the Central Autonomic Network. We investigate the two-way Brain–Heart interaction during a Go/NoGo task. Spectral EEG ϑ, α powerbands, and HRV parameters (Complexity Index (CI), Low Frequency (LF) and High Frequency (HF) powers) were recorded. Methods: Fourteen healthy volunteers were enrolled. We used a modified version of the classical Go/NoGo task, based on Rule Shift Cards, characterized by a baseline and two different tasks of different complexity. The participants were divided into subjects with Good (GP) and Poor (PP) performances. Results: In the baseline, CI was negatively correlated with α/ϑ. In task 1, the CI was negatively correlated with the errors and α/ϑ, while the errors were positively correlated with α/ϑ. In task 2, CI was negatively correlated with the Reaction Time and positively with α, and the errors were negatively correlated with the Reaction Time and positively correlated with α/ϑ. The GP group showed, at baseline, a negative correlation between CI and α/ϑ. Conclusions: We provide a new combined Brain–Heart model underlying inhibitory control abilities. The results are consistent with the complementary role of α and ϑ oscillations in cognitive control.
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