1
|
Laukkonen RE, Sacchet MD, Barendregt H, Devaney KJ, Chowdhury A, Slagter HA. Cessations of consciousness in meditation: Advancing a scientific understanding of nirodha samāpatti. Prog Brain Res 2023; 280:61-87. [PMID: 37714573 DOI: 10.1016/bs.pbr.2022.12.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/17/2023]
Abstract
Absence of consciousness can occur due to a concussion, anesthetization, intoxication, epileptic seizure, or other fainting/syncope episode caused by lack of blood flow to the brain. However, some meditation practitioners also report that it is possible to undergo a total absence of consciousness during meditation, lasting up to 7 days, and that these "cessations" can be consistently induced. One form of extended cessation (i.e., nirodha samāpatti) is thought to be different from sleep because practitioners are said to be completely impervious to external stimulation. That is, they cannot be 'woken up' from the cessation state as one might be from a dream. Cessations are also associated with the absence of any time experience or tiredness, and are said to involve a stiff rather than a relaxed body. Emergence from meditation-induced cessations is said to have profound effects on subsequent cognition and experience (e.g., resulting in a sudden sense of clarity, openness, and possibly insights). In this paper, we briefly outline the historical context for cessation events, present preliminary data from two labs, set a research agenda for their study, and provide an initial framework for understanding what meditation induced cessation may reveal about the mind and brain. We conclude by integrating these so-called nirodha and nirodha samāpatti experiences-as they are known in classical Buddhism-into current cognitive-neurocomputational and active inference frameworks of meditation.
Collapse
Affiliation(s)
- Ruben E Laukkonen
- Faculty of Health, Southern Cross University, Gold Coast, QLD, Australia.
| | - Matthew D Sacchet
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Henk Barendregt
- Faculty of Science, Radboud University, Nijmegen, The Netherlands
| | - Kathryn J Devaney
- UC Berkeley Center for the Science of Psychedelics, Berkeley, CA, United States
| | - Avijit Chowdhury
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Heleen A Slagter
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, the Netherlands & Institute for Brain and Behavior, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| |
Collapse
|
2
|
Davis JJJ, Kozma R, Schübeler F. Analysis of Meditation vs. Sensory Engaged Brain States Using Shannon Entropy and Pearson's First Skewness Coefficient Extracted from EEG Data. Sensors (Basel) 2023; 23:1293. [PMID: 36772332 PMCID: PMC9920060 DOI: 10.3390/s23031293] [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] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 01/19/2023] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
It has been proposed that meditative states show different brain dynamics than other more engaged states. It is known that when people sit with closed eyes instead of open eyes, they have different brain dynamics, which may be associated with a combination of deprived sensory input and more relaxed inner psychophysiological and cognitive states. Here, we study such states based on a previously established experimental methodology, with the aid of an electro-encephalography (EEG) array with 128 electrodes. We derived the Shannon Entropy (H) and Pearson's 1st Skewness Coefficient (PSk) from the power spectrum for the modalities of meditation and video watching, including 20 participants, 11 meditators and 9 non-meditators. The discriminating performance of the indices H and PSk was evaluated using Student's t-test. The results demonstrate a statistically significant difference between the mean H and PSk values during meditation and video watch modes. We show that the H index is useful to discriminate between Meditator and Non-Meditator participants during meditation over both the prefrontal and occipital areas, while the PSk index is useful to discriminate Meditators from Non-Meditators based on the prefrontal areas for both meditation and video modes. Moreover, we observe episodes of anti-correlation between the prefrontal and occipital areas during meditation, while there is no evidence for such anticorrelation periods during video watching. We outline directions of future studies incorporating further statistical indices for the characterization of brain states.
Collapse
Affiliation(s)
- Joshua J. J. Davis
- Department of Physics, Dodd-Walls Centre for Photonics and Quantum Technologies, University of Auckland, Auckland 1142, New Zealand
| | - Robert Kozma
- Department of Mathematics, University of Memphis, Memphis, TN 38152, USA
- Kozmos Research Laboratories, Boston, MA 02215, USA
- School of Informatics, Obuda University, H-1034 Budapest, Hungary
| | | |
Collapse
|
3
|
Alnes SL, Lucia M, Rossetti AO, Tzovara A. Complementary roles of neural synchrony and complexity for indexing consciousness and chances of surviving in acute coma. Neuroimage 2021; 245:118638. [PMID: 34624502 DOI: 10.1016/j.neuroimage.2021.118638] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 09/28/2021] [Accepted: 10/05/2021] [Indexed: 11/23/2022] Open
Abstract
An open challenge in consciousness research is understanding how neural functions are altered by pathological loss of consciousness. To maintain consciousness, the brain needs synchronized communication of information across brain regions, and sufficient complexity in neural activity. Coordination of brain activity, typically indexed through measures of neural synchrony, has been shown to decrease when consciousness is lost and to reflect the clinical state of patients with disorders of consciousness. Moreover, when consciousness is lost, neural activity loses complexity, while the levels of neural noise, indexed by the slope of the electroencephalography (EEG) spectral exponent decrease. Although these properties have been well investigated in resting state activity, it remains unknown whether the sensory processing network, which has been shown to be preserved in coma, suffers from a loss of synchronization or information content. Here, we focused on acute coma and hypothesized that neural synchrony in response to auditory stimuli would reflect coma severity, while complexity, or neural noise, would reflect the presence or loss of consciousness. Results showed that neural synchrony of EEG signals was stronger for survivors than non-survivors and predictive of patients' outcome, but indistinguishable between survivors and healthy controls. Measures of neural complexity and neural noise were not informative of patients' outcome and had high or low values for patients compared to controls. Our results suggest different roles for neural synchrony and complexity in acute coma. Synchrony represents a precondition for consciousness, while complexity needs an equilibrium between high or low values to support conscious cognition.
Collapse
|
4
|
Tivadar RI, Knight RT, Tzovara A. Automatic Sensory Predictions: A Review of Predictive Mechanisms in the Brain and Their Link to Conscious Processing. Front Hum Neurosci 2021; 15:702520. [PMID: 34489663 PMCID: PMC8416526 DOI: 10.3389/fnhum.2021.702520] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [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: 04/29/2021] [Accepted: 07/12/2021] [Indexed: 01/22/2023] Open
Abstract
The human brain has the astonishing capacity of integrating streams of sensory information from the environment and forming predictions about future events in an automatic way. Despite being initially developed for visual processing, the bulk of predictive coding research has subsequently focused on auditory processing, with the famous mismatch negativity signal as possibly the most studied signature of a surprise or prediction error (PE) signal. Auditory PEs are present during various consciousness states. Intriguingly, their presence and characteristics have been linked with residual levels of consciousness and return of awareness. In this review we first give an overview of the neural substrates of predictive processes in the auditory modality and their relation to consciousness. Then, we focus on different states of consciousness - wakefulness, sleep, anesthesia, coma, meditation, and hypnosis - and on what mysteries predictive processing has been able to disclose about brain functioning in such states. We review studies investigating how the neural signatures of auditory predictions are modulated by states of reduced or lacking consciousness. As a future outlook, we propose the combination of electrophysiological and computational techniques that will allow investigation of which facets of sensory predictive processes are maintained when consciousness fades away.
Collapse
Affiliation(s)
| | - Robert T. Knight
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
- Department of Psychology, University of California, Berkeley, Berkeley, CA, United States
| | - Athina Tzovara
- Institute of Computer Science, University of Bern, Bern, Switzerland
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
- Sleep-Wake Epilepsy Center | NeuroTec, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| |
Collapse
|
5
|
Schindler KA, Nef T, Baud MO, Tzovara A, Yilmaz G, Tinkhauser G, Gerber SM, Gnarra O, Warncke JD, Schütz N, Knobel SEJ, Schmidt MH, Krack P, Fröhlich F, Sznitman R, Rothen S, Bassetti CLA. NeuroTec Sitem-Insel Bern: Closing the Last Mile in Neurology. CTN 2021; 5:13. [DOI: 10.3390/ctn5020013] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Neurology is focused on a model where patients receive their care through repeated visits to clinics and doctor’s offices. Diagnostic tests often require expensive and specialized equipment that are only available in clinics. However, this current model has significant drawbacks. First, diagnostic tests, such as daytime EEG and sleep studies, occur under artificial conditions in the clinic, which may mask or wrongly emphasize clinically important features. Second, early detection and high-quality management of chronic neurological disorders require repeat measurements to accurately capture the dynamics of the disease process, which is impractical to execute in the clinic for economical and logistical reasons. Third, clinic visits remain inaccessible to many patients due to geographical and economical circumstances. Fourth, global disruptions to daily life, such as the one caused by COVID-19, can seriously harm patients if access to in-person clinical visits for diagnostic and treatment purposes is throttled. Thus, translating diagnostic and treatment procedures to patients’ homes will convey multiple substantial benefits and has the potential to substantially improve clinical outcomes while reducing cost. NeuroTec was founded to accelerate the re-imagining of neurology and to promote the convergence of technological, scientific, medical and societal processes. The goal is to identify and validate new digital biomarkers that can close the last mile in neurology by enabling the translation of personalized diagnostics and therapeutic interventions from the clinic to the patient’s home.
Collapse
|
6
|
Lasaponara S, D'Onofrio M, Pinto M, Aiello M, Pellegrino M, Scozia G, De Lucia M, Doricchi F. Individual EEG profiling of attention deficits in left spatial neglect: A pilot study. Neurosci Lett 2021; 761:136097. [PMID: 34237413 DOI: 10.1016/j.neulet.2021.136097] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 05/13/2021] [Accepted: 06/29/2021] [Indexed: 11/24/2022]
Abstract
Electrophysiological group studies in brain-damaged patients can be run to capture the EEG correlates of specific cognitive impairments. Nonetheless, this procedure is not adequate to characterize the inter-individual variability present in major neuropsychological syndromes. We tested the possibility of getting a reliable individual EEG characterization of deficits of endogenous orienting of spatial attention in right-brain damaged (RBD) patients with left spatial neglect (N+). We used a single-trial topographical analysis (STTA; [39] of individual scalp EEG topographies recorded during leftward and rightward orienting of attention with central cues in RBD patients with and without (N-) neglect and in healthy controls (HC). We found that the STTA successfully decoded EEG signals related to leftward and rightward orienting in five out of the six N+, five out of the six N- patients and in all the six HC. In agreement with findings from conventional average-group studies, successful classifications of EEG signals in N+ were observed during the 400-800 ms period post-cue-onset, which reflects preserved voluntary engagement of attention resources (ADAN component). These results suggest the possibility of acquiring reliable individual EEG profiles of neglect patients.
Collapse
Affiliation(s)
- Stefano Lasaponara
- Dipartimento di Psicologia 39, Università degli Studi di Roma "La Sapienza", Via dei Marsi 78, 00185 Roma, Italy; Fondazione Santa Lucia, Centro Ricerche di Neuropsicologia, IRCCS, Via Ardeatina 306, 00179 Roma, Italy.
| | - Marianna D'Onofrio
- Dipartimento di Psicologia 39, Università degli Studi di Roma "La Sapienza", Via dei Marsi 78, 00185 Roma, Italy
| | - Mario Pinto
- Fondazione Santa Lucia, Centro Ricerche di Neuropsicologia, IRCCS, Via Ardeatina 306, 00179 Roma, Italy
| | | | - Michele Pellegrino
- Dipartimento di Psicologia 39, Università degli Studi di Roma "La Sapienza", Via dei Marsi 78, 00185 Roma, Italy; Fondazione Santa Lucia, Centro Ricerche di Neuropsicologia, IRCCS, Via Ardeatina 306, 00179 Roma, Italy
| | - Gabriele Scozia
- Dipartimento di Psicologia 39, Università degli Studi di Roma "La Sapienza", Via dei Marsi 78, 00185 Roma, Italy
| | - Marzia De Lucia
- Centre for Research in Neuroscience - Department of Clinical Neurosciences, CHUV - UNIL, Chemin de Mont-Paisible,16, 1011 Lausanne, Switzerland
| | - Fabrizio Doricchi
- Dipartimento di Psicologia 39, Università degli Studi di Roma "La Sapienza", Via dei Marsi 78, 00185 Roma, Italy; Fondazione Santa Lucia, Centro Ricerche di Neuropsicologia, IRCCS, Via Ardeatina 306, 00179 Roma, Italy
| |
Collapse
|
7
|
Kustermann T, Ata Nguepnjo Nguissi N, Pfeiffer C, Haenggi M, Kurmann R, Zubler F, Oddo M, Rossetti AO, De Lucia M. Brain functional connectivity during the first day of coma reflects long-term outcome. Neuroimage Clin 2020; 27:102295. [PMID: 32563037 PMCID: PMC7305428 DOI: 10.1016/j.nicl.2020.102295] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [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: 06/14/2019] [Revised: 04/30/2020] [Accepted: 05/04/2020] [Indexed: 01/02/2023]
Abstract
Coma patients show different connectivity patterns depending on long-term outcome. Time-variance of functional connectivity is an early prognostic marker for coma patients. Connectivity patterns observed in chronic patients may develop early after coma onset.
Objective In patients with disorders of consciousness (DOC), properties of functional brain networks at rest are informative of the degree of consciousness impairment and of long-term outcome. Here we investigate whether connectivity differences between patients with favorable and unfavorable outcome are already present within 24 h of coma onset. Methods We prospectively recorded 63-channel electroencephalography (EEG) at rest during the first day of coma after cardiac arrest. We analyzed 98 adults, of whom 57 survived beyond unresponsive wakefulness. Functional connectivity was estimated by computing the ‘debiased weighted phase lag index’ over epochs of five seconds duration. We evaluated the network’s topological features, including clustering coefficient, path length, modularity and participation coefficient and computed their variance over time. Finally, we estimated the predictive value of these topological features for patients’ outcomes by splitting the patient sample in training and test datasets. Results Group-level analysis revealed lower clustering coefficient, higher modularity and path length variance in patients with favorable compared to those with unfavorable outcomes (p < 0.01). Within all features, the path length variance in the network provided the best positive predictive value (PPV) for favorable outcome and specificity for unfavorable outcome in the test dataset (PPV: 0.83, p < 0.01; specificity: 0.86, p < 0.01) with above-chance negative predictive value and accuracy. Of note, the exclusion of patients with epileptiform activity (20 in total) eliminates all false positive predictions (n = 6) for path length variance. Interpretation Topological features of functional connectivity differ as a function of long-term outcome in patients on the first day of coma. These differences are not interpretable in terms of consciousness levels as all patients were in a deep unconscious state. The time variance of path length is informative of comatose patients’ outcome, as patients with favorable outcome exhibit a richer repertoire of path length than those with unfavorable outcomes.
Collapse
Affiliation(s)
- Thomas Kustermann
- Laboratoire de Recherche en Neuroimagerie (LREN), University Hospital (CHUV) & University of Lausanne, Switzerland.
| | | | | | - Matthias Haenggi
- Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Rebekka Kurmann
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Frédéric Zubler
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Mauro Oddo
- Department of Intensive Care Medicine, University Hospital (CHUV) & University of Lausanne, Switzerland
| | - Andrea O Rossetti
- Department of Neurology, University Hospital (CHUV) & University of Lausanne, Switzerland
| | - Marzia De Lucia
- Laboratoire de Recherche en Neuroimagerie (LREN), University Hospital (CHUV) & University of Lausanne, Switzerland
| |
Collapse
|
8
|
Zuk NJ, Teoh ES, Lalor EC. EEG-based classification of natural sounds reveals specialized responses to speech and music. Neuroimage 2020; 210:116558. [DOI: 10.1016/j.neuroimage.2020.116558] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 12/23/2019] [Accepted: 01/14/2020] [Indexed: 11/30/2022] Open
|
9
|
Salvari V, Paraskevopoulos E, Chalas N, Müller K, Wollbrink A, Dobel C, Korth D, Pantev C. Auditory Categorization of Man-Made Sounds Versus Natural Sounds by Means of MEG Functional Brain Connectivity. Front Neurosci 2019; 13:1052. [PMID: 31636532 PMCID: PMC6787283 DOI: 10.3389/fnins.2019.01052] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [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: 06/10/2019] [Accepted: 09/19/2019] [Indexed: 01/27/2023] Open
Abstract
Previous neuroimaging studies have shown that sounds can be discriminated due to living-related or man-made-related characteristics and involve different brain regions. However, these studies have mainly provided source space analyses, which offer simple maps of activated brain regions but do not explain how regions of a distributed system are functionally organized under a specific task. In the present study, we aimed to further examine the functional connectivity of the auditory processing pathway across different categories of non-speech sounds in healthy adults, by means of MEG. Our analyses demonstrated significant activation and interconnection differences between living and man-made object sounds, in the prefrontal areas, anterior-superior temporal gyrus (aSTG), posterior cingulate cortex (PCC), and supramarginal gyrus (SMG), occurring within 80–120 ms post-stimulus interval. Current findings replicated previous ones, in that other regions beyond the auditory cortex are involved during auditory processing. According to the functional connectivity analysis, differential brain networks across the categories exist, which proposes that sound category discrimination processing relies on distinct cortical networks, a notion that has been strongly argued in the literature also in relation to the visual system.
Collapse
Affiliation(s)
- Vasiliki Salvari
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | - Evangelos Paraskevopoulos
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany.,School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Nikolas Chalas
- School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Kilian Müller
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | - Andreas Wollbrink
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | - Christian Dobel
- Department of Otorhinolaryngology, Friedrich-Schiller University of Jena, Jena, Germany
| | - Daniela Korth
- Department of Otorhinolaryngology, Friedrich-Schiller University of Jena, Jena, Germany
| | - Christo Pantev
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| |
Collapse
|
10
|
Pfeiffer C, Nguissi NAN, Chytiris M, Bidlingmeyer P, Haenggi M, Kurmann R, Zubler F, Accolla E, Viceic D, Rusca M, Oddo M, Rossetti AO, De Lucia M. Somatosensory and auditory deviance detection for outcome prediction during postanoxic coma. Ann Clin Transl Neurol 2018; 5:1016-1024. [PMID: 30250859 PMCID: PMC6144443 DOI: 10.1002/acn3.600] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [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: 03/14/2018] [Revised: 05/16/2018] [Accepted: 06/07/2018] [Indexed: 11/26/2022] Open
Abstract
Objective Prominent research in patients with disorders of consciousness investigated the electrophysiological correlates of auditory deviance detection as a marker of consciousness recovery. Here, we extend previous studies by investigating whether somatosensory deviance detection provides an added value for outcome prediction in postanoxic comatose patients. Methods Electroencephalography responses to frequent and rare stimuli were obtained from 66 patients on the first and second day after coma onset. Results Multivariate decoding analysis revealed an above chance‐level auditory discrimination in 25 patients on the first day and in 31 patients on the second day. Tactile discrimination was significant in 16 patients on the first day and in 23 patients on the second day. Single‐day sensory discrimination was unrelated to patients’ outcome in both modalities. However, improvement of auditory discrimination from first to the second day was predictive of good outcome with a positive predictive power (PPV) of 0.73 (CI = 0.52–0.88). Analyses considering the improvement of tactile, auditory and tactile, or either auditory or tactile discrimination showed no significant prediction of good outcome (PPVs = 0.58–0.68). Interpretation Our results show that in the acute phase of coma deviance detection is largely preserved for both auditory and tactile modalities. However, we found no evidence for an added value of somatosensory to auditory deviance detection function for coma‐outcome prediction.
Collapse
Affiliation(s)
- Christian Pfeiffer
- Laboratoire de Recherche en Neuroimagerie (LREN) University Hospital (CHUV) & University of Lausanne Lausanne Switzerland
| | - Nathalie Ata Nguepnjo Nguissi
- Laboratoire de Recherche en Neuroimagerie (LREN) University Hospital (CHUV) & University of Lausanne Lausanne Switzerland
| | - Magali Chytiris
- Laboratoire de Recherche en Neuroimagerie (LREN) University Hospital (CHUV) & University of Lausanne Lausanne Switzerland
| | - Phanie Bidlingmeyer
- Laboratoire de Recherche en Neuroimagerie (LREN) University Hospital (CHUV) & University of Lausanne Lausanne Switzerland
| | - Matthias Haenggi
- Department of Intensive Care Medicine Inselspital Bern University Hospital University of Bern Bern Switzerland
| | - Rebekka Kurmann
- Department of Neurology Inselspital Bern University Hospital University of Bern Bern Switzerland
| | - Frédéric Zubler
- Department of Neurology Inselspital Bern University Hospital University of Bern Bern Switzerland
| | - Ettore Accolla
- Neurology Unit Department of Medicine Hôpital Cantonal Fribourg (HFR) Fribourg Switzerland.,Laboratory for Cognitive and Neurological Sciences Department of Medicine University of Fribourg Fribourg Switzerland
| | | | - Marco Rusca
- Intensive Care Medicine Hôpital du Valais Sion Switzerland
| | - Mauro Oddo
- Department of Intensive Care Medicine University Hospital (CHUV) & University of Lausanne Lausanne Switzerland
| | - Andrea O Rossetti
- Neurology Service University Hospital (CHUV) & University of Lausanne Lausanne Switzerland
| | - Marzia De Lucia
- Laboratoire de Recherche en Neuroimagerie (LREN) University Hospital (CHUV) & University of Lausanne Lausanne Switzerland
| |
Collapse
|
11
|
Juan E, Nguepnjo Nguissi NA, Tzovara A, Viceic D, Rusca M, Oddo M, Rossetti AO, De Lucia M. Evidence of trace conditioning in comatose patients revealed by the reactivation of EEG responses to alerting sounds. Neuroimage 2016; 141:530-41. [DOI: 10.1016/j.neuroimage.2016.07.039] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Revised: 06/08/2016] [Accepted: 07/17/2016] [Indexed: 11/20/2022] Open
|
12
|
Namazi H, Khosrowabadi R, Hussaini J, Habibi S, Farid AA, Kulish VV. Analysis of the influence of memory content of auditory stimuli on the memory content of EEG signal. Oncotarget 2016; 7:56120-56128. [PMID: 27528219 PMCID: PMC5302900 DOI: 10.18632/oncotarget.11234] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [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: 06/04/2016] [Accepted: 07/29/2016] [Indexed: 11/25/2022] Open
Abstract
One of the major challenges in brain research is to relate the structural features of the auditory stimulus to structural features of Electroencephalogram (EEG) signal. Memory content is an important feature of EEG signal and accordingly the brain. On the other hand, the memory content can also be considered in case of stimulus. Beside all works done on analysis of the effect of stimuli on human EEG and brain memory, no work discussed about the stimulus memory and also the relationship that may exist between the memory content of stimulus and the memory content of EEG signal. For this purpose we consider the Hurst exponent as the measure of memory. This study reveals the plasticity of human EEG signals in relation to the auditory stimuli. For the first time we demonstrated that the memory content of an EEG signal shifts towards the memory content of the auditory stimulus used. The results of this analysis showed that an auditory stimulus with higher memory content causes a larger increment in the memory content of an EEG signal. For the verification of this result, we benefit from approximate entropy as indicator of time series randomness. The capability, observed in this research, can be further investigated in relation to human memory.
Collapse
Affiliation(s)
- Hamidreza Namazi
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
| | - Reza Khosrowabadi
- Institute for Cognitive and Brain Science, Shahid Beheshti University, Tehran, Iran
| | - Jamal Hussaini
- Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Selangor, Malaysia
| | | | - Ali Akhavan Farid
- Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia
| | - Vladimir V. Kulish
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
| |
Collapse
|
13
|
Tzovara A, Rossetti AO, Juan E, Suys T, Viceic D, Rusca M, Oddo M, Lucia MD. Prediction of awakening from hypothermic postanoxic coma based on auditory discrimination. Ann Neurol 2016; 79:748-757. [DOI: 10.1002/ana.24622] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2015] [Revised: 02/17/2016] [Accepted: 02/17/2016] [Indexed: 11/12/2022]
Affiliation(s)
- Athina Tzovara
- Neuroimaging Research Laboratory, Department of Clinical Neurosciences; Lausanne University Hospital and University of Lausanne; Lausanne Switzerland
- Department of Psychiatry, Psychotherapy; and Psychosomatics and Neuroscience Centre Zurich; University of Zurich Switzerland
| | - Andrea O. Rossetti
- Neurology Service, Department of Clinical Neurosciences; Lausanne University Hospital and University of Lausanne; Lausanne Switzerland
| | - Elsa Juan
- Neuroimaging Research Laboratory, Department of Clinical Neurosciences; Lausanne University Hospital and University of Lausanne; Lausanne Switzerland
- Neurology Service, Department of Clinical Neurosciences; Lausanne University Hospital and University of Lausanne; Lausanne Switzerland
| | - Tamarah Suys
- Department of Intensive Care Medicine; Lausanne University Hospital and University of Lausanne; Lausanne Switzerland
| | | | - Marco Rusca
- Intensive Care Medicine Service; Valais Hospital; Sion Switzerland
| | - Mauro Oddo
- Department of Intensive Care Medicine; Lausanne University Hospital and University of Lausanne; Lausanne Switzerland
| | - Marzia De Lucia
- Neuroimaging Research Laboratory, Department of Clinical Neurosciences; Lausanne University Hospital and University of Lausanne; Lausanne Switzerland
| |
Collapse
|
14
|
Affiliation(s)
- Marzia De Lucia
- Laboratoire de Recherche en Neuroimagerie (LREN), Department of Clinical Neuroscience, Lausanne University and University Hospital, Lausanne, CH-1011, Switzerland
| | - Athina Tzovara
- Laboratoire de Recherche en Neuroimagerie (LREN), Department of Clinical Neuroscience, Lausanne University and University Hospital, Lausanne, CH-1011, Switzerland Department of Psychiatry, Psychotherapy, and Psychosomatics, University of Zurich, CH-8032, Switzerland Neuroscience Centre Zurich University of Zurich, CH-8032, Switzerland
| |
Collapse
|
15
|
Abstract
Much research on the laterality of affective auditory stimuli features emotional speech. However, environmental sounds can also carry affective information, but their lateralized processing for affect has been studied much less. We studied this in 2 experiments. In Experiment 1 we explored whether the detection of affective environmental sounds (from International Affective Digital Sounds) that appeared in auditory scenes was lateralized. While we found that negative targets were detected more rapidly, detection latencies were the same on the left and right. In Experiment 2 we examined whether conscious appraisal of the stimulus was needed for lateralization patterns to emerge, and asked participants to rate the stimuli's pleasantness in a dichotic listening test. This showed that when positive/negative environmental sounds were in the attended to-be-rated channel, ratings were the same regardless of laterality. However, when participants rated neutral stimuli and the unattended channel was positive/negative, the valence of the unattended channel affected the neutral ratings more strongly with left ear (right hemisphere, RH) processing of the affective sound. We link our findings to previous work that suggests that the RH may specialize in the unconscious processing of emotion via subcortical routes.
Collapse
Affiliation(s)
- Astrid Schepman
- a Department of Psychology , University of Chester , Chester , UK
| | - Paul Rodway
- a Department of Psychology , University of Chester , Chester , UK
| | - Hayley Pritchard
- a Department of Psychology , University of Chester , Chester , UK
| |
Collapse
|
16
|
Tzovara A, Chavarriaga R, De Lucia M. Quantifying the time for accurate EEG decoding of single value-based decisions. J Neurosci Methods 2015; 250:114-25. [DOI: 10.1016/j.jneumeth.2014.09.029] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2014] [Revised: 09/25/2014] [Accepted: 09/25/2014] [Indexed: 11/20/2022]
|
17
|
Chouiter L, Tzovara A, Dieguez S, Annoni JM, Magezi D, De Lucia M, Spierer L. Experience-based Auditory Predictions Modulate Brain Activity to Silence as do Real Sounds. J Cogn Neurosci 2015; 27:1968-80. [PMID: 26042500 DOI: 10.1162/jocn_a_00835] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Interactions between stimuli's acoustic features and experience-based internal models of the environment enable listeners to compensate for the disruptions in auditory streams that are regularly encountered in noisy environments. However, whether auditory gaps are filled in predictively or restored a posteriori remains unclear. The current lack of positive statistical evidence that internal models can actually shape brain activity as would real sounds precludes accepting predictive accounts of filling-in phenomenon. We investigated the neurophysiological effects of internal models by testing whether single-trial electrophysiological responses to omitted sounds in a rule-based sequence of tones with varying pitch could be decoded from the responses to real sounds and by analyzing the ERPs to the omissions with data-driven electrical neuroimaging methods. The decoding of the brain responses to different expected, but omitted, tones in both passive and active listening conditions was above chance based on the responses to the real sound in active listening conditions. Topographic ERP analyses and electrical source estimations revealed that, in the absence of any stimulation, experience-based internal models elicit an electrophysiological activity different from noise and that the temporal dynamics of this activity depend on attention. We further found that the expected change in pitch direction of omitted tones modulated the activity of left posterior temporal areas 140-200 msec after the onset of omissions. Collectively, our results indicate that, even in the absence of any stimulation, internal models modulate brain activity as do real sounds, indicating that auditory filling in can be accounted for by predictive activity.
Collapse
Affiliation(s)
| | - Athina Tzovara
- University of Lausanne.,University Hospital of Lausanne.,University of Zürich
| | | | | | | | | | | |
Collapse
|
18
|
Tzovara A, Simonin A, Oddo M, Rossetti AO, De Lucia M. Neural detection of complex sound sequences in the absence of consciousness. Brain 2015; 138:1160-6. [PMID: 25740220 DOI: 10.1093/brain/awv041] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [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: 08/05/2014] [Accepted: 12/09/2014] [Indexed: 12/14/2022] Open
Abstract
The neural response to a violation of sequences of identical sounds is a typical example of the brain's sensitivity to auditory regularities. Previous literature interprets this effect as a pre-attentive and unconscious processing of sensory stimuli. By contrast, a violation to auditory global regularities, i.e. based on repeating groups of sounds, is typically detectable when subjects can consciously perceive them. Here, we challenge the notion that global detection implies consciousness by testing the neural response to global violations in a group of 24 patients with post-anoxic coma (three females, age range 45-87 years), treated with mild therapeutic hypothermia and sedation. By applying a decoding analysis to electroencephalographic responses to standard versus deviant sound sequences, we found above-chance decoding performance in 10 of 24 patients (Wilcoxon signed-rank test, P < 0.001), despite five of them being mildly hypothermic, sedated and unarousable. Furthermore, consistently with previous findings based on the mismatch negativity the progression of this decoding performance was informative of patients' chances of awakening (78% predictive of awakening). Our results show for the first time that detection of global regularities at neural level exists despite a deeply unconscious state.
Collapse
Affiliation(s)
- Athina Tzovara
- 1 Centre for Biomedical Imaging (CIBM), Department of Radiology, Lausanne, University Hospital and University of Lausanne, CH-1011 Lausanne, Switzerland 2 Laboratoire de Recherche en Neuroimagerie (LREN), Department of Clinical Neurosciences, Lausanne University and University Hospital, Lausanne, CH-1011, Switzerland
| | - Alexandre Simonin
- 3 Department of Clinical Neurosciences, University Hospital, Lausanne, CH-1011, Switzerland
| | - Mauro Oddo
- 4 Department of Intensive Care Medicine, CH-1011, Lausanne University Hospital, Switzerland
| | - Andrea O Rossetti
- 3 Department of Clinical Neurosciences, University Hospital, Lausanne, CH-1011, Switzerland
| | - Marzia De Lucia
- 1 Centre for Biomedical Imaging (CIBM), Department of Radiology, Lausanne, University Hospital and University of Lausanne, CH-1011 Lausanne, Switzerland 2 Laboratoire de Recherche en Neuroimagerie (LREN), Department of Clinical Neurosciences, Lausanne University and University Hospital, Lausanne, CH-1011, Switzerland
| |
Collapse
|
19
|
De Lucia M, Tzovara A. Decoding auditory EEG responses in healthy and clinical populations: A comparative study. J Neurosci Methods 2014; 250:106-13. [PMID: 25445243 DOI: 10.1016/j.jneumeth.2014.10.019] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [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: 05/30/2014] [Revised: 10/21/2014] [Accepted: 10/22/2014] [Indexed: 12/17/2022]
Abstract
BACKGROUND Analyses of brain responses to external stimuli are typically based on the means computed across conditions. However in many cognitive and clinical applications, taking into account their variability across trials has turned out to be statistically more sensitive than comparing their means. NEW METHOD In this study we present a novel implementation of a single-trial topographic analysis (STTA) for discriminating auditory evoked potentials at predefined time-windows. This analysis has been previously introduced for extracting spatio-temporal features at the level of the whole neural response. Adapting the STTA on specific time windows is an essential step for comparing its performance to other time-window based algorithms. RESULTS We analyzed responses to standard vs. deviant sounds and showed that the new implementation of the STTA gives above-chance decoding results in all subjects (in comparison to 7 out of 11 with the original method). In comatose patients, the improvement of the decoding performance was even more pronounced than in healthy controls and doubled the number of significant results. COMPARISON WITH EXISTING METHOD(S) We compared the results obtained with the new STTA to those based on a logistic regression in healthy controls and patients. We showed that the first of these two comparisons provided a better performance of the logistic regression; however only the new STTA provided significant results in comatose patients at group level. CONCLUSIONS Our results provide quantitative evidence that a systematic investigation of the accuracy of established methods in normal and clinical population is an essential step for optimizing decoding performance.
Collapse
Affiliation(s)
- Marzia De Lucia
- Laboratoire de recherche en Neuroimagerie (LREN), Department of Clinical Neurosciences, Lausanne University and University Hospital, 1011 Lausanne, Switzerland; Radiology Department, Vaudois University Hospital and University of Lausanne, 1011, Switzerland; Center for Biomedical Imaging (CIBM) of Lausanne and Geneva, 1011, Switzerland.
| | - Athina Tzovara
- Laboratoire de recherche en Neuroimagerie (LREN), Department of Clinical Neurosciences, Lausanne University and University Hospital, 1011 Lausanne, Switzerland; Radiology Department, Vaudois University Hospital and University of Lausanne, 1011, Switzerland; Center for Biomedical Imaging (CIBM) of Lausanne and Geneva, 1011, Switzerland
| |
Collapse
|