58 research outputs found

    Detecting and interpreting conscious experiences in behaviorally non-responsive patients

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    Decoding the contents of consciousness from brain activity is one of the most challenging frontiers of cognitive neuroscience. The ability to interpret mental content without recourse to behavior is most relevant for understanding patients who may be demonstrably conscious, but entirely unable to speak or move willfully in any way, precluding any systematic investigation of their conscious experience. The lack of consistent behavioral responsivity engenders unique challenges to decoding any conscious experiences these patients may have solely based on their brain activity. For this reason, paradigms that have been successful in healthy individuals cannot serve to interpret conscious mental states in this patient group. Until recently, patient studies have used structured instructions to elicit willful modulation of brain activity according to command, in order to decode the presence of willful brain-based responses in this patient group. In recent work, we have used naturalistic paradigms, such as watching a movie or listening to an audio-story, to demonstrate that a common neural code supports conscious experiences in different individuals. Moreover, we have demonstrated that this code can be used to interpret the conscious experiences of a patient who had remained non-responsive for several years. This approach is easy to administer, brief, and does not require compliance with task instructions. Rather, it engages attention naturally through meaningful stimuli that are similar to the real-world sensory information in a patient\u27s environment. Therefore, it may be particularly suited to probing consciousness and revealing residual brain function in highly impaired, acute, patients in a comatose state, thus helping to improve diagnostication and prognostication for this vulnerable patient group from the critical early stages of severe brain-injury

    Healthy Aging and Dementia: Two Roads Diverging in Midlife?

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    Dementia, particularly Alzheimer’s disease (AD), is a growing pandemic that presents profound challenges to healthcare systems, families, and societies throughout the world. By 2050, the number of people living with dementia worldwide could almost triple, from 47 to 132 million, with associated costs rising to $3 trillion. To reduce the future incidence of dementia, there is an immediate need for interventions that target the disease process from its earliest stages. Research programs are increasingly starting to focus on midlife as a critical period for the beginning of AD-related pathology, yet the indicators of the incipient disease process in asymptomatic individuals remain poorly understood. We address this important knowledge gap by examining evidence for cognitive and structural brain changes that may differentiate, from midlife, healthy aging and pathological AD-related processes. This review crystallizes emerging trends for divergence between the two and highlights current limitations and opportunities for future research in this area

    While you were sleeping: Evidence for high-level executive processing of an auditory narrative during sleep

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    During sleep we lack conscious awareness of the external environment. Yet, our internal mental state suggests that high-level cognitive processes persist. The nature and extent to which the external environment is processed during sleep remain largely unexplored. Here, we used an fMRI synchronization-based approach to examine responses to a narrative during wakefulness and sleep. The stimulus elicited the auditory network and a frontoparietal pattern of activity, consistent with high-level narrative plot-following. During REM sleep, the same frontoparietal pattern was observed in one of three participants, and partially in one other, confirming that it is possible to track and follow the moment-to-moment complexities of a narrative during REM sleep. Auditory network recruitment was observed in both non-REM and REM sleep, demonstrating preservation of low-level auditory processing, even in deep sleep. This novel approach investigating cognitive processing at different levels of awareness demonstrates that the brain can meaningfully process the external environment during REM sleep

    Assessing the feasibility of time-resolved fNIRS to detect brain activity during motor imagery

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    Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical technique for detecting brain activity, which has been previously used during motor and motor executive tasks. There is an increasing interest in using fNIRS as a brain computer interface (BCI) for patients who lack the physical, but not the mental, ability to respond to commands. The goal of this study is to assess the feasibility of time-resolved fNIRS to detect brain activity during motor imagery. Stability tests were conducted to ensure the temporal stability of the signal, and motor imagery data were acquired on healthy subjects. The NIRS probes were placed on the scalp over the premotor cortex (PMC) and supplementary motor area (SMA), as these areas are responsible for motion planning. To confirm the fNIRS results, subjects underwent functional magnetic resonance imaging (fMRI) while performing the same task. Seven subjects have participated to date, and significant activation in the SMA and/or the PMC during motor imagery was detected by both fMRI and fNIRS in 4 of the 7 subjects. No activation was detected by either technique in the remaining three participants, which was not unexpected due to the nature of the task. The agreement between the two imaging modalities highlights the potential of fNIRS as a BCI, which could be adapted for bedside studies of patients with disorders of consciousness

    Can time-resolved NIRS provide the sensitivity to detect brain activity during motor imagery consistently?

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    Previous functional magnetic resonance imaging (fMRI) studies have shown that a subgroup of patients diagnosed as being in a vegetative state are aware and able to communicate by performing a motor imagery task in response to commands. Due to the fMRI\u27s cost and accessibility, there is a need for exploring different imaging modalities that can be used at the bedside. A promising technique is functional near infrared spectroscopy (fNIRS) that has been successfully applied to measure brain oxygenation in humans. Due to the limited depth sensitivity of continuous-wave NIRS, time-resolved (TR) detection has been proposed as a way of enhancing the sensitivity to the brain, since late arriving photons have a higher probability of reaching the brain. The goal of this study was to assess the feasibility and sensitivity of TR fNIRS in detecting brain activity during motor imagery. Fifteen healthy subjects were recruited in this study, and the fNIRS results were validated using fMRI. The change in the statistical moments of the distribution of times of flight (number of photons, mean time of flight and variance) were calculated for each channel to determine the presence of brain activity. The results indicate up to an 86% agreement between fMRI and TR-fNIRS and the sensitivity ranging from 64 to 93% with the highest value determined for the mean time of flight. These promising results highlight the potential of TR-fNIRS as a portable brain computer interface for patients with disorder of consciousness

    Modeling an auditory stimulated brain under altered states of consciousness using the generalized ising model

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    Propofol is a short-acting medication that results in decreased levels of consciousness and is used for general anesthesia. Although it is the most commonly used anesthetic in the world, much remains unknown about the mechanisms by which it induces a loss of consciousness. Characterizing anesthesia-induced alterations to brain network activity might provide a powerful framework for understanding the neural mechanisms of unconsciousness. The aim of this work was to model brain activity in healthy brains during various stages of consciousness, as induced by propofol, in the auditory paradigm. We used the generalized Ising model (GIM) to fit the empirical fMRI data of healthy subjects while they listened to an audio clip from a movie. The external stimulus (audio clip) is believed to be at least partially driving a synchronization process of the brain activity and provides a similar conscious experience in different subjects. In order to observe the common synchronization among the subjects, a novel technique called the inter subject correlation (ISC) was implemented. We showed that the GIM—modified to incorporate the naturalistic external field—was able to fit the empirical task fMRI data in the awake state, in mild sedation, in deep sedation, and in recovery, at a temperature T* which is well above the critical temperature. To our knowledge this is the first study that captures human brain activity in response to real-life external stimuli at different levels of conscious awareness using mathematical modeling. This study might be helpful in future to assess the level of consciousness of patients with disorders of consciousness and help in regaining their consciousness

    Towards the assessment of quality of life in patients with disorders of consciousness

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    © 2019, Springer Nature Switzerland AG. Purpose: To generate foundational knowledge in the creation of a quality-of-life instrument for patients who are clinically diagnosed as being in a vegetative or minimally conscious state but are able to communicate by modulating their brain activity (i.e., behaviourally nonresponsive and covertly aware). The study aimed to identify a short list of key domains that could be used to formulate questions for an instrument that determines their self-reported quality of life. Methods: A novel two-pronged strategy was employed: (i) a scoping review of quality-of-life instruments created for patient populations sharing some characteristics with patients who are behaviourally nonresponsive and covertly aware was done to compile a set of potentially relevant domains of quality of life; and (ii) a three-round Delphi consensus process with a multidisciplinary panel of experts was done to determine which of the identified domains of quality of life are most important to those who are behaviourally nonresponsive and covertly aware. Five expert groups were recruited for this study including healthcare workers, neuroscientists, bioethicists, quality-of-life methodologists, and patient advocates. Results: Thirty-five individuals participated in the study with an average response rate of 95% per round. Over the three rounds, experts reached consensus on 34 of 44 domains (42 domains were identified in the scoping review and two new domains were added based on suggestions by experts). 22 domains were rated as being important for inclusion in a quality-of-life instrument and 12 domains were deemed to be of less importance. Participants agreed that domains related to physical pain, communication, and personal relationships were of primary importance. Based on subgroup analyses, there was a high degree of consistency among expert groups. Conclusions: Quality of life should be a central patient-reported outcome in all patient populations regardless of patients’ ability to communicate. It remains to be determined how covertly aware patients perceive their circumstances and quality of life after suffering a life-altering injury. Nonetheless, it is important that any further dialogue on what constitutes a life worth living should not occur without direct patient input

    Assessing awareness in severe Alzheimer's disease

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    There is an urgent need to understand the nature of awareness in people with severe Alzheimer's disease (AD) to ensure effective person-centered care. Objective biomarkers of awareness validated in other clinical groups (e.g., anesthesia, minimally conscious states) offer an opportunity to investigate awareness in people with severe AD. In this article we demonstrate the feasibility of using Transcranial magnetic stimulation (TMS) combined with EEG, event related potentials (ERPs) and fMRI to assess awareness in severe AD. TMS-EEG was performed in six healthy older controls and three people with severe AD. The perturbational complexity index (PCIST) was calculated as a measure of capacity for conscious awareness. People with severe AD demonstrated a PCIST around or below the threshold for consciousness, suggesting reduced capacity for consciousness. ERPs were recorded during a visual perception paradigm. In response to viewing faces, two patients with severe AD provisionally demonstrated similar visual awareness negativity to healthy controls. Using a validated fMRI movie-viewing task, independent component analysis in two healthy controls and one patient with severe AD revealed activation in auditory, visual and fronto-parietal networks. Activation patterns in fronto-parietal networks did not significantly correlate between the patient and controls, suggesting potential differences in conscious awareness and engagement with the movie. Although methodological issues remain, these results demonstrate the feasibility of using objective measures of awareness in severe AD. We raise a number of challenges and research questions that should be addressed using these biomarkers of awareness in future studies to improve understanding and care for people with severe AD
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