Measuring brain activity cycling (BAC) in long term EEG monitoring of preterm babies

Recent advances in the field of neural rehabilitation, facilitated through technological innovation and improved neurophysiological knowledge of impaired motor control, have opened up new research directions. Such advances increase the relevance of existing interventions, as well as allow novel methodologies and technological synergies. New approaches attempt to partially overcome long-term disability caused by spinal cord injury, using either invasive bridging technologies or noninvasive human–machine interfaces. Muscular dystrophies benefit from electromyography and novel sensors that shed light on underlying neuromotor mechanisms in people with Duchenne. Novel wearable robotics devices are being tailored to specific patient populations, such as traumatic brain injury, stroke, and amputated individuals. In addition, developments in robot-assisted rehabilitation may enhance motor learning and generate movement repetitions by decoding the brain activity of patients during therapy. This is further facilitated by artificial intelligence algorithms coupled with faster electronics. The practical impact of integrating such technologies with neural rehabilitation treatment can be substantial. They can potentially empower nontechnically trained individuals—namely, family members and professional carers—to alter the programming of neural rehabilitation robotic setups, to actively get involved and intervene promptly at the point of care. This narrative review considers existing and emerging neural rehabilitation technologies through the perspective of replacing or restoring functions, enhancing, or improving natural neural output, as well as promoting or recruiting dormant neuroplasticity. Upon conclusion, we discuss the future directions for neural rehabilitation research, diagnosis, and treatment based on the discussed technologies and their major roadblocks. This future may eventually become possible through technological evolution and convergence of mutually beneficial technologies to create hybrid solutions.

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Preliminary Study of the Use of Root with Sedline® EEG Monitoring for Assessment of Anesthesia Depth in 6 Horses

Applied Sciences ◽

10.3390/app10031050 ◽

2020 ◽

Vol 10 (3) ◽

pp. 1050

Author(s):

Olga Drewnowska ◽

Bernard Turek ◽

Barbara Lisowska ◽

Charles E. Short

Keyword(s):

Brain Activity ◽

Muscle Relaxation ◽

Eeg Monitoring ◽

Careful Monitoring ◽

Spectral Edge Frequency ◽

Non Invasive ◽

Anesthesia Monitoring ◽

Physiologic Parameters ◽

Preliminary Study ◽

Anesthesia Depth

Management of equine anesthesia monitoring is still a challenge. Careful monitoring to provide guidelines for anesthesia depth assessment currently relies upon eye signs, cardiopulmonary responses, and the level of muscle relaxation. Electroencephalography, as a non-invasive brain activity monitor, may be used to complement the routinely monitored physiologic parameters. Six horses, undergoing various surgical procedures and anesthesia protocols, were monitored with the use of a Root with Sedline EEG monitor and a routine monitor of life parameters. The life parameters were compared to the changes on the EEG density spectral array observed live during anesthesia. During all procedures the level of awareness was monitored using the EEG, with higher frequency and power of waves indicating a higher level of awareness. It was evident from this that there were variations according to the type of procedure and the anesthetic protocol. Cerebral activity was elevated during painful moments of the surgery and recovery, requiring adjustments in anesthetic concentrations. Evaluation of changes in the spectral edge frequency (SEF) could show the periods when the patient is stabilized. EEG monitoring has the potential to be used in clinical anesthesiology of horses. It was shown that this system may be used in horses under general anesthesia but is currently less effective in a standing horse for diagnostic or minor procedures.

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Technical implementation and clinical findings/results of monitoring oxygen saturation in patients referred for long term EEG monitoring

Electroencephalography and Clinical Neurophysiology ◽

10.1016/s0013-4694(96)95206-2 ◽

1996 ◽

Vol 99 (5) ◽

pp. 432-439 ◽

Cited By ~ 7

Author(s):

J.R. Ives ◽

N.R. Mainwaring ◽

K.B. Krishnamurthy ◽

A.S. Blum ◽

F.W. Drislane ◽

...

Keyword(s):

Oxygen Saturation ◽

Clinical Findings ◽

Eeg Monitoring

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O27 Long-term EEG monitoring in the early premature

Neurophysiologie Clinique ◽

10.1016/s0987-7053(05)80465-4 ◽

1990 ◽

Vol 20 ◽

pp. 10s

Keyword(s):

Eeg Monitoring

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Timing, Storage, and Comparison of Stimulus Duration Engage Discrete Anatomical Components of a Perceptual Timing Network

Journal of Cognitive Neuroscience ◽

10.1162/jocn.2008.20153 ◽

2008 ◽

Vol 20 (12) ◽

pp. 2185-2197 ◽

Cited By ~ 99

Author(s):

Jennifer T. Coull ◽

Bruno Nazarian ◽

Franck Vidal

Keyword(s):

Stimulus Duration ◽

Brain Activity ◽

Temporal Discrimination ◽

Superior Temporal Gyrus ◽

Motor Preparation ◽

Long Term Memory ◽

Temporal Encoding ◽

Perceptual Timing ◽

The Right

The temporal discrimination paradigm requires subjects to compare the duration of a probe stimulus to that of a sample previously stored in working or long-term memory, thus providing an index of timing that is independent of a motor response. However, the estimation process itself comprises several component cognitive processes, including timing, storage, retrieval, and comparison of durations. Previous imaging studies have attempted to disentangle these components by simply measuring brain activity during early versus late scanning epochs. We aim to improve the temporal resolution and precision of this approach by using rapid event-related functional magnetic resonance imaging to time-lock the hemodynamic response to presentation of the sample and probe stimuli themselves. Compared to a control (color-estimation) task, which was matched in terms of difficulty, sustained attention, and motor preparation requirements, we found selective activation of the left putamen for the storage (“encoding”) of stimulus duration into working memory (WM). Moreover, increased putamen activity was linked to enhanced timing performance, suggesting that the level of putamen activity may modulate the depth of temporal encoding. Retrieval and comparison of stimulus duration in WM selectively activated the right superior temporal gyrus. Finally, the supplementary motor area was equally active during both sample and probe stages of the task, suggesting a fundamental role in timing the duration of a stimulus that is currently unfolding in time.

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Studying the effect of Heartfulness Meditation on Brain Activity

Inquiry@Queen's Undergraduate Research Conference Proceedings ◽

10.24908/iqurcp.10470 ◽

2018 ◽

Author(s):

Pallavi Gupta ◽

Jahnavi Mundluru ◽

Arth Patel ◽

Shankar Pathmakanthan

Keyword(s):

Problem Solving ◽

Creative Thinking ◽

Brain Activity ◽

Cognitive Task ◽

Thinking Skills ◽

Cognitive Tasks ◽

Logical Thinking ◽

Meditation Practice ◽

Guided Relaxation

Long-term meditation practice is increasingly recognized for its health benefits. Heartfulness meditation represents a quickly growing set of practices that is largely unstudied. Heartfulness is unique in that it is a meditation practice that focuses on the Heart. It helps individuals to connect to themselves and find inner peace. In order to deepen ones’ meditation, the element of Yogic Energy (‘pranahuti’) is used as an aid during meditation. The purpose of this study was to determine whether consistent EEG effects of Heartfulness meditation be observed in sixty experienced Heartfulness meditators, each of whom attended 6 testing sessions. In each session, participants performed three conditions: a set of cognitive tasks, Heartfulness guided relaxation, and Heartfulness Meditation. Participants during the cognitive portion were required to answer questions that tested their logical thinking (Cognitive Reflective Test) and creative thinking skills. (Random Associative Test) The order of condition was randomly counter balanced across six sessions. It was hypothesized that Heartfulness meditation would bring increased alpha (8-12Hz) brain activity during meditation and better cognitive task scores in sessions where the tasks followed meditation. Heartfulness meditation produces a significant decrease in brain activity (as indexed by higher levels of alpha during the early stages of meditation. As the meditation progressed deep meditative state (as indexed by higher levels of delta) were observed until the end of the condition. This lead to the conclusion that Heartfulness Meditation produces a state that is clearly distinguishable from effortful problem solving.

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