scholarly journals The brain-bases of responsiveness variability under moderate anaesthesia

2020 ◽  
Author(s):  
Feng Deng ◽  
Nicola Taylor ◽  
Adrian M. Owen ◽  
Rhodri Cusack ◽  
Lorina Naci
Keyword(s):  
Information Processing ◽  
Executive Control ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Reaction Times ◽  
Grey Matter Volume ◽  
Clinical Anaesthesia ◽  
Powerful Approach ◽  
First Time ◽  
The Brain

AbstractAnaesthesia combined with functional neuroimaging provides a powerful approach for understanding the brain mechanisms that change as consciousness fades. Although propofol is used ubiquitously in clinical interventions that reversibly suppress consciousness, its effect varies substantially between individuals, and the brain bases of this variability remain poorly understood. We asked whether three networks that are primary sites of propofol-induced sedation and key to conscious cognition — the dorsal attention (DAN), executive control (ECN), and default mode (DMN) network — underlie responsiveness variability under anaesthesia. Healthy participants (N=17) underwent propofol sedation inside the fMRI scanner at dosages of ‘moderate’ anaesthesia, and behavioural responsiveness was measured with a target detection task. To assess information processing, participants were scanned during an active engagement condition comprised of a suspenseful auditory narrative, in addition to the resting state. A behavioural investigation in a second group of non-anesthetized participants (N=25) qualified the attention demands of narrative understanding, which we then related to the brain activity of participants who underwent sedation. 30% of participants showed no delay in reaction times relative to wakefulness, whereas the others, showed significantly delayed and fragmented responses, or full omission of responses. These responsiveness differences did not relate to information processing differences. Rather, only the functional connectivity within the ECN during wakefulness differentiated the participants’ responsiveness level, with significantly stronger connectivity in the fast relative to slow responders. Consistent with this finding, fast responders had significantly higher grey matter volume in the frontal cortex aspect of the ECN. For the first time, these results show that responsiveness variability during propofol anaesthesia relates to inherent differences in brain function and structure within the executive control network, which can be predicted prior to sedation. These results shed light on the brain bases of responsiveness differences and highlight novel markers that may help to improve the accuracy of awareness monitoring during clinical anaesthesia.

The brain represents people as the mental states they habitually experience

2018 ◽  
Author(s):  
Mark Allen Thornton ◽  
Miriam E. Weaverdyck ◽  
Diana Tamir
Keyword(s):  
Social Life ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Activity Patterns ◽  
Reaction Times ◽  
Mental States ◽  
Weighted Sums ◽  
Famous Person ◽  
Binary Choices ◽  
The Brain

Social life requires us to treat each person according to their unique disposition: habitually enthusiastic friends need occasional grounding, whereas pessimistic colleagues require cheering-up. To tailor our behavior to specific individuals, we must represent their idiosyncrasies. Here we advance a hypothesis about how the brain achieves this goal: our representations of other people reflect the mental states we perceive those people to habitually experience. That is, rather than representing other people via traits, our brains represent people as the sums of their states. For example, if a perceiver observes that another person is frequently cheerful, sometimes thoughtful, and rarely grumpy, the perceiver’s representation of that person will be comprised of their representations of the mental states cheerfulness, thoughtfulness, and grumpiness, combined in a corresponding ratio. We tested this hypothesis by measuring whether neural representations of people could be accurately reconstructed by summing state representations. Separate participants underwent functional neuroimaging while considering famous individuals and individual mental states. Online participants rated how often each famous person experiences each state. Results supported the summed state hypothesis: frequency-weighted sums of state-specific brain activity patterns accurately reconstructed person-specific patterns. Moreover, the summed state account outperformed the established alternative – that people represent others using trait dimensions – in explaining interpersonal similarity, as measured through neural patterns, explicit ratings, binary choices, reaction times, and the semantics of biographical text. Together these findings demonstrate that the brain represents other people as the sums of the mental states they are perceived to experience.

Information-based decoding of the coupling among human brain activity and movement paths

2021 ◽  
pp. 1-10
Author(s):  
Shahul Mujib Kamal ◽  
Norazryana Mat Dawi ◽  
Hamidreza Namazi
Keyword(s):  
Brain Activity ◽  
Point Of View ◽  
Physiological Signals ◽  
Human Walking ◽  
Eeg Signals ◽  
Rehabilitation Science ◽  
Information Contents ◽  
First Time ◽  
The Brain ◽  
Brain Reaction

BACKGROUND: Walking like many other actions of a human is controlled by the brain through the nervous system. In fact, if a problem occurs in our brain, we cannot walk correctly. Therefore, the analysis of the coupling of brain activity and walking is very important especially in rehabilitation science. The complexity of movement paths is one of the factors that affect human walking. For instance, if we walk on a path that is more complex, our brain activity increases to adjust our movements. OBJECTIVE: This study for the first time analyzed the coupling of walking paths and brain reaction from the information point of view. METHODS: We analyzed the Shannon entropy for electroencephalography (EEG) signals versus the walking paths in order to relate their information contents. RESULTS: According to the results, walking on a path that contains more information causes more information in EEG signals. A strong correlation (p= 0.9999) was observed between the information contents of EEG signals and walking paths. Our method of analysis can also be used to investigate the relation among other physiological signals of a human and walking paths, which has great benefits in rehabilitation science.

scholarly journals Recent advances in functional neuroimaging analysis for cognitive neuroscience

2018 ◽  
Vol 2 ◽  
pp. 239821281775272 ◽  
Author(s):  
Nitin Williams ◽  
Richard N. Henson
Keyword(s):  
Functional Neuroimaging ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Recent Analysis ◽  
Temporal Data ◽  
New Methods ◽  
Neuroimaging Data ◽  
The Rich ◽  
Scientific Questions ◽  
The Brain

Functional magnetic resonance imaging and electro-/magneto-encephalography are some of the main neuroimaging technologies used by cognitive neuroscientists to study how the brain works. However, the methods for analysing the rich spatial and temporal data they provide are constantly evolving, and these new methods in turn allow new scientific questions to be asked about the brain. In this brief review, we highlight a handful of recent analysis developments that promise to further advance our knowledge about the working of the brain. These include (1) multivariate approaches to decoding the content of brain activity, (2) time-varying approaches to characterising states of brain connectivity, (3) neurobiological modelling of neuroimaging data, and (4) standardisation and big data initiatives.

scholarly journals Human Empathy Through the Lens of Social Neuroscience

2006 ◽  
Vol 6 ◽  
pp. 1146-1163 ◽  
Author(s):  
Jean Decety ◽  
Claus Lamm
Keyword(s):  
Information Processing ◽  
Cognitive Neuroscience ◽  
Executive Control ◽  
Perspective Taking ◽  
Functional Neuroimaging ◽  
Social Neuroscience ◽  
Neural Mechanisms ◽  
The Self ◽  
Neural Systems

Empathy is the ability to experience and understand what others feel without confusion between oneself and others. Knowing what someone else is feeling plays a fundamental role in interpersonal interactions. In this paper, we articulate evidence from social psychology and cognitive neuroscience, and argue that empathy involves both emotion sharing (bottom-up information processing) and executive control to regulate and modulate this experience (top-down information processing), underpinned by specific and interacting neural systems. Furthermore, awareness of a distinction between the experiences of the self and others constitutes a crucial aspect of empathy. We discuss data from recent behavioral and functional neuroimaging studies with an emphasis on the perception of pain in others, and highlight the role of different neural mechanisms that underpin the experience of empathy, including emotion sharing, perspective taking, and emotion regulation.

scholarly journals Concurrent MEG-articulography for investigating neuromotor control of speech articulation

2020 ◽  
Author(s):  
Blake Johnson ◽  
Qinqing Meng ◽  
Ioanna Anastasopoulou ◽  
Louise Ratko ◽  
Tunde Szalay ◽  
...  
Keyword(s):  
Speech Production ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Typically Developing ◽  
Facial Movements ◽  
Electromagnetic Articulography ◽  
Neuromotor Control ◽  
Brain Responses ◽  
First Time ◽  
Speech Kinematics

AbstractArticulography and functional neuroimaging are two major tools for studying the neurobiology of speech production. Until now, however, it has generally not been possible to use both in the same experimental setup because of technical incompatibilities between the two methodologies. Here we describe results from a novel articulography system dubbed Magneto-articulography for the Assessment of Speech Kinematics (MASK), used for the first time to obtain kinematic profiles of oro-facial movements during speech together with concurrent magnetoencephalographic (MEG) measurements of neuromotor brain activity. MASK was used to characterise speech kinematics in a healthy adult, and the results were compared to measurements from the same participant with a conventional electromagnetic articulography (EMA) setup. We also characterised speech movement kinematics with MASK in a group of ten typically developing children, aged 8-12 years. Analyses targeted the gestural landmarks of the utterances /ida/, /ila/ and reiterated productions of /pataka/. These results demonstrate that the MASK technique can be used to reliably characterise movement profiles and kinematic parameters that reflect development of speech motor control, together with MEG measurements of brain responses from speech sensorimotor cortex. This new capability sets the stage for cross-disciplinary efforts to understand the developmental neurobiology of human speech production.

scholarly journals Brain activity is contingent on neuropsychological function in an fMRI study of Verbal Working Memory in Amyotrophic Lateral Sclerosis

2021 ◽  
Author(s):  
Xenia Kobeleva ◽  
Judith Machts ◽  
Maria Veit ◽  
Stefan Vielhaber ◽  
Susanne Petri ◽  
...  
Keyword(s):  
Working Memory ◽  
Amyotrophic Lateral Sclerosis ◽  
Functional Neuroimaging ◽  
Current Knowledge ◽  
Brain Activity ◽  
Reaction Times ◽  
Verbal Working Memory ◽  
Research Field ◽  
Fmri Study ◽  
Lateral Sclerosis

AbstractAmyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease that causes progressive degeneration of neurons in motor and non-motor regions, affecting multiple cognitive domains. In order to contribute to the growing research field that employs structural and functional neuroimaging to investigate the effect of ALS on different working memory components, we conducted a functional magnetic resonance imaging (fMRI) study exploring the localization and intensity of alterations in neural activity. Being the first study to specifically address verbal working memory via fMRI in the context of ALS, we employed the verbal n-back task with 0-back and 2-back conditions. Despite ALS patients showing unimpaired accuracies and reaction times, there was significantly increased brain activity of frontotemporal and parietal regions in the 2-back minus 0-back contrast in patients compared to controls. This increased brain activity was largely associated with a better neuropsychological performance within the ALS group, suggesting a compensatory effect. This study therefore adds to the current knowledge on neural correlates of working memory in ALS and contributes to a more nuanced understanding of hyperactivity during cognitive processes in fMRI studies of ALS.

COMPLEXITY-BASED ANALYSIS OF BRAINS’ SYNCHRONIZATION IN HUMAN–HUMAN INTERACTION

Fractals ◽  
2020 ◽  
Vol 28 (07) ◽  
pp. 2050102 ◽  
Author(s):  
MOHAMED RASMI ASHFAQ AHAMED ◽  
MOHAMMAD HOSSEIN BABINI ◽  
NAJMEH PAKNIYAT ◽  
HAMIDREZA NAMAZI
Keyword(s):  
Fractal Analysis ◽  
Brain Activity ◽  
Human Interaction ◽  
Physiological Signals ◽  
Eeg Signals ◽  
Human Voice ◽  
The Mean ◽  
First Time ◽  
The Relationship ◽  
The Brain

Talking is the most common type of human interaction that people have in their daily life. Besides all conducted studies on the analysis of human behavior in different conditions, no study has been reported yet that analyzed how the brain activity of two persons is related during their conversation. In this research, for the first time, we investigate the relationship between brain activities of people while communicating, considering human voice as the mean of this connection. For this purpose, we employ fractal analysis in order to investigate how the complexity of electroencephalography (EEG) signals for two persons are related. The results showed that the variations of complexity of EEG signals for two persons are correlated while communicating. Statistical analysis also supported the result of analysis. Therefore, it can be stated that the brain activities of two persons are correlated during communication. Fractal analysis can be employed to analyze the correlation between other physiological signals of people while communicating.

scholarly journals Information Processing in the Brain as Optimal Entropy Transport: A Theoretical Approach

Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1231
Author(s):  
Carlos Islas ◽  
Pablo Padilla ◽  
Marco Antonio Prado
Keyword(s):  
Information Processing ◽  
Information Flow ◽  
Optimal Transport ◽  
Brain Activity ◽  
Entropy Condition ◽  
Informational Entropy ◽  
Information Theoretic ◽  
Entropy Transport ◽  
Monge Ampere ◽  
The Brain

We consider brain activity from an information theoretic perspective. We analyze the information processing in the brain, considering the optimality of Shannon entropy transport using the Monge–Kantorovich framework. It is proposed that some of these processes satisfy an optimal transport of informational entropy condition. This optimality condition allows us to derive an equation of the Monge–Ampère type for the information flow that accounts for the branching structure of neurons via the linearization of this equation. Based on this fact, we discuss a version of Murray’s law in this context.

Information-Based Classification of Electroencephalography (EEG) Signals for Healthy Adolescents and Adolescents with Symptoms of Schizophrenia

2020 ◽  
Vol 19 (04) ◽  
pp. 2050033 ◽  
Author(s):  
Hamidreza Namazi
Keyword(s):  
Information Content ◽  
Shannon Entropy ◽  
Healthy Subjects ◽  
Brain Activity ◽  
Research Area ◽  
Eeg Signal ◽  
Brain Disorders ◽  
Eeg Signals ◽  
First Time ◽  
The Brain

Analysis of the brain activity is the major research area in human neuroscience. Besides many works that have been conducted on analysis of brain activity in case of healthy subjects, investigation of brain activity in case of patients with different brain disorders also has aroused the attention of many researchers. An interesting category of works belong to the comparison of brain activity between healthy subjects and patients with brain disorders. In this research, for the first time, we compare the brain activity between adolescents with symptoms of schizophrenia and healthy subjects, by information-based analysis of their Electroencephalography (EEG) signals. For this purpose, we benefit from the Shannon entropy as the indicator of information content. Based on the results of analysis, EEG signal in case of healthy subjects contains more information than EEG signal in case of subjects with schizophrenia. The result of statistical analysis showed the significant variation in the Shannon entropy of EEG signal between healthy adolescents and adolescents with symptoms of schizophrenia in case of P3, O1 and O2 channels. The employed method of analysis in this research can be further extended in order to investigate the variations in the information content of EEG signal in case of subjects with other brain disorders versus healthy subjects.

scholarly journals Utility of SPECT Functional Neuroimaging of Pain

2021 ◽  
Vol 12 ◽  
Author(s):  
Mohammed Bermo ◽  
Mohammed Saqr ◽  
Hunter Hoffman ◽  
David Patterson ◽  
Sam Sharar ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Photon Emission ◽  
Brain Activation ◽  
Brain Perfusion ◽  
Functional Brain Imaging ◽  
Functional Brain ◽  
Clinical Scenarios ◽  
The Brain

Functional neuroimaging modalities vary in spatial and temporal resolution. One major limitation of most functional neuroimaging modalities is that only neural activation taking place inside the scanner can be imaged. This limitation makes functional neuroimaging in many clinical scenarios extremely difficult or impossible. The most commonly used radiopharmaceutical in Single Photon Emission Tomography (SPECT) functional brain imaging is Technetium 99 m-labeled Ethyl Cysteinate Dimer (ECD). ECD is a lipophilic compound with unique pharmacodynamics. It crosses the blood brain barrier and has high first pass extraction by the neurons proportional to regional brain perfusion at the time of injection. It reaches peak activity in the brain 1 min after injection and is then slowly cleared from the brain following a biexponential mode. This allows for a practical imaging window of 1 or 2 h after injection. In other words, it freezes a snapshot of brain perfusion at the time of injection that is kept and can be imaged later. This unique feature allows for designing functional brain imaging studies that do not require the patient to be inside the scanner at the time of brain activation. Functional brain imaging during severe burn wound care is an example that has been extensively studied using this technique. Not only does SPECT allow for imaging of brain activity under extreme pain conditions in clinical settings, but it also allows for imaging of brain activity modulation in response to analgesic maneuvers whether pharmacologic or non-traditional such as using virtual reality analgesia. Together with its utility in extreme situations, SPECTS is also helpful in investigating brain activation under typical pain conditions such as experimental controlled pain and chronic pain syndromes.

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