Explore the Functional Connectivity between Brain Regions during a Chemistry Working Memory Task.

Previous studies have rarely examined how temporal dynamic patterns, event-related coherence, and phase-locking are related to each other. This study assessed reaction-time-sorted spectral perturbation and event-related spectral perturbation in order to examine the temporal dynamic patterns in the frontal midline (F), central parietal (CP), and occipital (O) regions during a chemistry working memory task at theta, alpha, and beta frequencies. Furthermore, the functional connectivity between F-CP, CP-O, and F-O were assessed by component event-related coherence (ERCoh) and component phase-locking (PL) at different frequency bands. In addition, this study examined whether the temporal dynamic patterns are consistent with the functional connectivity patterns across different frequencies and time courses. Component ERCoh/PL measured the interactions between different independent components decomposed from the scalp EEG, mixtures of time courses of activities arising from different brain, and artifactual sources. The results indicate that the O and CP regions' temporal dynamic patterns are similar to each other. Furthermore, pronounced component ERCoh/PL patterns were found to exist between the O and CP regions across each stimulus and probe presentation, in both theta and alpha frequencies. The consistent theta component ERCoh/PL between the F and O regions was found at the first stimulus and after probe presentation. These findings demonstrate that temporal dynamic patterns at different regions are in accordance with the functional connectivity patterns. Such coordinated and robust EEG temporal dynamics and component ERCoh/PL patterns suggest that these brain regions' neurons work together both to induce similar event-related spectral perturbation and to synchronize or desynchronize simultaneously in order to swiftly accomplish a particular goal. The possible mechanisms for such distinct component phase-locking and coherence patterns were also further discussed

Psychotextiles and their interaction with the human brain

This work crosses the boundaries between design and technology, and it focuses on pattern design, its relationship with neuroscience and how new SMART products can be developed from this interaction. What we see in our environment has significant influence on our emotion and behaviour. A simple shape and form is able to impact on our emotions. This research has explored the emotional effect evoked by different visual pattern characteristics. Two paired pattern categories were investigated: repeating/non-repeating and weak/intense. Repeating patterns contain regularly repeating elements and have symmetrical and continuous features; in contrast, non-repeating patterns contain irregularly repeating elements and have asymmetrical and discontinuous features. Weak patterns are faint, light and simple compared to intense patterns that are high in contrast, bold and complex. The emotional response to each type of pattern was investigated directly by brain and cardiac activities of twenty subjects by electroencephalography (EEG) and electrocardiography (ECG) measurements and by self-evaluation; the former is used to measure the brain wave activity, and the ECG to analyse the heart rate changes. These physiological signals were then analysed, interpreted and correlated with people’s self-evaluation of their emotional response to the pattern. It was found that repeating patterns produce a more pleasant sensation than non-repeating patterns, and intense patterns evoke a higher level of excitement than weak patterns. The significant changes in the emotional effects found by changes of pattern and the good correlation of the objective and subjective emotional measurements encouraged the implementation of pattern change by design and production of SMART fabrics. Four knitted fabrics with the ability of switching their pattern appearance from repeating to non-repeating, and from weak to intense have been successfully produced with a purpose made electrochromic composite yarn. The emotional effects of pattern-changing of these fabrics have been further investigated. The notion of influencing human emotion by engineering the pattern design and characteristics of SMART textiles is established and these fabrics are named Psychotextiles. Finally the event-related potential (ERP) investigation of the visual brain (no thinking, or memory) revealed that there may be an influence on human emotional effects in less than 1 second from the time of seeing the object; a time sufficiently short for these to be little analysis within the brain

Coupled Correlates of Attention and Consciousness

Introduction: Brain Computer Interfaces (BCIs) have been shown to restore lost motor function that occurs in stroke using electrophysiological signals. However, little evidence exists for the use of BCIs to restore non-motor stroke deficits, such as the attention deficits seen in hemineglect. Attention is a cognitive function that selects objects or ideas for further neural processing, presumably to facilitate optimal behavior. Developing BCIs for attention is different from developing motor BCIs because attention networks in the brain are more distributed and associative than motor networks. For example, hemineglect patients have reduced levels of arousal, which exacerbates their attentional deficits. More generally, attention is a state of high arousal and salient conscious experience. Current models of consciousness suggest that both slow wave sleep and Propofol-induced unconsciousness lie at one end of the consciousness spectrum, while attentive states lie at the other end. Accordingly, investigating the electrophysiology underlying attention and the extremes of consciousness will further the development of attentional BCIs. Phase amplitude coupling (PAC) of neural oscillations has been suggested as a mechanism for organizing local and global brain activity across regions. While evidence suggests that delta-high-gamma PAC, which includes very low frequencies (i.e. delta, 1-3 Hz) coupled with very high frequencies (i.e. gamma 70-150 Hz), is implicated in attention, less evidence exists for the involvement of coupled mid-range frequencies (i.e. theta, 4-7Hz, alpha: 8-15 Hz, beta: 15-30 Hz and low-gamma: 30-50 Hz, aka TABL PAC). We found that TABL PAC correlates with reaction time in an attention task. These mid-range frequencies are important because they can be used in non-invasive electroencephalography (EEG) BCI’s. Therefore, we investigated the origins of these mid-frequency interactions in both attention and consciousness. In this work, we evaluate the relationship between PAC to attention and arousal, with emphasis on developing control signals for an attentional BCI. Objective: To understand how PAC facilitates attention and arousal for building BCI’s that restore lost attentional function. More generally, our objective was to discover and understand potential control features for BCIs that enhance attention and conscious experience. Methods: We used four electrophysiological datasets in human subjects. The first dataset included six subjects with invasive ECoG recordings while subjects engaged in a Posner cued spatial attention task. The second dataset included five subjects with ECoG recordings during sleep and awake states. The third dataset included 6 subjects with invasively monitored ECoG during induction and emergence from Propofol anesthesia. We validated findings from the second dataset with an EEG dataset that included 39 subjects with EEG and sleep scoring. We developed custom, wavelet-based, signal processing algorithms designed to optimally calculate differences in mid-frequency-range (i.e. TABL) PAC and compare them to DH PAC across different attentional and conscious states. We developed non-parametric cluster-based permutation tests to infer statistical significance while minimizing the false-positive rate. In the attention experiment, we used the location of cued spatial stimuli and reaction time (RT) as markers of attention. We defined stimulus-related and behaviorally-related cortical sites and compared their relative PAC magnitudes. In the sleep dataset, we compared PAC across sleep states (e.g. Wake vs Slow Wave Sleep). In the anesthesia dataset, we compared the beginning and ending of induction and emergence (e.g. Wake vs Propofol Induced Loss of Consciousness) Results: We found different patterns of activity represented by TABL PAC and DH PAC in both attention and sleep datasets. First, during a spatial attention task TABL PAC robustly predicted whether a subject would respond quickly or slowly. TABL PAC maintained a consistent phase-preference across all cortical sites and was strongest in behaviorally-relevant cortical sites. In contrast, DH PAC represented the location of attention in spatially-relevant cortical sites. Furthermore, we discovered that sharp waves caused TABL PAC. These sharp waves appeared to be transient beta (50ms) waves that occurred at ~140 ms intervals, corresponding to a theta oscillation. In the arousal dataset DH PAC increased in both slow wave sleep (SWS) and Propofol-induced loss of consciousness (PILOC) states. However, TABL PAC increased only during PILOC and decreased during SWS, when compared to waking states. We provide evidence that TABL PAC represents “gating by inhibition” in the human brain. Conclusions: Our goal was to develop electrophysiological signals representing attention and to understand how these features explain the relationship between attention and low-arousal states. We found a novel biomarker, TABL PAC, that predicted non-spatial aspects of attention and discriminated between two states of unconsciousness. The evidence suggested that TABL PAC represents inhibitory activity that filters out irrelevant information in attention tasks. This inhibitory mechanism of was confirmed by significant increases in TABL PAC during Propofol anesthesia, when compared to SWS or waking brain activity. We conclude that TABL PAC informs the development of electrophysiological control signals for attention and the discrimination of unconscious states

Frontal Alpha Asymmetry and Theta Oscillations Associated With Information Sharing Intention

Social media has gained increasing importance in many aspects of everyday life, from building relationships to establishing collaborative networks between individuals worldwide. Sharing behavior is an essential part of maintaining these dynamic networks. However, the precise neural factors that could be related to sharing behavior in online communities remain unclear. In this study, we recorded electroencephalographic (EEG) oscillations of human subjects while they were watching short videos. The subjects were later asked to evaluate the videos based on how much they liked them and whether they would share them. We found that, at the population level, subjects watching videos that would not be shared had higher power spectral density (PSD) amplitudes in the theta band (4–8 Hz), primarily over the frontal and parietal sites of the right hemisphere, than subjects watching videos that would be shared. Previous studies have associated task disengagement with an increase in scalp-wide theta activation, which can be interpreted as a mind-wandering effect. This might suggest that the decision to not share the video may lead to a more automatic/effortless neural pattern. We also found that watching videos that would be shared was associated with lower PSD amplitudes in the alpha band (8–12 Hz) over the central and right frontal sites, and with more negative scores of frontal alpha asymmetry (FAA) index scores. These results may be related to previous work linking right-sided frontal EEG asymmetry to the pursuit of social conformity and avoidance of negative outcomes, such as social isolation. Finally, using support vector machine (SVM) algorithms, we show that these EEG parameters and preference rating scores can be used to improve the predictability of sharing information behavior. The information sharing-related EEG pattern described here could therefore improve our understanding of the neural markers associated with sharing behavior and contribute to studies about stimuli propagation

Relationships between subjective experience, electroencephalogram, and heart rate variability during a series of cosmetic behavior

IntroductionCosmetic behavior is an important daily activity, especially for women, because it increases visual attractiveness, self-confidence, and positive emotions. However, it is unknown whether a relationship exists between physiological measures and subjective experiences during the series of cosmetic behaviors.MethodsElectroencephalograms (EEG) and electrocardiograms (ECG) from thirty female participants who were asked to look in a mirror after applying skincare, as well as base, eye, cheek, and lip makeup were recorded. The price range of cosmetic products was also considered. Subjective evaluations of the skin surface, emotions, and self-confidence were equally measured after looking in the mirror at each step of the cosmetic behavior. Linear mixed models were fitted to examine whether the subjective experience could be explained by the variety of cosmetic products and/or physiological responses.ResultsThe subjective evaluation was summarized into the following three factors using a factor analysis: self-confidence, hedonic perception, and negative emotion. Each theta-band (4–6 Hz) power, alpha-band (8–13 Hz) power of the EEG, and heart rate variability measures were subjected to a principal component analysis separately. The linear mixed models indicated that the variation in the self-confidence score and the negative emotion score was explained only by the steps of cosmetic behaviors, that is, self-confidence increased while negative emotions decreased as the steps of cosmetic behaviors proceeded. On the other hand, the hedonic perception score was explained by the interaction of the steps of cosmetic behaviors and price, indicating that positive tactile perception and positive emotion were higher when luxury cosmetic products were applied than when affordable products were applied. Furthermore, the model indicated that the hedonic perception score was positively associated with the alpha-band power over occipital sites whereas sympathetic nervous system activity was negatively associated with the alpha-band power over lateral central sites.DiscussionThese results suggest that positive perceptual and emotional experiences are associated with greater attention to somatosensory information than to visual information and sympathetic autonomic nervous system activities. The current results also emphasize the possibility of using physiological measurements as objective measures of cosmetic behavior

The Theta Paradox: 4-8 Hz EEG Oscillations Reflect Both Sleep Pressure and Cognitive Control

Human electroencephalographic (EEG) oscillations characterize specific behavioral and vigilance states. The frequency of these oscillations is typically sufficient to distinguish a given state; however, theta oscillations (4-8 Hz) have instead been found in near-opposite conditions of drowsiness during sleep deprivation and alert cognitive control. While the latter has been extensively studied and is often referred to as "frontal midline theta," (fmTheta) the former has been investigated far less but is considered a marker for sleep pressure during wake. In this study we investigated to what extent theta oscillations differed during cognitive tasks and sleep deprivation. We measured high-density EEG in 18 young healthy adults (nine female) performing six tasks under three levels of sleep deprivation. We found both cognitive load and sleep deprivation increased theta power in medial prefrontal cortical areas; however, sleep deprivation caused additional increases in theta in many other, predominantly frontal, areas. The sources of sleep deprivation theta (sdTheta) were task dependent, with a visual-spatial task and short-term memory (STM) task showing the most widespread effects. Notably, theta was highest in supplementary motor areas during passive music listening, and highest in the inferior temporal cortex (responsible for object recognition) during a spatial game. Furthermore, while changes in task performance were correlated with increases in theta during sleep deprivation, this relationship was not specific to the EEG of the same task and did not survive correction for multiple comparisons. Altogether, these results suggest that both during sleep deprivation and cognition theta oscillations may preferentially occur in cortical areas not involved in ongoing behavior.SIGNIFICANCE STATEMENT Electroencephalographic (EEG) research in sleep has often remained separate from research in cognition. This has led to two incompatible interpretations of the function of theta brain oscillations (4-8 Hz): that they reflect local sleep events during sleep deprivation, or that they reflect cognitive processing during tasks. With this study, we found no fundamental differences between theta oscillations during cognition and theta during sleep deprivation that would suggest different functions. Instead, our results indicate that in both cases, theta oscillations are generated by cortical areas not required for ongoing behavior. Therefore, at least in humans, theta may reflect either cortical disengagement or inhibition

Alpha and theta mechanisms operating in internal-external attention competition

Attention is the ability to prioritize a set of information at expense of others and can be internally- or externally-oriented. Alpha and theta oscillations have been extensively implicated in attention. However, it is unclear how these oscillations operate when sensory distractors are presented continuously during task-relevant internal processes, in close-to-real-life conditions. Here, EEG signals from healthy participants were obtained at rest and in three attentional conditions, characterized by the execution of a mental math task (internal attention), presentation of pictures on a monitor (external attention), and task execution under the distracting action of picture presentation (internal-external competition). Alpha and theta power were investigated at scalp level and at some cortical regions of interest (ROIs); moreover, functional directed connectivity was estimated via spectral Granger Causality. Results show that frontal midline theta was distinctive of mental task execution and was more prominent during competition compared to internal attention alone, possibly reflecting higher executive control; anterior cingulate cortex appeared as mainly involved and causally connected to distant (temporal/ occipital) regions. Alpha power in visual ROIs strongly decreased in external attention alone, while it assumed values close to rest during competition, reflecting reduced visual engagement against distractors; connectivity results suggested that bidirectional alpha influences between frontal and visual regions could contribute to reduce visual interference in internal attention. This study can help to understand how our brain copes with internal-external attention competition, a condition intrinsic in the human sensory-cognitive interplay, and to elucidate the relationships between brain oscillations and attentional functions/dysfunctions in daily tasks

Spectral power density analysis of the resting-state as a marker of the central effects of opioid use in fibromyalgia

Spectral power density (SPD) indexed by electroencephalogram (EEG) recordings has recently gained attention in elucidating neural mechanisms of chronic pain syndromes and medication use. We compared SPD variations between 15 fibromyalgia (FM) women in use of opioid in the last three months (73.33% used tramadol) with 32 non-users. EEG data were obtained with Eyes Open (EO) and Eyes Closed (EC) resting state. SPD peak amplitudes between EO-EC were smaller in opioid users in central theta, central beta, and parietal beta, and at parietal delta. However, these variations were positive for opioid users. Multivariate analyses of variance (ANOVAs) revealed that EO-EC variations in parietal delta were negatively correlated with the disability due to pain, and central and parietal beta activity variations were positively correlated with worse sleep quality. These clinical variables explained from 12.5 to 17.2% of SPD variance. In addition, central beta showed 67% sensitivity / 72% specificity and parietal beta showed 73% sensitivity/62% specificity in discriminating opioid users from non-users. These findings suggest oscillations in EEG might be a sensitive surrogate marker to screen FM opioid users and a promising tool to understand the effects of opioid use and how these effects relate to functional and sleep-related symptoms

EEG theta oscillations during sleep deprivation

Brain oscillations of different frequencies characterize the electroencephalogram (EEG) during distinct cognitive and vigilant states. Theta oscillations (4-8 Hz) are unusual because they have been found in the near-opposite conditions of sleepiness and alert cognitive control. Most neuroscience research fo-cuses exclusively on the latter, leaving this paradox unresolved. With this thesis, I focus instead on the-ta during sleep deprivation (sdTheta), which has been hypothesized to reflect intrusions of local slow wave sleep on wake, based on a study in rats. The goal was to determine whether sdTheta in humans could also be considered a form of local sleep in wake, or if it was a manifestation of more typical cog-nition-related theta. I collected high-density EEG data from young healthy adults undergoing sleep deprivation to observe how sdTheta is affected by time awake, time of day, different tasks, and condi-tions. To independently track the effects of sleep deprivation, I also conducted extensive questionnaires and collected pupillometry data. I found that sdTheta can be widespread across the brain, although the specific sources depend on the ongoing task. Curiously, theta mostly originated from areas not critical for the task. I found that sdTheta occurs in bursts, making it unlike the isolated theta events thought to reflect local sleep. Furthermore, I found that independently from changes in the occurrences of such bursts, wake oscillation amplitudes increase with time awake, following a homeostatic trajectory. This supports the hypothesis that neuronal connectivity increases with time awake, which is what underlies sleep need. Unexpectedly, I found that the wake maintenance zone, a time before habitual bedtime when it is difficult to fall asleep, can mask these homeostatic changes in oscillation amplitudes. How-ever, the wake maintenance zone only minimally affects the presence of sdTheta bursts. Finally, I could not find any evidence that theta bursts were the cause of behavioral lapses nor compensating for sleep loss, supporting the previous finding of sdTheta originating from task-unrelated areas. Therefore, I ten-tatively propose that sdTheta bursts are a manifestation of unneeded parts of the brain at rest, alt-hough not necessarily “local sleep.” If this means that sdTheta is a different type of oscillation from theta involved in cognition, then care will be needed to dissociate the two types. Regardless of what it does, theta makes for a robust marker of sleep need and can have many clinical diagnostic applications, especially when analyzed effectively