Theta Band Power Research Articles

892 Pain Intensity Is Characterized by Theta Band Dynamics and Opioid Pain Medication Effect at Gamma Band Dynamics Within the Human Subcortical Structures

INTRODUCTION: Chronic pain is a multifaceted condition that involves processes of sensation, cognition, and emotion. Given its complexity, characterizing the dynamic changes in pain intensity for patients with chronic pain has remained a challenge. Several EEG studies have shown chronic pain patients to exhibit an increased theta and alpha band power, and acute pain to induce an increased gamma power. However, these do not inform the dynamical changes in pain fluctuations, and critically at the subcortical hubs that modulate the processes of sensation, cognition, and emotion. METHODS: The patients continuously rated their pain level for approximately 10 minutes, and we characterized the pain reduction that occurred spontaneously and that occurred via opioid pain medication. We used a novel method coined variance of auto-information (VAI), that would parameterize the stochasticity (i.e., randomness) of the theta and gamma bandpass filtered LFP. RESULTS: In all four patients, the theta VAI (randomness) was found to be lower as pain was relieved both spontaneously (p = 0.01) and via fentanyl (p = 0.03). The gamma VAI was higher when pain was relieved via fentanyl (p = 0.03). CONCLUSIONS: The results demonstrate characterizing pain intensity using the human neuronal oscillatory activity from the subcortical structures. We also introduce the VAI method that consistently characterize pain relief among chronic pain patients. These findings may help to identify biomarkers for pain intensity, and potentially guide stimulation targets for closed-loop neuromodulatory treatment.

Task-irrelevant decorative pictures increase cognitive load during text processing but have no effects on learning or working memory performance: an EEG and eye-tracking study

Decorative pictures (DP) are often used in multimedia task materials and are commonly considered so-called seductive details as they are commonly not task-relevant. Typically, DP result in mixed effects on behavioral performance measures. The current study focused on the effects of DP on the cognitive load during text reading and working memory task performance. The theta and alpha frequency band power of the electroencephalogram (EEG) and pupil dilation served as proxies of cognitive load. The number of fixations, mean fixation durations, and the number of transitions served as proxies of the attentional focus. For both, text reading and n-back working memory tasks, the presence and congruency of DP were manipulated in four task conditions. DP did neither affect behavioral performance nor subjective ratings of emotional–motivational factors. However, in both tasks, DP increased the cognitive load as revealed by the EEG alpha frequency band power and (at least to some extent) by subjective effort ratings. Notably, the EEG alpha frequency band power was a quite reliable and sensitive proxy of cognitive load. Analyzing the EEG data stimulus-locked and fixation-related, the EEG alpha frequency band power revealed a difference in global and local cognitive load. In sum, the current study underlines the feasibility and use of EEG for multimedia research, especially when combined with eye-tracking.

Distinct and common mechanisms of cross-model semantic conflict and response conflict in an auditory relevant task.

The mechanisms of semantic conflict and response conflict in the Stroop task have mainly been investigated in the visual modality. However, the understanding of these mechanisms in cross-modal modalities remains limited. In this electroencephalography (EEG) study, an audiovisual 2-1 mapping Stroop task was utilized to investigate whether distinct and/or common neural mechanisms underlie cross-modal semantic conflict and response conflict. The response time data showed significant effects on both cross-modal semantic and response conflicts. Interestingly, the magnitude of semantic conflict was found to be smaller in the fast response time bins than in the slow response time bins, whereas no such difference was observed for response conflict. The EEG data demonstrated that cross-modal semantic conflict specifically increased the N450 amplitude. However, cross-modal response conflict specifically enhanced theta band power and theta phase synchronization between the medial frontal cortex (MFC) and lateral prefrontal electrodes as well as between the MFC and motor electrodes. In addition, both cross-modal semantic conflict and response conflict led to a decrease in P3 amplitude. Taken together, these findings provide cross-modal evidence for domain-specific mechanism in conflict detection and suggest both domain-specific and domain-general mechanisms exist in conflict resolution.

EEG Frequency Correlates with α2-Receptor Density in Parkinson's Disease.

Increased theta and delta power and decreased alpha and beta power, measured with quantitative electroencephalography (EEG), have been demonstrated to have utility for predicting the development of dementia in patients with Parkinson's disease (PD). Noradrenaline modulates cortical activity and optimizes cognitive processes. We claim that the loss of noradrenaline may explain cognitive impairment and the pathological slowing of EEG waves. Here, we test the relationship between the number of noradrenergic α2 adrenoceptors and changes in the spectral EEG ratio in patients with PD. We included nineteen patients with PD and thirteen healthy control (HC) subjects in the study. We used positron emission tomography (PET) with [11C]yohimbine to quantify α2 adrenoceptor density. We used EEG power in the delta (δ, 1.5-3.9 Hz), theta (θ, 4-7.9 Hz), alpha (α, 8-12.9 Hz) and beta (β, 13-30 Hz) bands in regression analyses to test the relationships between α2 adrenoceptor density and EEG band power. PD patients had higher power in the theta and delta bands compared to the HC volunteers. Patients' theta band power was inversely correlated with α2 adrenoceptor density in the frontal cortex. In the HC subjects, age was correlated with, and occipital background rhythm frequency (BRF) was inversely correlated with, α2 adrenoceptor density in the frontal cortex, while occipital BRF was inversely correlated with α2 adrenoceptor density in the thalamus. The findings support the claim that the loss or dysfunction of noradrenergic neurotransmission may relate to the parallel processes of cognitive decline and EEG slowing.

Predicting the therapeutic response to valproic acid in childhood absence epilepsy through electroencephalogram analysis using machine learning

Childhood absence epilepsy (CAE) is a common type of idiopathic generalized epilepsy, manifesting as daily multiple absence seizures. Although seizures in most patients can be adequately controlled with first-line antiseizure medication (ASM), approximately 25 % of patients respond poorly to first-line ASM. In addition, an accurate method for predicting first-line medication responsiveness is lacking. We used the quantitative electroencephalogram (QEEG) features of patients with CAE along with machine learning to predict the therapeutic effects of valproic acid in this population. We enrolled 25 patients with CAE from multiple medical centers. Twelve patients who required additional medication for seizure control or who were shifted to another ASM and 13 patients who achieved seizure freedom with valproic acid within 6 months served as the nonresponder and responder groups. Using machine learning, we analyzed the interictal background EEG data without epileptiform discharge before ASM. The following features were analyzed: EEG frequency bands, Hjorth parameters, detrended fluctuation analysis, Higuchi fractal dimension, Lempel–Ziv complexity (LZC), Petrosian fractal dimension, and sample entropy (SE). We applied leave-one-out cross-validation with support vector machine, K-nearest neighbor (KNN), random forest, decision tree, Ada boost, and extreme gradient boosting, and we tested the performance of these models. The responders had significantly higher alpha band power and lower delta band power than the nonresponders. The Hjorth mobility, LZC, and SE values in the temporal, parietal, and occipital lobes were higher in the responders than in the nonresponders. Hjorth complexity was higher in the nonresponders than in the responders in almost all the brain regions, except for the leads FP1 and FP2. Using KNN classification with theta band power in the temporal lobe yielded optimal performance, with sensitivity of 92.31 %, specificity of 76.92 %, accuracy of 84.62 %, and area under the curve of 88.46 %.We used various EEG features along with machine learning to accurately predict whether patients with CAE would respond to valproic acid. Our method could provide valuable assistance for pediatric neurologists in selecting suitable ASM.

Exploring Embodied Cognition and Brain Dynamics under Multi-tasks Target Detection in Immerse Projector-based Augmented Reality (IPAR) Scenarios.

Embodied cognition explores the intricate interaction between the brain, body, and the surrounding environment. The advancement of mobile devices, such as immersive interactive computing and wireless electroencephalogram (EEG) devices, has presented new challenges and opportunities for studying embodied cognition. To address how mobile technology within immersive hybrid settings affects embodied cognition, we propose a target detection multitask incorporating mixed body movement interference and an environmental distraction light signal. We aim to investigate human embodied cognition in immersive projector-based augmented reality (IPAR) scenarios using wireless EEG technology. We recruited and engaged fifteen participants in four multitasking conditions: standing without distraction (SND), walking without distraction (WND), standing with distraction (SD), and walking with distraction (WD). We pre-processed the EEG data using Independent Component Analysis (ICA) to isolate brain sources and K-means clustering to categorize Independent Components (ICs). Following that, we conducted time-frequency and correlation analyses to identify neural dynamics changes associated with multitasking. Our findings reveal a decline in behavioral performance during multitasking activities. We also observed decreases in alpha and beta power in the frontal and motor cortex during standing target search tasks, decreases in theta power, and increases in alpha power in the occipital lobe during multitasking. We also noted perturbations in theta band power during distraction tasks. Notably, physical movement induced more significant fluctuations in the frontal and motor cortex than distractions from social environment light signals. Particularly in scenarios involving walking and multitasking, there was a noticeable reduction in beta suppression. Our study underscores the importance of brain-body collaboration in multitasking scenarios, where the simultaneous engagement of the body and brain in complex tasks highlights the dynamic nature of cognitive processes within the framework of embodied cognition. Furthermore, integrating immersive augmented reality technology into embodied cognition research enhances our understanding of the interplay between the body, environment, and cognitive functions, with profound implications for advancing human-computer interaction and elucidating cognitive dynamics in multitasking.

Effects of Virtual Reality Cognitive Training on Neuroplasticity: A Quasi-Randomized Clinical Trial in Patients with Stroke.

Cognitive Rehabilitation (CR) is a therapeutic approach designed to improve cognitive functioning after a brain injury, including stroke. Two major categories of techniques, namely traditional and advanced (including virtual reality-VR), are widely used in CR for patients with various neurological disorders. More objective outcome measures are needed to better investigate cognitive recovery after a stroke. In the last ten years, the application of electroencephalography (EEG) as a non-invasive and portable neuroimaging method has been explored to extract the hallmarks of neuroplasticity induced by VR rehabilitation approaches, particularly within the chronic stroke population. The aim of this study is to investigate the neurophysiological effects of CR conducted in a virtual environment using the VRRS device. Thirty patients with moderate-to-severe ischemic stroke in the chronic phase (at least 6 months after the event), with a mean age of 58.13 (±8.33) for the experimental group and 57.33 (±11.06) for the control group, were enrolled. They were divided into two groups: an experimental group and a control group, receiving neurocognitive stimulation using VR and the same amount of conventional neurorehabilitation, respectively. To study neuroplasticity changes after the training, we focused on the power band spectra of theta, alpha, and beta EEG rhythms in both groups. We observed that when VR technology was employed to amplify the effects of treatments on cognitive recovery, significant EEG-related neural improvements were detected in the primary motor circuit in terms of power spectral density and time-frequency domains. Indeed, EEG analysis suggested that VR resulted in a significant increase in both the alpha band power in the occipital areas and the beta band power in the frontal areas, while no significant variations were observed in the theta band power. Our data suggest the potential effectiveness of a VR-based rehabilitation approach in promoting neuroplastic changes even in the chronic phase of ischemic stroke.

Real‐time Memory‐related Neurofeedback Training Improves Intrinsic Brain Oscillations in Older Adults

AbstractBackgroundMild cognitive impairment (MCI), manifesting as working memory deficits for example, is the most common and earliest symptom of Alzheimer’s disease and related dementias (AD/ADRD). To combat the brain aging processes, early intervention is needed. Electroencephalogram (EEG)‐based neurofeedback (NF) has been found to be beneficial in treating a variety of brain disorders. Increased intrinsic delta power and decreased alpha is associated with brain aging and AD pathologies. We have developed an ERP‐based NF protocol to reward memory‐related potentials. In this study, we aim to evaluate the effect of NF training protocol.MethodThree older males (ages, 63, 78, and 79) participated in a newly developed NF training protocol including baseline and memory‐related NF training (twice a week). Each participant was recorded using 90‐second of eyes closed (EC) before multiple NF sessions during each visit. Their brain signals were collected with a 14‐channel wireless electroencephalogram (EEG) headset and processed in real‐time. The NF training contained 2 sham sessions followed by 2 intervention sessions. Compared to the intervention, visual feedback in the sham was provided in random order rather than triggered by participants’ ERP fluctuations. The EEG signal collected with EC before the experiment (Baseline, T0), 3 days after the sham (Sham, T1), and 3 days after the intervention (post‐intervention, T2) were preprocessed as 4s epoch windows and computed as the delta, theta, alpha, beta, and gamma band power. The average EEG band powers from T0, T1, and T2 and memory performances from the three participants were calculated.ResultThe working memory performance (accuracy and reaction times during retrievals of memory target and rejection of nontarget) did not show significant change among the three participants. In contrast, the EC intrinsic delta and alpha power changed towards brainwaves seen in younger brains after several sessions of NF training. Additionally, sham also improves in the alpha band (associated with attention and vigilance).ConclusionThe pilot results demonstrated the effectiveness of a newly developed NF training using working memory related potentials in two out of three older adults. The results indicate the promise of cognitive enhancement using event‐related potentials‐based NF training in real time.

Enhanced low-gamma band power in the hippocampus and prefrontal cortex in a rat model of depression is reversed by orexin-1 receptor antagonism

The hippocampal-prefrontal cortex network dynamics is reported to be involved in various cognitive functions and in different mood disturbances including depression. It has been suggested that blocking orexin-1 receptors can be beneficial in depression. The purpose of this study is to determine whether orexin-1 receptor antagonists have an impact on changes in brain oscillations in the hippocampus and prefrontal cortex in a rat model of depression. Forty-eight male Wistar rats were divided into six experimental groups: control, chronic mild stress (CMS), acute SB-334867, a selective orexin-1 receptor antagonist, treated rats (SB), chronic SB-treated (CSB), CMS+SB, and CMS+CSB. Two stainless steel recording electrodes were placed in the coordinates of the hippocampus (HPC) and the prefrontal cortex (PFC). After behavioral verification of the model, local field potentials were recorded at 1 kHz sampling frequency. The absolute power of different frequency bands was obtained using the Fast Fourier Transform (FFT) function, and the power spectral density (PSD) of each frequency band was calculated for each animal. In the CMS- treated animals, the low-gamma band power increased both in the HPC and PFC (p ≤ 0.05), which were reversed by chronic SB-334867 treatment (p ≤ 0.05). The alterations in theta, and high-gamma band power were not significant in CMS treated rats, while acute and chronic SB-334867 treatment diminished the theta and high-gamma band power (p ≤ 0.05), respectively. The hippocampal-prefrontal coherence decreased in the delta (p ≤ 0.01), theta (p ≤ 0.01), and alpha (p ≤ 0.05) band range of the CMS exposed rats. It is concluded that CMS boosts the low-gamma band power, which is reversed by CSB treatment. The low-frequency band coherence is attenuated after CMS treatment.

Electrophysiological effects of smartphone notifications on cognitive control following a brief mindfulness induction

Smartphone use is nearly ubiquitous, with 93% of adults among economically developed countries, including the United States, Canada, Israel, and South Korea owning a smartphone (Taylor & Silver, 2019). Multiple studies have demonstrated the distracting effects of smartphone notifications on behavioral measures of cognition. Fewer studies have examined the effects of notifications on neural activity underlying higher-level cognitive processes or behavioral inductions to reduce smartphone-related distraction. Using EEG spectral frequency power densities, we assessed the effects of smartphone notifications (vs. control trials) on engagement of attentional shifting processes involved in cognitive control during a Navon Letter visual oddball task. Participants were randomly assigned to a brief mindfulness induction (N = 44) or a neutral narration control condition (N = 43). Overall, participants had lower theta-band power, but higher alpha- and beta-band power densities on target letter trials preceded by smartphone notifications. Additionally, participants in the mindfulness (vs. control) condition had a larger attention shifting oddball assessed via theta power density and theta/beta ratio (TBR) values—reflecting increased engagement of cognitive control—particularly on smartphone notification (vs. control) trials. Altogether, these results provide evidence supporting the idea that smartphone notifications can decrease activity of neural correlates of cognitive control, and offer the promise of a brief mindfulness induction to buffer against the effects of smartphone notifications on cognitive control. The findings indicate a need for further research on mindfulness inductiosn as a means to reduce potential distraction caused by smartphones.

Combining EEG and 3D-eye-tracking to study the prediction of upcoming speech in naturalistic virtual environments: A proof of principle

EEG and eye-tracking provide complementary information when investigating language comprehension. Evidence that speech processing may be facilitated by speech prediction comes from the observation that a listener's eye gaze moves towards a referent before it is mentioned if the remainder of the spoken sentence is predictable. However, changes to the trajectory of anticipatory fixations could result from a change in prediction or an attention shift. Conversely, N400 amplitudes and concurrent spectral power provide information about the ease of word processing the moment the word is perceived. In a proof-of-principle investigation, we combined EEG and eye-tracking to study linguistic prediction in naturalistic, virtual environments. We observed increased processing, reflected in theta band power, either during verb processing - when the verb was predictive of the noun - or during noun processing - when the verb was not predictive of the noun. Alpha power was higher in response to the predictive verb and unpredictable nouns. We replicated typical effects of noun congruence but not predictability on the N400 in response to the noun. Thus, the rich visual context that accompanied speech in virtual reality influenced language processing compared to previous reports, where the visual context may have facilitated processing of unpredictable nouns. Finally, anticipatory fixations were predictive of spectral power during noun processing and the length of time fixating the target could be predicted by spectral power at verb onset, conditional on the object having been fixated. Overall, we show that combining EEG and eye-tracking provides a promising new method to answer novel research questions about the prediction of upcoming linguistic input, for example, regarding the role of extralinguistic cues in prediction during language comprehension.

Resting-state background features demonstrate multidien cycles in long-term EEG device recordings

BackgroundLongitudinal EEG recorded by implanted devices is critical for understanding and managing epilepsy. Recent research reports patient-specific, multi-day cycles in device-detected epileptiform events that coincide with increased likelihood of clinical seizures. Understanding these cycles could elucidate mechanisms generating seizures and advance drug and neurostimulation therapies. Objective/hypothesisWe hypothesize that seizure-correlated cycles are present in background neural activity, independent of interictal epileptiform spikes, and that neurostimulation may temporarily interrupt these cycles. MethodsWe analyzed regularly-recorded seizure-free data epochs from 20 patients implanted with a responsive neurostimulation (RNS) device for at least 1.5 years, to explore the relationship between cycles in device-detected interictal epileptiform activity (dIEA), clinician-validated interictal spikes, background EEG features, and neurostimulation. ResultsBackground EEG features tracked the cycle phase of dIEA in all patients (AUC: 0.63 [0.56–0.67]) with a greater effect size compared to clinically annotated spike rate alone (AUC: 0.55 [0.53–0.61], p < 0.01). After accounting for circadian variation and spike rate, we observed significant population trends in elevated theta and beta band power and theta and alpha connectivity features at the cycle peaks (sign test, p < 0.05). In the period directly after stimulation we observe a decreased association between cycle phase and EEG features compared to background recordings (AUC: 0.58 [0.55–0.64]). ConclusionsOur findings suggest that seizure-correlated dIEA cycles are not solely due to epileptiform discharges but are associated with background measures of brain state; and that neurostimulation may temporarily interrupt these cycles. These results may help elucidate mechanisms underlying seizure generation, provide new biomarkers for seizure risk, and facilitate monitoring, treating, and managing epilepsy with implantable devices.

Exploring Horizontally Flipped Interaction in Virtual Reality for Improving Spatial Ability.

Virtual reality (VR) is a high-fidelity medium that can offer experiences that are close to real-life. Spatial ability plays an important role in human life, including academic achievement and advancement in work settings. Spatial ability is known to be improved by practicing relevant tasks. Mental rotation and spatial perception are among such tasks that improve spatial skills. In this research, we investigated a "mirror-reversed" interaction technique in a cup stacking task in VR and looked into its effects on spatial ability, brain activity regarding spatial processing and attention (measured with EEG), performance, and user experience in male participants. Participants stacked cups according to given patterns using direct manipulation with horizontally flipped controls, similar to looking in a mirror while performing object manipulation in real life. In a between-subjects user study, we compared this novel interaction with a baseline where the participants completed the same task with regular controls. Although there was no significant main effect of group on the mental rotation and perspective taking/spatial orientation tests scores, within-group analysis indicated a trend toward an improvement in the mirror-reversed group in spatial orientation, while both groups showed a trend toward improvement in mental rotation. Participants in both groups got better at the task over time (their task completion durations decreased). EEG data revealed significant theta band power increase in the mirror-reversed group whereas there was no difference in the alpha band power between the two groups. Our results are encouraging for exploring spatially challenging interactions in VR for spatial skills training. We share the implementation and user study results, and discuss the implications.

Neural Oscillation Disorder in the Hippocampal CA1 Region of Different Alzheimer's Disease Mice.

Alzheimer's disease (AD) is a well-known neurodegenerative disease that gradually induces neural network dysfunction and progressive memory deficits. Neural network activity is represented by rhythmic oscillations that influence local field potentials (LFPs). However, changes in hippocampal neural rhythmic oscillations in the early stage of AD remain largely unexplored. This study investigated neural rhythmic oscillations in 3-month-old APP/PS1 and 5x- FAD mice to assess early neural connectivity in AD. LFPs were recorded from the hippocampal CA1 region with implanted microelectrode arrays while the mice were in the awake resting stage. Welch fast Fourier transforms, continuous wavelet transforms, and phase-amplitude coupling analyses were used to compute the power density of different frequency bands and phase-amplitude modulation indices in the LFPs. Our results showed impaired theta, low gamma, and high gamma frequency band power in APP/PS1 and 5xFAD mice during the awake resting stage. AD mice also showed decreased delta, alpha, and beta frequency band power. Impaired theta-low gamma and theta-high gamma phaseamplitude coupling were observed in 5xFAD mice. This study revealed neural network activity differences in oscillation power and cross-frequency coupling in the early stage of AD, providing a new perspective for developing biomarkers for early AD diagnosis.

Temporal dynamics of oscillatory activity during nonlexical language decoding: Evidence from Morse code and magnetoencephalography.

Understanding encoded languages, such as written script or Morse code, requires nonlexical and lexical processing components that act in a parallel and interactive fashion. Decoding written script-as for example in reading-is typically very fast, making the investigation of the lexical and nonlexical components and their underlying neural mechanisms challenging. In the current study, we aimed to accomplish this problem by using Morse code as a model for language decoding. The decoding of Morse code is slower and thus allows a better and more fine-grained investigation of the lexical and nonlexical components of language decoding. In the current study, we investigated the impact of various components of nonlexical decoding of Morse code using magnetoencephalography. For this purpose, we reconstructed the time-frequency responses below 40 Hz in brain regions significantly involved in Morse code decoding and word comprehension that were identified in a previous study. Event-related reduction in beta- and alpha-band power were found in left inferior frontal cortex and angular gyrus, respectively, while event-related theta-band power increase was found at frontal midline. These induced oscillations reflect working-memory encoding, long-term memory retrieval as well as demanding cognitive control, respectively. In sum, by using Morse code and MEG, we were able to identify a cortical network underlying language decoding in a time- and frequency-resolved manner.

Studying perceptual bias in favor of the from-above Necker cube perspective in a goal-directed behavior.

When viewing a completely ambiguous image, different interpretations can switch involuntarily due to internal top-down processing. In the case of the Necker cube, an entirely ambiguous stimulus, observers often display a bias in perceptual switching between two interpretations based on their perspectives: one with a from-above perspective (FA) and the other with a from-below perspective (FB). Typically, observers exhibit a priori top-down bias in favor of the FA interpretation, which may stem from a statistical tendency in everyday life where we more frequently observe objects from above. However, it remains unclear whether this perceptual bias persists when individuals voluntarily decide on the Necker cube's interpretation in goal-directed behavior, and the impact of ambiguity in this context is not well-understood. In our study, we instructed observers to voluntarily identify the orientation of a Necker cube while manipulating its ambiguity from low (LA) to high (HA). Our investigation aimed to test two hypotheses: (i) whether the perspective (FA or FB) would result in a bias in response time, and (ii) whether this bias would depend on the level of stimulus ambiguity. Additionally, we analyzed electroencephalogram (EEG) signals to identify potential biomarkers that could explain the observed perceptual bias. The behavioral results confirmed a perceptual bias in favor of the from-above perspective, as indicated by shorter response times. However, this bias diminished for stimuli with high ambiguity. For the LA stimuli, the occipital theta-band power consistently exceeded the frontal theta-band power throughout most of the decision-making time. In contrast, for the HA stimuli, the frontal theta-band power started to exceed the occipital theta-band power during the 0.3-s period preceding the decision. We propose that occipital theta-band power reflects evidence accumulation, while frontal theta-band power reflects its evaluation and decision-making processes. For the FB perspective, occipital theta-band power exhibited higher values and dominated over a longer duration, leading to an overall increase in response time. These results suggest that more information and more time are needed to encode stimuli with a FB perspective, as this template is less common for the observers compared to the template for a cube with a FA perspective.

Theta power relates to infant object encoding in naturalistic mother-infant interactions.

This study investigates infants' neural and behavioral responses to maternal ostensive signals during naturalistic mother-infant interactions and their effects on object encoding. Mothers familiarized their 9- to 10-month-olds (N = 35, 17 females, mainly White, data collection: 2018-2019) with objects with or without mutual gaze, infant-directed speech, and calling the infant's name. Ostensive signals focused infants' attention on objects and their mothers. Infant theta activity synchronized and alpha activity desynchronized during interactions compared to a nonsocial resting phase (Cohen' d: 0.49-0.75). Yet, their amplitudes were unrelated to maternal ostensive signals. Ostensive signals did not facilitate object encoding. However, higher infant theta power during encoding predicted better subsequent object recognition. Results strengthen the role of theta-band power for early learning processes.

Take your time: Slow brain rhythms predict fluid intelligence

Evidence is mixed whether fluid intelligence (Gf) is associated with increased or decreased alpha and beta band activity (7–30 Hz). Moreover, the Gf relationship with the delta and theta band activity (1–7 Hz) is unknown. We recorded electroencephalographic (EEG) data in 160 healthy adults solving Raven's Advanced Progressive Matrices with a randomized item order to control for item difficulty unaffected by sequential effects. The participants studied each matrix for 30 s before the response bank onset, so we could track the time course of neural activity during problem solving. We measured Gf using six tests. Gf positively correlated with the delta band power, while there was no correlation with the theta band power. For almost all of the participants, we identified the specific slow rhythm frequency, which varied in power as a function of item difficulty. We observed that the lower this frequency, the higher Gf, but only in men. Finally, the alpha and low-beta activity correlated negatively with Gf after we had filtered out the activity during idle intervals (the latter reflecting waiting for the response bank). Overall, the brain activity in the delta, alpha, and beta bands explained 22.6% of Gf variance.

Electrocortical activity correlated with locomotor adaptation during split-belt treadmill walking.

Locomotor adaptation is crucial for daily gait adjustments to changing environmental demands and obstacle avoidance. Mobile brain imaging with high-density electroencephalography (EEG) now permits quantification of electrocortical dynamics during human locomotion. To determine the brain areas involved in human locomotor adaptation, we recorded high-density EEG from healthy, young adults during split-belt treadmill walking. We incorporated a dual-electrode EEG system and neck electromyography to decrease motion and muscle artefacts. Voluntary movement preparation and execution have been linked to alpha (8-13Hz) and beta band (13-30Hz) desynchronizations in the sensorimotor and posterior parietal cortices, whereas theta band (4-7Hz) modulations in the anterior cingulate have been correlated with movement error monitoring. We hypothesized that relative to normal walking, split-belt walking would elicit: (1) decreases in alpha and beta band power in sensorimotor and posterior parietal cortices, reflecting enhanced motor flexibility; and (2) increases in theta band power in anterior cingulate cortex, reflecting instability and balance errors that will diminish with practice. We found electrocortical activity in multiple regions that was associated with stages of gait adaptation. Data indicated that sensorimotor and posterior parietal cortices had decreased alpha and beta band spectral power during early adaptation to split-belt treadmill walking that gradually returned to pre-adaptation levels by the end of the adaptation period. Our findings emphasize that multiple brain areas are involved in adjusting gait under changing environmental demands during human walking. Future studies could use these findings on healthy, young participants to identify dysfunctional supraspinal mechanisms that may be impairing gait adaptation. KEY POINTS: Identifying the location and time course of electrical changes in the brain correlating with gait adaptation increases our understanding of brain function and provides targets for brain stimulation interventions. Using high-density EEG in combination with 3D biomechanics, we found changes in neural oscillations localized near the sensorimotor, posterior parietal and cingulate cortices during split-belt treadmill adaptation. These findings suggest that multiple cortical mechanisms may be associated with locomotor adaptation, and their temporal dynamics can be quantified using mobile EEG. Results from this study can serve as a reference model to examine brain dynamics in individuals with movement disorders that cause gait asymmetry and reduced gait adaptation.

Neural correlates of evaluations of non-binary social feedback: An EEG study

PurposeIn complex and diverse social circumstances, decision making is affected by social feedback. Although previous studies have examined the electrophysiological correlates of social feedback with a binary valence, those related to non-binary feedback, or the magnitude of social feedback, remain unclear. This study investigated the electrophysiological correlates of non-binary social feedback and subsequent action selection processing. MethodsParticipants were asked to complete a Gabor patch direction judgment task in which they were required to make judgments before and after receiving social feedback. They were informed that the feedback stimuli represented the degree to which other participants made the same choice. Results & conclusionThe results revealed that feedback that was highly concordant with the participant's judgments elicited greater P300 activity, which was associated with the fulfillment of expectations regarding social reward. Moreover, moderately concordant feedback induced stronger theta band power, which may indicate monitoring of subjective conflict. Temporal changes in theta power during feedback phase may also relate to adjustments in prediction error. Additionally, when an initial judgment was maintained following social feedback, we observed a stronger increase in beta power, indicating an association with post-social-feedback action processing.