Endovascular treatment of direct carotid cavernous fistula resulting from rupture of intracavernous carotid aneurysm: A case report.

BACKGROUND: Direct carotid cavernous fistulas (CCFs) are typically the result of a severe traumatic brain injury. High-flow arteriovenous shunts secondary to rupture of an intracavernous aneurysm, resulting in direct CCFs, are rare. The use of a pipeline embolization device in conjunction with coils and Onyx glue for treatment of direct high-flow CCF resulting from ruptured cavernous carotid artery aneurysm in a clinical setting is not well documented. CASE SUMMARY: A 58-year-old woman presented to our department with symptoms of blepharoptosis and intracranial bruits for 1 wk. During physical examination, there was right eye exophthalmos and ocular motor palsy. The rest of the neurological examination was clear. Notably, the patient had no history of head injury. The patient was treated with a pipeline embolization device in the ipsilateral internal carotid artery across the fistula. Coils and Onyx were placed through the femoral venous route, followed by placement of the pipeline embolization device with assistance from a balloon-coiling technique. No intraoperative or perioperative complications occurred. Preoperative symptoms of bulbar hyperemia and bruits subsided immediately after the operation. CONCLUSION: Pipeline embolization device in conjunction with coiling and Onyx may be a safe and effective approach for direct CCFs.

Entomopathogenic fungi-based silver nanoparticles: a potential substitute of synthetic insecticides to counter behavioral and physiological immunity in Aedes aegypti mosquito (Diptera: Culicidae).

Excessive use of synthetic insecticides has resulted in environmental contamination and adverse effects on humans and other non-target organisms. Entomopathogenic fungi offer eco-friendly alternatives; however, their application for pest control requires significant advancement owing to limitations like slow killing time and effectiveness only when applied in higher amounts, whereas exposure to UV radiation, high temperature, and humidity can also reduce their viability and shelf-life. The nanoparticles synthesized using fungal extracellular extracts provide a new approach to use fungal pathogens. Our study focused on the synthesis of Metarhizium anisopliae-based silver nanoparticles (AgNPs) and evaluation of their efficiency on various physiological and behavioral parameters of the mosquito Aedes aegypti. The synthesis, size (27.6 d.nm, PDI = 0.209), zeta potential (- 24.3 mV), and shape of the AgNPs were determined through dynamic light scattering, scanning and transmission electron microscopic, and UV-visual spectroscopic analyses (432 nm). Our results showed significantly reduced survival (100% decrease in case of 3.2 and 1.8 µL/cm2 volumes, and 60% decrease in case of 0.8 µL/cm2 volume), phenoloxidase activity (t = 39.91; p = 0.0001), and gut microbiota, with increased oxidative stress and cell apoptosis in AgNPs-challenged mosquitoes. Furthermore, the AgNPs-exposed mosquitoes presented a concentration-specific decrease in flight locomotor activity (F = 17.312; p < 0.0001), whereas no significant changes in antifungal activity, self-grooming frequencies, or time spent were found. These findings enhance our understanding of mosquito responses to AgNPs exposure, and offer a more efficient mosquito control strategy using entomopathogenic fungi.

Neural manifestation of L2 novel concept acquisition from multi-contexts via both episodic memory and semantic memory systems.

This study aims to examine the process of L2 novel word learning through the combination of episodic and semantic memory, and how the process differs between the formation of thematic and taxonomic relations. The major approach adopted was observing the neural effects of word learning, which is manifested in the N400 from event-related potentials (ERPs). Eighty-eight participants were recruited for the experiment. In the learning session, L2 contextual discourses related to novel words were learned by participants. In the testing session, discourses embedded with incongruous and congruous novel words in the final position were used for participants to judge the congruency which affected the N400 neural activity. The results showed that both recurrent and new-theme discourses elicited significant N400 effects, while taxonomic sentences did not. These results confirmed the formation of episodic and semantic memory during L2 new word learning, in which semantic memory was mainly supported by thematic relations.

Multilevel and multifaceted brain response features in spiking, ERP and ERD: experimental observation and simultaneous generation in a neuronal network model with excitation-inhibition balance.

Brain as a dynamic system responds to stimulations with specific patterns affected by its inherent ongoing dynamics. The patterns are manifested across different levels of organization-from spiking activity of neurons to collective oscillations in local field potential (LFP) and electroencephalogram (EEG). The multilevel and multifaceted response activities show patterns seemingly distinct and non-comparable from each other, but they should be coherently related because they are generated from the same underlying neural dynamic system. A coherent understanding of the interrelationships between different levels/aspects of activity features is important for understanding the complex brain functions. Here, based on analysis of data from human EEG, monkey LFP and neuronal spiking, we demonstrated that the brain response activities from different levels of neural system are highly coherent: the external stimulus simultaneously generated event-related potentials, event-related desynchronization, and variation in neuronal spiking activities that precisely match with each other in the temporal unfolding. Based on a biologically plausible but generic network of conductance-based integrate-and-fire excitatory and inhibitory neurons with dense connections, we showed that the multiple key features can be simultaneously produced at critical dynamical regimes supported by excitation-inhibition (E-I) balance. The elucidation of the inherent coherency of various neural response activities and demonstration of a simple dynamical neural circuit system having the ability to simultaneously produce multiple features suggest the plausibility of understanding high-level brain function and cognition from elementary and generic neuronal dynamics. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09889-w.

Entomopathogenic fungal infection following immune gene silencing decreased behavioral and physiological fitness in Aedes aegypti mosquitoes.

Entomopathogenic fungi are a promising category of biocontrol agents with mosquitocidal properties. Prior studies have proved their potential to reduce fecundity, human biting and vector competence, all of them together determine vectorial capacity of the mosquitoes. Unfortunately, conventional vector control strategies are inadequate with growing problem of insecticide resistance and environmental deterioration. Therefore, alternate vector control measures are immediately needed and to accomplish that, an improved understanding of behavioral and physiological defense mechanisms of the mosquitoes against fungal infection is essential. In this study, fitness was considered with respect to different behavioral (self-grooming and flight), physiological (antifungal activity and antimicrobial peptides) parameters and survival rates as compared to the control group. We found a significant upregulation in CLSP2, TEP22, Rel1 and Rel2 genes at multiple time periods of fungal infection, which indicates the successful fungal infection and activation of Toll and IMD pathways in mosquitoes. RNAi-mediated silencing of Rel1 and Rel2 genes (transcription factors of Toll and IMD pathways, respectively) significantly reduced the survival, self-grooming frequencies and durations, and flight locomotor activity among adult Ae. aegypti female mosquitoes. Moreover, Rel1 and Rel2 knockdown significantly decreased antifungal activity and antimicrobial peptides expression levels in target mosquitoes. These results indicate an overall decrease in fitness of the mosquitoes after fungal challenge following Rel1 and Rel2 silencing. These findings provide an improved understanding of behavioral and physiological responses in mosquitoes with altered immunity against entomopathogenic fungal infections which can guide us towards the development of novel biocontrol strategies against mosquitoes.

Exploiting Information in Event-Related Brain Potentials from Average Temporal Waveform, Time-Frequency Representation, and Phase Dynamics.

Characterizing the brain's dynamic pattern of response to an input in electroencephalography (EEG) is not a trivial task due to the entanglement of the complex spontaneous brain activity. In this context, the brain's response can be defined as (1) the additional neural activity components generated after the input or (2) the changes in the ongoing spontaneous activities induced by the input. Moreover, the response can be manifested in multiple features. Three commonly studied examples of features are (1) transient temporal waveform, (2) time-frequency representation, and (3) phase dynamics. The most extensively used method of average event-related potentials (ERPs) captures the first one, while the latter two and other more complex features are attracting increasing attention. However, there has not been much work providing a systematic illustration and guidance for how to effectively exploit multifaceted features in neural cognitive research. Based on a visual oddball ERPs dataset with 200 participants, this work demonstrates how the information from the above-mentioned features are complementary to each other and how they can be integrated based on stereotypical neural-network-based machine learning approaches to better exploit neural dynamic information in basic and applied cognitive research.

Comparative analysis of multifaceted neural effects associated with varying endogenous cognitive load.

Contemporary neuroscience has firmly established that mental state variation concurs with changes in neural dynamic activity in a complex way that a one-to-one mapping cannot describe. To explore the scenario of the multifaceted changes in neural dynamics associated with simple mental state variation, we took cognitive load - a common cognitive manipulation in psychology - as a venue to characterize how multiple neural dynamic features are simultaneously altered by the manipulation and how their sensitivity differs. Electroencephalogram was collected from 152 participants performing stimulus-free tasks with different demands. The results show that task demand alters wide-ranging neural dynamic features, including band-specific oscillations across broad frequency bands, scale-free dynamics, and cross-frequency phase-amplitude coupling. The scale-free dynamics outperformed others in indexing cognitive load variation. This study demonstrates a complex relationship between cognitive dynamics and neural dynamics, which points to a necessity to integrate multifaceted neural dynamic features when studying mind-brain relationship in the future.

Stable Lanthanide-Organic Frameworks: Crystal Structure, Photoluminescence, and Chemical Sensing of Vanillylmandelic Acid as a Biomarker of Pheochromocytoma.

Several isostructural lanthanide metal-organic frameworks, viz. [Ln(DCHB)1.5phen]n (Ln-MOFs, where Ln = Eu for 1, Tb for 2, Sm for 3 and Dy for 4), are successfully synthesized through the hydrothermal reactions of 4'-di(4-carboxylphenoxy)hydroxyl-2, 2'-bipyridyl (H2DCHB) and lanthanide nitrates as well as chelator 1,10-phenantroline (phen). These structures are characterized by single-crystal X-ray diffraction, and the representative Ln-MOF 1 is a fivefold interpenetrated framework with the uncoordinated Lewis base N sites form DCHB2- ligands. The photoluminescence research studies reveal that Ln-MOFs 1-4 exhibit characteristic fluorescent emissions from ligand-induced lanthanide Ln(III) ions, while the single-component emission spectra of Ln-MOF 4 are all located in a white region under different excitations. The absence of coordinated water and the interpenetration property of the structures are conducive to the structure rigidity, and the results display that Ln-MOF 1 has high thermal/chemical stabilities in common solvents and a wide pH range as well as the boiling water. Notably, luminescent sensing studies reveal that Ln-MOF 1 with prominent fluorescence properties can perform in highly sensitive and selective sensing of vanillylmandelic acid (VMA) in aqueous systems (KSV = 562.8 L·mol-1; LOD = 4.6 × 10-4 M), which can potentially establish a detection platform for the diagnosis of pheochromocytoma via multiquenching mechanisms. Moreover, the 1@MMMs sensing membranes comprised of Ln-MOF 1 and a poly(vinylidene fluoride) (PVDF) polymer can also be facilely developed for VMA detection in aqueous media, suggesting the enhanced convenience and efficiency of practical sensing applications.

Differential associations between scale-free neural dynamics and different levels of cognitive ability.

As indicators of cognitive function, scale-free neural dynamics are gaining increasing attention in cognitive neuroscience. Although the functional relevance of scale-free dynamics has been extensively reported, one fundamental question about its association with cognitive ability remains unanswered: is the association universal across a wide spectrum of cognitive abilities or confined to specific domains? Based on dual-process theory, we designed two categories of tasks to analyze two types of cognitive processes-automatic and controlled-and examined their associations with scale-free neural dynamics characterized from resting-state electroencephalography (EEG) recordings obtained from a large sample of human adults (N = 102). Our results showed that resting-state scale-free neural dynamics did not predict individuals' behavioral performance in tasks that primarily engaged the automatic process but did so in tasks that primarily engaged the controlled process. In addition, by fitting the scale-free parameters separately in different frequency bands, we found that the cognitive association of scale-free dynamics was more strongly manifested in higher-band EEG spectrum. Our findings indicate that resting-state scale-free dynamics are not universal neural indicators for all cognitive abilities but are mainly associated with high-level cognition that entails controlled processes. This finding is compatible with the widely claimed role of scale-free dynamics in reflecting properties of complex dynamic systems.

A generic neural factor linking resting-state neural dynamics and the brain's response to unexpectedness in multilevel cognition.

The brain's response to change is fundamental to learning and adaptation; this implies the presence of a universal neural mechanism under various contexts. We hypothesized that this mechanism manifests in neural activity patterns across low and high levels of cognition during task processing as well as in resting-state neural dynamics, because both these elements are different facets of the same dynamical system. We tested our hypothesis by (i) characterizing (a) the neural response to changes in low-level continuous information stream and unexpectedness at different cognitive levels and (b) the spontaneous neural dynamics in resting state, and (ii) examining the associations among the dynamics according to cross-individual variability (n = 200). Our results showed that the brain's response magnitude was monotonically correlated with the magnitude of information fluctuation in a low-level task, forming a simple psychophysical function; moreover, this effect was found to be associated with the brain's response to unexpectedness in high-level cognitive tasks (including language processing). These coherent multilevel neural effects in task processing were also shown to be strongly associated with resting-state neural dynamics characterized by the waxing and waning of Alpha oscillation. Taken together, our results revealed large-scale consistency between the neural dynamic system and multilevel cognition.

Multimodal Evidence of Atypical Processing of Eye Gaze and Facial Emotion in Children With Autistic Traits.

According to the shared signal hypothesis (SSH) the impact of facial expressions on emotion processing partially depends on whether the gaze is directed toward or away from the observer. In autism spectrum disorder (ASD) several aspects of face processing have been found to be atypical, including attention to eye gaze and the identification of emotional expressions. However, there is little research on how gaze direction affects emotional expression processing in typically developing (TD) individuals and in those with ASD. This question is investigated here in two multimodal experiments. Experiment 1 required processing eye gaze direction while faces differed in emotional expression. Forty-seven children (aged 9-12 years) participated. Their Autism Diagnostic Observation Schedule (ADOS) scores ranged from 0 to 6 in the experiment. Event-related potentials (ERPs) were sensitive to gaze direction and emotion, but emotion processing did not depend on gaze direction. However, for angry faces the gaze direction effect on the N170 amplitude, as typically observed in TD individuals, diminished with increasing ADOS score. For neutral expressions this correlation was not significant. Experiment 2 required explicit emotion classifications in a facial emotion composite task while eye gaze was manipulated incidentally. A group of 22 children with ASD was compared to a propensity score-matched group of TD children (mean age = 13 years). The same comparison was carried out for a subgroup of nine children with ASD who were less trained in social cognition, according to clinician's report. The ASD group performed overall worse in emotion recognition than the TD group, independently of emotion or gaze direction. However, for disgust expressions, eye tracking data revealed that TD children fixated relatively longer on the eyes of the stimulus face with a direct gaze as compared with averted gaze. In children with ASD we observed no such modulation of fixation behavior as a function of gaze direction. Overall, the present findings from ERPs and eye tracking confirm the hypothesis of an impaired sensitivity to gaze direction in children with ASD or elevated autistic traits, at least for specific emotions. Therefore, we conclude that multimodal investigations of the interaction between emotional processing and stimulus gaze direction are promising to understand the characteristics of individuals differing along the autism trait dimension.

Automated analysis of microplastics based on vibrational spectroscopy: are we measuring the same metrics?

The traditional manual analysis of microplastics has been criticized for its labor-intensive, inaccurate identification of small microplastics, and the lack of uniformity. There are already three automated analysis strategies for microplastics based on vibrational spectroscopy: laser direct infrared (LDIR)-based particle analysis, Raman-based particle analysis, and focal plane array-Fourier transform infrared (FPA-FTIR) imaging. We compared their performances in terms of quantification, detection limit, size measurement, and material identification accuracy and speed by analyzing the same standard and environmental samples. LDIR-based particle analysis provides the fastest analysis speed, but potentially questionable material identification and quantification results. The number of particles smaller than 60 µm recognized by LDIR-based particle analysis is much less than that recognized by Raman-based particle analysis. Misidentification could occur due to the narrow tuning range from 1800 to 975 cm-1 and dispersive artifact distortion of infrared spectra collected in reflection mode. Raman-based particle analysis has a submicrometer detection limit but should be cautiously used in the automated analysis of microplastics in environmental samples because of the strong fluorescence interference. FPA-FTIR imaging provides relatively reliable quantification and material identification for microplastics in environmental samples greater than 20 µm but might provide an imprecise description of the particle shapes. Optical photothermal infrared (O-PTIR) spectroscopy can detect submicron-sized environmental microplastics (0.5-5 µm) intermingled with a substantial amount of biological matrix; the resulting spectra are searchable in infrared databases without the influence of fluorescence interference, but the process would need to be fully automated.

Handling EEG artifacts and searching individually optimal experimental parameter in real time: a system development and demonstration.

Objective.Neuroadaptive paradigms that systematically assess event-related potential (ERP) features across many different experimental parameters have the potential to improve the generalizability of ERP findings and may help to accelerate ERP-based biomarker discovery by identifying the exact experimental conditions for which ERPs differ most for a certain clinical population. Obtaining robust and reliable ERPs online is a prerequisite for ERP-based neuroadaptive research. One of the key steps involved is to correctly isolate electroencephalography artifacts in real time because they contribute a large amount of variance that, if not removed, will greatly distort the ERP obtained. Another key factor of concern is the computational cost of the online artifact handling method. This work aims to develop and validate a cost-efficient system to support ERP-based neuroadaptive research.Approach.We developed a simple online artifact handling method, single trial PCA-based artifact removal (SPA), based on variance distribution dichotomies to distinguish between artifacts and neural activity. We then applied this method in an ERP-based neuroadaptive paradigm in which Bayesian optimization was used to search individually optimal inter-stimulus-interval (ISI) that generates ERP with the highest signal-to-noise ratio.Main results.SPA was compared to other offline and online algorithms. The results showed that SPA exhibited good performance in both computational efficiency and preservation of ERP pattern. Based on SPA, the Bayesian optimization procedure was able to quickly find individually optimal ISI.Significance.The current work presents a simple yet highly cost-efficient method that has been validated in its ability to extract ERP, preserve ERP effects, and better support ERP-based neuroadaptive paradigm.

Temporally resolved neural dynamics underlying handwriting.

How do the temporal dynamics of neural activity encode highly coordinated visual-motor behaviour? To capture the millisecond-resolved neural activations associated with fine visual-motor skills, we devised a co-registration system to simultaneously record electroencephalogram and handwriting kinematics while participants were performing four handwriting tasks (writing in Chinese/English scripts with their dominant/non-dominant hand). The neural activation associated with each stroke was clearly identified with a well-structured and reliable pattern. The functional significance of this pattern was validated by its significant associations with language, hand and the cognitive stages and kinematics of handwriting. Furthermore, the handwriting rhythmicity was found to be synchronised to the brain's ongoing theta oscillation, and the synchronisation was associated with the factor of language and hand. These major findings imply an implication between motor skill formation and the interplay between the rhythms in the brain and the peripheral systems.

[Research progress in establishment of N-methyl-N'-nitro-N-nitroso-guanidine-induced rat model of Precancerous lesion of gastric cancer].

Gastric cancer(GC), one of the most common malignancies worldwide, seriously threatens human health due to its high morbidity and mortality. Precancerous lesion of gastric cancer(PLGC) is a critical stage for preventing the occurrence of gastric cancer, and PLGC therapy has frequently been investigated in clinical research. Exploring the proper animal modeling methods is necessary since animal experiment acts as the main avenue of the research on GC treatment. At present, N-methyl-N'-nitro-N-nitroso-guanidine(MNNG) serves as a common chemical inducer for the rat model of GC and PLGC. In this study, MNNG-based methods for modeling PLGC rats in related papers were summarized, and the applications and effects of these methods were demonstrated by examples. Additionally, the advantages, disadvantages, and precautions of various modeling methods were briefly reviewed, and the experience of this research group in exploring modeling methods was shared. This study is expected to provide a reference for the establishment of MNNG-induced PLGC animal model, and a model support for the following studies on PLGC.

Online recognition of handwritten characters from scalp-recorded brain activities during handwriting.

Objective.Brain-computer interfaces aim to build an efficient communication with the world using neural signals, which may bring great benefits to human society, especially to people with physical impairments. To date, the ability to translate brain signals to effective communication outcome remains low. This work explores whether the handwriting process could serve as a potential interface with high performance. To this end, we first examined how much the scalp-recorded brain signals encode information related to handwriting and whether it is feasible to precisely retrieve the handwritten content solely from the scalp-recorded electrical data.Approach.Five participants were instructed to write the sentence 'HELLO, WORLD!' repeatedly on a tablet while their brain signals were simultaneously recorded by electroencephalography (EEG). The EEG signals were first decomposed by independent component analysis for extracting features to be used to train a convolutional neural network (CNN) to recognize the written symbols.Main results.The accuracy of the CNN-based classifier trained and applied on the same participant (training and test data separated) ranged from 76.8% to 97.0%. The accuracy of cross-participant application was more diverse, ranging from 14.7% to 58.7%. These results showed the possibility of recognizing the handwritten content directly from the scalp level brain signal. A demonstration of the recognition system in an online mode was presented. The major factor that grounded the recognition was the close association between the rich dynamics of electroencephalogram source activities and the kinematic information during the handwriting movements.Significance.This work revealed an explicit and precise mapping between scalp-level electrophysiological signals and linguistic information conveyed by handwriting, which provided a novel approach to developing brain computer interfaces that focus on semantic communication.

Morphological facilitation and semantic interference in compound production: An ERP study.

This study investigates the production of nominal compounds (Experiment 1) and simple nouns (Experiment 2) in a picture-word interference (PWI) paradigm to test models of morpho-lexical representation and processing. The continuous electroencephalogram (EEG) was registered and event-related brain potentials [ERPs] were analyzed in addition to picture-naming latencies. Experiment 1 used morphologically and semantically related distractor words to tap into different pre-articulatory planning stages during compound production. Relative to unrelated distractors, naming was speeded when distractors corresponded to morphemes of the compound (sun or flower for the target sunflower), but slowed when distractors were from the same semantic category as the compound (tulip ➔ sunflower). Distractors from the same category as the compound's first constituent (moon ➔ sunflower) had no influence. The diverging effects for semantic and morphological distractors replicate results from earlier studies. ERPs revealed different effects of morphological and semantic distractors with an interesting time course: morphological effects had an earlier onset. Comparable to the naming latencies, no ERP effects were obtained for distractors from the same semantic category as the compound's first constituent. Experiment 2 investigated the effectiveness of the latter distractors, presenting them with pictures of the compounds' first constituents (e.g., moon ➔ sun). Interference was confirmed both behaviorally and in the ERPs, showing that the absence of an effect in Experiment 1 was not due to the materials used. Considering current models of speech production, the data are best explained by a cascading flow of activation throughout semantic, lexical and morpho-phonological steps of speech planning.

Mechanisms of face specificity - Differentiating speed and accuracy in face cognition by event-related potentials of central processing.

Given the crucial role of face recognition in social life, it is hardly surprising that cognitive processes specific for faces have been identified. In previous individual differences studies, the speed (measured in easy tasks) and accuracy (difficult tasks) of face cognition (FC, involving perception and recognition of faces) have been shown to form distinct abilities, going along with divergent factorial structures. This result has been replicated, but remained unexplained. To fill this gap, we first parameterized the sub-processes underlying speed vs. accuracy in easy and difficult memory tasks for faces and houses in a large sample. Then, we analyzed event-related potentials (ERPs) extracted from the EEG by using residue iteration decomposition (RIDE), yielding a central (C) component that is comparable to a purified P300. Structural equation modeling (SEM) was applied to estimate face specificity of C component latencies and amplitudes. If performance in easy tasks relies on purely general processes that are insensitive to stimulus content, there should be no specificity of individual differences in the latency recorded in easy tasks. However, in difficult tasks specificity was expected. Results indicated that, contrary to our predictions, specificity occurred in the C component latency of both speed-based and accuracy-based measures, but was stronger in accuracy. Further analyses suggested specific relationships between the face-related C latency and FC ability. Finally, we detected specificity in RTs of easy tasks when single tasks were modeled, but not when multiple tasks were jointly modeled. This suggests that the mechanisms leading to face specificity in performance speed are distinct across tasks.

What Does Temporal Brain Signal Complexity Reveal About Verbal Creativity?

Recent empirical evidence reveals that creative idea generation builds upon an interplay of multiple neural networks. Measures of temporal complexity yield important information about the underlying mechanisms of these co-activated neural networks. A few neurophysiological studies investigated brain signal complexity (BSC) during the production of creative verbal associations and resting states, aiming to relate it with creative task performance. However, it is unknown whether the complexity of brain signals can distinguish between productions of typical and original verbal associations. In the present study, we investigated verbal creativity with multiscale entropy (MSE) of electroencephalography (EEG) signals, which quantifies complexity over multiple timescales, capturing unique dynamic features of neural networks. MSE was measured in verbal divergent thinking (DT) states while emphasizing on producing either typical verbal associations or original verbal associations. We hypothesized that MSE differentiates between brain states characterizing the production of typical and original associations and is a sensitive neural marker of individual differences in producing original associations. Results from a sample of N = 92 young adults revealed slightly higher average MSE for original as compared with typical association production in small and medium timescales at frontal electrodes and slightly higher average MSE for typical association production in higher timescales at parietal electrodes. However, measurement models failed to uncover specificity of individual differences as MSE in typical vs. original associations was perfectly correlated. Hence, individuals with higher MSE in original association condition also exhibit higher MSE during the production of typical associations. The difference between typical and original association MSE was not significantly associated with human-rated originality of the verbal associations. In sum, we conclude that MSE is a potential marker of creative verbal association states, but replications and extensions are needed, especially with respect to the brain-behavior relationships.

Characterizing the brain's dynamical response from scalp-level neural electrical signals: a review of methodology development.

The brain displays dynamical system behaviors at various levels that are functionally and cognitively relevant. Ample researches have examined how the dynamical properties of brain activity reflect the neural cognitive working mechanisms. A prevalent approach in this field is to extract the trial-averaged brain electrophysiological signals as a representation of the dynamical response of the complex neural system to external stimuli. However, the responses are intrinsically variable in latency from trial to trial. The variability compromises the accuracy of the detected dynamical response pattern based on trial-averaged approach, which may mislead subsequent modelling works. More accurate characterization of the brain's dynamical response incorporating single trial variability information is of profound significance in deepening our understanding of neural cognitive dynamics and brain's working principles. Various methods have been attempted to address the trial-to-trial asynchrony issue in order to achieve an improved representation of the dynamical response. We review the latest development of methodology in this area and the contribution of latency variability-based decomposition and reconstruction of dynamical response to neural cognitive researches.