Temporal-spatial deciphering mental subtraction in the human brain

Mental subtraction, involving numerical processing and operation, requires a complex interplay among several brain regions. Diverse studies have utilized scalp electroencephalograph, electrocorticogram, or functional magnetic resonance imaging to resolve the structure pattern and functional activity during subtraction operation. However, a high resolution of the spatial-temporal understanding of the neural mechanisms involved in mental subtraction is unavailable. Thus, this study obtained intracranial stereoelectroencephalography recordings from 20 patients with pharmacologically resistant epilepsy. Specifically, two sample-delayed mismatch paradigms of numeric comparison and subtracting results comparison were used to help reveal the time frame of mental subtraction. The brain sub-regions were chronologically screened using the stereoelectroencephalography recording for mental subtraction. The results indicated that the anterior cortex, containing the frontal, insular, and parahippocampous, worked for preparing for mental subtraction; moreover, the posterior cortex, such as parietal, occipital, limbic, and temporal regions, cooperated during subtraction. Especially, the gamma band activities in core regions within the parietal-cingulate-temporal cortices mediated the critical mental subtraction. Overall, this research is the first to describe the spatiotemporal activities underlying mental subtraction in the human brain. It provides a comprehensive insight into the cognitive control activity underlying mental arithmetic.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-023-09937-z.

Detecting cognitive traits and occupational proficiency using EEG and statistical inference

Machine learning (ML) is widely used in classification tasks aimed at detecting various cognitive states or neurological diseases using noninvasive electroencephalogram (EEG) time series. However, successfully detecting specific cognitive skills in a healthy population, independent of subject, remains challenging. This study compared the subject-independent classification performance of three different pipelines: supervised and Riemann projections with logistic regression and handcrafted power spectral features with light gradient boosting machine (LightGBM). 128-channel EEGs were recorded from 26 healthy volunteers while they solved arithmetic, logical, and verbal tasks. The participants were divided into two groups based on their higher education and occupation: specialists in mathematics and humanities. The balanced accuracy of the education type was significantly above chance for all pipelines: 0.84-0.89, 0.85-0.88, and 0.86-0.88 for each type of task, respectively. All three pipelines allowed us to distinguish mathematical proficiency based on learning experience with different trade-offs between performance and explainability. Our results suggest that ML approaches could also be effective for recognizing individual cognitive traits using EEG.

Electroencephalographic oscillations of alpha and beta rhythms during phrase-guessing procedure

Phrases-guessing is one of the essential reasoning abilities in problem solving for human beings. However, it is still an open question about why individuals perform differently during the same reasoning task. In this study, we utilized a bilingual phrase-guessing task to explore the neural activities under the individually different performances with electroencephalography. Participants who had no knowledge of Greek were required to guess the meaning of a Greek phrase (long or short in length) by making an either-or selection as to which translation-equivalent Chinese word corresponds to Greek word. Names of color were used as experimental stimuli for which two Chinese words denoted the same color with one as a conventional color name and the other as a novel color name. The experiment yielded length of phrases (long vs. short) and novelty of phrases (novel vs. conventional) as variables. The behavioral results revealed significant length-by-novelty interaction on the number of selections. However, neither main effects nor interactive effects were found on response time. Further, the amplitude spectrums of high alpha rhythm, low alpha rhythm, and low beta rhythm during the task were positively associated with the participants' number of selections for a long Greek phrase with a novel and complex Chinese phrase (LNc) and a short Greek phrase with a conventional Chinese phrase (SCo), while negatively correlated with the response time of selections for LNc and SCo. Our findings suggested that the consistency between participants' behavior and electrophysiological oscillations (alpha and beta bands) could be employed as biomarkers for decoding the phrase-guessing procedure.

Parkinson's disease: Cause factors, measurable indicators, and early diagnosis

Parkinson's disease (PD) is a neurodegenerative disease of the central nervous system caused due to the loss of dopaminergic neurons. It is classified under movement disorder as patients with PD present with tremor, rigidity, postural changes, and a decrease in spontaneous movements. Comorbidities including anxiety, depression, fatigue, and sleep disorders are observed prior to the diagnosis of PD. Gene mutations, exposure to toxic substances, and aging are considered as the causative factors of PD even though its genesis is unknown. This paper reviews PD etiologies, progression, and in particular measurable indicators of PD such as neuroimaging and electrophysiology modalities. In addition to gene therapy, neuroprotective, pharmacological, and neural transplantation treatments, researchers are actively aiming at identifying biological markers of PD with the goal of early diagnosis. Neuroimaging modalities used together with advanced machine learning techniques offer a promising path for the early detection and intervention in PD patients.

Temporal and spectral EEG dynamics can be indicators of stealth placement

Stealth placement marketing, where consumers are unaware that they are being marketed to, attempts to reduce the audiences' resistance to traditional persuasive advertising. It is a form of advertising that involves targeted exposure of brands or products incorporated in other works, usually with or without explicit reference to the brands or products. Brand placement can be presented in different visual and auditory forms in video programs. The present study proposed that different 'representations' (i.e., representable or non-representable) and 'sounds' (i.e., speech or musical sound) of brand placement can affect the viewers' perception of the brand. Event-related potential results indicated significant differences in P1, N1, P2, N270, and P3. Further, event-related spectral perturbation results indicated significant differences in theta, alpha, beta, and gamma (30-100 Hz), in the right parietal, right occipital area, and limbic lobe. 'Non-representable' or 'speech sound' brand placement induced significant temporal and spectral EEG dynamics in viewers.

The analysis of EEG coherence reflects middle childhood differences in mathematical achievement

Symbolic numerical magnitude processing is crucial to arithmetic development, and it is thought to be supported by the functional activation of several brain-interconnected structures. In this context, EEG beta oscillations have been recently associated with attention and working memory processing that underlie math achievement. Due to that EEG coherence represents a useful measure of brain functional connectivity, we aimed to contrast the EEG coherence in forty 8-to-9-year-old children with different math skill levels (High: HA, and Low achievement: LA) according to their arithmetic scores in the Fourth Edition of the Wide Range Achievement Test (WRAT-4) while performing a symbolic magnitude comparison task (i.e. determining which of two numbers is numerically larger). The analysis showed significantly greater coherence over the right hemisphere in the two groups, but with a distinctive connectivity pattern. Whereas functional connectivity in the HA group was predominant in parietal areas, especially involving beta frequencies, the LA group showed more extensive frontoparietal relationships, with higher participation of delta, theta and alpha band frequencies, along with a distinct time-frequency domain expression. The results seem to reflect that lower math achievements in children mainly associate with cognitive processing steps beyond stimulus encoding, along with the need of further attentional resources and cognitive control than their peers, suggesting a lower degree of numerical processing automation.

Humor drawings evoked temporal and spectral EEG processes

The study aimed to explore the humor processing elicited through the manipulation of artistic drawings. Using the Comprehension-Elaboration Theory of humor as the main research background, the experiment manipulated the head portraits of celebrities based on the independent variables of facial deformation (large/small) and addition of affective features (positive/negative). A 64-channel electroencephalography was recorded in 30 participants while viewing the incongruous drawings of celebrities. The electroencephalography temporal and spectral responses were measured during the three stages of humor which included incongruity detection, incongruity comprehension and elaboration of humor. Analysis of event-related potentials indicated that for humorous vs non-humorous drawings, facial deformation and the addition of affective features significantly affected the degree of humor elicited, specifically: large > small deformation; negative > positive affective features. The N170, N270, N400, N600-800 and N900-1200 components showed significant differences, particularly in the right prefrontal and frontal regions. Analysis of event-related spectral perturbation showed significant differences in the theta band evoked in the anterior cingulate cortex, parietal region and posterior cingulate cortex; and in the alpha and beta bands in the motor areas. These regions are involved in emotional processing, memory retrieval, and laughter and feelings of amusement induced by elaboration of the situation.

Right Fronto-Temporal EEG can Differentiate the Affective Responses to Award-Winning Advertisements

Affective engineering aims to improve service/product design by translating the customer's psychological feelings. Award-winning advertisements (AAs) were selected on the basis of the professional standards that consider creativity as a prerequisite. However, it is unknown if AA is related to satisfactory advertising performance among customers or only to the experts' viewpoints towards the advertisements. This issue in the field of affective engineering and design merits in-depth evaluation. We recruited 30 subjects and performed an electroencephalography (EEG) experiment while watching AAs and non-AAs (NAAs). The event-related potential (ERP) data showed that AAs evoked larger positive potentials 250-1400 [Formula: see text]ms after stimulus onset, particularly in the right fronto-temporal regions. The behavioral results were consistent with the professional recognition given to AAs by experts. The perceived levels of creativity and "product-like" quality were higher for the AAs than for the NAAs. Event-related spectral perturbation (ERSP) analysis further revealed statistically significant differences in the theta, alpha, beta, and gamma band activity in the right fronto-temporal regions between the AAs and NAAs. Our results confirm that EEG features from the time/frequency domains can differentiate affective responses to AAs at a neural circuit level, and provide scientific evidence to support the identification of AAs.

EEG Alpha and Gamma Modulators Mediate Motion Sickness-Related Spectral Responses

Motion sickness (MS) is a common experience of travelers. To provide insights into brain dynamics associated with MS, this study recruited 19 subjects to participate in an electroencephalogram (EEG) experiment in a virtual-reality driving environment. When riding on consecutive winding roads, subjects experienced postural instability and sensory conflict between visual and vestibular stimuli. Meanwhile, subjects rated their level of MS on a six-point scale. Independent component analysis (ICA) was used to separate the filtered EEG signals into maximally temporally independent components (ICs). Then, reduced logarithmic spectra of ICs of interest, using principal component analysis, were decomposed by ICA again to find spectrally fixed and temporally independent modulators (IMs). Results demonstrated that a higher degree of MS accompanied increased activation of alpha ([Formula: see text]) and gamma ([Formula: see text]) IMs across remote-independent brain processes, covering motor, parietal and occipital areas. This co-modulatory spectral change in alpha and gamma bands revealed the neurophysiological demand to regulate conflicts among multi-modal sensory systems during MS.