Dissociating prefrontal and parietal cortex activation during arithmetic processing

Study on different brain activation rearrangement during cognitive workload from ERD/ERS and coherence analysis

The functional activities of the brain during any task like imaginary, motor, or cognitive are different in pattern as well as their area of activation in the brain is also different. This variation in pattern is also found in the brain's electrical variations that can be measured from the scalp of the brain using an electroencephalogram (EEG). This work exclusively studied a group of subjects' EEG data (available at: https://archive.physionet.org/physiobank/database/eegmat/) to unravel the activation pattern of the human brain during a mental arithmetic task. Since any cognitive task creates variations in EEG signal pattern, the relative changes in the signal power also occur which is also known as event-related desynchronization/synchronization (ERD/ERS). In this work, ERD/ERS have calculated the band-wise power spectral density (PSD) using Welch's method from the EEG signals. Besides, the coherence analysis was also performed to verify the results of ERD/ERS analysis from several randomly chosen subjects' EEG data. Here, subjects performing mental arithmetic tasks were grouped based on their performances: good (subtraction solved > 10 on average) and bad (subtraction solved ≤ 10 on average) to conduct group-specific ERD/ERS analysis regarding their performance in cognitive tasks. It was found that when the brain is on count condition, the variations found in the band power of theta and beta. The amounts of ERS in the left hemisphere are increased. When the task complexity increases, it contributes to an increase in relative ERD/ERS amounts and durations. The left and right hemispheres were asymmetrically distributed by both the pre-stimulus stages of the corresponding band power and relative ERD/ERS.

Arithmetic in two languages: Localizing simple multiplication processing in the adult bilingual brain

Verbally memorized multiplication tables are thought to create language-specific memories. Supporting this idea, bilinguals are typically faster and more accurate in the language in which they learned math (LA+) than in their other language (LA- ) . No study has yet revealed the underlying neurocognitive mechanisms explaining this effect, or the role of problem size in explaining the recruitment of different brain regions in LA+ and LA- . To fill this gap in the literature, 29 Spanish-English early bilingual adults, proficient in both languages, verified simple multiplication problems in each language while functional magnetic resonance imaging (fMRI) was acquired. More specifically, this study aimed to answer two questions: 1) Does LA+ recruit left superior and middle temporal gyri (STG/MTG) to a greater extent than LA- , reflecting more robust verbal representations of multiplication facts in LA+? In contrast, does LA- recruit the inferior frontal gyrus (IFG), reflecting more effortful retrieval, or the intraparietal sulcus (IPS), reflecting reliance on quantity processes? 2) Is there an interaction between language and problem size, where language differences are more pronounced for less practiced, large multiplication problems (e.g., 8 × 9) in comparison to more familiar, small problems (e.g., 2 × 3). Functional localizer tasks were used to identify hypothesis-driven regions of interest in verbal areas associated with verbal representations of arithmetic facts (left STG/MTG) and with the effortful retrieval of these facts (left IFG) and quantity areas engaged when calculation-based strategies are used (bilateral IPS). In planned analyses, no cluster reached significance for the direct comparison of languages (question 1) or for the interaction between language and problem size (question 2). An exploratory analysis found a main effect of problem size, where small problems recruited left STG/MTG and left IFG to a greater extent than large problems, suggesting greater verbal involvement for these problems in both languages. Additionally, large problems recruited right IPS to a greater extent than small problems, suggesting reliance on quantity processes. Our results suggest that proficient early bilingual adults engage similar brain regions in both languages, even for more difficult, large problems.

Dynamic modulation of the processing of unpredicted technical errors by the posterior cingulate and the default mode network

The pervasive use of information technologies (IT) has tremendously benefited our daily lives. However, unpredicted technical breakdowns and errors can lead to the experience of stress, which has been termed technostress. It remains poorly understood how people dynamically respond to unpredicted system runtime errors occurring while interacting with the IT systems on a behavioral and neuronal level. To elucidate the mechanisms underlying such processes, we conducted a functional magnetic resonance imaging (fMRI) study in which 15 young adults solved arithmetic problems of three difficulty levels (easy, medium and hard) while two types of system runtime errors (problem errors and feedback errors) occurred in an unexpected manner. The problem error condition consisted of apparently defective displays of the arithmetic problem and the feedback error condition involved erroneous feedback. We found that the problem errors positively influenced participants' problem-solving performance at the high difficulty level (i.e., hard tasks) at the initial stage of the session, while feedback errors disturbed their performance. These dynamic behavioral changes are mainly associated with brain activation changes in the posterior cingulate and the default mode network, including the posterior cingulate cortex, the mPFC, the retrosplenial cortex and the parahippocampal gyrus. Our study illustrates the regulatory role of the posterior cingulate in coping with unpredicted errors as well as with dynamic changes in the environment.

Probing Our Built-in Calculator: A Systematic Narrative Review of Noninvasive Brain Stimulation Studies on Arithmetic Operation-Related Brain Areas

This systematic review presented a comprehensive survey of studies that applied transcranial magnetic stimulation and transcranial electrical stimulation to parietal and nonparietal areas to examine the neural basis of symbolic arithmetic processing. All findings were compiled with regard to the three assumptions of the triple-code model (TCM) of number processing. Thirty-seven eligible manuscripts were identified for review (33 with healthy participants and 4 with patients). Their results are broadly consistent with the first assumption of the TCM that intraparietal sulcus both hold a magnitude code and engage in operations requiring numerical manipulations such as subtraction. However, largely heterogeneous results conflicted with the second assumption of the TCM that the left angular gyrus subserves arithmetic fact retrieval, such as the retrieval of rote-learned multiplication results. Support is also limited for the third assumption of the TCM, namely, that the posterior superior parietal lobule engages in spatial operations on the mental number line. Furthermore, results from the stimulation of brain areas outside of those postulated by the TCM show that the bilateral supramarginal gyrus is involved in online calculation and retrieval, the left temporal cortex in retrieval, and the bilateral dorsolateral prefrontal cortex and cerebellum in online calculation of cognitively demanding arithmetic problems. The overall results indicate that multiple cortical areas subserve arithmetic skills.

An analysis of physiological responses as indicators of driver takeover readiness in conditionally automated driving

By the year 2045, it is projected that Autonomous Vehicles (AVs) will make up half of the new vehicle market. Successful adoption of AVs can reduce drivers' stress and fatigue, curb traffic congestion, and improve safety, mobility, and economic efficiency. Due to the limited intelligence in relevant technologies, human-in-the-loop modalities are still necessary to ensure the safety of AVs at current or near future stages, because the vehicles may not be able to handle all emergencies. Therefore, it is important to know the takeover readiness of the drivers to ensure the takeover quality and avoid any potential accidents. To achieve this, a comprehensive understanding of the drivers' physiological states is crucial. However, there is a lack of systematic analysis of the correlation between different human physiological responses and takeover behaviors which could serve as important references for future studies to determine the types of data to use. This paper provides a comprehensive analysis of the effects of takeover behaviors on the common physiological indicators. A program for conditional automation was developed based on a game engine and applied to a driving simulator. The experiment incorporated three types of secondary tasks, three takeover events, and two traffic densities. Brain signals, Skin Conductance Level (SCL), and Heart Rate (HR) of the participants were collected while they were performing the driving simulations. The Frontal Asymmetry Index (FAI) (as an indicator of engagement) and Mental Workload (MWL) were calculated from the brain signals to indicate the mental states of the participants. The results revealed that the FAI of the drivers would slightly decrease after the takeover alerts were issued when they were doing secondary tasks prior to the takeover activities, and the higher difficulty of the secondary tasks could lead to lower overall FAI during the takeover periods. In contrast, The MWL and SCL increased during the takeover periods. The HR also increased rapidly at the beginning of the takeover period but dropped back to a normal level quickly. It was found that a fake takeover alert would lead to lower overall HR, slower increase, and lower peak of SCL during the takeover periods. Moreover, the higher traffic density scenarios were associated with higher MWL, and a more difficult secondary task would lead to higher MWL and HR during the takeover activities. A preliminary discussion of the correlation between the physiological data, takeover scenario, and vehicle data (that relevant to takeover readiness) was then conducted, revealing that although takeover event, SCL, and HR had slightly higher correlations with the maximum acceleration and reaction time, none of them dominated the takeover readiness. In addition, the analysis of the data across different participants was conducted, which emphasized the importance of considering standardization or normalization of the data when they were further used as input features for estimating takeover readiness. Overall, the results presented in this paper offer profound insights into the patterns of physiological data changes during takeover periods. These findings can be used as benchmarks for utilizing these variables as indicators of takeover preparedness and performance in future research endeavors.

Arithmetic problem size modulates brain activations in females but not in males

Numerous empirical studies have reported that males and females perform equally well in mathematical achievement. However, still to date, very limited is understood about the brain response profiles that are particularly characteristic of males and females when solving mathematical problems. The present study aimed to tackle this issue by manipulating arithmetic problem size to investigate functional significance using functional magnetic resonance imaging (fMRI) in young adults. Participants were instructed to complete two runs of simple calculation tasks with either large or small problem sizes. Behavioural results suggested that the performance did not differ between females and males. Neuroimaging data revealed that sex/gender-related patterns of problem size effect were found in the brain regions that are conventionally associated with arithmetic, including the left middle frontal gyrus (MFG), left intraparietal sulcus (IPS) and insula. Specifically, females demonstrated substantial brain responses of problem size effect in these regions, whereas males showed marginal effects. Moreover, the machine learning method implemented over the brain signal levels within these regions demonstrated that sex/gender is discriminable. These results showed sex/gender effects in the activating patterns varying as a function of the distinct math problem size, even in a simple calculation task. Accordingly, our findings suggested that females and males use two complementary brain resources to achieve equally successful performance levels and highlight the pivotal role of neuroimaging facilities in uncovering neural mechanisms that may not be behaviourally salient.

Effects of a 14-week community health program of exercise and learning/education in older adults: A single-arm pre-post comparison study

This study was initiated in 2022 in Miyaki Town, Saga Prefecture, Japan, to determine the impact of an intervention that combined brain and physical function training and health education in older residents. Miyaki has a population of approximately 26,000, 35% of whom are considered to be aging. A 14-week program consisting of strength training, brain function training, and health lectures was conducted with 34 older residents of the community. Body composition, motor function, brain function, and various blood tests were evaluated before and after the intervention. Brain function was assessed using the Trail Making Test-A. Physical function was assessed by Open-Close Stepping, Functional Reach Test, Open-Leg Standing Time, and Two-Step Test. The intervention group showed significant improvements in brain function (p< 0.0001), physical function (p = 0.0037), body composition (p = 0.0053), and LDL-C (p = 0.017). This study provides substantial evidence that community-based combined programs can be beneficial for older adults.

Fear of missing out (FOMO) associates with reduced cortical thickness in core regions of the posterior default mode network and higher levels of problematic smartphone and social media use

BACKGROUND AND AIMS

Fear of missing out (FOMO) promotes the desire or urge to stay continuously connected with a social reference group and updated on their activities, which may result in escalating and potentially addictive smartphone and social media use. The present study aimed to determine whether the neurobiological basis of FOMO encompasses core regions of the reward circuitry or social brain, and associations with levels of problematic smartphone or social media use.

METHODS

We capitalized on a dimensional neuroimaging approach to examine cortical thickness and subcortical volume associations in a sample of healthy young individuals (n = 167). Meta-analytic network and behavioral decoding analyses were employed to further characterize the identified regions.

RESULTS

Higher levels of FOMO associated with lower cortical thickness in the right precuneus. In contrast, no associations between FOMO and variations in striatal morphology were observed. Meta-analytic decoding revealed that the identified precuneus region exhibited a strong functional interaction with the default mode network (DMN) engaged in social cognitive and self-referential domains.

DISCUSSION AND CONCLUSIONS

Together the present findings suggest that individual variations in FOMO are associated with the brain structural architecture of the right precuneus, a core hub within a large-scale functional network resembling the DMN and involved in social and self-referential processes. FOMO may promote escalating social media and smartphone use via social and self-referential processes rather than reward-related processes per se.

The first year in formal schooling improves working memory and academic abilities

Neurocognition and academic abilities during the period of 4 and 7 years of age are impacted by both the transition from kindergarten to primary school and age-related developmental processes. Here, we used a school cut-off design to tease apart the impact of formal schooling from age, on working memory (WM) function, vocabulary, and numeracy scores. We compared two groups of children with similar age, across two years: first-graders (FG), who were enrolled into primary school the year that they became eligible and kindergarteners (KG), who were deferred school entry until the following year. All children completed a change detection task while brain activation was recorded using portable functional near-infrared spectroscopy, a vocabulary assessment, and a numeracy screener. Our results revealed that FG children showed greater improvement in WM performance and greater engagement of a left-lateralized fronto-parietal network compared to KG children. Further, they also showed higher gains in vocabulary and non-symbolic numeracy scores. This improvement in vocabulary and non-symbolic numeracy scores following a year in primary school was predicted by WM function. Our findings contribute to a growing body of literature examining neurocognitive and academic benefits conferred to children following exposure to formal schooling.

Systems-level decoding reveals the cognitive and behavioral profile of the human intraparietal sulcus

INTRODUCTION

The human intraparietal sulcus (IPS) covers large portions of the posterior cortical surface and has been implicated in a variety of cognitive functions. It is, however, unclear how cognitive functions dissociate between the IPS's heterogeneous subdivisions, particularly in perspective to their connectivity profile.

METHODS

We applied a neuroinformatics driven system-level decoding on three cytoarchitectural distinct subdivisions (hIP1, hIP2, hIP3) per hemisphere, with the aim to disentangle the cognitive profile of the IPS in conjunction with functionally connected cortical regions.

RESULTS

The system-level decoding revealed nine functional systems based on meta-analytical associations of IPS subdivisions and their cortical coactivations: Two systems-working memory and numeric cognition-which are centered on all IPS subdivisions, and seven systems-attention, language, grasping, recognition memory, rotation, detection of motions/shapes and navigation-with varying degrees of dissociation across subdivisions and hemispheres. By probing the spatial overlap between systems-level co-activations of the IPS and seven canonical intrinsic resting state networks, we observed a trend toward more co-activation between hIP1 and the front parietal network, between hIP2 and hIP3 and the dorsal attention network, and between hIP3 and the visual and somatomotor network.

DISCUSSION

Our results confirm previous findings on the IPS's role in cognition but also point to previously unknown differentiation along the IPS, which present viable starting points for future work. We also present the systems-level decoding as promising approach toward functional decoding of the human connectome.

Selectivity of timing: A meta-analysis of temporal processing in neuroimaging studies using activation likelihood estimation and reverse inference

Over the last few decades, many researchers have investigated time perception and how it is processed in the brain. Past studies have identified cortical and subcortical regions that play an important role in implicit and/or explicit timing tasks. In regard to timing, different regions appear to have roles of varying importance depending on the duration (sub-second vs. supra-second), type of task (such as involving motor responses or passively observing stimuli), and modality (such as auditory, visual, and sensorimotor) resulting in the literature reporting divergent results that are contingent on the specifics of the task. This meta-analysis aims at identifying regions that show activation only for explicit timing tasks through reverse inference. As such, two datasets (the first including studies that involved explicit timing tasks while the second did not) were compared using the activation likelihood estimation (ALE) algorithm. Reverse inference was implemented through Bayes factor modeling, which allowed for the comparison of the activated regions between the two ALE-maps. Results showed a constellation of regions that exhibited selective activation likelihood in explicit timing tasks with the largest posterior probability of activation resulting in the left supplementary motor area (SMA) and the bilateral insula. Some areas that have been dubbed critical for time perception in past studies (i.e., the cerebellum) did not exhibit prevalent activation after analyses.

Neural evidence suggests phonological acceptability judgments reflect similarity, not constraint evaluation

Acceptability judgments are a primary source of evidence in formal linguistic research. Within the generative linguistic tradition, these judgments are attributed to evaluation of novel forms based on implicit knowledge of rules or constraints governing well-formedness. In the domain of phonological acceptability judgments, other factors including ease of articulation and similarity to known forms have been hypothesized to influence evaluation. We used data-driven neural techniques to identify the relative contributions of these factors. Granger causality analysis of magnetic resonance imaging (MRI)-constrained magnetoencephalography (MEG) and electroencephalography (EEG) data revealed patterns of interaction between brain regions that support explicit judgments of the phonological acceptability of spoken nonwords. Comparisons of data obtained with nonwords that varied in terms of onset consonant cluster attestation and acceptability revealed different cortical regions and effective connectivity patterns associated with phonological acceptability judgments. Attested forms produced stronger influences of brain regions implicated in lexical representation and sensorimotor simulation on acoustic-phonetic regions, whereas unattested forms produced stronger influence of phonological control mechanisms on acoustic-phonetic processing. Unacceptable forms produced widespread patterns of interaction consistent with attempted search or repair. Together, these results suggest that speakers' phonological acceptability judgments reflect lexical and sensorimotor factors.

Direct intracranial recordings in the human angular gyrus during arithmetic processing

The role of angular gyrus (AG) in arithmetic processing remains a subject of debate. In the present study, we recorded from the AG, supramarginal gyrus (SMG), intraparietal sulcus (IPS), and superior parietal lobule (SPL) across 467 sites in 30 subjects performing addition or multiplication with digits or number words. We measured the power of high-frequency-broadband (HFB) signal, a surrogate marker for regional cortical engagement, and used single-subject anatomical boundaries to define the location of each recording site. Our recordings revealed the lowest proportion of sites with activation or deactivation within the AG compared to other subregions of the inferior parietal cortex during arithmetic processing. The few activated AG sites were mostly located at the border zones between AG and IPS, or AG and SMG. Additionally, we found that AG sites were more deactivated in trials with fast compared to slow response times. The increase or decrease of HFB within specific AG sites was the same when arithmetic trials were presented with number words versus digits and during multiplication as well as addition trials. Based on our findings, we conclude that the prior neuroimaging findings of so-called activations in the AG during arithmetic processing could have been due to group-based analyses that might have blurred the individual anatomical boundaries of AG or the subtractive nature of the neuroimaging methods in which lesser deactivations compared to the control condition have been interpreted as "activations". Our findings offer a new perspective with electrophysiological data about the engagement of AG during arithmetic processing.

The role of the angular gyrus in arithmetic processing: a literature review

Since the pioneering work of the early 20th century neuropsychologists, the angular gyrus (AG), particularly in the left hemisphere, has been associated with numerical and mathematical processing. The association between the AG and numerical and mathematical processing has been substantiated by neuroimaging research. In the present review article, we will examine what is currently known about the role of the AG in numerical and mathematical processing with a particular focus on arithmetic. Specifically, we will examine the role of the AG in the retrieval of arithmetic facts in both typically developing children and adults. The review article will consider alternative accounts that posit that the involvement of the AG is not specific to arithmetic processing and will consider how numerical and mathematical processing and their association with the AG overlap with other neurocognitive processes. The review closes with a discussion of future directions to further characterize the relationship between the angular gyrus and arithmetic processing.

The neural correlates of retrieval and procedural strategies in mental arithmetic: A functional neuroimaging meta-analysis

Mental arithmetic is a complex skill of great importance for later academic and life success. Many neuroimaging studies and several meta-analyses have aimed to identify the neural correlates of mental arithmetic. Previous meta-analyses of arithmetic grouped all problem types into a single meta-analytic map, despite evidence suggesting that different types of arithmetic problems are solved using different strategies. We used activation likelihood estimation (ALE) to conduct quantitative meta-analyses of mental arithmetic neuroimaging (n = 31) studies, and subsequently grouped contrasts from the 31 studies into problems that are typically solved using retrieval strategies (retrieval problems) (n = 18) and problems that are typically solved using procedural strategies (procedural problems) (n = 19). Foci were compiled to generate probabilistic maps of activation for mental arithmetic (i.e., all problem types), retrieval problems, and procedural problems. Conjunction and contrast analyses were conducted to examine overlapping and distinct activation for retrieval and procedural problems. The conjunction analysis revealed overlapping activation for retrieval and procedural problems in the bilateral inferior parietal lobules, regions typically associated with magnitude processing. Contrast analyses revealed specific activation in the left angular gyrus for retrieval problems and specific activation in the inferior frontal gyrus and cingulate gyrus for procedural problems. These findings indicate that the neural bases of arithmetic systematically differs according to problem type, providing new insights into the dynamic and task-dependent neural underpinnings of the calculating brain.

Neurofeedback for the Education of Children with ADHD and Specific Learning Disorders: A Review

Neurofeedback (NF) is a type of biofeedback in which an individual’s brain activity is measured and presented to them to support self-regulation of ongoing brain oscillations and achieve specific behavioral and neurophysiological outcomes. NF training induces changes in neurophysiological circuits that are associated with behavioral changes. Recent evidence suggests that the NF technique can be used to train electrical brain activity and facilitate learning among children with learning disorders. Toward this aim, this review first presents a generalized model for NF systems, and then studies involving NF training for children with disorders such as dyslexia, attention-deficit/hyperactivity disorder (ADHD), and other specific learning disorders such as dyscalculia and dysgraphia are reviewed. The discussion elaborates on the potential for translational applications of NF in educational and learning settings with details. This review also addresses some issues concerning the role of NF in education, and it concludes with some solutions and future directions. In order to provide the best learning environment for children with ADHD and other learning disorders, it is critical to better understand the role of NF in educational settings. The review provides the potential challenges of the current systems to aid in highlighting the issues undermining the efficacy of current systems and identifying solutions to address them. The review focuses on the use of NF technology in education for the development of adaptive teaching methods and the best learning environment for children with learning disabilities.

Sensitive Channel Selection for Mental Workload Classification

Mental workload (MW) assessment has been widely studied in various human–machine interaction tasks. The existing researches on MW classification mostly use non-invasive electroencephalography (EEG) caps to collect EEG signals and identify MW levels. However, the activation region of the brain stimulated by MW tasks is not the same for every subject. It may be inappropriate to use EEG signals from all electrode channels to identify MW. In this paper, an EEG rhythm energy heatmap is first established to visually show the change trends in the energy of four EEG rhythms with time, EEG channels and MW levels. It can be concluded from the presented heatmaps that this change trend varies with subjects, rhythms and channels. Based on the analysis, a double threshold method is proposed to select sensitive channels for MW assessment. The EEG signals of personalized selected channels, named positive sensitive channels (PSCs) and negative sensitive channels (NSCs), are used for MW classification using the Support Vector Machine (SVM) algorithm. The results show that the selection of personalized sensitive channels generally contributes to improving the performance of MW classification.

The longitudinal development of large-scale functional brain networks for arithmetic ability from childhood to adolescence

Arithmetic ability is an important high-level cognitive function that requires interaction among multiple brain regions. Previous studies on arithmetic development have focused on task-induced activation in isolated brain regions or functional connectivity among particular seed regions. However, it remains largely unknown whether and how functional connectivity among large-scale brain modules contributes to arithmetic development. In the present study, we used a longitudinal sample of task-based functional magnetic resonance imaging (fMRI) data comprising 63 typically developing children, with two testing points being about two years apart. With graph theory, we examined the longitudinal development of large-scale brain modules for a multiplication task in younger (mean age 9.88 at time 1) and older children (mean age 12.34 at time 1), respectively. The results showed that the default-mode (DMN) and frontal-parietal networks (FPN) became increasingly segregated over time. Specifically, intra-connectivity within the DMN and FPN increased significantly with age, and inter-connectivity between the DMN and visual network decreased significantly with age. Such developmental changes were mainly observed in the younger children, but not in the older children. Moreover, the change in network segregation of the DMN was positively correlated with longitudinal gain in arithmetic performance in the younger children, and individual difference in network segregation of the FPN was positively correlated with arithmetic performance at time 2 in the older children. Taken together, the present results highlight the development of the functional architecture in large-scale brain networks from childhood to adolescence, which may provide insights into potential neural mechanisms underlying arithmetic development.

Transformer Model for Functional Near-Infrared Spectroscopy Classification

Functional near-infrared spectroscopy (fNIRS) is a promising neuroimaging technology. The fNIRS classification problem has always been the focus of the brain-computer interface (BCI). Inspired by the success of Transformer based on self-attention mechanism in the fields of natural language processing and computer vision, we propose an fNIRS classification network based on Transformer, named fNIRS-T. We explore the spatial-level and channel-level representation of fNIRS signals to improve data utilization and network representation capacity. Besides, a preprocessing module, which consists of one-dimensional average pooling and layer normalization, is designed to replace filtering and baseline correction of data preprocessing. It makes fNIRS-T an end-to-end network, called fNIRS-PreT. Compared with traditional machine learning classifiers, convolutional neural network (CNN), and long short-term memory (LSTM), the proposed models obtain the best accuracy on three open-access datasets. Specifically, in the most extensive ternary classification task (30 subjects) that includes three types of overt movements, fNIRS-T, CNN, and LSTM obtain 75.49%, 72.89%, and 61.94% on test sets, respectively. Compared to traditional classifiers, fNIRS-T is at least 27.41% higher than statistical features and 6.79% higher than well-designed features. In the individual subject experiment of the ternary classification task, fNIRS-T achieves an average subject accuracy of 78.22% and surpasses CNN and LSTM by a large margin of +4.75% and +11.33%. fNIRS-PreT using raw data also achieves competitive performance to fNIRS-T. Therefore, the proposed models improve the performance of fNIRS-based BCI significantly.

Research on Night Light Comfort of Pedestrian Space in Urban Park

The outdoor light environment significantly affects aspects of public psychological and physiological health. This study conducted experiments to quantify the effects of the light environment on visitor light comfort in urban park pedestrian space. Nine sets of lighting conditions with different average horizontal illuminance (2 lx, 6 lx, 10 lx) and colour temperatures (5600 K, 4300 K, 3000 K) were established virtual reality scenarios. Subjective light comfort was evaluated, and electroencephalogram (EEG) was measured on 18 subjects to comprehensively study the effects of different light environments on human light comfort. The results of the comprehensive evaluation showed that colour temperature had a very significant impact on subjective light comfort, with warm light being generally more favourable than cool light in enhancing human subjective light comfort. The results of the EEG analysis show that the average horizontal illuminance is an important factor in the level of physiological fatigue, and that physiological fatigue can be maintained in a superior state at an appropriate level of illuminance. Based on the results of both subjective and objective factors, a comprehensive analysis was carried out to propose a range of average horizontal illuminance (4.08 lx, 6.99 lx) and a range of colour temperature (3126 K, 4498 K) for the comprehensive light comfort zone in urban park pedestrian space.

Groupitizing modifies neural coding of numerosity

Numerical estimation of arrays of objects is faster and more accurate when items can be clustered into groups, a phenomenon termed “groupitizing.” Grouping can facilitate segregation into subitizable “chunks,” each easily estimated, then summed. The current study investigates whether spatial grouping of arrays drives specific neural responses during numerical estimation, reflecting strategies such as exact calculation and fact retrieval. Fourteen adults were scanned with fMRI while estimating either the numerosity or shape of arrays of items, either randomly distributed or spatially grouped. Numerosity estimation of both classes of stimuli elicited common activation of a right lateralized frontoparietal network. Grouped stimuli additionally recruited regions in the left hemisphere and bilaterally in the angular gyrus. Multivariate pattern analysis showed that classifiers trained with the pattern of neural activations read out from parietal regions, but not from the primary visual areas, can decode different numerosities both within and across spatial arrangements. The behavioral numerical acuity correlated with the decoding performance of the parietal but not with occipital regions. Overall, this experiment suggests that the estimation of grouped stimuli relies on the approximate number system for numerosity estimation, but additionally recruits regions involved in calculation.

Evaluation of the transient hypofrontality theory in the context of exercise: A systematic review with meta-analysis

Accumulating research suggests that, as a result of reduced neural activity in the prefrontal cortex (PFC), higher-order cognitive function may be compromised while engaging in high-intensity acute exercise, with this phenomenon referred to as the transient hypofrontality effect. However, findings in this field remain unclear and lack a thorough synthesis of the evidence. Therefore, the purpose of this meta-analysis was to evaluate the effects of in-task acute exercise on cognitive function, and further, to examine whether this effect is moderated by the specific type of cognition (i.e., PFC-dependent vs. non-PFC-dependent). Studies were identified by electronic databases in accordance with the PRISMA guidelines. In total, 22 studies met our inclusion criteria and intercept only meta-regression models with robust variance estimation were used to calculate the weighted average effect sizes across studies. Acute exercise at all intensities did not influence cognitive function (β = -0.16, 95% CI = [-0.58, 0.27], p = .45) when exercise occurred during the cognitive task, and no significant moderation effects emerged. However, there was evidence that cognitive task type (PFC-dependent vs. non-PFC-dependent) moderated the effect of high-intensity acute exercise on a concomitant cognitive performance (β = -0.81, 95% CI = [-1.60, -0.02], p = .04). Specifically, our findings suggest that PFC-dependent cognition is impaired while engaging in an acute bout of high-intensity exercise, providing support for the transient hypofrontality theory. We discuss these findings in the context of reticular-activating and cognitive-energetic perspectives.

Brain function associated with reaction time after sport-related concussion

Concussion is associated with significant functional disturbances in the first week post-injury. Computerized neurocognitive testing tools have become widely adopted in concussion management, to identify specific domains of impairment and obtain more objective measures of recovery. Reaction time (RT) slowing is a common sequela of concussion, however, the functional brain networks that underlie RT performance remain under-studied in both healthy and concussed athletic cohorts. This study used blood-oxygenation-level-dependent function magnetic resonance imaging (BOLD fMRI) to evaluate resting brain function of 45 university-level athletes with concussion in the first week post-injury, along with a control cohort of 102 athletes without recent concussion. We evaluated the main effects of concussion and RT on functional connectivity, along with concussion × RT interactions, using multivariate analysis techniques. Concussion was associated with reduced connectivity throughout the brain, whereas RT slowing was associated with elevated connectivity in parietal and temporal regions, for both control and concussed groups. For the concussed group, RT slowing was also associated with disrupted connectivity between fronto-insular and default mode networks. For concussed athletes, the brain networks associated with slower post-injury RT also showed similar but non-significant associations with longitudinal changes in RT performance relative to pre-injury baseline. These study findings provide new insights into the effects of concussion on neurocognitive function and suggest the presence of functional brain networks that are specific to concussion-related RT slowing.

Neural basis of approximate number in congenital blindness

Although humans are unique among animals in their ability to manipulate symbolic numbers, we share with other species an approximate number sense that allows us to estimate and compare the number of objects or events in a set, such as the number of apples in a tree. Our ability to discriminate the numerosity of two sets decreases as the ratio between them becomes smaller (e.g., 8 vs 16 items is harder to discriminate than 8 vs 32 items). The intraparietal sulcus (IPS) plays a key role in this numerical approximation. Neuronal populations within the IPS code for numerosity, with stimuli of different numerosities eliciting discriminable spatial patterns of activity. The developmental origins of these IPS number representations are not known. Here, we tested the hypothesis that representations of number in the IPS require visual experience with object sets, by working with individuals blind from birth. While undergoing fMRI, congenitally blind (n = 17) and blindfolded sighted (n = 25) participants judged which of two sequences of beeps was more numerous. In both sighted and blind individuals, patterns of activity in the IPS discriminated among different numerosities (4, 8, 16 vs 32), with better discrimination in the IPS of the blind group. In both groups, decoding performance decreased as the ratio between numerosities decreased (e.g., 8 vs 16 was less discriminable than 8 vs 32). These findings suggest that number representations in the IPS either have innate precursors, or that auditory or tactile experience with sets is sufficient for typical development.

The impact of a lack of mathematical education on brain development and future attainment

Formal education has a long-term impact on an individual's life. However, our knowledge of the effect of a specific lack of education, such as in mathematics, is currently poor but is highly relevant given the extant differences between countries in their educational curricula and the differences in opportunities to access education. Here we examined whether neurotransmitter concentrations in the adolescent brain could classify whether a student is lacking mathematical education. Decreased γ-aminobutyric acid (GABA) concentration within the middle frontal gyrus (MFG) successfully classified whether an adolescent studies math and was negatively associated with frontoparietal connectivity. In a second experiment, we uncovered that our findings were not due to preexisting differences before a mathematical education ceased. Furthermore, we showed that MFG GABA not only classifies whether an adolescent is studying math or not, but it also predicts the changes in mathematical reasoning ∼19 mo later. The present results extend previous work in animals that has emphasized the role of GABA neurotransmission in synaptic and network plasticity and highlight the effect of a specific lack of education on MFG GABA concentration and learning-dependent plasticity. Our findings reveal the reciprocal effect between brain development and education and demonstrate the negative consequences of a specific lack of education during adolescence on brain plasticity and cognitive functions.

Effects of Prenatal Alcohol Exposure on the Volumes of the Lateral and Medial Walls of the Intraparietal Sulcus

Fetal alcohol spectrum disorders (FASD) continue to be the leading preventable cause of intellectual disability in the U.S., Europe, and in endemic areas, such as the Western Cape region of South Africa. Arithmetic is highly sensitive to prenatal alcohol exposure (PAE). The intraparietal sulcus (IPS) is known to play a critical role in number processing. In this study, we investigate whether smaller IPS volumes play a role in the number-processing deficits observed in children with PAE. Participants were 52 9- to 14-year-old children from a historically disadvantaged community in Cape Town, who are participating in our ongoing studies on the effects of PAE on the brain. The IPS was manually parcellated into its medial (MIPS) and lateral (LIPS) walls on magnetic resonance images. The study aimed to examine: (1) the effects of PAE on IPS regional volumes and asymmetry, (2) whether IPS regional volumes are related to number processing performance and, if so, whether these relations are moderated by PAE and (3) potential mediation by regional IPS volumes of the relation between PAE and number processing performance. Total intracranial volume (TIV) was associated with volumes in all regions except the right LIPS. Both left MIPS and left LIPS volumes were significantly smaller in children in the fetal alcohol syndrome (FAS)/partial FAS (PFAS) group compared to controls. The finding in the left LIPS remained significant after controlling for potential confounders and after adjustment for the smaller overall brain size of the children in the FAS/PFAS group. Smaller left LIPS volumes in the FAS/PFAS group may account for the absence of left-right asymmetry in the LIPS in children with FAS/PFAS compared to controls and nonsyndromal heavily exposed (HE) children. Bilaterally, larger MIPS volumes were associated with better WISC IQ Arithmetic scores. These effects, however, were not moderated by the degree of PAE, and regional IPS volumes did not mediate the effect of PAE on WISC Arithmetic scores. Although we found that certain regions of the IPS were smaller in children with FAS and PFAS, these PAE-induced changes in IPS volume did not mediate the alcohol-related deficits in arithmetic.

Alpha and theta oscillations in mental addition for high and low performers

While many contemporary studies aim to explore the sources of notable individual differences in arithmetic skills, this study specifically aims to highlight cognitive differences between high and low math performers. Thirty-six undergraduate female students who were identified as either high or low math performers, according to an arithmetic fluency test, were recruited. In the main experiment, EEG recordings were taken, while the participants performed a mental addition task. The mental addition problems were classified as either easy or difficult, and were presented to participants in several forms. The results indicated that problem difficulty increases the gap in accuracy attainment between high and low math performers. Additionally, high performers displayed larger alpha power during mental arithmetic in P7, corresponding to the left parietal lobe. This indicated that combining behavioral and neural data can improve our understanding of the differences between high and low math performers. Interpretations and implications are discussed.

Cognitive Correlates of Math Performance in School-Aged Children with Sickle Cell Disease and Silent Cerebral Infarcts

OBJECTIVE

Attention, processing speed, executive functioning, and math difficulties are common in youth with sickle cell disease (SCD) with silent cerebral infarcts (SCI). This study investigated the cognitive underpinnings of math difficulties in children with SCD and SCI.

METHOD

Youth (n = 68) with SCD and SCI completed measures of attention [Digit Span forward (DSF); Conners Continuous Performance Test-Third Edition/Kiddie Conners Continuous Performance Test-Second Edition (CPT-3/KCPT-2)]; working memory [Wechsler Intelligence Scales (WPPSI-IV, WISC-IV, WISC-V, WAIS-IV), Working Memory Index (WMI), Digit Span backwards (DSB)]; processing speed [WPPSI-IV, WISC-IV, WISC-V, WAIS-IV Processing Speed Index (PSI)]; math reasoning [Wechsler Individual Achievement Test-Third Edition (WIAT-III) Mathematics composite (MC)]; and math fluency [WIAT-III Math Fluency composite (MF)] as part of a clinical neuropsychological evaluation. Parent ratings of attention and executive functioning were obtained [Behavior Assessment System for Children-Third Edition (BASC-3), Behavior Rating Inventory of Executive Function (BRIEF)].

RESULTS

MC was positively correlated with WMI (r = 0.59, p = 0.00), PSI (r = 0.40, p < 0.001), DSF (r = 0.29, p = 0.03), DSB (r = 0.47, p < 0.001), and MF (r = 0.71, p < 0.001). Correlations between MC, sustained attention, and parent ratings were nonsignificant. The linear regression model using correlated variables was significant [F(4,51) = 8.29, R2 = 0.39, p < 0.001]. WMI was the only significant variable within the model (p = 0.02).

CONCLUSIONS

Working memory deficits account for significant variance in untimed mathematical performance in this population-consistent with other populations with white matter dysfunction. Interventions targeting both mathematics and working memory may be beneficial.

The neural basis of counting sequences

Sequence processing is critical for complex behavior, and counting sequences hold a unique place underlying human numerical development. Despite this, the neural bases of counting sequences remain unstudied. We hypothesized that counting sequences in adults would involve representations in sensory, order, magnitude, and linguistic codes that implicate regions in auditory, supplementary motor, posterior parietal, and inferior frontal areas, respectively. In an fMRI scanner, participants heard four-number sequences in a 2 × 2 × 2 design. The sequences were adjacent or not (e.g., 5, 6, 7, 8 vs. 5, 6, 7, 9), ordered or not (e.g., 5, 6, 7, 8 vs. 8, 5, 7, 6), and were spoken by a voice of consistent or variable identity. Then, neural substrates of counting sequences were identified by testing for the effect of consecutiveness (ordered nonadjacent versus ordered adjacent, e.g., 5, 6, 7, 9 > 5, 6, 7, 8) in the hypothesized brain regions. Violations to consecutiveness elicited brain activity in the right inferior frontal gyrus (IFG) and the supplementary motor area (SMA). In contrast, no such activation was observed in the auditory cortex, despite violations in voice identity recruiting strong activity in that region. Also, no activation was observed in the inferior parietal lobule, despite a robust effect of orderedness observed in that brain region. These findings indicate that listening to counting sequences do not automatically elicit sensory or magnitude codes but suggest that the precise increments in the sequence are tracked by the mechanism for processing ordered associations in the SMA and by the mechanism for binding individual lexical items into a cohesive whole in the IFG.

Optimizing Mental Workload Estimation by Detecting Baseline State Using Vector Phase Analysis Approach

Improper baseline return from the previous task-evoked hemodynamic response (HR) can contribute to a large variation in the subsequent HR, affecting the estimation of mental workload in brain-computer interface systems. In this study, we proposed a method using vector phase analysis to detect the baseline state as being optimal or suboptimal. We hypothesize that selecting neuronal-related HR as observed in the optimal-baseline blocks can lead to an improvement in estimating mental workload. Oxygenated and deoxygenated hemoglobin concentration changes were integrated as parts of the vector phase. The proposed method was applied to a block-design functional near-infrared spectroscopy dataset (total blocks = 1384), measured on 24 subjects performing multiple difficulty levels of mental arithmetic task. Significant differences in hemodynamic signal change were observed between the optimal- and suboptimal-baseline blocks detected using the proposed method. This supports the effectiveness of the proposed method in detecting baseline state for better estimation of mental workload. The results further highlight the need of customized recovery duration. In short, the proposed method offers a practical approach to detect task-evoked signals, without the need of extra probes.

Shared Neural Circuits for Visuospatial Working Memory and Arithmetic in Children and Adults

Visuospatial working memory (VSWM) plays an important role in arithmetic problem solving, and the relationship between these two skills is thought to change over development. Even though neuroimaging studies have demonstrated that VSWM and arithmetic both recruit frontoparietal networks, inferences about common neural substrates have largely been made by comparisons across studies. Little work has examined how brain activation for VSWM and arithmetic converge within the same participants and whether there are age-related changes in the overlap of these neural networks. In this study, we examined how brain activity for VSWM and arithmetic overlap in 38 children and 26 adults. Although both children and adults recruited the intraparietal sulcus (IPS) for VSWM and arithmetic, children showed more focal activation within the right IPS, whereas adults recruited the bilateral IPS, superior frontal sulcus/middle frontal gyrus, and right insula. A comparison of the two groups revealed that adults recruited a more left-lateralized network of frontoparietal regions for VSWM and arithmetic compared with children. Together, these findings suggest possible neurocognitive mechanisms underlying the strong relationship between VSWM and arithmetic and provide evidence that the association between VSWM and arithmetic networks changes with age.

Neural substrates of verbal repetition deficits in primary progressive aphasia

In this cross-sectional study, we examined the relationship between cortical thickness and performance on several verbal repetition tasks in a cohort of patients with primary progressive aphasia in order to test predictions generated by theoretical accounts of phonological working memory that predict phonological content buffers in left posterior inferior frontal sulcus and supramarginal gyrus. Cortical surfaces were reconstructed from magnetic resonance imaging scans from 42 participants diagnosed with primary progressive aphasia. Cortical thickness was measured in a set of anatomical regions spanning the entire cerebral cortex. Correlation analyses were performed between cortical thickness and average score across three phonological working memory-related tasks: the Repetition sub-test from the Western Aphasia Battery, a forward digit span task, and a backward digit span task. Significant correlations were found between average working memory score across tasks and cortical thickness in left supramarginal gyrus and left posterior inferior frontal sulcus, in support of prior theoretical accounts of phonological working memory. Exploratory whole-brain correlation analyses performed for each of the three behavioural tasks individually revealed a distinct set of positively correlated regions for each task. Comparison of cortical thickness measures from different primary progressive aphasia sub-types to cortical thickness in age-matched controls further revealed unique patterns of atrophy in the different subtypes.

EEG microstate features according to performance on a mental arithmetic task

In this study, we hypothesized that task performance could be evaluated applying EEG microstate to mental arithmetic task. This pilot study also aimed at evaluating the efficacy of microstates as novel features to discriminate task performance. Thirty-six subjects were divided into good and poor performers, depending on how well they performed the task. Microstate features were derived from EEG recordings during resting and task states. In the good performers, there was a decrease in type C and an increase in type D features during the task compared to the resting state. Mean duration and occurrence decreased and increased, respectively. In the poor performers, occurrence of type D feature, mean duration and occurrence showed greater changes. We investigated whether microstate features were suitable for task performance classification and eleven features including four archetypes were selected by recursive feature elimination (RFE). The model that implemented them showed the highest classification performance for differentiating between groups. Our pilot findings showed that the highest mean Area Under Curve (AUC) was 0.831. This study is the first to apply EEG microstate features to specific cognitive tasks in healthy subjects, suggesting that EEG microstate features can reflect task achievement.

Neural Correlate Differences in Number Sense Between Children With Low and Middle/High Socioeconomic Status

Although some cognitive studies provided reasons that children with low socioeconomic status (SES) showed poor mathematical achievements, there was no explicit evidence to directly explain the root of lagged performance in children with low SES. Therefore, the present study explored the differences in neural correlates in the process of symbolic magnitude comparison between children with different SESs by the event-related potentials (ERPs). A total of 16 second-graders from low-SES families and 16 from middle/high-SES families participated in this study. According to the results of anterior N1 (early attention) and P2 (extraction of numerical meaning) over the frontal region, the differences among children with different SESs were manifested as differences in general neural activities in terms of attention and top-down cognitive control. In the late stage of cognitive processing, there was no significant difference in the average amplitude of the late positive component (LPC) between children with different SES, indicating that low SES did not influence the information encoding and memory updating of numerical representation, which was responsible by the parietal lobe. The educational implications of this study are mentioned in the discussion.

Dissociating Arithmetic Operations in the Parietal Cortex Using 1 Hz Repetitive Transcranial Magnetic Stimulation: The Importance of Strategy Use

The triple-code model (TCM) of number processing suggests the involvement of distinct parietal cortex areas in arithmetic operations: the bilateral horizontal segment of the intraparietal sulcus (hIPS) for arithmetic operations that require the manipulation of numerical quantities (e.g., subtraction) and the left angular gyrus (AG) for arithmetic operations that require the retrieval of answers from long-term memory (e.g., multiplication). Although neuropsychological, neuroimaging, and brain stimulation studies suggest the dissociation of these operations into distinct parietal cortex areas, the role of strategy (online calculation vs. retrieval) is not yet fully established. In the present study, we further explored the causal involvement of the left AG for multiplication and left hIPS for subtraction using a neuronavigated repetitive transcranial magnetic stimulation (rTMS) paradigm. Stimulation sites were determined based on an fMRI experiment using the same tasks. To account for the effect of strategy, participants were asked whether they used retrieval or calculation for each individual problem. We predicted that the stimulation of the left AG would selectively disrupt the retrieval of the solution to multiplication problems. On the other hand, stimulation of the left hIPS should selectively disrupt subtraction. Our results revealed that left AG stimulation was detrimental to the retrieval and online calculation of solutions for multiplication problems, as well as, the retrieval (but not online calculation) of the solutions to subtraction problems. In contrast, left hIPS stimulation had no detrimental effect on both operations regardless of strategy.

Children's neural activity during number line estimations assessed by functional near-infrared spectroscopy (fNIRS)

Number line estimation (NLE) is an educational task in which children estimate the location of a value (e.g., 25) on a blank line that represents a numerical range (e.g., 0-100). NLE performance is a strong predictor of success in mathematics, and error patterns on this task help provide a glimpse into how children may represent number internally. However, a missing and fundamental element of this puzzle is the identification of neural correlates of NLE in children. That is, understanding possible neural signatures related to NLE performance will provide valuable insight into the cognitive processes that underlie children's development of NLE ability. Using functional near-infrared spectroscopy (fNIRS), we provide the first investigation of concurrent behavioral and cortical signatures of NLE performance in children. Specifically, our results highlight significant fronto-parietal changes in cortical activation in response to increases in NLE scale (e.g., 0-100 vs. 0-100,000). Furthermore, our results demonstrate that NLE performance feedback (auditory, visual, or audiovisual), as well as children's grade (2nd vs. 3rd) influence cortical responding during an NLE task.

Damage to the Intraparietal Sulcus Impairs Magnitude Representations of Results of Complex Arithmetic Problems

Past research investigating the role of the intraparietal sulcus (IPS) in numerical processes focused mainly on quantity and numerical comparisons as well on single digit arithmetic. The present study investigates the involvement of the IPS in estimating the results of multi-digit multiplication problems. For this purpose, the performance a 24-year-old female (JD) with brain damage in the left IPS was compared to an age-matched control group in the computation estimation task. When required to estimate whether the results of multi-digit multiplication problems are smaller or larger than given reference numbers, JD, in contrast to controls, did not show the common patterns of distance and size effects. Her strategy use was also atypical. Most control participants used both the approximated calculation strategy that involves rounding and calculation procedures and the sense of magnitude strategy that relies on an intuitive approximated magnitude representation of the results. In contrast, JD used only the former but not the latter strategy. Together, these findings suggest that the damage to the IPS impaired JD's representations of magnitude that play an important role in this computation estimation task.

Hemispheric asymmetries in processing numerical meaning in arithmetic

Hemispheric asymmetries in arithmetic have been hypothesized based on neuropsychological, developmental, and neuroimaging work. However, it has been challenging to separate asymmetries related to arithmetic specifically, from those associated general cognitive or linguistic processes. Here we attempt to experimentally isolate the processing of numerical meaning in arithmetic problems from language and memory retrieval by employing novel non-symbolic addition problems, where participants estimated the sum of two dot arrays and judged whether a probe dot array was the correct sum of the first two arrays. Furthermore, we experimentally manipulated which hemisphere receive the probe array first using a visual half-field paradigm while recording event-related potentials (ERP). We find that neural sensitivity to numerical meaning in arithmetic arises under left but not right visual field presentation during early and middle portions of the late positive complex (LPC, 400-800 ms). Furthermore, we find that subsequent accuracy for judgements of whether the probe is the correct sum is better under right visual field presentation than left, suggesting a left hemisphere advantage for integrating information for categorization or decision making related to arithmetic. Finally, neural signatures of operational momentum, or differential sensitivity to whether the probe was greater or less than the sum, occurred at a later portion of the LPC (800-1000 ms) and regardless of visual field of presentation, suggesting a temporal and functional dissociation between magnitude and ordinal processing in arithmetic. Together these results provide novel evidence for differences in timing and hemispheric lateralization for several cognitive processes involved in arithmetic thinking.

What's in a Hub?-Representing Identity in Language and Mathematics

Hubs emerge in structural and resting state network analysis as areas highly connected to other parts of the brain and have been shown to respond to several task domains in functional imaging studies. A cognitive explanation for this multi-functionality is still wanting. We propose, that hubs subserve domain-general meta-cognitive functions, relevant to a variety of domain-specific networks and test this hypothesis for the example of processing explicit identity information. To isolate this meta-cognitive function from the processing of domain-specific context, we investigate the overlapping activations to linguistic identity processes (e.g. Mr. Dietrich is the dentist) on the one hand and numerical identity processes (e.g. do "3 × 8" and "36-12" give the same number) on the other hand. The main question was, whether these overlapping activations would fall within areas, consistently identified as hubs by network-based analyses. Indeed, the two contrasts showed significant conjunctions in the left inferior parietal lobe (IPL), precuneus (PC), and posterior cingulate. Accordingly, identity processing may well be one domain-general meta-cognitive function that hub-areas provide to domain-specific networks. For the parietal lobe we back up our hypothesis further with existing reports of activation peaks for other tasks that depend on identity processing, e.g., episodic recollection, theory of mind, and visual perspective taking.

Impaired cognitive performance under psychosocial stress in cannabis-dependent men is associated with attenuated precuneus activity

BACKGROUND

Deficient regulation of stress plays an important role in the escalation of substance use, addiction and relapse. Accumulating evidence suggests dysregulations in cognitive and reward-related processes and the underlying neural circuitry in cannabis dependence. However, despite the important regulatory role of the endocannabinoid system in the stress response, associations between chronic cannabis use and altered stress processing at the neural level have not been systematically examined.

METHODS

Against this background, the present functional MRI study examined psychosocial stress processing in cannabis-dependent men (n = 28) and matched controls (n = 23) using an established stress-induction paradigm (Montreal Imaging Stress Task) that combines computerized (adaptive) mental arithmetic challenges with social evaluative threat.

RESULTS

During psychosocial stress exposure, but not the no-stress condition, cannabis users demonstrated impaired performance relative to controls. In contrast, levels of experienced stress and cardiovascular stress responsivity did not differ from controls. Functional MRI data revealed that stress-induced performance deteriorations in cannabis users was accompanied by decreased precuneus activity and increased connectivity of this region with the superior frontal gyrus.

LIMITATIONS

Only male cannabis-dependent users were examined; the generalizability in female users remains to be determined.

CONCLUSION

Together, the present findings provide first evidence for exaggerated stress-induced cognitive performance deteriorations in cannabis users. The neural data suggest that deficient stress-related recruitment of the precuneus may be associated with the deterioration of performance at the behavioural level.

Functional lateralization of arithmetic processing in the intraparietal sulcus is associated with handedness

Functional lateralization is established for various cognitive functions, but was hardly ever investigated for arithmetic processing. Most neurocognitive models assume a central role of the bilateral intraparietal sulcus (IPS) in arithmetic processing and there is some evidence for more pronounced left-hemispheric activation for symbolic arithmetic. However, evidence was mainly obtained by studies in right-handers. Therefore, we conducted a functional near-infrared spectroscopy (fNIRS) study, in which IPS activation of left-handed adults was compared to right-handed adults in a symbolic approximate calculation task. The results showed that left-handers had a stronger functional right-lateralization in the IPS than right-handers. This finding has important consequences, as the bilateral IPS activation pattern for arithmetic processing seems to be shaped by functional lateralization and thus differs between left- and right-handers. We propose three possible accounts for the observed functional lateralization of arithmetic processing.

Simple additions: Dissociation between retrieval and counting with electrophysiological indexes

There is current debate about the way adult individuals solve simple additions composed of one-digit operands. There are two opposing views. The first view assumes that people retrieve the result of additions from memory, whilst the second view states that individuals use automatized counting procedures. Our study aimed to dissociate between these two hypotheses. To this end, we analysed the type of problem effect when participants resolved simple additions by comparing additions with operands between 1 and 4 and control additions with at least one operand larger than 4. Brain-waves activity of a group of 30 adult individuals were recorded with 64 scalp electrodes mounted on an elastic cap, referenced against an electrode between Cz and CPz and re-referenced to an average reference offline. We considered two electrophysiological indexes, event-related potentials, ERPs, time-locked to the addition problems to distinguish between retrieval from memory and the use of procedures: A late positivity component (LP, 500-650 time window) over posterior regions associated to memory retrieval difficulty with higher LP positivity when participants resolve difficult vs. easy additions, and a negative component (N400, 250-450 ms time window) over fronto-central regions related to the use memory retrieval vs. procedures with more pronounced N400 amplitudes when the difficulty in the retrieval of semantic information increased. LP modulations were observed depending on the type of problem over posterior regions, P3 and Pz electrodes, whilst the N400 component was not affected. This pattern of results suggests that adult individuals use retrieval from memory to solve simple additions.

Cortical collateralization induced by language and arithmetic in non-right-handers

The functional overlap of language and arithmetic is debatable. Although some studies have reported independent representations of arithmetic and language in the brain, other studies have reported shared activity of the two cognitive domains in the inferior frontal gyrus. Although most previous studies have evaluated right-handed individuals, variability of hemispheric dominance in non-right-handed individuals should provide important information on the functional collateralization of these two cognitive domains. The present study evaluated the cortical lateralization patterns of the two cognitive domains using functional magnetic resonance imaging in 30 non-right-handed participants who performed language and arithmetic tasks. We found that language and arithmetic tasks demonstrated shared activity in the bilateral inferior frontal gyrus (IFG). Furthermore, the lateralization patterns of language and arithmetic tasks were correlated with each other. Most participants with language dominance in the left hemisphere also exhibited dominance of arithmetic tasks in the left hemisphere; similarly, most participants with language dominance in the right hemisphere exhibited dominance of arithmetic tasks in the right hemisphere. Among all the brain regions, the precentral gyrus, which is located slightly posterior to the IFG, exhibited the highest correlation coefficient between laterality indices of language and arithmetic tasks. These results suggest a shared functional property between language and arithmetic in the brain.

Prenatal Alcohol Exposure Alters Error Detection During Simple Arithmetic Processing: An Electroencephalography Study

BACKGROUND

Arithmetic is the domain of academic achievement most consistently related to prenatal alcohol exposure (PAE). Error detection, an important aspect of arithmetic processing, can be examined in a mathematical verification task. Electroencephalographic (EEG) studies using such tasks have shown bursts of synchronized theta-band activity in response to errors. We assessed this activity for error detection in adolescents with PAE and typically developing (TD) matched controls. We predicted that the PAE group would show smaller theta bursts during error detection and weaker responses depending on the size of the error discrepancy.

METHODS

Participants' mothers were recruited during pregnancy and interviewed about their alcohol consumption using a timeline follow-back interview. Participants were followed from infancy and diagnosed for fetal alcohol syndrome (FAS) or partial FAS (PFAS) by expert dysmorphologists. EEGs were recorded for 48 adolescents during a verification task, which required differentiation between correct/incorrect solutions to simple equations; incorrect solutions had small or large deviations from correct solutions.

RESULTS

Performance was good-excellent. The PAE group showed lower accuracy than the TD group: Accuracy was inversely related to diagnosis severity. The TD and heavily exposed (HE) nonsyndromal groups showed the expected differentiation in theta-burst activity between correct/incorrect equations, but the FAS/PFAS groups did not. Degree of impairment in brain response to errors reflected severity of diagnosis: The HE group showed the same differentiation between correct/incorrect solutions as TD but failed to differentiate between levels of discrepancy; PFAS showed theta reactions only in response to large error discrepancies; and FAS did not respond to small or large discrepancies.

CONCLUSIONS

Arithmetical error-related theta activity is altered by PAE and can be used to distinguish between exposed and nonexposed individuals and within diagnostic groups, supporting the use of numerical and quantitative processing patterns to derive a neurocognitive profile that could facilitate diagnosis and treatment of fetal alcohol spectrum disorders.

Mental workload characteristics of manipulator teleoperators with different spatial cognitive abilities

The main research on manipulator teleoperation includes robust of high-degree of freedom manipulators, sensor measurement accuracy, time delay, and mechanical structure design. Increased mental capacity requirements for complex assignments result in an increased mental workload. Spatial cognitive ability was considered to be the key factor affecting teleoperation performance. To accomplish this, we had 50 participants performed teleoperation while recorded their electroencephalogram. Electroencephalogram data of each task were divided into two periods, which correspond to the observation and large-scale transfer stages of teleoperation, respectively (period 1) and adjust the attitude of the manipulator to approach and align with the target stage (period 2). Brain topographic maps of period 1 (period 1 wavelet packet energy minus resting state wavelet packet energy) and period 2 (period 2 wavelet packet energy minus resting state wavelet packet energy) show that the frontal, central, and occipital regions are the main working areas of low spatial cognitive operators in period 1, while the frontal, central, and occipital regions are the main working areas of high spatial cognitive operators in period 1. The main changes in period 2 were frontal, central, parietal, and occipital regions. This study has implication for the analysis of electroencephalogram signal characteristics of mental workload in different populations to improve operators’ well-being and safety at teleoperation work.

Developing, mature, and unique functions of the child's brain in reading and mathematics

Cognitive development research shows that children use basic "child-unique" strategies for reading and mathematics. This suggests that children's neural processes will differ qualitatively from those of adults during this developmental period. The goals of the current study were to 1) establish whether a within-subjects neural dissociation between reading and mathematics exists in early childhood as it does in adulthood, and 2) use a novel, developmental intersubject correlation method to test for "child-unique", developing, and adult-like patterns of neural activation within those networks. Across multiple tasks, children's reading and mathematics activity converged in prefrontal cortex, but dissociated in temporal and parietal cortices, showing similarities to the adult pattern of dissociation. "Child-unique" patterns of neural activity were observed in multiple regions, including the anterior temporal lobe and inferior frontal gyri, and showed "child-unique" profiles of functional connectivity to prefrontal cortex. This provides a new demonstration that "children are not just little adults" - the developing brain is not only quantitatively different from adults, it is also qualitatively different.

Detrended Fluctuation, Coherence, and Spectral Power Analysis of Activation Rearrangement in EEG Dynamics During Cognitive Workload

In the study of human cognitive activity using electroencephalogram (EEG), the brain dynamics parameters and characteristics play a crucial role. They allow to investigate the changes in functionality depending on the environment and task performance process, and also to access the intensity of the brain activity in various locations of the cortex and its dependencies. Usually, the dynamics of activation of different brain areas during the cognitive tasks are being studied by spectral analysis based on power spectral density (PSD) estimation, and coherence analysis, which are de facto standard tools in quantitative characterization of brain activity. PSD and coherence reflect the strength of oscillations and similarity of the emergence of these oscillations in the brain, respectively, while the concept of stability of brain activity over time is not well defined and less formalized. We propose to employ the detrended fluctuation analysis (DFA) as a measure of the EEG persistence over time, and use the DFA scaling exponent as its quantitative characteristics. We applied DFA to the study of the changes in activation in brain dynamics during mental calculations and united it with PSD and coherence estimation. In the experiment, EEGs during resting state and mental serial subtraction from 36 subjects were recorded and analyzed in four frequency ranges: θ1 (4.1-5.8 Hz), θ2 (5.9-7.4 Hz), β1 (13-19.9 Hz), and β2 (20-25 Hz). PSD maps to access the intensity of cortex activation and coherence to quantify the connections between different brain areas were calculated, the distribution of DFA scaling exponent over the head surface was exploited to measure the time characteristics of the dynamics of brain activity. Obtained arrangements of DFA scaling exponent suggest that normal functioning of the brain is characterized by long-term temporal correlations in the cortex. Topographical distribution of the DFA scaling exponent was comparable for θ and β frequency bands, demonstrating the largest values of DFA scaling exponent during cognitive activation. The study shows that the long-term temporal correlations evaluated by DFA can be of great interest for diagnosis of the variety of brain dysfunctions of different etiology in the future.

Individual Differences in Math Ability Determine Neurocognitive Processing of Arithmetic Complexity: A Combined fNIRS-EEG Study

Some individuals experience more difficulties with math than others, in particular when arithmetic problems get more complex. Math ability, on one hand, and arithmetic complexity, on the other hand, seem to partly share neural underpinnings. This study addresses the question of whether this leads to an interaction of math ability and arithmetic complexity for multiplication and division on behavioral and neural levels. Previously screened individuals with high and low math ability solved multiplication and division problems in a written production paradigm while brain activation was assessed by combined functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG). Arithmetic complexity was manipulated by using single-digit operands for simple multiplication problems and operands between 2 and 19 for complex multiplication problems and the corresponding division problems. On the behavioral level, individuals with low math ability needed more time for calculation, especially for complex arithmetic. On the neural level, fNIRS results revealed that these individuals showed less activation in the left supramarginal gyrus (SMG), superior temporal gyrus (STG) and inferior frontal gyrus (IFG) than individuals with high math ability when solving complex compared to simple arithmetic. This reflects the greater use of arithmetic fact retrieval and also the more efficient processing of arithmetic complexity by individuals with high math ability. Oscillatory EEG analysis generally revealed theta and alpha desynchronization with increasing arithmetic complexity but showed no interaction with math ability. Because of the discovered interaction for behavior and brain activation, we conclude that the consideration of individual differences is essential when investigating the neurocognitive processing of arithmetic.