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We tested whether the AI driver could create a human-like ride experience for passengers based on 69 participants' feedback in a real-road scenario. We designed a ride experience-based version of the non-verbal Turing test for automated driving. Participants rode in autonomous cars as a passenger and judged whether the driver was human or AI. The AI driver failed to pass our test because passengers detected the AI driver above chance. We further investigated how human passengers ascribe humanness in our test. Based on Lewin's field theory, we advanced a computational model combining signal detection theory with pre-trained language models to predict passengers' humanness rating behaviour. We employed affective transition between pre-study baseline and corresponding post-stage emotions as the signal strength of our model. Results showed that the passengers' ascription of humanness would increase with the greater affective transition, indicating an important role of affective transition in passengers' ascription of humanness.

Abacus‐based mental calculation (AMC) is a widely used educational tool for enhancing math learning, offering an accessible and cost‐effective method for classroom implementation. Despite its universal appeal, the neurocognitive mechanisms that drive the efficacy of AMC training remain poorly understood. Notably, although abacus training relies heavily on the rapid recall of number positions and sequences, the role of memory systems in driving long‐term AMC learning remains unknown. Here, we sought to address this gap by investigating the role of the medial temporal lobe (MTL) memory system in predicting long‐term AMC training gains in second‐grade children, who were longitudinally assessed up to fifth grade. Leveraging multimodal neuroimaging data, we tested the hypothesis that MTL systems, known for their involvement in associative memory, are instrumental in facilitating AMC‐induced improvements in math skills. We found that gray matter volume in bilateral MTL, along with functional connectivity between the MTL and frontal and ventral temporal‐occipital cortices, significantly predicted learning gains. Intriguingly, greater gray matter volume but weaker connectivity of the posterior parietal cortex predicted better learning outcomes, offering a more nuanced view of brain systems at play in AMC training. Our findings not only underscore the critical role of the MTL memory system in AMC training but also illuminate the neurobiological factors contributing to individual differences in cognitive skill acquisition. A video abstract of this article can be viewed at https://youtu.be/StVooNRc7T8. Research Highlights: We investigated the role of medial temporal lobe (MTL) memory system in driving children's math learning following abacus‐based mental calculation (AMC) training.AMC training improved math skills in elementary school children across their second and fifth grade.MTL structural integrity and functional connectivity with prefrontal and ventral temporal‐occipital cortices predicted long‐term AMC training‐related gains. [ABSTRACT FROM AUTHOR]

Autonomous cars are indispensable when humans go further down the hands-free route. Although existing literature highlights that the acceptance of the autonomous car will increase if it drives in a human-like manner, sparse research offers the naturalistic experience from a passenger's seat perspective to examine the humanness of current autonomous cars. The present study tested whether the AI driver could create a human-like ride experience for passengers based on 69 participants’ feedback in a real-road scenario. We designed a ride experience-based version of the non-verbal Turing test for automated driving. Participants rode in autonomous cars (driven by either human or AI drivers) as a passenger and judged whether the driver was human or AI. The AI driver failed to pass our test because passengers detected the AI driver above chance. In contrast, when the human driver drove the car, the passengers’ judgement was around chance. We further investigated how human passengers ascribe humanness in our test. Based on Lewin's field theory, we advanced a computational model combining signal detection theory with pre-trained language models to predict passengers’ humanness rating behaviour. We employed affective transition between pre-study baseline emotions and corresponding post-stage emotions as the signal strength of our model. Results showed that the passengers’ ascription of humanness would increase with the greater affective transition. Our study suggested an important role of affective transition in passengers’ ascription of humanness, which might become a future direction for autonomous driving. [ABSTRACT FROM AUTHOR]

Enhancing the accuracy of traffic prediction relies on building a graph that effectively captures the intricate spatiotemporal correlations in traffic data. It is a widely observed phenomenon that different urban traffic activities exhibit an asymmetric mutual influence. However, existing methods for graph construction largely overlook this characteristic. To bolster prediction performance, this article introduces an attention mechanism based on transfer entropy (TE) to quantify the complex and asymmetric spatiotemporal correlations among traffic data. Subsequently, a graph attention network based on simplified TE calculation is devised to construct directed spatiotemporal graphs from heterogeneous traffic data. Finally, a directed spatiotemporal graph neural network is employed for training and prediction purposes. Experimental results demonstrate that our approach surpasses existing mainstream methods for spatiotemporal graph construction, leading to significant improvements in predicting heterogeneous traffic data. Further analysis reveals that TE exhibits higher sensitivity to asymmetric spatiotemporal influences in heterogeneous traffic environments compared to commonly used data dependency inference algorithms. This finding further validates the feasibility and advancement of our method in predicting heterogeneous traffic data. [ABSTRACT FROM AUTHOR]

The study aimed to evaluate the effects of noninvasive brain stimulation on cognitive function in healthy older adults and patients with Alzheimer's disease. A comprehensive literature search was performed on noninvasive stimulation studies published from January 1990 to November 2014 in Pubmed and Web of Science. Fourteen articles with a total of 331 participants were identified as studies with healthy older adults, and the mean effect size and 95% confidence interval were estimated. A significant effect size of 0.42 was found for the cognitive outcome. Further subgroup analyses demonstrated more prominent effects for studies delivering the stimulation before the execution of the task and studies applying multiple sessions of stimulation. To assess the effects of stimulation on Alzheimer's disease patients, 11 studies with a total of 200 patients were included in the analysis. A significant effect size of 1.35 was found for the cognitive outcomes. Subgroup analyses indicated more pronounced effects for studies applying the stimulation during the execution of the task compared with studies delivering the stimulation before the execution of the task. Noninvasive brain stimulation has a positive effect on cognitive function in physiological and pathological aging.

The prospects of gaining reward and avoiding punishment widely influence human behavior. Despite of numerous attempts to investigate the influence of motivational signals on working memory (WM), whether the valence and the magnitude of motivational signals interactively influence WM performance remains unclear. To investigate this, the present study used a free‐recall working memory task with EEG recording to compare the effect of incentive valence (reward or punishment), as well as the magnitude of incentives on visual WM. Behavioral results revealed that the presence of incentive signals improved WM precision when compared with no‐incentive condition, and compared with punishing cues, rewarding cues led to greater facilitation in WM precision, as well as confidence ratings afterward. Moreover, event related potential (ERP) results suggested that compared with punishment, reward led to an earlier latency of late positive component (LPC), a larger amplitude of contingent negative variation (CNV) during the expectation period, and a larger P300 amplitude during the sample and delay periods. Furthermore, reward advantage over punishment in behavioral and neural results were correlated, such that individuals with larger CNV difference between reward and punishment conditions also report greater distinction in confidence ratings between the two conditions. In sum, our results demonstrate what and how rewarding cues cause more beneficial effects than punishing cues when incentivizing visual WM. Prospect Theory has long been proposed that people were more sensitive to punishment than reward. However, we challenged it using a money‐incentive free‐recall working memory task and observed the advantage of rewarding over punishing cues when incentivizing working memory from results of both behaviors and electroencephalography. [ABSTRACT FROM AUTHOR]

Previous studies revealed inconsistent findings about the effects of cognitively low or high demanding interpolated tasks during incubation period on post-incubation creative performance. To explain this contradiction, two intervention tasks were administered (Reflecting on the generated ideas [RF] and the Word puzzle task [WP]), which are supposed to elicit remote associative processes but with varying levels of cognitive demands, along with two verbal control tasks (phonemic fluency task and object characteristics task). A delayed-incubation paradigm was used to assess whether performance on verbal creative problem solving (Alternative Uses Task, AUT) could be stimulated by the applied intervention tasks. The results showed that only RF and WP tasks, but not the control tasks, were associated with significant incubation effects. The findings suggest that the interpolated tasks that were assumed to elicit remote associative processes can unfold beneficial effects on verbal creative problem solving, regardless of whether the task is cognitively low or high demanding.

Background: Repetitive transcranial magnetic stimulation has been employed to treat drug dependence, reduce drug use and improve cognition. The aim of the study was to analyze the effectiveness of intermittent theta-burst stimulation (iTBS) on cognition in individuals with methamphetamine use disorder (MUD). Methods: This was a secondary analysis of 40 MUD subjects receiving left dorsolateral prefrontal cortex (L-DLPFC) iTBS or sham iTBS for 20 times over 10 days (twice-daily). Changes in working memory (WM) accuracy, reaction time, and sensitivity index were analyzed before and after active and sham rTMS treatment. Resting-state EEG was also acquired to identify potential biological changes that may relate to any cognitive improvement. Results: The results showed that iTBS increased WM accuracy and discrimination ability, and improved reaction time relative to sham iTBS. iTBS also reduced resting-state delta power over the left prefrontal region. This reduction in resting-state delta power correlated with the changes in WM. Conclusions: Prefrontal iTBS may enhance WM performance in MUD subjects. iTBS induced resting EEG changes raising the possibility that such findings may represent a biological target of iTBS treatment response. [ABSTRACT FROM AUTHOR]

The present study aimed to explore the effect of intermittent theta-burst stimulation (iTBS) on visual working memory for people suffering from methamphetamine use disorder (MUD). Five sessions of iTBS were carried over the left dorsolateral prefrontal cortex (DLPFC) or the vertex as a sham control, with each session in one day. Orientation free-recall tasks were conducted before the iTBS stimulation, after the first and fifth sessions of stimulation. Results showed that when compared with the sham group, a single session of iTBS over the left DLPFC improved participants' working memory performance. Specifically, iTBS over the left DLPFC increased the working memory capacity and such effects enlarged with multiple sessions. The present finding suggested that iTBS over DLPFC could be a promising intervention method to enhance the cognitive function of addicts with MUD. [ABSTRACT FROM AUTHOR]

Working memory (WM) deficits have been widely documented in schizophrenia (SZ), and almost all existing studies attributed the deficits to decreased capacity as compared to healthy control (HC) subjects. Recent developments in WM research suggest that other components, such as precision, also mediate behavioral performance. It remains unclear how different WM components jointly contribute to deficits in schizophrenia. We measured the performance of 60 SZ (31 females) and 61 HC (29 females) in a classical delay-estimation visual working memory (VWM) task and evaluated several influential computational models proposed in basic science of VWM to disentangle the effect of various memory components. We show that the model assuming variable precision (VP) across items and trials is the best model to explain the performance of both groups. According to the VP model, SZ exhibited abnormally larger variability of allocating memory resources rather than resources or capacity per se. Finally, individual differences in the resource allocation variability predicted variation of symptom severity in PSZ, highlighting its functional relevance to schizophrenic pathology. This finding was further verified using distinct visual features and subject cohorts. These results provide an alternative view instead of the widely accepted decreased-capacity theory and highlight the key role of elevated resource allocation variability in generating atypical VWM behavior in schizophrenia. Our findings also shed new light on the utility of Bayesian observer models to characterize mechanisms of mental deficits in clinical neuroscience. Author summary: Working memory is a core cognitive function related to a broad range of cognitive domains such as problem-solving, attention, executive control, and IQ. Although working memory deficits have been well-documented in schizophrenia, the underlying mechanisms remain unclear. Conventional working memory theories attribute working memory deficits in schizophrenia to their reduced memory capacity, overlooking the potential roles of other memory components, such as precision. In this study, we take the approach of computational psychiatry and use computational modeling to uncover the major determinants of working memory deficits. We assess working memory performance of a large cohort of participants (60 schizophrenia patients and 61 demographic matched healthy controls) and evaluate multiple mainstream computational models of visual working memory. The variable precision model turns out to be the best model for both groups. We further find that the poorer performance of schizophrenia patients arises from heterogeneous distribution of memory resources when encoding items in memory. This resource allocation variability can also predict symptom severity in schizophrenia. Our study highlights the use of computational models in psychiatric researches. [ABSTRACT FROM AUTHOR]

In contrast to background white noise, the detrimental effects of background speech on verbal working memory (WM) were often explained by speech interference in the same verbal modality. Yet, those results were confounded with potential differences between arousal levels induced by speech and white noise. To address the role of arousal, in the present study, we minimized the verbal interference by using a visual WM task to test the influence of background speech or white noise. Electrodermal activity (EDA) was recorded simultaneously to indicate participants' arousal levels. Results showed that both background speech and white noise significantly improved visual WM performance, which further correlated with individuals' changes of EDA signals. Taken together, our results suggest that background sounds of both speech and white noise facilitate visual WM by raising the arousal level. [ABSTRACT FROM AUTHOR]

In studies of cognitive neuroscience, multivariate pattern analysis (MVPA) is widely used as it offers richer information than traditional univariate analysis. Representational similarity analysis (RSA), as one method of MVPA, has become an effective decoding method based on neural data by calculating the similarity between different representations in the brain under different conditions. Moreover, RSA is suitable for researchers to compare data from different modalities and even bridge data from different species. However, previous toolboxes have been made to fit specific datasets. Here, we develop NeuroRA, a novel and easy-to-use toolbox for representational analysis. Our toolbox aims at conducting cross-modal data analysis from multi-modal neural data (e.g., EEG, MEG, fNIRS, fMRI, and other sources of neruroelectrophysiological data), behavioral data, and computer-simulated data. Compared with previous software packages, our toolbox is more comprehensive and powerful. Using NeuroRA, users can not only calculate the representational dissimilarity matrix (RDM), which reflects the representational similarity among different task conditions and conduct a representational analysis among different RDMs to achieve a cross-modal comparison. Besides, users can calculate neural pattern similarity (NPS), spatiotemporal pattern similarity (STPS), and inter-subject correlation (ISC) with this toolbox. NeuroRA also provides users with functions performing statistical analysis, storage, and visualization of results. We introduce the structure, modules, features, and algorithms of NeuroRA in this paper, as well as examples applying the toolbox in published datasets. [ABSTRACT FROM AUTHOR]

Background: Currently, no study has evaluated metal accumulation in the brains of patients with Wilson's disease by using quantitative susceptibility mapping at 3T MRI. The objectives of this study were to qualitatively and quantitatively evaluate changes in magnetic susceptibility and R2* maps in deep gray matter nuclei to discriminate Wilson's disease patients from healthy controls and to evaluate their sensitivities in diagnosing Wilson's disease. Methods: Magnetic susceptibility and R2* maps and conventional T1‐weighted, T2‐weighted, and T2‐weighted fluid‐attenuated inversion recovery images were obtained from 17 Wilson's disease patients and 14 age‐matched healthy controls on a 3T MRI scanner. Differences between Wilson's disease and healthy control groups in susceptibility and R2* values in multiple deep nuclei were evaluated using a Mann‐Whitney U test and receiver operating characteristic curves. The correlations of susceptibility and R2* values with Unified Wilson's Disease Rating Scale score were also performed. Results: Magnetic susceptibility and R2* can effectively distinguish different types of signal abnormalities. Magnetic susceptibility and R2* values in multiple deep nuclei of Wilson's disease patients were significantly higher than those in healthy controls. Magnetic susceptibility value in the substantia nigra had the highest area under the curve (0.888). There were positive correlations of the Unified Wilson's Disease Rating Scale score with susceptibility values in the caudate nucleus (r = 0.757, P = 0.011), putamen (r = 0.679, P = 0.031), and red nucleus (r = 0.638, P = 0.047), as well as R2* values in the caudate nucleus (r = 0.754, P = 0.012). Conclusions: Quantitative susceptibility mapping at 3T could be a useful tool to evaluate metal accumulation in deep gray matter nuclei of Wilson's disease patients. © 2020 International Parkinson and Movement Disorder Society [ABSTRACT FROM AUTHOR]

It is debated whether perceptual expertise of nonface objects, such as visual words, is indicated by holistic processing, which is regarded as a marker of perceptual expertise of faces. We address this question by frequency-tagged electroencephalography. Different parts of real or pseudo Chinese characters are presented at distinctive frequencies (6 or 7.2 Hz), which induce frequency-tagged steady-state visual-evoked potentials at occipital brain areas. The intermodulation response (e.g., 6 + 7.2 = 13.2 Hz) would emerge when holistic integration takes place. Our results suggest that the intermodulation response to the real characters is left lateralized, which is contralateral to previous findings with faces. Furthermore, at the left occipital area, the intermodulation response to real characters is more prominent than pseudo characters, suggesting that holistic integration is enhanced for real characters than for pseudo ones. Taken together, our findings suggest that holistic integration is potentially a general expertise marker for both faces and non-face objects. [ABSTRACT FROM AUTHOR]

Dopamine system plays a pivotal role in specific kinds of substance use disorders (SUD, i. e., cocaine and methamphetamine use disorders). Many studies addressed whether dopamine-involved craving could be alleviated by non-invasive brain stimulation (NIBS) techniques. Nevertheless, the outcomes were highly inconsistent and the stimulating parameters were highly variable. In the current study, we ran a meta-analysis to identify an overall effect size of NIBS and try to find stimulating parameters of special note. We primarily find 2,530 unduplicated studies in PubMed, Psychology and Behavioral Sciences Collection, PsycARTICLES, PsycINFO, and Google Scholar database involving "Cocaine"/"Amphetamine"/"Methamphetamine" binded with "TMS"/"tDCS"/"non-invasive stimulation" in either field. After visual screening, 26 studies remained. While 16 studies were further excluded due to the lack of data, invalid craving scoring or the absence of sham condition. At last, 16 units of analysis in 12 eligible studies were coded and forwarded to a random-effect analysis. The results showed a large positive main effect of stimulation (Hedge's g = 1.116, CI = [0.597, 1.634]). Further subgroup analysis found that only high-frequency repetitive transcranial magnetic stimulation (rTMS) could elicit a significant decrease in craving, while the outcome of low-frequency stimulation was relatively controversial. Moreover, univariate meta regression revealed that the number of pulses per session could impose negative moderation toward the intervention. No significant moderation effect was found in types of abuse, overall days of stimulation and other variables of stimulating protocol. In conclusion, this meta-analysis offered a persuasive evidence for the feasibility of using NIBS to remit substance addictive behavior directly based on dopamine system. We also give clear methodological guidance that researchers are expected to use high-frequency, sufficiently segmented rTMS to improve the efficacy in future treatments. [ABSTRACT FROM AUTHOR]

Neural activity in the dorsolateral prefrontal cortex (DLPFC) has been suggested to integrate information from distinct sensory areas. However, how the DLPFC interacts with the bilateral primary somatosensory cortices (SIs) in tactile-visual cross-modal working memory has not yet been established. In the present study, we applied single-pulse transcranial magnetic stimulation (sp-TMS) over the contralateral DLPFC and bilateral SIs of human participants at various time points, while they performed a tactile-visual delayed matching-to-sample task with a 2-second delay. sp-TMS over the contralateral DLPFC or the contralateral SI at either an sensory encoding stage [i.e. 100 ms after the onset of a vibrotactile sample stimulus (200-ms duration)] or an early maintenance stage (i.e. 300 ms after the onset), significantly impaired the accuracy of task performance; sp-TMS over the contralateral DLPFC or the ipsilateral SI at a late maintenance stage (1600 ms and 1900 ms) also significantly disrupted the performance. Furthermore, at 300 ms after the onset of the vibrotactile sample stimulus, there was a significant correlation between the deteriorating effects of sp-TMS over the contralateral SI and the contralateral DLPFC. These results imply that the DLPFC and the bilateral SIs play causal roles at distinctive stages during cross-modal working memory, while the contralateral DLPFC communicates with the contralateral SI in the early delay, and cooperates with the ipsilateral SI in the late delay. [ABSTRACT FROM AUTHOR]

Previous studies have examined the neural correlates for crossmodal paired-associate (PA) memory and the temporal dynamics of its formation. However, the neural dynamics for feedback processing of crossmodal PA learning remain unclear. To examine this process, we recorded event-related scalp electrical potentials for PA learning of unimodal visual-visual pairs and crossmodal visual-tactile pairs when participants performed unimodal and crossmodal tasks. We examined event-related potentials (ERPs) after the onset of feedback in the tasks for three effects: feedback type (positive feedback vs. negative feedback), learning (as the learning progressed) and the task modality (crossmodal vs. unimodal). The results were as follows: (1) feedback type: the amplitude of P300 decreased with incorrect trials and the P400/N400 complex was only present in incorrect trials; (2) learning: progressive positive voltage shifts in frontal recording sites and negative voltage shifts in central and posterior recording sites were identified as learning proceeded; and (3) task modality: compared with the unimodal PA learning task, positive voltage shifts in frontal sites and negative voltage shifts in posterior sites were found in the crossmodal PA learning task. To sum up, these results shed light on cortical excitability related to feedback processing of crossmodal PA learning. [ABSTRACT FROM AUTHOR]

Studies have indicated that a cortical sensory system is capable of processing information from different sensory modalities. However, it still remains unclear when and how a cortical system integrates and retains information across sensory modalities during learning. Here we investigated the neural dynamics underlying crossmodal associations and memory by recording event-related potentials (ERPs) when human participants performed visuo-tactile (crossmodal) and visuo-visual (unimodal) paired-associate (PA) learning tasks. In a trial of the tasks, the participants were required to explore and learn the relationship (paired or non-paired) between two successive stimuli. EEG recordings revealed dynamic ERP changes during participants’ learning of paired-associations. Specifically, (1) the frontal N400 component showed learning-related changes in both unimodal and crossmodal tasks but did not show any significant difference between these two tasks, while the central P400 displayed both learning changes and task differences; (2) a late posterior negative slow wave (LPN) showed the learning effect only in the crossmodal task; (3) alpha-band oscillations appeared to be involved in crossmodal working memory. Additional behavioral experiments suggested that these ERP components were not relevant to the participants’ familiarity with stimuli per se. Further, by shortening the delay length (from 1300 ms to 400 ms or 200 ms) between the first and second stimulus in the crossmodal task, declines in participants’ task performance were observed accordingly. Taken together, these results provide insights into the cortical plasticity (induced by PA learning) of neural networks involved in crossmodal associations in working memory. [ABSTRACT FROM AUTHOR]

Laboratory studies have investigated how individuals with normal memory spans attained digit spans over 80 digits after hundreds of hours of practice. Experimental analyses of their memory skills suggested that their attained memory spans were constrained by the encoding time, for the time needed will increase if the length of digit sequences to be memorised becomes longer. These constraints seemed to be violated by a world-class memorist, Feng Wang (FW), who won the World Memory Championship by recalling 300 digits presented at 1 digit/s. In several studies we examined FW’s memory skills underlying his exceptional performance. First FW reproduced his superior memory span of 200 digits under laboratory condition, and we obtained his retrospective reports describing his encoding/retrieval processes (Experiment 1). Further experiments used self-paced memorisation to identify temporal characteristics of encoding of digits in 4-digit clusters (Experiment 2), and explored memory encoding at presentation speeds much faster than 1 digit/s (Experiment 3). FW’s superiority over previous digit span experts is explained by his acquisition of well-known mnemonic techniques and his training that focused on rapid memorisation. His memory performance supports the feasibility of acquiring memory skills for improved working memory based on storage in long-term memory. [ABSTRACT FROM AUTHOR]

Previous studies revealed inconsistent findings about the effects of cognitively low or high demanding interpolated tasks during incubation period on post-incubation creative performance. To explain this contradiction, two intervention tasks were administered (Reflecting on the generated ideas [RF] and the Word puzzle task [WP]), which are supposed to elicit remote associative processes but with varying levels of cognitive demands, along with two verbal control tasks (phonemic fluency task and object characteristics task). A delayed-incubation paradigm was used to assess whether performance on verbal creative problem solving (Alternative Uses Task, AUT) could be stimulated by the applied intervention tasks. The results showed that only RF and WP tasks, but not the control tasks, were associated with significant incubation effects. The findings suggest that the interpolated tasks that were assumed to elicit remote associative processes can unfold beneficial effects on verbal creative problem solving, regardless of whether the task is cognitively low or high demanding. [ABSTRACT FROM AUTHOR]

Abstract: Functional neuroimaging data have shown that mental calculation involves fronto-parietal areas that are composed of different subsystems shared with other cognitive functions such as working memory and language. Event-related potential (ERP) analysis has also indicated sequential information changes during the calculation process. However, little is known about the dynamic properties of oscillatory networks in this process. In the present study, we applied both ERP and event-related (de-)synchronization (ERS/ERD) analyses to EEG data recorded from normal human subjects performing tasks for sequential visual/auditory mental addition. Results in the study indicate that the late positive components (LPCs) can be decomposed into two separate parts. The earlier element LPC1 (around 360ms) reflects the computing attribute and is more prominent in calculation tasks. The later element LPC2 (around 590ms) indicates an effect of number size and appears larger only in a more complex 2-digit addition task. The theta ERS and alpha ERD show modality-independent frontal and parietal differential patterns between the mental addition and control groups, and discrepancies are noted in the beta ERD between the 2-digit and 1-digit mental addition groups. The 2-digit addition (both visual and auditory) results in similar beta ERD patterns to the auditory control, which may indicate a reliance on auditory-related resources in mental arithmetic, especially with increasing task difficulty. These results coincide with the theory of simple calculation relying on the visuospatial process and complex calculation depending on the phonological process. [Copyright &y& Elsevier]