N-back Working Memory Task Research Articles

Cognitive Load Moderates the Effects of Total Sleep Deprivation on Working Memory: Evidence from Event-Related Potentials.

Purpose: The function of working memory (WM) is impaired by total sleep deprivation (TSD) and cognitive load. However, it is unclear whether the load modulates the effect of TSD on WM. We conducted a pilot study to investigate the effects of 36 h of TSD on WM under different load levels. Materials and methods: Twenty-two male students aged 18-25 years were enrolled, who underwent two types of sleep conditions (baseline and 36 h TSD), where they performed two N-back WM tasks (one-back task and two-back task) with simultaneous electroencephalography recordings. Results: Repeated measures analysis of variance (ANOVA) indicated that, with the increasing load, the reaction time increased and the accuracy decreased. After TSD, the correct number per unit time decreased. The significant interaction effect of the P3 amplitudes between the load level and the sleep condition showed that the reduction in the amplitude of P3 in the two-back task due to TSD was more obvious than that in the one-back task. Conclusions: Our results provided evidence for the moderation of load on the impairment of TSD on WM. The degree of TSD-induced impairment for a higher load was greater than that for a lower load. The current study provides new insights into the mechanisms by which sleep deprivation affects cognitive function.

Working memory-related brain activity in cannabis use disorder: The role of cross-cultural differences in cannabis attitudes.

Cannabis legislation and attitudes towards use are changing. Given that evidence from cultural neuroscience research suggests that culture influences the neurobiological mechanisms underlying behaviour, it is of great importance to understand how cannabis legislation and attitudes might affect the brain processes underlying cannabis use disorder. Brain activity of 100 dependent cannabis users and 84 controls was recorded during an N-back working memory (WM) task in participants from the Netherlands (NL; users = 60, controls = 52) and Texas, USA (TX; users = 40, controls = 32). Participants completed a cannabis culture questionnaire as a measure of perceived benefits (positive) and perceived harms (negative) of cannabis from their personal, friends-family's and country-state's perspectives. Amount of cannabis use (grams/week), DSM-5 CUD symptoms and cannabis use-related problems were assessed. Cannabis users self-reported more positive and less negative (personal and friends-family) cannabis attitudes than controls, with this effect being significantly larger in the TX cannabis users. No site difference in country-state attitudes was observed. TX cannabis users, compared with NL cannabis users, and those cannabis users perceiving more positive country-state attitudes showed a more positive association between grams/week and WM-related activity in the superior parietal lobe. NL cannabis users, compared with TX cannabis users, and those cannabis users with less positive personal attitudes showed a more positive association between grams/week and WM-load-related activity in the temporal pole. Both site and cultural attitudes moderated the association of quantity of cannabis use with WM- and WM-load-related activity. Importantly, differences in legislation did not align with perceived cannabis attitudes and appear to be differentially associated with cannabis use-related brain activity.

The Effect of Acute Aerobic Exercise on Working Memory Among Female Students of Bingham University, Nigeria

Researches have showed that participation in a physical activity is associated with increased performance across a variety of tasks involving attention, cognition, and memory. The present study aimed at investigating the effects of aerobic exercise on working memory in non-athletic female students of Bingham University. A total of 53 participants who completed the physical activity readiness questionnaire (PAR-Q) were considered for this study. The study was conducted in three days, with day 1 being the baseline testing. Participants completed an N-back working memory task before the start of aerobic exercise. They were then required to perform an aerobic exercise on the treadmill for 10 min; and after which, were made to perform the N-back working memory task again. The same procedure was carried out on days 2 and 3. All data were analysed using analysis of variance at p<0.05. A significant (p<0.001) increase in total false alarm was observed in subjects after exercise and on days 2 and 3 compared to the first day before exercise. There was significant decrease in reaction time after the exercise, and on days 2 and 3 of the study as compared to the first day at p<0.001. This study has shown that acute aerobic exercise improved working memory in the female students’ population

Gamification of an n-back working memory task – Is it worth the effort? An EEG and eye-tracking study

Gamification of cognitive tasks might positively affect emotional-motivational factors (emotional design perspective) or negatively affect cognitive factors like working memory load (minimalistic design perspective). The current study examined the effects of gamification in a spatial n-back working memory task on task performance, task load (i.e., working memory load and effort), and subjective task experience. Task load was assessed by the physiological process measures pupil dilation and EEG theta (4–6 Hz) and alpha (8–13 Hz) frequency band power. Gamification was achieved by elements of emotional design (i.e., the visual screen design using, e.g., color, cartoon figures as n-back stimuli, and a narrative embedding of the task). While EEG and eye-tracking were recorded, participants conducted gamified and non-gamified 1-back and 2-back load levels. The gamification resulted in positive effects on subjective task experience and affect. Despite these effects, gamification did not affect task performance and task load. However, exploratory analyses revealed increased EEG theta power at right-parietal electrodes for gamified task versions compared to non-gamified ones. Potentially, this effect might indicate participants' increased effort or concentration in the gamified n-back task. In line with an emotional design perspective, gamification positively altered subjective task experience and affect without hampering task performance and therefore justify the extra effort of implementing game elements.

Disentangling working memory from multiple-object tracking: Evidence from dual-task interferences.

Multiple object tracking (MOT) is generally regarded as a pure attention-consuming task that draws heavily on attention resources. In the present study, we adopted a cross-channel visual-audio dual-task paradigm, i.e., the MOT task combined with the concurrent auditory N-back working memory task, to test whether working memory indeed plays a necessary role in the process of multiple tracking, as well as to further identify the specific types of working memory components involved in this process. Experiments 1a and 1b examined the relationship between the MOT task and nonspatial object working memory (OWM) processing by manipulatingthe tracking load and working memory load, respectively. Results in both experiments indicated that the concurrent nonspatial OWM task did not have a significant effect on the tracking capacity of the MOT task. In contrast, Experiments 2a and 2b examined the relationship between the MOT task and spatial working memory (SWM) processing by a similar approach. Results in both experiments indicated that the concurrent SWM task significantly impaired the tracking capacity of the MOT task, showing a gradual decrease with increasing SWM load. Overall, our study provides empirical evidence that multiple object tracking does involve working memory, primarily related to spatial working memory rather than nonspatial object working memory, which sheds more light on the mechanisms of multiple object tracking.

Brain functional abnormality in drug treated and drug naïve adolescents with borderline personality disorder: Evidence for default mode network dysfunction

BackgroundPatients with borderline personality disorder (BPD) have been found to show functional brain abnormality, including in the medial frontal cortex and other areas of the default mode network (DMN). The current study aimed to examine activations and de-activations in drug treated and medication-free female adolescents with the disorder. Methods39 DSM-5 adolescent female patients with BPD without psychiatric comorbidity and 31 matched healthy female adolescents underwent fMRI during the performance of 1-back and 2-back versions of the n-back working memory task. Linear models were used to obtain maps of within-group activations and de-activations and areas of differences between the groups. ResultsOn corrected whole-brain analysis, the BPD patients showed failure to de-activate a region of the medial frontal cortex in the 2-back > 1-back comparison. The 30 never-medicated patients additionally showed a failure to de-activate the right hippocampus in the 2-back versus baseline contrast. ConclusionsEvidence of DMN dysfunction was observed in adolescent patients with BPD. Because the relevant medial frontal and hippocampal changes were seen in unmedicated young patients without comorbidity, they might be considered intrinsic to the disorder.

Unbalance between working memory task-activation and task-deactivation networks in epilepsy: Simultaneous EEG-fMRI study.

Working memory (WM) is a cognitive function involving emergent properties of theta oscillations and large-scale network interactions. The synchronization of WM task-related networks in the brain enhanced WM performance. However, how these networks regulate WM processing is not well known, and the alteration of the interaction among these networks may play an important role in patients with cognitive dysfunction. In this study, we used simultaneous EEG-fMRI to examine the features of theta oscillations and the functional interactions among activation/deactivation networks during the n-back WM task in patients with idiopathic generalized epilepsy (IGE). The results showed that there was more enhancement of frontal theta power along with WM load increase in IGE, and the theta power was positively correlated with the accuracy of the WM tasks. Moreover, fMRI activations/deactivations correlated with n-back tasks were estimated, and we found that the IGE group had increased and widespread activations in high-load WM tasks, including the frontoparietal activation network and task-related deactivation areas, such as the default mode network and primary visual and auditory networks. In addition, the network connectivity results demonstrated decreased counteraction between the activation network and deactivation network, and the counteraction was correlated with the higher theta power in IGE. These results indicated the important role of the interactions between activation and deactivation networks during the WM process, and the unbalance among them may indicate the pathophysiological mechanism of cognitive dysfunction in generalized epilepsy.

Brain network integration, segregation and quasi‐periodic activation and deactivation during tasks and rest

Previous studies have shown that a re-organization of the brain's functional connectome expressed in terms of network integration and segregation may play a pivotal role for brain function. However, it has been proven difficult to fully capture both processes independently in a single methodological framework. In this study, by starting from pair-wise assessments of instantaneous phase synchronization and community membership, we assemble spatiotemporally flexible networks that reflect changes in integration/segregation that occur at a spectrum of spatial as well as temporal scales. This is achieved by iteratively assembling smaller networks into larger units under the constraint that the smaller units should be internally integrated, i.e. belong to the same community. The assembled subnetworks can be partly overlapping and differ in size across time. Our results show that subnetwork integration and segregation occur simultaneously in the brain. During task performance, global changes in synchronization between networks arise that are tied to the underlying temporal design of the experiment. We show that a hallmark property of the dynamics of the brain's functional connectome is a presence of quasi-periodic patterns of network activation and deactivation, which during task performance becomes intertwined with the underlying temporal structure of the experimental paradigm. Additionally, we show that the degree of network integration throughout a n-back working memory task is correlated to performance.

Reduced neural functional connectivity during working memory performance in methamphetamine use disorder

BackgroundMethamphetamine misuse, a surging cause of morbidity and mortality worldwide, identifies Methamphetamine Use Disorder (MUD) as a critical public health problem. Treatment for MUD typically is sought during early abstinence when patients are experiencing cognitive difficulties that may hamper their engagement in treatment and recovery. Cognitive difficulties, particularly those that involve executive functions, likely reflect disruptions in neural functioning involving multiple brain areas and circuits. MethodsTo extend knowledge in this area, we compared individuals with MUD (MUD group, n = 30) in early abstinence (3–11 days abstinent) with a healthy control group (HC, n = 33) on brain activation and network connectivity and topology, using functional magnetic resonance imaging (fMRI) during performance on an N-back working memory task. The N-back task involves the maintenance and manipulation of information in short-term memory and engages multiple neural processes related to executive functioning. The task was administered at two working-memory difficulty loads (1-back and 2-back). ResultsCompared with the HC group, the MUD group had worse task performance but no differences in task-related brain activation. Network-based statistics analyses, however, revealed that the MUD group exhibited less functional network connectivity at both difficulty loads of the N-back task than the HC group. Additional graph theory analyses showed that path lengths were longer, and clustering was lower across these networks, which also exhibited disrupted small-world properties in the MUD group. ConclusionThese results suggest a decoupling in network dynamics that may underlie deficits in cognition during early abstinence in MUD patients.

K-means Clustering Machine Learning Approach Reveals Groups of Homogeneous Individuals with Unique Brain Activation, Task, and Performance Dynamics using fNIRS.

Wearable functional near-infrared spectroscopy (fNIRS) for measuring brain function, in terms of hemodynamic responses, is pervading our everyday life and holds the potential to reliably classify cognitive load in a naturalistic environment. However, human's brain hemodynamic response, behavior, and cognitive and task performance vary, even within and across homogeneous individuals (with same training and skill sets), which limits the reliability of any predictive model for human. In the context of high-stakes tasks, such as in military and first-responder operations, the real-time monitoring of cognitive functions and relating it to the ongoing task, performance outcomes, and behavioral dynamics of the personnel and teams is invaluable. In this work, a portable wearable fNIRS system (WearLight) developed by the author was upgraded, and an experimental protocol was designed to image the prefrontal cortex (PFC) area of the brain of 25 healthy homogeneous participants in a naturalistic environment while participants performed n-back working memory (WM) tasks with four difficulty levels. The raw fNIRS signals were processed using a signal processing pipeline to derive the brain's hemodynamic responses. An unsupervised k-means machine learning (ML) clustering approach, utilizing the task-induced hemodynamic responses as input variables, suggested three unique participant groups. Task performance in terms of % correct, % missing, reaction time, inverse efficiency score (IES), and a proposed IES was extensively evaluated for each participant and the three groups. Results showed that, on average, brain hemodynamic response increased, whereas task performance degraded, with increasing WM load. However, the regression and correlation analysis of WM task, performance, and the brain's hemodynamic responses (TPH) revealedinteresting hidden characteristics and the variation in the TPH relationship between groups. The proposed IES also served as a better scoring method that had distinct score ranges for different load levels as opposed to the overlapping scores of the traditional IES method. Results showed that the k-means clustering has the potential to find groups of individuals in an unsupervised manner using the brain's hemodynamic responses and to study the underlying relationship between the TPH in groups. Using the method presented in this paper,real-time monitoring of cognitive and task performance of soldiers, and preferentially forming small units to accomplish tasks based on the insights and goals may be helpful. The results showed that WearLight can image PFC, and this study also suggests future directions for the multi-modal body sensor network (BSN) combining advanced ML algorithms for real-time state classification, cognitive and physical performance prediction, and the mitigation of performance degradation in the high-stakes environment.

Effects of Menstrual Cycle on Working Memory and its Correlation with Menstrual Distress Score: A Cross-sectional Study

Introduction: The menstrual cycle is a well known physiological model to study the ovarian steroid hormones, influencing cognitive functions like Working Memory (WM). Hormonal fluctuation during the menstrual cycle also affects menstrual distress-related symptoms, which indecently could the cognitive functions. However, the data were inconclusive regarding the change in WM functions during different phases of the menstrual cycle and the correlation of various WM functions with menstrual distress-related symptoms. Aim: To examine the verbal and visuospatial WM functions during the proliferative (day 10-14) and secretory phase (day 21-25) of the menstrual cycle and to correlate various WM functions with menstrual distress symptoms scores. Materials and Methods: A cross-sectional, observational study was carried out in the Department of Physiology at VMMC and Safdarjung Hospital, New Delhi, India, over a period of 18 months, from November 2020 to May 2022. A total of 40 young adult females with a history of regular menstrual cycles were selected for the study. Computerised software-based dual-task n-back WM tasks were given twice in the same menstrual cycle: first, the proliferative (day 10-14) and second, the secretory phase (day 21-25). In addition, a standardised Menstrual Distress Questionnaire (MDQ) based on various menstrual distress symptoms was also administered to each subject after completion of the WM task, first in the proliferative (day 10-14) and second, in the secretory phase (day 21-25). Based on MDQ, a score was calculated, a Menstrual Distress Score (MDS). Descriptive statistics such as mean, median, standard deviation, and mode were calculated and Pearson’s coefficient/ Spearman’s rank correlation coefficient was used to assess the correlation WM parameters with MDS. Data was compiled and analysed using the statistical software Graph PadPrism. Results: The mean age of the study population was 23.4 years with an average menstrual cycle length of 30 days. In the WM task, the ‘overall proportion of correct’ responses across all the tasks were significantly better in the secretory phase of the menstrual cycle than in the proliferative phase (p-value=0.040). Similarly, significantly improved performance in WM tasks during the secretory phase was also seen in the overall ‘hit rate’ of the visual target (p-value=0.020) and auditory targets (p-value=0.044). On the other hand, the correlation of WM parameters with MDS did not show any statistical significance except a significant negative correlation (r-value -0.369; p-value=0.019) between the ‘parametric sensitivity’ (subject’s ability to correctly distinguishing a target from a non target) of auditory WM of secretory phase and MDS of the proliferative phase. Conclusion: The visual and auditory WM skills were significantly improved during the secretory phase compared to the menstrual cycle’s proliferative phases in terms of the target ‘hit rate’. However, increased MDS had no significant detrimental effect on the performance of WM tasks during the normal menstrual cycle.

Physical fitness is associated with neural activity during working memory performance in major depressive disorder

BackgroundDeficits in cognition like working memory (WM) are highly prevalent symptoms related to major depressive disorder (MDD). Neuroimaging studies have described frontoparietal abnormalities in patients with MDD as a basis for these deficits. Based on research in healthy adults, it is hypothesized that increased physical fitness might be a protective factor for these deficits in MDD. However, the relationship between physical fitness and WM-related neural activity and performance has not been tested in MDD, to date. Understanding these associations could inform the development of physical exercise interventions in MDD. MethodsWithin a larger project, 111 (53female) MDD outpatients and 56 (34female) healthy controls performed an n-back task (0-, 1-, 2-, 3-back) during functional Magnetic Resonance Imaging. Physical fitness from a graded exercise test on a cycle ergometer was performed by 106 MDD patients. ResultsPatients showed reduced performance particularly at high loads of the n-back WM task and prolonged reaction times at all n-back loads. A whole-brain interaction analysis of group by WM load revealed reduced neural activity in six frontoparietal clusters at medium and high WM loads in MDD patients compared to healthy controls. Analysis of covariance within the MDD sample showed that physical fitness was associated with neural activity in right and left superior parietal lobules. Externally defined Regions of Interest confirmed this analysis. ConclusionsResults indicate frontoparietal hypoactivity in MDD at high demands, arguing for decreased WM capacity. We demonstrate a parietal fitness correlate which could be used to guide future research on effects of exercise on cognitive functioning in MDD.

Air-conducted ultrasound below the hearing threshold elicits functional changes in the cognitive control network.

Air-conducted ultrasound (> 17.8 kHz; US) is produced by an increasing number of technical devices in our daily environment. While several studies indicate that exposure to US in public spaces can lead to subjective symptoms such as 'annoyance' or 'difficulties in concentration', the effects of US on brain activity are poorly understood. In the present study, individual hearing thresholds (HT) for sounds in the US frequency spectrum were assessed in 21 normal-hearing participants. The effects of US were then investigated by means of functional magnetic resonance imaging (fMRI). 15 of these participants underwent three resting-state acquisitions, two with a 21.5 kHz tone presented monaurally at 5 dB above (ATC) and 10 dB below (BTC) the HT and one without auditory stimulation (NTC), as well as three runs of an n-back working memory task involving similar stimulus conditions (n-ATC, n-BTC, n-NTC). Comparing data gathered during n-NTC vs. fixation, we found that task performance was associated with the recruitment of regions within the cognitive control network, including prefrontal and parietal areas as well as the cerebellum. Direct contrasts of the two stimulus conditions (n-ATC & n-BTC) vs. n-NTC showed no significant differences in brain activity, irrespective of whether a whole-brain or a region of interest approach with primary auditory cortex as the seed was used. Likewise, no differences were found when the resting-state runs were compared. However, contrast analysis (n-BTC vs. n-ATC) revealed a strong activation in bilateral inferior frontal gyrus (IFG, triangular part) only when US was presented below the HT (p < 0.001, cluster > 30). In addition, IFG activation was also associated with faster reaction times during n-BTC (p = 0.033) as well as with verbal reports obtained after resting-state, i.e., the more unpleasant sound was perceived during BTC vs. ATC, the higher activation in bilateral IFG was and vice versa (p = 0.003). While this study provides no evidence for activation of primary auditory cortex in response to audible US (even though participants heard the sounds), it indicates that US can lead to changes in the cognitive control network and affect cognitive performance only when presented below the HT. Activation of bilateral IFG could reflect an increase in cognitive demand when focusing on task performance in the presence of slightly unpleasant and/or distracting US that may not be fully controllable by attentional mechanisms.

Programming ability prediction: Applying an attention-based convolutional neural network to functional near-infrared spectroscopy analyses of working memory.

Although theoretical studies have suggested that working-memory capacity is crucial for academic achievement, few empirical studies have directly investigated the relationship between working-memory capacity and programming ability, and no direct neural evidence has been reported to support this relationship. The present study aimed to fill this gap in the literature. Using a between-subject design, 17 programming novices and 18 advanced students performed an n-back working-memory task. During the experiment, their prefrontal hemodynamic responses were measured using a 48-channel functional near-infrared spectroscopy (fNIRS) device. The results indicated that the advanced students had a higher working-memory capacity than the novice students, validating the relationship between programming ability and working memory. The analysis results also showed that the hemodynamic responses in the prefrontal cortex can be used to discriminate between novices and advanced students. Additionally, we utilized an attention-based convolutional neural network to analyze the spatial domains of the fNIRS signals and demonstrated that the left prefrontal cortex was more important than other brain regions for programming ability prediction. This result was consistent with the results of statistical analysis, which in turn improved the interpretability of neural networks.

Reduced brain activity during a working memory task in middle-aged apolipoprotein E ε4 carriers with overweight/obesity.

The apolipoprotein E ε4 (APOE ε4) allele and midlife obesity are independent risk factors for Alzheimer's disease (AD). Both of these risk factors are also associated with differences in brain activation, as measured by blood oxygenation level-dependent (BOLD) responses, in the absence of detectable cognitive deficits. Although the presence of these risk factors may influence brain activity during working memory tasks, no study to date has examined whether the presence of the ε4 allele explains variation in working memory brain activity while matching for levels of overweight/obesity. The primary aim of this study was to determine whether the presence of the ε4 allele is associated with differences in task-functional magnetic resonance imaging (fMRI) brain activation in adults with overweight/obesity. We predicted that ε4 carriers would have greater brain activation in regions that support working memory. This ancillary study included 48 (n = 24 APOE ε4 carriers; n = 24 APOE ε4 non-carriers), sedentary middle-aged adults (Mean age = 44.63 ± 8.36 years) with overweight/obesity (Mean BMI = 32.43 ± 4.12 kg/m2) who were matched on demographic characteristics. Participants were a subsample enrolled in 12-month randomized clinical trial examining the impact of energy-restricted diet and exercise on cardiovascular health outcomes. Participants completed a n-back working memory task with fMRI, which were completed within one month of the start of the intervention. Participants also underwent pseudo-continuous arterial spin labeling scans, a MRI measure of cerebral blood flow (CBF). Compared to non-ε4 carriers with overweight/obesity, ε4 carriers with overweight/obesity had lower fMRI brain activity in the middle frontal gyrus, pre and post central gyrus, supramarginal gyrus, superior temporal gyrus, lateral occipital cortex, and angular gyrus (z range = 2.52-3.56) during the n-back working memory task. Differences persisted even when controlling for CBF in these brain regions. These results indicate that presence of the APOE ε4 allele in middle-aged adults with overweight/obesity is related to altered brain activity during a working memory paradigm, which may confer risk for accelerated neurocognitive decline in late adulthood. Future research is needed to clarify the clinical implications of these findings in the context of risk for AD.

Effects of Long-Term Exposure to 2260 m Altitude on Working Memory and Resting-State Activity in the Prefrontal Cortex: A Large-Sample Cross-Sectional Study.

It has been well established that very-high-altitude (>4000 m) environments can affect human cognitive function and brain activity. However, the effects of long-term exposure to moderate altitudes (2000–3000 m) on cognitive function and brain activity are not well understood. In the present cross-sectional study, we utilized an N-back working memory task and resting-state functional near-infrared spectroscopy to examine the effects of two years of exposure to 2260 m altitude on working memory and resting-state brain activity in 208 college students, compared with a control group at the sea level. The results showed that there was no significant change in spatial working memory performance after two years of exposure to 2260 m altitude. In contrast, the analysis of resting-state brain activity revealed changes in functional connectivity patterns in the prefrontal cortex (PFC), with the global efficiency increased and the local efficiency decreased after two years of exposure to 2260 m altitude. These results suggest that long-term exposure to moderate altitudes has no observable effect on spatial working memory performance, while significant changes in functional connectivity and brain network properties could possibly occur to compensate for the effects of mild hypoxic environments. To our knowledge, this study is the first to examine the resting state activity in the PFC associated with working memory in people exposed to moderate altitudes.

Functional neurodevelopment of working memory in early-onset schizophrenia: A longitudinal FMRI study

Schizophrenia, a debilitating disorder with typical manifestation of clinical symptoms in early adulthood, is characterized by cognitive impairments in executive processes such as in working memory (WM). However, there is a rare case of individuals with early-onset schizophrenia (EOS) starting before their 18th birthday, while WM and its neural substrates are still undergoing maturation. Using the WM n-back task with functional magnetic resonance imaging, we assessed the functional neurodevelopment of WM in adolescents with EOS and age- and gender-matched typically developing controls. Participants underwent neuroimaging in the same scanner twice, once at age 17 and at 21 (mean interscan interval = 4.3 years). General linear model analysis was performed to explore WM neurodevelopmental changes within and between groups. Psychopathological scores were entered in multiple regressions to detect brain regions whose longitudinal functional change was predicted by baseline symptoms in EOS. WM neurodevelopment was characterized by widespread functional reductions in frontotemporal and cingulate brain areas in patients and controls. No between-group differences were found in the trajectory of WM change. Baseline symptom scores predicted functional neurodevelopmental changes in frontal, cingulate, parietal, occipital, and cerebellar areas. The adolescent brain undergoes developmental processes such as synaptic pruning, which may underlie the refinement WM of network. Prefrontal and parietooccipital activity reduction is affected by clinical presentation of symptoms. Using longitudinal neuroimaging methods in a rare diagnostic sample of patients with EOS may help the advancement of neurodevelopmental biomarkers intended as pharmacological targets to tackle WM impairment.

Greater individual variability in functional brain activity during working memory performance in Schizophrenia Spectrum Disorders (SSD)

Heterogeneity has been a persistent challenge in understanding Schizophrenia Spectrum Disorders (SSD). Traditional case-control comparisons often show variable results, and may not map well onto individuals. To better understand heterogeneity and group differences in SSD compared to typically developing controls (TDC), we examined variability in functional brain activity during a working memory (WM) task with known deficits in SSD. Neuroimaging and behavioural data were extracted from two datasets collectively providing 34 TDC and 56 individuals with SSD (n = 90). Functional activity in response to an N-Back WM task (3-Back vs 1-Back) was examined between and within groups. Individual variability was calculated via the correlational distance of fMRI activity maps between participants; mean correlational distance from one participant to all others was defined as a ‘variability score’. Greater individual variability in functional activity was found in SSD compared to TDC (p = 0.00090). At the group level, a case-control comparison suggested SSD had reduced activity in task positive and task negative networks. However, when SSD were divided into high and low variability subgroups, the low variability groups showed no differences relative to TDC while the high variability group showed little activity at the group level. Our results imply prior case-control differences may be driven by a subgroup of SSD who do not show specific impairments but instead show more ‘idiosyncratic’ activity patterns. In SSD but not TDC, variability was also related to cognitive performance and age. This novel approach focusing on individual variability has important implications for understanding the neurobiology of SSD.

Analyses of n-back high-load working memory in early Parkinson's disease: An fMRI study

BackgroundCognitive impairment is common in Parkinson's disease (PD). Working memory is a group of basic processes that is part of many cognitive operations (from complex decision-making to selective attention). To date, there is not sufficient research on working memory impairment in early PD patients, especially patients under high load. AimThe aim of this study was to observe the activation of brain regions in early PD patients during verbal high-load cognitive tasks and to explore the correlation between cognitive behavior indexes and gray matter areas of brain structure. MethodsA total of 45 participants were included: 15 healthy controls and 30 PD patients without dementia. They underwent BOLD imaging during a digital N-back working memory task in a 3 T scanner, and their high-resolution T1-weighted three-dimensional brain anatomical images were collected. The SPM12 standard method was used to generate a comparison map with 2 plus 3-back greater than 0-back, and with age, sex, levodopa equivalent daily dose (LEDD) and education as covariables, and multiple regression analysis was conducted to analyze the correlation between MOCA, MES and brain gray matter volume. ResultsCompared with the control group, the frontoparietal region was significantly activated in patients with PD under the background of high working memory burden. In addition, there was a widespread area correlation between the brain structure and basic cognitive function. ConclusionsThe frontoparietal cortex is the core hub of working memory, and there may be a compensation mechanism in PD patients without dementia with a high-load of working memory.

Explainable machine learning approach to predict and explain the relationship between task-based fMRI and individual differences in cognition.

Despite decades of costly research, we still cannot accurately predict individual differences in cognition from task-based functional magnetic resonance imaging (fMRI). Moreover, aiming for methods with higher prediction is not sufficient. To understand brain-cognition relationships, we need to explain how these methods draw brain information to make the prediction. Here we applied an explainable machine-learning (ML) framework to predict cognition from task-based fMRI during the n-back working-memory task, using data from the Adolescent Brain Cognitive Development (n= 3,989). We compared 9 predictive algorithms in their ability to predict 12 cognitive abilities. We found better out-of-sample prediction from ML algorithms over the mass-univariate and ordinary least squares (OLS) multiple regression. Among ML algorithms, Elastic Net, a linear and additive algorithm, performed either similar to or better than nonlinear and interactive algorithms. We explained how these algorithms drew information, using SHapley Additive explanation, eNetXplorer, Accumulated Local Effects, and Friedman's H-statistic. These explainers demonstrated benefits of ML over the OLS multiple regression. For example, ML provided some consistency in variable importance with a previous study and consistency with the mass-univariate approach in the directionality of brain-cognition relationships at different regions. Accordingly, our explainable-ML framework predicted cognition from task-based fMRI with boosted prediction and explainability over standard methodologies.