Spatiotemporal and spectral dynamics of multi-item working memory as revealed by the n-back task using MEG

Chronometric TMS-fMRI of personalized left dorsolateral prefrontal target reveals state-dependency of subgenual anterior cingulate cortex effects

Transcranial magnetic stimulation (TMS) applied to a left dorsolateral prefrontal cortex (DLPFC) area with a specific connectivity profile to the subgenual anterior cingulate cortex (sgACC) has emerged as a highly effective non-invasive treatment option for depression. However, antidepressant outcomes demonstrate significant variability among therapy plans and individuals. One overlooked contributing factor is the individual brain state at the time of treatment. In this study we used interleaved TMS-fMRI to investigate the influence of brain state on acute TMS effects, both locally and remotely. TMS was performed during rest and during different phases of cognitive task processing. Twenty healthy participants were included in this study. In the first session, imaging data for TMS targeting were acquired, allowing for identification of individualized targets in the left DLPFC based on highest anti-correlation with the sgACC. The second session involved chronometric interleaved TMS-fMRI measurements, with 10 Hz triplets of TMS administered during rest and at distinct timings during an N-back task. Consistent with prior findings, interleaved TMS-fMRI revealed significant BOLD activation changes in the targeted network. The precise timing of TMS relative to the cognitive states during the task demonstrated distinct BOLD response in clinically relevant brain regions, including the sgACC. Employing a standardized timing approach for TMS using a task revealed more consistent modulation of the sgACC at the group level compared to stimulation during rest. In conclusion, our findings strongly suggest that acute local and remote effects of TMS are influenced by brain state during stimulation. This study establishes a basis for considering brain state as a significant factor in designing treatment protocols, possibly improving TMS treatment outcomes.

Age-related changes in brain oscillatory patterns during an n-back task in children and adolescents

The development of brain oscillatory responses and their possible role in the working memory (WM) performance of children, adolescents and young adults was investigated. A set of 0- and 1-back tasks with letter stimuli were administered to a final sample of 131 subjects (between 6 and 20 years of age). A decrease in response times (RTs) and an increase of the sensitivity index d-prime (d') were seen with increased age. RTs increased and d' decreased with load, indicating higher difficulty for higher loads. Event-related synchronization (ERS) and event-related desynchronization (ERD) were obtained by the convolution of Morlet wavelets on the recorded EEG. Statistical analyses were performed of the absolute and relative power of brain oscillations defined by topography, frequency and latency. Posterior alpha and beta ERD, and frontocentral theta ERS, were induced by the stimuli presented during the n-back task. While relative theta ERS increased with age, absolute theta ERS, absolute and relative alpha and, absolute beta ERD, decreased with age. Age-related improvement in behavioral performance was mediated by relative theta. Alpha and beta ERD were more pronounced for the most difficult task (1-back) and for the target condition. Globally, there was high consistency of the effects of target type and task load across development. Theta ERS maturation is a crucial step for improving WM performance during development, while alpha and beta ERD maturation seem to be less critical for behavioral performance improvement with age, possibly due to a sufficient level of alpha-beta ERD for good performance in young children.

Event-related theta and gamma band oscillatory dynamics during visuo-spatial sequence memory in younger and older adults

Visuo-spatial working memory (VSWM) for sequences is thought to be crucial for daily behaviors. Decades of research indicate that oscillations in the gamma and theta bands play important functional roles in the support of visuo-spatial working memory, but the vast majority of that research emphasizes measures of neural activity during memory retention. The primary aims of the present study were (1) to determine whether oscillatory dynamics in the Theta and Gamma ranges would reflect item-level sequence encoding during a computerized spatial span task, (2) to determine whether item-level sequence recall is also related to these neural oscillations, and (3) to determine the nature of potential changes to these processes in healthy cognitive aging. Results indicate that VSWM sequence encoding is related to later (∼700 ms) gamma band oscillatory dynamics and may be preserved in healthy older adults; high gamma power over midline frontal and posterior sites increased monotonically as items were added to the spatial sequence in both age groups. Item-level oscillatory dynamics during the recall of VSWM sequences were related only to theta-gamma phase amplitude coupling (PAC), which increased monotonically with serial position in both age groups. Results suggest that, despite a general decrease in frontal theta power during VSWM sequence recall in older adults, gamma band dynamics during encoding and theta-gamma PAC during retrieval play unique roles in VSWM and that the processes they reflect may be spared in healthy aging.

Effect of homeostatic pressure and circadian arousal on the storage and executive components of working memory: Evidence from EEG power spectrum

Diurnal fluctuations in working memory (WM) performance, characterized by task-specific peaks and troughs, are likely attributed to the differential regulation of WM subcomponents by interactions between circadian and homeostatic processes. The current study aimed to investigate the independent effects of circadian and homeostatic processes on the storage and executive subcomponents of WM. We assessed the change in frontal-midline theta (FMT) power supporting WM executive component and posterior alpha/beta power supporting WM storage during N-back tasks in the morning, midafternoon with and without a nap from 31 healthy adults. The results suggested that when the accumulated sleep homeostasis was alleviated in the midafternoon by a daytime nap, higher ACC, less number of omissions, and a stronger increase in FMT power from the no nap to nap conditions. Compared to the morning, a stronger decrease in posterior alpha power, and posterior beta power (only in the 3-back task), was observed in the no-nap condition because of circadian arousal regulation. These findings suggest that the circadian process primarily influences the storage aspect of WM supported by posterior alpha and beta activity, while sleep homeostasis has a greater impact on the execution aspect supported by FMT activity.

A data-driven network decomposition of the temporal, spatial, and spectral dynamics underpinning visual-verbal working memory processes

The brain dynamics underlying working memory (WM) unroll via transient frequency-specific large-scale brain networks. This multidimensionality (time, space, and frequency) challenges traditional analyses. Through an unsupervised technique, the time delay embedded-hidden Markov model (TDE-HMM), we pursue a functional network analysis of magnetoencephalographic data from 38 healthy subjects acquired during an n-back task. Here we show that this model inferred task-specific networks with unique temporal (activation), spectral (phase-coupling connections), and spatial (power spectral density distribution) profiles. A theta frontoparietal network exerts attentional control and encodes the stimulus, an alpha temporo-occipital network rehearses the verbal information, and a broad-band frontoparietal network with a P300-like temporal profile leads the retrieval process and motor response. Therefore, this work provides a unified and integrated description of the multidimensional working memory dynamics that can be interpreted within the neuropsychological multi-component model of WM, improving the overall neurophysiological and neuropsychological comprehension of WM functioning.

Neural dynamics underlying successful auditory short-term memory performance

Listeners often operate in complex acoustic environments, consisting of many concurrent sounds. Accurately encoding and maintaining such auditory objects in short-term memory is crucial for communication and scene analysis. Yet, the neural underpinnings of successful auditory short-term memory (ASTM) performance are currently not well understood. To elucidate this issue, we presented a novel, challenging auditory delayed match-to-sample task while recording MEG. Human participants listened to 'scenes' comprising three concurrent tone pip streams. The task was to indicate, after a delay, whether a probe stream was present in the just-heard scene. We present three key findings: First, behavioural performance revealed faster responses in correct versus incorrect trials as well as in 'probe present' versus 'probe absent' trials, consistent with ASTM search. Second, successful compared with unsuccessful ASTM performance was associated with a significant enhancement of event-related fields and oscillatory activity in the theta, alpha and beta frequency ranges. This extends previous findings of an overall increase of persistent activity during short-term memory performance. Third, using distributed source modelling, we found these effects to be confined mostly to sensory areas during encoding, presumably related to ASTM contents per se. Parietal and frontal sources then became relevant during the maintenance stage, indicating that effective STM operation also relies on ongoing inhibitory processes suppressing task-irrelevant information. In summary, our results deliver a detailed account of the neural patterns that differentiate successful from unsuccessful ASTM performance in the context of a complex, multi-object auditory scene.

Investigating cortico-striatal beta oscillations in Parkinson's disease cognitive decline

This scientific commentary refers to ‘Corticostriatal beta oscillation changes associated with cognitive function in Parkinson’s disease’ by Paulo et al. (https://doi.org/10.1093/brain/awad206).

Differential working memory function between phonological and visuospatial strategies: a magnetoencephalography study using a same visual task

Previous studies have reported that, in working memory, the processing of visuospatial information and phonological information have different neural bases. However, in these studies, memory items were presented via different modalities. Therefore, the modality in which the memory items were presented and the strategy for memorizing them were not rigorously distinguished. In the present study, we explored the neural basis of two working memory strategies. Nineteen right-handed young adults memorized seven sequential directions presented visually in a task in which the memory strategy was either visuospatial or phonological (visuospatial/phonological condition). Source amplitudes of theta-band (5-7 Hz) rhythm were estimated from magnetoencephalography during the maintenance period and further analyzed using cluster-based permutation tests. Behavioral results revealed that the accuracy rates showed no significant differences between conditions, while the reaction time in the phonological condition was significantly longer than that in the visuospatial condition. Theta activity in the phonological condition was significantly greater than that in the visuospatial condition, and the cluster in spatio-temporal matrix with p < 5% difference extended to right prefrontal regions in the early maintenance period and right occipito-parietal regions in the late maintenance period. The theta activity results did not indicate strategy-specific neural bases but did reveal the dynamics of executive function required for phonological processing. The functions seemed to move from attention control and inhibition control in the prefrontal region to inhibition of irrelevant information in the occipito-parietal region.

Advances in Neurodegenerative Diseases

Neurological disorders are the leading cause of physical and cognitive disability across the globe, currently affecting approximately 15% of the worldwide population [...].

Temporary amnesia from sleep loss: A framework for understanding consequences of sleep deprivation

Throughout its modern history, sleep research has been concerned with both the benefits of sleep and the deleterious impact of sleep disruption for cognition, behavior, and performance. When more specifically examining the impact of sleep on memory and learning, however, research has overwhelmingly focused on how sleep following learning facilitates memory, with less attention paid to how lack of sleep prior to learning can disrupt subsequent memory. Although this imbalance in research emphasis is being more frequently addressed by current investigators, there is a need for a more organized approach to examining the effect of sleep deprivation before learning. The present review briefly describes the generally accepted approach to analyzing effects of sleep deprivation on subsequent memory and learning by means of its effects on encoding. Then, we suggest an alternative framework with which to understand sleep loss and memory in terms of temporary amnesia from sleep loss (TASL). The review covers the well-characterized properties of amnesia arising from medial temporal lobe lesions and shows how the pattern of preserved and impaired aspects of memory in amnesia may also be appearing during sleep loss. The view of the TASL framework is that amnesia and the amnesia-like deficits observed during sleep deprivation not only affect memory processes but will also be apparent in cognitive processes that rely on those memory processes, such as decision-making. Adoption of the TASL framework encourages movement away from traditional explanations based on narrowly defined domains of memory functioning, such as encoding, and taking instead a more expansive view of how brain structures that support memory, such as the hippocampus, interact with higher structures, such as the prefrontal cortex, to produce complex cognition and behavioral performance, and how this interaction may be compromised by sleep disruption.

Robust estimation of 1/f activity improves oscillatory burst detection

Neural oscillations often occur as transient bursts with variable amplitude and frequency dynamics. Quantifying these effects is important for understanding brain-behaviour relationships, especially in continuous datasets. To robustly measure bursts, rhythmical periods of oscillatory activity must be separated from arrhythmical background 1/f activity, which is ubiquitous in electrophysiological recordings. The Better OSCillation (BOSC) framework achieves this by defining a power threshold above the estimated background 1/f activity, combined with a duration threshold. Here we introduce a modification to this approach called fBOSC, which uses a spectral parametrisation tool to accurately model background 1/f activity in neural data. fBOSC (which is openly available as a MATLAB toolbox) is robust to power spectra with oscillatory peaks and can also model non-linear spectra. Through a series of simulations, we show that fBOSC more accurately models the 1/f power spectrum compared with existing methods. fBOSC was especially beneficial where power spectra contained a 'knee' below ~.5-10 Hz, which is typical in neural data. We also found that, unlike other methods, fBOSC was unaffected by oscillatory peaks in the neural power spectrum. Moreover, by robustly modelling background 1/f activity, the sensitivity for detecting oscillatory bursts was standardised across frequencies (e.g., theta- and alpha-bands). Finally, using openly available resting state magnetoencephalography and intracranial electrophysiology datasets, we demonstrate the application of fBOSC for oscillatory burst detection in the theta-band. These simulations and empirical analyses highlight the value of fBOSC in detecting oscillatory bursts, including in datasets that are long and continuous with no distinct experimental trials.

Cognitive-motor telerehabilitation in multiple sclerosis (CoMoTeMS): study protocol for a randomised controlled trial

Background

The management of cognitive impairment is an important goal in the treatment of multiple sclerosis (MS). While cognitive rehabilitation has been proven to be effective in improving cognitive performance in MS, research in the elderly indicates a higher effectiveness of combined cognitive-motor rehabilitation. Here, we present the protocol of a randomised controlled clinical trial to assess whether a combined cognitive-motor telerehabilitation programme is more effective in improving working memory than only cognitive or motor training.

Methods/design

The CoMoTeMS-trial is a two-centre, randomised, controlled and blinded clinical trial. A total of 90 patients with MS will receive 12 weeks of either a combined cognitive-motor telerehabilitation programme or only cognitive or motor training. The primary outcome is a change in the digit span backwards. Secondary outcomes are other cognitive changes (Brief International Cognitive Assessment for Multiple Sclerosis and Backward Corsi), Expanded Disability Status Scale (EDSS), 6-Min Walk Test, 25-Foot Walk Test, 9-Hole Peg Test, anxiety and depression, fatigue, quality of life, cognitive and physical activity level, electroencephalography and magnetic resonance imaging of the brain.

Discussion

We hypothesise that the improvement in digit span backwards after 12 weeks of treatment will be significantly higher in the group treated with the combined cognitive-motor telerehabilitation programme, compared to the groups receiving only cognitive and only motor training.

Trial registration

ClinicalTrials.gov NCT05355389. Registered on 2 May 2022.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06697-9.

Associations between abstract working memory abilities and brain activity underlying long-term recognition of auditory sequences

Memory is a complex cognitive process composed of several subsystems, namely short- and long-term memory and working memory (WM). Previous research has shown that adequate interaction between subsystems is crucial for successful memory processes such as encoding, storage, and manipulation of information. However, few studies have investigated the relationship between different subsystems at the behavioral and neural levels. Thus, here we assessed the relationship between individual WM abilities and brain activity underlying the recognition of previously memorized auditory sequences. First, recognition of previously memorized versus novel auditory sequences was associated with a widespread network of brain areas comprising the cingulate gyrus, hippocampus, insula, inferior temporal cortex, frontal operculum, and orbitofrontal cortex. Second, we observed positive correlations between brain activity underlying auditory sequence recognition and WM. We showed a sustained positive correlation in the medial cingulate gyrus, a brain area that was widely involved in the auditory sequence recognition. Remarkably, we also observed positive correlations in the inferior temporal, temporal-fusiform, and postcentral gyri, brain areas that were not strongly associated with auditory sequence recognition. In conclusion, we discovered positive correlations between WM abilities and brain activity underlying long-term recognition of auditory sequences, providing new evidence on the relationship between memory subsystems. Furthermore, we showed that high WM performers recruited a larger brain network including areas associated with visual processing (i.e., inferior temporal, temporal-fusiform, and postcentral gyri) for successful auditory memory recognition.

Magnetoencephalography can reveal deep brain network activities linked to memory processes

Recording from deep neural structures such as hippocampus noninvasively and yet with high temporal resolution remains a major challenge for human neuroscience. Although it has been proposed that deep neuronal activity might be recordable during cognitive tasks using magnetoencephalography (MEG), this remains to be demonstrated as the contribution of deep structures to MEG recordings may be too small to be detected or might be eclipsed by the activity of large‐scale neocortical networks. In the present study, we disentangled mesial activity and large‐scale networks from the MEG signals thanks to blind source separation (BSS). We then validated the MEG BSS components using intracerebral EEG signals recorded simultaneously in patients during their presurgical evaluation of epilepsy. In the MEG signals obtained during a memory task involving the recognition of old and new images, we identified with BSS a putative mesial component, which was present in all patients and all control subjects. The time course of the component selectively correlated with stereo‐electroencephalography signals recorded from hippocampus and rhinal cortex, thus confirming its mesial origin. This finding complements previous studies with epileptic activity and opens new possibilities for using MEG to study deep brain structures in cognition and in brain disorders.

Brain age as a surrogate marker for cognitive performance in multiple sclerosis

Background and purpose

Data from neuro‐imaging techniques allow us to estimate a brain's age. Brain age is easily interpretable as ‘how old the brain looks’ and could therefore be an attractive communication tool for brain health in clinical practice. This study aimed to investigate its clinical utility by investigating the relationship between brain age and cognitive performance in multiple sclerosis (MS).

Methods

A linear regression model was trained to predict age from brain magnetic resonance imaging volumetric features and sex in a healthy control dataset (HC_train, n = 1673). This model was used to predict brain age in two test sets: HC_test (n = 50) and MS_test (n = 201). Brain‐predicted age difference (BPAD) was calculated as BPAD = brain age minus chronological age. Cognitive performance was assessed by the Symbol Digit Modalities Test (SDMT).

Results

Brain age was significantly related to SDMT scores in the MS_test dataset (r = −0.46, p < 0.001) and contributed uniquely to variance in SDMT beyond chronological age, reflected by a significant correlation between BPAD and SDMT (r = −0.24, p < 0.001) and a significant weight (−0.25, p = 0.002) in a multivariate regression equation with age.

Conclusions

Brain age is a candidate biomarker for cognitive dysfunction in MS and an easy to grasp metric for brain health.

Age of onset modulates resting-state brain network dynamics in Friedreich Ataxia

This magnetoencephalography (MEG) study addresses (i) how Friedreich ataxia (FRDA) affects the sub‐second dynamics of resting‐state brain networks, (ii) the main determinants of their dynamic alterations, and (iii) how these alterations are linked with FRDA‐related changes in resting‐state functional brain connectivity (rsFC) over long timescales. For that purpose, 5 min of resting‐state MEG activity were recorded in 16 FRDA patients (mean age: 27 years, range: 12–51 years; 10 females) and matched healthy subjects. Transient brain network dynamics was assessed using hidden Markov modeling (HMM). Post hoc median‐split, nonparametric permutations and Spearman rank correlations were used for statistics. In FRDA patients, a positive correlation was found between the age of symptoms onset (ASO) and the temporal dynamics of two HMM states involving the posterior default mode network (DMN) and the temporo‐parietal junctions (TPJ). FRDA patients with an ASO <11 years presented altered temporal dynamics of those two HMM states compared with FRDA patients with an ASO > 11 years or healthy subjects. The temporal dynamics of the DMN state also correlated with minute‐long DMN rsFC. This study demonstrates that ASO is the main determinant of alterations in the sub‐second dynamics of posterior associative neocortices in FRDA patients and substantiates a direct link between sub‐second network activity and functional brain integration over long timescales.

Alterations in brain structure and function in patients with osteonecrosis of the femoral head: a multimodal MRI study

Background

Pain, a major symptom of osteonecrosis of the femoral head (ONFH), is a complex sensory and emotional experience that presents therapeutic challenges. Pain can cause neuroplastic changes at the cortical level, leading to central sensitization and difficulties with curative treatments; however, whether changes in structural and functional plasticity occur in patients with ONFH remains unclear.

Methods

A total of 23 ONFH inpatients who did not undergo surgery (14 males, nine females; aged 55.61 ± 13.79 years) and 20 controls (12 males, eight females; aged 47.25 ± 19.35 years) were enrolled. Functional indices of the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and a structural index of tract-based spatial statistics (TBSS) were calculated for each participant. The probability distribution of fiber direction was determined according to the ALFF results.

Results

ONFH patients demonstrated increased ALFF in the bilateral dorsolateral superior frontal gyrus, right medial superior frontal gyrus, right middle frontal gyrus, and right supplementary motor area. In contrast, ONFH patients showed decreased ReHo in the left superior parietal gyrus and right inferior temporal gyrus. There were no significant differences in TBSS or probabilistic tractography.

Conclusion

These results indicate cerebral pain processing in ONFH patients. It is advantageous to use functional magnetic resonance imaging to better understand pain pathogenesis and identify new therapeutic targets in ONFH patients.

Testing covariance models for MEG source reconstruction of hippocampal activity

Beamforming is one of the most commonly used source reconstruction methods for magneto- and electroencephalography (M/EEG). One underlying assumption, however, is that distant sources are uncorrelated and here we tested whether this is an appropriate model for the human hippocampal data. We revised the Empirical Bayesian Beamfomer (EBB) to accommodate specific a-priori correlated source models. We showed in simulation that we could use model evidence (as approximated by Free Energy) to distinguish between different correlated and uncorrelated source scenarios. Using group MEG data in which the participants performed a hippocampal-dependent task, we explored the possibility that the hippocampus or the cortex or both were correlated in their activity across hemispheres. We found that incorporating a correlated hippocampal source model significantly improved model evidence. Our findings help to explain why, up until now, the majority of MEG-reported hippocampal activity (typically making use of beamformers) has been estimated as unilateral.

Local Functional MR Change Pattern and Its Association With Cognitive Function in Objectively-Defined Subtle Cognitive Decline

Introduction: To identify individuals with preclinical cognitive impairment, researchers proposed the concept of objectively-defined subtle cognitive decline (Obj-SCD). However, it is not clear whether Obj-SCD has characteristic brain function changes. In this study, we aimed at exploring the changing pattern of brain function activity in Obj-SCD individuals and the similarities and differences with mild cognitive impairments (MCI). Method: 37 healthy control individuals, 25 Obj-SCD individuals (with the impairment in memory and language domain), and 28 aMCI individuals were included. Resting-state fMRI and neuropsychological tests were performed. fALFF was used to reflect the local functional activity and compared between groups. Finally, we analyzed the correlation between the fALFF values of significantly changed regions and neuropsychological performance. Results: We found similar functional activity enhancements in some local brain regions in the Obj-SCD and aMCI groups, including the left orbital part of the inferior frontal gyrus and the left median cingulate and paracingulate gyri. However, some changes in local functional activities of the Obj-SCD group showed different patterns from the aMCI group. Compared with healthy control (HC), the Obj-SCD group showed increased local functional activity in the right middle occipital gyrus, decreased local functional activity in the left precuneus and the left inferior temporal gyrus. In the Obj-SCD group, in normal band, the fALFF value of the right middle occipital gyrus was significantly negatively correlated with Mini-Mental State Examination (MMSE) score (r = -0.450, p = 0.024) and Animal Verbal Fluency Test (AFT) score (r = -0.402, p = 0.046); the left inferior temporal gyrus was significantly positively correlated with MMSE score (r = 0.588, p = 0.002). In slow-4 band, the fALFF value of the left precuneus was significantly positively correlated with MMSE score (r = 0.468, p = 0.018) and AFT score (r = 0.600, p = 0.002). In the aMCI group, the fALFF value of the left orbital part of the inferior frontal gyrus was significantly positively correlated with Auditory Verbal Learning Test (AVLT) long delay cued recall score (r = 0.506, p = 0.006). Conclusion: The Obj-SCD group showed a unique changing pattern; the functional changes of different brain regions have a close but different correlation with cognitive impairment, indicating that there may be a complex pathological basis inside. This suggests that Obj-SCD may be a separate stage of cognitive decline before aMCI and is helpful to the study of preclinical cognitive decline.

The role of hippocampal theta oscillations in working memory impairment in multiple sclerosis

Working memory (WM) problems are frequently present in people with multiple sclerosis (MS). Even though hippocampal damage has been repeatedly shown to play an important role, the underlying neurophysiological mechanisms remain unclear. This study aimed to investigate the neurophysiological underpinnings of WM impairment in MS using magnetoencephalography (MEG) data from a visual-verbal 2-back task. We analysed MEG recordings of 79 MS patients and 38 healthy subjects through event-related fields and theta (4-8 Hz) and alpha (8-13 Hz) oscillatory processes. Data was source reconstructed and parcellated based on previous findings in the healthy subject sample. MS patients showed a smaller maximum theta power increase in the right hippocampus between 0 and 400 ms than healthy subjects (p = .014). This theta power increase value correlated negatively with reaction time on the task in MS (r = -.32, p = .029). Evidence was provided that this relationship could not be explained by a 'common cause' confounding relationship with MS-related neuronal damage. This study provides the first neurophysiological evidence of the influence of hippocampal dysfunction on WM performance in MS.

Effects of Sleep Deprivation on Working Memory: Change in Functional Connectivity Between the Dorsal Attention, Default Mode, and Fronto-Parietal Networks

Sleep deprivation (SD) is very common in modern society and has a profound effect on cognitive function, in particular on working memory (WM). This type of memory is required for completion of many tasks and is adversely affected by SD. However, the cognitive neural mechanism by which SD affects WM, remains unclear. In this study, we investigated the changes in the brain network involved in WM after SD. Twenty-two healthy subjects underwent functional magnetic resonance imaging scan while in a state of resting wakefulness and again after 36 h of total SD and performed a WM task before each scanning session. Nineteen main nodes of the default mode network (DMN), dorsal attention network (DAN), fronto-parietal network (FPN), salience network (SN), and other networks were selected for functional analysis of brain network connections. Functional connectivity measures were computed between seed areas for region of interest (ROI)-to-ROI analysis and to identify patterns of ROI-to-ROI connectivity. The relationship between the significant changes in functional connectivity in the brain network and WM performance were then examined by Pearson's correlation analysis. WM performance declined significantly after SD. Compared with the awake state, the functional connectivity between DAN and DMN significantly increased after SD while that between FPN and DMN significantly decreased. Correlation analysis showed that the enhanced functional connectivity between DAN and DMN was negatively correlated with the decline in WM performance and that the decline in functional connectivity between FPN and DMN was positively correlated with decreased WM performance. These findings suggested that SD may affect WM by altering the functional connectivity among DMN, DAN, and FPN.

Spatiotemporal and spectral dynamics of multi-item working memory as revealed by the n-back task using MEG

Multi‐item working memory (WM) is a complex cognitive function thought to arise from specific frequency band oscillations and their interactions. While some theories and consistent findings have been established, there is still a lot of unclarity about the sources, temporal dynamics, and roles of event‐related fields (ERFs) and theta, alpha, and beta oscillations during WM activity. In this study, we performed an extensive whole‐brain ERF and time‐frequency analysis on n‐back magnetoencephalography data from 38 healthy controls. We identified the previously unknown sources of the n‐back M300, the right inferior temporal and parahippocampal gyrus and left inferior temporal gyrus, and frontal theta power increase, the orbitofrontal cortex. We shed new light on the role of the precuneus during n‐back activity, based on an early ERF and theta power increase, and suggest it to be a crucial link between lower‐level and higher‐level information processing. In addition, we provide strong evidence for the central role of the hippocampus in multi‐item WM behavior through the dynamics of theta and alpha oscillatory changes. Almost simultaneous alpha power decreases observed in the hippocampus and occipital fusiform gyri, regions known to be involved in letter processing, suggest that these regions together enable letter recognition, encoding and storage in WM. In summary, this study offers an extensive investigation into the spatial, temporal, and spectral characteristics of n‐back multi‐item WM activity.