Medial temporal lobe BOLD activity at rest predicts individual differences in memory ability in healthy young adults

Impaired odor recognition memory in Parkinson's disease linked to absent functional hippocampal asymmetry

Odor recognition memory (ORM) combines olfaction and episodic memory, both linked to dementia and impaired in Parkinson's Disease (PD). Measuring ORM may indicate early PD dementia and aid in selecting device-aided Parkinson therapy. This study investigates ORM capacity and hippocampal dynamic functional connectivity in PD. Thirty-one PD participants and 31 healthy controls (HC) underwent functional MRI during an ORM task. Co-activation pattern analysis identified active hippocampal networks. The PD group showed impaired ORM and a sequence of four activated hippocampal networks. The fourth network, involving the dorsal Attention Network (dAN), had fewer and shorter expressions during correct ORM responses in PD compared with HC. Hippocampal functional asymmetry was observed in HC but not in PD. These findings suggest that impaired ORM in PD is linked to reduced hippocampal functional asymmetry. Future research should explore differences in functional dynamics of odor memory-related brain regions in PD patients with and without cognitive decline.

Heterogenous brain activations across individuals localize to a common network

Task functional magnetic resonance imaging research has generally shielded away from studying individuals due to the low reproducibility. Here, we propose that heterogeneous brain activations across individuals localize to a common network. To test this hypothesis, we use working memory (WM) as our example. First, we showed that discrete-brain-based reproducibility of brain activation during WM across individuals was low. Then, we used activation network mapping (ANM) technique to identify each individual's brain network of WM and found that network-based reproducibility was rather high. Prediction analyses using machine learning algorithms indicated that individual WM networks identified via ANM can predict WM behavioral performance. This predictive ability even outperformed that of brain activations. Our study provides a new explanation on the low reproducibility of brain activations across individuals. The results suggest that ANM can be used to identify individual brain networks of cognitive processes, thus promising broad potential applications.

Similarity of brain activity patterns during learning and subsequent resting state predicts memory consolidation

Spontaneous reactivation of brain activity from learning to a subsequent off-line period has been implicated as a neural mechanism underlying memory consolidation. However, similarities in brain activity may also emerge as a result of individual, trait-like characteristics. Here, we introduced a novel approach for analyzing continuous electroencephalography (EEG) data to investigate learning-induced changes as well as trait-like characteristics in brain activity underlying memory consolidation. Thirty-one healthy young adults performed a learning task, and their performance was retested after a short (∼1 h) delay. Consolidation of two distinct types of information (serial-order and probability) embedded in the task were tested to reveal similarities in functional networks that uniquely predict the changes in the respective memory performance. EEG was recorded during learning and pre- and post-learning rest periods. To investigate brain activity associated with consolidation, we quantified similarities in EEG functional connectivity between learning and pre-learning rest (baseline similarity) and learning and post-learning rest (post-learning similarity). While comparable patterns of these two could indicate trait-like similarities, changes from baseline to post-learning similarity could indicate learning-induced changes, possibly spontaneous reactivation. Higher learning-induced changes in alpha frequency connectivity (8.5-9.5 Hz) were associated with better consolidation of serial-order information, particularly for long-range connections across central and parietal sites. The consolidation of probability information was associated with learning-induced changes in delta frequency connectivity (2.5-3 Hz) specifically for more local, short-range connections. Furthermore, there was a substantial overlap between the baseline and post-learning similarities and their associations with consolidation performance, suggesting robust (trait-like) differences in functional connectivity networks underlying memory processes.

Intersubject similarity in neural representations underlies shared episodic memory content

Individuals generally form their unique memories from shared experiences, yet the neural representational mechanisms underlying this subjectiveness of memory are poorly understood. The current study addressed this important question from the cross-subject neural representational perspective, leveraging a large functional magnetic resonance imaging dataset (n = 415) of a face-name associative memory task. We found that individuals' memory abilities were predicted by their synchronization to the group-averaged, canonical trial-by-trial activation level and, to a lesser degree, by their similarity to the group-averaged representational patterns during encoding. More importantly, the memory content shared between pairs of participants could be predicted by their shared local neural activation pattern, particularly in the angular gyrus and ventromedial prefrontal cortex, even after controlling for differences in memory abilities. These results uncover neural representational mechanisms for individualized memory and underscore the constructive nature of episodic memory.

Individual differences in sensory processing sensitivity amplify effects of post-learning activity for better and for worse

Sensory processing sensitivity (SPS) is a biologically-based trait associated with greater reactivity to both positive and negative environments. Recent studies suggest that the activity following learning can support or hinder memory retention. Here, we employed a within-subject experiment to examine whether and how individual differences in SPS contribute to differences in memory retention. Sixty-four participants encoded and immediately recalled two word lists: one followed by 8-min of eyes-closed, wakeful resting; and the other by a distraction task. After 7 days, participants completed a surprise free recall test for both word lists. If participants wakefully rested after encoding, memory retention increased as a function of higher SPS. However, in the distraction condition, a negative curvilinear relationship indicated that memory retention was especially hindered for highly sensitive individuals. These results suggest that individual differences in SPS are an important factor to consider when examining the effects of environmental conditions on learning and memory.

Cognitive Aging: How the Brain Ages?

Cognitive aging refers to the cognitive changes or functional decline that comes with age. The relation between aging and functional declines involves various aspects of cognition, including memory, attention, processing speed, and executive function. In this chapter, we have introduced several dimensions about cognitive aging trajectories. Meanwhile, we have reviewed the history of the study of cognitive aging and expatiated two trends that are particularly noteworthy in the effort to elucidate the process of aging. One is that the differences between components of mental abilities have become gradually specified. The other one is a growing interest in the neural process, which relates changes in the brain structure to age-related changes in cognition. Lastly, as the basis of cognitive function, brain structures and functions change during aging, and these changes are reflected in a corresponding decline in cognitive function. We have discussed the patterns of reorganization of various structural and functional aging processes of the brain and their relationship with cognitive function.

Fornix alterations induce the disruption of default mode network in patients with adamantinomatous craniopharyngiomas

Adamantinomatous craniopharyngioma (ACPs) are rare embryonic tumors and often involve the hypothalamus. The underlying neural substrate of the hypothalamic involvement (HI)-related cognitive decline in patients with ACP is still unclear. We aimed to combine the multi-modal neuroimaging and histological characteristics of the ACP to explore the potential neural substrate of the HI-related cognitive decline. 45 patients with primary ACPs (invasive, 23; noninvasive, 22) and 52 healthy control subjects (HCs) were admitted to the cross-sectional study. No significant difference in cognitive domains was observed between HCs and patients with noninvasive ACPs (NACP). Patients with invasive ACPs (IACP) showed significantly lower working memory performance (WM, p = 0.002) than patients with NACP. The WM decline was correlated with the disruption of the medial temporal lobe (MTL) subsystem in the default mode network (DMN) (r = 0.45, p = 0.004). The increased radial diffusivity of the fornix, indicating demyelinating process, was correlated with the disruption of the MTL subsystem (r = -0.48, p = 0.002). Our study demonstrated that the fornix alterations link DMN disruption to HI-related cognitive decline in patients with ACPs. ACPs that invade the hypothalamus can provide a natural disease model to investigate the potential neural substrate of HI-related cognitive decline.

Young Adults with a Parent with Dementia Show Early Abnormalities in Brain Activity and Brain Volume in the Hippocampus: A Matched Case-Control Study

Having a parent with Alzheimer’s disease (AD) and related dementias confers a risk for developing these types of neurocognitive disorders in old age, but the mechanisms underlying this risk are understudied. Although the hippocampus is often one of the earliest brain regions to undergo change in the AD process, we do not know how early in the lifespan such changes might occur or whether they differ early in the lifespan as a function of family history of AD. Using a rare sample, young adults with a parent with late-onset dementia, we investigated whether brain abnormalities could already be detected compared with a matched sample. Moreover, we employed simple yet novel techniques to characterize resting brain activity (mean and standard deviation) and brain volume in the hippocampus. Young adults with a parent with dementia showed greater resting mean activity and smaller volumes in the left hippocampus compared to young adults without a parent with dementia. Having a parent with AD or a related dementia was associated with early aberrations in brain function and structure. This early hippocampal dysfunction may be due to aberrant neural firing, which may increase the risk for a diagnosis of dementia in old age.

Large-scale functional brain networks for consciousness

The generation and maintenance of consciousness are fundamental but difficult subjects in the fields of psychology, philosophy, neuroscience, and medicine. However, recent developments in neuro-imaging techniques coupled with network analysis have greatly advanced our understanding of consciousness. The present review focuses on large-scale functional brain networks based on neuro-imaging data to explain the awareness (contents) and wakefulness of consciousness. Despite limitations, neuroimaging data suggests brain maps for important psychological and cognitive processes such as attention, language, self-referential, emotion, motivation, social behavior, and wakefulness. We considered a review of these advancements would provide new insights into research on the neural correlates of consciousness.

Default-mode network streams for coupling to language and control systems

The human brain is organized into large-scale networks identifiable using resting-state functional connectivity (RSFC). These functional networks correspond with broad cognitive domains; for example, the Default-mode network (DMN) is engaged during internally oriented cognition. However, functional networks may contain hierarchical substructures corresponding with more specific cognitive functions. Here, we used individual-specific precision RSFC to test whether network substructures could be identified in 10 healthy human brains. Across all subjects and networks, individualized network subdivisions were more valid-more internally homogeneous and better matching spatial patterns of task activation-than canonical networks. These measures of validity were maximized at a hierarchical scale that contained ∼83 subnetworks across the brain. At this scale, nine DMN subnetworks exhibited topographical similarity across subjects, suggesting that this approach identifies homologous neurobiological circuits across individuals. Some DMN subnetworks matched known features of brain organization corresponding with cognitive functions. Other subnetworks represented separate streams by which DMN couples with other canonical large-scale networks, including language and control networks. Together, this work provides a detailed organizational framework for studying the DMN in individual humans.

Reconstruction of behavior-relevant individual brain activity: an individualized fMRI study

Different patterns of brain activity are observed in various subjects across a wide functional domain. However, these individual differences, which are often neglected through the group average, are not yet completely understood. Based on the fundamental assumption that human behavior is rooted in the underlying brain function, we speculated that the individual differences in brain activity are reflected in the individual differences in behavior. Adopting 98 behavioral measures and assessing the brain activity induced at seven task functional magnetic resonance imaging states, we demonstrated that the individual differences in brain activity can be used to predict behavioral measures of individual subjects with high accuracy using the partial least square regression model. In addition, we revealed that behavior-relevant individual differences in brain activity transferred between different task states and can be used to reconstruct individual brain activity. Reconstructed individual brain activity retained certain individual differences which were lost in the group average and could serve as an individual functional localizer. Therefore, our results suggest that the individual differences in brain activity contain behavior-relevant information and should be included in group averaging. Moreover, reconstructed individual brain activity shows a potential use in precise and personalized medicine.

Primary Disruption of the Memory-Related Subsystems of the Default Mode Network in Alzheimer's Disease: Resting-State Functional Connectivity MRI Study

Background: Recent studies have indicated that the default mode network (DMN) comprises at least three subsystems: The medial temporal lobe (MTL) and dorsal medial prefrontal cortex (DMPFC) subsystems and a core comprising the anterior MPFC (aMPFC) and posterior cingulate cortex (PCC). Additionally, the disruption of the DMN is related to Alzheimer’s disease (AD). However, little is known regarding the changes in these subsystems in AD, a progressive disease characterized by memory impairment. Here, we performed a resting-state functional connectivity (FC) analysis to test our hypothesis that the memory-related MTL subsystem was predominantly disrupted in AD.

Method: To reveal specific subsystem changes, we calculated the strength and number of FCS in the DMN intra- and inter-subsystems across individuals and compared the FC of the two groups. To further examine which pairs of brain regional functional connections contributed to the subsystem alterations, correlation coefficients between any two brain regions in the DMN were compared across groups. Additionally, to identify which regions made the strongest contributions to the subsystem changes, we calculated the regional FC strength (FCS), which was compared across groups.

Results: For the intra-subsystem, decreased FC number and strength occurred in the MTL subsystem of AD patients but not in the DMPFC subsystem or core. For the inter-subsystems, the AD group showed decreased FCS and number between the MTL subsystem and PCC and a decreased number between the PCC and DMPFC subsystem. Decreased inter-regional FCS were found within the MTL subsystem in AD patients relative to controls: The posterior inferior parietal lobule (pIPL) showed decreased FC with the hippocampal formation (HF), parahippocampal cortex (PHC) and ventral MPFC (vMPFC). Decreased inter-regional FCS of the inter-subsystems were also found in AD patients: The HF and/or PHC showed decreased FC with dMPFC and TPJ, located in the DMPFC subsystem, and with PCC. AD patients also showed decreased FC between the PCC and TLC of the dMPFC subsystem. Furthermore, the HF and PHC in the MTL subsystem showed decreased regional FCS.

Conclusion: Decreased intrinsic FC was mainly associated with the MTL subsystem of the AD group, suggesting that the MTL subsystem is predominantly disrupted.

Knowledge acquisition is governed by striatal prediction errors

Discrepancies between expectations and outcomes, or prediction errors, are central to trial-and-error learning based on reward and punishment, and their neurobiological basis is well characterized. It is not known, however, whether the same principles apply to declarative memory systems, such as those supporting semantic learning. Here, we demonstrate with fMRI that the brain parametrically encodes the degree to which new factual information violates expectations based on prior knowledge and beliefs-most prominently in the ventral striatum, and cortical regions supporting declarative memory encoding. These semantic prediction errors determine the extent to which information is incorporated into long-term memory, such that learning is superior when incoming information counters strong incorrect recollections, thereby eliciting large prediction errors. Paradoxically, by the same account, strong accurate recollections are more amenable to being supplanted by misinformation, engendering false memories. These findings highlight a commonality in brain mechanisms and computational rules that govern declarative and nondeclarative learning, traditionally deemed dissociable.

Interpreting and Utilising Intersubject Variability in Brain Function

We consider between-subject variance in brain function as data rather than noise. We describe variability as a natural output of a noisy plastic system (the brain) where each subject embodies a particular parameterisation of that system. In this context, variability becomes an opportunity to: (i) better characterise typical versus atypical brain functions; (ii) reveal the different cognitive strategies and processing networks that can sustain similar tasks; and (iii) predict recovery capacity after brain damage by taking into account both damaged and spared processing pathways. This has many ramifications for understanding individual learning preferences and explaining the wide differences in human abilities and disabilities. Understanding variability boosts the translational potential of neuroimaging findings, in particular in clinical and educational neuroscience.

Bimanual coordination positively predicts episodic memory: A combined behavioral and MRI investigation

Some people remember events more completely and accurately than other people, but the origins of individual differences in episodic memory are poorly understood. One way to advance understanding is by identifying characteristics of individuals that reliably covary with memory performance. Recent research suggests motor behavior is related to memory performance, with individuals who consistently use a single preferred hand for unimanual actions performing worse than individuals who make greater use of both hands. This research has relied on self-reports of behavior. It is unknown whether objective measures of motor behavior also predict memory performance. Here, we tested the predictive power of bimanual coordination, an important form of manual dexterity. Bimanual coordination, as measured objectively on the Purdue Pegboard Test, was positively related to correct recall on the California Verbal Learning Test-II and negatively related to false recall. Furthermore, MRI data revealed that cortical surface area in right lateral prefrontal regions was positively related to correct recall. In one of these regions, cortical thickness was negatively related to bimanual coordination. These results suggest that individual differences in episodic memory may partially reflect morphological variation in right lateral prefrontal cortex and suggest a relationship between neural correlates of episodic memory and motor behavior.

Clinical Concepts Emerging from fMRI Functional Connectomics

Recent advances in connectomics have led to a synthesis of perspectives regarding the brain's functional organization that reconciles classical concepts of localized specialization with an appreciation for properties that emerge from interactions across distributed functional networks. This provides a more comprehensive framework for understanding neural mechanisms of normal cognition and disease. Although fMRI has not become a routine clinical tool, research has already had important influences on clinical concepts guiding diagnosis and patient management. Here we review illustrative examples. Studies demonstrating the network plasticity possible in adults and the global consequences of even focal brain injuries or disease both have had substantial impact on modern concepts of disease evolution and expression. Applications of functional connectomics in studies of clinical populations are challenging traditional disease classifications and helping to clarify biological relationships between clinical syndromes (and thus also ways of extending indications for, or "re-purposing," current treatments). Large datasets from prospective, longitudinal studies promise to enable the discovery and validation of functional connectomic biomarkers with the potential to identify people at high risk of disease before clinical onset, at a time when treatments may be most effective. Studies of pain and consciousness have catalyzed reconsiderations of approaches to clinical management, but also have stimulated debate about the clinical meaningfulness of differences in internal perceptual or cognitive states inferred from functional connectomics or other physiological correlates. By way of a closing summary, we offer a personal view of immediate challenges and potential opportunities for clinically relevant applications of fMRI-based functional connectomics.

Decoupling of large-scale brain networks supports the consolidation of durable episodic memories

At a large scale, the human brain is organized into modules of interconnected regions, some of which play opposing roles in supporting cognition. In particular, the Default-Mode Network (DMN) has been linked to operations on internal representations, while task-positive networks are recruited during interactions with the external world. Here, we test the hypothesis that the generation of durable long-term memories depends on optimal recruitment of such antagonistic large-scale networks. As long-term memory consolidation is a process ongoing for days and weeks after an experience, we propose that individuals characterized by strong decoupling of the DMN and task-positive networks at rest operate in a mode beneficial for the long-term stabilization of episodic memories. To capture network connectivity unaffected by transient task demands and representative of brain behavior outside an experimental setting, 87 participants were scanned during rest before performing an associative encoding task. To link individual resting-state functional connectivity patterns to time-dependent memory consolidation processes, participants were given an unannounced memory test, either after a brief interval or after a retention period of ~6 weeks. We found that participants with a resting state characterized by high synchronicity in a DMN-centered network system and low synchronicity between task-positive networks showed superior recollection weeks after encoding. These relationships were not observed for information probed only hours after encoding. Furthermore, the two network systems were found to be anticorrelated. Our results suggest that this memory-relevant antagonism between DMN and task-positive networks is maintained through complex regulatory interactions between the systems.

Task-free MRI predicts individual differences in brain activity during task performance

When asked to perform the same task, different individuals exhibit markedly different patterns of brain activity. This variability is often attributed to volatile factors, such as task strategy or compliance. We propose that individual differences in brain responses are, to a large degree, inherent to the brain and can be predicted from task-independent measurements collected at rest. Using a large set of task conditions, spanning several behavioral domains, we train a simple model that relates task-independent measurements to task activity and evaluate the model by predicting task activation maps for unseen subjects using magnetic resonance imaging. Our model can accurately predict individual differences in brain activity and highlights a coupling between brain connectivity and function that can be captured at the level of individual subjects.

Abnormal resting-state functional connectivity within the default mode network subregions in male patients with obstructive sleep apnea

BACKGROUND AND OBJECTIVE

Abnormal resting-state functional connectivity (rs-FC) between the central executive network and the default mode network (DMN) in patients with obstructive sleep apnea (OSA) has been reported. However, the effect of OSA on rs-FC within the DMN subregions remains uncertain. This study was designed to investigate whether the rs-FC within the DMN subregions was disrupted and determine its relationship with clinical symptoms in patients with OSA.

METHODS

Forty male patients newly diagnosed with severe OSA and 40 male education- and age-matched good sleepers (GSs) underwent functional magnetic resonance imaging (fMRI) examinations and clinical and neuropsychologic assessments. Seed-based region of interest rs-FC method was used to analyze the connectivity between each pair of subregions within the DMN, including the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), hippocampus formation (HF), inferior parietal cortices (IPC), and medial temporal lobe (MTL). The abnormal rs-FC strength within the DMN subregions was correlated with clinical and neuropsychologic assessments using Pearson correlation analysis in patients with OSA.

RESULTS

Compared with GSs, patients with OSA had significantly decreased rs-FC between the right HF and the PCC, MPFC, and left MTL. However, patients with OSA had significantly increased rs-FC between the MPFC and left and right IPC, and between the left IPC and right IPC. The rs-FC between the right HF and left MTL was positively correlated with rapid eye movement (r=0.335, P=0.035). The rs-FC between the PCC and right HF was negatively correlated with delayed memory (r=-0.338, P=0.033).

CONCLUSION

OSA selectively impairs the rs-FC between right HF and PCC, MPFC, and left MTL within the DMN subregions, and provides an imaging indicator for assessment of cognitive dysfunction in OSA patients.

Sleep deprivation disturbed regional brain activity in healthy subjects: evidence from a functional magnetic resonance-imaging study

OBJECTIVE

The aim of this study was to use amplitude of low-frequency fluctuation (ALFF) to explore regional brain activities in healthy subjects after sleep deprivation (SD).

MATERIALS AND METHODS

A total of 16 healthy subjects (eight females, eight males) underwent the session twice: once was after normal sleep (NS), and the other was after SD. ALFF was used to assess local brain features. The mean ALFF-signal values of the different brain areas were evaluated to investigate relationships with clinical features and were analyzed with a receiver-operating characteristic curve.

RESULTS

Compared with NS subjects, SD subjects showed a lower response-accuracy rate, longer response time, and higher lapse rate. Compared with NS subjects, SD subjects showed higher ALFF area in the right cuneus and lower ALFF area in the right lentiform nucleus, right claustrum, left dorsolateral prefrontal cortex, and left inferior parietal cortex. ALFF differences in regional brain areas showed high sensitivity and specificity. In the SD group, mean ALFF of the right claustrum showed a significant positive correlation with accuracy rate (r=0.687, P=0.013) and a negative correlation with lapse rate (r=-0.706, P=0.01). Mean ALFF of the dorsolateral prefrontal cortex showed a significant positive correlation with response time (r=0.675, P=0.016).

CONCLUSION

SD disturbed the regional brain activity of the default-mode network, its anticorrelated "task-positive" network, and the advanced cognitive function brain areas.

Basal Hippocampal Activity and Its Functional Connectivity Predicts Cocaine Relapse

BACKGROUND

Cocaine-induced neuroplastic changes may result in a heightened propensity for relapse. Using regional cerebral blood flow (rCBF) as a marker of basal neuronal activity, this study assessed alterations in rCBF and related resting state functional connectivity (rsFC) to prospectively predict relapse in patients following treatment for cocaine use disorder (CUD).

METHODS

Pseudocontinuous arterial spin labeling functional magnetic resonance imaging and resting blood oxygen level-dependent functional magnetic resonance imaging data were acquired in the same scan session in abstinent participants with CUD before residential treatment discharge and in 20 healthy matched control subjects. Substance use was assessed twice weekly following discharge. Relapsed participants were defined as those who used stimulants within 30 days following treatment discharge (n = 22); early remission participants (n = 18) did not.

RESULTS

Voxel-wise, whole-brain analysis revealed enhanced rCBF only in the left posterior hippocampus (pHp) in the relapsed group compared with the early remission and control groups. Using this pHp as a seed, increased rsFC strength with the posterior cingulate cortex (PCC)/precuneus was seen in the relapsed versus early remission subgroups. Together, both increased pHp rCBF and strengthened pHp-PCC rsFC predicted relapse with 75% accuracy at 30, 60, and 90 days following treatment.

CONCLUSIONS

In CUD participants at risk of early relapse, increased pHp basal activity and pHp-PCC circuit strength may reflect the propensity for heightened reactivity to cocaine cues and persistent cocaine-related ruminations. Mechanisms to mute hyperactivated brain regions and delink dysregulated neural circuits may prove useful to prevent relapse in patients with CUD.

Rest Is Not Idleness: Implications of the Brain's Default Mode for Human Development and Education

When people wakefully rest in the functional MRI scanner, their minds wander, and they engage a so-called default mode (DM) of neural processing that is relatively suppressed when attention is focused on the outside world. Accruing evidence suggests that DM brain systems activated during rest are also important for active, internally focused psychosocial mental processing, for example, when recalling personal memories, imagining the future, and feeling social emotions with moral connotations. Here the authors review evidence for the DM and relations to psychological functioning, including associations with mental health and cognitive abilities like reading comprehension and divergent thinking. This article calls for research into the dimensions of internally focused thought, ranging from free-form daydreaming and off-line consolidation to intensive, effortful abstract thinking, especially with socioemotional relevance. It is argued that the development of some socioemotional skills may be vulnerable to disruption by environmental distraction, for example, from certain educational practices or overuse of social media. The authors hypothesize that high environmental attention demands may bias youngsters to focus on the concrete, physical, and immediate aspects of social situations and self, which may be more compatible with external attention. They coin the term constructive internal reflection and advocate educational practices that promote effective balance between external attention and internal reflection.

The Default Mode of Human Brain Function Primes the Intentional Stance

Humans readily adopt an intentional stance to other people, comprehending their behavior as guided by unobservable mental states such as belief, desire, and intention. We used fMRI in healthy adults to test the hypothesis that this stance is primed by the default mode of human brain function present when the mind is at rest. We report three findings that support this hypothesis. First, brain regions activated by actively adopting an intentional rather than nonintentional stance to a social stimulus were anatomically similar to those demonstrating default responses to fixation baseline in the same task. Second, moment-to-moment variation in default activity during fixation in the dorsomedial PFC was related to the ease with which participants applied an intentional—but not nonintentional—stance to a social stimulus presented moments later. Finally, individuals who showed stronger dorsomedial PFC activity at baseline in a separate task were generally more efficient when adopting the intentional stance and reported having greater social skills. These results identify a biological basis for the human tendency to adopt the intentional stance. More broadly, they suggest that the brain's default mode of function may have evolved, in part, as a response to life in a social world.

Recollection-related increases in functional connectivity predict individual differences in memory accuracy

Recollection involves retrieving specific contextual details about a prior event. Functional neuroimaging studies have identified several brain regions that are consistently more active during successful versus failed recollection-the "core recollection network." In the present study, we investigated whether these regions demonstrate recollection-related increases not only in activity but also in functional connectivity in healthy human adults. We used fMRI to compare time-series correlations during successful versus unsuccessful recollection in three separate experiments, each using a different operational definition of recollection. Across experiments, a broadly distributed set of regions consistently exhibited recollection-related increases in connectivity with different members of the core recollection network. Regions that demonstrated this effect included both recollection-sensitive regions and areas where activity did not vary as a function of recollection success. In addition, in all three experiments the magnitude of connectivity increases correlated across individuals with recollection accuracy in areas diffusely distributed throughout the brain. These findings suggest that enhanced functional interactions between distributed brain regions are a signature of successful recollection. In addition, these findings demonstrate that examining dynamic modulations in functional connectivity during episodic retrieval will likely provide valuable insight into neural mechanisms underlying individual differences in memory performance.

Functional connectivity of paired default mode network subregions in primary insomnia

OBJECTIVE

The aim of this study is to explore the resting-state functional connectivity (FC) differences between the paired default mode network (DMN) subregions in patients with primary insomnia (PIs).

METHODS

Forty-two PIs and forty-two age- and sex-matched good sleepers (GSs) were recruited. All subjects underwent the resting-state functional magnetic resonance imaging scans. The seed-based region-to-region FC method was used to evaluate the abnormal connectivity within the DMN subregions between the PIs and the GSs. Pearson correlation analysis was used to investigate the relationships between the abnormal FC strength within the paired DMN subregions and the clinical features in PIs.

RESULTS

Compared with the GSs, the PIs showed higher Pittsburgh Sleep Quality Index score, Hamilton Anxiety Rating Scale score, Hamilton Depression Rating Scale score, Self-Rating Depression Scale score, Self Rating Anxiety Scale score, Self-Rating Scale of Sleep score, and Profile of Mood States score (P<0.001). Compared with the GSs, the PIs showed significant decreased region-to-region FC between the medial prefrontal cortex and the right medial temporal lobe (t=-2.275, P=0.026), and between the left medial temporal lobe and the left inferior parietal cortices (t=-3.32, P=0.001). The abnormal FC strengths between the DMN subregions did not correlate with the clinical features.

CONCLUSION

PIs showed disrupted FC within the DMN subregions.

Long-term total sleep deprivation decreases the default spontaneous activity and connectivity pattern in healthy male subjects: a resting-state fMRI study

OBJECTIVE

The aim of this study is to use resting-state functional connectivity (rsFC) and amplitude of low-frequency fluctuation (ALFF) methods to explore intrinsic default-mode network (DMN) impairment after sleep deprivation (SD) and its relationships with clinical features.

METHODS

Twelve healthy male subjects underwent resting-state functional magnetic resonance imaging twice: once following rested wakefulness (RW) and the other following 72 hours of total SD. Before the scans, all subjects underwent the attention network test (ANT). The independent component analysis (ICA), rsFC, and ALFF methods were used to examine intrinsic DMN impairment. Receiver operating characteristic (ROC) curve was used to distinguish SD status from RW status.

RESULTS

Compared with RW subjects, SD subjects showed a lower accuracy rate (RW =96.83%, SD =77.67%; P<0.001), a slower reaction time (RW =695.92 ms; SD =799.18 ms; P=0.003), a higher lapse rate (RW =0.69%, SD =19.29%; P<0.001), and a higher intraindividual coefficient of variability in reaction time (RW =0.26, SD =0.33; P=0.021). The ICA method showed that, compared with RW subjects, SD subjects had decreased rsFC in the right inferior parietal lobule (IPL, BA40) and in the left precuneus (PrC)/posterior cingulate cortex (PCC) (BA30, 31). The two different areas were selected as regions of interest (ROIs) for future rsFC analysis. Compared with the same in RW subjects, in SD subjects, the right IPL showed decreased rsFC with the left PrC (BA7) and increased rsFC with the left fusiform gyrus (BA37) and the left cluster of middle temporal gyrus and inferior temporal gyrus (BA37). However, the left PrC/PCC did not show any connectivity differences. Compared with RW subjects, SD subjects showed lower ALFF area in the left IPL (BA39, 40). The left IPL, as an ROI, showed decreased rsFC with the right cluster of IPL and superior temporal gyrus (BA39, 40). ROC curve analysis showed that the area under the curve (AUC) value of the left IPL was 0.75, with a cutoff point of 0.834 (mean ALFF signal value). Further diagnostic analysis exhibited that the AUC alone discriminated SD status from RW status, with 75% sensitivity and 91.7% specificity.

CONCLUSION

Long-term SD disturbed the spontaneous activity and connectivity pattern of DMN.

Differential lateralization of hippocampal connectivity reflects features of recent context and ongoing demands: an examination of immediate post-task activity

Neuroimaging studies have shown that task demands affect connectivity patterns in the human brain not only during task performance but also during subsequent rest periods. Our goal was to determine whether ongoing connectivity patterns during rest contain information about both the current rest state, as well as the recently terminated task. Our experimental design consisted of two types of active tasks that were followed by two types of low-demand rest states. Using this design, we examined whether hippocampal functional connectivity during wakeful rest reflects both features of a recently terminated task and those of the current resting-state condition. We identified four types of networks: (i) one whose connectivity with the hippocampus was determined only by features of a recently terminated task, (ii) one whose connectivity was determined only by features of the current resting-state, (iii) one whose connectivity reflected aspects of both the recently terminated task and ongoing resting-state features, and (iv) one whose connectivity with the hippocampus was strong, but not affected by any external factor. The left and right hippocampi played distinct roles in these networks. These findings suggest that ongoing hippocampal connectivity networks mediate information integration across multiple temporal scales, with hippocampal laterality moderating these connectivity patterns.

Flexible modulation of network connectivity related to cognition in Alzheimer's disease

Functional neuroimaging tools, such as fMRI methods, may elucidate the neural correlates of clinical, behavioral, and cognitive performance. Most functional imaging studies focus on regional task-related activity or resting state connectivity rather than how changes in functional connectivity across conditions and tasks are related to cognitive and behavioral performance. To investigate the promise of characterizing context-dependent connectivity-behavior relationships, this study applies the method of generalized psychophysiological interactions (gPPI) to assess the patterns of associative-memory-related fMRI hippocampal functional connectivity in Alzheimer's disease (AD) associated with performance on memory and other cognitively demanding neuropsychological tests and clinical measures. Twenty-four subjects with mild AD dementia (ages 54-82, nine females) participated in a face-name paired-associate encoding memory study. Generalized PPI analysis was used to estimate the connectivity between the hippocampus and the whole brain during encoding. The difference in hippocampal-whole brain connectivity between encoding novel and encoding repeated face-name pairs was used in multiple-regression analyses as an independent predictor for 10 behavioral, neuropsychological and clinical tests. The analysis revealed connectivity-behavior relationships that were distributed, dynamically overlapping, and task-specific within and across intrinsic networks; hippocampal-whole brain connectivity-behavior relationships were not isolated to single networks, but spanned multiple brain networks. Importantly, these spatially distributed performance patterns were unique for each measure. In general, out-of-network behavioral associations with encoding novel greater than repeated face-name pairs hippocampal-connectivity were observed in the default-mode network, while correlations with encoding repeated greater than novel face-name pairs hippocampal-connectivity were observed in the executive control network (p<0.05, cluster corrected). Psychophysiological interactions revealed significantly more extensive and robust associations between paired-associate encoding task-dependent hippocampal-whole brain connectivity and performance on memory and behavioral/clinical measures than previously revealed by standard activity-behavior analysis. Compared to resting state and task-activation methods, gPPI analyses may be more sensitive to reveal additional complementary information regarding subtle within- and between-network relations. The patterns of robust correlations between hippocampal-whole brain connectivity and behavioral measures identified here suggest that there are 'coordinated states' in the brain; that the dynamic range of these states is related to behavior and cognition; and that these states can be observed and quantified, even in individuals with mild AD.

Functional and structural brain changes in anti-N-methyl-D-aspartate receptor encephalitis

OBJECTIVE

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is an autoimmune encephalitis with a characteristic neuropsychiatric syndrome and severe and prolonged clinical courses. In contrast, standard clinical magnetic resonance imaging (MRI) remains normal in the majority of patients. Here, we investigated structural and functional brain changes in a cohort of patients with anti-NMDAR encephalitis.

METHODS

Twenty-four patients with established diagnosis of anti-NMDAR encephalitis and age- and gender-matched controls underwent neuropsychological testing and multimodal MRI, including T1w/T2w structural imaging, analysis of resting state functional connectivity, analysis of white matter using diffusion tensor imaging, and analysis of gray matter using voxel-based morphometry.

RESULTS

Patients showed significantly reduced functional connectivity of the left and right hippocampus with the anterior default mode network. Connectivity of both hippocampi predicted memory performance in patients. Diffusion tensor imaging revealed extensive white matter changes, which were most prominent in the cingulum and which correlated with disease severity. In contrast, no differences in T1w/T2w structural imaging and gray matter morphology were observed between patients and controls.

INTERPRETATION

Anti-NMDAR encephalitis is associated with characteristic alterations of functional connectivity and widespread changes of white matter integrity despite normal findings in routine clinical MRI. These results may help to explain the clinicoradiological paradox in anti-NMDAR encephalitis and advance the pathophysiological understanding of the disease. Correlation of imaging abnormalities with disease symptoms and severity suggests that these changes play an important role in the symptomatology of anti-NMDAR encephalitis.

Portraying the unique contribution of the default mode network to internally driven mnemonic processes

Numerous neuroimaging studies have implicated default mode network (DMN) involvement in both internally driven processes and memory. Nevertheless, it is unclear whether memory operations reflect a particular case of internally driven processing or alternatively involve the DMN in a distinct manner, possibly depending on memory type. This question is critical for refining neurocognitive memory theorem in the context of other endogenic processes and elucidating the functional significance of this key network. We used functional MRI to examine DMN activity and connectivity patterns while participants overtly generated words according to nonmnemonic (phonemic) or mnemonic (semantic or episodic) cues. Overall, mnemonic word fluency was found to elicit greater DMN activity and stronger within-network functional connectivity compared with nonmnemonic fluency. Furthermore, two levels of functional organization of memory retrieval were shown. First, across both mnemonic tasks, activity was greater mainly in the posterior cingulate cortex, implying selective contribution to generic aspects of memory beyond its general involvement in endogenous processes. Second, parts of the DMN showed distinct selectivity for each of the mnemonic conditions; greater recruitment of the anterior prefrontal cortex, retroesplenial cortex, and hippocampi and elevated connectivity between anterior and posterior medial DMN nodes characterized the semantic condition, whereas increased recruitment of posterior DMN components and elevated connectivity between them characterized the episodic condition. This finding emphasizes the involvement of DMN elements in discrete aspects of memory retrieval. Altogether, our results show a specific contribution of the DMN to memory processes, corresponding to the specific type of memory retrieval.

Parcellating an individual subject's cortical and subcortical brain structures using snowball sampling of resting-state correlations

We describe methods for parcellating an individual subject's cortical and subcortical brain structures using resting-state functional correlations (RSFCs). Inspired by approaches from social network analysis, we first describe the application of snowball sampling on RSFC data (RSFC-Snowballing) to identify the centers of cortical areas, subdivisions of subcortical nuclei, and the cerebellum. RSFC-Snowballing parcellation is then compared with parcellation derived from identifying locations where RSFC maps exhibit abrupt transitions (RSFC-Boundary Mapping). RSFC-Snowballing and RSFC-Boundary Mapping largely complement one another, but also provide unique parcellation information; together, the methods identify independent entities with distinct functional correlations across many cortical and subcortical locations in the brain. RSFC parcellation is relatively reliable within a subject scanned across multiple days, and while the locations of many area centers and boundaries appear to exhibit considerable overlap across subjects, there is also cross-subject variability-reinforcing the motivation to parcellate brains at the level of individuals. Finally, examination of a large meta-analysis of task-evoked functional magnetic resonance imaging data reveals that area centers defined by task-evoked activity exhibit correspondence with area centers defined by RSFC-Snowballing. This observation provides important evidence for the ability of RSFC to parcellate broad expanses of an individual's brain into functionally meaningful units.

The brain's default network and its adaptive role in internal mentation

During the many idle moments that comprise daily life, the human brain increases its activity across a set of midline and lateral cortical brain regions known as the "default network." Despite the robustness with which the brain defaults to this pattern of activity, surprisingly little is known about the network's precise anatomical organization and adaptive functions. To provide insight into these questions, this article synthesizes recent literature from structural and functional imaging with a growing behavioral literature on mind wandering. Results characterize the default network as a set of interacting hubs and subsystems that play an important role in "internal mentation"-the introspective and adaptive mental activities in which humans spontaneously and deliberately engage in every day.

Hippocampal contributions to the processing of social emotions

Inducing and experiencing emotions about others' mental and physical circumstances is thought to involve self-relevant processing and personal memories of similar experiences. The hippocampus is important for self-referential processing during recall and prospection; however, its contributions during social emotions have not been systematically investigated. We use event-related averaging and Granger causal connectivity mapping to investigate hippocampal contributions during the processing of varieties of admiration and compassion pertaining to protagonists' mental versus physical circumstances [admiration for virtue (AV) versus for skill; compassion for social/psychological pain (CSP) versus for physical pain]. Data were collected using a multistep emotion-induction paradigm that included psychosocial interviews, BOLD fMRI, and simultaneous psychophysiological recording. Given that mnemonic demands were equivalent among conditions, we tested whether: (1) the hippocampi would be recruited more strongly and for a longer duration during the processing of AV and CSP; and (2) connectivity between the hippocampi and cortical systems involved in visceral somatosensation/emotional feeling, social cognitive, and self-related processing would be more extensive during AV and CSP. Results elucidate the hippocampus' facilitative role in inducing and sustaining appropriate emotional reactions, the importance of self-related processing during social emotions, and corroborate the conception that varieties of emotional processing pertaining to others' mental and physical situations engage at least partially distinct neural mechanisms.

Concepts and principles in the analysis of brain networks

The brain is a large-scale network, operating at multiple levels of information processing ranging from neurons, to local circuits, to systems of brain areas. Recent advances in the mathematics of graph theory have provided tools with which to study networks. These tools can be employed to understand how the brain's behavioral repertoire is mediated by the interactions of objects of information processing. Within the graph-theoretic framework, networks are defined by independent objects (nodes) and the relationships shared between them (edges). Importantly, the accurate incorporation of graph theory into the study of brain networks mandates careful consideration of the assumptions, constraints, and principles of both the mathematics and the underlying neurobiology. This review focuses on understanding these principles and how they guide what constitutes a brain network and its elements, specifically focusing on resting-state correlations in humans. We argue that approaches that fail to take the principles of graph theory into consideration and do not reflect the underlying neurobiological properties of the brain will likely mischaracterize brain network structure and function.

The structural basis of inter-individual differences in human behaviour and cognition

Inter-individual variability in perception, thought and action is frequently treated as a source of 'noise' in scientific investigations of the neural mechanisms that underlie these processes, and discarded by averaging data from a group of participants. However, recent MRI studies in the human brain show that inter-individual variability in a wide range of basic and higher cognitive functions - including perception, motor control, memory, aspects of consciousness and the ability to introspect - can be predicted from the local structure of grey and white matter as assessed by voxel-based morphometry or diffusion tensor imaging. We propose that inter-individual differences can be used as a source of information to link human behaviour and cognition to brain anatomy.

Prediction of subsequent recognition performance using brain activity in the medial temporal lobe

Application of multivoxel pattern analysis (MVPA) to functional magnetic resonance imaging (fMRI) data enables reconstruction and classification of cognitive status from brain activity. However, previous studies using MVPA have extracted information about cognitive status that is experienced simultaneously with fMRI scanning, but not one that will be observed after the scanning. In this study, by focusing on activity in the medial temporal lobe (MTL), we demonstrate that MVPA on fMRI data is capable of predicting subsequent recognition performance. In this experiment, six runs of fMRI signals were acquired during encoding of phonogram stimuli. In the analysis, using data acquired in runs 1-3, we first conducted MVPA-based voxel-wise search for the clusters in the MTL whose signals contained the most information about subsequent recognition performance. Next, using the fMRI signals acquired in runs 1-3 from the selected clusters, we trained a classifier function in MVPA. Finally, the trained classifier function was applied to fMRI signals acquired in runs 4-6. Consequently, we succeeded in predicting the subsequent recognition performance for stimuli studied in runs 4-6 with significant accuracy. This accurate prediction suggests that MVPA can extract information that is associated not only with concurrent cognitive status, but also with behavior in the near future.

Brain activation during autobiographical relationship episode narratives: a core conflictual relationship theme approach

The authors combined the core conflictual relationship theme (CCRT) method and functional magnetic resonance imaging (fMRI) to identify brain regions involved in recall of autobiographical relationship episodes, a key process in psychotherapy. Relationship narratives were obtained from healthy subjects and scored for CCRT relationship themes and emotion. Autobiographical personal and nonautobiographical control narratives were presented in a block-design fMRI experiment. Personal versus control narratives showed activations in anterior cingulate, precuneus, inferior and middle frontal gyri, and inferior parietal lobule. These are regions involved in autobiographical memory, theory of mind, self-referential processing, and emotion. In an exploratory analysis, higher CCRT scores correlated with increased brain activation in the left hippocampus, parahippocampal gyrus, and middle occipital gyrus. This suggests that brain systems subserving memory processes are more active when recalling relationship episodes with greater CCRT content.

Intrinsic interhemispheric hippocampal functional connectivity predicts individual differences in memory performance ability

When given challenging episodic memory tasks, young adults demonstrate notable individual differences in performance. Recent evidence suggests that individual differences in human behavior may be related to the strength of functional connectivity of large-scale functional networks as measured by spontaneous fluctuations in regional brain activity during quiet wakefulness (the "resting state"), in the absence of task performance. In this study, we sought to determine whether individual differences in memory performance could be predicted by the interhemispheric functional connectivity of the two hippocampi, hypothesized to reflect the intrinsic connectivity within the large-scale medial temporal lobe memory system. Results demonstrated that interhemispheric hippocampal functional connectivity during quiet wakefulness was predictive of the capacity to freely recall recently learned information (r = 0.47, P < 0.05). In contrast, functional connectivity of bilateral motor cortices had no relationship to free recall, supporting the specificity of the hippocampal data. Thus, individual differences in the capacity to perform episodic memory tasks, which may be persistent behavioral traits or transient states, may be at least partly subserved by individual differences in the functional connectivity of large-scale functional-anatomic memory networks.

Intrinsic connectivity between the hippocampus and posteromedial cortex predicts memory performance in cognitively intact older individuals

Coherent fluctuations of spontaneous brain activity are present in distinct functional-anatomic brain systems during undirected wakefulness. However, the behavioral significance of this spontaneous activity has only begun to be investigated. Our previous studies have demonstrated that successful memory formation requires coordinated neural activity in a distributed memory network including the hippocampus and posteromedial cortices, specifically the precuneus and posterior cingulate (PPC), thought to be integral nodes of the default network. In this study, we examined whether intrinsic connectivity during the resting state between the hippocampus and PPC can predict individual differences in the performance of an associative memory task among cognitively intact older individuals. The intrinsic connectivity, between regions within the hippocampus and PPC that were maximally engaged during a subsequent memory fMRI task, was measured during a period of rest prior to the performance of the memory paradigm. Stronger connectivity between the hippocampal and posteromedial regions during rest predicted better performance on the memory task. Furthermore, hippocampal-PPC intrinsic connectivity was also significantly correlated with episodic memory measures on neuropsychological tests, but not with performance in non-memory domains. Whole-brain exploratory analyses further confirmed the spatial specificity of the relationship between hippocampal-default network posteromedial cortical connectivity and memory performance in older subjects. Our findings provide support for the hypothesis that one of the functions of this large-scale brain network is to subserve episodic memory processes. Research is ongoing to determine if impaired connectivity between these regions may serve as a predictor of memory decline related to early Alzheimer's disease.

Sustained activity within the default mode network during an implicit memory task

Recent neuroimaging studies have shown that several brain regions--namely, the posterior cingulate cortex (PCC), ventral medial prefrontal cortex (vmPFC), and the bilateral angular gyrus--are more active during resting states than during cognitive tasks (i.e., default mode network). Although there is evidence showing that the default mode network is associated with unconscious state, it is unclear whether this network is associated with unconscious processing when normal human subjects perform tasks without awareness. We manipulated the level of conscious processing in normal subjects by asking them to perform an implicit and an explicit memory task, and analyzed signal changes in the default mode network for the stimuli versus baseline in both tasks. The functional magnetic resonance imaging (fMRI) analysis showed that the level of activation in regions within this network during the implicit task was not significantly different from that during the baseline, except in the left angular gyrus and the insula. There was strong deactivation for the explicit task when compared with the implicit task in the default mode regions, except in the left angular gyrus and the left middle temporal gyrus. These data suggest that the activity in the default network is sustained and less disrupted when an implicit memory task is performed, but is suspended when explicit retrieval is required. These results provide evidence that the default mode network is associated with unconscious processing when human subjects perform an implicit memory task.

Enhanced brain correlations during rest are related to memory for recent experiences

Long-term storage of episodic memories is hypothesized to result from the off-line transfer of information from the hippocampus to neocortex, allowing a hippocampal-independent cortical representation to emerge. However, off-line hippocampal-cortical interactions have not been demonstrated to be linked with long-term memory. Here, using functional magnetic resonance imaging, we examined if hippocampal-cortical BOLD correlations during rest following an associative encoding task are related to later associative memory performance. Our data show enhanced functional connectivity between the hippocampus and a portion of the lateral occipital complex (LO) during rest following a task with high subsequent memory compared to pretask baseline resting connectivity. This effect is not seen during rest following a task with poor subsequent memory. Furthermore, the magnitude of hippocampal-LO correlations during posttask rest predicts individual differences in later associative memory. These results demonstrate the importance of postexperience resting brain correlations for memory for recent experiences.

Age differences in default mode activity on easy and difficult spatial judgment tasks

The default network is a system of brain areas that are engaged when the mind is not involved in goal-directed activity. Most previous studies of age-related changes in default mode processing have used verbal tasks. We studied non-verbal spatial tasks that vary in difficulty. We presented old and young participants with two spatial judgment tasks: an easy categorical judgment and a more demanding coordinate judgment. We report that (a) Older adults show markedly less default network modulation than young on the demanding spatial task, but there is age equivalence on the easy task; (b) This Age × Task interaction is restricted to the default network: Brain areas that are deactivated by the tasks, but that are outside the default network, show no interaction; (c) Young adults exhibit significantly stronger functional connectivity among posterior regions of the default network compared with older adults, whereas older adults exhibit stronger connectivity between medial prefrontal cortex and other sites; and (d) The relationship of default activity to reaction time performance on the spatial tasks is mediated by age: in old adults, those who deactivate the default network most also perform best, whereas the opposite is true in younger adults. These results extend the findings of age-related changes in default mode processing and connectivity to visuo-spatial tasks and demonstrate that the results are specific to the default network.

Altered local coherence in the default mode network due to sevoflurane anesthesia

Recently we introduced a robust measure, integrated local correlation (ILC), of local connectivity in the brain using fMRI data which reflects the temporal correlation of brain activity in every voxel neighborhood. The current work studies ILC in fMRI data obtained in the absence and presence of sevoflurane anesthesia (0%, 2%, and 1% end-tidal concentration, respectively) administered to healthy volunteers. ILC was determined specifically in regions of the default mode network (DMN) to address local changes in each state. In addition, a potential confound in analyses based on correlations due to signal-to-noise variations was addressed by wavelet denoising. This accommodated decreases in signal power commonly seen during anesthesia without artificially reducing derived correlations. Results showed that ILC was significantly reduced in the entire DMN during 2% sevoflurane yet recovered in the posterior and anterior cingulate cortices as well as inferior parietal cortex during 1% sevoflurane. By contrast, ILC remained attenuated prefrontally in the 1% condition, which indicates uncoupling of the frontal areas of DMN during light anesthesia. These results confirm widespread anesthetic-induced cortical suppression but also demonstrate that the local connectivity of the prefrontal cortex is rapidly reduced by sevoflurane. It remains to be seen whether these alterations arise locally as a direct consequence of anesthetic action on local neurons or are driven by distant changes in oscillations and activity elsewhere in the brain.

Correlated low-frequency BOLD fluctuations in the resting human brain are modulated by recent experience in category-preferential visual regions

The resting brain is associated with significant intrinsic activity fluctuations, such as the correlated low-frequency (LF) blood oxygen level-dependent (BOLD) fluctuations measured by functional magnetic resonance imaging. Despite a recent expansion of studies investigating resting-state LF-BOLD correlations, their nature and function are poorly understood. A major constraint on LF-BOLD correlations appears to be stable properties of anatomic connectivity. There is also evidence that coupling can be modulated by recent or ongoing task performance, suggesting that certain components of correlated dynamics are malleable on short timescales. Here, we compared activity during extended periods of rest following performance of 2 distinct cognitive tasks using different categories of visual stimuli-faces and complex scenes. Prolonged exposure to these distinct categories of visual information caused frontal networks to couple differentially with posterior category-preferential visual regions during subsequent periods of rest. In addition, we report preliminary evidence suggesting that conditions exist in which the degree of modulation of LF-BOLD correlations predicts subsequent memory. The finding that resting-state LF-BOLD correlations are modulated by recent experience in functionally specific brain regions engaged during prior task performance clarifies their role as a dynamic phenomenon which may be involved in mnemonic processes.

Intellectual enrichment is linked to cerebral efficiency in multiple sclerosis: functional magnetic resonance imaging evidence for cognitive reserve

The cognitive reserve hypothesis helps to explain the incomplete relationship between brain disease and cognitive status in people with neurologic diseases, including Alzheimer's; disease and multiple sclerosis. Lifetime intellectual enrichment (estimated with education or vocabulary knowledge) lessens the negative impact of brain disease on cognition, such that people with greater enrichment are able to withstand more severe neuropathology before suffering cognitive impairment or dementia. The current research is the first to investigate directly the relationship between intellectual enrichment and an index of cerebral activity (the blood oxygen level dependent signal) in a neurologic sample. Multiple sclerosis patients completed a vocabulary-based estimate of lifetime intellectual enrichment. Disease severity was estimated with brain atrophy. Cognitive status was measured with the Symbol Digit Modalities Test. Cerebral activity (functional magnetic resonance imaging blood oxygen level dependent signal) and behavioural performance (accuracy, reaction time) were recorded during the visual N-Back working memory task (three levels of demand: 0-, 1-, 2-Back). All patients produced perfect/nearly perfect accuracy during lower demands (0- and 1-Back), and reaction time was unrelated to intellectual enrichment; however, voxelwise partial correlations controlling for brain atrophy revealed strong positive correlations between intellectual enrichment and cerebral activity within the brain's; default network (e.g. anterior and posterior cingulate corticies), indicating that patients with greater enrichment were able to maintain resting state activity during cognitive processing better. In turn, intellectual enrichment was negatively associated with prefrontal recruitment, suggesting that patients with lesser enrichment required more cerebral resources to perform the same cognitive task as patients with greater enrichment. This same pattern of enrichment-related cerebral activity was observed when cognitive demands increased (2-Back), and intellectual enrichment was negatively associated with reaction time. Principle components analysis revealed a single cognitive reserve network across tasks (greater default network, lesser prefrontal recruitment). Expression of this network almost fully mediated the positive relationship between intellectual enrichment and cognitive status (Symbol Digit Modalities Test). Also, expression of this network was positively associated with brain atrophy when controlling for cognitive status, indicating that patients with greater expression of this network can withstand more severe brain disease before exhibiting cognition similar to patients with lesser network expression. Of note, similar functional magnetic resonance imaging research with healthy adults has not found an association between intelligence and cerebral efficiency. The unique relationship between intellectual enrichment and cerebral efficiency in neurologic patients is consistent with the cognitive reserve hypothesis, which does not posit that enrichment leads to gains in neurocognitive functioning per se; rather, enrichment protects against neurocognitive decline secondarily to disease.

Impact of working memory load on FMRI resting state pattern in subsequent resting phases

Background

The default-mode network (DMN) is a functional network with increasing relevance for psychiatric research, characterized by increased activation at rest and decreased activation during task performance. The degree of DMN deactivation during a cognitively demanding task depends on its difficulty. However, the relation of hemodynamic responses in the resting phase after a preceding cognitive challenge remains relatively unexplored. We test the hypothesis that the degree of activation of the DMN following cognitive challenge is influenced by the cognitive load of a preceding working-memory task.

Methodology/Principal Findings

Twenty-five healthy subjects were investigated with functional MRI at 3 Tesla while performing a working-memory task with embedded short resting phases. Data were decomposed into statistically independent spatio-temporal components using Tensor Independent Component Analysis (TICA). The DMN was selected using a template-matching procedure. The spatial map contained rest-related activations in the medial frontal cortex, ventral anterior and posterior cingulate cortex. The time course of the DMN revealed increased activation at rest after 1-back and 2-back blocks compared to the activation after a 0-back block.

Conclusion/Significance

We present evidence that a cognitively challenging working-memory task is followed by greater activation of the DMN than a simple letter-matching task. This might be interpreted as a functional correlate of self-evaluation and reflection of the preceding task or as relocation of cerebral resources representing recovery from high cognitive demands. This finding is highly relevant for neuroimaging studies which include resting phases in cognitive tasks as stable baseline conditions. Further studies investigating the DMN should take possible interactions of tasks and subsequent resting phases into account.