Lesion network mapping demonstrates that mind-wandering is associated with the default mode network

Unveiling altered connectivity between cognitive networks and cerebellum in schizophrenia

Cognitive functioning is a crucial aspect in schizophrenia (SZ), and when altered it has devastating effects on patients' quality of life and treatment outcomes. Several studies suggested that they could result from altered communication between the cortex and cerebellum. However, the neural correlates underlying these impairments have not been identified. In this study, we investigated resting state functional connectivity (rsFC) in SZ patients, by considering the interactions between cortical networks supporting cognition and cerebellum. In addition, we investigated the relationship between SZ patients' rsFC and their symptoms. We used fMRI data from 74 SZ patients and 74 matched healthy controls (HC) downloaded from the publicly available database SchizConnect. We implemented a seed-based connectivity approach to identify altered functional connections between specific cortical networks and cerebellum. We considered ten commonly studied resting state networks, whose functioning encompasses specific cognitive functions, and the cerebellum, whose involvement in supporting cognition has been recently identified. We then explored the relationship between altered rsFC values and Positive and Negative Syndrome Scale (PANSS) scores. The SZ group showed increased connectivity values compared with HC group for cortical networks involved in attentive processes, which were also linked to PANSS items describing attention and language-related processing. We also showed decreased connectivity between cerebellar regions, and increased connectivity between them and attentive networks, suggesting the contribution of cerebellum to attentive and affective deficits. In conclusion, our findings highlighted the link between negative symptoms in SZ and altered connectivity within the cerebellum and between the same and cortical networks supporting cognition.

Taking time to compose thoughts with prefrontal schemata

Under what conditions can prefrontal cortex direct the composition of brain states, to generate coherent streams of thoughts? Using a simplified Potts model of cortical dynamics, crudely differentiated into two halves, we show that once activity levels are regulated, so as to disambiguate a single temporal sequence, whether the contents of the sequence are mainly determined by the frontal or by the posterior half, or by neither, depends on statistical parameters that describe its microcircuits. The frontal cortex tends to lead if it has more local attractors, longer lasting and stronger ones, in order of increasing importance. Its guidance is particularly effective to the extent that posterior cortices do not tend to transition from state to state on their own. The result may be related to prefrontal cortex enforcing its temporally-oriented schemata driving coherent sequences of brain states, unlike the atemporal "context" contributed by the hippocampus. Modelling a mild prefrontal (vs. posterior) lesion offers an account of mind-wandering and event construction deficits observed in prefrontal patients.

The language network as a natural kind within the broader landscape of the human brain

Language behaviour is complex, but neuroscientific evidence disentangles it into distinct components supported by dedicated brain areas or networks. In this Review, we describe the 'core' language network, which includes left-hemisphere frontal and temporal areas, and show that it is strongly interconnected, independent of input and output modalities, causally important for language and language-selective. We discuss evidence that this language network plausibly stores language knowledge and supports core linguistic computations related to accessing words and constructions from memory and combining them to interpret (decode) or generate (encode) linguistic messages. We emphasize that the language network works closely with, but is distinct from, both lower-level - perceptual and motor - mechanisms and higher-level systems of knowledge and reasoning. The perceptual and motor mechanisms process linguistic signals, but, in contrast to the language network, are sensitive only to these signals' surface properties, not their meanings; the systems of knowledge and reasoning (such as the system that supports social reasoning) are sometimes engaged during language use but are not language-selective. This Review lays a foundation both for in-depth investigations of these different components of the language processing pipeline and for probing inter-component interactions.

Left superior parietal lobe mediates the link between spontaneous mind-wandering tendency and task-switching performance

While increasing studies have documented the link between mind wandering and task switching, less is known about which brain regions mediate this relationship. Using the MPI-Leipzig Mind-Brain-Body dataset (N = 173), we investigated the association between trait-level tendencies of mind wandering, task-switching performance, structural connectivity, and resting-state functional connectivity. At the behavioral level, we found that higher spontaneous mind-wandering trait scores were associated with shorter reaction times on both repeat and switch trials. The whole brain cortical thickness analysis revealed a strong mediating role of the left superior parietal lobe, which is part of the dorsal attention network, in the link between spontaneous mind-wandering tendency and task-switching performance. The resting-state functional connectivity analysis further demonstrated that this association was partly mediated by the negative dorsal attention network-default mode network functional connectivity. No significant mediating effects were found for deliberate mind-wandering tendency. Overall, the findings highlight the pivotal role of the left superior parietal lobe in activating new mental set during mind-wandering and task-switching processes, providing another evidence in favor of a role for switching in mind wandering.

The road not taken: Common and distinct neural correlates of regret and relief

Humans anticipate and evaluate both obtained and counterfactual outcomes - outcomes that could have been had an alternate decision been taken - and experience associated emotions of regret and relief. Although many functional magnetic resonance imaging (fMRI) studies have examined the neural correlates of these emotions, there is substantial heterogeneity in their results. We conducted coordinate-based ALE and network-based ANM meta-analysis of fMRI studies of experienced regret and relief to examine commonalities and differences in their neural correlates. Regionally, we observed that the experience of both regret and relief was associated with greater activation in the right ventral striatum (VS), which is implicated in tracking reward prediction error. At the network level, regret and relief shared the reward-sensitive mesocorticolimbic network with preferential activation of the medial orbitofrontal cortex (mOFC) for regret processing and medial cingulate cortex (MCC) for relief processing. Our research identified shared and separable brain systems subserving regret and relief experience, which may inform the treatment of regret-related mood disorders.

Not all discounts are created equal: Regional activity and brain networks in temporal and effort discounting

Reward outcomes associated with costs like time delay and effort investment are generally discounted in decision-making. Standard economic models predict rewards associated with different types of costs are devalued in a similar manner. However, our review of rodent lesion studies indicated partial dissociations between brain regions supporting temporal- and effort-based decision-making. Another debate is whether options involving low and high costs are processed in different brain substrates (dual-system) or in the same regions (single-system). This research addressed these issues using coordinate-based, connectivity-based, and activation network-based meta-analyses to identify overlapping and separable neural systems supporting temporal (39 studies) and effort (20 studies) discounting. Coordinate-based activation likelihood estimation and resting-state connectivity analyses showed immediate-small reward and delayed-large reward choices engaged distinct regions with unique connectivity profiles, but their activation network mapping was found to engage the default mode network. For effort discounting, salience and sensorimotor networks supported low-effort choices, while the frontoparietal network supported high-effort choices. There was little overlap between the temporal and effort networks. Our findings underscore the importance of differentiating different types of costs in decision-making and understanding discounting at both regional and network levels.

The role of posterior parietal cortex and medial prefrontal cortex in distraction and mind-wandering

Distraction reflects a drift of attention away from the task at hand towards task-irrelevant external or internal information (mind-wandering). The right posterior parietal cortex (PPC) and the medial prefrontal cortex (mPFC) are known to mediate attention to external information and mind-wandering, respectively, but it is not clear whether they support each process selectively or rather they play similar roles in supporting both. In this study, participants performed a visual search task including salient color singleton distractors before and after receiving cathodal (inhibitory) transcranial direct current stimulation (tDCS) to the right PPC, the mPFC, or sham tDCS. Thought probes assessed the intensity and contents of mind-wandering during visual search. The results show that tDCS to the right PPC but not mPFC reduced the attentional capture by the singleton distractor during visual search. tDCS to both mPFC and PPC reduced mind-wandering, but only tDCS to the mPFC specifically reduced future-oriented mind-wandering. These results suggest that the right PPC and mPFC play a different role in directing attention towards task-irrelevant information. The PPC is involved in both external and internal distraction, possibly by mediating the disengagement of attention from the current task and its reorienting to salient information, be this a percept or a mental content (mind-wandering). By contrast, the mPFC uniquely supports mind-wandering, possibly by mediating the endogenous generation of future-oriented thoughts capable to draw attention inward, away from ongoing activities.

20 years of the default mode network: A review and synthesis

The discovery of the default mode network (DMN) has revolutionized our understanding of the workings of the human brain. Here, I review developments that led to the discovery of the DMN, offer a personal reflection, and consider how our ideas of DMN function have evolved over the past two decades. I summarize literature examining the role of the DMN in self-reference, social cognition, episodic and autobiographical memory, language and semantic memory, and mind wandering. I identify unifying themes and propose new perspectives on the DMN's role in human cognition. I argue that the DMN integrates and broadcasts memory, language, and semantic representations to create a coherent "internal narrative" reflecting our individual experiences. This narrative is central to the construction of a sense of self, shapes how we perceive ourselves and interact with others, may have ontogenetic origins in self-directed speech during childhood, and forms a vital component of human consciousness.

Functional and structural lesion network mapping in neurological and psychiatric disorders: a systematic review

Background

The traditional approach to studying the neurobiological mechanisms of brain disorders and localizing brain function involves identifying brain abnormalities and comparing them to matched controls. This method has been instrumental in clinical neurology, providing insight into the functional roles of different brain regions. However, it becomes challenging when lesions in diverse regions produce similar symptoms. To address this, researchers have begun mapping brain lesions to functional or structural networks, a process known as lesion network mapping (LNM). This approach seeks to identify common brain circuits associated with lesions in various areas. In this review, we focus on recent studies that have utilized LNM to map neurological and psychiatric symptoms, shedding light on how this method enhances our understanding of brain network functions.

Methods

We conducted a systematic search of four databases: PubMed, Scopus, and Web of Science, using the term "Lesion network mapping." Our focus was on observational studies that applied lesion network mapping in the context of neurological and psychiatric disorders.

Results

Following our screening process, we included 52 studies, comprising a total of 6,814 subjects, in our systematic review. These studies, which utilized functional connectivity, revealed several regions and network overlaps across various movement and psychiatric disorders. For instance, the cerebellum was found to be part of a common network for conditions such as essential tremor relief, parkinsonism, Holmes tremor, freezing of gait, cervical dystonia, infantile spasms, and tics. Additionally, the thalamus was identified as part of a common network for essential tremor relief, Holmes tremor, and executive function deficits. The dorsal attention network was significantly associated with fall risk in elderly individuals and parkinsonism.

Conclusion

LNM has proven to be a powerful tool in localizing a broad range of neuropsychiatric, behavioral, and movement disorders. It holds promise in identifying new treatment targets through symptom mapping. Nonetheless, the validity of these approaches should be confirmed by more comprehensive prospective studies.

Large-scale lesion symptom mapping of depression identifies brain regions for risk and resilience

Understanding neural circuits that support mood is a central goal of affective neuroscience, and improved understanding of the anatomy could inform more targeted interventions in mood disorders. Lesion studies provide a method of inferring the anatomical sites causally related to specific functions, including mood. Here, we performed a large-scale study evaluating the location of acquired, focal brain lesions in relation to symptoms of depression. Five hundred and twenty-six individuals participated in the study across two sites (356 male, average age 52.4 ± 14.5 years). Each subject had a focal brain lesion identified on structural imaging and an assessment of depression using the Beck Depression Inventory-II, both obtained in the chronic period post-lesion (>3 months). Multivariate lesion-symptom mapping was performed to identify lesion sites associated with higher or lower depression symptom burden, which we refer to as 'risk' versus 'resilience' regions. The brain networks and white matter tracts associated with peak regional findings were identified using functional and structural lesion network mapping, respectively. Lesion-symptom mapping identified brain regions significantly associated with both higher and lower depression severity (r = 0.11; P = 0.01). Peak 'risk' regions include the bilateral anterior insula, bilateral dorsolateral prefrontal cortex and left dorsomedial prefrontal cortex. Functional lesion network mapping demonstrated that these 'risk' regions localized to nodes of the salience network. Peak 'resilience' regions include the right orbitofrontal cortex, right medial prefrontal cortex and right inferolateral temporal cortex, nodes of the default mode network. Structural lesion network mapping implicated dorsal prefrontal white matter tracts as 'risk' tracts and ventral prefrontal white matter tracts as 'resilience' tracts, although the structural lesion network mapping findings did not survive correction for multiple comparisons. Taken together, these results demonstrate that lesions to specific nodes of the salience network and default mode network are associated with greater risk versus resiliency for depression symptoms in the setting of focal brain lesions.

Dynamic changes of resting state functional network following acute ischemic stroke

Stroke, the second common cause of death in the world, is commonly considered to the well-known phenomenon of diaschisis. After stroke, regions far from the lesion can show altered neural activity. However, the comprehensive treatment recovery mechanism of acute ischemic stroke remains unclear. This study aims to investigate the impact of comprehensive treatment on resting state brain functional connectivity to reveal the therapeutic mechanism through a three time points study design. Twenty-one acute ischemic stroke patients and twenty matched healthy controls (HC) were included. Resting state functional magnetic resonance imaging (fMRI) and clinical evaluations were assessed in three stages: baseline (less than 72hours after stroke onset), post-first month and post-third month. Amplitude of low-frequency fluctuations (ALFF) and Independent component analysis (ICA) were conducted. We found: 1) stroke patients had decreased ALFF in the right cuneus (one of the important parts of the visual network). After three months, ALFF increased to the normal level; 2) the decreased functional connectivity in the right cuneus within the visual network and restored three months after onset. However, the decreased functional connectivity in the right precuneus within the default mode network restored one month after onset; 3) a significant association was found between the clinical scale score change over time and improvement in the cuneus and precuneus functional connectivity. Our results demonstrate the importance of the cuneus and precuneus within the visual network and default mode network in stroke recovery. These findings suggest that the different restored patterns of neural functional networks may contribute to the neurological function recovery. It has potential applications from stroke onset through rehabilitation because different rehabilitation phase corresponds to specific strategies.

Self-caught methodologies for measuring mind wandering with meta-awareness: A systematic review

Mind wandering, also known as task-unrelated thought, refers to the drift of attention from a focal task or train of thought. Because self-caught measures of mind wandering require participants to spontaneously indicate when they notice their attention drift, self-caught methodologies provide a way to measure mind wandering with meta-awareness. Given the proposed role of meta-awareness in mental health and psychological interventions, an overview of existing self-caught methodologies would help clinicians and researchers make informed decisions when choosing or adapting a mind wandering or meta-awareness measure. This systematic review included 39 studies after 790 studies were assessed for eligibility. All studies operationalised mind wandering as instances of attention drift from a primary task. Three types of primary task were identified: (1) tasks adapted from computerised continuous performance tests (CPT) of sustained attention, (2) tasks involving focusing on the breath or a stream of aural beats, akin to in-vivo mindfulness meditation, (3) tasks involving an everyday life activity such as reading. Although data on mind wandering without meta-awareness (e.g., measured with probe-caught measures) was also obtained in many studies, such data was not always used in conjunction with self-caught mind wandering data to determine level of mind wandering meta-awareness. Few studies reported both reliability and validity of the measures used. This review shows that considerable methodological heterogeneity exists in the literature. Methodological variants of self-caught mind wandering methodologies are documented and examined, and suggestions for future research and clinical work are suggested.

Convergent gray matter alterations across drugs of abuse and network-level implications: A meta-analysis of structural MRI studies

BACKGROUND

Neuroimaging studies often consider brain alterations linked with substance abuse within the context of individual drugs (e.g., nicotine), while neurobiological theories of addiction emphasize common brain network-level alterations across drug classes. Using emergent meta-analytic techniques, we identified common structural brain alterations across drugs and characterized the functionally-connected networks with which such structurally altered regions interact.

METHODS

We identified 82 articles characterizing gray matter (GM) volume differences for substance users vs. controls. Using the anatomical likelihood estimation algorithm, we identified convergent GM reductions across drug classes. Next, we performed resting-state and meta-analytic functional connectivity analyses using each structurally altered region as a seed and computed whole-brain functional connectivity profiles as the union of both maps. We characterized an "extended network" by identifying brain areas demonstrating the highest degree of functional coupling with structurally impacted regions. Finally, hierarchical clustering was performed leveraging extended network nodes' functional connectivity profiles to delineate subnetworks.

RESULTS

Across drug classes, we identified medial frontal/ventromedial prefrontal, and multiple regions in anterior cingulate (ACC) and insula as regions displaying convergent GM reductions among users. Overlap of these regions' functional connectivity profiles identified ACC, inferior frontal, PCC, insula, superior temporal, and putamen as regions of an impacted extended network. Hierarchical clustering revealed 3 subnetworks closely corresponding to default mode (PCC, angular), salience (dACC, caudate), and executive control networks (dlPFC and parietal).

CONCLUSIONS

These outcomes suggest that substance-related structural brain alterations likely have implications for the functioning of canonical large-scale networks and the perpetuation of substance use and neurocognitive alterations.

Activation network mapping for integration of heterogeneous fMRI findings

Functional neuroimaging techniques have been widely used to probe the neural substrates of facial emotion processing in healthy people. However, findings are largely inconsistent across studies. Here, we introduce a new technique termed activation network mapping to examine whether heterogeneous functional magnetic resonance imaging findings localize to a common network for emotion processing. First, using the existing method of activation likelihood estimation meta-analysis, we showed that individual-brain-based reproducibility was low across studies. Second, using activation network mapping, we found that network-based reproducibility across these same studies was higher. Validation analysis indicated that the activation network mapping-localized network aligned with stimulation sites, structural abnormalities and brain lesions that disrupt facial emotion processing. Finally, we verified the generality of the activation network mapping technique by applying it to another cognitive process, that is, rumination. Activation network mapping may potentially be broadly applicable to localize brain networks of cognitive functions.

Sleep to Internalizing Pathway in Young Adolescents (SIPYA): A proposed neurodevelopmental model

The prevalence of internalizing disorders, i.e., anxiety and depressive disorders, spikes in adolescence and has been increasing amongst adolescents despite the existence of evidence-based treatments, highlighting the need for advancing theories on how internalizing disorders emerge. The current review presents a theoretical model, called the Sleep to Internalizing Pathway in Young Adolescents (SIPYA) Model, to explain how risk factors, namely sleep-related problems (SRPs), are prospectively associated with internalizing disorders in adolescence. Specifically, SRPs during late childhood and early adolescence, around the initiation of pubertal development, contribute to the interruption of intrinsic brain networks dynamics, both within the default mode network and between the default mode network and other networks in the brain. This interruption leaves adolescents vulnerable to repetitive negative thought, such as worry or rumination, which then increases vulnerability to internalizing symptoms and disorders later in adolescence. Sleep-related behaviors are observable, modifiable, low-stigma, and beneficial beyond treating internalizing psychopathology, highlighting the intervention potential associated with understanding the neurodevelopmental impact of SRPs around the transition to adolescence. This review details support for the SIPYA Model, as well as gaps in the literature and future directions.

Mindfulness meditation increases default mode, salience, and central executive network connectivity

Recent research has begun to identify the neural mechanisms underlying the beneficial impact of mindfulness meditation training (MMT) on health and cognition. However, little is known about the effects of MMT on the global interplay of large-scale networks (LSNs) in the brain. In the present study, healthy, meditation-naïve adults (N = 46) underwent resting state fMRI prior to and upon completing 31 days of MMT or an active control intervention. Independent component analysis, sliding time window, and seed-based correlation analyses were performed to assess training-related changes in functional connectivity (FC) within and between networks with relevance to mindfulness meditation. Across sliding time window analyses and seed-based correlation analyses, we found increased FC between nodes of the default mode network (DMN) and nodes of the salience network (SN) in participants of the MMT. Seed-based correlation analyses revealed further connectivity increases between the SN and key regions of the central executive network (CEN). These results indicate, that, among multiple LSNs, one month of mindfulness meditation effectively increases interconnectivity between networks of the triple network model (DMN, SN, CEN), hereby introducing a potential mechanistic concept underlying the beneficial impact of MMT.

Clinical trial registration: This study is listed as a clinical trial on the ISRCTN registry with trial ID ISRCTN95197731 (date of first registration: 15/02/2022).

Mind-wandering: mechanistic insights from lesion, tDCS, and iEEG

Cognitive neuroscience has witnessed a surge of interest in investigating the neural correlates of the mind when it drifts away from an ongoing task and the external environment. To that end, functional neuroimaging research has consistently implicated the default mode network (DMN) and frontoparietal control network (FPCN) in mind-wandering. Yet, it remains unknown which subregions within these networks are necessary and how they facilitate mind-wandering. In this review, we synthesize evidence from lesion, transcranial direct current stimulation (tDCS), and intracranial electroencephalogram (iEEG) studies demonstrating the causal relevance of brain regions, and providing insights into the neuronal mechanism underlying mind-wandering. We propose that the integration of complementary approaches is the optimal strategy to establish a comprehensive understanding of the neural basis of mind-wandering.

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Navigating through the ebbs and flows of language

Is progress in understanding the neural basis for spatial navigation relevant to the human language faculty? Not so much at the shortest scale, where movement is continuous, a recent study in the space of vowels suggests. At a much larger scale, however, that of the verbalization of run-away thoughts, a rich phenomenology appears to involve critical contributions by some of the brain structures also involved in spatial cognition. Their interactions may have to be approached with models operating at an integrated cortical level and allowing for the compositionality of multiple local attractor states. A useful window on the latching dynamics enabled by cortico-cortical interactions may be offered by altered states of consciousness. As an example, psychedelic states have been reported to alter the graph properties of functional connectivity in the cortex so as to facilitate wide-ranging trips.

Predicting lapses of attention with sleep-like slow waves

Attentional lapses occur commonly and are associated with mind wandering, where focus is turned to thoughts unrelated to ongoing tasks and environmental demands, or mind blanking, where the stream of consciousness itself comes to a halt. To understand the neural mechanisms underlying attentional lapses, we studied the behaviour, subjective experience and neural activity of healthy participants performing a task. Random interruptions prompted participants to indicate their mental states as task-focused, mind-wandering or mind-blanking. Using high-density electroencephalography, we report here that spatially and temporally localized slow waves, a pattern of neural activity characteristic of the transition toward sleep, accompany behavioural markers of lapses and preceded reports of mind wandering and mind blanking. The location of slow waves could distinguish between sluggish and impulsive behaviours, and between mind wandering and mind blanking. Our results suggest attentional lapses share a common physiological origin: the emergence of local sleep-like activity within the awake brain.

Prediction of stimulus-independent and task-unrelated thought from functional brain networks

Neural substrates of "mind wandering" have been widely reported, yet experiments have varied in their contexts and their definitions of this psychological phenomenon, limiting generalizability. We aimed to develop and test the generalizability, specificity, and clinical relevance of a functional brain network-based marker for a well-defined feature of mind wandering-stimulus-independent, task-unrelated thought (SITUT). Combining functional MRI (fMRI) with online experience sampling in healthy adults, we defined a connectome-wide model of inter-regional coupling-dominated by default-frontoparietal control subnetwork interactions-that predicted trial-by-trial SITUT fluctuations within novel individuals. Model predictions generalized in an independent sample of adults with attention-deficit/hyperactivity disorder (ADHD). In three additional resting-state fMRI studies (total n = 1115), including healthy individuals and individuals with ADHD, we demonstrated further prediction of SITUT (at modest effect sizes) defined using multiple trait-level and in-scanner measures. Our findings suggest that SITUT is represented within a common pattern of brain network interactions across time scales and contexts.