Task-positive State Research Articles

Dynamic reconfiguration of brain coactivation states that underlying working memory correlates with cognitive decline in clinically unimpaired older adults.

Impairments in working memory (WM) are evident in both clinically diagnosed patients with mild cognitive decline and older adults at risk, as indicated by lower scores on neuropsychological tests. Examining the WM-related neural signatures in at-risk older adults becomes essential for timely intervention. WM functioning relies on dynamic brain activities, particularly within the frontoparietal system. However, it remains unclear whether the cognitive decline would be reflected in the decreased dynamic reconfiguration of brain coactivation states during WM tasks. We enrolled 47 older adults and assessed their cognitive function using the Montreal Cognitive Assessment. The temporal dynamics of brain coactivations during a WM task were investigated through graph-based time-frame modularity analysis. Four primary recurring states emerged: two task-positive states with positive activity in the frontoparietal system (dorsal attention and central executive); two task-negative states with positive activity in the default mode network accompanied by negative activity in the frontoparietal networks. Heightened WM load was associated with increased flexibility of the frontoparietal networks, but the cognitive decline was correlated with reduced capacity for neuroplastic changes in response to increased task demands. These findings advance our understanding of aberrant brain reconfiguration linked to cognitive decline, potentially aiding early identification of at-risk individuals.

Effect of LSD and music on the time-varying brain dynamics

RationalePsychedelics are getting closer to being widely used in clinical treatment. Music is known as a key element of psychedelic-assisted therapy due to its psychological effects, specifically on the emotion, meaning-making, and sensory processing. However, there is still a lack of understanding in how psychedelics influence brain activity in experimental settings involving music listening.ObjectivesThe main goal of our research was to investigate the effect of music, as a part of “setting,” on the brain states dynamics after lysergic acid diethylamide (LSD) intake.MethodsWe used an open dataset, where a group of 15 participants underwent two functional MRI scanning sessions under LSD and placebo influence. Every scanning session contained three runs: two resting-state runs separated by one run with music listening. We applied K-Means clustering to identify the repetitive patterns of brain activity, so-called brain states. For further analysis, we calculated states’ dwell time, fractional occupancy and transition probability.ResultsThe interaction effect of music and psychedelics led to change in the time-varying brain activity of the task-positive state. LSD, regardless of the music, affected the dynamics of the state of combined activity of DMN, SOM, and VIS networks. Crucially, we observed that the music itself could potentially have a long-term influence on the resting-state, in particular on states involving task-positive networks.ConclusionsThis study indicates that music, as a crucial element of “setting,” can potentially have an influence on the subject’s resting-state during psychedelic experience. Further studies should replicate these results on a larger sample size.

Quantitative Trading Using Artificial Intelligence on Trend-following Indicators: An Example in 2020

<h3>Abstract</h3> Much of our lives are spent in unconstrained rest states, yet cognitive brain processes are primarily investigated using task-constrained states. It may be possible to utilize the insights gained from experimental control of task processes as reference points for investigating unconstrained rest. To facilitate comparison of rest and task functional MRI (fMRI) data we focused on activation amplitude patterns, commonly used for task but not rest analyses. During rest, we identified spontaneous changes in temporally extended whole-brain activation pattern states. This revealed a hierarchical organization of rest states. The top consisted of two competing states consistent with previously identified “task-positive” and “task-negative” activation patterns. These states were composed of more specific states that repeated over time and across individuals. Contrasting with the view that rest consists of only task-negative states, task-positive states occurred 40% of the time while individuals “rested,” suggesting task-focused activity occurs during rest. Further, analysis of task data revealed a similar hierarchical structure of brain states. Together these results suggest brain activation dynamics form a general hierarchy across task and rest, with a small number of dominant general states reflecting basic functional modes and a variety of specific states likely reflecting a rich variety of cognitive processes.

Temporal Dynamics of Functional Brain States Underlie Cognitive Performance.

The functional organization of the human brain adapts dynamically in response to a rapidly changing environment. However, the relation of these rapid changes in functional organization to cognitive functioning is not well understood. This study used a graph-based time-frame modularity analysis approach to identify temporally recurrent functional configuration patterns in neural responses to an n-back working memory task during fMRI. Working memory load was manipulated to investigate the functional relevance of the identified brain states. Four distinct brain states were defined by the predominant patterns of activation in the task-positive, default-mode, sensorimotor, and visual networks. Associated with escalating working memory load, the occurrence of the task-positive state and the probability of transitioning into this state increased. In contrast, the occurrence of the default-mode and sensorimotor states and the probability of these 2 states transitioning away from the task-positive state decreased. The task-positive state occurrence rate and the probability of transitioning from the default-mode state back to the task-positive state explained a significant and unique portion of the variance in task performance. The results demonstrate that dynamic brain activities support successful cognitive functioning and may have heuristic value for understanding abnormal cognitive functioning associated with multiple neuropsychiatric disorders.

Tracking the Development of Functional Connectomes for Face Processing.

Face processing capacities become more specialized and advanced during development, but neural underpinnings of these processes are not fully understood. The present study applied graph theory-based network analysis to task-negative (resting blocks) and task-positive (viewing faces) functional magnetic resonance imaging data in children (5-17 years) and adults (18-42 years) to test the hypothesis that the development of a specialized network for face processing is driven by task-positive processing (face viewing) more than by task-negative processing (visual fixation) and by both progressive and regressive changes in network properties. Predictive modeling was used to predict age from node-based network properties derived from task-positive and task-negative states in a whole-brain network (WBN) and a canonical face network (FN). The best-fitting model indicated that FN maturation was marked by both progressive and regressive changes in information diffusion (eigenvector centrality) in the task-positive state, with regressive changes outweighing progressive changes. Hence, FN maturation was characterized by reductions in information diffusion potentially reflecting the development of more specialized modules. In contrast, WBN maturation was marked by a balance of progressive and regressive changes in hub-connectivity (betweenness centrality) in the task-negative state. These findings suggest that the development of specialized networks like the FN depends on dynamic developmental changes associated with domain-specific information (e.g., face processing), but maturation of the brain as a whole can be predicted from task-free states.

The Human Brain Traverses a Common Activation-Pattern State Space Across Task and Rest.

Much of our lives are spent in unconstrained rest states, yet cognitive brain processes are primarily investigated using task-constrained states. It may be possible to utilize the insights gained from experimental control of task processes as reference points for investigating unconstrained rest. To facilitate comparison of rest and task functional magnetic resonance imaging data, we focused on activation amplitude patterns, commonly used for task but not rest analyses. During rest, we identified spontaneous changes in temporally extended whole-brain activation-pattern states. This revealed a hierarchical organization of rest states. The top consisted of two competing states consistent with previously identified "task-positive" and "task-negative" activation patterns. These states were composed of more specific states that repeated over time and across individuals. Contrasting with the view that rest consists of only task-negative states, task-positive states occurred 40% of the time while individuals "rested," suggesting task-focused activity may occur during rest. Together our results suggest that brain activation dynamics form a general hierarchy across task and rest, with a small number of dominant general states reflecting basic functional modes and a variety of specific states potentially reflecting a wide variety of cognitive processes.

Consciousness, Functional Networks and Delirium Screening.

Consciousness, the medium of sentient thought, requires integrity of functional networks and their connectivity. In health, they function as a co-operative but mutually exclusive paradigm of introspection versus external awareness subserved via the Default Mode Network and Task Positive State, respectively. Higher thinking in the conscious state is then segregated according to need. There is research evidence to suggest that functional networks may be impacted in disorders of consciousness and conceptual support for a mechanistic role in delirium. This potentially central aspect of delirium manifestation is relatively unexplored. This article describes the role of disrupted functional networks in delirium. How this relates to current understanding of delirium neurobiology and the ramifications for clinical diagnosis is discussed. A review of the role of functional networks, particularly DMN and TPN, has been undertaken with respect to health and delirium. An exploration of how symptoms of delirium may be related to functional network aberrancy has been undertaken. Implications for research and clinical practice in delirium have been presented. In delirium, a disturbance of consciousness, the DMN is pathologically co-activated and functional cortical connectivity is compromised. The clinical correlate is of an experiential singularity where internal and external drivers become indistinguishable, reality and delusion merge and the notion of self is effaced. Our group propose that functional network disruption in conjunction with cortical disconnectivity is central to the mechanism of delirium. Clinical tools may exploit the neurobiology of delirium to improve its diagnosis and an example of such a simple screening instrument (SQeeC) is provided. Functional networks are critically disrupted in delirium and may be central to clinical features. A better understanding of the neurobiology of delirium will generate research opportunities with potential for therapeutic gains in detection, diagnosis, and management.

Small Changes, But Huge Impact? The Right Anterior Insula's Loss of Connection Strength during the Transition of Old to Very Old Age

A major contribution to our understanding of the aging brain comes either from studies comparing young with older adults or from studies investigating pathological aging and using the healthy aging older adults as control group. In consequence, we know relatively well, what distinguishes young from old brains or pathological aging from healthy but that does not mean that we really understand the structural and functional transformations characterizing the healthy aging brain. By analyzing task-free fMRI data from a large cross-sectional sample of 186 older adults (mean age = 70.4, 97 female), we aimed to elucidate age-related changes in the intrinsically active functional architecture of the brain in our study group covering an age range from 65 to 85 years. First, we conducted an intrinsic connectivity contrast analysis (ICC) in order to detect the brain regions whose degree of connectedness was significantly correlated with increasing age. Secondly, using connectivity analyses we investigated how the clusters highlighted by the ICC analysis functionally related to the other major resting-state networks. The most important finding was the right anterior insula's loss of connectedness in the older participants of the study group because of the region's causal role in the switching from the task-negative to the task-positive state of the brain. Further, we found a higher functional dedifferentiation of two of the brain's major intrinsic connectivity networks, the DMN, and the cingulo-opercular network, caused by a reduction of functional connection strength, especially in the frontal regions. At last, we showed that all these age-related changes have the potential to impair older adult's performance of working memory tasks.