A cognitive framework for becoming deliberately conscious Meditation training is widely used to enhance mental well-being. However, a mechanistic cognitive science framework for understanding how it transforms mental processing is still needed. The act of practicing meditation involves trying to be deliberately conscious of a target content. This requires monitoring the contents of one’s consciousness and regulating them in favor of the target. I propose, this involves a metacognitive template of the target being present in consciousness, which when compared to the actual conscious content generates a “metacognitive prediction error” (MPE). MPE leads to efficient regulation of conscious content by helping fine-tune the frequency of monitoring, downstream unconscious processing, and the metacognitive template itself. The proposed framework parsimoniously explains existing neuroscientific findings on meditation and generates testable hypotheses.
Spatiotemporal integration of contextual and sensory information within the cortical hierarchy in human pain experience ain is not a mere reflection of noxious input. Rather, it is constructed through the dynamic integration of current predictions with incoming sensory input. However, the temporal dynamics of the behavioral and neural processes underpinning this integration remain elusive. In the current study involving 59 human participants, we identified a series of brain mediators that integrated cue-induced expectations with noxious inputs into ongoing pain predictions using a semicircular scale designed to capture rating trajectories. Temporal mediation analysis revealed that during the early-to-mid stages of integration, the frontoparietal and dorsal attention network regions, such as the lateral prefrontal, premotor, and parietal cortex, mediated the cue effects. Conversely, during the mid-to-late stages of integration, the somatomotor network regions mediated the effects of stimulus intensity, suggesting that the integration occurs along the cortical hierarchy from the association to sensorimotor brain systems. Our findings advance the understanding of how the brain integrates contextual and sensory information into pain experience over time.
Brain state and cortical layer-specific mechanisms underlying perception at threshold Identical stimuli can be perceived or go unnoticed across successive presentations, producing divergent behavioral outcomes despite similarities in sensory input. We sought to understand how fluctuations in behavioral state and cortical layer and cell class-specific neural activity underlie this perceptual variability. We analyzed physiological measurements of state and laminar electrophysiological activity in visual area V4 while monkeys were rewarded for correctly reporting a stimulus change at perceptual threshold. Hit trials were characterized by a behavioral state with heightened arousal, greater eye position stability, and enhanced decoding performance of stimulus identity from neural activity. Target stimuli evoked stronger responses in V4 in hit trials, and excitatory neurons in the superficial layers, the primary feed-forward output of the cortical column, exhibited lower variability. Feed-forward interlaminar population correlations were stronger on hits. Hit trials were further characterized by greater synchrony between the output layers of the cortex during spontaneous activity, while the stimulus-evoked period showed elevated synchrony in the feed-forward pathway. Taken together, these results suggest that a state of elevated arousal and stable retinal images allow enhanced processing of sensory stimuli, which contributes to hits at perceptual threshold.
Pupil Trend Reflects Sub-Optimal Alertness Maintenance Over 10 Seconds in Vigilance and Working Memory Performance: An Exploratory Study Maintaining concentration on demanding cognitive tasks, such as vigilance (VG) and working memory (WM) tasks, is crucial for successful task completion. Previous research suggests that internal concentration maintenance fluctuates, potentially declining to sub-optimal states, which can influence trial-by-trial performance in these tasks. However, the timescale of such alertness maintenance, as indicated by slow changes in pupil diameter, has not been thoroughly investigated. This study explored whether “pupil trends”—which selectively signal sub-optimal tonic alertness maintenance at various timescales—negatively correlate with trial-by-trial performance in VG and WM tasks. Using the Psychomotor Vigilance Task (VG) and the Visual-Spatial 2-back Task (WM), we found that human pupil trends lasting over 10 seconds were significantly higher in trials with longer reaction times, indicating poorer performance, compared to shorter reaction time trials, which indicated better performance. The Attention Network Test further validated that these slow trends reflect sub-optimal states related to (tonic) alertness maintenance rather than sub-optimal performance specific to VG and WM tasks, which is more associated with (phasic) responses to instantaneous interference. These findings highlight the potential role of detecting and compensating for non-optimal states in VG and WM performance, significantly beyond the 10-second timescale. Additionally, the findings suggest the possibility of estimating human concentration during various visual tasks, even when rapid pupil changes occur due to luminance fluctuations.
Synesthesia is linked to large and extensive differences in brain structure and function as determined by whole-brain biomarkers derived from the HCP (Human Connectome Project) cortical parcellation approach There is considerable interest in understanding the developmental origins and health implications of individual differences in brain structure and function. In this pre-registered study we demonstrate that a hidden subgroup within the general population—people with synesthesia (e.g. who “hear” colors)—show a distinctive behavioral phenotype and wide-ranging differences in brain structure and function. We assess the performance of 13 different brain-based biomarkers (structural and functional MRI) for classifying synesthetes against general population samples, using machine learning models. The features in these models were derived from subject-specific parcellations of the cortex using the Human Connectome Project approach. All biomarkers performed above chance with intracortical myelin being a particularly strong predictor that has not been implicated in synesthesia before. Resting state data show widespread changes in the functional connectome (including less hub-based connectivity). These brain-based individual differences within the neurotypical population can be as large as those that differentiate neurotypical from clinical brain states.
Interdependent scaling exponents in the human brain We apply the phenomenological renormalization group to resting-state fMRI time series of brain activity in a large population. By recursively coarse-graining the data, we compute scaling exponents for the series variance, log probability of silence, and largest covariance eigenvalue. The exponents clearly exhibit linear interdependencies, which we derive analytically in a mean-field approach. We find a significant correlation of exponent values with the gray matter volume and cognitive performance. Akin to scaling relations near critical points in thermodynamics, our findings suggest scaling interdependencies are intrinsic to brain organization and may also exist in other complex systems.
Reward processing deficits arise early in familial frontotemporal dementia Reward processing involves evaluation of stimuli to inform what an individual works to pursue or avoid. Patients with behavioral variant frontotemporal dementia (bvFTD) often display reward processing changes, including insensitivity to aversive stimuli. It is unknown how early in the disease course reward changes are detectable. We recruited mutation positive (symptomatic and asymptomatic) and negative members of families with known mutations in progranulin (GRN), microtubule-associated protein tau (MAPT) and chromosome 9 open reading frame 72 (C9orf72). The sample included 4 groups: asymptomatic non-carriers (n = 34), asymptomatic carriers [Clinical Dementia Rating (CDR) 0, n = 16], mildly symptomatic carriers (CDR 0.5, n = 10) and bvFTD (sporadic and genetic, n = 45). A series of tasks utilized pleasant, unpleasant, and neutral olfactants to probe reward consumption and effort to obtain reward. A group by valence interaction showed unpleasant scent ratings were more positive in groups with greater disease severity [χ2(6) = 87.983, p < 0.001]. Mildly symptomatic carriers showed a small difference in ratings of pleasant and unpleasant stimuli, similar to bvFTD. In an effort task, where participants chose to avoid or receive scents, mildly symptomatic carriers and bvFTD chose to smell unpleasant scents more frequently than asymptomatic groups, with mildly symptomatic carriers exceeding bvFTD in their frequency of choosing to smell unpleasant scents. In this same task, motivated effort, determined by rate of button press, determined success at obtaining or avoiding scents. Success rate, calculated based on the number of responses where participants’ button presses exceeded an individual threshold set in a practice trial, differed across groups (p = 0.048), driven by mildly symptomatic carriers, who were consistently unsuccessful. There was a group difference in variability in button press rate across trials (p = 0.007), driven by mildly symptomatic carriers who showed less varied effort between scents. These findings suggest alterations to reward functioning can be detected early in bvFTD, even before meeting diagnostic criteria. These results may aid in identifying distinctive, initial reward changes in bvFTD that can facilitate early and accurate diagnosis and inspire efforts to identify anatomic underpinnings of early symptomatic changes.
Fueling neurodegeneration: metabolic insights into microglia functions Microglia, the resident immune cells of the central nervous system, emerge in the brain during early embryonic development and persist throughout life. They play essential roles in brain homeostasis, and their dysfunction contributes to neuroinflammation and the progression of neurodegenerative diseases. Recent studies have uncovered an intricate relationship between microglia functions and metabolic processes, offering fresh perspectives on disease mechanisms and possible treatments. Despite these advancements, there are still significant gaps in our understanding of how metabolic dysregulation affects microglial phenotypes in these disorders. This review aims to address these gaps, laying the groundwork for future research on the topic. We specifically examine how metabolic shifts in microglia, such as the transition from oxidative phosphorylation and mitochondrial metabolism to heightened glycolysis during proinflammatory states, impact the disease progression in Alzheimer’s disease, multiple sclerosis, Parkinson’s disease, amyotrophic lateral sclerosis, and Huntington’s disease. Additionally, we explore the role of iron, fatty and amino acid metabolism in microglial homeostasis and repair. Identifying both distinct and shared metabolic adaptations in microglia across neurodegenerative diseases could reveal common therapeutic targets and provide a deeper understanding of disease-specific mechanisms underlying multiple CNS disorders.