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Rogge-Obando, K.

Publications and source records attributed to Rogge-Obando, K..

4 recordsLinked to original sources

Distributed fMRI patterns coupled to low-frequency cardiorespiratory dynamics provide markers of aging

How aging affects brain-body connections can be investigated through changes in the coupling between functional magnetic resonance imaging (fMRI) signals and bodily autonomic processes across the adult lifespan. Recent studies using univariate approaches have identified age-related changes in the association between fMRI signals from multiple individual brain regions and low-frequency respiratory and cardiac activity. Here, we investigate if whole-brain spatial fMRI patterns associated with low-frequency physiological processes (heart rate and respiratory volume fluctuations) present generalizable changes with age. Data from human participants of both sexes are included in the analysis. We find that chronological age can be predicted statistically beyond chance from patterns of low-frequency fMRI-physiology coupling, even after accounting for individual differences in physiological signal characteristics and brain anatomy. Notably, brain areas implicated in central autonomic regulation, including nodes within salience and ventral attention networks (e.g., insula and middle cingulate cortex), are amongst the strongest contributors to age prediction. Further, we observe that after removing physiological effects from fMRI data, the residual blood oxygen level-dependent (BOLD) signal variability is still a reliable indicator of age. Together, these findings underscore the close integration between brain and body physiology, and highlight this interaction as a potential biomarker of the aging process. Significance StatementThe association between brain activity and respiratory or cardiac activity is often dismissed as "noise" in functional magnetic resonance imaging (fMRI) studies. However, emerging evidence suggests that coupling between fMRI and peripheral physiological signals can provide valuable insight into the brain-body connection. In this study, we show that whole brain patterns of coupling between fMRI signals and low-frequency respiratory and cardiac processes can reliably predict age across the adult lifespan. Brain regions involved in autonomic regulation, such as insula and cingulate cortex, were among the most informative predictors of age. These findings suggest that fMRI-physiology coupling may capture aging-related changes in brain vascular health and autonomic function and may have broader relevance for tracking disease-related disruptions in brain-body interaction.

neuroscience↗

The Physiological Component of the BOLD Signal: Impact of Age and Heart Rate Variability Biofeedback Training

Aging is associated with declines in autonomic nervous system (ANS) function, including reduced heart rate variability (HRV), impaired neurovascular coupling, and diminished cerebrovascular responsiveness--factors that may contribute to cognitive decline and neurodegenerative diseases. Understanding how aging alters physiological signal integration in the brain is crucial for identifying potential interventions to promote brain health. This study examines age-related differences in how cardiac and respiratory fluctuations influence the blood oxygenation level-dependent (BOLD) signal, using two independent resting-state fMRI datasets with concurrent physiological recordings from younger and older adults. Our findings reveal significant age-related reductions in the percent variance of the BOLD signal explained by heart rate (HR), respiratory variation (RV), and end-tidal CO2, particularly in regions involved in autonomic regulation, including the orbitofrontal cortex, anterior cingulate cortex, insula, basal ganglia, and white matter. Cross-correlation analysis also revealed that younger adults exhibited stronger HR-BOLD coupling in white matter, as well as a more rapid BOLD response to RV and CO2 in gray matter. Additionally, we investigated the effects of heart rate variability biofeedback (HRV-BF) training, a non-invasive intervention designed to modulate heart rate oscillations. The intervention altered physiological-BOLD coupling in an age- and training-dependent manner: older adults who underwent HRV-BF to enhance HR oscillations exhibited a shift toward younger-like HR-BOLD coupling patterns, while younger adults who trained to suppress HR oscillations showed increased CO2-BOLD coupling. These findings suggest that HRV-BF may help mitigate age-related declines in autonomic or cerebrovascular function. Overall, this study underscores the role of physiological dynamics in brain aging and highlights the importance of considering autonomic function when interpreting BOLD signals. By demonstrating that HRV-BF can modulate physiological-BOLD interactions, our findings suggest a potential pathway for enhancing cerebrovascular function and preserving brain health across the lifespan.

neuroscience↗

Abnormal multisensory facilitation patterns relate to disorganized thinking severity and cognitive decline in schizophrenia

Past research has demonstrated that patients with schizophrenia (SP) have visual processing and multisensory integration deficits. Additional studies report that sensory abnormalities are related to positive symptoms. To further understand how multisensory abnormalities relate to positive symptoms, we administered a multisensory integration task requiring the evaluation of perceived distance from auditory, visual, and multisensory stimuli with varying synchrony as well as clinical and neurocognitive assessments. Overall, patients had greater facilitation than healthy controls and the near synchronous condition had the most facilitation in comparison to other conditions. To further examine how multisensory facilitation relates to symptom severity, we performed a Ward cluster analysis that grouped participants by their multisensory facilitation profile. In contrast to what was expected, none of the Ward clusters were populated by a single group. Patients in cluster 3 had a significantly greater disorganization factor score than those in cluster 1. Our in-depth comparison between Ward clusters and neuropsychological tests reveal patients with greater multisensory facilitation experience the most cognitive deficits. Overall, our results demonstrate that multisensory integration is related to behavioral and cognitive deficits in complex ways. Further research is needed to understand the relationship between multisensory integration and schizophrenia symptomology. HighlightsO_LIPatients with schizophrenia have greater multisensory facilitation in perceived synchronous conditions C_LIO_LIMultisensory facilitation patterns are heterogenous across patients with Schizophrenia. C_LIO_LIDifferent multisensory patterns relate to cognitive decline and disorganized thinking in Schizophrenia. C_LI

neuroscience↗

The neurocomputational architecture of explore-exploit decision making

Humans and other animals often make the difficult decision to try new options (exploration) and forego immediate rewards (exploitation). Novelty-seeking is an adaptive solution to this explore-exploit dilemma, but our understanding of the neural computations supporting novelty-seeking in humans is limited. Here, we presented the same explore-exploit decision making task to monkeys and humans and found evidence that the computational basis for novelty-seeking is conserved across primate species. Critically, through computational model-based decomposition of event-related functional magnetic resonance imaging (fMRI) in humans, these findings reveal a previously unidentified cortico-subcortical architecture mediating explore-exploit behavior in humans.

neuroscience↗