Sympathetic activity contributes to the fMRI signal

Autonomic physiological coupling of the global fMRI signal

The brain is closely attuned to visceral signals from the body's internal environment, as evidenced by the numerous associations between neural, hemodynamic and peripheral physiological signals. Here we show that a major mode of these brain-body cofluctuations can be captured by a single spatiotemporal pattern. Across several independent samples, as well as single-echo and multi-echo functional magnetic resonance imaging (fMRI) data acquisition sequences, we identify widespread cofluctuations in the low-frequency range (0.01-0.1 Hz) between resting-state global fMRI signals, electroencephalogram (EEG) activity, and a host of peripheral autonomic signals spanning cardiovascular, pulmonary, exocrine and smooth muscle systems. The same brain-body cofluctuations observed at rest are elicited by cued deep breathing and intermittent sensory stimuli, as well as spontaneous phasic EEG events during sleep. Furthermore, we show that the spatial structure of global fMRI signals is maintained under experimental suppression of end-tidal carbon dioxide variations, suggesting that respiratory-driven fluctuations in arterial CO2 accompanying arousal cannot fully explain the origin of these signals in the brain. These findings suggest that the global fMRI signal is a substantial component of the arousal response governed by the autonomic nervous system.

The functional overlap between respiration and global signal and its behavioral relevance

Resting-state fMRI studies encounter the challenge of interpreting fluctuations in the global signal (GS). The GS has been linked to arousal, vigilance states, cognition, and psychiatric disorders, suggesting its functional relevance. However, GS also partially arises from physiological factors, particularly respiration. In this study, we investigate whether respiration and GS exhibit functional topographic overlap in the brain and its impact on behavior. Using resting-state fMRI data from the Human Connectome Project (N = 770), we find strong spatial consistency between GS and respiration topography with regional specificity. Furthermore, canonical correlation analysis reveals a shared pattern between the GS-behavior and respiration-behavior relationships, demonstrated as the linking between default mode network and psychiatric problems. In contrast, only GS topography correlates with cognitive performance. The reliability of respiration-GS relationships is confirmed via 10-fold cross-validated canonical correlation analysis. Additionally, this relationship is not replicated for another physiological signal, i.e., cardiac activity. Our findings underscore the functional and cognitive relevance of respiration to GS, rather than mere physiological noise. We propose the importance of considering respiration's multifaceted roles in modulating GS dynamics that underpin brain-body integration supporting mental health and cognitive function.

Amplitude fluctuations of cerebrovascular oscillations and CSF movement desynchronize during NREM3 sleep

Fluctuations in cerebral blood volume (CBV) are a dominant mechanism aiding cerebrospinal fluid (CSF) movement in the brain during wakefulness and non-rapid eye movement (NREM) sleep. However, it is unclear if the amplitudes of CBV oscillations also change in proportion to the changes in amplitude of CSF movement across specific NREM sleep states. It is also not known if the coupling strength between them varies between NREM sleep states. To investigate these relationships, we measured cerebral hemodynamics and craniad CSF movement at the fourth ventricle simultaneously during wakefulness and NREM sleep states using concurrent Electroencephalography and functional Magnetic Resonance Imaging. We found that the amplitude fluctuations of cerebral hemodynamics and CSF oscillations desynchronize from one another only during deep NREM3 state, despite the strong mechanical coupling between CBV changes and CSF movement, which was consistent across all states. This suggests the existence of a different mechanism, linked to the cortical interstitial volume/resistance change, that regulates the NREM3 CSF inflow into the brain.

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 CO 2 , 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 CO 2 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 CO 2 -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.

Arousal threshold reveals novel neural markers of sleep depth independently from the conventional sleep stages

Reports of sleep-specific brain activity patterns have been constrained by assessing brain function as it related to the conventional polysomnographic sleep stages. This limits the variety of sleep states and underlying activity patterns that one can discover. The current study used all-night functional MRI sleep data and defined sleep behaviorally with auditory arousal threshold (AAT) to characterize sleep depth better by searching for novel neural markers of sleep depth that are neuroanatomically localized and temporally unrelated to the conventional stages. Functional correlation values calculated in a four-min time window immediately before the determination of AAT were entered into a linear mixed effects model, allowing multiple arousals across the night per subject into the analysis, and compared to models with sleep stage to determine the unique relationships with AAT. These unique relationships were for thalamocerebellar correlations, the relationship between the right language network and the right "default-mode network dorsal medial prefrontal cortex subsystem," and the relationship between thalamus and ventral attention network. These novel neural markers of sleep depth would have remained undiscovered if the data were merely analyzed with the conventional sleep stages.

Arousal as a universal embedding for spatiotemporal brain dynamics

Neural activity in awake organisms shows widespread and spatiotemporally diverse correlations with behavioral and physiological measurements. We propose that this covariation reflects in part the dynamics of a unified, multidimensional arousal-related process that regulates brain-wide physiology on the timescale of seconds. By framing this interpretation within dynamical systems theory, we arrive at a surprising prediction: that a single, scalar measurement of arousal (e.g., pupil diameter) should suffice to reconstruct the continuous evolution of multidimensional, spatiotemporal measurements of large-scale brain physiology. To test this hypothesis, we perform multimodal, cortex-wide optical imaging and behavioral monitoring in awake mice. We demonstrate that spatiotemporal measurements of neuronal calcium, metabolism, and brain blood-oxygen can be accurately and parsimoniously modeled from a low-dimensional state-space reconstructed from the time history of pupil diameter. Extending this framework to behavioral and electrophysiological measurements from the Allen Brain Observatory, we demonstrate the ability to integrate diverse experimental data into a unified generative model via mappings from an intrinsic arousal manifold. Our results support the hypothesis that spontaneous, spatially structured fluctuations in brain-wide physiology-widely interpreted to reflect regionally-specific neural communication-are in large part reflections of an arousal-related process. This enriched view of arousal dynamics has broad implications for interpreting observations of brain, body, and behavior as measured across modalities, contexts, and scales.

Sleep neuroimaging: Review and future directions

Sleep research has evolved considerably since the first sleep electroencephalography recordings in the 1930s and the discovery of well-distinguishable sleep stages in the 1950s. While electrophysiological recordings have been used to describe the sleeping brain in much detail, since the 1990s neuroimaging techniques have been applied to uncover the brain organization and functional connectivity of human sleep with greater spatial resolution. The combination of electroencephalography with different neuroimaging modalities such as positron emission tomography, structural magnetic resonance imaging and functional magnetic resonance imaging imposes several challenges for sleep studies, for instance, the need to combine polysomnographic recordings to assess sleep stages accurately, difficulties maintaining and consolidating sleep in an unfamiliar and restricted environment, scanner-induced distortions with physiological artefacts that may contaminate polysomnography recordings, and the necessity to account for all physiological changes throughout the sleep cycles to ensure better data interpretability. Here, we review the field of sleep neuroimaging in healthy non-sleep-deprived populations, from early findings to more recent developments. Additionally, we discuss the challenges of applying concurrent electroencephalography and imaging techniques to sleep, which consequently have impacted the sample size and generalizability of studies, and possible future directions for the field.

Cardiorespiratory dynamics in the brain: Review on the significance of cardiovascular and respiratory correlates in functional MRI signal

Cardiorespiratory signals have long been treated as "noise" in functional magnetic resonance imaging (fMRI) research, with the goal of minimizing their impact to isolate neural activity. However, there is a growing recognition that these signals, once seen as confounding variables, provide valuable insights into brain function and overall health. This shift reflects the dynamic interaction between the cardiovascular, respiratory, and neural systems, which together support brain activity. In this review, we explore the role of cardiorespiratory dynamics-such as heart rate variability (HRV), respiratory sinus arrhythmia (RSA), and changes in blood flow, oxygenation, and carbon dioxide levels-embedded within fMRI signals. These physiological signals reflect critical aspects of neurovascular coupling and are influenced by factors such as physiological stress, breathing patterns, and age-related changes. We also discuss the complexities of distinguishing these signals from neuronal activity in fMRI data, given their significant contribution to signal variability and interactions with cerebrospinal fluid (CSF). Recognizing the influence of these cardiorespiratory dynamics is crucial for improving the interpretation of fMRI data, shedding light on heart-brain and respiratory-brain connections, and enhancing our understanding of circulation, oxygen delivery, and waste elimination within the brain.

Noncanonical EEG-BOLD coupling by default and in schizophrenia

Neuroimaging methods rely on models of neurovascular coupling that assume hemodynamic responses evolve seconds after changes in neural activity. However, emerging evidence reveals noncanonical BOLD (blood oxygen level dependent) responses that are delayed under stress and aberrant in neuropsychiatric conditions. To investigate BOLD coupling to resting-state fluctuations in neural activity, we simultaneously recorded EEG and fMRI in people with schizophrenia and psychiatrically unaffected participants. We focus on alpha band power to examine voxelwise, time-lagged BOLD correlations. Principally, we find diversity in the temporal profile of alpha-BOLD coupling within regions of the default mode network (DMN). This includes early coupling (0-2 seconds BOLD lag) for more posterior regions, thalamus and brainstem. Anterior regions of the DMN show coupling at canonical lags (4-6 seconds), with greater lag scores associated with self-reported measures of stress and greater lag scores in participants with schizophrenia. Overall, noncanonical alpha-BOLD coupling is widespread across the DMN and other non-cortical regions, and is delayed in people with schizophrenia. These findings are consistent with a "hemo-neural" hypothesis, that blood flow and/or metabolism can regulate ongoing neural activity, and further, that the hemo-neural lag may be associated with subjective arousal or stress. Our work highlights the need for more studies of neurovascular coupling in psychiatric conditions.

Intra-subject test-retest reliability for auditory-evoked functional near-infrared spectroscopy responses: effects of systemic physiology correction

Significance

Functional near-infrared spectroscopy (fNIRS) is a valuable neuroimaging tool for non-invasively measuring hemodynamic changes in response to neural activity, particularly in auditory research. Although fNIRS shows strong test-retest reliability at the group level, individual-subject level reliability is often compromised by systemic noise.

Aim

We investigate how correcting for systemic-physiological signals affects reliability in single-subject fNIRS data.

Approach

fNIRS data were collected from one participant over 10 sessions during a passive auditory task. Using general linear modeling, six correction approaches were compared: no correction, physiology correction, short-channel correction, short-channel + physiology correction, short-channel + physiology + lag correction, and short-channel + tCCA correction.

Results

Intraclass correlation coefficient analysis revealed that physiology correction yielded the highest test-retest reliability score, whereas short-channel correction had the lowest. These results align with previous findings suggesting that global systemic artifacts bolster reliability, and regressing such artifacts enhances the clarity of the observed neuronal response, as supported by visual comparisons of raw and denoised signals.

Conclusions

We highlight the impact of correcting for extra-cerebral signals in single-subject auditory research and demonstrate that, while incorporating short channels in fNIRS data collection may reduce reliability, it offers a more accurate representation of the neuronal response.

Sex-specific age-related differences in cerebrospinal fluid clearance assessed by resting-state functional magnetic resonance imaging

Cerebrospinal fluid (CSF) flow may assist the clearance of brain wastes, such as amyloid-β (Aβ) and tau, and thus play an important role in aging and dementias. However, a lack of non-invasive tools to assess the CSF dynamics-related clearance in humans hindered the understanding of the relevant changes in healthy aging. The global infra-slow (<0.1 Hz) brain activity measured by the global mean resting-state fMRI signal (gBOLD) was recently found to be coupled by large CSF movements. This coupling has been found to correlate with various pathologies of Alzheimer's disease (AD), particularly Aβ pathology, linking it to waste clearance. Using resting-state fMRI data from a group of 719 healthy aging participants, we examined the sex-specific differences of the gBOLD-CSF coupling over a wide age range between 36-100 years of age. We found that this coupling index remains stable before around age 55 and then starts to decline afterward, particularly in females. Menopause may contribute to the accelerated decline in females.

Multimodal state-dependent connectivity analysis of arousal and autonomic centers in the brainstem and basal forebrain

Vigilance is a continuously altering state of cortical activation that influences cognition and behavior and is disrupted in multiple brain pathologies. Neuromodulatory nuclei in the brainstem and basal forebrain are implicated in arousal regulation and are key drivers of widespread neuronal activity and communication. However, it is unclear how their large-scale brain network architecture changes across dynamic variations in vigilance state (i.e., alertness and drowsiness). In this study, we leverage simultaneous EEG and 3T multi-echo functional magnetic resonance imaging (fMRI) to elucidate the vigilance-dependent connectivity of arousal regulation centers in the brainstem and basal forebrain. During states of low vigilance, most of the neuromodulatory nuclei investigated here exhibit a stronger global correlation pattern and greater connectivity to the thalamus, precuneus, and sensory and motor cortices. In a more alert state, the nuclei exhibit the strongest connectivity to the salience, default mode, and auditory networks. These vigilance-dependent correlation patterns persist even after applying multiple preprocessing strategies to reduce systemic vascular effects. To validate our findings, we analyze two large 3T and 7T fMRI datasets from the Human Connectome Project and demonstrate that the static and vigilance-dependent connectivity profiles of the arousal nuclei are reproducible across 3T multi-echo, 3T single-echo, and 7T single-echo fMRI modalities. Overall, this work provides novel insights into the role of neuromodulatory systems in vigilance-related brain activity.

Decoupling Between Brain Activity and Cerebrospinal Fluid Movement in Neurological Disorders

Recent research has identified a link between the global mean signal of resting-state functional MRI (fMRI) and macro-scale cerebrospinal fluid movement, indicating the potential link between this resting-state dynamic and brain waste clearance. Consistent with this notion, the strength of this coupling has been associated with multiple neurodegenerative disease pathologies, especially the build-up of toxic proteins. This article aimed to review the latest advancements in this research area, emphasizing studies on spontaneous global brain activity that is tightly linked to the global mean resting-state fMRI signal, and aimed to discuss potential mechanisms through which this activity and associated physiological modulations might affect brain waste clearance. The available evidence supports the presence of a highly organized global brain activity that is linked to arousal and memory systems. This global brain dynamic, along with its associated physiological modulations, has the potential to influence brain waste clearance through multiple pathways through multiple pathways. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

Widespread Autonomic Physiological Coupling Across the Brain-Body Axis

The brain is closely attuned to visceral signals from the body's internal environment, as evidenced by the numerous associations between neural, hemodynamic, and peripheral physiological signals. We show that these brain-body co-fluctuations can be captured by a single spatiotemporal pattern. Across several independent samples, as well as single-echo and multi-echo fMRI data acquisition sequences, we identify widespread co-fluctuations in the low-frequency range (0.01 - 0.1 Hz) between resting-state global fMRI signals, neural activity, and a host of autonomic signals spanning cardiovascular, pulmonary, exocrine and smooth muscle systems. The same brain-body co-fluctuations observed at rest are elicited by arousal induced by cued deep breathing and intermittent sensory stimuli, as well as spontaneous phasic EEG events during sleep. Further, we show that the spatial structure of global fMRI signals is maintained under experimental suppression of end-tidal carbon dioxide (PETCO2) variations, suggesting that respiratory-driven fluctuations in arterial CO2 accompanying arousal cannot explain the origin of these signals in the brain. These findings establish the global fMRI signal as a significant component of the arousal response governed by the autonomic nervous system.

Effect of sleep deprivation and NREM sleep stage on physiological brain pulsations

Introduction

Sleep increases brain fluid transport and the power of pulsations driving the fluids. We investigated how sleep deprivation or electrophysiologically different stages of non-rapid-eye-movement (NREM) sleep affect the human brain pulsations.

Methods

Fast functional magnetic resonance imaging (fMRI) was performed in healthy subjects (n = 23) with synchronous electroencephalography (EEG), that was used to verify arousal states (awake, N1 and N2 sleep). Cardiorespiratory rates were verified with physiological monitoring. Spectral power analysis assessed the strength, and spectral entropy assessed the stability of the pulsations.

Results

In N1 sleep, the power of vasomotor (VLF < 0.1 Hz), but not cardiorespiratory pulsations, intensified after sleep deprived vs. non-sleep deprived subjects. The power of all three pulsations increased as a function of arousal state (N2 > N1 > awake) encompassing brain tissue in both sleep stages, but extra-axial CSF spaces only in N2 sleep. Spectral entropy of full band and respiratory pulsations decreased most in N2 sleep stage, while cardiac spectral entropy increased in ventricles.

Discussion

In summary, the sleep deprivation and sleep depth, both increase the power and harmonize the spectral content of human brain pulsations.

Resting-state global brain activity affects early β-amyloid accumulation in default mode network

It remains unclear why β-amyloid (Aβ) plaque, a hallmark pathology of Alzheimer's disease (AD), first accumulates cortically in the default mode network (DMN), years before AD diagnosis. Resting-state low-frequency ( < 0.1 Hz) global brain activity recently was linked to AD, presumably due to its role in glymphatic clearance. Here we show that the preferential Aβ accumulation in the DMN at the early stage of Aβ pathology was associated with the preferential reduction of global brain activity in the same regions. This can be partly explained by its failure to reach these regions as propagating waves. Together, these findings highlight the important role of resting-state global brain activity in early preferential Aβ deposition in the DMN.

An autonomic mode of brain activity

The relevance of interactions between autonomic and central nervous systems remains unclear for human brain function and health, particularly when both systems are challenged under sleep deprivation (SD). We measured brain activity (with fMRI), pulse and respiratory signals, and baseline brain amyloid beta burden (with PET) in healthy participants. We found that SD relative to rested wakefulness (RW) resulted in a significant increase in synchronized low frequency (LF, < 0.1 Hz) activity in an autonomically-related network (AN), including dorsal attention, visual, and sensorimotor regions, which we previously found to have consistent temporal coupling with LF pulse signal changes (regulated by sympathetic tone). SD resulted in a significant phase coherence between the LF component of the pulse signal and a medial network with peak effects in the midbrain reticular formation, and between LF component of the respiratory variations (regulated by respiratory motor output) and a cerebellar network. The LF power of AN during SD was significantly and independently correlated with pulse-medial network and respiratory-cerebellar network phase coherences (total adjusted R2 = 0.78). Higher LF power of AN during SD (but not RW) was associated with lower amyloid beta burden (Cohen's d = 0.8). In sum, SD triggered an autonomic mode of synchronized brain activity that was associated with distinct autonomic-central interactions. Findings highlight the direct relevance of global cortical synchronization to brain clearance mechanisms.

Global brain activity and its coupling with cerebrospinal fluid flow is related to tau pathology

Amyloid-β (Aβ) and tau deposition constitute Alzheimer's disease (AD) neuropathology. Cortical tau deposits first in the entorhinal cortex and hippocampus and then propagates to neocortex in an Aβ-dependent manner. Tau also tends to accumulate earlier in higher-order association cortex than in lower-order primary sensory-motor cortex. While previous research has examined the production and spread of tau, little attention has been paid to its clearance. Low-frequency (<0.1 Hz) global brain activity during the resting state is coupled with cerebrospinal fluid (CSF) flow and potentially reflects glymphatic clearance. Here we report that tau deposition in subjects with evaluated Aβ, accompanied by cortical thinning and cognitive decline, is strongly associated with decreased coupling between CSF flow and global brain activity. Substantial modulation of global brain activity is also manifested as propagating waves of brain activation between higher- and lower-order regions, resembling tau spreading. Together, the findings suggest an important role of resting-state global brain activity in AD tau pathology.

Altered brain dynamic in major depressive disorder: state and trait features

Temporal neural synchrony disruption can be linked to a variety of symptoms of major depressive disorder (MDD), including mood rigidity and the inability to break the cycle of negative emotion or attention biases. This might imply that altered dynamic neural synchrony may play a role in the persistence and exacerbation of MDD symptoms. Our study aimed to investigate the changes in whole-brain dynamic patterns of the brain functional connectivity and activity related to depression using the hidden Markov model (HMM) on resting-state functional magnetic resonance imaging (rs-fMRI) data. We compared the patterns of brain functional dynamics in a large sample of 314 patients with MDD (65.9% female; age (mean ± standard deviation): 35.9 ± 13.4) and 498 healthy controls (59.4% female; age: 34.0 ± 12.8). The HMM model was used to explain variations in rs-fMRI functional connectivity and averaged functional activity across the whole-brain by using a set of six unique recurring states. This study compared the proportion of time spent in each state and the average duration of visits to each state to assess stability between different groups. Compared to healthy controls, patients with MDD showed significantly higher proportional time spent and temporal stability in a state characterized by weak functional connectivity within and between all brain networks and relatively strong averaged functional activity of regions located in the somatosensory motor (SMN), salience (SN), and dorsal attention (DAN) networks. Both proportional time spent and temporal stability of this brain state was significantly associated with depression severity. Healthy controls, in contrast to the MDD group, showed proportional time spent and temporal stability in a state with relatively strong functional connectivity within and between all brain networks but weak averaged functional activity across the whole brain. These findings suggest that disrupted brain functional synchrony across time is present in MDD and associated with current depression severity.

Identifying the distinct spectral dynamics of laminar-specific interhemispheric connectivity with bilateral line-scanning fMRI

Despite extensive efforts to identify interhemispheric functional connectivity (FC) with resting-state (rs-) fMRI, correlated low-frequency rs-fMRI signal fluctuation across homotopic cortices originates from multiple sources. It remains challenging to differentiate circuit-specific FC from global regulation. Here, we developed a bilateral line-scanning fMRI method to detect laminar-specific rs-fMRI signals from homologous forepaw somatosensory cortices with high spatial and temporal resolution in rat brains. Based on spectral coherence analysis, two distinct bilateral fluctuation spectral features were identified: ultra-slow fluctuation (<0.04 Hz) across all cortical laminae versus Layer (L) 2/3-specific evoked BOLD at 0.05 Hz based on 4 s on/16 s off block design and resting-state fluctuations at 0.08-0.1 Hz. Based on the measurements of evoked BOLD signal at corpus callosum (CC), this L2/3-specific 0.05 Hz signal is likely associated with neuronal circuit-specific activity driven by the callosal projection, which dampened ultra-slow oscillation less than 0.04 Hz. Also, the rs-fMRI power variability clustering analysis showed that the appearance of L2/3-specific 0.08-0.1 Hz signal fluctuation is independent of the ultra-slow oscillation across different trials. Thus, distinct laminar-specific bilateral FC patterns at different frequency ranges can be identified by the bilateral line-scanning fMRI method.

Cognition is entangled with metabolism: relevance for resting-state EEG-fMRI

The brain is a living organ with distinct metabolic constraints. However, these constraints are typically considered as secondary or supportive of information processing which is primarily performed by neurons. The default operational definition of neural information processing is that (1) it is ultimately encoded as a change in individual neuronal firing rate as this correlates with the presentation of a peripheral stimulus, motor action or cognitive task. Two additional assumptions are associated with this default interpretation: (2) that the incessant background firing activity against which changes in activity are measured plays no role in assigning significance to the extrinsically evoked change in neural firing, and (3) that the metabolic energy that sustains this background activity and which correlates with differences in neuronal firing rate is merely a response to an evoked change in neuronal activity. These assumptions underlie the design, implementation, and interpretation of neuroimaging studies, particularly fMRI, which relies on changes in blood oxygen as an indirect measure of neural activity. In this article we reconsider all three of these assumptions in light of recent evidence. We suggest that by combining EEG with fMRI, new experimental work can reconcile emerging controversies in neurovascular coupling and the significance of ongoing, background activity during resting-state paradigms. A new conceptual framework for neuroimaging paradigms is developed to investigate how ongoing neural activity is "entangled" with metabolism. That is, in addition to being recruited to support locally evoked neuronal activity (the traditional hemodynamic response), changes in metabolic support may be independently "invoked" by non-local brain regions, yielding flexible neurovascular coupling dynamics that inform the cognitive context. This framework demonstrates how multimodal neuroimaging is necessary to probe the neurometabolic foundations of cognition, with implications for the study of neuropsychiatric disorders.

Sex-specific age-related changes in glymphatic function assessed by resting-state functional magnetic resonance imaging

The glymphatic system that clears out brain wastes, such as amyloid-β (Aβ) and tau, through cerebrospinal fluid (CSF) flow may play an important role in aging and dementias. However, a lack of non-invasive tools to assess the glymphatic function in humans hindered the understanding of the glymphatic changes in healthy aging. The global infra-slow (<0.1 Hz) brain activity measured by the global mean resting-state fMRI signal (gBOLD) was recently found to be coupled by large CSF movements. This coupling has been used to measure the glymphatic process and found to correlate with various pathologies of Alzheimer's disease (AD), including Aβ pathology. Using resting-state fMRI data from a large group of 719 healthy aging participants, we examined the sex-specific changes of the gBOLD-CSF coupling, as a measure of glymphatic function, over a wide age range between 36-100 years old. We found that this coupling index remains stable before around age 55 and then starts to decline afterward, particularly in females. Menopause may contribute to the accelerated decline in females.

Neural activity induced by sensory stimulation can drive large-scale cerebrospinal fluid flow during wakefulness in humans

Cerebrospinal fluid (CSF) flow maintains healthy brain homeostasis, facilitating solute transport and the exchange of brain waste products. CSF flow is thus important for brain health, but the mechanisms that control its large-scale movement through the ventricles are not well understood. While it is well established that CSF flow is modulated by respiratory and cardiovascular dynamics, recent work has also demonstrated that neural activity is coupled to large waves of CSF flow in the ventricles during sleep. To test whether the temporal coupling between neural activity and CSF flow is in part due to a causal relationship, we investigated whether CSF flow could be induced by driving neural activity with intense visual stimulation. We manipulated neural activity with a flickering checkerboard visual stimulus and found that we could drive macroscopic CSF flow in the human brain. The timing and amplitude of CSF flow was matched to the visually evoked hemodynamic responses, suggesting neural activity can modulate CSF flow via neurovascular coupling. These results demonstrate that neural activity can contribute to driving CSF flow in the human brain and that the temporal dynamics of neurovascular coupling can explain this effect.

Psychedelics and fNIRS neuroimaging: exploring new opportunities

In this Outlook paper, we explain to the optical neuroimaging community as well as the psychedelic research community the great potential of using optical neuroimaging with functional near-infrared spectroscopy (fNIRS) to further explore the changes in brain activity induced by psychedelics. We explain why we believe now is the time to exploit the momentum of the current resurgence of research on the effects of psychedelics and the momentum of the increasing progress and popularity of the fNIRS technique to establish fNIRS in psychedelic research. With this article, we hope to contribute to this development.

Brain and cardiovascular-related changes are associated with aging, hypertension, and atrial fibrillation

PURPOSE

The neural pathways in which the brain regulates the cardiovascular system is via sympathetic and parasympathetic control of the heart and sympathetic control of the systemic vasculature. Various cortical and sub-cortical sites are involved, but how these critical brain regions for cardiovascular control are altered in healthy aging and other risk conditions that may contribute to cardiovascular disease is uncertain.

METHODS

Here we review the functional and structural brain changes in healthy aging, hypertension, and atrial fibrillation - noting their potential influence on the autonomic nervous system and hence on cardiovascular control.

RESULTS

Evidence suggests that aging, hypertension, and atrial fibrillation are each associated with functional and structural changes in specific areas of the central nervous system involved in autonomic control. Increased muscle sympathetic nerve activity (MSNA) and significant alterations in the brain regions involved in the default mode network are commonly reported in aging, hypertension, and atrial fibrillation.

CONCLUSIONS

Further studies using functional and structural magnetic resonance imaging (MRI) coupled with autonomic nerve activity in healthy aging, hypertension, and atrial fibrillation promise to reveal the underlying brain circuitry modulating the abnormal sympathetic nerve activity in these conditions. This understanding will guide future therapies to rectify dysregulation of autonomic and cardiovascular control by the brain.

An orderly sequence of autonomic and neural events at transient arousal changes

Resting-state functional magnetic resonance imaging (rsfMRI) allows the study of functional brain connectivity based on spatially structured variations in neuronal activity. Proper evaluation of connectivity requires removal of non-neural contributions to the fMRI signal, in particular hemodynamic changes associated with autonomic variability. Regression analysis based on autonomic indicator signals has been used for this purpose, but may be inadequate if neuronal and autonomic activities covary. To investigate this potential co-variation, we performed rsfMRI experiments while concurrently acquiring electroencephalography (EEG) and autonomic indicator signals, including heart rate, respiratory depth, and peripheral vascular tone. We identified a recurrent and systematic spatiotemporal pattern of fMRI (named as fMRI cascade), which features brief signal reductions in salience and default-mode networks and the thalamus, followed by a biphasic global change with a sensory-motor dominance. This fMRI cascade, which was mostly observed during eyes-closed condition, was accompanied by large EEG and autonomic changes indicative of arousal modulations. Importantly, the removal of the fMRI cascade dynamics from rsfMRI diminished its correlations with various signals. These results suggest that the rsfMRI correlations with various physiological and neural signals are not independent but arise, at least partly, from the fMRI cascades and associated neural and physiological changes at arousal modulations.

Laminar-specific functional connectivity mapping with multi-slice line-scanning fMRI

Despite extensive studies detecting laminar functional magnetic resonance imaging (fMRI) signals to illustrate the canonical microcircuit, the spatiotemporal characteristics of laminar-specific information flow across cortical regions remain to be fully investigated in both evoked and resting conditions at different brain states. Here, we developed a multislice line-scanning fMRI (MS-LS) method to detect laminar fMRI signals in adjacent cortical regions with high spatial (50 μm) and temporal resolution (100 ms) in anesthetized rats. Across different trials, we detected either laminar-specific positive or negative blood-oxygen-level-dependent (BOLD) responses in the surrounding cortical region adjacent to the most activated cortex under the evoked condition. Specifically, in contrast to typical Layer (L) 4 correlation across different regions due to the thalamocortical projections for trials with positive BOLD, a strong correlation pattern specific in L2/3 was detected for trials with negative BOLD in adjacent regions, which indicated brain state-dependent laminar-fMRI responses based on corticocortical interaction. Also, in resting-state (rs-) fMRI study, robust lag time differences in L2/3, 4, and 5 across multiple cortices represented the low-frequency rs-fMRI signal propagation from caudal to rostral slices. In summary, our study provided a unique laminar fMRI mapping scheme to better characterize trial-specific intra- and inter-laminar functional connectivity in evoked and resting-state MS-LS.

A temporal sequence of thalamic activity unfolds at transitions in behavioral arousal state

Awakening from sleep reflects a profound transformation in neural activity and behavior. The thalamus is a key controller of arousal state, but whether its diverse nuclei exhibit coordinated or distinct activity at transitions in behavioral arousal state is unknown. Using fast fMRI at ultra-high field (7 Tesla), we measured sub-second activity across thalamocortical networks and within nine thalamic nuclei to delineate these dynamics during spontaneous transitions in behavioral arousal state. We discovered a stereotyped sequence of activity across thalamic nuclei and cingulate cortex that preceded behavioral arousal after a period of inactivity, followed by widespread deactivation. These thalamic dynamics were linked to whether participants subsequently fell back into unresponsiveness, with unified thalamic activation reflecting maintenance of behavior. These results provide an outline of the complex interactions across thalamocortical circuits that orchestrate behavioral arousal state transitions, and additionally, demonstrate that fast fMRI can resolve sub-second subcortical dynamics in the human brain.

Cerebrovascular activity is a major factor in the cerebrospinal fluid flow dynamics

Cerebrospinal fluid (CSF) provides physical protection to the central nervous system as well as an essential homeostatic environment for the normal functioning of neurons. Additionally, it has been proposed that the pulsatile movement of CSF may assist in glymphatic clearance of brain metabolic waste products implicated in neurodegeneration. In awake humans, CSF flow dynamics are thought to be driven primarily by cerebral blood volume fluctuations resulting from a number of mechanisms, including a passive vascular response to blood pressure variations associated with cardiac and respiratory cycles. Recent research has shown that mechanisms that rely on the action of vascular smooth muscle cells ("cerebrovascular activity") such as neuronal activity, changes in intravascular CO2, and autonomic activation from the brainstem, may lead to CSF pulsations as well. Nevertheless, the relative contribution of these mechanisms to CSF flow remains unclear. To investigate this further, we developed an MRI approach capable of disentangling and quantifying CSF flow components of different time scales associated with these mechanisms. This approach was evaluated on human control subjects (n = 12) performing intermittent voluntary deep inspirations, by determining peak flow velocities and displaced volumes between these mechanisms in the fourth ventricle. We found that peak flow velocities were similar between the different mechanisms, while displaced volumes per cycle were about a magnitude larger for deep inspirations. CSF flow velocity peaked at around 10.4 s (range 7.1-14.8 s, n = 12) following deep inspiration, consistent with known cerebrovascular activation delays for this autonomic challenge. These findings point to an important role of cerebrovascular activity in the genesis of CSF pulsations. Other regulatory triggers for cerebral blood flow such as autonomic arousal and orthostatic challenges may create major CSF pulsatile movement as well. Future quantitative comparison of these and possibly additional types of CSF pulsations with the proposed approach may help clarify the conditions that affect CSF flow dynamics.

A parsimonious description of global functional brain organization in three spatiotemporal patterns

Resting-state functional magnetic resonance imaging (MRI) has yielded seemingly disparate insights into large-scale organization of the human brain. The brain's large-scale organization can be divided into two broad categories: zero-lag representations of functional connectivity structure and time-lag representations of traveling wave or propagation structure. In this study, we sought to unify observed phenomena across these two categories in the form of three low-frequency spatiotemporal patterns composed of a mixture of standing and traveling wave dynamics. We showed that a range of empirical phenomena, including functional connectivity gradients, the task-positive/task-negative anti-correlation pattern, the global signal, time-lag propagation patterns, the quasiperiodic pattern and the functional connectome network structure, are manifestations of these three spatiotemporal patterns. These patterns account for much of the global spatial structure that underlies functional connectivity analyses and unifies phenomena in resting-state functional MRI previously thought distinct.

The Spatiotemporal Dynamics of Cerebral Autoregulation in Functional Magnetic Resonance Imaging

The thigh-cuff release (TCR) maneuver is a physiological challenge that is widely used to assess dynamic cerebral autoregulation (dCA). It is often applied in conjunction with Transcranial Doppler ultrasound (TCD), which provides temporal information of the global flow response in the brain. This established method can only yield very limited insights into the regional variability of dCA, whereas functional MRI (fMRI) has the ability to reveal the spatial distribution of flow responses in the brain with high spatial resolution. The aim of this study was to use whole-brain blood-oxygenation-level-dependent (BOLD) fMRI to characterize the spatiotemporal dynamics of the flow response to the TCR challenge, and thus pave the way toward mapping dCA in the brain. We used a data driven approach to derive a novel basis set that was then used to provide a voxel-wise estimate of the TCR associated haemodynamic response function (HRF TCR ). We found that the HRF TCR evolves with a specific spatiotemporal pattern, with gray and white matter showing an asynchronous response, which likely reflects the anatomical structure of cerebral blood supply. Thus, we propose that TCR challenge fMRI is a promising method for mapping spatial variability in dCA, which will likely prove to be clinically advantageous.

Systemic physiology augmented functional near-infrared spectroscopy: a powerful approach to study the embodied human brain

In this Outlook paper, we explain why an accurate physiological interpretation of functional near-infrared spectroscopy (fNIRS) neuroimaging signals is facilitated when systemic physiological activity (e.g., cardiorespiratory and autonomic activity) is measured simultaneously by employing systemic physiology augmented functional near-infrared spectroscopy (SPA-fNIRS). The rationale for SPA-fNIRS is twofold: (i) SPA-fNIRS enables a more complete interpretation and understanding of the fNIRS signals measured at the head since they contain components originating from neurovascular coupling and from systemic physiological sources. The systemic physiology signals measured with SPA-fNIRS can be used for regressing out physiological confounding components in fNIRS signals. Misinterpretations can thus be minimized. (ii) SPA-fNIRS enables to study the embodied brain by linking the brain with the physiological state of the entire body, allowing novel insights into their complex interplay. We envisage the SPA-fNIRS approach will become increasingly important in the future.

Task-related hemodynamic responses in human early visual cortex are modulated by task difficulty and behavioral performance

Early visual cortex exhibits widespread hemodynamic responses in the absence of visual stimulation, which are entrained to the timing of a task and not predicted by local spiking or local field potential. Such task-related responses (TRRs) covary with reward magnitude and physiological signatures of arousal. It is unknown, however, if TRRs change on a trial-to-trial basis according to behavioral performance and task difficulty. If so, this would suggest that TRRs reflect arousal on a trial-to-trial timescale and covary with critical task and behavioral variables. We measured functional magnetic resonance imaging blood-oxygen-level-dependent (fMRI-BOLD) responses in the early visual cortex of human observers performing an orientation discrimination task consisting of separate easy and hard runs of trials. Stimuli were presented in a small portion of one hemifield, but the fMRI response was measured in the ipsilateral hemisphere, far from the stimulus representation and focus of spatial attention. TRRs scaled in amplitude with task difficulty, behavioral accuracy, reaction time, and lapses across trials. These modulations were not explained by the influence of respiration, cardiac activity, or head movement on the fMRI signal. Similar modulations with task difficulty and behavior were observed in pupil size. These results suggest that TRRs reflect arousal and behavior on the timescale of individual trials.

Autonomic arousals contribute to brain fluid pulsations during sleep

During sleep, slow waves of neuro-electrical activity engulf the human brain and aid in the consolidation of memories. Recent research suggests that these slow waves may also promote brain health by facilitating the removal of metabolic waste, possibly by orchestrating the pulsatile flow of cerebrospinal fluid (CSF) through local neural control over vascular tone. To investigate the role of slow waves in the generation of CSF pulsations, we analyzed functional MRI data obtained across the full sleep-wake cycle and during a waking respiratory task. This revealed a novel generating mechanism that relies on the autonomic regulation of cerebral vascular tone without requiring slow electrocortical activity or even sleep. Therefore, the role of CSF pulsations in brain waste clearance may, in part, depend on proper autoregulatory control of cerebral blood flow.

Rapid fluctuations in brain oxygenation during glucose-drinking behavior in trained rats

Proper inflow of oxygen into brain tissue is essential for maintaining normal neural functions. Although oxygen levels in the brain's extracellular space depend upon a balance between its delivery from arterial blood and its metabolic consumption, the use of high-speed electrochemical detection revealed rapid increases in brain oxygen levels elicited by various salient sensory stimuli. These stimuli also increase intrabrain heat production, an index of metabolic neural activation, but these changes are slower and more prolonged than changes in oxygen levels. Therefore, under physiological conditions, the oxygen inflow into brain tissue exceeds its loss due to consumption, thus preventing any metabolic deficit. Here, we used oxygen sensors coupled with amperometry to examine the pattern of real-time oxygen fluctuations in the nucleus accumbens during glucose-drinking behavior in trained rats. Following the exposure to a glucose-containing cup, oxygen levels rapidly increased, peaked when the rat initiated drinking, and relatively decreased during consumption. Similar oxygen changes but more episodic drinking occurred when Stevia, a calorie-free sweet substance, was substituted for glucose. When water was substituted for glucose, rats tested the water but refused to consume all of it. Although the basic pattern of oxygen changes during this water test was similar to that with glucose drinking, the increases were larger. Finally, oxygen increases were significantly larger when rats were exposed to concealed glucose and made multiple unsuccessful attempts to obtain and consume it. Based on these data, we discuss the mechanisms underlying behavior-related brain oxygen fluctuations and their functional significance.NEW & NOTEWORTHY Oxygen sensors coupled with high-speed amperometry were used to examine brain oxygen fluctuations during glucose-drinking behavior in trained rats. Oxygen levels rapidly increased following presentation of a glucose-contained cup, peaking at the initiation of glucose drinking, and relatively decreasing during drinking. Oxygen increases were larger when rats were exposed to concealed glucose and made multiple attempts to obtain it. We discuss the mechanisms underlying behavior-related brain oxygen fluctuations and their functional significance.

State-related neural influences on fMRI connectivity estimation

The spatiotemporal structure of functional magnetic resonance imaging (fMRI) signals has provided a valuable window into the network underpinnings of human brain function and dysfunction. Although some cross-regional temporal correlation patterns (functional connectivity; FC) exhibit a high degree of stability across individuals and species, there is growing acknowledgment that measures of FC can exhibit marked changes over a range of temporal scales. Further, FC can covary with experimental task demands and ongoing neural processes linked to arousal, consciousness and perception, cognitive and affective state, and brain-body interactions. The increased recognition that such interrelated neural processes modulate FC measurements has raised both challenges and new opportunities in using FC to investigate brain function. Here, we review recent advances in the quantification of neural effects that shape fMRI FC and discuss the broad implications of these findings in the design and analysis of fMRI studies. We also discuss how a more complete understanding of the neural factors that shape FC measurements can resolve apparent inconsistencies in the literature and lead to more interpretable conclusions from fMRI studies.

Single-neuron firing cascades underlie global spontaneous brain events

The resting brain consumes enormous energy and shows highly organized spontaneous activity. To investigate how this activity is manifest among single neurons, we analyzed spiking discharges of ∼10,000 isolated cells recorded from multiple cortical and subcortical regions of the mouse brain during immobile rest. We found that firing of a significant proportion (∼70%) of neurons conformed to a ubiquitous, temporally sequenced cascade of spiking that was synchronized with global events and elapsed over timescales of 5 to 10 s. Across the brain, two intermixed populations of neurons supported orthogonal cascades. The relative phases of these cascades determined, at each moment, the response magnitude evoked by an external visual stimulus. Furthermore, the spiking of individual neurons embedded in these cascades was time locked to physiological indicators of arousal, including local field potential power, pupil diameter, and hippocampal ripples. These findings demonstrate that the large-scale coordination of low-frequency spontaneous activity, which is commonly observed in brain imaging and linked to arousal, sensory processing, and memory, is underpinned by sequential, large-scale temporal cascades of neuronal spiking across the brain.

Imaging the temporal dynamics of brain states with highly sampled fMRI

The spontaneous dynamics of the brain modulate its function from moment to moment, shaping neural computation and cognition. Functional MRI (fMRI), while classically used as a tool for spatial localization, is increasingly being used to identify the temporal dynamics of brain activity. fMRI analyses focused on the temporal domain have revealed important new information about the dynamics underlying states such as arousal, attention, and sleep. Dense temporal sampling – either by using fast fMRI acquisition, or multiple repeated scan sessions within individuals – can further enrich the information present in these studies. This review focuses on recent developments in using fMRI to identify dynamics across brain states, particularly vigilance and sleep states, and the potential for highly temporally sampled fMRI to answer these questions.

Representation learning of resting state fMRI with variational autoencoder

Resting state functional magnetic resonance imaging (rsfMRI) data exhibits complex but structured patterns. However, the underlying origins are unclear and entangled in rsfMRI data. Here we establish a variational auto-encoder, as a generative model trainable with unsupervised learning, to disentangle the unknown sources of rsfMRI activity. After being trained with large data from the Human Connectome Project, the model has learned to represent and generate patterns of cortical activity and connectivity using latent variables. The latent representation and its trajectory represent the spatiotemporal characteristics of rsfMRI activity. The latent variables reflect the principal gradients of the latent trajectory and drive activity changes in cortical networks. Representational geometry captured as covariance or correlation between latent variables, rather than cortical connectivity, can be used as a more reliable feature to accurately identify subjects from a large group, even if only a short period of data is available in each subject. Our results demonstrate that VAE is a valuable addition to existing tools, particularly suited for unsupervised representation learning of resting state fMRI activity.

High γ Activity in Cortex and Hippocampus Is Correlated with Autonomic Tone during Sleep

Studies in animals have demonstrated a strong relationship between cortical and hippocampal activity, and autonomic tone. However, the extent, distribution, and nature of this relationship have not been investigated with intracranial recordings in humans during sleep. Cortical and hippocampal population neuronal firing was estimated from high γ band activity (HG) from 70 to 110 Hz in local field potentials (LFPs) recorded from 15 subjects (nine females) during nonrapid eye movement (NREM) sleep. Autonomic tone was estimated from heart rate variability (HRV). HG and HRV were significantly correlated in the hippocampus and multiple cortical sites in NREM stages N1-N3. The average correlation between HG and HRV could be positive or negative across patients given anatomic location and sleep stage and was most profound in lateral temporal lobe in N3, suggestive of greater cortical activity associated with sympathetic tone. Patient-wide correlation was related to δ band activity (1-4 Hz), which is known to be correlated with high γ activity during sleep. The percentage of statistically correlated channels was weaker in N1 and N2 as compared with N3, and was strongest in regions that have previously been associated with autonomic processes, such as anterior hippocampus and insula. The anatomic distribution of HRV-HG correlations during sleep did not reproduce those usually observed with positron emission tomography (PET) or functional magnetic resonance imaging (fMRI) during waking. This study aims to characterize the relationship between autonomic tone and neuronal firing rate during sleep and further studies are needed to investigate finer temporal resolutions, denser coverages, and different frequency bands in both waking and sleep.

The interconnected causes and consequences of sleep in the brain

Sleep is essential for brain function in a surprisingly diverse set of ways. In the short term, lack of sleep leads to impaired memory and attention; in the longer term, it produces neurological dysfunction or even death. I discuss recent advances in understanding how sleep maintains the physiological health of the brain through interconnected systems of neuronal activity and fluid flow. The neural dynamics that appear during sleep are intrinsically coupled to its consequences for blood flow, cerebrospinal fluid dynamics, and waste clearance. Recognizing these linked causes and consequences of sleep has shed new light on why sleep is important for such disparate aspects of brain function.

Contribution of animal models toward understanding resting state functional connectivity

Functional connectivity, which reflects the spatial and temporal organization of intrinsic activity throughout the brain, is one of the most studied measures in human neuroimaging research. The noninvasive acquisition of resting state functional magnetic resonance imaging (rs-fMRI) allows the characterization of features designated as functional networks, functional connectivity gradients, and time-varying activity patterns that provide insight into the intrinsic functional organization of the brain and potential alterations related to brain dysfunction. Functional connectivity, hence, captures dimensions of the brain's activity that have enormous potential for both clinical and preclinical research. However, the mechanisms underlying functional connectivity have yet to be fully characterized, hindering interpretation of rs-fMRI studies. As in other branches of neuroscience, the identification of the neurophysiological processes that contribute to functional connectivity largely depends on research conducted on laboratory animals, which provide a platform where specific, multi-dimensional investigations that involve invasive measurements can be carried out. These highly controlled experiments facilitate the interpretation of the temporal correlations observed across the brain. Indeed, information obtained from animal experimentation to date is the basis for our current understanding of the underlying basis for functional brain connectivity. This review presents a compendium of some of the most critical advances in the field based on the efforts made by the animal neuroimaging community.

Internal State: Dynamic, Interconnected Communication Loops Distributed Across Body, Brain, and Time

Internal state profoundly alters perception and behavior. For example, a starved fly may approach and consume foods that it would otherwise find undesirable. A socially engaged newt may remain engaged in the presence of a predator, whereas a solitary newt would otherwise attempt to escape. Yet, the definition of internal state is fluid and ill-defined. As an interdisciplinary group of scholars spanning five career stages (from undergraduate to full professor) and six academic institutions, we came together in an attempt to provide an operational definition of internal state that could be useful in understanding the behavior and the function of nervous systems, at timescales relevant to the individual. In this perspective, we propose to define internal state through an integrative framework centered on dynamic and interconnected communication loops within and between the body and the brain. This framework is informed by a synthesis of historical and contemporary paradigms used by neurobiologists, ethologists, physiologists, and endocrinologists. We view internal state as composed of both spatially distributed networks (body-brain communication loops), and temporally distributed mechanisms that weave together neural circuits, physiology, and behavior. Given the wide spatial and temporal scales at which internal state operates-and therefore the broad range of scales at which it could be defined-we choose to anchor our definition in the body. Here we focus on studies that highlight body-to-brain signaling; body represented in endocrine signaling, and brain represented in sensory signaling. This integrative framework of internal state potentially unites the disparate paradigms often used by scientists grappling with body-brain interactions. We invite others to join us as we examine approaches and question assumptions to study the underlying mechanisms and temporal dynamics of internal state.

Naturalistic Stimuli: A Paradigm for Multi-Scale Functional Characterization of the Human Brain

Movies, audio stories, and virtual reality are increasingly used as stimuli for functional brain imaging. Such naturalistic paradigms are in sharp contrast to the tradition of experimental reductionism in neuroscience research. Being complex, dynamic, and diverse, naturalistic stimuli set up a more ecologically relevant condition and induce highly reproducible brain responses across a wide range of spatiotemporal scales. Here, we review recent technical advances and scientific findings on imaging the brain under naturalistic stimuli. Then we elaborate on the premise of using naturalistic paradigms for multi-scale, multi-modal, and high-throughput functional characterization of the human brain. We further highlight the growing potential of using deep learning models to infer neural information processing from brain responses to naturalistic stimuli. Lastly, we advocate large-scale collaborations to combine brain imaging and recording data across experiments, subjects, and labs that use the same set of naturalistic stimuli.

Revisiting the neurovascular unit

The brain is supplied by an elaborate vascular network that originates extracranially and reaches deep into the brain. The concept of the neurovascular unit provides a useful framework to investigate how neuronal signals regulate nearby microvessels to support the metabolic needs of the brain, but it does not consider the role of larger cerebral arteries and systemic vasoactive signals. Furthermore, the recently emerged molecular heterogeneity of cerebrovascular cells indicates that there is no prototypical neurovascular unit replicated at all levels of the vascular network. Here, we examine the cellular and molecular diversity of the cerebrovascular tree and the relative contribution of systemic and brain-intrinsic factors to neurovascular function. Evidence supports the concept of a 'neurovascular complex' composed of segmentally diverse functional modules that implement coordinated vascular responses to central and peripheral signals to maintain homeostasis of the brain. This concept has major implications for neurovascular regulation in health and disease and for brain imaging.

Decoding the brain state-dependent relationship between pupil dynamics and resting state fMRI signal fluctuation

Pupil dynamics serve as a physiological indicator of cognitive processes and arousal states of the brain across a diverse range of behavioral experiments. Pupil diameter changes reflect brain state fluctuations driven by neuromodulatory systems. Resting-state fMRI (rs-fMRI) has been used to identify global patterns of neuronal correlation with pupil diameter changes; however, the linkage between distinct brain state-dependent activation patterns of neuromodulatory nuclei with pupil dynamics remains to be explored. Here, we identified four clusters of trials with unique activity patterns related to pupil diameter changes in anesthetized rat brains. Going beyond the typical rs-fMRI correlation analysis with pupil dynamics, we decomposed spatiotemporal patterns of rs-fMRI with principal component analysis (PCA) and characterized the cluster-specific pupil-fMRI relationships by optimizing the PCA component weighting via decoding methods. This work shows that pupil dynamics are tightly coupled with different neuromodulatory centers in different trials, presenting a novel PCA-based decoding method to study the brain state-dependent pupil-fMRI relationship.

Physiological noise modeling in fMRI based on the pulsatile component of photoplethysmograph

The blood oxygenation level-dependent (BOLD) contrast mechanism allows the noninvasive monitoring of changes in deoxyhemoglobin content. As such, it is commonly used in functional magnetic resonance imaging (fMRI) to study brain activity since levels of deoxyhemoglobin are indirectly related to local neuronal activity through neurovascular coupling mechanisms. However, the BOLD signal is severely affected by physiological processes as well as motion. Due to this, several noise correction techniques have been developed to correct for the associated confounds. The present study focuses on cardiac pulsatility fMRI confounds, aiming to refine model-based techniques that utilize the photoplethysmograph (PPG) signal. Specifically, we propose a new technique based on convolution filtering, termed cardiac pulsatility model (CPM) and compare its performance with the cardiac-related RETROICOR (Card-RETROICOR), which is a technique commonly used to model fMRI fluctuations due to cardiac pulsatility. Further, we investigate whether variations in the amplitude of the PPG pulses (PPG-Amp) covary with variations in amplitude of pulse-related fMRI fluctuations, as well as with the systemic low frequency oscillations (SLFOs) component of the fMRI global signal (GS - defined as the mean signal across all gray matter voxels). Capitalizing on 3T fMRI data from the Human Connectome Project, CPM was found to explain a significantly larger fraction of the fMRI signal variance compared to Card-RETROICOR, particularly for subjects with larger heart rate variability during the scan. The amplitude of the fMRI pulse-related fluctuations did not covary with PPG-Amp; however, PPG-Amp explained significant variance in the GS that was not attributed to variations in heart rate or breathing patterns. Our results suggest that the proposed approach can model high-frequency fluctuations due to pulsation as well as low-frequency physiological fluctuations more accurately compared to model-based techniques commonly employed in fMRI studies.

Physiological and motion signatures in static and time-varying functional connectivity and their subject identifiability

Human brain connectivity yields significant potential as a noninvasive biomarker. Several studies have used fMRI-based connectivity fingerprinting to characterize individual patterns of brain activity. However, it is not clear whether these patterns mainly reflect neural activity or the effect of physiological and motion processes. To answer this question, we capitalize on a large data sample from the Human Connectome Project and rigorously investigate the contribution of the aforementioned processes on functional connectivity (FC) and time-varying FC, as well as their contribution to subject identifiability. We find that head motion, as well as heart rate and breathing fluctuations, induce artifactual connectivity within distinct resting-state networks and that they correlate with recurrent patterns in time-varying FC. Even though the spatiotemporal signatures of these processes yield above-chance levels in subject identifiability, removing their effects at the preprocessing stage improves identifiability, suggesting a neural component underpinning the inter-individual differences in connectivity.

The effect of body posture on resting-state functional connectivity

INTRODUCTION

An important but under-investigated confound of functional MRI (fMRI) is body posture. Although it is well-established that body position changes cerebral blood flow, the amount of cerebrospinal fluid in the brain, intracranial pressure, and even the firing rate of certain cell types, there is currently no study that directly examines its effect on fMRI measurements. Moreover, fMRI is typically done in a supine position, which often does not correspond to how these processes are performed in everyday settings.

METHODS

In this study, 20 healthy adults underwent resting-state fMRI under three body positions: supine, right lateral decubitus (RLD), and left lateral decubitus (LLD). We first investigated whether there were differences in overall organization of whole-brain connectivity between conditions using graph theory. Second, we examined whether functional connectivity of two most studied default mode network (DMN) seeds to the rest of the brain was altered as a function of body position.

RESULTS

Nonparametric statistical analyses revealed that global network measures differed among conditions, with the supine and LLD showing identical results compared to the RLD. There was decreased connectivity for DMN seeds in the RLD condition compared to the supine and LLD, but there were no significant differences between the latter two conditions.

DISCUSSION

Potential mechanisms underlying these alterations include gravity, changes in physiology, and body anatomy. Our results suggest that, compared to supine and LLD, the RLD position leads to changes in whole-brain and DMN connectivity. Finally, depending on the research question, combining imaging modalities that allow for more naturalistic settings can provide a better understanding of certain phenomena.