Biology subjects

Schumacher, E. H.

Publications and source records attributed to Schumacher, E. H..

9 recordsLinked to original sources

bioRxiv2026

Time-Varying Directed Interactions in Functional Brain Networks: Modeling and Validation

Brain function depends on time-resolved directional organization: influence is continuously redistributed across regions, shaping who drives whom, when, and for how long. Yet dynamic neuroimaging has largely emphasized undirected fluctuations in functional connectivity, limiting biological interpretation of asymmetric interactions. Here we show that directed influence can be resolved into two biologically distinct signatures: strength, reflecting the efficacy of influence, and duration, reflecting its temporal extent. To test this principle, we developed sliding-window prediction correlation (SWpC), a framework for estimating these signatures in fMRI and related signals. Across simultaneous rat local field potential (LFP)-fMRI and human motor-task fMRI, strength more closely tracks neural-BOLD coupling and task-evoked reconfiguration, whereas duration captures temporally extended BOLD patterns more susceptible to hemodynamic timing. In post-concussion vestibular dysfunction, altered strength-duration profiles define reproducible vestibular-multisensory states and improve patient-control discrimination. Together, these findings support a general principle of dynamic brain organization spanning neurophysiology, behavior, and disease.

bioengineering↗

bioRxiv2024

Variation in the Distribution of Large-scale Spatiotemporal Patterns of Activity Across Brain States

A few large-scale spatiotemporal patterns of brain activity (quasiperiodic patterns or QPPs) account for most of the spatial structure observed in resting state functional magnetic resonance imaging (rs-fMRI). The QPPs capture well-known features such as the evolution of the global signal and the alternating dominance of the default mode and task positive networks. These widespread patterns of activity have plausible ties to neuromodulatory input that mediates changes in nonlocalized processes, including arousal and attention. To determine whether QPPs exhibit variations across brain conditions, the relative magnitude and distribution of the three strongest QPPs were examined in two scenarios. First, in data from the Human Connectome Project, the relative incidence and magnitude of the QPPs was examined over the course of the scan, under the hypothesis that increasing drowsiness would shift the expression of the QPPs over time. Second, using rs-fMRI in rats obtained with a novel approach that minimizes noise, the relative incidence and magnitude of the QPPs was examined under three different anesthetic conditions expected to create distinct types of brain activity. The results indicate that both the distribution of QPPs and their magnitude changes with brain state, evidence of the sensitivity of these large-scale patterns to widespread changes linked to alterations in brain conditions.

neuroscience↗

bioRxiv2024

Infraslow dynamic patterns in human cortical networks track a spectrum of external to internal attention

Early efforts to understand the human cerebral cortex focused on localization of function, assigning functional roles to specific brain regions. More recent evidence depicts the cortex as a dynamic system, organized into flexible networks with patterns of spatiotemporal activity corresponding to attentional demands. In functional MRI (fMRI), dynamic analysis of such spatiotemporal patterns is highly promising for providing non-invasive biomarkers of neurodegenerative diseases and neural disorders. However, there is no established neurotypical spectrum to interpret the burgeoning literature of dynamic functional connectivity from fMRI across attentional states. In the present study, we apply dynamic analysis of network-scale spatiotemporal patterns in a range of fMRI datasets across numerous tasks including a left-right moving dot task, visual working memory tasks, congruence tasks, multiple resting state datasets, mindfulness meditators, and subjects watching TV. We find that cortical networks show shifts in dynamic functional connectivity across a spectrum that tracks the level of external to internal attention demanded by these tasks. Dynamics of networks often grouped into a single task positive network show divergent responses along this axis of attention, consistent with evidence that definitions of a single task positive network are misleading. Additionally, somatosensory and visual networks exhibit strong phase shifting along this spectrum of attention. Results were robust on a group and individual level, further establishing network dynamics as a potential individual biomarker. To our knowledge, this represents the first study of its kind to generate a spectrum of dynamic network relationships across such an axis of attention. Significance StatementThis study provides significant insight into how cortical dynamics shift along a spectrum of external vs internal attention. Association and sensory networks show shifts in their relationship with the default mode network (DMN) along this spectrum. Notably, the constituent networks of the task positive network (TPN), such as the DAN, frontoparietal network (FPN), and ventral attention network (VAN) show divergent responses along this spectrum, indicating that definitions of a single "task positive" network are misleading. This is one of the first studies of large-scale spatiotemporal dynamics across such a breadth of tasks. These results provide a neurotypical reference spanning an axis of attention to interpret the growing functional dynamics literature and to help characterize functional dynamics as a potential biomarker.

neuroscience↗

bioRxiv2023

Time-varying Functional Connectivity Predicts Fluctuations in Sustained Attention in a Serial Tapping Task

The mechanisms for how large-scale brain networks contribute to sustained attention is unknown. Attention fluctuates from moment to moment and this continuous change is consistent with dynamic changes in functional connectivity between brain networks involved in the internal and external allocation of attention. In this study, we investigated how brain network activity varied across different levels of attentional focus (i.e., "zones"). Participants performed a finger-tapping task, and guided by previous research, in-the-zone performance or state was identified by low reaction time variability and out-of-the-zone as the inverse. Employing a novel method of time-varying functional connectivity, called the quasi-periodic pattern analysis (i.e., reliable network-level low-frequency fluctuations), we found that the activity between the default mode network (DMN) and task positive network is significantly more anti-correlated during in-the-zone states versus out-of-the-zone states. Furthermore, it is the fronto-parietal control network (FPCN) that drives this difference. Activity in the dorsal attention network (DAN) and DMN were desynchronized across both zone states. During in-the-zone periods, FPCN synchronized with DAN, while during out-of-the-zone periods, FPCN synchronized with DMN. In contrast, the ventral attention network synchronized more closely with DMN during in-the-zone periods compared to out-of-the-zone periods. These findings demonstrate that time-varying functional connectivity across different brain networks varies with fluctuations in sustained attention.

neuroscience↗

bioRxiv2022

The effect of random and systematic visual stimulation on entrained infraslow quasi-periodic global waves in human brain activity

One prominent feature of the infraslow BOLD signal during rest or task is quasi-periodic spatiotemporal pattern (QPP) of signal changes that involves an alternation of activity in key functional networks and propagation of activity across brain areas, and that is known to tie to the infraslow neural activity involved in attention and arousal fluctuations. This ongoing whole-brain pattern of activity might potentially modify the response to incoming stimuli or be modified itself by the induced neural activity. To investigate this, we presented checkerboard sequences flashing at 6Hz to subjects. This is a salient visual stimulus that is known to produce a strong response in visual processing regions. Two different visual stimulation sequences were employed, a systematic stimulation sequence in which the visual stimulus appeared every 20.3 secs and a random stimulation sequence in which the visual stimulus occurred randomly every 14~62.3 secs. Three central observations emerged. First, the two different stimulation conditions affect the QPP waveform in different aspects, i.e., systematic stimulation has greater effects on its phase and random stimulation has greater effects on its magnitude. Second, the QPP was more frequent in the systematic condition with significantly shorter intervals between consecutive QPPs compared to the random condition. Third, the BOLD signal response to the visual stimulus across both conditions was swamped by the QPP at the stimulus onset. These results provide novel insights into the relationship between intrinsic patterns and stimulated brain activity.

neuroscience↗

bioRxiv2021

Dynamic Brain Network States during Suspenseful Film Viewing

Studies of brain activity evoked by naturalistic stimuli have found narrative suspense produces reliable patterns of activation consistent with increased attention to the narrative and decreased processing of non-narrative stimuli (Bezdek et al., 2015). Yet the progression of brain states (i.e. patterns of activity levels across the whole brain) at suspense peaks and how they differ from suspense valleys or resting state scans has not previously been investigated. We used a fast fMRI acquisition sequence to measure sub-second brain states at peaks and valleys of narrative suspense and during rest. We found five brain states that occur during suspenseful film viewing, four of which differ in their frequency near suspense peaks compared to valleys. The pattern of results is consistent with the theoretical view that suspense captures and focuses attentional processing, triggering subsequent cognitive processing of narrative events.

neuroscience↗

bioRxiv2021

Dissociating the Neural Correlates of Planning and Executing Hierarchical Task Sets

Task processing (e.g., the preparation and execution of responses) and task representation (e.g., the activation and maintenance of stimulus-response and context information) are two facets of cognitive control supported by lateral frontal cortex (LFC). However, the mechanistic overlap (or distinction) between these two facets is unknown. We explored this by combining a complex task mapping with a pre-cueing procedure. Participants made match/non-match judgments on pairs of stimuli during fMRI recording. Pre-cues on each trial gave variable amounts of information to the participant in anticipation of the stimulus. Our results demonstrated that regions throughout LFC were more active at the stimulus (when responses could be executed) than at the cue (when they could only be prepared), indicating that they supported execution of the task agnostic to the specific task representation. A subset of regions in left caudal LFC showed increased activity with more cue information at the cue and the reverse at the stimulus, suggesting their involvement in reducing uncertainty within the task representation. These results suggest that one component of task processing is preparing and executing the task according to the relevant representation, confined to left caudal LFC, while non-representational functions that occur primarily during execution are supported by different regions throughout the rest of LFC. We further conducted an exploratory investigation of connectivity between the two groups of regions in this study and their potential relationship to the fronto-parietal and cingulo-opercular networks. Regions with both patterns of activity appear to be part of the fronto-parietal network.

neuroscience↗

bioRxiv2019

Prefrontal-posterior coupling mediates emotion transitions and their influence on executive function

Although emotions often result from dynamic experiences with self-regulation unfolding over time, most research has focused on responses to affective stimuli from a rather static perspective. We studied and analyzed emotion transitions, attempting to reveal brain functions related to affect dynamics. EEG responses were examined during exposure to stable versus changing emotion-eliciting images (static vs dynamic conditions) plus their impact on executive function (EF) assessed with the flanker task. During dynamic conditions, reduced prefrontal to posterior EEG coherence in the beta frequency band and greater left frontal activity occurred compared to the static conditions. Among individuals suffering higher chronic stress, subsequent EF was hindered after dynamic conditions. Furthermore, the adverse effects of emotion transitions on EF for more chronically stressed individuals were mediated by prefrontal-posterior coherence in low beta frequency band during emotional image sequences. Emotion appears to influence EF through changes in large-scale synchronization. Individuals high in chronic stress are vulnerable to these effects.

neuroscience↗

bioRxiv2017

Quasi-Periodic Patterns of Intrinsic Brain Activity in Individuals and their Relationship to Global Signal

Quasiperiodic patterns (QPPs) as reported by Majeed et al., 2011 are prominent features of the brains intrinsic activity that involve important large-scale networks (default mode, DMN; task positive, TPN) and are likely to be major contributors to widely used measures of functional connectivity. We examined the variability of these patterns in 470 individuals from the Human Connectome Project resting state functional MRI dataset. The QPPs from individuals can be coarsely categorized into two types: one where strong anti-correlation between the DMN and TPN is present, and another where most areas are strongly correlated. QPP type could be predicted by an individuals global signal, with lower global signal corresponding to QPPs with strong anti-correlation. After regression of global signal, all QPPs showed strong anti-correlation between DMN and TPN. QPP occurrence and type was similar between a subgroup of individuals with extremely low motion (or even high motion) and the rest of the sample, which shows that motion is not a major contributor to the QPPs. After regression of estimates of slow respiratory and cardiac induced signal fluctuations, more QPPs showed strong anti-correlation between DMN and TPN, an indication that while physiological noise influences the QPP type, it is not the primary source of the QPP itself. QPPs were more similar for the same subjects scanned on different days than for different subjects. These results provide the first assessment of the variability in individual QPPs and their relationship to physiological parameters.

neuroscience↗