Biology subjects

Keilholz, S. D.

Publications and source records attributed to Keilholz, S. D..

6 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↗

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↗

bioRxiv2020

Spatiotemporal functional interactivity among large-scale brain networks

The macro-scale intrinsic functional network architecture of the human brain has been well characterized. Early studies revealed robust and enduring patterns of static connectivity, while more recent work has begun to explore the temporal dynamics of these large-scale brain networks. Little work to date has investigated directed connectivity within and between these networks, or the temporal patterns of afferent (input) and efferent (output) connections between network nodes. Leveraging a novel analytic approach, prediction correlation, we investigated the causal interactions within and between large-scale networks of the brain using resting-state fMRI. This technique allows us to characterize information transfer between brain regions in both the spatial (direction) and temporal (duration) scales. Using data from the Human Connectome Project (N=200) we applied prediction correlation techniques to four resting state fMRI runs (total TRs = 4800). Three central observations emerged. First, the strongest and longest duration connections were observed within the somatomotor, visual and dorsal attention networks. Second, the short duration connections were observed for high-degree nodes in the visual and default networks, as well as in hippocampus. Specifically, the connectivity profile of the highest-degree nodes was dominated by efferent connections to multiple cortical areas. Moderate high-degree nodes, particularly in hippocampal regions, showed an afferent connectivity profile. Finally, multimodal association nodes in lateral prefrontal brain regions demonstrated a short duration, bidirectional connectivity profile, consistent with this regions role in integrative and modulatory processing. These results provide novel insights into the spatiotemporal dynamics of human brain function.

bioinformatics↗

bioRxiv2019

Resting brain fluctuations are intrinsically coupled to visual response dynamics

How do intrinsic brain dynamics interact with processing of external sensory stimuli? We sought new insights using functional (f)MRI to track spatiotemporal activity patterns at the whole brain level in lightly anesthetized mice, during both resting conditions and visual stimulation trials. Our results provide evidence that quasiperiodic patterns (QPPs) govern mouse resting brain dynamics. QPPs captured the temporal alignment of global brain fluctuations, anti-correlation of the Default Mode (DMN)- and Task Positive (TPN)-like networks, and activity in neuromodulatory nuclei of the reticular formation. While visual stimulation could trigger a transient spatiotemporal pattern highly similar to intrinsic QPPs, global signal fluctuations and QPPs during rest periods could explain variance in the following visual responses. QPPs and the global signal thus appeared to capture a common arousal-related brain-state fluctuation, orchestrated through neuromodulation. Our findings provide new frontiers to understand the neural processes that shape functional brain states and modulate sensory input processing.

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↗