Biology subjects

Colcombe, S. J.

Publications and source records attributed to Colcombe, S. J..

7 recordsLinked to original sources

bioRxiv2026

MERIT: A No-Code Platform for Unifying High-Precision Cognitive Assessment Across Laboratory and Real-World Settings

Cognitive tasks are moving from the laboratory onto participants' own devices. Browser runtimes make that move easy. Their stimulus timing, however, can vary by tens of milliseconds across devices. We asked how much timing error cognitive and neural measures can tolerate. We injected per-trial stimulus-timing jitter into a public EEG dataset (ERP CORE, N = 40) and re-measured three event-related potential components. Under a prespecified criterion of half the between-participant SD, the N170 tolerated jitter up to 15.8 ms, limited by peak-latency bias. The slower MMN and P3 tolerated more than 20 ms. The full jitter distribution predicted the loss. Heavy-tailed jitter cost less than Gaussian jitter of the same RMS. In simulated reaction-time data, the same tail shape determined whether platform error raised or lowered the ex-Gaussian {tau}, a candidate attentional biomarker. A single RMS timing figure therefore cannot tell whether a platform is adequate for these measures. We built the Mobile Experimental Research Investigative Toolkit (MERIT) to meet these requirements without code. Researchers design tasks in a visual builder that supports reaction-time, continuous-control, drawing, and sequential task families. A Unity engine embedded natively in the Curious iOS and Android apps runs the tasks. Measured with an optical sensor, inter-stimulus-interval SD was 0.71 to 0.96 ms on three current phones and tablets. It was 3.73 ms on a 2019 budget Android phone. Every device measured at least four times below the N170 ceiling. In the laboratory, the same task definition streams event markers to Lab Streaming Layer (LSL) for synchronized EEG and physiological recording. In the field, it runs on ecological momentary assessment schedules. Native mobile players, no-code builders, and EMA platforms each exist as separate systems. MERIT combines them, so the task characterized against brain and body recordings in the laboratory is the same task participants complete at home.

neuroscience↗

bioRxiv2026

Temporal Dynamics of BOLD fMRI Predict Intracranially-Confirmed Seizure Onset Zones in Drug-Resistant Epilepsy

ObjectiveIn individuals with drug-resistant epilepsy, accurately identifying the brain regions where seizures originate is a critical prerequisite to guide surgical treatment and achieve seizure freedom. To accomplish this, intracranial EEG is considered the gold standard, providing the spatiotemporal high-resolution data necessary to pinpoint epileptogenic activity. However, this precision is achieved through an invasive procedure with significant patient burden, which is fundamentally limited by the electrode placement and spatial coverage. MethodsIn this study, we investigated the potential utility of preoperative resting-state fMRI to non-invasively map alterations in brain dynamics at the whole brain level. Region-wise brain dynamics were quantified with complementary measures of local autocorrelation decay rates. We assessed the capacity of these derived features to effectively identify intracranial EEG confirmed seizure onset zones in 18 individuals with drug-resistant medial temporal lobe epilepsy. Overall, the study cohort contained 3867 implanted electrodes of which 159 classified as seizure onset zones by two independent board-certified epileptologists. ResultsOverall, our findings reveal more constrained temporal dynamics for brain regions associated with seizure onsets compared to non-seizure onset zones. Individual-level prediction showed a performance better than chance in 15 of the 18 patients. The overall predictive performance across all patients yielded a median AUC of 0.81, a median true positive rate of 0.75, and a median true negative rate of 0.83. Furthermore, in a subset of 13 patients, those with negative seizure outcomes showed higher probabilities of seizure onset zone predictions outside the resection area compared to those with good outcomes. SignificanceOverall, our findings suggest that altered temporal dynamics derived from preoperative resting-state fMRI represent a promising non-invasive approach for delineating epileptogenic tissue, potentially informing intervention strategies and guiding electrode placement.

neuroscience↗

bioRxiv2025

cpCST: A New Continuous Performance Test for High-Precision Assessment of Attention Across the Lifespan

Assessing sustained attention presents methodological challenges, particularly when spanning diverse populations whose baseline sensorimotor functioning may vary significantly. This study introduces the Continuous Performance Critical Stability Task (cpCST), a novel paradigm combining high-density sampling of behavior (30Hz), individualized calibration, and fixed-difficulty assessment to measure attentional control. In a sample of 166 adults (ages 18-76), we evaluated the psychometric properties of the cpCSTs instantaneous reaction time (iRT) metric derived through dynamic time warping. Results demonstrated exceptional reliability (bootstrap split-half r = .999), age invariance, and predictive validity for cognitive performance (flanker and Woodcock-Johnson) and cardiorespiratory fitness (est. VO2max). The cpCST achieved high temporal efficiency, with just two minutes of data correlating at r = .94 with full-task performance, outperforming a standard arrow-based flanker task. The cpCSTs individualized calibration effectively isolated attentional control processes from baseline sensorimotor function, eliminating age-related slowing effects typically observed in reaction time tasks. This approach offers methodological advantages for lifespan studies, clinical populations, integration with neurophysiological measures, and computational modeling approaches while addressing limitations of existing attention assessment paradigms.

animal behavior and cognition↗

bioRxiv2023

Fast Connectivity Gradient Approximation: Maintaining spatially fine-grained connectivity gradients while reducing computational costs

Brain connectome analysis suffers from the high dimensionality of connectivity data, often forcing a reduced representation of the brain at a lower spatial resolution or parcellation. However, maintaining high spatial resolution can both allow fine-grained topographical analysis and preserve subtle individual differences otherwise lost. This work presents a computationally efficient approach to estimate spatially fine-grained connectivity gradients and demonstrates its application in improving brain-behavior predictions.

neuroscience↗

bioRxiv2022

Naturalistic viewing: An open-access dataset using simultaneous EEG-fMRI

In this work, we present a dataset that combines functional magnetic imaging (fMRI) and electroencephalography (EEG) to use as a resource for understanding human brain function in these two imaging modalities. The dataset can also be used for optimizing preprocessing methods for simultaneously collected imaging data. The dataset includes simultaneously collected recordings from 22 individuals (ages: 23-51) across various visual and naturalistic stimuli. In addition, physiological, eye tracking, electrocardiography, and cognitive and behavioral data were collected along with this neuroimaging data. Visual tasks include a flickering checkerboard collected outside and inside the MRI scanner (EEG-only) and simultaneous EEG-fMRI recordings. Simultaneous recordings include rest, the visual paradigm Inscapes, and several short video movies representing naturalistic stimuli. Raw and preprocessed data are openly available to download. We present this dataset as part of an effort to provide open-access data to increase the opportunity for discoveries and understanding of the human brain and evaluate the correlation between electrical brain activity and blood oxygen level-dependent (BOLD) signals.

neuroscience↗

bioRxiv2019

Estimates of locus coeruleus function with functional magnetic resonance imaging are influenced by localization approaches and the use of multi-echo data

The locus coeruleus (LC) plays a central role in regulating human cognition, arousal, and autonomic states. Efforts to characterize the LCs function in humans using functional magnetic resonance imaging have been hampered by its small size and location near a large source of noise, the fourth ventricle. We tested whether the ability to characterize LC function is improved by employing neuromelanin-T1 weighted images (nmT1) for LC localization and multi-echo functional magnetic resonance imaging (ME-fMRI) for estimating intrinsic functional connectivity (iFC). Analyses indicated that, relative to a probabilistic atlas, utilizing nmT1 images to individually localize the LC increases the specificity of seed time series and clusters in the iFC maps. When combined with independent components analysis (ME-ICA), ME-fMRI data provided significant gains in the temporal signal to noise ratio relative to denoised single-echo (1E) data. The effects of acquiring nmT1 images and ME-fMRI data did not appear to only reflect increases in power: iFC maps for each approach only moderately overlapped. This is consistent with findings that ME-fMRI offers substantial advantages over 1E data acquisition and denoising. It also suggests that individually identifying LC with nmT1 scans is likely to reduce the influence of other nearby brainstem regions on estimates of LC function.\n\nHighlightsO_LIManual tracing of locus coeruleus increased specificity of seed time series\nC_LIO_LIManual tracing of locus coeruleus increased specificity of intrinsic connectivity\nC_LIO_LIMulti-echo fMRI increased temporal signal-to-noise ratio compared to single-echo fMRI\nC_LIO_LIConnectivity maps across methodologies overlapped only moderately\nC_LIO_LIMeasurement of LC function benefits from multi-echo fMRI and tracing ROIs\nC_LI

neuroscience↗

bioRxiv2019

Relative Concentration of Brain Iron (rcFe) Derived from Standard Functional MRI.

Brain iron plays key roles in catecholaminergic neurotransmitter synthesis and early life brain development. It is also central to cellular energetics and neurotransmitter metabolism throughout the lifespan. Disturbances in brain iron have been implicated in a growing number of psychiatric and late-life neurodegenerative disorders. Additionally, brain iron accumulations are thought to play a deleterious role in neuroinflammatory processes in later life. Despite its importance, the role of brain iron in development, aging, and psychiatric disorders remains comparatively understudied. This is partly due to technical challenges inherent in implementation and analysis of formal iron imaging protocols and practical constraints on scan session durations. Here, we introduce a method to estimate relative brain iron concentrations that is 1) computationally simple, 2) shows excellent correspondence with formal iron imaging in-vivo, 3) replicates clinically-relevant findings from formal iron imaging, 4) yields novel insights into brain iron and cognition across the lifespan, and 5) leverages a widely available and frequently shared brain imaging modality: functional MRI. The computationally simple nature of the measure, coupled with the availability of fMRI datasets across the lifespan and disorders, has the potential to transform our understanding of the complex and critical relationship between iron and brain health.

neuroscience↗