Biology subjects

Giesbrecht, B.

Publications and source records attributed to Giesbrecht, B..

10 recordsLinked to original sources

bioRxiv2026

Stress Recovery Through Mindful Breathing: Convergent NeuralSignatures in Around-Ear and Scalp EEG

Mindfulness-based interventions effectively reduce stress and anxiety, yet the neural mechanisms underlying contemplative practices and their optimal implementation parameters remain poorly understood. A critical barrier to real-world application is the absence of validated minimally invasive neural recording technologies. Here, we simultaneously recorded full-coverage scalp and around-ear EEG during a 2x2x2 factorial design manipulating (1) cognitive state (mental arithmetic stress vs. passive viewing), (2) recovery strategy (mindful breathing meditation vs. mind-wandering), and (3) sensory context (eyes open vs. eyes closed). Mental arithmetic robustly elevated subjective stress and modulated canonical oscillatory patterns: increased midline frontal theta power (3-7 Hz), suppressed posterior alpha power (10-12 Hz), and enhanced posterior beta and gamma power (25-48 Hz). All rest conditions reduced subjective stress following stress induction, with eyes-closed mindful breathing producing maximal reduction. Critically, mindful breathing differentially modulated temporal beta and gamma power in a context-dependent manner, with effects determined by prior cognitive state and eye position. Eyes-closed meditation maximally suppressed gamma power within 20 seconds following arithmetic stress, whereas eyes-open meditation alone was sufficient for gamma suppression following passive viewing. Around-ear electrodes detected these stress and meditation signatures with comparable fidelity to scalp recordings. These findings reveal that mindful breathing engages rapid, context-dependent neural regulation mechanisms and establish that wearable EEG can reliably capture these dynamics, enabling real-world stress monitoring and mindfulness guidance. Impact StatementMindfulness-based interventions reduce stress, yet their neural mechanisms and optimal implementation remain unclear, partly due to limited real-world neural measurement tools. Using simultaneous scalp and around-ear EEG, we show that mindful breathing rapidly and context-dependently regulates stress-related brain activity via changes in high-frequency EEG oscillations (i.e., gamma band activity), with effects shaped by prior cognitive state and eye condition. Importantly, around-ear EEG captured these neural signatures with fidelity comparable to scalp recordings, enabling wearable neurotechnology for real-world stress monitoring and personalized mindfulness guidance.

neuroscience↗

bioRxiv2026

The temporal organization of memory and emotion is reciprocally coupled

Emotional experiences unfold over time and can bias the appraisal and memory of subsequent events. Yet, it remains unclear whether and how the temporal organization of memory regulates the persistence of affect over time, or affective spillover--and conversely, how emotional-valence dynamics sculpts temporal memory. We developed a novel paradigm employing positive and negative emotional sequences and combined EEG and behavioral measures of temporal memory and affective spillover. Longer remembered temporal distance for emotional-sequence items predicted reduced affective spillover onto later-shown neutral stimuli, whereas better order memory predicted greater spillover. Alpha burst time during emotional-sequence encoding predicted longer remembered temporal distance and modulated spillover in a valence-dependent manner. Conversely, emotional-valence shifts expanded remembered temporal distance and enhanced order memory across sequences. These findings demonstrate reciprocal coupling between temporal memory organization and affect dynamics, revealing how memory structure shapes--and is shaped by--the persistence of emotion.

neuroscience↗

bioRxiv2025

No Disconnection Syndrome after Near-Complete Callosotomy

Sensorimotor processing in the human brain is largely lateralized, with the corpus callosum integrating these processes into a unified experience. Following complete callosotomy, this integration breaks down, resulting in disconnection syndromes. We asked how much of the corpus callosum is sufficient to support functional unity--the absence of disconnection syndrome--by comparing three complete callosotomy patients with one retaining only the splenium. Using lateralized tasks across visual, tactile, visuospatial, and language domains, we predicted domain-specific deficits in the splenium-only patient based on established anatomical models of callosal topography. Strikingly, while complete callosotomy patients exhibited disconnection syndromes, the splenium patient demonstrated functional unity across all domains--as if his entire corpus callosum were intact. Our findings highlight the brains remarkable capacity to maintain behavioral integration through minimal preserved pathways, highlighting how the structure-dependent reorganizational capacity of the human brain allows to preserve functional unity.

neuroscience↗

bioRxiv2025

Full inter-hemispheric integration sustained by a fraction of posterior callosal fibers

The dynamic integration of the lateralized and specialized capacities of the cerebral hemispheres constitutes a hallmark feature of human brain function. This inter-hemispheric exchange of information critically depends upon the corpus callosum. Classical descriptions of callosal organization outline a topographic gradient, such that specific fibers integrate distinct aspects of brain function. Here we present a challenge to this conventional model. Using neuroimaging data obtained from a new cohort of adult corpus callosotomy patients, we leverage modern network neuroscience techniques to show--for the first time--that full inter-hemispheric integration can be achieved via a small proportion ([~]1 cm) of intact posterior callosal fibers. Only complete callosotomy patients demonstrated the expected dissolution of typical inter-hemispheric network architectures, aligning with disconnection syndromes long-thought to reflect diminished information propagation and communication across the brain. These findings motivate a novel mechanistic understanding of synchronized inter-hemispheric neural activity for large-scale human brain function and behavior.

neuroscience↗

bioRxiv2023

Cardiac-sympathetic contractility and neural alpha-band power: cross-modal collaboration during approach-avoidance conflict

As evidence mounts that the cardiac-sympathetic system reacts to challenging cognitive settings, we ask if these responses are passive companions or if they are instead fundamentally intertwined with cognitive function. Healthy human participants performed an approach-avoidance paradigm, trading off monetary reward for painful electric shock, while we recorded simultaneous neural and cardiac signals. Participants were reward-sensitive, but also experienced approach-avoidance "conflict" when the subjective appeal of the reward was near equivalent to the revulsion of the cost. Drift-diffusion model parameters revealed that participants managed conflict in part by integrating larger volumes of evidence into choices (wider decision boundaries). Late alpha-band (neural) dynamics suggested that widening decision boundaries served to combat reward-sensitivity and spread attention more fairly to all dimensions of available information. Independently, wider boundaries were also associated with cardiac "contractility" (an index of sympathetically-mediated positive inotropy). We also saw evidence of conflict-specific collaboration between the neural and cardiac-sympathetic signals. Specific to states of conflict, the alignment (i.e., product) of alpha dynamics and contractility were associated with a further widening of the boundary, independent of either signals singular influence. Cross-trial coherence analyses provided additional support for a direct role of cardiac-sympathetics in nurturing fair assessment of information streams during conflict by disrupting the prepotent reward signals. We conclude that cardiac-sympathetic activity is not a mere companion, rather it is a critical component collaborating with cognitive processes to combat reward-sensitivity during the approach-avoidance conflict.

physiology↗

bioRxiv2023

Establishing the Validity of Compressed Sensing Diffusion Spectrum Imaging

Diffusion Spectrum Imaging (DSI) using dense Cartesian sampling of q-space has been shown to provide important advantages for modeling complex white matter architecture. However, its adoption has been limited by the lengthy acquisition time required. Sparser sampling of q-space combined with compressed sensing (CS) reconstruction techniques has been proposed as a way to reduce the scan time of DSI acquisitions. However prior studies have mainly evaluated CS-DSI in post-mortem or non-human data. At present, the capacity for CS-DSI to provide accurate and reliable measures of white matter anatomy and microstructure in the living human brain remains unclear. We evaluated the accuracy and inter-scan reliability of 6 different CS-DSI schemes that provided up to 80% reductions in scan time compared to a full DSI scheme. We capitalized on a dataset of twenty-six participants who were scanned over eight independent sessions using a full DSI scheme. From this full DSI scheme, we subsampled images to create a range of CS-DSI images. This allowed us to compare the accuracy and inter-scan reliability of derived measures of white matter structure (bundle segmentation, voxel-wise scalar maps) produced by the CS-DSI and the full DSI schemes. We found that CS-DSI estimates of both bundle segmentations and voxel-wise scalars were nearly as accurate and reliable as those generated by the full DSI scheme. Moreover, we found that the accuracy and reliability of CS-DSI was higher in white matter bundles that were more reliably segmented by the full DSI scheme. As a final step, we replicated the accuracy of CS-DSI in a prospectively acquired dataset (n=20, scanned once). Together, these results illustrate the utility of CS-DSI for reliably delineating in vivo white matter architecture in a fraction of the scan time, underscoring its promise for both clinical and research applications.

neuroscience↗

bioRxiv2022

Within- and between-subject reproducibility and variability in multi-modal, longitudinal brain networks

Network analysis provides new and important insights into the function of complex systems such as the brain by examining structural and functional networks constructed from diffusion Magnetic Resonance Imaging (dMRI), functional MRI (fMRI) and Electro/Magnetoencephalography (E/MEG) data. Although network models can shed light on cognition and pathology, questions remain regarding the importance of these findings, due in part to the reproducibility of the core measurements and subsequent modeling strategies. In order to ensure that results are reproducible, we need a better understanding of within- and between-subject variability over long periods of time. Here, we analyze a longitudinal, 8 session, multi-modal (dMRI, and simultaneous EEG-fMRI), and multiple task imaging data set. We first investigate the reproducibility of individual brain connections and network measures and find that across all modalities, within-subject reproducibility is higher than between-subject reproducibility, reaffirming the ability to detect individual differences in network structure in both structural and functional human brain networks. We see high variability in the reproducibility of pairwise connections between brain regions, but observe that in EEG-derived networks, during both rest and task, alpha-band connectivity is consistently more reproducible than networks derived from other frequency bands. Further, reproducible connections correspond to strong connections. Structural networks show a higher reliability in network statistics than functional networks, and certain measures such as synchronizability and eigenvector centrality are consistently less reliable than other network measures across all modalities. Finally, we find that structural dMRI networks outperform functional networks in their ability to identify individuals using a fingerprinting analysis. Our results highlight that functional networks likely reflect state-dependent variability not present in structural networks, and that the analysis of either structural or functional networks to study individual differences should depend on whether or not one wants to take into account state dependencies of the observed networks.

neuroscience↗

bioRxiv2020

EEG signatures of contextual influences on visual search with real scenes

The use of scene context is a powerful way by which biological organisms guide and facilitate visual search. Although many studies have shown enhancements of target-related electroencephalographic activity (EEG) with synthetic cues, there have been fewer studies demonstrating such enhancements during search with scene context and objects in real world scenes. Here, observers covertly searched for a target in images of real scenes while we used EEG to measure the steady state visual evoked response to objects flickering at different frequencies. The target appeared in its typical contextual location or out of context while we controlled for low-level properties of the image including target saliency against the background and retinal eccentricity. A pattern classifier using EEG activity at the relevant modulated frequencies showed target detection accuracy increased when the target was in a contextually appropriate location. A control condition for which observers searched the same images for a different target orthogonal to the contextual manipulation, resulted in no effects of scene context on classifier performance, confirming that image properties cannot explain the contextual modulations of neural activity. Pattern classifier decisions for individual images was also related to the aggregated observer behavioral decisions for individual images. Together, these findings demonstrate target-related neural responses are modulated by scene context during visual search with real world scenes and can be related to behavioral search decisions. Significance StatementContextual relationships among objects are fundamental for humans to find objects in real world scenes. Although there is a larger literature understanding the brain mechanisms when a target appears at a location indicated by a synthetic cue such as an arrow or box, less is known about how the scene context modulates target-related neural activity. Here we show how neural activity predictive of the presence of a searched object in cluttered real scenes increases when the target object appears at a contextual location and diminishes when it appears at a place that is out of context. The results increase our understanding of how the brain processes real scenes and how context modulates object processing.

neuroscience↗

bioRxiv2020

QSIPrep: An integrative platform for preprocessing and reconstructing diffusion MRI

Diffusion-weighted magnetic resonance imaging (dMRI) has become the primary method for non-invasively studying the organization of white matter in the human brain. While many dMRI acquisition sequences have been developed, they all sample q-space in order to characterize water diffusion. Numerous software platforms have been developed for processing dMRI data, but most work on only a subset of sampling schemes or implement only parts of the processing workflow. Reproducible research and comparisons across dMRI methods are hindered by incompatible software, diverse file formats, and inconsistent naming conventions. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing upon a diverse set of software suites to capitalize upon their complementary strengths, QSIPrep automatically applies best practices for dMRI preprocessing, including denoising, distortion correction, head motion correction, coregistration, and spatial normalization. Throughout, QSIPrep provides both visual and quantitative measures of data quality as well as "glass-box" methods reporting. Taken together, these features facilitate easy implementation of best practices for processing of diffusion images while simultaneously ensuring reproducibility.

bioinformatics↗

bioRxiv2018

Dual process coding of recalled location in human oscillatory brain activity

A mental representation of the location of an object can be constructed using sensory information selected from the environment and information stored internally. Human electrophysiological evidence indicates that behaviorally relevant locations, regardless of the source of sensory information, are represented in alpha-band oscillations suggesting a shared process. Here we present evidence from human subjects of either sex for two distinct alpha-band based processes that separately support the representation of location, exploiting sensory evidence sampled either externally or internally.\n\nSignificance StatementOur sensory environment and our internal trains of thought are coded in patterns of brain activity and are used to guide coherent behavior. Oscillations in the alpha frequency band are a predominant feature of human brain activity. This oscillation plays a central role in both selective attention and working memory, suggesting that these important cognitive functions are mediated by a unitary mechanism. We show that the alpha oscillation reflects two distinct processes, one that is supported by continuous sampling of the external sensory environment, and one that is based on sampling from internal representations coded in visual short-term memory. This represents a significant change in our understanding of the nature of alpha oscillations and their relationship to attention and memory.

neuroscience↗