Biology subjects

Goodall-Halliwell, I.

Publications and source records attributed to Goodall-Halliwell, I..

6 recordsLinked to original sources

bioRxiv2026

Brain-thought states during movie-watching reflect shared sensory anchors and film- and person- specific processes in association cortex

Naturalistic paradigms such as movie-watching have transformed functional neuroimaging by capturing cognitive dynamics during rich, real-world experiences. A fundamental challenge, however, is determining whether the neural signatures identified during these experiences reflect general principles of cognition or the specific contexts in which they are measured. To address this question, we combined fMRI data from participants watching eight diverse films with continuous reports of ongoing thought. We found that the generalizability of brain-thought relationships depends on the cognitive process being recruited. Neural signatures linked to sensory processing remained robust across films, whereas those involving memory-related association networks depended on how we modelled between-film variability, indicating that cognition becomes increasingly context-dependent along the cortical hierarchy from sensory to association cortex. Within default and limbic networks, we identified two contrasting memory-related states with opposite consequences for comprehension. One, reflecting the integration of prior knowledge with ongoing experience, predicted better narrative comprehension and was revealed only after accounting for between-film variability. The other, associated with stimulus-independent thought, predicted poorer comprehension and emerged only when between-film variability was not modelled. Together, these findings establish when brain-experience relationships measured during naturalistic paradigms can generalize across contexts and when they instead reflect interactions between cognition and the specific environments in which cognition unfolds. More broadly, the consistency of a given brain-experiential association may depend less on where it occurs in the brain and more on the viewer's contextual experience: perceiving the film, drawing on memory to understand it, or drifting away.

neuroscience↗

bioRxiv2026

MICAFlow: Fast and Robust MRI Preprocessing Bridging Research Neuroimaging and Clinical Practice

MICAFlow is a fully automated MRI preprocessing pipeline designed to translate advanced neuroimaging workflows from research into routine clinical practice. The pipeline emphasizes speed, robustness, and ease of use, focusing on structural and diffusion MRI. Key innovations include a Label-Augmented Modality-Agnostic Registration (LAMAReg) technique driven by deep learning segmentations for reliable cross-modal alignment, integration of state-of-the-art distortion corrections, and adherence to reproducible standards (Snakemake workflow, BIDSApp specifications). We describe the design of MICAFlow and evaluate its performance across heterogeneous datasets. First, accessibility: MICAFlow processes a multimodal MRI exam in minutes with clinically accessible hardware and without requiring GPU access, making it feasible for same-day clinical use. Second, registration accuracy: LAMAReg achieves cutting-edge multi-modal registration accuracy, yielding accurate alignment of diffusion MRI, FLAIR, and intra-subject T1-weighted images while remaining generally robust to common artifacts. Third, data reliability: Using identifiability, we show MICAFlow maintains consistent performance across diverse datasets, including subjects with pathology, and is closely comparable to contemporary pipelines. In sum, MICAFlows combination of machine learning and efficient workflows produces research-grade data quality with clinical-grade speed. This work demonstrates that advanced MRI preprocessing can be done fast and robustly, helping close the gap between research neuroimaging and broad clinical application of quantitative MRI techniques. The source code for MICAFlow is available here: https://github.com/MICA-MNI/micaflow, and for LAMAReg here: https://github.com/MICA-MNI/LAMAReg.

bioinformatics↗

bioRxiv2026

The stability of thought: using experience sampling and brain imaging to determine the contextually bound nature of human cognition.

Human behavior is highly flexible, allowing efficient performance across a wide range of task contexts. A distributed set of frontal and parietal regions, commonly termed the multiple-demand network (MDN), is consistently engaged during diverse cognitively demanding tasks and is thought to support this flexibility. However, it remains unclear how patterns of MDN engagement relate to the qualitative features of ongoing cognition experienced during task performance. To address this issue, we examined the reliability of self-reported experiential features sampled during performance of a broad range of tasks. Across tasks, we found little evidence that particular patterns of thought were intrinsically more reliable than others, nor that individual tasks were associated with stable, characteristic thought profiles. Instead, the reliability of specific experiential features varied systematically across task contexts, with the same patterns showing high stability in some tasks and low stability in others. We next asked whether stable patterns of thought were associated with distinct neural signatures. We found that patterns of brain activity resembling the MDN tended to be present for tasks in which deliberate task focus was high, and when distraction was lower, adding to an emerging body of research suggesting that coordinated activity within frontal and parietal regions helps to establish a stable goal-focused mode of thoughts and actions.

neuroscience↗

bioRxiv2026

Precision mapping and molecular contextualization of surgical outcome epicenters in temporal lobe epilepsy

AO_SCPLOWBSTRACTC_SCPLOWTemporal lobe epilepsy is the most common drug-resistant epilepsy, with surgical resection offering the primary path to seizure freedom. Despite standardized approaches, a substantial proportion of patients experience seizure recurrence, and the neurobiological substrates underlying these divergent outcomes remain unclear. We applied an individualized normative modeling framework to multimodal preoperative MRI data in a group that subsequently underwent surgical resection, to characterize patient-specific structural deviations and identify disease epicenters. Patients who became seizure-free exhibited spatially coherent abnormalities localized to the hippocampus and ipsilateral association regions, anchored in agranular limbic territories and enriched for genes linked to calcium-dependent signaling. Non-seizure-free patients, on the other hand, showed a more heterogeneous and distributed pattern of deviations, consistent with a "temporal-plus" network organization, and broader neuromodulatory dysregulation. Crucially, overlap between resected tissue and network-defined epicenters was closely associated with seizure freedom, independent of total resection volume. These findings provide a multiscale framework for precision surgical planning, shifting the focus from standardized tissue removal to targeted disconnection of patient-specific pathological hubs.

neuroscience↗

bioRxiv2024

Mapping patterns of thought onto brain activity during movie-watching

Movie-watching is a central aspect of our lives and an important paradigm for understanding the brain mechanisms behind cognition as it occurs in daily life. Contemporary views of ongoing thought argue that the ability to make sense of events in the here and now depend on the neural processing of incoming sensory information by auditory and visual cortex, which are kept in check by systems in association cortex. However, we currently lack an understanding of how patterns of ongoing thoughts map onto the different brain systems when we watch a film, partly because methods of sampling experience disrupt the dynamics of brain activity and the experience of movie-watching. Our study established a novel method for mapping thought patterns onto the brain activity that occurs at different moments of a film, which does not disrupt the time course of brain activity or the movie-watching experience. We found moments when experience sampling highlighted engagement with multi-sensory features of the film or highlighted thoughts with episodic features, regions of sensory cortex were more active and subsequent memory for events in the movie was better--on the other hand, periods of intrusive distraction emerged when activity in regions of association cortex within the frontoparietal system was reduced. These results highlight the critical role sensory systems play in the multi- modal experience of movie-watching and provide evidence for the role of association cortex in reducing distraction when we watch films. Significance statementStates like movie-watching provide a window into the brain mechanisms behind cognition in daily life. However, we know relatively little about the mapping between brain activity during movies and associated thought patterns because of difficulties in measuring cognition without disrupting how brain activity naturally unfolds. We establish a novel method to link different experiential states to brain activity during movie-watching with minimal interruptions to viewers or disruptions to brain dynamics. We found states of sensory engagement occur in moments of films when activity in visual and auditory cortex are high. In contrast, states of distraction are reduced when activity in frontoparietal regions is high. Our study, therefore, establishes both sensory and association cortex as core features of the movie-watching experience.

neuroscience↗

bioRxiv2022

Patterns of Ongoing Thought in the Real-World

Previous research has indicated that health and well-being are impacted on by both the way we think, and the things we do. In the laboratory, studies suggest that specific task contexts affect this process because the people we are with, the places we are in, and the activities we perform may influence our thought patterns. In our study participants completed multi-dimensional experience-sampling surveys eight times per day for 5 days to generate thought data across a variety of dimensions in daily life. Principal component analysis was used to decompose the experience sampling data, and linear mixed modelling related these patterns to the activity in daily life in which they emerged. Our study replicated the influence of socializing on patterns of ongoing thought observed in our prior study and established that this is part of a broader set of relationship that links our current activities to how our thoughts are organised in daily life. We also found that factors such as time of day and the physical location are associated with reported patterns of thought, factors that are important for future studies to explore. Our study suggests that sampling thinking in the real world may be able to provide a set of comprehensive thinking-activity mappings that will be useful to researchers and health care professionals interested in health and well-being.

neuroscience↗