Biology subjects

Aydogan, D. B.

Publications and source records attributed to Aydogan, D. B..

6 recordsLinked to original sources

bioRxiv2026

Autoencoder-based anomaly mapping and visualization of white matter deformation with application to glioma cases

Introduction: Gliomas can alter white matter pathways, causing structural deformation and functional impairments. However, there is no method to map these structural alterations across the whole brain to support diagnosis, prognosis, and treatment planning. To address this gap, we propose a novel framework based on a convolutional autoencoder that learns geometry-preserving streamline embeddings for mapping structural connectivity anomalies. Methods: We trained and validated the autoencoder on 100 million synthetic streamlines and evaluated the anomaly-mapping pipeline using data from 118 healthy subjects. We analyzed how different tractography algorithms affect anomaly scores and demonstrated its feasibility in five glioma patients using multi-shell and single-shell diffusion MRI. Results: Latent-space distances strongly associated with native-space geometric distances (R2 = 0.82-0.98), supporting preserved streamline geometry in the learned embeddings. Anomaly scores varied with both the input and reference tractography methods. Patient anomaly maps showed elevated scores near gliomas and extending distally along affected pathways. These whole-brain anomaly maps were generated within minutes. Conclusion: The framework offers a practical way to quantify and visualize geometric deviations in whole-brain tractograms, providing novel insights beyond current network and microstructural analyses, with relevance to clinical applications where white matter deformation is pertinent.

neuroscience↗

bioRxiv2026

HARP: Hierarchical Anatomical Refinement of Pathways for Whole-Brain Tractography

Diffusion MRI tractography is an ill-posed inverse problem that requires anatomical constraints to ensure the plausibility of reconstructed white-matter pathways. Yet, encoding whole-brain constraints is challenging because neuroanatomical knowledge is fragmented and unevenly distributed across regions and spatial scales. We introduce HARP, a flexible framework that hierarchically injects anatomical constraints at different levels of detail, in parallel with more and more granular brain segmentations. Unlike existing fixed rule-based approaches, HARP enables the systematic, scalable integration of diverse priors within a unified framework. Across multiple tractography algorithms and acquisition protocols, HARP achieves up to a 9% reduction in implausible streamlines. These rejected connections are absent from a ground truth brain phantom, indicating their artifactual origin, and cannot be reliably identified using post-hoc filtering weights alone. By reducing false positive reconstructions, HARP improves the anatomical specificity of tract reconstructions and downstream connectome estimates. More broadly, HARP represents a step toward a collaborative effort to encode neuroanatomical insights in tractography pipelines, with the goal of advancing in vivo whole-brain connectivity studies.

neuroscience↗

bioRxiv2026

Distinct cortical excitability and connectivity profiles within the human SMA complex

Introduction and aimUnderstanding brain functions increasingly relies on a network-based perspective, emphasizing interactions across distributed regions. High-order cognitive functions, like language and executive processes, engage such networks rather than isolated cortical areas, yet mapping their dynamics in humans remains challenging. The supplementary motor area (SMA) complex serves as a crucial hub, functioning as an interface between cognitive and sensorimotor processing. Navigated transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) enables causal, time-resolved assessment of cortical excitability and connectivity with high temporal and spatial precision. Extending prior proof-of-concept work, this study aims to provide normative neurophysiological signatures of the SMA complex (pre-SMA and SMA). MethodsTwenty-one healthy subjects underwent a TMS-EEG session where six stimulation targets over the SMA complex (three in pre-SMA, one in the border between pre-SMA and SMA, two in SMA) were recorded. Global cortical excitability via global mean field power (GMFP) was computed over three time-windows (10-50, 50-100, and 100-200 ms) and compared across targets. Normalized power in different frequency bands (, {beta}1, {beta}2, {gamma}) and natural frequency (NF) were also computed and compared across stimulation sites. Then, we calculated tractography-derived connectivity metrics to examine corticothalamic projections from each stimulation site. Apparent fiber density (AFD)-derived connection strength quantified intra-axonal fibre volume along pathways to the whole thalamus, whereas fibre bundle capacity (FBC) assessed the aggregate intra-axonal cross-sectional area at pathway endpoints, providing an estimate of information transmission capacity to each of the 23 thalamic nuclei. ResultsCortical excitability and oscillatory properties varied significantly across TMS targets. A gradient in cortical excitability was observed, where anterior and middle portions of pre-SMA exhibited significantly lower GMFP in the early post-stimulus phase (i.e., 10-50 ms) than SMA portions; interestingly, these differences were clearly dampened in a later time-window (50-100 ms) and disappeared after this period. Furthermore, higher and lower {beta}2 power were observed in anterior pre-SMA than posterior pre-SMA portions. No differences were observed in NF. Crucially, we also observed significant differences in whole- and single-nuclei thalamic structural connectivity. DiscussionThese findings provide direct human in vivo evidence for distinct neurophysiological and structural connectivity profiles of the pre-SMA and SMA, possibly reflecting their different cytoarchitectonic, myeloarchitectonic and connectivity properties. Variations in cortical excitability, oscillatory dynamics, and FBC along the rostro-caudal axis may mirror functional specialization, with pre-SMA supporting cognitive control processes and SMA engaging motor-related thalamocortical networks. Together, the results demonstrate the sensitivity of TMS-EEG and diffusion-weighted connectomics to measure fine-grained neurophysiological differences of corticothalamic projections, which can lead to individualized neuromodulation targeting.

neuroscience↗

bioRxiv2024

Optimization of TMS target engagement: novel evidence based on combined TMS-EEG and dMRI tractography of brain circuitry

Neuromodulation is based on the principle that brain stimulation produces plastic changes in cerebral circuitry. Given the intersubject structural and functional variability, neuromodulation has a personalized effect in the brain. Moreover, because of cerebral dominance and interhemispheric functional and structural differences in the same individual, the characterization of specific brain circuitries involved is currently not feasible. This notion is extremely important for neuromodulation treatments applied in neuropsychiatry. Specifically, the efficacy of the neuromodulation treatments is critically dependent on the anatomical precision of the brain target and the circuitry which has been affected. However, a complete understanding of how the brain behaves under stimulation needs a combined characterization of its neurophysiological response. This can be achieved by TMS-EEG guided by current multimodal neuroimaging techniques in real time. Herein, we present novel data based on dMRI tractography-guided TMS-EEG on one healthy young adult volunteer.

neuroscience↗

bioRxiv2023

Real-time tractography-assisted neuronavigation for TMS

BackgroundState-of-the-art navigated transcranial magnetic stimulation (nTMS) systems can display the TMS coil position relative to the structural magnetic resonance image (MRI) of the subjects brain and calculate the induced electric field. However, the local effect of TMS propagates via the white-matter network to different areas of the brain, and currently there is no commercial or research neuronavigation system that can highlight in real time the brains structural connections during TMS. ObjectiveTo develop a real-time tractography-assisted TMS neuronavigation system and investigate its feasibility. MethodWe propose a modular framework that seamlessly integrates offline (preparatory) analysis of diffusion MRI data with online (real-time) tractography. For tractography and neuronavigation we combine our custom software Trekker and InVesalius, respectively. We evaluate the feasibility of our system by comparing online and offline tractography results in terms of streamline count and their overlap. ResultsA real-time tractography-assisted TMS neuronavigation system is developed. Key features include the application of state-of-the-art tractography practices, the ability to tune tractography parameters on the fly, and the display of thousands of new streamlines every few seconds using a novel uncertainty visualization technique. We demonstrate in a video the feasibility and quantitatively show the agreement with offline filtered streamlines. ConclusionReal-time tractography-assisted TMS neuronavigation is feasible. With our system, it is possible to target specific brain regions based on their structural connectivity, and to aim for the fiber tracts that make up the brains networks.

neuroscience↗

bioRxiv2018

Limits to anatomical accuracy of diffusion tractography using modern approaches

Diffusion MRI fiber tractography is widely used to probe the structural connectivity of thebrain, with a range of applications in both clinical and basic neuroscience. Despite widespread use, tractography has well-known pitfalls that limits the anatomical accuracy of this technique. Numerous modern methods have been developed to address these shortcomings through advances in acquisition, modeling, and computation. To test whether these advances improve tractography accuracy, we organized the ISBI 2018 3D Validation of Tractography with Experimental MRI (3D-VoTEM) challenge. We made available three unique independent tractography validation datasets - a physical phantom and two ex vivo brain specimens - resulting in 176 distinct submissions from 9 research groups. By comparing results over a wide range of fiber complexities and algorithmic strategies, this challenge provides a more comprehensive assessment of tractographys inherent limitations than has been reported previously. The central results were consistent across all sub-challenges in that, despite advances in tractography methods, the anatomical accuracy of tractography has not dramatically improved in recent years. Taken together, our results independently confirm findings from decades of tractography validation studies, demonstrate inherent limitations in reconstructing white matter pathways using diffusion MRI data alone, and highlight the need for alternative or combinatorial strategies to accurately map the fiber pathways of the brain.

neuroscience↗