Biology subjects

Stangl, M.

Publications and source records attributed to Stangl, M..

8 recordsLinked to original sources

bioRxiv2025

Altered coding of environmental boundaries in human aging: an fMRI study

Aging is associated with changes in spatial memory and navigation, yet the mechanisms underlying these changes are not yet fully understood. Environmental boundaries are among the most salient and reliable spatial cues, supporting both spatial memory and orientation. Here, we investigated how aging affects the use and the neural representation of boundary information during a virtual object location memory task. Healthy young and older adults navigated a square virtual environment while undergoing functional magnetic resonance imaging, allowing us to assess moment-to-moment encoding of distance to environmental boundaries in the entorhinal cortex and subiculum. Behaviorally, both age groups showed more accurate memory for objects located near boundaries, but this effect was amplified in older adults, whose spatial precision declined more steeply with increasing distance from boundaries. Older adults also exhibited a stronger bias to recall objects closer to boundaries. Analysis of navigation behaviour revealed that older adults followed boundary-oriented paths regardless of target location, whereas young adults flexibly adapted their navigation based on spatial context. Neurally, older adults--but not young adults--showed significant blood-oxygen-level-dependent modulation by boundary distance in the entorhinal cortex and subiculum, with activity decreasing as participants moved farther from boundaries. This effect was most pronounced in low-performing older adults and was associated with stronger behavioral boundary bias, suggesting a maladaptive reliance on proximity-based cues. Together, our results provide converging behavioral and neural evidence that aging alters the use and representation of boundary information, with downstream effects on spatial memory. Altered boundary processing may represent a key mechanism contributing to age-related declines in spatial cognition.

neuroscience↗

bioRxiv2025

A Novel TRPC6 Mutation Causes Autosomal Dominant FSGS

FSGS is the most common primary glomerular lesion that causes kidney failure in the US. FSGS results from injury or loss of glomerular visceral epithelial cells (i.e. podocytes). Pathogenic variants in TRPC6 can cause FSGS through dysregulated calcium conductance and associated disturbances in podocyte physiology. Here, we describe a 5-generation kindred with FSGS caused by a novel compound C-terminal TRPC6 mutation. Analysis of patient-specific iPSC-derived podocytes and glomerular capillary wall-on-a-chip systems revealed that the compound variants disrupt TRPC6 protein structure, intermolecular interactions, and membrane localization. Combined therapy with Sildenafil and Losartan ameliorated these disturbances compared to conventional immunosuppressive treatment.

genetics↗

bioRxiv2024

Human neural dynamics of real-world and imagined navigation

The ability to form episodic memories and later imagine them is integral to the human experience, influencing our recollection of the past and our ability to envision the future. While research on spatial navigation in rodents suggests the involvement of the medial temporal lobe (MTL), especially the hippocampus, in these cognitive functions, it is uncertain if these insights apply to the human MTL, especially regarding imagination and the reliving of events. Importantly, by involving human participants, imaginations can be explicitly instructed and their mental experiences verbally reported. In this study, we investigated the role of hippocampal theta oscillations in both real-world and imagined navigation, leveraging motion capture and intracranial electroencephalographic recordings from individuals with chronically implanted MTL electrodes who could move freely. Our results revealed intermittent theta dynamics, particularly within the hippocampus, which encoded spatial geometry and partitioned navigational routes into linear segments during real-world navigation. During imagined navigation, theta dynamics exhibited similar, repetitive patterns despite the absence of external environmental cues. Furthermore, a computational model, generalizing from real-world to imagined navigation, successfully reconstructed participants imagined positions using neural data. These findings offer unique insights into the neural mechanisms underlying human navigation and imagination, with implications for understanding episodic memory formation and retrieval in real-world settings.

neuroscience↗

bioRxiv2023

Path integration selectively predicts midlife risk of Alzheimer's disease

The entorhinal cortex (EC) is the first cortical region to exhibit neurodegeneration in Alzheimers disease (AD), associated with EC grid cell dysfunction. Given the role of grid cells in path integration, we predicted that path integration impairment would represent the first behavioural change in adults at-risk of AD. Using immersive virtual reality, we found that midlife path integration impairments predicted both hereditary and physiological AD risk, with no corresponding impairment on tests of episodic memory or other spatial behaviours. Impairments related to poorer angular estimation and were associated with hexadirectional grid-like fMRI signal in the posterior-medial EC. These results indicate that altered path integration may represent the transition point from at-risk state to disease onset in AD, prior to impairment in other cognitive domains.

neuroscience↗

bioRxiv2022

Entorhinal grid-like codes and time-locked network dynamics track others navigating through space

Navigating through crowded, dynamically changing social environments requires the ability to keep track of other individuals. Grid cells in the entorhinal cortex are a central component of self-related navigation but whether they also track others movement is unclear. Here, we propose that entorhinal grid-like codes make an essential contribution to socio-spatial navigation. Sixty human participants underwent functional magnetic resonance imaging (fMRI) while observing and re-tracing different paths of a demonstrator that navigated a virtual reality environment. Results revealed that grid-like codes in the entorhinal cortex tracked the other individual navigating through space. Further, the activity of grid-like codes was time-locked to increases in co-activation and entorhinal-cortical connectivity that included the striatum, the hippocampus, parahippocampal and right posterior parietal cortices, altogether modulated by accuracy when subsequently re-tracing the paths. This suggests that network dynamics time-locked to entorhinal grid-cell-related activity might serve to distribute information about the socio-spatial map throughout the brain.

neuroscience↗

bioRxiv2020

Wireless Programmable Recording and Stimulation of Deep Brain Activity in Freely Moving Humans

Current implantable devices that allow for recording and stimulation of brain activity in humans are not inherently designed for research and thus lack programmable control and integration with wearable sensors. We developed a platform that enables wireless and programmable intracranial electroencephalographic recording and deep brain stimulation integrated with wearable technologies. This methodology, when used in freely moving humans with implanted neural devices, can provide an ecologically valid environment conducive to elucidating the neural mechanisms underlying naturalistic behaviors and developing viable therapies for neurologic and psychiatric disorders.

neuroscience↗

bioRxiv2018

Sources of path integration error in young and aging humans

Path integration is a vital function in navigation: it enables the continuous tracking of ones position in space by integrating self-motion cues. Path integration abilities vary across individuals but tend to deteriorate in old age. The specific causes of path integration errors, however, remain poorly characterized. Here, we combined tests of path integration performance with a novel analysis based on the Langevin diffusion equation, which allowed us to decompose errors into distinct causes that can corrupt path integration computations. Across age groups, the dominant errors were due to noise and a bias in speed estimation. Noise-driven errors accumulated with travel distance not elapsed time, suggesting that the dominant noise originates in the velocity input rather than within the integrator. Age-related declines were traced primarily to a growth in this unbiased noise. Together, these findings shed light on the contributors to path integration error and the mechanisms underlying age-related navigational deficits.

neuroscience↗

bioRxiv2017

The GridCAT: A toolbox for automated analysis of human grid cell codes in fMRI

Human fMRI studies examining the putative firing of grid cells (i.e., the grid code) suggest that this cellular mechanism supports not only spatial navigation, but also more abstract cognitive processes. This research area, however, remains relatively unexplored, perhaps us to the complexities of data analysis. To overcome this, we have developed the Matlab-based Grid Code Analysis Toolbox (GridCAT), providing a graphical user interface, and open-source code, for the analysis of fMRI data. The GridCAT performs all analyses, from estimation and fitting of the grid code in the general linear model, to the generation of grid code metrics and plots. Moreover, it is flexible in allowing the specification of bespoke analysis pipelines; example data are provided to demonstrate the GridCATs main functionality. We believe the GridCAT is essential to opening this research area to the imaging community, and helping to elucidate the role of human grid codes in higher-order cognitive processes.\n\nHighlightsO_LIThe putative firing of grid cells (i.e., the grid code) can be examined using fMRI\nC_LIO_LINecessary steps for grid code analysis are reviewed\nC_LIO_LIThe Matlab-based grid code analysis toolbox (GridCAT) is introduced\nC_LIO_LIAutomated grid code analysis can be conducted either via a graphical user interface or open-source code\nC_LIO_LIA detailed manual and an example dataset are provided\nC_LI

neuroscience↗