Biology subjects

Forstmann, B. U.

Publications and source records attributed to Forstmann, B. U..

5 recordsLinked to original sources

bioRxiv2026

Giving you five: A neuroimaging atlas of the nigrosomes in the substantia nigra based on 3D histology

Nigrosomes are formed by clusters of pigmented dopaminergic cells in the substantia nigra that critically contribute to dopaminergic function. The ever-increasing resolution of ultra-high-field MRI brings clinical imaging of these clusters into reach, promising unprecedented insight into the functional role of the nigrosomes and their early degeneration in Parkinsons disease. However, due to the nigrosomes small extents and intricate shapes, they are not included in current MRI brain atlases, preventing nigrosome-specific MRI data analysis. We provide a comprehensive 3D histological atlas of the five nigrosomes co-aligned to the widely-used MNI152 2009b space. This atlas is based on 3D-reconstructed, ultra-high-resolution block-face images and gold-standard nigrosome delineations in calbindin-D28K immunohistochemistry. We validated the atlass accuracy using the multimodal ultra-high-resolution post mortem BigBrain dataset and demonstrated its consistency with qualitative nigrosome atlases based on classical 2D histology. We provide detailed usage instructions for applying our atlas to ultra-high-resolution and -field MRI data. The openly available atlas enables neuroimaging studies of the nigrosomes, opening a new avenue toward understanding the differential involvement of the nigrosomes in the healthy and diseased brain and the development of neuroimaging biomarkers of dopaminergic neurodegeneration.

neuroscience↗

bioRxiv2024

Morphometrical asymmetries and tractography of speech-relevant cortex in relation to language lateralisation and rapid temporal processing

Differences in the functional roles of the left and right cortices for speech-related processes have been known since the findings of Broca [1] and Wernicke [2]. Nearly 100 years later anatomical asymmetries of speech-related cortex was emphasised as a potential substrate to such functional lateralisations [3]. Exploration of associations of anatomical asymmetries and functional lateralisations in speech has since continued, with developing technologies and theoretical insights mutually affording increasingly refined understandings. The present study is another such continuance; we outline and report associations of neuroanatomical (morphometrical) and connective (diffusion tractography) measures of speech-related cortex with differences of participant speech lateralisation and rapid temporal acuity (a hypothesised general auditory ability that contributes to superior speech processing). Review and support of developments in methodological approaches to morphometry and tractography to are also provided. Overall, our study affirms complex and selectively overlapping relationships of anatomy and connectivity (especially in the planum temporale) with behavioural language lateralisation and the processing of rapid temporal acoustics. Implications, limitations, and recommendations are discussed.

neuroscience↗

bioRxiv2024

Exploring working memory updating processes of the human subcortex using 7T MRI

A growing body of research suggests that dopamine is involved in working memory updating and that the striatum takes up a critical role in the subprocess of working memory gating (Braver & Cohen, 2000; Cools & DEsposito, 2011; DArdenne et al., 2012; Jongkees, 2020). In this study, we investigated subcortical-in particular, possible dopaminergic-involvement in working memory updating subprocesses using the reference-back task and ultra-high field 7 Tesla fMRI. Using a scanning protocol optimized for BOLD-sensitivity in the subcortex, we found no evidence of subcortical activation during working memory gate opening, predominantly activations in frontoparietal network regions, which challenges the idea of a striatal gating mechanism. However, during gate closing, subcortical activation was observed. Furthermore, a ready-to-update mode demonstrated large-spread subcortical activation, including basal ganglia nuclei, suggesting that the basal ganglia are engaged in general updating processes rather than specifically controlling the working memory gate. Moreover, substituting new information into working memory elicited activation in dopamine-producing midbrain regions along with the striatum, thalamus, and prefrontal cortex, indicating engagement of the basal ganglia-thalamo-cortical loop possibly driven by (potential) dopaminergic activity. These findings expand our understanding of subcortical regions involved in working memory updating, shifting the focus from gate opening to substitution as a midbrain-driven updating process.

neuroscience↗

bioRxiv2020

A new model of decision processing in instrumental learning tasks

Learning and decision making are interactive processes, yet cognitive modelling of error-driven learning and decision making have largely evolved separately. Recently, evidence accumulation models (EAMs) of decision making and reinforcement learning (RL) models of error-driven learning have been combined into joint RL-EAMs that can in principle address these interactions. However, we show that the most commonly used combination, based on the diffusion decision model (DDM) for binary choice, consistently fails to capture crucial aspects of response times observed during reinforcement learning. We propose a new RL-EAM based on an advantage racing diffusion (ARD) framework for choices among two or more options that not only addresses this problem but captures stimulus difficulty, speed-accuracy trade-off, and stimulus-response-mapping reversal effects. The RL-ARD avoids fundamental limitations imposed by the DDM on addressing effects of absolute values of choices, as well as extensions beyond binary choice, and provides a computationally tractable basis for wider applications.

neuroscience↗

bioRxiv2019

Denoising High-field Multi-dimensional MRI with Local Complex PCA

Modern high field and ultra high field magnetic resonance imaging (MRI) experiments routinely collect multi-dimensional data with high spatial resolution, whether multi-parametric structural, diffusion or functional MRI. While diffusion and functional imaging have benefited from recent advances in multi-dimensional signal analysis and denoising, structural MRI has remained untouched. In this work, we propose a denoising technique for multi-parametric quantitative MRI, combining a highly popular denoising method from diffusion imaging, over-complete local PCA, with a reconstruction of the complex-valued MR signal in order to define stable estimates of the noise in the decomposition. With this approach, we show signal to noise ratio (SNR) improvements in high resolution MRI without compromising the spatial accuracy or generating spurious perceptual boundaries.

bioinformatics↗