Michelle Moerel

Post-COVID is a complex, multi-system disorder with symptoms persisting for months to years. While it affects increasing numbers of individuals worldwide, no targeted treatments currently exist. To address this gap, we used pyBioDataFuse to construct a disease-specific post-COVID knowledge graph, integrating transcriptomics data from post-COVID patient muscle biopsies with data from multiple curated molecular resources. The resulting graph comprised 13,284 nodes and 54,009 edges, covering molecular interactions, gene-disease associations, and drug-target relationships. Two complementary network-based drug repurposing algorithms, DREAMwalk and PoLo, were applied to prioritize therapeutic candidates. The identified candidates span mechanistically distinct drug classes including GABAergic modulators, ion channel modulators, and BTK inhibitors. These candidates collectively reflect the multi-faceted nature of post-COVID. Several GABAergic modulators and Metformin, a metabolic agent with anti-inflammatory properties, emerged as the strongest cross-algorithm candidates, with Metformin supported by observational evidence of an association with reduced post-COVID incidence. This reproducible, open-source pipeline provides a transparent and extensible framework for network-based drug repurposing in post-COVID and other complex diseases

The thalamic reticular nucleus (TRN) is a thin, inhibitory shell surrounding the thalamus. It regulates the thalamocortical information flow, and thereby plays a central role in attention, task switching, and the sleep-wake cycle. Despite its importance, the TRN remains poorly studied in the human brain. This is largely because its small size and deep anatomical location limit its visibility with conventional non-invasive neuroimaging techniques. Here, we assessed whether the human TRN can be reliably visualised and segmented in vivo using ultra-high field (UHF) magnetic resonance imaging (MRI) at 7 Tesla. High resolution (0.35 mm isotropic) partial-brain T2* and T1 scans were acquired from healthy individuals, followed by manual delineation of the TRN. These in vivo segmentations were compared with TRN estimates obtained from two high-quality postmortem datasets serving as an anatomical reference. In vivo segmentations of TRN volume and thickness closely matched measurements derived from the postmortem reference datasets, and quantitative comparisons showed high consistency in TRN shape and location across individuals while also capturing meaningful inter-individual variability. Using these segmentations, we constructed a publicly available probabilistic atlas of the human TRN. This atlas provides a new resource for incorporating TRN anatomy into functional, structural, and clinical neuroimaging studies. Our findings demonstrate that the human TRN can be robustly mapped in vivo at 7T and establish a foundation for future investigations into its structure and function.

Memory plays a crucial role in human cognitive processes and daily functioning. While memory has a genetic basis, identifying the specific genetic factors influencing memory performance has proven challenging. This challenge arises because memory is a complex trait, whose genetic architecture likely comprises an accumulation of many low-effect size common variants. Thus, study sample sizes are easily insufficient, leading to underpowered genetic association analyses. This limitation is especially pronounced in studies that prioritize deep phenotyping over broader recruitment, resulting in smaller cohorts. Given these limitations, important biological signals may remain undetected when relying solely on conventional genome-wide significance thresholds. However, even variants that fall below these thresholds can yield meaningful insights when analyzed in a broader biological context. Therefore, we propose that relevant biological information can still be extracted by employing a less stringent p -value threshold paired with elaborate variant mapping and functional annotation to identify candidate variants, genes, and biological pathways associated with memory performance. We present three independent genome-wide association studies within the Human Connectome Project on a (i) Penn-Word verbal episodic memory test ( n = 1131), a (ii) Picture Sequence visual episodic memory test ( n = 1133), and a (iii) List Sorting verbal working memory test ( n = 1134). Subsequent variant mapping, functional annotation, and pathway identification were performed using FUMA, Cytoscape, KEGG, Reactome, and WikiPathways. At the pathway level, but not single variant or gene level, we observed substantial overlap in results across the three memory tests, and between our results and previously reported findings. Several identified genes and pathways were previously associated with memory-related disorders, and processes related to cognition, neurodevelopment, and neurological dysfunction. We interpret the common pathways as reflecting shared biological mechanisms underlying memory. Our findings underscore the potential of our proposed approach, which we provide as an openly accessible pipeline, for exploring other complex polygenic traits.

Mitochondria play a crucial role in human biology, affecting cellular processes at the smallest spatial scale as well as those involved in the functionality of the whole system. Imaging is the most important research tool for studying the fundamental role of mitochondria across these diverse spatial scales. A wide array of available imaging techniques have enabled us to visualize mitochondrial structure and behavior, as well as their effect on cells and tissues in a range from micrometers to centimeters. Each of the various imaging techniques that are available offers unique advantages tailored to specific research needs. Selecting an appropriate technique suitable for the scale and application of interest is therefore crucial, but can be challenging due to the large range of possibilities. The aim of this review is two-fold. First, we provide an overview of the available imaging techniques and discuss their strengths and limitations for applications across the sub-mitochondrial, cellular, tissue and organ levels for the imaging of mitochondria. Second, we identify opportunities for novel applications and advancement in the field. We emphasize the importance of integration across scales in mitochondrial imaging studies, particularly to bridge the gap between microscopic and non-invasive techniques. While integrating these diverse scales is challenging, primarily because such multi-scale approaches require expertise that spans different imaging modalities, we argue that integration has the potential to provide groundbreaking insights into mitochondrial biology. By providing a comprehensive overview of imaging techniques, this review paves the way for multi-scale imaging initiatives in mitochondrial research.

Selective attention enables the preferential processing of relevant stimulus aspects. Invasive animal studies have shown that attending a sound feature rapidly modifies neuronal tuning throughout the auditory cortex. Human neuroimaging studies have reported enhanced auditory cortical responses with selective attention. To date, it remains unclear how the results obtained with functional magnetic resonance imaging (fMRI) in humans relate to the electrophysiological findings in animal models. Here we aim to narrow the gap between animal and human research by combining a selective attention task similar in design to those used in animal electrophysiology with high spatial resolution ultra-high field fMRI at 7 Tesla. Specifically, human participants perform a detection task, whereas the probability of target occurrence varies with sound frequency. Contrary to previous fMRI studies, we show that selective attention resulted in population receptive field sharpening, and consequently reduced responses, at the attended sound frequencies. The difference between our results to those of previous fMRI studies supports the notion that the influence of selective attention on auditory cortex is diverse and may depend on context, stimulus, and task.

Tinnitus is a clinical condition where a sound is perceived without external sound source. Homeostatic plasticity (HSP), serving to increase neural activity as compensation for the reduced input to the auditory pathway after hearing loss, has been proposed as causal mechanism underlying tinnitus. In support, animal models of tinnitus show evidence of increased neural activity after hearing loss, including increased spontaneous and sound-driven firing rate, as well as increased neural noise throughout the auditory processing pathway. Bridging these findings to human tinnitus, however, has proven to be challenging. Here we implement hearing loss-induced HSP in a Wilson-Cowan Cortical Model of the auditory cortex to predict how homeostatic principles operating at the microscale translate to the meso- to macroscale accessible through human neuroimaging. We observed HSP-induced response changes in the model that were previously proposed as neural signatures of tinnitus. As expected, HSP increased spontaneous and sound-driven responsiveness in hearing-loss affected frequency channels of the model. We furthermore observed evidence of increased neural noise and the appearance of spatiotemporal modulations in neural activity, which we discuss in light of recent human neuroimaging findings. Our computational model makes quantitative predictions that require experimental validation, and may thereby serve as the basis of future human tinnitus studies. Highlights: We implement homeostatic plasticity (HSP) in an auditory cortex computational model After HSP, model behavior shows neural signatures of tinnitus Increased neural noise and oscillations match human neuroimaging findings The proposed model can serve to design future human tinnitus studies

Selective attention enables the preferential processing of relevant stimulus aspects. Invasive animal studies have shown that attending a sound feature rapidly modifies neuronal tuning throughout the auditory cortex. Human neuroimaging studies have reported enhanced auditory cortical responses with selective attention. To date, it remains unclear how the results obtained with functional magnetic resonance imaging (fMRI) in humans relate to the electrophysiological findings in animal models. Here we aim to close the gap between animal and human research by combining a selective attention task similar in design to those used in animal electrophysiology with high spatial resolution ultra-high field fMRI at 7 Tesla. Specifically, human participants perform a detection task, while the probability of target occurrence varies with sound frequency. Contrary to previous fMRI studies, we show that selective attention reduces responses to the attended frequencies in those neuronal populations preferring the attended frequency. Through population receptive field (pRF) mapping, we furthermore show that these response reductions are at least partially driven by frequency-induced pRF narrowing. The difference between our results to those of previous fMRI studies supports the notion that the influence of selective attention on auditory cortex is diverse and may depend on context, task, and auditory processing stage.

Recent studies have highlighted the possible contributions of direct connectivity between early sensory cortices to audiovisual integration. Anatomical connections between the early auditory and visual cortices are concentrated in visual sites representing the peripheral field of view. Here, we aimed to engage early sensory interactive pathways with simple, far-peripheral audiovisual stimuli (auditory noise and visual gratings). Using a modulation detection task in one modality performed at an 84% correct threshold level, we investigated multisensory interactions by simultaneously presenting weak stimuli from the other modality in which the temporal modulation was barely-detectable (at 55 and 65% correct detection performance). Furthermore, we manipulated the temporal congruence between the cross-sensory streams. We found evidence for an influence of barely-detectable visual stimuli on the response times for auditory stimuli, but not for the reverse effect. These visual-to-auditory influences only occurred for specific phase-differences (at onset) between the modulated audiovisual stimuli. We discuss our findings in the light of a possible role of direct interactions between early visual and auditory areas, along with contributions from the higher-order association cortex. In sum, our results extend the behavioral evidence of audio-visual processing to the far periphery, and suggest – within this specific experimental setting – an asymmetry between the auditory influence on visual processing and the visual influence on auditory processing.