Biology subjects

Gallinat, J.

Publications and source records attributed to Gallinat, J..

13 recordsLinked to original sources

bioRxiv2025

Amyloid-β 42-carrying extracellular vesicles are associated with neurodegeneration and neuroinflammation in Alzheimer's disease

Alzheimers disease (AD) is the most common form of dementia, characterized by progressive amyloid-{beta} (A{beta}) accumulation and neurodegeneration. Extracellular vesicles (EVs) have been implicated in AD pathology, but their relationship to disease progression and the cerebrospinal fluid (CSF) proteome remains poorly understood. In this study, we analysed plasma-derived A{beta}42-containing EVs from participants of the Alzheimers Disease Neuroimaging Initiative (ADNI) and calculated the ratio between the percentage of A{beta}42-positive peripheral EVs and CSF A{beta}42 (rA{beta}42). This ratio was elevated in AD and positively correlated with amyloid pathology as measured by PET. Longitudinal analyses revealed that higher rA{beta}42 values predicted accelerated hippocampal atrophy and cognitive decline, independent of CSF A{beta}42 concentrations. Proteomic profiling of CSF using the SomaScan platform showed that rA{beta}42 was associated with an inflammatory signature characterized by myeloid activation and type II interferon-related signalling pathways. Together, these findings indicate that A{beta}42-carrying EVs reflect an active and inflammatory component of AD pathology and may represent a novel class of biomarkers for disease progression. Understanding the mechanisms that link A{beta}42-positive EVs to neuroinflammatory signalling could open new avenues for pathway-specific diagnostics and therapeutic strategies in AD.

neuroscience↗

bioRxiv2023

Linking cognitive integrity to working memory dynamics in the aging human brain

Aging is accompanied by a decline of multiple cognitive capacities, including working memory: the ability to maintain information online for the flexible control of behavior. Working memory involves stimulus-selective neural activity, persisting after stimulus presentation in widely distributed cortical areas. Here, we unraveled the mechanisms of working memory in healthy older adults and patients with mild cognitive impairment (MCI), a condition associated with increased risk of developing dementia. We studied a sample of 19 older adults diagnosed with MCI and 20 older healthy controls using a combination of model-based behavioral psychophysics, neuropsychological assessment, and magnetoencephalographic (MEG) recordings of brain activity. Twenty-one younger healthy adults were studied with model-based behavioral psychophysics only. All subjects performed a visuo-spatial delayed-match-to-sample working memory task under systematic manipulation of the temporal delay and the spatial distance between successively presented sample and test stimuli. We developed a computational model of the latent dynamics underlying task behavior and fit this to individual behavior. In the model, working memory representations diffused over time, a threshold was applied to produce a match/non-match decision about sample and test locations, and occasional lapses produced random decisions. For the older participants, we related the individual model parameters to a summary measure of individual cognitive integrity obtained from a large neuropsychological test battery, as well as to cortical MEG activity during the delay interval of the working memory task. For all groups, task accuracy decreased with delay duration and sample-test distance. When sample/test distances were small, older adults exhibited larger false alarm rates than younger adults. The behavioral effects were well captured by the model, which explained the age-related differences in terms of a deterioration of the quality of working memory representations, rather than differences in task strategy (i.e., threshold parameter). Task accuracy as well as the parameters governing behavioral stochasticity (diffusion noise and lapse rate combined) were correlated with overall cognitive integrity in the MCI group, but not in the older healthy controls. Individual task accuracy and stochasticity parameters (diffusion noise and lapse rate) were also correlated with stimulus-selective cortical activity during the delay interval, as assessed by decoding of the MEG signals, corroborating their validity as markers of cortical working memory mechanisms. Our findings provide insight into the mechanistic basis of aging-related changes in working memory maintenance and reveal a link between individual working memory dynamics and cognitive integrity in MCI.

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bioRxiv2023

A Latent Clinical-anatomical Dimension Relating Metabolic Syndrome to Brain Morphology - Evidence from a Multivariate Imaging Analysis of 40,087 Individuals

The link between metabolic syndrome (MetS) and neurodegenerative as well cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between MetS and brain health by conducting a comprehensive examination of cardiometabolic risk factors, cortical morphology, and cognitive function in 40,087 individuals. Multivariate, data-driven statistics identified a latent dimension linking more severe MetS to widespread brain morphological abnormalities, accounting for up to 71% of shared variance in the data. This dimension was replicable across sub-samples. In a mediation analysis we could demonstrate that MetS-related brain morphological abnormalities mediated the link between MetS severity and cognitive performance in multiple domains. Employing imaging transcriptomics and connectomics, our results also suggest that MetS-related morphological abnormalities are linked to the regional cellular composition and macroscopic brain network organization. By leveraging extensive, multi-domain data combined with a dimensional stratification approach, our analysis provides profound insights into the association of MetS and brain health. These findings can inform effective therapeutic and risk mitigation strategies aimed at maintaining brain integrity.

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bioRxiv2022

Brain Network Architecture Constrains Age-related Cortical Thinning

Age-related cortical atrophy, approximated by cortical thickness measurements from magnetic resonance imaging, follows a characteristic pattern over the lifespan. Although its determinants remain unknown, mounting evidence demonstrates correspondence between the connectivity profiles of structural and functional brain networks and cortical atrophy in health and neurological disease. Here, we performed a cross-sectional multimodal neuroimaging analysis of 2633 individuals from a large population-based cohort to characterize the association between age-related differences in cortical thickness and functional as well as structural brain network topology. We identified a widespread pattern of age-related cortical thickness differences including "hotspots" of strong age effects located in brain areas with high centrality (structural network hubs). Regional age-related differences were furthermore strongly correlated within the structurally defined node neighborhood. The overall pattern of thickness differences as well as its change throughout the later lifespan was found to be anchored in the functional network hierarchy as encoded by macroscale functional connectivity gradients. Lastly, the identified difference pattern covaried significantly with cognitive and motor performance. Our findings indicate that connectivity profiles of functional and structural brain networks might act as organizing principles behind age-related cortical thinning as an imaging surrogate of cortical atrophy.

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bioRxiv2022

Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity

Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates R1 and [Formula], proton density PD, and magnetization transfer saturation MTsat) that are sensitive to microstructural tissue properties such as iron and myelin content. Their capability to reveal microstructural brain differences, however, is tightly bound to controlling random noise and artefacts (e.g. caused by head motion) in the signal. Here, we introduced a method to estimate the local error of PD, R1 and MTsat maps that captures both noise and artefacts on a routine basis without requiring additional data. To investigate the methods sensitivity to random noise, we calculated the model-based signal-to-noise ratio (mSNR) and showed in measurements and simulations that it correlated linearly with an experimental raw-image-based SNR map. We found that the mSNR varied with MPM protocols, magnetic field strength (3T vs. 7T) and MPM parameters: it halved from PD to R1 and decreased from PD to MTsat by a factor of 3-4. Exploring the artefact-sensitivity of the error maps, we generated robust MPM parameters using two successive acquisitions of each contrast and the acquisition-specific errors to down-weight erroneous regions. The resulting robust MPM parameters showed reduced variability at the group level as compared to their single-repeat or averaged counterparts. The error and mSNR maps may better inform power-calculations by accounting for local data quality variations across measurements. Code to compute the mSNR maps and robustly combined MPM maps is available in the open-source hMRI toolbox.

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bioRxiv2019

Stereoscopic Rendering in a Head Mounted Display Elicits Higher Functional Connectivity During Virtual Reality

Virtual reality (VR) simulates real world scenarios by creating a presence in users. Such immersive scenarios lead to more similar behaviour to that displayed in real world settings, which may facilitate the transfer of knowledge and skills acquired in VR to real world situations. VR has already been used in education, psychotherapy, rehabilitation and it is an appealing choice for training intervention. The aim was to investigate to what extend VR technology can be used in a magnetic resonance imaging scanner(MRI), addressing the question of whether brain connectivity differs between VR and screen via mirror projection presentations. Moreover, we investigate whether stereoscopic goggle stimulation, where eyes receive different input, would elicit more brain connectivity than stimulation where both eyes receive the same input (monoscopic). To our knowledge, there is no previous research addressing this question. Multiple analyses were performed to cover different aspects of brain connectivity: fractional low frequency fluctuation, independent component analysis, seed-based functional connectivity and graph analysis. In goggles (mono and stereoscopic) vs. screen, we found connectivity differences in cerebellum and postcentral gyrus and in visual and frontal inferior cortex in visual/default-mode networks. Considering specific areas, we found higher connectivity between superior frontal cortex and temporal lobe, as well as inferior parietal cortex with calcarine and lingual. Furthermore, superior frontal cortex and insula/putamen were more strongly connected in stereoscopic, in line with our hypothesis. We assume that conditions eliciting most connectivity should be suited for long-term interventions as extended training under these conditions could permanently improve functional/structural connectivity.

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bioRxiv2019

Sleep, regional grey matter volumes, and psychological functioning in adolescents

Changing sleep rhythms in adolescents often lead to sleep deficits and increased variability in sleep schedules. The adolescent brain, and in particular the rapidly developing structures involved in emotional control, are vulnerable to external and internal factors. In our previous study in adolescents at age 14, we observed a strong relationship between weekend sleep schedules and regional medial prefrontal cortex grey matter volumes. Here, we aimed to assess whether this relationship remained in this group of adolescents of the general population at the age of 16 (n=101; mean age 16.8 years; 55% girls). We further examined grey matter volumes in the hippocampi and the amygdalae, calculated with voxel-based morphometry. In addition, we investigated the relationship between regional grey matter volumes with psychological functioning. Sleep was assessed with self-reports and psychological functioning with the Strengths and Difficulties Questionnaire and tests on working memory and impulsivity. Later weekend wake-up times were associated with smaller grey matter volumes in the medial prefrontal cortex and the amygdalae, and greater weekend delays in wake-up time were associated with smaller grey matter volumes in the right hippocampus and amygdala. The medial prefrontal cortex region mediated the correlation between weekend wake up time and both externalising and internalising symptoms. Paying attention to regular sleep habits during adolescence could act as a protective factor against the emergence of psychopathology via enabling favourable brain development.

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bioRxiv2018

Altered resting state functional connectivity in a thalamo-cortico-cerebellar network in patients with schizophrenia

Schizophrenia is described as a disease in which complex psychopathology together with cognitive and behavioral impairments are related to widely disrupted brain circuitry causing a failure in coordinating information across multiple brain sites. This led to the hypothesis of schizophrenia as a network disease e.g. in the cognitive dysmetria model and the dysconnectivity theory. Nevertheless, there is no consensus regarding localized mechanisms, namely dysfunction of certain networks underlying the multifaceted symptomatology.\n\nIn this study, we investigated potential functional disruptions in 35 schizophrenic patients and 41controls using complex cerebral network analysis, namely network-based statistic (NBS) and graph theory in resting state fMRI. NBS can reveal locally impaired subnetworks whereas graph analysis characterizes whole brain network topology.\n\nUsing NBS we observed a local hyperconnected thalamo-cortico-cerebellar subnetwork in the schizophrenia group. Furthermore, nodal graph measures retrieved from the thalamo-cortico-cerebellar subnetwork revealed that the total number of connections from/to (degree) of the thalamus is higher in patients with schizophrenia. Interestingly, graph analysis on the whole brain functional networks did not reveal group differences. Together, our results suggest that disruptions in the brain networks of schizophrenia patients are situated at the local level of the hyperconnected thalamo-cortico-cerebellar rather than globally spread in brain.\n\nOur results provide further evidence for the importance of the thalamus and cerebellum in schizophrenia and to the notion that schizophrenia is a network disease in line with the dysconnectivity theory and cognitive dysmetria model.

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bioRxiv2018

Reduced Resting-State Connectivity in the Precuneus is correlated with Apathy in Patients with Schizophrenia

A diagnosis of schizophrenia is associated with a heterogeneous psychopathology including positive and negative symptoms. The disconnection hypothesis, an early pathophysiological framework conceptualizes the diversity of symptoms as a result from disconnections in neural networks. In line with this hypothesis, previous neuroimaging studies of patients with schizophrenia reported alterations within the default mode network (DMN), the most prominent network at rest.\n\nAim of the present study was to investigate the functional connectivity during rest in patients with schizophrenia and healthy individuals and explore whether observed functional alterations are related to the psychopathology of patients. Therefore, functional magnetic resonance images at rest were recorded of 35 patients with schizophrenia and 41 healthy individuals. Independent component analysis (ICA) was used to extract resting state networks.\n\nComparing ICA results between groups indicated alterations only within the network of the DMN. More explicitly, reduced connectivity in the precuneus was observed in patients with schizophrenia compared to healthy controls. Connectivity in this area was negatively correlated with the severity of negative symptoms, more specifically with the domain of apathy.\n\nTaken together, the current results provide further evidence for a role DMN alterations might play in schizophrenia and especially in negative symptom such as apathy.

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bioRxiv2018

New graph-theoretical-multimodal approach using temporal and structural correlations reveal disruption in the thalamo-cortical network in patients with schizophrenia

Schizophrenia has been understood as a network disease with altered functional and structural connectivity in multiple brain networks compatible to the extremely broad spectrum of psychopathological, cognitive and behavioral symptoms in this disorder.\n\nWhen building brain networks, functional and structural networks are typically modelled independently: functional network models are based on temporal correlations among brain regions, whereas structural network models are based on anatomical characteristics. Combining both features may give rise to more realistic and reliable models of brain networks.\n\nIn this study, we applied a new flexible graph-theoretical-multimodal model called FD (F, the functional connectivity matrix, and D, the structural matrix) to construct brain networks combining functional, structural and topological information of MRI measurements (structural and resting state imaging) to patients with schizophrenia (N=35) and matched healthy individuals (N=41). As a reference condition, the traditional pure functional connectivity (pFC) analysis was carried out.\n\nBy using the FD model, we found disrupted connectivity in the thalamo-cortical network in schizophrenic patients, whereas the pFC model failed to extract group differences after multiple comparison correction. We interpret this observation as evidence that the FD model is superior to conventional connectivity analysis, by stressing relevant features of the whole brain connectivity including functional, structural and topological signatures. The FD model can be used in future research to model subtle alterations of functional and structural connectivity resulting in pronounced clinical syndromes and major psychiatric disorders. Lastly, FD is not limited to the analysis of resting state fMRI, and can be applied to EEG, MEG etc.

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bioRxiv2018

Evaluation of FlowVR: a virtual reality game for improvement of depressive mood

ObjectiveThis study evaluated the efficacy of FlowVR, a virtual reality (VR) game designed to improve mood and reduce feelings of depression. The aim is to contribute to the question of whether and how VR could be used for depression therapy, as research in this area is quite rare.\n\nMethod18 healthy participants (9 female; Mage = 25.9) underwent three conditions, playing FlowVR in VR with a head-mounted display, playing FlowVR on a tablet or reading a text on a tablet. For each condition, they were tested on a separate day at the same time of day within a two-week period. Before and after every condition participants completed the Becks Depression Inventory II (BDI-II), the state part of the State-Trait-Anxiety-Depression-Inventory (STADI(S)) and the Positive Affect Negative Affect Schedule-Expanded Form (PANAS-X).\n\nResultsWhile the participants showed only a reduction in acute anxiety in the control and the tablet conditions, they showed improved affectivity in all variables measured in the VR condition. In addition, VR had significantly better results than the control condition in improving positive affectivity, negative affectivity and acute feelings of depression. Using a less conservative statistical approach, these significant differences could also be found between the tablet and the VR condition. There were no significant differences between the tablet and the control condition.\n\nConclusionThe results indicate that due to its immersive nature, VR can be used effectively to improve mood and temporarily reduce feelings of depression. Long-term effects of FlowVR on participants with depression must be investigated in consecutive research.

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bioRxiv2018

3-D navigation: A core driver of brain plasticity in video game interventions

Recent evidence has repeatedly shown that 3D platform video game training leads to substantial brain structural plasticity in hippocampus, prefrontal cortex and cerebellum. However, a great disadvantage of using complex video game interventions is the difficulty to attribute the observed effects to specific game mechanics.\n\nIn order to address this caveat, we conducted a longitudinal training study in which 40 participants were randomly assigned to train with a 3D platformer game or a 2D platformer game. The main difference between the two games lies within their affordance for spatial exploration. After a training phase of two months, we observed extended brain structural increases in the 3D in comparison to the 2D condition in bilateral prefrontal areas, hippocampus/ entorhinal cortex as well as precuneus and the temporal lobe. In the reverse contrast an increase in bilateral caudate nucleus was observed.\n\nThe results demonstrate a crucial role of 3D spatial navigation for widespread brain plasticity effects within a two-months training setup. Given the vast complexity of video games, spatial navigation seems to play an outstanding role in structural plasticity. Since prefrontal, temporal and hippocampal volume deficits are prominent risk factors for several psychiatric disorders, daily navigation habits (outdoor movement, using GPS devices etc.) have to be considered in future mental disorders prevention research.

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bioRxiv2018

Influence of nutritional tyrosine on cognition and functional connectivity in healthy old humans

Tyrosine is precursor for monoamine neurotransmitters such as dopamine (DA), which is one of the key neurotransmitters in the frontostriatal network and of crucial relevance for mental disorders. Recent research reported that high dose tyrosine application resulted in increased brain DA synthesis, which is consistent with the observation of positive associations between daily tyrosine intake and cognitive test performance. In the present study, we investigated the associations between working memory (WM) dependent tasks and self-reported nutritional tyrosine intake within a large group of healthy elderly humans (286 subjects) by additionally including brain functional data. We observed a negative correlation between tyrosine intake and resting-state functional connectivity (rsFC) between the striatum (putamen) and the prefrontal cortex. That is to say, we found higher rsFC in individuals consuming less tyrosine per day. At the same time, this increased rsFC or hyperconnectivity was associated with lower WM performance. These findings suggest that lower or insufficient supply of tyrosine might result in dysfunctional connectivity between striatal and frontal regions leading to lower WM capacity in healthy elderly humans.

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