Biology subjects

Bergmann, E.

Publications and source records attributed to Bergmann, E..

7 recordsLinked to original sources

bioRxiv2026

Preserved implicit metacognitive sensitivity distinguishes psychosis risk from first-episode psychosis: A cross-sectional virtual reality-based study

Relatively preserved insight distinguishes individuals at risk for psychosis from those with full-blown psychosis. Metacognitive processes thought to support insight and uncertainty monitoring may therefore serve as early markers of illness progression. Yet findings have been inconsistent, perhaps partly due to reliance on explicit confidence ratings that introduce reflection and response biases. To address these limitations, we used a novel implicit confidence measure derived from post-decision gaze in a virtual-reality probabilistic learning task. Gaze-based confidence quantifies the alignment between spatial predictions and gaze direction. We assessed first-order learning and gaze-based metacognition in four groups: clinical high-risk for psychosis (CHR-P), first episode psychosis (FEP), help-seeking controls (HSC), and healthy controls (HC). We tested whether implicit metacognition differentiates psychosis risk from psychosis. Learning accuracy was reduced in both CHR-P and FEP compared to control groups. At the metacognitive level, CHR-P confidence levels were approximately commensurate with their reduced first-order performance, indicating preserved confidence calibration, along with preserved metacognitive sensitivity--the ability to distinguish correct from incorrect decisions. In contrast, FEP showed impaired confidence calibration and reduced metacognitive sensitivity. Metacognitive calibration and sensitivity distinguished CHR-P from FEP and provided predictive value in distinguishing CHR-P from FEP, whereas learning accuracy did not. These findings reveal a dissociation between first-order cognitive processes and distinct aspects of implicit metacognition, including confidence calibration and metacognitive sensitivity, across the psychosis continuum. This dissociation may refine early clinical characterization and improve identification of preserved insight-related mechanisms in psychosis risk.

neuroscience↗

bioRxiv2026

The Periaqueductal Gray Selectively Supports Reversal Learning During a Flexible Discrimination Task in Mice

Flexible, goal-directed behavior depends on the ability to update value representations in response to changing contingencies. This ability depends on distributed brain networks, calling for use of whole-brain imaging. Widely used in human research, whole-brain imaging in rodents has been a major challenge that has only recently been properly addressed. Using functional MRI in behaving mice performing a go/no-go odor discrimination task, we compared neural activity during initial cue-reward learning (acquisition) and subsequent contingency reversal. To link neural activity to underlying learning processes, we modeled value updating using a model-free reinforcement-learning algorithm. Trial-by-trial estimates of state-action values allowed us to dissociate acquisition from reversal-related signals, revealing that ventral striatal responses tracked expected value during acquisition, whereas reversal learning additionally recruited the periaqueductal gray (PAG), a midbrain structure classically linked to threat processing and aversive learning. PAG activity closely followed model-derived signatures of reversal learning, implicating it in the suppression of previously rewarded actions and in updating behavior in the absence of explicit punishment. These findings reveal a previously unrecognized computational role for the PAG in value-based decision-making and cognitive flexibility, and substantiate task-fMRI as a powerful tool to study the rodent brain at a mesoscale resolution.

neuroscience↗

bioRxiv2020

Structural and Functional Brain-wide Alterations in A350V IQSEC2 Mutant Mice Displaying Autistic-like Behavior

IQSEC2 is an X-linked gene which is associated with autism spectrum disorder (ASD), intellectual disability and epilepsy. IQSEC2 is a postsynaptic density protein, localized on excitatory synapses as part of the NMDA receptor complex and is suggested to play a role in AMPA receptor trafficking and mediation of long-term depression. Here, we present brain-wide structural volumetric and functional connectivity characterization in a novel mouse model with a missense mutation in the IQ domain of IQSEC2 (A350V). Using high-resolution structural and functional MRI, we show that animals with the A350V mutation display increased whole-brain volume which was further found to be specific to the cortex and hippocampus. Moreover, using a data-driven approach we demonstrate that A350V mice present alterations in structure-function relations of the frontal, auditory, and visual networks. Examination of these alterations revealed an increase in functional connectivity between the anterior cingulate cortex and the dorsomedial striatum. We also show that corticostriatal functional connectivity is correlated with individual variability in social behavior only in A350V mice, as assessed using the three-chamber social preference test. Our results at the systems-level bridge the impact of previously reported changes in AMPA receptor trafficking to network-level disruption and impaired social behavior. Further, the A350V mouse model recapitulates similarly reported brain-wide changes in other ASD mouse models, with substantially different cellular-level pathologies that nonetheless result in similar brain-wide alterations, suggesting that novel therapeutic approaches in ASD that result in systems-level rescue will be relevant to IQSEC2 mutations. Significance StatementSeveral recent studies have characterized the changes in the organization of brain networks in animal models of autism spectrum disorders (ASD). Here we assessed the effect of an A350V missense mutation in the IQSEC2 gene, which is associated with ASD, on brain-wide functional connectivity and its relation to social behavior deficits in A350V mice relative to controls. We found that the A350V IQSEC2 model results in disrupted functional connectivity of the anterior cingulate cortex and the dorsomedial striatum. Critically, disrupted increased corticostriatal functional connectivity is predictive of individual variability in social interaction only in A350V mice implicating this pathway in the pathophysiology of the A350V IQSEC2 mutation.

neuroscience↗

bioRxiv2020

Individual variability in functional connectivity architecture of the mouse brain

The functional organization of brain networks can be estimated using fMRI by examining the coherence of spontaneous fluctuations in the fMRI signal, a method known as resting-state functional connectivity MRI. Previous studies in humans reported that such functional networks are dominated by stable group and individual factors, demonstrating that fMRI is suited to measuring subject-specific characteristics, and suggesting the utility of such precision fMRI approach in personalized medicine. However, mechanistic investigations to the sources of individual variability in health and disease are limited in humans and thus require animal models. Here, we used repeated-measurement resting-state fMRI in awake mice to quantify the contribution of individual variation to the functional architecture of the mouse cortex. Comparing the organization of functional networks across the group, we found dominant common organizational principles. The data also revealed stable individual features, which create a unique fingerprint that allow identification of individual mice from the group. Examining the distribution of individual variation across the mouse cortex, we found it is homogeneously distributed in both sensory and association networks. Finally, connectome-based predictive modeling of motor behavior in the rotarod task revealed that individual variation in functional connectivity explained behavioral variability. Collectively, these results show that mouse functional networks are characterized by individual variations suggesting that individual variation characterizes the mammalian cortex in general, and not only the primate cortex. These findings lay the foundation for future mechanistic investigations of individual brain organization and pre-clinical studies of brain disorders in the context of personalized medicine.

neuroscience↗

bioRxiv2019

Loss of function in the autism and learning disabilities associated gene Nf1 disrupts corticocortical and corticostriatal functional connectivity in human and mouse

Children with the autosomal dominant single gene disorder, neurofibromatosis type 1 (NF1), display multiple structural and functional changes in the central nervous system, resulting in neuropsychological cognitive abnormalities. Here we assessed the pathological functional organization that may underlie the behavioral impairments in NF1 using resting-state functional connectivity MRI. Coherent spontaneous fluctuations in the fMRI signal across the entire brain were used to interrogate the pattern of functional organization of corticocortical and corticostriatal networks in both NF1 pediatric patients and mice with a heterozygous mutation in the Nf1 gene (Nf1+/-). Children with NF1 demonstrated abnormal organization of cortical association networks and altered posterior-anterior functional connectivity in the default network. Examining the contribution of the striatum revealed that corticostriatal functional connectivity was altered. NF1 children demonstrated reduced functional connectivity between striatum and the frontoparietal network and increased striatal functional connectivity with the limbic network. Awake passive mouse functional connectivity MRI in Nf1+/- mice similarly revealed reduced posterior-anterior connectivity along the cingulate cortex as well as disrupted corticostriatal connectivity. The striatum of Nf1+/- mice showed increased functional connectivity to somatomotor and frontal cortices and decreased functional connectivity to the auditory cortex. Collectively, these results demonstrate similar alterations across species, suggesting that NF1 pathogenesis is linked to striatal dysfunction and disrupted corticocortical connectivity in the default network.

neuroscience↗

bioRxiv2019

Individual structural features constrain the functional connectome

Whole brain dynamics intuitively depends upon the internal wiring of the brain; but to which extent the individual structural connectome constrains the corresponding functional connectome is unknown, even though its importance is uncontested. After acquiring structural data from individual mice, we virtualized their brain networks and simulated in silico functional MRI data. Theoretical results were validated against empirical awake functional MRI data obtained from the same mice. We demonstrate that individual structural connectomes predict the functional organization of individual brains. Using a virtual mouse brain derived from the Allen Mouse Brain Connectivity Atlas, we further show that the dominant predictors of individual structure-function relations are the asymmetry and the weights of the structural links. Model predictions were validated experimentally using tracer injections, identifying which missing connections (not measurable with diffusion MRI) are important for whole brain dynamics in the mouse. Individual variations thus define a specific structural fingerprint with direct impact upon the functional organization of individual brains, a key feature for personalized medicine.\n\nSIGNIFICANCE STATEMENTThe structural connectome is a key determinant of brain function and dysfunction. The connectome-based model approach aims to understand the functional organization of the brain by modeling the brain as a dynamical system and then studying how the functional architecture rises from the underlying structural skeleton. Here, taking advantage of mice studies, we systematically investigated the informative content of different structural features in explaining the emergence of the functional ones. We demonstrate that individual variations define a specific structural fingerprint with a direct impact upon the functional organization of individual brains stressing the importance of using individualized models to understand brain function. We show how limitations of connectome reconstruction with the diffusion-MRI method restrict our comprehension of the structural-functional relation.

neuroscience↗

bioRxiv2017

Lancet: genome-wide somatic variant calling using localized colored DeBruijn graphs

Reliable detection of somatic variations is of critical importance in cancer research. Lancet is an accurate and sensitive somatic variant caller which detects SNVs and indels by jointly analyzing reads from tumor and matched normal samples using colored DeBruijn graphs. Extensive experimental comparison on synthetic and real whole-genome sequencing datasets demonstrates that Lancet has better accuracy, especially for indel detection, than widely used somatic callers, such as MuTect, MuTect2, LoFreq, Strelka, and Strelka2. Lancet features a reliable variant scoring system which is essential for variant prioritization and detects low frequency mutations without sacrificing the sensitivity to call longer insertions and deletions empowered by the local assembly engine. In addition to genome-wide analysis, Lancet allows inspection of somatic variants in graph space, which augments the traditional read alignment visualization to help confirm a variant of interest. Lancet is available as an open-source program at https://github.com/nygenome/lancet.

bioinformatics↗