Julia Moser

Salience network expansion as a transdiagnostic neural marker for psychopathology risk in adolescence

The paper examines whether increased salience network surface area in adolescents is specific to depression or a general marker of psychopathology, finding stronger associations with overall psychopathology than depression alone.

Precision Confidence Mapping: An approach to determining individualized network topography with limited data

This paper introduces PCM, a method to assess network assignment confidence in rs-fMRI data, improving precision with limited scan durations.

BIBSNet: A Deep Learning Baby Image Brain Segmentation Network for MRI Scans

BIBSNet is a deep learning model for infant brain segmentation in MRI scans that outperforms JLF in accuracy and speed, with compatible outputs for further analysis.

Precision Functional Mapping of the Individual Human Brain Near Birth

The paper uses functional MRI to map cortical areas in neonates, finding that their arrangement is individually specific and reliably identifiable.

Precision Functional Neuroimaging Reveals Individually Specific Auditory Responses in Infants

The paper demonstrates the feasibility of precision functional imaging in infants to identify individual-specific auditory responses and their relation to brain functional networks.

Precision functional imaging in infants using multi-echo fMRI at 7T

This paper demonstrates that 7T MRI improves spatial resolution and data quality for functional brain mapping in infants compared to 3T MRI, enabling more reliable developmental studies.

Frequency tagging evidence supports perceptual separation of rapid stimuli in human fetuses

This study uses frequency tagging in fetal MEG to show that the fetal cortex generates separate neural responses to rapid auditory stimuli, suggesting perceptual separation rather than fusion.

fMRIPrep Lifespan: Extending A Robust Pipeline for Functional MRI Preprocessing to Developmental Neuroimaging

The paper extends fMRIPrep to handle MRI data from infancy to old age, demonstrating high-quality preprocessing across a wide age range.

Multi-echo Acquisition and Thermal Denoising Advances Precision Functional Imaging

This paper introduces multi-echo acquisition and thermal denoising methods to improve precision functional MRI in adults, children, and newborns, showing increased signal-to-noise ratio and reliability.

Predictive learning shapes the representational geometry of the human brain

This study shows predictive learning reshapes the brain's representational geometry to align with sensory input statistics, with prediction error encoding strength correlating with representational shifts.

Sex differences in prenatal development of neural complexity in the human brain

This study examines how neural complexity changes during prenatal development and finds it decreases with maturation, more rapidly in male fetuses.

Dynamics of nonlinguistic statistical learning: From neural entrainment to the emergence of explicit knowledge

This study investigates how neural entrainment during nonlinguistic statistical learning relates to the emergence of explicit knowledge using magnetoencephalography.

Magnetoencephalographic Signatures of Conscious Processing Before Birth

This study uses fetal magnetoencephalography to show that fetuses in the last trimester can process auditory stimuli through hierarchical rule learning, developing memory traces for complex patterns.

Magnetoencephalographic Signatures of Hierarchical Rule Learning in Newborns

This study uses MEG to show newborns can learn hierarchical auditory rules, with early responses to first-order violations and late responses to second-order violations in active infants.

Evaluating Complexity of Fetal MEG Signals: A Comparison of Different Metrics and Their Applicability

This study evaluates information-based metrics for measuring brain complexity in fetal and neonatal fMEG data to assess consciousness, finding LZW compression as the most usable metric with mixed results for fetal data.