Biology subjects

Miehlbradt, J.

Publications and source records attributed to Miehlbradt, J..

5 recordsLinked to original sources

bioRxiv2026

Layer-specific functional gradients uncover intrinsic-network organization and feedback processing

Functional cortical gradients capture the brains large-scale organization along sensory-to-association (G1) and visual-to-somatomotor (G2) axes, yet the laminar circuitry that supports these axes remains largely unknown. Leveraging whole-brain submillimeter 7T resting-state fMRI, we estimated functional connectivity within deep, middle, and superficial cortical depths, integrated these into a multilayer network, and derived depth-resolved functional gradients across the cortex. We then computed an inter-regional dissimilarity index quantifying how distinct each region is from the rest of the cortex, and discovered a systematic dissociation across depth: the superficial-layer index closely followed G1, whereas the deep-layer index aligned with G2. The deep-layer index peaked in receive-dominant regions, consistent with deep layers as principal targets of feedback projections, while the superficial-layer index was maximal in cytoarchitecturally less differentiated transmodal cortex, consistent with its dense recurrent circuitry. Together, these findings demonstrate that functional gradients relate to laminar connectivity, and establish a mesoscale framework for decomposing whole-brain cortical connectivity.

neuroscience↗

bioRxiv2025

Maternal singing synchronizes the preterm infants' brain

Singing to infants is a universal human practice that has beneficial effects on infants cognitive and affective development. Children born preterm have impaired brain development, and their perception of maternal speech is known to be affected by the atypical hospital auditory environment. Understanding how preterm infants perceive maternal singing is of critical importance, yet it remains largely unexplored. Using high-density EEG, we examined neural responses to the same melody presented through maternal singing, stranger singing, and instrument, and compared the responses in 12 preterm infants. Moreover, to examine their processing of spatialisation, auditory stimuli were presented under monaural and binaural conditions. Preterm newborns are able to discriminate the same melody when sung by their mother, a stranger, or played by an instrument. When presented monaurally, the mothers singing voice enhances widespread brain synchrony across the entire scalp. In contrast, this synchrony diminishes with binaural spatialization. These findings suggest that maternal singing constitutes a highly salient auditory stimulus for preterm newborns, eliciting a distinct neural signature. Given that brain synchrony is a critical component of healthy brain function and development, harnessing maternal singing may offer a promising, natural intervention to support neurodevelopment--particularly in vulnerable populations such as preterm infants.

neuroscience↗

bioRxiv2022

Dynamic rewiring of electrophysiological brain networks during learning

Human learning is an active and complex process. However, the brain mechanisms underlying human skill learning and the effect of learning on the communication between brain regions, at different frequency bands, are still largely unknown. Here, we tracked changes in large-scale electrophysiological networks over a 6-week training period during which participants practiced a series of motor sequences during 30 home training sessions. Our findings showed that brain networks become more flexible with learning in all the frequency bands from theta to gamma ranges. We found consistent increase of flexibility in the prefrontal and limbic areas in the theta and alpha band, and over somatomotor and visual areas in the alpha band. Specific to the beta rhythm, we revealed that higher flexibility of prefrontal regions during the early stage of learning strongly correlated with better performance measured during home training sessions. Our findings provide novel evidence that prolonged motor skill practice results in higher, frequency-specific, temporal variability in brain network structure. AUTHOR SUMMARYWe investigated the large-scale organization of electrophysiological brain networks of a cohort of 30 participants practicing a series of motor sequences during 6 weeks of training. With learning, we observed a progressive modulation of the dynamics of prefrontal and limbic regions from theta to alpha frequencies, and of centro-parietal and occipital regions within visuomotor networks in the alpha band. In addition, higher prefrontal regional flexibility during early practice correlated with learning occurring during the 6 weeks of training. This provides novel evidence of a frequency-specific reorganization of brain networks with prolonged motor skill learning and an important neural basis for non-invasive research into the role of cortical functional interactions in (visuo)motor learning.

neuroscience↗

bioRxiv2020

Immersive virtual reality alters selection of head-trunk coordination strategies in young children

The acquisition of postural control is an elaborate process, which relies on the balanced integration of multisensory inputs. Current models suggest that young children rely on an en-block control of their upper body before sequentially acquiring a segmental control around the age of 7, and that they resort to the former strategy under challenging conditions. While recent works suggest that a virtual sensory environment alters visuomotor integration in healthy adults, little is known about the effects on younger individuals. Here we show that this coordination pattern is disrupted by an immersive virtual reality framework where a steering role is assigned to the trunk, which causes 6- to 8-year-olds to employ an ill-adapted segmental strategy. These results provide an alternate trajectory of motor development and emphasize the immaturity of postural control at these ages.

neuroscience↗

bioRxiv2019

Motor improvement estimation and task adaptation for personalized robot-aided therapy: a feasibility study

BackgroundIn the past years, robotic systems have become increasingly popular in both upper and lower limb rehabilitation. Nevertheless, clinical studies have so far not been able to confirm superior efficacy of robotic therapy over conventional methods. The personalization of robot-aided therapy according to the patients individual motor deficits has been suggested as a pivotal step to improve the clinical outcome of such approaches.\n\nMethodsHere, we present a model-based approach to personalize robot-aided rehabilitation therapy within training sessions. The proposed method combines the information from different motor performance measures recorded from the robot to continuously estimate patients motor improvement for a series of point-to-point reaching movements in different directions and comprises a personalization routine to automatically adapt the rehabilitation training. We engineered our approach using an upper limb exoskeleton and tested it with seventeen healthy subjects, who underwent a motor-adaptation paradigm, and two subacute stroke patients, exhibiting different degrees of motor impairment, who participated in a pilot test.\n\nResultsThe experiments illustrated the models capability to differentiate distinct motor improvement progressions among subjects and subtasks. The model suggested personalized training schedules based on motor improvement estimations for each movement in different directions. Patients motor performances were retained when training movements were reintroduced at a later stage.\n\nConclusionsOur results demonstrated the feasibility of the proposed model-based approach for the personalization of robot-aided rehabilitation therapy. The pilot test with two subacute stroke patients further supported our approach, while providing auspicious results for the applicability in clinical settings.\n\nTrial registrationThis study is registered in ClinicalTrials.gov (NCT02770300, registered 30 March 2016, https://clinicaltrials.gov/ct2/show/NCT02770300).

bioengineering↗