Biology subjects

Frens, M. A.

Publications and source records attributed to Frens, M. A..

5 recordsLinked to original sources

bioRxiv2026

Cerebellar influences on neocortical development in humans and mice

The cerebellum has long been considered a late-maturing structure subordinate to neocortical development, therefore its potential role as an early driver of cortical organization remains largely unexplored. Using two large longitudinal neuroimaging cohorts of developing children together with lesion experiments in mice, we show that early cerebellar morphology may drive neocortical maturation in a regionally specific manner. These cross-species findings implicate the cerebellum as a possible regulator of neocortical organization.

neuroscience↗

bioRxiv2023

Large Data on the Small Brain: Population-wide Cerebellar Growth Models of Children and Adolescents

In the past, the cerebellum has been best known for its crucial role in motor function. However, increasingly more findings highlight the importance of cerebellar contributions in cognitive functions and neurodevelopment. Using large scale, population-wide neuroimaging data, we describe and provide detailed, openly available models of cerebellar development in childhood and adolescence, an important time period for brain development and onset of neuropsychiatric disorders. Next to a traditionally used anatomical parcellation of the cerebellum, we generated growth models based on a recently proposed functional parcellation. In both, we find an anterior-posterior growth gradient mirroring the age-related improvements of underlying behavior and function, which is analogous to cerebral maturation patterns and offers new evidence for directly related cerebello-cortical developmental trajectories. Finally, we illustrate how the current approach can be used to detect cerebellar abnormalities in clinical samples.

neuroscience↗

bioRxiv2023

Estimating cortical thickness trajectories in children across different scanners using transfer learning from normative models

This work illustrates the use of normative models in a longitudinal neuroimaging study of children aged 6-17 years and demonstrates how such models can be used to make meaningful comparisons in longitudinal studies, even when individuals are scanned with different scanners across successive study waves. More specifically, we first estimated a large-scale reference normative model using hierarchical Bayesian regression from N=40,435 individuals across the lifespan and from dozens of sites. We then transfer these models to a longitudinal developmental cohort (N=5,985) with three measurement waves acquired on two different scanners that were unseen during estimation of the reference models. We show that the use of normative models provides individual deviation scores that are independent of scanner effects and efficiently accommodate inter-site variations. Moreover, we provide empirical evidence to guide the optimization of sample size for the transfer of prior knowledge about the distribution of regional cortical thicknesses. We show that a transfer set containing as few as 25 samples per site can lead to good performance metrics on the test set. Finally, we demonstrate the clinical utility of this approach by showing that deviation scores obtained from the transferred normative models are able to detect and chart morphological heterogeneity in individuals born pre-term.

neuroscience↗

bioRxiv2021

Purkinje Cell Activity During Suppression of Voluntary Eye Movements in Rhesus Macaques

Volitional suppression of responses to distracting external stimuli enables us to achieve our goals. This volitional inhibition of a specific behavior is supposed to be mainly mediated by the cerebral cortex. However, recent evidence supports the involvement of the cerebellum in this process. It is currently not known whether different parts of the cerebellar cortex play differential or synergistic roles in planning and execution of this behavior. Here, we measured Purkinje cell (PC) responses in the medial and lateral cerebellum in two rhesus macaques during a pro- and antisaccade task. During an antisaccade trial, non-human primates were instructed to make a saccadic eye movement away from a target, rather than towards it, as in prosaccade trials. Our data shows that the cerebellum plays an important role not only during execution of the saccades, but also during the volitional inhibition of eye movements towards the target. Simple Spike (SS) modulation during the instruction and execution period of pro- and antisaccades was prominent in PCs of both medial and lateral cerebellum. However, only the SS activity in the lateral cerebellar cortex contained information about trial identity and showed a stronger reciprocal interaction with complex spikes. Moreover, SS activity of different PC groups modulated bidirectionally in both regions, but the PCs that showed facilitating and suppressive activity were predominantly associated with instruction and execution, respectively. These findings show that different cerebellar regions and PC groups contribute to goal-directed behavior and volitional inhibition, but with different propensities, highlighting the rich repertoire of cerebellar control in executive functions. Significance StatementThe antisaccade task is commonly used in research and clinical evaluation as a test of volitional and flexible control of behavior. It requires volitional suppression of prosaccades, a function that has been attributed to the neocortex. However, recent findings indicate that cerebellum also contributes to this behavior. We recorded from neurons in the medial and lateral cerebellum to evaluate their responses in this task. We found that both regions significantly modulated their activity during this task, but only cells in the lateral cerebellum encoded the stimulus identity in each trial. These results indicate that the cerebellum actively contributes to the control of flexible behavior and that lateral and medial cerebellum play different roles during volitional eye movements.

neuroscience↗

bioRxiv2017

Individual differences in motor noise and adaptation rate are optimally related

Individual variations in motor adaptation rate were recently shown to correlate with movement variability or \"motor noise\" in a forcefield adaptation task. However, this finding could not be replicated in a meta-analysis of visuomotor adaptation experiments. Possibly, this inconsistency stems from noise being composed of distinct components which relate to adaptation rate in different ways. Indeed, previous modeling and electrophysiological studies have suggested that motor noise can be factored into planning noise, originating from the brain, and execution noise, stemming from the periphery. Were the motor system optimally tuned to these noise sources, planning noise would correlate positively with adaptation rate and execution noise would correlate negatively with adaptation rate, a phenomenon familiar in Kalman filters. To test this prediction, we performed a visuomotor adaptation experiment in 69 subjects. Using a novel Bayesian fitting procedure, we succeeded in applying the well-established state-space model of adaptation to individual data. We found that adaptation rate correlates positively with planning noise (r=0.27; 95%HDI=[0.05 0.50]) and negatively with execution noise (r=-0.41; 95%HDI=[-0.63 -0.16]). In addition, the steady-state Kalman gain calculated from state and execution noise correlated positively with adaptation rate (r = 0.31; 95%HDI = [0.09 0.54]). These results suggest that motor adaptation is tuned to approximate optimal learning, consistent with the \"optimal control\" framework that has been used to explain motor control. Since motor adaptation is thought to be a largely cerebellar process, the results further suggest the sensitivity of the cerebellum to both planning noise and execution noise.\n\nSIGNIFICANCE STATEMENTOur study shows that the adaptation rate is optimally tuned to planning noise and execution noise across individuals. This suggests that motor adaptation is tuned to approximate optimal learning, consistent with \"optimal control\" approaches to understanding the motor system. In addition, our results imply sensitivity of the cerebellum to both planning noise and execution noise, an idea not previously considered. Finally, our Bayesian statistical approach represents a powerful, novel method for fitting the well-established state-space models that could have an influence on the methodology of the field.

neuroscience↗