Biology subjects

Nettekoven, C.

Publications and source records attributed to Nettekoven, C..

10 recordsLinked to original sources

bioRxiv2026

Individualized parcellation reveals functional boundaries in human prefrontal cortex

Human prefrontal cortex (PFC) supports diverse higher-order cognitive functions during task execution. Increasing evidence suggests that these functions are organized along large-scale gradients, such as a rostro-caudal axis supporting progressively abstract-to-concrete information processing. At the same time, regional specialization within PFC, including focal patches selective for specific stimulus categories, suggests the presence of discrete functional boundaries. Whether PFC organization is best characterized by continuous gradients or discrete subdivisions remains unresolved. Here we show that task-evoked functional organization in PFC exhibits substantial inter-individual variability, limiting the usefulness of conventional group atlases in testing for functional boundaries. To address this challenge, we estimated individualized functional parcellations by combining a group atlas with task-evoked fMRI data spanning diverse cognitive tasks. The group atlas revealed large-scale functional gradients across PFC, whereas individualized parcellations additionally uncovered sharp functional boundaries obscured by group averaging. Moreover, functional organization in PFC was substantially more fine-grained than in other association cortices, consistent with its integrative role in cognitive control. Together, these findings suggest that PFC organization reflects an individualized mosaic of fine-grained functional subdivisions embedded within broader large-scale gradients, with important implications for defining core constructs such as the multiple-demand system.

neuroscience↗

bioRxiv2026

Multi-Task Batteries for Precision Functional Mapping

Functional brain mapping is an important tool to understand the organization of the human brain, both at the group level, but also to an increasing degree at the level of the individual. There are currently two main approaches to do so. Resting-state fMRI relies on inter-regional correlations of random fluctuations of the signal. In contrast, task-based localizers typically use a single-contrast between a task of interest and a matched control task to identify the location of a functional region in an individual brain. In this paper, we propose and evaluate a third approach: the use of multi-task batteries for both localization of a single functional region and parcellation of multiple functional regions. We show that multi-task localizers produce more consistent estimation of a single functional region across subjects than the single-contrast approach using the same amount of fMRI data. Furthermore, we demonstrate that the multi-task approach is sensitive to true inter-individual differences in region size, and does not suffer the same influence of signal-to-noise ratio that biases the single-contrast localizer. We then address the question of how to select tasks for the battery, and present a data-driven strategy that optimizes the characterization of a brain structure of interest. We show that such batteries outperform randomly selected batteries both for building individual parcellations as well as individual connectivity models. Finally, we demonstrate that an interspersed design - where all tasks are presented in each imaging run - yields more reliable results than splitting the tasks across different runs. We present an open source toolbox for the implementation of multi-task batteries, along with a library containing group-averaged activity patterns that can be used to optimize battery selection for different brain structures of interest.

neuroscience↗

bioRxiv2026

Multi-task fMRI outperforms resting-state fMRI for revealing task-invariant organization of the human brain

Resting-state functional Magnetic Resonance Imaging (fMRI) is widely used to infer the intrinsic functional organization of the brain, yet it remains unclear how well this approach can predict the structure of brain activity observed across a diverse set of mental states. Here we compare resting-state to task-based fMRI using diverse task batteries within the same individuals. We find that multi-task fMRI data consistently outperform resting-state estimates in predicting functional organization during novel tasks. This advantage persists across preprocessing strategies, brain regions, and independent datasets. While task activation estimates do show task-dependency when using only few tasks, increasing task diversity reduced task-specific bias, with convergence achieved using modest task sets. These improvements translate into superior individual parcellations and connectivity models. Together, our results dissociate reliability from validity in neuroimaging and challenge the prevailing assumption that rest provides a privileged window into intrinsic brain organization. Instead, functional architecture appears most faithfully revealed when the brain is actively driven through diverse task states.

neuroscience↗

bioRxiv2026

Aging is associated with uniform structural decline across cerebellar regions while preserving topological organization and showing no relation with sensorimotor function

Aging affects cerebellar structure, yet the regional specificity of this decline and its relationship to sensorimotor functions remain unclear. In this study, we quantified age-related cerebellar gray matter differences in 50 young and 80 older adults using both anatomically defined cerebellar parcellations and a functionally defined cerebellar atlas. Across both anatomical and functional parcellations, older adults showed robust reductions in gray matter volume relative to young adults. This age-related gray matter vulnerability was region-specific as age differences varied significantly across regions: both the current dataset and the additionally used Cam-CAN dataset demonstrated a larger negative effect of age in the posterior than the anterior lobe, and a smaller difference in the action domains than in the other functional domains . Structural covariance analyses revealed that correlations between cerebellar regions were determined primarily by spatial proximity and, to a lesser extent, by medial-ateral (vermis-hemisphere) organization or functional similarity. Importantly, the topological organization of the cerebellum did not differ across age groups, indicating preserved structural patterns despite widespread gray matter loss. Finally, despite substantial interindividual variability in behavioral, regional cerebellar gray matter volumes, whether anatomically or functionally defined, did not predict inter-individual variability for any of our eight cerebellum-dependent outcomes. This absence of structure-function relationship suggests that behavioral performance is maintained through compensatory mechanisms or microstructural features not captured by regional gray matter volume. Together, the results suggest heterogeneous age-related cerebellar degeneration alongside preserved topological organization and no measurable impact on cerebellar sensorimotor function, supporting the notion of a robust cerebellar reserve throughout healthy aging.

neuroscience↗

bioRxiv2025

Closed-loop beta stimulation enhances beta activity and motor behaviour

Movement-related beta event-related synchronization (ERS) has been linked to motor control and learning, showing potential as a therapeutic target for those with movement deficits, such as stroke survivors. However, whether directly modulating beta ERS can causally influence motor performance remains unclear, largely due to the lack of methods designed to specifically target this neural activity. To address this gap, we developed a novel behaviourally-driven, closed-loop transcranial alternating current stimulation (tACS) approach to target movement-related beta ERS during a visuomotor adaptation task. We found that the behaviourally-driven, closed-loop beta-tACS specifically enhances beta ERS without affecting beta event-related desynchronization (ERD). Critically, this targeted enhancement significantly improves retention of motor adaptation. These findings establish a causal relationship between beta ERS and motor behaviour and highlight the potential of behaviourally-driven beta-tACS as a therapeutic approach for improving motor function in clinical populations characterized by impaired beta activity.

neuroscience↗

bioRxiv2025

Baclofen, a GABAB receptor agonist, impairs motor learning in healthy people and changes inhibitory dynamics in motor areas

Inhibition mediated by {gamma}-aminobutyric acid (GABA) is implicated in motor plasticity and learning, with [GABA] in the motor cortex decreasing during motor learning. However, the causal relationship between [GABA] and learning has yet to be determined. Here, we conducted a within-subject, double-blind, placebo-controlled, crossover study to investigate the effect of increased GABAergic inhibition via GABAB-receptor agonist baclofen on motor learning and Magnetic Resonance Spectroscopic Imaging (MRSI) metrics. Increasing GABA-mediated inhibition with baclofen did not change response times, but significantly impaired motor sequence learning. In parallel, we demonstrated a blunting of the expected decrease in [GABA] during motor learning. These results highlight a causal role for GABAergic inhibition in motor learning and may have clinical implications: baclofen is commonly used to treat post brain-injury spasticity, but may impair motor learning during rehabilitation.

neuroscience↗

bioRxiv2024

Altered cortico-cerebellar connectivity in cerebellar degeneration patients improves with motor training

People with cerebellar degeneration show characteristic ataxic motor impairments. Despite cerebellar dysfunction, they can still improve motor performance through sensorimotor training. Yet, how such training affects functional brain networks affected by cerebellar degeneration is unknown. We here investigated neuroplastic changes in the cortico-cerebellar network after a five-day forearm movement training in 40 patients with mild to severe cerebellar degeneration and 40 age- and sex-matched healthy controls. Participants were assigned to one of four motor training conditions, varying online visual feedback and explicit verbal feedback. Anatomical and resting-state fMRI was collected on the days before and after training. To overcome the limitations of standard brain templates that fail in the presence of severe anatomical abnormalities, we developed a specific template for comparing cerebellar patients with age-matched controls. Our new template reduced the spatial spread of cerebellar anatomical landmarks by 30% relative to existing templates and tripled fMRI noise classification accuracy. Using this pipeline, we found that patients showed impaired connectivity between cerebellar motor regions and neocortical visuomotor and premotor regions at baseline compared to controls, whereas their cortico-cortical connectivity remained intact. Training with vision strengthened connectivity in the cortico-cerebellar visuomotor network contralateral to the trained arm in all participants. Cerebellar patients exhibited additional increased connectivity ipsilateral to the training arm in this network. Further, training with explicit verbal feedback facilitated connectivity between a cerebellar cognitive region and dorsolateral prefrontal cortex. These results indicate that motor training in cerebellar degeneration leads to enhanced functional connectivity of the cortico-cerebellar network.

neuroscience↗

bioRxiv2023

A hierarchical Bayesian brain parcellation framework for fusion of functional imaging datasets

One important barrier in the development of complex models of human brain organization is the lack of a large and comprehensive task-based neuro-imaging dataset. Therefore, current atlases of functional brain organization are mainly based on single and homogeneous resting-state datasets. Here, we propose a hierarchical Bayesian framework that can learn a probabilistically defined brain parcellation across numerous task-based and resting-state datasets, exploiting their combined strengths. The framework is partitioned into a spatial arrangement model that defines the probability of a specific individual brain parcellation, and a set of dataset-specific emission models that defines the probability of the observed data given the individual brain organization. We show that the framework optimally combines information from different datasets to achieve a new population-based atlas of the human cerebellum. Furthermore, we demonstrate that, using only 10 min of individual data, the framework is able to generate individual brain parcellations that outperform group atlases.

neuroscience↗

bioRxiv2023

Selective recruitment: Evidence for task-dependent gating of inputs to the cerebellum

fMRI studies have documented cerebellar activity across a wide array of tasks. However, the functional contribution of the cerebellum within these task domains remains unclear because cerebellar activity is often studied in isolation. This is problematic, as cerebellar fMRI activity may simply reflect the transmission of neocortical activity through fixed connections. Here we present a new approach that addresses this problem. Rather than focus on task-dependent activity changes in the cerebellum alone, we ask if neocortical inputs to the cerebellum are gated in a task-dependent manner. We hypothesize that input is upregulated when the cerebellum functionally contributes to a task. We first validated this approach using a finger movement task, where the integrity of the cerebellum has been shown to be essential for the coordination of rapid alternating movements but not for force generation. While both neocortical and cerebellar activity increased with increasing speed and force, the speed-related changes in the cerebellum were larger than predicted by an optimized cortico-cerebellar connectivity model. We then applied the same approach in a cognitive domain, assessing how the cerebellum supports working memory. Enhanced gating was associated with the encoding of items in working memory, but not with the manipulation or retrieval of the items. Focusing on task-dependent gating of neocortical inputs to the cerebellum offers a promising approach for using fMRI to understand the specific contributions of the cerebellum to cognitive function.

neuroscience↗

bioRxiv2022

tDCS induced GABA change is associated with the simulated electric field in M1, an effect mediated by grey matter volume in the MRS voxel

Background and ObjectiveTranscranial direct current stimulation (tDCS) has wide ranging applications in neuro-behavioural and physiological research, and in neurological rehabilitation. However, it is currently limited by substantial inter-subject variability in responses, which may be explained, at least in part, by anatomical differences that lead to variability in the electric field (E-field) induced in the cortex. Here, we tested whether the variability in the E-field in the stimulated cortex during tDCS, estimated using computational simulations, explains the variability in tDCS induced changes in GABA, a neurophysiological marker of stimulation effect. MethodsData from five previously conducted MRS studies were combined. The anode was placed over the left primary motor cortex (M1, 3 studies, N = 24) or right temporal cortex (2 studies, N = 32), with the cathode over the contralateral supraorbital ridge. Single voxel spectroscopy was performed in a 2x2x2cm voxel under the anode in all cases. MRS data were acquired before and either during or after 1mA tDCS using either a sLASER sequence (7T) or a MEGA-PRESS sequence (3T). sLASER MRS data were analysed using LCModel, and MEGA-PRESS using FID-A and Gannet. E-fields were simulated in a finite element model of the head, based on individual MPRAGE images, using SimNIBS. Separate linear mixed effects models were run for each E-field variable (mean and 95th percentile; magnitude, and components normal and tangential to grey matter surface, within the MRS voxel). The model included effects of time (pre or post tDCS), E-field, grey matter volume in the MRS voxel, and a 3-way interaction between time, E-field and grey matter volume. Additionally, we ran a permutation analysis using PALM to determine whether E-field anywhere in the brain, not just in the MRS voxel, correlated with GABA change. ResultsIn M1, higher mean E-field magnitude was associated with greater tDCS-induced decreases in GABA (t(24) = 3.24, p = 0.003). Further, the association between mean E-field magnitude and GABA change was moderated by the grey matter volume in the MRS voxel (t(24) = -3.55, p =0.002). These relationships were consistent across all E-field variables except the mean of the normal component. No significant relationship was found between tDCS-induced GABA decrease and E-field in the temporal voxel. No significant clusters were found in the whole brain analysis. ConclusionsOur data suggest that the electric field induced by tDCS within the brain is variable, and is significantly related to tDCS-induced decrease in GABA, a key neurophysiological marker of stimulation. These findings strongly support individualised dosing of tDCS, at least in M1. Further studies examining E-fields in relation to other outcome measures, including behaviour, will help determine the optimal E-fields required for any desired effects. HighlightsO_LIWe study the link between individually simulated electric field dose and tDCS-induced change in GABA in the cortex. C_LIO_LIThe electric field strength in the brain correlates with a decrease in GABA in the motor cortex. C_LIO_LIThe correlation between the electric field and GABA change is modulated by the amount of grey matter in the MRS voxel. C_LIO_LIWe find no association between the electric field and GABA in the temporal cortex. C_LI

neuroscience↗