
Functional neuroimaging data does not provide evidence for the involvement of the indirect or hyperdirect cortico-basal-ganglia pathways in successful response inhibition, but shows increased subcortical activity during failed inhibition trials.


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This study investigates the functional network underlying response inhibition in the human brain, particularly the role of the basal ganglia in successful action cancellation. Functional magnetic resonance imaging (fMRI) approaches have frequently used the stop-signal task (SST) to examine this network. We merge five such datasets, using a novel aggregatory method allowing the unification of raw fMRI data across sites. This meta-analysis, along with other recent aggregatory fMRI studies, do not find evidence for the innervation of the hyperdirect or indirect cortico-basal-ganglia pathways in successful response inhibition. What we do find, is large subcortical activity profiles for failed stop trials. We discuss possible explanations for the mismatch of findings between the fMRI results presented here and results from other research modalities that have implicated nodes of the basal ganglia in successful inhibition. We also highlight the substantial effect smoothing can have on the conclusions drawn from task-specific GLMs. First and foremost, this study presents a proof of concept for meta-analytical methods that enable the merging of extensive, unprocessed or unreduced datasets. It demonstrates the significant potential that open-access data sharing can offer to the research community. With an increasing number of datasets being shared publicly, researchers will have the ability to conduct meta-analyses on more than just summary data.

### Competing Interest Statement

The authors have declared no competing interest.

Multi-study fMRI outlooks on subcortical BOLD responses in the stop-signal paradigm

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Functional Magnetic Resonance Imaging Reveals Subcortical Involvement in Failed Response Inhibition


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The authors propose a novel approach to improve the reproducibility of neuroimaging results by converting statistic maps across different functional MRI (fMRI) analysis pipelines using diffusion models.


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Mitigating Analytical Variability in fMRI Results Through Style Transfer Using Diffusion Models



Automated surface-based parcellation and vertex-wise analysis of ultra high-resolution 7T ex vivo MRI data from 82 brain donors with Alzheimer's disease and related dementias reveals significant associations between cortical thickness and neuropathological markers of disease.


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Ultra High-Resolution 7T Ex Vivo MRI Analysis Reveals Structural-Pathological Associations in Alzheimer's Disease and Related Dementias



DeepFDR kombiniert Deep Learning mit Bildsegmentierung zur effektiven Kontrolle der FDR in Neuroimaging-Analysen.


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DeepFDR: Ein tiefenlernbasiertes Verfahren zur Kontrolle des False Discovery Rate für Neuroimaging-Daten



Die stochastische Corticale Selbstrekonstruktion bietet einen innovativen Ansatz zur Erstellung gesunder Referenzen für die Cortical Thickness.


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Stochastische kortikale Selbstrekonstruktion: Ein neuer Ansatz zur Erstellung gesunder Referenzen für die Cortical Thickness



Die Studie zeigt Fortschritte bei der Dekodierung visueller Prozesse im menschlichen Gehirn.


dekodierung-des-gehirns-auf-dem-weg-zur-echtzeit-rekonstruktion-der-visuellen-wahrnehmung


Dekodierung des Gehirns: Auf dem Weg zur Echtzeit-Rekonstruktion der visuellen Wahrnehmung



Implantable RF surface coil design enables high-resolution awake mouse fMRI at 14 Tesla, revealing brain-wide functional mapping of sensory signal processing in higher association cortical areas.


High-resolution awake mouse fMRI remains challenging despite extensive efforts to address motion-induced artifacts and stress. This study introduces an implantable radiofrequency (RF) surface coil design that minimizes image distortion caused by the air/tissue interface of mouse brains while simultaneously serving as a headpost for fixation during scanning. Using a 14T scanner, high-resolution fMRI enabled brain-wide functional mapping of visual and vibrissa stimulation at 100x100x200µm resolution with a 2s per frame sampling rate. Besides activated ascending visual and vibrissa pathways, robust BOLD responses were detected in the anterior cingulate cortex upon visual stimulation and spread through the ventral retrosplenial area (VRA) with vibrissa air-puff stimulation, demonstrating higher-order sensory processing in association cortices of awake mice. In particular, the rapid hemodynamic responses in VRA upon vibrissa stimulation showed a strong correlation with the hippocampus, thalamus, and prefrontal cortical areas. Cross-correlation analysis with designated VRA responses revealed early positive BOLD signals at the contralateral barrel cortex (BC) occurring 2 seconds prior to the air-puff in awake mice with repetitive stimulation, which was not detectable with the randomized stimulation paradigm. This early BC activation indicated learned anticipation through the vibrissa system and association cortices in awake mice under continuous training of repetitive air-puff stimulation. This work establishes a high-resolution awake mouse fMRI platform, enabling brain-wide functional mapping of sensory signal processing in higher association cortical areas.

Significance Statement This awake mouse fMRI platform was developed by implementing an advanced implantable radiofrequency (RF) coil scheme, which simultaneously served as a headpost to secure the mouse head during scanning. The ultra-high spatial resolution (100x100x200µm) BOLD fMRI enabled the brain-wide mapping of activated visual and vibrissa systems during sensory stimulation in awake mice, including association cortices, e.g. anterior cingulate cortex and retrosplenial cortex, for high order sensory processing. Also, the activation of barrel cortex at 2 s prior to the air-puff indicated a learned anticipation of awake mice under continuous training of the repetitive vibrissa stimulation.

### Competing Interest Statement

MRIBOT LLC. is a spinoff company co-founded by XY. All other authors declare no competing interests related to this work.

High-resolution awake mouse fMRI at 14 Tesla

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High-Resolution Awake Mouse fMRI at 14 Tesla



Unified data fusion framework for EEG and MEG data using coupled generator decomposition.


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Coupled Generator Decomposition for EEG and MEG Data Fusion



高品質なfMRIから画像への再構築を少ないデータで実現する。


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MindEye2: High-Quality fMRI-to-Image Reconstruction with Minimal Data



Exploring the nature of direct functional connectivity in visual brain networks through fMRI time series analysis.


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Understanding Direct Functional Connectivity in Visual Brain Network
