Grodd, W. | Search bioRxiv

bioRxiv2025

Functional connectivity of thalamic nuclei during sensorimotor task-based fMRI at 9.4 Tesla

The thalamus is the brains central communication hub, playing a key role in processing and relaying sensorimotor and cognitive information between the cerebral cortex and other brain regions. It consists of specific and non-specific nuclei, each with a different role. Specific thalamic nuclei relay sensory and motor information to specific cortical and subcortical regions to ensure precise communication. In contrast, non-specific thalamic nuclei are involved in general functions such as attention or consciousness through broader and less targeted connections. In the present study, we aimed to investigate the functional connectivity patterns of the thalamic nuclei identified in our previous study as being involved in motor (finger-tapping) and sensory (finger-touch) tasks. The results of this study show that thalamic nuclei are not static hubs with a predefined role in neural signal processing, as they show different task-specific functional connectivity patterns in the anterior, middle, lateral, and posterior thalamic nuclei. Instead, they are all functional hubs that can flexibly change their connections to other brain regions in response to task demands. This work has important implications for understanding task-dependent functional connectivity between thalamic nuclei and different brain regions using task-based fMRI at 9.4 Tesla.

neuroscience↗

bioRxiv2017

Inflated False Negative Rates Undermine Reproducibility In Task-Based fMRI

Reproducibility is generally regarded as a hallmark of scientific validity. It can be undermined by two very different factors, namely inflated false positive rates or inflated false negative rates. Here we investigate the role of the second factor, i.e. the degree to which true effects are not detected reliably. The availability of large public databases and also supercomputing allows us to tackle this problem quantitatively. Specifically, we estimated the reproducibility in task-based fMRI data over different samples randomly drawn from a large cohort of subjects obtained from the Human Connectome Project. We use the full cohort as a standard of reference to approximate true positive effects, and compute the fraction of those effects that was detected reliably using standard software packages at various smaller sample sizes. We found that with standard sample sizes this fraction was less than 25 percent. We conclude that inflated false negative rates are a major factor that undermine reproducibility. We introduce a new statistical inference algorithm based on a novel test statistic and show that it improves reproducibility without inflating false positive rates.

neuroscience↗