Investigating Intra-Individual Networks of Response Inhibition and Interference Resolution using 7T MRI.

Response inhibition and interference resolution are often considered subcomponents of an overarching inhibition system that utilizes the so-called cortico-basal-ganglia loop. Up until now, most previous functional magnetic resonance imaging (fMRI) literature has compared the two using between-subject designs, pooling data in the form of a meta-analysis or comparing different groups. Here, we investigate the overlap of activation patterns underlying response inhibition and interference resolution on a within-subject level, using ultra-high field MRI. In this model-based study, we furthered the functional analysis with cognitive modelling techniques to provide a more in-depth understanding of behaviour. We applied the stop-signal task and multi-source interference task to measure response inhibition and interference resolution, respectively. Our results lead us to conclude that these constructs are rooted in anatomically distinct brain areas and provide little evidence for spatial overlap. Across the two tasks, common BOLD responses were observed in the inferior frontal gyrus and anterior insula. Interference resolution relied more heavily on subcortical components, specifically nodes of the commonly referred to indirect and hyperdirect pathways, as well as the anterior cingulate cortex, and pre-supplementary motor area. Our data indicated that orbitofrontal cortex activation is specific to response inhibition. Our model-based approach provided evidence for the dissimilarity in behavioural dynamics between the two tasks. The current work exemplifies the importance of reducing inter-individual variance when comparing network patterns and the value of UHF-MRI for high resolution functional mapping.

Visualizing the Human Subcortex Using Ultra-high Field Magnetic Resonance Imaging.

With the recent increased availability of ultra-high field (UHF) magnetic resonance imaging (MRI), substantial progress has been made in visualizing the human brain, which can now be done in extraordinary detail. This review provides an extensive overview of the use of UHF MRI in visualizing the human subcortex for both healthy and patient populations. The high inter-subject variability in size and location of subcortical structures limits the usability of atlases in the midbrain. Fortunately, the combined results of this review indicate that a large number of subcortical areas can be visualized in individual space using UHF MRI. Current limitations and potential solutions of UHF MRI for visualizing the subcortex are also discussed.

Sequential Sampling Models in Cognitive Neuroscience: Advantages, Applications, and Extensions.

Sequential sampling models assume that people make speeded decisions by gradually accumulating noisy information until a threshold of evidence is reached. In cognitive science, one such model--the diffusion decision model--is now regularly used to decompose task performance into underlying processes such as the quality of information processing, response caution, and a priori bias. In the cognitive neurosciences, the diffusion decision model has recently been adopted as a quantitative tool to study the neural basis of decision making under time pressure. We present a selective overview of several recent applications and extensions of the diffusion decision model in the cognitive neurosciences.

Quantifying inter-individual anatomical variability in the subcortex using 7 T structural MRI.

Functional magnetic resonance imaging (MRI) data are usually registered into standard anatomical space. However, standard atlases, such as LPBA40, the Harvard-Oxford atlas, FreeSurfer, and the Jülich cytoarchitectonic maps all lack important detailed information about small subcortical structures like the substantia nigra and subthalamic nucleus. Here we introduce a new subcortical probabilistic atlas based on ultra-high resolution in-vivo anatomical imaging from 7 T MRI. The atlas includes six important but elusive subcortical nuclei: the striatum, the globus pallidus internal and external segment (GPi/e), the subthalamic nucleus, the substantia nigra, and the red nucleus. With a sample of 30 young subjects and carefully cross-validated delineation protocols, our atlas is able to capture the anatomical variability within healthy populations for each of the included structures at an unprecedented level of detail. All the generated probabilistic atlases are registered to MNI standard space and are publicly available.

Cortical and subcortical contributions to interference resolution and inhibition - An fMRI ALE meta-analysis.

Interacting with our environment requires the selection of appropriate responses and the inhibition of others. Such effortful inhibition is achieved by a number of interference resolution and global inhibition processes. This meta-analysis including 57 studies and 73 contrasts revisits the overlap and differences in brain areas supporting interference resolution and global inhibition in cortical and subcortical brain areas. Activation likelihood estimation was used to discern the brain regions subserving each type of cognitive control. Individual contrast analysis revealed a common activation of the bilateral insula and supplementary motor areas. Subtraction analyses demonstrated the voxel-wise differences in recruitment in a number of areas including the precuneus in the interference tasks and the frontal pole and dorsal striatum in the inhibition tasks. Our results display a surprising lack of subcortical involvement within these types of cognitive control, a finding that is likely to reflect a systematic gap in the field of functional neuroimaging.

A test-retest reliability analysis of diffusion measures of white matter tracts relevant for cognitive control.

Recent efforts to replicate structural brain-behavior correlations have called into question the replicability of structural brain measures used in cognitive neuroscience. Here, we report an evaluation of test-retest reliability of diffusion tensor imaging (DTI) measures, including fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, in several white matter tracts previously shown to be involved in cognitive control. In a data set consisting of 34 healthy participants scanned twice on a single day, we observe overall stability of DTI measures. This stability remained in a subset of participants who were also scanned a third time on the same day as well as in a 2-week follow-up session. We conclude that DTI measures in these tracts show relative stability, and that alternative explanations for the recent failures of replication must be considered.

Effects of aging on T1, T2*, and QSM MRI values in the subcortex.

The aging brain undergoes several anatomical changes that can be measured with Magnetic Resonance Imaging (MRI). Early studies using lower field strengths have assessed changes in tissue properties mainly qualitatively, using [Formula: see text]- or [Formula: see text]- weighted images to provide image contrast. With the development of higher field strengths (7 T and above) and more advanced MRI contrasts, quantitative measures can be acquired even of small subcortical structures. This study investigates volumetric, spatial, and quantitative MRI parameter changes associated with healthy aging in a range of subcortical nuclei, including the basal ganglia, red nucleus, and the periaqueductal grey. The results show that aging has a heterogenous effects across regions. Across the subcortical areas an increase of [Formula: see text] values is observed, most likely indicating a loss of myelin. Only for a number of areas, a decrease of [Formula: see text] and increase of QSM is found, indicating an increase of iron. Aging also results in a location shift for a number of structures indicating the need for visualization of the anatomy of individual brains.

Toward a model-based cognitive neuroscience of mind wandering.

People often "mind wander" during everyday tasks, temporarily losing track of time, place, or current task goals. In laboratory-based tasks, mind wandering is often associated with performance decrements in behavioral variables and changes in neural recordings. Such empirical associations provide descriptive accounts of mind wandering - how it affects ongoing task performance - but fail to provide true explanatory accounts - why it affects task performance. In this perspectives paper, we consider mind wandering as a neural state or process that affects the parameters of quantitative cognitive process models, which in turn affect observed behavioral performance. Our approach thus uses cognitive process models to bridge the explanatory divide between neural and behavioral data. We provide an overview of two general frameworks for developing a model-based cognitive neuroscience of mind wandering. The first approach uses neural data to segment observed performance into a discrete mixture of latent task-related and task-unrelated states, and the second regresses single-trial measures of neural activity onto structured trial-by-trial variation in the parameters of cognitive process models. We discuss the relative merits of the two approaches, and the research questions they can answer, and highlight that both approaches allow neural data to provide additional constraint on the parameters of cognitive models, which will lead to a more precise account of the effect of mind wandering on brain and behavior. We conclude by summarizing prospects for mind wandering as conceived within a model-based cognitive neuroscience framework, highlighting the opportunities for its continued study and the benefits that arise from using well-developed quantitative techniques to study abstract theoretical constructs.

Perceptual decision neurosciences - a model-based review.

In this review we summarize findings published over the past 10 years focusing on the neural correlates of perceptual decision-making. Importantly, this review highlights only studies that employ a model-based approach, i.e., they use quantitative cognitive models in combination with neuroscientific data. The model-based approach allows capturing latent decision-making processes such as strategic adjustments of response thresholds and relate these to interindividual differences or single-trial blood-oxygenated level dependent (BOLD) functional Magnetic Resonance Imaging (fMRI) responses. The review shows that different cortico-subcortical networks are responsive to different latent decision-making processes. More concretely, we show that evidence accumulation is associated with a fronto-parietal network which is partly overlapping with choice bias in perceptual decision making. The setting of decision thresholds is associated with fronto-basal ganglia networks which are also found for choice bias. In sum, we argue that the model-based approach holds great promises to understand the neural correlates of latent cognitive processes.