Echoes from Intrinsic Connectivity Networks in the Subcortex.

Decades of research have greatly improved our understanding of intrinsic human brain organization in terms of functional networks and the transmodal hubs within the cortex at which they converge. However, substrates of multinetwork integration in the human subcortex are relatively uncharted. Here, we leveraged recent advances in subcortical atlasing and ultra-high field (7 T) imaging optimized for the subcortex to investigate the functional architecture of 14 individual structures in healthy adult males and females with a fully data-driven approach. We revealed that spontaneous neural activity in subcortical regions can be decomposed into multiple independent subsignals that correlate with, or "echo," the activity in functional networks across the cortex. Distinct subregions of the thalamus, striatum, claustrum, and hippocampus showed a varied pattern of echoes from attention, control, visual, somatomotor, and default mode networks, demonstrating evidence for a heterogeneous organization supportive of functional integration. Multiple network activity furthermore converged within the globus pallidus externa, substantia nigra, and ventral tegmental area but was specific to one subregion, while the amygdala and pedunculopontine nucleus preferentially affiliated with a single network, showing a more homogeneous topography. Subregional connectivity of the globus pallidus interna, subthalamic nucleus, red nucleus, periaqueductal gray, and locus coeruleus did not resemble patterns of cortical network activity. Together, these finding describe potential mechanisms through which the subcortex participates in integrated and segregated information processing and shapes the spontaneous cognitive dynamics during rest.SIGNIFICANCE STATEMENT Despite the impact of subcortical dysfunction on brain health and cognition, large-scale functional mapping of subcortical structures severely lags behind that of the cortex. Recent developments in subcortical atlasing and imaging at ultra-high field provide new avenues for studying the intricate functional architecture of the human subcortex. With a fully data-driven analysis, we reveal subregional connectivity profiles of a large set of noncortical structures, including those rarely studied in fMRI research. The results have implications for understanding how the functional organization of the subcortex facilitates integrative processing through cross-network information convergence, paving the way for future work aimed at improving our knowledge of subcortical contributions to intrinsic brain dynamics and spontaneous cognition.

Catching wandering minds with tapping fingers: neural and behavioral insights into task-unrelated cognition.

When the human mind wanders, it engages in episodes during which attention is focused on self-generated thoughts rather than on external task demands. Although the sustained attention to response task is commonly used to examine relationships between mind wandering and executive functions, limited executive resources are required for optimal task performance. In the current study, we aimed to investigate the relationship between mind wandering and executive functions more closely by employing a recently developed finger-tapping task to monitor fluctuations in attention and executive control through task performance and periodical experience sampling during concurrent functional magnetic resonance imaging (fMRI) and pupillometry. Our results show that mind wandering was preceded by increases in finger-tapping variability, which was correlated with activity in dorsal and ventral attention networks. The entropy of random finger-tapping sequences was related to activity in frontoparietal regions associated with executive control, demonstrating the suitability of this paradigm for studying executive functioning. The neural correlates of behavioral performance, pupillary dynamics, and self-reported attentional state diverged, thus indicating a dissociation between direct and indirect markers of mind wandering. Together, the investigation of these relationships at both the behavioral and neural level provided novel insights into the identification of underlying mechanisms of mind wandering.

Charting human subcortical maturation across the adult lifespan with in vivo 7 T MRI.

The human subcortex comprises hundreds of unique structures. Subcortical functioning is crucial for behavior, and disrupted function is observed in common neurodegenerative diseases. Despite their importance, human subcortical structures continue to be difficult to study in vivo. Here we provide a detailed account of 17 prominent subcortical structures and ventricles, describing their approximate iron and myelin contents, morphometry, and their age-related changes across the normal adult lifespan. The results provide compelling insights into the heterogeneity and intricate age-related alterations of these structures. They also show that the locations of many structures shift across the lifespan, which is of direct relevance for the use of standard magnetic resonance imaging atlases. The results further our understanding of subcortical morphometry and neuroimaging properties, and of normal aging processes which ultimately can improve our understanding of neurodegeneration.

A unified model for reconstruction and R2* mapping of accelerated 7T data using the quantitative recurrent inference machine.

Quantitative MRI (qMRI) acquired at the ultra-high field of 7 Tesla has been used in visualizing and analyzing subcortical structures. qMRI relies on the acquisition of multiple images with different scan settings, leading to extended scanning times. Data redundancy and prior information from the relaxometry model can be exploited by deep learning to accelerate the imaging process. We propose the quantitative Recurrent Inference Machine (qRIM), with a unified forward model for joint reconstruction and R2*-mapping from sparse data, embedded in a Recurrent Inference Machine (RIM), an iterative inverse problem-solving network. To study the dependency of the proposed extension of the unified forward model to network architecture, we implemented and compared a quantitative End-to-End Variational Network (qE2EVN). Experiments were performed with high-resolution multi-echo gradient echo data of the brain at 7T of a cohort study covering the entire adult life span. The error in reconstructed R2* from undersampled data relative to reference data significantly decreased for the unified model compared to sequential image reconstruction and parameter fitting using the RIM. With increasing acceleration factor, an increasing reduction in the reconstruction error was observed, pointing to a larger benefit for sparser data. Qualitatively, this was following an observed reduction of image blurriness in R2*-maps. In contrast, when using the U-Net as network architecture, a negative bias in R2* in selected regions of interest was observed. Compressed Sensing rendered accurate, but less precise estimates of R2*. The qE2EVN showed slightly inferior reconstruction quality compared to the qRIM but better quality than the U-Net and Compressed Sensing. Subcortical maturation over age measured by a linearly increasing interquartile range of R2* in the striatum was preserved up to an acceleration factor of 9. With the integrated prior of the unified forward model, the proposed qRIM can exploit the redundancy among repeated measurements and shared information between tasks, facilitating relaxometry in accelerated MRI.

Probing the neural signature of mind wandering with simultaneous fMRI-EEG and pupillometry.

Mind wandering reflects the shift in attentional focus from task-related cognition driven by external stimuli toward self-generated and internally-oriented thought processes. Although such task-unrelated thoughts (TUTs) are pervasive and detrimental to task performance, their underlying neural mechanisms are only modestly understood. To investigate TUTs with high spatial and temporal precision, we simultaneously measured fMRI, EEG, and pupillometry in healthy adults while they performed a sustained attention task with experience sampling probes. Features of interest were extracted from each modality at the single-trial level and fed to a support vector machine that was trained on the probe responses. Compared to task-focused attention, the neural signature of TUTs was characterized by weaker activity in the default mode network but elevated activity in its anticorrelated network, stronger functional coupling between these networks, widespread increase in alpha, theta, delta, but not beta, frequency power, predominantly reduced amplitudes of late, but not early, event-related potentials, and larger baseline pupil size. Particularly, information contained in dynamic interactions between large-scale cortical networks was predictive of transient changes in attentional focus above other modalities. Together, our results provide insight into the spatiotemporal dynamics of TUTs and the neural markers that may facilitate their detection.

Towards a mechanistic understanding of the human subcortex.

The human subcortex is a densely populated part of the brain, of which only 7% of the individual structures are depicted in standard MRI atlases. In vivo MRI of the subcortex is challenging owing to its anatomical complexity and its deep location in the brain. The technical advances that are needed to reliably uncover this 'terra incognita' call for an interdisciplinary human neuroanatomical approach. We discuss the emerging methods that could be used in such an approach and the incorporation of the data that are generated from these methods into model-based cognitive neuroscience frameworks.

fMRI protocol optimization for simultaneously studying small subcortical and cortical areas at 7 ​T.

Most fundamental cognitive processes rely on brain networks that include both cortical and subcortical structures. Studying such networks using functional magnetic resonance imaging (fMRI) requires a data acquisition protocol that provides blood-oxygenation-level dependent (BOLD) sensitivity across the entire brain. However, when using standard single echo, echo planar imaging protocols, researchers face a tradeoff between BOLD-sensitivity in cortex and in subcortical areas. Multi echo protocols avoid this tradeoff and can be used to optimize BOLD-sensitivity across the entire brain, at the cost of an increased repetition time. Here, we empirically compare the BOLD-sensitivity of a single echo protocol to a multi echo protocol. Both protocols were designed to meet the specific requirements for studying small, iron rich subcortical structures (including a relatively high spatial resolution and short echo times), while retaining coverage and BOLD-sensitivity in cortical areas. The results indicate that both sequences lead to similar BOLD-sensitivity across the brain at 7 â€‹T.

Sharpness in motion corrected quantitative imaging at 7T.

Sub-millimeter imaging at 7T has opened new possibilities for qualitatively and quantitatively studying brain structure as it evolves throughout the life span. However, subject motion introduces image blurring on the order of magnitude of the spatial resolution and is thus detrimental to image quality. Such motion can be corrected for, but widespread application has not yet been achieved and quantitative evaluation is lacking. This raises a need to quantitatively measure image sharpness throughout the brain. We propose a method to quantify sharpness of brain structures at sub-voxel resolution, and use it to assess to what extent limited motion is related to image sharpness. The method was evaluated in a cohort of 24 healthy volunteers with a wide and uniform age range, aiming to arrive at results that largely generalize to larger populations. Using 3D fat-excited motion navigators, quantitative R1, R2* and Quantitative Susceptibility Maps and T1-weighted images were retrospectively corrected for motion. Sharpness was quantified in all modalities for selected regions of interest (ROI) by fitting the sigmoidally shaped error function to data within locally homogeneous clusters. A strong, almost linear correlation between motion and sharpness improvement was observed, and motion correction significantly improved sharpness. Overall, the Full Width at Half Maximum reduced from 0.88 mm to 0.70 mm after motion correction, equivalent to a 2.0 times smaller voxel volume. Motion and sharpness were not found to correlate with the age of study participants. We conclude that in our data, motion correction using fat navigators is overall able to restore the measured sharpness to the imaging resolution, irrespective of the amount of motion observed during scanning.

The Amsterdam Ultra-high field adult lifespan database (AHEAD): A freely available multimodal 7 Tesla submillimeter magnetic resonance imaging database.

Normative databases allow testing of novel hypotheses without the costly collection of magnetic resonance imaging (MRI) data. Here we present the Amsterdam Ultra-high field adult lifespan database (AHEAD). The AHEAD consists of 105 7 Tesla (T) whole-brain structural MRI scans tailored specifically to imaging of the human subcortex, including both male and female participants and covering the entire adult life span (18-80 yrs). We used these data to create probability maps for the subthalamic nucleus, substantia nigra, internal and external segment of the globus pallidus, and the red nucleus. Data was acquired at a submillimeter resolution using a multi-echo (ME) extension of the second gradient-echo image of the MP2RAGE sequence (MP2RAGEME) sequence, resulting in complete anatomical alignment of quantitative, R1-maps, R2*-maps, T1-maps, T1-weighted images, T2*-maps, and quantitative susceptibility mapping (QSM). Quantitative MRI maps, and derived probability maps of basal ganglia structures are freely available for further analyses.

Functional neuroanatomical review of the ventral tegmental area.

The ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) are assumed to play a key role in dopamine-related functions such as reward-related behaviour, motivation, addiction and motor functioning. Although dopamine-producing midbrain structures are bordering, they show significant differences in structure and function that argue for a distinction when studying the functions of the dopaminergic midbrain, especially by means of neuroimaging. First, unlike the SNc, the VTA is not a nucleus, which makes it difficult to delineate the structure due to lack of clear anatomical borders. Second, there is no consensus in the literature about the anatomical nomenclature to describe the VTA. Third, these factors in combination with limitations in magnetic resonance imaging (MRI) complicate VTA visualization. We suggest that developing an MRI-compatible probabilistic atlas of the VTA will help to overcome these issues. Such an atlas can be used to identify the individual VTA and serve as region-of-interest for functional MRI.

Modeling distracted performance.

The sustained attention to response task (SART) has been the primary method of studying the phenomenon of mind wandering. We develop and experimentally test the first integrated cognitive process model that quantitatively explains all stationary features of behavioral performance in the SART. The model assumes that performance is generated by a competitive race between a stimulus-related decision process and a stimulus-unrelated rhythmic response process. We propose that the stimulus-unrelated process entrains to timing regularities in the task environment, and is unconditionally triggered as a habit or 'insurance policy' to protect against the deleterious effects of mind wandering on ongoing task performance. For two SART experiments the model provided a quantitatively precise account of a range of previously reported trends in choice, response time and self-reported mind wandering data. It also accounted for three previously unidentified features of response time distributions that place critical constraints on cognitive models of performance in situations when people might engage in task-unrelated thoughts. Furthermore, the parameters of the rhythmic race model were meaningfully associated with participants' self-reported distraction, even though the model was never informed by these data. In a validation test, we disrupted the latent rhythmic component with a manipulation of inter-trial-interval variability, and showed that the architecture of the model provided insight into its counter-intuitive effect. We conclude that performance in the presence of mind wandering can be conceived as a competitive latent decision vs. rhythmic response process. We discuss how the rhythmic race model is not restricted to the study of distraction or mind wandering; it is applicable to any domain requiring repetitive responding where evidence accumulation is assumed to be an underlying principle of behavior.

Frontosubthalamic Circuits for Control of Action and Cognition.

The subthalamic nucleus (STN) of the basal ganglia appears to have a potent role in action and cognition. Anatomical and imaging studies show that different frontal cortical areas directly project to the STN via so-called hyperdirect pathways. This review reports some of the latest findings about such circuits, including simultaneous recordings from cortex and the STN in humans, single-unit recordings in humans, high-resolution fMRI, and neurocomputational modeling. We argue that a major function of the STN is to broadly pause behavior and cognition when stop signals, conflict signals, or surprise signals occur, and that the fronto-STN circuits for doing this, at least for stopping and conflict, are dissociable anatomically and in terms of their spectral reactivity. We also highlight recent evidence for synchronization of oscillations between prefrontal cortex and the STN, which may provide a preferential "window in time" for single neuron communication via long-range connections.

Comparing functional MRI protocols for small, iron-rich basal ganglia nuclei such as the subthalamic nucleus at 7 T and 3 T.

The basal ganglia (BG) form a network of subcortical nuclei. Functional magnetic resonance imaging (fMRI) in the BG could provide insight in its functioning and the underlying mechanisms of Deep Brain Stimulation (DBS). However, fMRI of the BG with high specificity is challenging, because the nuclei are small and variable in their anatomical location. High resolution fMRI at field strengths of 7 Tesla (T) could help resolve these challenges to some extent. A set of MR protocols was developed for functional imaging of the BG nuclei at 3 T and 7 T. The protocols were validated using a stop-signal reaction task (Logan et al. []: J Exp Psychol: Human Percept Perform 10:276-291). Compared with sub-millimeter 7 T fMRI protocols aimed at cortex, a reduction of echo time and spatial resolution was strictly necessary to obtain robust Blood Oxygen Level Dependent (BOLD) sensitivity in the BG. An fMRI protocol at 3 T with identical resolution to the 7 T showed no robust BOLD sensitivity in any of the BG nuclei. The results suggest that the subthalamic nucleus, as well as the substantia nigra, red nucleus, and the internal and external parts of the globus pallidus show increased activation in failed stop trials compared with successful stop and go trials. Hum Brain Mapp 38:3226-3248, 2017. © 2017 Wiley Periodicals, Inc.

Revisiting the evidence for collapsing boundaries and urgency signals in perceptual decision-making.

For nearly 50 years, the dominant account of decision-making holds that noisy information is accumulated until a fixed threshold is crossed. This account has been tested extensively against behavioral and neurophysiological data for decisions about consumer goods, perceptual stimuli, eyewitness testimony, memories, and dozens of other paradigms, with no systematic misfit between model and data. Recently, the standard model has been challenged by alternative accounts that assume that less evidence is required to trigger a decision as time passes. Such "collapsing boundaries" or "urgency signals" have gained popularity in some theoretical accounts of neurophysiology. Nevertheless, evidence in favor of these models is mixed, with support coming from only a narrow range of decision paradigms compared with a long history of support from dozens of paradigms for the standard theory. We conducted the first large-scale analysis of data from humans and nonhuman primates across three distinct paradigms using powerful model-selection methods to compare evidence for fixed versus collapsing bounds. Overall, we identified evidence in favor of the standard model with fixed decision boundaries. We further found that evidence for static or dynamic response boundaries may depend on specific paradigms or procedures, such as the extent of task practice. We conclude that the difficulty of selecting between collapsing and fixed bounds models has received insufficient attention in previous research, calling into question some previous results.

Transcranial Direct Current Stimulation Does Not Influence the Speed-Accuracy Tradeoff in Perceptual Decision-making: Evidence from Three Independent Studies.

In perceptual decision-making tasks, people balance the speed and accuracy with which they make their decisions by modulating a response threshold. Neuroimaging studies suggest that this speed-accuracy tradeoff is implemented in a corticobasal ganglia network that includes an important contribution from the pre-SMA. To test this hypothesis, we used anodal transcranial direct current stimulation (tDCS) to modulate neural activity in pre-SMA while participants performed a simple perceptual decision-making task. Participants viewed a pattern of moving dots and judged the direction of the global motion. In separate trials, they were cued to either respond quickly or accurately. We used the diffusion decision model to estimate the response threshold parameter, comparing conditions in which participants received sham or anodal tDCS. In three independent experiments, we failed to observe an influence of tDCS on the response threshold. Additional, exploratory analyses showed no influence of tDCS on the duration of nondecision processes or on the efficiency of information processing. Taken together, these findings provide a cautionary note, either concerning the causal role of pre-SMA in decision-making or on the utility of tDCS for modifying response caution in decision-making tasks.

Automated segmentation of the substantia nigra, subthalamic nucleus and red nucleus in 7T data at young and old age.

With recent developments in MR acquisition at 7T, smaller brainstem structures such as the red nuclei, substantia nigra and subthalamic nuclei can be imaged with good contrast and resolution. These structures have important roles both in the study of the healthy brain and in diseases such as Parkinson's disease, but few methods have been described to automatically segment them. In this paper, we extend a method that we have previously proposed for segmentation of the striatum and globus pallidus to segment these deeper and smaller structures. We modify the method to allow more direct control over segmentation smoothness by using a Markov random field prior. We investigate segmentation performance in three age groups and show that the method produces consistent results that correspond well with manual segmentations. We perform a vertex-based analysis to identify changes with age in the shape of the structures and present results suggesting that the method may be at least as effective as manual delineation in capturing differences between subjects.

Striatal activation reflects urgency in perceptual decision making.

Deciding between multiple courses of action often entails an increasing need to do something as time passes - a sense of urgency. This notion of urgency is not incorporated in standard theories of speeded decision making that assume information is accumulated until a critical fixed threshold is reached. Yet, it is hypothesized in novel theoretical models of decision making. In two experiments, we investigated the behavioral and neural evidence for an "urgency signal" in human perceptual decision making. Experiment 1 found that as the duration of the decision making process increased, participants made a choice based on less evidence for the selected option. Experiment 2 replicated this finding, and additionally found that variability in this effect across participants covaried with activation in the striatum. We conclude that individual differences in susceptibility to urgency are reflected by striatal activation. By dynamically updating a response threshold, the striatum is involved in signaling urgency in humans.

Automatic segmentation of the striatum and globus pallidus using MIST: Multimodal Image Segmentation Tool.

Accurate segmentation of the subcortical structures is frequently required in neuroimaging studies. Most existing methods use only a T1-weighted MRI volume to segment all supported structures and usually rely on a database of training data. We propose a new method that can use multiple image modalities simultaneously and a single reference segmentation for initialisation, without the need for a manually labelled training set. The method models intensity profiles in multiple images around the boundaries of the structure after nonlinear registration. It is trained using a set of unlabelled training data, which may be the same images that are to be segmented, and it can automatically infer the location of the physical boundary using user-specified priors. We show that the method produces high-quality segmentations of the striatum, which is clearly visible on T1-weighted scans, and the globus pallidus, which has poor contrast on such scans. The method compares favourably to existing methods, showing greater overlap with manual segmentations and better consistency.

The Age-ility Project (Phase 1): Structural and functional imaging and electrophysiological data repository.

Our understanding of the complex interplay between structural and functional organisation of brain networks is being advanced by the development of novel multi-modal analyses approaches. The Age-ility Project (Phase 1) data repository offers open access to structural MRI, diffusion MRI, and resting-state fMRI scans, as well as resting-state EEG recorded from the same community participants (n=131, 15-35 y, 66 male). Raw imaging and electrophysiological data as well as essential demographics are made available via the NITRC website. All data have been reviewed for artifacts using a rigorous quality control protocol and detailed case notes are provided.