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

Changes in Functional Connectivity Relate to Modulation of Cognitive Control by Subthalamic Stimulation

Subthalamic (STN) deep brain stimulation (DBS) in Parkinson's disease (PD) patients not only improves kinematic parameters of movement but also modulates cognitive control in the motor and non-motor domain, especially in situations of high conflict. The objective of this study was to investigate the relationship between DBS-induced changes in functional connectivity at rest and modulation of response- and movement inhibition by STN-DBS in a visuomotor task involving high conflict. During DBS ON and OFF conditions, we conducted a visuomotor task in 14 PD patients who previously underwent resting-state functional MRI (rs-fMRI) acquisitions DBS ON and OFF as part of a different study. In the task, participants had to move a cursor with a pen on a digital tablet either toward (automatic condition) or in the opposite direction (controlled condition) of a target. STN-DBS induced modulation of resting-state functional connectivity (RSFC) as a function of changes in behavior ON versus OFF DBS was estimated using link-wise network-based statistics. Behavioral results showed diminished reaction time adaptation and higher pen-to-target movement velocity under DBS. Reaction time reduction was associated with attenuated functional connectivity between cortical motor areas, basal ganglia, and thalamus. On the other hand, increased movement velocity ON DBS was associated with stronger pallido-thalamic connectivity. These findings suggest that decoupling of a motor cortico-basal ganglia network underlies impaired inhibitory control in PD patients undergoing subthalamic DBS and highlight the concept of functional network modulation through DBS.

The human subthalamic nucleus transiently inhibits active attentional processes

The subthalamic nucleus (STN) of the basal ganglia is key to the inhibitory control of movement. Consequently, it is a primary target for the neurosurgical treatment of movement disorders like Parkinson's disease, where modulating the STN via deep brain stimulation (DBS) can release excess inhibition of thalamocortical motor circuits. However, the STN is also anatomically connected to other thalamocortical circuits, including those underlying cognitive processes like attention. Notably, STN-DBS can also affect these processes. This suggests that the STN may also contribute to the inhibition of non-motor activity and that STN-DBS may cause changes to this inhibition. Here we tested this hypothesis in humans. We used a novel, wireless outpatient method to record intracranial local field potentials (LFP) from STN DBS implants during a visual attention task (Experiment 1, n = 12). These outpatient measurements allowed the simultaneous recording of high-density EEG, which we used to derive the steady state visual evoked potential (SSVEP), a well established neural index of visual attentional engagement. By relating STN activity to this neural marker of attention (instead of overt behaviour), we avoided possible confounds resulting from STN's motor role. We aimed to test whether the STN contributes to the momentary inhibition of the SSVEP caused by unexpected, distracting sounds. Furthermore, we causally tested this association in a second experiment, where we modulated STN via DBS across two sessions of the task, spaced at least 1 week apart (n = 21, no sample overlap with Experiment 1). The LFP recordings in Experiment 1 showed that reductions of the SSVEP after distracting sounds were preceded by sound-related γ-frequency (>60 Hz) activity in the STN. Trial-to-trial modelling further showed that this STN activity statistically mediated the sounds' suppressive effect on the SSVEP. In Experiment 2, modulating STN activity via DBS significantly reduced these sound-related SSVEP reductions. This provides causal evidence for the role of the STN in the surprise-related inhibition of attention. These findings suggest that the human STN contributes to the inhibition of attention, a non-motor process. This supports a domain-general view of the inhibitory role of the STN. Furthermore, these findings also suggest a potential mechanism underlying some of the known cognitive side effects of STN-DBS treatment, especially on attentional processes. Finally, our newly established outpatient LFP recording technique facilitates the testing of the role of subcortical nuclei in complex cognitive tasks, alongside recordings from the rest of the brain, and in much shorter time than peri-surgical recordings.

Consistency and stability of individualized cortical functional networks parcellation at 3.0 T and 5.0 T MRI

Background

Individualized cortical functional networks parcellation has been reported as highly reproducible at 3.0 T. However, in view of the complexity of cortical networks and the greatly increased sensitivity provided by ultra-high field 5.0 T MRI, the parcellation consistency between different magnetic fields is unclear.

Purpose

To explore the consistency and stability of individualized cortical functional networks parcellation at 3.0 T and 5.0 T MRI based on spatial and functional connectivity analysis.

Materials and methods

Thirty healthy young participants were enrolled. Each subject underwent resting-state fMRI at both 3.0 T and 5.0 T in a random order in less than 48 h. The individualized cortical functional networks was parcellated for each subject using a previously proposed iteration algorithm. Dice coefficient was used to evaluate the spatial consistency of parcellated networks between 3.0 T and 5.0 T. Functional connectivity (FC) consistency was evaluated using the Euclidian distance and Graph-theory metrics.

Results

A functional cortical atlas consisting of 18 networks was individually parcellated at 3.0 T and 5.0 T. The spatial consistency of these networks at 3.0 T and 5.0 T for the same subject was significantly higher than that of inter-individuals. The FC between the 18 networks acquired at 3.0 T and 5.0 T were highly consistent for the same subject. Positive cross-subject correlations in Graph-theory metrics were found between 3.0 T and 5.0 T.

Conclusion

Individualized cortical functional networks at 3.0 T and 5.0 T showed consistent and stable parcellation results both spatially and functionally. The 5.0 T MR provides finer functional sub-network characteristics than that of 3.0 T.

Functional connectivity across the human subcortical auditory system using an autoregressive matrix-Gaussian copula graphical model approach with partial correlations

The auditory system comprises multiple subcortical brain structures that process and refine incoming acoustic signals along the primary auditory pathway. Due to technical limitations of imaging small structures deep inside the brain, most of our knowledge of the subcortical auditory system is based on research in animal models using invasive methodologies. Advances in ultrahigh-field functional magnetic resonance imaging (fMRI) acquisition have enabled novel noninvasive investigations of the human auditory subcortex, including fundamental features of auditory representation such as tonotopy and periodotopy. However, functional connectivity across subcortical networks is still underexplored in humans, with ongoing development of related methods. Traditionally, functional connectivity is estimated from fMRI data with full correlation matrices. However, partial correlations reveal the relationship between two regions after removing the effects of all other regions, reflecting more direct connectivity. Partial correlation analysis is particularly promising in the ascending auditory system, where sensory information is passed in an obligatory manner, from nucleus to nucleus up the primary auditory pathway, providing redundant but also increasingly abstract representations of auditory stimuli. While most existing methods for learning conditional dependency structures based on partial correlations assume independently and identically Gaussian distributed data, fMRI data exhibit significant deviations from Gaussianity as well as high-temporal autocorrelation. In this paper, we developed an autoregressive matrix-Gaussian copula graphical model (ARMGCGM) approach to estimate the partial correlations and thereby infer the functional connectivity patterns within the auditory system while appropriately accounting for autocorrelations between successive fMRI scans. Our results show strong positive partial correlations between successive structures in the primary auditory pathway on each side (left and right), including between auditory midbrain and thalamus, and between primary and associative auditory cortex. These results are highly stable when splitting the data in halves according to the acquisition schemes and computing partial correlations separately for each half of the data, as well as across cross-validation folds. In contrast, full correlation-based analysis identified a rich network of interconnectivity that was not specific to adjacent nodes along the pathway. Overall, our results demonstrate that unique functional connectivity patterns along the auditory pathway are recoverable using novel connectivity approaches and that our connectivity methods are reliable across multiple acquisitions.

A high-resolution 7 Tesla resting-state fMRI dataset optimized for studying the subcortex

To achieve a comprehensive understanding of spontaneous brain dynamics in humans, in vivo acquisition of intrinsic activity across both cortical and subcortical regions is necessary. Here we present advanced whole-brain, resting-state functional magnetic resonance imaging (rs-fMRI) data acquired at 7 Tesla with 1.5 mm isotropic voxel resolution. Functional images were obtained from 56 healthy adults (33 females, ages 19-39 years) in two runs of 15 min eyes-open wakeful rest. The high spatial resolution and short echo times of the multiband echo-planar imaging (EPI) protocol optimizes blood oxygen level-dependent (BOLD)-sensitivity for the subcortex while concurrent respiratory and cardiac measures enable retrospective correction of physiological noise, resulting in data that is highly suitable for researchers interested in subcortical BOLD signal. Functional timeseries were coregistered to high-resolution T1-weighted structural data (0.75 mm isotropic voxels) acquired during the same scanning session. To accommodate data reutilization, functional and structural images were formatted to the Brain Imaging Data Structure (BIDS) and preprocessed with fMRIPrep.

7 T and beyond: toward a synergy between fMRI-based presurgical mapping at ultrahigh magnetic fields, AI, and robotic neurosurgery

Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical morbidity. Here, we discuss presurgical fMRI mapping at ultra-high magnetic fields (UHF), i.e., ≥ 7 T, in the light of the current growing interest in artificial intelligence (AI) and robot-assisted neurosurgery. The potential of submillimetre fMRI mapping can help better appreciate uncertainty on resection margins, though geometric distortions at UHF might lessen the accuracy of fMRI maps. A useful trade-off for UHF fMRI is to collect data with 1-mm isotropic resolution to ensure high sensitivity and subsequently a low risk of false negatives. Scanning at UHF might yield a revival interest in slow event-related fMRI, thereby offering a richer depiction of the dynamics of fMRI responses. The potential applications of AI concern denoising and artefact removal, generation of super-resolution fMRI maps, and accurate fusion or coregistration between anatomical and fMRI maps. The latter can benefit from the use of T1-weighted echo-planar imaging for better visualization of brain activations. Such AI-augmented fMRI maps would provide high-quality input data to robotic surgery systems, thereby improving the accuracy and reliability of robot-assisted neurosurgery. Ultimately, the advancement in fMRI at UHF would promote clinically useful synergies between fMRI, AI, and robotic neurosurgery.Relevance statement This review highlights the potential synergies between fMRI at UHF, AI, and robotic neurosurgery in improving the accuracy and reliability of fMRI-based presurgical mapping.Key points• Presurgical fMRI mapping at UHF improves spatial resolution and sensitivity.• Slow event-related designs offer a richer depiction of fMRI responses dynamics.• AI can support denoising, artefact removal, and generation of super-resolution fMRI maps.• AI-augmented fMRI maps can provide high-quality input data to robotic surgery systems.

Corticospinal excitability reductions during action preparation and action stopping in humans: Different sides of the same inhibitory coin?

Motor functions and cognitive processes are closely associated with each other. In humans, this linkage is reflected in motor system state changes both when an action must be prepared and stopped. Single-pulse transcranial magnetic stimulation showed that both action preparation and action stopping are accompanied by a reduction of corticospinal excitability, referred to as preparatory and response inhibition, respectively. While previous efforts have been made to describe both phenomena extensively, an updated and comprehensive comparison of the two phenomena is lacking. To ameliorate such deficit, this review focuses on the role and interpretation of single-coil (single-pulse and paired-pulse) and dual-coil TMS outcome measures during action preparation and action stopping in humans. To that effect, it aims to identify commonalities and differences, detailing how TMS-based outcome measures are affected by states, traits, and psychopathologies in both processes. Eventually, findings will be compared, and open questions will be addressed to aid future research.

Association of emotional and behavioral problems with the development of the substantia nigra, subthalamic nucleus, and red nucleus volumes and asymmetries from childhood to adolescence: A longitudinal cohort study

The substantia nigra (SN), subthalamic nucleus (STN), and red nucleus (RN) have been widely studied as important biomarkers of degenerative diseases. However, how they develop in childhood and adolescence and are affected by emotional behavior has not been studied thus far. This population-based longitudinal cohort study used data from a representative sample followed two to five times. Emotional and behavioral problems were assessed with the Strengths and Difficulties Questionnaire (SDQ). Linear mixed models were used to map developmental trajectories and behavioral regulation. Using an innovative automated image segmentation technique, we quantified the volumes and asymmetries of the SN, STN and RN with 1226 MRI scans of a large longitudinal sample of 667 subjects aged 6-15 years and mapped their developmental trajectories. The results showed that the absolute and relative volumes of the bilateral SN and right STN showed linear increases, while the absolute volume of the right RN and relative volume of the bilateral RN decreased linearly, these effects were not affected by gender. Hyperactivity/inattention weakened the increase in SN volume and reduced the absolute volume of the STN, conduct problems impeded the RN volume from decreasing, and emotional symptoms changed the direction of SN lateralization. This longitudinal cohort study mapped the developmental trajectories of SN, STN, and RN volumes and asymmetries from childhood to adolescence, and found the association of emotional symptoms, conduct problems, and hyperactivity/inattention with these trajectories, providing guidance for preventing and intervening in cognitive and emotional behavioral problems.

Joint Modelling of Latent Cognitive Mechanisms Shared Across Decision-Making Domains

Decision-making behavior is often understood using the framework of evidence accumulation models (EAMs). Nowadays, EAMs are applied to various domains of decision-making with the underlying assumption that the latent cognitive constructs proposed by EAMs are consistent across these domains. In this study, we investigate both the extent to which the parameters of EAMs are related between four different decision-making domains and across different time points. To that end, we make use of the novel joint modelling approach, that explicitly includes relationships between parameters, such as covariances or underlying factors, in one combined joint model. Consequently, this joint model also accounts for measurement error and uncertainty within the estimation of these relations. We found that EAM parameters were consistent between time points on three of the four decision-making tasks. For our between-task analysis, we constructed a joint model with a factor analysis on the parameters of the different tasks. Our two-factor joint model indicated that information processing ability was related between the different decision-making domains. However, other cognitive constructs such as the degree of response caution and urgency were only comparable on some domains.

The brainstem's red nucleus was evolutionarily upgraded to support goal-directed action

The red nucleus is a large brainstem structure that coordinates limb movement for locomotion in quadrupedal animals (Basile et al., 2021). The humans red nucleus has a different pattern of anatomical connectivity compared to quadrupeds, suggesting a unique purpose (Hatschek, 1907). Previously the function of the human red nucleus remained unclear at least partly due to methodological limitations with brainstem functional neuroimaging (Sclocco et al., 2018). Here, we used our most advanced resting-state functional connectivity (RSFC) based precision functional mapping (PFM) in highly sampled individuals (n = 5) and large group-averaged datasets (combined N ~ 45,000), to precisely examine red nucleus functional connectivity. Notably, red nucleus functional connectivity to motor-effector networks (somatomotor hand, foot, and mouth) was minimal. Instead, red nucleus functional connectivity along the central sulcus was specific to regions of the recently discovered somato-cognitive action network (SCAN; (Gordon et al., 2023)). Outside of primary motor cortex, red nucleus connectivity was strongest to the cingulo-opercular (CON) and salience networks, involved in action/cognitive control (Dosenbach et al., 2007; Newbold et al., 2021) and reward/motivated behavior (Seeley, 2019), respectively. Functional connectivity to these two networks was organized into discrete dorsal-medial and ventral-lateral zones. Red nucleus functional connectivity to the thalamus recapitulated known structural connectivity of the dento-rubral thalamic tract (DRTT) and could prove clinically useful in functionally targeting the ventral intermediate (VIM) nucleus. In total, our results indicate that far from being a 'motor' structure, the red nucleus is better understood as a brainstem nucleus for implementing goal-directed behavior, integrating behavioral valence and action plans.

Distinct Neural Components of Visually Guided Grasping during Planning and Execution

Selecting suitable grasps on three-dimensional objects is a challenging visuomotor computation, which involves combining information about an object (e.g., its shape, size, and mass) with information about the actor's body (e.g., the optimal grasp aperture and hand posture for comfortable manipulation). Here, we used functional magnetic resonance imaging to investigate brain networks associated with these distinct aspects during grasp planning and execution. Human participants of either sex viewed and then executed preselected grasps on L-shaped objects made of wood and/or brass. By leveraging a computational approach that accurately predicts human grasp locations, we selected grasp points that disentangled the role of multiple grasp-relevant factors, that is, grasp axis, grasp size, and object mass. Representational Similarity Analysis revealed that grasp axis was encoded along dorsal-stream regions during grasp planning. Grasp size was first encoded in ventral stream areas during grasp planning then in premotor regions during grasp execution. Object mass was encoded in ventral stream and (pre)motor regions only during grasp execution. Premotor regions further encoded visual predictions of grasp comfort, whereas the ventral stream encoded grasp comfort during execution, suggesting its involvement in haptic evaluation. These shifts in neural representations thus capture the sensorimotor transformations that allow humans to grasp objects.SIGNIFICANCE STATEMENT Grasping requires integrating object properties with constraints on hand and arm postures. Using a computational approach that accurately predicts human grasp locations by combining such constraints, we selected grasps on objects that disentangled the relative contributions of object mass, grasp size, and grasp axis during grasp planning and execution in a neuroimaging study. Our findings reveal a greater role of dorsal-stream visuomotor areas during grasp planning, and, surprisingly, increasing ventral stream engagement during execution. We propose that during planning, visuomotor representations initially encode grasp axis and size. Perceptual representations of object material properties become more relevant instead as the hand approaches the object and motor programs are refined with estimates of the grip forces required to successfully lift the object.

Neural mechanisms of domain-general inhibitory control

Inhibitory control is a fundamental mechanism underlying flexible behavior and features in theories across many areas of cognitive and psychological science. However, whereas many theories implicitly or explicitly assume that inhibitory control is a domain-general process, the vast majority of neuroscientific work has hitherto focused on individual domains, such as motor, mnemonic, or attentional inhibition. Here, we attempt to close this gap by highlighting recent work that demonstrates shared neuroanatomical and neurophysiological signatures of inhibitory control across domains. We propose that the regulation of thalamocortical drive by a fronto-subthalamic mechanism operating in the β band might be a domain-general mechanism for inhibitory control in the human brain.

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.

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.

Reinforcement learning with associative or discriminative generalization across states and actions: fMRI at 3 T and 7 T

The model-free algorithms of "reinforcement learning" (RL) have gained clout across disciplines, but so too have model-based alternatives. The present study emphasizes other dimensions of this model space in consideration of associative or discriminative generalization across states and actions. This "generalized reinforcement learning" (GRL) model, a frugal extension of RL, parsimoniously retains the single reward-prediction error (RPE), but the scope of learning goes beyond the experienced state and action. Instead, the generalized RPE is efficiently relayed for bidirectional counterfactual updating of value estimates for other representations. Aided by structural information but as an implicit rather than explicit cognitive map, GRL provided the most precise account of human behavior and individual differences in a reversal-learning task with hierarchical structure that encouraged inverse generalization across both states and actions. Reflecting inference that could be true, false (i.e., overgeneralization), or absent (i.e., undergeneralization), state generalization distinguished those who learned well more so than action generalization. With high-resolution high-field fMRI targeting the dopaminergic midbrain, the GRL model's RPE signals (alongside value and decision signals) were localized within not only the striatum but also the substantia nigra and the ventral tegmental area, including specific effects of generalization that also extend to the hippocampus. Factoring in generalization as a multidimensional process in value-based learning, these findings shed light on complexities that, while challenging classic RL, can still be resolved within the bounds of its core computations.

Neuroimaging at 7 Tesla: a pictorial narrative review

Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.

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.

Functional magnetic resonance imaging responses during perceptual decision-making at 3 and 7 T in human cortex, striatum, and brainstem

While functional magnetic resonance imaging (fMRI) at ultra‐high field (7 T) promises a general increase in sensitivity compared to lower field strengths, the benefits may be most pronounced for specific applications. The current study aimed to evaluate the relative benefit of 7 over 3 T fMRI for the assessment of responses evoked in different brain regions by a well‐controlled cognitive task. At 3 and 7 T, the same participants made challenging perceptual decisions about visual motion combined with monetary rewards for correct choices. Previous work on this task has extensively characterized the underlying cognitive computations and single‐cell responses in cortical and subcortical structures. We quantified the evoked fMRI responses in extrastriate visual cortical areas, the striatum, and the brainstem during the decision interval and the post‐feedback interval of the task. The dependence of response amplitudes on field strength during the decision interval differed between cortical, striatal, and brainstem regions, with a generally bigger 7 versus 3 T benefit in subcortical structures. We also found stronger responses during relatively easier than harder decisions at 7 T for dopaminergic midbrain nuclei, in line with reward expectation. Our results demonstrate the potential of 7 T fMRI for illuminating the contribution of small brainstem nuclei to the orchestration of cognitive computations in the human brain.

Advances in spiral fMRI: A high-resolution study with single-shot acquisition

Spiral fMRI has been put forward as a viable alternative to rectilinear echo-planar imaging, in particular due to its enhanced average k-space speed and thus high acquisition efficiency. This renders spirals attractive for contemporary fMRI applications that require high spatiotemporal resolution, such as laminar or columnar fMRI. However, in practice, spiral fMRI is typically hampered by its reduced robustness and ensuing blurring artifacts, which arise from imperfections in both static and dynamic magnetic fields. Recently, these limitations have been overcome by the concerted application of an expanded signal model that accounts for such field imperfections, and its inversion by iterative image reconstruction. In the challenging ultra-high field environment of 7 Tesla, where field inhomogeneity effects are aggravated, both multi-shot and single-shot 2D spiral imaging at sub-millimeter resolution was demonstrated with high depiction quality and anatomical congruency. In this work, we further these advances towards a time series application of spiral readouts, namely, single-shot spiral BOLD fMRI at 0.8 mm in-plane resolution. We demonstrate that high-resolution spiral fMRI at 7 T is not only feasible, but delivers both excellent image quality, BOLD sensitivity, and spatial specificity of the activation maps, with little artifactual blurring. Furthermore, we show the versatility of the approach with a combined in/out spiral readout at a more typical resolution (1.5 mm), where the high acquisition efficiency allows to acquire two images per shot for improved sensitivity by echo combination.

Structure-function similarities in deep brain stimulation targets cross-species

Deep Brain Stimulation (DBS) is an effective neurosurgical treatment to alleviate motor symptoms of advanced Parkinson's disease. Due to its potential, DBS usage is rapidly expanding to target a large number of brain regions to treat a wide range of diseases and neuropsychiatric disorders. The identification and validation of new target regions heavily rely on the insights gained from rodent and primate models. Here we present a large-scale automatic meta-analysis in which the structure-function associations within and between species are compared for 21 DBS targets in humans. The results indicate that the structure-function association for the majority of the 21 included subcortical areas were conserved cross-species. A subset of structures showed overlapping functional association. This can potentially be attributed to shared brain networks and might explain why multiple brain areas are targeted for the same disease or neuropsychiatric disorder.

Parallel cognitive processing streams in human prefrontal cortex: Parsing areal-level brain network for response inhibition

Multiple cognitive processes are recruited to achieve adaptive behavior. However, it is poorly understood how such cognitive processes are implemented in temporal cascades of human cerebral cortical areas as processing streams to achieve behavior. In the present study, we identify cortical processing streams for response inhibition and examine relationships among the processing streams. Functional magnetic resonance imaging (MRI) and time-resolved single-pulse transcranial magnetic stimulation (TMS) reveal three distinct critical timings of transient disruption in the functionally essential cortical areas that belong to two distinct cerebrocortical networks. Furthermore, single-pulse TMS following suppression of the ventral posterior inferior frontal cortex (vpIFC) with repetitive TMS reveals information flow from the vpIFC to the presupplementary motor area (preSMA) within the same network but not to the dorsal posterior inferior frontal cortex (dpIFC) across different networks. These causal behavioral effects suggest two parallel processing streams (vpIFC-preSMA versus dpIFC-intraparietal sulcus) that act concurrently during response inhibition.

Advances in resting state fMRI acquisitions for functional connectomics

Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.

Towards real-world generalizability of a circuit for action-stopping

Two decades of cross-species neuroscience research on rapid action-stopping in the laboratory has provided motivation for an underlying prefrontal-basal ganglia circuit. Here we provide an update of key studies from the past few years. We conclude that this basic neural circuit is on increasingly firm ground, and we move on to consider whether the action-stopping function implemented by this circuit applies beyond the simple laboratory stop signal task. We advance through a series of studies of increasing 'real-worldness', starting with laboratory tests of stopping of speech, gait and bodily functions, and then going beyond the laboratory to consider neural recordings and stimulation during moments of control presumably required in everyday activities such as walking and driving. We end by asking whether stopping research has clinical relevance, focusing on movement disorders such as stuttering, tics and freezing of gait. Overall, we conclude there are hints that the prefrontal-basal ganglia action-stopping circuit that is engaged by the basic stop signal task is recruited in myriad scenarios; however, truly proving this for real-world scenarios requires a new generation of studies that will need to overcome substantial technical and inferential challenges.

Mapping functional gradients of the striatal circuit using simultaneous microelectric stimulation and ultrahigh-field fMRI in non-human primates

Advances in functional magnetic resonance imaging (fMRI) have significantly enhanced our understanding of the striatal system of both humans and non-human primates (NHP) over the last few decades. However, its circuit-level functional anatomy remains poorly understood, partly because in-vivo fMRI cannot directly perturb a brain system and map its casual input-output relationship. Also, routine 3T fMRI has an insufficient spatial resolution. We performed electrical microstimulation (EM) of the striatum in lightly-anesthetized NHPs while simultaneously mapping whole-brain activation, using contrast-enhanced fMRI at ultra-high-field 7T. By stimulating multiple positions along the striatum's main (dorsal-to-ventral) axis, we revealed its complex functional circuit concerning mutually connected subsystems in both cortical and subcortical areas. Indeed, within the striatum, there were distinct brain activation patterns across different stimulation sites. Specifically, dorsal stimulation revealed a medial-to-lateral elongated shape of activation in upper caudate and putamen areas, whereas ventral stimulation evoked areas confined to the medial and lower caudate. Such dorsoventral gradients also appeared in neocortical and thalamic activations, indicating consistent embedding profiles of the striatal system across the whole brain. These findings reflect different forms of within-circuit and inter-regional neuronal connectivity between the dorsal and ventromedial striatum. These patterns both shared and contrasted with previous anatomical tract-tracing and in-vivo resting-state fMRI studies. Our approach of combining microstimulation and whole-brain fMRI mapping in NHPs provides a unique opportunity to integrate our understanding of a targeted brain area's meso- and macro-scale functional systems.

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.

Tuned neural responses to haptic numerosity in the putamen

The ability to perceive the numerosity of items in the environment is critical for behavior of species across the evolutionary tree. Though the focus of studies of numerosity perception lays on the parietal and frontal cortices, the ability to perceive numerosity by a range of species suggests that subcortical nuclei may be implicated in the process. Recently, we have uncovered tuned neural responses to haptic numerosity in the human cortex. Here, we questioned whether subcortical nuclei are also engaged in perception of haptic numerosity. To that end, we utilized a task of haptic numerosity exploration, together with population receptive field model of numerosity selective responses measured at ultra-high field MRI (7T). We found tuned neural responses to haptic numerosity in the bilateral putamen. Similar to the cortex, the population receptive fields tuning width increased with numerosity. The tuned responses to numerosity in the putamen extend its role in cognition and propose that the motor-sensory loops of the putamen and basal ganglia might take an active part in numerosity perception and preparation for future action.

Anticipatory human subthalamic area beta-band power responses to dissociable tastes correlate with weight gain

The availability of enticing sweet, fatty tastes is prevalent in the modern diet and contribute to overeating and obesity. In animal models, the subthalamic area plays a role in mediating appetitive and consummatory feeding behaviors, however, its role in human feeding is unknown. We used intraoperative, subthalamic field potential recordings while participants (n = 5) engaged in a task designed to provoke responses of taste anticipation and receipt. Decreased subthalamic beta-band (15-30 Hz) power responses were observed for both sweet-fat and neutral tastes. Anticipatory responses to taste-neutral cues started with an immediate decrease in beta-band power from baseline followed by an early beta-band rebound above baseline. On the contrary, anticipatory responses to sweet-fat were characterized by a greater and sustained decrease in beta-band power. These activity patterns were topographically specific to the subthalamic nucleus and substantia nigra. Further, a neural network trained on this beta-band power signal accurately predicted (AUC ≥ 74%) single trials corresponding to either taste. Finally, the magnitude of the beta-band rebound for a neutral taste was associated with increased body mass index after starting deep brain stimulation therapy. We provide preliminary evidence of discriminatory taste encoding within the subthalamic area associated with control mechanisms that mediate appetitive and consummatory behaviors.

Quantity and quality: Normative open-access neuroimaging databases

The focus of this article is to compare twenty normative and open-access neuroimaging databases based on quantitative measures of image quality, namely, signal-to-noise (SNR) and contrast-to-noise ratios (CNR). We further the analysis through discussing to what extent these databases can be used for the visualization of deeper regions of the brain, such as the subcortex, as well as provide an overview of the types of inferences that can be drawn. A quantitative comparison of contrasts including T1-weighted (T1w) and T2-weighted (T2w) images are summarized, providing evidence for the benefit of ultra-high field MRI. Our analysis suggests a decline in SNR in the caudate nuclei with increasing age, in T1w, T2w, qT1 and qT2* contrasts, potentially indicative of complex structural age-dependent changes. A similar decline was found in the corpus callosum of the T1w, qT1 and qT2* contrasts, though this relationship is not as extensive as within the caudate nuclei. These declines were accompanied by a declining CNR over age in all image contrasts. A positive correlation was found between scan time and the estimated SNR as well as a negative correlation between scan time and spatial resolution. Image quality as well as the number and types of contrasts acquired by these databases are important factors to take into account when selecting structural data for reuse. This article highlights the opportunities and pitfalls associated with sampling existing databases, and provides a quantitative backing for their usage.

A probabilistic atlas of the human ventral tegmental area (VTA) based on 7 Tesla MRI data

Functional magnetic resonance imaging (fMRI) BOLD signal is commonly localized by using neuroanatomical atlases, which can also serve for region of interest analyses. Yet, the available MRI atlases have serious limitations when it comes to imaging subcortical structures: only 7% of the 455 subcortical nuclei are captured by current atlases. This highlights the general difficulty in mapping smaller nuclei deep in the brain, which can be addressed using ultra-high field 7 Tesla (T) MRI. The ventral tegmental area (VTA) is a subcortical structure that plays a pivotal role in reward processing, learning and memory. Despite the significant interest in this nucleus in cognitive neuroscience, there are currently no available, anatomically precise VTA atlases derived from 7 T MRI data that cover the full region of the VTA. Here, we first provide a protocol for multimodal VTA imaging and delineation. We then provide a data description of a probabilistic VTA atlas based on in vivo 7 T MRI data.

Unexpected Sounds Nonselectively Inhibit Active Visual Stimulus Representations

The brain's capacity to process unexpected events is key to cognitive flexibility. The most well-known effect of unexpected events is the interruption of attentional engagement (distraction). We tested whether unexpected events interrupt attentional representations by activating a neural mechanism for inhibitory control. This mechanism is most well characterized within the motor system. However, recent work showed that it is automatically activated by unexpected events and can explain some of their nonmotor effects (e.g., on working memory representations). Here, human participants attended to lateralized flickering visual stimuli, producing steady-state visual evoked potentials (SSVEPs) in the scalp electroencephalogram. After unexpected sounds, the SSVEP was rapidly suppressed. Using a functional localizer (stop-signal) task and independent component analysis, we then identified a fronto-central EEG source whose activity indexes inhibitory motor control. Unexpected sounds in the SSVEP task also activated this source. Using single-trial analyses, we found that subcomponents of this source differentially relate to sound-induced SSVEP changes: While its N2 component predicted the subsequent suppression of the attended-stimulus SSVEP, the P3 component predicted the suppression of the SSVEP to the unattended stimulus. These results shed new light on the processes underlying fronto-central control signals and have implications for phenomena such as distraction and the attentional blink.

Imaging of the human subthalamic nucleus

The human subthalamic nucleus (STN) is a small lens shaped iron rich nucleus, which has gained substantial interest as a target for deep brain stimulation surgery for a variety of movement disorders. The internal anatomy of the human STN has not been fully elucidated, and an intensive debate, discussing the level of overlap between putative limbic, associative, and motor zones within the STN is still ongoing. In this chapter, we have summarized anatomical information obtained using different neuroimaging modalities focusing on the anatomy of the STN. Additionally, we have highlighted a number of major challenges faced when using magnetic resonance imaging (MRI) approaches for the visualization of small iron rich deep brain structures such as the STN. In vivo MRI and postmortem microscopy efforts provide valuable complementary information on the internal structure of the STN, although the results are not always fully aligned. Finally, we provide an outlook on future efforts that could contribute to the development of an integrative research approach that will help with the reconciliation of seemingly divergent results across research approaches.

Multi-contrast anatomical subcortical structures parcellation

The human subcortex is comprised of more than 450 individual nuclei which lie deep in the brain. Due to their small size and close proximity, up until now only 7% have been depicted in standard MRI atlases. Thus, the human subcortex can largely be considered as terra incognita. Here, we present a new open-source parcellation algorithm to automatically map the subcortex. The new algorithm has been tested on 17 prominent subcortical structures based on a large quantitative MRI dataset at 7 Tesla. It has been carefully validated against expert human raters and previous methods, and can easily be extended to other subcortical structures and applied to any quantitative MRI dataset. In sum, we hope this novel parcellation algorithm will facilitate functional and structural neuroimaging research into small subcortical nuclei and help to chart terra incognita.

Red nucleus structure and function: from anatomy to clinical neurosciences

The red nucleus (RN) is a large subcortical structure located in the ventral midbrain. Although it originated as a primitive relay between the cerebellum and the spinal cord, during its phylogenesis the RN shows a progressive segregation between a magnocellular part, involved in the rubrospinal system, and a parvocellular part, involved in the olivocerebellar system. Despite exhibiting distinct evolutionary trajectories, these two regions are strictly tied together and play a prominent role in motor and non-motor behavior in different animal species. However, little is known about their function in the human brain. This lack of knowledge may have been conditioned both by the notable differences between human and non-human RN and by inherent difficulties in studying this structure directly in the human brain, leading to a general decrease of interest in the last decades. In the present review, we identify the crucial issues in the current knowledge and summarize the results of several decades of research about the RN, ranging from animal models to human diseases. Connecting the dots between morphology, experimental physiology and neuroimaging, we try to draw a comprehensive overview on RN functional anatomy and bridge the gap between basic and translational research.

Topographic organization of the human subcortex unveiled with functional connectivity gradients

Brain atlases are fundamental to understanding the topographic organization of the human brain, yet many contemporary human atlases cover only the cerebral cortex, leaving the subcortex a terra incognita. We use functional MRI (fMRI) to map the complex topographic organization of the human subcortex, revealing large-scale connectivity gradients and new areal boundaries. We unveil four scales of subcortical organization that recapitulate well-known anatomical nuclei at the coarsest scale and delineate 27 new bilateral regions at the finest. Ultrahigh field strength fMRI corroborates and extends this organizational structure, enabling the delineation of finer subdivisions of the hippocampus and the amygdala, while task-evoked fMRI reveals a subtle subcortical reorganization in response to changing cognitive demands. A new subcortical atlas is delineated, personalized to represent individual differences and used to uncover reproducible brain-behavior relationships. Linking cortical networks to subcortical regions recapitulates a task-positive to task-negative axis. This new atlas enables holistic connectome mapping and characterization of cortico-subcortical connectivity.

Methodological Considerations for Neuroimaging in Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson's Disease Patients

Deep brain stimulation (DBS) of the subthalamic nucleus is a neurosurgical intervention for Parkinson's disease patients who no longer appropriately respond to drug treatments. A small fraction of patients will fail to respond to DBS, develop psychiatric and cognitive side-effects, or incur surgery-related complications such as infections and hemorrhagic events. In these cases, DBS may require recalibration, reimplantation, or removal. These negative responses to treatment can partly be attributed to suboptimal pre-operative planning procedures via direct targeting through low-field and low-resolution magnetic resonance imaging (MRI). One solution for increasing the success and efficacy of DBS is to optimize preoperative planning procedures via sophisticated neuroimaging techniques such as high-resolution MRI and higher field strengths to improve visualization of DBS targets and vasculature. We discuss targeting approaches, MRI acquisition, parameters, and post-acquisition analyses. Additionally, we highlight a number of approaches including the use of ultra-high field (UHF) MRI to overcome limitations of standard settings. There is a trade-off between spatial resolution, motion artifacts, and acquisition time, which could potentially be dissolved through the use of UHF-MRI. Image registration, correction, and post-processing techniques may require combined expertise of traditional radiologists, clinicians, and fundamental researchers. The optimization of pre-operative planning with MRI can therefore be best achieved through direct collaboration between researchers and clinicians.

Cross-Task Contributions of Frontobasal Ganglia Circuitry in Response Inhibition and Conflict-Induced Slowing

Why are we so slow in choosing the lesser of 2 evils? We considered whether such slowing relates to uncertainty about the value of these options, which arises from the tendency to avoid them during learning, and whether such slowing relates to frontosubthalamic inhibitory control mechanisms. In total, 49 participants performed a reinforcement-learning task and a stop-signal task while fMRI was recorded. A reinforcement-learning model was used to quantify learning strategies. Individual differences in lose-lose slowing related to information uncertainty due to sampling, and independently, to less efficient response inhibition in the stop-signal task. Neuroimaging analysis revealed an analogous dissociation: subthalamic nucleus (STN) BOLD activity related to variability in stopping latencies, whereas weaker frontosubthalamic connectivity related to slowing and information sampling. Across tasks, fast inhibitors increased STN activity for successfully canceled responses in the stop task, but decreased activity for lose-lose choices. These data support the notion that fronto-STN communication implements a rapid but transient brake on response execution, and that slowing due to decision uncertainty could result from an inefficient release of this "hold your horses" mechanism.

Hyperdirect insula-basal-ganglia pathway and adult-like maturity of global brain responses predict inhibitory control in children

Inhibitory control is fundamental to children's self-regulation and cognitive development. Here we investigate cortical-basal ganglia pathways underlying inhibitory control in children and their adult-like maturity. We first conduct a comprehensive meta-analysis of extant neurodevelopmental studies of inhibitory control and highlight important gaps in the literature. Second, we examine cortical-basal ganglia activation during inhibitory control in children ages 9-12 and demonstrate the formation of an adult-like inhibitory control network by late childhood. Third, we develop a neural maturation index (NMI), which assesses the similarity of brain activation patterns between children and adults, and demonstrate that higher NMI in children predicts better inhibitory control. Fourth, we show that activity in the subthalamic nucleus and its effective connectivity with the right anterior insula predicts children's inhibitory control. Fifth, we replicate our findings across multiple cohorts. Our findings provide insights into cortical-basal ganglia circuits and global brain organization underlying the development of inhibitory control.

Modulation of tonotopic ventral medial geniculate body is behaviorally relevant for speech recognition

Sensory thalami are central sensory pathway stations for information processing. Their role for human cognition and perception, however, remains unclear. Recent evidence suggests an involvement of the sensory thalami in speech recognition. In particular, the auditory thalamus (medial geniculate body, MGB) response is modulated by speech recognition tasks and the amount of this task-dependent modulation is associated with speech recognition abilities. Here, we tested the specific hypothesis that this behaviorally relevant modulation is present in the MGB subsection that corresponds to the primary auditory pathway (i.e., the ventral MGB [vMGB]). We used ultra-high field 7T fMRI to identify the vMGB, and found a significant positive correlation between the amount of task-dependent modulation and the speech recognition performance across participants within left vMGB, but not within the other MGB subsections. These results imply that modulation of thalamic driving input to the auditory cortex facilitates speech recognition.

Spatial Resolution and Imaging Encoding fMRI Settings for Optimal Cortical and Subcortical Motor Somatotopy in the Human Brain

There is much controversy about the optimal trade-off between blood-oxygen-level-dependent (BOLD) sensitivity and spatial precision in experiments on brain’s topology properties using functional magnetic resonance imaging (fMRI). The sparse empirical evidence and regional specificity of these interactions pose a practical burden for the choice of imaging protocol parameters. Here, we test in a motor somatotopy experiment the impact of fMRI spatial resolution on differentiation between body part representations in cortex and subcortical structures. Motor somatotopy patterns were obtained in a block-design paradigm and visually cued movements of face, upper and lower limbs at 1.5, 2, and 3 mm spatial resolution. The degree of segregation of the body parts’ spatial representations was estimated using a pattern component model. In cortical areas, we observed the same level of segregation between somatotopy maps across all three resolutions. In subcortical areas the degree of effective similarity between spatial representations was significantly impacted by the image resolution. The 1.5 mm 3D EPI and 3 mm 2D EPI protocols led to higher segregation between motor representations compared to the 2 mm 3D EPI protocol. This finding could not be attributed to differential BOLD sensitivity or delineation of functional areas alone and suggests a crucial role of the image encoding scheme – i.e., 2D vs. 3D EPI. Our study contributes to the field by providing empirical evidence about the impact of acquisition protocols for the delineation of somatotopic areas in cortical and sub-cortical brain regions.

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.

Subthalamic Nucleus Activation Occurs Early during Stopping and Is Associated with Trait Impulsivity

The subthalamic nucleus (STN) is thought to be a central regulator of behavioral inhibition, which is thought to be a major determinant of impulsivity. Thus, it would be reasonable to hypothesize that STN function is related to impulsivity. However, it has been difficult to test this hypothesis because of the challenges in noninvasively and accurately measuring this structure's signal in humans. We utilized a novel approach for STN signal localization that entails identifying this structure directly on fMRI images for each individual participant in native space. Using this approach, we measured STN responses during the stop signal task in a sample of healthy adult participants. We confirmed that the STN exhibited selective activation during "Stop" trials. Furthermore, the magnitude of STN activation during successful Stop trials inversely correlated with individual differences in trait impulsivity as measured by a personality inventory. Time course analysis revealed that early STN activation differentiated successful from unsuccessful Stop trials, and individual differences in the magnitude of STN activation inversely correlated with stop signal RT, an estimate of time required to stop. These results are consistent with the STN playing a central role in inhibition and related behavioral proclivities, with implications for both normal range function and clinical syndromes of inhibitory dyscontrol. Moreover, the methods utilized in this study for measuring STN fMRI signal in humans may be gainfully applied in future studies to further our understanding of the role of the STN in regulating behavior and neuropsychiatric conditions.

Large scale structure-function mappings of the human subcortex

Currently little is known about structure-function mappings in the human subcortex. Here we present a large-scale automated meta-analysis on the literature to understand the structure-function mapping in the human subcortex. The results provide converging evidence into unique large scale structure-function mappings of the human subcortex based on their functional and anatomical similarity.

The Connectivity Fingerprint of the Human Frontal Cortex, Subthalamic Nucleus, and Striatum

Within the cortico basal ganglia (BG)-thalamic network, the direct and indirect pathways comprise of projections from the cortex to the striatum (STR), whereas the hyperdirect pathway(s) consist of cortical projections toward the subthalamic nucleus (STN). Each pathway possesses a functionally distinct role for action selection. The current study quantified and compared the structural connectivity between 17 distinct cortical areas with the STN and STR using 7 Tesla diffusion weighted magnetic resonance imaging (dMRI) and resting-state functional MRI (rs-fMRI) in healthy young subjects. The selection of these cortical areas was based on a literature search focusing on animal tracer studies. The results indicate that, relative to other cortical areas, both the STN and STR showed markedly weaker structural connections to areas assumed to be essential for action inhibition such as the inferior frontal cortex pars opercularis. Additionally, the cortical connectivity fingerprint of the STN and STR indicated relatively strong connections to areas related to voluntary motor initiation such as the cingulate motor area and supplementary motor area. Overall the results indicated that the cortical-STN connections were sparser compared to the STR. There were two notable exceptions, namely for the orbitofrontal cortex and ventral medial prefrontal cortex, where a higher tract strength was found for the STN. These two areas are thought to be involved in reward processing and action bias.

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.