Microstructural organizational patterns in the human corticostriatal system

Functional network mirrored in the prefrontal cortex, caudate nucleus, and thalamus: high-resolution functional imaging and structural connectivity

Despite myriads of studies on a parallel organization of cortico-striatal-thalamo-cortical loops, direct evidence of this has been lacking for the healthy human brain. Here, we scrutinize the functional specificity of the cortico-subcortical loops depending on varying levels of cognitive hierarchy as well as their structural connectivity with high-resolution fMRI and diffusion-weighted MRI (dMRI) at 7 tesla. Three levels of cognitive hierarchy were implemented in two domains: second language and nonlanguage. In fMRI, for the higher level, activations were found in the ventroanterior portion of the prefrontal cortex (PFC), the head of the caudate nucleus (CN), and the ventral anterior nucleus (VA) in the thalamus. Conversely, for the lower level, activations were located in the posterior region of the PFC, the body of the CN, and the medial dorsal nucleus (MD) in the thalamus. This gradient pattern of activations was furthermore shown to be tenable by the parallel connectivity in dMRI tractography connecting the anterior regions of the PFC with the head of the CN and the VA in the thalamus, whereas the posterior activations of the PFC were linked to the body of the CN and the MD in the thalamus. This is the first human in vivo study combining fMRI and dMRI showing that the functional specificity is mirrored within the cortico-subcortical loop substantiated by parallel networks.

Basal ganglia and thalamic morphology in schizophrenia and bipolar disorder

In this study, we examined the morphology of the basal ganglia and thalamus in bipolar disorder (BP), schizophrenia-spectrum disorders (SCZ-S), and healthy controls (HC) with particular interest in differences related to the absence or presence of psychosis. Volumetric and shape analyses of the basal ganglia and thalamus were performed in 33 BP individuals [12 without history of psychotic features (NPBP) and 21 with history of psychotic features (PBP)], 32 SCZ-S individuals [28 with SCZ and 4 with schizoaffective disorder], and 27 HC using FreeSurfer-initiated large deformation diffeomorphic metric mapping. Significant volume differences were found in the caudate and globus pallidus, with volumes smallest in the NPBP group. Shape abnormalities showing inward deformation of superior regions of the caudate were observed in BP (and especially in NPBP) compared with HC. Shape differences were also found in the globus pallidus and putamen when comparing BP and SCZ-S groups. No significant differences were seen in the nucleus accumbens and thalamus. In summary, structural abnormalities in the caudate and globus pallidus are present in BP and SCZ-S. Differences were more apparent in the NPBP subgroup. The findings herein highlight the potential importance of separately examining BP subgroups in neuroimaging studies.

The organization and dynamics of corticostriatal pathways link the medial orbitofrontal cortex to future behavioral responses

Accurately making a decision in the face of incongruent options increases the efficiency of making similar congruency decisions in the future. Contextual factors like reward can modulate this adaptive process, suggesting that networks associated with monitoring previous success and failure outcomes might contribute to this form of behavioral updating. To evaluate this possibility, a group of healthy adults (n = 30) were tested with functional MRI (fMRI) while they performed a color-word Stroop task. In a conflict-related region of the medial orbitofrontal cortex (mOFC), stronger BOLD responses predicted faster response times (RTs) on the next trial. More importantly, the degree of behavioral adaptation of RTs was correlated with the magnitude of mOFC-RT associations on the previous trial, but only after accounting for network-level interactions with prefrontal and striatal regions. This suggests that congruency sequencing effects may rely on interactions between distributed corticostriatal circuits. This possibility was evaluated by measuring the convergence of white matter projections from frontal areas into the striatum with diffusion-weighted imaging. In these pathways, greater convergence of corticostriatal projections correlated with stronger functional mOFC-RT associations that, in turn, provided an indirect pathway linking anatomical structure to behavior. Thus distributed corticostriatal processing may mediate the orbitofrontal cortex's influence on behavioral updating, even in the absence of explicit rewards.

Advanced diffusion MRI fiber tracking in neurosurgical and neurodegenerative disorders and neuroanatomical studies: A review

Diffusion MRI enabled in vivo microstructural imaging of the fiber tracts in the brain resulting in its application in a wide range of settings, including in neurological and neurosurgical disorders. Conventional approaches such as diffusion tensor imaging (DTI) have been shown to have limited applications due to the crossing fiber problem and the susceptibility of their quantitative indices to partial volume effects. To overcome these limitations, the recent focus has shifted to the advanced acquisition methods and their related analytical approaches. Advanced white matter imaging techniques provide superior qualitative data in terms of demonstration of multiple crossing fibers in their spatial orientation in a three dimensional manner in the brain. In this review paper, we discuss the advancements in diffusion MRI and introduce their roles. Using examples, we demonstrate the role of advanced diffusion MRI-based fiber tracking in neuroanatomical studies. Results from its preliminary application in the evaluation of intracranial space occupying lesions, including with respect to future directions for prognostication, are also presented. Building upon the previous DTI studies assessing white matter disease in Huntington's disease and Amyotrophic lateral sclerosis; we also discuss approaches which have led to encouraging preliminary results towards developing an imaging biomarker for these conditions.

Use of diffusion spectrum imaging in preliminary longitudinal evaluation of amyotrophic lateral sclerosis: development of an imaging biomarker

Previous diffusion tensor imaging (DTI) studies have shown white matter pathology in amyotrophic lateral sclerosis (ALS), predominantly in the motor pathways. Further these studies have shown that DTI can be used longitudinally to track pathology over time, making white matter pathology a candidate as an outcome measure in future trials. DTI has demonstrated application in group studies, however its derived indices, for example fractional anisotropy, are susceptible to partial volume effects, making its role questionable in examining individual progression. We hypothesize that changes in the white matter are present in ALS beyond the motor tracts, and that the affected pathways and associated pattern of disease progression can be tracked longitudinally using automated diffusion connectometry analysis. Connectometry analysis is based on diffusion spectrum imaging and overcomes the limitations of a conventional tractography approach and DTI. The identified affected white matter tracts can then be assessed in a targeted fashion using High definition fiber tractography (a novel white matter MR imaging technique). Changes in quantitative and qualitative markers over time could then be correlated with clinical progression. We illustrate these principles toward developing an imaging biomarker for demonstrating individual progression, by presenting results for five ALS patients, including with longitudinal data in two. Preliminary analysis demonstrated a number of changes bilaterally and asymmetrically in motoric and extramotoric white matter pathways. Further the limbic system was also affected possibly explaining the cognitive symptoms in ALS. In the two longitudinal subjects, the white matter changes were less extensive at baseline, although there was evidence of disease progression in a frontal pattern with a relatively spared postcentral gyrus, consistent with the known pathology in ALS.

Mapping topographic structure in white matter pathways with level set trees

Fiber tractography on diffusion imaging data offers rich potential for describing white matter pathways in the human brain, but characterizing the spatial organization in these large and complex data sets remains a challenge. We show that level set trees--which provide a concise representation of the hierarchical mode structure of probability density functions--offer a statistically-principled framework for visualizing and analyzing topography in fiber streamlines. Using diffusion spectrum imaging data collected on neurologically healthy controls (N = 30), we mapped white matter pathways from the cortex into the striatum using a deterministic tractography algorithm that estimates fiber bundles as dimensionless streamlines. Level set trees were used for interactive exploration of patterns in the endpoint distributions of the mapped fiber pathways and an efficient segmentation of the pathways that had empirical accuracy comparable to standard nonparametric clustering techniques. We show that level set trees can also be generalized to model pseudo-density functions in order to analyze a broader array of data types, including entire fiber streamlines. Finally, resampling methods show the reliability of the level set tree as a descriptive measure of topographic structure, illustrating its potential as a statistical descriptor in brain imaging analysis. These results highlight the broad applicability of level set trees for visualizing and analyzing high-dimensional data like fiber tractography output.

Corticostriatal output gating during selection from working memory

Convergent evidence suggests that corticostriatal interactions act as a gate to select the input to working memory (WM). However, not all information in WM is relevant for behavior simultaneously. For this reason, a second "output gate" might advantageously govern which contents of WM influence behavior. Here, we test whether frontostriatal circuits previously implicated in input gating also support output gating during selection from WM. fMRI of a hierarchical rule task with dissociable input and output gating demands demonstrated greater lateral prefrontal cortex (PFC) recruitment and frontostriatal connectivity during output gating. Moreover, PFC and striatum correlated with distinct behavioral profiles. Whereas PFC recruitment correlated with mean efficiency of selection from WM, striatal recruitment and frontostriatal interactions correlated with its reliability, as though such dynamics stochastically gate WM's output. These results support the output gating hypothesis, suggesting that contextual representations in PFC influence striatum to select which information in WM drives responding.

The visual corticostriatal loop through the tail of the caudate: circuitry and function

Although high level visual cortex projects to a specific region of the striatum, the tail of the caudate, and participates in corticostriatal loops, the function of this visual corticostriatal system is not well understood. This article first reviews what is known about the anatomy of the visual corticostriatal loop across mammals, including rodents, cats, monkeys, and humans. Like other corticostriatal systems, the visual corticostriatal system includes both closed loop components (recurrent projections that return to the originating cortical location) and open loop components (projections that terminate in other neural regions). The article then reviews what previous empirical research has shown about the function of the tail of the caudate. The article finally addresses the possible functions of the closed and open loop connections of the visual loop in the context of theories and computational models of corticostriatal function.

Indirection and symbol-like processing in the prefrontal cortex and basal ganglia

The ability to flexibly, rapidly, and accurately perform novel tasks is a hallmark of human behavior. In our everyday lives we are often faced with arbitrary instructions that we must understand and follow, and we are able to do so with remarkable ease. It has frequently been argued that this ability relies on symbol processing, which depends critically on the ability to represent variables and bind them to arbitrary values. Whereas symbol processing is a fundamental feature of all computer systems, it remains a mystery whether and how this ability is carried out by the brain. Here, we provide an example of how the structure and functioning of the prefrontal cortex/basal ganglia working memory system can support variable binding, through a form of indirection (akin to a pointer in computer science). We show how indirection enables the system to flexibly generalize its behavior substantially beyond its direct experience (i.e., systematicity). We argue that this provides a biologically plausible mechanism that approximates a key component of symbol processing, exhibiting both the flexibility, but also some of the limitations, that are associated with this ability in humans.

Functional and structural connectivity of frontostriatal circuitry in Autism Spectrum Disorder

Abnormalities in frontostriatal circuitry potentially underlie the two core deficits in Autism Spectrum Disorder (ASD); social interaction and communication difficulties and restricted interests and repetitive behaviors. Whilst a few studies have examined connectivity within this circuitry in ASD, no previous study has examined both functional and structural connectivity within the same population. The present study provides the first exploration of both functional and structural frontostriatal connectivity in ASD. Twenty-eight right-handed Caucasian male ASD (17.28 ± 3.57 years) and 27 right-handed male, age and IQ matched controls (17.15 ± 3.64 years) took part in the study. Resting state functional connectivity was carried out on 21 ASD and control participants, and tractography was carried out on 22 ASD and 24 control participants, after excluding subjects for excessive motion and poor data quality. Functional connectivity analysis was carried out between the frontal cortex and striatum after which tractography was performed between regions that showed significant group differences in functional connectivity. The ASD group showed increased functional connectivity between regions in the frontal cortex [anterior cingulate cortex (ACC), middle frontal gyrus (MFG), paracingulate gyrus (Pcg) and orbitofrontal cortex (OFC)], and striatum [nucleus accumbens (NAcc) and caudate]. Increased functional connectivity between ACC and caudate was associated with deactivation to social rewards in the caudate, as previously reported in the same participants. Greater connectivity between the right MFG and caudate was associated with higher restricted interests and repetitive behaviors and connectivity between the bilateral Pcg and NAcc, and the right OFC and NAcc, was negatively associated with social and communicative deficits. Although tracts were reliably constructed for each subject, there were no group differences in structural connectivity. Results are in keeping with previously reported increased corticostriatal functional connectivity in ASD.

Explicating the face perception network with white matter connectivity

A network of multiple brain regions is recruited in face perception. Our understanding of the functional properties of this network can be facilitated by explicating the structural white matter connections that exist between its functional nodes. We accomplished this using functional MRI (fMRI) in combination with fiber tractography on high angular resolution diffusion weighted imaging data. We identified the three nodes of the core face network: the "occipital face area" (OFA), the "fusiform face area" (mid-fusiform gyrus or mFus), and the superior temporal sulcus (STS). Additionally, a region of the anterior temporal lobe (aIT), implicated as being important for face perception was identified. Our data suggest that we can further divide the OFA into multiple anatomically distinct clusters - a partitioning consistent with several recent neuroimaging results. More generally, structural white matter connectivity within this network revealed: 1) Connectivity between aIT and mFus, and between aIT and occipital regions, consistent with studies implicating this posterior to anterior pathway as critical to normal face processing; 2) Strong connectivity between mFus and each of the occipital face-selective regions, suggesting that these three areas may subserve different functional roles; 3) Almost no connectivity between STS and mFus, or between STS and the other face-selective regions. Overall, our findings suggest a re-evaluation of the "core" face network with respect to what functional areas are or are not included in this network.

Corticostriatal connectivity and its role in disease

Corticostriatal projections are essential components of forebrain circuits and are widely involved in motivated behaviour. These axonal projections are formed by two distinct classes of cortical neurons, intratelencephalic (IT) and pyramidal tract (PT) neurons. Convergent evidence points to IT versus PT differentiation of the corticostriatal system at all levels of functional organization, from cellular signalling mechanisms to circuit topology. There is also growing evidence for IT/PT imbalance as an aetiological factor in neurodevelopmental, neuropsychiatric and movement disorders - autism, amyotrophic lateral sclerosis, obsessive-compulsive disorder, schizophrenia, Huntington's and Parkinson's diseases and major depression are highlighted here.

Mathematical logic in the human brain: semantics

As a higher cognitive function in humans, mathematics is supported by parietal and prefrontal brain regions. Here, we give an integrative account of the role of the different brain systems in processing the semantics of mathematical logic from the perspective of macroscopic polysynaptic networks. By comparing algebraic and arithmetic expressions of identical underlying structure, we show how the different subparts of a fronto-parietal network are modulated by the semantic domain, over which the mathematical formulae are interpreted. Within this network, the prefrontal cortex represents a system that hosts three major components, namely, control, arithmetic-logic, and short-term memory. This prefrontal system operates on data fed to it by two other systems: a premotor-parietal top-down system that updates and transforms (external) data into an internal format, and a hippocampal bottom-up system that either detects novel information or serves as an access device to memory for previously acquired knowledge.

Co-analysis of brain structure and function using fMRI and diffusion-weighted imaging

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when studying the brain, as the functional role that a brain area fulfills may be largely defined by its connections to other brain areas. In this report, we describe a novel, non-invasive approach for relating brain structure and function using magnetic resonance imaging (MRI). This approach, a combination of structural imaging of long-range fiber connections and functional imaging data, is illustrated in two distinct cognitive domains, visual attention and face perception. Structural imaging is performed with diffusion-weighted imaging (DWI) and fiber tractography, which track the diffusion of water molecules along white-matter fiber tracts in the brain (Figure 1). By visualizing these fiber tracts, we are able to investigate the long-range connective architecture of the brain. The results compare favorably with one of the most widely-used techniques in DWI, diffusion tensor imaging (DTI). DTI is unable to resolve complex configurations of fiber tracts, limiting its utility for constructing detailed, anatomically-informed models of brain function. In contrast, our analyses reproduce known neuroanatomy with precision and accuracy. This advantage is partly due to data acquisition procedures: while many DTI protocols measure diffusion in a small number of directions (e.g., 6 or 12), we employ a diffusion spectrum imaging (DSI)(1, 2) protocol which assesses diffusion in 257 directions and at a range of magnetic gradient strengths. Moreover, DSI data allow us to use more sophisticated methods for reconstructing acquired data. In two experiments (visual attention and face perception), tractography reveals that co-active areas of the human brain are anatomically connected, supporting extant hypotheses that they form functional networks. DWI allows us to create a "circuit diagram" and reproduce it on an individual-subject basis, for the purpose of monitoring task-relevant brain activity in networks of interest.

Finding parallels in fronto-striatal organization

Evidence suggests that lateral frontal cortex is hierarchically organized such that rostral frontal regions support more abstract representations than caudal regions. A recent fMRI study of language processing proposes that striatum may exhibit an analogous organization. We consider this hypothetical correspondence at both the cognitive and anatomical levels.

Hierarchical reinforcement learning and decision making

The hierarchical structure of human and animal behavior has been of critical interest in neuroscience for many years. Yet understanding the neural processes that give rise to such structure remains an open challenge. In recent research, a new perspective on hierarchical behavior has begun to take shape, inspired by ideas from machine learning, and in particular the framework of hierarchical reinforcement learning. Hierarchical reinforcement learning builds on traditional reinforcement learning mechanisms, extending them to accommodate temporally extended behaviors or subroutines. The resulting computational paradigm has begun to influence both theoretical and empirical work in neuroscience, conceptually aligning the study of hierarchical behavior with research on other aspects of learning and decision making, and giving rise to some thought-provoking new findings.