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The brain atlas is essential for exploring the anatomical structure and function of the brain. Non-human primates, such as cynomolgus macaque, have received increasing attention due to their genetic similarity to humans. However, current macaque brain atlases only offer coarse sections with intervals along the coronal direction, failing to meet the needs of single-cell resolution studies in functional and multi-omics research of the macaque brain. To address this issue, we utilized fluorescence micro-optical sectioning tomography to obtain sub-micron resolution cytoarchitectonic images of the macaque brain at the sagittal plane. Based on the obtained 8000 image sequences, a reference brain atlas comprising 45 sagittal sections was created, delineating 270 brain regions other than the cortex. Additionally, a website was established to share the reference atlas corresponding image data. This study is expected to provide an essential dataset and tool for scientists studying the macaque brain. [ABSTRACT FROM AUTHOR]

Striatal hyperdopaminergia is implicated in the pathoetiology of schizophrenia, but how this relates to dopaminergic midbrain activity is unclear. Neuromelanin (NM)-sensitive magnetic resonance imaging provides a marker of long-term dopamine function. We examined whether midbrain NM-sensitive magnetic resonance imaging contrast-to-noise ratio (NM-CNR) was higher in people with schizophrenia than in healthy control (HC) participants and whether this correlated with dopamine synthesis capacity. One hundred fifty-four participants (schizophrenia group: n = 74, HC group: n = 80) underwent NM-sensitive magnetic resonance imaging of the substantia nigra and ventral tegmental area (SN-VTA). A subset of the schizophrenia group (n = 38) also received [18F]-DOPA positron emission tomography to measure dopamine synthesis capacity (K i cer) in the SN-VTA and striatum. SN-VTA NM-CNR was significantly higher in patients with schizophrenia than in HC participants (effect size = 0.38, p =.019). This effect was greatest for voxels in the medial and ventral SN-VTA. In patients, SN-VTA K i cer positively correlated with SN-VTA NM-CNR (r = 0.44, p =.005) and striatal K i cer (r = 0.71, p <.001). Voxelwise analysis demonstrated that SN-VTA NM-CNR was positively associated with striatal K i cer (r = 0.53, p =.005) and that this relationship seemed strongest between the ventral SN-VTA and associative striatum in schizophrenia. Our results suggest that NM levels are higher in patients with schizophrenia than in HC individuals, particularly in midbrain regions that project to parts of the striatum that receive innervation from the limbic and association cortices. The direct relationship between measures of NM and dopamine synthesis suggests that these aspects of schizophrenia pathophysiology are linked. Our findings highlight specific mesostriatal circuits as the loci of dopamine dysfunction in schizophrenia and thus as potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Humans exhibit complex mathematical skills attributed to the exceptional enlargement of neocortical regions throughout evolution. In the current work, we initiated a novel exploration of the ancient subcortical neural network essential for mathematical cognition. Using a neuropsychological approach, we report that degeneration of two subcortical structures, the cerebellum and basal ganglia, impairs performance in symbolic arithmetic. We identify distinct computational impairments in male and female participants with cerebellar degeneration (CD) or Parkinson's disease (PD). The CD group exhibited a disproportionate cost when the arithmetic sum increased, suggesting that the cerebellum is critical for iterative procedures required for calculations. The PD group showed a disproportionate cost for equations with increasing addends, suggesting that the basal ganglia are critical for chaining multiple operations. In Experiment 2, the two patient groups exhibited intact practice gains for repeated equations at odds with an alternative hypothesis that these impairments were related to memory retrieval. Notably, we discuss how the counting and chaining operations relate to cerebellar and basal ganglia function in other task domains (e.g., motor processes). Overall, we provide a novel perspective on how the cerebellum and basal ganglia contribute to symbolic arithmetic. Our studies demonstrate the constraints on the computational role of two subcortical regions in higher cognition. [ABSTRACT FROM AUTHOR]

Comorbidity has been frequently observed between generalized anxiety disorder (GAD) and major depressive disorder (MDD), however, common and distinguishable alterations in the topological organization of functional brain networks remain poorly understood. We sought to determine a robust and sensitive functional connectivity marker for diagnostic classification and symptom severity prediction. Multi-layered dynamic functional connectivity including whole brain, network-node and node-node layers via graph theory and gradient analyses were applied to functional MRI resting-state data obtained from 31 unmedicated GAD and 34 unmedicated MDD patients as well as 33 age and education matched healthy controls (HC). GAD and MDD symptoms were assessed using Penn State Worry Questionnaire and Beck Depression Inventory II, respectively. Three network measures including global properties (i.e., global efficiency, characteristic path length), regional nodal property (i.e., degree) and connectivity gradients were computed. Results showed that both patient groups exhibited abnormal dynamic cortico-subcortical topological organization compared to healthy controls, with MDD > GAD > HC in degree of randomization. Furthermore, our multi-layered dynamic functional connectivity network model reached 77% diagnostic accuracy between GAD and MDD and was highly predictive of symptom severity, respectively. Gradients of functional connectivity for superior frontal cortex-subcortical regions, middle temporal gyrus-subcortical regions and amygdala-cortical regions contributed more in this model compared to other gradients. We found shared and distinct cortico-subcortical connectivity features in dynamic functional brain networks between GAD and MDD, which together can promote the understanding of common and disorder-specific topological organization dysregulations and facilitate early neuroimaging-based diagnosis. • Both MDD and GAD showed abnormal multi-layered dynamic cortico-subcortical FC. • The degree of topological randomization demonstrated MDD > GAD > HC. • The SVM model with cortico-subcortical dFC metrics yielded the highest accuracy. • Abnormal dFC metrics significantly predicted the symptom severity of MDD and GAD. [ABSTRACT FROM AUTHOR]

A recent study by Peysakhovich and colleagues reveals how the superior colliculus (SC), a deep brain structure commonly associated with spatial orienting and motor control, causally contributes to the abstraction of visual categories. This highlights how subcortical areas with motor-control labels may have central roles in high-level visual cognition and opens avenues for investigation. [ABSTRACT FROM AUTHOR]

Researchers often attribute higher cognition to the enlargement of cortical regions throughout evolution, reflecting the belief that humans sit at the top of the cognitive pyramid. Implicitly, this approach assumes that the subcortex is of secondary importance for higher-order cognition. While it is now recognized that subcortical regions can be involved in various cognitive domains, it remains unclear how they contribute to computations essential for higher-level cognitive processes such as endogenous attention and numerical cognition. Herein, we identify three models of subcortical–cortical relations in these cognitive processes: (i) subcortical regions are not involved in higher cognition; (ii) subcortical computations support elemental forms of higher cognition mainly in species without a developed cortex; and (iii) higher cognition depends on a whole-brain dynamic network, requiring integrated cortical and subcortical computations. Based on evolutionary theories and recent data, we propose the SEED hypothesis: the Subcortex is Essential for the Early Development of higher cognition. According to the five principles of the SEED hypothesis, subcortical computations are essential for the emergence of cognitive abilities that enable organisms to adapt to an ever-changing environment. We examine the implications of the SEED hypothesis from a multidisciplinary perspective to understand how the subcortex contributes to various forms of higher cognition. [ABSTRACT FROM AUTHOR]

Background: There is emerging evidence that the neuroanatomy of autism forms a spectrum which extends into the general population. However, whilst several studies have identified cortical morphology correlates of autistic traits, it is not established whether morphological differences are present in the subcortical structures of the brain. Additionally, it is not clear to what extent previously reported structural associations may be confounded by co-occurring psychopathology. To address these questions, we utilised neuroimaging data from the Adolescent Brain Cognitive Development Study to assess whether a measure of autistic traits was associated with differences in child subcortical morphology, and if any observed differences persisted after adjustment for child internalising and externalising symptoms. Methods: Our analyses included data from 7005 children aged 9–10 years (female: 47.19%) participating in the Adolescent Brain Cognitive Development Study. Autistic traits were assessed using scores from the Social Responsiveness Scale (SRS). Volumes of subcortical regions of interest were derived from structural magnetic resonance imaging data. Results: Overall, we did not find strong evidence for an association of autistic traits with differences in subcortical morphology in this sample of school-aged children. Whilst lower absolute volumes of the nucleus accumbens and putamen were associated with higher scores of autistic traits, these differences did not persist once a global measure of brain size was accounted for. Limitations: It is important to note that autistic traits were assessed using the SRS, of which higher scores are associated with general behavioural problems, and therefore may not be wholly indicative of autism-specific symptoms. In addition, individuals with a moderate or severe autism diagnosis were excluded from the ABCD study, and thus, the average level of autistic traits will be lower than in the general population which may bias findings towards the null. Conclusions: These findings from our well-powered study suggest that other metrics of brain morphology, such as cortical morphology or shape-based phenotypes, may be stronger candidates to prioritise when attempting to identify robust neuromarkers of autistic traits. [ABSTRACT FROM AUTHOR]

A well‐documented amygdala‐dorsomedial prefrontal circuit is theorized to promote attention to threat ("threat vigilance"). Prior research has implicated a relationship between individual differences in trait anxiety/vigilance, engagement of this circuitry, and anxiogenic features of the environment (e.g., through threat‐of‐shock and movie‐watching). In the present study, we predicted that—for those scoring high in self‐reported anxiety and a behavioral measure of threat vigilance—this circuitry is chronically engaged, even in the absence of anxiogenic stimuli. Our analyses of resting‐state fMRI data (N = 639) did not, however, provide evidence for such a relationship. Nevertheless, in our planned exploratory analyses, we saw a relationship between threat vigilance behavior (but not self‐reported anxiety) and intrinsic amygdala‐periaqueductal gray connectivity. Here, we suggest this subcortical circuitry may be chronically engaged in hypervigilant individuals, but that amygdala‐prefrontal circuitry may only be engaged in response to anxiogenic stimuli. [ABSTRACT FROM AUTHOR]

The promotion of recovery in patients who have entered a disorder of consciousness (DOC; e.g., coma or vegetative states) following severe brain injury remains an enduring medical challenge despite an ever-growing scientific understanding of these conditions. Indeed, recent work has consistently implicated altered cortical modulation by deep brain structures (e.g., the thalamus and the basal ganglia) following brain damage in the arising of, and recovery from, DOCs. The (re)emergence of low-intensity focused ultrasound (LIFU) neuromodulation may provide a means to selectively modulate the activity of deep brain structures noninvasively for the study and treatment of DOCs. This technique is unique in its combination of relatively high spatial precision and noninvasive implementation. Given the consistent implication of the thalamus in DOCs and prior results inducing behavioral recovery through invasive thalamic stimulation, here we applied ultrasound to the central thalamus in 11 acute DOC patients, measured behavioral responsiveness before and after sonication, and applied functional MRI during sonication. With respect to behavioral responsiveness, we observed significant recovery in the week following thalamic LIFU compared with baseline. With respect to functional imaging, we found decreased BOLD signals in the frontal cortex and basal ganglia during LIFU compared with baseline. In addition, we also found a relationship between altered connectivity of the sonicated thalamus and the degree of recovery observed post-LIFU. [ABSTRACT FROM AUTHOR]

• Prenatal activity shapes the newborn's ability to perceive face and gaze signals. • Perception of face identity, expression and gaze is highly context specific. • Race and culture represent contexts involving experience and social categorization. • Processing of face and gaze occurs in interacting subcortical and cortical pathways. • Processing of face and gaze involves a bottom-up and top-down flow of information. This review summarizes human perception and processing of face and gaze signals. Face and gaze signals are important means of non-verbal social communication. The review highlights that: (1) some evidence is available suggesting that the perception and processing of facial information starts in the prenatal period; (2) the perception and processing of face identity, expression and gaze direction is highly context specific, the effect of race and culture being a case in point. Culture affects by means of experiential shaping and social categorization the way in which information on face and gaze is collected and perceived; (3) face and gaze processing occurs in the so-called 'social brain'. Accumulating evidence suggests that the processing of facial identity, facial emotional expression and gaze involves two parallel and interacting pathways: a fast and crude subcortical route and a slower cortical pathway. The flow of information is bi-directional and includes bottom-up and top-down processing. The cortical networks particularly include the fusiform gyrus, superior temporal sulcus (STS), intraparietal sulcus, temporoparietal junction and medial prefrontal cortex. [ABSTRACT FROM AUTHOR]

The growing interest in the human subcortex is accompanied by an increasing number of parcellation procedures to identify deep brain structures in magnetic resonance imaging (MRI) contrasts. Manual procedures continue to form the gold standard for parcellating brain structures and is used for the validation of automated approaches. Performing manual parcellations is a tedious process which requires a systematic and reproducible approach. For this purpose, we created a series of protocols for the anatomical delineation of 21 individual subcortical structures. The intelligibility of the protocols was assessed by calculating Dice similarity coefficients for ten healthy volunteers. In addition, dilated Dice coefficients showed that manual parcellations created using these protocols can provide high-quality training data for automated algorithms. Here, we share the protocols, together with three example MRI datasets and the created manual delineations. The protocols can be applied to create high-quality training data for automated parcellation procedures, as well as for further validation of existing procedures and are shared without restrictions with the research community. [ABSTRACT FROM AUTHOR]

Background: Arousal and awareness are two important components of consciousness states. Functional neuroimaging has furthered our understanding of cortical and thalamocortical mechanisms of awareness. Investigating the relationship between subcortical functional connectivity and arousal has been challenging owing to the relatively small size of brainstem structures and thalamic nuclei, and their depth in the brain.Methods: Resting state functional MRI scans of 72 healthy volunteers were acquired before, during, 1 h after, and 1 day after sevoflurane general anaesthesia. Functional connectivity of subcortical regions of interest vs whole brain and homotopic functional connectivity for assessment of left-right symmetry analyses of both cortical and subcortical regions of interest were performed. Both analyses used high resolution atlases generated from deep brain stimulation applications.Results: Functional connectivity in subcortical loci within the thalamus and of the ascending reticular activating system was sharply restricted under anaesthesia, featuring a general lateralisation of connectivity. Similarly, left-right homology was sharply reduced under anaesthesia. Subcortical bilateral functional connectivity was not fully restored after emergence from anaesthesia, although greater restoration was seen between ascending reticular activating system loci and specific thalamic nuclei thought to be involved in promoting and maintaining arousal. Functional connectivity was fully restored to baseline by the following day.Conclusions: Functional connectivity in the subcortex is sharply restricted and lateralised under general anaesthesia. This restriction may play a part in loss and return of consciousness.Clinical Trial Registration: NCT02275026. [ABSTRACT FROM AUTHOR]

An increasing number of studies have found that a few, specific subcortical regions are involved in creative visual divergent thinking. In addition, creative thinking is heavily reliant on the fronto-striatal dopaminergic pathways. This study aimed to explore whether spontaneous fluctuations in the subcortex, which contribute to our creative abilities, showed significant differences between individuals with different levels of creativity based on resting-state functional magnetic resonance imaging data. We calculated subcortical regions' seed-wise and dynamic functional connectivity (dFC), and then examined the differences between the high and low visual creativity groups. Furthermore, the topological properties of the subcortical network were measured, and their relationship with creative visual divergent thinking was calculated using brain–behavior correlation analyses. The results showed that functional connectivity (FC) between the putamen, pallidum, and thalamus indicated group differences within the subcortex. Whole-brain FC results showed group differences across subcortical (i.e., the thalamus and pallidum) and cerebral regions (i.e., the insula, middle frontal gyrus, and middle temporal gyrus). In addition, subcortical FC demonstrated a positive correlation with visual divergent thinking scores across the pallidum, putamen, and thalamus. Our findings provide novel insights into the relationship between visual divergent thinking and the activities of the subcortex. It is likely that not only fronto-striatal dopaminergic pathways, but also "motor" pathways, are involved in creative visual divergent thinking processing. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Characterizing changing brain structure in neurodegeneration is fundamental to understanding long-term effects of pathology and ultimately providing therapeutic targets. It is well established that Huntington's disease (HD) gene carriers undergo progressive brain changes during the course of disease, yet the long-term trajectory of cortical atrophy is not well defined. Given that genetic therapies currently tested in HD are primarily expected to target the cortex, understanding atrophy across this region is essential. Capitalizing on a unique longitudinal dataset with a minimum of 3 and maximum of 7 brain scans from 49 HD gene carriers and 49 age-matched control subjects, we implemented a novel dynamical systems approach to infer patterns of regional neurodegeneration over 10 years. We use Bayesian hierarchical modeling to map participant- and group-level trajectories of atrophy spatially and temporally, additionally relating atrophy to the genetic marker of HD (CAG-repeat length) and motor and cognitive symptoms. We show, for the first time, that neurodegenerative changes exhibit complex temporal dynamics with substantial regional variation around the point of clinical diagnosis. Although widespread group differences were seen across the cortex, the occipital and parietal regions undergo the greatest rate of cortical atrophy. We have established links between atrophy and genetic markers of HD while demonstrating that specific cortical changes predict decline in motor and cognitive performance. HD gene carriers display regional variability in the spatial pattern of cortical atrophy, which relates to genetic factors and motor and cognitive symptoms. Our findings indicate a complex pattern of neuronal loss, which enables greater characterization of HD progression. [ABSTRACT FROM AUTHOR]

Background: There is no established pathogenesis of hemiparkinsonism-hemiatrophy syndrome (HPHA), and the varied clinical presentations have been reported in several case studies. To the best of our knowledge, the present report describes the first case of HPHA with unusual brain imaging findings.Case Presentation: A 20-year-old man presented with a 6-month history of weakness and clumsiness in his right limbs. He showed right-sided parkinsonism with dystonic hand posture; however, body asymmetry was not noted. Brain imaging revealed hemiatrophy of the left hemisphere subcortical structures and brainstem, and iron deposition in the left globus pallidus and substantia nigra. In addition, dopamine transporter imaging demonstrated normal presynaptic dopaminergic function. The patient was treated with levodopa, which had little to no effect.Conclusions: This case demonstrates the unique imaging characteristics of HPHA associated with widespread brain hemiatrophy and iron deposition. Further studies are needed to elucidate the diagnostic criteria for this heterogeneous syndrome. [ABSTRACT FROM AUTHOR]

Background: The pathology of Parkinson's disease leads to morphological changes in brain structure. Currently, the progressive changes in gray matter volume that occur with time and are specific to patients with Parkinson's disease, compared to healthy controls, remain unclear. High-tesla magnetic resonance imaging might be useful in differentiating neurological disorders by brain cortical changes. Purpose: We aimed to investigate patterns in gray matter changes in patients with Parkinson's disease by using an automated segmentation method with 7-tesla magnetic resonance imaging. Material and Methods: High-resolution T1-weighted 7 tesla magnetic resonance imaging volumes of 24 hemispheres were acquired from 12 Parkinson's disease patients and 12 age- and sex-matched healthy controls with median ages of 64.5 (range, 41–82) years and 60.5 (range, 25–74) years, respectively. Subgroup analysis was performed according to whether axial motor symptoms were present in the Parkinson's disease patients. Cortical volume, cortical thickness, and subcortical volume were measured using a high-resolution image processing technique based on the Desikan-Killiany-Tourville atlas and an automated segmentation method (FreeSurfer version 6.0). Results: After cortical reconstruction, in 7 tesla magnetic resonance imaging volume segmental analysis, compared with the healthy controls, the Parkinson's disease patients showed global cortical atrophy, mostly in the prefrontal area (rostral middle frontal, superior frontal, inferior parietal lobule, medial orbitofrontal, rostral anterior cingulate area), and subcortical volume atrophy in limbic/paralimbic areas (fusiform, hippocampus, amygdala). Conclusion: We first demonstrated that 7 tesla magnetic resonance imaging detects structural abnormalities in Parkinson's disease patients compared to healthy controls using an automated segmentation method. Compared with the healthy controls, the Parkinson's disease patients showed global prefrontal cortical atrophy and hippocampal area atrophy. [ABSTRACT FROM AUTHOR]

Understanding the similarity of cortico-subcortical networks topologies between humans and nonhuman primate species is critical to study the origin of network alternations underlying human neurologic and neuropsychiatric diseases. The New World common marmoset (Callithrix jacchus) has become popular as a nonhuman primate model for human brain function. Most marmoset connectomic research, however, has exclusively focused on cortical areas, with connectivity to subcortical networks less extensively explored. Here, we aimed to first isolate patterns of subcortical connectivity with cortical resting-state networks in awake marmosets using resting-state fMRI, then to compare these networks with those in humans using connectivity fingerprinting. In this study, we used 5 marmosets (4 males, 1 female). While we could match several marmoset and human resting-state networks based on their functional fingerprints, we also found a few striking differences, for example, strong functional connectivity of the default mode network with the superior colliculus in marmosets that was much weaker in humans. Together, these findings demonstrate that many of the core cortico-subcortical networks in humans are also present in marmosets, but that small, potentially functionally relevant differences exist. [ABSTRACT FROM AUTHOR]

Fast saccades are rapid automatic oculomotor responses to salient and ecologically important visual stimuli such as animals and faces. Discriminating the number of friends, foe, or prey may also have an evolutionary advantage. In this study, participants were asked to saccade rapidly towards the more numerous of two arrays. Participants could discriminate numerosities with high accuracy and great speed, as fast as 190 ms. Intermediate numerosities were more likely to elicit fast saccades than very low or very high numerosities. Reaction-times for vocal responses (collected in a separate experiment) were slower, did not depend on numerical range, and correlated only with the slow not the fast saccades, pointing to different systems. The short saccadic reaction-times we observe are surprising given that discrimination using numerosity estimation is thought to require a relatively complex neural circuit, with several relays of information through the parietal and prefrontal cortex. Our results suggest that fast numerosity-driven saccades may be generated on a single feed-forward pass of information recruiting a primitive system that cuts through the cortical hierarchy and rapidly transforms the numerosity information into a saccade command. [ABSTRACT FROM AUTHOR]

Most of the studies employing neuroimaging have focused on cortical and subcortical signals individually to obtain neurophysiological signatures of cognitive functions. However, understanding the dynamic communication between the cortex and subcortical structures is essential for unraveling the neural correlates of cognition. In this quest, magnetoencephalography (MEG) and electroencephalography (EEG) are the methods of choice because they are noninvasive electrophysiological recording techniques with high temporal resolution. Sophisticated MEG/EEG source estimation techniques and network analysis methods, developed recently, can provide a more comprehensive understanding of the neurophysiological mechanisms of fundamental cognitive processes. Used together with noninvasive modulation of cortical–subcortical communication, these approaches may open up new possibilities for expanding the repertoire of noninvasive cognitive neurotechnology. Advances in neuroimaging methods, combined with new brain magnetic sensors and neuromodulatory technology, open important new avenues for future research. Recent studies in brain electrophysiological imaging offer compelling evidence that, under favorable circumstances, localizing brain signals is possible, even from deep brain structures. Methodological and technological developments have opened new possibilities for comprehensive investigation of cortical–subcortical temporal dynamics. A cortical–subcortical integrative approach is essential for understanding human cognition and the mind–brain relationship. [ABSTRACT FROM AUTHOR]

Multimodal evidence suggests that brain regions accumulate information over timescales that vary according to anatomical hierarchy. Thus, these experimentally defined “temporal receptive windows” are longest in cortical regions that are distant from sensory input. Interestingly, spontaneous activity in these regions also plays out over relatively slow timescales (i.e., exhibits slower temporal autocorrelation decay). These findings raise the possibility that hierarchical timescales represent an intrinsic organizing principle of brain function. Here, using resting-state functional MRI, we show that the timescale of ongoing dynamics follows hierarchical spatial gradients throughout human cerebral cortex. These intrinsic timescale gradients give rise to systematic frequency differences among large-scale cortical networks and predict individual-specific features of functional connectivity. Whole-brain coverage permitted us to further investigate the large-scale organization of subcortical dynamics. We show that cortical timescale gradients are topographically mirrored in striatum, thalamus, and cerebellum. Finally, timescales in the hippocampus followed a posterior-to-anterior gradient, corresponding to the longitudinal axis of increasing representational scale. Thus, hierarchical dynamics emerge as a global organizing principle of mammalian brains. [ABSTRACT FROM AUTHOR]

Fast saccades are rapid automatic oculomotor responses to salient and ecologically important visual stimuli such as animals and faces. Discriminating the number of friends, foe, or prey may also have an evolutionary advantage. In this study, participants were asked to saccade rapidly towards the more numerous of two arrays. Participants could discriminate numerosities with high accuracy and great speed, as fast as 190 ms. Intermediate numerosities were more likely to elicit fast saccades than very low or very high numerosities. Reaction-times for vocal responses (collected in a separate experiment) were slower, did not depend on numerical range, and correlated only with the slow not the fast saccades, pointing to different systems. The short saccadic reaction-times we observe are surprising given that discrimination using numerosity estimation is thought to require a relatively complex neural circuit, with several relays of information through the parietal and prefrontal cortex. Our results suggest that fast numerosity-driven saccades may be generated on a single feed-forward pass of information recruiting a primitive system that cuts through the cortical hierarchy and rapidly transforms the numerosity information into a saccade command. [ABSTRACT FROM AUTHOR]

• Precise statistical control for subcortical effects on cortical connectivity. • Removal of subcortex significantly changes cortical network architecture. • Cortical topology becomes less segregated and more integrated overall. • Topography of change mirrors hierarchical organization of cortex. • Accounting for subcortical effects reduces integrity of the limbic system. fMRI of the human brain reveals spatiotemporal patterns of functional connectivity (FC), forming distinct cortical networks. Lately, subcortical contributions to these configurations are receiving renewed interest, but investigations rarely focus explicitly on their effects on cortico-cortical FC. Here, we employ a straightforward multivariable approach and graph-theoretic tools to assess subcortical impact on topological features of cortical networks. Given recent evidence showing that structures like the thalamus and basal ganglia integrate input from multiple networks, we expect increased segregation between cortical networks after removal of subcortical effects on their FC patterns. We analyze resting state data of young and healthy participants (male and female; N = 100) from the human connectome project. We find that overall, the cortical network architecture becomes less segregated, and more integrated, when subcortical influences are accounted for. Underlying these global effects are the following trends: 'Transmodal' systems become more integrated with the rest of the network, while 'unimodal' networks show the opposite effect. For single nodes this hierarchical organization is reflected by a close correspondence with the spatial layout of the principal gradient of FC (Margulies et al., 2016). Lastly, we show that the limbic system is significantly less coherent with subcortical influences removed. The findings are validated in a (split-sample) replication dataset. Our results provide new insight regarding the interplay between subcortex and cortical networks, by putting the integrative impact of subcortex in the context of macroscale patterns of cortical organization. [ABSTRACT FROM AUTHOR]

Functional neuroimaging studies have led to understanding the brain as a collection of spatially segregated functional networks. It is thought that each of these networks is in turn composed of a set of distinct sub-regions that together support each network's function. Considering the sub-regions to be an essential part of the brain's functional architecture, several strategies have been put forward that aim at identifying the functional sub-units of the brain by means of functional parcellations. Current parcellation strategies typically employ a bottom-up strategy, creating a parcellation by clustering smaller units. We propose a novel top-down parcellation strategy, using time courses of instantaneous connectivity to subdivide an initial region of interest into sub-regions. We use split-half reproducibility to choose the optimal number of sub-regions. We apply our Instantaneous Connectivity Parcellation (ICP) strategy on high-quality resting-state FMRI data, and demonstrate the ability to generate parcellations for thalamus, entorhinal cortex, motor cortex, and subcortex including brainstem and striatum. We evaluate the subdivisions against available cytoarchitecture maps to show that our parcellation strategy recovers biologically valid subdivisions that adhere to known cytoarchitectural features. [ABSTRACT FROM AUTHOR]

Huntington's disease is an inherited, degenerative brain disease, characterized by involuntary movements, cognitive disorder and neuropsychiatric change. Men and women are affected equally. Symptoms emerge at around 40 years, although there is wide variation. A rare juvenile form has onset in childhood or adolescence. The evolution of disease is insidious and structural and functional brain changes may be present more than a decade before symptoms and signs become manifest. The earliest site of pathology is the striatum and neuroimaging measures of striatal change correlate with neurological and cognitive markers of disease. Chorea and other aspects of the movement disorder are the most visible aspect of the disease. However, non-motor features have greatest affect on functional independence and quality of life, so require recognition and management. The evidence-base for non-pharmacological treatments in Huntington's disease is currently limited, but recent intervention studies are encouraging. [ABSTRACT FROM AUTHOR]

The aging brain undergoes several anatomical changes that can be measured with Magnetic Resonance Imaging (MRI). Early studies using lower field strengths have assessed changes in tissue properties mainly qualitatively, using $$T_{1}$$ - or $$T_{2}^{*}$$ - weighted images to provide image contrast. With the development of higher field strengths (7 T and above) and more advanced MRI contrasts, quantitative measures can be acquired even of small subcortical structures. This study investigates volumetric, spatial, and quantitative MRI parameter changes associated with healthy aging in a range of subcortical nuclei, including the basal ganglia, red nucleus, and the periaqueductal grey. The results show that aging has a heterogenous effects across regions. Across the subcortical areas an increase of $$T_{1}$$ values is observed, most likely indicating a loss of myelin. Only for a number of areas, a decrease of $$T_{2}^{*}$$ and increase of QSM is found, indicating an increase of iron. Aging also results in a location shift for a number of structures indicating the need for visualization of the anatomy of individual brains. [ABSTRACT FROM AUTHOR]

Certain numerical abilities appear to be relatively ubiquitous in the animal kingdom, including the ability to recognize and differentiate relative quantities. This skill is present in human adults and children, as well as in nonhuman primates and, perhaps surprisingly, is also demonstrated by lower species such as mosquitofish and spiders, despite the absence of cortical computation available to primates. This ubiquity of numerical competence suggests that representations that connect to numerical tasks are likely subserved by evolutionarily conserved regions of the nervous system. Here, we test the hypothesis that the evaluation of relative numerical quantities is subserved by lower-order brain structures in humans. Using a monocular/dichoptic paradigm, across four experiments, we show that the discrimination of displays, consisting of both large (5-80) and small (1-4) numbers of dots, is facilitated in the monocular, subcortical portions of the visual system. This is only the case, however, when observers evaluate larger ratios of 3:1 or 4:1, but not smaller ratios, closer to 1:1. This profile of competence matches closely the skill with which newborn infants and other species can discriminate numerical quantity. These findings suggest conservation of ontogenetically and phylogenetically lower-order systems in adults' numerical abilities. The involvement of subcortical structures in representing numerical quantities provokes a reconsideration of current theories of the neural basis of numerical cognition, inasmuch as it bolsters the cross-species continuity of the biological system for numerical abilities. [ABSTRACT FROM AUTHOR]

Modern systems neuroscience increasingly leans on large-scale multi-lab neuroinformatics initiatives to provide necessary capacity for biologically realistic modeling of primate whole-brain activity. Here, we present a framework to assemble primate brain's biologically plausible anatomical backbone for such modeling initiatives. In this framework, structural connectivity is determined by adding complementary information from invasive macaque axonal tract tracing and non-invasive human diffusion tensor imaging. Both modalities are combined by means of available interspecies registration tools and a newly developed Bayesian probabilistic modeling approach to extract common connectivity evidence. We demonstrate how this novel framework is embedded in the whole-brain simulation platform called The Virtual Brain (TVB). Hum Brain Mapp 38:2080-2093, 2017. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Structural neuroimaging of humans with typical and atypical sex-chromosome complements has established the marked influence of both Yand X-/Y-chromosome dosage on total brain volume (TBV) and identified potential cortical substrates for the psychiatric phenotypes associated with sex-chromosome aneuploidy (SCA). Here, in a cohort of 354 humans with varying karyotypes (XX, XY, XXX, XXY, XYY, XXYY, XXXXY), we investigate sex and SCA effects on subcortical size and shape; focusing on the striatum, pallidum and thalamus. We find large effect-size differences in the volume and shape of all three structures as a function of sex and SCA. We correct for TBV effects with a novel allometric method harnessing normative scaling rules for subcortical size and shape in humans, which we derive here for the first time. We show that all three subcortical volumes scale sublinearly with TBV among healthy humans, mirroring known relationships between subcortical volume and TBV among species. Traditional TBV correction methods assume linear scaling and can therefore invert or exaggerate sex and SCA effects on subcortical anatomy. Allometric analysis restricts sex-differences to: (1) greater pallidal volume (PV) in males, and (2) relative caudate head expansion and ventral striatum contraction in females. Allometric analysis of SCA reveals that supernumerary X- and Y-chromosomes both cause disproportionate reductions in PV, and coordinated deformations of striatopallidal shape. Our study provides a novel understanding of sex and sex-chromosome dosage effects on subcortical organization, using an allometric approach that can be generalized to other basic and clinical structural neuroimaging settings. [ABSTRACT FROM AUTHOR]

• The subcortical gray matter areas of macaque monkeys are reliably mapped by QSM, much as they are in humans. • Combining T1w and QSM images improves the visualization and segmentation of white matter, cortex, and subcortical structures in the macaque monkey. • The proposed dual contrast TQ-SILiCON provides a similar image quality also in humans. • TQ-SILiCON facilitates comparative and translational neuroscience studies investigating subcortical structures. Recent progress in quantitative susceptibility mapping (QSM) has enabled the accurate delineation of submillimeter-scale subcortical brain structures in humans. However, the simultaneous visualization of cortical, subcortical, and white matter structure remains challenging, utilizing QSM data solely. Here we present TQ-SILiCON, a fusion method that enhances the contrast of cortex and subcortical structures and provides an excellent white matter delineation by combining QSM and conventional T1-weighted (T1w) images. In this study, we first applied QSM in the macaque monkey to map iron-rich subcortical structures. Implementing the same QSM acquisition and analysis methods allowed a similar accurate delineation of subcortical structures in humans. However, the QSM contrast of white and cortical gray matter was not sufficient for appropriate segmentation. Applying automatic brain tissue segmentation to TQ-SILiCON images of the macaque improved the classification of subcortical brain structures as compared to the single T1 contrast by maintaining an excellent white to cortical gray matter contrast. Furthermore, we validated our dual-contrast fusion approach in humans and similarly demonstrated improvements in automated segmentation of the cortex and subcortical structures. We believe the proposed contrast will facilitate translational studies in nonhuman primates to investigate the pathophysiology of neurodegenerative diseases that affect subcortical structures such as the basal ganglia in humans. [Display omitted] [ABSTRACT FROM AUTHOR]

• Quantitative recurrent inference machine (qRIM) for accelerated R 2 * mapping. • Unified forward model for joint reconstruction and R2* mapping from sparse data. • Experiments at 7T with sub-millimeter resolution in a cohort study covering the entire adult life span. • An increasing reduction in the reconstruction error with increasing acceleration factor in subcortical regions. • Subcortical maturation over age preserved up to 9-fold acceleration. 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 R 2 * -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 R 2 * 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 R 2 * -maps. In contrast, when using the U-Net as network architecture, a negative bias in R 2 * in selected regions of interest was observed. Compressed Sensing rendered accurate, but less precise estimates of R 2 *. 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 R 2 * 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. [ABSTRACT FROM AUTHOR]

• A vast literature of subcortical studies is analysed from multiple axes: imaging protocols; regions of interest; methodology. • High-resolution atlases together with machine learning present a great opportunity for subcortical exploration with application to many clinical and research areas. • Detailed atlases target multiple typically ignored – small nuclei; machine learning is able to model the complex relationship between appearance and anatomy with fast inference. • Computational requirements, robustness and validation are associated challenges that we need to address for a widespread use of machine-learning in subcortical segmentation. This paper reviews almost three decades of work on atlasing and segmentation methods for subcortical structures in human brain MRI. In writing this survey, we have three distinct aims. First, to document the evolution of digital subcortical atlases of the human brain, from the early MRI templates published in the nineties, to the complex multi-modal atlases at the subregion level that are available today. Second, to provide a detailed record of related efforts in the automated segmentation front, from earlier atlas-based methods to modern machine learning approaches. And third, to present a perspective on the future of high-resolution atlasing and segmentation of subcortical structures in in vivo human brain MRI, including open challenges and opportunities created by recent developments in machine learning. [ABSTRACT FROM AUTHOR]

Background: Autism spectrum disorder (ASD) is characterized by atypical development of cortical and subcortical gray matter volume. Subcortical structural changes have been associated with restricted and repetitive behavior (RRB), a core component of ASD. Behavioral studies have identified insistence on sameness (IS) as a separable RRB dimension prominent in high-functioning ASD, though no simple brain-behavior relationship has emerged. Structural covariance, a measure of morphological coupling among brain regions using magnetic resonance imaging (MRI), has proven an informative measure of anatomical relationships in typical development and neurodevelopmental disorders. In this study, we use this measure to characterize the relationship between brain structure and IS. Methods: We quantified the structural covariance of cortical and subcortical gray matter volume in 55 individuals with high-functioning ASD using 3T MRI. We then related these structural metrics to individual IS scores, as assessed by the Repetitive Behavior Scale-Revised (RBS-R). Results: We found that increased coupling among subcortical regions and between subcortical and cortical regions related to greater IS symptom severity. Most pronounced, the striatum and amygdala participated in a plurality of identified relationships, indicating a central role for these structures in IS symptomatology. These structural associations were specific to IS and did not relate to any of the other RRB subcomponents measured by the RBS-R. Conclusions: This study indicates that behavioral dimensions in ASD can relate to the coordination of development across multiple brain regions, which might be otherwise obscured using typical brain-behavior correlations. It also expands the structures traditionally related to RRB in ASD and provides neuroanatomical evidence supportive of IS as a separate RRB dimension. [ABSTRACT FROM AUTHOR]

Background: Autism spectrum disorder (ASD) is characterized by atypical development of cortical and subcortical gray matter volume. Subcortical structural changes have been associated with restricted and repetitive behavior (RRB), a core component of ASD. Behavioral studies have identified insistence on sameness (IS) as a separable RRB dimension prominent in high-functioning ASD, though no simple brain-behavior relationship has emerged. Structural covariance, a measure of morphological coupling among brain regions using magnetic resonance imaging (MRI), has proven an informative measure of anatomical relationships in typical development and neurodevelopmental disorders. In this study, we use this measure to characterize the relationship between brain structure and IS. Methods: We quantified the structural covariance of cortical and subcortical gray matter volume in 55 individuals with high-functioning ASD using 3T MRI. We then related these structural metrics to individual IS scores, as assessed by the Repetitive Behavior Scale-Revised (RBS-R). Results: We found that increased coupling among subcortical regions and between subcortical and cortical regions related to greater IS symptom severity. Most pronounced, the striatum and amygdala participated in a plurality of identified relationships, indicating a central role for these structures in IS symptomatology. These structural associations were specific to IS and did not relate to any of the other RRB subcomponents measured by the RBS-R. Conclusions: This study indicates that behavioral dimensions in ASD can relate to the coordination of development across multiple brain regions, which might be otherwise obscured using typical brain-behavior correlations. It also expands the structures traditionally related to RRB in ASD and provides neuroanatomical evidence supportive of IS as a separate RRB dimension. [ABSTRACT FROM AUTHOR]

The pathological hallmark of Parkinson's disease is the degeneration of dopaminergic nigrostriatal neurons, leading to depletion of striatal dopamine. Recent neuroanatomical work has identified pathways for communication across striatal subdivisions, suggesting that the striatum provides a platform for integration of information across parallel corticostriatal circuits. The aim of this study was to investigate whether dopaminergic dysfunction in Parkinson's disease was associated with impairments in functional connectivity across striatal subdivisions, which could potentially reflect reduced integration across corticostriatal circuits. Utilizing resting-state functional magnetic resonance imaging (fMRI), we analyzed functional connectivity in 39 patients with Parkinson's disease, both 'on' and 'off' their regular dopaminergic medications, along with 40 age-matched healthy controls. Our results demonstrate widespread impairments in connectivity across subdivisions of the striatum in patients with Parkinson's disease in the 'off' state. The administration of dopaminergic medication significantly improved connectivity across striatal subdivisions in Parkinson's disease, implicating dopaminergic deficits in the pathogenesis of impaired striatal interconnectivity. In addition, impaired striatal interconnectivity in the Parkinson's disease 'off' state was associated with pathological decoupling of the striatum from the thalamic and sensorimotor (SM) networks. Specifically, we found that although the strength of striatal interconnectivity was positively correlated with both (i) the strength of internal thalamic connectivity, and (ii) the strength of internal SM connectivity, in both healthy controls and the Parkinson's disease 'on' state, these relationships were absent in Parkinson's disease when in the 'off' state. Taken together our findings emphasize the central role of dopamine in integrated striatal function and the pathological consequences of striatal dopamine denervation in Parkinson's disease. Hum Brain Mapp 36:1278-1291, 2015. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Subcortical structures are a relative neurophysiological ' terra incognita ' owing to their location within the skull. While perioperative subcortical sensing has been performed for more than 20 years, the neurophysiology of the basal ganglia in the home setting has remained almost unexplored. However, with the recent advent of implantable pulse generators (IPG) that are able to record neural activity, the opportunity to chronically record local field potentials (LFPs) directly from electrodes implanted for deep brain stimulation opens up. This allows for a breakthrough of chronic subcortical sensing into fundamental research and clinical practice. In this review an extensive overview of the current state of subcortical sensing is provided. The widespread potential of chronic subcortical sensing for investigational and clinical use is discussed. Finally, status and future perspectives of the most promising application of chronic subcortical sensing — i.e. , adaptive deep brain stimulation (aDBS)— are discussed in the context of movement disorders. The development of aDBS based on both chronic subcortical and cortical sensing has the potential to dramatically change clinical practice and the life of patients with movement disorders. However, several barriers still stand in the way of clinical implementation. Advancements regarding IPG and lead technology, physiomarkers, and aDBS algorithms as well as harnessing artificial intelligence, multimodality and sensing in the naturalistic setting are needed to bring aDBS to clinical practice. [ABSTRACT FROM AUTHOR]

• Time-averaged small world measures in fMRI do not yield consistent results. • Entropy of small world dynamics is a robust predictor of levels of awareness. • Network dynamics have predictive power beyond functional connectivity dynamics. • Subcortical dynamics have more predictive power than cortical dynamics. • Participation coefficient dynamics are independently predictive in the cerebellum. Small world topologies are thought to provide a valuable insight into human brain organisation and consciousness. However, functional magnetic resonance imaging studies in consciousness have not yielded consistent results. Given the importance of dynamics for both consciousness and cognition, here we investigate how the diversity of small world dynamics (quantified by sample entropy; dSW-E 1 1 dSW-E= dynamic small world entropy) scales with decreasing levels of awareness (i.e., sedation and disorders of consciousness). Paying particular attention to result reproducibility, we show that dSW-E is a consistent predictor of levels of awareness even when controlling for the underlying functional connectivity dynamics. We find that dSW-E of subcortical, and cortical areas are predictive, with the former showing higher and more robust effect sizes across analyses. We find that the network dynamics of intermodular communication in the cerebellum also have unique predictive power for levels of awareness. Consequently, we propose that the dynamic reorganisation of the functional information architecture, in particular of the subcortex, is a characteristic that emerges with awareness and has explanatory power beyond that of the complexity of dynamic functional connectivity. [ABSTRACT FROM AUTHOR]

Abstract: Puberty is characterized by hormonal, physical and psychological transformation. The human brain undergoes significant changes between childhood and adulthood, but little is known about how puberty influences its structural development. Using a longitudinal sample of 711 magnetic resonance imaging scans from 275 individuals aged 7–20years, we examined how subcortical brain regions change in relation to puberty. Our regions of interest included the amygdala, hippocampus and corpus striatum including the nucleus accumbens (NA), caudate, putamen and globus pallidus (GP). Pubertal development was significantly related to structural volume in all six regions in both sexes. Pubertal development and age had both independent and interactive influences on volume for the amygdala, hippocampus and putamen in both sexes, and the caudate in females. There was an interactive puberty-by-age effect on volume for the NA and GP in both sexes, and the caudate in males. These findings suggest a significant role for puberty in structural brain development. [Copyright &y& Elsevier]

Subcortical contributions to core linguistic computations pertaining to syntax-semantics remain drastically under-studied. We critique the cortico-centric focus which has largely accompanied research into these higher-order linguistic functions and suggest that, while much remains unknown, there is nevertheless a rich body of research concerning the possible roles of subcortex in natural language. Although much current evidence emerges from distinct domains of cognitive neuroscience, in this review article we attempt to show that there is a clear place for subcortex in models of natural language syntax-semantics, including a role in binary set-formation, categorized object maintenance, lexico-semantic processing, conceptual-to-lexical transformations, morphosyntactic linearization, semantic feature-binding, and cross-cortical representational integration. In particular, we consult models of language processing relying on oscillatory brain dynamics in order to investigate both the apparent and possible functional roles of subcortex in language. • We review apparent and possible roles for subcortical structures in natural language syntax. • Core linguistic computations such as binary set-formation and categorized object maintenance are subserved by subcortex. • Cross-frequency oscillatory interactions are highlighted to ground formal properties of language within neural systems. [ABSTRACT FROM AUTHOR]

Both cortical and subcortical regions can be functionally organized into networks. Regions of the basal ganglia are extensively interconnected with the cortex via reciprocal connections that relay and modulate cortical function. Here we employ an edge-centric approach, which computes co-fluctuations among region pairs in a network to investigate the role and interaction of subcortical regions with cortical systems. By clustering edges into communities, we show that cortical systems and subcortical regions couple via multiple edge communities, with hippocampus and amygdala having a distinct pattern from striatum and thalamus. We show that the edge community structure of cortical networks is highly similar to one obtained from cortical nodes when the subcortex is present in the network. Additionally, we show that the edge community profile of both cortical and subcortical nodes can be estimates solely from cortico-subcortical interactions. Finally, we used a motif analysis focusing on edge community triads where a subcortical region coupled to two cortical regions and found that two community triads where one community couples the subcortex to the cortex were overrepresented. In summary, our results show organized coupling of the subcortex to the cortex that may play a role in cortical organization of primary sensorimotor/attention and heteromodal systems and puts forth the motif analysis of edge community triads as a promising method for investigation of communication patterns in networks. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: The present study compared the patterns of brain activation elicited by two-digit addition and subtraction problems. Thirty-two Chinese undergraduates of the same educational background and of similar age were asked to assess whether arithmetic operations were true or false during functional magnetic resonance imaging. Results showed that both complex addition and subtraction were supported by the broad neural system that involved regions within the inferior parietal lobule, the precuneus, and the inferior occipital gyrus, as well as some subcortical structures. Nevertheless, complex problems involving addition elicited more activation mainly in the bilateral medial frontal gyrus, whereas problems involving subtraction had more activation in the precentral gyrus and the thalamus in the right hemisphere, as well as the inferior parietal lobule in the left hemisphere. This pattern of dissociated activation suggests that partially separate neuronal networks might support these different operations. It also suggests that complex addition has a greater reliance on the fronto-parietal cortical circuit and subtraction on the parieto-subcortical circuit. [Copyright &y& Elsevier]

Abstract: Previous work has demonstrated less accurate alignment of cortical structures for patients with schizophrenia than for matched control subjects when using affine registration techniques. Such a mismatch presents a potential confound for functional neuroimaging studies conducting between-group comparisons. Critically, the same issues may be present for subcortical structures. However, to date no study has explicitly investigated alignment precision for major subcortical structures in patients with schizophrenia. Thus, to address this question we used methods previously validated for assessment of cortical alignment precision to examine alignment precision of subcortical structures. In contrasts to our results with cortex, we found that major subcortical structures (i.e. amygdala, caudate, hippocampus, pallidum, putamen and thalamus) showed similar alignment precision for schizophrenia (N =48) and control subjects (N =45) regardless of the template used (other individuals with schizophrenia or healthy controls). Taken together, the present results show that, unlike cortex, alignment for six major subcortical structures is not compromised in patients with schizophrenia and as such is unlikely to confound between-group functional neuroimaging investigations. [Copyright &y& Elsevier]

Abstract: Objective: To achieve a unified and plausible concept of the aetiology of psychosis. Background: From an evolutionary point of view, the capacity for language evolved relatively abruptly 150,000–200,000 years ago as a result of a saltational genetic change that allowed the two hemispheres to develop with a degree of independence. According to the predisposition to schizophrenia might be a component of Homo sapiens-specific variation associated with the capacity for language. suggested that schizophrenia is “the price that Homo sapiens pays for language”. Language impairment is one of the, core phenomenological characteristics of patients with schizophrenia (). These symptoms might be understood as a breakdown of bi-hemispheric coordination of language. After reviewing the literature and regarding our own data concerning subcortical ambiguity processing, we suggest that subcortical language processing might play a crucial role as a missing link between the evolution of language (genetics), hemispheric dysbalance and language disorder in schizophrenia. Concentrating on the long time underestimated subcortical role of high order language function might open new perspectives in understanding the aetiology of psychosis. Conclusion: From our point of view there might be at least two pathways useful in forming a neurolinguistic approach to understand language symptoms in schizophrenia: first, hemispheric imbalance might play a crucial role in the development of schizophrenia. The second pathway leads to a potentially disturbed interdependency between fronto-temporo-parietal and subcortical neural networks and their importance in the processing of high order linguistic functions (such as decoding ambiguities). [Copyright &y& Elsevier]

Abstract: Consistent with the hypothesis that the amygdala is central to fear activation, brain imaging studies show that fear stimuli activate the amygdala, even when conscious recognition is prevented by backward masking. The bulk of the data suggest that the amygdala can be activated from potentially accessible but unattended fear stimuli. Activation of the amygdala facilitates low level visual processing. Several lines of evidence suggest that activation of the amygdala is mediated by a subcortical pathway. Thus, according to data from patients with lesions in the primary visual cortex, the amygdala can be activated in the absence of cortical processing. There is considerable support for the hypothesis that visual stimuli can access the amygdala via a pathway that includes the superior colliculus and the pulvinar nucleus of the thalamus. These data are consistent with an evolutionary argument, focusing of the role of snakes as a predator on primates. [Copyright &y& Elsevier]

Abstract: Pulvinar activation has been observed while viewing fearful expressions, but the necessity of this activation to their recognition has not been previously assessed. We measured the processing of emotional facial expressions in a rare patient with complete unilateral loss of the pulvinar. With brief presentations, patient CJ was incapable of recognizing fearful expressions in his contralesional field. Three other patients, with damage limited to the anterior and to the lateral pulvinar, showed no deficits in recognition. In conjunction with anatomical studies of the monkey pulvinar, these results suggest that fear recognition is mediated by the human medial pulvinar. We outline the possible role of the pulvinar in fear recognition, considering both the pulvinar''s direct and indirect cortical connections with the amygdala, and we suggest that the integrative role of the pulvinar may be primary. Our results suggest that the cortex in isolation from the entire pulvinar is incapable of recognizing fearful expressions. [Copyright &y& Elsevier]

• We present the Subcortical Atlas of the Rhesus Macaque (SARM). • Digital maps at multiple spatial scales allow for flexible analysis and labeling. • The maps are based on 210 primary regions-of-interest (ROIs) and composites thereof. • SARM facilitates subcortical neuroimaging analysis and experimental planning. • SARM is in the NMT v2 template space and complements the CHARM atlas for the cortex. Digitized neuroanatomical atlases that can be overlaid onto functional data are crucial for localizing brain structures and analyzing functional networks identified by neuroimaging techniques. To aid in functional and structural data analysis, we have created a comprehensive parcellation of the rhesus macaque subcortex using a high-resolution ex vivo structural imaging scan. This anatomical scan and its parcellation were warped to the updated NIMH Macaque Template (NMT v2), an in vivo population template, where the parcellation was refined to produce the Subcortical Atlas of the Rhesus Macaque (SARM) with 210 primary regions-of-interest (ROIs). The subcortical parcellation and nomenclature reflect those of the 4th edition of the Rhesus Monkey Brain in Stereotaxic Coordinates (Paxinos et al., in preparation), rather than proposing yet another novel atlas. The primary ROIs are organized across six spatial hierarchical scales from small, fine-grained ROIs to broader composites of multiple ROIs, making the SARM suitable for analysis at different resolutions and allowing broader labeling of functional signals when more accurate localization is not possible. As an example application of this atlas, we have included a functional localizer for the dorsal lateral geniculate (DLG) nucleus in three macaques using a visual flickering checkerboard stimulus, identifying and quantifying significant fMRI activation in this atlas region. The SARM has been made openly available to the neuroimaging community and can easily be used with common MRI data processing software, such as AFNI, where the atlas has been embedded into the software alongside cortical macaque atlases. [ABSTRACT FROM AUTHOR]

• 7 Tesla submillimeter whole-brain dataset. • 105 intrinsically aligned quantitative contrasts from a single scan acquisition. • Probabilistic atlases of the basal ganglia based on >1000 manual delineations. • Data freely available for further analyses. Normative databases allow testing of novel hypotheses without the costly collection of magnetic resonance imaging (MRI) data. Here we present the A msterdam Ultra- h igh fi e ld a dult lifespan d atabase (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, R 1 -maps, R 2 *-maps, T 1 -maps, T 1 -weighted images, T 2 *-maps, and quantitative susceptibility mapping (QSM). Quantitative MRI maps, and derived probability maps of basal ganglia structures are freely available for further analyses. [ABSTRACT FROM AUTHOR]

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 ​T. • Single and multi echo EPI protocols were compared for studying subcortex and cortex. • Both protocols had high spatial resolution, short echo times and whole-brain coverage. • The results show marginal differences in BOLD-sensitivity across the brain. [ABSTRACT FROM AUTHOR]

The basal ganglia, thalamus, and cerebral cortex form an interconnected network implicated in many neurological and psychiatric illnesses. A better understanding of cortico-subcortical circuits in individuals will aid in development of personalized treatments. Using precision functional mapping—individual-specific analysis of highly sampled human participants—we investigated individual-specific functional connectivity between subcortical structures and cortical functional networks. This approach revealed distinct subcortical zones of network specificity and multi-network integration. Integration zones were systematic, with convergence of cingulo-opercular control and somatomotor networks in the ventral intermediate thalamus (motor integration zones), dorsal attention and visual networks in the pulvinar, and default mode and multiple control networks in the caudate nucleus. The motor integration zones were present in every individual and correspond to consistently successful sites of deep brain stimulation (DBS; essential tremor). Individually variable subcortical zones correspond to DBS sites with less consistent treatment effects, highlighting the importance of PFM for neurosurgery, neurology, and psychiatry. • Precision functional mapping identifies subcortical integration zones in individuals • Systematic connectivity reveals motor, cognitive, and visual attention integration zones • Subcortical functional organization has individually variable and conserved features • Integration zones map onto variably effective DBS sites, suggesting clinical utility Individual functional mapping of the human subcortex revealed network integration zones (motor, cognitive, visual attention) that were variable and consistent across people. These individualized maps of cortico-subcortical circuits may have immediate clinical translation for invasive personalized treatments (e.g., deep brain stimulation). [ABSTRACT FROM AUTHOR]