Subcortical Nuclei Research Articles

Characterization of the blood oxygen level dependent hemodynamic response function in human subcortical regions with high spatiotemporal resolution.

Subcortical brain regions are absolutely essential for normal human function. These phylogenetically early brain regions play critical roles in human behaviors such as the orientation of attention, arousal, and the modulation of sensory signals to cerebral cortex. Despite the critical health importance of subcortical brain regions, there has been a dearth of research on their neurovascular responses. Blood oxygen level dependent (BOLD) functional MRI (fMRI) experiments can help fill this gap in our understanding. The BOLD hemodynamic response function (HRF) evoked by brief (<4 s) neural activation is crucial for the interpretation of fMRI results because linear analysis between neural activity and the BOLD response relies on the HRF. Moreover, the HRF is a consequence of underlying local blood flow and oxygen metabolism, so characterization of the HRF enables understanding of neurovascular and neurometabolic coupling. We measured the subcortical HRF at 9.4T and 3T with high spatiotemporal resolution using protocols that enabled reliable delineation of HRFs in individual subjects. These results were compared with the HRF in visual cortex. The HRF was faster in subcortical regions than cortical regions at both field strengths. There was no significant undershoot in subcortical areas while there was a significant post-stimulus undershoot that was tightly coupled with its peak amplitude in cortex. The different BOLD temporal dynamics indicate different vascular dynamics and neurometabolic responses between cortex and subcortical nuclei.

Functional connectivity gradients of the insula to different cerebral systems.

The diverse functional roles of the insula may emerge from its heavy connectivity to an extensive network of cortical and subcortical areas. Despite several previous attempts to investigate the hierarchical organization of the insula by applying the recently developed gradient approach to insula-to-whole brain connectivity data, little is known about whether and how there is variability across connectivity gradients of the insula to different cerebral systems. Resting-state functional MRI data from 793 healthy subjects were used to discover and validate functional connectivity gradients of the insula, which were computed based on its voxel-wise functional connectivity profiles to distinct cerebral systems. We identified three primary patterns of functional connectivity gradients of the insula to distinct cerebral systems. The connectivity gradients to the higher-order transmodal associative systems, including the prefrontal, posterior parietal, temporal cortices, and limbic lobule, showed a ventroanterior-dorsal axis across the insula; those to the lower-order unimodal primary systems, including the motor, somatosensory, and occipital cortices, displayed radiating transitions from dorsoanterior toward both ventroanterior and dorsoposterior parts of the insula; the connectivity gradient to the subcortical nuclei exhibited an organization along the anterior-posterior axis of the insula. Apart from complementing and extending previous literature on the heterogeneous connectivity patterns of insula subregions, the presented framework may offer ample opportunities to refine our understanding of the role of the insula in many brain disorders.

Joint Progressive and Coarse-to-Fine Registration of Brain MRI via Deformation Field Integration and Non-Rigid Feature Fusion.

Registration of brain MRI images requires to solve a deformation field, which is extremely difficult in aligning intricate brain tissues, e.g., subcortical nuclei, etc. Existing efforts resort to decomposing the target deformation field into intermediate sub-fields with either tiny motions, i.e., progressive registration stage by stage, or lower resolutions, i.e., coarse-to-fine estimation of the full-size deformation field. In this paper, we argue that those efforts are not mutually exclusive, and propose a unified framework for robust brain MRI registration in both progressive and coarse-to-fine manners simultaneously. Specifically, building on a dual-encoder U-Net, the fixed-moving MRI pair is encoded and decoded into multi-scale sub-fields from coarse to fine. Each decoding block contains two proposed novel modules: i) in Deformation Field Integration (DFI), a single integrated deformation sub-field is calculated, warping by which is equivalent to warping progressively by sub-fields from all previous decoding blocks, and ii) in Non-rigid Feature Fusion (NFF), features of the fixed-moving pair are aligned by DFI-integrated deformation field, and then fused to predict a finer sub-field. Leveraging both DFI and NFF, the target deformation field is factorized into multi-scale sub-fields, where the coarser fields alleviate the estimate of a finer one and the finer field learns to make up those misalignments insolvable by previous coarser ones. The extensive and comprehensive experimental results on both private and two public datasets demonstrate a superior registration performance of brain MRI images over progressive registration only and coarse-to-fine estimation only, with an increase by at most 8% in the average Dice.

The Tail of the Mouse Striatum Contains a Novel Large Type of GABAergic Neuron Incorporated in a Unique Disinhibitory Pathway That Relays Auditory Signals to Subcortical Nuclei.

The most caudal part of the striatum in rodents, the tail of the striatum (TS), has many features that distinguish it from the rostral striatum, such as its biased distributions of dopamine receptor subtypes, lack of striosomes and matrix compartmentalization, and involvement in sound-driven behaviors. However, information regarding the TS is still limited. We demonstrate in this article that the TS of the male mouse contains GABAergic neurons of a novel type that were detected immunohistochemically with the neurofilament marker SMI-32. Their somata were larger than cholinergic giant aspiny neurons, were located in a narrow space adjacent to the globus pallidus (GP), and extended long dendrites laterally toward the intermediate division (ID) of the trilaminar part of the TS, the region targeted by axons from the primary auditory cortex (A1). Although vesicular glutamate transporter 1-positive cortical axon terminals rarely contacted these TS large (TSL) neurons, glutamic acid decarboxylase-immunoreactive and enkephalin-immunoreactive boutons densely covered somata and dendrites of TSL neurons, forming symmetrical synapses. Analyses of GAD67-CrePR knock-in mice revealed that these axonal boutons originated from nearby medium spiny neurons (MSNs) in the ID. All MSNs examined in the ID in turn received inputs from the A1. Retrograde tracers injected into the rostral zona incerta and ventral medial nucleus of the thalamus labeled somata of TSL neurons. TSL neurons share many morphological features with GP neurons, but their strategically located dendrites receive inputs from closely located MSNs in the ID, suggesting faster responses than distant GP neurons to facilitate auditory-evoked, prompt disinhibition in their targets.SIGNIFICANCE STATEMENT This study describes a newly found population of neurons in the mouse striatum, the brain region responsible for appropriate behaviors. They are large GABAergic neurons located in the most caudal part of the striatum [tail of the striatum (TS)]. These TS large (TSL) neurons extended dendrites toward a particular region of the TS where axons from the primary auditory cortex (A1) terminated. These dendrites received direct synaptic inputs heavily from nearby GABAergic neurons of the striatum that in turn received inputs from the A1. TSL neurons sent axons to two subcortical regions outside basal ganglia, one of which is related to arousal. Specialized connectivity of TSL neurons suggests prompt disinhibitory actions on their targets to facilitate sound-evoked characteristic behaviors.

Subcortical-cortical dynamical states of the human brain and their breakdown in stroke

The mechanisms controlling dynamical patterns in spontaneous brain activity are poorly understood. Here, we provide evidence that cortical dynamics in the ultra-slow frequency range (<0.01–0.1 Hz) requires intact cortical-subcortical communication. Using functional magnetic resonance imaging (fMRI) at rest, we identify Dynamic Functional States (DFSs), transient but recurrent clusters of cortical and subcortical regions synchronizing at ultra-slow frequencies. We observe that shifts in cortical clusters are temporally coincident with shifts in subcortical clusters, with cortical regions flexibly synchronizing with either limbic regions (hippocampus/amygdala), or subcortical nuclei (thalamus/basal ganglia). Focal lesions induced by stroke, especially those damaging white matter connections between basal ganglia/thalamus and cortex, provoke anomalies in the fraction times, dwell times, and transitions between DFSs, causing a bias toward abnormal network integration. Dynamical anomalies observed 2 weeks after stroke recover in time and contribute to explaining neurological impairment and long-term outcome.

Quantitative susceptibility atlas construction in Montreal Neurological Institute space: towards histological-consistent iron-rich deep brain nucleus subregion identification.

Iron-rich deep brain nuclei (DBN) of the human brain are involved in various motoric, emotional and cognitive brain functions. The abnormal iron alterations in the DBN are closely associated with multiple neurological and psychiatric diseases. Quantitative susceptibility mapping (QSM) provides the spatial distribution of the magnetic susceptibility of human brain tissues. Compared to traditional structural imaging, QSM provides superiority for imaging the iron-rich DBN owing to the susceptibility difference existing between brain tissues. In this study, we constructed a Montreal Neurological Institute (MNI) space unbiased QSM human brain atlas via group-wise registration from 100 healthy subjects aged 19-29 years. The atlas construction process was guided by hybrid images that were fused from multi-modal magnetic resonance images (MRI). We named it as Multi-modal-fused magnetic Susceptibility (MuSus-100) atlas. The high-quality susceptibility atlas provides extraordinary image contrast between iron-rich DBN with their surroundings. Parcellation maps of DBN and their subregions that are highly related to neurological and psychiatric pathology were then manually labeled based on the atlas set with the assistance of an image border-enhancement process. Especially, the bilateral thalamus was delineated into 64 detailed subregions referring to the Schaltenbrand-Wahren stereotactic atlas. To our best knowledge, the histological-consistent thalamic nucleus parcellation map is well defined for the first time in the MNI space. Compared with existing atlases that emphasizing DBN parcellation, the newly proposed atlas outperforms on the task of atlas-guided individual brain image DBN segmentation both in accuracy and robustness. Moreover, we applied the proposed DBN parcellation map to conduct detailed identification of the pathology-related iron content alterations in subcortical nuclei for Parkinson's Disease (PD) patients. We envision that the MuSus-100 atlas can play a crucial role in improving the accuracy of DBN segmentation for the research of neurological and psychiatric disease progress and also be helpful for target planning in deep brain stimulation surgery.

Associations of medication with subcortical morphology across the lifespan in OCD: Results from the international ENIGMA Consortium

BackgroundWidely used psychotropic medications for obsessive-compulsive disorder (OCD) may change the volumes of subcortical brain structures, and differently in children vs. adults. We measured subcortical volumes cross-sectionally in patients finely stratified for age taking various common classes of OCD drugs. MethodsThe ENIGMA-OCD consortium sample (1081 medicated/1159 unmedicated OCD patients and 2057 healthy controls aged 6–65) was divided into six successive 6–10-year age-groups. Individual structural MRIs were parcellated automatically using FreeSurfer into 8 regions-of-interest (ROIs). ROI volumes were compared between unmedicated and medicated patients and controls, and between patients taking serotonin reuptake inhibitors (SRIs), tricyclics (TCs), antipsychotics (APs), or benzodiazepines (BZs) and unmedicated patients. ResultsCompared to unmedicated patients, volumes of accumbens, caudate, and/or putamen were lower in children aged 6–13 and adults aged 50–65 with OCD taking SRIs (Cohen's d = −0.24 to −0.74). Volumes of putamen, pallidum (d = 0.18–0.40), and ventricles (d = 0.31–0.66) were greater in patients aged 20–29 receiving APs. Hippocampal volumes were smaller in patients aged 20 and older taking TCs and/or BZs (d = −0.27 to −1.31). ConclusionsResults suggest that TCs and BZs could potentially aggravate hippocampal atrophy of normal aging in older adults with OCD, whereas SRIs may reduce striatal volumes in young children and older adults. Similar to patients with psychotic disorders, OCD patients aged 20–29 may experience subcortical nuclear and ventricular hypertrophy in relation to APs. Although cross-sectional, present results suggest that commonly prescribed agents exert macroscopic effects on subcortical nuclei of unknown relation to therapeutic response.

Single-neuron bursts encode pathological oscillations in subcortical nuclei of patients with Parkinson’s disease and essential tremor

Deep brain stimulation procedures offer an invaluable opportunity to study disease through intracranial recordings from awake patients. Here, we address the relationship between single-neuron and aggregate-level (local field potential; LFP) activities in the subthalamic nucleus (STN) and thalamic ventral intermediate nucleus (Vim) of patients with Parkinson's disease (n = 19) and essential tremor (n = 16), respectively. Both disorders have been characterized by pathologically elevated LFP oscillations, as well as an increased tendency for neuronal bursting. Our findings suggest that periodic single-neuron bursts encode both pathophysiological beta (13 to 33 Hz; STN) and tremor (4 to 10 Hz; Vim) LFP oscillations, evidenced by strong time-frequency and phase-coupling relationships between the bursting and LFP signals. Spiking activity occurring outside of bursts had no relationship to the LFP. In STN, bursting activity most commonly preceded the LFP oscillation, suggesting that neuronal bursting generated within STN may give rise to an aggregate-level LFP oscillation. In Vim, LFP oscillations most commonly preceded bursting activity, suggesting that neuronal firing may be entrained by periodic afferent inputs. In both STN and Vim, the phase-coupling relationship between LFP and high-frequency oscillation (HFO) signals closely resembled the relationships between the LFP and single-neuron bursting. This suggests that periodic single-neuron bursting is likely representative of a higher spatial and temporal resolution readout of periodic increases in the amplitude of HFOs, which themselves may be a higher resolution readout of aggregate-level LFP oscillations. Overall, our results may reconcile "rate" and "oscillation" models of Parkinson's disease and shed light on the single-neuron basis and origin of pathophysiological oscillations in movement disorders.

Two subtypes of schizophrenia identified by an individual-level atypical pattern of tensor-based morphometric measurement.

Difficulties in parsing the multiaspect heterogeneity of schizophrenia (SCZ) based on current nosology highlight the need to subtype SCZ using objective biomarkers. Here, utilizing a large-scale multisite SCZ dataset, we identified and validated 2 neuroanatomical subtypes with individual-level abnormal patterns of the tensor-based morphometric measurement. Remarkably, compared with subtype 1, which showed moderate deficits of some subcortical nuclei and an enlarged striatum and cerebellum, subtype 2, which showed cerebellar atrophy and more severe subcortical nuclei atrophy, had a higher subscale score of negative symptoms, which is considered to be a core aspect of SCZ and is associated with functional outcome. Moreover, with the neuroimaging-clinic association analysis, we explored the detailed relationship between the heterogeneity of clinical symptoms and the heterogeneous abnormal neuroanatomical patterns with respect to the 2 subtypes. And the neuroimaging-transcription association analysis highlighted several potential heterogeneous biological factors that may underlie the subtypes. Our work provided an effective framework for investigating the heterogeneity of SCZ from multilevel aspects and may provide new insights for precision psychiatry.

Challenges and Perspectives of Mapping Locus Coeruleus Activity in the Rodent with High-Resolution fMRI.

The locus coeruleus (LC) is one of the most commonly studied brainstem nuclei when investigating brain–behavior associations. The LC serves as a major brainstem relay for both ascending bottom-up and descending top-down projections. Specifically, noradrenergic (NA) LC neurons not only connect globally to higher-order subcortical nuclei and cortex to mediate arousal and attention but also directly project to other brainstem nuclei and to the spinal cord to control autonomic function. Despite the extensive investigation of LC function using electrophysiological recordings and cellular/molecular imaging for both cognitive research and the contribution of LC to different pathological states, the role of neuroimaging to investigate LC function has been restricted. For instance, it remains challenging to identify LC-specific activation with functional MRI (fMRI) in animal models, due to the small size of this nucleus. Here, we discuss the complexity of fMRI applications toward LC activity mapping in mouse brains by highlighting the technological challenges. Further, we introduce a single-vessel fMRI mapping approach to elucidate the vascular specificity of high-resolution fMRI signals coupled to LC activation in the mouse brainstem.

The importance of resource allocation for the interplay between automatic and cognitive control in response inhibition – An EEG source localization study

Goal-directed behavior often requires the inhibition of prepotent automatic responses. Response inhibition encompasses several top-down cognitive operations embedded in a neural network extending from fronto-cortical regions to subcortical nuclei. Yet, it has remained unclear whether the early allocation of cognitive resources also modulates response inhibition performance and neural structures involved in this process. To investigate this question, we used a Simon Nogo task, which was designed to manipulate the relationship between automaticity and cognitive control during response inhibition, and combined it with an electroencephalogram (EEG) and source localization approach. We showed that the early allocation of cognitive resources, as reflected by the P2 amplitude, might be a critical determinant in the interplay between automaticity and cognitive control in response inhibition. Specifically, the obtained results demonstrated that individual variations in cognitive resource allocation modulated the need for conflict monitoring and engagement in cognitive control processes, as reflected by N2 and P3b amplitudes, respectively. Importantly, larger P2 amplitudes were associated with higher activation in cortical regions encompassing the temporo-parietal junction (TPJ). This stresses the importance of this cortical region for the encoding of relevant stimulus information to resolve conflicting contexts in response inhibition. The increased cognitive control in more automatic contexts was also reflected by higher activation of the superior and medial frontal cortices. These findings provide a new perspective on response inhibition, suggesting that early resource allocation is a central modulator of the interaction between automaticity and cognitive control.

When a trophic process turns toxic: Alzheimer's disease as an aberrant recapitulation of a developmental mechanism.

Here we review the idea that Alzheimer's disease (AD) results from aberrant activation of a normal developmental mechanism. This process operates in primarily vulnerable, subcortical nuclei with a distinguishing embryological provenance: the basal rather than the alar plate. All cells are dependent for growth on calcium influx yet these neurons retain a sensitivity to trophic factors into maturity. However, as the brain matures this action becomes detrimental such that the trophic process could turn toxic if triggered in adult brain, in retaliation to an initial insult. The signalling molecule driving this trophic-toxic mechanism is a 14mer peptide (T14) that acts on the alpha-7 receptor to enhance calcium entry, inducing excitotoxicity and proliferation of the receptor, perpetuating a feedforward cycle of neurodegeneration including production of beta-amyloid and p-tau. The T14 system has been previously unrecognised as a basic biological process, yet its pharmaceutical manipulation could have valuable clinical applications.

Subcortical and hippocampal brain segmentation in 5-year-old children: Validation of FSL-FIRST and FreeSurfer against manual segmentation.

Developing accurate subcortical volumetric quantification tools is crucial for neurodevelopmental studies, as they could reduce the need for challenging and time‐consuming manual segmentation. In this study, the accuracy of two automated segmentation tools, FSL‐FIRST (with three different boundary correction settings) and FreeSurfer, were compared against manual segmentation of the hippocampus and subcortical nuclei, including the amygdala, thalamus, putamen, globus pallidus, caudate and nucleus accumbens, using volumetric and correlation analyses in 80 5‐year‐olds.Both FSL‐FIRST and FreeSurfer overestimated the volume on all structures except the caudate, and the accuracy varied depending on the structure. Small structures such as the amygdala and nucleus accumbens, which are visually difficult to distinguish, produced significant overestimations and weaker correlations with all automated methods. Larger and more readily distinguishable structures such as the caudate and putamen produced notably lower overestimations and stronger correlations. Overall, the segmentations performed by FSL‐FIRST's default pipeline were the most accurate, whereas FreeSurfer's results were weaker across the structures.In line with prior studies, the accuracy of automated segmentation tools was imperfect with respect to manually defined structures. However, apart from amygdala and nucleus accumbens, FSL‐FIRST's agreement could be considered satisfactory (Pearson correlation > 0.74, intraclass correlation coefficient (ICC) > 0.68 and Dice score coefficient (DSC) > 0.87) with highest values for the striatal structures (putamen, globus pallidus, caudate) (Pearson correlation > 0.77, ICC > 0.87 and DSC > 0.88, respectively). Overall, automated segmentation tools do not always provide satisfactory results, and careful visual inspection of the automated segmentations is strongly advised.

Three-Dimensional Spatial Analyses of Cholinergic Neuronal Distributions Across The Mouse Septum, Nucleus Basalis, Globus Pallidus, Nucleus Accumbens, and Caudate-Putamen

Neuronal networks are regulated by three-dimensional spatial and structural properties. Despite robust evidence of functional implications in the modulation of cognition, little is known about the three-dimensional internal organization of cholinergic networks in the forebrain. Cholinergic networks in the forebrain primarily occur in subcortical nuclei, specifically the septum, nucleus basalis, globus pallidus, nucleus accumbens, and the caudate-putamen. Therefore, the present investigation analyzed the three-dimensional spatial organization of 14,000 cholinergic neurons that expressed choline acetyltransferase (ChAT) in these subcortical nuclei of the mouse forebrain. Point process theory and graph signal processing techniques identified three topological principles of organization. First, cholinergic interneuronal distance is not uniform across brain regions. Specifically, in the septum, globus pallidus, nucleus accumbens, and the caudate-putamen, the cholinergic neurons were clustered compared with a uniform random distribution. In contrast, in the nucleus basalis, the cholinergic neurons had a spatial distribution of greater regularity than a uniform random distribution. Second, a quarter of the caudate-putamen is composed of axonal bundles, yet the spatial distribution of cholinergic neurons remained clustered when axonal bundles were accounted for. However, comparison with an inhomogeneous Poisson distribution showed that the nucleus basalis and caudate-putamen findings could be explained by density gradients in those structures. Third, the number of cholinergic neurons varies as a function of the volume of a specific brain region but cell body volume is constant across regions. The results of the present investigation provide topographic descriptions of cholinergic somata distribution and axonal conduits, and demonstrate spatial differences in cognitive control networks. The study provides a comprehensive digital database of the total population of ChAT-positive neurons in the reported structures, with the x,y,z coordinates of each neuron at micrometer resolution. This information is important for future digital cellular atlases and computational models of the forebrain cholinergic system enabling models based on actual spatial geometry.

Characterization and diagnostic potential of R2* in early-stage progressive supranuclear palsy variants

IntroductionIron accumulation in subcortical brain nuclei has been shown to be differentially increased in atypical parkinsonian disorders. It is unclear whether the patterns of iron accumulation are consistent between variants of progressive supranuclear palsy (PSP) and their diagnostic utility in early to moderately advanced stages of the diseases. MethodsBrain iron content (R2*) was quantified using magnetic resonance imaging in patients clinically diagnosed as PSP – parkinsonism (PSP–P, n = 15), PSP – Richardson's syndrome (PSP-RS, n = 14), Parkinson's disease (PD, n = 15), or the parkinsonian variant of multiple system atrophy (MSA-P, n = 14) using established criteria, and healthy controls (HC). Disease duration was less than 5 years in all patients. The quantification of regional R2* was performed using a semi-automatized approach. ResultsSignificant group differences in R2*, primarily within the red nucleus and the substantia nigra, were identified between PSP, PD, MSA-P, and HC, but not between PSP-P and PSP-RS. However, distinct R2* correlation patterns across brain regions were observed for the different groups. Good classification performances (sensitivity and specificity >80%) were only obtained for PSP vs. HC. For all other comparisons, sensitivity and/or specificity was below <70%. ConclusionIron accumulation in subcortical brain nuclei has distinct correlated patterns in PSP-P and PSP-RS, which could be reflecting different pathophysiological mechanisms. Increased iron content in these nuclei appears to be a predictor for atypical parkinsonian disorders such as PSP and MSA. Further studies are required to reproduce this finding and elucidate the evolution of these patterns over the course of the disease.

Characterizing thalamic and basal ganglia nuclei in medically intractable focal epilepsy by MR fingerprinting.

Magnetic resonance fingerprinting (MRF) is a novel, quantitative, and noninvasive technique to measure brain tissue properties. We aim to use MRF for characterizing normal-appearing thalamic and basal ganglia nuclei in the epileptic brain. A three-dimensional (3D) MRF protocol (1 mm3 isotropic resolution) was acquired from 48 patients with unilateral medically intractable focal epilepsy and 39 healthy controls (HCs). Whole-brain T1 and T2 maps (containing T1 and T2 relaxation times) were reconstructed for each subject. Ten subcortical nuclei in the thalamus and basal ganglia were segmented as regions of interest (ROIs), within which the mean T1 and T2 values, as well as their coefficient of variation (CV) were compared between the patients and HCs at the group level. Subgroup and correlation analyses were performed to examine the relationship between significant MRF measures and various clinical characteristics. Using significantly abnormal MRF measures from the group-level analyses, support vector machine (SVM) and logistic regression machine learning models were built and tested with 5-fold and 10-fold cross-validations, to separate patients from HCs, and to separate patients with left-sided and right-sided epilepsy, at the individual level. MRF revealed increased T1 mean value in the ipsilateral thalamus and nucleus accumbens; increased T1 CV in the bilateral thalamus, bilateral pallidum, and ipsilateral caudate; and increased T2 CV in the ipsilateral thalamus in patients compared to HCs (p < .05, false discovery rate [FDR] corrected). The SVM classifier produced 78.2% average accuracy to separate individual patients from HCs, with an area under the curve (AUC) of 0.83. The logistic regression classifier produced 67.4% average accuracy to separate patients with left-sided and right-sided epilepsy, with an AUC of 0.72. MRF revealed bilateral tissue-property changes in the normal-appearing thalamus and basal ganglia, with ipsilateral predominance and thalamic preference, suggesting subcortical involvement/impairment in patients with medically intractable focal epilepsy. The individual-level performance of the MRF-based machine-learning models suggests potential opportunities for predicting lateralization.

A model description of beta oscillations in the external globus pallidus.

The external globus pallidus (GPe), a subcortical nucleus located in the indirect pathway of the basal ganglia, is widely considered to have tight associations with abnormal beta oscillations (13-30 Hz) observed in Parkinson's disease (PD). Despite that many mechanisms have been put forward to explain the emergence of these beta oscillations, however, it is still unclear the functional contributions of the GPe, especially, whether the GPe itself can generate beta oscillations. To investigate the role played by the GPe in producing beta oscillations, we employ a well described firing rate model of the GPe neural population. Through extensive simulations, we find that the transmission delay within the GPe-GPe pathway contributes significantly to inducing beta oscillations, and the impacts of the time constant and connection strength of the GPe-GPe pathway on generating beta oscillations are non-negligible. Moreover, the GPe firing patterns can be significantly modulated by the time constant and connection strength of the GPe-GPe pathway, as well as the transmission delay within the GPe-GPe pathway. Interestingly, both increasing and decreasing the transmission delay can push the GPe firing pattern from beta oscillations to other firing patterns, including oscillation and non-oscillation firing patterns. These findings suggest that if the transmission delays within the GPe are at least 9.8 ms, beta oscillations can be produced originally in the GPe neural population, which also may be the origin of PD-related beta oscillations and should be regarded as a promising target for treatments for PD.

Sexually divergent development of depression-related brain networks during healthy human adolescence.

Sexual differences in human brain development could be relevant to sex differences in the incidence of depression during adolescence. We tested for sex differences in parameters of normative brain network development using fMRI data on N = 298 healthy adolescents, aged 14 to 26 years, each scanned one to three times. Sexually divergent development of functional connectivity was located in the default mode network, limbic cortex, and subcortical nuclei. Females had a more “disruptive” pattern of development, where weak functional connectivity at age 14 became stronger during adolescence. This fMRI-derived map of sexually divergent brain network development was robustly colocated with i prior loci of reward-related brain activation ii a map of functional dysconnectivity in major depressive disorder (MDD), and iii an adult brain gene transcriptional pattern enriched for genes on the X chromosome, neurodevelopmental genes, and risk genes for MDD. We found normative sexual divergence in adolescent development of a cortico-subcortical brain functional network that is relevant to depression.

Association between aerobic fitness and the functional connectome in patients with schizophrenia

BackgroundSchizophrenia is accompanied by widespread alterations in static functional connectivity associated with symptom severity and cognitive deficits. Improvements in aerobic fitness have been demonstrated to ameliorate symptomatology and cognition in people with schizophrenia, but the intermediary role of macroscale connectivity patterns remains unknown.ObjectiveTherefore, we aim to explore the relation between aerobic fitness and the functional connectome in individuals with schizophrenia. Further, we investigate clinical and cognitive relevance of the identified fitness-connectivity links.MethodsPatients diagnosed with schizophrenia were included in this cross-sectional resting-state fMRI analysis. Multilevel Bayesian partial correlations between aerobic fitness and functional connections across the whole brain as well as between static functional connectivity patterns and clinical and cognitive outcome were performed. Preliminary causal inferences were enabled based on mediation analyses.ResultsStatic functional connectivity between the subcortical nuclei and the cerebellum as well as between temporal seeds mediated the attenuating relation between aerobic fitness and total symptom severity. Functional connections between cerebellar seeds affected the positive link between aerobic fitness and global cognition, while the functional interplay between central and limbic seeds drove the beneficial association between aerobic fitness and emotion recognition.ConclusionThe current study provides first insights into the interactions between aerobic fitness, the functional connectome and clinical and cognitive outcome in people with schizophrenia, but causal interpretations are preliminary. Further interventional aerobic exercise studies are needed to replicate the current findings and to enable conclusive causal inferences.Trial registrationThe study which the manuscript is based on is registered in the International Clinical Trials Database (ClinicalTrials.gov identifier [NCT number]: NCT03466112) and in the German Clinical Trials Register (DRKS-ID: DRKS00009804).

The brainstem connectome database

Connectivity data of the nervous system and subdivisions, such as the brainstem, cerebral cortex and subcortical nuclei, are necessary to understand connectional structures, predict effects of connectional disorders and simulate network dynamics. For that purpose, a database was built and analyzed which comprises all known directed and weighted connections within the rat brainstem. A longterm metastudy of original research publications describing tract tracing results form the foundation of the brainstem connectome (BC) database which can be analyzed directly in the framework neuroVIISAS. The BC database can be accessed directly by connectivity tables, a web-based tool and the framework. Analysis of global and local network properties, a motif analysis, and a community analysis of the brainstem connectome provides insight into its network organization. For example, we found that BC is a scale-free network with a small-world connectivity. The Louvain modularity and weighted stochastic block matching resulted in partially matching of functions and connectivity. BC modeling was performed to demonstrate signal propagation through the somatosensory pathway which is affected in Multiple sclerosis.