Validation of connectivity-based thalamic segmentation with direct electrophysiologic recordings from human sensory thalamus

Connectivity-based segmentation of the thalamic motor region for deep brain stimulation in essential tremor: A comparison of deterministic and probabilistic tractography

OBJECTIVE

Deep brain stimulation (DBS) studies have shown that stimulation of the motor segment of the thalamus based on probabilistic tractography is predictive of improvement in essential tremor (ET). However, probabilistic methods are computationally demanding, requiring the need for alternative tractography methods for use in the clinical setting. The purpose of this study was to compare probabilistic vs deterministic tractography methods for connectivity-based targeting in patients with ET.

METHODS

Probabilistic and deterministic tractography methods were retrospectively applied to diffusion-weighted data sets in 36 patients with refractory ET. The thalamus and precentral gyrus were selected as regions of interest and fiber tracking was performed between these regions to produce connectivity-based thalamic segmentations, per prior methods. The resultant deterministic target maps were compared with those of thresholded probabilistic maps. The center of gravity (CG) of each connectivity map was determined and the differences in spatial distribution between the tractography methods were characterized. Furthermore, the intersection between the connectivity maps and CGs with the therapeutic volume of tissue activated (VTA) was calculated. A mixed linear model was then used to assess clinical improvement in tremor with volume of overlap.

RESULTS

Both tractography methods delineated the region of the thalamus with connectivity to the precentral gyrus to be within the posterolateral aspect of the thalamus. The average CG of deterministic maps was more medial-posterior in both the left (3.7 ± 1.3 mm3) and the right (3.5 ± 2.2 mm3) hemispheres when compared to 30 %-thresholded probabilistic maps. Mixed linear model showed that the volume of overlap between CGs of deterministic and probabilistic targeting maps and therapeutic VTAs were significant predictors of clinical improvement.

CONCLUSIONS

Deterministic tractography can reconstruct DBS thalamic target maps in approximately 5 min comparable to those produced by probabilistic methods that require > 12 h to generate. Despite differences in CG between the methods, both deterministic-based and probabilistic targeting were predictive of clinical improvement in ET.

Thalamic Segmentation and Neural Activation Modeling Based on Individual Tissue Microstructure in Deep Brain Stimulation for Essential Tremor

OBJECTIVE

Thalamic deep brain stimulation (DBS) is the primary surgical therapy for essential tremor (ET). Thalamic DBS traditionally uses an atlas-based targeting approach, which, although nominally accurate, may obscure individual anatomic differences from population norms. The objective of this study was to compare this traditional atlas-based approach with a novel quantitative modeling methodology grounded in individual tissue microstructure (N-of-1 approach).

MATERIALS AND METHODS

The N-of-1 approach uses individual patient diffusion tensor imaging (DTI) data to perform thalamic segmentation and volume of tissue activation (VTA) modeling. For each patient, the thalamus was individually segmented into 13 nuclei using DTI-based k-means clustering. DBS-induced VTAs associated with tremor suppression and side effects were then computed for each patient with finite-element electric-field models incorporating DTI microstructural data. Results from N-of-1 and traditional atlas-based modeling were compared for a large cohort of patients with ET treated with thalamic DBS.

RESULTS

The size and shape of individual N-of-1 thalamic nuclei and VTAs varied considerably across patients (N = 22). For both methods, tremor-improving therapeutic VTAs showed similar overlap with motor thalamic nuclei and greater motor than sensory nucleus overlap. For VTAs producing undesirable sustained paresthesia, 94% of VTAs overlapped with N-of-1 sensory thalamus estimates, whereas 74% of atlas-based segmentations overlapped. For VTAs producing dysarthria/motor contraction, the N-of-1 approach predicted greater spread beyond the thalamus into the internal capsule and adjacent structures than the atlas-based method.

CONCLUSIONS

Thalamic segmentation and VTA modeling based on individual tissue microstructure explain therapeutic stimulation equally well and side effects better than a traditional atlas-based method in DBS for ET. The N-of-1 approach may be useful in DBS targeting and programming, particularly when patient neuroanatomy deviates from population norms.

Thalamic stereoelectroencephalography in epilepsy surgery: a scoping literature review

OBJECTIVE

Stereoelectroencephalography (sEEG) is a well-established surgical method for defining the epileptogenic network. Traditionally reserved for identifying discrete cortical regions for resection or ablation, sEEG in current practice is also used for identifying more broadly involved subcortical epileptic network components, driven by the availability of brain-based neuromodulation strategies. In particular, sEEG investigations including thalamic nuclei are becoming more frequent in parallel with the increase in therapeutic strategies involving thalamic targets such as deep brain stimulation (DBS) and responsive neurostimulation (RNS). The objective to this study was to evaluate existing evidence and trends regarding the purpose, techniques, and relevant electrographic findings of thalamic sEEG.

METHODS

MEDLINE and Embase databases were systematically queried for eligible peer-reviewed studies involving sEEG electrode implantation into thalamic nuclei of patients with epilepsy. Available data were abstracted concerning preoperative workup and purpose for implanting the thalamus, thalamic targets and trajectories, and electrophysiological methodology and findings.

RESULTS

sEEG investigations have included thalamic targets for both basic and clinical research purposes. Medial pulvinar, dorsomedial, anterior, and centromedian nuclei have been the most frequently studied. Few studies have reported any complications with thalamic sEEG implantation, and no studies have reported long-term complications. Various methods have been utilized to characterize thalamic activity in epileptic disorders including evoked potentials, power spectrograms, synchronization indices, and the epileptogenicity index. Thalamic intracranial recordings are beginning to be used to guide neuromodulation strategies including RNS and DBS, as well as to understand complex, network-dependent seizure disorders.

CONCLUSIONS

Inclusion of thalamic coverage during sEEG evaluation in drug-resistant epilepsy is a growing practice and is amenable to various methods of electrographic data analysis. Further study is required to establish well-defined criteria for thalamic implantation during invasive investigations as well as safety and ethical considerations.

Connectivity-based thalamus parcellation and surgical targeting of somatosensory subnuclei

OBJECTIVE

The anatomy of the posterolateral thalamus varies substantially between individuals, presenting a challenge for surgical targeting. Patient-specific, connectivity-based parcellation of the thalamus may effectively approximate the ventrocaudal nucleus (Vc). This remains to be robustly validated or assessed as a method to guide surgical targeting. The authors assessed the validity of connectivity-based parcellation for targeting the Vc and its potential for improving clinical outcomes of pain surgery.

METHODS

A cohort of 19 patients with regional, chronic neuropathic pain underwent preoperative structural and diffusion MRI, then progressed to deep brain stimulation targeting the Vc based on traditional atlas coordinates. Surgical thalami were retrospectively segmented and then parcellated based on tractography estimates of thalamocortical connectivity. The location of each patient's electrode array was analyzed with respect to their primary somatosensory cortex (S1) parcel and compared across patients with reference to the thalamic homunculus.

RESULTS

Ten patients achieved long-term pain relief. Sixty-one percent of an average array (interquartile range 42%-74%) was located in the S1 parcel. In patients who achieved long-term benefit from surgery, array location in the individually generated S1 parcels was medial for face pain, centromedial for arm pain, and centrolateral for leg pain. Patients who did not benefit from surgery did not follow this pattern. Standard stereotactic coordinates of electrode locations diverged from this pattern.

CONCLUSIONS

Connectivity-based parcellation of the thalamus appears to be a reliable method for segmenting the Vc. Identifying the Vc in this way, and targeting mediolaterally as appropriate for the region of pain, merits exploration in an effort to increase the yield of successful surgical procedures.

Imaging versus electrographic connectivity in human mood-related fronto-temporal networks

BACKGROUND

The efficacy of psychiatric DBS is thought to be driven by the connectivity of stimulation targets with mood-relevant fronto-temporal networks, which is typically evaluated using diffusion-weighted tractography.

OBJECTIVE

Leverage intracranial electrophysiology recordings to better predict the circuit-wide effects of neuromodulation to white matter targets. We hypothesize strong convergence between tractography-predicted structural connectivity and stimulation-induced electrophysiological responses.

METHODS

Evoked potentials were elicited by single-pulse stimulation to two common DBS targets for treatment-resistant depression - the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VCVS) - in two patients undergoing DBS with stereo-electroencephalographic (sEEG) monitoring. Evoked potentials were compared with predicted structural connectivity between DBS leads and sEEG contacts using probabilistic, patient-specific diffusion-weighted tractography.

RESULTS

Evoked potentials and tractography showed strong convergence in both patients in orbitofrontal, ventromedial prefrontal, and lateral prefrontal cortices for both SCC and VCVS stimulation targets. Low convergence was found in anterior cingulate (ACC), where tractography predicted structural connectivity from SCC targets but produced no evoked potentials during SCC stimulation. Further, tractography predicted no connectivity to ACC from VCVS targets, but VCVS stimulation produced robust evoked potentials.

CONCLUSION

The two connectivity methods showed significant convergence, but important differences emerged with respect to the ability of tractography to predict electrophysiological connectivity between SCC and VCVS to regions of the mood-related network. This multimodal approach raises intriguing implications for the use of tractography in surgical targeting and provides new data to enhance our understanding of the network-wide effects of neuromodulation.

Ventral intermediate nucleus structural connectivity-derived segmentation: anatomical reliability and variability

The Ventral intermediate nucleus (Vim) of thalamus is the most targeted structure for the treatment of drug-refractory tremors. Since methodological differences across existing studies are remarkable and no gold-standard pipeline is available, in this study, we tested different parcellation pipelines for tractography-derived putative Vim identification. Thalamic parcellation was performed on a high quality, multi-shell dataset and a downsampled, clinical-like dataset using two different diffusion signal modeling techniques and two different voxel classification criteria, thus implementing a total of four parcellation pipelines. The most reliable pipeline in terms of inter-subject variability has been picked and parcels putatively corresponding to motor thalamic nuclei have been selected by calculating similarity with a histology-based mask of Vim. Then, spatial relations with optimal stimulation points for the treatment of essential tremor have been quantified. Finally, effect of data quality and parcellation pipelines on a volumetric index of connectivity clusters has been assessed. We found that the pipeline characterized by higher-order signal modeling and threshold-based voxel classification criteria was the most reliable in terms of inter-subject variability regardless data quality. The maps putatively corresponding to Vim were those derived by precentral and dentate nucleus-thalamic connectivity. However, tractography-derived functional targets showed remarkable differences in shape and sizes when compared to a ground truth model based on histochemical staining on seriate sections of human brain. Thalamic voxels connected to contralateral dentate nucleus resulted to be the closest to literature-derived stimulation points for essential tremor but at the same time showing the most remarkable inter-subject variability. Finally, the volume of connectivity parcels resulted to be significantly influenced by data quality and parcellation pipelines. Hence, caution is warranted when performing thalamic connectivity-based segmentation for stereotactic targeting.

DTI for brain targeting: Diffusion weighted imaging fiber tractography-Assisted deep brain stimulation

Fiber tractography assisted Deep Brain Stimulation (DBS) has been performed by different groups for more than 10 years to now. Groups around the world have adapted initial approaches to currently embrace the fiber tractography technology mainly for treating tremor (DBS and lesions), psychiatric indications (OCD and major depression) and pain (DBS). Despite the advantages of directly visualizing the target structure, the technology is demanding and is vulnerable to inaccuracies especially since it is performed on individual level. In this contribution, we will focus on tremor and psychiatric indications, and will show future applications of sophisticated tractography applications for subthalamic nucleus (STN) DBS surgery and stimulation steering as an example.

Deep Brain Stimulation of the Subgenual Cingulate Cortex for the Treatment of Chronic Low Back Pain

OBJECTIVES

Despite converging basic scientific and clinical evidence of the link between chronic pain and depression, existing therapies do not often take advantage of this overlap. Here, we provide a critical review of the literature that highlights the intersection in brain networks between chronic low back pain (CLBP) and depression and discuss findings from previous deep brain stimulation (DBS) studies for pain. Based on a multidimensional model of pain processing and the connectivity of the subgenual cingulate cortex (SCC) with areas that are implicated in both CLBP and depression, we propose a novel approach to the treatment of CLBP using DBS of the SCC.

MATERIALS AND METHODS

A narrative review with literature assessment.

RESULTS

CLBP is associated with a shift away from somatosensory representation toward brain regions that mediate emotional processes. There is a high degree of overlap between these regions and those involved in depression, including the anterior cingulate cortex, medial prefrontal cortex, nucleus accumbens, and amygdala. Whereas targets sites from previous DBS trials for pain were not anatomically positioned to engage these areas and their associated networks, the SCC is structurally connected to all of these regions and as well as others involved in mediating sensory, cognitive, and affective processing in CLBP.

CONCLUSIONS

CLBP and depression share a common underlying brain network interconnected by the SCC. Current data and novel technology provide an optimal opportunity to develop clinically effective trials of SCC DBS for CLBP.

Evoked Potentials During Peripheral Stimulation Confirm Electrode Location in Thalamic Subnuclei in Children With Secondary Dystonia

Deep brain stimulation is an elective surgical intervention that improves the function and quality of life in children with dystonia and other movement disorders. Both basal ganglia and thalamic nuclei have been found to be relevant targets for treatment of dystonia in children, including the ventral intermediate nucleus of the thalamus, in which stimulation can control dystonic spasms. Electrophysiological confirmation of correct electrode location within the ventralis intermediate nucleus is thus important for the success of the surgical outcome. The present work shows the evoked potentials response during contralateral median-nerve stimulation at the wrist at low frequency (9 Hz) provides physiological evidence of the electrode's localization within the thalamus. We show the correlation between evoked potentials and magnetic resonance imaging (MRI) and computed tomography (CT) in 14 children undergoing implantation of deep brain stimulation electrodes for secondary dystonia. High fidelity and reproducibility of our results provides a new approach to ensure the electrode localization in the thalamic subnuclei.

Association of self-regulation with white matter correlates in boys with and without autism spectrum disorder

Previous studies demonstrated distinct neural correlates underpinning impaired self-regulation (dysregulation) between individuals with autism spectrum disorder (ASD) and typically developing controls (TDC). However, the impacts of dysregulation on white matter (WM) microstructural property in ASD and TDC remain unclear. Diffusion spectrum imaging was acquired in 59 ASD and 62 TDC boys. We investigated the relationship between participants’ dysregulation levels and microstructural property of 76 WM tracts in a multivariate analysis (canonical correlation analysis), across diagnostic groups. A single mode of brain-behavior co-variation was identified: participants were spread along a single axis linking diagnosis, dysregulation, diagnosis-by-dysregulation interaction, and intelligence to a specific WM property pattern. This mode corresponds to diagnosis-distinct correlates underpinning dysregulation, which showed higher generalized fractional anisotropy (GFA) associated with less dysregulation in ASD but greater dysregulation in TDC, in the tracts connecting limbic and emotion regulation systems. Moreover, higher GFA of the tracts implicated in memory, attention, sensorimotor processing, and perception associated with less dysregulation in TDC but worse dysregulation in ASD. No shared WM correlates of dysregulation between ASD and TDC were identified. Corresponding to previous studies, we demonstrated that ASD and TDC have broad distinct white matter microstructural property underpinning self-regulation.

Dynamic tractography: Integrating cortico-cortical evoked potentials and diffusion imaging

INTRODUCTION

Cortico-cortical evoked potentials (CCEPs) are utilized to identify effective networks in the human brain. Following single-pulse electrical stimulation of cortical electrodes, evoked responses are recorded from distant cortical areas. A negative deflection (N1) which occurs 10-50 ​ms post-stimulus is considered to be a marker for direct cortico-cortical connectivity. However, with CCEPs alone it is not possible to observe the white matter pathways that conduct the signal or accurately predict N1 amplitude and latency at downstream recoding sites. Here, we develop a new approach, termed "dynamic tractography," which integrates CCEP data with diffusion-weighted imaging (DWI) data collected from the same patients. This innovative method allows greater insights into cortico-cortical networks than provided by each method alone and may improve the understanding of large-scale networks that support cognitive functions. The dynamic tractography model produces several fundamental hypotheses which we investigate: 1) DWI-based pathlength predicts N1 latency; 2) DWI-based pathlength negatively predicts N1 voltage; and 3) fractional anisotropy (FA) along the white matter path predicts N1 propagation velocity.

METHODS

Twenty-three neurosurgical patients with drug-resistant epilepsy underwent both extraoperative CCEP recordings and preoperative DWI scans. Subdural grids of 3 ​mm diameter electrodes were used for stimulation and recording, with 98-128 eligible electrodes per patient. CCEPs were elicited by trains of 1 ​Hz stimuli with an intensity of 5 ​mA and recorded at a sample rate of 1 ​kHz. N1 peak and latency were defined as the maximum of a negative deflection within 10-50 ​ms post-stimulus with a z-score > 5 relative to baseline. Electrodes and DWI were coregistered to construct electrode connectomes for white matter quantification.

RESULTS

Clinical variables (age, sex, number of anti-epileptic drugs, handedness, and stimulated hemisphere) did not correlate with the key outcome measures (N1 peak amplitude, latency, velocity, or DWI pathlength). All subjects and electrodes were therefore pooled into a group-level analysis to determine overall patterns. As hypothesized, DWI path length positively predicted N1 latency (R² ​= ​0.81, β ​= ​1.51, p ​= ​4.76e-16) and negatively predicted N1 voltage (R² ​= ​0.79, β ​= ​-0.094, p ​= ​9.30e-15), while FA predicted N1 propagation velocity (R² ​= ​0.35, β ​= ​48.0, p ​= ​0.001).

CONCLUSION

We have demonstrated that the strength and timing of the CCEP N1 is dependent on the properties of the underlying white matter network. Integrated CCEP and DWI visualization allows robust localization of intact axonal pathways which effectively interconnect eloquent cortex.

Quantifying deep grey matter atrophy using automated segmentation approaches: A systematic review of structural MRI studies

The deep grey matter (DGM) nuclei of the brain play a crucial role in learning, behaviour, cognition, movement and memory. Although automated segmentation strategies can provide insight into the impact of multiple neurological conditions affecting these structures, such as Multiple Sclerosis (MS), Huntington's disease (HD), Alzheimer's disease (AD), Parkinson's disease (PD) and Cerebral Palsy (CP), there are a number of technical challenges limiting an accurate automated segmentation of the DGM. Namely, the insufficient contrast of T1 sequences to completely identify the boundaries of these structures, as well as the presence of iso-intense white matter lesions or extensive tissue loss caused by brain injury. Therefore in this systematic review, 269 eligible studies were analysed and compared to determine the optimal approaches for addressing these technical challenges. The automated approaches used among the reviewed studies fall into three broad categories, atlas-based approaches focusing on the accurate alignment of atlas priors, algorithmic approaches which utilise intensity information to a greater extent, and learning-based approaches that require an annotated training set. Studies that utilise freely available software packages such as FIRST, FreeSurfer and LesionTOADS were also eligible, and their performance compared. Overall, deep learning approaches achieved the best overall performance, however these strategies are currently hampered by the lack of large-scale annotated data. Improving model generalisability to new datasets could be achieved in future studies with data augmentation and transfer learning. Multi-atlas approaches provided the second-best performance overall, and may be utilised to construct a "silver standard" annotated training set for deep learning. To address the technical challenges, providing robustness to injury can be improved by using multiple channels, highly elastic diffeomorphic transformations such as LDDMM, and by following atlas-based approaches with an intensity driven refinement of the segmentation, which has been done with the Expectation Maximisation (EM) and level sets methods. Accounting for potential lesions should be achieved with a separate lesion segmentation approach, as in LesionTOADS. Finally, to address the issue of limited contrast, R2*, T2* and QSM sequences could be used to better highlight the DGM due to its higher iron content. Future studies could look to additionally acquire these sequences by retaining the phase information from standard structural scans, or alternatively acquiring these sequences for only a training set, allowing models to learn the "improved" segmentation from T1-sequences alone.

Building connectomes using diffusion MRI: why, how and but

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments.

The role of diffusion MRI in neuroscience

Diffusion-weighted imaging has pushed the boundaries of neuroscience by allowing us to examine the white matter microstructure of the living human brain. By doing so, it has provided answers to fundamental neuroscientific questions, launching a new field of research that had been largely inaccessible. We briefly summarize key questions that have historically been raised in neuroscience concerning the brain's white matter. We then expand on the benefits of diffusion-weighted imaging and its contribution to the fields of brain anatomy, functional models and plasticity. In doing so, this review highlights the invaluable contribution of diffusion-weighted imaging in neuroscience, presents its limitations and proposes new challenges for future generations who may wish to exploit this powerful technology to gain novel insights.

Electrophysiologic mapping for deep brain stimulation for movement disorders

Electrophysiologic mapping remains an integral component of deep brain stimulation (DBS) surgical procedures, particularly in movement disorder cases where functional maps are used to guide DBS lead placement in patients with Parkinson's disease, dystonia, or tremor. Overall, the goal of the surgical procedure is to implant the distal end of a chronic, multicontact depth electrode into a specific brain region for the purpose of delivering therapeutic electrical stimulation. Regions that are currently targeted for patients with movement disorders include the subthalamic nucleus, the ventral intermediate nucleus of the thalamus, and the globus pallidus. Multiple imaging modalities are used initially to derive a stereotactic plan and guide the initial microelectrode trajectory. Changes in neuronal firing rate and pattern, both spontaneous and in response to somatosensory stimulation, are used to establish the location of the tip of the microelectrode(s), while acute stimulation can be used to estimate the proximity of neighboring brain regions. In this chapter, we will provide an overview of the microelectrode recording process as it is commonly applied to refine image-based targeting of lead placement for DBS surgery.

Pediatric Deep Brain Stimulation Using Awake Recording and Stimulation for Target Selection in an Inpatient Neuromodulation Monitoring Unit

Deep brain stimulation (DBS) for secondary (acquired, combined) dystonia does not reach the high degree of efficacy achieved in primary (genetic, isolated) dystonia. We hypothesize that this may be due to variability in the underlying injury, so that different children may require placement of electrodes in different regions of basal ganglia and thalamus. We describe a new targeting procedure in which temporary depth electrodes are placed at multiple possible targets in basal ganglia and thalamus, and probing for efficacy is performed using test stimulation and recording while children remain for one week in an inpatient Neuromodulation Monitoring Unit (NMU). Nine Children with severe secondary dystonia underwent the NMU targeting procedure. In all cases, 4 electrodes were implanted. We compared the results to 6 children who had previously had 4 electrodes implanted using standard intraoperative microelectrode targeting techniques. Results showed a significant benefit, with 80% of children with NMU targeting achieving greater than 5-point improvement on the Burke–Fahn–Marsden Dystonia Rating Scale (BFMDRS), compared with 50% of children using intraoperative targeting. NMU targeting improved BFMDRS by an average of 17.1 whereas intraoperative targeting improved by an average of 10.3. These preliminary results support the use of test stimulation and recording in a Neuromodulation Monitoring Unit (NMU) as a new technique with the potential to improve outcomes following DBS in children with secondary (acquired) dystonia. A larger sample size will be needed to confirm these results.

Connectivity-based segmentation of the brainstem by probabilistic tractography

Diffusion magnetic resonance imaging is a non-invasive tool increasingly used for the investigation of brain connectivity in vivo. In this paper we propose a method that allows segmentation of the brainstem to four subregions (frontopontine, motor, sensory and reticular) based on connections to supratentorial structures, thereby eliminating the need for using anatomical landmarks within the brainstem for the identification of these subregions. The feasibility of connectivity-based brainstem segmentation was investigated in a group of healthy subjects (n = 20). Multifiber probabilistic tractography was performed using the FMRIB Software Library, and connections between a pontomesencephalic seed mask and four supratentorial target regions (anterior and posterior limbs of the internal capsule, sensory and medial thalamus) were used to determine connectivity maps of the brainstem. Results were compared with a neuroanatomy atlas and histological sections, confirming good anatomic correspondence. The four subregions detected by the connectivity-based segmentation showed good intersubject reproducibility. The presented method may be a potential tool to investigate brainstem connectivity in diseases that distort normal anatomy, and quantitative analyses of the diffusion-related parameters may provide additional information on the involvement of brainstem pathways in certain disease states (e.g., traumatic brain injury, demyelinating disorders, brainstem tumors). The potential clinical applicability of the method is demonstrated in two cases of severe traumatic brain injury.

Diffusion MRI tractography for improved transcranial MRI-guided focused ultrasound thalamotomy targeting for essential tremor

Purpose

To evaluate the use of diffusion magnetic resonance imaging (MRI) tractography for neurosurgical guidance of transcranial MRI-guided focused ultrasound (tcMRgFUS) thalamotomy for essential tremor (ET).

Materials and methods

Eight patients with medication-refractory ET were treated with tcMRgFUS targeting the ventral intermediate nucleus (Vim) of the thalamus contralateral to their dominant hand. Diffusion and structural MRI data and clinical evaluations were acquired pre-treatment and post-treatment. To identify the optimal target location, tractography was performed on pre-treatment diffusion MRI data between the treated thalamus and the hand-knob region of the ipsilateral motor cortex, the entire ipsilateral motor cortex and the contralateral dentate nucleus. The tractography-identified locations were compared to the lesion location delineated on 1 year post-treatment T₂-weighted MR image. Their overlap was correlated with the clinical outcomes measured by the percentage change of the Clinical Rating Scale for Tremor scores acquired pre-treatment, as well as 1 month, 3 months, 6 months and 1 year post-treatment.

Results

The probabilistic tractography was consistent from subject-to-subject and followed the expected anatomy of the thalamocortical radiation and the dentatothalamic tract. Higher overlap between the tractography-identified location and the tcMRgFUS treatment-induced lesion highly correlated with better treatment outcome (r = −0.929, −0.75, −0.643, p = 0.00675, 0.0663, 0.139 for the tractography between the treated thalamus and the hand-knob region of the ipsilateral motor cortex, the entire ipsilateral motor cortex and the contralateral dentate nucleus, respectively, at 1 year post-treatment). The correlation for the tractography between the treated thalamus and the hand-knob region of the ipsilateral motor cortex is the highest for all time points (r = −0.719, −0.976, −0.707, −0.929, p = 0.0519, 0.000397, 0.0595, 0.00675 at 1 month, 3 months, 6 months and 1 year post-treatment, respectively).

Conclusion

Our data support the use of diffusion tractography as a complementary approach to current targeting methods for tcMRgFUS thalamotomy.

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Retrospectively used tractography to define a target for MRgFUS thalamotomy for ET.

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Larger overlap between tractography and lesion correlates with better outcomes.

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Strongest correlations for tract between the thalamus and motor hand-knob region

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Diffusion tractography is a complementary approach to current targeting methods.

Segmentation of the Globus Pallidus Internus Using Probabilistic Diffusion Tractography for Deep Brain Stimulation Targeting in Parkinson Disease

BACKGROUND AND PURPOSE

Although globus pallidus internus deep brain stimulation is a widely accepted treatment for Parkinson disease, there is persistent variability in outcomes that is not yet fully understood. In this pilot study, we aimed to investigate the potential role of globus pallidus internus segmentation using probabilistic tractography as a supplement to traditional targeting methods.

MATERIALS AND METHODS

Eleven patients undergoing globus pallidus internus deep brain stimulation were included in this retrospective analysis. Using multidirection diffusion-weighted MR imaging, we performed probabilistic tractography at all individual globus pallidus internus voxels. Each globus pallidus internus voxel was then assigned to the 1 ROI with the greatest number of propagated paths. On the basis of deep brain stimulation programming settings, the volume of tissue activated was generated for each patient using a finite element method solution. For each patient, the volume of tissue activated within each of the 10 segmented globus pallidus internus regions was calculated and examined for association with a change in the Unified Parkinson Disease Rating Scale, Part III score before and after treatment.

RESULTS

Increasing volume of tissue activated was most strongly correlated with a change in the Unified Parkinson Disease Rating Scale, Part III score for the primary motor region (Spearman r = 0.74, P = .010), followed by the supplementary motor area/premotor cortex (Spearman r = 0.47, P = .15).

CONCLUSIONS

In this pilot study, we assessed a novel method of segmentation of the globus pallidus internus based on probabilistic tractography as a supplement to traditional targeting methods. Our results suggest that our method may be an independent predictor of deep brain stimulation outcome, and evaluation of a larger cohort or prospective study is warranted to validate these findings.

Cortical parcellation based on structural connectivity: A case for generative models

One of the major challenges in systems neuroscience is to identify brain networks and unravel their significance for brain function -this has led to the concept of the 'connectome'. Connectomes are currently extensively studied in large-scale international efforts at multiple scales, and follow different definitions with respect to their connections as well as their elements. Perhaps the most promising avenue for defining the elements of connectomes originates from the notion that individual brain areas maintain distinct (long-range) connection profiles. These connectivity patterns determine the areas' functional properties and also allow for their anatomical delineation and mapping. This rationale has motivated the concept of connectivity-based cortex parcellation. In the past ten years, non-invasive mapping of human brain connectivity has led to immense advances in the development of parcellation techniques and their applications. Unfortunately, many of these approaches primarily aim for confirmation of well-known, existing architectonic maps and, to that end, unsuitably incorporate prior knowledge and frequently build on circular argumentation. Often, current approaches also tend to disregard the specific apertures of connectivity measurements, as well as the anatomical specificities of cortical areas, such as spatial compactness, regional heterogeneity, inter-subject variability, the multi-scaling nature of connectivity information, and potential hierarchical organisation. From a methodological perspective, however, a useful framework that regards all of these aspects in an unbiased way is technically demanding. In this commentary, we first outline the concept of connectivity-based cortex parcellation and discuss its prospects and limitations in particular with respect to structural connectivity. To improve reliability and efficiency, we then strongly advocate for connectivity-based cortex parcellation as a modelling approach; that is, an approximation of the data based on (model) parameter inference. As such, a parcellation algorithm can be formally tested for robustness -the precision of its predictions can be quantified and statistics about potential generalization of the results can be derived. Such a framework also allows the question of model constraints to be reformulated in terms of hypothesis testing through model selection and offers a formative way to integrate anatomical knowledge in terms of prior distributions.

A method for pre-operative single-subject thalamic segmentation based on probabilistic tractography for essential tremor deep brain stimulation

PURPOSE

Deep brain stimulation is a common treatment for medication-refractory essential tremor. Current coordinate-based targeting methods result in variable outcomes due to variation in thalamic structure and the optimal patient-specific functional location. The purpose of this study was to compare the coordinate-based pre-operative targets to patient-specific thalamic segmentation utilizing a probabilistic tractography methodology.

METHODS

Using available diffusion MRI of 32 subjects from the Human Connectome Project database, probabilistic tractography was performed. Each thalamic voxel was coded based on one of six predefined cortical targets. The segmentation results were analyzed and compared to a 2-mm spherical target centered at the coordinate-based location of the ventral intermediate thalamic nucleus.

RESULTS

The traditional coordinate-based target had maximal overlap with the junction of the region most connected to primary motor cortex (M1) (36.6 ± 25.7% of voxels on left; 58.1 ± 28.5% on right) and the area connected to the supplementary motor area/premotor cortex (SMA/PMC) (44.9 ± 21.7% of voxels on left; 28.9 ± 22.2% on right). There was a within-subject coefficient of variation from right-to-left of 69.4 and 63.1% in the volume of overlap with the SMA/PMC and M1 regions, respectively.

CONCLUSION

Thalamic segmentation based on structural connectivity measures is a promising technique that may enhance traditional targeting methods by generating reproducible, patient-specific pre-operative functional targets. Our results highlight the problematic intra- and inter-subject variability of indirect, coordinate-based targets. Future prospective clinical studies will be needed to validate this targeting methodology in essential tremor patients.

Transcranial Alternating Current Stimulation (tACS) Mechanisms and Protocols

Perception, cognition and consciousness can be modulated as a function of oscillating neural activity, while ongoing neuronal dynamics are influenced by synaptic activity and membrane potential. Consequently, transcranial alternating current stimulation (tACS) may be used for neurological intervention. The advantageous features of tACS include the biphasic and sinusoidal tACS currents, the ability to entrain large neuronal populations, and subtle control over somatic effects. Through neuromodulation of phasic, neural activity, tACS is a powerful tool to investigate the neural correlates of cognition. The rapid development in this area requires clarity about best practices. Here we briefly introduce tACS and review the most compelling findings in the literature to provide a starting point for using tACS. We suggest that tACS protocols be based on functional brain mechanisms and appropriate control experiments, including active sham and condition blinding.

Variations in Thalamic Anatomy Affect Targeting in Deep Brain Stimulation for Epilepsy

BACKGROUND

Thalamic size and shape vary significantly across patients - with changes specific to the anterior thalamus occurring with age and in the setting of chronic epilepsy. Such ambiguity raises concerns regarding electrode position and potential implications for seizure outcomes.

METHODS

MRIs from 6 patients from a single center underwent quantitative analysis. In addition to direct measurements from postimplantation MRIs, the CRAnialVault Explorer suite was used to normalize electrode position to a common reference system. Relationships between thalamic dimensions, electrode location, and seizure outcome were analyzed.

RESULTS

Although this study group was too small to sufficiently power statistical analysis, general trends were identified. There was a trend towards smaller thalamic volumes in nonresponders. Electrode locations demonstrated more variation after normalization. There was a trend towards a more lateral, posterior, and inferior electrode position in nonresponders.

CONCLUSIONS

Variations in thalamic shape and volume necessitate direct targeting. Given that changes occur to thalamic anatomy with age and in the setting of epilepsy, improved methods for visualizing and targeting the anterior nucleus are necessary. Pronounced thalamic atrophy may preclude proper electrode placement and serve as a poor prognostic indicator. A greater understanding of thalamic anatomy and connectivity is necessary to optimize deep brain stimulation for epilepsy.

Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves

At rest, healthy human brain activity is characterized by large electroencephalography (EEG) fluctuations in the 8-13 Hz range, commonly referred to as the alpha band. Although it is well known that EEG alpha activity varies across individuals, few studies have investigated how this may be related to underlying morphological variations in brain structure. Specifically, it is generally believed that the lateral geniculate nucleus (LGN) and its efferent fibres (optic radiation, OR) play a key role in alpha activity, yet it is unclear whether their shape or size variations contribute to its inter-subject variability. Given the widespread use of EEG alpha in basic and clinical research, addressing this is important, though difficult given the problems associated with reliably segmenting the LGN and OR. For this, we employed a multi-modal approach and combined diffusion magnetic resonance imaging (dMRI), functional magnetic resonance imaging (fMRI) and EEG in 20 healthy subjects to measure structure and function, respectively. For the former, we developed a new, semi-automated approach for segmenting the OR and LGN, from which we extracted several structural metrics such as volume, position and diffusivity. Although these measures corresponded well with known morphology based on previous post-mortem studies, we nonetheless found that their inter-subject variability was not significantly correlated to alpha power or peak frequency (p >0.05). Our results therefore suggest that alpha variability may be mediated by an alternative structural source and our proposed methodology may in general help in better understanding the influence of anatomy on function such as measured by EEG or fMRI.

Proceedings of the Second Annual Deep Brain Stimulation Think Tank: What's in the Pipeline

The proceedings of the 2nd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, and computational work on DBS for the treatment of neurological and neuropsychiatric disease and represent the insights of a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers and members of industry. Presentations and discussions covered a broad range of topics, including advocacy for DBS, improving clinical outcomes, innovations in computational models of DBS, understanding of the neurophysiology of Parkinson's disease (PD) and Tourette syndrome (TS) and evolving sensor and device technologies.

Assessment of a method to determine deep brain stimulation targets using deterministic tractography in a navigation system

Recent advances in imaging permit radiologic identification of target structures for deep brain stimulation (DBS) for movement disorders. However, these methods cannot detect the internal subdivision and thus cannot determine the appropriate DBS target located within those subdivisions. The aim of this study is to provide a straightforward method to obtain an optimized target (OT) within DBS target nuclei using a widely available navigation system. We used T1- and T2-weighted images, fluid-attenuated inversion recovery (FLAIR) sequence, and diffusion tensor imaging (DTI) of nine patients operated for DBS in our center. Using the StealthViz® software, we segmented the targeted deep structures (subcortical targets) and the anatomically identifiable areas to which these target nuclei were connected (projection areas). We generated fiber tracts from the projection areas. By identifying their intersections with the subcortical targets, we obtained an OT within the DBS target nuclei. We computed the distances from the clinically effective electrode contacts (CEEC) to the OT obtained by our method and the targets provided by the atlas. These distances were compared using a Wilcoxon signed-rank test, with p < 0.05 considered statistically significant. We were able to identify OT coincident with the motor part of the subthalamic nucleus and the ventral intermediate nucleus. We clinically tested the results and found that the CEEC were significantly more closely related to the OT than with the targets obtained by the atlas. Our present results show that this novel method permits optimization of the stimulation site within the internal subdivisions of target nuclei for DBS.

Does Navigated Transcranial Stimulation Increase the Accuracy of Tractography? A Prospective Clinical Trial Based on Intraoperative Motor Evoked Potential Monitoring During Deep Brain Stimulation

BACKGROUND:

Tractography based on diffusion tensor imaging has become a popular tool for delineating white matter tracts for neurosurgical procedures.

OBJECTIVE:

To explore whether navigated transcranial magnetic stimulation (nTMS) might increase the accuracy of fiber tracking.

METHODS:

Tractography was performed according to both anatomic delineation of the motor cortex (n = 14) and nTMS results (n = 9). After implantation of the definitive electrode, stimulation via the electrode was performed, defining a stimulation threshold for eliciting motor evoked potentials recorded during deep brain stimulation surgery. Others have shown that of arm and leg muscles. This threshold was correlated with the shortest distance between the active electrode contact and both fiber tracks. Results were evaluated by correlation to motor evoked potential monitoring during deep brain stimulation, a surgical procedure causing hardly any brain shift.

RESULTS:

Distances to fiber tracks clearly correlated with motor evoked potential thresholds. Tracks based on nTMS had a higher predictive value than tracks based on anatomic motor cortex definition (P &lt; .001 and P = .005, respectively). However, target site, hemisphere, and active electrode contact did not influence this correlation.

CONCLUSION:

The implementation of tractography based on nTMS increases the accuracy of fiber tracking. Moreover, this combination of methods has the potential to become a supplemental tool for guiding electrode implantation.

The role of probabilistic tractography in the surgical treatment of thalamic gliomas

BACKGROUND

Thalamic gliomas represent a great challenge for neurosurgeons because of the high surgical risk of damaging the surrounding anatomy. Preoperative planning may considerably help the surgeon find the most ideal operative trajectory, avoiding thalamic nuclei and important white matter pathways adjacent to the tumor tissue. Thalamic segmentation is a promising imaging tool based on diffusion tensor magnetic resonance imaging. It provides the possibility to predict the relationship of the tumor to thalamic nuclei.

OBJECTIVE

To propose a new tool in thalamic glioma surgery that may help to differentiate between normal thalamus and tumor tissue, making preoperative planning possible and facilitating the choice of the optimal surgical approach and trajectory for neuronavigation-assisted surgery.

METHODS

Four patients with thalamic gliomas preoperatively underwent conventional and diffusion-weighted magnetic resonance imaging conducted on 1.5 T. Subsequently, probabilistic tractography and thalamic segmentation were performed with the FSL Software as preoperative planning. We also present a case when thalamic segmentation was applied retrospectively using preoperative images. All patients went through neuronavigation-assisted surgery (1 partial, 4 subtotal resections).

RESULTS

Surgery performed based on the output of thalamic segmentation caused no deterioration in the neurological symptoms of our patients. Indeed, we noticed improvement in the neurological condition in 3 cases; furthermore, in 2 patients, a concern-free state was achieved.

CONCLUSION

We suggest that thalamic segmentation may be applied successfully and routinely in the surgical treatment of thalamic gliomas.

Modulation of the Cerebello-Thalamo-Cortical Network in Thalamic Deep Brain Stimulation for Tremor

Background:

Deep brain stimulation alleviates tremor of various origins. Several regions like the ventralis intermediate nucleus of thalamus, the caudal zona incerta, and the posterior subthalamic region are generally targeted. Previous work with fiber tractography has shown the involvement of the cerebello-thalamo-cortical network in tremor control.

Objective:

To report the results of a prospective trial in a group of patients with tremor who underwent post hoc tractographic analysis after treatment with traditional thalamic deep brain stimulation.

Methods:

A total of 11 patients (aged 64 ± 17 years, 6 male) were enrolled (essential tremor [6], Parkinson tremor [3], and myoclonic tremor in myoclonus dystonia [2]). Patients received 1 (3 patients), 2 (7 patients), or 3 (1 patient) quadripolar electrodes. A 32-direction diffusion tensor magnetic resonance imaging sequence was acquired preoperatively. Tractography was processed postoperatively for evaluation and the dentato-rubro-thalamic tract (DRT) was individually tracked. Electrode positions were determined with helical computed tomography. Electric fields (EFs) were simulated according to individual stimulation parameters in a standardized atlas brain space (ICBM-MNI 152).

Results:

Tremor was reduced in all patients (69.4% mean) on the global (bilateral) tremor score. Effective contacts were located inside or in proximity to the DRT. In moderate tremor reduction (2 patients), the EFs were centered on its anterior border. In good and excellent tremor reduction (9 patients), EFs focused on its center.

Conclusion:

Deep brain stimulation of the cerebello-thalamo-cortical network reduces tremor. The DRT connects 3 traditional target regions for deep brain stimulation in tremor disease. Tractography techniques can be used to directly visualize the DRT and, therefore, optimize target definition in individual patients.

The variability of atlas-based targets in relation to surrounding major fibre tracts in thalamic deep brain stimulation

BACKGROUND

In essential tremor (ET), the main target for deep brain stimulation (DBS) is the thalamic ventralis intermedius nucleus (Vim). This target cannot be identified on conventional magnetic resonance imaging (MRI). Therefore, targeting depends on probabilistic coordinates derived from stereotactic atlases. The goal of our study was to investigate the variability of atlas-based Vim targets in relation to surrounding major fibre tracts.

METHODS

With the MRI and computed tomography (CT) scan data of ten patients who underwent DBS, we planned atlas based Vim targets in both hemispheres. We also performed deterministic fibre-tracking with diffusion tensor imaging (DTI) of the dentato-rubro-thalamic tract (DRTT), pyramidal tract (PT) and lemniscus medialis (LM) in all 20 hemispheres. Subsequently, we measured the distance from the atlas-based Vim target to each tract along the medial/lateral (x-coordinate), anterior/posterior (y-coordinate) and superior/inferior axis (z-coordinate).

RESULTS

Seventeen out of 20 DRTTs could be depicted with our standardised DTI/fibre-tracking parameters. The PT and the LM could be displayed in all 20 hemispheres. The atlas-based Vim target was found inside the DRTT in 11 (concerning the x-coordinate) and 10 hemispheres (concerning the z-coordinate). Regarding the anterior/posterior direction, the target was posterior to the DRTT in 11 cases. In 19 hemispheres the Vim target was located medial and superior to the PT and in 17 hemispheres posterior to it. Concerning the LM, the Vim target was found inside the LM in 16 (regarding the x-coordinate) and in 14 cases (regarding the z-coordinate). In eight cases it was located inside and in 12 cases anterior to the LM concerning the y-coordinate.

CONCLUSIONS

We found a considerable variability of the location of atlas-based target points of the ventralis intermedius nucleus in relation to neighbouring major fibre tracts in individual patients. These results suggest that individualised targeting to structures not directly visible on conventional MRI is necessary.

Averaging of diffusion tensor imaging direction-encoded color maps for localizing substantia nigra

Diffusion tensor imaging (DTI) is a form of MRI that has been used extensively to map in vivo the white matter architecture of the human brain. It is also used for mapping subcortical nuclei because of its general sensitivity to tissue orientation differences and effects of iron accumulation on the diffusion signal. While DTI provides excellent spatial resolution in individual subjects, a challenge is visualizing consistent patterns of diffusion orientation across subjects. Here we present a simple method for averaging direction-encoded color anisotropy maps in standard space, explore this technique for visualizing the substantia nigra (SN) in relation to other midbrain structures, and show with signal-to-noise analysis that averaging improves the direction-encoded color signature. SN is distinguished on averaged maps from neighboring structures, including red nucleus (RN) and cerebral crus, and is proximal to SN location from existing brain atlases and volume of interest (VOI) delineation on individual scans using two blinded raters.

Human thalamus regulates cortical activity via spatially specific and structurally constrained phase-amplitude coupling

Although the thalamus is believed to regulate and coordinate cortical activity both within and across functional regions, such as motor and visual cortices, direct evidence for such regulation and the mechanism of regulation remains poorly described. Using simultaneous invasive recordings of cortical and thalamic electrophysiological activity in 2 awake and spontaneously behaving human subjects, we provide direct evidence of thalamic regulation of cortical activity through a mechanism of phase-amplitude coupling (PAC), in which the phase of low frequency oscillations regulates the amplitude of higher frequency oscillations. Specifically, we show that cortical PAC between the theta phase and beta amplitude is spatially dependent on and time variant with the magnitude of thalamocortical theta coherence. Moreover, using causality analysis and MR diffusion tractography, we provide evidence that thalamic theta activity drives cortical theta oscillations and PAC across structures and that these thalamocortical relationships are structurally constrained by anatomic pathways. This relationship allows for new evidence of thalamocortical PAC. Given the diffuse connectivity of the thalamus with the cerebral cortex, thalamocortical PAC may play an important role in addressing the binding problem, including both integration and segregation of information within and across cortical areas.

The evolving role of diffusion magnetic resonance imaging in movement disorders

Significant advances have allowed diffusion magnetic resonance imaging (MRI) to evolve into a powerful tool in the field of movement disorders that can be used to study disease states and connectivity between brain regions. Diffusion MRI is a promising potential biomarker for Parkinson's disease and other forms of parkinsonism, and may allow the distinction of different forms of parkinsonism. Techniques such as tractography have contributed to our current thinking regarding the pathophysiology of dystonia and possible mechanisms of penetrance. Diffusion MRI measures could potentially assist in monitoring disease progression in Huntington's disease, and in uncovering the nature of the processes and structures involved the development of essential tremor. The ability to represent structural connectivity in vivo also makes diffusion MRI an ideal adjunctive tool for the surgical treatment of movement disorders. We review recent studies using diffusion MRI in movement disorders research and present the current state of the science as well as future directions.

The parcellation-based connectome: limitations and extensions

The human connectome is an intricate system of interconnected elements, providing the basis for integrative brain function. An essential step in the macroscopic mapping and examination of this network of structural and functional interactions is the subdivision of the brain into large-scale regions. Parcellation approaches used for the formation of macroscopic brain networks include application of predefined anatomical templates, randomly generated templates and voxel-based divisions. In this review, we discuss the use of such parcellation approaches for the examination of connectome characteristics. We specifically address the impact of the choice of parcellation scheme and resolution on the estimation of the brain's topological and spatial network features. Although organizational principles of functional and structural brain networks appear to be largely independent of the adopted parcellation approach, quantitative measures of these principles may be significantly modulated. Future parcellation-based connectome studies might benefit from the adoption of novel network tools and promising advances in connectivity-based parcellation approaches.

Mapping changes of in vivo connectivity patterns in the human mediodorsal thalamus: correlations with higher cognitive and executive functions

The mediodorsal thalamic nucleus is recognized as an association hub mediating interconnections with mainly the prefrontal cortex. Tracer studies in primates and in vivo diffusion tensor tractography findings in both humans and monkeys confirm its role in relaying networks that connect to the dorsolateral prefrontal, orbitofrontal, frontal medial and cingulate cortex. Our study was designed to use in vivo probabilistic tractography to describe the pathways emerging from or projecting to the mediodorsal nucleus; moreover, to use such information to automatically define subdivisions based on the divergence of remote structural connections. Diffusion tensor MR imaging data of 156 subjects were utilized to perform connectivity-based segmentation of the mediodorsal nucleus by employing a k-means clustering algorithm. Two domains were revealed (medial and lateral) that are separated from each other by a sagittally oriented plane. For each subject, general assessment of cognitive performance by means of the Wechsler Abbreviated Scale of Intelligence and measures of Delis-Kaplan Executive Function System (D-KEFS) test was utilized. Inter-subject variability in terms of connectivity-based cluster sizes was discovered and the relative sizes of the lateral mediodorsal domain correlated with the individuals' performance in the D-KEFS Sorting test (r = 0.232, p = 0.004). Our results show that the connectivity-based parcellation technique applied to the mediodorsal thalamic nucleus delivers a single subject level descriptor of connectional topography; furthermore, we revealed a possible weak interaction between executive performance and the size of the thalamic area from which pathways converge to the lateral prefrontal cortex.

Altered brain morphometry in carpal tunnel syndrome is associated with median nerve pathology

Objective

Carpal tunnel syndrome (CTS) is a common median nerve entrapment neuropathy characterized by pain, paresthesias, diminished peripheral nerve conduction velocity (NCV) and maladaptive functional brain neuroplasticity. We evaluated structural reorganization in brain gray matter (GM) and white matter (WM) and whether such plasticity is linked to altered median nerve function in CTS.

Methods

We performed NCV testing, T1-weighted structural MRI, and diffusion tensor imaging (DTI) in 28 CTS and 28 age-matched healthy controls (HC). Voxel-based morphometry (VBM) contrasted regional GM volume for CTS versus HC. Significant clusters were correlated with clinical metrics and served as seeds to define associated WM tracts using DTI data and probabilistic tractography. Within these WM tracts, fractional anisotropy (FA), axial (AD) and radial (RD) diffusivity were evaluated for group differences and correlations with clinical metrics.

Results

For CTS subjects, GM volume was significantly reduced in contralesional S1 (hand-area), pulvinar and frontal pole. GM volume in contralesional S1 correlated with median NCV. NCV was also correlated with RD and was negatively correlated with FA within U-fiber cortico-cortical association tracts identified from the contralesional S1 VBM seed.

Conclusions

Our study identified clear morphometric changes in the CTS brain. This central morphometric change is likely secondary to peripheral nerve pathology and altered somatosensory afference. Enhanced axonal coherence and myelination within cortico-cortical tracts connecting primary somatosensory and motor areas may accompany peripheral nerve deafferentation. As structural plasticity was correlated with NCV and not symptomatology, the former may be a better determinant of appropriate clinical intervention for CTS, including surgery.

Structural human brain networks: hot topics in diffusion tractography

PURPOSE OF REVIEW

After more than 10 years of methodological developments and clinical applications, diffusion imaging tractography has reached a crossroad. Although the method is still in its infancy, the time has come to address some important questions. Can tractography reproduce reliably known anatomy or describe new anatomical pathways? Are interindividual differences, for example in tract lateralization, important to understand heterogeneity of clinical manifestations? Do novel tractography algorithms provide a real advantage over previous methods? Here we focus on some of the most exciting recent advancements in diffusion tractography and critically highlight their advantages and limitations.

RECENT FINDINGS

A flourishing of diffusion methods and models are bringing new solutions to the well known limitations of classical tractography based on the tensor model. However, these methods pose also new challenges and require the convergence and integration of different disciplines before they can replace what is currently widely available.

SUMMARY

Rigorous postmortem validation, clinical optimization and experimental confirmation are obligatory steps before advanced diffusion technologies can translate into clear benefits for neurological patients.

Delineation of motor and somatosensory thalamic subregions utilizing probabilistic diffusion tractography and electrophysiology

PURPOSE

To employ and compare probabilistic diffusion tractography (PDT) for the explicit localization of connections from the thalamus to somatosensory cortex (S1) and primary motor cortex (M1) / supplementary motor area (SMA) with microelectrode electrophysiology in patients undergoing deep brain stimulation (DBS) surgery.

MATERIALS AND METHODS

These tractography-derived connections were used to categorize voxels in the thalamus as corresponding to sensory or motor physiology. A novel model (referred to in this work as the "mixture" model) to delineate PDT-based thalamic functional subregions by thresholding fiber intensities, ie, connectivity-defined regions (CDR), was devised. Regions created using this classification method were compared with the most commonly used model (referred to in this work as the "separation" or "winner takes all" model) for defining CDRs.

RESULTS

Electrophysiology data corresponded better for S1 CDRs created using the mixture model for both sensory and motor cells. Separation model CDRs showed poor correspondence against electrophysiology, with few sensory cells corresponding to the S1 separation model CDR.

CONCLUSION

Mixture model-based CDRs may offer a significant improvement in delineation of functional subregions of subcortical structures.

Connectivity-based structural and functional parcellation of the human cortex using diffusion imaging and tractography

The parcellation of the cortex via its anatomical properties has been an important research endeavor for over a century. To date, however, a universally accepted parcellation scheme for the human brain still remains elusive. In the current review, we explore the use of in vivo diffusion imaging and white matter tractography as a non-invasive method for the structural and functional parcellation of the human cerebral cortex, discussing the strengths and limitations of the current approaches. Cortical parcellation via white matter connectivity is based on the premise that, as connectional anatomy determines functional organization, it should be possible to segregate functionally-distinct cortical regions by identifying similarities and differences in connectivity profiles. Recent studies have provided initial evidence in support of the efficacy of this connectional parcellation methodology. Such investigations have identified distinct cortical subregions which correlate strongly with functional regions identified via fMRI and meta-analyses. Furthermore, a strong parallel between the cortical regions defined via tractographic and more traditional cytoarchitectonic parcellation methods has been observed. However, the degree of correspondence and relative functional importance of cytoarchitectonic- versus connectivity-derived parcellations still remains unclear. Diffusion tractography remains one of the only methods capable of visualizing the structural networks of the brain in vivo. As such, it is of vital importance to continue to improve the accuracy of the methodology and to extend its potential applications in the study of cognition in neurological health and disease.

Finding thalamic BOLD correlates to posterior alpha EEG

Oscillatory electrical brain activity in the alpha (8-13 Hz) band is a prominent feature of human electroencephalography (EEG) during alert wakefulness, and is commonly thought to arise primarily from the occipital and parietal parts of the cortex. While the thalamus is considered to play a supportive role in the generation and modulation of cortical alpha rhythms, its precise function remains controversial and incompletely understood. To address this, we evaluated the correlation between the blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) signals in the thalamus and the spontaneous modulation of posterior alpha rhythms based on EEG-fMRI data acquired concurrently during an eyes-closed task-free condition. We observed both negative and positive correlations in the thalamus. The negative correlations were mostly seen within the visual thalamus, with a preference for the pulvinar over lateral geniculate nuclei. The positive correlations were found at the anterior and medial dorsal nuclei. Through functional connectivity analysis of the fMRI data, the pulvinar was found to be functionally associated with the same widespread cortical visual areas where the fMRI signals were negatively correlated with the posterior alpha modulation. In contrast, the dorsal nuclei were part of a distinct functional network that included brain stem, cingulate cortex and cerebellum. These observations are consistent with previous animal electrophysiology studies and the notion that the visual thalamus, and the pulvinar in particular, is intimately involved in the generation and spontaneous modulation of posterior alpha rhythms, facilitated by its reciprocal and widespread interaction with the cortical visual areas. We further postulate that the anterior and medial dorsal nuclei, being part of the ascending neuromodulatory system, may indirectly modulate cortical alpha rhythms by affecting vigilance and arousal levels.