Deep brain stimulation (DBS) is a neurosurgical intervention where electrodes are permanently implanted into the brain in order to modulate pathologic neural activity. The post-operative reconstruction of the DBS electrodes is important for an efficient stimulation parameter tuning. A major limitation of existing approaches for electrode reconstruction from post-operative imaging that prevents the clinical routine use is that they are manual or semi-automatic, and thus both time-consuming and subjective. Moreover, the existing methods rely on a simplified model of a straight line electrode trajectory, rather than the more realistic curved trajectory. The main contribution of this paper is that for the first time we present a highly accurate and fully automated method for electrode reconstruction that considers curved trajectories. The robustness of our proposed method is demonstrated using a multi-center clinical dataset consisting of N = 44 electrodes. In all cases the electrode trajectories were successfully identified and reconstructed. In addition, the accuracy is demonstrated quantitatively using a high-accuracy phantom with known ground truth. In the phantom experiment, the method could detect individual electrode contacts with high accuracy and the trajectory reconstruction reached an error level below 100 μm (0.046 ± 0.025 mm). An implementation of the method is made publicly available such that it can directly be used by researchers or clinicians. This constitutes an important step towards future integration of lead reconstruction into standard clinical care.

Highlights d Developed the first holographic interface for building axonal pathways d Group-based interactive definition of axonal trajectories by neuroanatomists d Translation of decades of amassed knowledge into a 3D human axonal pathway atlas

OBJECTIVE Diffusion-weighted MRI (DWI) and tractography allows noninvasive mapping of the structural connections of the brain, and may provide important information for neurosurgical planning. The hyperdirect pathway, connecting the subthalamic nucleus (STN) with the motor cortex, is assumed to play a key role in mediating the effects of deep brain stimulation (DBS), which is an effective but poorly understood treatment for Parkinson disease. This study aimed to apply recent methodological advances in DWI acquisition and analysis to the delineation of the hyperdirect pathway in patients with Parkinson disease selected for surgery. METHODS High spatial and angular resolution DWI data were acquired preoperatively from 5 patients with Parkinson disease undergoing DBS. The authors compared the delineated hyperdirect pathways and associated STN target maps generated by 2 different tractography methods: a tensor-based deterministic method, typically available in clinical settings, and an advanced probabilistic method based on constrained spherical deconvolution. In addition, 10 high-resolution data sets with the same scanning parameters were acquired from a healthy control participant to assess the robustness of the tractography results. RESULTS Both tractography approaches identified connections between the ipsilateral motor cortex and the STN. However, the 2 methods provided substantially different target regions in the STN, with the target center of gravity differing by > 1.4 mm on average. The probabilistic method (based on constrained spherical deconvolution) plausibly reconstructed a continuous set of connections from the motor cortex, terminating in the dorsolateral region of the STN. In contrast, the tensor-based method reconstructed a comparatively sparser and more variable subset of connections. Furthermore, across the control scans, the probabilistic method identified considerably more consistent targeting regions within the STN compared with the deterministic tensor-based method, which demonstrated a 1.9-2.4 times higher variation. CONCLUSIONS These data provide a strong impetus for the use of a robust probabilistic tractography framework based on constrained spherical deconvolution, or similar advanced DWI models, in clinical settings. The inherent limitations and demonstrated inaccuracy of the tensor-based method leave it questionable for use in high-precision stereotactic DBS surgery. The authors have also described a straightforward method for importing tractography-derived information into any clinical neuronavigation system, based on the generation of track-density images.

The transition to motherhood, and the resultant experience of caregiving, may change the way women respond to affective, infant signals in their environments. Nonhuman animal studies have robustly demonstrated that mothers process both infant and other salient signals differently from nonmothers. Here, we investigated how women with and without young infants respond to vocalisations from infants and adults (both crying and neutral). We examined mothers with infants ranging in age (1–14 months) to examine the effects of duration of maternal experience. Using functional magnetic resonance imaging, we found that mothers showed greater activity than nonmothers to vocalisations from adults or infants in a range of cortical regions implicated in the processing of affective auditory cues. This main effect of maternal status suggests a general difference in vocalisation processing across infant and adult sounds. We found that a longer duration of motherhood, and therefore more experience with an infant, was associated with greater infant-specific activity in key parental brain regions, including the orbitofrontal cortex and amygdala. We suggest that these incremental differences in neural activity in the maternal brain reflect the building of parental capacity over time. This is consistent with conceptualizations of caregiving as a dynamic, learning process in humans.

Overall we find that volBrain is superior in thalamus and hippocampus segmentation compared to FSL, FreeSurfer and SPM. Furthermore, the choice of segmentation technique and training library affects quantitative results from diffusivity measures in thalamus and hippocampus.

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Worsening of verbal fluency after treatment with deep brain stimulation in Parkinson's disease patients is one of the most often reported cognitive adverse effect. The underlying mechanisms of this decline are not well understood. The present focused review assesses the evidence for the reliability of the often-reported decline of verbal fluency, as well as the evidence for the suggested mechanisms including disease progression, reduced medication levels, electrode positions, and stimulation effect vs. surgical effects. Finally, we highlight the need for more systematic investigations of the large degree of heterogeneity in the prevalence of verbal fluency worsening after DBS, as well as provide suggestions for future research.

Objectives Parkinson's disease (PD) commonly affects visuospatial navigation causing postural instability and falls. Our overarching aim was to examine the visual and vestibular systems governing visuospatial navigation in PD. We hypothesize that PD affects vestibular and visual motion perception but to a different extent. The effects of PD on motion perception are dependent on the severity of the disease. Methods The two‐alternative‐forced‐choice task objectively measured the motion perception during two experiments. One experiment examined the vestibular motion perception with en bloc movement of the platform. The second experiment tested the visual motion perception using an immersive virtual reality goggle. Results We found that accuracy, threshold, and precision of vestibular perception were more impaired in advanced‐PD patients compared to those with a mild form of the disease. The parameters also correlated with the disease duration, overall axial motor impairment causing postural instability and falls, and subjective rating of the balance function. Such changes were present but less severe in visual motion perception. Conclusion We conclude that PD affects motion perception in the visual and vestibular domains in a severity‐dependent manner. The impact of the disease in the vestibular domain is more severe compared to the visual domain. © 2020 International Parkinson and Movement Disorder Society