Neuroanatomy education is a challenging field which could benefit from modern innovations, such as augmented reality (AR) applications. This study investigates the differences on test scores, cognitive load, and motivation after neuroanatomy learning using AR applications or using cross-sections of the brain. Prior to two practical assignments, a pretest (extended matching questions, double-choice questions and a test on cross-sectional anatomy) and a mental rotation test (MRT) were completed. Sex and MRT scores were used to stratify students over the two groups. The two practical assignments were designed to study (1) general brain anatomy and (2) subcortical structures. Subsequently, participants completed a posttest similar to the pretest and a motivational questionnaire. Finally, a focus group interview was conducted to appraise participants' perceptions. Medical and biomedical students (n = 31); 19 males (61.3%) and 12 females (38.7%), mean age 19.2 ± 1.7 years participated in this experiment. Students who worked with cross-sections (n = 16) showed significantly more improvement on test scores than students who worked with GreyMapp-AR (P = 0.035) (n = 15). Further analysis showed that this difference was primarily caused by significant improvement on the cross-sectional questions. Students in the cross-section group, moreover, experienced a significantly higher germane (P = 0.009) and extraneous cognitive load (P = 0.016) than students in the GreyMapp-AR group. No significant differences were found in motivational scores. To conclude, this study suggests that AR applications can play a role in future anatomy education as an add-on educational tool, especially in learning three-dimensional relations of anatomical structures. Anat Sci Educ 13: 350-362.

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Classic anatomical atlases depict a contralateral hemispheral representation of each side of the face. Recently, however, a bilateral projection of each hemiface was hypothesized, based on animal studies that showed the coexistence of an additional trigeminothalamic tract sprouting from the trigeminal principal sensory nucleus that ascends ipsilaterally. This study aims to provide an anatomical substrate for the hypothesized bilateral projection. Three post-mortem human brainstems were scanned for anatomical and diffusion magnetic resonance imaging at 11.7T. The trigeminal tracts were delineated in each brainstem using track density imaging (TDI) and tractography. To evaluate the reconstructed tracts, the same brainstems were sectioned for polarized light imaging (PLI). Anatomical 11.7T MRI shows a dispersion of the trigeminal tract ( tt ) into a ventral and dorsal portion. This bifurcation was also seen on the TDI maps, tractography results and PLI images of all three specimens. Referring to a similar anatomic feature in primate brains, the dorsal and ventral tracts were named the dorsal and ventral trigeminothalamic tract ( dtt and vtt ), respectively. This study shows that both the dtt and vtt are present in humans, indicating that each hemiface has a bilateral projection, although the functional relevance of these tracts cannot be determined by the present anatomical study. If both tracts convey noxious stimuli, this could open up new insights into and treatments for orofacial pain in patients.

Orofacial pain in patients relies on the anatomical pathways that conduct nociceptive information, originating from the periphery towards the trigeminal sensory nucleus complex (TSNC) and finally, to the thalami and the somatosensorical cortical regions. The anatomy and function of the so-called trigeminothalamic tracts have been investigated before. In these animal-based studies from the previous century, the intracerebral pathways were mapped using different retro- and anterograde tracing methods. We review the literature on the trigeminothalamic tracts focusing on these animal tracer studies. Subsequently, we related the observations of these studies to clinical findings using fMRI trials. The intracerebral trigeminal pathways can be subdivided into three pathways: a ventral (contralateral) and dorsal (mainly ipsilateral) trigeminothalamic tract and the intranuclear pathway. Based on the reviewed evidence we hypothesize the co-existence of an ipsilateral nociceptive conduction tract to the cerebral cortex and we translate evidence from animal-based research to the human anatomy. Our hypothesis differs from the classical idea that orofacial pain arises only from nociceptive information via the contralateral, ventral trigeminothalamic pathway. Better understanding of the histology, anatomy and connectivity of the trigeminal fibers could contribute to the discovery of a more effective pain treatment in patients suffering from various orofacial pain syndromes.

BACKGROUND Predicting outcome after aneurysmal subarachnoid hemorrhage (aSAH) is known to be challenging and complex. Machine learning approaches, of which feedforward artificial neural networks (ffANNs) are the most widely used, could contribute to the patient-specific outcome prediction. OBJECTIVE To investigate the prediction capacity of an ffANN for the patient-specific clinical outcome and the occurrence of delayed cerebral ischemia (DCI) and compare those results with the predictions of 2 internationally used scoring systems. METHODS A prospective database was used to predict (1) death during hospitalization (ie, mortality) (n = 451), (2) unfavorable modified Rankin Scale (mRS) at 6 mo (n = 413), and (3) the occurrence of DCI (n = 362). Additionally, the predictive capacities of the ffANN were compared to those of Subarachnoid Haemorrhage International Trialists (SAHIT) and VASOGRADE to predict clinical outcome and occurrence of DCI. RESULTS The area under the curve (AUC) of the ffANN showed to be 88%, 85%, and 72% for predicting mortality, an unfavorable mRS, and the occurrence of DCI, respectively. Sensitivity/specificity rates of the ffANN for mortality, unfavorable mRS, and the occurrence of DCI were 82%/80%, 94%/80%, and 74%/68%. The ffANN and SAHIT calculator showed similar AUCs for predicting personalized outcome. The presented ffANN and VASOGRADE were found to perform equally with regard to personalized prediction of occurrence of DCI. CONCLUSION The presented ffANN showed equal performance when compared with VASOGRADE and SAHIT scoring systems while using less individual cases. The web interface launched simultaneously with the publication of this manuscript allows for usage of the ffANN-based prediction tool for individual data (https://nutshell-tool.com/).