The speed of high-resolution optical imaging has been a rate-limiting factor for meso-scale mapping of brain structures and functional circuits, which is of fundamental importance for neuroscience research. Here, we describe a new microscopy method of Volumetric Imaging with Synchronized on-the-fly-scan and Readout (VISoR) for high-throughput, high-quality brain mapping. Combining synchronized scanning beam illumination and oblique imaging over cleared tissue sections in smooth motion, the VISoR system effectively eliminates motion blur to obtain undistorted images. By continuously imaging moving samples without stopping, the system achieves high-speed 3D image acquisition of an entire mouse brain within 1.5 hours, at a resolution capable of visualizing synaptic spines. A pipeline is developed for sample preparation, imaging, 3D image reconstruction and quantification. Our approach is compatible with immunofluorescence methods, enabling flexible cell-type specific brain mapping and is readily scalable for large biological samples such as primate brains. Using this system, we examined behaviorally relevant whole-brain neuronal activation in 16 c-Fos-shEGFP mice under resting or forced swimming conditions. Our results indicate the involvement of multiple subcortical areas in stress response. Intriguingly, neuronal activation in these areas exhibits striking individual variability among different animals, suggesting the necessity of sufficient cohort size for such studies.

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Artificial sensors on the skin are proposed as a way to capture information that can be used in intracortical microstimulation or peripheral intraneural stimulation to restore sensory feedback to persons with tetraplegia. However, the ability of these artificial sensors to replicate the density and complexity of the natural mechanoreceptors is limited. One relatively unexplored approach is to make use of the signals from surviving tactile and proprioceptive receptors in existing limbs by recording from their transmitting axons within the primary sensory nerves. Here, a novel spiked ultraflexible neural (SUN) interface that is implanted into the peripheral nervous system to capture sensory information from these mechanoreceptors in acute rat experiments is described. The novel 3D design, which integrates spiked structures for intrafascicular nerve recording with an ultraflexible substrate, enables a unique conformal interface to the target nerve. With the high-quality recording (average signal-to-noise-ratio of 1.4) provided by the electrode, tactile from proprioceptive stimuli can be differentiated in terms of the firing rate. In toe pinching experiments, high spatial resolution classification can be achieved with support vector machine classifier. Further work remains to be done to assess the chronic recording capability of the SUN interface.

Strabismic amblyopia is now acknowledged to be more than a simple loss of acuity and to involve alterations in visually driven attention, though whether this applies to both stimulus-driven and goal-directed attention has not been explored. Hence we investigated monocular threshold performance during a motion salience-driven attention task involving detection of a coherent dot motion target in one of four quadrants in adult controls and those with strabismic amblyopia. Psychophysical motion thresholds were impaired for the strabismic amblyopic eye, requiring longer inspection time and consequently slower target speed for detection compared to the fellow eye or control eyes. We compared fMRI activation and functional connectivity between four ROIs of the occipital-parieto-frontal visual attention network [primary visual cortex (V1), motion sensitive area V5, intraparietal sulcus (IPS) and frontal eye fields (FEF)], during a suprathreshold version of the motion-driven attention task, and also a simple goal-directed task, requiring voluntary saccades to targets randomly appearing along a horizontal line. Activation was compared when viewed monocularly by controls and the amblyopic and its fellow eye in strabismics. BOLD activation was weaker in IPS, FEF and V5 for both tasks when viewing through the amblyopic eye compared to viewing through the fellow eye or control participants' non-dominant eye. No difference in V1 activation was seen between the amblyopic and fellow eye, nor between the two eyes of control participants during the motion salience task, though V1 activation was significantly less through the amblyopic eye than through the fellow eye and control group non-dominant eye viewing during the voluntary saccade task. Functional correlations of ROIs within the attention network were impaired through the amblyopic eye during the motion salience task, whereas this was not the case during the voluntary saccade task. Specifically, FEF showed reduced functional connectivity with visual cortical nodes during the motion salience task through the amblyopic eye, despite suprathreshold detection performance. This suggests that the reduced ability of the amblyopic eye to activate the frontal components of the attention networks may help explain the aberrant control of visual attention and eye movements in amblyopes.

A BS TRACT: Background: Subthalamic deep brain stimulation (STN DBS) may relieve refractory motor complications in Parkinson's disease (PD) patients. Despite careful screening, it remains difficult to determine severity of alpha-synucleinopathy involvement which influences the risk of postoperative complications including cognitive deterioration. Quantitative electroencephalography (qEEG) reflects cognitive dysfunction in PD and may provide biomarkers of postoperative cognitive decline. Objective: To develop an automated machine learning model based on preoperative EEG data to predict cognitive deterioration 1 year after STN DBS. Methods: Sixty DBS candidates were included; 42 patients had available preoperative EEGs to compute a fully automated machine learning model. Movement Disorder Society criteria classified patients as cognitively stable or deteriorated at 1-year follow-up. A total of 16,674 EEG-features were extracted per patient; a Boruta algorithm selected EEG-features to reflect representative neurophysiological signatures for each class. A random forest classifier with 10-fold cross-validation with Bayesian optimization provided class-differentiation.Results: Tweny-five patients were classified as cognitively stable and 17 patients demonstrated cognitive decline. The model differentiated classes with a mean (SD) accuracy of 0.88 (0.05), with a positive predictive value of 91.4% (95% CI 82.9, 95.9) and negative predictive value of 85.0% (95% CI 81.9, 91.4). Predicted probabilities between classes were highly differential (hazard ratio 11.14 [95% CI 7.25, 17.12]); the risk of cognitive decline in patients with high probabilities of being prognosticated as cognitively stable (>0.5) was very limited. Conclusions: Preoperative EEGs can predict cognitive deterioration after STN DBS with high accuracy. Cortical neurophysiological alterations may indicate future cognitive decline and can be used as biomarkers during the DBS screening.

PurposeThe purpose of this paper is to explore the task design and assignment of full-text generation on mass Chinese historical archives (CHAs) by crowdsourcing, with special attention paid to how to best divide full-text generation tasks into smaller ones assigned to crowdsourced volunteers and to improve the digitization of mass CHAs and the data-oriented processing of the digital humanities.Design/methodology/approachThis paper starts from the complexities of character recognition of mass CHAs, takes Sheng Xuanhuai archives crowdsourcing project of Shanghai Library as a case study, and makes use of the theories of archival science, including diplomatics of Chinese archival documents, and the historical approach of Chinese archival traditions as the theoretical basis and analysis methods. The results are generated through the comprehensive research.FindingsThis paper points out that volunteer tasks of full-text generation include transcription, punctuation, proofreading, metadata description, segmentation, and attribute annotation in digital humanities and provides a metadata element set for volunteers to use in creating or revising metadata descriptions and also provides an attribute tag set. The two sets can be used across the humanities to construct overall observations about texts and the archives of which they are a part. Along these lines, this paper presents significant insights for application in outlining the principles, methods, activities, and procedures of crowdsourced full-text generation for mass CHAs.Originality/valueThis study is the first to explore and identify the effective design and allocation of tasks for crowdsourced volunteers completing full-text generation on CHAs in digital humanities.

Background: Studies have implicated hypofrontality in the pathogenesis of impaired theory of mind (ToM) and executive function (EF) in major depressive disorder (MDD). These symptoms are usually resistant to treatment. Repetitive transcranial magnetic stimulation (rTMS) has been shown to reverse hypofrontality. Moreover, BDNF is an effective biomarker of antidepressant effects, but there have been very few studies on the correlation between BDNF and rTMS. We aimed to evaluate the efficacy of 20 sessions of a 10 Hz unilateral rTMS intervention over the left dorsolateral prefrontal cortex (DLPFC) in improving ToM and EF in patients with MDD and its correlation with BDNF. Methods: A total of 120 MDD patients were enrolled in this randomized, sham-controlled, double-blind trial. Each participant received 20 sessions of rTMS at 10 Hz frequency through the active or the sham coil over 4 weeks. ToM was assessed with the facial emotion identification test (FEIT) and hinting task (HT). EF was assessed with the Wisconsin card sorting test (WCST). BDNF assessments were carried out at baseline and 2-, 4-, 12-, and 24-week follow-ups. Results: The improvement in the ToM (FEIT, HT) in the active rTMS group was significantly different from that in the sham rTMS group (F = 18.09, p < 0.001; F = 5.02, p = 0.026). There were significant differences in the WCST (categories completed, response errors, response perseverative errors, non-response perseverative errors) after logarithmic transformation at different time points in the active rTMS group (F = 14.71, p < 0.001; F = 5.99, p = 0.046; F = 8.90, p = 0.031; F = 2.31, p = 0.048). However, there was no significant difference in log transformed BDNF concentration between the two groups (t = 0.07 to t = 1.29, p > 0.05). BDNF was negatively correlated with WCST categories completed at the 24th week (r = −0.258, p = 0.046). Conclusions: The results show that rTMS may improve the ToM and EF of patients with MDD and there was no significant correlation with serum BDNF concentration. RTMS can not only be used for treatment of patients with MDD but also has a positive effect on ToM and EF.

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