The right intraparietal sulcus (rIPS) is a key region for the endogenous control of selective visual attention in the human brain. Previous studies suggest that the rIPS is especially involved in top-down control and spatial distribution of attention across both visual hemifields. We further explored these attentional functions using transcranial direct current stimulation (tDCS) of the rIPS to modulate behavioral performance in a partial report task. Performance was analyzed according to the theory of visual attention (TVA) (Bundesen, 1990), which provides a computational framework to investigate different parameters of visuo-attentional processing such as top-down control, attentional weighting, capacity of visual short term memory, and processing speed. We investigated the effects of different tDCS current strengths (1 mA and 2 mA) in two experiments: 1 mA tDCS (anodal, cathodal, sham) did not affect any of the TVA parameters, but cathodal 2 mA stimulation significantly enhanced top-down control as evidenced by a reduction of the ␣ parameter of TVA, regardless of hemifield. This differential impact on the top-down control component of attentional processing suggests that the horizontal rIPS is mainly involved in attentional selection as none of the spatial or resource variables of TVA were altered. Furthermore, the data add evidence to previous work highlighting (1) the importance of using appropriate current strength in stimulation protocols, and (2) that the often reported inhibitory effect of cathodal stimulation in e.g., motor tasks might not extend to cognitive paradigms.

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Image-based machine learning tools hold great promise for clinical applications in nephropathology and kidney research. However, the ideal end-users of these computational tools (e.g., pathologists and biological scientists) often face prohibitive challenges in using these tools to their full potential, including the lack of technical expertise, suboptimal user interface, and limited computation power. We have developed Histo-Cloud, a tool for segmentation of whole slide images (WSIs) that has an easy-to-use graphical user interface. This tool runs a state-of-the-art convolutional neural network (CNN) for segmentation of WSIs in the cloud and allows the extraction of features from segmented regions for further analysis. By segmenting glomeruli, interstitial fibrosis and tubular atrophy, and vascular structures from renal and non-renal WSIs, we demonstrate the scalability, best practices for transfer learning, and effects of dataset variability. Finally, we demonstrate an application for animal model research, analyzing glomerular features in murine models of aging, diabetic nephropathy, and HIV associated nephropathy. The ability to access this tool over the internet will facilitate widespread use by computational non-experts. Histo-Cloud is open source and adaptable for segmentation of any histological structure regardless of stain. Histo-Cloud will greatly accelerate and facilitate the generation of datasets for machine learning in the analysis of kidney histology, empowering computationally novice end-users to conduct deep feature analysis of tissue slides.

Gesture processing deficits constitute a key symptom of apraxia, a disorder of motor cognition frequently observed after left-hemispheric stroke. The clinical relevance of apraxia stands in stark contrast to the paucity of therapeutic options available. Transcranial direct current stimulation (tDCS) is a promising tool for modulating disturbed network function after stroke. Here, we investigate the effect of parietal tDCS on gesture processing in healthy human subjects. Neuropsychological and imaging studies suggest that the imitation and matching of hand gestures involve the left inferior parietal lobe (IPL). Using neuronavigation based on cytoarchitectonically defined anatomical probability maps, tDCS was applied over left IPL-areas PF, PFm, or PG in healthy participants (n ϭ 26). Before and after tDCS, subjects performed a gesture matching task and a person discrimination task for control. Changes in error rates and reaction times were analyzed for the effects of anodal and cathodal tDCS (compared with sham tDCS). Matching of hand gestures was specifically facilitated by anodal tDCS applied over the cytoarchitectonically defined IPL-area PFm, whereas tDCS over IPL-areas PF and PG did not elucidate significant effects. Taking into account tDCS electrode size and the central position of area PFm within IPL, it can be assumed that the observed effect is rather the result of a combined stimulation of the supramarginal and angular gyrus than an isolated PFm stimulation. Our data confirm the pivotal role of the left IPL in gesture processing. Furthermore, anatomically guided tDCS of the left IPL may constitute a promising approach to neurorehabilitation of apraxic patients with gesture processing deficits.