Differences in the horizontal positions of retinal images-binocular disparity-provide important cues for three-dimensional object recognition and manipulation. We investigated the neural coding of three-dimensional shape defined by disparity in anterior intraparietal (AIP) area. Robust selectivity for disparity-defined slanted and curved surfaces was observed in a high proportion of AIP neurons, emerging at relatively short latencies. The large majority of AIP neurons preserved their three-dimensional shape preference over different positions in depth, a hallmark of higher-order disparity selectivity. Yet both stimulus type (concave-convex) and position in depth could be reliably decoded from the AIP responses. The neural coding of three-dimensional shape was based on first-order (slanted surfaces) and second-order (curved surfaces) disparity selectivity. Many AIP neurons tolerated the presence of disparity discontinuities in the stimulus, but the population of AIP neurons provided reliable information on the degree of curvedness of the stimulus. Finally, AIP neurons preserved their three-dimensional shape preference over different positions in the frontoparallel plane. Thus, AIP neurons extract or have access to three-dimensional object information defined by binocular disparity, consistent with previous functional magnetic resonance imaging data. Unlike the known representation of three-dimensional shape in inferior temporal cortex, the neural representation in AIP appears to emphasize object parameters required for the planning of grasping movements.

Temporal cortical neurons are known to respond to visual dynamic-action displays. Many human psychophysical and functional imaging studies examining biological motion perception have used treadmill walking, in contrast to previous macaque single-cell studies. We assessed thecodingoflocomotioninrhesusmonkey(Macacamulatta)temporalcortexusingmoviesofstationarywalkers,varyingbothformandmotion (i.e.,differentfacingdirections)orvaryingonlytheframesequence(i.e.,forwardvsbackwardwalking).Themajorityofsuperiortemporalsulcus and inferior temporal neurons were selective for facing direction, whereas a minority distinguished forward from backward walking. Support vector machines using the temporal cortical population responses as input classified facing direction well, but forward and backward walking less so. Classification performance for the latter improved markedly when the within-action response modulation was considered, reflecting differences in momentary body poses within the locomotion sequences. Responses to static pose presentations predicted the responses during the course of the action. Analyses of the responses to walking sequences wherein the start frame was varied across trials showed that some neurons also carried a snapshot sequence signal. Such sequence information was present in neurons that responded to static snapshot presentationsandinneuronsthatrequiredmotion.Ourdatasuggestthatactionsareanalyzedbytemporalcorticalneuronsusingdistinctmechanisms. Most neurons predominantly signal momentary pose. In addition, temporal cortical neurons, including those responding to static pose, are sensitive to pose sequence, which can contribute to the signaling of learned action sequences.

Before considering using eHealth technology in clinical practice, professionals should always check whether patients are familiar with using information and communication technology, and whether they are willing to use technology for health-related purposes.

Objects vary not only in their shape but also in the material from which they are made. Knowledge of the material properties can contribute to object recognition as well as indicate properties of the object (e.g. ripeness of a fruit). We examined the coding of images of materials by single neurons of the macaque inferior temporal (IT) cortex, an area known to support object recognition and categorization. Stimuli were images of 12 real materials that were illuminated from three different directions. The material textures appeared within five different outline shapes. The majority of responsive IT neurons responded selectively to the material textures, and this selectivity was largely independent of their shape selectivity. The responses of the large majority of neurons were strongly affected by illumination direction. Despite the generally weak illumination-direction invariance of the responses, Support Vector Machines that used the neural responses as input were able to classify the materials across illumination direction better than by chance. A comparison between the responses to the original images and those to images with a random spectral phase, but matched power spectrum, indicated that the material texture selectivity did not depend merely on differences in the power spectrum but required phase information.

This paper presents the NeuroSelect software for managing the electronic depth control of cerebral CMOS-based microprobes for extracellular in vivo recordings. These microprobes contain up to 500 electronically switchable electrodes which can be appropriately selected with regard to specific neuron locations in the course of a recording experiment. NeuroSelect makes it possible to scan the electrodes electronically and to (re)select those electrodes of best signal quality resulting in a closed-loop design of a neural acquisition system. The signal quality is calculated by the relative power of the spikes compared with the background noise. The spikes are detected by an adaptive threshold using a robust estimator of the standard deviation. Electrodes can be selected in a manual or semi-automatic mode based on the signal quality. This electronic depth control constitutes a significant improvement for multielectrode probes, given that so far the only alternative has been the fine positioning by mechanical probe translation. In addition to managing communication with the hardware controller of the probe array, the software also controls acquisition, processing, display and storage of the neural signals for further analysis.

Traditional quantitative and qualitative research methods inadequately capture the complexity of patients' daily self-management. Contextual inquiry methodology, using home visits, allows a more in-depth understanding of how patients integrate immunosuppressive medication intake, physical activity, and healthy eating in their daily lives, and which difficulties they experience when doing so. This mixed-method study comprised 2 home visits in 19 purposively selected adult heart, lung, liver, and kidney transplant patients, asking them to demonstrate how they implement the aforementioned health behaviors. Meanwhile, conversations were audio-taped and photographs were taken. Audio-visual materials were coded using directed content analysis. Difficulties and supportive strategies were identified via inductive thematic analysis. We learned that few patients understood what "sufficiently active" means. Physical discomforts and poor motivation created variation across activity levels observed. Health benefits of dietary guidelines were insufficiently understood, and their implementation into everyday life considered difficult. Many underestimated the strictness of immunosuppressive medication intake, and instructions on handling late doses were unclear. Interruptions in routine and busyness contributed to nonadherence. We also learned that professionals often recommend supportive strategies, which patients not always like or need. This contextual inquiry study revealed unique insights, providing a basis for patient-tailored self-management interventions.

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