No abstract

The macaque medial superior temporal area (MST) is proposed to be specialized for analyzing complex 'optic flow' information. Such space-varying motion patterns provide a rich source of information about self motion, scene structure and object shape. We report the performance of rhesus macaques on a two-alternative 'heading' task, in which they reported whether horizontally varying, simulated trajectories were to left or right of center. Monkeys were sensitive to small heading angles; thresholds averaged 1.5-3 degrees. Heading estimates were stable in the face of changing stimulus location and smooth pursuit eye movements. In addition, we tested the role of area MST in heading judgements by electrically activating columns of neurons in this area while the monkeys performed the heading task. Activation of MST frequently affected performance, usually causing choice biases. These induced biases were often large and usually concordant with the preference of the neurons being activated. In addition, the induced biases were often larger in the presence of smooth pursuit eye movements. These results favor the hypothesis that MST is involved in recovering self-motion direction from optic flow cues and in the process by which heading perception is compensated for ongoing eye movements.

In many sensory systems, exposure to a prolonged stimulus causes adaptation, which tends to reduce neural responses to subsequent stimuli. Such effects are usually stimulus-specific, making adaptation a powerful probe into information processing. We used dynamic random dot kinematograms to test the magnitude and selectivity of adaptation effects in the middle temporal area (MT) and to compare them to effects on human motion discrimination. After 3 s of adaptation to a random dot pattern moving in the preferred direction, MT neuronal responses to subsequent test patterns were reduced by 26% on average compared with adaptation to a static pattern. This reduction in response magnitude was largely independent of what test stimulus was presented. However, adaptation in the opposite direction changed responses less often and very inconsistently. Therefore motion adaptation systematically and profoundly affects the neurons in MT representing the adapted direction, but much less those representing the opposite direction. In human psychophysical experiments, such adapting stimuli affected direction discrimination, biasing choices away from the adaptation direction. The magnitude of this perceptual shift was consistent with the magnitude of the changes seen in area MT, if one assumes that a motion comparison step occurs after MT.

Abstract. Recent advances in smart glasses, wearable computers in the form of glasses, bring new therapeutic and monitoring possibilities for people with Parkinson's disease (PD). For example, it can provide visual and auditory cues during activities of daily living that have long been used to improve gait disturbances. Furthermore, smart glasses can personalize therapies based on the state of the user and/or the user environment in real-time using object recognition and motion tracking. To provide guidelines for developers in creating new PD applications for smart glasses, a self-reported questionnaire was designed to survey the requirements, constraints, and attitudes of people with PD with respect to this new technology. The survey was advertised online over an 11 month period on the website of the Parkinson Vereninging. The results were derived from 62 participants (54.8% men and 45.2% women, average age of 65.7 ± 9.1), representing a response rate of 79.5%. The participants were overall very enthusiastic about smart glasses as an assistive technology to facilitate daily living activities, especially its potential to selfmanage motor problems and provide navigational guidance, thereby restoring their confidence and independence. The reported level of usage of mobile technologies like tablets and smartphones suggests that smart glasses could be adopted relatively easily, especially by younger people with PD. However, the respondents were concerned about the cost, appearance, efficacy, and potential side effects of smart glasses. To accommodate a wide range of symptoms, personal preferences, and comfort level with technology, smart glasses should be designed to allow simple operation and personalization.

Toll-like receptors (TLRs) are part of the innate immune system and can initiate an immune response upon exposure to harmful microorganisms. Neuronal TLRs are considered to be part of an established framework of interactions between the immune system and the nervous system, the major sensing systems in mammals. TLRs in the nervous system and neuronal TLRs are suspected to be important during inflammation and neurodegenerative diseases. The aim of this review is to offer an overview of the current knowledge about TLRs in neurodegenerative pathologies, with a focus on Parkinson's disease. More research focusing on the role of TLRs in health and disease of the nervous system is needed and remains to be explored.

The current study investigates if early visual cortical areas, V1, V2 and V3, use predictive coding to process motion information. Previous studies have reported biased visual motion responses at locations where novel visual information was presented (i.e., the motion trailing edge), which is plausibly linked to the predictability of visual input. Using high-field functional magnetic resonance imaging (fMRI), we measured brain activation during predictable versus unpreceded motion-induced contrast changes during several motion stimuli. We found that unpreceded moving dots appearing at the trailing edge gave rise to enhanced BOLD responses, whereas predictable moving dots at the leading edge resulted in suppressed BOLD responses. Furthermore, we excluded biases in directional sensitivity, shifts in cortical stimulus representation, visuo-spatial attention and classical receptive field effects as viable alternative explanations. The results clearly indicate the presence of predictive coding mechanisms in early visual cortex for visual motion processing, underlying the construction of stable percepts out of highly dynamic visual input.

Magnetic drug delivery is a promising method to target a drug to a diseased area while reducing negative side effects caused by systemic administration of drugs. In magnetic drug delivery a therapeutic agent is coupled to a magnetic nanoparticle. The particles are injected and at the target location withdrawn from blood flow by a magnetic field. In this study a FePd nanowire is developed with optimised properties for magnetic targeting. The nanowires have a high magnetic moment to reduce the field gradient needed to capture them with a magnet. The dimensions and the materials of the nanowire and coating are such that they are dispersable in aqueous media, non-cytotoxic, easily phagocytosed and not complement activating. This is established in several in-vitro tests with macrophage and endothelial cell lines.Along with the nanowires a magnet is designed, optimised for capture of the nanowires from the blood flow in the hind leg of a rat. The system is used in a pilot scale in-vivo experiment. No negative side effects from injection of the nanowires were found within the limited time span of the experiment. In this first pilot experiment no nanowires were found to be targeted by the magnet, or in the liver, kidneys or spleen, most likely the particles were removed during the fixation procedure.

Neural prosthetics may provide a promising solution to restore visual perception in some forms of blindness. The restored prosthetic percept is rudimentary compared to normal vision and can be optimized with a variety of image preprocessing techniques to maximize relevant information transfer. Extracting the most useful features from a visual scene is a nontrivial task and optimal preprocessing choices strongly depend on the context. Despite rapid advancements in deep learning, research currently faces a difficult challenge in finding a general and automated preprocessing strategy that can be tailored to specific tasks or user requirements. In this paper, we present a novel deep learning approach that explicitly addresses this issue by optimizing the entire process of phosphene generation in an end-to-end fashion. The proposed model is based on a deep auto-encoder architecture and includes a highly adjustable simulation module of prosthetic vision. In computational validation experiments, we show that such an approach is able to automatically find a task-specific stimulation protocol. The results of these proof-of-principle experiments illustrate the potential of end-to-end optimization for prosthetic vision. The presented approach is highly modular and our approach could be extended to automated dynamic optimization of prosthetic vision for everyday tasks, given any specific constraints, accommodating individual requirements of the end-user.