115,729 research outputs found

    Flora robotica -- An Architectural System Combining Living Natural Plants and Distributed Robots

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    Key to our project flora robotica is the idea of creating a bio-hybrid system of tightly coupled natural plants and distributed robots to grow architectural artifacts and spaces. Our motivation with this ground research project is to lay a principled foundation towards the design and implementation of living architectural systems that provide functionalities beyond those of orthodox building practice, such as self-repair, material accumulation and self-organization. Plants and robots work together to create a living organism that is inhabited by human beings. User-defined design objectives help to steer the directional growth of the plants, but also the system's interactions with its inhabitants determine locations where growth is prohibited or desired (e.g., partitions, windows, occupiable space). We report our plant species selection process and aspects of living architecture. A leitmotif of our project is the rich concept of braiding: braids are produced by robots from continuous material and serve as both scaffolds and initial architectural artifacts before plants take over and grow the desired architecture. We use light and hormones as attraction stimuli and far-red light as repelling stimulus to influence the plants. Applied sensors range from simple proximity sensing to detect the presence of plants to sophisticated sensing technology, such as electrophysiology and measurements of sap flow. We conclude by discussing our anticipated final demonstrator that integrates key features of flora robotica, such as the continuous growth process of architectural artifacts and self-repair of living architecture.Comment: 16 pages, 12 figure

    Predict or classify: The deceptive role of time-locking in brain signal classification

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    Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying assumption that the ability to classify the brain signal is equivalent to predict the decision itself. Here we show instead that it is possible to correctly classify a signal even if it does not contain any predictive information about the decision. We first define a simple stochastic model that mimics the random decision process between two equivalent alternatives, and generate a large number of independent trials that contain no choice-predictive information. The trials are first time-locked to the time point of the final event and then classified using standard machine-learning techniques. The resulting classification accuracy is above chance level long before the time point of time-locking. We then analyze the same trials using information theory. We demonstrate that the high classification accuracy is a consequence of time-locking and that its time behavior is simply related to the large relaxation time of the process. We conclude that when time-locking is a crucial step in the analysis of neural activity patterns, both the emergence and the timing of the classification accuracy are affected by structural properties of the network that generates the signal.Comment: 23 pages, 5 figure

    Expression of A152T human tau causes age-dependent neuronal dysfunction and loss in transgenic mice.

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    A152T-variant human tau (hTau-A152T) increases risk for tauopathies, including Alzheimer's disease. Comparing mice with regulatable expression of hTau-A152T or wild-type hTau (hTau-WT), we find age-dependent neuronal loss, cognitive impairments, and spontaneous nonconvulsive epileptiform activity primarily in hTau-A152T mice. However, overexpression of either hTau species enhances neuronal responses to electrical stimulation of synaptic inputs and to an epileptogenic chemical. hTau-A152T mice have higher hTau protein/mRNA ratios in brain, suggesting that A152T increases production or decreases clearance of hTau protein. Despite their functional abnormalities, aging hTau-A152T mice show no evidence for accumulation of insoluble tau aggregates, suggesting that their dysfunctions are caused by soluble tau. In human amyloid precursor protein (hAPP) transgenic mice, co-expression of hTau-A152T enhances risk of early death and epileptic activity, suggesting copathogenic interactions between hTau-A152T and amyloid-β peptides or other hAPP metabolites. Thus, the A152T substitution may augment risk for neurodegenerative diseases by increasing hTau protein levels, promoting network hyperexcitability, and synergizing with the adverse effects of other pathogenic factors
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