It has been suggested that Marr took the three levels he famously identifies to be independent. In this paper, we argue that Marr's view is more nuanced. Specifically, we show that the view explicitly articulated in his work attempts to integrate the levels, and in doing so results in Marr attacking both reductionism and vagueness. The result is a perspective in which both high-level informatio...

B. subtilis adapts to changing environments by reprogramming its genetic expression through a variety of transcriptional regulators from the global transition state regulators that allow a complete resetting of the cell genetic expression, to stress specific regulators controlling only a limited number of key genes required for optimal adaptation. Among them, MarR-type transcriptional regulator...

The structure of the MarR-family transcription factor NMB1585 from Neisseria meningitidis has been solved using data extending to a resolution of 2.1 A. Overall, the dimeric structure resembles those of other MarR proteins, with each subunit comprising a winged helix-turn-helix (wHtH) domain connected to an alpha-helical dimerization domain. The spacing of the recognition helices of the wHtH do...

Current views of cerebellar function have been heavily influenced by the models of Marr and Albus, who suggested that the climbing fibre input to the cerebellum acts as a teaching signal for motor learning. It is commonly assumed that this teaching signal must be motor error (the difference between actual and correct motor command), but this approach requires complex neural structures to estima...

Since edge detection is in the forefront of image processing for object detection, it is crucial to have a good understanding of edge detection algorithms. This paper introduces a new classification of most important and commonly used edge detection algorithms, namely ISEF, Canny, Marr-Hildreth, Sobel, Kirsch, Lapla1 and Lapla2. Five categories are included in our classification, and then advan...

Segmentation in volumetric images deals with separating ‘objects’ from their ‘background’ in a given 3D data. Usually, one starts with ‘edge detectors’ that give binary clues on the locations of the objects boundaries. Classical edge detectors that can be adopted from 2D are the Marr–Hildreth, and Haralick or Canny edge detectors. Next, usually one integrates these clues into meaningful contour...

Neuroscientists study the brain at many different levels, from molecular to psychological. Despite progress on many of these levels, there is a disappointing lack of coherence in neuroscience research: we have yet to find an overarching theoretical framework for understanding what the brain does. Vision is one of the most intensively studied areas of brain function. Yet, even in this field, the...