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Human Brain Imaging by Optical Coherence Tomography
Published in Francesco S. Pavone, Shy Shoham, Handbook of Neurophotonics, 2020
Caroline Magnain, Jean C. Augustinack, David Boas, Bruce Fischl, Taner Akkin, Ender Konukoglu, Hui Wang
Figure 18.12 shows the boundary between the entorhinal cortex (Brodmann area 28) and perirhinal cortex (Brodmann area 35). The boundary delineation is entirely based on the OCT contrast. In entorhinal cortex, the cell-dense areas occur in layers II and IV. This translates to bright bands in the AIP image in Figure 18.12A. The neurons of these layers (II and IV) are large enough to distinguish individually on the MIP as well on Figure 18.12B. As shown previously in Figure 18.8, the contrast in layer II shows the islands created by the neuronal dense and non-dense areas. The boundary between BA28 and BA35 can be detected based on the arrangement of the neurons of layer II, with area 28 being rounder than area 35. In BA35, the neurons form columns instead of islands, and are illustrated on the AIP. Moreover, the subdivisions of perirhinal cortex into BA35a (closest to BA28) and BA35b can easily be seen on the AIP. Layer IV of BA28 continues into the transition area of perirhinal cortex, 35a. The oblique layer is another classic attribute of BA35a and appears as a dark layer, starting close to layer II and going deeper in the cortex along the length of the transition region. The subdivision 35b has brighter layers corresponding to the layers II and III and a dark dysgranular layer IV. The cortical boundaries between adjacent regions, with the exception of the primary cortices, are generally subtler than the boundary between entorhinal cortex and perirhinal cortex shown in the previous example. Other cortical boundaries will benefit from the 3D reconstruction of the cortex over several cubic centimeters.
A mosaic of Chu spaces and Channel Theory II: applications to object identification and mereological complexity
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2019
Chris Fields, James F. Glazebrook
Young infants exhibit robust object memory, particularly for familiar faces, and emotional responses to objects, again from the earliest ages tested. Feelings of familiarity and their attendant emotions correlate with feature-based object recognition at the level of perirhinal cortex (Eichenbaum, Yonelinas, & Ranganath, 2007). Memory for a particular, individual, re-identifiable object requires a memory-resident representation of that individual object, what Zimmer and Ecker (2010) have termed an ‘object token.’ Recognising a novel object as a distinct, individual thing not encountered before involves encoding a new object token specifically for it. Recognition or re-identification of the same individual object on a later occasion is then a process of matching the current object file to this previously encoded object token (Figure 2). This process is, in general, not straightforward, as object features, behaviours and locations may change between encounters. Even very young infants expect identified objects to maintain constant features, behaviours, and locations over periods of non-observation of seconds to a few minutes (Baillargeon, 2008; Baillargeon et al., 2012). Both feature matching and, after about four years of age, the construction of unobserved and hence confabulated, that is fictive causal histories (FCHs) of objects are employed to establish individual object identity across observations separated by more than a few minutes (reviewed in Fields, 2012). Enabling object recognition across feature, behaviour and context changes requires object tokens to have a ‘core’ of essential properties that change only slowly through time. The distinction between core and variable properties in object tokens is category-dependent and not well understood (see Scholl, 2007, for review).