A comparative biology approach to DNN modeling of vision: A focus on differences, not similarities.

Deep neural networks (DNNs) have revolutionized computer science and are now widely used for neuroscientific research. A hot debate has ensued about the usefulness of DNNs as neuroscientific models of the human visual system; the debate centers on to what extent certain shortcomings of DNNs are real failures and to what extent they are redeemable. Here, we argue that the main problem is that we often do not understand which human functions need to be modeled and, thus, what counts as a falsification.

Crowding in humans is unlike that in convolutional neural networks.

Object recognition is a primary function of the human visual system. It has recently been claimed that the highly successful ability to recognise objects in a set of emergent computer vision systems-Deep Convolutional Neural Networks (DCNNs)-can form a useful guide to recognition in humans. To test this assertion, we systematically evaluated visual crowding, a dramatic breakdown of recognition in clutter, in DCNNs and compared their performance to extant research in humans.

CMV retinitis after allogeneic bone marrow transplantation: a report of five cases.

Four cases of cytomegalovirus (CMV) retinitis (CMVR) after allogeneic blood stem cell transplant (SCT) were documented in Huddinge University Hospital between 1994 and 1999. Prior to 1994, only one case was documented. All five patients were transplanted due to malignant disease, two with sibling donors and three with matched unrelated donors.

Identification of a determinant of epidermal growth factor receptor ligand-binding specificity using a truncated, high-affinity form of the ectodomain.

Murine and human epidermal growth factor receptors (EGFRs) bind human EGF (hEGF), mouse EGF (mEGF), and human transforming growth factor alpha (hTGF-alpha) with high affinity despite the significant differences in the amino acid sequences of the ligands and the receptors. In contrast, the chicken EGFR can discriminate between mEGF (and hEGF) and hTGF-alpha and binds the EGFs with approximately 100-fold lower affinity. The regions responsible for this poor binding are known to be Arg(45) in hEGF and the L2 domain in the chicken EGFR.