Blue cone monochromacy: causative mutations and associated phenotypes.

PurposeTo perform a phenotypic assessment of members of three British families with blue cone monochromatism (BCM), and to determine the underlying molecular genetic basis of disease.MethodsAffected members of three British families with BCM were examined clinically and underwent detailed electrophysiological and psychophysical testing. Blood samples were taken for DNA extraction. Molecular analysis involved the amplification of the coding regions of the long (L) and medium (M) wave cone opsin genes and the upstream locus control region (LCR) by polymerase chain reaction (PCR). Gene products were directly sequenced and analyzed.ResultsIn all three families, genetic analysis identified that the underlying cause of BCM involved an unequal crossover within the opsin gene array, with an inactivating mutation. Family 1 had a single 5'-L-M-3' hybrid gene, with an inactivating Cys203Arg (C203R) mutation. Family 3 had an array composed of a C203R inactivated 5'-L-M-3' hybrid gene followed by a second inactive gene. Families 1 and 3 had typical clinical, electrophysiological, and psychophysical findings consistent with stationary BCM. A novel mutation was detected in Family 2 that had a single hybrid gene lacking exon 2. This family presented clinical and psychophysical evidence of a slowly progressive phenotype.ConclusionsTwo of the BCM-causing family genotypes identified in this study comprised different hybrid genes, each of which contained the commonly described C203R inactivating mutation. The genotype in the family with evidence of a slowly progressive phenotype represents a novel BCM mutation. The deleted exon 2 in this family is not predicted to result in a shift in the reading frame, therefore we hypothesize that an abnormal opsin protein product may accumulate and lead to cone cell loss over time. This is the first report of slow progression associated with this class of mutation in the L or M opsin genes in BCM

Retinal Ganglion Cells-Diversity of Cell Types and Clinical Relevance.

Retinal ganglion cells (RGCs) are the bridging neurons that connect the retinal input to the visual processing centres within the central nervous system. There is a remarkable diversity of RGCs and the various subtypes have unique morphological features, distinct functions, and characteristic pathways linking the inner retina to the relevant brain areas. A number of psychophysical and electrophysiological tests have been refined to investigate this large and varied population of RGCs. Technological advances, such as high-resolution optical coherence tomography imaging, have provided additional tools to define the pattern of RGC involvement and the chronological sequence of events in both inherited and acquired optic neuropathies. The mechanistic insights gained from these studies, in particular the selective vulnerability and relative resilience of particular RGC subtypes, are of fundamental importance as they are directly relevant to the development of targeted therapies for these invariably progressive blinding diseases. This review provides a comprehensive description of the various types of RGCs, the developments in proposed methods of classification, and the current gaps in our knowledge of how these RGCs are differentially affected depending on the underlying aetiology. The synthesis of the current body of knowledge on the diversity of RGCs and the pathways that are potentially amenable to therapeutic modulation will hopefully lead to much needed effective treatments for patients with optic neuropathies

Cognitive impairment from early to middle adulthood in patients with affective and nonaffective psychotic disorders

Background.—Cognitive impairment is a core feature of psychotic disorders, but the profile of impairment across adulthood, particularly in African-American populations, remains unclear. Methods.—Using cross-sectional data from a case–control study of African-American adults with affective (n = 59) and nonaffective (n = 68) psychotic disorders, we examined cognitive functioning between early and middle adulthood (ages 20–60) on measures of general cognitive ability, language, abstract reasoning, processing speed, executive function, verbal memory, and working memory. Results.—Both affective and nonaffective psychosis patients showed substantial and widespread cognitive impairments. However, comparison of cognitive functioning between controls and psychosis groups throughout early (ages 20–40) and middle (ages 40–60) adulthood also revealed age-associated group differences. During early adulthood, the nonaffective psychosis group showed increasing impairments with age on measures of general cognitive ability and executive function, while the affective psychosis group showed increasing impairment on a measure of language ability. Impairments on other cognitive measures remained mostly stable, although decreasing impairments on measures of processing speed, memory and working memory were also observed. Conclusions.—These findings suggest similarities, but also differences in the profile of cognitive dysfunction in adults with affective and nonaffective psychotic disorders. Both affective and nonaffective patients showed substantial and relatively stable impairments across adulthood. The nonaffective group also showed increasing impairments with age in general and executiv

RSPB-2016-0164 Danilova Mollon Exp1 data

data obtained for experiment

RSPB-2016-0164 Danilova Mollon Suppl exp data

data used for p.5: Hue and saturation thresholds very close to the white poin

What kind of network is the brain?

The different areas of the cerebral cortex are linked by a network of white matter, comprising the myelinated axons of pyramidal cells. Is this network a neural net, in the sense that representations of the world are embodied in the structure of the net, its pattern of nodes, and connections? Or is it a communications network, where the same physical substrate carries different information from moment to moment? This question is part of the larger question of whether the brain is better modeled by connectionism or by symbolic artificial intelligence (AI), but we review it in the specific context of the psychophysics of stimulus comparison and the format and protocol of information transmission over the long-range tracts of the brain.Preparation of the paper was supported by BBSRC Grant BB/S000623/1 to Cambridge University and by Russian Ministry of Science and Higher Education grant to Pavlov Center “Integrative Physiology for Medicine, High-tech Healthcare and Stress Tolerance Technologies” (Agreement No. 075-1502020-921)

RSPB-2016-0164 Danilova Mollon control exp data

data used in the control experimen

Individual differences in visual science: What can be learned and what is good experimental practice?

We all pass out our lives in private perceptual worlds. The differences in our sensory and perceptual experiences often go unnoticed until there emerges a variation (such as 'The Dress') that is large enough to generate different descriptions in the coarse coinage of our shared language. In this essay, we illustrate how individual differences contribute to a richer understanding of visual perception, but we also indicate some potential pitfalls that face the investigator who ventures into the field