Optometry and Vision Sciences - Research Publications

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    Frequency Responses of Rat Retinal Ganglion Cells
    Hadjinicolaou, AE ; Cloherty, SL ; Hung, Y-S ; Kameneva, T ; Ibbotson, MR ; Agudo-Barriuso, M (PUBLIC LIBRARY SCIENCE, 2016-06-24)
    There are 15-20 different types of retinal ganglion cells (RGC) in the mammalian retina, each encoding different aspects of the visual scene. The mechanism by which post-synaptic signals from the retinal network generate spikes is determined by each cell's intrinsic electrical properties. Here we investigate the frequency responses of morphologically identified rat RGCs using intracellular injection of sinusoidal current waveforms, to assess their intrinsic capabilities with minimal contributions from the retinal network. Recorded cells were classified according to their morphological characteristics (A, B, C or D-type) and their stratification (inner (i), outer (o) or bistratified) in the inner plexiform layer (IPL). Most cell types had low- or band-pass frequency responses. A2, C1 and C4o cells were band-pass with peaks of 15-30 Hz and low-pass cutoffs above 56 Hz (A2 cells) and ~42 Hz (C1 and C4o cells). A1 and C2i/o cells were low-pass with peaks of 10-15 Hz (cutoffs 19-25 Hz). Bistratified D1 and D2 cells were also low-pass with peaks of 5-10 Hz (cutoffs ~16 Hz). The least responsive cells were the B2 and C3 types (peaks: 2-5 Hz, cutoffs: 8-11 Hz). We found no difference between cells stratifying in the inner and outer IPL (i.e., ON and OFF cells) or between cells with large and small somas or dendritic fields. Intrinsic physiological properties (input resistance, spike width and sag) had little impact on frequency response at low frequencies, but account for 30-40% of response variability at frequencies >30 Hz.
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    PHASE SENSITIVITY OF COMPLEX CELLS IN PRIMARY VISUAL CORTEX
    Hietanen, MA ; Cloherty, SL ; van Kleef, JP ; Wang, C ; Dreher, B ; Ibbotson, MR (PERGAMON-ELSEVIER SCIENCE LTD, 2013-05-01)
    Neurons in the primary visual cortex are often classified as either simple or complex based on the linearity (or otherwise) of their response to spatial luminance contrast. In practice, classification is typically based on Fourier analysis of a cell's response to an optimal drifting sine-wave grating. Simple cells are generally considered to be linear and produce responses modulated at the fundamental frequency of the stimulus grating. In contrast, complex cells exhibit significant nonlinearities that reduce the response at the fundamental frequency. Cells can therefore be easily and objectively classified based on the relative modulation of their responses - the ratio of the phase-sensitive response at the fundamental frequency of the stimulus (F₁) to the phase-invariant sustained response (F₀). Cells are classified as simple if F₁/F₀>1 and complex if F₁/F₀<1. This classification is broadly consistent with criteria based on the spatial organisation of cells' receptive fields and is accordingly presumed to reflect disparate functional roles of simple and complex cells in coding visual information. However, Fourier analysis of spiking responses is sensitive to the number of spikes available - F₁/F₀ increases as the number of spikes is reduced, even for phase-invariant complex cells. Moreover, many complex cells encountered in the laboratory exhibit some phase sensitivity, evident as modulation of their responses at the fundamental frequency. There currently exists no objective quantitative means of assessing the significance or otherwise of these modulations. Here we derive a statistical basis for objectively assessing whether the modulation of neuronal responses is reliable, thereby adding a level of statistical certainty to measures of phase sensitivity. We apply our statistical analysis to neuronal responses to moving sine-wave gratings recorded from 367 cells in cat primary visual cortex. We find that approximately 60% of complex cells exhibit statistically significant (α<0.01) modulation of their responses to optimal moving gratings. These complex cells are phase sensitive and reliably encode spatial phase.
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    Stripe-rearing changes multiple aspects of the structure of primary visual cortex
    Hughes, NJ ; Hunt, JJ ; Cloherty, SL ; Ibbotson, MR ; Sengpiel, F ; Goodhill, GJ (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2014-07-15)
    An important example of brain plasticity is the change in the structure of the orientation map in mammalian primary visual cortex in response to a visual environment consisting of stripes of one orientation. In principle there are many different ways in which the structure of a normal map could change to accommodate increased preference for one orientation. However, until now these changes have been characterised only by the relative sizes of the areas of primary visual cortex representing different orientations. Here we extend to the stripe-reared case a recently proposed Bayesian method for reconstructing orientation maps from intrinsic signal optical imaging data. We first formulated a suitable prior for the stripe-reared case, and developed an efficient method for maximising the marginal likelihood of the model in order to determine the optimal parameters. We then applied this to a set of orientation maps from normal and stripe-reared cats. This analysis revealed that several parameters of overall map structure, specifically the difference between wavelength, scaling and mean of the two vector components of maps, changed in response to stripe-rearing, which together give a more nuanced assessment of the effect of rearing condition on map structure than previous measures. Overall this work expands our understanding of the effects of the environment on brain structure.
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    Intrinsic physiological properties of rat retinal ganglion cells with a comparative analysis
    Wong, RCS ; Cloherty, SL ; Ibbotson, MR ; O'Brien, BJ (AMER PHYSIOLOGICAL SOC, 2012-10)
    Mammalian retina contains 15-20 different retinal ganglion cell (RGC) types, each of which is responsible for encoding different aspects of the visual scene. The encoding is defined by a combination of RGC synaptic inputs, the neurotransmitter systems used, and their intrinsic physiological properties. Each cell's intrinsic properties are defined by its morphology and membrane characteristics, including the complement and localization of the ion channels expressed. In this study, we examined the hypothesis that the intrinsic properties of individual RGC types are conserved among mammalian species. To do so, we measured the intrinsic properties of 16 morphologically defined rat RGC types and compared these data with cat RGC types. Our data demonstrate that in the rat different morphologically defined RGC types have distinct patterns of intrinsic properties. Variation in these properties across cell types was comparable to that found for cat RGC types. When presumed morphological homologs in rat and cat retina were compared directly, some RGC types had very similar properties. The rat A2 cell exhibited patterns of intrinsic properties nearly identical to the cat alpha cell. In contrast, rat D2 cells (ON-OFF directionally selective) had a very different pattern of intrinsic properties than the cat iota cell. Our data suggest that the intrinsic properties of RGCs with similar morphology and suspected visual function may be subject to variation due to the behavioral needs of the species.