Efficient Coding by Midget and Parasol Ganglion Cells in the Human Retina

In humans, midget and parasol ganglion cells account for most of the input from the eyes to the brain. Yet, how they encode visual information is unknown. Here, we perform large-scale multi-electrode array recordings from retinas of treatment-naive patients who underwent enucleation surgery for choroidal malignant melanomas. We identify robust differences in the function of midget and parasol ganglion cells, consistent asymmetries between their ON and OFF types (that signal light increments and decrements, respectively) and divergence in the function of human versus non-human primate retinas. Our computational analyses reveal that the receptive fields of human midget and parasol ganglion cells divide naturalistic movies into adjacent spatiotemporal frequency domains with equal stimulus power, while the asymmetric response functions of their ON and OFF types simultaneously maximize stimulus coverage and information transmission and minimize metabolic cost. Thus, midget and parasol ganglion cells in the human retina efficiently encode our visual environment.

Slow presynaptic mechanisms that mediate adaptation in the olfactory pathway of Drosophila

The olfactory system encodes odor stimuli as combinatorial activity of populations of neurons whose response depends on stimulus history. How and on which timescales previous stimuli affect these combinatorial representations remains unclear. We use in vivo optical imaging in Drosophila to analyze sensory adaptation at the first synaptic step along the olfactory pathway. We show that calcium signals in the axon terminals of olfactory receptor neurons (ORNs) do not follow the same adaptive properties as the firing activity measured at the antenna. While ORNs calcium responses are sustained on long timescales, calcium signals in the postsynaptic projection neurons (PNs) adapt within tens of seconds. We propose that this slow component of the postsynaptic response is mediated by a slow presynaptic depression of vesicle release and enables the combinatorial population activity of PNs to adjust to the mean and variance of fluctuating odor stimuli.

Describing complex cells in primary visual cortex: a comparison of context and multifilter LN models

Receptive field (RF) models are an important tool for deciphering neural responses to sensory stimuli. The two currently popular RF models are multifilter linear-nonlinear (LN) models and context models. Models are, however, never correct, and they rely on assumptions to keep them simple enough to be interpretable. As a consequence, different models describe different stimulus-response mappings, which may or may not be good approximations of real neural behavior. In the current study, we take up two tasks: 1) we introduce new ways to estimate context models with realistic nonlinearities, that is, with logistic and exponential functions, and 2) we evaluate context models and multifilter LN models in terms of how well they describe recorded data from complex cells in cat primary visual cortex. Our results, based on single-spike information and correlation coefficients, indicate that context models outperform corresponding multifilter LN models of equal complexity (measured in terms of number of parameters), with the best increase in performance being achieved by the novel context models. Consequently, our results suggest that the multifilter LN-model framework is suboptimal for describing the behavior of complex cells: the context-model framework is clearly superior while still providing interpretable quantizations of neural behavior. NEW & NOTEWORTHY We used data from complex cells in primary visual cortex to estimate a wide variety of receptive field models from two frameworks that have previously not been compared with each other. The models included traditionally used multifilter linear-nonlinear models and novel variants of context models. Using mutual information and correlation coefficients as performance measures, we showed that context models are superior for describing complex cells and that the novel context models performed the best.

Light adaptation increases response latency of alpha ganglion cells via a threshold-like nonlinearity

Adaptation is an important process of sensory systems to adjust sensitivity to ensure the appropriate information encoding. Sensitivity and kinetics of retinal ganglion cell (RGC) responses have been studied extensively using a brief flash superimposed on different but steady backgrounds. However, it is still unclear if light adaptation exerts any effect on more complex response properties, such as response nonlinearity. In this study, we found that the latency of spike responses to a repeated flashing spot stimulation increased by 30 ms in the mouse ON α RGCs (An ON-type RGC is excited when a spot is turned on in the center of its receptive field). A single dimming event preceding the test flash on a steady adapting background could also produce similar effect in increasing latency of light responses. A simple computational model with a linear transformation of the light stimulus and a threshold-like nonlinearity could account for the experimental data. Moreover, the strength of the measured nonlinearity and the response latency were affected by the duration of light adaptation. The possible biological processes underlying this nonlinearity were explored. Voltage clamp recording revealed the presence of the increase in latency and threshold-like nonlinearity in the excitatory input of RGCs. However, no comparable nonlinearity was observed in the light responses of the ON cone bipolar cells. We further excluded GABAergic and glycinergic inhibition, N-methyl-D-aspartate receptor rectification and voltage-gated Na(+) channels as potential sources of this nonlinearity by pharmacological experiments. Our results indicate the bipolar cell terminals as the potential site of nonlinearity. Computational modeling constrained by experimental data supports that conclusion and suggests the voltage-sensitive Ca(++) channels and Ca(++)-dependent vesicle release in the bipolar cell terminals as mechanistic basis.