Burkitt, A. N. | Search bioRxiv

bioRxiv2018

Predictive coding with neural transmission delays: a real-time temporal alignment hypothesis

Hierarchical predictive coding is an influential model of cortical organization, in which sequential hierarchical layers are connected by feedback connections carrying predictions, as well as feedforward connections carrying prediction errors. To date, however, predictive coding models have neglected to take into account that neural transmission itself takes time. For a time-varying stimulus, such as a moving object, this means that feedback predictions become misaligned with new sensory input. We present an extended model implementing both feed-forward and feedback extrapolation mechanisms that realigns feedback predictions to minimize prediction error. This realignment has the consequence that neural representations across all hierarchical stages become aligned in real-time. Using visual motion as an example, we show that the model is neurally plausible, that it is consistent with evidence of extrapolation mechanisms throughout the visual hierarchy, that it predicts several known motion-position illusions, and that it provides a solution to the temporal binding problem.

neuroscience↗

bioRxiv2018

Minimizing activation of overlying axons with epiretinal stimulation: The role of fiber orientation and electrode configuration

AO_SCPCAPBSTRACTC_SCPCAPObjective. Currently, a challenge in electrical stimulation of the retina is to excite only the cells lying directly under the electrode in the ganglion cell layer, while avoiding excitation of the axons that pass over the surface of the retina in the nerve fiber layer. Since these passing fibers may originate from distant regions of the ganglion cell layer. Stimulation of both target retinal ganglion cells and overlying axons results in irregular visual percepts, significantly limiting perceptual efficacy. This research explores how differences in fiber orientation between the nerve fiber layer and ganglion cell layer leads to differences in the activation of the axon initial segment and axons of passage. Approach. Axons of passage of retinal ganglion cells in the nerve fiber layer are characterized by a narrow distribution of fiber orientations, causing highly anisotropic spread of applied current. In contrast, proximal axons in the ganglion cell layer have a wider distribution of orientations. A four-layer computational model of epiretinal extracellular stimulation that captures the effect of neurite orientation in anisotropic tissue has been developed using a modified version of the standard volume conductor model, known as the cellular composite model. Simulations are conducted to investigate the interaction of neural tissue orientation, stimulating electrode configuration, and stimulation pulse duration and amplitude. Main results. The dependence of fiber activation on the anisotropic nature of the nerve fiber layer is first established. Via a comprehensive search of key parameters, our model shows that the simultaneous stimulation with multiple electrodes aligned with the nerve fiber layer can be used to achieve selective activation of axon initial segments rather than passing fibers. This result can be achieved with only a slight increase in total stimulus current and modest increases in the spread of activation in the ganglion cell layer, and is shown to extend to the general case of arbitrary electrode array positioning and arbitrary target neural volume. Significance. These results elucidate a strategy for more targeted stimulation of retinal ganglion cells with experimentally-relevant multi-electrode geometries and readily achievable stimulation requirements.

biophysics↗