Intraneuronal information processing, directional selectivity and memory for spatio-temporal sequences.

Interacting intracellular signalling pathways can perform computations on a scale that is slower, but more fine-grained, than the interactions between neurons upon which we normally build our computational models of the brain (Bray D 1995 Nature 376 307-12). What computations might these potentially powerful intraneuronal mechanisms be performing? The answer suggested here is: storage of spatio-temporal trajectories; thus, neurons have some of the capacities required to perform such a task. In the retina, it is suggested that calcium-induced calcium release (CICR) may provide the basis for directional selectivity. In the cortex, if activation mechanisms with different delays could be separately reinforced at individual synapses then each such Hebbian super-synapse would store a memory trace of the delay between pre- and post-synaptic activity, forming an ideal basis for the memory and response to phase sequences

Evidence for a neural model to evaluate symmetry in V1

50 years ago Hubel and Wiesel discovered simple and complex cells in V1, but there is still no consensus on their functional roles. It is agreed that complex cells are more often selective for direction of motion than simple cells, that there are differences in the way they combine information within their receptive fields, and that complex cells probably receive most of their input from simple cells, but what this serial hierarchy achieves is not understood. There is another puzzling dichotomy that we think is related, namely that of cross-correlation, which is widely accepted as the operation performed on the input image by simple cells, and auto-correlation, which some think underlies the perception of Glass patterns, and possibly motion. We propose the hypothesis that complex cells signal auto-correlations in the visual image, but to evaluate them they require the preliminary analysis done by simple cells, and also pinwheels - structures intervening between simple cells and complex cells that were quite unknown to Hubel and Wiesel. We shall first present psychophysical evidence, using a new kind of random dot display, which suggests that both cross-correlation and auto-correlation are performed in early vision. We then point to recent evidence on the micro-circuitry of pinwheels, and mappings of their intrinsic activity, which shows how pinwheels might enable complex cells to respond selectively to autocorrelations in the input image that activates the simple cells. Auto-correlation is a powerful tool for detecting symmetry, and many may be surprised by evidence that such an abstract property is detected so early in visual perception

Evidence for Auto-Correlation and Symmetry Detection in Primary Visual Cortex

The detectability of patterns in random dot arrays was measured as a function of dot density and compared with the statistical limit set by different methods of detecting the pattern. For filtering, cross-correlation, convolution, or template matching, the limit is expected to be inversely proportional to the square root of dot density. But for auto-correlation, which can detect symmetries of various types, the limit is unaffected by dot density under many conditions. Confirming previous results, we found that the coherence-threshold is often constant for Glass patterns, but the range of constancy depends on details of the display procedure. Coherence-thresholds were found to increase when the average number of dots expected at each location rose towards or exceeded a value of one; we therefore think it results from the non-linear effects of occlusion that occur when a later-programmed dot falls in the same location as an earlier one. To test this, these non-linear effects were prevented by arranging the luminance of each location to be directly proportional to the number of times that location was covered by a dot. Millions of dots can be used for these images, and they retain the streakiness of Glass patterns, while discrete dots disappear. The constant coherence threshold for detecting this streakiness is maintained over a huge range of dot densities, extending right down to the range where discrete dots become visible and up to patterns that are essentially full-tone images with no discrete dots. At threshold, all these patterns have similar auto-correlation functions, as we can see from the way both low dot-number Glass-patterns and these mega-dot, multi-tone, Glass-like images are formed. This startling fact raises the question whether primary visual cortex computes auto-correlations as well as, or even instead of, the local, Fourier-type, wavelet analysis of the currently popular paradigm

Interview of Horace Barlow

Filmed on 5 March 2012 by Alan Macfarlane and edited by Sarah HarrisonAn interview on the life and work of the scientist Horace Barlo