Whether general principles can explain the layouts of cortical maps remains unresolved. In primary visual cortex of ferret, the relationships between the maps of visual space and response features are predicted by a "dimension-reduction" model. The representation of visual space is anisotropic, with the elevation and azimuth axes having different magnification. This anisotropy is reflected in the orientation, ocular dominance, and spatial frequency domains, which are elongated such that their directions of rapid change, or high-gradient axes, are orthogonal to the high-gradient axis of the visual map. The feature maps are also strongly interdependent-their high-gradient regions avoid one another and intersect orthogonally where essential, so that overlap is minimized. Our results demonstrate a clear influence of the visual map on each feature map. In turn, the local representation of visual space is smooth, as predicted when many features are mapped within a cortical area.

Several studies have shown that the information conveyed by bell-shaped tuning curves increases as their width decreases, leading to the notion that sharpening of tuning curves improves population codes. This notion, however, is based on assumptions that the noise distribution is independent among neurons and independent of the tuning curve width. Here we reexamine these assumptions in networks of spiking neurons by using orientation selectivity as an example. We compare two principal classes of model: one in which the tuning curves are sharpened through cortical lateral interactions, and one in which they are not. We report that sharpening through lateral interactions does not improve population codes but, on the contrary, leads to a severe loss of information. In addition, the sharpening models generate complicated codes that rely extensively on pairwise correlations. Our study generates several experimental predictions that can be used to distinguish between these two classes of model.

Recent in vitro studies have shown that acetylcholine (ACh) selectively reduces the efficacy of lateral cortical connections via a muscarinic mechanism, while boosting the efficacy of thalamocortical/feed-forward connections via a nicotinic mechanism. This suggests that high levels of ACh should reduce center-surround interactions of neurons in primary visual cortex, making cells more reliant on feed-forward information. In line with this hypothesis, we show that local iontophoretic application of ACh in primate primary visual cortex reduced the extent of spatial integration, assessed by recording a neurons? length tuning. When ACh was externally applied, neurons? preferred length shifted toward shorter bars, showing reduced impact of the extra-classical receptive field. We fitted a difference and a ratio of Gaussian model to these data to determine the underlying mechanisms of this dynamic change of spatial integration. These models assume overlapping summation and suppression areas with different widths and gains to be responsible for spatial integration and size tuning. ACh significantly reduced the extent of the summation area, but had no significant effect on the extent of the suppression area. In line with previous studies, we also show that applying ACh enhanced the response in the majority of cells, especially in the later (sustained) part of the response. These findings are similar to effects of attention on neuronal activity. The natural release of ACh is strongly linked with states of arousal and attention. Our results may therefore be relevant to the neurobiological mechanism of attention.

Neocortical synapses express differential dynamic properties. When activated at high frequencies, the amplitudes of the subsequent postsynaptic responses may increase or decrease, depending on the stimulation frequency and on the properties of that particular synapse. Changes in the synaptic dynamics can dramatically affect the communication between nerve cells. Motivated by this question, we studied dynamic properties at synapses to layer 2/3 pyramidal cells with intracellular recordings in slices of rat visual cortex. Synaptic responses were evoked by trains of test stimuli, which consisted of 10 pulses at different frequencies (5-40 Hz). Test stimulation was applied either without any adaptation (control) or 2 s after an adaptation stimulus, which consisted of 4 s stimulation of these same synapses at 10, 25, or 40 Hz. The synaptic parameters were then assessed from fitting the data with a model of synaptic dynamics. Our estimates of the synaptic parameters in control, without adaptation are broadly consistent with previous studies. Adaptation led to pronounced changes of synaptic transmission. After adaptation, the amplitude of the response to the first pulse in the test train decreased for several seconds and then recovered back to the control level with a time constant of 2-18 s. Analysis of the data with extended models, which include interaction between different pools of synaptic vesicles, suggests that the decrease of the response amplitude was due to a synergistic action of two factors, decrease of the release probability and depletion of the available transmitter. After a weak (10 Hz) adaptation, the decrease of the response amplitude was accompanied by and correlated with the decrease of the release probability. After a strong adaptation (25 or 40 Hz), the depletion of synaptic resources was the main cause for the reduced response amplitude. Adaptation also led to pronounced changes of the time constants of facilitation and recovery, however, these changes were not uniform in all synapses, and on the population level, the only consistent and significant effect was an acceleration of the recovery after a strong adaptation. Taken together, our results suggest, that apart from decreasing the amplitude of postsynaptic responses, adaptation may produce synapse-specific effects, which could result in a kind of re-distribution of activity within neural networks.