SummaryAttention improves perception by affecting different aspects of the neuronal code. It enhances firing rates, it reduces firing rate variability and noise correlations of neurons, and it alters the strength of oscillatory activity. Attention-induced rate enhancement in striate cortex requires cholinergic mechanisms. The neuropharmacological mechanisms responsible for attention-induced variance and noise correlation reduction or those supporting changes in oscillatory activity are unknown. We show that ionotropic glutamatergic receptor activation is required for attention-induced rate variance, noise correlation, and LFP gamma power reduction in macaque V1, but not for attention-induced rate modulations. NMDA receptors mediate attention-induced variance reduction and attention-induced noise correlation reduction. Our results demonstrate that attention improves sensory processing by a variety of mechanisms that are dissociable at the receptor level.

Local field potentials (LFPs) sampled with extracellular electrodes are frequently used as a measure of population neuronal activity. However, relating such measurements to underlying neuronal behaviour and connectivity is non-trivial. To help study this link, we developed the Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX). We first identified a reduced neuron model that retained the spatial and frequency filtering characteristics of extracellular potentials from neocortical neurons. We then developed VERTEX as an easy-to-use Matlab tool for simulating LFPs from large populations (>100,000 neurons). A VERTEX-based simulation successfully reproduced features of the LFPs from an in vitro multi-electrode array recording of macaque neocortical tissue. Our model, with virtual electrodes placed anywhere in 3D, allows direct comparisons with the in vitro recording setup. We envisage that VERTEX will stimulate experimentalists, clinicians, and computational neuroscientists to use models to understand the mechanisms underlying measured brain dynamics in health and disease.Electronic supplementary materialThe online version of this article (doi:10.1007/s00429-014-0793-x) contains supplementary material, which is available to authorized users.

Perceptual learning, the improvement in perceptual abilities with training, is thought to be mediated by an alteration of neuronal tuning. It remains poorly understood how tuning properties change as training progresses, whether improved stimulus tuning directly links to increased behavioural readout of sensory information, or how population coding mechanisms change with training. Here, we recorded continuously from multiple neuronal clusters in area V4 while macaque monkeys learned a fine contrast categorization task. Training increased neuronal coding abilities by shifting the steepest point of contrast response functions towards the categorization boundary. Population coding accuracy of difficult discriminations resulted largely from an increased information coding of individual channels, particularly for those channels that in early learning had larger ability for easy discriminations, but comparatively small encoding abilities for difficult discriminations. Population coding was also enhanced by specific changes in correlations. Neuronal activity became more indicative of upcoming choices with training.

Attention affects neuronal processing and improves behavioural performance. In extrastriate visual cortex these effects have been explained by normalization models, which assume that attention influences the circuit that mediates surround suppression. While normalization models have been able to explain attentional effects, their validity has rarely been tested against alternative models. Here we investigate how attention and surround/mask stimuli affect neuronal firing rates and orientation tuning in macaque V1. Surround/mask stimuli provide an estimate to what extent V1 neurons are affected by normalization, which was compared against effects of spatial top down attention. For some attention/surround effect comparisons, the strength of attentional modulation was correlated with the strength of surround modulation, suggesting that attention and surround/mask stimulation (i.e. normalization) might use a common mechanism. To explore this in detail, we fitted multiplicative and additive models of attention to our data. In one class of models, attention contributed to normalization mechanisms, whereas in a different class of models it did not. Model selection based on Akaike's and on Bayesian information criteria demonstrated that in most cells the effects of attention were best described by models where attention did not contribute to normalization mechanisms. This demonstrates that attentional influences on neuronal responses in primary visual cortex often bypass normalization mechanisms.

Rhesus monkeys underwent training in a contrast discrimination task, in which grating stimuli were presented at parafoveal and peripheral visual field locations. Subjects had to compare a sample stimulus that had a fixed contrast of 30% to a test stimulus that varied in contrast from trial to trial. Extensive practice yielded improvements in contrast discrimination that were observed across the full range of test stimulus contrasts. These improvements occurred across multiple sessions, as well as across trials within individual sessions. The finer the contrast discriminations required, the longer it took for subjects to improve. Improvements in psychophysical performance resulted in the steepening of psychometric functions and/or shifts in the point of subjective equality towards the contrast of the sample stimulus. Enhancement in discrimination was especially pronounced around the contrast level of the sample stimulus, to which the subject was consistently exposed. The changes resulted in increased accuracy overall, lower discrimination thresholds, and faster response times. Partial transfer of learning, from vertically oriented training stimuli to horizontally oriented testing stimuli, was observed, while transfer to stimuli with different spatial frequencies was less pronounced. The results demonstrate the existence of perceptual learning in the contrast domain, whereby learning affects multiple performance-related psychophysical metrics.