Neurons in the cerebral cortex are organized into anatomical columns, with ensembles of cells arranged from the surface to the white matter. Within a column, neurons often share functional properties, such as selectivity for stimulus orientation; columns with distinct properties, such as different preferred orientations, tile the cortical surface in orderly patterns. This functional architecture was discovered with the relatively sparse sampling of microelectrode recordings. Optical imaging of membrane voltage or metabolic activity elucidated the overall geometry of functional maps, but is averaged over many cells (resolution >100 microm). Consequently, the purity of functional domains and the precision of the borders between them could not be resolved. Here, we labelled thousands of neurons of the visual cortex with a calcium-sensitive indicator in vivo. We then imaged the activity of neuronal populations at single-cell resolution with two-photon microscopy up to a depth of 400 microm. In rat primary visual cortex, neurons had robust orientation selectivity but there was no discernible local structure; neighbouring neurons often responded to different orientations. In area 18 of cat visual cortex, functional maps were organized at a fine scale. Neurons with opposite preferences for stimulus direction were segregated with extraordinary spatial precision in three dimensions, with columnar borders one to two cells wide. These results indicate that cortical maps can be built with single-cell precision.

The response of a cortical cell to a repeated stimulus can be highly variable from one trial to the next. Much lower variability has been reported of retinal cells. We recorded visual responses simultaneously from three successive stages of the cat visual system: retinal ganglion cells (RGCs), thalamic (LGN) relay cells, and simple cells in layer 4 of primary visual cortex. Spike count variability was lower than that of a Poisson process at all three stages but increased at each stage. Absolute and relative refractory periods largely accounted for the reliability at all three stages. Our results show that cortical responses can be more reliable than previously thought. The differences in reliability in retina, LGN, and cortex can be explained by (1) decreasing firing rates and (2) decreasing absolute and relative refractory periods.

In the visual cortex of higher mammals, neurons are arranged across the cortical surface in an orderly map of preferred stimulus orientations. This map contains 'orientation pinwheels', structures that are arranged like the spokes of a wheel such that orientation changes continuously around a centre. Conventional optical imaging first demonstrated these pinwheels, but the technique lacked the spatial resolution to determine the response properties and arrangement of cells near pinwheel centres. Electrophysiological recordings later demonstrated sharply selective neurons near pinwheel centres, but it remained unclear whether they were arranged randomly or in an orderly fashion. Here we use two-photon calcium imaging in vivo to determine the microstructure of pinwheel centres in cat visual cortex with single-cell resolution. We find that pinwheel centres are highly ordered: neurons selective to different orientations are clearly segregated even in the very centre. Thus, pinwheel centres truly represent singularities in the cortical map. This highly ordered arrangement at the level of single cells suggests great precision in the development of cortical circuits underlying orientation selectivity.

The subplate forms a transient circuit required for development of connections between the thalamus and the cerebral cortex. When subplate neurons are ablated, ocular dominance columns do not form in the visual cortex despite the robust presence of thalamic axons in layer 4. We show that subplate ablation also prevents formation of orientation columns. Visual responses are weak and poorly tuned to orientation. Furthermore, thalamocortical synaptic transmission fails to strengthen, whereas intracortical synapses are unaffected. Thus, subplate circuits are essential not only for the anatomical segregation of thalamic inputs but also for key steps in synaptic remodeling and maturation needed to establish the functional architecture of visual cortex.

Neural activation increases blood flow locally. This vascular signal is used by functional imaging techniques to infer the location and strength of neural activity 1,2 . However, the precise spatial scale over which neural and vascular signals are correlated is unknown. Furthermore, the relative role of synaptic and spiking activity in driving hemodynamic signals is controversial [3][4][5][6][7][8][9] . Prior studies recorded local field potentials (LFPs) as a measure of synaptic activity together with spiking activity and low-resolution hemodynamic imaging. Here we used two-photon microscopy to measure sensory-evoked responses of individual blood vessels (dilation, blood velocity) while imaging synaptic and spiking activity in the surrounding tissue using fluorescent glutamate and calcium sensors. In cat primary visual cortex, where neurons are clustered by their preference for stimulus orientation, we discovered new maps for excitatory synaptic activity, which were organized similar to spiking activity but were less selective for stimulus orientation and direction. We generated tuning curves for individual vessel responses for the first time and found that parenchymal vessels in cortical layer 2/3 were orientation selective. Neighboring penetrating arterioles had different orientation preferences. Pial surface arteries in cats, as well as surface arteries and penetrating arterioles in rat visual cortex (where orientation maps do not exist 10 ), responded to visual stimuli but had no orientation selectivity. We integrated synaptic or spiking responses around individual parenchymal vessels in cats and established that the vascular and neural responses had the same orientation preference. However, synaptic and spiking responses were more selective than vascular responses-vessels frequently responded robustly to stimuli that evoked little to no neural activity in the surrounding tissue. Thus, local neural and hemodynamic signals were partly decoupled. Together, these results indicate that intrinsic cortical properties, such as propagation of vascular dilation between neighboring columns, need to be accounted for when decoding hemodynamic signals.To determine how neural activity leads to changes in cerebral blood flow, the hemodynamic responses of individual vessels need to be compared to neural activity in the surrounding tissue 11 . While sensory-evoked responses of individual vessels have been measured in the Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

We demonstrate that Alexa Fluor 633 hydrazide (Alexa Fluor 633) selectively labels neocortical arteries and arterioles by binding to elastin fibers. We measured sensory stimulus–evoked arteriole dilation dynamics in mouse, rat and cat visual cortex using Alexa Fluor 633 together with neuronal activity using calcium indicators or blood flow using fluorescein dextran. Arteriole dilation decreased fluorescence recorded from immediately underlying neurons, representing a potential artifact during neuronal functional imaging experiments.

In invertebrate predators like the praying mantis and vertebrate predators such as wild cats, the ability to detect small differences in inter-ocular retinal disparities is a critical means for accurately determining the depth of moving objects such as prey1. In mammals, the first neurons along the visual pathway that encode binocular disparities are found in the visual cortex. However, a precise functional architecture for binocular disparity has never been demonstrated in any species, and coarse maps for disparity have been found in only one primate species2,3. Moreover, the dominant approach for assaying the developmental plasticity of binocular cortical neurons employed monocular tests of ocular dominance to infer binocular function4. The few studies that examined the relationship between ocular dominance and binocular disparity of individual cells used single-unit recordings and have provided conflicting results as to whether ocular dominance can predict the selectivity or sensitivity to binocular disparity5–9. Here we use two-photon calcium imaging to sample the response to monocular and binocular visual stimuli from nearly every adjacent neuron in a small region of the cat visual cortex, area 18. We show that local circuits for ocular dominance always have smooth and graded transitions from one apparently monocular functional domain to an adjacent binocular region. Most unexpectedly, we discovered a new map in the cat visual cortex that had a precise functional micro-architecture for binocular disparity selectivity. At the level of single cells, ocular dominance was unrelated to binocular disparity selectivity or sensitivity. When the local maps for ocular dominance and binocular disparity both had measurable gradients at a given cortical site, the two gradient directions were orthogonal to each other. Together, these results suggest that from the perspective of the spiking activity of individual neurons, ocular dominance cannot predict binocular disparity tuning. However, the precise local arrangement of ocular dominance and binocular disparity maps provide new clues on how monocular and binocular depth cues may be combined and decoded.

Electrical stimulation of the thalamus has been widely used to test for the existence of monosynaptic input to cortical neurons, typically with stimulation currents that evoke cortical spikes with high probability. We stimulated the lateral geniculate nucleus (LGN) of the thalamus and recorded monosynaptically evoked spikes from layer 4 neurons in visual cortex. We found that with moderate currents, cortical spikes were evoked with low to moderate probability and their occurrence was modulated by ongoing sensory (visual) input. Furthermore, when repeated at 8 -12 Hz, electrical stimulation of the thalamic afferents caused such profound inhibition that cortical spiking activity was suppressed, aside from electrically evoked monosynaptic spikes. Visual input to layer 4 cortical cells between electrical stimuli must therefore have derived exclusively from LGN afferents. We used white-noise visual stimuli to make a 2D map of the receptive field of each cortical simple cell during repetitive electrical stimulation in the LGN. The receptive field of electrically evoked monosynaptic spikes (and thus of the thalamic input alone) was significantly elongated. Its primary subfield was comparable to that of the control receptive field, but secondary (flanking) subfields were weaker. These findings extend previous results from intracellular recordings, but also demonstrate the effectiveness of an extracellular method of measuring subthreshold afferent input to cortex. O rientation selective neurons in primary visual cortex receive feed-forward input from lateral geniculate nucleus (LGN) cells that are themselves poorly oriented. Experiments that have examined the role of the feed-forward thalamocortical pathway in this receptive field transformation have yielded two independent findings. First, the thalamic input to cortical simple cells is highly specific; LGN cells make monosynaptic connections with simple cells predominantly when the pre-and postsynaptic receptive fields overlap and match in sign, size, and time course (1, 2). Second, when intracortical inputs are silenced by cooling or by electrical stimulation in cortex, intracellular recordings demonstrate that the summed thalamic input to a layer 4 simple cell is orientation selective (3, 4). Here, we present a technique that we have used to examine a related but hitherto untested hypothesis: that the spatial receptive field of a simple cell is very similar to the receptive field of its summed thalamic input. We have concentrated on two receptive-field parameters, the elongation of the strongest subfield and the relative strength of antagonistic, flanking subfields.The experimental approach that we took to examine these questions was based on two independent characteristics of electrical stimulation: (i) if electrical stimulation is not 100% effective in evoking cortical spikes, then the probability of evoking a spike will depend on the subthreshold activity of the cortical neuron at the time of the stimulus, and (ii) strong electrical stimulation leads to prolonged (...