Spatial organization of astrocytes in ferret visual cortex.

Astrocytes form an intricate partnership with neural circuits to influence numerous cellular and synaptic processes. One prominent organizational feature of astrocytes is the "tiling" of the brain with non-overlapping territories. There are some documented species and brain region-specific astrocyte specializations, but the extent of astrocyte diversity and circuit specificity are still unknown. We quantitatively defined the rules that govern the spatial arrangement of astrocyte somata and territory overlap in ferret visual cortex using a combination of in vivo two-photon imaging, morphological reconstruction, immunostaining, and model simulations. We found that ferret astrocytes share, on average, half of their territory with other astrocytes. However, a specific class of astrocytes, abundant in thalamo-recipient cortical layers ("kissing" astrocytes), overlap markedly less. Together, these results demonstrate novel features of astrocyte organization indicating that different classes of astrocytes are arranged in a circuit-specific manner and that tiling does not apply universally across brain regions and species. J. Comp. Neurol. 524:3561-3576, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

Simple method to improve spatial resolution for in vivo two-photon fluorescence imaging.

There is a growing effort to image single neurons in vivo, and observe their individual contribution to the brain's functional organization. This effort generally relies on two-photon imaging to explore the structure and activity of cortical columns extending beneath the brain's surface. The need to protect living tissue, however, demands the introduction of coverslips and similar objects that can modify the optics of the imaging beam. This paper develops three-dimensional (3D) analytical and numerical models to characterize and correct for the resulting degradation of image quality. We have illustrated the use of these models by describing a simple, practical technique to reduce the effect of spherical aberration for in vivo two-photon fluorescence experiments.

Spatial Attention and Temporal Expectation Under Timed Uncertainty Predictably Modulate Neuronal Responses in Monkey V1.

The brain uses attention and expectation as flexible devices for optimizing behavioral responses associated with expected but unpredictably timed events. The neural bases of attention and expectation are thought to engage higher cognitive loci; however, their influence at the level of primary visual cortex (V1) remains unknown. Here, we asked whether single-neuron responses in monkey V1 were influenced by an attention task of unpredictable duration. Monkeys covertly attended to a spot that remained unchanged for a fixed period and then abruptly disappeared at variable times, prompting a lever release for reward. We show that monkeys responded progressively faster and performed better as the trial duration increased. Neural responses also followed monkey's task engagement-there was an early, but short duration, response facilitation, followed by a late but sustained increase during the time monkeys expected the attention spot to disappear. This late attentional modulation was significantly and negatively correlated with the reaction time and was well explained by a modified hazard function. Such bimodal, time-dependent changes were, however, absent in a task that did not require explicit attentional engagement. Thus, V1 neurons carry reliable signals of attention and temporal expectation that correlate with predictable influences on monkeys' behavioral responses.

Cortical maps: a role for astrocytes?

Astrocytes are a multifunctional cell type in the nervous system that can influence neurons and synapses in numerous ways. Astrocytes have been suggested to play important roles in synapse formation during development, as well as in multiple forms of synaptic plasticity in the developing and adult brain. Astrocytes respond to nearby neural activity with elevations in cytosolic calcium concentration, and in sensory cortex these calcium responses have been shown to be topographically aligned to neuronal sensory maps. Here, we review recent evidence for astrocyte interactions with neural circuits, with particular emphasis on how these interactions may shape the development, arrangement and plasticity of cortical sensory maps.

Two-way communication with neural networks in vivo using focused light.

Neuronal networks process information in a distributed, spatially heterogeneous manner that transcends the layout of electrodes. In contrast, directed and steerable light offers the potential to engage specific cells on demand. We present a unified framework for adapting microscopes to use light for simultaneous in vivo stimulation and recording of cells at fine spatiotemporal resolutions. We use straightforward optics to lock onto networks in vivo, to steer light to activate circuit elements and to simultaneously record from other cells. We then actualize this 'free' augmentation on both an 'open' two-photon microscope and a leading commercial one. By following this protocol, setup of the system takes a few days, and the result is a noninvasive interface to brain dynamics based on directed light, at a network resolution that was not previously possible and which will further improve with the rapid advance in development of optical reporters and effectors. This protocol is for physiologists who are competent with computers and wish to extend hardware and software to interface more fluidly with neuronal networks.

Functional biases in visual cortex neurons with identified projections to higher cortical targets.

BACKGROUND: Visual perception involves information flow from lower- to higher-order cortical areas, which are known to process different kinds of information. How does this functional specialization arise? As a step toward addressing this question, we combined fluorescent retrograde tracing with in vivo two-photon calcium imaging to simultaneously compare the tuning properties of neighboring neurons in areas 17 and 18 of ferret visual cortex that have different higher cortical projection targets. RESULTS: Neurons projecting to the posterior suprasylvian sulcus (PSS) were more direction selective and preferred shorter stimuli, higher spatial frequencies, and higher temporal frequencies than neurons projecting to area 21, anticipating key differences between the functional properties of the target areas themselves. These differences could not be explained by a correspondence between anatomical and functional clustering within early visual cortex, and the largest differences were in properties generated within early visual cortex (direction selectivity and length preference) rather than in properties present in its retinogeniculate inputs. CONCLUSIONS: These projection cell groups, and hence the higher-order visual areas to which they project, likely obtain their functional properties not from biased retinogeniculate inputs but from highly specific circuitry within the cortex.

Influence of a subtype of inhibitory interneuron on stimulus-specific responses in visual cortex.

Inhibition modulates receptive field properties and integrative responses of neurons in cortical circuits. The contribution of specific interneuron classes to cortical circuits and emergent responses is unknown. Here, we examined neuronal responses in primary visual cortex (V1) of adult Dlx1(-/-) mice, which have a selective reduction in cortical dendrite-targeting interneurons (DTIs) that express calretinin, neuropeptide Y, and somatostatin. The V1 neurons examined in Dlx1(-/-) mice have reduced orientation selectivity and altered firing rates, with elevated late responses, suggesting that local inhibition at dendrites has a specific role in modulating neuronal computations. We did not detect overt changes in the physiological properties of thalamic relay neurons and features of thalamocortical projections, such as retinotopic maps and eye-specific inputs, in the mutant mice, suggesting that the defects are cortical in origin. These experimental results are well explained by a computational model that integrates broad tuning from dendrite-targeting and narrower tuning from soma-targeting interneuron subclasses. Our findings suggest a key role for DTIs in the fine-tuning of stimulus-specific cortical responses.

Denoising two-photon calcium imaging data.

Two-photon calcium imaging is now an important tool for in vivo imaging of biological systems. By enabling neuronal population imaging with subcellular resolution, this modality offers an approach for gaining a fundamental understanding of brain anatomy and physiology. Proper analysis of calcium imaging data requires denoising, that is separating the signal from complex physiological noise. To analyze two-photon brain imaging data, we present a signal plus colored noise model in which the signal is represented as harmonic regression and the correlated noise is represented as an order autoregressive process. We provide an efficient cyclic descent algorithm to compute approximate maximum likelihood parameter estimates by combing a weighted least-squares procedure with the Burg algorithm. We use Akaike information criterion to guide selection of the harmonic regression and the autoregressive model orders. Our flexible yet parsimonious modeling approach reliably separates stimulus-evoked fluorescence response from background activity and noise, assesses goodness of fit, and estimates confidence intervals and signal-to-noise ratio. This refined separation leads to appreciably enhanced image contrast for individual cells including clear delineation of subcellular details and network activity. The application of our approach to in vivo imaging data recorded in the ferret primary visual cortex demonstrates that our method yields substantially denoised signal estimates. We also provide a general Volterra series framework for deriving this and other signal plus correlated noise models for imaging. This approach to analyzing two-photon calcium imaging data may be readily adapted to other computational biology problems which apply correlated noise models.

Response features of parvalbumin-expressing interneurons suggest precise roles for subtypes of inhibition in visual cortex.

Inhibitory interneurons in the cerebral cortex include a vast array of subtypes, varying in their molecular signatures, electrophysiological properties, and connectivity patterns. This diversity suggests that individual inhibitory classes have unique roles in cortical circuits; however, their characterization to date has been limited to broad classifications including many subtypes. We used the Cre/LoxP system, specifically labeling parvalbumin(PV)-expressing interneurons in visual cortex of PV-Cre mice with red fluorescent protein (RFP), followed by targeted loose-patch recordings and two-photon imaging of calcium responses in vivo to characterize the visual receptive field properties of these cells. Despite their relative molecular and morphological homogeneity, we find that PV+ neurons have a diversity of feature-specific visual responses that include sharp orientation and direction-selectivity, small receptive fields, and band-pass spatial frequency tuning. These results suggest that subsets of parvalbumin interneurons are components of specific cortical networks and that perisomatic inhibition contributes to the generation of precise response properties.

A statistical model for multiphoton calcium imaging of the brain.

Multiphoton calcium fluorescence imaging has gained prominence as a valuable tool for the study of brain cells, but the corresponding analytical regimes remain rather naive. In this paper, we develop a statistical framework that facilitates principled quantitative analysis of multiphoton images. The proposed methods discriminate the stimulus-evoked response of a neuron from the background firing and image artifacts. We develop a harmonic regression model with colored noise, and estimate the model parameters with computationally efficient algorithms. We apply this model to in vivo characterization of cells from the ferret visual cortex. The results demonstrate substantially improved tuning curve fitting and image contrast.

The operating regime of local computations in primary visual cortex.

In V1, local circuitry depends on the position in the orientation map: close to pinwheel centers, recurrent inputs show variable orientation preferences; within iso-orientation domains, inputs are relatively uniformly tuned. Physiological properties such as cell's membrane potentials, spike outputs, and temporal characteristics change systematically with map location. We investigate in a firing rate and a Hodgkin-Huxley network model what constraints these tuning characteristics of V1 neurons impose on the cortical operating regime. Systematically varying the strength of both recurrent excitation and inhibition, we test a wide range of model classes and find the likely models to account for the experimental observations. We show that recent intracellular and extracellular recordings from cat V1 provide the strongest evidence for a regime where excitatory and inhibitory recurrent inputs are balanced and dominate the feed-forward input. Our results are robust against changes in model assumptions such as spatial extent and strength of lateral inhibition. Intriguingly, the most likely recurrent regime is in a region of parameter space where small changes have large effects on the network dynamics, and it is close to a regime of "runaway excitation," where the network shows strong self-sustained activity. This could make the cortical response particularly sensitive to modulation.

Tuned responses of astrocytes and their influence on hemodynamic signals in the visual cortex.

Astrocytes have long been thought to act as a support network for neurons, with little role in information representation or processing. We used two-photon imaging of calcium signals in the ferret visual cortex in vivo to discover that astrocytes, like neurons, respond to visual stimuli, with distinct spatial receptive fields and sharp tuning to visual stimulus features including orientation and spatial frequency. The stimulus-feature preferences of astrocytes were exquisitely mapped across the cortical surface, in close register with neuronal maps. The spatially restricted stimulus-specific component of the intrinsic hemodynamic mapping signal was highly sensitive to astrocyte activation, indicating that astrocytes have a key role in coupling neuronal organization to mapping signals critical for noninvasive brain imaging. Furthermore, blocking astrocyte glutamate transporters influenced the magnitude and duration of adjacent visually driven neuronal responses.

Dynamics of orientation tuning in cat v1 neurons depend on location within layers and orientation maps.

Analysis of the timecourse of the orientation tuning of responses in primary visual cortex (V1) can provide insight into the circuitry underlying tuning. Several studies have examined the temporal evolution of orientation selectivity in V1 neurons, but there is no consensus regarding the stability of orientation tuning properties over the timecourse of the response. We have used reverse-correlation analysis of the responses to dynamic grating stimuli to re-examine this issue in cat V1 neurons. We find that the preferred orientation and tuning curve shape are stable in the majority of neurons; however, more than forty percent of cells show a significant change in either preferred orientation or tuning width between early and late portions of the response. To examine the influence of the local cortical circuit connectivity, we analyzed the timecourse of responses as a function of receptive field type, laminar position, and orientation map position. Simple cells are more selective, and reach peak selectivity earlier, than complex cells. There are pronounced laminar differences in the timing of responses: middle layer cells respond faster, deep layer cells have prolonged response decay, and superficial cells are intermediate in timing. The average timing of neurons near and far from pinwheel centers is similar, but there is more variability in the timecourse of responses near pinwheel centers. This result was reproduced in an established network model of V1 operating in a regime of balanced excitatory and inhibitory recurrent connections, confirming previous results. Thus, response dynamics of cortical neurons reflect circuitry based on both vertical and horizontal location within cortical networks.

In vivo two-photon imaging reveals a role of arc in enhancing orientation specificity in visual cortex.

Cortical representations of visual information are modified by an animal's visual experience. To investigate the mechanisms in mice, we replaced the coding part of the neural activity-regulated immediate early gene Arc with a GFP gene and repeatedly monitored visual experience-induced GFP expression in adult primary visual cortex by in vivo two-photon microscopy. In Arc-positive GFP heterozygous mice, the pattern of GFP-positive cells exhibited orientation specificity. Daily presentations of the same stimulus led to the reactivation of a progressively smaller population with greater reactivation reliability. This adaptation process was not affected by the lack of Arc in GFP homozygous mice. However, the number of GFP-positive cells with low orientation specificity was greater, and the average spike tuning curve was broader in the adult homozygous compared to heterozygous or wild-type mice. These results suggest a physiological function of Arc in enhancing the overall orientation specificity of visual cortical neurons during the post-eye-opening life of an animal.

Bottom-up and top-down dynamics in visual cortex.

A key emergent property of the primary visual cortex (V1) is the orientation selectivity of its neurons. Recent experiments demonstrate remarkable bottom-up and top-down plasticity in orientation networks of the adult cortex. The basis for such dynamics is the mechanism by which orientation tuning is created and maintained, by integration of thalamocortical and intracortical inputs. Intracellular measurements of excitatory and inhibitory synaptic conductances reveal that excitation and inhibition balance each other at all locations in the cortex. This balance is particularly critical at pinwheel centers of the orientation map, where neurons receive intracortical input from a wide diversity of local orientations. The orientation tuning of neurons in adult V1 changes systematically after short-term exposure to one stimulus orientation. Such reversible physiological shifts in tuning parallel the orientation tilt aftereffect observed psychophysically. Neurons at or near pinwheel centers show pronounced changes in orientation preference after adaptation with an oriented stimulus, while neurons in iso-orientation domains show minimal changes. Neurons in V1 of alert, behaving monkeys also exhibit short-term orientation plasticity after very brief adaptation with an oriented stimulus, on the time scale of visual fixation. Adaptation with stimuli that are orthogonal to a neuron's preferred orientation does not alter the preferred orientation but sharpens orientation tuning. Thus, successive fixation on dissimilar image patches, as happens during natural vision, combined with mechanisms of rapid cortical plasticity, actually improves orientation discrimination. Finally, natural vision involves judgements about where to look next, based on an internal model of the visual world. Experiments in behaving monkeys in which information about future stimulus locations can be acquired in one set of trials but not in another demonstrate that V1 neurons signal the acquisition of internal representations. Such Bayesian updating of responses based on statistical learning is fundamental for higher level vision, for deriving inferences about the structure of the visual world, and for the regulation of eye movements.

Invariant computations in local cortical networks with balanced excitation and inhibition.

Cortical computations critically involve local neuronal circuits. The computations are often invariant across a cortical area yet are carried out by networks that can vary widely within an area according to its functional architecture. Here we demonstrate a mechanism by which orientation selectivity is computed invariantly in cat primary visual cortex across an orientation preference map that provides a wide diversity of local circuits. Visually evoked excitatory and inhibitory synaptic conductances are balanced exquisitely in cortical neurons and thus keep the spike response sharply tuned at all map locations. This functional balance derives from spatially isotropic local connectivity of both excitatory and inhibitory cells. Modeling results demonstrate that such covariation is a signature of recurrent rather than purely feed-forward processing and that the observed isotropic local circuit is sufficient to generate invariant spike tuning.

Local networks in visual cortex and their influence on neuronal responses and dynamics.

Networks of neurons in the cerebral cortex generate complex outputs that are not simply predicted by their inputs. These emergent responses underlie the function of the cortex. Understanding how cortical networks carry out such transformations requires a description of the responses of individual neurons and of their networks at multiple levels of analysis. We focus on orientation selectivity in primary visual cortex as a model system to understand cortical network computations. Recent experiments in our laboratory and others provide significant insight into how cortical networks generate and maintain orientation selectivity. We first review evidence for the diversity of orientation tuning characteristics in visual cortex. We then describe experiments that combine optical imaging of orientation maps with intracellular and extracellular recordings from individual neurons at known locations in the orientation map. The data indicate that excitatory and inhibitory synaptic inputs are summed across the cortex in a manner that is consistent with simple rules of integration of local inputs. These rules arise from known anatomical projection patterns in visual cortex. We propose that the generation and plasticity of orientation tuning is strongly influenced by local cortical networks-the diversity of these properties arises in part from the diversity of neighbourhood features that derive from the orientation map.

Synaptic integration by V1 neurons depends on location within the orientation map.

Neurons in the primary visual cortex (V1) are organized into an orientation map consisting of orientation domains arranged radially around "pinwheel centers" at which the representations of all orientations converge. We have combined optical imaging of intrinsic signals with intracellular recordings to estimate the subthreshold inputs and spike outputs of neurons located near pinwheel centers or in orientation domains. We find that neurons near pinwheel centers have subthreshold responses to all stimulus orientations but spike responses to only a narrow range of orientations. Across the map, the selectivity of inputs covaries with the selectivity of orientations in the local cortical network, while the selectivity of spike outputs does not. Thus, the input-output transformation performed by V1 neurons is powerfully influenced by the local structure of the orientation map.

Cortical plasticity: time for a change.

Two recent studies have tested whether synaptic learning rules, inferred earlier from work on cell cultures and brain slices, apply in intact brains. The evidence indicates that they do, and reveals interesting implications for brain development and perceptual learning.