Journal Scan – Calcium Imaging in Auditory and Visual Cortex

4 03 2010

A few papers on in vivo calcium imaging have just come out and are worth a careful read.

The first two examine the fine organization of layer 2/3 of the mouse auditory cortex.  The canonical view of auditory cortex organization is that neurons are arranged in a tonotopic pattern, with a smooth gradient in auditory frequency tuning across the surface of the cortex.  Using two-photon imaging in anesthetized mice, the groups saw that, while there was an overall gradient, the tuning of neighboring neurons was highly variable.  These are similar results to what Sato et al and Kerr et al found in the whisker barrel cortex back in 2007.  Moral of the story : mapping brain organization by microstimulation or sparse sampling (as in the classic papers) can be very misleading.

UPDATE : David Kleinfeld kindly directed me to the 40 year old work by Moshe Abeles and others that showed a similar spread in frequency tuning using microelectrodes…

Now, back to the more recent papers…

Functional organization and population dynamics in the mouse primary auditory cortexRothschild GNelken IMizrahi A. Nat Neurosci. 2010 Mar;13(3):353-60. Epub 2010 Jan 31.

Cortical processing of auditory stimuli involves large populations of neurons with distinct individual response profiles. However, the functional organization and dynamics of local populations in the auditory cortex have remained largely unknown. Using in vivo two-photon calcium imaging, we examined the response profiles and network dynamics of layer 2/3 neurons in the primary auditory cortex (A1) of mice in response to pure tones. We found that local populations in A1 were highly heterogeneous in the large-scale tonotopic organization. Despite the spatial heterogeneity, the tendency of neurons to respond together (measured as noise correlation) was high on average. This functional organization and high levels of noise correlations are consistent with the existence of partially overlapping cortical subnetworks. Our findings may account for apparent discrepancies between ordered large-scale organization and local heterogeneity.

In vivo two-photon calcium imaging from dozens of neurons simultaneously in A1.

Dichotomy of functional organization in the mouse auditory cortexBandyopadhyay SShamma SAKanold PO. Nat Neurosci. 2010 Mar;13(3):361-8. Epub 2010 Jan 31.

The sensory areas of the cerebral cortex possess multiple topographic representations of sensory dimensions. The gradient of frequency selectivity (tonotopy) is the dominant organizational feature in the primary auditory cortex, whereas other feature-based organizations are less well established. We probed the topographic organization of the mouse auditory cortex at the single-cell level using in vivo two-photon Ca(2+) imaging. Tonotopy was present on a large scale but was fractured on a fine scale. Intensity tuning, which is important in level-invariant representation, was observed in individual cells, but was not topographically organized. The presence or near absence of putative subthreshold responses revealed a dichotomy in topographic organization. Inclusion of subthreshold responses revealed a topographic clustering of neurons with similar response properties, whereas such clustering was absent in supra-threshold responses. This dichotomy indicates that groups of nearby neurons with locally shared inputs can perform independent parallel computations in the auditory cortex.

Tonotopy exists in A1 and AAF on a large scale, but not on small spatial scales.

The third paper uses a GECI (YC3.6) to do chronic imaging in visual cortex. Their results are noteworthy in that they look at visual responses to both a passive viewing and an ACTIVE discrimination task in an awake, head-fixed mouse.  The patterns of neural activity between anesthetized, awake but passively receiving sensory input, and awake while paying attention and using the sensory input are likely to be hugely different. Recording from neurons that are actively involved in a discrimination task is essential to understanding how the cortex is actually processing information.  Although this paper is more focused on simply presenting the technique rather than in depth analysis of the activity, we will be seeing more of this style of neuroscience in high-profile journals very soon…

Chronic cellular imaging of mouse visual cortex during operant behavior and passive viewing  –  Andermann ML, Kerlin AM and Reid RC, Front. Cell. Neurosci. 4:3.

Nearby neurons in mammalian neocortex demonstrate a great diversity of cell types and connectivity patterns. The importance of this diversity for computation is not understood. While extracellular recording studies in visual cortex have provided a particularly rich description of behavioral modulation of neural activity, new methods are needed to dissect the contribution of specific circuit elements in guiding visual perception. Here, we describe a method for three-dimensional cellular imaging of neural activity in the awake mouse visual cortex during active discrimination and passive viewing of visual stimuli. Head-fixed mice demonstrated robust discrimination for many hundred trials per day after initial task acquisition. To record from multiple neurons during operant behavior with single-trial resolution and minimal artifacts, we built a sensitive microscope for two-photon calcium imaging, capable of rapid tracking of neurons in three dimensions. We demonstrate stable recordings of cellular calcium activity during discrimination behavior across hours, days, and weeks, using both synthetic and genetically-encoded calcium indicators. When combined with molecular and genetic technologies in mice (e.g., cell-type specific transgenic labeling), this approach allows the identification of neuronal classes in vivo. Physiological measurements from distinct classes of neighboring neurons will enrich our understanding of the coordinated roles of diverse elements of cortical microcircuits in guiding sensory perception and perceptual learning. Further, our method provides a high-throughput, chronic in vivo assay of behavioral influences on cellular activity that is applicable to a wide range of mouse models of neurologic disease.

Mapping visual responses in identified excitatory and inhibitory neurons in awake mice

Updated: fMRI Based Visual Stimulus Reconstruction

11 12 2008

A simple view of what the brain does is acquire input, process it, then produce output. One strategy for understanding what processing takes place is to record the patterns of brain activity while showing many patterns of input, then see if you can use the information gained to predict a novel input, given the pattern of brain activity. The canonical example of this approach is visual input reconstruction based on recorded spike trains in the visual system of the blowfly.

The blowfly is a relatively simple system (though quite efficient) with a tiny brain. Could a similar approach work in humans?  Although we can’t drop electrodes into the visual cortex (usually), we can put people in fMRI scanners to visualize the pattern of blood oxygenation, which is correlated with neural activity.

In Visual Image Reconstruction from Human Brain Activity using a Combination of Multiscale Local Image Decoders, Miyawaki et al demonstrate visual input prediction using fMRI responses. Using 3mm3 voxels, the group measured the activity level across early visual cortex (V1-V4) for numerous 10×10 binary patterns of visual stimuli. They looked at correlations in 1×1, 1×2, 2×1 and 2×2 bins of voxel activity to hundreds of visual test patterns. The activity represented local image elements. Then they displayed novel visual input and used a linear combination of the local image element responses to predict the visual input from the brain activity alone. It is noteworthy that they only required several hundred training images before visual input prediction was possible.

Predicted visual input from fMRI activity in V1 and V2

Predicted visual input from fMRI activity in V1 and V2

Note that a rentinotopic map, where the relative spatial position of visual input is reflected in the activity across the visual cortex, is not strictly required for this technique to work. What is required is that the response of each local element is consistent across similar patterns of input in the element’s receptive field. Furthermore, the spatial scale of pattern representation in early processing regions of human visual cortex is broad enough to be picked up by the fMRI scanner.

It would be interesting to see how much higher visual resolution could be predicted with an fMRI approach. Could this approach be adapted to predict input from the responses of cells with more complex receptive fields in higher cortical areas? Or, are those cells too intermingled with neighbors with vastly different response properties to be separable by fMRI?  Higher areas are vital for our own brains to rapidly perceive the contours of complex images. I’d also like to see how well non-contiguous images are predicted.

Cellular resolution calcium imaging with bulk loaded dyes has been used to map fine-grained detail of receptive fields in lower animals visual and somatosensory cortex. Is input prediction possible from these recordings? Is the input training set too limited? Could more complex input be perceived using a fewer number of complex cells from higher visual areas (V2 and above)?