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Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex

The mammalian neocortex is composed of many types of excitatory and inhibitory neurons, each with specific electrophysiological and biochemical ...

RIKEN Brain Science Institute

The glial cells missing (gcm) gene in Drosophila encodes a GCM-motif transcription factor that functions as a binary switch to select between glial and neuronal cell fates. To understand the function of gcm in vertebrates, we isolated the zebrafish gcmb and analyzed the function of this gene using antisense morpholino oligonucleotides against gcmb mRNA (gcmb-MO) and transgenic overexpression. Zebrafish gcmb is expressed in the pharyngeal arch epithelium and in cells of the macrophage lineage. gcmb-MO-injected larvae show significantly reduced branchial arch cartilages. fgf3-MO-injected larvae display a similar phenotype to that of gcmb-MO-injected larvae with respect to the lack of pharyngeal cartilage formation. In addition, gcmb expression in the pharyngeal arches is down-regulated in fgf3-MO-injected larvae. The gcmb transgenic larvae show a protrusion of the lower jaw and abnormal spatial arrangement of the pharyngeal cartilage elements. These results suggest that gcmb is required for normal pharyngeal cartilage formation in zebrafish and that its expression is dependent on fgf3 activity.

Zebrafish gcmb is required for pharyngeal cartilage formation.

The reasons for using natural stimuli to study sensory function are quickly mounting, as recent studies have revealed important differences in neural responses to natural and artificial stimuli. However, natural stimuli typically contain strong correlations and are spherically asymmetric (i.e. stimulus intensities are not symmetrically distributed around the mean), and these statistical complexities can bias receptive field (RF) estimates when standard techniques such as spike-triggered averaging or reverse correlation are used. While a number of approaches have been developed to explicitly correct the bias due to stimulus correlations, there is no complementary technique to correct the bias due to stimulus asymmetries. Here, we develop a method for RF estimation that corrects reverse correlation RF estimates for the spherical asymmetries present in natural stimuli. Using simulated neural responses, we demonstrate how stimulus asymmetries can bias reverse-correlation RF estimates (even for uncorrelated stimuli) and illustrate how this bias can be removed by explicit correction. We demonstrate the utility of the asymmetry correction method under experimental conditions by estimating RFs from the responses of retinal ganglion cells to natural stimuli and using these RFs to predict responses to novel stimuli.

Estimating receptive fields from responses to natural stimuli with asymmetric intensity distributions.

"How is information decoded in the brain?" is one of the most difficult and important questions in neuroscience. We have developed a general framework for investigating to what extent the decoding process in the brain can be simplified. First, we hierarchically constructed simplified probabilistic models of neural responses that ignore more than Kth-order correlations using the maximum entropy principle. We then computed how much information is lost when information is decoded using these simplified probabilistic models (i.e., "mismatched decoders"). To evaluate the information obtained by mismatched decoders, we introduced an information theoretic quantity, I*, which was derived by extending the mutual information in terms of communication rate across a channel. We showed that I* provides consistent results with the minimum mean-square error as well as the mutual information, and demonstrated that a previously proposed measure quantifying the importance of correlations in decoding substantially deviates from I* when many cells are analyzed. We then applied this proposed framework to spike data for vertebrate retina using short natural scene movies of 100 ms duration as a set of stimuli and computing the information contained in neural activities. Although significant correlations were observed in population activities of ganglion cells, information loss was negligibly small even if all orders of correlation were ignored in decoding. We also found that, if we inappropriately assumed stationarity for long durations in the information analysis of dynamically changing stimuli, such as natural scene movies, correlations appear to carry a large proportion of total information regardless of their actual importance.

Mismatched decoding in the brain.

The zebrafish dorsal habenula (dHb) shows conspicuous asymmetry in its connection with the interpeduncular nucleus (IPN) and is equivalent to the mammalian medial habenula. Genetic inactivation of the lateral subnucleus of dHb (dHbL) biased fish towards freezing rather than the normal flight response to a conditioned fear stimulus, suggesting that the dHbL-IPN pathway is important for controlling experience-dependent modification of fear responses.

The habenula is crucial for experience-dependent modification of fear responses in zebrafish.

A major question in neocortical research is the extent to which neuronal organization is stereotyped. Previous studies have revealed functional clustering and neuronal interactions among cortical neurons located within tens of micrometers in the tangential orientation (orientation parallel to the pial surface). In the tangential orientation at this scale, however, it is unknown whether the distribution of neuronal subtypes is random or has any stereotypy. We found that the tangential arrangement of subcerebral projection neurons, which are a major pyramidal neuron subtype in mouse layer V, was not random but significantly periodic. This periodicity, which was observed in multiple cortical areas, had a typical wavelength of 30 μm. Under specific visual stimulation, neurons in single repeating units exhibited strongly correlated c-Fos expression. Therefore, subcerebral projection neurons have a periodic arrangement, and neuronal activity leading to c-Fos expression is similar among neurons in the same repeating units. These results suggest that the neocortex has a periodic functional micro-organization composed of a major neuronal subtype in layer V.

Periodic organization of a major subtype of pyramidal neurons in neocortical layer V.

The mammalian neocortex contains many cell types, but whether they organize into repeated structures has been unclear. We discovered that major cell types in neocortical layer 5 form a lattice structure in many brain areas. Large-scale three-dimensional imaging revealed that distinct types of excitatory and inhibitory neurons form cell type-specific radial clusters termed microcolumns. Thousands of microcolumns, in turn, are patterned into a hexagonal mosaic tessellating diverse regions of the neocortex. Microcolumn neurons demonstrate synchronized in vivo activity and visual responses with similar orientation preference and ocular dominance. In early postnatal development, microcolumns are coupled by cell type-specific gap junctions and later serve as hubs for convergent synaptic inputs. Thus, layer 5 neurons organize into a brainwide modular system, providing a template for cortical processing.

Article	Year
Zebrafish gcmb is required for pharyngeal cartilage formation. Mechanisms of development\| PubMed ID: 15327784	2004
Estimating receptive fields from responses to natural stimuli with asymmetric intensity distributions. PloS one\| PubMed ID: 18725977	2008
Mismatched decoding in the brain. The Journal of neuroscience : the official journal of the Society for Neuroscience\| PubMed ID: 20357132	2010
The habenula is crucial for experience-dependent modification of fear responses in zebrafish. Nature neuroscience\| PubMed ID: 20935642	2010
Periodic organization of a major subtype of pyramidal neurons in neocortical layer V. The Journal of neuroscience : the official journal of the Society for Neuroscience\| PubMed ID: 22171052	2011
Lattice system of functionally distinct cell types in the neocortex. Science (New York, N.Y.)\| PubMed ID: 29097542	2017

Toshihiko Hosoya

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