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A synaptic organizing principle for cortical neuronal groups.

ABSTRACT: Neuronal circuitry is often considered a clean slate that can be dynamically and arbitrarily molded by experience. However, when we investigated synaptic connectivity in groups of pyramidal neurons in the neocortex, we found that both connectivity and synaptic weights were surprisingly predictable. Synaptic weights follow very closely the number of connections in a group of neurons, saturating after only 20% of possible connections are formed between neurons in a group. When we examined the network topology of connectivity between neurons, we found that the neurons cluster into small world networks that are not scale-free, with less than 2 degrees of separation. We found a simple clustering rule where connectivity is directly proportional to the number of common neighbors, which accounts for these small world networks and accurately predicts the connection probability between any two neurons. This pyramidal neuron network clusters into multiple groups of a few dozen neurons each. The neurons composing each group are surprisingly distributed, typically more than 100 ?m apart, allowing for multiple groups to be interlaced in the same space. In summary, we discovered a synaptic organizing principle that groups neurons in a manner that is common across animals and hence, independent of individual experiences. We speculate that these elementary neuronal groups are prescribed Lego-like building blocks of perception and that acquired memory relies more on combining these elementary assemblies into higher-order constructs.

SUBMITTER: Perin R

PROVIDER: S-EPMC3069183 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

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A synaptic organizing principle for cortical neuronal groups.

Perin Rodrigo R Berger Thomas K TK Markram Henry H

Proceedings of the National Academy of Sciences of the United States of America 20110307 13

Neuronal circuitry is often considered a clean slate that can be dynamically and arbitrarily molded by experience. However, when we investigated synaptic connectivity in groups of pyramidal neurons in the neocortex, we found that both connectivity and synaptic weights were surprisingly predictable. Synaptic weights follow very closely the number of connections in a group of neurons, saturating after only 20% of possible connections are formed between neurons in a group. When we examined the netw ...[more]

PMID: 21383177

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Project description:BackgroundWith the advent of whole-genome analysis for profiling tumor tissue, a pressing need has emerged for principled methods of organizing the large amounts of resulting genomic information. We propose the concept of multiplicity measures on cancer and gene networks to organize the information in a clinically meaningful manner. Multiplicity applied in this context extends Fearon and Vogelstein's multi-hit genetic model of colorectal carcinoma across multiple cancers.MethodsUsing the Catalogue of Somatic Mutations in Cancer (COSMIC), we construct networks of interacting cancers and genes. Multiplicity is calculated by evaluating the number of cancers and genes linked by the measurement of a somatic mutation. The Kamada-Kawai algorithm is used to find a two-dimensional minimum energy solution with multiplicity as an input similarity measure. Cancers and genes are positioned in two dimensions according to this similarity. A third dimension is added to the network by assigning a maximal multiplicity to each cancer or gene. Hierarchical clustering within this three-dimensional network is used to identify similar clusters in somatic mutation patterns across cancer types.ResultsThe clustering of genes in a three-dimensional network reveals a similarity in acquired mutations across different cancer types. Surprisingly, the clusters separate known causal mutations. The multiplicity clustering technique identifies a set of causal genes with an area under the ROC curve of 0.84 versus 0.57 when clustering on gene mutation rate alone. The cluster multiplicity value and number of causal genes are positively correlated via Spearman's Rank Order correlation (rs(8) = 0.894, Spearman's t = 17.48, p < 0.05). A clustering analysis of cancer types segregates different types of cancer. All blood tumors cluster together, and the cluster multiplicity values differ significantly (Kruskal-Wallis, H = 16.98, df = 2, p < 0.05).ConclusionWe demonstrate the principle of multiplicity for organizing somatic mutations and cancers in clinically relevant clusters. These clusters of cancers and mutations provide representations that identify segregations of cancer and genes driving cancer progression.

Project description:The molecular mechanism of long-term memory has been extensively studied in the context of the hippocampus-dependent recent memory examined within several days. However, months-old remote memory maintained in the cortex for long-term has not been investigated much at the molecular level yet. Various epigenetic mechanisms are known to be important for long-term memory, but how the 3D chromatin architecture and its regulator molecules contribute to neuronal plasticity and systems consolidation is still largely unknown. CCCTC-binding factor (CTCF) is an 11-zinc finger protein well known for its role as a genome architecture molecule. Male conditional knock-out mice in which CTCF is lost in excitatory neurons during adulthood showed normal recent memory in the contextual fear conditioning and spatial water maze tasks. However, they showed remarkable impairments in remote memory in both tasks. Underlying the remote memory-specific phenotypes, we observed that female CTCF conditional knock-out mice exhibit disrupted cortical LTP, but not hippocampal LTP. Similarly, we observed that CTCF deletion in inhibitory neurons caused partial impairment of remote memory. Through RNA sequencing, we observed that CTCF knockdown in cortical neuron culture caused altered expression of genes that are highly involved in cell adhesion, synaptic plasticity, and memory. These results suggest that remote memory storage in the cortex requires CTCF-mediated gene regulation in neurons, whereas recent memory formation in the hippocampus does not.SIGNIFICANCE STATEMENT CCCTC-binding factor (CTCF) is a well-known 3D genome architectural protein that regulates gene expression. Here, we use two different CTCF conditional knock-out mouse lines and reveal, for the first time, that CTCF is critically involved in the regulation of remote memory. We also show that CTCF is necessary for appropriate expression of genes, many of which we found to be involved in the learning- and memory-related processes. Our study provides behavioral and physiological evidence for the involvement of CTCF-mediated gene regulation in the remote long-term memory and elucidates our understanding of systems consolidation mechanisms.

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A synaptic organizing principle for cortical neuronal groups.

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A synaptic organizing principle for cortical neuronal groups.

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