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 μm 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.cell assemblies | Edelman | Hebb | brain development | learning H ebb's (1) contributions to the theory of learning and memory have shaped psychological, philosophical, and neuroscientific theories for over 60 y. Three of the concepts that he put forward were particularly important. The first defines a correlation-based learning rule, namely that when one neuron persistently drives another, then the connection between them will be strengthened. The second states that this leads to the formation of clustered synaptic coupling of neurons into cell assemblies whose network topologies are molded by experience; the third suggests that such elementary cell assemblies are synaptically linked by the same learning rule to form trains of percepts (a phase sequence), constituting thoughts (1-6). There is a vast body of evidence for all three concepts (5, 7-10).Despite this evidence, theorists have pointed out that the first postulate would cause synapses within cell assemblies to saturate, restricting their dynamic range and limiting memory storage capacity (11)(12)(13)(14)(15)(16)(17)(18)(19)(20). Experimental studies have confirmed that saturated long-term potentiation (LTP) is unfavorable to learning and memory (21,22). Although Hebb (1) had suggested a mechanism for passive weakening of unused synaptic connections, these objections suggested the need for an active depressive mechanism (16,17,23), inspiring the discoveries of long-term depression (LTD) (24) and bidirectional and spike timing-dependent plastici...

Functional organization of excitatory synaptic strength in primary visual cortex

“…5). Connections between bidirectionally connected pairs generated larger EPSPs than unidirectionally connected pairs, consistent with previous reports 3,4,17 , and the RF maps of bidirectionally connected neurons were significantly more correlated than RFs of unidirectionally connected or unconnected pairs (Extended Data Fig. 5).…”

Inferring cortical function in the mouse visual system through large-scale systems neuroscience

“…The connections and synaptic properties in the network models are established following distance-and cell type-dependent rules adopted from the literature (32)(33)(34)(35) as well as based on in-house data. Synaptic connections are established between neurons based on the locations of their cell bodies, with synapses placed randomly over the dendritic tree (dependent on the type of connection, such as excitatory to excitatory, inhibitory to excitatory, etc.…”

Time scales of memory, learning, and plasticity

“…Regarding the neural correlate of memory, potential memory items were found, for example, in songbirds during song and recapitulation as stereotypical sequences of spike burst (Hahnloser et al 2002) or during a spatial task, as spatiotemporal patterns (Harris et al 2003) in the hippocampus. Additionally, typical connectivity structures, so-called motifs, were measured in the cortex (Song et al 2005;Perin et al 2011). However, it is not clear whether spatiotemporal patterns or motifs are memory items [or cell assemblies, see (6)] and whether they are subject to long-term plasticity as suggested by Hebb.…”