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 plasticity (STDP) (25). Bidirectional plasticity provided a plausible mechanism for synaptic weights to assume arbitrary values depending on correlated activity among neurons. In artificial neural networks incorporating these modified Hebbian mechanisms, experience can mold the network topology of cell assemblies, endowing them with remarkable information processing and memory capabilities (11-20). However, these models are based on two key assumptions. The first is that memory is stored in the configuration of the connectivity of neurons in an assembly and in the set of synaptic weights of the connections; the second is that experience can freely mold the network connectivity and synaptic weights. What is known about the network topology of cortical microcircuits? Intracellular recordings from multiple neurons have shown that different types of neurons have different connection probabilities and different numbers and distributions of synapses (26) (27) (28) (29) (30) . Connection probabilities between neocortical neurons also vary according to the layer in which they reside (31, 32), the brain regions to which they project, and the brain regions from which they receive input (33, 34) . Although these findings provide evidence for synaptic clustering, it is likely that these forms of clustering also involve genetically determined, topographical, and neuron-specific connectivity principles (35-38). Evidence for synaptic clustering between neurons of the same type in a microcircuit began with the finding that layer 5 pyramidal neurons are reciprocally connected more often than expected from their unidirectional connection probabilities (39). A systematic study of triplets of these same pyramidal neurons by Song et al. (40) led to the discovery of three-cell motifs of connectivity. There is considerable evidence for circuit plasticity between neocortical pyramidal neurons. When neurons lie within about 50 μm of each other (i.e., within the dimensions of a minicolumn), the axon of every pyramidal neuron is structurally connected to the dendrites of virtually every other pyramidal neuron in the immediate vicinity (41). This structural tabula rasa offers enormous opportunities for functional rewiring of neuron connectivities without major growth and reorganization of their neural arbors (42-44). Indeed, the synaptic circuitry of these layer 5 pyramidal neurons dynamically rewires after stimulation (45), indicating that activity can influence synaptic connectivity. Transmission across these established synaptic connections also undergoes lasting changes (46) driven by the relative timing of spikes emitted by pre-and postsynaptic neurons (47), providing a mechanism for stimuli to specifically mold the synaptic weights. Indeed, numerous models have shown that timing-dependent bidirectional plasticity rules have the potential to uniquely configure cell assemblies in ways that represent specific stimuli, allowing assemblies to learn from experience (48-52). What is not known, however, is whether such plasticity mechanisms have free range to arbitrarily mold neuron assemblies starting from a clean slate, as suggested by the structural tabula rasa, or whether they must operate under constraints of some prescribed Author contributions: H.M. conceived the 12-patch system and experiments; R.P. built the 12-patch system; R.P. and T.K.B. performed experiments; R.P. and H.M. analyzed the data; and H.M. and R.P. wrote the paper. The authors declare no conflict of interest. This article is a PNAS Direct Submission. Freely available online through the PNAS open access option.
Perin et al. showed evidence for synaptic clustering, where small groups of neurons (a few dozen) form small-world networks without hubs REF .
A synaptic organizing principle for cortical neuronal groups
Proceedings of the National Academy of Sciences of the United States of America
Proceedings of the National Academy of Sciences of the United States of America
Computer Science Medicine