Small world with a difference

The Blue Brain Project at Lausanne, led by Henry Markram, is to my mind, the most interesting and promising meeting of computer science and neurobiology. They recently published a paper (see citation) on the connectivity in the newborn visual cortex. They showed that neurons in small groups were interconnected independent of experience and that the connection between these groups was the level at which experience must operate. This is very definitely not a blank slate but rather a distinct architecture on which perception rests. It seems probable that animals are born with the equipment to perceive the world – we all perceive the world similarly. But how we interpret, learn from and react to that perception is plastic and molded by experience.

 

Here is the 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 um 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.

 

Quoting the Blue Brain EPFL site:

The researchers were able to demonstrate that small clusters of pyramidal neurons in the neocortex interconnect according to a set of immutable and relatively simple rules…These clusters contain an estimated fifty neurons, on average. The scientists look at them as essential building blocks, which contain in themselves a kind of fundamental, innate knowledge – for example, representations of certain simple workings of the physical world. Acquired knowledge, such as memory, would involve combining these elementary building blocks at a higher level of the system. “This could explain why we all share similar perceptions of physical reality, while our memories reflect our individual experience”, explains Markram…If the circuits had only been formed from the experiences lived by the different animals, the values should have diverged considerably from one individual to the next. Thus, the neuronal connectivity must in some way have been programmed in advance. …Current technology is now allowing us to qualify the “tabula rasa” hypothesis, which argues that our brains are a “blank slate” at birth, and we only gain knowledge through experience. It’s an idea that has permeated science for centuries. There is no question that knowledge, in the sense that we typically understand it (reading and writing, recognizing our friends, learning a language), is the result of our experiences. But the EPFL team’s work demonstrates that some of our fundamental representations or basic knowledge is inscribed in our genes. This discovery redistributes the balance between innate and acquired, and represents a considerable advance in our understanding of how the brain works.

 

The paper discusses the differences between the models of Edelman and Hebbs:

This study reports a form of synaptic clustering in neocortical microcircuits, where call assemblies are not arranged randomly or in a lattice but as small world networks without hubs. This assemblies extend beyond the diameter of neocortical miniclumns, probably contain only a few dozen neurons, and are interlaced with other assemblies within the same space. … The finding that connection probability between neurons and the mean synaptic weight within groups of neurons is predictable and tightly related to each other indicates that experiences cannot freely mold network topology and synaptic weights. … We speculate that this synaptic organizing principle is genetically prescribed and developmentally expressed, because it applies across different animals. … The synaptic clustering we found provides experimental evidence for the primary repertoires proposed earlier by the theory of neuronal group selection by Edelman. Unlike Hebb’s proposal, this theory suggests that functional neural circuitry arises by selection among neuronal groups that already emerged during embryonic development independent of experience. In Edelman’s theory, subsequent experience selects neuronal groups to form secondary repertoires that have survival value. In Hebb’s view, experience carves out and reinforces chains of such elementary assemblies to form phase sequences supporting specific trains of thought. A key difference between Edelman’s theory and Hebb’s proposals is reflected by Edelman’s emphasis on selection, as apposed to instruction, of repertoires of neuronal groups iteratively during perception in a process called reentry. … The elementary assemblies that we found are interconnected by fewer and weaker strands of connections than within assemblies, which are more amenable to experience-dependent modification.

 

ResearchBlogging.org

Perin, R., Berger, T., & Markram, H. (2011). A synaptic organizing principle for cortical neuronal groups Proceedings of the National Academy of Sciences, 108 (13), 5419-5424 DOI: 10.1073/pnas.1016051108

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