Is intelligence the result of nurture or nature?

Among the neuroscientists who research how the brain works to process and encode information, there's a simple saying that summarizes their understanding of the basic biology involved, which would give the answer to that question to be "nurture":

"Cells that fire together, wire together."

The cells in this case would be groups of neurons, where the phrase describes how many neuroscientists believe these cells within a brain process new information by "firing" to create neural networks whenever a new stimulus is experienced. If that stimulus is experienced over and over again, the brain responds by triggering the same groups of neurons tied to the same sensory inputs again and again, where memory and learning is established through a form of path dependence, where the connections between the neurons are strengthened by their repeated firings in response the same stimulus, thanks in good part to the work of a "master switch" found in the brain's individual neurons: the NMDA receptor.

But the results of new research suggest that the neurons within the brain may be working in a wholly different way to process and learn new information. Instead of the adaptive "fire and wire" experiential learning system described by the older research, the newer research suggests that the brain's neural networks are already prewired together, which when exposed to stimuli, are combined into what the neuroscientists call "functional connectivity motifs" according to a simple mathematical relationship.

So, instead of its neural pathways being generated entirely through experience, the way the brain is wired together is inherently built into its structure, where its "nature" is what causes learning and memory to work the way they do. Here's the abstract from the recently published paper describing the new findings:

There is considerable scientific interest in understanding how cell assemblies—the long-presumed computational motif—are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic (N = 2ⁱ–1), producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories, as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive, emotional and social information. However, modulatory neurons, such as dopaminergic (DA) neurons, use a simpler logic despite their distinct subtypes. Interestingly, this specific-to-general permutation logic remained largely intact although NMDA receptors—the synaptic switch for learning and memory—were deleted throughout adulthood, suggesting that the logic is developmentally pre-configured. Moreover, this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques—which preferentially encode specific and low-combinatorial features and project inter-cortically—is ideal for maximizing cross-modality novel pattern-extraction, pattern-discrimination and pattern-categorization using sparse code, consequently explaining why it requires hippocampal offline-consolidation. In contrast, the nonrandomness in layers 5/6—which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems—is ideal for feedback-control of motivation, emotion, consciousness and behaviors. These observations suggest that the brain's basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum, ranging from the simplest neural networks to the most complex.

That's a very interesting finding, so we've built the following tool to do the related math to indicate just how many neural network "cliques" or pre-existing clusters of connected neurons are involved to process a given number of information inputs. If you're reading this article on a site that republishes our RSS news feed, please click here to access a working version of this tool!

That the relationship indicated by the tool above appears to hold is suggested by the neuroscientists' experimental results using mice.

If the brain really operates on N= 2ⁱ-1, the theory should hold for multiple types of cognitive tasks. Putting the idea to the test, the researchers fitted mice with arrays of electrodes to listen in on their neural chatter.

In one experiment, they gave the animals different combinations of four types of food — standard chow, sugar pellets, rice or skim milk droplets. According to the theory, the mice should have 15 (N= 2⁴-1) neuronal cliques to fully represent each food type and their various combinations.

And that’s what they found.

When recording from the amygdala, a brain area that processes emotions, some neurons responded generally to all kinds of food, whereas others were more specific. When clustered for their activity patterns, a total of 15 cliques emerged — just as the theory predicted.

In another experiment aimed at triggering fear, the animals were subjected to four scary scenarios: a sudden puff of air, an earthquake-like shake, an unexpected free-fall or a light electrical zap to the feet. This time, recordings from a region of the cortex important for controlling fear also unveiled 15 cell cliques.

Similar results were found in other areas of the brain — altogether, seven distinct regions.

The most interesting part of the researchers' experiments was that they found the mathematical relationship held even in mice that had been genetically-modified so that their brain's neurons lacked the NMDA receptor, which therefore could not possibly "fire" in response to the experimental stimuli to form neural networks according to the long prevailing theory of how memories are formed.

The other really interesting finding from the new research is that the brain's reward center would appear to operate according to different parameters.

The notable exception was dopamine neurons in the reward circuit, which tend to fire in a more binary manner to encode things like good or bad.

Overall, these new findings indicate new directions for research into the brain's plasticity, which has important applications for developing treatments for traumatic injuries to the brain.

References

Xie, Kun; Fox, Grace E.; Liu, June; Lyu, Cheng; Lee, Jason C.; Kuang, Hui; Jacobs, Stephanie; Li, Meng; Liu, Tianming; Song, Sen; Tsien, Joe Z. Brain Computation Is Organized via Power-of-Two-Based Permutation Logic. Frontiers in Systems Neuroscience, 15 November 2016 | http://dx.doi.org/10.3389/fnsys.2016.00095.