Neuropoiesis: proposal for a connectionistic neurobiology

Neurodynamical Computing at the Information Boundaries of Intelligent Systems

Artificial intelligence has not achieved defining features of biological intelligence despite models boasting more parameters than neurons in the human brain. In this perspective article, we synthesize historical approaches to understanding intelligent systems and argue that methodological and epistemic biases in these fields can be resolved by shifting away from cognitivist brain-as-computer theories and recognizing that brains exist within large, interdependent living systems. Integrating the dynamical systems view of cognition with the massive distributed feedback of perceptual control theory highlights a theoretical gap in our understanding of nonreductive neural mechanisms. Cell assemblies—properly conceived as reentrant dynamical flows and not merely as identified groups of neurons—may fill that gap by providing a minimal supraneuronal level of organization that establishes a neurodynamical base layer for computation. By considering information streams from physical embodiment and situational embedding, we discuss this computational base layer in terms of conserved oscillatory and structural properties of cortical-hippocampal networks. Our synthesis of embodied cognition, based in dynamical systems and perceptual control, aims to bypass the neurosymbolic stalemates that have arisen in artificial intelligence, cognitive science, and computational neuroscience.

The RNA-centred view of the synapse: non-coding RNAs and synaptic plasticity

If mRNAs were the only RNAs made by a neuron, there would be a simple mapping of mRNAs to proteins. However, microRNAs and other non-coding RNAs (ncRNAs; endo-siRNAs, piRNAs, BC1, BC200, antisense and long ncRNAs, repeat-related transcripts, etc.) regulate mRNAs via effects on protein translation as well as transcriptional and epigenetic mechanisms. Not only are genes ON or OFF, but their ability to be translated can be turned ON or OFF at the level of synapses, supporting an enormous increase in information capacity. Here, I review evidence that ncRNAs are expressed pervasively within dendrites in mammalian brain; that some are activity-dependent and highly enriched near synapses; and that synaptic ncRNAs participate in plasticity responses including learning and memory. Ultimately, ncRNAs can be viewed as the post-it notes of the neuron. They have no literal meaning of their own, but derive their functions from where (and to what) they are stuck. This may explain, in part, why ncRNAs differ so dramatically from protein-coding genes, both in terms of the usual indicators of functionality and in terms of evolutionary constraints. ncRNAs do not appear to be direct mediators of synaptic transmission in the manner of neurotransmitters or receptors, yet they orchestrate synaptic plasticity—and may drive species-specific changes in cognition.

Exosomal transfer of proteins and RNAs at synapses in the nervous system

Background

Many cell types have been reported to secrete small vesicles called exosomes, that are derived from multivesicular bodies and that can also form from endocytic-like lipid raft domains of the plasma membrane. Secretory exosomes contain a characteristic composition of proteins, and a recent report indicates that mast cell exosomes harbor a variety of mRNAs and microRNAs as well. Exosomes express cell recognition molecules on their surface that facilitate their selective targeting and uptake into recipient cells.

Results

In this review, I suggest that exosomal secretion of proteins and RNAs may be a fundamental mode of communication within the nervous system, supplementing the known mechanisms of anterograde and retrograde signaling across synapses. In one specific scenario, exosomes are proposed to bud from the lipid raft region of the postsynaptic membrane adjacent to the postsynaptic density, in a manner that is stimulated by stimuli that elicit long-term potentiation. The exosomes would then transfer newly synthesized synaptic proteins (such as CAM kinase II alpha) and synaptic RNAs to the presynaptic terminal, where they would contribute to synaptic plasticity.

Conclusion

The model is consistent with the known cellular and molecular features of synaptic neurobiology and makes a number of predictions that can be tested in vitro and in vivo.

Open peer review

Reviewed by Etienne Joly, Gaspar Jekely, Juergen Brosius and Eugene Koonin. For the full reviews, please go to the Reviewers' comments section.

A fuzzy theory of cortical computation: neuropoietic engrams, fuzzy hypercubes, and the nature of consciousness

We apply fuzzy logic to a theory of memory representation and computation in the human cerebral cortex. The theory termed neuropoiesis is based on the hypothetical transfer of mRNA polyribosomes from the post-synaptic dendritic spine of cortical pyramidal neurons to the presynaptic boutons of connecting axons through a hypothetical process termed retroduction. The net effect of this process is a vast increase in predicted memory storage. The fuzzification of memory engrams permits this expansion in memory capacity and requires multiplex signaling which, in turn, requires the formation of a spike packet whose length is determined by the EEG frequencies generated by the thalamo-cortical rhythm generators. The role of the EEG frequencies is to provide a wavelet-like transform of the multiplex signal which in turn determines the degree of data compression that is required for memory recruitment at a given level of vigilance during cortical computation. In this conceptual model cortical computation is hypothesized to be a form of cluster analysis that can be represented by a fuzzy hypercube in which each dimension of the unit hypercube represents an apical dendrite of a layer 5 pyramidal cell in a cortical fascicle. The tuftal area of the apical dendrite in cortical layer one corresponds to the MIN or zero point of the hypercube's dimension and the cell body in layer 5 corresponds to the MAX or one point of that dimension in the unit hypercube. The neuroanatomical location of synapses on the apical dendrites in the fascicle is mapped onto the fuzzy hypercube. These synapses form clusters composed of both bottom-up and top-down signals represented as metasynaptic fuzzy sets-as-points in the hypercube. Soft winner-take-all gating by inhibitory neurons is proposed to supply the only non-linear operation needed for cortical computation. Feed-forward inhibition is envisioned to play the decisive role of spicing or de-fuzzifying the output signal. Proper transmission of the multiplex signal that carries the fuzzy engram requires synchrony of neuronal firing. For this fuzzy cortical model, synchrony of firing, multiplex signaling, winner-take-all gating, and the known spectrum of EEG frequencies are all derivable from the fundamental mechanism termed synaptopoiesis as described in the theory of neuropoiesis. Finally, this theory predicts that the neural correlate of consciousness must include inhibitory subcortical connections and that its function is largely that of limiting coherence to a narrow range of cortical engrams.

The flexible brain. On mind and brain, neural darwinism and psychiatry

A theoretical introduction is given in which several theoretical viewpoints concerning the mind-brain problem are discussed. During the last decade philosophers like Searle, Dennett and the Churchlands have taken a more or less pure materialistic position in explaining mental phenomena. Investigators in biological psychiatry have hardly ever taken a clear position in this discussion, whereas we believe it is important that the conclusions drawn from biological research are embedded in a theoretical framework related to the mind-brain problem. In this article the thesis is defended that the theory of neural darwinism represents a major step forward and may bridge previous distinctions between biological, clinical and social psychiatry.