[FoRK] Phosphorylate a substrate while traversing scale! Nature uses 6-bit bytes
sdw at lig.net
Sat Mar 10 12:39:35 PST 2012
Biobytes? Nytes? (Neural bytes)
Amazing and exciting, if all of this is verified.
Where is the code? I want to play with the models for these.
> In a paper in the March 8 issue of the /PLoS Computational Biology/, University of Arizona anesthesiologist Stuart Hameroff, MD,
> and physicists Travis Craddock and Jack Tuszynski of the University of Alberta demonstrate a plausible mechanism for encoding
> synaptic memory in microtubules, major components of the structural cytoskeleton within neurons.
> Microtubules are cylindrical hexagonal lattice polymers of the protein tubulin, comprising 15% of total brain protein.
> Microtubules define neuronal architecture, regulate synapses, and are suggested to process information via interactive bit-like
> states of tubulin. But any semblance of a common code connecting microtubules to synaptic activity has been missing. Until now.
> The standard experimental model for neuronal memory is long term potentiation (LTP) in which brief pre-synaptic excitation results
> in prolonged post-synaptic sensitivity. An essential player in LTP is the hexagonal enzyme calcium/calmodulin-dependent protein
> kinase II (CaMKII). Upon pre-synaptic excitation, calcium ions entering post-synaptic neurons cause the snowflake-shaped CaMKII to
> transform, extending sets of 6 leg-like kinase domains above and below a central domain, the activated CaMKII resembling a
> double-sided insect. Each kinase domain can phosphorylate a substrate, and thus encode one bit of synaptic information. Ordered
> arrays of bits are termed bytes, and 6 kinase domains on one side of each CaMKII can thus phosphorylate and encode
> calcium-mediated synaptic inputs as 6-bit bytes. But where is the intra-neuronal substrate for memory encoding by CaMKII
> phosphorylation? Enter microtubules.
> Using molecular modeling, Craddock et al reveal a perfect match among spatial dimensions, geometry and electrostatic binding of
> the insect-like CaMKII, and hexagonal lattices of tubulin proteins in microtubules. They show how CaMKII kinase domains can
> collectively bind and phosphorylate 6-bit bytes, resulting in hexagonally-based patterns of phosphorylated tubulins in
> microtubules (Figure). They calculate enormous information capacity at low energy cost, and show how patterns of phosphorylated
> tubulins in microtubules can not only store memory, but control neuronal functions by triggering axonal firings, regulating
> synapses, and traversing scale.
Cytoskeletal Signaling: Is Memory Encoded in Microtubule Lattices by CaMKII Phosphorylation?
Memory is attributed to strengthened synaptic connections among particular brain neurons, yet synaptic membrane components are
transient, whereas memories can endure. This suggests synaptic information is encoded and ‘hard-wired’ elsewhere, e.g. at molecular
levels within the post-synaptic neuron. In long-term potentiation (LTP), a cellular and molecular model for memory, post-synaptic
calcium ion (Ca^2+ ) flux activates the hexagonal Ca^2+ -calmodulin dependent kinase II (CaMKII), a dodacameric holoenzyme
containing 2 hexagonal sets of 6 kinase domains. Each kinase domain can either phosphorylate substrate proteins, or not (i.e.
encoding one bit). Thus each set of extended CaMKII kinases can potentially encode synaptic Ca^2+ information via phosphorylation as
ordered arrays of binary ‘bits’. Candidate sites for CaMKII phosphorylation-encoded molecular memory include microtubules (MTs),
cylindrical organelles whose surfaces represent a regular lattice with a pattern of hexagonal polymers of the protein tubulin. Using
molecular mechanics modeling and electrostatic profiling, we find that spatial dimensions and geometry of the extended CaMKII kinase
domains precisely match those of MT hexagonal lattices. This suggests sets of six CaMKII kinase domains phosphorylate hexagonal MT
lattice neighborhoods collectively, e.g. conveying synaptic information as ordered arrays of six “bits”, and thus “bytes”, with 64
to 5,281 possible bit states per CaMKII-MT byte. Signaling and encoding in MTs and other cytoskeletal structures offer rapid, robust
solid-state information processing which may reflect a general code for MT-based memory and information processing within neurons
and other eukaryotic cells.
The Deepak connection etc. seems a little suspect: Is the mystical consciousness and scientific explanation of consciousness really
going to be happy with each other? However, some of the papers are interesting at a glance:
Lateral Information Processing by Spiking Neurons:
A Theoretical Model of the Neural Correlate of Consciousness
Marc Ebner1 and Stuart Hameroff2
Cognitive brain functions, for example, sensory perception, motor control and learning, are understood as computation by axonal-
dendritic chemical synapses in networks of integrate-and-fire neurons. Cognitive brain functions may occur either consciously or
nonconsciously (on “autopilot”). Conscious cognition is marked by gamma synchrony EEG, mediated largely by dendritic- dendritic gap
junctions, sideways connections in input/integration layers. Gap-junction-connected neurons define a sub-network within a larger
neural network. A theoretical model (the “conscious pilot”) suggests that as gap junctions open and close, a gamma- synchronized
subnetwork, or zone moves through the brain as an executive agent, converting nonconscious “auto-pilot” cognition to consciousness,
and enhancing computation by coherent processing and collective integration. In this study we implemented sideways “gap junctions”
in a single-layer artificial neural network to perform figure/ground separation. The set of neurons connected through gap junctions
form a reconfigurable resistive grid or sub-network zone. In the model, outgoing spikes are temporally integrated and spatially
averaged using the fixed resistive grid set up by neurons of similar function which are connected through gap-junctions. This
spatial average, essentially a feedback signal from the neuron’s output, determines whether particular gap junctions between neurons
will open or close. Neurons connected through open gap junctions synchronize their output spikes. We have tested our
gap-junction-defined sub-network in a one-layer neural network on artificial retinal inputs using real-world images. Our system is
able to perform figure/ground separation where the laterally connected sub-network of neurons represents a perceived object. Even
though we only show results for visual stimuli, our approach should generalize to other modalities. The system demonstrates a moving
sub-network zone of synchrony, within which the contents of perception are represented and contained. This mobile zone can be viewed
as a model of the neural correlate of consciousness in the brain.
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