m8ta
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{1570} | |||||||||||||
Kickback cuts Backprop's red-tape: Biologically plausible credit assignment in neural networks Bit of a meh -- idea is, rather than propagating error signals backwards through a hierarchy, you propagate only one layer + use a signed global reward signal. This works by keeping the network ‘coherent’ -- positive neurons have positive input weights, and negative neurons have negative weights, such that the overall effect of a weight change does not change sign when propagated forward through the network. This is kind of a lame shortcut, imho, as it limits the types of functions that the network can model & the computational structure of the network. This is already quite limited by the dot-product-rectifier common structure (as is used here). Much more interesting and possibly necessary (given much deeper architectures now) is to allow units to change sign. (Open question as to whether they actually frequently do!). As such, the model is in the vein of "how do we make backprop biologically plausible by removing features / communication" rather than "what sorts of signals and changes does the brain use perceive and generate behavior". This is also related to the literature on what ResNets do; what are the skip connections for? Amthropic has some interesting analyses for Transformer architectures, but checking the literature on other resnets is for another time. | |||||||||||||
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Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits
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Going in circles is the way forward: the role of recurrence in visual inference I think the best part of this article are the references -- a nicely complete listing of, well, the current opinion in Neurobiology! (Note that this issue is edited by our own Karel Svoboda, hence there are a good number of Janelians in the author list..) The gestalt of the review is that deep neural networks need to be recurrent, not purely feed-forward. This results in savings in overall network size, and increase in the achievable computational complexity, perhaps via the incorporation of priors and temporal-spatial information. All this again makes perfect sense and matches my sense of prevailing opinion. Of course, we are left wanting more: all this recurrence ought to be structured in some way. To me, a rather naive way of thinking about it is that feed-forward layers cause weak activations, which are 'amplified' or 'selected for' in downstream neurons. These neurons proximally code for 'causes' or local reasons, based on the supported hypothesis that the brain has a good temporal-spatial model of the visuo-motor world. The causes then can either explain away the visual input, leading to balanced E-I, or fail to explain it, in which the excess activity is either rectified by engaging more circuits or engaging synaptic plasticity. A critical part of this hypothesis is some degree of binding / disentanglement / spatio-temporal re-assignment. While not all models of computation require registers / variables -- RNNs are Turning-complete, e.g., I remain stuck on the idea that, to explain phenomenological experience and practical cognition, the brain much have some means of 'binding'. A reasonable place to look is the apical tuft dendrites, which are capable of storing temporary state (calcium spikes, NMDA spikes), undergo rapid synaptic plasticity, and are so dense that they can reasonably store the outer-product space of binding. There is mounting evidence for apical tufts working independently / in parallel is investigations of high-gamma in ECoG: PMID-32851172 Dissociation of broadband high-frequency activity and neuronal firing in the neocortex. "High gamma" shows little correlation with MUA when you differentiate early-deep and late-superficial responses, "consistent with the view it reflects dendritic processing separable from local neuronal firing" | |||||||||||||
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A 6-nm ultra-photostable DNA Fluorocube for fluorescence imaging Also including some correspondence with the authors: Me Nice work and nice paper, thanks for sharing .. and not at all what I had expected from Ron's comments! Below are some comments ... would love your opinion. I'd expect that the molar absorption coefficients for the fluorocubes should be ~6x larger than for the free dyes and the single dye cubes (measured?), yet the photon yields for all except Cy3N maybe are around the yield for one dye molecule. So the quantum yield must be decreased by ~6x? This in turn might be from a middling FRET which reduces lifetime, thereby the probability of ISC, photoelectron transfer, and hence photobleaching. I wonder if in the case of ATTO 647N Cy5 and Cy3, the DNA is partly shielding the fluorphores from solvent (ala ethidium bromide), which also helps with stability, just like in fluorescent proteins. ATTO 647N generates a lot of singlet oxygen, who knows what it's doing to DNA. Can you do a log-log autocorrelation of the blinking timeseries of the constructs? This may reveal different rate constants controlling dark/light states (though, for 6 coupled objects, might not be interpretable!) Also, given the effect of DNA shielding, have you compared to free dyes to single-dye cubes other than supp fig 10? The fact that sulfonation made such a huge effect in brightness is suggestive. Again, these are super interesting & exciting results! Author I haven't directly looked at the molar absorption coefficient but judging from the data that I collected for the absorption spectra, there is certainly an increase for the fluorocubes compared to single dyes. I agree that this would be an interesting experiment and I am planning collect data to measure the molar absorption coefficient. I would also expect a ~6 fold increase for the Fluorocubes. Yes, we suspect homo FRET to help reduce photobleaching. So far we only measured lifetimes in bulk but are planning to obtain lifetime data on the single-molecule level soon. We also wondered if the DNA is providing some kind of shield for the fluorophores but could not design an experiment to directly test this hypothesis. If you have a suggestion, that would be wonderful. The log-log autocorrelation of blinking events is indeed difficult to interpret. Already individual intensity traces of fluorocubes are difficult to analyze as many of them get brighter before they bleach. We are also wondering if some fluorocubes are emitting two photons simultaneously. We will hopefully be able to measure this soon. | |||||||||||||
{1459} |
ref: -2018
tags: Michael Levin youtube talk NIPS 2018 regeneration bioelectricity organism patterning flatworm
date: 04-09-2019 18:50 gmt
revision:1
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What Bodies Think About: Bioelectric Computation Outside the Nervous System - NeurIPS 2018
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Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures
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Materials and technologies for soft implantable neuroprostheses
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PMID-11327505 Flexible polyimide-based intracortical electrode arrays with bioactive capability.
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Evolutionary Plasticity and Innovations in Complex Metabolic Reaction Networks
Summary thoughts: This is a highly interesting study, insofar that the authors show substantial support for their hypotheses that phenotypes can be explored through random-walk non-lethal mutations of the genotype, and this is somewhat invariant to the source of carbon for known biochemical reactions. What gives me pause is the use of linear programming / optimization when setting the relative concentrations of biomolecules, and the permissive criteria for accepting these networks; real life (I would imagine) is far more constrained. Relative and absolute concentrations matter. Still, the study does reflect some robustness. I suggest that a good control would be to ‘fuzz’ the list of available reactions based on statistical criteria, and see if the results still hold. Then, go back and make the reactions un-biological or less networked, and see if this destroys the measured degrees of robustness. | |||||||||||||
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PMID-24677434 A Review of Organic and Inorganic Biomaterials for Neural Interfaces
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PMID-18485471[0] Characterization of microglial attachment and cytokine release on biomaterials of differing surface chemistry
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Things to read! decoding:
electrodes:
other random scribblings: Vascularization {1027} histology {736},{737} and size {1028},{747},{1026}, insulation {1033}. How very very important -- as important or moreso than the recording technology. What has happened to {149} ? | |||||||||||||
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PMID-20577634 Biocompatibility of intracortical microelectrodes: current status and future prospects.
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PMID-17946847[0] Preliminary study of multichannel flexible neural probes coated with hybrid biodegradable polymer. ____References____
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PMID-10906696[0] Tissue response to single-polymer fibers of varying diameters: evaluation of fibrous encapsulation and macrophage density.
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{750} |
ref: Menei-1994.09
tags: microspheres beads polycaprolactone biocompatible drug delivery histology
date: 01-27-2013 20:54 gmt
revision:3
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PMID-7814435 Fate and biocompatibility of three types of microspheres implanted into the brain.
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PMID-19703712[0] The insulation performance of reactive parylene films in implantable electronic devices.
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PMID-17266019[0] The brain tissue response to implanted silicon microelectrode arrays is increased when the device is tethered to the skull. ____References____
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PMID-20161810[0] Bridging the Divide between Neuroprosthetic Design, Tissue Engineering and Neurobiology
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{349} |
ref: thesis-0
tags: clementine 042007 operant conditioning biofeedback tlh24
date: 01-06-2012 03:08 gmt
revision:4
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channel 29 controlled the X direction: channel 81, the Y direction (this one was very highly modulated, and the monkey could get to a high rate ~60Hz. note that both units are sorted as one -- I ought to do the same on the other channels from now on, as this was rather predictive (this is duplicating Debbie Won's results): However, when I ran a wiener filter on the binned spike rates (this is not the rates as estimated through the polynomial filter), ch 81 was most predictive for target X position; ch 29, Y target position (?). This is in agreement with population-wide predictions of target position: target X was predicted with low fidelity (1.12; cc = 0.35 or so); target Y was, apparently, unpredicted. I don't understand why this is, as I trained the monkey for 1/2 hour on just the opposite. Actually this is because the targets were not in a random sequence - they were in a CCW sequence, hence the neuronal activity was correlated to the last target, hence ch 81 to target X! for reference, here is the ouput of bmi_sql: order of columns: unit,channel, lag, snr, variable ans = 1.0000 80.0000 5.0000 1.0909 7.0000 1.0000 80.0000 4.0000 1.0705 7.0000 1.0000 80.0000 3.0000 1.0575 7.0000 1.0000 80.0000 2.0000 1.0485 7.0000 1.0000 80.0000 1.0000 1.0402 7.0000 1.0000 28.0000 4.0000 1.0318 8.0000 1.0000 76.0000 2.0000 1.0238 11.0000 1.0000 76.0000 5.0000 1.0225 11.0000 1.0000 17.0000 0 1.0209 11.0000 1.0000 63.0000 3.0000 1.0202 8.0000 movies of the performance are here: | |||||||||||||
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PMID-15132510[0] A fully Integrated Neural Recording Amplifier with DC Input Stabilization
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Our ancestor, a proton powered rock?-- great article, wish i knew more of the biochemistry behind this research. linked from that, something of a less pure science: Future women, shorter, plumper, more fertile --read the comments, some of them are insane (but provocative?)! Viz:
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{730} |
ref: -0
tags: recroding biopotential MOS-bipolar pseudoresistor
date: 04-15-2009 22:03 gmt
revision:0
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Linear transconductor with rail-to-rail input swing for very large time constanct applications
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{715} |
ref: Legenstein-2008.1
tags: Maass STDP reinforcement learning biofeedback Fetz synapse
date: 04-09-2009 17:13 gmt
revision:5
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PMID-18846203[0] A Learning Theory for Reward-Modulated Spike-Timing-Dependent Plasticity with Application to Biofeedback
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PMID-17234689[0] Volitional control of neural activity: implications for brain-computer interfaces (part of a symposium)
humm.. this paper came out a month ago, and despite the fact that he is much older and more experienced than i, we have arrived at the same conclusions by looking at the same set of data/papers. so: that's good, i guess. ____References____ | |||||||||||||
{565} |
ref: Walker-2005.12
tags: algae transfection transformation protein synthesis bioreactor
date: 03-21-2008 17:22 gmt
revision:1
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Microalgae as bioreactors PMID-16136314
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This was written for the plik-l mailing list, Nov 16 2007 I actually had a bit of an argument yesterday with my dentist, no less, about global warming:
Mostly I'd have to agree with the dentist - the oil is going to be burned eventually, because it is just such a cheap source of energy. We are going to have to deal with the consequences. However, for coal - of which we have a far greater supply, and is considerably more dangerous / expensive to obtain - there is good reason to search for alternatives, and putting a tax on oil/natural gas now fund development of alternatives is probably very future-responsible, and will shift the energy climate so we relinquish coal (and maybe some oil) earlier, resulting in less CO2 in the atmosphere. There are infinitely many things more worthy/long-range responsible than the war, but our leaders have not touched on that. Correct me if I'm wrong, but there is little evidence that they even measured the worth of all alternatives, and decided rationally, based on integrating (over time and path probability) best-of-present knowledge of benefits and consequences. Or maybe they decided rationally, but with the worth of alternatives measured *personally*. It is this that truly angers me. Bayes for president 2008! Comments:
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http://www.neuroconnex.com/ -- looks like they have some excellent products, but not sure how to purchase them.
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