Tag Archives: synapses

Fast mapping technique will revolutionize brain research

Tony Zador of Cold Spring Harbor Laboratory devised a new technique for mapping connections among neurons. It is much faster than other methods and at least as accurate as the most accurate competing methods, including fluorescence techniques. The technique, MAPseq, uses genetically modified viruses to insert unique RNA sequences (“bar codes”) into each neuron. Post-mortem DNA sequencing identifies connections among all neurons in the sample. The resulting model is structural, not functional. Derived models are not spatially accurate (i.e., not to scale and not physiographically representative). The models identify intraneural connections but not specific messaging among neurons. Zador is pursuing functional analysis by combining MAPseq with other techniques. MAPseq currently can map about 100,000 neurons per week. Increasing hardware and software efficiency and power will improve throughput dramatically over time.

This is the most startling brain research development Mark has come across recently. The implications are tantalizing. Start with embedding unique codes (think of inventory numbers) in each neuron. Presumably using a virus to add a consistent unique identifier to every cell in an organism could result in a unique  “bar code” for every human and every other organism. We already have such a code in our genome, but this method could create a simpler code that would be easily readable by miniature, portable DNA sequencers. It could be a shorthand code linked to a person’s full genome record. 

Back to brain research, once Zador and others find ways to combine real-time functional mapping and non-destructive ‘reading’ of the cellular IDs, increasingly faster computing and smarter (AI-enabled) software may make it possible to map not only a person’s neural connectome, but the functional dynamics playing out in the brain from moment to moment. That, in turn, could make it possible to create a high-fidelity, functional copy of a human mind (aka, a ‘mindclone’). It would probably not be necessary to explicitly model every neuron, synapse, and intraneural communication, but that may one day be possible. 

Source: https://www.quantamagazine.org/new-brain-maps-with-unmatched-detail-may-change-neuroscience-20180404/ 

70-year-old Hebbs synaptic learning theory wrong

Neural learning occurs at dendrite roots, not in synapses.

The newly suggested learning scenario indicates that learning occurs in a few dendrites that are in much closer proximity to the neuron, as opposed to the previous notion. …

The new learning scenario occurs in different sites of the brain and therefore calls for a reevaluation of current treatments for disordered brain functionality. … In addition, the learning mechanism is at the basis of recent advanced machine learning and deep learning achievements. The change in the learning paradigm opens new horizons for different types of deep learning algorithms and artificial intelligence based applications imitating our brain functions, but with advanced features and at a much faster speed.

Source: https://www.sciencedaily.com/releases/2018/03/180323084818.htm

Neuroplasticity at the neuron and synapse level – Neurons sort into functional networks

“Until recently, scientists had thought that most synapses of a similar type and in a similar location in the brain behaved in a similar fashion with respect to how experience induces plasticity,” Friedlander said. “In our work, however, we found dramatic differences in the plasticity response, even between neighboring synapses in response to identical activity experiences.”

“Individual neurons whose synapses are most likely to strengthen in response to a certain experience are more likely to connect to certain partner neurons, while those whose synapses weaken in response to a similar experience are more likely to connect to other partner neurons,” Friedlander said. “The neurons whose synapses do not change at all in response to that same experience are more likely to connect to yet other partner neurons, forming a more stable but non-plastic network.”

Read more at: https://medicalxpress.com/news/2016-02-scientists-brain-plasticity-assorted-functional.html#jCp