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.
Sophisticated, sometimes AI-enabled data analytics tools allow construction of individual personality profiles accurate enough to support targeted manipulation of individuals’ perceptions and actions.
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Last night Facebook announced bans against Cambridge Analytica, its parent company and several individuals for allegedly sharing and keeping data that they had promised to delete. This data reportedly included information siphoned from hundreds of thousands of Amazon Mechanical Turkers who were paid to use a “personality prediction app” that collected data from them and also anyone they were friends with — about 50 million accounts. That data reportedly turned into information used by the likes of Robert Mercer, Steve Bannon and the Donald Trump campaign for social media messaging and “micro-targeting” individuals based on shared characteristics.
A Guardian article last October brings the darker aspects of the attention economy, particularly the techniques and tools of neural hijacking, into sharp focus. The piece summarizes some interaction design principles and trends that signal a fundamental shift in means, deployment, and startling effectiveness of mass persuasion. The mechanisms reliably and efficiently leverage neural reward (dopamine) circuits to seize, hold, and direct attention toward whatever end the designer and content providers choose.
The organizer of a $1,700 per person event convened to show marketers and technicians “how to manipulate people into habitual use of their products,” put it baldly.
subtle psychological tricks … can be used to make people develop habits, such as varying the rewards people receive to create “a craving”, or exploiting negative emotions that can act as “triggers”. “Feelings of boredom, loneliness, frustration, confusion and indecisiveness often instigate a slight pain or irritation and prompt an almost instantaneous and often mindless action to quell the negative sensation”
Particularly telling of the growing ethical worry are the defections from social media among Silicon Valley insiders.
Pearlman, then a product manager at Facebook and on the team that created the Facebook “like”, … confirmed via email that she, too, has grown disaffected with Facebook “likes” and other addictive feedback loops. She has installed a web browser plug-in to eradicate her Facebook news feed, and hired a social media manager to monitor her Facebook page so that she doesn’t have to.
It is revealing that many of these younger technologists are weaning themselves off their own products, sending their children to elite Silicon Valley schools where iPhones, iPads and even laptops are banned. They appear to be abiding by a Biggie Smalls lyric from their own youth about the perils of dealing crack cocaine: never get high on your own supply.
If you read the article, please comment on any future meeting topics you detect. I find it a vibrant collection of concepts for further exploration.
Albuquerque Brain, Mind, and Artificial Intelligence Discussion Group