Taken together, these morphological characteristics suggest that neurons in the elephant cortex may synthesize a wider variety of input than the cortical neurons in other mammals.
In terms of cognition, my colleagues and I believe that the integrative cortical circuitry in the elephant supports the idea that they are essentially contemplative animals. Primate brains, by comparison, seem specialized for rapid decision-making and quick reactions to environmental stimuli.
Kurzweil builds and supports a persuasive vision of the emergence of a human-level engineered intelligence in the early-to-mid twenty-first century. In his own words,
With the reverse engineering of the human brain we will be able to apply the parallel, self-organizing, chaotic algorithms of human intelligence to enormously powerful computational substrates. This intelligence will then be in a position to improve its own design, both hardware and software, in a rapidly accelerating iterative process.
In Kurzweil’s view, we must and will ensure we evade obsolescence by integrating emerging metabolic and cognitive technologies into our bodies and brains. Through self-augmentation with neurotechnological prostheses, the locus of human cognition and identity will gradually (but faster than we’ll expect, due to exponential technological advancements) shift from the evolved substrate (the organic body) to the engineered substrate, ultimately freeing the human mind to develop along technology’s exponential curve rather than evolution’s much flatter trajectory.
The book is extensively noted and indexed, making the deep-diving reader’s work a bit easier.
If you have read it, feel free to post your observations in the comments below. (We’ve had a problem with the comments section not appearing. It may require more troubleshooting.)
Two independent teams of scientists from the University of Utah and the University of Massachusetts Medical School have discovered that a gene crucial for learning, called Arc, can send its genetic material from one neuron to another by employing a strategy commonly used by viruses. The studies, both published in Cell, unveil a new way that nervous system cells interact.
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.
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.
Given the human brain’s approximately 80 billion neurons, it would take tens of thousands of these devices to record a substantial volume of neuron-level activities. Still, this is a remarkable achievement.
The system would simultaneously acquire data from more than 1 million neurons in real time. It would convert the spike data (using bit encoding) and send it via an effective communication format for processing and storage on conventional computer systems. It would also provide feedback to a subject in under 25 milliseconds — stimulating up to 100,000 neurons.
Monitoring large areas of the brain in real time. Applications of this new design include basic research, clinical diagnosis, and treatment. It would be especially useful for future implantable, bidirectional BMIs and BCIs, which are used to communicate complex data between neurons and computers. This would include monitoring large areas of the brain in paralyzed patients, revealing an imminent epileptic seizure, and providing real-time feedback control to robotic arms used by quadriplegics and others.
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.
A 2017 BBC article concisely reviews essential concepts of quantum physics and summarizes the state of scientific speculation into the possible interactions of consciousness and quantum mechanics. Of interest are some specific, possibly testable, suggestions about chemical structures that could sustain nuclear spin entanglements in the brain for up to two days.
New Scientist article: Applying the mathematical field of topology to brain science suggests gaps in densely connected brain regions serve essential cognitive functions. Newly discovered densely connected neural groups are characterized by a gap in the center, with one edge of the ring (cycle) being very thin. It’s speculated that this architecture evolved to enable the brain to better time and sequence the integration of information from different functional areas into a coherent pattern.
Aspects of the findings appear to support Edelman’s and Tononi’s (2000, p. 83) theory of neuronal group selection (TNGS, aka neural Darwinism).