Keep Calm and Carry On – Reacting to the Boston Marathon Bombing

I’ve had some deep discussions today about the Boston Marathon bombings with friends. Here’s something I shared with a friend who lives in the Boston area in Massachusetts. His predominant feeling right now is disillusionment. If you’re in the same boat, I hope you find it helpful in some way. Thanks for any feedback.

Friend, I hope this event won’t shake your faith in humanity or in the continued acceleration of global progress, or in our ability to better understand what progress is, and for reasons yet to be discovered, why accelerating progress seems only partly under our control, and partly driven by the amazingly intelligent and self-correcting environment into which we were born.

There are always half of one percent of us who are seriously broken in some way. It is surprising, when you stop to think about it, that majority of us are so strongly against doing such cowardly and terrible things. Almost all violence is rapidly self-limiting. It can be a calculation of fairness, a seeking of justice in the wild. Or a case of beliefs being seriously out of step with reality, or emotions not being sufficiently regulated. Fortunately, for the vast majority of us, our moral sentiments and desire to cooperate are incredibly deep, selected and self-organized over countless previous life cycles. At the same time, our tools and policies for protecting the world system get only better and smarter. We must understand these processes better, and aggressively work to improve them in society and the individual.

The mentally ill, extremists and oligarchs throughout history are a persistently tiny fraction of society. The main effect of mental illness events like this (these particular bombings, irrational as they are, are even more a mental and psychological illness than an extremist/terrorist event, as I see it), aside from their tragic short-term cost, is to grow our global immunity to them in future years. If we learn from them (a critical “if”), they accelerate the emergence of the transparency tools and social development programs that we know is our future, and as long as it is increasingly a bottom-up, citizen-driven transparency and social development process, we gain greater control over both the extremists and the autocrats, our democracy strengthens, and the world gets collectively more intelligent. Imagine, as social and media futurist Alvis Brigis says, if it was ten years in the future and one out of twenty people in that Boston crowd had been wearing Google Glass or an equivalent? (I’m a Glass Explorer, so I’m looking forward to getting an early adopter version of this fantastic new wearable computer and lifelogging tech). They’d all be able to share their recent archives and feeds and it wouldn’t be long before we’d have the perpetrators identities and last public locations.

Mental illness is one issue, but what about oligarchy (government by elites, without representation) and plutocracy (government by the wealthy), and the way such governments breed extremism in the developing world by replacing culture with commercialism, removing self-determination and representation, and inducing cornered cultures to react with Fundamentalism? If increasing political, economic, and social fairness is a clear vector of social progress, how do we keep building it in all our societies in the years ahead?

With regard to the plutocrats, there is good news: our global rich poor divide has never been smaller. It was highest in the 13th century  under Feudalism by several measures, and has slowly decreased ever since. But the problem we face is that in the world’s leading and fastest developing countries inequality seesaws, at first going up as the wealth of new technology revolutions is initially captured by the well-capitalized few, and then later down again as the revolution works its way out to the many, where the maturing and cheapening tech allows disruptive new entrepreneurship on top of the platform, and as new rights and entitlements eventually emerge.

The Finland Phenomenon, a great film on the education reform the US needs to make more self-reliant, innovative, and less fearful citizens.

As Joseph Stiglitz discusses in The Price of Inequality, 2013, we need a certain amount of income inequality to spur innovation, but if we let it get too big, the wealthy and the corporations capture our political machinery, only their interests are represented, and democracy, political reform, and political compromise and moderation die. Due to tech globalization’s great wealth creation, income inequality has grown rapidly in the last 60 years in a handful of nations, in the 1970′s-80′s in the US, UK, and Israel, and in the 1990′s and 2000′s also in rapidly developing countries like China and Brazil (and to a much lower degree, in a few low-inequality countries like Germany and Sweden). In the U.S., asset inequality is now so extreme that just 1% of us own 40% of the nation’s wealth. When our lower and middle classes can no longer find meaningful jobs under constant technological change, while we see other developed nations doing far better with education and job creation, we should not be surprised. We let this happen, by letting our MNCs get larger than governments (instead of splitting them up, as we used to), and by dismantling progressive income and inheritance tax for the wealthy (which last existed seriously in the US in the 1950′s).

To bring this back to the theme of this post, another big price of plutocracy is that our citizens lose the ability to engage with the developing world an empathic and positive-sum way, and our fear grows. We fear technological progress, as the job disruption dumps us into a degraded society that doesn’t keep job creation and retraining as the top priority. We fear the further loss of jobs via outsourcing. We fear immigration, and forget that merit-based immigration is one of the fastest creators of new jobs, science, and industries. We fear other belief systems, and we demonize the other, rather than finding common cause with the moderates in every religion and group. As our political system gets captured by unresponsive and polarized elites (they are wealth driven and fight hard to divide the spoils among themselves), tough social problems like educational reform don’t get done. See The Finland Phenomenon for an excellent example of what we can will one day do to fix our broken educational system, when we finally get the political will. In the meantime, our citizens grow increasingly globally ignorant, inward-focused, and politically apathetic, or polarized and uncompromising like their wealthy masters.

Source: Growing Unequal?, OECD 2008.
Click the graphic for the report.

But, thank the Universe, America is an outlier, with our elites capturing such an outsized portion of the new technological wealth in the last six decades that we are going temporarily against the global trend. We will eventually reverse this and be forced, by accelerating technoeconomic integration, to get back to the global trend. The developed OCED countries as a whole aren’t following our sad course of sixty years of rapidly increasing income inequality and 60% higher levels of income poverty, as the 2008 OECD graphic at right shows. Remember that for the global economy, the absolute size of the inequity gap is still closing since Feudalism. As visionary books like Abundance, 2012, make clear, we can see how extreme global economic and educational poverty will disappear just a few decades hence.  Many of the emerging nations are now in the process of growing their GDP two or three times faster than us. Check out Gapminder.org for some beautiful graphs telling that story. If we’re thinking at all about accelerating tech, we can see a new world of the conversational interface and of teacherless education (to use futurist Thomas Frey’s great phrase) less than ten years hence, where every literate and illiterate child has a wearable waterproof smartphone on their wrist, listening in to what they are learning and teaching them who knows what.

Accelerating technology always causes evolutionary disruption in the first phase. More money goes to the rich and the leading corporations, at first, rather than the rest of society from any new technological and trade revolution, be it industrial, transportation, mass consumption, communications, personal computing, internet, web services, or any other revolution affecting the global marketplace. In the U.S. and a few other countries, these and other revolutions have been the dominant story of the latest 60 years of globalization. In turn, the vast new wealth increase of the MNCs, many of whom now have revenues larger than those of the leading countries, and their unrestrained effects on the developing world, has been a great driver of the clash of cultures and the extremist events we see today. We are pushing citizens in many of these cultures to change at a rate far faster than their reformists are comfortable with, and successive waves of technology innovation are driving them (and us, but always to a far lesser degree) continually out of their livelihoods into a globally wealthier but, in the absence of good retraining and social safety nets, a much more socially uncertain future.

Eventually the global system, being not only evolutionary but also developmental, always gains irreversible new levels of total positive-sum integration, and immunity. For the system as a whole, virtuous cycles are always underway and antifragility will increasingly dominate, if global development is like living systems development, as I believe it is. I hope you can find a way to see and guide the positive changes that will come from this tragic event, as they surely must.

Bruce Schneier, Security Maven

So regarding our emotions and actions around this bombing, with a potential to cause disproportionate fear and immune response, as occurred after 9/11, I think Bruce Schneier’s brief piece in The Atlantic says it best: “Keep Calm and Carry On.” Let’s not overreact, overspend, overregulate. Let’s not fixate on or overgeneralize this rare event itself, or get scared. Let’s continue to work calmly on the social development processes (income equity, representation, education, psych services, job creation, civics, religious tolerance and reform) that will reduce the probability of this happening again, and the transparency processes (primarily bottom up, and secondarily top down cameras, sensors, networks, databases, pattern recognizers, human intelligence) that will increase our ability to find, isolate, and help (or at least, prevent from further harm) the broken folks or individual who did this.

Let’s implement our actions carefully and incrementally, while always insuring their social benefits exceed their costs. Let’s keep calm and carry on.

Leadership of Technological Change (35 min video)

A recent keynote, at USNI’s West Conference, Jan 2013, San Diego, CA. The talk has three parts:

1. A brief intro to evolutionary developmental foresight, a strategically useful theory of change for leaders,

2. A selection of important developmental (highly probable) opportunities, disruptions, and threats I think we can expect in coming years due to accelerating technological change,

3. Strategies for innovation, management, and foresight (IMF) with respect to technological change that can be employed by middle and senior mgmt.

Those who want one quick takeaway may enjoy the last minute, starting at 35:06, which wraps up with a Navy innovation brand vision for an Open Oceans GIS Platform. I think something like this could be a big win-win for Navy global transparency and partnership activities, and with luck, some Navy service leader is out there now championing a variant of this idea.

Hope you like it! As always let me know your thoughts below or by email (johnsmart{at}accelerating{dot}org),  thanks.

Obama’s BRAIN Initiative – A Failure of Mapping Vision

A “clarified” mouse brain at right (lipids removed, all else stays in place). Transparent to optical microscopy, all proteins, receptors, RNAs can be repetitively interrogated with molecular probes. Amazing!

[4/18/2013 Update: The Stanford press release on 4/10 announcing CLARITY, the Karl Deisseroth lab's amazing new method for optically transparent brain mapping, just makes everything I said below even more correct and urgent, from my perspective. Deisseroth is one of the 15 experts on Obama's neuroscience dream team, so I'm sure he advised the White House of its implications. The CLARITY paper was accepted for review at Nature in September 2012. The CLARITY method is like PCR, a multipurpose, revolutionary new research tool that will open up vast new imaging and molecular phenotyping research capabilities in any biological tissue, and in particular the brain. Salk's Terry Sejnowski said: "It's exactly the technique everyone's been waiting for." He told the Associate Press that it will speed up brain anatomy research by "10 to 100 times."

And yet Obama's team still proposed just $100M in funding for brain mapping for the first year. That's simply ridiculous. Please, America, wake up! It's time to spend some real money on neuroscience and bust humanity out of its ignorance. Stop being scared of how much better things will soon be, once we've cracked the riddles of neural information processing. Someone also needs to give Deisseroth a serious prize or two. Optogenetics and CLARITY, both out of his lab, are each profoundly important biological sciences breakthroughs.]

This post goes in my deviants category, as it is about someone who I believe has made an important but correctable mistake, and who should therefore be called out and (in this case gently) reproved, so they might act better in the future.

Obama’s BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative, announced today, concerns what is arguably the most important scientific project we humans are doing today: figuring out how higher biological intelligence works, by using new tools to explore and map it at all relevant resolutions. Neuroscientists have developed powerful new optogenetics tools for monitoring neural action in vivo at molecular, cellular and circuit levels  (activity maps). There are also new tools for the automated mapping of synaptic connections (connectomics maps) in chemically preserved brains, tools that led Ken Hayworth and I to co-found the Brain Preservation Foundation. Many tools are still to be developed, but several are already proven, they just need funding to use them to build activity and connectomics maps and conduct more experiments that tell us what’s going on in the brain. Brain mapping has many potential benefits for science and medicine, but its greatest promise, in my opinion, is that it will allow us to improve our models of intelligence in our much faster and eventually far more capable electronic systems.

Maps matter for many reasons, one being that some of the brain’s circuit structure and function will turn out to be highly similar from brain to brain (developmental) and some will be unpredictably different (sometimes called “evolutionary” or “Darwinian” differences). Understanding the developmental parts of the brain, and how they constrain and enable the evolutionary parts, will get us much farther down the road of building self-improving artificial intelligences. Activity and connectomics maps, and a few other new tools for monitoring neural activity at molecular scale will finally allow us to uncover the neural coding system, the ways networks of neurons store short and long term information in their association patterns and strengths. Having these maps and other monitoring tools will of course provide many medical and neuroscientific benefits, and these can be sold most easily to the general public, but the intelligence benefit for science and society, via advances in computational neuroscience and machine learning may quickly become the most important for us.

Obama hinted in his State of the Union address in February that he wanted to see America’s brain-mapping and related neuroscience efforts  “reach level of research and development not seen since the height of the Space Race.”  But in his announcement today he has committed just $100M to the project for its first year budget. $100M! And the money committed so far is a hodge-podge that is not project or map focused. Consider that Europe’s Human Brain Project just got $1.3B committed from the EU for the next ten years, even though that project is doing far less critical, lower-resolution simulation work that will very likely have a poorer payoff. The Europeans, at least, are putting their money where their mouth is, and focusing on a big project. Our effort is, unfortunately, a very lame start. Yes, the Human Genome Project started with the same small seed funding the first year. But that was when genomics was untested, proteomics a dream, and understanding and mapping the brain still largely unreachable. We’re way beyond that now. We know how important this is. It’s time to match real funds with the rhetoric.

The scientists involved in the BRAIN initiative know we’ll need at least $3B to make major discoveries with activity maps alone, and this estimate doesn’t even include synapse-level connectomics maps, which deserve a few billion as well, if we really want to figure out the neural coding language. $5B is not a lot of money for the incredible intellectual advances we can expect. This is a whole new domain of neuroscience we are opening up. To put this in perspective, we are presently spending $85 billion per month on QE3. Obama cobbled this $100M together by redirecting existing funds in NIH, DARPA, and NSF budgets, so it isn’t even new money, it’s just reclassified R&D. An NIH working group has been designated to develop a multi-year plan with cost estimates by June 2014, and Obama has fast tracked the group by asking for an interim report by fall 2013. But its still quite unclear what the goals of the project are, and whether connectomics maps will even play a role.  With regard to connectomics maps, we are not talking about the misnamed “Human Connectome Project”, which is actually just a Projectome Project (a map of white matter axons, not synapses). We are talking about a real synapse-level connectome. If they pass on funding at least a representative subset of synapse-level connectomics maps, that will be a major failure of nerve.

Isn’t $100M a great start for Year 1? Not in my book. I think it is reasonable, for a project of this potential benefit, to expect us to start with a level of finding that is ten times more, at least a billion dollars up front, and a commitment to seek at least a billion a year for the next ten years. That’s enough to influence more folks going into the field, and this project is worth every dollar. We should and can demand a lot more from this second term president, particularly one who understands science and tech the way he does. Obama has committed to a commission to study bioethical issues related to the project (a concession to conservatives perhaps), but so far his “dream team” of 15 neuroscientists have not committed to connectomics maps, or to a massive push to crack the neural coding algorithms. Perhaps they will, but given the vagueness of today’s announcement, it’s quite possible we will miss a very important chance to make this a well-defined project, and prioritize what matters most.

Perhaps what’s needed next is an open letter, by a number of leading neuroscientists, about immense social promise of these new brain mapping and research technologies, and a statement of the likely benefits to come if we spend big on them now. Something like the Einstein-Szilard letter to Franklin D. Roosevelt, which helped launch the Manhattan Project, but this letter would be public, and benefits-driven, rather than private, and dangers-driven. The Manhattan Project cost roughly $26 billion in 2013 dollars. That’s the scale, give or take ten billion, at which brain sciences investment today would make a profound difference to the future of humanity.

As just one example of a health-focused bill we could all get behind, starting now, would be a ten year, ten billion dollar effort focused on preventing or delaying Alzheimer’s and normal age-related memory loss, which we know needs more basic research if we are to solve this problem in our lifetimes. Such a bill could easily include a commitment to five billion dollars of brain mapping over the decade, and a specific push to understand learning and memory and crack the neural coding algorithms. Understanding normal maps, seeing how maps change in memory loss, and how the brain compensates via neuroplasticity, would be huge advances for medical science and therapy. I recommend reading Norman Doidge, in The Brain that Changes Itself, 2007,  for fantastic and motivating examples of how resilient our brains can be to memory loss and damage.

Ultimately, as readers of this blog know, whether second-term American politicians have the courage to say it publicly or not yet, I think smarter machines, not more 20th century jobs, have become the primary wealth creator, so that’s where our thoughts should go first, as we look for ways to improve our lot. I think it’s time we got serious as a species about realizing what kind of progress the universe has engaged us in. We are here to use our wits and works to become something greater than ourselves. Our highest role appears to be to take what the universe has done with us and make something even smarter, more ethical, more productive, and more resilient as our progeny. This is what civilization has been about, since the birth of technology, as I see it.

Want to let the Obama administration know your thoughts on making Brain Mapping, including connectomics maps, a top funding priority? You can send a brief email to the White House by using this form, as I have. Thanks.

Development Tourism: How Would You Help Ten Kids in the Developing World?

If you wanted to help ten kids in the developing world while on a brief vacation to a place you’ve never been, what ideas, tools, or strategies would you recommend?

My wife and I and my friend Clement Vidal are going to Ghana, West Africa next month. Rather than ecotourism, we are much more interested in “development tourism,” or mixing our self-serving vacation tourism with some people-serving, capacity-building activity at the same time. Development tourism is a term already in use by a few foresighted tourism groups today. In an ideal world I think it would be more popular than ecotourism, also a worthy goal but I think quite secondary to people and institutional support. Consider for example how freeing and educating women stops future population growth in developing nations. This is perhaps the single best strategy for improving our global environment.

There is a lot of cynicism attached to the idea of development tourism by some, with castigation of the “cowboys” and “outsiders” who dare to consider themselves as doing development work when they are in a developing country for any period less than a year. I’m sure a lot of the criticism is justified, but as with any good new idea, it will be easy to fault the pioneers, and poorly done at first. We can only afford to spend two weeks in Ghana, and that will be perennially true for the vast majority of tourists who go to the developing world for vacations, and we want to do something helpful while we are there. So let’s get on with finding good solutions for the millions of folks who are in a similar situation every year.

StuffYourRucksack.com, a nonprofit started by Kate Humble, a UK television broadcaster and journalist, is the best program I’ve found so far in the development tourism space. On StuffYourRucksack tourists can find local charities near where they’ll be vacationing in the developing world, see small things these charities need, and bring them in their suitcases. It took me just 60 seconds on their site to find a development group near where we are going, serving a small community called Akiwidaa fishing village near Sekondi-Takoradi, and to pick something useful to bring.

Consider also Kiva.org, a global leader in development microfinance. It would be great to see Kiva add a development tourism section to their website, encouraging you, if you are going to a developing country for tourism, to also bring useful wish-list items, or to work for a short stint with the folks to whom you are loaning money. Just the act of visiting them in person, to check up on your investment, make friends, and give encouragement, may also help them to succeed. I’ve made a small loan to First Choice Group, a group of 13 women selling plastic products and other items in Accra. But Kiva doesn’t give me any way to contact them and find out if they’d like me to bring anything or meet with them when I’m in Accra. So it’s missing this key human element, which many lenders would love to see.

There’s power in appropriately naming a category, and getting that name to spread. I’d like to see Kate’s and Kiva’s and similar websites agree to use an easily recognizable term like “development tourism”, and others like it, so we can easily find many such organizations using a web search on the term, and so the behavior spreads as quickly as possible. Development tourism also needs its own wikipedia page, to accompany and compete with ecotourism there. Anyone want to create the stub?

Perhaps my contacts at the Foresight Education and Research Network (FERNweb.org) will be of help. FERN runs the GlobalForesight.org wiki, a collection of foresight resources around the world. I co-founded FERN a few years ago with a few other futurists, and under its great new Executive Director, Susan Fant, it has been growing steadily in size and scope. Through FERN leader Karen Arvidsson, I’ve reached out to André Roux, who runs the Masters and PhD programs in Futures Studies at the U. of Stellenbosch in South Africa, Africa’s leading foresight training program, and also to the folks who run Foresight for Development, a group of South African futurists promoting greater use of foresight tools to improve Africa’s future. I’ve asked if any of them know any Ghanaian futurists, so I can make contacts when I’m there.

Thanks to my futurist friend Scott Lemon, who notes that the Bill and Melinda Gates Foundation, in partnership with Cannes Lions, an advertising industry organization, just funded a multi-round competition for ways to help the public in affluent countries to understand the impact of foreign aid, and specifically to show how development investments are succeeding, particularly on the one-to-one level, the fastest growing segment of foreign aid. As globalization and immigration increase, and as money transfer gets cheaper and easier, remittances, money sent back to family members from immigrants to the industrialized world, has grown so much that it now greatly exceeds foreign direct investment and foreign aid combined in many of the poorest countries. For the entire continent of Africa, remittances account for more than 50% of all development assistance. For some of the poorest African states, and for Haiti in the Americas, remittances account for more than 50% of national GDP.

One-to-one, bottom-up transnational strategies have worked well before. Back in the 1970′s physicist Robert Fuller pioneered the radical idea of citizen diplomacy, encouraging individuals to do their best to fight Cold War animosities by promoting US-Soviet cultural contacts, extended visits, and mutual aid, regardless of the official attitudes of both countries at the time. Several groups are continuing this courageous culture work in conflict zones such as Israel-Palestine, India-Pakistan, and Iran and North Korea vs. The Rest Of The World.  At the same time, what we might call “remittance diplomacy” has grown these last few decades to become the diplomatic elephant in the room. It’s time we recognized this, and made it easier and cheaper for immigrants and guest workers to aid their families back home, and highlighted their stories. It’s also time we grow the ideas and communities of development tourism until they are a significant percentage of the $6 Trillion dollar global Travel and Tourism industry.

Kids in Akiwidaa Fishing Village, Ghana

As for my little part, I’m particularly interested in taking actions that will positively impact at least ten people, and perhaps hundreds or thousands if others choose to do the same. I also am interested in finding worthy projects that will scale most easily. For this reason I favor solutions like technology and business, and in helping women and students, as I think changing their lives can have some of the greatest long-term impact.

We’ll be starting out in the capital city, Accra, visiting some of the visionary folks running Ashesi University, a truly inspiring private college educating a new generation of ethical, entrepreneurial African leaders, and Meltwater, one of Ghana’s promising new tech incubators. Then we’ll be heading out to some of the towns and villages along the west coast.

Before I go I’m reading and challenging myself to do some top-down, outsider thinking about what might be valuable to bring. I’ve watched some great online videos, and have found Martin Meredith’s The Fate of Africa: A History of the Continent Since Independence, 2011, a particularly sobering and highly recommended read. Did you know that the 2010 GDP of the entire continent of Africa, 54 nations and 1.0 billion people, is roughly the same, at $1.2 Trillion, as the single developing country of Mexico ($1.16 Trillion, 112 million)? This statistic grossly implies that there is nine times less per capita economic development in Africa than Mexico.  It is best fact I presently know to communicate just how significant Africa’s political, institutional, and economic challenges are.

It would be a copout to take the position that there’s nothing I, a white privileged outsider can plan to bring to Africa before I go that will be of value unless I’m willing to visit multiple times and spend years on the ground, neither of which I may ever do. My life so far has convinced me that while bottom up approaches are the main driver of improvement in complex systems, top-down solutions also have some merit, and a role to play.

It seems ethical, given the great needs of the bottom billion human beings, to limit our own tourism to some small fraction of our income. But if we’re going to travel, we can do our best to bring some development to the tourism we do. So let me ask you: If you wanted to bring some technology, financial support, or other aid to a developing country that you’ve never visited, will be visiting only briefly, and may never visit again, what would you be moved to do? 

One clever technology I’m Johnny Appleseeding while I’m there is a centrifugal (spin) dryer. This model, by Laundry Alternative, purchased on Amazon for $150, is small enough to bring in my suitcase. I’ve got another company’s version in my gym (Elgin Suitmate, horribly overpriced), and it takes literally sixty seconds after a swim, and very little electricity versus a conventional dryer, for my swim trunks to get spun dry to the touch after I place them inside. These would be hugely useful in all equatorial countries, as one’s swimming clothes, towels, and regular clothes (after rains) are constantly getting wet, but there’s no cheap or quick way to dry them. Hanging them out just doesn’t work in humid climates. None of the inns had them in Costa Rica when I was there, so I realized last year that there was a big opportunity here. Having something like this at all the beach inns would increase tourism, so it classifies as developmental tourism in my book, as it would improve the tourism experience in any place that has electricity, as it makes it easy for tourists to reuse more and pack fewer clothes and towels. I offered to bring this one and pay half of the cost of it, or $75, for an inn we’ll be staying at. They are also excited to use it for quick-drying some of their sheets during room refreshes. I’ll also be demoing it to a few other inns as well beforehand, to try to get more folks to use them. Ideally, every inn at the beach in Ghana and every other equatorial country would have one of these, and make them easily accessible to tourists.  Entrepreneurs: There is a good business opportunity in selling and servicing these globally. Here’s a company in India that makes industrial ones. I wonder how cheaply they could make a hotel version?

Eton Microlink Radio-Light-Charger

For my main development activity I want to try to be helpful to ten students in one of the local villages with some technology. My current plan is to bring ten small solar + hand crank radios, with LED lights for reading at night and during power outages. Theft is a persistent issue in Ghana as in many developing countries, so I’m thinking a small unit you can keep with you or easily hide away would be good. This Eton Microlink F160 solar and handcrank radio, for $30, may be the best inexpensive version of these devices. You can listen with earbuds without disturbing sleeping family members, a great feature for kids who like to stay up late, and you can attach and recharge USB devices (ipods, videopods, phones) via the crank. Eton’s is the best-built small unit I can find on Amazon at present. The crank, solar cell, and battery all seem to work well, replacement rechargeable NiMh batteries are available, and it’s reasonably water resistant, which will hopefully make this radio particularly useful in places still lacking electricity, like Akiwidaa village.

I’m planning to give them to one of the local charities, with the recommendation to give them to a respected teacher, and the recommendation that they give half of them to their hardest working students so far this year, and half to their most improved. I’m a big believer that small incentives in school, tied to controllable outcomes, like attendance, hard work, improvement, and good citizenship behaviors can go a long way to empowering kids to study more, work harder, excel, and support each other in their formative years. I’m looking forward to finding out when I get there if the charity thinks these are good ideas, or if they’ve got a better plan.

LPTV setup for broadcasting video in a neighborhood.

Ghana’s media are among the freest in Africa since 1995. Telecommunications in Ghana are also growing, with 25% mobile penetration (6M users), but just 3% internet (750K users). There are ~30 TV stations in the country, and ~130 FM radio stations. So after cellular voice and SMS, radio is their best network at present. Call-in shows are particularly popular, and families sit around the radios listening to them, the way the our grandparents in the developed nations did in the 1930′s.

To complement cellular, it looks like radios are a sweet spot for inexpensive technology network development in many underdeveloped countries. Getting some solar powered satellite TV dishes for villages and many analog low-power TV (LPTV) transmitters in the towns could also be a great next step.  

Are there any nonprofits anyone knows of that are focused on growing low power radio and TV, and inexpensive cellular networks in developing countries? If so, let us know in the comments, and I’ll list them here.

Adding permanent new systemic networks of distributed, many-to-many communication to a country’s infrastructure is I think one of the most powerful ways of reducing systemic political and institutional corruption and insulation against accountability, transparency, and change. The latter are the greatest problems in our least-developed, most historically exploited countries, as Meredith documents so well in The Fate of Africa, that saddening yet grounding book I recommend above.

Imagine a wearable wrist radio, and a wrist radio+TV, powered by quickly replaceable coin-cell batteries that can be solar charged with a separate small solar charging station. One wrist radio per child. If there are good local citizen-access low power radio stations in the villages for the local community to broadcast on, folks with radios could much more easily get together for sports, cultural events, and other mass activities, including political activism.

In an era when you can find this wrist radio+TV for $35 on Alibaba, you know a low-cost, bulletproof, solar powered version of this is doable today. A good design would be multipurpose, something that could be worn on a lanyard, clipped to pants, or worn on the wrist per individual taste, like the little two way radio MediVoice Alert Radio seen here.

So here’s a great $100M development project for a forward-thinking philanthropist. There are 25 million Ghanaians. Give away three million of these devices, in merit based competitions over the next few years, to the 10% hardest-working, most community-oriented kids and citizens in Ghana. Subsidize at-cost access for the rest. Help Ghana’s towns build several new commercial and public-access TV and radio stations, and many more cellular and SMS networks. Keep lowering the cost of this network development philanthropy with competitive bidding, transparency accounting, and long term operation and training staffed primarily by outside experts.  Then watch how quickly their levels of entertainment, socialization, education, activism, and democracy improve. Others will soon copy your success in all the least-corrupt, most communication-permissive underdeveloped countries of the world, and later, everywhere. Any takers?

If you have any advice to offer before we go on our trip, I’d love to hear it, thanks.

Preserving the Self for Later Emulation: What Brain Features Do We Need?

Let me propose to you four interesting statements about the future:

1. As I argue in this video, chemical brain preservation is a technology that may soon be validated to inexpensively preserve the key features of our memories and identity at our biological death.
2. If either chemical or cryogenic brain preservation can be validated to reliably store retrievable and useful individual mental information, these medical procedures should be made available in all societies as an option at biological death.
3. If computational neuroscience, microscopy, scanning, and robotics technologies continue to improve at their historical rates, preserved memories and identity may be affordably reanimated by being “uploaded” into computer simulations, beginning well before the end of this century.
4. In all societies where a significant minority (let’s say 100,000 people) have done brain preservation at biological death, significant positive social change will result in those societies today, regardless of how much information is eventually recovered from preserved brains.

These are all extraordinary claims, each requiring strong evidence. Many questions must be answered before we can believe any of them. Yet I provisionally believe all four of these statements, and that is why I co-founded the Brain Preservation Foundation in 2010 with the neuroscientist Ken Hayworth. BPF is a 501c3 noprofit, chartered to put the emerging science of brain preservation under the microscope. Check us out, and join our newsletter if you’d like to stay updated on our efforts.

As one of the themes of this blog I’ll try to explain why I’m optimistic about these technologies, and to enlist your help in pushing forward their validation or falsification as fast as feasible. If validated, I’ll be pitching to you for help in making the brain preservation option accessible and affordable around the world, as fast as feasible. To these ends, thank you for any frank and constructive feedback you can leave in the comments.

In this post, I’d like to try to provisionally answer a question relevant to the first three statements above:

To preserve the self for later emulation in a computer simulation, what brain features do we need?

We can distinguish three distinct information processing layers in the brain:[1]

1. Electrical Activity (“Sensation, Thought, and Consciousness”)
These brain features are stored from milliseconds to seconds, in electrical circuits.
2. Short-term Chemical Activity (Short- and Intermediate-term Learning – “Synapse I”)
These brain features are stored from seconds to a few days in our neural synapses (synaptome), by temporary molecular changes made to preexisting neural signaling proteins and synapses.
3. Long-term Molecular Changes (Long-term Learning – “Nucleus and Synapse II”)
These are stored from years to a lifetime in our neuron’s connectome, nucleus (epigenome) and synaptome, by permanent molecular changes to neural DNA, the synthesis of new neural proteins and receptors in existing synapses, and the creation of new synapses.

At present, it is a reasonable assumption that only the third layer, where long-term durable molecular changes occur, must be preserved for later memory and identity reanimation. The following overview of each of these layers should help explain this assumption.

1. Electrical Activity (“Sensation, Thought, and Consciousness”)

Our electrical brain includes short-distance ionic diffusion in and between neurons and their supporting cells (i.e., calcium wave communication in astrocytes), action potentials (how neurons send signals from their dendrites to their synapses), synaptic potentials (how signals cross the gaps between neurons), circuits (loops and networks) and synchrony (neurons that fire in unison, though they are widely separated). Electrical features operate at very fast timescales, from milliseconds to a few seconds, and are variable (not exact), volatile, and easily disrupted.

Neural Synchrony – Our Leading Model of Higher Perception and Consciousness . Image: Senkowski et.al., 2008

These features certainly feel very important to us. They include our sensations (sensory memory) and current thoughts (commonly called “short-term” memory by neuroscientists). Recurrent loops, special electrical circuits that cycle back on themselves, hold our current thoughts (when you rehearse some information to avoid forgetting it, you are literally keeping it “in the loop”). Neural synchrony creates our conscious perceptions, and when it happens in the self-modeling areas of our brain, it gives us self-aware consciousness.

Yet electrical features are also fleeting. When you sleep, or are knocked unconscious, or are given an anesthetic, your consciousness disappears, only to be “rebooted” later, from more stable parts of your brain. Our memories aren’t even recalled with precision but are rather recreated, as volatile electrical processes, from these molecular long-term stores, in ways easily influenced by our mental state and cognitive priming (what else is on our mind). That’s why eyewitness testimony is so variable and unreliable.

The electrical features of our self are thus like the “foam” on the top of the wave of our long-term memories and personality. They make us unique for a moment, as they hold only our most immediate thinking processes.[2] Amazingly, people who undergo special surgeries that stop their heart, and some who drown in very cold water, can have no detectable EEG (electrical patterns) for more than thirty minutes, and their brains successfully reboot after rewarming them. Essentially, these individuals are recovering from clinical brain death. Not only do they not have consciousness during this period, they have no unconscious thoughts. Yet because their deeper layers aren’t too disrupted, they can restart their electrical activities.

An excellent book about neural spikes, loops, and synchrony is Rhythms of the Brain, Gyorgy Buzsaki, 2006. It explains the emergent properties and integrative functions of these “highest order” electrical features of our brain. See also this recent discovery of electric field coupling among neighboring neurons, by leading neuroscientists Henry Markram, Christof Koch, and others, and reported by Peter Hankins on his great cognitive science blog, Conscious Entities. Ephaptic coupling is a way for neurons to synchronize spike timing in neighboring neurons, via a mechanism completely independent of synapses. Neurons are much more versatile in modes of communication and synchrony than previously thought.

My late mentor at UCSD, Francis Crick, and his Caltech collaborator, Christof Koch, call this topic the search for the Neural Correlates of Consciousness. It’s a great phrase. Consciousness is not a mystery we’ll never solve, but according to a number of neuroscientists it is a physical process of neural synchrony, in particular regions of your brain. These brief, rhythmic synchronizations share information between groups of neurons in distant regions of the brain by tightening up (“binding”) their interdependent sequences of action potentials. The synchronizations are controlled by the inhibitory neurons in our brain, which use the GABA neurotransmitter. Disrupt gamma synch, as with anesthesia, and you take away consciousness. Give a drug like zolpidem, which activates GABA neurons and increases gamma synch, to patients who are in persistent vegetative state, and amazingly, you will wake 60% of them up from their comas, to varying degrees! Wikipedia doesn’t yet have a good explanation of the gamma synchrony model of consciousness, but they will in a few more years. Laura Colgin at Kavli has found two reliable gamma synch mechanisms in rat hippocampus. She speculates that slow gamma makes stored memories available to current consciousness, and fast gamma integrates sensations to create conscious perceptions.  Though neuroscientists don’t yet all agree on the details, many have found neural correlates of sensations, thoughts, emotions, and consciousness in the electrical features of our brains. In conjunction with the short-term chemical changes we will describe next, these processes represent both our “highest” and our most volatile and impermanent self.

2. Short-term Chemical Activity (Short- and Intermediate-term Learning – “Synapse I”)

Short-term chemical activity is the next layer down. It involves all our short- and intermediate term learning and memory, everything beyond our sensations, current thoughts, and consciousness, but not including our long-term memories. We can call this layer “Synapse I.”

As our electrical experiences and thoughts race around the various circuits in our heads, we make a number of short-term learning changes in our neural networks to capture, for the moment, what we’ve just experienced and learned. These involve changes to preexisting proteins in our preexisting synapses (communication junctions), changes that last for minutes (short-term) to days (intermediate-term). These are changes in both the mechanics of neurotransmitter release and short-term facilitation (strengthening) or depression (weakening) of synaptic effectiveness. Synapses are temporarily modified by the precise timing and frequency of electrical signals (action potentials) received by the postsynaptic neuron, a process called spike-timing dependent plasticity. There are short-term changes in signaling molecules (neurotransmitters, cAMP, Ca++, CamKII, PKA, MAPK), and membrane receptors (NMDA). Phosphorylation states (chemical tags) are altered on some of these molecules, and a temporary equilibrium between kinases (enzymes that add phosphates to key molecules) and phosphatases (enzymes that take them away) is established in the synapse. [Note: In late 2012, Ye et. al. showed in Aplysia how precise spatiotemporal signaling in the synapse involving PKA holds short-term memories in synaptic electrochemical networks, and the interaction of PKA and MAPK holds intermediate-term memories in these networks, in a process called synaptic facilitation.] If any of these short- or intermediate-term memories or thinking patterns are selected to become long-term, communication with the cell nucleus must now occur, and new membrane proteins and synapses are then built, involving new or altered circuits in the connectome. If not, the new memory or pattern dies out.[3]

Every night, when we sleep, our short- and intermediate-term brain writes important parts of its experiences to our long-term memory, building durable new synaptic connections, where this learning can now stay with us for years to life, in a process called memory consolidation. This process moves a subset of our recent learning and memories, apparently the most relevant parts, from temporary spatiotemporal signaling states to permanent new synaptic structures, anchored to the cytoskeleton of each neuron. We can think of these new proteins, synapses, and circuits established in neural synapses and nuclei in a way that is very roughly like DNA, as they are long-term stable structures, encoded in a partly digital form, that will endure all the flux and variability of the biochemistry within each neuron, over a lifetime.  It is these unique synaptic and epigenetic networks that we must preserve, scan, and upload in creating neural emulations, as we will discuss. Long-term memory formation happens best when we are in slow wave (deep and dreamless) sleep, which we get in cycles during the night (and especially well if our sleeping room is dark and quiet) and also during a good nap (a great way to “lock in” what you’ve learned, after a demanding learning period that will naturally make you sleepy).

Neural dendrites, cell body,  action potential, and synapses. Image: Gallant’s Biology.

All our neurons work in circuits, and strengthen or weaken their connections based on chemical and electrical activity, in a process called Hebbian learning. Just like your muscles, which come in two sets that oppose each other around every joint, neural circuits are both excitatory and inhibitory at many decision points in the network. Perhaps most important decision points are the cell bodies of each neuron, where the nucleus is. The electrochemical current from all the dendrites (“roots”) of each neuron flows toward its cell body, and action potentials (current waves) flow from the cell body to its synapses (“branches”), along the axon (“trunk”) of each neuron. Glutamate is the main neurotransmitter we use to send excitatory current from a synapse to the dendrite of the next neuron in a circuit (the postsynaptic neuron). Glutaminergic synapses are thus called “positive” in sign, and they promote electrical activity throughout the brain. GABA is the main neurotransmitter we use to let inhibitory current leak out of a postsynaptic dendrite. GABAergic synapses are thus called “negative” in sign, and they depress circuits throughout the brain.

Each neuron sums the net result of the positive and negative inputs it receives from its dendrites, over milliseconds to seconds. If the current exceeds that neuron’s threshold,  it sends an action potential (depolarizing electrochemical signal) to all its synapses. As the brain learns, our synapses enlarge or shrink, giving them greater or lesser excitatory or inhibitory effect, and we may grow more or lose our synapses. With few exceptions, each neuron also uses just one type of neurotransmitter (eg., glutamate or GABA), or the same small set of neurotransmitters, at all its synapses.

The architecture of memory, thought, emotion, and consciousness may thus be reducible to a surprisingly simple set of algorithms, connections, weights, signaling molecules and electrical features in each neuron, working together in a massively parallel way to create computational networks that are far more complex than the individual parts.

Hippocampus and frontal lobes. Image: NIH

In higher animals, the neurons in our hippocampi (two c-shaped areas of ancient, primitive, three-layer cortex in each hemisphere of our brain), and the connections they make to the rest of our cerebral cortex (especially to our frontal cortex), store all kinds of episodic (experiential) and declarative (fact-based) information, all from our last few days of life. At the same time, neurons in our cerebellum (a more primitive, “little brain” at the base of our skull) store procedural learning and memory (how to move our bodies in space). Experiments with rats and primates tell us that each hippocampus makes perhaps tens of thousands of new neurons every day, from neural stem cells. Other than for repair after certain kinds of injury, no other part of the adult brain is able to use stem cells in detectable numbers, as far as we know. The rest of our brain is postmitotic (unable to use cell division to maintain its structure), as neuroscientists demonstrated in an elegant experiment in 2006. Our neurons must be maintained by our immune and repair systems, and as they die via natural aging, or kill themselves in apoptosis, memories start to die.

Hippocampal dendritic spines. Image: Fiala & Harris, 2000.

Our hippocampal neurons have the very tough job of temporarily holding, in their uniquely dense synapses, and via their connections to the rest of the cortex, much of the new information we have learned over the last day or two, during our entire adult life. Here is a picture of a computer reconstruction of a small section of ten columns of synapse-rich “spiny dendrites”, from the CA1 (input) region of the hippocampus. CA1 contains areas like place cells, imprinted genetically with detailed maps of 3D space. Like the digestive cells lining our gut, and the skin cells at our fingertips, certain hippocampal neurons appear to get worn out on a regular basis by this demanding short-term memory holding function, and so some neuroscientists think new ones must regularly grow and mature to replace them.

People whose hippocampi are both surgically removed, like the memory disorder patient Henry Moliason, who had this done at the age of 27, can’t update their long-term episodic and declarative memories. H.M.’s long-term memory and personality was mostly “frozen” at 27. He could occasionally add bits of new information to long-term memories of the same type he’d built before the surgery, and he could learn new procedural (spatial and muscle) memories in his cerebellum, but he had no cerebral knowledge that he’d added these memories. H.M.’s amazing life suggests that if the brain preservation process damaged our hippocampi, but not the rest of our brain, we’d come back without our most recent experiences (two-day amnesia), but all our older memories and personality would still be intact.  Ted Berger at USC managed to build a simple version of an artificial electronic hippocampus for mice in 2005, so there’s a good reason to believe that this part of our brain, though important, isn’t irreplaceable. As long as you could install an artificial hippocampus in the computer emulation constructed from your scanned brain, you’d be back in business as a learning organism, with only some of your more recent memories and learning erased. This all helps us understand that what cognitive scientist Daniel Dennett would call our center of narrative gravity, our most unique self, is our long-term memory.

The fact that only special areas of our hippocampus can add new cells during life exposes a harsh reality about our biological brains. We are all born with a very large but fixed long-term memory capacity, and this capacity gets increasingly used up, pruned and potentiated, the older we get. Anyone over 40, like myself, knows they are considerably less flexible at learning new things than they were at 20. It’s far easier for older people to add more twigs to branches of knowledge we’ve previously built in our “tree of experience” than to form new branches. We can do it, but gets progressively tougher and slower the older we get.

This means, if we want to be lifelong learners in a world of accelerating technological and job change, it is critical to get an early education that is as categorically complete (global, cosmopolitan, and scientific), moral (socially good, positive sum) and evidence-based as possible. Our children need the best mental scaffolds they can get early on, or they’ll spend the rest of their lives trying to prune away harmful and untrue thoughts and beliefs acquired in their youth. Psychologists have long known that it is much easier to add increasing specificity to a neural network than it is to unlearn (depress) any branch, once it’s built. We need to be careful about what we allow into our memory palaces.

That said, children also benefit greatly from freedom, early on in life, to study what they themselves desire to learn, and to have a good degree of control over learning outcomes and style. This freedom, and appropriate rewards for effort of any kind, induce them to build intricate mental specializations in areas they are personally passionate about. For those who want to know how to implement a 50/50 balance of broad, state-mandated learning in future-critical STEM fields, analytical thinking, and civics (the “hilt of the sword”, basic protective world knowledge), and a personalized program of student-directed specialized learning, creativity, and play in the other half of the time, mastering whatever they can convince their teachers is worth studying (the “blade of the sword”, passionate specialization allowing them to cut their own unique path of new knowledge and value in the world), I strongly recommend The Finland Phenomenon, 2010 . This exceptional film, and to a lesser extent Tony Wagner’s book Creating Innovators, 2012, demonstrate key elements of the future of learning for enlightened societies, in my opinion. It may take 20 years for the evidence to be incontrovertible, but you can give it to your child now, if you find it appealing. The US will eventually realize that if the Finns did it, rejuvenating their previously failing education system over a twenty year period, we can too.

Cybertwin – Virtual Assistants With Simple Models of Our Interests Will Be Useful for Many of Us By the Early 2020′s. Image: MyCyberTwin.com

It is also liberating to realize that while our biological brains are less able to learn fundamentally new things as they age, all the digital technologies we use, technologies which will bring our emulations back at an affordable price later this century, will continue to get exponentially more powerful every year. Most of us don’t realize this, but everyone who uses a social network, email, or any other technology to capture things they say, see, and write about is also creating a digital simulation of themselves. By 2020 we’ll all be talking to and with our best search engines in complex sentences (the conversational interface), and shortly thereafter, we’ll all be able to use simple software agents, Cybertwins, or “Twins,” which will have crude maps of our interests and personality, so they can serve us better. Computational linguists know that if you capture what a person says for just two years, we are so repetitive about what we care about that a cybertwin could whisper into our ear the word that natural language processing algorithms predict we want when we are having a senior moment, and they’ll be right most of the time. That’s how repetitive we are, and how good web search will be by 2020. As I wrote in 2005, people who don’t run cybertwins will be much less productive, so they’ll be very popular, even though they’ll bring lots of new social problems in their first generation.

Now here’s the kicker: These simulations won’t be turned off by our loved ones when we die. Our children, friends, and colleagues will use them to interact conversationally, and only in appropriate contexts, with these semantic simulations of us, to keep the best of our thoughts, experiences and personalities accessible to them when desired. Once folks realize that their Twins really are a “digital immortalization” of parts of themselves, and once neuroscience has proven – in the next ten to twenty years perhaps – that we can read (“upload”) particular memories from preserved and scanned animal brains, even very primitive ones, at that point preserving one’s brain for later uploading into a Twin, to improve the quality of the simulation at least, and perhaps even to come back in a self-aware state, at best, will be an increasingly obvious and responsible choice for dying individuals, especially if the cost to do so is quite affordable. What’s more, recent advances in molecular scale MRI scanning strongly suggest that future scanning technologies should be able to nondestructively scan entire preserved brains, to upload their molecular states, memories, and higher functions into a Twin. So if the first scan isn’t perfect, it can always be updated later, from the preserved, “immortal” brain.

Given all this, we can see that teaching our children and ourselves to be digital natives and digital activists, to use the social web and the first affordable commercial lifelogs, like Google glass, when they arrive, is an important way for us to build an ever more capable cybertwin for ourselves and for our loved ones when we die (and ideally, are preserved), even as our biological self naturally slows down and simplifies (prunes away branches of knowledge and memories we once had ready access to) with advancing age.

Now we arrive at our truest self, the part we care most about preserving and sharing with our loved ones and society. It is this self that I expect will later merge with the Twin that many of us will leave behind in the 2020′s, as strange as that might sound today.

Experience-based learning. Image: Graham Paterson, Children’s Hospital Boston

3. Long-term Molecular Changes (Long-term Learning – “Nucleus and Synapse II”)

The production of long-term memory, personality, and identity requires all the short-term synaptic changes above, plus permanent molecular changes in the neuron’s Nucleus (DNA and its histones, or wrapping proteins), and the permanent creation of new cellular proteins, synapses, and circuits (Synapse II). Here’s a brief summary of our understanding of the process[4]:

Nucleus (“Genome, Transcriptome, and Epigenome”)
1. Retrograde transport and signaling from the synapse to the nucleus
2. Activation of nuclear transcription factors and induction of gene expression
3. Chromatin alteration and epigenetic changes in gene expression (gene-protein networks)
Synapse II (“Connectome and Synaptome”)
4. Synaptic capture of new gene products, local protein synthesis, and seeding of new synaptic sites
5. Permanent synaptic changes, activation of preexisting silent synapses, formation of new synapses.

We used several “-ome” words above. Let us briefly consider each. They are very roughly ordered below in terms of their likely contribution to our unique self, from least to most important:

The Genome. These are inherited genes and gene regulatory networks that control instinctual behaviors. Our genome includes the unique alleles we received from our parents. It is easy to preserve, as it is the same in all cells. With one tissue sample we can create a clone later, either physically, or far more likely, in a computer simulation. But this clone has only our inherited uniqueness. We’ll need contributions from the next four “omes” to add our life memories and learning to the emulation.

The Transcriptome. This is the set of proteins made (transcribed) by cells. While proteomics (another “ome” word) is in its infancy, scientists estimate each of our cells has the DNA to express ~20,000 basic protein types. Each type can be further modified after creation by adding or removing chemical tags like phosphate, methyl, ubiquitin, and other small molecules, so that more than a million protein subtypes may exist in a typical human body. Fortunately, each of our ~220 cell types only uses around 5,000 of these 20,000, and perhaps less than 2,000 of the 5,000 are unique to each cell type. Neurons and glia, the cell types we are most interested in, may use just a few hundred protein types to store our higher learning and memory in the nucleus and synapses. The other proteins are there to keep all of our cells alive, which is a critical precondition to being able to store long-term memories in a special subset of neural structures. All this suggests the proteomics of memory and identity, and of later memory and identity reconstruction from scanned brains, are not impossibly complex, but rather highly challenging, fascinating and eventually solvable problems.

The Epigenome. These are learning-based changes in gene-protein networks that happen in the nucleus of each neuron, mostly during the life of the organism. The Dutch famine of 1944 and the Överkalix study in Sweden tell us that some epigenetic changes can be inherited in humans, so we all should seek good nutrition and avoid toxin exposure, as we may pass some of that to our children in the form of compromised and undermethylated epigenomes. But there is a lot more to the epigenome story still to be uncovered, as this 2011 article on epigenetic regulation in learning and memory in Drosophila makes clear. Our epigenome is a gene-regulatory layer that involves chemical changes, mostly methylation, to DNA and to the histone proteins that wrap and expose DNA in the cell nucleus. These changes determine how DNA, RNA, and protein are expressed in the nucleus, and thus may affect, at least to some degree, how neurons uniquely manage their synapses as they grow and learn.

The Connectome. This is a map of our neural cell types, and how they connect. Our connectomes and much of our dendrite structure is very similar in all of us. This shared developmental structure makes it easy for us to communicate as collectives, for ideas or “memes” to jump from brain to brain. Yet with 100 billion neurons making an average of 1,000 connections to other neurons, and most of these not being developmentally controlled, we’ve got the ability to make 100 trillion connections, the large majority of which will be unique to each individual.

The Synaptome. These are key features of the ~1,000 synapses that each neuron makes to others. They are the particular long-term molecular features that determine the strength and type of each synapse, its signaling states and electrical properties, as we’ve described them above. The synaptome is the weight and type of the 100 trillion connections described above, and this information may be the most important “recording” of our unique self. Fortunately, because memories are stored in a highly redundant, distributed, and associative manner in our synaptic connections, our synaptome is to some degree fault tolerant to cell death. Both artificial and biological neural networks experience graceful degradation (partial recall, incremental death) of higher memories as individual neurons die. We also know the molecular code of long term memory is fault tolerant to the noise, deformations, and chaos of wet biology. The feedback loops between the electrical and gene-protein network subsystems interact somehow to stabilize long term memories in a special subset of durable molecular changes, in spite of all the other biochemistry furiously going on to keep the cell alive.

Single-celled animal. Image: Anthony Horth

I am sure the distinguished futurist and technologist Ray Kurzweil will have a lot more to say about these topics in his next book, How to Create a Mind, which comes out next month. You can preorder a copy here. To understand how these subsystems interact in a living organism, let’s start in as simple a model organism as we can find, single-celled animals, organisms that don’t even have nervous systems as we know them. Wetware, Dennis Bray, 2009 is a great tour of these animals. Single-celled eukaryotes like Stentor, Paramecium, and Amoeba do complex information processing, and hold short-term memories in their chemical networks. In 2008, we learned that Amoeba remember and anticipate cold shocks, for example. These networks include the cell’s genome, epigenome, cellular proteins, cytoskeleton, receptors, and cell membrane. They are true computational networks, with both neural-network like and Boolean logic properties. Genes and proteins integrate signals from other genes and proteins, and selectively switch and transmit signals, just like neurons do. The genes in each cell, via RNA, determine which proteins are made, when and where. Most protein changes are part of the short term computation being done in a cell, but a special few will lead to lasting changes in the epigenome and the cytoskeleton and receptors in and on the surface of the cell. These long-term changes are the ones we care most about, as they store the cell’s unique memory and identity.

Until computational neuroscience[5] can predictively model how the gene-protein networks in a Paramecium allows these animals to evaluate options, assign priorities, regulate their moment-by-moment computational attention, continually vary strategies for chasing prey and avoiding toxins, and chemically store their representations, habituations, and memories in an intracellular environment, all within a single cell that has no proper nervous system, the field will be missing its Rosetta Stone. Electrical waves exist in these single-celled animals, but with the exception of mitochondrial energy production, they are of the most primitive, diffusion-based kind. All the considerable intelligence in these animals is coursing, moment by moment, through their gene-protein networks.

In multicellular organisms with neurons, the cytoskeleton and receptors have specialized into the synaptome, the pre-and post-synaptic molecular modification of our synapses, including phosphorylation of switching proteins like calmodulin kinase II. While there are over 50 known neuromodulators and 14 neurotransmitters in our brain, only six neurotransmitters have been regularly implicated in long term learning and memory in our synaptome. It is these and their partner molecules in the synapse and nucleus that are probably most important to understand and model to crack the long-term memory code.

C. elegans connectome. Image: OpenWorm.org

Fortunately, even with our very partial molecular and functional maps today we have still managed to work out some basics of neural network interaction in very small neural ensembles, like the somatogastric nervous system (~30 neurons) in lobsters. We’ve even created early maps of very small whole-animal neural systems, like the nematode worm C. elegans, with its 302 neurons and ~6,000 synapses. We mapped the C. elegans connectome in 1986, but we still know just pieces of its synaptome and transcriptome, and even less about its epigenome. Fabio Piano et. al. give us an overview of the state of C. elegans gene-protein network knowledge in 2006. Note their subtitle is “A Beginning.” Jeff Kaufman has recently summarized the very early status today of whole brain emulation in nematodes. David Dalrymple in Ed Boyden’s lab at MIT is working on C. elegans simulation, and he is optimistic about new tools in neural state recording, optogenetics, and viral tagging for characterizing each neuron’s function. As Derya Unmatz reports in a blog post that sounds like science fiction,  Sharad Ramanathan et. al. at Harvard can now take control of C. elegans locomotion by firing precisely targeted lasers at individual neurons in an optogenetically modified worm’s brain, controlling its chemotactic behavior and convincing it that food is nearby.

A small international collaboration exists to emulate the C. elegans nervous system, called OpenWorm. There’s even a Whole (Human) Brain Emulation Roadmap, started in 2007 by Anders Sandberg and Nick Bostrom at Oxford, and a few other visionary folks in biology, computer science, and philosophy. These important projects are quite early and extremely underfunded at present. The biggest problem today is getting more funded people working on them.

To emulate how C. elegans, Drosophila, Aplysia, Danio, Mus, and other neural networks actually work, and to begin to extract even crude and partial memories from the scanned brains of any of these and other model organisms, we’ll need a better understanding of behavioral plasticity, and the way the synapse, the nucleus, and neuromodulators bias the pattern generators in neural circuits into a particular set of behavioral patterns. This may require not only better neural circuit maps, but better maps of several still partly-hidden intracellular systems involved in long-term memory formation: gene regulatory networks, the transcriptome, and the epigenome[6]. There are gene-protein networks controlling human neural development, neural evolution, and our long-term learning and memory. A special few of these regulatory networks, their proteins, and the epigenomic changes these networks store during a lifetime of human learning may be as important as the synapse, if not more, in determining how our brain encodes and stores useful information about the world.

A great textbook on gene regulatory networks is The Regulatory Genome: Gene Regulatory Networks in Development and Evolution, Eric Davidson, 2006. It will amaze you how much Davidson’s group has learned about these networks, primarily by studying the evolutionary development of one simple organism, the sea-urchin, over several decades. Last month, Isabelle Peter and others in Davidson’s group at Caltech published the first highly predictive model of how these networks control all the steps in sea urchin embryo development over the first 30 hours of its life. 50 genes are involved, and their regulatory interactions can be fully described in Boolean logic. Now they want to model all of development, and some of the networks controlling its variational processes. Consider the magnitude of their achievement: Davidson et. al. have reduced an incredibly complex biochemical process down to a far simpler algorithm. This is what must happen in long-term memory, if we are to use scanned brains to abstract the key subsets of molecular structures that reliably encode it in our neurons.

Protein Microarrays – An Exciting New Tool. Image:  Eye-Research.org

Neural proteomics and the transcriptome are entering an exciting new phase as we use DNA and RNA microarrays, and now protein microarrays to catalog neural transcriptomes and compare them to other types of human cells, and to other primate and mammal neurons. In August, Genevieve Konopka and colleagues published an exciting paper comparing human, chimpanzee, and rhesus monkey neural transcriptomes. We’re finding genes and proteins unique to particular areas in human brains, especially our frontal lobes. We’re building our first maps of the critical differences in the gene and protein regulatory networks that allowed us to wake up, make tools, and walk out of Africa less than two million years ago.

Epigenome (methylated DNA and modified histones). Image: RoadmapEpigenomics.org

We recently learned that what was long called “Junk” DNA, the 98% of each cell’s non-exonic DNA (DNA that doesn’t code directly for proteins), participates at various levels in gene regulatory networks, and through epigenomics these networks can change to some degree over the life of the cell. We’re learning now to map gene-protein interactions in these networks, including epigenomic changes, using tools like Chromatin ImmunoPrecipitation and sequencing (ChIP-seq). Unfortunately, this work is also seriously underfunded. We’ve known about the importance of the epigenome for over a decade. Epigenomic changes can be inherited (watch what you do with your body, as your kids will inherit a record of some of your bad or good life habits in their epigenome), and thus record unique learning in each cell over its lifetime, in ways we are still uncovering.

The NIH started a Roadmap Epigenomics Project for mapping the human epigenome in 2008, but the funding is a pittance, roughly $40 million a year. There is also a global collaborative research database, ENCODE, for sharing what is presently known about all the functional elements in the human genome. We give it roughly $20M/year, barely life support. There are also various Human Proteome Projects under way, but no one seems to be funding any of these seriously, either. None of the politicians or key philanthropists who could make the Human Proteome and Epigenome into national research priorities have proposed any big initiatives, as far as I know. Even our science documentaries don’t adequately convey the promise of these fields. The scientific community is tooling along as best it can in spite of the fact that the public still hasn’t gotten the clue on how much better medicine would be in ten years if we were spending a whole lot more money on this right now.

Recall by contrast the Human Genome Project, which began with fanfare in 1990 and was rough draft completed in 2000, for $3 billion, a price gladly paid by the U.S. and four other motivated nations. The Human Genome Project was, to put it in proper perspective, our planet’s Moon Shot in the 1990’s, our species latest great leap into “inner space.” As those who’ve read my Race to Inner Space post know, I think understanding the machinery of life and intelligence, and nanotechnology in general, is a destination far, far more valuable to us than outer and human scale (as opposed to cell and molecule-scale) space. We need an international Human Proteome and Epigenome Project race. With good funding and leadership, we might nail our first good maps of the neural gene-protein interaction layer in a decade. With business-as-usual, it will likely take much longer.

As we learn the languages of gene regulatory networks, the transcriptome, and the epigenome in coming years, we should learn how to influence these networks in many powerful ways. Do you think the trillion dollar global pharmaceutical industry is big now? Wait for the therapeutics that may start to arrive in the late 2020s, as we begin to learn how to intervene in these networks. I think it is only when we have good maps of these gene-protein networks that we can finally expect medical advances like better learning and memory formation, elimination of a vast range of diseases including cancer and Alzheimer’s, immune system boosting, aging reduction (epigenomics repair), and perhaps even the uncovering of genetically latent skills like tissue regeneration and hibernation. We are not talking about gene modification (inserting new genes in the germline, or in an adult), but rather about improving dysfunctional gene network regulation, and learning how to assay and minimize important parts of the network dysregulation that goes wrong in each of us as we get older and get various diseases.

Ken Hayworth

There’s a nice analogy here, pointed out by my Brain Preservation Foundation co-founder, Ken Hayworth. The Human Genome Project gave the world affordable gene sequencing in the mid-2000’s, and ten years later, we are beginning to see the major fruits: the uncovering the previously hidden worlds of gene regulation networks, the transcriptome, and the epigenome. Likewise, the Human Connectome Project and the still-unfunded Human Proteome and Epigenome Projects could get us affordable neural circuit tracing and functional gene regulatory network modeling in the late 2010s. Just as the Human Genome Project showed us we had a lot fewer genes than we thought (~21,000 rather than 100,000) the Human Epigenome Project may tell us that our gene regulatory networks are functionally simpler than we currently think, and that of the ~5,000 proteins in a typical cell, there are just a handful that matter to our long-term self. With luck, the remaining hidden layers of the neural transcriptome and epigenome will be functionally understood in the late 2020s. In that exciting time, our ability to understand memory and learning, to read memories from the scanned brains of model organisms, and to build biologically-inspired computer models, will all be greatly enhanced.

So to answer our original question, we need to find out if both chemical preservation and cryopreservation will preserve the connectome, the synaptome, and any long-term memory-related changes in the epigenome in a living brain.

Our Brain Preservation Technology Prize, which focuses on the connectome and many but not all features of the synaptome, is an important start down this road. As we understand better what molecular features in the synaptome and epigenome need to be preserved to capture and later retrieve memories, we’ll also need to find out if either chemical or cryopreservation, or ideally both, will reliably preserve those structures at the end of our biological lives, and whether it will be possible for future scanning algorithms to repair any damage done by the preservation process. We’re too early to answer such questions today, but it is encouraging to remember that long-term memory is a very redundant, resilient and distributed system.  Extensive neural destruction can occur in brains via Alzheimer’s, stroke, and other diseases before our memories are substantially erased and cognitive reserve is no longer available.

Sixty years of histology practice tells us that good perfusion of special chemical fixatives such formaldehyde and glutaraldehyde at death will immediately preserve everything we can see by electron microscopy in neurons. A great book on how this works is John Kiernan’s Histological and Histochemical Methods: Theory and Practice, 4th Ed., 2008. Kiernan has been publishing since 1964, and is a leader in the theory and practice of chemical fixation. There are even a few published fixation methods for whole mice brains. Here’s a 2005 paper by Kenneth Eichenbaum et.al. demonstrating a whole brain fixation technique that claims “complete preservation of cellular ultrastructure”, “artifact-free brain fixation” and “no signs of cellular necrosis” in an entire mouse brain. Presumably these methods also protect DNA methylation and histone modification in the epigenome, the phosphorylation of dendritic proteins like CamKII, the anchoring of AMPA receptors in the synapse, and any other elements of long-term memory formation. Presumably these molecules are protected today for years just by aldehyde fixation, if kept at low temperature (4 degrees).  Companies like Biomatrica have even developed ways to store human and bacterial DNA and RNA at room temperature for years. Long term storage of whole brain connectomes, synaptomes and epigenomes at room temperature, an ideal outcome for simplicity and affordability, may work today via additional chemical fixation steps like osmium tetroxide, a process that crosslinks fats and cell membranes, and plastination, a process that draws all the water out of a preserved brain and replaces it with resin.

But all this remains to be proven. If you know of experts who have done work in this area who would be willing to help BPF write position papers on these topics, and who can envision research projects that will answer these questions more definitively, please let me know, in the comments or by email at johnsmart{at}gmail{dot}com. Thanks.

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Footnotes:

1. There is a much older layer of unique learning in each of us that is also important, the intelligent behaviors that gene networks have recorded in each of us over evolutionary time, as instinctual programs, and the unique assortment and variants of genes we each received at birth. Such networks determine our inherited neural programs, instincts and behaviors that are executed mostly unthinkingly and robustly, and during which other forms of learning, like short-term learning, often does not even occur. To preserve this layer we just need a DNA sample of the preserved person, and that particular uniqueness can be incorporated in any future emulation, assuming future computers are up to the task.

2. Some scientists working on brain emulation, like BPF Advisor Randal Koene, suspect that measuring and modeling the brain’s electrical processes, a topic called Computational Neurophysiology, will give us powerful new insights into artificial intelligence. There are new tools emerging for in situ functional recording of electrical features of the neuron. These may be critical to establish the “reference class” of normal electrical responses, for each type of neuron and neural architecture, the class of electrical representations of information. But if the model I’ve presented here is correct, we won’t need to record any electrical features of individual brains in order to successfully reanimate them later. We’ll see.

3. In Aplysia (sea slug), the sensory neuron neurotransmitter serotonin (5-HT) binds to postsynaptic receptors, activates adenylyl cyclase (AC) in the cell to make the second messenger cAMP, causing a short-term facilitation (STF) in strength of the sensory to motor neuron connection. More of the excitatory neurotransmitter glutamate is released by the neuron to its follower motor cells, and Aplysia pulls away harder from its shock. The neuron is also sensitized: K+ channels are depressed, more Ca++ enters the presynaptic terminal, and the action potential spike broadens. Kinases and phosphatases (phosphate adding and removing enzymes) including cAMP-dependent PK, PKA, PKC, and CamKII control duration and strength of these changes. In facilitation, the spike broadens temporarily, as both pre- and post-synaptic Ca++ and CamKII make molecular changes that temporarily strengthen the electrical signal across the synapse. In short-term depression (STD), the same mechanism temporarily weakens the signal. If water is gently shot at Aplysia’s gills ten times in a row, it temporarily learns not withdraw them, via synaptic depression of motor circuits. This short-term memory lasts for ten minutes, and involves a short-term reduction in the number of glutamate vesicles that are docked at presynaptic release sites in sensory neurons (undocked vesicles can’t be immediately used). Repeat this training four times and the slug will turn this into an intermediate-term memory, making chemical and electrical changes in the synapse that now last for three weeks. Again, all this involves changes only to preexisting proteins and synaptic connections in neurons.

4. In rat and human hippocampus, the primary excitatory neurotransmitter is glutamate. This causes Ca++ influx through NMDA receptors at postsynaptic membranes, and activation of CamKII, PKC, and MAPK. Permanent synaptic changes (Early LTP) include increased insertion of AMPA receptors in the membrane, and phosphorylation of proteins to change the properties of the channel. These receptors are anchored to the neural cytoskeleton, so they have reliable long term effects. Later LTP involves recruitment of pre- and postsynaptic molecules to create new synaptic sites. A few key gene-regulatory networks are involved, with transcriptional and translational control at both the nucleus and the synapse, and control molecules including BDNF, mTOR, CREB, and CPEB. We’ve recently found a memory encoding master control gene, Npas4, that encodes nuclear transcription factors (the copying of other genes into messenger RNA) which interact with hippocampal neurons to encode episodic memory. When Npas4 is knocked out of mice, they can’t learn. We’ve found RNA binding proteins like Orb2, that bind to genes involved in long-term memory. A great and reasonably current text on the molecular basis of memory and learning is Mechanisms of Memory, David Sweatt, 2009. We’re still figuring out the epigenomic regulation that occurs in long-term learning and memory, so you’ll need to go to journals for most of that story, like this 2011 PloS Biology paper on epigenetic regulation of learning and memory in Drosophila. The full size of the memory puzzle is becoming clearer every day. Now we just need to fund the work to complete it. We sure could use this knowledge in all kinds of good ways today, if we had it. Here’s a cartoon of long-term memory formation in both Aplysia and rat hippocampus, from Learning and Memory, John Byrne (Ed.), 2008 (Vol 4., David Sweatt, p. 14):

5. Computational Neuroscience seeks to model brain function at multiple spatial-temporal scales. The brain uses a vast range of different schemes for representation and manipulation of information, and it passes some of this information from one system to another all the time. Consider the way neurons integrate signals from the receptors at their dendrites, the timing and shape of their action potentials, the way synapses interact with postsynaptic dendrites from other neurons, how neurons encode and store associative memory, specialize for perceiving and storing certain types of information (edge detection, grandmother cells), do inference and other calculations, work in functional subunits like cortical columns, and organize receptive fields. It all seems formidably complex, but useful simplifications exist, as we’ve described above.

6. Most folks in the neural emulation community don’t talk much about modeling gene regulatory networks or the epigenome and its interaction with the synaptome, and I think that’s their loss. Some focus only on easier stuff to see, like electrical features, and assume that might be enough to get a predictive model. But I think that’s like looking for your keys under the streetlights when they are in the shadows. If spikes, loops, and synchrony are a network layer that has grown on top of cell morphology and gene-protein networks, the way single-celled animals eventually grew neurons, we may learn surprisingly little by measuring and modeling electrical features. Attempting to do so may be like trying to infer the structure of hidden layers in a very large neural network [genome, epigenome, connectome, synaptome, and electrical features] by analyzing just the input/output layer, electrical features. We need all the hidden layers if we expect to have enough computational complexity to predictively characterize learning, memory, and behavior.