The real problem

aeon_coverWhat is the best way to understand consciousness? In philosophy, centuries-old debates continue to rage over whether the Universe is divided, following René Descartes, into ‘mind stuff’ and ‘matter stuff’. But the rise of modern neuroscience has seen a more pragmatic approach gain ground: an approach that is guided by philosophy but doesn’t rely on philosophical research to provide the answers. Its key is to recognise that explaining why consciousness exists at all is not necessary in order to make progress in revealing its material basis – to start building explanatory bridges from the subjective and phenomenal to the objective and measurable.

This is the start of an essay I recently wrote for the website, which publishes an essay a day, focusing on ideas and culture.  The basic idea is to chart a pragmatic path for the scientific study of consciousness, respecting but not directly targeting the deep metaphysical mysteries so eloquently exposed by Chalmers’ famous distinction between the ‘easy’ and ‘hard’ problems.  Much of what I say has been said before (e.g., in the tradition of neurophenomenology) but I hope to bring things together in a new way and with a distinctive empirical angle.  Anyway, best make up your own mind – I’d be keen to hear what you think!

At the edges of awareness

Imagine this. Following a brain injury you lie in a hospital bed and from the outside you appear to be totally unconscious. You don’t respond to anything the doctors or your family say, you make no voluntary movements, and although you still go to sleep and wake up there seems to be nobody at home. But your ‘inner universe’ of conscious awareness still remains, perhaps flickering and inconsistent, but definitely there. How could anyone else ever know, and how could you ever communicate with your loved ones again?

Two new radio dramas, The Sky is Wider and Real Worlds, engage with these critical questions by drawing on the cutting edge of the neurology and neuroscience. Recent advances have enabled researchers to not only diagnose ‘residual’ awareness following severe brain injuries, but also to open new channels of communication with behaviourally unresponsive patients. The key medical challenge is to distinguish between the so-called ‘vegetative state’ in which there truly is no conscious awareness, from ‘minimally conscious’ or ‘locked-in’ conditions where some degree of consciousness persists (even normal consciousness, in the locked-in state), even though there are no outward signs.


Brain activity during mental imagery, in a behaviourally unresponsive patient and in a  control subject.  Source: MRC via The Guardian

Linda Marshall Griffith’s drama The Sky is Wider takes inspiration from an ‘active approach’ in which the neurologist asks questions of the patient and monitors their brain activity for signs of response. In a classic study from about 10 years ago, Adrian Owen and his team asked behaviourally unresponsive patients to imagine either walking around their house or playing tennis, while their brains were scanned using functional MRI (which measures regional metabolic activity in the brain). These questions were chosen because imagining these different behaviours activates different parts of the brain, and so if we see these selective activations in a patient, we know that they have understood and are voluntarily following the instructions. If they can do this, they must be conscious. It turns out that between 10-20% of patients behaviourally diagnosed as being in the vegetative state can pass this test. Equally important, this same method can be used to establish simple communication by (for example) asking a patient to imagine playing ‘tennis’ to answer ‘yes’ and walking around a house to answer ‘no’.

These developments represent a revolution in clinical neurology. Current research is increasing the efficiency of active approaches by using the more portable electroencephalography (EEG) instead of bulky and expensive MRI. ‘Passive’ techniques in which residual consciousness can be inferred without requiring patients to perform any task are also rapidly improving. These methods are important because active approaches may underestimate the incidence of residual awareness since not all conscious patients may understand or be able to follow verbal instructions.

Alongside these scientific developments we encounter pressing ethical questions. How should we treat patients in these liminal states of awareness? And given a means of communication, what kinds of questions should we ask? The Sky is Wider explores these challenging ethical issues in a compelling narrative which gives dramatic voice to the mysterious conditions of the vegetative and minimally conscious states.


In Real Worlds, Jane Rogers takes us several years into the future. Communication with behaviourally unresponsive patients is now far advanced and is based on amazing developments in ‘virtual reality’. The clinical context for this drama is the ‘locked-in syndrome’ where a patient may have more-or-less normal conscious experiences but completely lack the ability to move. In Real Worlds, a locked-in patient transcends these limitations by controlling a virtual reality avatar directly using brain signals. These avatars inhabit virtual worlds in which the avatars of different people can interact, while the ‘real’ person behind each may remain hidden and unknown.

This drama deliberately inhabits the realm of science fiction, but there is solid science behind it too. The development of so-called ‘brain computer interfaces’ (BCI) is moving fast. These interfaces combine brain imaging methods (like EEG or fMRI, or sometimes more ‘invasive’ methods’ in which electrodes are inserted directly into the brain) with advanced machine learning methods to perform a kind of ‘brain-reading’. The idea is to infer, from brain activity alone, intended movements, perceptions, and perhaps even thoughts. These decoded ‘thoughts’ can then be used to control robotic devices, or virtual avatars. In some cases, a person’s own body might be controlled via direct stimulation of muscles. Progress in this area has been remarkably rapid. In a landmark but rather showy example, the Brazilian neuroscientist Miguel Nicolelis used a BCI to allow a paralysed person to ‘kick’ the first ball of the 2014 football world cup, through brain-control of a robotic avatar. More recently, brain-reading methods have allowed a paralysed man to play Guitar Hero for the first time since his injury.

The other technology highlighted in Real Worlds is virtual reality (VR), which – thanks to its enormous consumer potential – is developing even more rapidly. All the major technology and AI companies are getting in on the act, and VR headsets are finally becoming cheap enough, comfortable enough, and powerful enough to define a new technological landscape. Here at the Sackler Centre for Consciousness Science at the University of Sussex, we are exploring how VR can help shed light on our normal conscious experience. In one example, we use a method called ‘augmented reality’ (AR) to project a ‘virtual’ body into the real world as seen through a camera mounted on the front of a VR headset. This experiment revealed how our perception of what is (and what is not) our own body can be easily manipulated, indicating that our experience of ‘body ownership’, which is so easy to take for granted, is in fact continuously and actively generated by the brain. In a second example, we developed a method called ‘substitutional reality’ in which a VR headset is coupled with panoramic video and audio taken from a real environment, manipulated in various ways. The resulting experiences are much more immersive than current computer-generated virtual environments and in some cases people cannot distinguish them from actually ‘real’ environments.


A ‘virtual reality’ hand, part of a Sackler Centre study to explore the mechanisms underlying experiences of body ownership.  VR programming by Dr. Keisuke Suzuki.

Just as in the first drama, ethical questions risk outpacing the science and technology. As VR becomes increasingly immersive and pervasive, its potential to impact our real lives is ever more powerful. While benefits are easy to imagine – for instance in bringing distant relatives together or enabling remote experiences of inaccessible places – there are also legitimate concerns. High on the list would be what happens if people become increasingly unable to distinguish the real world from the virtual, whether in the moment or (more plausibly) in their memories. And what if they progressively withdrew from ‘reality’ if the available virtual worlds became more appealing places to be? Of course, simple dichotomies are unhelpful since VR technologies are part of our real worlds, just like mobile phones and laptop computers. Jane Rogers’ Real Worlds explores these complex ethical issues by imagining VR as a future treatment – perhaps ‘prosthesis’ would be a better word – for the disorders of consciousness like those encountered in The Sky is Wider.

Together, these dramas explore the human and societal consequences of existing and near-future clinical technologies. With artistic license they ask important questions that scientists and clinicians are not yet equipped to address. Ultimately, I think they convey an optimistic message, that we can understand and treat – if not cure – severely debilitating conditions that may otherwise have remained undiagnosed let alone treated. But they also lead us to consider, not just what we could do, but what we should do.

The Sky is Wider (written by Linda Marshall Griffiths) and Real Worlds (written by Jane Rogers) were produced by Nadia Molinari for BBC Radio 4. I acted as the scientific consultant. The original ideas were formulated during a 2014 Wellcome Trust ‘Experimental Stories’ workshop in a conversation between myself, Nadia, and Linda.

The science of selfhood

lorna-zoe-wanamaker-by-johan-persson2-1200x800.jpgZoë Wanamaker as Lorna in Nick Payne’s Elegy.

“The brain is wider than the sky,
For, put them side by side,
The one the other would contain,
With ease, and you besides”

Emily Dickinson, Complete Poems, 1924

What does it mean to be a self? And what happens to the social fabric of life, to our ethics and morality, when the nature of selfhood is called into question?

In neuroscience and psychology, the experience of ‘being a self’ has long been a central concern. One of the most important lessons, from decades of research, is that there is no single thing that is the self. Rather, the self is better thought of as an integrated network of processes that distinguish self from non-self at many different levels. There is the bodily self – the experience of identifying with and owning a particular body, which at a more fundamental level involves the amorphous experience of being a self-sustaining organism. There is the perspectival self, the experience of perceiving the world from a particular first-person point-of-view. The volitional self involves experiences of intention of agency, of urges to do this-or-that (or, perhaps more importantly, to refrain from doing this-or-that) and of being the cause of things that happen.

At higher levels we encounter narrative and social selves. The narrative self is where the ‘I’ comes in, as the experience of being a continuous and distinctive person over time. This narrative self – the story we tell ourselves about who we are – is built from a rich set of autobiographical memories that are associated with a particular subject. Finally, the social self is that aspect of my self-experience and personal identity that depends on my social milieu, on how others perceive and behave towards me, and on how I perceive myself through their eyes and minds.

In daily life, it can be hard to differentiate these dimensions of selfhood. We move through the world as seemingly unified wholes, our experience of bodily self seamlessly integrated with our memories from the past, and with our experiences of volition and agency. But introspection can be a poor guide. Many experiments and neuropsychological case studies tell a rather different story, one in which the brain actively and continuously generates and coordinates these diverse aspects of self-experience.

The many ways of being a self can come apart in surprising and revealing situations. For example, it is remarkably easy to alter the experience of bodily selfhood. In the so-called ‘rubber hand illusion,’ I ask you to focus your attention on a fake hand while your real hand is kept out of sight. If I then simultaneously stroke your real hand and the fake hand with a soft paintbrush, you may develop the uncanny feeling that the fake hand is now, somehow, part of your body. A more dramatic disturbance of the experience of body ownership happens in somatoparaphrenia, a condition in which people experience that part of their body is no longer theirs, that it belongs to someone else – perhaps their doctor or family member. Both these examples involve changes in brain activity, in particular within the ‘temporo-parietal junction’, showing how even very basic aspects of personal identity are actively constructed by the brain.

Moving through levels of selfhood, autoscopic hallucinations involve seeing oneself from a different perspective, much like ‘out of body’ experiences. In akinetic mutism, people seem to lack any experiences of volition or intention (and do very little), while in schizophrenia or anarchic hand syndrome, people can experience their intentions or voluntary actions as having external causes. At the other end of the spectrum, disturbances of social self emerge in autism, where difficulties in perceiving others’ states of mind seems to be a core problem, though the exact nature of the autistic condition is still much debated.

When it comes to the ‘I’, memory is the key. Specifically, autobiographical memory: the recollection of personal experiences of people, objects, and places and other episodes from an individual’s life. While there are as many types of memory as there are varieties of self (for example, we have separate memory processes for facts, for the short term and the long term, and for skills that we learn), autobiographical memories are those most closely associated with our sense of personal identity. This is well illustrated by some classic medical cases in which, as a result of surgery or disease, the ability to lay down new memories is lost. In 1953 Henry Moliason (also known as the patient HM) had large parts of his medial temporal lobes removed in order to relieve severe epilepsy. From 1957 until his death in 2008, HM was studied closely by the neuropsychologist Brenda Milner, yet he was never able to remember meeting her. In 1985 the accomplished musician Clive Wearing suffered a severe viral brain disease that affected similar parts of his brain. Now 77, he frequently believes he has just awoken from a coma, spending each day in a constant state of re-awakening.

Surprisingly, both HM and Wearing remained able to learn new skills, forming new ‘procedural’ memories, despite never recalling the learning process itself. Wearing could still play the piano, and conduct his choir, though he would immediately forget having done so. The music appears to carry him along from moment to moment, restoring his sense of self in a way his memory no longer can. And his love for his wife Deborah seems undiminished, so that he expresses an enormous sense of joy on seeing her, even though he cannot tell whether their last meeting was years, or seconds, in the past. Love, it seems, persists when much else is gone.

For people like HM and Clive Wearing, memory loss has been unintended and unwanted. But as scientific understanding develops, could we be moving towards a world where specific memories and elements of our identity can be isolated or removed through medical intervention? And could the ability to lay down new memories ever be surgically restored? Some recent breakthroughs suggest these developments may not be all that far-fetched.

In 2013, Jason Chan and Jessica LaPaglia, from Iowa State University showed that specific human memories could indeed be deleted. They took advantage of the fact that when memories are explicitly recalled they become more vulnerable. By changing details about a memory, while it was being remembered, they induced a selective amnesia which lasted for at least 24 hours. Although an important advance, this experiment was limited by relying on ‘non-invasive’ methods – which means not using drugs or directly interfering with the brain.

More recent animal experiments have shown even more striking effects. In a ground-breaking 2014 study at the University of California, using genetically engineered mice, Sadegh Nabavi and colleagues managed to block and then re-activate a specific memory. They used a powerful (invasive) technique called optogenetics to activate (or inactivate) the biochemical processes determining how neurons change their connectivity. And elsewhere in California, Ted Berger is working on the first prototypes of so-called ‘hippocampal prostheses’ which replace a part of the brain essential for memory with a computer chip. Although these advances are still a long way from implementation in humans, they show an extraordinary potential for future medical interventions.

The German philosopher Thomas Metzinger believes that “no such things as selves exist in the world”. Modern neuroscience may be on his side, with memory being only one thread in the rich tapestry of processes shaping our sense of selfhood. At the same time, the world outside the laboratory is still full of people who experience themselves – and each other – as distinct, integrated wholes. How the new science of selfhood will change this everyday lived experience, and society with it, is a story that is yet to be told.

Originally commissioned for the Donmar Warehouse production of Elegy, with support from The Wellcome Trust.  Reprinted in the programme notes and in Nick Payne’s published script.

Can we figure out the brain’s wiring diagram?


The human brain, it is often said, is the most complex object in the known universe. Counting all the connections among its roughly 90 billion neurons, at the rate of one each second, would take about 3 million years – and just counting these connections says nothing about their intricate patterns of connectivity. A new study, published this week in Proceedings of the National Academy of Sciences USA, shows that mapping out these patterns is likely to be much more difficult than previously thought — but also shows what we need to do, to succeed.

Characterizing the detailed point-to-point connectivity of the brain is increasingly recognized as a key objective for neuroscience. Many even think that without knowing the ‘connectome’ – the brain’s wiring diagram – we will never understand how its electrochemical alchemy gives rise to our thoughts, actions, perceptions, beliefs, and ultimately to our consciousness. There is a good precedent for thinking along these lines. Biology has been galvanized by sequencing of the genome (of humans and of other species), and genetic medicine is gathering pace as whole-genome sequencing becomes fast and cheap enough to be available to the many, not just the few. Big-science big-money projects like the Human Genome Project were critical to these developments. Similar efforts in brain science – like the Human Connectome Project in the US and the Human Brain Project in Europe – are now receiving vast amounts of funding (though not without criticism, especially in the European case) (see also here). The hope is that the genetic revolution can be replicated in neuroscience, delivering step changes in our understanding of the brain and in our ability to treat neurological and psychiatric disorders.

Mapping the networks of the human brain relies on non-invasive neuroimaging methods that can be applied without risk to living people. These methods almost exclusively depend on ‘diffusion magnetic resonance imaging (dMRI) tractography’. This technology measures, for each location (or ‘voxel’) in the brain, the direction in which water is best able to diffuse. Taking advantage of the fact that water diffuses more easily along the fibre bundles connecting different brain regions, than across them, dMRI tractography has been able to generate accurate, informative, and surprisingly beautiful pictures of the major superhighways in the brain.

Diffusion MRI of the human brain.  Source: Human Connectome Project.

Diffusion MRI of the human brain. Source: Human Connectome Project.

But identifying these neuronal superhighways is only a step towards the connectome. Think of a road atlas: knowing only about motorways may tell you how cities are connected, but its not going to tell you how to get from one particular house to another. The assumption in neuroscience has been that as brain scanning improves in resolution and as tracking algorithms gain sophistication, dMRI tractography will be able to reveal the point-to-point long-range anatomical connectivity needed to construct the full connectome.

In a study published this week we challenge this assumption, showing that basic features of brain anatomy pose severe obstacles to measuring cortical connectivity using dMRI. The study, a collaboration between the University of Sussex in the UK and the National Institutes of Health (NIH) in the US, applied dMRI tractography to ultra-high resolution dMRI data obtained from extensive scanning of the macaque monkey brain – data of much higher quality than can be presently obtained from human studies. Our analysis, led by Profs. Frank Ye and David Leopold of NIH and Ph.D student Colin Reveley of Sussex, took a large number of starting points (‘seed voxels’) in the brain, and investigated which other parts of the brain could be reached using dMRI tractography.

The result: roughly half of the brain could not be reached, meaning that even our best methods for mapping the connectome aren’t up to the job. What’s more, by looking carefully at the actual brain tissue where tractography failed, we were able to figure out why. Lying just beneath many of the deep valleys in the brain (the ‘sulci’ – but in some other places too), are dense weaves of neuronal fibres (‘white matter’) running largely parallel to the cortical surface. The existence of these ‘superficial white matter fibre systems’, as we call them, prevents the tractography algorithms from detecting where small tributaries leave the main neuronal superhighways, cross into the cortical grey matter, and reach their destinations. Back to the roads: imagine that small minor roads occasionally leave the main motorways, which are flanked by other major roads busy with heavy traffic. If we tried to construct a detailed road atlas by measuring the flow of vehicles, we might well miss these small but critical branching points.

This image shows, on a colour scale, the 'reachability' of different parts of the brain by diffusion tractography.

This image shows, on a colour scale, the ‘reachability’ of different parts of the brain by diffusion tractography.

Identifying the connectome remains a central objective for neuroscience, and non-invasive brain imaging – especially dMRI – is a powerful technology that is improving all the time. But a comprehensive and accurate map of brain connectivity is going to require more than simply ramping up scanning resolution and computational oomph, a message that mega-budget neuroscience might usefully heed. This is not bad news for brain research. Solving a problem always requires fully understanding what the problem is, and our findings open new opportunities and objectives for studies of brain connectivity. Still, it goes to show that the most complex object in the universe is not quite ready to give up all its secrets.

Colin Reveley, Anil K. Seth, Carlo Pierpaoli, Afonso C. Silva, David Yu, Richard C. Saunders, David A. Leopold*, and Frank Q. Ye. (2015) Superficial white-matter fiber systems impede detection of long-range cortical connections in diffusion MR tractography. Proc. Nat. Acad. Sci USA (2015). doi/10.1073/pnas.1418198112

*David A. Leopold is the corresponding author.

Open your MIND

is a brand new collection of original research publications on the mind, brain, and consciousness
. It is now freely available online. The collection contains altogether 118 articles from 90 senior and junior researchers, in the always-revealing format of target articles, commentaries, and responses.

This innovative project is the brainchild of Thomas Metzinger and Jennifer Windt, of the MIND group of the Johanes Gutenburg University in Mainz, Germany (Windt has since moved to Monash University in Melbourne). The MIND group was set up by Metzinger in 2003 to catalyse the development of young German philosophers by engaging them with the latest developments in philosophy of mind, cognitive science, and neuroscience. Open MIND celebrates the 10th anniversary of the MIND group, in a way that is so much more valuable to the academic community than ‘just another meeting’ with its quick-burn excitement and massive carbon footprint. Editors Metzinger and Windt explain:

“With this collection, we wanted to make a substantial and innovative contribution that will have a major and sustained impact on the international debate on the mind and the brain. But we also wanted to create an electronic resource that could also be used by less privileged students and researchers in countries such as India, China, or Brazil for years to come … The title ‘Open MIND’ stands for our continuous search for a renewed form of academic philosophy that is concerned with intellectual rigor, takes the results of empirical research seriously, and at the same time remains sensitive to ethical and social issues.”

As a senior member of the MIND group, I was lucky enough to contribute a target article, which was commented on by Wanja Wiese, one of the many talented graduate students with Metzinger and a junior MIND group member. My paper marries concepts in cybernetics and predictive control with the increasingly powerful perspective of ‘predictive processing’ or the Bayesian brain, with a focus on interoception and embodiment. I’ll summarize the main points in a different post, but you can go straight to the target paper, Wanja’s commentary, and my response.

Open MIND is a unique resource in many ways. The Editors were determined to maximize its impact, so, unlike in many otherwise similar projects, the original target papers have not been circulated prior to launch. This means there is a great deal of highly original material now available to be discovered. The entire project was compressed into about 10 months from submission of initial drafts, to publication this week of the complete collection. This means the original content is completely up-to-date. Also, Open MIND  shows how excellent scientific publication can  sidestep the main publishing houses, given the highly developed resources now available, coupled of course with extreme dedication and hard work. The collection was assembled, rigorously reviewed, edited, and produced entirely in-house – a remarkable achievement.

Thomas Metzinger with the Open MIND student team

Thomas Metzinger with the Open MIND student team

Above all Open MIND opened a world of opportunity for its junior members, the graduate students and postdocs who were involved in every stage of the project: soliciting and reviewing papers, editing, preparing commentaries, and organizing the final collection. As Metzinger and Windt say

“The whole publication project is itself an attempt to develop a new format for promoting junior researchers, for developing their academic skills, and for creating a new type of interaction between senior and junior group members.”

The results of Open MIND are truly impressive and will undoubtedly make a lasting contribution to the philosophy of mind, especially in its most powerful multidisciplinary and empirically grounded forms.

Take a look, and open your mind too.

Open MIND contributors: Adrian John Tetteh Alsmith, Michael L. Anderson, Margherita Arcangeli, Andreas Bartels, Tim Bayne, David H. Baßler, Christian Beyer, Ned Block, Hannes Boelsen, Amanda Brovold, Anne-Sophie Brüggen, Paul M. Churchland, Andy Clark, Carl F. Craver, Holk Cruse, Valentina Cuccio, Brian Day, Daniel C. Dennett, Jérôme Dokic, Martin Dresler, Andrea R. Dreßing, Chris Eliasmith, Maximilian H. Engel, Kathinka Evers, Regina Fabry, Sascha Fink, Vittorio Gallese, Philip Gerrans, Ramiro Glauer, Verena Gottschling, Rick Grush, Aaron Gutknecht, Dominic Harkness, Oliver J. Haug, John-Dylan Haynes, Heiko Hecht, Daniela Hill, John Allan Hobson, Jakob Hohwy, Pierre Jacob, J. Scott Jordan, Marius Jung, Anne-Kathrin Koch, Axel Kohler, Miriam Kyselo, Lana Kuhle, Victor A. Lamme, Bigna Le Nggenhager, Caleb Liang, Ying-Tung Lin, Christophe Lopez, Michael Madary, Denis C. Martin, Mark May, Lucia Melloni, Richard Menary, Aleksandra Mroczko-Wąsowicz, Saskia K. Nagel, Albert Newen, Valdas Noreika, Alva Noë, Gerard O’Brien, Elisabeth Pacherie, Anita Pacholik-Żuromska, Christian Pfeiffer, Iuliia Pliushch, Ulrike Pompe-Alama, Jesse J. Prinz, Joëlle Proust, Lisa Quadt, Antti Revonsuo, Adina L. Roskies, Malte Schilling, Stephan Schleim, Tobias Schlicht, Jonathan Schooler, Caspar M. Schwiedrzik, Anil Seth, Wolf Singer, Evan Thompson, Jarno Tuominen, Katja Valli, Ursula Voss, Wanja Wiese, Yann F. Wilhelm, Kenneth Williford, Jennifer M. Windt.

Open MIND press release.
The cybernetic Bayesian brain: from interoceptive inference to sensorimotor contingencies
Perceptual presence in the Kuhnian-Popperian Bayesian brain
Inference to the best prediction

Should we fear the technological singularity?


Could wanting the latest mobile phone for Christmas lead to human extermination? Existential risks to our species have long been part of our collective psyche – in the form of asteroid impacts, pandemics, global nuclear cataclysm, and more recently, climate change. The idea is not simply that humans and other animals could be wiped out, but that basic human values and structures of society would change so as to become unrecognisable.

Last week, Stephen Hawking claimed that technological progress, while perhaps intended for human betterment, might lead to a new kind of existential threat in the form of self-improving artificial intelligence (AI). This worry is based on the “law of accelerating returns”, which applies when the rate at which technology improves is proportional to how good the technology is, yielding exponential – and unpredictable – advances in its capabilities. The idea is that a point might be reached where this process leads to wholesale and irreversible changes in how we live. This is the technological singularity, a concept made popular by AI maverick and Google engineering director Ray Kurzweil.

We are already familiar with accelerating returns in the rapid development of computer power (“Moore’s law”), and Kurzweil’s vision of the singularity is actually a sort of utopian techno-rapture. But there are scarier scenarios where exponential technological growth might exceed our ability to foresee and prevent unintended consequences. Genetically modified food is an early example of this worry, but now the spotlight is on bio- and nano-technology, and – above all – AI, the engineering of artificial minds.

Moore's law: the exponential growth in computational power since 1900.

Moore’s law: the exponential growth in computational power since 1900.

A focus on AI might seem weird given how disappointing present-day ‘intelligent robots’ are. They can hardly vacuum your living room let alone take over the world, and reports that the famous Turing Test for AI has been passed are greatly exaggerated. Yet AI has developed a surprising behind-the-scenes momentum. New ‘deep learning’ algorithms have been developed which, when coupled with vast amounts of data, show remarkable abilities to tackle everyday problems like speech comprehension and face recognition. As well as world-beating chess players like Deep Blue, we have Apple Siri and Google Now helping us navigate our messy and un-chesslike environments in ways that mimic our natural cognitive abilities. Huge amounts of money have followed, with Google this year paying £400M for AI start-up DeepMind in a deal which Google CEO Eric Schmidt heralded as enabling products that are “infinitely more intelligent”.

"Hello Dave".

“Hello Dave”.

What if the ability to engineer artificial minds leads to these minds engineering themselves, developing their own goals, and bootstrapping themselves beyond human understanding and control? This dystopian prospect has been mined by many sci-fi movies – think Blade Runner, HAL in 2001, Terminator, Matrix – but while sci-fi is primarily for entertainment, the accelerating developments in AI give pause for thought. Enter Hawking, who now warns that “the full development of AI could spell the end of the human race”. He joins real-world-Iron-Man Elon Musk and Oxford philosopher Nick Bostrom in declaring AI the most serious existential threat we face. (Hawking in fact used the term ‘singularity’ long ago to describe situations where the laws of physics break down, like at the centre of a black hole).

However implausible a worldwide AI revolution might seem, Holmes will tell you there is all the difference in the world between the impossible and the merely improbable. Even if highly unlikely, the seismic impact of a technological singularity is such that it deserves to be taken seriously, both in estimating and mitigating its likelihood, and in planning potential responses. Cambridge University’s new Centre for the Study for Existential Risk has been established to do just this, with Hawking and ex-Astronomer Royal Sir Martin Rees among the founders.

Dystopian eventualities aside, the singularity concept is inherently interesting because it pushes us to examine what we mean by being human (as my colleague Murray Shanahan argues in a forthcoming book). While intelligence is part of the story, being human is also about having a body and an internal physiology; we are self-sustaining flesh bags. It is also about consciousness; we are each at the centre of a subjective universe of experience. Current AI has little to say about these issues, and it is far from clear whether truly autonomous and self-driven AI is possible in their absence. The ethical minefield deepens when we realize that AIs becoming conscious would entail ethical responsibilities towards them, regardless of their impact on us.

At the moment, AI like any powerful technology has the potential for good and ill, long before any singularity is reached. On the dark side, AI gives us the tools to wreak our own havoc by distancing ourselves from the consequences of our actions. Remote controlled military drones already reduce life-and-death decisions to the click of a button: with enhanced AI there would be no need for the button. On the side of the angels, AI can make our lives healthier and happier, and our world more balanced and sustainable, by complementing our natural mental prowess with the unprecedented power of computation. The pendulum may swing from the singularity-mongerers to the techno-mavens; and we should listen to both, but proceed serenely with the angels.

This post is an amended version of a commisioned comment for The Guardian: Why we must not stall technological progress, despite its threat to humanity, published on December 03, 2014.  It was part of a flurry of comments occasioned by a BBC interview with Stephen Hawking, which you can listen to here. I’m actually quite excited to see Eddie Redmayne’s rendition of the great physicist.

Training synaesthesia: How to see things differently in half-an-hour a day

Image courtesy of Phil Wheeler Illustrations

Can you learn to see the world differently? Some people already do. People with synaesthesia experience the world very differently indeed, in a way that seems linked to creativity, and which can shed light on some of the deepest mysteries of consciousness. In a paper published in Scientific Reports, we describe new evidence suggesting that non-synaesthetes can be trained to experience the world much like natural synaesthetes. Our results have important implications for understanding individual differences in conscious experiences, and they extend what we know about the flexibility (‘plasticity’) of perception.

Synaesthesia means that an experience of one kind (like seeing a letter) consistently and automatically evokes an experience of another kind (like seeing a colour), when the normal kind of sensory stimulation for the additional experience (the colour) isn’t there. This example describes grapheme-colour synaesthesia, but this is just one among many fascinating varieties. Other synaesthetes experience numbers as having particular spatial relationships (spatial form synaesthesia, probably the most common of all). And there are other more unusual varieties like mirror-touch synaesthesia, where people experience touch on their own bodies when they see someone else being touched, and taste-shape synaesthesia, where triangles might taste sharp, and ellipses bitter.

The richly associative nature of synaesthesia, and the biographies of famous case studies like Vladimir Nabokov and Wassily Kandinsky (or, as the Daily Wail preferred: Lady Gaga and Pharrell Williams), has fuelled its association with creativity and intelligence. Yet the condition is remarkably common, with recent estimates suggesting about 1 in 23 people have some form of synaesthesia. But how does it come about? Is it in your genes, or is it something you can learn?

It is widely believed that Kandinsky was synaesthetic. For instance he said: “Colour is the keyboard, the eyes are the harmonies, the soul is the piano with many strings. The artist is the hand that plays, touching one key or another, to cause vibrations in the soul”

As with most biological traits the truth is: a bit of both. But this still begs the question of whether being synaesthetic is something that can be learnt, even as an adult.

There is a rather long history of attempts to train people to be synaesthetic. Perhaps the earliest example was by E.L. Kelly who in 1934 published a paper with the title: An experimental attempt to produce artificial chromaesthesia by the technique of the conditioned response. While this attempt failed (the paper says it is “a report of purely negative experimental findings”) things have now moved on.

More recent attempts, for instance the excellent work of Olympia Colizoli and colleagues in Amsterdam, have tried to mimic (grapheme-colour) synaesthesia by having people read books in which some of the letters are always coloured in with particular colours. They found that it was possible to train people to display some of the characteristics of synaesthesia, like being slower to name coloured letters when they were presented in a colour conflicting with the training (the ‘synaesthetic Stroop’ effect). But crucially, until now no study has found that training could lead to people actually reporting synaesthesia-like conscious experiences.

An extract from the ‘coloured reading’ training material, used in our study, and similar to the material used by Colizoli and colleagues. The text is from James Joyce. Later in training we replaced some of the letters with (appropriately) coloured blocks to make the task even harder.

Our approach was based on brute force. We decided to dramatically increase the length and rigour of the training procedure that our (initially non-synaesthetic) volunteers undertook. Each of them (14 in all) came in to the lab for half-an-hour each day, five days a week, for nine weeks! On each visit they completed a selection of training exercises designed to cement specific associations between letters and colours. Crucially, we adapted the difficulty of the tasks to each volunteer and each training session, and we also gave them financial rewards for good performance. Over the nine-week regime, some of the easier tasks were dropped entirely, and other more difficult tasks were introduced. Our volunteers also had homework to do, like reading the coloured books. Our idea was that the training must always be challenging, in order to have a chance of working.

The results were striking. At the end of the nine-week exercise, our dedicated volunteers were tested for behavioural signs of synaesthesia, and – crucially – were also asked about their experiences, both inside and outside the lab. Behaviourally they all showed strong similarities with natural-born synaesthetes. This was most striking in measures of ‘consistency’, a test which requires repeated selection of the colour associated with a particular letter, from a palette of millions.

The consistency test for synaesthesia. This example from David Eagleman’s popular ‘synaesthesia battery’.

Natural-born synaesthetes show very high consistency: the colours they pick (for a given letter) are very close to each other in colour space, across repeated selections. This is important because consistency is very hard to fake. The idea is that synaesthetes can simply match a colour to their experienced ‘concurrent’, whereas non-synaesthetes have to rely on less reliable visual memory, or other strategies.

Our trained quasi-synaesthetes passed the consistency test with flying colours (so to speak). They also performed much like natural synaesthetes on a whole range of other behavioural tests, including synaesthetic stroop, and a ‘synaesthetic conditioning’ task which shows that trained colours can elicit automatic physiological responses, like increases in skin conductance. Most importantly, most (8/14) of our volunteers described colour experiences much like those of natural synaesthetes (only 2 reported no colour phenomenology at all). Strikingly, some of these experience took place even outside the lab:

“When I was walking into campus I glanced at the University of Sussex sign and the letters were coloured” [according to their trained associations]

Like natural synaesthetes, some of our volunteers seemed to experience the concurrent colour ‘out in the world’ while others experienced the colours more ‘in the head’:

“When I am looking at a letter I see them in the trained colours”

“When I look at the letter ‘p’ … its like the inside of my head is pink”

For grapheme colour synaesthetes, letters evoke specific colour experiences. Most of our trained quasi-synaesthetes reported similar experiences. This image is however quite misleading. Synaesthetes (natural born or not) also see the letters in their actual colour, and they typically know that the synaesthetic colour is not ‘real’. But that’s another story.

These results are very exciting, suggesting for the first time that with sufficient training, people can actually learn to see the world differently. Of course, since they are based on subjective reports about conscious experiences, they are also the hardest to independently verify. There is always the slight worry that our volunteers said what they thought we wanted to hear. Against this worry, we were careful to ensure that none of our volunteers knew the study was about synaesthesia (and on debrief, none of them did!). Also, similar ‘demand characteristic’ concerns could have affected other synaesthesia training studies, yet none of these led to descriptions of synaesthesia-like experiences.

Our results weren’t just about synaesthesia. A fascinating side effect was that our volunteers registered a dramatic increase in IQ, gaining an average of about 12 IQ points (compared to a control group which didn’t undergo training). We don’t yet know whether this increase was due to the specifically synaesthetic aspects of our regime, or just intensive cognitive training in general. Either way, our findings provide support for the idea that carefully designed cognitive training could enhance normal cognition, or even help remedy cognitive deficits or decline. More research is needed on these important questions.

What happened in the brain as a result of our training? The short answer is: we don’t know, yet. While in this study we didn’t look at the brain, other studies have found changes in the brain after similar kinds of training. This makes sense: changes in behaviour or in perception should be accompanied by neural changes of some kind. At the same time, natural-born synaesthetes appear to have differences both in the structure of their brains, and in their activity patterns. We are now eager to see what kind of neural signatures underlie the outcome of our training paradigm. The hope is, that because our study showed actual changes in perceptual experience, analysis of these signatures will shed new light on the brain basis of consciousness itself.

So, yes, you can learn to see the world differently. To me, the most important aspect of this work is that it emphasizes that each of us inhabits our own distinctive conscious world. It may be tempting to think that while different people – maybe other cultures – have different beliefs and ways of thinking, still we all see the same external reality. But synaesthesia, along with other emerging theories of ‘predictive processing’ – shows that the differences go much deeper. We each inhabit our own personalised universe, albeit one which is partly defined and shaped by other people. So next time you think someone is off in their own little world: they are.

The work described here was led by Daniel Bor and Nicolas Rothen, and is just one part of an energetic inquiry into synaesthesia taking place at Sussex University and the Sackler Centre for Consciousness Science. With Jamie Ward and (recently) Julia Simner also working here, we have a uniquely concentrated expertise in this fascinating area. In other related work I have been interested in why synaesthetic experiences lack a sense of reality and how this give an important clue about the nature of ‘perceptual presence’. I’ve also been working on the phenomenology of spatial form synaesthesia, and whether synaesthetic experiences can be induced through hypnosis. And an exciting brain imaging study of natural synaesthetes will shortly hit the press! Nicolas Rothen is an authority on the relationship between synaesthesia and memory, and Jamie Ward and Julia Simner have way too many accomplishments in this field to mention. (OK, Jamie has written the most influential review paper in the area – featuring a lot of his own work – and Julia (with Ed Hubbard) has written the leading textbook. That’s not bad to start with.)

Our paper, Adults can be Trained to Acquire Synesthetic Experiences (sorry for US spelling) is published (open access, free!) in Scientific Reports, part of the Nature family. The authors were Daniel Bor, Nicolas Rothen, David Schwartzman, Stephanie Clayton, and Anil K. Seth. There has been quite a lot of media coverage of this work, for instance in the New Scientist and the Daily Fail. Other coverage is summarized here.

Eye Benders: the science of seeing and believing, wins Royal Society prize!


An unexpected post.  I’m very happy to have learnt today that the book Eye Benders has won the 2014 Royal Society Young Person’s Book Prize.  Eye Benders was written by Clive Gifford (main author) and me (consultant).  It was published by Ivy Press, who are also the redoubtable publishers of the so-far-prizeless but nonetheless worthy 30 Second Brain. A follow-up to Eye Benders, Brain Twister, is in the works: More brain, less optical illusions, but same high quality young-person-neuroscience-fare.

The Royal Society says this about the prize: “Each year the Royal Society awards a prize to the best book that communicates science to young people. The prize aims to inspire young people to read about science and promotes the best science writing for the under-14s.”

This year, the shortlist was chosen by Professor James Hough FRS, Dr Rhaana Starling, Mr Michael Heyes, Professor Iain Stewart and Dr Anjana Ahuja. Well done all, good shortlisting.  More importantly, the winner was chosen by groups of young persons themselves.  Here is what some of the 2014 young people had to say about Eye Benders:

Matt, 12 said “Science from a different perspective. Factual and interesting – a spiral of a read!”

Beth, 14 said “It was way, way cool!

Ethan, 12 said “The illustrations were absolutely amazing”

Joe, 12 said “A great, well written and well thought-out book; the illustrations are clear, detailed and amazing. The front cover is beautiful.”

Felix, 10 said “Eye popping and mind-blowingly fun!’

So there it is. Matt and friends have spoken, and here is a picture of Clive accepting the award in Newcastle (alas I wasn’t there) accompanied with a young person being enthused:


Here’s a sneak at what the book looks like, on the inside:


A personal note: I remember well going through the final layouts for Eye Benders, heavily dosed on painkillers in hospital in Barcelona following emergency surgery, while at the same time my father was entering his final weeks back in Oxfordshire. A dark time.  Its lovely, if bittersweet, to see something like this emerge from it.

Other coverage:

GrrlScientist in The Guardian.
Optical illusion book wins Royal Society prize
Clive shares some of the best Eye Benders illusions online
Royal Society official announcement
University of Sussex press release

I just dropped in (to see what condition my condition was in): How ‘blind insight’ changes our view of metacognition


Image from 30 Second Brain, Ivy Press, available at all good booksellers.

Neuroscientists long appreciated that people can make accurate decisions without knowing they are doing so. This is particularly impressive in blindsight: a phenomenon where people with damage to the visual parts of their brain can still make accurate visual discriminations while claiming to not see anything. But even in normal life it is quite possible to make good decisions without having reliable insight into whether you are right or wrong.

In a paper published this week in Psychological Science, our research group – led by Ryan Scott – has for the first time shown the opposite phenomenon: blind insight. This is the situation in which people know whether or not they’ve made accurate decisions, even though they can’t make decisions accurately!

This is important because it changes how we think about metacognition. Metacognition, strictly speaking, is ‘knowing about knowing’. When we make a perceptual judgment, or a decision of any kind, we typically have some degree of insight into whether our decision was correct or not. This is metacognition, which in experiments is usually measured by asking people how confident they are in a previous decision. Good metacognitive performance is indicated by high correlations between confidence and accuracy, which can be quantified in various ways.

Most explanations of metacognition assume that metacognitive judgements are based on the same information as the original (‘first-order’) decision. For example, if you are asked to decide whether a dim light was present or not, you might make a (first-order) judgment based on signals flowing from your eyes to your brain. Perhaps your brain sets a threshold below which you will say ‘No’ and above which you will say ‘Yes’. Metacognitive judgments are typically assumed to work on the same data. If you are asked whether you were guessing or were confident, maybe you will set additional thresholds a bit further apart. The idea is that your brain may need more sensory evidence to be confident in judging that a dim light was in fact present, than when merely guessing that it was.

This way of looking at things is formalized by signal detection theory (SDT). The nice thing about SDT is that it can give quantitative mathematical expressions for how well a person can make both first-order and metacognitive judgements, in ways which are not affected by individual biases to say ‘yes’ or ‘no’, or ‘guess’ versus ‘confident’. (The situation is a bit trickier for metacognitive confidence judgements but we can set these details aside for now: see here for the gory details). A simple schematic of SDT is shown below.


Signal detection theory. The ‘signal’ refers to sensory evidence and the curves show hypothetical probability distributions for stimulus present (solid line) and stimulus absent (dashed line). If a stimulus (e.g., a dim light) is present, then the sensory signal is likely to be stronger (higher) – but because sensory systems are assumed to be noisy (probabilistic), some signal is likely even when there is no stimulus. The difficulty of the decision is shown by the overlap of the distributions. The best strategy for the brain is to place a single ‘decision criterion’ midway between the peaks of the two distributions, and to say ‘present’ for any signal above this threshold, and ‘absent’ for any signal below. This determines the ‘first order decision’. Metacognitive judgements are then specified by additional ‘confidence thresholds’ which bracket the decision criterion. If the signal lies in between the two confidence thresholds, the metacognitive response is ‘guess’; if it lies to the two extremes, the metacognitive response is ‘confident’. The mathematics of SDT allow researchers to calculate ‘bias free’ measures of how well people can make both first-order and metacognitive decisions (these are called ‘d-primes’). As well as providing a method for quantifying decision making performance, the framework is also frequently assumed to say something about what the brain is actually doing when it is making these decisions. It is this last assumption that our present work challenges.

On SDT it is easy to see that one can make above-chance first order decisions while displaying low or no metacognition. One way to do this would be to set your metacognitive thresholds very far apart, so that you are always guessing. But there is no way, on this theory (without making various weird assumptions), that you could be at chance in your first-order decisions, yet above chance in your metacognitive judgements about these decisions.

Surprisingly, until now, no-one had actually checked to see whether this could happen in practice. This is exactly what we did, and this is exactly what we found. We analysed a large amount of data from a paradigm called artificial grammar learning, which is a workhorse in psychological laboratories for studying unconscious learning and decision-making. In artificial grammar learning people are shown strings of letters and have to decide whether each string belongs to ‘grammar A’ or ‘grammar B’. Each grammar is just an arbitrary set of rules determining allowable patterns of letters. Over time, most people can learn to classify letter strings at better than chance. However, over a large sample, there will always be some people that can’t: for these unfortunates, their first-order performance remains at ~50% (in SDT terms they have a d-prime not different from zero).


Artificial grammar learning. Two rule sets (shown on the left) determine which letter strings belong to ‘grammar A’ or ‘grammar B’. Participants are first shown examples of strings generated by one or the other grammar (training). Importantly, they are not told about the grammatical rules, and in most cases they remain unaware of them. Nonetheless, after some training they are able to successfully (i.e., above chance) classify novel letter strings appropriately (testing).

Crucially, subjects in our experiments were asked to make confidence judgments along with their first-order grammaticality judgments. Focusing on those subjects who remained at chance in their first-order judgements, we found that they still showed above-chance metacognition. That is, they were more likely to be confident when they were (by chance) right, than when they were (by chance) wrong. We call this novel finding blind insight.

The discovery of blind insight changes the way we think about decision-making. Our results show that theoretical frameworks based on SDT are, at the very least, incomplete. Metacognitive performance during blind insight cannot be explained by simply setting different thresholds on a single underlying signal. Additional information, or substantially different transformations of the first-order signal, are needed. Exactly what is going on remains an open question. Several possible mechanisms could account for our results. One exciting possibility appeals to predictive processing, which is the increasingly influential idea that perception depends on top-down predictions about the causes of sensory signals. If top-down influences are also involved in metacognition, they could carry the additional information needed for blind insight. This would mean that metacognition, like perception, is best understood as a process of probabilistic inference.


In predictive processing theories of brain function, perception depends on top-down predictions (blue) about the causes of sensory signals. Sensory signals carry ‘prediction errors’ (magenta) which update top-down predictions according to principles of Bayesian inference. Maybe a similar process underlies metacognition. Image from 30 Second Brain, Ivy Press.

This brings us to consciousness (of course). Metacognitive judgments are often used as a proxy for consciousness, on the logic that confident decisions are assumed to be based on conscious experiences of the signal (e.g., the dim light was consciously seen), whereas guesses signify that the signal was processed only unconsciously. If metacognition involves top-down inference, this raises the intriguing possibility that metacognitive judgments actually give rise to conscious experiences, rather than just provide a means for reporting them. While speculative, this idea fits neatly with the framework of predictive processing which says that top-down influences are critical in shaping the nature of perceptual contents.

The discovery of blindsight many years ago has substantially changed the way we think about vision. Our new finding of blind insight may similarly change the way we think about metacognition, and about consciousness too.

The paper is published open access (i.e. free!) in Psychological Science. The authors were Ryan Scott, Zoltan Dienes, Adam Barrett, Daniel Bor, and Anil K Seth. There are also accompanying press releases and coverage:

Sussex study reveals how ‘blind insight’ confounds logic.  (University of Sussex, 13/11/2014)
People show ‘blind insight’ into decision making performance (Association for Psychological Science, 13/11/2014)

The Human Brain Project risks becoming a missed opportunity

Image concept of a network of neurons in the human brain.

The brain is much on our minds at the moment. David Cameron is advocating a step-change in dementia research, brain-computer interfaces promise new solutions to paralysis, and the ongoing plight of Michael Schumacher has reminded us of the terrifying consequences of traumatic brain injury. Articles in scholarly journals and in the media are decorated with magical images of the living brain, like the one shown below, to illuminate these stories. Yet, when asked, most neuroscientists will say we still know very little about how the brain works, or how to fix it when it goes wrong.

A diffusion tensor image showing some of the main pathways along which brain connections are organized.

The €1.2bn Human Brain Project (HBP) is supposed to change all this. Funded by the European Research Council, the HBP brings together more than 80 research institutes in a ten-year endeavour to unravel the mysteries of the brain, and to emulate its powers in new technologies. Following examples like the Human Genome Project and the Large Hadron Collider (where Higgs’ elusive boson was finally found), the idea is that a very large investment will deliver very significant results. But now a large contingent of prominent European neuroscientists are rebelling against the HBP, claiming that its approach is doomed to fail and will undermine European neuroscience for decades to come.

Stepping back from the fuss, it’s worth thinking whether the aims of the HBP really make sense. Sequencing the genome and looking for Higgs were both major challenges, but in these cases the scientific community agreed on the objectives, and on what would constitute success. There is no similar consensus among neuroscientists.

It is often said that the adult human brain is the most complex object in the universe. It contains about 90 billion neurons and a thousand times more connections, so that if you counted one connection each second it would take about three million years to finish. The challenge for neuroscience is to understand how this vast, complex, and always changing network gives rise to our sensations, perceptions, thoughts, actions, beliefs, desires, our sense of self and of others, our emotions and moods, and all else that guides our behaviour and populates our mental life, in health and in disease. No single breakthrough could ever mark success across such a wide range of important problems.

The central pillar of the HBP approach is to build computational simulations of the brain. Befitting the huge investment, these simulations would be of unprecedented size and detail, and would allow brain scientists to integrate their individual findings into a collective resource. What distinguishes the HBP – besides the money – is its aggressively ‘bottom up’ approach: the vision is that by taking care of the neurons, the big things – thoughts, perceptions, beliefs, and the like – will take care of themselves. As such, the HBP does not set out to test any specific hypothesis or collection of hypotheses, marking another distinction with common scientific practice.

Could this work? Certainly, modern neuroscience is generating an accelerating data deluge demanding new technologies for visualisation and analysis. This is the ‘big data’ challenge now common in many settings. It is also clear that better pictures of the brain’s wiring diagram (the ‘connectome’) will be essential as we move ahead. On the other hand, more detailed simulations don’t inevitably lead to better understanding. Strikingly, we don’t fully understand the brain of the tiny worm Caenorhabtis elegans even though it has only 302 neurons and the wiring diagram is known exactly. More generally, a key ability in science is to abstract away from the specifics to see more clearly what underlying principles are at work. In the limit, a perfectly accurate model of the brain may become as difficult to understand as the brain itself, as Borges long ago noted when describing the tragic uselessness of the perfectly detailed map.

Jorge Luis Borges at Harvard University, 1967/8

Neuroscience is, and should remain, a broad church. Understanding the brain does not reduce to simulating the collective behaviour of all its miniscule parts, however interesting a part of the final story this might become. Understanding the brain means grasping complex interactions cross-linking many different levels of description, from neurons to brain regions to individuals to societies. It means complementing bottom-up simulations with new theories describing what the brain is actually doing, when its neurons are buzzing merrily away. It means designing elegant experiments that reveal how the mind constructs its reality, without always worrying about the neuronal hardware underneath. Sometimes, it means aiming directly for new treatments for devastating neurological and psychiatric conditions like coma, paralysis, dementia, and depression.

Put this way, neuroscience has enormous potential to benefit society, well deserving of high profile and large-scale support. It would be a great shame if the Human Brain Project, through its singular emphasis on massive computer simulation, ends up as a lightning rod for dissatisfaction with ‘big science’ rather than fostering a new and powerfully productive picture of the biological basis of the mind.

This article first appeared online in The Guardian on July 8 2014.  It appeared in print in the July 9 edition, on page 30 (comment section).

Post publication notes:

The HBP leadership have published a response to the open letter here. I didn’t find it very convincing. There have been a plethora of other commentaries on the HBP, as it comes up to its first review.  I can’t provide an exhaustive list but I particularly liked Gary Marcus’ piece in the New York Times (July 11). There was also trenchant criticism in the editorial pages of Nature.  Paul Verschure has a nice TED talk addressing some of the challenges facing big data, encompassing the HBP.