On 12 October, the Panel for the Future of Science and Technology (STOA), in collaboration with the International Brain Initiative (IBI) and the Kavli Foundation, organised a workshop at the European Parliament entitled “The International Brain Initiative – Shaping the future of globally coordinated neuroscience”.
Keynote speaker was Prof Edvard Moser, founding director of the Kavli Institute for Systems Neuroscience and Co-Director of the Centre for Neural Computation.
In 2014 he won, together with his then-wife and long-term collaborator May-Britt Moser, the Nobel prize in Physiology or Medicine for their work discovering ‘grid cells’: a type of nerve cell, that allows for precise positioning and navigation, a kind of ‘inner GPS’. We asked him for an update on neuroscience and his opinion of the International Brain Initiative.
Despite the recent developments in neuroscience, the (human) brain remains a big unknown. In your opinion, how much do we know about the brain?
Although a lot of information is still missing, neuroscience has developed enormously in the last decades. During the last century, the focus rested mostly on individual cells, but brains are a collection of neurons working together – it is the understanding of this ensemble that will allow us to get a glimpse into higher brain functions like cognition, imagination, memory, planning, decision making…
Such research into neuronal networks was previously technically not possible. But now you can perform simultaneous recordings in many thousands of cells, which allows a mechanistic understanding which was not possible before. In short, even though we could say that neuroscience is still in its infancy, it is evolving at an accelerated speed, and new knowledge is soon to follow this development.
Which is the most exciting unknown about the human brain?
I am particularly interested in cognitive functions, in how we think. Perhaps the least-understood high-level function is consciousness, that human-specific characteristic that leads to self-awareness of your own actions, thoughts…, even of ourselves. However, given its complexity, I think that will probably be one of the last questions to solve.
Neuroscience is characterised by its complexity. How could new technologies (e.g., artificial intelligence and big data) help us better understand how the brain works?
First, although not necessarily a new technology, newly developed statistical methods to reduce data complexity and focus on the dominant dimensions explaining the variance are helping to extract meaningful information from data. Secondly, artificial intelligence and machine learning can better interpret ‘hidden’ or not so obvious patterns in the data.
From your point of view, which has been the most revolutionary technique in neuroscience in the last ten years?
I could not pick only one. On the one hand, technical developments like neuropixel probes – chips with thousands of recording sites, have allowed recording the activity of hundreds to thousands cells simultaneously. Similarly, imaging techniques like two-photon microscopy in combination with fluorescent indicators allow investigating cell activity during normal animal behaviour.
In addition, methods to manipulate the activity of specific neurons, for instance with optogenetics, have allowed us to explore the roles of certain types of neurons. And, naturally, the development of the statistical and analytical tools necessary to make sense of the huge amount of data generated with the above techniques.
Which will be the hottest topics in neuroscience in the next five to ten years?
In general, I think that progress into the neural basis of high brain functions, from memory to abstract thinking or even language, which are the most difficult to investigate, is to be expected. This progress will depend on previous advances in cell population recordings and behavioural data, for instance. However, another important point is that a theoretical basis to explain the results achieved with these technical developments is still missing. Therefore, theoretical neuroscience is a field with developmental potential.
The brain has been compared to a computer. How accurate is this comparison?
Despite the superficial similarities between the brain and a computer, there are several differences, including the much slower processing speed of the brain and its high energy efficiency. But one of the biggest differences from traditional computers is that the brain can interactively process information across hundreds of processing channels. That being said, parallel computing can simultaneously process several lines of information similarly to the brain. For all the above, I think that the brain-computer analogy is a limited one, although the analogy is still useful in describing many properties of brain function.
Why are international collaborative efforts like the International Brain Initiative (IBI), or the European Human Brain Project needed for neuroscience research?
International collaboration is important at two levels. First, low-scale international collaboration (lab to lab) is necessary because neuroscience is an interdisciplinary field. Mathematicians, biologists and computer scientists need to join efforts.
Second, large-scale initiatives like the IBI or the European Human Brain Project have been vital to enable big technological developments. For instance, in particular the BRAIN initiative worked on developing new techniques for neuroscience research that would serve as a basis for expanding our knowledge on the brain.
An important limiting factor for scientific collaboration is data format. How to facilitate data sharing and reutilisation?
There needs to be data consistency. Neuroscientists have been dealing this issue for a while, but every experiment requires a particular data format, which limits standardisation. However, there is already an awareness about the need for sharing accessible data and, therefore, a need for collecting, curating, and maintaining data. A function now implemented by the European EBRAINS initiative, for instance.
The human connectome project aims to map the brain. What do you think will be its outcome?
The connectome is like an atlas. It helps knowing the location of certain neurons/connections in the brain, but it cannot provide information on how it works. However, once available, this information will be a starting point for future functional analysis.
Are there any ethical challenges associated with neuroimplants or brain-computer interfaces?
Brain-computer interfaces use a computer to record or interpret brain signals which are used for prosthetics [for example for paralysed people to be able to e.g., turn the lights on by thinking about it], or artificial vision [technology – usually visual implants – that allows blind people to see by relaying images to the brain through either cameras or photoreceptor arrays].
For prosthetics there would be no major ethical issues, since the computer simply performs a specific task the patient cannot do in a normal way due to injury or disease. However, if the process would be the opposite, to transfer information into the brain, for instance, creating/removing memories, or by erasing them out of the brain, then there would be obvious ethical issues. However, this is a very remote possibility today since, for instance, memories are widely distributed in the brain, and we do not have access to the particular neurons involved in a specific memory, so technically it is hardly possible at this point. Yet neuroscience and ethics need to meet to avoid possible future situations we do not want to get into.
What do you think of neuroethics in general?
Ethics needs to be involved from the start and evolve together with neuroscience research. However, most ethical issues will probably arise in the future, since the research is not yet so advanced that access to private data, like thoughts, could be possible. However, we need to be aware of these issues and prepared for what’s to come.
• Workshop of the Panel for the Future of Science and Technology (STOA) : European Parliament: “The International Brain Initiative: Shaping the future of globally coordinated neuroscience”
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