McGovern faculty predict the future of neuroscience

Cellular & Molecular Neuroscience


“I hope that our understanding of the brain — how it functions and how it goes awry in neurologic and neuropsychiatric diseases — will be at the stage that cancer biology is at today, with a fundamental understanding of the biology and with novel potent therapeutics based on that understanding.

It is the investment over the past decades in basic aspects of biology that has led to the revolutionary advancements in cancer treatments, and it is only with a similar investment in the study of basic aspects of nervous system biology — how the nervous system develops and works — that such advances will occur in the field of neuroscience.”

Genome Engineering


“We will see great expansion of gene therapy in clinics and we will have cures for many severe neurodevelopmental and neurological disorders that are caused by simple genetic mutations.

Single cell technologies will empower us to develop drugs that precisely treat psychiatric disorders with minimal side effects. I also envision non-invasive devices for modulating brain functions such as attention, sleep, and emotion.”

Computational Neuroscience


“In 20 years or less we will self-driving cars that are safer than human-driven cars on many specific roads and under some restrictions. But I do not expect that a self-driven car, even in 20 years, will be able to adapt, like a human driver can, to uncommon driving conditions (dirty roads, insufficent road signals, special situations such an accident, police presence etc) for which it was not programmed. In 20 years it will not yet have “common sense” nor a real understanding of what is going on. I expect the same to be true for AI systems, such as Alexa or Siri. They will be much better and much more useful than they are today but they will be still far from human intelligence, especially in terms of breadth, flexibility and real understanding. They will be superior however, in terms on raw knowledge and connectivity. The next 20 years are going to be a golden age of AI systems that are not really intelligent but will enable us to greatly expand our effective intelligence.

My personal bet is that real progress in AI, over the next 50-100 years, will come from the science of intelligence, that is from neuroscience and computational neuroscience. I would like to have a glimpse — both experimentally and theoretically —  at how circuits of neurons compute “abstract concepts” or more precisely how circuits of neurons create “programs” and “routines” that underly typically human abilities such as  language, reasoning and the development of mathematics and science.


“In the last 20 years, we’ve made great strides in modeling cognition and basic circuit interactions in the brain. In the next twenty years, we will connect the two: how circuit interactions give rise to sophisticated cognition — the brain/neural basis of cognition.”


Systems Neuroscience


“Techniques for exploring how the brain works, across all levels, will escalate greatly in power. Huge improvements will be made in treatments targeted to the central and peripheral nervous systems — akin to the near-abolishment of polio, or to the treatment of type I diabetes.

Organ systems will become recognized as interrelated parts of our biological makeup, so that information and treatment options can be shared. With parallel advances in other fields, such as engineering and physics, treatments will become less invasive or even fully non-invasive.”



“What my team and I aspire to is to develop tools that would break artificial sub-field barriers in neuroscience. In my mind there is no reason why molecular neuroscience cannot also be systems neuroscience or cognitive neuroscience. By leveraging materials chemistry and physics we envisage devices that would monitor and modulate specific receptors in identifiable neurons (and non-neuronal cells such as glia or endocrine cells) during behavior. These tools will operate at scales of individual proteins and will eliminate the need for hardware. It will likely be some form of synth-ware merging physical, chemical, and biological principles.

As a neuroscientist, I hope to understand how the neural circuit dynamics changes over the disease progression (for instance during addiction, over the course of Parkinson’s disease progression, or altered social development). I am particularly interested in how the peripheral organs and autonomic nervous system communicate with the brain and how that communication evolves as the disease emerges or progresses.”


“There are thousands of genes in the human genome, and thousands of cell types in the brain, that leads to an emergent complexity that is almost unimaginable.

In 20 years, I predict we will be able to watch these gene products and cells in real time as they compute and change in disease states, to map out how they are organized, down to single molecule precision, and to control their functions with molecular precision. This will yield understandings of complex diseases that will let us design ultra-targeted therapies, because we will know what has gone wrong.”


“Computing devices will integrate silicon and biological circuits to significantly expand the capability of computing.

Continued advances in our ability to decode neural circuitry and development of synthetic complex neural tissues such as organoids will yield powerful biological devices. For example, a biological device employing a synthetic smell circuitry will be able to detect years in advance that a person is developing Parkinson’s disease based on that person’s scent.”

Cognitive Neuroscience


“Brain imaging and cognitive neuroscience will offer new views of how variation in brain structure and function makes each of us unique, and this will fuel a revolution in personalized mental health treatments and educational practices that will empower flourishing in so many more of us.”