The Future of Neuroscience

In the current animal model of depression, a mouse is placed in a jar of water and struggles to swim to avoid drowning, in the aptly named “forced-swim” test(1). After a few minutes, the mouse stops trying to escape, instead choosing to float immobile in the water. At this point, the mouse is said to experience “behavioural despair” (the mouse loses hope to escape the stressful environment) and the mouse is then classified as suffering from “depression”. This is the standard model used to test antidepressant drugs – the time spent immobile versus swimming in mice given the drug is compared to that of controls. Clearly, this is a simplistic model with very little resemblance to the highly complex, multi-faceted disorder of clinical depression in humans. Yet, although its efficacy has long been contested(2), this is still the most common mouse model used in the majority of research into “depression”. 

This is not just the case for depression. Many psychiatric disorders are still studied using simplistic animal models which – though important – essentially bear little resemblance to the experiences of those suffering from the disease on a daily basis. 

On top of this there, is a pervasive disconnect between psychology and neuroscience. It is fundamentally impossible to study affective or cognitive phenomena such as emotion or foresight using animal models, since mice, rats and monkeys are all unable to communicate what they are feeling with humans. Instead, researchers study behaviours as a proxy – for instance, what a mouse does before it gets a reward, which is largely a matter of interpretation. But we lack a way to study actual emotions in mice – which, besides, are likely vastly different subjective experiences to those of humans. While mouse models have their uses, they are generally an insufficient representation of brain disease or even normal brain function in humans. 

It is without surprise then, that over the past 40 years there has been little improvements in the outcomes of patients with the most common brain diseases. Some pharmaceutical companies are abandoning research into drugs for psychiatric diseases altogether due to the high cost and low success rate. For example for Alzheimer’s, every time we think we have a promising new drug in development to break down the toxic amyloid plaques, we find that it fails in clinical trials, and moreover, we find that we were coming at the problem from the wrong angle altogether(3). We now know that we need to intervene long before amyloid deposits are prevalent, and long before symptoms are seen. Some research shows a portion of patients diagnosed with Alzheimer’s do not even have significantly more amyloid-β plaques in their brains than healthy controls, and amyloid pathology has been observed in cognitively healthy elderly individuals, suggesting that amyloid-driven tauopathy may at best only be part of the problem. Thus, we currently lack even an effective diagnostic criteria for neurodegenerative disorders. Treatment for Alzheimer’s is largely symptomatic; we are a long way off from understanding the root causes of the disease. Progress is slow, but we are learning. 

There is also the problem of brain scanning. The most prevalent form of brain imaging in neuroscience and psychology is undoubtedly functional magnetic resonance imaging (fMRI). However, again, this is a proxy – fMRI measures blood flow across the brain while the subject is engaged in a particular task or activity; it does not directly measure neuronal activity(4). One unpublished study from 2009 found apparent cognitive activity in the brain of a dead salmon(5), highlighting the risk of false positives in fMRI studies. Similarly, electroencephalography (EEG) measures electrical activity at the brain surface – however it lacks specificity in that it does not measure the activity of specific neurons or sets of neurons, but rather of a crude combination of electrical currents across a particular brain area. Unfortunately, it is not yet possible to measure the activity of a specific set of neurons in living, human brain tissue. 

However, a small minority of forward-thinking neuroengineers are currently working on measuring real-time electrical brain activity in vivo, in humans. This is already possible in the brains of mice and in monkeys, but not yet in humans. Thus, hopefully in the not-too-distant future, we will be able to record activity from specific sub-sets of neurons and correlate this with not only behaviour, but with thought, emotion and, of course, depression. 

With a little imagination, let’s fast forward 100, or perhaps only 50 years. We now understand the root causes of Alzheimer’s, Parkinson’s, depression, schizophrenia etc., and are able to deliver targeted genetic or drug therapies, custom-made for each patient, to treat brain disease both symptomatically, and more importantly, prophylactically. Furthermore, we now understand that these disorders which we considered one disease, were in fact different diseases with similar symptoms but vastly different biological causes, each requiring a different treatment. We will look back to the primitive days of neuroscience – the early 21st century – and be amazed that the majority of brain diseases were being treated with the wrong drugs, which were more often than not completely ineffective, or even counter-productive(6,7).

In order to achieve this, we first had to figure out how to get electrodes through the skull and into the brains of healthy, living humans, without causing any risk to the subject. Rather than drilling holes through the skull, we use microelectrodes so small that they can be inserted without rupturing any blood vessels, thus avoiding the risk of stroke. We might even use lasers. As technology progresses, we will be able to record from thousands of electrodes at once using smart, robotic, microscopic implantations which work their way around blood vessels and through the brain tissue. Eventually, this will be possible using wearable devices which the subject can implant into their brain and go about their day, while the device is constantly collecting and uploading high-resolution neuronal activity directly from their brain to the computer of a researcher, or their doctor, for analysis. Combined with powerful yet harmless lasers able to pass through the skull and produce images of neurons and synapses with sub-cellular precision, we are able to decipher not only the connectome, but the precise patterns of activity between specific neurons during a particular function, on an individual level, for each patient. By collecting masses of data from millions of patients, we can mathematically calculate – with the aid of superfast computers – what exactly is going wrong in neurological diseases such as Alzheimer’s. Furthermore, we have finally managed to bridge the gap between psychology and neuroscience, by being able to ask the patients about their emotional, subjective experiences, and correlate this with their neuronal activity at that exact point in time. 

At some point, these wearable devices will become commercialised by the likes of Google, Amazon and Apple, offering free services to customers in exchange for their private data – their thoughts. Having learned from our mistakes in the early 21st century regarding privacy and data harvesting, customers will demand rights and legislation to decide how their personal brain activity is used by multinational corporations. However, this will prove ineffective, and customers will willingly sacrifice their privacy anyway, by updating to the latest version of Apple iBrain® without reading the terms and conditions. This will open up a whole Pandora’s box of neuro-hacking and neuro-spyware, as well as further driving inequality and elitism – since only those in first-world countries can access the devices, and only the wealthiest of those can afford the latest and greatest bio-upgrades. The societal, political and economic ramifications of this could fill an entire book in and of itself. But from a neuroscientific perspective, this will be a turning-point; a revolution in neuroscience research, allowing for not only the enhancement of normal brain function – or biohacking – but also significant advances in the treatment of brain diseases. Alzheimer’s, schizophrenia, autism, ADHD, addiction, depression and anxiety disorders will all be things of the past. 

So too will smartphones. Generation Y will tell their kids, “I remember when we had to type our text messages with our thumbs, or ask Alexa to add vegan meat to the shopping list. We never had Google Think® in my day”, or “I remember when we had to go to college to study for years, we had to sit down and read books to learn things. We never had Amazon HiveMind® in my day”. Meanwhile their kids seamlessly communicate via Apple iThought®, video chat via Skype Hologram®, and instantaneously download entire textbooks and literature via an ultra-fast 100Gb/s subscription to Amazon’s entire library for only $19.99 per month. Fake news will become a thing of the past, as every news article you download is instantly verified against thousands of peer-reviewed sources – reviewed both by humans and by sophisticated AI technology. You will never forget anything ever again, as any memory you choose to remember will be uploaded to the cloud, ready to be accessed and relived at will. Alternatively, should you choose, you can delete a traumatic or stressful memory, like it never happened. Without delving too far into the realm of science fiction, the possibilities are Limitless®. Anything is possible, so long as we can dream it – or Google DeepDream® it. 

Our knowledge of neuroscience is only in its infancy. Our understanding the human brain in all its complexity is only a mere few steps away from exponential growth. As technology combines with neuroscience, we become ever closer to understanding ourselves, and to an entirely interconnected consciousness. Societies working together as a collective intelligence are capable of amazing things – just look at bees and ants. Times are changing, for better or for worse.

Now, back to those mice...

References: 

1. Can, Adem, Dao, David T., Arad, Michal, Terrillion, Chantelle E., et al. (2012) ‘The Mouse Forced Swim Test’. Journal of Visualized Experiments : JoVE, (59). [online] Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3353513/

2. Borsini, Franco, Volterra, Giovanna and Meli, Alberto (1986) ‘Does the behavioral “despair” test measure “despair”?’ Physiology & Behavior, 38(3), pp. 385–386.

3. Castello, Michael A., Jeppson, John David and Soriano, Salvador (2014) ‘Moving beyond anti-amyloid therapy for the prevention and treatment of Alzheimer’s disease’. BMC Neurology, 14, p. 169.

4. Ekstrom, Arne (2010) ‘How and when the fMRI BOLD signal relates to underlying neural activity: The danger in dissociation’. Brain Research Reviews, 62(2), pp. 233–244.

5. Scicurious (2012) ‘IgNobel Prize in Neuroscience: The dead salmon study’. Scientific American Blog Network. [online] Available from: http://blogs.scientificamerican.com/scicurious-brain/ignobel-prize-in-neuroscience-the-dead-salmon-study/ (Accessed 27 April 2016)

6. Anon (2016) ‘Most antidepressant drugs ineffective for children and teens, study finds’. University of Oxford. [online] Available from: http://www.ox.ac.uk/news/2016-06-08-most-antidepressant-drugs-ineffective-children-and-teens-study-finds (Accessed 6 July 2018)
7. Cipriani, Andrea, Zhou, Xinyu, Giovane, Cinzia Del, Hetrick, Sarah E., et al. (2016) ‘Comparative efficacy and tolerability of antidepressants for major depressive disorder in children and adolescents: a network meta-analysis’. The Lancet, 388(10047), pp. 881–890.