IN A statement released by the American Psychiatric Association on May 3, 2013, David Kupfer, the Chair of a task force set up to discuss the future of mental health research, said: “The promise of the science of mental disorders is great. In the future, we hope to be able to identify disorders using biological and genetic markers that provide precise diagnoses that can be delivered with complete reliability and validity. Yet, this promise, which we have anticipated since the 1970s, remains disappointingly distant. We’ve been telling patients for several decades that we are waiting for biomarkers. We’re still waiting. In the absence of such major discoveries, it is clinical experience and evidence, as well as growing empirical research, that have advanced our understanding of disorders such as autism spectrum disorder, bipolar disorder and schizophrenia.”
What this statement does not mention is the spectacular advances that have been made in the field of neuroscience, particularly the ability to unravel the role of the connectivity between brain cells (the neurons) and the intricate circuitry that carries signals from one neuron to the other in the highly complex neural network, which today seems to hold the promise of leading to a better understanding of the causal links to mental disorders and thus pave the way towards positive therapeutic interventions in not too distant a future.
What has made this possible is the development of the technology called “optogenetics” pioneered by Karl Deisseroth, a professor of psychiatry and behavioural sciences and a professor of bioengineering at Stanford University. This revolutionary technology was voted the “Method of the Year” in 2010 by the journal Nature . With optogenetics and advances in imaging technology, it is now possible to observe thousands of neurons as they get activated and respond to external stimuli in an intact brain and in real time. Deisseroth exemplifies that small but growing community of researchers in mental health that bridges the divide, typified perhaps by Kupfer’s statement itself, between psychiatrists and geneticists on the one hand and neuroscientists on the other.
It is pertinent to quote Deisseroth from a Scientific American article titled “Controlling Brain with Light” that he wrote in 2010:
“Despite the enormous efforts of clinicians and researchers, our limited insight into psychiatric disease (the worldwide-leading cause of years of life lost to death or disability) hinders the search for cures and contributes to stigmatisation. Clearly, we need new answers in psychiatry. But… before we can find the answers, we need the power to ask new questions. In other words, we need new technology.
“Developing appropriate techniques is difficult, however, because the mammalian brain is beyond compare in its complexity. It is an intricate system in which tens of billions of intertwined neurons—with multitudinous distinct characteristics and wiring patterns—compute with precisely timed, millisecond-scale electrical signals, as well as with a rich diversity of biochemical messengers. Because of that complexity, neuroscientists lack a deep grasp of what the brain is really doing—of how specific activity patterns within specific brain cells ultimately give rise to thoughts, feelings and memories. By extension, we also do not know how the brain’s physical failures produce distinct psychiatric disorders such as depression or schizophrenia. The ruling paradigm of psychiatric disorders—casting them in terms of chemical imbalances and altered levels of neurotransmitters —does not do justice to the brain’s high-speed electrical neural circuitry. And psychiatric treatments have historically been largely serendipitous: helpful for many but rarely illuminating, and suffering from the same challenges as basic neuroscience.”
Deisseroth has provided that breakthrough technology to overcome the limitations that neuroscience faced 10 years ago and has enabled neuroscientists to “ask new questions”. In a telephonic interview, Frontline spoke to the well-known neuroscientist Sumantra Chattarji, a professor at the National Centre for Biological Sciences (NCBS), Bengaluru, about the current status of neuroscience and the understanding of the causes of mental disorders that it has enabled in recent times. Chattarji is one of the few in the tribe of neuroscientists in the country who have also attempted to bridge that divide by collaborating with Sanjeev Jain (see separate interview), a clinical psychiatrist at the National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru. However, he sees no sign—even in the biggest hospitals in the country where they appreciate the importance of research—of any structural changes being envisaged to enable that wide gap to be bridged so that the country can progress towards better mental health care.
Chattarji’s own research has shown that prolonged stress leaves its mark by enhancing both the physiological and structural basis of synaptic connectivity between cells in the amygdala (a region of the brain located below the hippocampus, another area of the brain; see Figures 1 and 2), thereby triggering the emotional symptoms observed in stress-related psychiatric disorders. His laboratory also studies synaptic defects and their reversal in fragile X syndrome ( Frontline , July 16, 2010), the leading identified cause of autism. In his more recent work, Chattarji’s laboratory has studied ( Frontline , January 9, 2015) the neuronal basis and the biochemical pathway in the amygdala that is involved in the hyperactive fear syndrome called post-traumatic stress disorder (PTSD).
Chattarji received his postgraduate degree in physics from the Indian Institute of Technology Kanpur. He then did a PhD in neuroscience under Terry Sejnowski at the Johns Hopkins University and the Salk Institute. After postdoctoral research at Yale University and the Massachusetts Institute of Technology, he started his own laboratory at the NCBS in 1999. Excerpts from the interview:
How far has neuroscience progressed towards enabling an understanding of the causal connections between the functioning of the different parts of the brain and various mental disorders?
Nature had organised a closed-door meeting in Hannover a few months ago where I had an interesting conversation. A group of scientists, including psychiatrists, geneticists and neuroscientists, had been invited from all over the world to understand what was wrong with contemporary psychiatric research and why it was not progressing. It did not consist of the usual talks and lectures but was held to identify a kind of road map for the future. What I gleaned from that is that a large chunk of early research had focussed on genetics: identifying genetic causes, finding one gene after another. Now you have about a hundred genes; depending upon how you measure, there would be many more, by studying families, and so on. What that has done—which I found quite astounding—is that this gene space of the geneticists bypassed the circuit or the brain area question altogether. These people were of the view that [neural] circuits, synapses, and things like that were not very important. They think that you got a gene, you got a target—a molecular target—and you can drug it. And you treat the rest as a black box. And you go straight to pre-clinical models, look at the behaviour pattern and do some basic in vitro stuff and go to pharmacology and biochemistry, do molecular design and focus largely on that receptor [target]. That is what you have now, which has given rise to [drugs such as] Prozac and the whole industry. These are all 30 years old, and nothing much has moved after that. Except for changing the chemicals a little bit here and there to reduce side effects, etc., there has been no big breakthrough. That genetics-pharmacology-based pre-clinical model [approach], which does not look at your brain areas, circuits and connections and a mechanistic understanding of that, bypassing all that and treating that as a black box, and searching for the cure—that is where we are now.
In the same period of time, in the last 30 years, neuroscience, however, has moved rapidly. Now, we have a fantastic understanding of basic brain functions at the cellular, synaptic and circuit levels—learning and memory, emotion, vision, motor coordination and things like that. And models have got increasingly more specific. And yet, these two fields don’t talk to each other. And that is the pretty stark reality. As someone at the meeting asked, “You have a hundred genes now [for mental disorders]; soon you will have 400 genes, then what? What will you tell me, who is trying to get a mechanistic understanding, to change my experiment? And tell me something that I did not know before.” And the answer was zero. So there is nothing to build bridges.
Now, if you forget that aspect, there have been rapid advances on the circuit side in the last 10 years. We have just completed 10 years of “optogenetics”. You can now actually establish causal links. That is, if you activate (or silence) a certain group of neurons within a particular circuit, you can modulate a specific affectation or disease behaviour—like you can make a mouse act like an addicted mouse, although it is not exposed to cocaine or any other intoxicant. You can induce an addiction, you can create a memory, you can erase a memory or create a false memory. You can do all this stuff now. For the first time, that vital gap is being bridged where, instead of having correlations—which is to knock out a particular gene and see the behavioural change, or cleave the gene in this area and see the behavioural change, or lesion this area and see the behavioural change—you can now keep the brain intact and activate specific subsets of circuits and modulate the behaviour in a predictable fashion, saying that these are the causative cells. Now, that information needs to go back [to psychiatric-geneticists]. The problem is that the researchers who are doing this circuit analysis are largely quantitative neuroscientists—people coming from engineering, physics, and so on who are equipped to deal with the computational aspect, develop new techniques for the technical challenges. The psychiatric-genetics community and the pharmacology community are far from it. There is a cultural divide which is hurting the field, I think.
The rapid movement and progress in our understanding from the neuroscience side needs to get translated. This community to which I belong is not very culturally interested in diseases. They do look towards diseases to get their grants but the fundamental aim is to know how the brain works, which is purely a physicist or computational researcher approach. And the psychiatrists, who are truly interested in the diseases, many of whom are M.Ds or M.D.-PhDs, who are seeing cases in the hospital, are not speaking this language or using this language. That’s the problem. As for psychiatry, if you ask me, for anxiety disorders, depression and things like that, and neurological disorders like epilepsy, you are better off—the clinical understanding and the science has evolved better—than for schizophrenia or bipolar disorder where we are truly, truly stuck. Even Alzheimer’s, for all the money that has gone in, nothing much has happened. And, again, that is because of the singular molecular-genetic focus where you look at the molecule, look at the receptor and ignore the context and the circuit in which they are implanted.
As we have shown and others have shown, if you ignore the circuit and just look at the cells, the molecule and the synapses, depending on the circuit, the same molecule does different things. Then you have a big challenge, right? Then the drug now needs to do different things in different circuits. How can a single drug do different things? That is just one example. What I call “cultural divide” is that these groups of people are far apart—their sciences don’t meet, they don’t talk to each other, they don’t go to the same meetings. They are almost suspicious of each other’s work in some ways. That’s one. The progress, the momentum is entirely happening in the circuit, the cellular-synaptic circuit domain. That community is not motivated by the disease.
But how far have efforts like your own interactions with clinicians like Sanjeev Jain at NIMHANS and elsewhere helped bridge this divide?
That divide I think is a lot less in the West, basically because the M.D.-PhDs working in the hospital also do research in their own labs. That does not exist in India. And there is no sign that this is going to change anytime soon. That is my definitive view. In the West, that gap has been bridged enormously. I will give you an example. Karl Deisseroth, the man who revolutionised neuroscience with optogenetics, is an M.D.; he is an associate professor in psychiatry. He is a trained psychiatrist and he is pushing the technology, right? In the United States, that integration [of the two approaches] has happened. Can you imagine a psychiatrist pushing that technology in India? It would be impossible. I am working with people in Edinburgh who have integrated [disciplines] too. They are practising doctors, seeing patients, running clinics and running a lab as well. I don’t know how they do it, but they do it. Here, Sanjeev Jain is the only person who is keen on it, but he knows that he can’t do it. The conditions are such that he can only do so much. The only way is to think and change the next generation.
In terms of arriving at a causal understanding of mental disorders, which part of the brain structure are scientists still grappling with? Is it at the basic cellular level or at the neurotransmitter level or elsewhere?
The basic cellular, molecular and genetic understanding of signal pathways, what is going on at the cellular and the synaptic level, has progressed a lot. Similarly, neurotransmitter-level data are also very good. But what is missing is the intervening level—the circuit and the network. So, you have the cellular molecular data and you have the behavioural data. The in-between layers were hard to grapple with—the large-scale circuit level, involving thousands of cells and their connections. That has now changed completely because of high-resolution, high-speed imaging techniques, where you can image thousands of neurons at a time in vivo in the intact brain and you can causally manipulate them with optogenetics and you can link that with the behaviour. That is the revolution in the last 10 years and that technology is being pushed by engineers and physicists. I think on that front the field has moved very rapidly and I am very optimistic with the progress that has been made.
But we need even better imaging techniques and that has to come from physics because, with the current techniques, you can look at thousands of cells in vitro or in frontal cells of the cortex [of the brain] in vivo , but you cannot go deep. The resolution of MRI is only sub-millimetre. So, MRI is not going to give you anything more. So, the whole world of imaging technology has to be revolutionised to go to the next level. You need high spatio-temporal resolution; you need new physical devices to enable you to look at thousands of neurons at a time in a known behaviour. That is now becoming possible. I think that’s where the action lies. And I hope some subset of people [in this country] like Sanjeev Jain and myself will have access to these techniques so that we can translate some of these findings into disease models.
As of now, disease models are essentially stuck wherever they were 30 years ago. Nothing has changed in models of depression, for example. You keep repeating the same thing with the same models, and publish a paper and nobody questions that. You keep propagating the same stuff. We need to break away from that and take a look at devising new models. But most people don’t want to do that.
How far do you think that an improved understanding of the functioning of the network would push a model-based understanding of diseases?
That should happen. That’s again a cultural divide. How many of these [circuit] people would take an interest in doing that? If you ask me right now, that number is relatively small. The way to go will be when they realise that the only way to get funding from the National Institutes of Health [in the U.S.] and other agencies is when they do that kind of work; then they will do it. That kind of pressure should become the motivating factor.
Now all the models that one has today are probably largely based on cognitive and behavioural kind of observations and data, right?
Absolutely. For some disorders, you look at the cortex, hippocampus and amygdala and for some other the subcortical brain regions as well….
So what you are saying is that we know pretty well the brain region that is involved in a particular disorder, but we need to look into the interior of each of those areas in terms of the underlying detailed circuitry of the neural network….
The anatomical details of the circuitry are also known. Now the functional circuitry—how the circuits function when activated, which cells talk to which cells, what is the sequence of activation, what sequence of firing gives rise one kind of aberration or the other. We need that kind of cell-level and circuit-level understanding, the dynamics of it in a living circuit, in a living animal. That’s what is missing right now.
But how much of this can be done in real time?
It is all being done in real time. Optogenetics lets you do that and some of the imaging techniques let you do that. Optogenetics is manipulation and imaging is just recording the read-out. What people are doing now is merging the two—manipulate and get the read-out in the same file frame with high resolution. Right now, it is restricted to superficial parts of the brain, which is a problem. You look at the cortex mostly. It is the deeper sites where lots of diseases happen. Someone like me, who loves the technology, can’t use it [because of its current limitation]. I have to wait till they improve it. But a lot of work is being done in the cortex region itself.
But how far do you think this can actually lead to better therapeutic intervention? Any progress on that front?
I think if we understand the circuit, we can then merge that data with molecular data. At present, the technology is where we can manipulate cells based on those molecular signatures. We can activate a specific type of cell that is specific to this molecule. That is the power of optogenetics. Then you begin to understand that it is really this [particular] circuit and these [specific] cells and then you can start manipulating disease models. If you change these cells now, do the therapeutic intervention, will the circuit act differently? All this kind of stuff is well within reach now.
The other big thing that will happen is with regard to ethical issues. How sure are we that rat and mouse models are valid for human diseases? Do rats and mice have depression, for example? Can you tell if a mouse is happy? I can’t. There is a big debate on this issue. So, primate models can help bridge that gap. But we find that in primates, in monkeys, it is difficult to do these interventions because of ethical issues. But for autism, primate models have been used—mostly in macaque monkeys—in Japan already. China is also building primate models for some diseases. So there are things that are coming from Asia now. In the West, there are severe restrictions.