Join Amit Kumar, a rising researcher in neurochemistry, as he interviews Associate Professor Jess Nithianantharajah, Head of Florey Department of Neuroscience and Mental Health, University of Melbourne. Together, they explore groundbreaking insights into the complexities of schizophrenia, the challenges in understanding its diverse symptoms, and recent breakthroughs in neurochemical research. From the role of dopamine to the impact of AI on mental health treatments, this conversation dives deep into the innovations that shape the future of neurochemistry.
Amit: Could you share the insights that shaped your research hypothesis on the complexities of schizophrenia and the challenges in addressing its diverse symptoms?
Jess: In a complex condition like schizophrenia, from a diagnostic point of view, there are three major symptom categories. First, there are the positive symptoms, like hallucinations and delusions. Then, there are the negative symptoms. These include challenges with motivation and anhedonia — difficulty in experiencing rewards and pleasure. Finally, we have cognitive symptoms, which affect how we think, process information, make decisions, learn, and remember. Despite the positive symptoms being the most well-known, cognitive and negative symptoms remain the most important predictor of someone’s recovery.
All these symptoms manifest differently in each person, which makes the condition challenging to treat. Not every person with schizophrenia presents in the same way. Instead, individuals may show different clusters of symptoms. One of our research goals is to develop preclinical models that tackle these varied symptom clusters we see in people. In the past, we thought we needed to just create one model to explain schizophrenia, but that’s not the reality.
This brings us to the brain’s inner workings. During the session we discussed the dominant dopamine hypothesis, which posits that schizophrenia is the result of elevated dopamine levels. Current medications that alleviate the positive symptoms do target increased dopamine, so there’s truth to this. However, we now understand that brain systems don’t work in isolation. It’s not just one region or neurochemical or receptor that’s affected; when one part shifts, others shift too.
One of my key interests is exploring these shifts. We know there are dopamine changes, but we think this may be driven by other factors — like an imbalance between glutamate and GABA, therefore affecting the balance of excitatory-inhibitory communication in the brain. Our understanding of these system-level interactions has really advanced, giving us a deeper view of the complex neurochemistry behind mental health conditions.
Amit: How do your findings connect the reward system and adaptive behavior in schizophrenia, especially considering challenges like disrupted motivation and cognitive symptoms?
Jess: Really good question. The negative and cognitive symptoms involve interconnected brain processes. So, if I think about it, to adapt our behaviour effectively, you need systems in the brain that can be rapidly regulated so it can tune up or down to respond to new information, but then return to baseline. That dynamic range in brain processes is critical to enable control of emotional and cognitive responses and therefore, adaptive behaviors. Our recent work is showing that dynamic interactions between different neurochemical systems, namely GABAergic and dopaminergic circuits in the prefrontal cortex, is critical for supporting adaptive behaviour.
When processes in the brain are either constantly heightened or dampened, you lose the ability to process information in the same way. For example, working memory is often disrupted in schizophrenia. This suggests the processes that support the way information is encoded and held temporarily in the brain aren’t working as effectively as it could, and this impacts adaptability.
If you can’t retain information, you can’t use it to inform and update your behavior. Therefore, people with schizophrenia can be more impulsive, repetitive or inflexible in their behavior, making choices that others might consider irrational.
Amit: What insights does your research offer about the unique role of dopamine activity in areas like the prefrontal cortex compared to regions like the nucleus accumbens and VTA in schizophrenia?
Jess: This has been one of the most striking things about our findings, and it’s also what I love about research. As researchers, we start with hypotheses about what we think is happening, but it’s only through discovery and evidence that we refine our understanding.
We know there are dopamine changes in the striatum in schizophrenia, and that the dopamine circuitry consists of cell bodies located in one part of the brain, the VTA, that project their terminals to release dopamine in other areas like the nucleus accumbens and prefrontal cortex. Our work shows that disrupting inhibitory GABAergic connections in the brain can lead to region-specific changes in dopamine activity, specifically in the prefrontal cortex, and impairs adaptive decision-making. This is exciting because the prefrontal cortex is a special region that regulates higher order cognitive functions and is particularly altered in schizophrenia, so this work is telling us more about how prefrontal dysfunction might contribute to cognitive symptoms.
Amit: What about how cannabis exposure, particularly during key developmental stages, might influence the risk of developing schizophrenia-like symptoms?
Jess: I think it’s important to recognize that nothing is definitively causative. We know that people can have different susceptibilities based on genetic and environmental factors, which influences how a condition like schizophrenia develops. Epidemiological studies have shown that one such environmental trigger is cannabis exposure. This doesn’t mean that cannabis exposure will directly cause schizophrenia; but it suggests that drug use, particularly cannabis exposure during specific developmental stages — like adolescence which is a vulnerable time for brain maturation — can alter the normal trajectory of brain development and increase the risk of developing schizophrenia.
As for preclinically modeling this, one of the advantages of animal models is that we can examine direct cause and effect by manipulating genetic or environmental factors at different developmental stages. For instance, we can expose animals to THC at different neurodevelopmental time points, and studies have shown this leads to an increased likelihood of developing psychosis-like symptoms.
When it comes to understanding schizophrenia symptoms using preclinical models, there’s a lot of data focused on psychosis, but one thing I highlighted in my talk is the need to address the negative and cognitive symptoms. These symptoms have received less attention partly because they’re harder to study and model in animals. Human behaviour is very complex, so while animal models are essential for treatment development, it’s critical for translation that we carefully choose models that best represent the behavior in question. For example, when modeling cognitive symptoms, we should evaluate how well the model replicates human cognitive constructs. And there have been incredible advancements in the models and cognitive behavioural assays that are now available. So, I’d love to see more detailed behavioural and cognitive phenotyping — in clinical populations and animal models — to better understand symptoms and which aspects of behavior are disrupted.
Amit: What are the challenges in developing touchscreen tasks to model or assess symptoms like visual hallucinations in psychosis research?
Jess: All the touchscreen tests I presented today at the Flagship School Session use visual stimuli to assess cognitive processes, and our work with these visual tests has primarily focused on cognitive symptoms. But you rightly highlight the challenge of measuring something like visual hallucinations in a rodent touchscreen-based task; it’s difficult.
There’s a famous quote: ‘All models are wrong, but some are useful,’ which is relevant here. Understanding the limitations of the tools we use is essential. While visual tests can be adapted to explore visual perception and processing, modeling and measuring hallucinations in rodents is challenging. For example, we know that increasing dopamine using psychostimulants for example, can lead to psychomotor agitation and hyperactivity in animals, which we use as a proxy for psychosis-like behaviour. While this doesn’t replicate psychosis as it appears in individuals, it does involve the same neurochemical changes. This test remains a valuable model to explore this aspect of psychosis and has predictive validity, thus provides one way to assess the effectiveness of novel antipsychotic treatments.
Amit: With the recent FDA approval of Cobenfy, do you see this as a groundbreaking step in antipsychotic treatment after 70 years? How far have we come in developing more effective therapies for schizophrenia?
Jess: What an incredible watershed moment – 70 years since we’ve seen a new mechanism of action drug developed for schizophrenia. This is truly something to celebrate — it highlights the hard work of discovery science, and the impact research can have in creating new treatments. It’s been a long journey, but this breakthrough shows that progress is possible.
Current medications for schizophrenia directly target dopamine receptors to alleviate the positive symptoms. While these work for many, they don’t work for all, and there’s still a need to improve these treatments, especially given the large side effect profiles that impact compliance. Reducing the burden of side effects remains essential for new treatments. Cobenfy hits an entirely different neurochemical system in the brain, confirming that new medications that target different pathways and systems in the brain can positively alleviate symptoms in schizophrenia, with potentially less side-effects.
We’re at a great point in understanding the complexity and heterogeneity of schizophrenia — recognizing that not everyone responds to the same treatment because the underlying neurobiological basis is different between people. This knowledge pushes us to develop treatments that more directly address specific symptoms. Additionally, huge advancements in drug discovery mean the design of new medicines is far more sophisticated. There have been major learnings on how to target molecules to only bind to certain parts of receptors, thus being able to finely dial-up or dial-down function, or primarily hit the brain over the rest of the body. These refined approaches can significantly reduce off-target effects, so treatments have fewer systemic side effects that lead to metabolic issues like weight gain, diabetes, cardiovascular disease or sleep problems, which still challenge individuals with schizophrenia.
We’ve come a long way, but we have much further to go. A key takeaway, especially from this Flagship School, is the importance of collaboration across disciplines. We’ve heard from clinicians about their perspectives and needs from the patient side, and from fundamental neuroscientists who’ve shared the biological insights they’re uncovering about mental ill-health. Maintaining this communication between fields and fuelling multidisciplinary approaches is crucial for progress and advancing the translational impact of research.
Amit: What role do you see AI playing in the diagnosis and treatment of schizophrenia? How might it help address some of the current challenges?
Jess: One of the exciting aspects of big data science is the capacity to integrate different pieces of the puzzle. Ultimately, achieving predictive therapeutic diagnosis won’t come from any single factor alone. Advanced AI offers hope here, as it can combine information from multiple levels for an individual to better inform which treatments someone might respond best to. We’re not there yet, but we’re getting closer and closer to a more effective approach. This is where I believe AI can make a big difference.
Amit: AI is a game-changer because it can analyse thousands of brain scans and imaging data in just seconds — something that would take an individual months to complete.
Jess: And it’s multimodal, right? As we gather more comprehensive data sets at multiple levels —genetics, blood markers, neuroimaging, symptom profiling — for individuals, AI can integrate whatever information is available into a more holistic model to support that predictive therapeutic diagnosis. As more data is obtained, we can feed it back into these models to update the predictions. AI shouldn’t be seen as a threat to replace consultation by healthcare professionals, but as a tool to help healthcare professionals refine their decision-making on diagnosis and optimal treatment selection for each person.
Amit: What are your thoughts on the societal stigma surrounding schizophrenia, and how do you think we can work toward greater understanding and acceptance?
Jess: I think this is such an important point about schizophrenia. Unlike other mental health conditions — like anxiety or depression, which society broadly accepts — schizophrenia is still very misunderstood. Even the term ‘schizophrenia’ began with the idea of a ‘split brain’ or ‘split personality,’ which has contributed to misunderstandings over the years. Schizophrenia is a complex, chronic condition, and the lack of understanding around it means that stigma is still a major issue.
While awareness campaigns have helped shift perceptions over the years, and progress has been made, really tackling this stigma and promoting acceptance relies on more biological understandings – knowledge is the key. The better we understand schizophrenia and provide a clearer picture of its neurobiological basis, the more we can demystify and break down the black box of what it means to have this condition. The more we share about its cases and underlying biology — including the fact that these processes are different for everyone — the more society can view it like any other health condition and embrace greater acceptance.
An ultimate goal for mental health conditions like schizophrenia is to have them viewed and accepted in the same way as physical health conditions.
Jess: So, how was your experience at the Flagship School this week?
Amit: This is my first time being selected for the Flagship School, and I was chosen along with 40 other students from all the applications — it’s been a huge opportunity to be here and to share thoughts with experts like yourself. The Flagship School offers a truly unique experience and is committed to providing opportunities on a global scale, especially for students from countries with fewer resources. Beyond that, it creates an environment of genuine interaction and collaboration.
We covered so many different mental health conditions, discussing both clinical needs and the power of pre-clinical research. It’s been fascinating to see perspectives from people all around the world, each bringing a fresh outlook to research. It’s also inspiring to see how many have moved internationally to pursue their work. This exchange of ideas has been incredibly valuable for me, and I appreciate how everyone here plays an important role in global neurochemistry.