Clinical Deep Dives

PSYCH 024: Computational Modelling Approaches to Psychiatry

56 min · Gestern
Episode PSYCH 024: Computational Modelling Approaches to Psychiatry Cover

Beschreibung

Psychiatry often deals with processes that cannot be directly observed - beliefs, predictions, learning, and perception. Computational psychiatry offers a way to formalise these processes, translating them into models that can be tested, refined, and understood. In this episode, we explore how mathematical and computational frameworks are used to describe how the brain processes information. Concepts such as prediction, uncertainty, reinforcement learning, and Bayesian inference provide a language for understanding cognition and behaviour. We examine how the brain can be conceptualised as a prediction-generating system - constantly updating its expectations based on incoming information. When these processes are disrupted, perception, belief formation, and decision-making can become distorted. This provides powerful insights into psychiatric conditions. Psychosis, for example, can be framed as a disturbance in how the brain assigns meaning or salience to information. Anxiety may reflect altered processing of uncertainty and threat prediction. Computational models do not replace clinical understanding - they deepen it. They allow psychiatry to move from descriptive frameworks to mechanistic explanations of how the mind works. This chapter represents a shift towards precision - where subjective experience is linked to underlying computational processes. Key Takeaways * Computational psychiatry models how the brain processes information. * Key concepts include prediction, uncertainty, and reinforcement learning. * The brain can be understood as a system that generates and updates expectations. * Psychiatric disorders may reflect disruptions in these computational processes. * Models provide a bridge between subjective experience and biological mechanisms. * Computational approaches enhance mechanistic understanding of mental illness. * These frameworks complement, rather than replace, clinical insight. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit drmanaankarray.substack.com/subscribe [https://drmanaankarray.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_2]

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Episode PSYCH 024: Computational Modelling Approaches to Psychiatry Cover

PSYCH 024: Computational Modelling Approaches to Psychiatry

Psychiatry often deals with processes that cannot be directly observed - beliefs, predictions, learning, and perception. Computational psychiatry offers a way to formalise these processes, translating them into models that can be tested, refined, and understood. In this episode, we explore how mathematical and computational frameworks are used to describe how the brain processes information. Concepts such as prediction, uncertainty, reinforcement learning, and Bayesian inference provide a language for understanding cognition and behaviour. We examine how the brain can be conceptualised as a prediction-generating system - constantly updating its expectations based on incoming information. When these processes are disrupted, perception, belief formation, and decision-making can become distorted. This provides powerful insights into psychiatric conditions. Psychosis, for example, can be framed as a disturbance in how the brain assigns meaning or salience to information. Anxiety may reflect altered processing of uncertainty and threat prediction. Computational models do not replace clinical understanding - they deepen it. They allow psychiatry to move from descriptive frameworks to mechanistic explanations of how the mind works. This chapter represents a shift towards precision - where subjective experience is linked to underlying computational processes. Key Takeaways * Computational psychiatry models how the brain processes information. * Key concepts include prediction, uncertainty, and reinforcement learning. * The brain can be understood as a system that generates and updates expectations. * Psychiatric disorders may reflect disruptions in these computational processes. * Models provide a bridge between subjective experience and biological mechanisms. * Computational approaches enhance mechanistic understanding of mental illness. * These frameworks complement, rather than replace, clinical insight. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit drmanaankarray.substack.com/subscribe [https://drmanaankarray.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_2]

Gestern56 min
Episode PSYCH 023: Basic Systems Neuroscience Cover

PSYCH 023: Basic Systems Neuroscience

Understanding individual neurons is only the beginning. This chapter shifts the lens to systems neuroscience - exploring how networks of interconnected regions work together to produce cognition, emotion, and action. In this episode, we examine how the brain operates as a set of distributed systems rather than isolated modules. Circuits linking cortical and subcortical regions coordinate functions such as attention, memory, emotion regulation, and decision-making. We explore key principles of organisation - integration, segregation, and hierarchical processing - showing how specialised regions contribute to broader network function. No single area “contains” a psychiatric disorder; rather, dysfunction emerges from altered interactions within and between systems. This perspective is central to modern psychiatry. Disorders are increasingly understood as disruptions in network dynamics - shifts in connectivity, balance, and coordination - rather than focal lesions. This chapter invites a systems-level view: to see the brain not as a collection of parts, but as an orchestra - where harmony depends on timing, coordination, and the relationships between players. Key Takeaways * Systems neuroscience focuses on networks of interacting brain regions. * Brain function arises from distributed circuits, not isolated areas. * Key principles include integration, segregation, and hierarchical organisation. * Cognitive and emotional processes emerge from coordinated network activity. * Psychiatric disorders reflect disruptions in system-level dynamics. * Connectivity and balance between networks are central to brain function. * Understanding systems enhances clinical reasoning in psychiatry. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit drmanaankarray.substack.com/subscribe [https://drmanaankarray.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_2]

6. Juni 202654 min
Episode PSYCH 022: Animal Models in Psychiatry Cover

PSYCH 022: Animal Models in Psychiatry

Much of what we understand about brain function and psychiatric illness has been built through animal research. Yet modelling the human mind in animals is inherently complex. This chapter explores how animal models are used in psychiatry - and the limits of what they can truly represent. In this episode, we examine different types of animal models, including those based on genetic manipulation, pharmacological induction, and behavioural paradigms. These models allow us to study neural circuits, molecular mechanisms, and treatment effects in controlled environments. We explore the concept of validity - face validity, construct validity, and predictive validity - and how each determines the usefulness of a model. No model fully captures human psychiatric experience; instead, each isolates specific components of complex conditions. This raises an important tension: animal models offer precision and control, but human psychiatry involves subjective experience, meaning, and context - elements that are difficult, if not impossible, to replicate. This chapter encourages a nuanced view. Animal models are not replicas of psychiatric disorders, but tools - valuable for understanding mechanisms, yet always requiring careful interpretation when applied to human experience. Key Takeaways * Animal models are used to study mechanisms underlying psychiatric disorders. * Models may be genetic, pharmacological, or behavioural in design. * Validity is assessed through face, construct, and predictive criteria. * No model fully captures the complexity of human psychiatric conditions. * Animal research provides mechanistic insight and supports treatment development. * Translation to human psychiatry requires careful interpretation. * Models are tools for understanding components, not entire disorders. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit drmanaankarray.substack.com/subscribe [https://drmanaankarray.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_2]

5. Juni 202652 min
Episode PSYCH 021: Pharmacogenetics Cover

PSYCH 021: Pharmacogenetics

Why does one patient respond well to a medication while another experiences no benefit - or significant side effects? Pharmacogenetics seeks to answer this question by examining how genetic variation influences drug metabolism, efficacy, and tolerability. In this episode, we explore how differences in genes encoding drug-metabolising enzymes, receptors, and transporters can alter how medications are processed and how they act within the brain. Variations in systems such as cytochrome P450 enzymes can determine whether a drug is broken down too quickly, too slowly, or unpredictably. We examine how these differences translate into clinical outcomes - affecting dosing, response rates, and risk of adverse effects. This introduces the possibility of more personalised prescribing, moving away from trial-and-error approaches. However, pharmacogenetics also comes with limitations. Genetic factors are only one part of the picture; environment, comorbidity, and psychological context also shape treatment response. The promise of precision must therefore be balanced with clinical judgement. This chapter reframes prescribing as an interpretive process - where biology informs decisions, but does not dictate them. It offers a glimpse of a more tailored future, while reminding us of the complexity inherent in treating the human mind. Key Takeaways * Pharmacogenetics studies how genetic variation affects drug response. * Genes influence drug metabolism, receptor sensitivity, and transport mechanisms. * Variations in enzymes (e.g. cytochrome P450) can alter drug levels and effects. * Genetic differences contribute to variability in efficacy and side effects. * Pharmacogenetics supports more personalised approaches to prescribing. * Clinical decisions must still integrate non-genetic factors. * Precision medicine enhances, but does not replace, clinical judgement. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit drmanaankarray.substack.com/subscribe [https://drmanaankarray.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_2]

4. Juni 202640 min
Episode PSYCH 020: Epigenetics in Psychiatry: The Promise for New Biomarkers and Treatments Cover

PSYCH 020: Epigenetics in Psychiatry: The Promise for New Biomarkers and Treatments

If the genome provides the script, epigenetics determines how it is read. This chapter explores how environmental influences - from early life experiences to chronic stress - can modify gene expression without altering the underlying DNA sequence. In this episode, we examine mechanisms such as DNA methylation and histone modification, which regulate whether genes are activated or silenced. These processes act as molecular switches, shaping how genetic potential is realised across development and throughout life. Crucially, epigenetics provides a bridge between biology and experience. It offers a framework for understanding how adversity, trauma, and environment can become biologically embedded - influencing vulnerability to psychiatric disorders. We also explore the emerging potential of epigenetic markers as biomarkers for diagnosis and prognosis, as well as targets for novel treatments. However, this promise is accompanied by complexity - epigenetic changes are dynamic, context-dependent, and not easily reduced to simple clinical tools. This chapter reframes nature versus nurture as a false dichotomy. Instead, it presents a dynamic interaction where experience continuously shapes biology - and biology, in turn, shapes experience. Key Takeaways * Epigenetics involves changes in gene expression without altering DNA sequence. * Mechanisms include DNA methylation and histone modification. * Environmental factors can influence gene expression across the lifespan. * Epigenetics provides a biological link between experience and psychiatric vulnerability. * Adversity and stress can become biologically embedded through these mechanisms. * Epigenetic markers hold potential as biomarkers and treatment targets. * Gene–environment interaction is central to understanding psychiatric disorders. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit drmanaankarray.substack.com/subscribe [https://drmanaankarray.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_2]

3. Juni 20261 h 8 min