PSYCH 026: Electroencephalography in Psychiatry

PSYCH 026: Electroencephalography in Psychiatry

If imaging reveals structure, electroencephalography (EEG) captures activity in real time. This chapter explores how electrical signals generated by neuronal populations can be recorded from the scalp, offering a dynamic view of brain function. In this episode, we examine how EEG reflects synchronised activity across neural networks, producing patterns that can be analysed in terms of frequency, amplitude, and coherence. These rhythms - from slow delta waves to fast gamma activity - represent different states of brain function. We explore how EEG is used clinically, particularly in epilepsy and sleep medicine, but also its growing role in psychiatric research. Subtle alterations in brain rhythms have been associated with conditions such as schizophrenia, depression, and attention disorders. A key theme is temporal resolution. Unlike structural imaging, EEG captures the brain as it unfolds moment by moment - revealing patterns of timing, synchrony, and disruption that are otherwise invisible. However, EEG also has limitations. Its spatial precision is limited, and interpretation requires careful contextualisation. It offers a window into function, but not a complete map. This chapter highlights the importance of timing in brain activity - showing that when signals occur, and how they synchronise, is as important as where they originate. Key Takeaways * EEG records electrical activity from neuronal populations in real time. * Brain activity is reflected in rhythmic patterns across different frequencies. * EEG provides high temporal resolution but limited spatial precision. * It is widely used in epilepsy and sleep medicine, with growing psychiatric applications. * Altered brain rhythms are associated with various psychiatric conditions. * EEG reveals patterns of synchrony, timing, and network dynamics. * Functional insight requires careful interpretation within clinical context. 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]

PSYCH 025: Nuclear Magnetic Resonance Imaging and Spectroscopy: Basic Principles and Recent Findings in Neuropsychiatric Disorders

Much of psychiatry has historically relied on inference - understanding brain function indirectly through behaviour and experience. Nuclear magnetic resonance (NMR) techniques, including MRI and spectroscopy, have transformed this landscape, allowing us to visualise both structure and chemistry in vivo. In this episode, we explore the principles underlying magnetic resonance imaging - how magnetic fields and radiofrequency signals are used to generate detailed images of brain anatomy. We then move beyond structure to spectroscopy, which provides insight into the brain’s biochemical composition. These tools allow us to observe patterns associated with psychiatric disorders - changes in volume, connectivity, and neurochemical markers. Yet interpretation remains complex: findings are often subtle, variable, and not specific to a single condition. We examine how these technologies contribute to research and, increasingly, clinical practice - while also recognising their limitations. Imaging does not “diagnose” psychiatry in isolation; it adds another layer of understanding to an already complex picture. This chapter reflects a broader shift: from unseen processes to visualised systems - offering a window into the living brain, while reminding us that what we see is only part of the story. Key Takeaways * MRI uses magnetic fields and radiofrequency signals to image brain structure. * Spectroscopy provides information about brain biochemistry in vivo. * These techniques allow observation of structural and chemical changes in psychiatric disorders. * Findings are often subtle and not specific to individual diagnoses. * Imaging enhances understanding but does not replace clinical assessment. * Interpretation requires integration with broader clinical and scientific context. * Neuroimaging is a tool for insight, not a standalone diagnostic solution. 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]

PSYCH 025: Nuclear Magnetic Resonance Imaging and Spectroscopy: Basic Principles and Recent Findings in Neuropsychiatric Disorders

Much of psychiatry has historically relied on inference - understanding brain function indirectly through behaviour and experience. Nuclear magnetic resonance (NMR) techniques, including MRI and spectroscopy, have transformed this landscape, allowing us to visualise both structure and chemistry in vivo. In this episode, we explore the principles underlying magnetic resonance imaging - how magnetic fields and radiofrequency signals are used to generate detailed images of brain anatomy. We then move beyond structure to spectroscopy, which provides insight into the brain’s biochemical composition. These tools allow us to observe patterns associated with psychiatric disorders - changes in volume, connectivity, and neurochemical markers. Yet interpretation remains complex: findings are often subtle, variable, and not specific to a single condition. We examine how these technologies contribute to research and, increasingly, clinical practice - while also recognising their limitations. Imaging does not “diagnose” psychiatry in isolation; it adds another layer of understanding to an already complex picture. This chapter reflects a broader shift: from unseen processes to visualised systems - offering a window into the living brain, while reminding us that what we see is only part of the story. Key Takeaways * MRI uses magnetic fields and radiofrequency signals to image brain structure. * Spectroscopy provides information about brain biochemistry in vivo. * These techniques allow observation of structural and chemical changes in psychiatric disorders. * Findings are often subtle and not specific to individual diagnoses. * Imaging enhances understanding but does not replace clinical assessment. * Interpretation requires integration with broader clinical and scientific context. * Neuroimaging is a tool for insight, not a standalone diagnostic solution. 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]

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]

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]