Introduction Part III: Neuroimaging and Models of Psychedelic Action

Written By Michael Angyus

Introduction

Welcome curious friends to Psychedelic Neuroscience, where we use advances in psychedelic research to learn about brain, mind, and soul. I’m your host, Michael Angyus, and today we’re going to talk about the neuroimaging work with psychedelics as well as some of the leading models of psychedelic action that it has contributed to.

The simple story of the DMN

Early brain imaging work by Dr. Robin Carhart-Harris at Imperial College London showed a reduction in default mode network (DMN) activity during the acute effects of psychedelics (Carhart-Harris et al., 2012). The DMN is a network of brain regions involved in self-referential thinking such as autobiographical memory and contemplation of one’s relationships with others (Raichle, 2015). Michael Pollan discusses the DMN in his popular book How to Change Your Mind, which has played a major role in the increasing popularity of psychedelics by capturing a snapshot of psychedelics at a pivotal time for clinical trials treating mental illness. In the book, Pollan explains that this decrease in DMN activity is related to psychedelic induced ‘ego dissolution’ (Nour et al., 2016); the quieting of the DMN leads to the quieting of self-referential thought, and therefore the quieting of the self. This change activity is thought to be important for therapeutic change. Indeed, fMRI studies have consistently shown that there is disruption between nodes of the DMN under psychedelics (Preller et al., 2018; Carhart-Harris et al., 2012; Carhart-Harris et al., 2016; Muller et al., 2018; Palhano-Fontes et al., 2015; Muthukumaraswamy et al., 2013), and this has also been found with SSRIs (Klaassens et al., 2015) and non-hallucinogenic ‘psychedelic’ MDMA (Muller et al., 2021). This indicates the effect may be a feature of the serotonin system that is unspecific to psychedelics. We still might then wonder what could explain the rest of psychedelic effects, particularly the mystical aspects of the experience. In the previous episode, we discussed how the 5HT-2A receptor (one of 14 serotonin receptor subtypes) is essential for subjective psychedelic effects. In this episode, we are going to explore a more holistic view of the brain through the various neuroimaging-based theories on how psychedelics produce their effects.

Adding complexity to neuroimaging data

The popularized DMN perspective of psychedelic action is an oversimplification. In fact, reanalysis has shown that the DMN activity is not actually reduced by psychedelics, but it is indeed disrupted, along with the activity of several other important networks in the brain. I’m going to add some complexity to the DMN-ego dissolution view of psychedelics, but first we have to review the organization of the brain. The brain can be broken into two levels, the lower-level sensory processing areas, which sit near the back of the brain and find things like edges and objects in the case of vision, and higher-level association areas, which sit near the front of the brain and are thought to collect information from sensory levels to unify them into a single consciousness. The DMN is one of these higher-level association networks, which makes sense because it needs to pull information from the senses to construct a unified understanding of self. The other thing we need to know about the brain is that the idea of a “network” is based on what is called functional integration, which is the amount of coactivity between different nodes of a network. (So when a few regions of the brain are showing correlated activity – they are active at the same times over the course of a brain scan – these regions have high functional integration). This is thought to represent those brain regions talking to each other a lot, which is why we decide to call it a network.

It turns out that high-level networks show decreases in functional integration, while lower-level sensory networks show increases in functional integration under LSD, psilocybin, and ayahuasca (LSD: Preller et al., 2018; Roseman et al., 2016; Carhart-Harris et al., 2016; Muller et al., 2018; psilocybin: Preller et al., 2020; Lord et al., 2019; Carhart-Harris et al., 2012; Muthukumaraswamy et al., 2013; Madsen et al., 2021; ayahuasca: Palhano-Fontes et al., 2015). While under the influence of psychedelics, markers of neural activity increase in frontal cortical regions but decrease in sensory cortices (Vollenweider et al., 1997; Lewis et al., 2017; Gouzoulis-Mayfrank et al., 1999; Vollenweider, 1998; Riba et al., 2006; Hermle et al., 1992), implying differential effects of psychedelics on high-level cognitive and lower-level sensory networks. Interestingly, these results align with gene maps and PET data documenting 5HT-2A receptor distribution (Preller et al., 2018; Komorowski et al., 2017), supporting the hypothesis that the brainwide and subjective action of psychedelics is primarily conducted through this receptor.

Each of the three theories mentioned in episode one explains these findings differently. In the next section, I will explore how the groups proposing the cortico-striatal thalamo-cortical (CSTC) model, the cortico-claustro-cortical (CCC) model, and the relaxed beliefs under psychedelics (REBUS) model have gathered evidence for their perspectives.

Interpreting these results using the CSTC model

Starting with the thalamic gating theory From Zurich, Switzerland, their interpretation is that disruption of the usual gatekeeper of sensory information, the thalamus, leads the cortex to be flooded with information, akin to breaking a sensory dam. This overwhelms the associative cortices, inhibiting reflection and integration (Vollenweider & Preller, 2020). Imaging work on thalamo-cortical interactions has broadly supported this interpretation, showing altered connectivity between the prefrontal cortex and thalamus. These have primarily been increases in thalamus to cortex information flow, supporting the idea of a broken dam (Preller et al., 2018, Muller et al., 2017; Preller et al., 2019). Subjective hallucinations have been related to changes in thalamus connectivity (Muller et al., 2021; Muller et al., 2017), suggesting this may be an alternative explanation for the unique hallucinogenic effects of psychedelics. Interestingly, thalamic connectivity alterations have also been found in people at risk for schizophrenia (Anticevic et al., 2015). The overlap between psychedelics and schizophrenia risk may point to a non-pathogenic mechanism underpinning hallucination, something first contemplated by early psychedelic researchers when naming the compounds “hallucinogens”.

Interpreting these results using the CCC model

The cortico-claustro-cortical (CCC) model proposed by the Johns Hopkins group in Baltimore interprets the disruption of association networks like the DMN as being primarily driven by the claustrum (Doss et al., 2022). The claustrum is highly connected to various cortical and subcortical regions and has high 5HT-2A expression (Mathur, 2014; Nichols, 2016; Nichols et al., 2017). This makes it a potentially important orchestrator of neural activity that is going to be sensitive to psychedelic substances. Additionally, the claustrum has been implicated in cognitive control (Atlan et al., 2018, Krimmel et al., 2019, White and Mathur, 2018) and direct activation through optogenetics stimulates widespread cortical activation (Narikiyo et al., 2020). Similar to the thalamus, the activity of the claustrum is modulated by inputs from the prefrontal cortex (White et al., 2017). Recent support for CCC has surfaced from a single studying involving Psilocybin (Barrett et al., 2020). The psychedelic reduced activity in the claustrum which was correlated with decreases in high-level network integration. Further, this was linked to reports of ‘ineffability’, suggesting the claustrum may provide a novel pathway by which the unique subjective effects of psychedelics occur. While focusing on different circuits, the CCC and CSTC models converge on a shared notion: impaired modulation by the prefrontal cortex ultimately hinders the brains ability to perform its regular integrative processing of information.

Interpreting these results using the REBUS model

In terms of Carhart-Harris’s REBUS model, the interpretation is of computational nature. As such, the specifics of neural circuits are swapped for a computational perspective that hinges on a hierarchically-structured brain (Carhart-Harris & Friston, 2019). Karl Friston is widely known for his development of the free energy principle (FEP), which proposes that the brain is always trying to minimize its “free energy” by finding the most efficient model for biological success (Friston, 2010). Accruing over 6000 citations, this thermodynamic approach has reverberated popularly throughout neuroscience. Statistical mechanics and information theory, which form the core mathematics of thermodynamics, have increasingly been applied to the brain through computational neuroscience. One notable application was Carhart-Harris’s entropic brain hypothesis (EBH), a theory of consciousness informed by psychedelic neuroimaging research (Carhart-Harris et al., 2014; Carhart-Harris, 2018). REBUS emerged as a marriage of the EBH with Fristons computational mechanism of the FEP, predictive coding (Friston & Kiebel, 2009).

Predictive coding organizes the brain into a hierarchically structured prediction machine, each layer of which compares bottom-up encoded models of sensory information with top-down learned prior models. The prior models suppress predictable information, indicating the model is correct and should not be modified. However, unpredictable stimuli are not suppressed, and this ‘prediction error’ is sent up the hierarchy to influence the revision of incorrect models. As models accrue evidence, they become less sensitive to new evidence that disagrees with them, especially if the evidence is not reliable. Bayesian statistics have been used to model this computation, allowing for the assignment of confidence to both the bottom-up evidence as well as the top-down models (Ma et al., 2023). This has been broadly applied in sensorimotor learning to show the brain often abides by Bayesian statistics (Kording & Wolpert, 2004). If confidence in the prior model is strong, and evidence is weak, the brain will ignore the error and maintain the model. We can see how this scenario might play out in psychopathology, such as the rigid negative self-perception associated with depression may blind people to hope. Indeed, REBUS and subsequent theories have proposed that overly strengthened priors play a role in mental illness (Carhart-Harris et al., 2023).

REBUS proposes that the high-level networks that are disrupted by psychedelics are normally responsible for exerting top-down control broadly across the brain, and that the disruption by 5HT-2A activity relaxes this control, loosening the brain into a more entropic brain state (Carhart-Harris & Friston, 2019). Entropy, the measure of a system’s disorder, is a concept from information theory that has gained popularity in neuroimaging analysis over the last two decades (Keshmiri, 2020). Thought to be representative of the information content of the chosen signal of brain activity, entropy has been linked to conscious states, ageing, and disease (Carhart-Harris et al., 2014; Carhart-Harris, 2018; Keshmiri, 2020). For a neural system to have high entropy means that it is visiting or exploring a high number of its potential states. REBUS posits that psychedelic relaxation of high-level priors increases the diversity of brain states, subsequently allowing for the release of pathological patterns and the therapeutic habituation of new ones. In support of this, numerous studies have found increased entropy in neuroimaging data taken during a psychedelic experience (Atasoy et al., 2018; Jobst et al., 2021; Li et al., 2022; Varley et al., 2020; Viol et al., 2017; Tagliazucchi et al., 2014; Toker et al., 2021; Eckernas et al., 2023), and many studies have found this change related to subjective experience (Alonso et al., 2015; Lebedev et al., 2016; Luppi et al., 2021; Timmerman et al., 2019). The relaxation of priors is also thought to impair the ability to suppress sensory stimuli, resulting in the observed flooding of sensory information and hallucinations.

Reconciliation of the three models

Importantly, these three models are not mutually exclusive. It is conceivable that high expression of 5HT-2A receptors in association cortices disrupts their coordinated activity. This results in a lack of top-down control of the prefrontal cortex over the thalamus and the claustrum. This undams the bottom-up stimuli from the thalamus and loosens claustral control over the association networks. Therefore, each of the current circuit mechanisms fit into the computational perspective of REBUS and additional specific circuits will likely be discovered in the future. Additional research will help outline the comparative relevance of these circuits in the production of different subjective experiences.

Problems with neuroimaging

While these theories feel like they converge on a common explanation, it is important to remember that brain imaging is highly variable in analysis techniques and direct replication of findings in psychedelic neuroimaging is lacking (McCulloch et al., 2022). For instance, studies without global signal regression (GSR), which is the normalization to a measured signal intended to remove physiological artifacts and movement, have shown mixed changes by psychedelics, but when adding GSR have been consistent (see box 2 of Vollenweider & Preller, 2020 for discussion of GSR). Additionally, studies of entropy are varied in both their calculations of entropy as well as the type of imaging data they are applied to, suggesting that in each analysis these results are measuring a different kind of ‘entropy’ (McCulloch et al., 2022). This latter point could place the abstract concept of entropy as a surprisingly valid but regionally unspecific model of neural information processing. Indeed, global measurements of entropy have been shown to be more reliable predictors of cognitive ability than regional entropy (Liu et al., 2020).

 

The problems of neuroimaging begin before data analysis takes place. Compared to cellular and molecular studies, which remove as much of the brain as possible to explore a specific pathway without confounds, neuroimaging includes countless additional variables that prevent firm conclusions. While improving sample sizes (Marek et al., 2022) and using clever methodology (Carp, 2012; Botvinik-Nezer et al., 2020) has improved replicability to a degree, an often-overlooked assumption is that the same neural activity will correspond to behavior across subjects and context (Westlin et al., 2023). Westlin et al., (2023) discuss three overlooked assumptions that are commonly made in neuroimaging: 1) that psychological events can be traced to a single region; 2) that this activity is specific to this region across people and experimental strategies; and 3) that this activity will occur independent of alternative neural signals active during the experiment. Psychedelic research has long respected the importance of set (the individual psychology of a user) and setting (the environmental context the user’s psychology interacts with) (Hartogson, 2017). Brains are significantly complicated and interdependent systems, likely more interdependent and complex than our concepts of self (since the concept of self indeed is represented by a subset of our brains neural processing). While simplification of variables is necessary to explore the relationships questioned by neuroscience, the use of statistics to identify population averages rather than trends within an individual has arguably hindered efforts to understand the brain.

We must come up with creative ways to address these complex variables. One novel approach to controlling for the complexity of brain activity showed watching a movie outperformed resting state data when using functional connectivity to predict behaviour, likely due to controlling for variations in activity that occur during ‘resting states’ (Finn & Bandettini, 2021). Additionally, Timmerman et al., (2023) have offered a ‘neurophenomenological’ approach to study non-ordinary states of consciousness which attempts to clarify the connection between neural activity and the contents of subjective experience. These solutions are an early glimpse at the potential innovations in study design that will improve our elucidation of neural correlates of behavior and psychological content.

 

Closing

Neuroimaging is itself an area in its infancy, and while psychedelic neuroimaging has built a significant foundation for us to construct models of mechanistic action, we have a long way to go before we can pair the subjective and therapeutic effects of psychedelics with brain activity. I look forward to keeping you updated as we discover more about this brain-mind connection.

Thanks for tuning in to another episode of psychedelic neuroscience, where we use psychedelic research to learn about brain, mind, and soul. This was the third episode of a four-part introduction series, where I’m giving you an overview of the field from the molecule up to the mystery. This episode covered neuroimaging and models of psychedelic action in the brain. In the next episode, I will stretch the imagination with discussions of subjective effects, offering some more fun but less scientifically grounded perspectives on what could be connecting the neuroscience to the experience.

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Michael Angyus
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