Yesterday we published a new mini-review article in Trends in Cognitive Sciences. Needless to say we’re pretty happy about this. Our article “Unravelling the Neurobiology of Interoceptive Inference” discusses two recent landmark papers in the systems neuroscience of interoception, and proposes a novel “interoceptive self-inference” model of insula function to account for these new findings.
You can read the article here:
And an open access preprint is available here:
What exactly is “self inference”? This is something we’ve been working on for a number of years. The basic concept is that the brain not only encodes a prediction of interoceptive states, but uses these states to estimate its own expected uncertainty or precision. Expected uncertainty is critical for optimizing learning, attention, and metacognition. Our model suggests then that when we estimate how reliable or certain our future beliefs and sensations will be, we take into account the constant influence of the body on the noise levels of our sensory apparatus. Put simply, our model argues that the “state noise” term considered in most formal accounts of decision-making is in large part driven by visceral fluctuations, and that the brain utilizes interoception to sample and control these noise trajectories, i.e. through metacognitive active inference.
So what has the ‘self’ got to do with that? That is something we are continuously expanding on – in the next year we have another major review in the pipeline, as well as a book chapter focused on consciousness science. In a very basic sense, we call it “self inference” because the brain is combining predictions about the body and the world to produce an estimate of its own reliability. You could think of it as something like a hybrid between global workspace, FEP, and higher-order thought theories of consciousness. In practical terms it is a bit like having a computing cluster which can monitor the temperature of the CPU to limit down-throttling, spreading load around to cooler CPUs when needed. By monitoring our own noise levels, we build more precise estimates of expected uncertainty, which can then be leveraged to determine how much we should update our models of the world (and self) when we encounter surprising events.
The implications of the self-inference model are fascinating, to us at least. For one, we pick up on existing strands of theory that suggest that Bayesian meta-cognitive inferences over expected precision underlie selfhood and perhaps even consciousness itself. By inferring (and controlling, through active inference) our own embodied noise trajectories, we are effectively estimating the influence of ‘the self’ on our re-afferent data streams. That is to say, we’re actively accounting for the minimal self or minimal embodied perspective as the constant source of noise influencing sensory flow and beliefs. The implication here is that, disruptions in self-belief can alter our visceral experiences (e.g., embodied hallucination), and conversely, disrupted interoception can ‘leak’ into our perceptual and metacognitive inferences, producing a variety of affective and decision biases. At the extreme, we think that maladaptive self-inference underlies a wide spectrum of psychiatric and even neurological disorders.
But that is just a sneak peak. You can follow the development of the self-inference model (perhaps we’ll call it MISE, for “metacognitive and interoceptive self inference”) in our recent publications:
1. forthcoming BBS commentary article:
2. An early book chapter with Manos Tsakiris:
3. Our recent computational model of interoceptive self-inference:
Stay tuned for more! We have one or two more major theory articles in the works this year, which should fully ‘flesh’ out the self-inference model and its implications for the phenomenology of the self, consciousness, and computational psychiatry.
Today we are thrilled to announce the release of our lab’s first software package, Systole! Systole is a comprehensive python package intended to help you clean, transform, and analyze your cardiac time-series data, particularly in the context of psycho-physiological research. In addition to these basic functions, Systole offers built-in support for synchronizing your PsychoPy experiments with the heartbeat, making it easier to present stimuli at specific phases of the cardiac cycle. This is of particular interest for research in brain-body interaction and interoception. Unfortunately, most new studies in this area do no use open code, limiting reproducibility. Enter systole!
As of today, Systole is provided as an early ‘pre-release’, and is far from feature complete – so please use with caution! For our initial release, we’ve focused on offering native support for the popular Nonin USB XPod pulse oximeter, which is frequently used in interoception experiments and offers a cheap (~300 GBP), easy to use platform for plethysmographic cardiac data collection. We hope that this will enable users to design robust interoception and cardiac synchrony tasks, and to share them with the community.
The toolbox also supports basic formats such as RR-interval time series, or instantaneous heart-rate data. Future packages and releases will include other data formats, such as ECG, electrogastrography, and respiration, and we hope the community will help to add support for other devices.
… plus an entire suite of plotting functions to produce these graphics, and more!
Further, at the Systole website you can find complete documentation as well as interactive tutorials for a variety of workflows including:
We’ll be using Systole extensively in our ongoing Visceral Mind Project, and expect to continuously revise and improve it as we add new features and discover use-cases. Further, Systole is provided as a fully open software, so we invite you to contribute your own additions through Github!
In the near future, we will publish a methods paper + tutorial detailing the Systole package. In the meantime, if you use Systole in your research, please cite:
Nicolas Legrand, & Micah Allen. (2020, January 14). embodied-computation-group/systole: Pre-Alpha (Version 0.0.1). Zenodo. http://doi.org/10.5281/zenodo.3607913
Please let us know what you think! Happy heartbeat counting 😉
Last week we successfully submitted an ERC starting grant for our ongoing work investigating how cannabinoids influence learning, interoception, and brain-body interaction! The grant proposes a series of four interlocking experiments probing the neurovisceral mechanisms underlying behavioral, subjective, and interoceptive effects of pharmaceutical THC and CBD. This work continues our recent collaboration with Dr. Samia Joca, investigating the influence of CBD on affective bias. We’re excited to continue this work as it will open up fascinating new research questions for our lab, and will also provide us with new pharmacological manipulations and models we can apply in our computational psychiatry research. We’ll keep our fingers crossed for good reviews – watch this space in the next 6 months!
We’re happy to announce that Micah Allen was recently awarded the Early Career Prize by The British Association for Cognitive Neuroscience! The ‘Early Career Prize’ is awarded to young researchers who have contributed their high-standard and pioneering work to the field of cognitive neuroscience. The aim of the prize is to reward and recognize distinguished scholarship and research excellence undertaken over a period by a cognitive neuroscientist who is currently active in research, and who has made a substantial contribution to Cognitive Neuroscience in the UK. Micah received the award in September 2019, and give an early career prize lecture at the annual meeting in Cambridge entitled “Interoceptive Self-Infeerence: An Embodied Approach to Computational Psychiatry”. Here is the lecture abstract:
“Our ability to learn from an ever-changing, volatile world is essential. Convergent evidence suggests that deficits in the ability to update beliefs in the face of such uncertainty may underpin a variety of psychiatric illnesses. In parallel, we know that many such disorders are accompanied by profound somatic and visceral disruptions, and these are in turn underpinned by the very same neural machinery which encodes decision uncertainty. Here, I will present evidence that metacognitive awareness of uncertainty is biased by visceral arousal. On the basis of these findings, we recently proposed a new computational model of “interoceptive self-inference”, in which the brain samples the volatility of visceral rhythms to predict future decision uncertainty. On this basis, we argue that disordered interoceptive beliefs and/or visceral sensation can both act to produce pervasive decision biases such as those which characterize the major mood and neurodevelopmental disorders.”
It brings me great pleasure to officially announce that I have been awarded joint starting fellowships from the Lundbeck Foundation and Aarhus Institute of Advanced Studies (AIAS)! These fellowships will enable me to launch my own research lab, the Embodied Computation Group (ECG), which will be based at both Aarhus University and Cambridge Psychiatry. This is an incredibly exciting development – obviously for my own sanity as an early career researcher, but also more importantly for the budding field of embodied neuroscience and computational psychiatry!
As an Associate Professor at Aarhus University and a visiting Senior Research Fellow at Cambridge Psychiatry, I will develop the ECG into a multi-disciplinary research group investigating the computational mechanisms of brain-body interaction, and their disruption in a variety of health-harming and psychiatric disorders. The ECG will initially focus on the Visceral Mind Project – an unprecedented chance to map the neural mechanisms through which interoception and arousal shape our decision-making, awareness, and metacognition.
The ECG will be built around The Visceral Mind Project, which aims ultimately to provide a mechanistic basis for understanding brain-body disruption through the lens of computational psychiatry (henceforth, ‘embodied computational psychiatry’). The project will use a variety of techniques developed throughout my postdoc, with an emphasis on computational modelling, machine learning, and causal manipulation of visceral signals to identify how the body shapes decision-making and awareness. This project will be *fully* open; as we progress, we’ll be regularly sharing updates through our lab notebook, and all data, code, and experimental materials will be made available to the public. Our goal is not only to understand brain-body interaction in predictive processing, but to build the first ever open neuroimaging database in this newly emerging research domain. In this way the ECG will act as a catalyst for mechanism-based research in interoception and the computational psychiatry of disordered brain-body interaction.
In Denmark, the ECG will be based at the Danish Neuroscience Centre at Aarhus University Hospital, the Centre for Functionally Integrative Neuroscience, and the Aarhus Institute for Advanced Studies. For this arm of the project, we’ll scan 500 Danes performing a metacognitive learning task, concurrently with quantitative MRI and functional brain imaging. This will enable us to establish how visceral signals from the heart, lungs, and stomach shape the precision-weighted balance of priors and prediction errors in both perceptual and metacognitive beliefs. Further, by applying canonical covariate and other machine learning techniques to brain connectivity and microstructure, we’ll identify sensitive cortical fingerprints indexing individual differences in visceral-weighting. This arm of the project will bring together the latest in fMRI, MEG, and statistical modelling of brain data to answer two key questions: 1) how do visceral signals shape decision computations, and 2) can we use individual differences in the sensitivity to visceral signals as an index of sub-clinical psychiatric symptoms.
At Cambridge Psychiatry and Addenbrookes Hospital, together with Professor Paul Fletcher and the MRC-Wellcome Translational Research Facility, the ECG will use these tasks and models to probe disordered brain-body interaction in a variety of health-harming and psychiatric disorders. Foremost among these are our ongoing investigations of healthy participants undergoing total prophylactic gastrectomy – the surgical removal of the stomach and vagus nerve. Our PTG patients have a mutation of a specific gene which renders them extremely likely to develop profuse gastric cancer, a highly fatal disease. Because of this, when they undergo the procedure they are on average 25 years old and otherwise completely healthy, unlike many other vagotomy and bariatric surgery populations. As such, these patients present an unprecedented opportunity to understand what happens to interoception, decision-making, and visceral weighting when the enteric nervous system and brain-body axis is fundamentally disrupted. More importantly, this project will directly inform the surgeons, patients, and family members going through this difficult process, as currently almost nothing is known about the cognitive or affective impacts of this surgery. This project will thus combine ultra-high field 7T imaging and computational modelling to better understand how profound visceral disruption influences the canonical micro-circuitry associated with metacognitive learning and interoception. More generally, the ECG will use a similar approach to investigate the role of aberrant visceral weighting in hunger, obesity, and other psychiatric disorders such as anxiety and psychosis.
As a third parallel research arm, across both our basic and clinical research sites at Aarhus and Cambridge, respectively, we’ll be developing novel pharmacological, psychophysiological, and electrophysiological techniques to directly manipulate interoceptive predictions and prediction errors. This is a critical long-term goal of our research, as we seek to not only map brain-body interactions, but also to understand how their causal manipulation might one day provide a window into the treatment of mental illness. This research will combine innovative techniques such as vagal nerve stimulation and gastric learning to probe how causal fluctuations in visceral predictability and volatility shape perceptual decisions and metacognition.
In sum, the Visceral Mind Project represents a stunning opportunity to propel our understanding of how our bodies shape our minds. The project is supported by a stellar core network of international collaborators at UCL, Cambridge, and ETH Zurich. Our trainees will enjoy the opportunity to visit and work with these world class centres and investigators, as we work towards building a bridge between the stellar Danish clinical neuroscience community and our collaborators who are experts in computational modelling, psychiatry, and neuroimaging. As I said during my Lundbeck interview, my goal is to build tools that will help Danish clinicians ask better, more mechanistic questions about how symptoms of mental illness arise and that is exactly what we will do!
If any of the above sounds exciting to you, please get in touch! The ECG will be hiring a variety of positions at Aarhus University and Cambridge Psychiatry, including graduate RAs, PhD students, and post-docs! We launch February 2019 – so send us an email as soon as possible! You can read more about our recruitment here and here. We’re looking for ambitious, talented young trainees who want to get in on the ground floor of embodied computational neuroscience and psychiatry. Further, if you would like to collaborate with the ECG, please watch this space. As the project develops we’ll be creating a comprehensive Github repository for all of our code, models, and tasks. This will not only ensure we’re following a fully transparent research ethos, but also facilitate collaboration and communication with our colleagues around the world. We’re excited to build a fully open approach to understanding the embodied mind and its disruption in mental illness.
I’d be remiss if I didn’t take some time here to thank all the amazing friends, family, and colleagues who made this possible. As many of you know, the past two years have been a difficult time for me. In general, the transition from postdoc to ECR is never an easy one. Grant writing and interviewing is a gruelling process and I could not have made it to this point without the unfailing support of my social network. First and foremost, I must thank my amazing wife and ever-present collaborator, Francesca Fardo. Francesca dedicated countless hours to help me formulate the ideas that form the core of the Visceral Mind Project, to endlessly rehearse my interview pitch and preparation, and most importantly, to keeping me sane through all the trials and tribulations. She’s amazing, and I look forward to helping her build her own research group whom will undoubtably become the ECG’s closest collaborators. I must also thank my Grandmother Sharon Allen; my guardian angel who rescued me from hell and made me everything that I am today. Thanks Dad for shaping me into a hardworking and independent person. Thanks to my cousins Marissa and Corey; I’m so proud of you and the great things you’ve already accomplished the things you have yet to do – thanks for being the best siblings I could ever ask for. Thanks to all of our Italian family in Marostica – especially my mother in law Mirella for keeping me fed and warm over so many family vacations. Thanks to our Danish friends for teaching us the real meaning of hygge and making Denmark a warmer place for us.
Thanks to Shaun Gallagher and Andreas Roepstorff, my unfailing mentors who recognized my potential when no one else would and gave me every opportunity to become the scientist I am today. You discovered and nurtured me when it mattered most. Warm thanks to Chris and Uta Frith, for your mentorship and friendship. Thanks to Leif Ostergaard, my mentor for this project – thanks for all your help and for so warmly welcoming me back to CFIN. Thanks to Simon Jeppe Berg who worked tirelessly to help me prepare these grants – even working late in the evening when we were on vacation in California! And thanks to Jorgen Frokiaer for your support and guidance in establishing my group at the department of clinical medicine! Thanks to everyone at Interacting Minds and CFIN – I know we’re going to do some awesome research together!
In the UK – thanks to Tobias Hauser; we’ve come a long way buddy and I couldn’t have done this without your friendship and collaboration. Thanks to Geraint Rees and Karl Friston, whose mentorship and supervision enabled me to branch out and take the risks I needed to take to reach full independence. Thanks to everyone at the FIL and ICN who made me such a better scientist and person, and who made my years in London awesome – you know who you are. Thanks to Paul Fletcher for sharing and amplifying my vision for an embodied approach to computational psychiatry. Thanks to Ray Dolan and Klaas Enno Stephan for your support and guidance of this project! And thanks to all my friends, colleagues, and collaborators who have helped me reach this point!
Thank all of you in the neuroscience hivemind who have encouraged, challenged, and supported my development as a scientist. This win is yours too.
Thanks Mom – I wish you could see this.
Micah Allen – Associate Professor, AIAS & Lundbeck Fellow, and Visiting Senior Research Fellow at Cambridge Psychiatry.