Fundamentally rethinking what a mind is and how a brain works.

The February Issue of Trends in Cognitive Science has an open source Opinions article from Lisa Feldman Barrett and collaborators that suggests that new research approaches grounded in different ontological commitments will be required to properly describe brain-behavior relationships. Here is a clip of the introductory text and a graphic clip from the article. Finally, I pass on the concluding remarks on fundamentally rethinking what a mind is and how a brain works.

Most brain imaging studies present stimuli and measure behavioral responses in temporal units (trials) that are ordered randomly. Participants’ brain signals are typically aggregated to model structured variation that allows inferences about the broader population from which people were sampled. These methodological details, when used to study any phenomenon of interest, often give rise to brain-behavior findings that vary unexpectedly (across stimuli, context, and people). Such findings are typically interpreted as replication failures, with the observed variation discounted as error caused by less than rigorous experimentation (Box 1). Methodological rigor is of course important, but replication problems may stem, in part, from a more pernicious source: faulty assumptions (i.e., ontological commitments) that mis-specify the psychological phenomena of interest.

In this paper, we review three questionable assumptions whose reconsideration may offer opportunities for a more robust and replicable science: 

 (1) The localization assumption: the instances that constitute a category of psychological events (e.g., instances of fear) are assumed to be caused by a single, dedicated psychological process implemented in a dedicated neural ensemble (see Glossary). 

 (2) The one-to-one assumption: the dedicated neural ensemble is assumed to map uniquely to that psychological category, such that the mapping generalizes across contexts, people, measurement strategies, and experimental designs. 

 (3) The independence assumption: the dedicated neural ensemble is thought to function independently of contextual factors, such as the rest of the brain, the body, and the surrounding world, so the ensemble can be studied alone without concern for those other factors. Contextual factors might moderate activity in the neural ensemble but should not fundamentally change its mapping to the instances of a psychological category. 

 These three assumptions are rooted in a typological view of the mind, brain, and behavior [1. ] that was modeled on 19th century physics and continues to guide experimental practices in much of brain-behavior research to the present day. In this paper, we have curated examples from studies of human functional magnetic resonance imaging (fMRI) and neuroscience research using non-human animals that call each assumption into question. We then sketch the beginnings of an alternative approach to study brain-behavior relationships, grounded in different ontological commitments: (i) a mental event comprises distributed activity across the whole brain; (ii) brain and behavior are linked by degenerate (i.e., many-to-one) mappings; and (iii) mental events emerge as a complex ensemble of weak, nonlinearly interacting signals from the brain, body, and external world.

 

Concluding remarks

Scientific communities tacitly agree on assumptions about what exists (called ontological commitments), what questions to ask, and what methods to use. All assumptions are firmly rooted in a philosophy of science that need not be acknowledged or discussed but is practiced nonetheless. In this article, we questioned the ontological commitments of a philosophy of science that undergirds much of modern neuroscience research and psychological science in particular. We demonstrated that three common commitments should be reconsidered, along with a corresponding course correction in methods. Our suggestions require more than merely improved methodological rigor for traditional experimental design. Such improvements are important, but may aid robustness and replicability only when the ontological assumptions behind those methods are valid. Accordingly, a productive way forward may be to fundamentally rethink what a mind is and how a brain works. We have suggested that mental events arise from a complex ensemble of signals across the entire brain, as well as the from the sensory surfaces of the body that inform on the states of the inner body and outside world, such that more than one signal ensemble maps to a single instance of a single psychological category (maybe even in the same context. To this end, scientists might find inspiration by mining insights from adjacent fields, such as evolution, anatomy, development, and ecology , as well as cybernetics and systems theory. At stake is nothing less than a viable science of how a brain creates a mind through its constant interactions with its body, its physical environment, and with the other brains-in-bodies that occupy its social world.

Sadder but Wiser? Maybe Not.

It looks like another universally accepted result of psychological research may be wrong - that depressed people have a more accurate reading of their ability to affect outcomes. Barry points to work by Dev et al. that fails to replicate experiments of Alloy and Abramson done 43 years ago that led to the hypothesis of “depressive realism,” that depressed people having a more realistic view of their conditions because they are free of the optimistic bias of their cheerful peers. The new research was unable to find any association between depressive symptoms and outcome bias. While Barry's review notes debate over whether differences in the design of the older and newer experiments may account for the variance in results, there now is certainly less confidence in the original findings.

The brain chemistry underlying mental exhaustion.

Emily Underwood does a review of work by Wiehler et al. (open source) on the brain chemistry underlying mental fatigue, also describing several reservations expressed by other researchers. From her description:

The researchers divided 39 paid study participants into two groups, assigning one to a series of difficult cognitive tasks that were designed to induce mental exhaustion. In one, participants had to decide whether letters and numbers flashing on a computer screen in quick succession were green or red, uppercase or lowercase, and other variations. In another, volunteers had to remember whether a number matched one they’d seen three characters earlier...As the day dragged on, the researchers repeatedly measured cognitive fatigue by asking participants to make choices that required self-control—deciding to forgo cash that was immediately available so they could earn a larger amount later, for example. The group that had been assigned to more difficult tasks made about 10% more impulsive choices than the group with easier tasks, the researchers observed. At the same time, their glutamate levels rose by about 8% in the lateral prefrontal cortex—a pattern that did not show up in the other group...

Here is the Wiehler et al. abstract:  

Highlights

• Cognitive fatigue is explored with magnetic resonance spectroscopy during a workday 

• Hard cognitive work leads to glutamate accumulation in the lateral prefrontal cortex 

• The need for glutamate regulation reduces the control exerted over decision-making 

• Reduced control favors the choice of low-effort actions with short-term rewards

Summary

Behavioral activities that require control over automatic routines typically feel effortful and result in cognitive fatigue. Beyond subjective report, cognitive fatigue has been conceived as an inflated cost of cognitive control, objectified by more impulsive decisions. However, the origins of such control cost inflation with cognitive work are heavily debated. Here, we suggest a neuro-metabolic account: the cost would relate to the necessity of recycling potentially toxic substances accumulated during cognitive control exertion. We validated this account using magnetic resonance spectroscopy (MRS) to monitor brain metabolites throughout an approximate workday, during which two groups of participants performed either high-demand or low-demand cognitive control tasks, interleaved with economic decisions. Choice-related fatigue markers were only present in the high-demand group, with a reduction of pupil dilation during decision-making and a preference shift toward short-delay and little-effort options (a low-cost bias captured using computational modeling). At the end of the day, high-demand cognitive work resulted in higher glutamate concentration and glutamate/glutamine diffusion in a cognitive control brain region (lateral prefrontal cortex [lPFC]), relative to low-demand cognitive work and to a reference brain region (primary visual cortex [V1]). Taken together with previous fMRI data, these results support a neuro-metabolic model in which glutamate accumulation triggers a regulation mechanism that makes lPFC activation more costly, explaining why cognitive control is harder to mobilize after a strenuous workday.

Dissecting and improving motor skill acquisition in older adults

 From the introduction of Elvira et al. (open source):

We designed a study intended to identify (i) the main factors leading to differences in motor skill acquisition with aging and (ii) the effect of applying noninvasive brain stimulation during motor training. Comparing different components of motor skill acquisition in young and older adults, constituting the extremes of performance in this study, we found that the improvement of the sequence-tapping task is maximized by the early consolidation of the spatial properties of the sequence in memory (i.e., sequence order), leading to a reduced error of execution, and by the optimization of its temporal features (i.e., chunking). We found the consolidation of spatiotemporal features to occur early in training in young adults, suggesting the emergence of motor chunks to be a direct consequence of committing the sequence elements to memory. This process, seemingly less efficient in older adults, could be partially restored using atDCS by enabling the early consolidation of spatial features, allowing them to prioritize the increase of their speed of execution, ultimately leading to an earlier consolidation of motor chunks. This separate consolidation of spatial and temporal features seen in older adults suggests that the emergence of temporal patterns, commonly identified as motor chunks at a behavioral level, stem from the optimization of the execution of the motor sequence resulting from practice, which can occur only after the sequence order has been stored in memory.

Here is their abstract:

Practicing a previously unknown motor sequence often leads to the consolidation of motor chunks, which enable its accurate execution at increasing speeds. Recent imaging studies suggest the function of these structures to be more related to the encoding, storage, and retrieval of sequences rather than their sole execution. We found that optimal motor skill acquisition prioritizes the storage of the spatial features of the sequence in memory over its rapid execution early in training, as proposed by Hikosaka in 1999. This process, seemingly diminished in older adults, was partially restored by anodal transcranial direct current stimulation over the motor cortex, as shown by a sharp improvement in accuracy and an earlier yet gradual emergence of motor chunks. These results suggest that the emergence of motor chunks is preceded by the storage of the sequence in memory but is not its direct consequence; rather, these structures depend on, and result from, motor practice.

Motor learning without movement

Fascinating work from Kim et al. on the influence of the prediction errors that are essential in calibrating actions of our predictive minds:

Significance

Our brains control aspects of our movements without conscious awareness, allowing many of us to effortlessly pick up a glass of water or wave hello. Here, we demonstrate that this implicit motor system can learn to refine movements that we plan but ultimately decide not to perform. Participants planned to reach to a target but sometimes withheld these reaches while an animation simulated missing the target. Afterward, participants unknowingly reached opposite the direction of the apparent mistake, indicating that the implicit motor system had learned from the animated error. These findings indicate that movement is not strictly necessary for motor adaptation, and we can learn to update our actions without physically performing them.

Abstract

Prediction errors guide many forms of learning, providing teaching signals that help us improve our performance. Implicit motor adaptation, for instance, is thought to be driven by sensory prediction errors (SPEs), which occur when the expected and observed consequences of a movement differ. Traditionally, SPE computation is thought to require movement execution. However, recent work suggesting that the brain can generate sensory predictions based on motor imagery or planning alone calls this assumption into question. Here, by measuring implicit motor adaptation during a visuomotor task, we tested whether motor planning and well-timed sensory feedback are sufficient for adaptation. Human participants were cued to reach to a target and were, on a subset of trials, rapidly cued to withhold these movements. Errors displayed both on trials with and without movements induced single-trial adaptation. Learning following trials without movements persisted even when movement trials had never been paired with errors and when the direction of movement and sensory feedback trajectories were decoupled. These observations indicate that the brain can compute errors that drive implicit adaptation without generating overt movements, leading to the adaptation of motor commands that are not overtly produced.

Efficiently irrational: deciphering the riddle of human choice

Highlights of an open source article from Paul Glimcher:

A central question for decision-making scholars is: why are humans and animals so predictably inconsistent in their choices? In the language of economics, why are they irrational?

Data suggest that this reflects an optimal trade-off between the precision with which the brain represents the values of choices and the biological costs of that precision. Increasing representational precision may improve choice consistency, but the metabolic cost of increased precision is significant.

Given the cost of precision, the brain might use efficient value-encoding mechanisms that maximize informational content. Mathematical analyses suggest that a mechanism called divisive normalization approximates maximal efficiency per action potential in decision systems.

Behavioral studies appear to validate this claim. Inconsistencies produced by decision-makers can be well modeled as the byproduct of efficient divisive normalization mechanisms that maximize information while minimizing metabolic costs.

Testerone production in adult men is regulated by an adolescent period sensitive to family experiences.

 From Gettler et al.:

Significance

Testosterone influences how animals devote energy and time toward reproduction, including opposing demands of mating and competition versus parenting. Reflecting this, testosterone often declines in new fathers and lower testosterone is linked to greater caregiving. Given these roles, there is strong interest in factors that affect testosterone, including early-life experiences. In this multidecade study, Filipino sons whose fathers were present and involved with raising them when they were adolescents had lower testosterone when they later became fathers, compared to sons whose fathers were present but uninvolved or were not coresident. Sons’ own parenting behaviors did not explain these patterns. These results connect key social experiences during adolescence to adult testosterone, and point to possible intergenerational effects of parenting style.

Abstract

Across vertebrates, testosterone is an important mediator of reproductive trade-offs, shaping how energy and time are devoted to parenting versus mating/competition. Based on early environments, organisms often calibrate adult hormone production to adjust reproductive strategies. For example, favorable early nutrition predicts higher adult male testosterone in humans, and animal models show that developmental social environments can affect adult testosterone. In humans, fathers’ testosterone often declines with caregiving, yet these patterns vary within and across populations. This may partially trace to early social environments, including caregiving styles and family relationships, which could have formative effects on testosterone production and parenting behaviors. Using data from a multidecade study in the Philippines (n = 966), we tested whether sons’ developmental experiences with their fathers predicted their adult testosterone profiles, including after they became fathers themselves. Sons had lower testosterone as parents if their own fathers lived with them and were involved in childcare during adolescence. We also found a contributing role for adolescent father–son relationships: sons had lower waking testosterone, before and after becoming fathers, if they credited their own fathers with their upbringing and resided with them as adolescents. These findings were not accounted for by the sons’ own parenting and partnering behaviors, which could influence their testosterone. These effects were limited to adolescence: sons’ infancy or childhood experiences did not predict their testosterone as fathers. Our findings link adolescent family experiences to adult testosterone, pointing to a potential pathway related to the intergenerational transmission of biological and behavioral components of reproductive strategies.

Our brains store concepts as sensory-motor and affective information

Fascinating work from Fernandino et al., who show that concept representations are not independent of sensory-motor experience: 

Significance

The ability to identify individual objects or events as members of a kind (e.g., “knife,” “dog,” or “party”) is a fundamental aspect of human cognition. It allows us to quickly access a wealth of information pertaining to a newly encountered object or event and use it to guide our behavior. How is this information represented in the brain? We used functional MRI to analyze patterns of brain activity corresponding to hundreds of familiar concepts and quantitatively characterized the informational structure of these patterns. Our results indicate that conceptual knowledge is stored as patterns of neural activity that encode sensory-motor and affective information about each concept, contrary to the long-held idea that concept representations are independent of sensory-motor experience.

Abstract

The nature of the representational code underlying conceptual knowledge remains a major unsolved problem in cognitive neuroscience. We assessed the extent to which different representational systems contribute to the instantiation of lexical concepts in high-level, heteromodal cortical areas previously associated with semantic cognition. We found that lexical semantic information can be reliably decoded from a wide range of heteromodal cortical areas in the frontal, parietal, and temporal cortex. In most of these areas, we found a striking advantage for experience-based representational structures (i.e., encoding information about sensory-motor, affective, and other features of phenomenal experience), with little evidence for independent taxonomic or distributional organization. These results were found independently for object and event concepts. Our findings indicate that concept representations in the heteromodal cortex are based, at least in part, on experiential information. They also reveal that, in most heteromodal areas, event concepts have more heterogeneous representations (i.e., they are more easily decodable) than object concepts and that other areas beyond the traditional “semantic hubs” contribute to semantic cognition, particularly the posterior cingulate gyrus and the precuneus.

Attention and executive functions - improvements and declines with ageing.

From Verissimo et al.:

Many but not all cognitive abilities decline during ageing. Some even improve due to lifelong experience. The critical capacities of attention and executive functions have been widely posited to decline. However, these capacities are composed of multiple components, so multifaceted ageing outcomes might be expected. Indeed, prior findings suggest that whereas certain attention/executive functions clearly decline, others do not, with hints that some might even improve. We tested ageing effects on the alerting, orienting and executive (inhibitory) networks posited by Posner and Petersen’s influential theory of attention, in a cross-sectional study of a large sample (N = 702) of participants aged 58–98. Linear and nonlinear analyses revealed that whereas the efficiency of the alerting network decreased with age, orienting and executive inhibitory efficiency increased, at least until the mid-to-late 70s. Sensitivity analyses indicated that the patterns were robust. The results suggest variability in age-related changes across attention/executive functions, with some declining while others improve.

Our brains have multiple representations of the same body part.

Here is a neat finding. Remember your elementary biology textbook picture of the homunculi in our somatosensory and motor cortices? The small human figure spread across the surface of the brain, with a cortical location for each part of the hand or other body part? Matsumiya shows that when we direct our eye and hand movements to the same body part these two movements are found to be guided by different body maps! Here is his abstract:  

Significance

Accurate motor control depends on maps of the body in the brain, called the body schema. Disorders of the body schema cause motor deficits. Although we often execute actions with different motor systems such as the eye and hand, how the body schema operates during such actions is unknown. In this study, participants simultaneously directed eye and hand movements to the same body part. These two movements were found to be guided by different body maps. This finding demonstrates multiple motor system–specific representations of the body schema, suggesting that the choice of motor system toward one’s body can determine which of the brain’s body maps is observed. This may offer a new way to visualize patients’ body schema.

Abstract

Purposeful motor actions depend on the brain’s representation of the body, called the body schema, and disorders of the body schema have been reported to show motor deficits. The body schema has been assumed for almost a century to be a common body representation supporting all types of motor actions, and previous studies have considered only a single motor action. Although we often execute multiple motor actions, how the body schema operates during such actions is unknown. To address this issue, I developed a technique to measure the body schema during multiple motor actions. Participants made simultaneous eye and reach movements to the same location of 10 landmarks on their hand. By analyzing the internal configuration of the locations of these points for each of the eye and reach movements, I produced maps of the mental representation of hand shape. Despite these two movements being simultaneously directed to the same bodily location, the resulting hand map (i.e., a part of the body schema) was much more distorted for reach movements than for eye movements. Furthermore, the weighting of visual and proprioceptive bodily cues to build up this part of the body schema differed for each effector. These results demonstrate that the body schema is organized as multiple effector-specific body representations. I propose that the choice of effector toward one’s body can determine which body representation in the brain is observed and that this visualization approach may offer a new way to understand patients’ body schema.

Higher performance and fronto-parietal brain activity following active versus passive learning

From a brief open source PNAS report by Stillesjö et al. that has a nice graphic of the fMRI data supporting their observations:

We here demonstrate common neurocognitive long-term memory effects of active learning that generalize over course subjects (mathematics and vocabulary) by the use of fMRI. One week after active learning, relative to more passive learning, performance and fronto-parietal brain activity was significantly higher during retesting, possibly related to the formation and reactivation of semantic representations. These observations indicate that active learning conditions stimulate common processes that become part of the representations and can be reactivated during retrieval to support performance. Our findings are of broad interest and educational significance related to the emerging consensus of active learning as critical in promoting good long-term retention.

Coevolution of tool use and language - shared syntactic processes and basal ganglia substrates

Thibault et al. show that tool use and language share syntactic processes. Functional magnetic resonance imaging reveals that tool use and syntax in language elicit similar patterns of brain activation within the basal ganglia. This indicates common neural resources for the two abilities. Indeed, learning transfer occurs across the two domains: Tool-use motor training improves syntactic processing in language and, reciprocally, linguistic training with syntactic structures improves tool use. Here is their entire structured abstract:   

INTRODUCTION

Tool use is a hallmark of human evolution. Beyond its sensorimotor components, the complexity of which has been extensively investigated, tool use affects cognition from a different perspective. Indeed, tool use requires integrating an external object as a body part and embedding its functional structure in the motor program. This adds a hierarchical level into the motor plan of manual actions, subtly modifying the relationship between interdependent subcomponents. Embedded structures also exist in language, and syntax is the cognitive function handling these linguistic hierarchies. One example is center-embedded object-relative clauses: “The poet [that the scientist admires] reads the paper.” Accordingly, researchers have advanced a role for syntax in action and the existence of similarities between the processes underlying tool use and language, so that shared neural resources for a common cognitive function could be at stake.

RATIONALE

We first tested the existence of shared neural substrates for tool use and syntax in language. Second, we tested the prediction that training one ability should affect performance in the other. In a first experiment, we measured participants’ brain activity with functional magnetic resonance imaging during tool use or, as a control, manual actions. In separate runs, the same participants performed a linguistic task on complex syntactic structures. We looked for common activations between tool use and the linguistic task, predicting similar patterns of activity if they rely on common neural resources. In further behavioral experiments, we tested whether motor training with the tool selectively improves syntactic performance in language and if syntactic training in language, in turn, selectively improves motor performance with the tool.

RESULTS

Tool-use planning and complex syntax processing (i.e., object relatives) elicited neural activity anatomically colocalized within the basal ganglia. A control experiment ruled out verbal working memory and manual (i.e., without a tool) control processes as an underlying component of this overlap. Multivariate analyses revealed similar spatial distributions of neural patterns prompted by tool-use planning and object-relative processing. This agrees with the recruitment of the same neural resources by both abilities and with the existence of a supramodal syntactic function. The shared neurofunctional resources were moreover reflected behaviorally by cross-domain learning transfer. Indeed, tool-use training significantly improved linguistic performance with complex syntactic structures. No learning transfer was observed on language syntactic abilities if participants trained without the tool. The reverse was also true: Syntactic training with complex sentences improved motor performance with the tool more than motor performance in a task without the tool and matched for sensorimotor difficulty. No learning transfer was observed on tool use if participants trained with simpler syntactic structures in language.

CONCLUSION

These findings reveal the existence of a supramodal syntactic function that is shared between language and motor processes. As a consequence, training tool-use abilities improves linguistic syntax and, reciprocally, training linguistic syntax abilities improves tool use. The neural mechanisms allowing for boosting performance in one domain by training syntax in the other may involve priming processes through preactivation of common neural resources, as well as short-term plasticity within the shared network. Our findings point to the basal ganglia as the neural site of supramodal syntax that handles embedded structures in either domain and also support longstanding theories of the coevolution of tool use and language in humans.

Precision and the Bayesian brain

I've been studying and trying to understand the new prevailing model of how our brains work that is emerging - the brain as a Baysean predictive processing machine that compares its prior knowledge with incoming evidence of its correctness. If a mis-match occurs that might suggest alterning a prior expectation, the precision of the incoming evidence is very important. In a recent issue of Current Biology Yon and Frith offer a very simple and lucid primer (open source) on what precision is how it influences adrenergic and dopaminergic neuromodulatory systems to alter the synaptic gain afforded to top-down predictions and bottom-up evidence.:

Scientific thinking about the minds of humans and other animals has been transformed by the idea that the brain is Bayesian. A cornerstone of this idea is that agents set the balance between prior knowledge and incoming evidence based on how reliable or ‘precise’ these different sources of information are — lending the most weight to that which is most reliable. This concept of precision has crept into several branches of cognitive science and is a lynchpin of emerging ideas in computational psychiatry — where unusual beliefs or experiences are explained as abnormalities in how the brain estimates precision. But what precisely is precision? In this Primer we explain how precision has found its way into classic and contemporary models of perception, learning, self-awareness, and social interaction. We also chart how ideas around precision are beginning to change in radical ways, meaning we must get more precise about how precision works.

You Are Not Who You Think You Are

I want to point to the NYTimes piece by polymath David Brooks that does a nice summary of several themes that have been emphasized in MindBlog posts - on the recent work of Barrett, Friston, Hoffman, Johnson, and others. He touches on several areas in which our understanding of how our minds work has been completely transformed by work and ideas over just the past 10 years. I suggest you read the whole article and click on links to the articles he references. Here are a few clips:

You may think you understand the difference between seeing something and imagining it. When you see something, it’s really there; when you imagine it, you make it up. That feels very different...It turns out, reality and imagination are completely intermixed in our brain...the separation between our inner world and the outside world is not as clear as we might like to think.

...most of seeing is making mental predictions about what you expect to see, based on experience, and then using sensory input to check and adjust your predictions. Thus, your memory profoundly influences what you see...The conversation between senses and memory produces a “controlled hallucination,” which is the closest we can get to registering reality.

...humans have come up with all sorts of concepts to describe different thinking activities: memory, perception, emotion, attention, decision-making. But now, as scientists develop greater abilities to look at the brain doing its thing, they often find that the activity they observe does not fit the neat categories our culture has created, and which we rely on to understand ourselves...Barrett of Northeastern University argues that people construct emotions and thoughts, and there is no clear distinction between them...emotions assign value to things, so they are instrumental to reason, not separate from or opposed to it.

...there is no such thing as disembodied understanding. Your neural, chemical and bodily responses are in continual conversation with one another, so both understanding and experiencing are mental and physical simultaneously...When faced with a whole person...we shouldn’t think that they can be divided into a ‘mind’ and a ‘body.

...You realize that neither the term ‘decision-making’ nor the term ‘attention’ actually corresponds to a thing in the brain...the concepts at the core of how we think about thinking need to be radically revised...neuroscientists spent a lot of time trying to figure out what region of the brain did what function. (Fear is in the amygdala!) Today they also look at the ways vast networks across the brain, body and environment work together to create comprehensive mental states. Now there is much more emphasis on how people and groups creatively construct their own realities, and live within their own constructions.

Graphic depictions of an integrative model of mind

To hopefully enhance the chance that you will pay attention to the creative and seminal thinking in the open source Laukkonen and Slagter review article whose abstract I passed on in my July 21 post,  I now pass on their striking concluding statement and then  two graphics whose legends summarize the main ideas presented. I think this work offers a plausible and appealing integration of neuroscience and meditative traditions.  

We have taken on the daunting task of providing a theory for understanding the effects of meditation within the predictive processing framework. Contemplative science is a young field and predictive processing is a new theory, although both have roots going much farther back. All theories are subject to change, but perhaps particularly so for such new domains of enquiry. Nevertheless, we think the conditions are suitable for a more overarching theory that may also thwart further siloing and fragmentation of scientific research, as has been commonplace among the mind-sciences. A strength of our framework is its simplicity: Being in the here and now reduces predictive processing. And yet, this basic idea can explain how each meditation technique uniquely deconstructs the minds tendency to project the past onto the present, how certain insights may arise, the nature of hierarchical self-processing, and the plasticity of the human mind. There is scope here, we think, to eventually reveal what makes a meditator an expert, why meditation has such broad clinical effects, and how we might begin mitigating some of the negative consequences of meditation. Last but not least, our framework seems to bring ancient Eastern and modern scientific ideas closer together, showing how the notion of conditioned experience in Buddhism aligns with the notion of the experience-dependent predictive brain.

Fig. 1. Here we use the Pythagoras Tree to provide an intuitive illustration of how organisms represent the world with increasing counterfactual depth or abstraction. The tree is constructed using squares that are scaled down by the square root of 2 divided by 2 and placed such that the corners of the squares meet and form a triangle between them, recursively. Analogously, the brain constructs experience from temporally precise and unimodal models of present-moment sensory representations and input (e.g., pixels on a screen), into ever more abstract, transmodal, and temporally deep models (e.g., a theory paper). Meditation brings one increasingly into the present moment, thus reducing the tendency to conceptualize away from the here and now, akin to observing the pixels rather than the words. This reduction of conceptualization ought to also have profound effects on the sense of self, which also relies on abstract model building, and ultimately is said to reveal an underlying seemingly “unconditioned” state of consciousness as such (like the white background underlying the pixels).

 

Fig. 2. In this schematic we illustrate two aspects of the many-to-(n)one model. The first and most foundational proposal is that meditation gradually flattens the predictive hierarchy or ‘prunes the counterfactual tree’, by bringing the meditator into the here and now, illustrated in the left figure. Thus, meditative depth is defined by the extent that the organism is not constructing temporally thick predictions. In the right figure, we dissect the predictive hierarchy into three broad levels. We propose that thinking (and therefore the narrative self [NS]) sits at the top of the predictive hierarchy (Carhart-Harris and Friston, 2010, 2019). Sensing and perceiving and therefore the embodied experiencing self [ES] sits below it (Gallagher, 2000; Seth, 2013). Finally, a basal form of self-hood characterized by the subject-object [S/O] duality sits at the earliest level. FA brings the practitioner out of the narrative self and into a more experiencing and embodied mode of being. Then, through dereification from present moment experience (including bodily sensations) OM brings the practitioner more into a state where contents of experience are treated equally, and one is able to experience non-judgmentally (sensing without appraisal), but even in very advanced states, a subject-object duality remains. During OM, certain epistemic discoveries or insights about the nature and behavior of generative models may occur. Finally, through ND practices the subject-object distinction may fall away and the background or “groundless ground” of all experience—awareness itself—can be uncovered. Another way to characterize this process is as follows: FA employs regular (conditional) attention to an object of sensing, OM employs bare (unconditional) attention, and ND practice employs reflexive awareness that permits the non-dual witnessing of the subject-object dichotomy and finally pure or non-dual awareness by releasing attention altogether.

 

 

From many to (n)one: Meditation and the plasticity of the predictive mind

I had a chat with my former University of Wisconsin colleague Richard Davidson during my visit to Madison, WI last week, and he pointed me to an excellent open source review article by Laukkonen and Slagter, From many to (n)one: Meditation and the plasticity of the predictive mind. They offer an integrated predictive processing account of three main styles of meditation. I just finished reading through their lucid account and plan to carefully re-read it several times. I pass on the summary points and abstract: 

Highlights

• Predictive processing provides a novel theoretical window on meditation. 

• Deconstructive meditations progressively reduce temporally deep processing. 

• Insight experiences arise during meditation due to Bayesian model reduction 

• Meditation deconstructs self models by reducing abstract processing. 

• Non-dual awareness or pure consciousness is the ‘here and now’.

Abstract

How profoundly can humans change their own minds? In this paper we offer a unifying account of deconstructive meditation under the predictive processing view. We start from simple axioms. First, the brain makes predictions based on past experience, both phylogenetic and ontogenetic. Second, deconstructive meditation brings one closer to the here and now by disengaging anticipatory processes. We propose that practicing meditation therefore gradually reduces counterfactual temporally deep cognition, until all conceptual processing falls away, unveiling a state of pure awareness. Our account also places three main styles of meditation (focused attention, open monitoring, and non-dual) on a single continuum, where each technique relinquishes increasingly engrained habits of prediction, including the predicted self. This deconstruction can also permit certain insights by making the above processes available to introspection. Our framework is consistent with the state of empirical and (neuro)phenomenological evidence and illuminates the top-down plasticity of the predictive mind. Experimental rigor, neurophenomenology, and no-report paradigms are needed to further understanding of how meditation affects predictive processing and the self.

Watching a brain encode present, past, and future….

We all exist as an ongoing simulation of past, present, and future in our brains, with the hallucination we take to be reality being perturbed only when our brains’ expectations are not met. Dotson and Yartsev do experiments in flying bats (of a sort not permitted in humans) that record from the hippocampus showing patterns of neuron activity of the sort needed to support this process. They find that this activity not only encodes the bat’s present location but also signals its positions in the past and future. The technology involved in doing the brain implants that record and wirelessly transmit the neuronal activity, as well as the sophisticated data analysis, is truly awesome (One has to download a massive technical supplement, much too large to include in the article, to get the details.) Here I pass on only the editor’s summary and the abstract for the article:  

Representing space in past and future

As an organism moves through space, its brain has to remember its most recent location and anticipate its future position, not just its current place in the world. Earlier studies reported so-called retrospective and prospective place coding in rats while they were running along linear tracks. However, it would be advantageous to study an animal that rapidly moves through three-dimensional space with high precision. Dotson and Yartsev recorded from flying bats to investigate whether place cell activity in hippocampus area CA1 represents local (current) or nonlocal positions. They discovered that the hippocampus not only encodes the bat's present location but also signals its positions in the past and future.

Abstract

Navigation occurs through a continuum of space and time. The hippocampus is known to encode the immediate position of moving animals. However, active navigation, especially at high speeds, may require representing navigational information beyond the present moment. Using wireless electrophysiological recordings in freely flying bats, we demonstrate that neural activity in area CA1 predominantly encodes nonlocal spatial information up to meters away from the bat’s present position. This spatiotemporal representation extends both forward and backward in time, with an emphasis on future locations, and is found during both random exploration and goal-directed navigation. The representation of position thus extends along a continuum, with each moment containing information about past, present, and future, and may provide a key mechanism for navigating along self-selected and remembered paths.

Coffee is good for you, mostly....

I am dysfunctional on waking every morning until I have had a strong cup of coffee, a personal experience that makes me want to pass on Jane Brody's nice review of studies showing that drinking coffee reduces risk of all kinds of ailments, including Parkinson’s disease, melanoma, prostate cancer, even suicide.

...in numerous studies conducted throughout the world, consuming four or five eight-ounce cups of coffee (or about 400 milligrams of caffeine) a day has been associated with reduced death rates.

But,

..coffee doesn't warrant a totally clean bill of health...The most common ill effect associated with caffeinated coffee is sleep disturbance...People vary widely in how rapidly they metabolize caffeine, enabling some to sleep soundly after drinking caffeinated coffee at dinner while others have trouble sleeping if they have coffee at lunch. But even if you can fall asleep readily after an evening coffee, it may disrupt your ability to get adequate deep sleep, Mr. Pollan states in his forthcoming book, “This Is Your Mind on Plants.”

Caffeine is one of more than a thousand chemicals in coffee, not all of which are beneficial. Among others with positive effects are polyphenols and antioxidants. Polyphenols can inhibit the growth of cancer cells and lower the risk of Type 2 diabetes; antioxidants, which have anti-inflammatory effects, can counter both heart disease and cancer, the nation’s leading killers.

Decision-making ability, psychopathology, and brain connectivity

An open access review offered by Dolan and his colleagues continues the story of correlating our human competencies with our brain structures. They describe

...a new cognitive construct—decision acuity—that captures global decision-making ability. High decision acuity prominently reflected low decision variability. Decision acuity showed acceptable reliability, increased with age, and was associated with mental health symptoms independently of intelligence. Crucially, it was associated with distinctive resting-state networks, in particular in brain regions typically engaged by decision-making tasks. The association between decision acuity and functional connectivity was temporally stable and distinct from that of IQ.

Highlights

• Young people have a general decision-making ability, which we call “decision acuity” 

• Decision acuity is reflected in how strongly connected certain brain networks are 

• Low decision acuity is associated with general social function psychopathology

Summary

Decision-making is a cognitive process of central importance for the quality of our lives. Here, we ask whether a common factor underpins our diverse decision-making abilities. We obtained 32 decision-making measures from 830 young people and identified a common factor that we call “decision acuity,” which was distinct from IQ and reflected a generic decision-making ability. Decision acuity was decreased in those with aberrant thinking and low general social functioning. Crucially, decision acuity and IQ had dissociable brain signatures, in terms of their associated neural networks of resting-state functional connectivity. Decision acuity was reliably measured, and its relationship with functional connectivity was also stable when measured in the same individuals 18 months later. Thus, our behavioral and brain data identify a new cognitive construct that underpins decision-making ability across multiple domains. This construct may be important for understanding mental health, particularly regarding poor social function and aberrant thought patterns.

Our 'Self' extends vastly beyond our brain.

I want to pass on two interesting articles that review how the self we usually take to be largely inside our heads (somewhere behind the eyes) in fact has meaning only in contexts that extend vastly beyond the little grey cells in our cranium. Annie Murphy Paul notes four basic extensions that let our brains be less workhorse, and more orchestra conductor.

...the first and most obvious being our tools. Technology is designed to fulfill just this function — who remembers telephone numbers anymore, now that our smartphones can supply them?

Our external memory stores have evolved from marks on clay tablets through printed books to bytes stored in the cloud. 

A second resource is our bodies:

The burgeoning field of embodied cognition has demonstrated that the body — its sensations, gestures and movements — plays an integral role in the thought processes that we usually locate above the neck. The body is especially adept at alerting us to patterns of events and experience, patterns that are too complex to be held in the conscious mind. When a scenario we encountered before crops up again, the body gives us a nudge: communicating with a shiver or a sigh, a quickening of the breath or a tensing of the muscles. Those who are attuned to such cues can use them to make more-informed decisions. A study led by a team of economists and neuroscientists in Britain, for instance, reported that financial traders who were better at detecting their heartbeats — a standard test of what is known as interoception, or the ability to perceive internal signals — made more profitable investments and lasted longer in that notoriously volatile profession.

This second extension is the subject of the other article I want to mention, in which Emily Underwood does a review of communication between the brain and other organs, mediated by the vagus nerve, that shapes how we think, remember, and feel (not open source, but motivated readers can obtain a copy by emailing me).

Scientists are unraveling how our organs talk to the brain and how the brain talks back. That two-way communication, known as interoception, encompasses a complex system of nerves and hormones, including the vagus nerve, a massive network of fibers that travel from nearly every internal organ to the base of the brain and back again. Scientist have long known the vagus nerve carries signals between the organs and the brainstem. But new studies show signals carried by the vagus climb beyond the brainstem and into brain regions involved in memory, emotion, and decision-making. The research is challenging traditional distinctions between disorders of the brain and body, and may even hold clues to the nature of consciousness.

Now, back to Paul's article, and her third extension of our brain:

Another extraneural resource available for our use is physical space. Moving mental contents out of our heads and onto the space of a sketch pad or whiteboard allows us to inspect it with our senses, a cognitive bonus that the psychologist Daniel Reisberg calls “the detachment gain.”...Three-dimensional space offers additional opportunities for offloading mental work and enhancing the brain’s powers. When we turn a problem to be solved into a physical object that we can interact with, we activate the robust spatial abilities that allow us to navigate through real-world landscapes. This suite of human strengths, honed over eons of evolution, is wasted when we sit still and think.

A fourth extension of our minds...

...can be found in other people’s minds. We are fundamentally social creatures, oriented toward thinking with others. Problems arise when we do our thinking alone — for example, the well-documented phenomenon of confirmation bias, which leads us to preferentially attend to information that supports the beliefs we already hold. According to the argumentative theory of reasoning, advanced by the cognitive scientists Hugo Mercier and Dan Sperber, this bias is accentuated when we reason in solitude. Humans’ evolved faculty for reasoning is not aimed at arriving at objective truth, Mercier and Sperber point out; it is aimed at defending our arguments and scrutinizing others’. It makes sense, they write, “for a cognitive mechanism aimed at justifying oneself and convincing others to be biased and lazy. The failures of the solitary reasoner follow from the use of reason in an ‘abnormal’ context’” — that is, a nonsocial one.

All four of these extraneural resources — technology, the body, physical space, social interaction — can be understood as mental extensions that allow the brain to accomplish far more than it could on its own. This is the theory of the extended mind, introduced more than two decades ago by the philosophers Andy Clark and David Chalmers. A 1998 article of theirs published in the journal Analysis began by posing a question that would seem to have an obvious answer: “Where does the mind stop and the rest of the world begin?” They went on to offer an unconventional response. The mind does not stop at the usual “boundaries of skin and skull,” they maintained. Rather, the mind extends into the world and augments the capacities of the biological brain with outside-the-brain resources.

Compared to the attention we lavish on the brain, we expend relatively little effort on cultivating our ability to think outside the brain...The limits of this approach have become painfully evident. The days when we could do it all in our heads are over. Our knowledge is too abundant, our expertise too specialized, our challenges too enormous. The best chance we have to thrive in the extraordinarily complex world we’ve created is to allow that world to assume some of our mental labor. Our brains can’t do it alone.