Highlights • A new view of emotion as active inference on the causes of interoceptive signals. • Extension of appraisal emotion theories to a contemporary inferential framework. • A unified ...predictive model of emotion and experience of body ownership. • Interpretation of neuropsychiatric conditions as disordered interoceptive inference. • How predictive integration of interoceptive and exteroceptive signals affects self.
Abstract
The Encyclopedia of DNA Elements (ENCODE) Data Coordinating Center has developed the ENCODE Portal database and website as the source for the data and metadata generated by the ENCODE ...Consortium. Two principles have motivated the design. First, experimental protocols, analytical procedures and the data themselves should be made publicly accessible through a coherent, web-based search and download interface. Second, the same interface should serve carefully curated metadata that record the provenance of the data and justify its interpretation in biological terms. Since its initial release in 2013 and in response to recommendations from consortium members and the wider community of scientists who use the Portal to access ENCODE data, the Portal has been regularly updated to better reflect these design principles. Here we report on these updates, including results from new experiments, uniformly-processed data from other projects, new visualization tools and more comprehensive metadata to describe experiments and analyses. Additionally, the Portal is now home to meta(data) from related projects including Genomics of Gene Regulation, Roadmap Epigenome Project, Model organism ENCODE (modENCODE) and modERN. The Portal now makes available over 13000 datasets and their accompanying metadata and can be accessed at: https://www.encodeproject.org/.
Modern psychology has long focused on the body as the basis of the self. Recently, predictive processing accounts of interoception (perception of the body ‘from within’) have become influential in ...accounting for experiences of body ownership and emotion. Here, we describe embodied selfhood in terms of ‘instrumental interoceptive inference’ that emphasises allostatic regulation and physiological integrity. We apply this approach to the distinctive phenomenology of embodied selfhood, accounting for its non-object-like character and subjective stability over time. Our perspective has implications for the development of selfhood and illuminates longstanding debates about relations between life and mind, implying, contrary to Descartes, that experiences of embodied selfhood arise because of, and not in spite of, our nature as ‘beast machines’.
We conceptualise experiences of embodied selfhood in terms of control-oriented predictive regulation (allostasis) of physiological states.
We account for distinctive phenomenological aspects of embodied selfhood, including its (partly) non-object-like nature and its subjective stability over time.
We explain predictive perception as a generalisation from a fundamental biological imperative to maintain physiological integrity: to stay alive.
We bring together several cognitive science traditions, including predictive processing, perceptual control theory, cybernetics, the free energy principle, and sensorimotor contingency theory.
We show how perception of the world around us, and of ourselves within it, happens with, through, and because of our living bodies.
We draw implications for developmental psychology and identify open questions in psychiatry and artificial intelligence.
Assessing directed functional connectivity from time series data is a key challenge in neuroscience. One approach to this problem leverages a combination of Granger causality analysis and network ...theory. This article describes a freely available MATLAB toolbox – ‘Granger causal connectivity analysis’ (GCCA) – which provides a core set of methods for performing this analysis on a variety of neuroscience data types including neuroelectric, neuromagnetic, functional MRI, and other neural signals. The toolbox includes core functions for Granger causality analysis of multivariate steady-state and event-related data, functions to preprocess data, assess statistical significance and validate results, and to compute and display network-level indices of causal connectivity including ‘causal density’ and ‘causal flow’. The toolbox is deliberately small, enabling its easy assimilation into the repertoire of researchers. It is however readily extensible given proficiency with the MATLAB language.
Active interoceptive inference and the emotional brain Seth, Anil K.; Friston, Karl J.
Philosophical transactions of the Royal Society of London. Series B. Biological sciences,
11/2016, Letnik:
371, Številka:
1708
Journal Article
Recenzirano
Odprti dostop
We review a recent shift in conceptions of interoception and its relationship to hierarchical inference in the brain. The notion of interoceptive inference means that bodily states are regulated by ...autonomic reflexes that are enslaved by descending predictions from deep generative models of our internal and external milieu. This re-conceptualization illuminates several issues in cognitive and clinical neuroscience with implications for experiences of selfhood and emotion. We first contextualize interoception in terms of active (Bayesian) inference in the brain, highlighting its enactivist (embodied) aspects. We then consider the key role of uncertainty or precision and how this might translate into neuromodulation. We next examine the implications for understanding the functional anatomy of the emotional brain, surveying recent observations on agranular cortex. Finally, we turn to theoretical issues, namely, the role of interoception in shaping a sense of embodied self and feelings. We will draw links between physiological homoeostasis and allostasis, early cybernetic ideas of predictive control and hierarchical generative models in predictive processing. The explanatory scope of interoceptive inference ranges from explanations for autism and depression, through to consciousness. We offer a brief survey of these exciting developments.
This article is part of the themed issue ‘Interoception beyond homeostasis: affect, cognition and mental health’.
Converging theories suggest that organisms learn and exploit probabilistic models of their environment. However, it remains unclear how such models can be learned in practice. The open-ended ...complexity of natural environments means that it is generally infeasible for organisms to model their environment comprehensively. Alternatively, action-oriented models attempt to encode a parsimonious representation of adaptive agent-environment interactions. One approach to learning action-oriented models is to learn online in the presence of goal-directed behaviours. This constrains an agent to behaviourally relevant trajectories, reducing the diversity of the data a model need account for. Unfortunately, this approach can cause models to prematurely converge to sub-optimal solutions, through a process we refer to as a bad-bootstrap. Here, we exploit the normative framework of active inference to show that efficient action-oriented models can be learned by balancing goal-oriented and epistemic (information-seeking) behaviours in a principled manner. We illustrate our approach using a simple agent-based model of bacterial chemotaxis. We first demonstrate that learning via goal-directed behaviour indeed constrains models to behaviorally relevant aspects of the environment, but that this approach is prone to sub-optimal convergence. We then demonstrate that epistemic behaviours facilitate the construction of accurate and comprehensive models, but that these models are not tailored to any specific behavioural niche and are therefore less efficient in their use of data. Finally, we show that active inference agents learn models that are parsimonious, tailored to action, and which avoid bad bootstraps and sub-optimal convergence. Critically, our results indicate that models learned through active inference can support adaptive behaviour in spite of, and indeed because of, their departure from veridical representations of the environment. Our approach provides a principled method for learning adaptive models from limited interactions with an environment, highlighting a route to sample efficient learning algorithms.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract Background Adults with chronic disease are often unable to meet medication and food needs, but no study has examined the relationship between cost-related medication underuse and food ...insecurity in a nationally representative sample. We examined which groups most commonly face unmet food and medication needs. Methods Cross-sectional analysis of data from chronically ill participants (self-report of arthritis, diabetes mellitus, cancer, asthma, chronic obstructive pulmonary disease, stroke, hypertension, coronary heart disease, or presence of a “psychiatric problem”) aged ≥20 years, in the 2011 National Health Interview Survey. We fit logistic regression models to identify factors associated with food insecurity, cost-related medication underuse, or both. Results There were 9696 adult National Health Interview Survey (NHIS) participants who reported chronic illness; 23.4% reported cost-related medication underuse; 18.8% reported food insecurity; and 11% reported both. Adults who reported food insecurity were significantly more likely to report cost-related medication underuse (adjusted odds ratio aOR 4.03). Participants with both cost-related medication underuse and food insecurity were more likely to be Hispanic (aOR 1.58), non-Hispanic black (aOR 1.58), and have more chronic conditions (aOR per additional chronic condition 1.56) than patients reporting neither. They also were less likely to have public, non-Medicare insurance (aOR 0.70) and report participation in the Special Supplemental Nutrition Assistance Program for Woman, Infants, and Children (aOR 0.39). Conclusions Approximately 1 in 3 chronically ill NHIS participants are unable to afford food, medications, or both. WIC and public health insurance participation are associated with less food insecurity and cost-related medication underuse.
Metal-organic frameworks (MOFs) are an important class of hybrid inorganic-organic materials. In this tutorial review, a progress report on the postsynthetic modification (PSM) of MOFs is provided. ...PSM refers to the chemical modification of the MOF lattice in a heterogeneous fashion. This powerful synthetic approach has grown in popularity and resulted in a number of advances in the functionalization and application of MOFs. The use of PSM to develop MOFs with improved gas sorption, catalytic activity, bioactivity, and more robust physical properties is discussed. The results reported to date clearly show that PSM is an important approach for the development and advancement of these hybrid solids.
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