Neuronal cell-type and circuit basis for visual predictive processing

Bayesian Brain theory suggests brain utilises predictive processing framework to interpret the noisy world. Predictive processing is essential to perception, action, cognition and psychiatric disease, but underlying neural circuit mechanisms remain undelineated. Here we show the neuronal cell-type and circuit basis for visual predictive processing in awake, head-fixed mice during self-initiated running. Preceding running, vasoactive intestinal peptide (VIP)-expressing inhibitory interneurons (INs) in primary visual cortex (V1) are robustly activated in absence of structured visual stimuli. This pre-running activation is mediated via distal top-down projections from frontal, parietal and retrosplenial areas known for motion planning, but not local excitatory inputs associated with the bottom-up pathway. Somatostatin (SST) INs show pre-running suppression and post-running activation, indicating a VIP-SST motif. Differential VIP-SST peri-running dynamics anisotropically suppress neighbouring pyramidal (Pyr) neurons, preadapting Pyr neurons to the incoming running. Our data delineate key neuron types and circuit elements of predictive processing brain employs in action and perception.

Hypernet Model of Media Communication: new qualities of risks for children

The technologically determined hyperbolic growth of communicative connectivity and the imperfection of administrative mechanisms of control over this process lead to an emergence of new phenomena and new risks, including risks in relation to the most vulnerable social group – children. The article proposes a new approach to describing the nature of the risks of the media space in relation to the health and development of children. Minimization of these risks is defined by the author as the goal of ensuring the information security of children. New qualities of risks are described on the basis of a hypernet model of media communication and developed on the basis of the hypernetwork brain theory. The author specifies the properties of hypernet education and their riskiness, mediated by the network morphology of connections, which implies the impossibility or ineffectiveness of the application of customary management practices. The vulnerability of the child group to these risks stem from the psychological immaturity. The importance of the phenomenalization of “media” and “information” is noted for the purposes of information policy and security – media security. The article reveals the tendencies of the media hypernetwork that increase the risks, especially the growth in the speed and volume of information transfer provided by technologies, which excludes the action of the well-known mechanisms for regulating the circulation of information and filtering content.

The thermodynamic theory of action potential propagation: a sound basis for unification of the physics of nerve impulses

The thermodynamic theory of action potential propagation challenges the conventional understanding of the nerve signal as an exclusively electrical phenomenon. Often misunderstood as to its basic tenets and predictions, the thermodynamic theory is virtually ignored in mainstream neuroscience. Addressing a broad audience of neuroscientists, we here attempt to stimulate interest in the theory. We do this by providing a concise overview of its background, discussion of its intimate connection to Albert Einstein’s treatment of the thermodynamics of interfaces and outlining its potential contribution to the building of a physical brain theory firmly grounded in first principles and the biophysical reality of individual nerve cells. As such, the paper does not attempt to advocate the superiority of the thermodynamic theory over any other approach to model the nerve impulse, but is meant as an open invitation to the neuroscience community to experimentally test the assumptions and predictions of the theory on their validity.

Brain Mass (Energy) Resistant to Hyperglycaemic Oversupply: A Systematic Review

Cerebral energy supply is determined by the energy content of the blood. Accordingly, the brain is undersupplied during hypoglycaemia. Whether or not there is an additional cerebral energy demand that depends upon the energy content of the brain is considered differently in two opposing theoretical approaches. The Selfish-Brain theory postulates that the brain actively demands energy from the body when needed, while long-held theories, the gluco-lipostatic theory and its variants, deny such active brain involvement and view the brain as purely passively supplied. Here we put the competing theories to the test. We conducted a systematic review of a condition in which the rival theories make opposite predictions, i.e., experimental T1DM. The Selfish-Brain theory predicts that induction of experimental type 1 diabetes causes minor mass (energy) changes in the brain as opposed to major glucose changes in the blood. This prediction becomes our hypothesis to be tested here. A total of 608 works were screened by title and abstract, and 64 were analysed in full text. According to strict selection criteria defined in our PROSPERO preannouncement and complying with PRISMA guidelines, 18 studies met all inclusion criteria. Thirteen studies provided sufficient data to test our hypothesis. The 13 evaluable studies (15 experiments) showed that the diabetic groups had blood glucose concentrations that differed from controls by +294 ± 96% (mean ± standard deviation) and brain mass (energy) that differed from controls by −4 ± 13%, such that blood changes were an order of magnitude greater than brain changes (T = 11.5, df = 14, p < 0.001). This finding confirms not only our hypothesis but also the prediction of the Selfish-Brain theory, while the predictions of the gluco-lipostatic theory and its variants were violated. The current paper completes a three-part series of systematic reviews, the two previous papers deal with a distal and a proximal bottleneck in the cerebral brain supply, i.e., caloric restriction and cerebral artery occlusion. All three papers demonstrate that accurate predictions are only possible if one regards the brain as an organ that regulates its energy concentrations independently and occupies a primary position in a hierarchically organised energy metabolism.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=156816, PROSPERO, identifier: CRD42020156816.

Pertinence of Predictive Models as Regards the Behavior of Observed Biological and Artificial Phenomena

In this assessment, we have made an effort of synthesis on the role of theoretical and observational investigations in the analysis of the concepts and functioning of different natural biological and artificial phenomena. In this context, we pursued the objective of examining published works relating to the behavioral prediction of phenomena associated with its observation. We have examined examples from the literature concerning phenomena with known behaviors that associated to knowledge uncertainty as well as cases concerning phenomena with unknown and changing random behaviors linked to random uncertainty. The concerned cases are relative to brain functioning in neuroscience, modern smart industrial devices, and health care predictive endemic protocols. As predictive modeling is very concerned by the problematics relative to uncertainties that depend on the degree of matching in the link prediction-observation, we investigated first how to improve the model to match better the observation. Thus, we considered the case when the observed behavior and its model are contrasting, that implies the development of revised or amended models. Then we studied the case concerning the practice of modeling for the prediction of future behaviors of a phenomenon that is well known, and owning identified behavior. For such case, we illustrated the situation of prediction matched to observation operated in two cases. These are the Bayesian Brain theory in neuroscience and the Digital Twins industrial concept. The last investigated circumstance concerns the use of modeling for the prediction of future behaviors of a phenomenon that is not well known, or owning behavior varying arbitrary. For this situation, we studied contagion infections with an unknown mutant virus where the prediction task is very complicated and would be constrained only to adjust the principal clinical observation protocol. Keywords: prediction, observation, Bayesian, neuroscience, brain functioning, mutant virus

Proximal Disruption of Brain Energy Supply Raises Systemic Blood Glucose: A Systematic Review

This work joins a series that methodically tests the predictions of the Selfish-Brain theory. The theory postulates a vital ability of the mammalian brain, namely to give priority to its own energy metabolism. The brain behaves “selfishly” in this respect. For the cerebral artery occlusion studied here, the theory predicts an increase in blood glucose concentration, what becomes the hypothesis to be tested. We conducted a systematic review of cerebral-artery-occlusion papers to test whether or not the included studies could confirm this hypothesis. We identified 239 records, screened 231 works by title or abstract, and analyzed 89 by full text. According to strict selection criteria (set out in our PROSPERO preregistration, complying with PRISMA guidelines), 7 papers provided enough information to decide on the hypothesis. Our hypothesis could be fully confirmed for the 3 to 24 h after the onset of a transient 2 h or permanent occlusion. As for the mechanism, the theory predicts that the energy-deprived brain suppresses insulin secretion via the sympathoadrenal system, thereby preventing insulin-mediated glucose uptake into muscle and fat and, as a result, enhancing insulin-independent glucose uptake via the blood-brain barrier. Evidence from our included studies actually demonstrated cerebral insulin suppression. In all, the current work confirms the second major prediction of the Selfish-Brain theory that relates to a proximal bottleneck of the cerebral supply chain, cerebral artery occlusion. Its first major prediction relates to a distal supply bottleneck, caloric restriction, and is fulfilled as shown by our previous work, whereas the prediction of the long held gluco-lipostatic theory, which sees the brain as only passively supplied, is violated (Sprengell et al., 2021). The crucial point was that caloric restriction elicits smaller changes in mass (energy) in the brain than in the body. Taken together, the evidence from the current and previous work clearly shows that the most accurate predictions are possible with a theory that views the brain as an independently self-regulating energy compartment occupying a primary position in energy metabolism.

A global framework for a systemic view of brain modeling

The brain is a complex system, due to the heterogeneity of its structure, the diversity of the functions in which it participates and to its reciprocal relationships with the body and the environment. A systemic description of the brain is presented here, as a contribution to developing a brain theory and as a general framework where specific models in computational neuroscience can be integrated and associated with global information flows and cognitive functions. In an enactive view, this framework integrates the fundamental organization of the brain in sensorimotor loops with the internal and the external worlds, answering four fundamental questions (what, why, where and how). Our survival-oriented definition of behavior gives a prominent role to pavlovian and instrumental conditioning, augmented during phylogeny by the specific contribution of other kinds of learning, related to semantic memory in the posterior cortex, episodic memory in the hippocampus and working memory in the frontal cortex. This framework highlights that responses can be prepared in different ways, from pavlovian reflexes and habitual behavior to deliberations for goal-directed planning and reasoning, and explains that these different kinds of responses coexist, collaborate and compete for the control of behavior. It also lays emphasis on the fact that cognition can be described as a dynamical system of interacting memories, some acting to provide information to others, to replace them when they are not efficient enough, or to help for their improvement. Describing the brain as an architecture of learning systems has also strong implications in Machine Learning. Our biologically informed view of pavlovian and instrumental conditioning can be very precious to revisit classical Reinforcement Learning and provide a basis to ensure really autonomous learning.

Brain More Resistant to Energy Restriction Than Body: A Systematic Review

The gluco-lipostatic theory and its modern variants assume that blood glucose and energy stores are controlled in closed-loop feedback processes. The Selfish Brain theory is based on the same assumptions, but additionally postulates that the brain, as an independent energy compartment, self-regulates its energy concentration with the highest priority. In some clinical situations these two theories make opposite predictions. To investigate one of these situations, namely caloric restriction, we formulated a hypothesis which, if confirmed, would match the predictions of the Selfish Brain theory—but not those of the gluco-lipostatic theory. Hypothesis: Calorie restriction causes minor mass (energy) changes in the brain as opposed to major changes in the body. We conducted a systematic review of caloric-restriction studies to test whether or not the evaluated studies confirmed this hypothesis. We identified 3,157 records, screened 2,804 works by title or abstract, and analyzed 232 by full text. According to strict selection criteria (set out in our PROSPERO preregistration, complying with PRISMA guidelines, and the pre-defined hypothesis-decision algorithm), 8 papers provided enough information to decide on the hypothesis: In animals, high-energy phosphates were measured by 31P-nuclear magnetic resonance, and organ and total body weights were measured by scales, while in humans organ sizes were determined by magnetic resonance imaging. All 8 decidable papers confirmed the hypothesis, none spoke against it. The evidence presented here clearly shows that the most accurate predictions are possible with a theory that regards the brain as independently self-regulating and as occupying a primary position in a hierarchically organized energy metabolism.

Crisis and Rehearsal in Frederick Douglass

Chapter 1 shows Douglass increasingly sensitive to the way that abolition turned democracy into a traumatic genre for those in power. Seeking the elusive “thing” to be abolished for emancipation to be achieved, Douglass reworks the affiliation of mesmerism with the Haitian revolution through a variety of eclectic influences, as we see in “The Heroic Slave” and in his application of the early brain theory of George Combe. Defusing the hasty association between abolition and race war required careful rehearsals (or in Mesmer’s terms, the generation of a “crisis state”) in order to expose the dangerous power of such fears. With his future taken from him by slavery, Douglass studies the violent behavior of his masters and later audience members interrupting his abolitionist lectures. In the process he exposes the social horizon of temporal disruptions later informing the Freudian notion of afterwardsness.