Bayesian Filtering with Multiple Internal Models: Toward a Theory of Social Intelligence

To exhibit social intelligence, animals have to recognize whom they are communicating with. One way to make this inference is to select among internal generative models of each conspecific who may be encountered. However, these models also have to be learned via some form of Bayesian belief updating. This induces an interesting problem: When receiving sensory input generated by a particular conspecific, how does an animal know which internal model to update? We consider a theoretical and neurobiologically plausible solution that enables inference and learning of the processes that generate sensory inputs (e.g., listening and understanding) and reproduction of those inputs (e.g., talking or singing), under multiple generative models. This is based on recent advances in theoretical neurobiology—namely, active inference and post hoc (online) Bayesian model selection. In brief, this scheme fits sensory inputs under each generative model. Model parameters are then updated in proportion to the probability that each model could have generated the input (i.e., model evidence). The proposed scheme is demonstrated using a series of (real zebra finch) birdsongs, where each song is generated by several different birds. The scheme is implemented using physiologically plausible models of birdsong production. We show that generalized Bayesian filtering, combined with model selection, leads to successful learning across generative models, each possessing different parameters. These results highlight the utility of having multiple internal models when making inferences in social environments with multiple sources of sensory information

Canonical neural networks perform active inference

This work considers a class of canonical neural networks comprising rate coding models, wherein neural activity and plasticity minimise a common cost function-and plasticity is modulated with a certain delay. We show that such neural networks implicitly perform active inference and learning to minimise the risk associated with future outcomes. Mathematical analyses demonstrate that this biological optimisation can be cast as maximisation of model evidence, or equivalently minimisation of variational free energy, under the well-known form of a partially observed Markov decision process model. This equivalence indicates that the delayed modulation of Hebbian plasticity-accompanied with adaptation of firing thresholds-is a sufficient neuronal substrate to attain Bayes optimal inference and control. We corroborated this proposition using numerical analyses of maze tasks. This theory offers a universal characterisation of canonical neural networks in terms of Bayesian belief updating and provides insight into the neuronal mechanisms underlying planning and adaptive behavioural control

Experimental validation of the free-energy principle with in vitro neural networks

Empirical applications of the free-energy principle are not straightforward because they entail a commitment to a particular process theory, especially at the cellular and synaptic levels. Using a recently established reverse engineering technique, we confirm the quantitative predictions of the free-energy principle using in vitro networks of rat cortical neurons that perform causal inference. Upon receiving electrical stimuli—generated by mixing two hidden sources—neurons self-organised to selectively encode the two sources. Pharmacological up- and downregulation of network excitability disrupted the ensuing inference, consistent with changes in prior beliefs about hidden sources. As predicted, changes in effective synaptic connectivity reduced variational free energy, where the connection strengths encoded parameters of the generative model. In short, we show that variational free energy minimisation can quantitatively predict the self-organisation of neuronal networks, in terms of their responses and plasticity. These results demonstrate the applicability of the free-energy principle to in vitro neural networks and establish its predictive validity in this setting

A Case of Bifid Mandibular Condyle

Bifid mandibular condyle is a rare anatomic anomaly that can result from congenital malformation, trauma, infection or tumor. We report a case of bifid mandibular condyle found after head injury. A bifid mandibular condyle was seen on the computed tomographic scan of a 41-year-old man after a car accident. The patient had asymmetry in the condylar angle and length of the condylar neck, and anomaly of occlusion resulting from many residual roots with deep caries. Mouth-opening and mandibular movements were normal, however, the presence of temporomandibular joint symptoms was unclear because of the patient’s unconsciousness at the time of the scan. The bifid mandibular condyle could have resulted from a bicycle accident when the patient was 7 years of age, based on information from the patient’s family.Isomura ET, Kobashi H, Tanaka S, Enomoto A, Kogo M (2017) A Case of Bifid Mandibular Condyle. OMICS J Radiol 6: 278. DOI: 10.4172/2167-7964.1000278

The emergence of synchrony in networks of mutually inferring neurons

This paper considers the emergence of a generalised synchrony in ensembles of coupled self-organising systems, such as neurons. We start from the premise that any self-organising system complies with the free energy principle, in virtue of placing an upper bound on its entropy. Crucially, the free energy principle allows one to interpret biological systems as inferring the state of their environment or external milieu. An emergent property of this inference is synchronisation among an ensemble of systems that infer each other. Here, we investigate the implications of neuronal dynamics by simulating neuronal networks, where each neuron minimises its free energy. We cast the ensuing ensemble dynamics in terms of inference and show that cardinal behaviours of neuronal networks – both in vivo and in vitro – can be explained by this framework. In particular, we test the hypotheses that (i) generalised synchrony is an emergent property of free energy minimisation; thereby explaining synchronisation in the resting brain: (ii) desynchronisation is induced by exogenous input; thereby explaining event-related desynchronisation and (iii) structure learning emerges in response to causal structure in exogenous input; thereby explaining functional segregation in real neuronal systems

A long-term follow-up of a girl with dilated cardiomyopathy after mitral valve replacement and septal anterior ventricular exclusion

We treated a 10 year 11 month old girl with severe mitral valve regurgitation, stenosis and dilated cardiomyopathy, presented with New York Heart Association (NYHA) functional classification IV. She acutely developed cardiogenic shock with a dyskinetic anterior-septal left ventricle and entered a shock state during our consultation about heart transplantation. Septal-anterior ventricular exclusion and mitral valve replacement were performed emergently. She successfully recovered from cardiogenic shock. Left ventricular end-diastolic diameter and fractional shortening improved from 71.5 mm (188.0% of normal) to 62.5 mm (144.2% of normal) and 7.6% to 18.3% respectively. Furthermore, her serum BNP decreased from 2217.5 pg/ml to 112.0 pg/ml. Her cardiac function has remained stable for 7 years since the procedures were performed

Influence of oxygen-coordination number on the electronic structure of single-layer La-based cuprates

We present an angle-resolved photoemission spectroscopy study of the single-layer T*-type structured cuprate SmLa$_{1-x}$Sr$_x$CuO$_4$ with unique five-fold pyramidal oxygen coordination. Upon varying oxygen content, T*-SmLa$_{1-x}$Sr$_x$CuO$_4$ evolved from a Mott-insulating to a metallic state where the Luttinger sum rule breaks down under the assumption of a large hole-like Fermi surface. This is in contrast with the known doping evolution of the structural isomer La$_{2-x}$Sr$_x$CuO$_4$ with six-fold octahedral coordination. In addition, quantitatively characterized Fermi surface suggests that the empirical $T_\mathrm{c}$ rule for octahedral oxygen-coordination systems does not apply to T*-SmLa$_{1-x}$Sr$_x$CuO$_4$. The present results highlight unique properties of the T*-type cuprates possibly rooted in its oxygen coordination, and necessitate thorough investigation with careful evaluation of disorder effects.Comment: Accepted for publication in Phys. Rev.

Measles vaccine coverage and factors related to uncompleted vaccination among 18-month-old and 36-month-old children in Kyoto, Japan

BACKGROUND: Due to low vaccine coverage, Japan has not only experienced outbreaks of measles but has also been exporting it overseas. This study aims to survey measles vaccine coverage and the factors uncompleted vaccination among community-living children. METHODS: Subjects were the parents whose children had undergone either an 18-month or a 36-month checkup publicly provided by Kyoto City during November 2001 to January 2002. An anonymous self-administered questionnaire survey was conducted. RESULTS: The coverage was 73.2% among the 18-month-old children (n = 2707) and 88.9% among the 36-month-old children (n = 2340), respectively. The following characteristics of mothers were related to uncompleted measles vaccination: aged below 30, working, concerned about the adverse events of the vaccine, and had insufficient knowledge. Similarly, the following characteristics among children were related to uncompleted measles vaccination: not the first-born child, interacting with other children in group settings. The coverage was the lowest among the children whose mothers were concerned about the adverse events of the vaccine without proper knowledge of measles and its vaccination. CONCLUSION: To increase vaccine coverage among children, parents' awareness about measles and vaccination against it should be promoted, especially for working mothers. Efforts to enhance access to vaccination services and to communicate with parents about changing vaccination schedules are necessary

A Molecular Platinum Cluster Junction: A Single-Molecule Switch

We present a theoretical study of the electronic transport through single-molecule junctions incorporating a Pt6 metal cluster bound within an organic framework. We show that the insertion of this molecule between a pair of electrodes leads to a fully atomically engineered nano-metallic device with high conductance at the Fermi level and two sequential high on/off switching states. The origin of this property can be traced back to the existence of a HOMO which consists of two degenerate and asymmetric orbitals, lying close in energy to the Fermi level of the metallic leads. Their degeneracy is broken when the molecule is contacted to the leads, giving rise to two resonances which become pinned close to the Fermi level and display destructive interference.Comment: 4 pages, 4 figures. Reprinted (adapted) with permission from J. Am. Chem. Soc., 2013, 135 (6), 2052. Copyright 2013 American Chemical Societ