Stable individual differences from dynamic patterns of function: brain network flexibility predicts openness/intellect, intelligence, and psychoticism.

A growing understanding of the nature of brain function has led to increased interest in interpreting the properties of large-scale brain networks. Methodological advances in network neuroscience provide means to decompose these networks into smaller functional communities and measure how they reconfigure over time as an index of their dynamic and flexible properties. Recent evidence has identified associations between flexibility and a variety of traits pertaining to complex cognition including creativity and working memory. The present study used measures of dynamic resting-state functional connectivity in data from the Human Connectome Project (n = 994) to test associations with Openness/Intellect, general intelligence, and psychoticism, three traits that involve flexible cognition. Using a machine-learning cross-validation approach, we identified reliable associations of intelligence with cohesive flexibility of parcels in large communities across the cortex, of psychoticism with disjoint flexibility, and of Openness/Intellect with overall flexibility among parcels in smaller communities. These findings are reasonably consistent with previous theories of the neural correlates of these traits and help to expand on previous associations of behavior with dynamic functional connectivity, in the context of broad personality dimensions.

Robust evidence for bisexual orientation among men.

The question whether some men have a bisexual orientation-that is, whether they are substantially sexually aroused and attracted to both sexes-has remained controversial among both scientists and laypersons. Skeptics believe that male sexual orientation can only be homosexual or heterosexual, and that bisexual identification reflects nonsexual concerns, such as a desire to deemphasize homosexuality. Although most bisexual-identified men report that they are attracted to both men and women, self-report data cannot refute these claims. Patterns of physiological (genital) arousal to male and female erotic stimuli can provide compelling evidence for male sexual orientation. (In contrast, most women provide similar physiological responses to male and female stimuli.) We investigated whether men who self-report bisexual feelings tend to produce bisexual arousal patterns. Prior studies of this issue have been small, used potentially invalid statistical tests, and produced inconsistent findings. We combined nearly all previously published data (from eight previous studies in the United States, United Kingdom, and Canada), yielding a sample of 474 to 588 men (depending on analysis). All participants were cisgender males. Highly robust results showed that bisexual-identified men's genital and subjective arousal patterns were more bisexual than were those who identified as exclusively heterosexual or homosexual. These findings support the view that male sexual orientation contains a range, from heterosexuality, to bisexuality, to homosexuality.

The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again.

Drawing from both enactivist and cognitivist perspectives on mind, I propose that explaining teleological phenomena may require reappraising both "Cartesian theaters" and mental homunculi in terms of embodied self-models (ESMs), understood as body maps with agentic properties, functioning as predictive-memory systems and cybernetic controllers. Quasi-homuncular ESMs are suggested to constitute a major organizing principle for neural architectures due to their initial and ongoing significance for solutions to inference problems in cognitive (and affective) development. Embodied experiences provide foundational lessons in learning curriculums in which agents explore increasingly challenging problem spaces, so answering an unresolved question in Bayesian cognitive science: what are biologically plausible mechanisms for equipping learners with sufficiently powerful inductive biases to adequately constrain inference spaces? Drawing on models from neurophysiology, psychology, and developmental robotics, I describe how embodiment provides fundamental sources of empirical priors (as reliably learnable posterior expectations). If ESMs play this kind of foundational role in cognitive development, then bidirectional linkages will be found between all sensory modalities and frontal-parietal control hierarchies, so infusing all senses with somatic-motoric properties, thereby structuring all perception by relevant affordances, so solving frame problems for embodied agents. Drawing upon the Free Energy Principle and Active Inference framework, I describe a particular mechanism for intentional action selection via consciously imagined (and explicitly represented) goal realization, where contrasts between desired and present states influence ongoing policy selection via predictive coding mechanisms and backward-chained imaginings (as self-realizing predictions). This embodied developmental legacy suggests a mechanism by which imaginings can be intentionally shaped by (internalized) partially-expressed motor acts, so providing means of agentic control for attention, working memory, imagination, and behavior. I further describe the nature(s) of mental causation and self-control, and also provide an account of readiness potentials in Libet paradigms wherein conscious intentions shape causal streams leading to enaction. Finally, I provide neurophenomenological handlings of prototypical qualia including pleasure, pain, and desire in terms of self-annihilating free energy gradients via quasi-synesthetic interoceptive active inference. In brief, this manuscript is intended to illustrate how radically embodied minds may create foundations for intelligence (as capacity for learning and inference), consciousness (as somatically-grounded self-world modeling), and will (as deployment of predictive models for enacting valued goals).

Default mode network connectivity change corresponds to ketamine's delayed glutamatergic effects.

Ketamine exerts rapid antidepressant effects peaking 24 h after a single infusion, which have been suggested to be reflected by both reduced functional connectivity (FC) within default mode network (DMN) and altered glutamatergic levels in the perigenual anterior cingulate cortex (pgACC) at 24 h. Understanding the interrelation and time point specificity of ketamine-induced changes of brain circuitry and metabolism is thus key to future therapeutic developments. We investigated the correlation of late glutamatergic changes with FC changes seeded from the posterior cingulate cortex (PCC) and tested the prediction of the latter by acute fractional amplitude of low-frequency fluctuations (fALFF). In a double-blind, randomized, placebo-controlled study of 61 healthy subjects, we compared effects of subanesthetic ketamine infusion (0.5 mg/kg over 40 min) on resting-state fMRI and MR-Spectroscopy at 7 T 1 h and 24 h post-infusion. FC decrease between PCC and dorsomedial prefrontal cortex (dmPFC) was found at 24 h post-infusion (but not 1 h) and this FC decrease correlated with glutamatergic changes at 24 h in pgACC. Acute increase in fALFF was found in ventral PCC at 1 h which was not observed at 24 h and inversely correlated with the reduced dPCC FC towards the dmPFC at 24 h. The correlation of metabolic and functional markers of delayed ketamine effects and their temporal specificity suggest a potential mechanistic relationship between glutamatergic modulation and reconfiguration of brain regions belonging to the DMN.

Neural Responses to Sexual Stimuli in Heterosexual and Homosexual Men and Women: Men's Responses Are More Specific.

Patterns of genital arousal in response to gendered sexual stimuli (i.e., sexual stimuli presenting members of only one sex at a time) are more predictive of men's than of women's sexual orientations. Additional lines of evidence may shed light on the nature of these differences. We measured neural activation in homosexual and heterosexual men and women using fMRI while they viewed three kinds of gendered sexual stimuli: pictures of nude individuals, pictures of same-sex couples interacting, and videos of individuals self-stimulating. The primary neural region of interest was the ventral striatum (VS), an area of central importance for reward processing. For all three kinds of stimuli and for both VS activation and self-report, men's responses were more closely related to their sexual orientations compared with women's. Furthermore, men showed a much greater tendency to respond more positively to stimuli featuring one sex than to stimuli featuring the other sex, leading to higher correlations among men's responses as well as higher correlations between men's responses and their sexual orientations. Whole-brain analyses identified several other regions showing a similar pattern to the VS, and none showed an opposite pattern. Because fMRI is measured identically in men and women, our results provide the most direct evidence to date that men's sexual arousal patterns are more gender specific than women's.

The neural basis of sex differences in sexual behavior: A quantitative meta-analysis.

Sexuality as to its etymology presupposes the duality of sexes. Using quantitative neuroimaging meta-analyses, we demonstrate robust sex differences in the neural processing of sexual stimuli in thalamus, hypothalamus, and basal ganglia. In a narrative review, we show how these relate to the well-established sex differences on the behavioral level. More specifically, we describe the neural bases of known poor agreement between self-reported and genital measures of female sexual arousal, of previously proposed male proneness to affective sexual conditioning, as well as hints of unconscious activation of bonding mechanisms during sexual stimulation in women. In summary, our meta-analytic review demonstrates that neurofunctional sex differences during sexual stimulation can account for well-established sex differences in sexual behavior.

A spectroscopic approach toward depression diagnosis: local metabolism meets functional connectivity.

Abnormal anterior insula (AI) response and functional connectivity (FC) is associated with depression. In addition to clinical features, such as severity, AI FC and its metabolism further predicted therapeutic response. Abnormal FC between anterior cingulate and AI covaried with reduced glutamate level within cingulate cortex. Recently, deficient glial glutamate conversion was found in AI in major depression disorder (MDD). We therefore postulate a local glutamatergic mechanism in insula cortex of depressive patients, which is correlated with symptoms severity and itself influences AI's network connectivity in MDD. Twenty-five MDD patients and 25 healthy controls (HC) matched on age and sex underwent resting state functional magnetic resonance imaging and magnetic resonance spectroscopy scans. To determine the role of local glutamate-glutamine complex (Glx) ratio on whole brain AI FC, we conducted regression analysis with Glx relative to creatine (Cr) ratio as factor of interest and age, sex, and voxel tissue composition as nuisance factors. We found that in MDD, but not in HC, AI Glx/Cr ratio correlated positively with AI FC to right supramarginal gyrus and negatively with AI FC toward left occipital cortex (p < 0.05 family wise error). AI Glx/Cr level was negatively correlated with HAMD score (p < 0.05) in MDD patients. We showed that the local AI ratio of glutamatergic-creatine metabolism is an underlying candidate subserving functional network disintegration of insula toward low level and supramodal integration areas, in MDD. While causality cannot directly be inferred from such correlation, our finding helps to define a multilevel network of response-predicting regions based on local metabolism and connectivity strength.

Deep CANALs: a deep learning approach to refining the canalization theory of psychopathology.

Psychedelic therapy has seen a resurgence of interest in the last decade, with promising clinical outcomes for the treatment of a variety of psychopathologies. In response to this success, several theoretical models have been proposed to account for the positive therapeutic effects of psychedelics. One of the more prominent models is "RElaxed Beliefs Under pSychedelics," which proposes that psychedelics act therapeutically by relaxing the strength of maladaptive high-level beliefs encoded in the brain. The more recent "CANAL" model of psychopathology builds on the explanatory framework of RElaxed Beliefs Under pSychedelics by proposing that canalization (the development of overly rigid belief landscapes) may be a primary factor in psychopathology. Here, we make use of learning theory in deep neural networks to develop a series of refinements to the original CANAL model. Our primary theoretical contribution is to disambiguate two separate optimization landscapes underlying belief representation in the brain and describe the unique pathologies which can arise from the canalization of each. Along each dimension, we identify pathologies of either too much or too little canalization, implying that the construct of canalization does not have a simple linear correlation with the presentation of psychopathology. In this expanded paradigm, we demonstrate the ability to make novel predictions regarding what aspects of psychopathology may be amenable to psychedelic therapy, as well as what forms of psychedelic therapy may ultimately be most beneficial for a given individual.

Neural correlates of sexual arousal in heterosexual and homosexual women and men.

Most men have a category-specific pattern of genital and subjective sexual arousal, responding much more strongly to erotic stimuli depicting their preferred sex than to erotic stimuli depicting their nonpreferred sex. In contrast, women tend to have a less specific arousal pattern. To better understand this sex difference, we used neuroimaging to explore its neural correlates. Heterosexual and homosexual women viewed erotic photographs of either men or women. Evoked neural activity was monitored via fMRI and compared with responses to the same stimuli in heterosexual and homosexual men. Overall, a network of limbic (as well as the anterior cingulate) and visual processing regions showed significantly less category-specific activity in women than men. This was primarily driven by weaker overall activations to preferred-sex stimuli in women, though there was also some evidence of stronger limbic activations to nonpreferred-sex stimuli in women. Primary results were similar for heterosexual and homosexual participants. Women did show some evidence of category-specific responses in the visual processing regions, although even in these regions they exhibited less differential activity than men. In the anterior cingulate, a region with high concentrations of sex-hormone receptors, subjective and neural category specificity measures correlated positively for women but negatively for men, suggesting a possible sex difference in the role of the anterior cingulate. Overall, results suggest that men tend to show more differentiated neural responses than do women to erotic photographs of one sex compared to the other sex, though women may not be entirely indifferent to which sex is depicted.

As without, so within: how the brain's temporo-spatial alignment to the environment shapes consciousness.

Consciousness is constituted by a structure that includes contents as foreground and the environment as background. This structural relation between the experiential foreground and background presupposes a relationship between the brain and the environment, often neglected in theories of consciousness. The temporo-spatial theory of consciousness addresses the brain-environment relation by a concept labelled 'temporo-spatial alignment'. Briefly, temporo-spatial alignment refers to the brain's neuronal activity's interaction with and adaption to interoceptive bodily and exteroceptive environmental stimuli, including their symmetry as key for consciousness. Combining theory and empirical data, this article attempts to demonstrate the yet unclear neuro-phenomenal mechanisms of temporo-spatial alignment. First, we suggest three neuronal layers of the brain's temporo-spatial alignment to the environment. These neuronal layers span across a continuum from longer to shorter timescales. (i) The background layer comprises longer and more powerful timescales mediating topographic-dynamic similarities between different subjects' brains. (ii) The intermediate layer includes a mixture of medium-scaled timescales allowing for stochastic matching between environmental inputs and neuronal activity through the brain's intrinsic neuronal timescales and temporal receptive windows. (iii) The foreground layer comprises shorter and less powerful timescales for neuronal entrainment of stimuli temporal onset through neuronal phase shifting and resetting. Second, we elaborate on how the three neuronal layers of temporo-spatial alignment correspond to their respective phenomenal layers of consciousness. (i) The inter-subjectively shared contextual background of consciousness. (ii) An intermediate layer that mediates the relationship between different contents of consciousness. (iii) A foreground layer that includes specific fast-changing contents of consciousness. Overall, temporo-spatial alignment may provide a mechanism whose different neuronal layers modulate corresponding phenomenal layers of consciousness. Temporo-spatial alignment can provide a bridging principle for linking physical-energetic (free energy), dynamic (symmetry), neuronal (three layers of distinct time-space scales) and phenomenal (form featured by background-intermediate-foreground) mechanisms of consciousness.

From distal to proximal to interactive: behavioral and brain synchrony during attraction, courtship, and sexual interaction-implications for clinical assessments of relationship style and quality.

INTRODUCTION: Synchronous behaviors between individuals are nonverbal signs of closeness and common purpose. In the flow from initial attraction to intimate sexual interaction, attention and synchrony move from distal to proximal to interactive and are mediated by sensitized activation of neural systems for sexual motivation, arousal, and desire and those that recognize and mimic common facial and body movements between individuals. When reinforced by sexual pleasure and other relationship rewards, this results in the strengthening of attraction and bonding and the display of more common motor patterns. As relationships falter, nonverbal behaviors likely become asynchronous. OBJECTIVES: To define behavioral, romantic, and sexual synchrony during phases of attraction and how their disruption can be observed and utilized by clinicians to assess individual relationship styles and quality. METHODS: We review the literature on behavioral and attentional synchrony in humans and animals in an effort to understand experiential and innate mechanisms of synchrony and asynchrony and how they develop, as well as implications for attraction, relationship initiation, maintenance of romantic and sexual closeness, and relationship disintegration. RESULTS: Evidence is presented that behavioral synchrony and the neural mechanisms that underlie it are vital to relationship formation and satisfaction. CONCLUSION: Behavioral synchrony helps to create feelings of sexual and romantic synergy, cohesion, and arousal among individuals. Asynchrony is aversive and can spark feelings of discontent, aversion, and jealousy. Thus, observing patterns of nonverbal sexual and romantic synchrony between individuals offers insights into the potential quality of their relationships.

Cognitive Science Below the Neck: Toward an Integrative Account of Consciousness in the Body.

Our culture and its scientific endeavor direly need a holistic characterization of mind and body. Many phenomena attest to the profound effects of beliefs on bodily function (e.g., open-label placebo's effects on chronic pain) and interoceptive systems' role in mental processes (e.g., the emerging role of gut microbiomes in the mood). We need a mechanistic, integrative framework to account for these phenomena and generate novel predictions. Major advances have been made in understanding how the nervous system senses and regulates the body and in modeling how the brain implements the computations that subserve such activities. However, the vestiges of Cartesianism have entrained a style of thinking in which systems from the brainstem downward exist as the implementation layer of computational processes supporting sensation and behavior, rather than a complementary locus of information processing. As speakers and microphones, rather than other members of the chorus. We are thus forced to perceive well-documented, belief-driven phenomena like placebo, ritual, and psychosomatic disorders as mysterious obstacles or dubious allies rather than as a wellspring of potential.

Preferential networks of the mediodorsal nucleus and centromedian-parafascicular complex of the thalamus--a DTI tractography study.

Distinct thalamic nuclei, like the mediodorsal (MD) nucleus and the centromedian/parafascicular complex (CM/Pf), are embedded in different basal ganglia-thalamocortical loops, which were shown to integrate cognitive and emotional aspects of human behavior. Despite well described connections on a microscopic scale, derived from tracing studies in animals, little is known about the intrinsic anatomical connections of these nuclei in humans. This lack of knowledge limits not only interpretation of functional imaging studies but also estimation of direct effects of deep brain stimulation which treats diseases as different as epilepsy or major depression. Therefore, non-invasive diffusion tensor imaging (DTI) studies are key to analyzing connectivity patterns and elaborate approaches to close this gap. For our study, we explored the structural connectivity of the MD thalamic nuclei and the CM/Pf complex towards five cortical and six subcortical regions by using a preferential fiber calculation. We found both thalamic nuclei to be preferentially associated to distinct networks: whereas the MD is preferentially connected to prefrontal and limbic cortical regions, the CM is linked to subcortical regions. The anterior insula was the only cortical region associated with the subcortical network of the CM and the cortical network of the MD comprised one subcortical hub, the caudate nucleus, suggesting an integrative role of these two regions. Adding to predescribed anatomical tract tracing connectivities in animal studies, our finding lends support to the existence of similar basal ganglia-thalamocortical circuits in humans and we could show a robust distinction of preferential connectivity for both thalamic nuclei.

The male bisexuality debate revisited: some bisexual men have bisexual arousal patterns.

Self-identified bisexual men report high sexual arousal to both male and female stimuli, but no study to date has compellingly demonstrated that such men have a bisexual pattern of genital arousal. We examined sexual arousal patterns among bisexual men recruited using stringent criteria designed to exclude those who were less likely to have sexual interest in both sexes. Furthermore, we included a bisexual stimulus depicting a man engaged in sex simultaneously with another man and a woman. On average, the bisexual men showed a bisexual arousal pattern, with respect to both self-reported and genital arousal. Additionally, the bisexual men were more aroused by the bisexual stimulus compared with the homosexual and heterosexual men. Some bisexual-identified men have bisexual genital arousal patterns, although it remains unclear how common they are.

Integrated world modeling theory expanded: Implications for the future of consciousness.

Integrated world modeling theory (IWMT) is a synthetic theory of consciousness that uses the free energy principle and active inference (FEP-AI) framework to combine insights from integrated information theory (IIT) and global neuronal workspace theory (GNWT). Here, I first review philosophical principles and neural systems contributing to IWMT's integrative perspective. I then go on to describe predictive processing models of brains and their connections to machine learning architectures, with particular emphasis on autoencoders (perceptual and active inference), turbo-codes (establishment of shared latent spaces for multi-modal integration and inferential synergy), and graph neural networks (spatial and somatic modeling and control). Future directions for IIT and GNWT are considered by exploring ways in which modules and workspaces may be evaluated as both complexes of integrated information and arenas for iterated Bayesian model selection. Based on these considerations, I suggest novel ways in which integrated information might be estimated using concepts from probabilistic graphical models, flow networks, and game theory. Mechanistic and computational principles are also considered with respect to the ongoing debate between IIT and GNWT regarding the physical substrates of different kinds of conscious and unconscious phenomena. I further explore how these ideas might relate to the "Bayesian blur problem," or how it is that a seemingly discrete experience can be generated from probabilistic modeling, with some consideration of analogies from quantum mechanics as potentially revealing different varieties of inferential dynamics. I go on to describe potential means of addressing critiques of causal structure theories based on network unfolding, and the seeming absurdity of conscious expander graphs (without cybernetic symbol grounding). Finally, I discuss future directions for work centered on attentional selection and the evolutionary origins of consciousness as facilitated "unlimited associative learning." While not quite solving the Hard problem, this article expands on IWMT as a unifying model of consciousness and the potential future evolution of minds.

Generalized Simultaneous Localization and Mapping (G-SLAM) as unification framework for natural and artificial intelligences: towards reverse engineering the hippocampal/entorhinal system and principles of high-level cognition.

Simultaneous localization and mapping (SLAM) represents a fundamental problem for autonomous embodied systems, for which the hippocampal/entorhinal system (H/E-S) has been optimized over the course of evolution. We have developed a biologically-inspired SLAM architecture based on latent variable generative modeling within the Free Energy Principle and Active Inference (FEP-AI) framework, which affords flexible navigation and planning in mobile robots. We have primarily focused on attempting to reverse engineer H/E-S "design" properties, but here we consider ways in which SLAM principles from robotics may help us better understand nervous systems and emergent minds. After reviewing LatentSLAM and notable features of this control architecture, we consider how the H/E-S may realize these functional properties not only for physical navigation, but also with respect to high-level cognition understood as generalized simultaneous localization and mapping (G-SLAM). We focus on loop-closure, graph-relaxation, and node duplication as particularly impactful architectural features, suggesting these computational phenomena may contribute to understanding cognitive insight (as proto-causal-inference), accommodation (as integration into existing schemas), and assimilation (as category formation). All these operations can similarly be describable in terms of structure/category learning on multiple levels of abstraction. However, here we adopt an ecological rationality perspective, framing H/E-S functions as orchestrating SLAM processes within both concrete and abstract hypothesis spaces. In this navigation/search process, adaptive cognitive equilibration between assimilation and accommodation involves balancing tradeoffs between exploration and exploitation; this dynamic equilibrium may be near optimally realized in FEP-AI, wherein control systems governed by expected free energy objective functions naturally balance model simplicity and accuracy. With respect to structure learning, such a balance would involve constructing models and categories that are neither too inclusive nor exclusive. We propose these (generalized) SLAM phenomena may represent some of the most impactful sources of variation in cognition both within and between individuals, suggesting that modulators of H/E-S functioning may potentially illuminate their adaptive significances as fundamental cybernetic control parameters. Finally, we discuss how understanding H/E-S contributions to G-SLAM may provide a unifying framework for high-level cognition and its potential realization in artificial intelligences.

On the Importance of Being Flexible: Dynamic Brain Networks and Their Potential Functional Significances.

In this theoretical review, we begin by discussing brains and minds from a dynamical systems perspective, and then go on to describe methods for characterizing the flexibility of dynamic networks. We discuss how varying degrees and kinds of flexibility may be adaptive (or maladaptive) in different contexts, specifically focusing on measures related to either more disjoint or cohesive dynamics. While disjointed flexibility may be useful for assessing neural entropy, cohesive flexibility may potentially serve as a proxy for self-organized criticality as a fundamental property enabling adaptive behavior in complex systems. Particular attention is given to recent studies in which flexibility methods have been used to investigate neurological and cognitive maturation, as well as the breakdown of conscious processing under varying levels of anesthesia. We further discuss how these findings and methods might be contextualized within the Free Energy Principle with respect to the fundamentals of brain organization and biological functioning more generally, and describe potential methodological advances from this paradigm. Finally, with relevance to computational psychiatry, we propose a research program for obtaining a better understanding of ways that dynamic networks may relate to different forms of psychological flexibility, which may be the single most important factor for ensuring human flourishing.

Back to square one: the bodily roots of conscious experiences in early life.

Most theoretical and empirical discussions about the nature of consciousness are typically couched in a way that endorses a tacit adult-centric and vision-based perspective. This paper defends the idea that consciousness science may be put on a fruitful track for its next phase by examining the nature of subjective experiences through a bottom-up developmental lens. We draw attention to the intrinsic link between consciousness, experiences and experiencing subjects, which are first and foremost embodied and situated organisms essentially concerned with self-preservation within a precarious environment. Our paper suggests that in order to understand what consciousness 'is', one should first tackle the fundamental question: how do embodied experiences 'arise' from square one? We then highlight one key yet overlooked aspect of human consciousness studies, namely that the earliest and closest environment of an embodied experiencing subject is the body of another human experiencing subject. We present evidence speaking in favour of fairly sophisticated forms of early sensorimotor integration of bodily signals and self-generated actions already being established in utero. We conclude that these primitive and fundamentally relational and co-embodied roots of our early experiences may have a crucial impact on the way human beings consciously experience the self, body and the world across their lifespan.

Robot navigation as hierarchical active inference.

Localization and mapping has been a long standing area of research, both in neuroscience, to understand how mammals navigate their environment, as well as in robotics, to enable autonomous mobile robots. In this paper, we treat navigation as inferring actions that minimize (expected) variational free energy under a hierarchical generative model. We find that familiar concepts like perception, path integration, localization and mapping naturally emerge from this active inference formulation. Moreover, we show that this model is consistent with models of hippocampal functions, and can be implemented in silico on a real-world robot. Our experiments illustrate that a robot equipped with our hierarchical model is able to generate topologically consistent maps, and correct navigation behaviour is inferred when a goal location is provided to the system.