1,987 publications from this institution
This chapter revisits seminal work on (Peircean) semiotics under the auspices of active inference, a theory of adaptive, belief-based behavior that has cast perception, learning, and action as forms of (variational or Bayesian) inference. We argue that active inference features a semiotic structure that admits a partial integration and formalization of semiotic concepts, notably including abductive inference, Peircean interpretants, and the icon/index/symbol triad. The resulting framework may motivate interdisciplinary treatments of semiotics in the sciences of life and mind – namely, neurosemiotics – to help understand the nature of meaning in relation to neuronal processes and accompanying perceptual inference.
We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference.
Over the last 2 decades, a large number of neurophysiological and neuroimaging studies of patients with schizophrenia have furnished in vivo evidence for dysconnectivity, ie, abnormal functional integration of brain processes. While the evidence for dysconnectivity in schizophrenia is strong, its etiology, pathophysiological mechanisms, and significance for clinical symptoms are unclear. First, dysconnectivity could result from aberrant wiring of connections during development, from aberrant synaptic plasticity, or from both. Second, it is not clear how schizophrenic symptoms can be understood mechanistically as a consequence of dysconnectivity. Third, if dysconnectivity is the primary pathophysiology, and not just an epiphenomenon, then it should provide a mechanistic explanation for known empirical facts about schizophrenia. This article addresses these 3 issues in the framework of the dysconnection hypothesis. This theory postulates that the core pathology in schizophrenia resides in aberrant N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic plasticity due to abnormal regulation of NMDARs by neuromodulatory transmitters like dopamine, serotonin, or acetylcholine. We argue that this neurobiological mechanism can explain failures of self-monitoring, leading to a mechanistic explanation for first-rank symptoms as pathognomonic features of schizophrenia, and may provide a basis for future diagnostic classifications with physiologically defined patient subgroups. Finally, we test the explanatory power of our theory against a list of empirical facts about schizophrenia.
A quantitative study of the regional cerebral responses to non-painful and painful thermal stimuli in six normal volunteers has been done by monitoring serial measurements of regional blood flow measured by positron emission tomography (PET). In comparison to a baseline of warm stimulation no statistically significant changes in blood flow were seen in relation to increasing non-painful heat. However, highly significant increases in blood flow were seen in response to painful heat in comparison to non-painful heat. These changes were in the contralateral cingulate cortex, thalamus and lenticular nucleus. These findings are discussed in relation to previous physiological observations of responses to nociceptive stimuli in man and primates.
Abstract Biological agents are the most complex systems humans have to model and predict. In predictive coding, high-level cortical areas inform sensory cortex about incoming sensory signals, a comparison between the predicted and actual sensory feedback is made and information about unpredicted sensory information is passed forward to higher-level areas. Predictions about animate motion – relative to inanimate motion – should result in prediction error and increase signal passing from lower level sensory area MT+/V5, which is responsive to all motion, to higher-order posterior superior temporal sulcus (pSTS), which is selectively activated by animate motion. We tested this hypothesis by investigating effective connectivity in a large-scale fMRI dataset from the Human Connectome Project. 132 participants viewed animations of triangles that were designed to move in a way that appeared animate (moving intentionally), or inanimate (moving in a mechanical way). We found that forward connectivity from V5 to the pSTS increased and inhibitory self-connection in the pSTS decreased, when viewing intentional motion versus inanimate motion. These prediction errors associated with animate motion may be the cause for increased attention to animate stimuli found in previous studies.
How much about our interactions with—and experience of—our world can be deduced from basic principles? This paper reviews recent attempts to understand the self-organised behaviour of embodied agents, like ourselves, as satisfying basic imperatives for sustained exchanges with the environment. In brief, one simple driving force appears to explain many aspects of perception, action and the perception of action. This driving force is the minimisation of surprise or prediction error, which—in the context of perception—corresponds to Bayes-optimal predictive coding (that suppresses exteroceptive prediction errors) and—in the context of action—reduces to classical motor reflexes (that suppress proprioceptive prediction errors). In what follows, we look at some of the phenomena that emerge from this single principle, such as the perceptual encoding of spatial trajectories that can both generate movement (of self) and recognise the movements (of others). These emergent behaviours rest upon prior beliefs about itinerant (wandering) states of the world—but where do these beliefs come from? In this paper, we focus on the nature of prior beliefs and how they underwrite the active sampling of a spatially extended sensorium. Put simply, to avoid surprising states of the world, it is necessary to minimise uncertainty about those states. When this minimisation is implemented via prior beliefs—about how we sample the world—the resulting behaviour is remarkably reminiscent of searches seen in foraging or visual searches with saccadic eye movements.
Traditionally, short-term memory (STM) has been assessed by asking participants to remember words, visual objects, or numbers for a short amount of time before their recall or recognition of those items is tested. However, this focus on memory for past sensory input might have obscured potential theoretical insights into the function of this cognitive faculty. Here, we suggest that STM may have an important role in predicting future sensory input. This reconceptualization of STM may provide a functional explanation for its capacity limitation.
Given that eye movement control can be framed as an inferential process, how are the requisite forces generated to produce anticipated or desired fixation? Starting from a generative model based on simple Newtonian equations of motion, we derive a variational solution to this problem and illustrate the plausibility of its implementation in the oculomotor brainstem. We show, through simulation, that the Bayesian filtering equations that implement 'planning as inference' can generate both saccadic and smooth pursuit eye movements. Crucially, the associated message passing maps well onto the known connectivity and neuroanatomy of the brainstem – and the changes in these messages over time are strikingly similar to single unit recordings of neurons in the corresponding nuclei. Furthermore, we show that simulated lesions to axonal pathways reproduce eye movement patterns of neurological patients with damage to these tracts.
The neural mechanisms involved in the selective processing of salient or behaviourally important stimuli are uncertain. We used an aversive conditioning paradigm in human volunteer subjects to manipulate the salience of visual stimuli (emotionally expressive faces) presented during positron emission tomography (PET) neuroimaging. Increases in salience, and conflicts between the innate and acquired value of the stimuli, produced augmented activation of the pulvinar nucleus of the right thalamus. Furthermore, this pulvinar activity correlated positively with responses in structures hypothesized to mediate value in the brain–right amygdala and basal forebrain (including the cholinergic nucleus basalis of Meynert). The results provide evidence that the pulvinar nucleus of the thalamus plays a crucial modulatory role in selective visual processing, and that changes in perceptual salience are mediated by value–dependent plasticity in pulvinar responses.
Although MEG/EEG signals are highly variable, systematic changes in distinct frequency bands are commonly encountered. These frequency-specific changes represent robust neural correlates of cognitive or perceptual processes (for example, alpha rhythms emerge on closing the eyes). However, their functional significance remains a matter of debate. Some of the mechanisms that generate these signals are known at the cellular level and rest on a balance of excitatory and inhibitory interactions within and between populations of neurons. The kinetics of the ensuing population dynamics determine the frequency of oscillations. In this work we extended the classical nonlinear lumped-parameter model of alpha rhythms, initially developed by Lopes da Silva and colleagues [Kybernetik 15 (1974) 27], to generate more complex dynamics. We show that the whole spectrum of MEG/EEG signals can be reproduced within the oscillatory regime of this model by simply changing the population kinetics. We used the model to examine the influence of coupling strength and propagation delay on the rhythms generated by coupled cortical areas. The main findings were that (1) coupling induces phase-locked activity, with a phase shift of 0 or π when the coupling is bidirectional, and (2) both coupling and propagation delay are critical determinants of the MEG/EEG spectrum. In forthcoming articles, we will use this model to (1) estimate how neuronal interactions are expressed in MEG/EEG oscillations and establish the construct validity of various indices of nonlinear coupling, and (2) generate event-related transients to derive physiologically informed basis functions for statistical modelling of average evoked responses.
This work represents an attempt to bring together two important themes in neuronal dynamics. The first is the characterization of dynamic correlations in multiunit recordings of spike activity using joint-peri-stimulus time histograms (J-PSTHs) [Aertsen and Preissl, 1991: Non Linear Dynamics and Neural Networks]. The second is transient phase-locking at high (gamma) frequencies, either in terms of spiking in separable spike trains [e.g., Eckhorn et al., 1988: Biol Cybern 60:121–130, Gray and Singer, 1989 Proc Natl Acad Sci USA 86:1698–1702], or using continuous electrical or biomagnetic signals [e.g., Desmedt and Tomberg, 1994 Neurosci Lett 168:126–129]. In this paper we suggest that transient phase-locking is necessary for frequency-specific, dynamic event-related correlations. This point is demonstrated using the gamma-frequency (36 Hz) component of neuromagnetic signals measured in the prefrontal and partial regions of a subject during self-paced movements. A J-PSTH analysis revealed dynamic changes in prefronto-parietal correlations in relation to movement onset. These frequency-specific dynamic correlations were associated with changes in the degree of phase-locking, of the sort reported by Desmedt and Tomberg [1994 Neurosci Lett 168:126–129]. Hum. Brain Mapping 5:48–57, 1997. © 1997 Wiley-Liss, Inc.
