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James A Roberts, Karl J Friston, Michael Breakspear
Brain activity derives from intrinsic dynamics (due to neurophysiology and anatomical connectivity) in concert with stochastic effects that arise from sensory fluctuations, brainstem discharges, and random microscopic states such as thermal noise. The dynamic evolution of systems composed of both dynamic and random fluctuations can be studied with stochastic dynamic models (SDMs). This article, Part II of a two-part series, reviews applications of SDMs to large-scale neural systems in health and disease. Stochastic models have already elucidated a number of pathophysiological phenomena, such as epilepsy and hypoxic ischemic encephalopathy, although their use in biological psychiatry remains rather nascent...
April 2017: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
James A Roberts, Karl J Friston, Michael Breakspear
Biological phenomena arise through interactions between an organism's intrinsic dynamics and stochastic forces-random fluctuations due to external inputs, thermal energy, or other exogenous influences. Dynamic processes in the brain derive from neurophysiology and anatomical connectivity; stochastic effects arise through sensory fluctuations, brainstem discharges, and random microscopic states such as thermal noise. The dynamic evolution of systems composed of both dynamic and random effects can be studied with stochastic dynamic models (SDMs)...
April 2017: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
Thomas Parr, Geraint Rees, Karl J Friston
Computational theories of brain function have become very influential in neuroscience. They have facilitated the growth of formal approaches to disease, particularly in psychiatric research. In this paper, we provide a narrative review of the body of computational research addressing neuropsychological syndromes, and focus on those that employ Bayesian frameworks. Bayesian approaches to understanding brain function formulate perception and action as inferential processes. These inferences combine 'prior' beliefs with a generative (predictive) model to explain the causes of sensations...
2018: Frontiers in Human Neuroscience
Gabriel Ziegler, Patrick Grabher, Alan Thompson, Daniel Altmann, Markus Hupp, John Ashburner, Karl Friston, Nikolaus Weiskopf, Armin Curt, Patrick Freund
OBJECTIVE: To quantify atrophy, demyelination, and iron accumulation over 2 years following acute spinal cord injury and to identify MRI predictors of clinical outcomes and determine their suitability as surrogate markers of therapeutic intervention. METHODS: We assessed 156 quantitative MRI datasets from 15 patients with spinal cord injury and 18 controls at baseline and 2, 6, 12, and 24 months after injury. Clinical recovery (including neuropathic pain) was assessed at each time point...
March 7, 2018: Neurology
James E Clark, Stuart Watson, Karl J Friston
The neurobiological understanding of mood, and by extension mood disorders, remains elusive despite decades of research implicating several neuromodulator systems. This review considers a new approach based on existing theories of functional brain organisation. The free energy principle (a.k.a. active inference), and its instantiation in the Bayesian brain, offers a complete and simple formulation of mood. It has been proposed that emotions reflect the precision of - or certainty about - the predicted sensorimotor/interoceptive consequences of action...
February 26, 2018: Psychological Medicine
Giovanni Pezzulo, Francesco Rigoli, Karl J Friston
Motivated control refers to the coordination of behaviour to achieve affectively valenced outcomes or goals. The study of motivated control traditionally assumes a distinction between control and motivational processes, which map to distinct (dorsolateral versus ventromedial) brain systems. However, the respective roles and interactions between these processes remain controversial. We offer a novel perspective that casts control and motivational processes as complementary aspects - goal propagation and prioritization, respectively - of active inference and hierarchical goal processing under deep generative models...
February 20, 2018: Trends in Cognitive Sciences
Thomas Parr, Karl J Friston
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...
January 30, 2018: Neuropsychologia
Michael Kirchhoff, Thomas Parr, Ensor Palacios, Karl Friston, Julian Kiverstein
This work addresses the autonomous organization of biological systems. It does so by considering the boundaries of biological systems, from individual cells to Home sapiens, in terms of the presence of Markov blankets under the active inference scheme-a corollary of the free energy principle. A Markov blanket defines the boundaries of a system in a statistical sense. Here we consider how a collective of Markov blankets can self-assemble into a global system that itself has a Markov blanket; thereby providing an illustration of how autonomous systems can be understood as having layers of nested and self-sustaining boundaries...
January 2018: Journal of the Royal Society, Interface
Andrew P Owens, Karl J Friston, David A Low, Christopher J Mathias, Hugo D Critchley
Predictive coding models, such as the 'free-energy principle' (FEP), have recently been discussed in relation to how interoceptive (afferent visceral feedback) signals update predictions about the state of the body, thereby driving autonomic mediation of homeostasis. This study appealed to 'interoceptive inference', under the FEP, to seek new insights into autonomic (dys)function and brain-body integration by examining the relationship between cardiac interoception and autonomic cardiac control in healthy controls and patients with forms of orthostatic intolerance (OI); to (i) seek empirical support for interoceptive inference and (ii) delineate if this relationship was sensitive to increased interoceptive prediction error in OI patients during head-up tilt (HUT)/symptom provocation...
January 9, 2018: Autonomic Neuroscience: Basic & Clinical
Roberto Limongi, Bartosz Bohaterewicz, Magdalena Nowicka, Aleksandra Plewka, Karl J Friston
Predictive coding and active inference formulations of the dysconnection hypothesis suggest that subjects with schizophrenia (SZ) hold unduly precise prior beliefs to compensate for a failure of sensory attenuation. This implies that SZ subjects should both initiate responses prematurely during evidence-accumulation tasks and fail to inhibit their responses at long stop-signal delays. SZ and healthy control subjects were asked to report the timing of billiards-ball collisions and were occasionally required to withhold their responses...
January 10, 2018: Schizophrenia Research
Maxwell J D Ramstead, Paul B Badcock, Karl J Friston
No abstract text is available yet for this article.
January 8, 2018: Physics of Life Reviews
M Berk Mirza, Rick A Adams, Christoph Mathys, Karl J Friston
In previous papers, we introduced a normative scheme for scene construction and epistemic (visual) searches based upon active inference. This scheme provides a principled account of how people decide where to look, when categorising a visual scene based on its contents. In this paper, we use active inference to explain the visual searches of normal human subjects; enabling us to answer some key questions about visual foraging and salience attribution. First, we asked whether there is any evidence for 'epistemic foraging'; i...
2018: PloS One
Kyesam Jung, Karl J Friston, Chongwon Pae, Hanseul Choi, Sungho Tak, Yoon Kyoung Choi, Bumhee Park, Chan-A Park, Chaejoon Cheong, Hae-Jeong Park
Although the relationship between resting-state functional connectivity and task-related activity has been addressed, the relationship between task and resting-state directed or effective connectivity - and its behavioral concomitants - remains elusive. We evaluated effective connectivity under an N-back working memory task in 24 participants using stochastic dynamic causal modelling (DCM) of 7 Tesla fMRI data. We repeated the analysis using resting-state data, from the same subjects, to model connectivity among the same brain regions engaged by the N-back task...
December 25, 2017: NeuroImage
Ryszard Auksztulewicz, Karl J Friston, Anna C Nobre
The brain is thought to generate internal predictions to optimize behaviour. However, it is unclear whether predictions signalling is an automatic brain function or depends on task demands. Here, we manipulated the spatial/temporal predictability of visual targets, and the relevance of spatial/temporal information provided by auditory cues. We used magnetoencephalography (MEG) to measure participants' brain activity during task performance. Task relevance modulated the influence of predictions on behaviour: spatial/temporal predictability improved spatial/temporal discrimination accuracy, but not vice versa...
December 2017: PLoS Biology
Thomas Parr, Karl J Friston
Visual neglect is a debilitating neuropsychological phenomenon that has many clinical implications and-in cognitive neuroscience-offers an important lesion deficit model. In this article, we describe a computational model of visual neglect based upon active inference. Our objective is to establish a computational and neurophysiological process theory that can be used to disambiguate among the various causes of this important syndrome; namely, a computational neuropsychology of visual neglect. We introduce a Bayes optimal model based upon Markov decision processes that reproduces the visual searches induced by the line cancellation task (used to characterize visual neglect at the bedside)...
February 1, 2018: Cerebral Cortex
Thomas Parr, Karl J Friston
Biological systems-like ourselves-are constantly faced with uncertainty. Despite noisy sensory data, and volatile environments, creatures appear to actively maintain their integrity. To account for this remarkable ability to make optimal decisions in the face of a capricious world, we propose a generative model that represents the beliefs an agent might possess about their own uncertainty. By simulating a noisy and volatile environment, we demonstrate how uncertainty influences optimal epistemic (visual) foraging...
November 2017: Journal of the Royal Society, Interface
Yuan Zhou, Karl J Friston, Peter Zeidman, Jie Chen, Shu Li, Adeel Razi
An important characteristic of spontaneous brain activity is the anticorrelation between the core default network (cDN) and the dorsal attention network (DAN) and the salience network (SN). This anticorrelation may constitute a key aspect of functional anatomy and is implicated in several brain disorders. We used dynamic causal modeling to assess the hypothesis that a causal hierarchy underlies this anticorrelation structure, using resting-state fMRI of healthy adolescent and young adults (N = 404). Our analysis revealed an asymmetric effective connectivity, such that the regions in the SN and DAN exerted an inhibitory influence on the cDN regions; whereas the cDN exerted an excitatory influence on the SN and DAN regions...
November 17, 2017: Cerebral Cortex
Hae-Jeong Park, Karl J Friston, Chongwon Pae, Bumhee Park, Adeel Razi
Context-sensitive and activity-dependent fluctuations in connectivity underlie functional integration in the brain and have been studied widely in terms of synaptic plasticity, learning and condition-specific (e.g., attentional) modulations of synaptic efficacy. This dynamic aspect of brain connectivity has recently attracted a lot of attention in the resting state fMRI community. To explain dynamic functional connectivity in terms of directed effective connectivity among brain regions, we introduce a novel method to identify dynamic effective connectivity using spectral dynamic causal modelling (spDCM)...
November 20, 2017: NeuroImage
Thomas Parr, Karl J Friston
The psychological concepts of working memory and attention are widely used in the cognitive and neuroscientific literatures. Perhaps because of the interdisciplinary appeal of these concepts, the same terms are often used to mean very different things. Drawing on recent advances in theoretical neurobiology, this paper tries to highlight the correspondence between these established psychological constructs and the formal processes implicit in mathematical descriptions of brain function. Here, we consider attention and salience from the perspective offered by active inference...
November 7, 2017: Scientific Reports
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