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Karl Friston

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https://www.readbyqxmd.com/read/28226255/action-perception-as-hypothesis-testing
#1
Francesco Donnarumma, Marcello Costantini, Ettore Ambrosini, Karl Friston, Giovanni Pezzulo
We present a novel computational model that describes action perception as an active inferential process that combines motor prediction (the reuse of our own motor system to predict perceived movements) and hypothesis testing (the use of eye movements to disambiguate amongst hypotheses). The system uses a generative model of how (arm and hand) actions are performed to generate hypothesis-specific visual predictions, and directs saccades to the most informative places of the visual scene to test these predictions - and underlying hypotheses...
January 31, 2017: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
https://www.readbyqxmd.com/read/28224285/abnormal-effective-connectivity-in-the-brain-is-involved-in-auditory-verbal-hallucinations-in-schizophrenia
#2
Baojuan Li, Long-Biao Cui, Yi-Bin Xi, Karl J Friston, Fan Guo, Hua-Ning Wang, Lin-Chuan Zhang, Yuan-Han Bai, Qing-Rong Tan, Hong Yin, Hongbing Lu
Information flow among auditory and language processing-related regions implicated in the pathophysiology of auditory verbal hallucinations (AVHs) in schizophrenia (SZ) remains unclear. In this study, we used stochastic dynamic causal modeling (sDCM) to quantify connections among the left dorsolateral prefrontal cortex (inner speech monitoring), auditory cortex (auditory processing), hippocampus (memory retrieval), thalamus (information filtering), and Broca's area (language production) in 17 first-episode drug-naïve SZ patients with AVHs, 15 without AVHs, and 19 healthy controls using resting-state functional magnetic resonance imaging...
February 21, 2017: Neuroscience Bulletin
https://www.readbyqxmd.com/read/28161288/the-depressed-brain-an-evolutionary-systems-theory
#3
REVIEW
Paul B Badcock, Christopher G Davey, Sarah Whittle, Nicholas B Allen, Karl J Friston
Major depression is a debilitating condition characterised by diverse neurocognitive and behavioural deficits. Nevertheless, our species-typical capacity for depressed mood implies that it serves an adaptive function. Here we apply an interdisciplinary theory of brain function to explain depressed mood and its clinical manifestations. Combining insights from the free-energy principle (FEP) with evolutionary theorising in psychology, we argue that depression reflects an adaptive response to perceived threats of aversive social outcomes (e...
February 1, 2017: Trends in Cognitive Sciences
https://www.readbyqxmd.com/read/28081125/the-neural-representation-of-prospective-choice-during-spatial-planning-and-decisions
#4
Raphael Kaplan, John King, Raphael Koster, William D Penny, Neil Burgess, Karl J Friston
We are remarkably adept at inferring the consequences of our actions, yet the neuronal mechanisms that allow us to plan a sequence of novel choices remain unclear. We used functional magnetic resonance imaging (fMRI) to investigate how the human brain plans the shortest path to a goal in novel mazes with one (shallow maze) or two (deep maze) choice points. We observed two distinct anterior prefrontal responses to demanding choices at the second choice point: one in rostrodorsal medial prefrontal cortex (rd-mPFC)/superior frontal gyrus (SFG) that was also sensitive to (deactivated by) demanding initial choices and another in lateral frontopolar cortex (lFPC), which was only engaged by demanding choices at the second choice point...
January 2017: PLoS Biology
https://www.readbyqxmd.com/read/28080966/active-interoceptive-inference-and-the-emotional-brain
#5
REVIEW
Anil K Seth, Karl J Friston
We review a recent shift in conceptions of interoception and its relationship to hierarchical inference in the brain. The notion of interoceptive inference means that bodily states are regulated by autonomic reflexes that are enslaved by descending predictions from deep generative models of our internal and external milieu. This re-conceptualization illuminates several issues in cognitive and clinical neuroscience with implications for experiences of selfhood and emotion. We first contextualize interoception in terms of active (Bayesian) inference in the brain, highlighting its enactivist (embodied) aspects...
November 19, 2016: Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
https://www.readbyqxmd.com/read/28044016/is-predictability-salient-a-study-of-attentional-capture-by-auditory-patterns
#6
Rosy Southwell, Anna Baumann, Cécile Gal, Nicolas Barascud, Karl Friston, Maria Chait
In this series of behavioural and electroencephalography (EEG) experiments, we investigate the extent to which repeating patterns of sounds capture attention. Work in the visual domain has revealed attentional capture by statistically predictable stimuli, consistent with predictive coding accounts which suggest that attention is drawn to sensory regularities. Here, stimuli comprised rapid sequences of tone pips, arranged in regular (REG) or random (RAND) patterns. EEG data demonstrate that the brain rapidly recognizes predictable patterns manifested as a rapid increase in responses to REG relative to RAND sequences...
February 19, 2017: Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
https://www.readbyqxmd.com/read/28018185/life-and-understanding-the-origins-of-understanding-in-self-organizing-nervous-systems
#7
REVIEW
Yan M Yufik, Karl Friston
This article is motivated by a formulation of biotic self-organization in Friston (2013), where the emergence of "life" in coupled material entities (e.g., macromolecules) was predicated on bounded subsets that maintain a degree of statistical independence from the rest of the network. Boundary elements in such systems constitute a Markov blanket; separating the internal states of a system from its surrounding states. In this article, we ask whether Markov blankets operate in the nervous system and underlie the development of intelligence, enabling a progression from the ability to sense the environment to the ability to understand it...
2016: Frontiers in Systems Neuroscience
https://www.readbyqxmd.com/read/28007997/stimulating-at-the-right-time-phase-specific-deep-brain-stimulation
#8
Hayriye Cagnan, David Pedrosa, Simon Little, Alek Pogosyan, Binith Cheeran, Tipu Aziz, Alexander Green, James Fitzgerald, Thomas Foltynie, Patricia Limousin, Ludvic Zrinzo, Marwan Hariz, Karl J Friston, Timothy Denison, Peter Brown
SEE MOLL AND ENGEL DOI101093/AWW308 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Brain regions dynamically engage and disengage with one another to execute everyday actions from movement to decision making. Pathologies such as Parkinson's disease and tremor emerge when brain regions controlling movement cannot readily decouple, compromising motor function. Here, we propose a novel stimulation strategy that selectively regulates neural synchrony through phase-specific stimulation. We demonstrate for the first time the therapeutic potential of such a stimulation strategy for the treatment of patients with pathological tremor...
January 2017: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/27996022/perceptual-learning-to-discriminate-the-intensity-and-spatial-location-of-nociceptive-stimuli
#9
Flavia Mancini, Karina Dolgevica, James Steckelmacher, Patrick Haggard, Karl Friston, Giandomenico D Iannetti
Accurate discrimination of the intensity and spatial location of nociceptive stimuli is essential to guide appropriate behaviour. The ability to discriminate the attributes of sensory stimuli is continuously refined by practice, even throughout adulthood - a phenomenon called perceptual learning. In the visual domain, perceptual learning to discriminate one of the features that define a visual stimulus (e.g., its orientation) can transfer to a different feature of the same stimulus (e.g., its contrast). Here, we performed two experiments on 48 volunteers to characterize perceptual learning in nociception, which has been rarely studied...
December 20, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27913429/heritability-of-the-effective-connectivity-in-the-resting-state-default-mode-network
#10
Junhai Xu, Xuntao Yin, Haitao Ge, Yan Han, Zengchang Pang, Baolin Liu, Shuwei Liu, Karl Friston
The default mode network (DMN) is thought to reflect endogenous neural activity, which is considered as one of the most intriguing phenomena in cognitive neuroscience. Previous studies have found that key regions within the DMN are highly interconnected. Here, we characterized the genetic influences on causal or directed information flow within the DMN during the resting state. In this study, we recruited 46 pairs of twins and collected fMRI imaging data using a 3.0 T scanner. Dynamic causal modeling was conducted for each participant, and a structural equation model was used to calculate the heritability of DMN in terms of its effective connectivity...
November 23, 2016: Cerebral Cortex
https://www.readbyqxmd.com/read/27871729/an-integrative-tinnitus-model-based-on-sensory-precision
#11
REVIEW
William Sedley, Karl J Friston, Phillip E Gander, Sukhbinder Kumar, Timothy D Griffiths
Tinnitus is a common disorder that often complicates hearing loss. Its mechanisms are incompletely understood. Current theories proposing pathophysiology from the ear to the cortex cannot individually - or collectively - explain the range of experimental evidence available. We propose a new framework, based on predictive coding, in which spontaneous activity in the subcortical auditory pathway constitutes a 'tinnitus precursor' which is normally ignored as imprecise evidence against the prevailing percept of 'silence'...
December 2016: Trends in Neurosciences
https://www.readbyqxmd.com/read/27870614/active-inference-a-process-theory
#12
Karl Friston, Thomas FitzGerald, Francesco Rigoli, Philipp Schwartenbeck, Giovanni Pezzulo
This article describes a process theory based on active inference and belief propagation. Starting from the premise that all neuronal processing (and action selection) can be explained by maximizing Bayesian model evidence-or minimizing variational free energy-we ask whether neuronal responses can be described as a gradient descent on variational free energy. Using a standard (Markov decision process) generative model, we derive the neuronal dynamics implicit in this description and reproduce a remarkable range of well-characterized neuronal phenomena...
January 2017: Neural Computation
https://www.readbyqxmd.com/read/27718099/bayesian-modelling-of-induced-responses-and-neuronal-rhythms
#13
Dimitris A Pinotsis, Roman Loonis, Andre M Bastos, Earl K Miller, Karl J Friston
Neural rhythms or oscillations are ubiquitous in neuroimaging data. These spectral responses have been linked to several cognitive processes; including working memory, attention, perceptual binding and neuronal coordination. In this paper, we show how Bayesian methods can be used to finesse the ill-posed problem of reconstructing-and explaining-oscillatory responses. We offer an overview of recent developments in this field, focusing on (i) the use of MEG data and Empirical Bayes to build hierarchical models for group analyses-and the identification of important sources of inter-subject variability and (ii) the construction of novel dynamic causal models of intralaminar recordings to explain layer-specific activity...
October 7, 2016: Brain Topography
https://www.readbyqxmd.com/read/27683898/neural-signatures-of-value-comparison-in-human-cingulate-cortex-during-decisions-requiring-an-effort-reward-trade-off
#14
Miriam C Klein-Flügge, Steven W Kennerley, Karl Friston, Sven Bestmann
UNLABELLED: Integrating costs and benefits is crucial for optimal decision-making. Although much is known about decisions that involve outcome-related costs (e.g., delay, risk), many of our choices are attached to actions and require an evaluation of the associated motor costs. Yet how the brain incorporates motor costs into choices remains largely unclear. We used human fMRI during choices involving monetary reward and physical effort to identify brain regions that serve as a choice comparator for effort-reward trade-offs...
September 28, 2016: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/27683002/active-inference-and-robot-control-a-case-study
#15
Léo Pio-Lopez, Ange Nizard, Karl Friston, Giovanni Pezzulo
Active inference is a general framework for perception and action that is gaining prominence in computational and systems neuroscience but is less known outside these fields. Here, we discuss a proof-of-principle implementation of the active inference scheme for the control or the 7-DoF arm of a (simulated) PR2 robot. By manipulating visual and proprioceptive noise levels, we show under which conditions robot control under the active inference scheme is accurate. Besides accurate control, our analysis of the internal system dynamics (e...
September 2016: Journal of the Royal Society, Interface
https://www.readbyqxmd.com/read/27639356/dynamic-causal-modelling-of-seizure-activity-in-a-rat-model
#16
Margarita Papadopoulou, Gerald Cooray, Richard Rosch, Rosalyn Moran, Daniele Marinazzo, Karl Friston
This paper presents a physiological account of seizure activity and its evolution over time using a rat model of induced epilepsy. We analyse spectral activity recorded in the hippocampi of three rats who received kainic acid injections in the right hippocampus. We use dynamic causal modelling of seizure activity and Bayesian model reduction to identify the key synaptic and connectivity parameters that underlie seizure onset. Using recent advances in hierarchical modelling (parametric empirical Bayes), we characterise seizure onset in terms of slow fluctuations in synaptic excitability of specific neuronal populations...
February 1, 2017: NeuroImage
https://www.readbyqxmd.com/read/27593199/intersubject-variability-and-induced-gamma-in-the-visual-cortex-dcm-with-empirical-bayes-and-neural-fields
#17
Dimitris A Pinotsis, Gavin Perry, Vladimir Litvak, Krish D Singh, Karl J Friston
This article describes the first application of a generic (empirical) Bayesian analysis of between-subject effects in the dynamic causal modeling (DCM) of electrophysiological (MEG) data. It shows that (i) non-invasive (MEG) data can be used to characterize subject-specific differences in cortical microcircuitry and (ii) presents a validation of DCM with neural fields that exploits intersubject variability in gamma oscillations. We find that intersubject variability in visually induced gamma responses reflects changes in the excitation-inhibition balance in a canonical cortical circuit...
December 2016: Human Brain Mapping
https://www.readbyqxmd.com/read/27535770/neural-processes-mediating-contextual-influences-on-human-choice-behaviour
#18
Francesco Rigoli, Karl J Friston, Raymond J Dolan
Contextual influences on choice are ubiquitous in ecological settings. Current evidence suggests that subjective values are normalized with respect to the distribution of potentially available rewards. However, how this context-sensitivity is realised in the brain remains unknown. To address this, here we examine functional magnetic resonance imaging (fMRI) data during performance of a gambling task where blocks comprise values drawn from one of two different, but partially overlapping, reward distributions or contexts...
August 18, 2016: Nature Communications
https://www.readbyqxmd.com/read/27517087/computational-phenotyping-in-psychiatry-a-worked-example
#19
Philipp Schwartenbeck, Karl Friston
Computational psychiatry is a rapidly emerging field that uses model-based quantities to infer the behavioral and neuronal abnormalities that underlie psychopathology. If successful, this approach promises key insights into (pathological) brain function as well as a more mechanistic and quantitative approach to psychiatric nosology-structuring therapeutic interventions and predicting response and relapse. The basic procedure in computational psychiatry is to build a computational model that formalizes a behavioral or neuronal process...
July 2016: ENeuro
https://www.readbyqxmd.com/read/27506256/bridging-the-gap-dynamic-causal-modeling-and-granger-causality-analysis-of-resting-state-functional-magnetic-resonance-imaging
#20
Sahil Bajaj, Bhim M Adhikari, Karl J Friston, Mukesh Dhamala
Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to determine the directed interactions among brain areas. Recent discussions have provided a constructive account of the merits and demerits. GC, on one side, considers dependencies among measured responses, whereas DCM, on the other, models how neuronal activity in one brain area causes dynamics in another. In this study, our objective was to establish construct validity between GC and DCM in the context of resting state functional magnetic resonance imaging (fMRI)...
September 16, 2016: Brain Connectivity
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