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https://www.readbyqxmd.com/read/28416414/deep-temporal-models-and-active-inference
#1
REVIEW
Karl J Friston, Richard Rosch, Thomas Parr, Cathy Price, Howard Bowman
How do we navigate a deeply structured world? Why are you reading this sentence first - and did you actually look at the fifth word? This review offers some answers by appealing to active inference based on deep temporal models. It builds on previous formulations of active inference to simulate behavioural and electrophysiological responses under hierarchical generative models of state transitions. Inverting these models corresponds to sequential inference, such that the state at any hierarchical level entails a sequence of transitions in the level below...
April 14, 2017: Neuroscience and Biobehavioral Reviews
https://www.readbyqxmd.com/read/28408874/editorial-mapping-psychopathology-with-fmri-and-effective-connectivity-analysis
#2
EDITORIAL
Baojuan Li, Adeel Razi, Karl J Friston
No abstract text is available yet for this article.
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28382008/a-goal-directed-bayesian-framework-for-categorization
#3
Francesco Rigoli, Giovanni Pezzulo, Raymond Dolan, Karl Friston
Categorization is a fundamental ability for efficient behavioral control. It allows organisms to remember the correct responses to categorical cues and not for every stimulus encountered (hence eluding computational cost or complexity), and to generalize appropriate responses to novel stimuli dependant on category assignment. Assuming the brain performs Bayesian inference, based on a generative model of the external world and future goals, we propose a computational model of categorization in which important properties emerge...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28345275/abnormal-frontoparietal-synaptic-gain-mediating-the-p300-in-patients-with-psychotic-disorder-and-their-unaffected-relatives
#4
Álvaro Díez, Siri Ranlund, Dimitris Pinotsis, Stella Calafato, Madiha Shaikh, Mei-Hua Hall, Muriel Walshe, Ángel Nevado, Karl J Friston, Rick A Adams, Elvira Bramon
The "dysconnection hypothesis" of psychosis suggests that a disruption of functional integration underlies cognitive deficits and clinical symptoms. Impairments in the P300 potential are well documented in psychosis. Intrinsic (self-)connectivity in a frontoparietal cortical hierarchy during a P300 experiment was investigated. Dynamic Causal Modeling was used to estimate how evoked activity results from the dynamics of coupled neural populations and how neural coupling changes with the experimental factors...
March 27, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28345153/the-functional-architectures-of-addition-and-subtraction-network-discovery-using-fmri-and-dcm
#5
Yang Yang, Ning Zhong, Karl Friston, Kazuyuki Imamura, Shengfu Lu, Mi Li, Haiyan Zhou, Haiyuan Wang, Kuncheng Li, Bin Hu
The neuronal mechanisms underlying arithmetic calculations are not well understood but the differences between mental addition and subtraction could be particularly revealing. Using fMRI and dynamic causal modeling (DCM), this study aimed to identify the distinct neuronal architectures engaged by the cognitive processes of simple addition and subtraction. Our results revealed significantly greater activation during subtraction in regions along the dorsal pathway, including the left inferior frontal gyrus (IFG), middle portion of dorsolateral prefrontal cortex (mDLPFC), and supplementary motor area (SMA), compared with addition...
March 27, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28341164/expectation-violation-and-attention-to-pain-jointly-modulate-neural-gain-in-somatosensory-cortex
#6
Francesca Fardo, Ryszard Auksztulewicz, Micah Allen, Martin J Dietz, Andreas Roepstorff, Karl J Friston
The neural processing and experience of pain are influenced by both expectations and attention. For example, the amplitude of event-related pain responses is enhanced by both novel and unexpected pain, and by moving the focus of attention towards a painful stimulus. Under predictive coding, this congruence can be explained by appeal to a precision-weighting mechanism, which mediates bottom-up and top-down attentional processes by modulating the influence of feedforward and feedback signals throughout the cortical hierarchy...
March 21, 2017: NeuroImage
https://www.readbyqxmd.com/read/28338892/embodiment-and-schizophrenia-a-review-of-implications-and-applications
#7
Wolfgang Tschacher, Anne Giersch, Karl Friston
In recent decades, embodiment has become an influential concept in psychology and cognitive neuroscience. Embodiment denotes the study of the reciprocal (causal) relationships between mind and body, with the mind not only affecting the body but also vice versa. Embodied cognition comes to the fore in sensorimotor coupling, predictive coding, and nonverbal behavior. Additionally, the embodiment of the mind constitutes the basis of social interaction and communication, as evident in research on nonverbal synchrony and mimicry...
March 3, 2017: Schizophrenia Bulletin
https://www.readbyqxmd.com/read/28334138/working-memory-modulation-of-frontoparietal-network-connectivity-in-first-episode-schizophrenia
#8
Jesper Duemose Nielsen, Kristoffer H Madsen, Zheng Wang, Zhening Liu, Karl J Friston, Yuan Zhou
Working memory (WM) impairment is regarded as a core aspect of schizophrenia. However, the neural mechanisms behind this cognitive deficit remain unclear. The connectivity of a frontoparietal network is known to be important for subserving WM. Using functional magnetic resonance imaging, the current study investigated whether WM-dependent modulation of effective connectivity in this network is affected in a group of first-episode schizophrenia (FES) patients compared with similarly performing healthy participants during a verbal n-back task...
February 25, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/28323165/on-the-importance-of-modeling-fmri-transients-when-estimating-effective-connectivity-a-dynamic-causal-modeling-study-using-asl-data
#9
Martin Havlicek, Alard Roebroeck, Karl J Friston, Anna Gardumi, Dimo Ivanov, Kamil Uludag
Effective connectivity is commonly assessed using blood oxygenation level-dependent (BOLD) signals. In (Havlicek et al., 2015), we presented a novel, physiologically informed dynamic causal model (P-DCM) that extends current generative models. We demonstrated the improvements afforded by P-DCM in terms of the ability to model commonly observed neuronal and vascular transients in single regions. Here, we assess the ability of the novel and previous DCM variants to estimate effective connectivity among a network of five ROIs driven by a visuo-motor task...
March 16, 2017: NeuroImage
https://www.readbyqxmd.com/read/28316456/functional-connectivity-of-the-pedunculopontine-nucleus-and-surrounding-region-in-parkinson-s-disease
#10
Ashwani Jha, Vladimir Litvak, Samu Taulu, Wesley Thevathasan, Jonathan A Hyam, Tom Foltynie, Patricia Limousin, Marko Bogdanovic, Ludvic Zrinzo, Alexander L Green, Tipu Z Aziz, Karl Friston, Peter Brown
Deep brain stimulation of the pedunculopontine nucleus and surrounding region (PPNR) is a novel treatment strategy for gait freezing in Parkinson's disease (PD). However, clinical results have been variable, in part because of the paucity of functional information that might help guide selection of the optimal surgical target. In this study, we use simultaneous magnetoencephalography and local field recordings from the PPNR in seven PD patients, to characterize functional connectivity with distant brain areas at rest...
January 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/28298703/a-tutorial-on-the-free-energy-framework-for-modelling-perception-and-learning
#11
Rafal Bogacz
This paper provides an easy to follow tutorial on the free-energy framework for modelling perception developed by Friston, which extends the predictive coding model of Rao and Ballard. These models assume that the sensory cortex infers the most likely values of attributes or features of sensory stimuli from the noisy inputs encoding the stimuli. Remarkably, these models describe how this inference could be implemented in a network of very simple computational elements, suggesting that this inference could be performed by biological networks of neurons...
February 2017: Journal of Mathematical Psychology
https://www.readbyqxmd.com/read/28266640/corrigendum-perceptual-learning-to-discriminate-the-intensity-and-spatial-location-of-nociceptive-stimuli
#12
Flavia Mancini, Karina Dolgilevica, James Steckelmacher, Patrick Haggard, Karl Friston, Giandomenico D Iannetti
No abstract text is available yet for this article.
March 7, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28259780/regression-dcm-for-fmri
#13
Stefan Frässle, Ekaterina I Lomakina, Adeel Razi, Karl J Friston, Joachim M Buhmann, Klaas E Stephan
The development of large-scale network models that infer the effective (directed) connectivity among neuronal populations from neuroimaging data represents a key challenge for computational neuroscience. Dynamic causal models (DCMs) of neuroimaging and electrophysiological data are frequently used for inferring effective connectivity but are presently restricted to small graphs (typically up to 10 regions) in order to keep model inversion computationally feasible. Here, we present a novel variant of DCM for functional magnetic resonance imaging (fMRI) data that is suited to assess effective connectivity in large (whole-brain) networks...
March 1, 2017: NeuroImage
https://www.readbyqxmd.com/read/28240422/cerebellar-lobules-and-dentate-nuclei-mirror-cortical-force-related-bold-responses-beyond-all-linear-expectations
#14
Adnan A S Alahmadi, Matteo Pardini, Rebecca S Samson, Karl J Friston, Ahmed T Toosy, Egidio D'Angelo, Claudia A M Gandini Wheeler-Kingshott
The relationship between the BOLD response and an applied force was quantified in the cerebellum using a power grip task. To investigate whether the cerebellum responds in an on/off way to motor demands or contributes to motor responses in a parametric fashion, similarly to the cortex, five grip force levels were investigated under visual feedback. Functional MRI data were acquired in 13 healthy volunteers and their responses were analyzed using a cerebellum-optimized pipeline. This allowed us to evaluate, within the cerebellum, voxelwise linear and non-linear associations between cerebellar activations and forces...
February 27, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28226417/an-efficient-multistage-algorithm-for-full-calibration-of-the-hemodynamic-model-from-bold-signal-responses
#15
Brian Zambri, Rabia Djellouli, Taous-Meriem Laleg-Kirati
We propose a computational strategy that falls into the category of prediction/correction iterative-type approaches, for calibrating the hemodynamic model. The proposed method is used to estimate consecutively the values of the two sets of model parameters. Numerical results corresponding to both synthetic and real functional magnetic resonance imaging measurements for a single stimulus as well as for multiple stimuli are reported to highlight the capability of this computational methodology to fully calibrate the considered hemodynamic model...
February 22, 2017: International Journal for Numerical Methods in Biomedical Engineering
https://www.readbyqxmd.com/read/28226255/action-perception-as-hypothesis-testing
#16
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...
April 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
#17
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/28219774/dynamic-causal-modelling-revisited
#18
K J Friston, Katrin H Preller, Chris Mathys, Hayriye Cagnan, Jakob Heinzle, Adeel Razi, Peter Zeidman
This paper revisits the dynamic causal modelling of fMRI timeseries by replacing the usual (Taylor) approximation to neuronal dynamics with a neural mass model of the canonical microcircuit. This provides a generative or dynamic causal model of laminar specific responses that can generate haemodynamic and electrophysiological measurements. In principle, this allows the fusion of haemodynamic and (event related or induced) electrophysiological responses. Furthermore, it enables Bayesian model comparison of competing hypotheses about physiologically plausible synaptic effects; for example, does attentional modulation act on superficial or deep pyramidal cells - or both? In this technical note, we describe the resulting dynamic causal model and provide an illustrative application to the attention to visual motion dataset used in previous papers...
February 17, 2017: NeuroImage
https://www.readbyqxmd.com/read/28161288/the-depressed-brain-an-evolutionary-systems-theory
#19
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...
March 2017: Trends in Cognitive Sciences
https://www.readbyqxmd.com/read/28132931/assessing-uncertainty-in-dynamic-functional-connectivity
#20
Maria Kudela, Jaroslaw Harezlak, Martin A Lindquist
Functional connectivity (FC) - the study of the statistical association between time series from anatomically distinct regions (Friston, 1994, 2011) - has become one of the primary areas of research in the field surrounding resting state functional magnetic resonance imaging (rs-fMRI). Although for many years researchers have implicitly assumed that FC was stationary across time in rs-fMRI, it has recently become increasingly clear that this is not the case and the ability to assess dynamic changes in FC is critical for better understanding of the inner workings of the human brain (Hutchison et al...
April 1, 2017: NeuroImage
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