51
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Lumaca M, Dietz MJ, Hansen NC, Quiroga-Martinez DR, Vuust P. Perceptual learning of tone patterns changes the effective connectivity between Heschl's gyrus and planum temporale. Hum Brain Mapp 2020; 42:941-952. [PMID: 33146455 PMCID: PMC7856650 DOI: 10.1002/hbm.25269] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 10/06/2020] [Accepted: 10/15/2020] [Indexed: 11/11/2022] Open
Abstract
Learning of complex auditory sequences such as music can be thought of as optimizing an internal model of regularities through unpredicted events (or “prediction errors”). We used dynamic causal modeling (DCM) and parametric empirical Bayes on functional magnetic resonance imaging (fMRI) data to identify modulation of effective brain connectivity that takes place during perceptual learning of complex tone patterns. Our approach differs from previous studies in two aspects. First, we used a complex oddball paradigm based on tone patterns as opposed to simple deviant tones. Second, the use of fMRI allowed us to identify cortical regions with high spatial accuracy. These regions served as empirical regions‐of‐interest for the analysis of effective connectivity. Deviant patterns induced an increased blood oxygenation level‐dependent response, compared to standards, in early auditory (Heschl's gyrus [HG]) and association auditory areas (planum temporale [PT]) bilaterally. Within this network, we found a left‐lateralized increase in feedforward connectivity from HG to PT during deviant responses and an increase in excitation within left HG. In contrast to previous findings, we did not find frontal activity, nor did we find modulations of backward connections in response to oddball sounds. Our results suggest that complex auditory prediction errors are encoded by changes in feedforward and intrinsic connections, confined to superior temporal gyrus.
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Affiliation(s)
- Massimo Lumaca
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University and The Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark
| | - Martin J Dietz
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Niels Chr Hansen
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University and The Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark.,Aarhus Institute of Advanced Studies, Aarhus University, Aarhus, Denmark
| | - David R Quiroga-Martinez
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University and The Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark
| | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University and The Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark
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52
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Holmes E, Zeidman P, Friston KJ, Griffiths TD. Difficulties with Speech-in-Noise Perception Related to Fundamental Grouping Processes in Auditory Cortex. Cereb Cortex 2020; 31:1582-1596. [PMID: 33136138 PMCID: PMC7869094 DOI: 10.1093/cercor/bhaa311] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 08/04/2020] [Accepted: 09/22/2020] [Indexed: 01/05/2023] Open
Abstract
In our everyday lives, we are often required to follow a conversation when background noise is present (“speech-in-noise” [SPIN] perception). SPIN perception varies widely—and people who are worse at SPIN perception are also worse at fundamental auditory grouping, as assessed by figure-ground tasks. Here, we examined the cortical processes that link difficulties with SPIN perception to difficulties with figure-ground perception using functional magnetic resonance imaging. We found strong evidence that the earliest stages of the auditory cortical hierarchy (left core and belt areas) are similarly disinhibited when SPIN and figure-ground tasks are more difficult (i.e., at target-to-masker ratios corresponding to 60% rather than 90% performance)—consistent with increased cortical gain at lower levels of the auditory hierarchy. Overall, our results reveal a common neural substrate for these basic (figure-ground) and naturally relevant (SPIN) tasks—which provides a common computational basis for the link between SPIN perception and fundamental auditory grouping.
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Affiliation(s)
- Emma Holmes
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UCL, London WC1N 3AR, UK
| | - Peter Zeidman
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UCL, London WC1N 3AR, UK
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UCL, London WC1N 3AR, UK
| | - Timothy D Griffiths
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, UCL, London WC1N 3AR, UK.,Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
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53
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Banellis L, Sokoliuk R, Wild CJ, Bowman H, Cruse D. Event-related potentials reflect prediction errors and pop-out during comprehension of degraded speech. Neurosci Conscious 2020; 2020:niaa022. [PMID: 33133640 PMCID: PMC7585676 DOI: 10.1093/nc/niaa022] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 07/08/2020] [Accepted: 08/06/2020] [Indexed: 11/20/2022] Open
Abstract
Comprehension of degraded speech requires higher-order expectations informed by prior knowledge. Accurate top-down expectations of incoming degraded speech cause a subjective semantic 'pop-out' or conscious breakthrough experience. Indeed, the same stimulus can be perceived as meaningless when no expectations are made in advance. We investigated the event-related potential (ERP) correlates of these top-down expectations, their error signals and the subjective pop-out experience in healthy participants. We manipulated expectations in a word-pair priming degraded (noise-vocoded) speech task and investigated the role of top-down expectation with a between-groups attention manipulation. Consistent with the role of expectations in comprehension, repetition priming significantly enhanced perceptual intelligibility of the noise-vocoded degraded targets for attentive participants. An early ERP was larger for mismatched (i.e. unexpected) targets than matched targets, indicative of an initial error signal not reliant on top-down expectations. Subsequently, a P3a-like ERP was larger to matched targets than mismatched targets only for attending participants-i.e. a pop-out effect-while a later ERP was larger for mismatched targets and did not significantly interact with attention. Rather than relying on complex post hoc interactions between prediction error and precision to explain this apredictive pattern, we consider our data to be consistent with prediction error minimization accounts for early stages of processing followed by Global Neuronal Workspace-like breakthrough and processing in service of task goals.
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Affiliation(s)
- Leah Banellis
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK
| | - Rodika Sokoliuk
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK
| | - Conor J Wild
- Brain and Mind Institute, University of Western Ontario, London, ON N6A 3K7, Canada
| | - Howard Bowman
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK
- School of Computing, University of Kent, Canterbury, Kent CT2 7NF, UK
| | - Damian Cruse
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK
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54
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Lecaignard F, Bertrand O, Caclin A, Mattout J. Empirical Bayes evaluation of fused EEG-MEG source reconstruction: Application to auditory mismatch evoked responses. Neuroimage 2020; 226:117468. [PMID: 33075561 DOI: 10.1016/j.neuroimage.2020.117468] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 09/08/2020] [Accepted: 10/09/2020] [Indexed: 12/12/2022] Open
Abstract
We here turn the general and theoretical question of the complementarity of EEG and MEG for source reconstruction, into a practical empirical one. Precisely, we address the challenge of evaluating multimodal data fusion on real data. For this purpose, we build on the flexibility of Parametric Empirical Bayes, namely for EEG-MEG data fusion, group level inference and formal hypothesis testing. The proposed approach follows a two-step procedure by first using unimodal or multimodal inference to derive a cortical solution at the group level; and second by using this solution as a prior model for single subject level inference based on either unimodal or multimodal data. Interestingly, for inference based on the same data (EEG, MEG or both), one can then formally compare, as alternative hypotheses, the relative plausibility of the two unimodal and the multimodal group priors. Using auditory data, we show that this approach enables to draw important conclusions, namely on (i) the superiority of multimodal inference, (ii) the greater spatial sensitivity of MEG compared to EEG, (iii) the ability of EEG data alone to source reconstruct temporal lobe activity, (iv) the usefulness of EEG to improve MEG based source reconstruction. Importantly, we largely reproduce those findings over two different experimental conditions. We here focused on Mismatch Negativity (MMN) responses for which generators have been extensively investigated with little homogeneity in the reported results. Our multimodal inference at the group level revealed spatio-temporal activity within the supratemporal plane with a precision which, to our knowledge, has never been achieved before with non-invasive recordings.
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Affiliation(s)
- Françoise Lecaignard
- Lyon Neuroscience Research Center, CRNL; INSERM, U1028; CNRS, UMR5292; Brain Dynamics and Cognition Team, Lyon, F-69000, France; University Lyon 1, Lyon, F-69000, France.
| | - Olivier Bertrand
- Lyon Neuroscience Research Center, CRNL; INSERM, U1028; CNRS, UMR5292; Brain Dynamics and Cognition Team, Lyon, F-69000, France; University Lyon 1, Lyon, F-69000, France
| | - Anne Caclin
- Lyon Neuroscience Research Center, CRNL; INSERM, U1028; CNRS, UMR5292; Brain Dynamics and Cognition Team, Lyon, F-69000, France; University Lyon 1, Lyon, F-69000, France
| | - Jérémie Mattout
- Lyon Neuroscience Research Center, CRNL; INSERM, U1028; CNRS, UMR5292; Brain Dynamics and Cognition Team, Lyon, F-69000, France; University Lyon 1, Lyon, F-69000, France
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55
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Witon A, Shirazibehehsti A, Cooke J, Aviles A, Adapa R, Menon DK, Chennu S, Bekinschtein T, Lopez JD, Litvak V, Li L, Friston K, Bowman H. Sedation Modulates Frontotemporal Predictive Coding Circuits and the Double Surprise Acceleration Effect. Cereb Cortex 2020; 30:5204-5217. [PMID: 32427284 PMCID: PMC7472187 DOI: 10.1093/cercor/bhaa071] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Revised: 01/22/2020] [Accepted: 02/20/2020] [Indexed: 12/14/2022] Open
Abstract
Two important theories in cognitive neuroscience are predictive coding (PC) and the global workspace (GW) theory. A key research task is to understand how these two theories relate to one another, and particularly, how the brain transitions from a predictive early state to the eventual engagement of a brain-scale state (the GW). To address this question, we present a source-localization of EEG responses evoked by the local-global task—an experimental paradigm that engages a predictive hierarchy, which encompasses the GW. The results of our source reconstruction suggest three phases of processing. The first phase involves the sensory (here auditory) regions of the superior temporal lobe and predicts sensory regularities over a short timeframe (as per the local effect). The third phase is brain-scale, involving inferior frontal, as well as inferior and superior parietal regions, consistent with a global neuronal workspace (GNW; as per the global effect). Crucially, our analysis suggests that there is an intermediate (second) phase, involving modulatory interactions between inferior frontal and superior temporal regions. Furthermore, sedation with propofol reduces modulatory interactions in the second phase. This selective effect is consistent with a PC explanation of sedation, with propofol acting on descending predictions of the precision of prediction errors; thereby constraining access to the GNW.
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Affiliation(s)
- Adrien Witon
- School of Computing, University of Kent, Kent CT2 7NF, UK.,Center for Neuroprosthetics, EPFL, Sion 1951, Switzerland
| | - Amirali Shirazibehehsti
- School of Computing, University of Kent, Kent CT2 7NF, UK.,East Kent Hospitals University NHS Foundation Trust, Kent & Canterbury Hospital, Canterbury CT1 3NG, UK
| | - Jennifer Cooke
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London SE5 8AF, UK
| | - Alberto Aviles
- School of Psychology, University of Birmingham, Birmingham B15 2TT, UK
| | - Ram Adapa
- Division of Anaesthesia, Box 97, Cambridge Biomedical Campus, University of Cambridge, Cambridge CB2 0QQ, UK
| | - David K Menon
- Division of Anaesthesia, Box 97, Cambridge Biomedical Campus, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Srivas Chennu
- School of Computing, University of Kent, Kent CT2 7NF, UK
| | | | - Jose David Lopez
- Electronic Engineering program, Universidad de Antioquia, Ciudad Universitaria, Medellín 1226, Colombia.,Wellcome Centre for Neuroimaging, University College London, London WC1N 3AR, UK
| | - Vladimir Litvak
- Wellcome Centre for Neuroimaging, University College London, London WC1N 3AR, UK
| | - Ling Li
- School of Computing, University of Kent, Kent CT2 7NF, UK
| | - Karl Friston
- Wellcome Centre for Neuroimaging, University College London, London WC1N 3AR, UK
| | - Howard Bowman
- School of Computing, University of Kent, Kent CT2 7NF, UK.,School of Psychology, University of Birmingham, Birmingham B15 2TT, UK
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56
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Barron HC, Auksztulewicz R, Friston K. Prediction and memory: A predictive coding account. Prog Neurobiol 2020; 192:101821. [PMID: 32446883 PMCID: PMC7305946 DOI: 10.1016/j.pneurobio.2020.101821] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Revised: 02/26/2020] [Accepted: 04/29/2020] [Indexed: 01/27/2023]
Abstract
The hippocampus is crucial for episodic memory, but it is also involved in online prediction. Evidence suggests that a unitary hippocampal code underlies both episodic memory and predictive processing, yet within a predictive coding framework the hippocampal-neocortical interactions that accompany these two phenomena are distinct and opposing. Namely, during episodic recall, the hippocampus is thought to exert an excitatory influence on the neocortex, to reinstate activity patterns across cortical circuits. This contrasts with empirical and theoretical work on predictive processing, where descending predictions suppress prediction errors to 'explain away' ascending inputs via cortical inhibition. In this hypothesis piece, we attempt to dissolve this previously overlooked dialectic. We consider how the hippocampus may facilitate both prediction and memory, respectively, by inhibiting neocortical prediction errors or increasing their gain. We propose that these distinct processing modes depend upon the neuromodulatory gain (or precision) ascribed to prediction error units. Within this framework, memory recall is cast as arising from fictive prediction errors that furnish training signals to optimise generative models of the world, in the absence of sensory data.
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Affiliation(s)
- Helen C Barron
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford, OX1 3TH, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, OX3 9DU, UK.
| | - Ryszard Auksztulewicz
- Max Planck Institute for Empirical Aesthetics, Frankfurt Am Main, 60322, Germany; Department of Biomedical Sciences, City University of Hong Kong, Hong Kong
| | - Karl Friston
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, WC1N 3BG, UK
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57
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Reduced effective connectivity between right parietal and inferior frontal cortex during audiospatial perception in neglect patients with a right-hemisphere lesion. Hear Res 2020; 399:108052. [PMID: 32800615 DOI: 10.1016/j.heares.2020.108052] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 07/15/2020] [Accepted: 07/19/2020] [Indexed: 11/23/2022]
Abstract
A lesion to the right hemisphere of the brain in humans commonly leads to perceptual neglect of the left side of the sensorium. The clinical observation that lesions to disparate cortical and subcortical areas converge upon similar behavioural symptoms points to neglect as a dysconnection syndrome that may result from the disruption of a distributed network, rather than aberrant computations in any particular brain region. To test this hypothesis, we used Bayesian analysis of effective connectivity based on electroencephalographic recordings in ten patients (6 male, 4 female; age range 41-68) with left-sided neglect following a right-hemisphere lesion. In line with previous research, age-matched healthy controls showed a contralateral increase in connection strength between parietal and frontal cortex with respect to the laterality of audiospatial oddball stimuli. Neglect patients, however, showed a dysconnection between parietal and frontal cortex in the right hemisphere when oddballs appeared on their left side, but preserved connectivity in the left hemisphere when stimuli appeared on their right. This preserved fronto-parietal connectivity was associated with lower neglect severity. Moreover, we saw ipsilateral fronto-temporal connectivity increases for oddballs appearing on the neglected side, which might be a compensatory mechanism for residual left side awareness. No group differences were found in intrinsic (within-region) connectivity. While further validation is required in a bigger sample, our findings are in keeping with the idea that neglect results from the disruption of a distributed network, rather than a lesion to any single brain region. SIGNIFICANCE STATEMENT: Lesions to the right hemisphere of the brain commonly lead to neglect syndrome, characterized by perceptual deficits where patients are unaware of the left side of their body and environment. Using analysis of non-invasive electrophysiological recordings, we provide evidence that patients with left-sided neglect have reduced connectivity between the right parietal and frontal cortex during audiospatial stimuli, but preserved connectivity between regions in the non-lesioned left hemisphere. Moreover, for these intact connections we observed an ipsilateral fronto-temporal increase in connectivity during oddballs appearing on the neglected side, which might be a compensatory mechanism for residual perception. Crucially, we found that patients with more severe neglect symptoms had reduced connectivity between parietal and frontal cortex in the left hemisphere. This suggests that neglect may be caused by the disruption of a distributed network in the brain, rather than a lesion to any particular brain region.
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58
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Hua L, Recasens M, Grent-'t-Jong T, Adams RA, Gross J, Uhlhaas PJ. Investigating cortico-subcortical circuits during auditory sensory attenuation: A combined magnetoencephalographic and dynamic causal modeling study. Hum Brain Mapp 2020; 41:4419-4430. [PMID: 32662585 PMCID: PMC7502827 DOI: 10.1002/hbm.25134] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 06/19/2020] [Accepted: 06/26/2020] [Indexed: 01/27/2023] Open
Abstract
Sensory attenuation refers to the decreased intensity of a sensory percept when a sensation is self‐generated compared with when it is externally triggered. However, the underlying brain regions and network interactions that give rise to this phenomenon remain to be determined. To address this issue, we recorded magnetoencephalographic (MEG) data from 35 healthy controls during an auditory task in which pure tones were either elicited through a button press or passively presented. We analyzed the auditory M100 at sensor‐ and source‐level and identified movement‐related magnetic fields (MRMFs). Regression analyses were used to further identify brain regions that contributed significantly to sensory attenuation, followed by a dynamic causal modeling (DCM) approach to explore network interactions between generators. Attenuation of the M100 was pronounced in right Heschl's gyrus (HES), superior temporal cortex (ST), thalamus, rolandic operculum (ROL), precuneus and inferior parietal cortex (IPL). Regression analyses showed that right postcentral gyrus (PoCG) and left precentral gyrus (PreCG) predicted M100 sensory attenuation. In addition, DCM results indicated that auditory sensory attenuation involved bi‐directional information flow between thalamus, IPL, and auditory cortex. In summary, our data show that sensory attenuation is mediated by bottom‐up and top‐down information flow in a thalamocortical network, providing support for the role of predictive processing in sensory‐motor system.
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Affiliation(s)
- Lingling Hua
- Institute for Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Marc Recasens
- Institute for Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Tineke Grent-'t-Jong
- Institute for Neuroscience and Psychology, University of Glasgow, Glasgow, UK.,Department of Child and Adolescent Psychiatry, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Rick A Adams
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Joachim Gross
- Institute for Neuroscience and Psychology, University of Glasgow, Glasgow, UK.,Institute of Biomagnetism and Biosignal analysis, Westphalian Wilhelms University Muenster, Münster, Germany
| | - Peter J Uhlhaas
- Institute for Neuroscience and Psychology, University of Glasgow, Glasgow, UK.,Department of Child and Adolescent Psychiatry, Charité-Universitätsmedizin Berlin, Berlin, Germany
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59
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Smout CA, Garrido MI, Mattingley JB. Global effects of feature-based attention depend on surprise. Neuroimage 2020; 215:116785. [DOI: 10.1016/j.neuroimage.2020.116785] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 03/09/2020] [Accepted: 03/26/2020] [Indexed: 10/24/2022] Open
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60
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Sumner RL, Spriggs MJ, Muthukumaraswamy SD, Kirk IJ. The role of Hebbian learning in human perception: a methodological and theoretical review of the human Visual Long-Term Potentiation paradigm. Neurosci Biobehav Rev 2020; 115:220-237. [PMID: 32562886 DOI: 10.1016/j.neubiorev.2020.03.013] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 03/02/2020] [Accepted: 03/12/2020] [Indexed: 11/17/2022]
Abstract
Long-term potentiation (LTP) is one of the most widely studied forms of neural plasticity, and is thought to be the principle mechanism underlying long-term memory and learning in the brain. Sensory paradigms utilising electroencephalography (EEG) and sensory stimulation to induce LTP have allowed translation from rodent and primate invasive research to non-invasive human investigations. This review focusses on visual sensory LTP induced using repetitive visual stimulation, resulting in changes in the visually evoked response recorded at the scalp with EEG. Across 15 years of use and replication in humans several major paradigm variants for eliciting visual LTP have emerged. The application of different paradigms, and the broad implementation of visual LTP across different populations combines to provide a rich and sensitive account of Hebbian LTP, and potentially non-Hebbian plasticity mechanisms. This review will conclude with a discussion of how these findings have advanced existing theories of perceptual learning by positioning Hebbian learning both alongside and within other major theories such as Predictive Coding and The Free Energy Principle.
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Affiliation(s)
| | - Meg J Spriggs
- Centre for Psychedelic Research, Division of Brain Sciences, Centre for Psychiatry, Imperial College London, UK
| | | | - Ian J Kirk
- Brain Research, New Zealand; School of Psychology, University of Auckland, New Zealand
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61
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Brain dynamics for confidence-weighted learning. PLoS Comput Biol 2020; 16:e1007935. [PMID: 32484806 PMCID: PMC7292419 DOI: 10.1371/journal.pcbi.1007935] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 06/12/2020] [Accepted: 05/07/2020] [Indexed: 12/11/2022] Open
Abstract
Learning in a changing, uncertain environment is a difficult problem. A popular solution is to predict future observations and then use surprising outcomes to update those predictions. However, humans also have a sense of confidence that characterizes the precision of their predictions. Bayesian models use a confidence-weighting principle to regulate learning: for a given surprise, the update is smaller when the confidence about the prediction was higher. Prior behavioral evidence indicates that human learning adheres to this confidence-weighting principle. Here, we explored the human brain dynamics sub-tending the confidence-weighting of learning using magneto-encephalography (MEG). During our volatile probability learning task, subjects’ confidence reports conformed with Bayesian inference. MEG revealed several stimulus-evoked brain responses whose amplitude reflected surprise, and some of them were further shaped by confidence: surprise amplified the stimulus-evoked response whereas confidence dampened it. Confidence about predictions also modulated several aspects of the brain state: pupil-linked arousal and beta-range (15–30 Hz) oscillations. The brain state in turn modulated specific stimulus-evoked surprise responses following the confidence-weighting principle. Our results thus indicate that there exist, in the human brain, signals reflecting surprise that are dampened by confidence in a way that is appropriate for learning according to Bayesian inference. They also suggest a mechanism for confidence-weighted learning: confidence about predictions would modulate intrinsic properties of the brain state to amplify or dampen surprise responses evoked by discrepant observations. Learning in a changing and uncertain world is difficult. In this context, facing a discrepancy between my current belief and new observations may reflect random fluctuations (e.g. my commute train is unexpectedly late, but it happens sometimes), if so, I should ignore this discrepancy and not change erratically my belief. However, this discrepancy could also denote a profound change (e.g. the train company changed and is less reliable), in this case, I should promptly revise my current belief. Human learning is adaptive: we change how much we learn from new observations, in particular, we promote flexibility when facing profound changes. A mathematical analysis of the problem shows that we should increase flexibility when the confidence about our current belief is low, which occurs when a change is suspected. Here, I show that human learners entertain rational confidence levels during the learning of changing probabilities. This confidence modulates intrinsic properties of the brain state (oscillatory activity and neuromodulation) which in turn amplifies or reduces, depending on whether confidence is low or high, the neural responses to discrepant observations. This confidence-weighting mechanism could underpin adaptive learning.
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62
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Pinotsis DA, Buschman TJ, Miller EK. Working Memory Load Modulates Neuronal Coupling. Cereb Cortex 2020; 29:1670-1681. [PMID: 29608671 DOI: 10.1093/cercor/bhy065] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Revised: 02/22/2018] [Accepted: 02/28/2018] [Indexed: 12/27/2022] Open
Abstract
There is a severe limitation in the number of items that can be held in working memory. However, the neurophysiological limits remain unknown. We asked whether the capacity limit might be explained by differences in neuronal coupling. We developed a theoretical model based on Predictive Coding and used it to analyze Cross Spectral Density data from the prefrontal cortex (PFC), frontal eye fields (FEF), and lateral intraparietal area (LIP). Monkeys performed a change detection task. The number of objects that had to be remembered (memory load) was varied (1-3 objects in the same visual hemifield). Changes in memory load changed the connectivity in the PFC-FEF-LIP network. Feedback (top-down) coupling broke down when the number of objects exceeded cognitive capacity. Thus, impaired behavioral performance coincided with a break-down of Prediction signals. This provides new insights into the neuronal underpinnings of cognitive capacity and how coupling in a distributed working memory network is affected by memory load.
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Affiliation(s)
- Dimitris A Pinotsis
- The Picower Institute for Learning & Memory and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.,The Wellcome Trust Centre for Neuroimaging, University College London, London, UK
| | - Timothy J Buschman
- The Picower Institute for Learning & Memory and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.,Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Earl K Miller
- The Picower Institute for Learning & Memory and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
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63
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Wei H, Jafarian A, Zeidman P, Litvak V, Razi A, Hu D, Friston KJ. Bayesian fusion and multimodal DCM for EEG and fMRI. Neuroimage 2020; 211:116595. [DOI: 10.1016/j.neuroimage.2020.116595] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Revised: 01/07/2020] [Accepted: 01/29/2020] [Indexed: 12/26/2022] Open
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64
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Todd J, Frost JD, Yeark M, Paton B. Context is everything: How context shapes modulations of responses to unattended sound. Hear Res 2020; 399:107975. [PMID: 32370880 DOI: 10.1016/j.heares.2020.107975] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2019] [Revised: 04/13/2020] [Accepted: 04/14/2020] [Indexed: 10/24/2022]
Abstract
The concept of perceptual inferences taking place over multiple timescales simultaneously raises questions about how the brain can balance the demands of remaining sensitive to local rarity while utilising more global longer-term predictability to modulate cortical responses. In the present study auditory evoked potentials to four presentations of the same sound sequence containing predictable structure on a local (milliseconds to seconds) and more global (many minutes) timescales were recorded. The results from 33 participants are used to demonstrate that predictions about both local (internal predictive models) and global (meta-models that define expected precisions associated with familiar internal model states) regularities are formed. The study exposes more local context-based modulations of the P1 but more global order-based modulations of the auditory evoked N2 components. The results are discussed in terms of theoretical links advocating that uncertainty at multiple timescales could lead to differential component modulations, and the importance of considering the broader learning context in auditory evoked potential studies.
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Affiliation(s)
- Juanita Todd
- School of Psychology, University of Newcastle, University Drive, Callaghan, NSW, Australia, 2308.
| | - Jade D Frost
- School of Psychology, University of Newcastle, University Drive, Callaghan, NSW, Australia, 2308
| | - Mattsen Yeark
- School of Psychology, University of Newcastle, University Drive, Callaghan, NSW, Australia, 2308
| | - Bryan Paton
- School of Psychology, University of Newcastle, University Drive, Callaghan, NSW, Australia, 2308
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Male AG, O’Shea RP, Schröger E, Müller D, Roeber U, Widmann A. The quest for the genuine visual mismatch negativity (vMMN): Event‐related potential indications of deviance detection for low‐level visual features. Psychophysiology 2020; 57:e13576. [DOI: 10.1111/psyp.13576] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 01/29/2020] [Accepted: 02/05/2020] [Indexed: 11/28/2022]
Affiliation(s)
- Alie G. Male
- Discipline of Psychology, College of Science, Health, Engineering and Education Murdoch University Perth WA Australia
| | - Robert P. O’Shea
- Discipline of Psychology, College of Science, Health, Engineering and Education Murdoch University Perth WA Australia
- Institute of Psychology Leipzig University Leipzig Germany
- Discipline of Psychology, School of Health and Human Sciences Southern Cross University Coffs Harbour NSW Australia
| | - Erich Schröger
- Institute of Psychology Leipzig University Leipzig Germany
| | - Dagmar Müller
- Institute of Psychology Leipzig University Leipzig Germany
| | - Urte Roeber
- Discipline of Psychology, College of Science, Health, Engineering and Education Murdoch University Perth WA Australia
- Institute of Psychology Leipzig University Leipzig Germany
| | - Andreas Widmann
- Institute of Psychology Leipzig University Leipzig Germany
- CBBS Research Group Neurocognitive Development Leibniz Institute for Neurobiology Magdeburg Germany
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66
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Zuanazzi A, Noppeney U. The Intricate Interplay of Spatial Attention and Expectation: a Multisensory Perspective. Multisens Res 2020; 33:383-416. [DOI: 10.1163/22134808-20201482] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 12/07/2019] [Indexed: 11/19/2022]
Abstract
Abstract
Attention (i.e., task relevance) and expectation (i.e., signal probability) are two critical top-down mechanisms guiding perceptual inference. Attention prioritizes processing of information that is relevant for observers’ current goals. Prior expectations encode the statistical structure of the environment. Research to date has mostly conflated spatial attention and expectation. Most notably, the Posner cueing paradigm manipulates spatial attention using probabilistic cues that indicate where the subsequent stimulus is likely to be presented. Only recently have studies attempted to dissociate the mechanisms of attention and expectation and characterized their interactive (i.e., synergistic) or additive influences on perception. In this review, we will first discuss methodological challenges that are involved in dissociating the mechanisms of attention and expectation. Second, we will review research that was designed to dissociate attention and expectation in the unisensory domain. Third, we will review the broad field of crossmodal endogenous and exogenous spatial attention that investigates the impact of attention across the senses. This raises the critical question of whether attention relies on amodal or modality-specific mechanisms. Fourth, we will discuss recent studies investigating the role of both spatial attention and expectation in multisensory perception, where the brain constructs a representation of the environment based on multiple sensory inputs. We conclude that spatial attention and expectation are closely intertwined in almost all circumstances of everyday life. Yet, despite their intimate relationship, attention and expectation rely on partly distinct neural mechanisms: while attentional resources are mainly shared across the senses, expectations can be formed in a modality-specific fashion.
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Affiliation(s)
- Arianna Zuanazzi
- 1Computational Neuroscience and Cognitive Robotics Centre, University of Birmingham, UK
- 2Department of Psychology, New York University, New York, NY, USA
| | - Uta Noppeney
- 1Computational Neuroscience and Cognitive Robotics Centre, University of Birmingham, UK
- 3Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
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67
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Trujillo JP, Simanova I, Özyürek A, Bekkering H. Seeing the Unexpected: How Brains Read Communicative Intent through Kinematics. Cereb Cortex 2020; 30:1056-1067. [PMID: 31504305 PMCID: PMC7132920 DOI: 10.1093/cercor/bhz148] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 06/06/2019] [Accepted: 06/12/2019] [Indexed: 11/12/2022] Open
Abstract
Social interaction requires us to recognize subtle cues in behavior, such as kinematic differences in actions and gestures produced with different social intentions. Neuroscientific studies indicate that the putative mirror neuron system (pMNS) in the premotor cortex and mentalizing system (MS) in the medial prefrontal cortex support inferences about contextually unusual actions. However, little is known regarding the brain dynamics of these systems when viewing communicatively exaggerated kinematics. In an event-related functional magnetic resonance imaging experiment, 28 participants viewed stick-light videos of pantomime gestures, recorded in a previous study, which contained varying degrees of communicative exaggeration. Participants made either social or nonsocial classifications of the videos. Using participant responses and pantomime kinematics, we modeled the probability of each video being classified as communicative. Interregion connectivity and activity were modulated by kinematic exaggeration, depending on the task. In the Social Task, communicativeness of the gesture increased activation of several pMNS and MS regions and modulated top-down coupling from the MS to the pMNS, but engagement of the pMNS and MS was not found in the nonsocial task. Our results suggest that expectation violations can be a key cue for inferring communicative intention, extending previous findings from wholly unexpected actions to more subtle social signaling.
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Affiliation(s)
- James P Trujillo
- Donders Institute for Brain, Cognition and Behaviour
- Centre for Language Studies, Radboud University Nijmegen, 6500HD Nijmegen, the Netherlands
| | | | - Asli Özyürek
- Centre for Language Studies, Radboud University Nijmegen, 6500HD Nijmegen, the Netherlands
- Max Planck Institute for Psycholinguistics, 6525XD Nijmegen, the Netherlands
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68
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Jafarian A, Litvak V, Cagnan H, Friston KJ, Zeidman P. Comparing dynamic causal models of neurovascular coupling with fMRI and EEG/MEG. Neuroimage 2020; 216:116734. [PMID: 32179105 PMCID: PMC7322559 DOI: 10.1016/j.neuroimage.2020.116734] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 03/06/2020] [Accepted: 03/10/2020] [Indexed: 01/09/2023] Open
Abstract
This technical note presents a dynamic causal modelling (DCM) procedure for evaluating different models of neurovascular coupling in the human brain - using combined electromagnetic (M/EEG) and functional magnetic resonance imaging (fMRI) data. This procedure compares the evidence for biologically informed models of neurovascular coupling using Bayesian model comparison. First, fMRI data are used to localise regionally specific neuronal responses. The coordinates of these responses are then used as the location priors in a DCM of electrophysiological responses elicited by the same paradigm. The ensuing estimates of model parameters are then used to generate neuronal drive functions, which model pre- or post-synaptic activity for each experimental condition. These functions form the input to a model of neurovascular coupling, whose parameters are estimated from the fMRI data. Crucially, this enables one to evaluate different models of neurovascular coupling, using Bayesian model comparison - asking, for example, whether instantaneous or delayed, pre- or post-synaptic signals mediate haemodynamic responses. We provide an illustrative application of the procedure using a single-subject auditory fMRI and MEG dataset. The code and exemplar data accompanying this technical note are available through the statistical parametric mapping (SPM) software.
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Affiliation(s)
| | - Vladimir Litvak
- The Wellcome Centre for Human Neuroimaging, University College London, UK
| | - Hayriye Cagnan
- MRC Brain Network Dynamics Unit (BNDU) at the University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Karl J Friston
- The Wellcome Centre for Human Neuroimaging, University College London, UK
| | - Peter Zeidman
- The Wellcome Centre for Human Neuroimaging, University College London, UK
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69
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Bowling JT, Friston KJ, Hopfinger JB. Top-down versus bottom-up attention differentially modulate frontal-parietal connectivity. Hum Brain Mapp 2020; 41:928-942. [PMID: 31692192 PMCID: PMC7267915 DOI: 10.1002/hbm.24850] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 08/28/2019] [Accepted: 10/21/2019] [Indexed: 01/01/2023] Open
Abstract
The moment-to-moment focus of our mind's eye results from a complex interplay of voluntary and involuntary influences on attention. Previous neuroimaging studies suggest that the brain networks of voluntary versus involuntary attention can be segregated into a frontal-versus-parietal or a dorsal-versus-ventral partition-although recent work suggests that the dorsal network may be involved in both bottom-up and top-down attention. Research with nonhuman primates has provided evidence that a key distinction between top-down and bottom-up attention may be the direction of connectivity between frontal and parietal areas. Whereas typical fMRI connectivity analyses cannot disambiguate the direction of connections, dynamic causal modeling (DCM) can model directionality. Using DCM, we provide new evidence that directed connections within the dorsal attention network are differentially modulated for voluntary versus involuntary attention. These results suggest that the intraparietal sulcus exerts a baseline inhibitory effect on the frontal eye fields that is strengthened during exogenous orienting and attenuated during endogenous orienting. Furthermore, the attenuation from endogenous attention occurs even with salient peripheral cues when those cues are known to be counter predictive. Thus, directed connectivity between frontal and parietal regions of the dorsal attention network is highly influenced by the type of attention that is engaged.
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Affiliation(s)
- Jake T. Bowling
- School of MedicineUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
| | - Karl J. Friston
- Wellcome Trust Centre for NeuroimagingUniversity College LondonLondonUK
| | - Joseph B. Hopfinger
- Department of Psychology and NeuroscienceUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
- Biomedical Research Imaging CenterUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
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70
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Walsh KS, McGovern DP, Clark A, O'Connell RG. Evaluating the neurophysiological evidence for predictive processing as a model of perception. Ann N Y Acad Sci 2020; 1464:242-268. [PMID: 32147856 PMCID: PMC7187369 DOI: 10.1111/nyas.14321] [Citation(s) in RCA: 109] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 01/21/2020] [Accepted: 02/03/2020] [Indexed: 12/12/2022]
Abstract
For many years, the dominant theoretical framework guiding research into the neural origins of perceptual experience has been provided by hierarchical feedforward models, in which sensory inputs are passed through a series of increasingly complex feature detectors. However, the long-standing orthodoxy of these accounts has recently been challenged by a radically different set of theories that contend that perception arises from a purely inferential process supported by two distinct classes of neurons: those that transmit predictions about sensory states and those that signal sensory information that deviates from those predictions. Although these predictive processing (PP) models have become increasingly influential in cognitive neuroscience, they are also criticized for lacking the empirical support to justify their status. This limited evidence base partly reflects the considerable methodological challenges that are presented when trying to test the unique predictions of these models. However, a confluence of technological and theoretical advances has prompted a recent surge in human and nonhuman neurophysiological research seeking to fill this empirical gap. Here, we will review this new research and evaluate the degree to which its findings support the key claims of PP.
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Affiliation(s)
- Kevin S. Walsh
- Trinity College Institute of Neuroscience and School of PsychologyTrinity College DublinDublinIreland
| | - David P. McGovern
- Trinity College Institute of Neuroscience and School of PsychologyTrinity College DublinDublinIreland
- School of PsychologyDublin City UniversityDublinIreland
| | - Andy Clark
- Department of PhilosophyUniversity of SussexBrightonUK
- Department of InformaticsUniversity of SussexBrightonUK
| | - Redmond G. O'Connell
- Trinity College Institute of Neuroscience and School of PsychologyTrinity College DublinDublinIreland
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71
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Bouwer FL, Honing H, Slagter HA. Beat-based and Memory-based Temporal Expectations in Rhythm: Similar Perceptual Effects, Different Underlying Mechanisms. J Cogn Neurosci 2020; 32:1221-1241. [PMID: 31933432 DOI: 10.1162/jocn_a_01529] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Predicting the timing of incoming information allows the brain to optimize information processing in dynamic environments. Behaviorally, temporal expectations have been shown to facilitate processing of events at expected time points, such as sounds that coincide with the beat in musical rhythm. Yet, temporal expectations can develop based on different forms of structure in the environment, not just the regularity afforded by a musical beat. Little is still known about how different types of temporal expectations are neurally implemented and affect performance. Here, we orthogonally manipulated the periodicity and predictability of rhythmic sequences to examine the mechanisms underlying beat-based and memory-based temporal expectations, respectively. Behaviorally and using EEG, we looked at the effects of beat-based and memory-based expectations on auditory processing when rhythms were task-relevant or task-irrelevant. At expected time points, both beat-based and memory-based expectations facilitated target detection and led to attenuation of P1 and N1 responses, even when expectations were task-irrelevant (unattended). For beat-based expectations, we additionally found reduced target detection and enhanced N1 responses for events at unexpected time points (e.g., off-beat), regardless of the presence of memory-based expectations or task relevance. This latter finding supports the notion that periodicity selectively induces rhythmic fluctuations in neural excitability and furthermore indicates that, although beat-based and memory-based expectations may similarly affect auditory processing of expected events, their underlying neural mechanisms may be different.
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Abstract
Evoked potentials provide valuable insight into brain processes that are integral to our ability to interact effectively and efficiently in the world. The mismatch negativity (MMN) component of the evoked potential has proven highly informative on the ways in which sensitivity to regularity contributes to perception and cognition. This review offers a compendium of research on MMN with a view to scaffolding an appreciation for its use as a tool to explore the way regularities contribute to predictions about the sensory environment over many timescales. In compiling this work, interest in MMN as an index of sensory encoding and memory are addressed, as well as attention. Perspectives on the possible underlying computational processes are reviewed as well as recent observations that invite consideration of how MMN relates to how we learn, what we learn, and why.
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Affiliation(s)
- Kaitlin Fitzgerald
- School of Psychology, University of Newcastle, Callaghan, NSW, Australia
| | - Juanita Todd
- School of Psychology, University of Newcastle, Callaghan, NSW, Australia
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73
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Cooray GK, Sundgren M, Brismar T. Mechanism of visual network dysfunction in relapsing-remitting multiple sclerosis and its relation to cognition. Clin Neurophysiol 2019; 131:361-367. [PMID: 31864125 DOI: 10.1016/j.clinph.2019.10.029] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 09/10/2019] [Accepted: 10/31/2019] [Indexed: 01/31/2023]
Abstract
OBJECTIVE To investigate if changes in brain network function and connectivity contribute to the abnormalities in visual event related potentials (ERP) in relapsing-remitting multiple sclerosis (RRMS), and explore their relation to a decrease in cognitive performance. METHODS We evaluated 72 patients with RRMS and 89 healthy control subjects in a cross-sectional study. Visual ERP were generated using illusory and non-illusory stimuli and recorded using 21 EEG scalp electrodes. The measured activity was modelled using Dynamic Causal Modelling. The model network consisted of 4 symmetric nodes including the primary visual cortex (V1/V2) and the Lateral Occipital Complex. Patients and controls were tested with a neuropsychological test battery consisting of 18 cognitive tests covering six cognitive domains. RESULTS We found reduced cortical connectivity in bottom-up and interhemispheric connections to the right lateral occipital complex in patients (p < 0.001). Furthermore, interhemispherical connections were related to cognitive dysfunction in several domains (attention, executive function, visual perception and organization, processing speed and global cognition) for patients (p < 0.05). No relation was seen between cortical network connectivity and cognitive function in the healthy control subjects. CONCLUSION Changes in the functional connectivity to higher cortical regions provide a neurobiological explanation for the changes of the visual ERP in RRMS. SIGNIFICANCE This study suggests that changes in connectivity to higher cortical regions partly explain visual network dysfunction in RRMS where a lower interhemispheric connectivity may contribute to impaired cognitive function.
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Affiliation(s)
- Gerald K Cooray
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden; Department of Clinical Neurophysiology, Karolinska University Hospital, Stockholm, Sweden.
| | - Mathias Sundgren
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden; Neuro Department, Karolinska University Hospital, Stockholm, Sweden
| | - Tom Brismar
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden; Department of Clinical Neurophysiology, Karolinska University Hospital, Stockholm, Sweden
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Krugliakova E, Gorin A, Fedele T, Shtyrov Y, Moiseeva V, Klucharev V, Shestakova A. The Monetary Incentive Delay (MID) Task Induces Changes in Sensory Processing: ERP Evidence. Front Hum Neurosci 2019; 13:382. [PMID: 31736730 PMCID: PMC6839045 DOI: 10.3389/fnhum.2019.00382] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Accepted: 10/14/2019] [Indexed: 01/08/2023] Open
Abstract
Numerous cognitive studies have demonstrated experience-induced plasticity in the primary sensory cortex, indicating that repeated decisions could modulate sensory processing. In this context, we investigated whether an auditory version of the monetary incentive delay (MID) task could change the neural processing of the incentive cues that code expected monetary outcomes. To study sensory plasticity, we presented the incentive cues as deviants during oddball sessions recorded before and after training in the two MID task sessions. We found that after 2 days of training in the MID task, incentive cues evoked a larger P3a (compared with the baseline condition), indicating there was an enhancement of the involuntary attention to the stimuli that predict rewards. At the individual level, the training-induced change of mismatch-related negativity was correlated with the amplitude of the feedback-related negativity (FRN) recorded during the first MID task session. Our results show that the MID task evokes plasticity changes in the auditory system associated with better passive discrimination of incentive cues and with enhanced involuntary attention switching towards these cues. Thus, the sensory processing of incentive cues is dynamically modulated by previous outcomes.
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Affiliation(s)
- Elena Krugliakova
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
| | - Alexey Gorin
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
| | - Tommaso Fedele
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
- Neurosurgery Department, University Hospital Zurich, Zurich, Switzerland
| | - Yury Shtyrov
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
- Department of Clinical Medicine, Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Aarhus, Denmark
- Laboratory of Behavioural Neurodynamics, Saint Petersburg State University, Saint Petersburg, Russia
| | - Victoria Moiseeva
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
| | - Vasily Klucharev
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
| | - Anna Shestakova
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
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75
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Golubic SJ, Jurasic MJ, Susac A, Huonker R, Gotz T, Haueisen J. Attention modulates topology and dynamics of auditory sensory gating. Hum Brain Mapp 2019; 40:2981-2994. [PMID: 30882981 PMCID: PMC6865797 DOI: 10.1002/hbm.24573] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Revised: 02/11/2019] [Accepted: 03/06/2019] [Indexed: 01/26/2023] Open
Abstract
This work challenges the widely accepted model of sensory gating as a preattention inhibitory process by investigating whether attention directed at the second tone (S2) within a paired-click paradigm could affect gating at the cortical level. We utilized magnetoencephalography, magnetic resonance imaging and spatio-temporal source localization to compare the cortical dynamics underlying gating responses across two conditions (passive and attention) in 19 healthy subjects. Source localization results reaffirmed the existence of a fast processing pathway between the prefrontal cortex (PFC) and bilateral superior temporal gyri (STG) that underlies the auditory gating process. STG source dynamics comprised two gating sub-components, Mb1 and Mb2, both of which showed significant gating suppression (>51%). The attention directed to the S2 tone changed the gating network topology by switching the prefrontal generator from a dorsolateral location, which was active in the passive condition (18/19), to a medial location, active in the attention condition (19/19). Enhanced responses to the attended stimulus caused a significant reduction in gating suppression in both STG gating components (>50%). Our results demonstrate that attention not only modulates sensory gating dynamics, but also exerts topological rerouting of information processing within the PFC. The present data, suggesting that the cortical levels of early sensory processing are subject to top-down influences, change the current view of gating as a purely automatic bottom-up process.
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Affiliation(s)
| | | | - Ana Susac
- Department of Physics, Faculty of ScienceUniversity of ZagrebZagrebCroatia
- Department of Applied Physics, Faculty of Electrical Engineering and ComputingUniversity of ZagrebZagrebCroatia
| | - Ralph Huonker
- Biomagnetic Center, Hans Berger Department of NeurologyJena University HospitalJenaGermany
| | - Theresa Gotz
- Biomagnetic Center, Hans Berger Department of NeurologyJena University HospitalJenaGermany
- Institute of Medical Statistics, Computer Sciences and Documentation, Jena University HospitalJenaGermany
| | - Jens Haueisen
- Biomagnetic Center, Hans Berger Department of NeurologyJena University HospitalJenaGermany
- Institute of Biomedical Engineering and Informatics, Technical University IlmenauIlmenauGermany
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76
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Quiroga-Martinez DR, Hansen NC, Højlund A, Pearce MT, Brattico E, Vuust P. Reduced prediction error responses in high-as compared to low-uncertainty musical contexts. Cortex 2019; 120:181-200. [PMID: 31323458 DOI: 10.1016/j.cortex.2019.06.010] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Revised: 04/05/2019] [Accepted: 06/19/2019] [Indexed: 02/05/2023]
Abstract
Theories of predictive processing propose that prediction error responses are modulated by the certainty of the predictive model or precision. While there is some evidence for this phenomenon in the visual and, to a lesser extent, the auditory modality, little is known about whether it operates in the complex auditory contexts of daily life. Here, we examined how prediction error responses behave in a more complex and ecologically valid auditory context than those typically studied. We created musical tone sequences with different degrees of pitch uncertainty to manipulate the precision of participants' auditory expectations. Magnetoencephalography was used to measure the magnetic counterpart of the mismatch negativity (MMNm) as a neural marker of prediction error in a multi-feature paradigm. Pitch, slide, intensity and timbre deviants were included. We compared high-entropy stimuli, consisting of a set of non-repetitive melodies, with low-entropy stimuli consisting of a simple, repetitive pitch pattern. Pitch entropy was quantitatively assessed with an information-theoretic model of auditory expectation. We found a reduction in pitch and slide MMNm amplitudes in the high-entropy as compared to the low-entropy context. No significant differences were found for intensity and timbre MMNm amplitudes. Furthermore, in a separate behavioral experiment investigating the detection of pitch deviants, similar decreases were found for accuracy measures in response to more fine-grained increases in pitch entropy. Our results are consistent with a precision modulation of auditory prediction error in a musical context, and suggest that this effect is specific to features that depend on the manipulated dimension-pitch information, in this case.
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Affiliation(s)
| | - Niels C Hansen
- The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Australia
| | - Andreas Højlund
- Center for Functionally Integrative Neuroscience, Aarhus University, Denmark
| | - Marcus T Pearce
- Center for Music in the Brain, Aarhus University and The Royal Academy of Music, Denmark; School of Electronic Engineering and Computer Science, Queen Mary University of London, UK
| | - Elvira Brattico
- Center for Music in the Brain, Aarhus University and The Royal Academy of Music, Denmark
| | - Peter Vuust
- Center for Music in the Brain, Aarhus University and The Royal Academy of Music, Denmark
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77
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Abadi AK, Yahya K, Amini M, Friston K, Heinke D. Excitatory versus inhibitory feedback in Bayesian formulations of scene construction. J R Soc Interface 2019; 16:20180344. [PMID: 31039693 PMCID: PMC6544897 DOI: 10.1098/rsif.2018.0344] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 04/02/2019] [Indexed: 11/22/2022] Open
Abstract
The selective attention for identification model (SAIM) is an established model of selective visual attention. SAIM implements translation-invariant object recognition, in scenes with multiple objects, using the parallel distributed processing (PDP) paradigm. Here, we show that SAIM can be formulated as Bayesian inference. Crucially, SAIM uses excitatory feedback to combine top-down information (i.e. object knowledge) with bottom-up sensory information. By contrast, predictive coding implementations of Bayesian inference use inhibitory feedback. By formulating SAIM as a predictive coding scheme, we created a new version of SAIM that uses inhibitory feedback. Simulation studies showed that both types of architectures can reproduce the response time costs induced by multiple objects-as found in visual search experiments. However, due to the different nature of the feedback, the two SAIM schemes make distinct predictions about the motifs of microcircuits mediating the effects of top-down afferents. We discuss empirical (neuroimaging) methods to test the predictions of the two inference architectures.
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Affiliation(s)
- Alireza Khatoon Abadi
- Department of Mathematics, Faculty of Mathematical Sciences, Tarbiat Modares University, Tehran 14115-134, Iran
| | - Keyvan Yahya
- Faculty of Informatics, Chemnitz University of Technology, Straße der Nationen 62, R. B216, 09111 Chemnitz, Germany
| | - Massoud Amini
- Department of Mathematics, Faculty of Mathematical Sciences, Tarbiat Modares University, Tehran 14115-134, Iran
| | - Karl Friston
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK
| | - Dietmar Heinke
- Centre for Computational Neuroscience and Cognitive Robotics, School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
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78
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Stefanics G, Stephan KE, Heinzle J. Feature-specific prediction errors for visual mismatch. Neuroimage 2019; 196:142-151. [PMID: 30978499 DOI: 10.1016/j.neuroimage.2019.04.020] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 03/30/2019] [Accepted: 04/04/2019] [Indexed: 01/08/2023] Open
Abstract
Predictive coding (PC) theory posits that our brain employs a predictive model of the environment to infer the causes of its sensory inputs. A fundamental but untested prediction of this theory is that the same stimulus should elicit distinct precision weighted prediction errors (pwPEs) when different (feature-specific) predictions are violated, even in the absence of attention. Here, we tested this hypothesis using functional magnetic resonance imaging (fMRI) and a multi-feature roving visual mismatch paradigm where rare changes in either color (red, green), or emotional expression (happy, fearful) of faces elicited pwPE responses in human participants. Using a computational model of learning and inference, we simulated pwPE and prediction trajectories of a Bayes-optimal observer and used these to analyze changes in blood oxygen level dependent (BOLD) responses to changes in color and emotional expression of faces while participants engaged in a distractor task. Controlling for visual attention by eye-tracking, we found pwPE responses to unexpected color changes in the fusiform gyrus. Conversely, unexpected changes of facial emotions elicited pwPE responses in cortico-thalamo-cerebellar structures associated with emotion and theory of mind processing. Predictions pertaining to emotions activated fusiform, occipital and temporal areas. Our results are consistent with a general role of PC across perception, from low-level to complex and socially relevant object features, and suggest that monitoring of the social environment occurs continuously and automatically, even in the absence of attention.
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Affiliation(s)
- Gabor Stefanics
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Wilfriedstrasse 6, 8032, Zurich, Switzerland; Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, Blümlisalpstrasse 10, 8006, Zurich, Switzerland.
| | - Klaas Enno Stephan
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Wilfriedstrasse 6, 8032, Zurich, Switzerland; Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, Blümlisalpstrasse 10, 8006, Zurich, Switzerland; Max Planck Institute for Metabolism Research, Cologne, Germany
| | - Jakob Heinzle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Wilfriedstrasse 6, 8032, Zurich, Switzerland
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79
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Feature binding in auditory modality requires attention as indexed by mismatch negativity and N2b in an active discrimination task. Neuroreport 2019; 29:308-313. [PMID: 29293173 DOI: 10.1097/wnr.0000000000000960] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Currently, there are two opposing views on feature binding in the auditory modality: according to behavioral studies, this process requires focused attention, whereas electrophysiological studies suggest that feature binding may be fully automatic and independent of attention. Here, we examined whether feature binding depends on higher-level attentional processes by manipulating the attentional focus. We used four auditory stimuli that differed in two features: pitch and location. Two rare deviants could be detected within a sequence of two frequent standards exclusively by feature conjunctions rather than by any single feature alone. Event-related potentials to auditory stimuli were analyzed for four conditions: selective attention to target auditory deviants, selective ignoring of nontarget auditory deviants, nonselective distributed attention to all stimuli within auditory modality, and selective attention diverted from auditory to visual modality. The negative difference (Nd) between event-related potentials to deviants and standards was measured within two time intervals, corresponding to mismatch negativity (100-200 ms) and N2b (200-300 ms). Only under the condition of selective attention to specific feature conjunctions, prominent Nd was observed in mismatch negativity as well in N2b time ranges, whereas no significant Nd was observed in other conditions. As Nd is considered a marker of deviance processing, our results support the view that deviance was not detected unless attention was focused on the stimuli, thus supporting the view that feature binding requires attention.
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80
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Gordon N, Tsuchiya N, Koenig-Robert R, Hohwy J. Expectation and attention increase the integration of top-down and bottom-up signals in perception through different pathways. PLoS Biol 2019; 17:e3000233. [PMID: 31039146 PMCID: PMC6490885 DOI: 10.1371/journal.pbio.3000233] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Accepted: 04/03/2019] [Indexed: 01/23/2023] Open
Abstract
Perception likely results from the interplay between sensory information and top-down signals. In this electroencephalography (EEG) study, we utilised the hierarchical frequency tagging (HFT) method to examine how such integration is modulated by expectation and attention. Using intermodulation (IM) components as a measure of nonlinear signal integration, we show in three different experiments that both expectation and attention enhance integration between top-down and bottom-up signals. Based on a multispectral phase coherence (MSPC) measure, we present two direct physiological measures to demonstrate the distinct yet related mechanisms of expectation and attention, which would not have been possible using other amplitude-based measures. Our results link expectation to the modulation of descending signals and to the integration of top-down and bottom-up information at lower levels of the visual hierarchy. Meanwhile, the results link attention to the modulation of ascending signals and to the integration of information at higher levels of the visual hierarchy. These results are consistent with the predictive coding account of perception.
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Affiliation(s)
- Noam Gordon
- Cognition and Philosophy Lab, Philosophy Department, Monash University, Clayton, Victoria, Australia
| | - Naotsugu Tsuchiya
- Monash Institute of Cognitive and Clinical Neurosciences, Monash University, Clayton, Victoria, Australia
- School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Osaka, Japan
- Advanced Telecommunications Research Computational Neuroscience Laboratories, Soraku-gun, Kyoto, Japan
| | - Roger Koenig-Robert
- School of Psychology, The University of New South Wales, Sydney, New South Wales, Australia
| | - Jakob Hohwy
- Cognition and Philosophy Lab, Philosophy Department, Monash University, Clayton, Victoria, Australia
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81
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Zuanazzi A, Noppeney U. Distinct Neural Mechanisms of Spatial Attention and Expectation Guide Perceptual Inference in a Multisensory World. J Neurosci 2019; 39:2301-2312. [PMID: 30659086 PMCID: PMC6433765 DOI: 10.1523/jneurosci.2873-18.2019] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 01/08/2019] [Accepted: 01/09/2019] [Indexed: 11/21/2022] Open
Abstract
Spatial attention (i.e., task-relevance) and expectation (i.e., signal probability) are two critical top-down mechanisms guiding perceptual inference. Spatial attention prioritizes processing of information at task-relevant locations. Spatial expectations encode the statistical structure of the environment. An unresolved question is how the brain allocates attention and forms expectations in a multisensory environment, where task-relevance and signal probability over space can differ across sensory modalities. We used functional magnetic resonance imaging in human participants (female and male) to investigate whether the brain encodes task-relevance and signal probability over space separately or interactively across sensory modalities. In a novel multisensory paradigm, we manipulated spatial attention and expectation selectively in audition and assessed their effects on behavioral and neural responses to auditory and visual stimuli. Our results show that both auditory and visual stimuli increased activations in a right-lateralized frontoparietal system, when they were presented at locations that were task-irrelevant in audition. Yet, only auditory stimuli increased activations in the medial prefrontal cortex when presented at expected locations and in audiovisual and frontoparietal cortices signaling a prediction error when presented at unexpected locations. This dissociation in multisensory generalization for attention and expectation effects shows that the brain controls attentional resources interactively across the senses but encodes the statistical structure of the environment as spatial expectations independently for each sensory system. Our results demonstrate that spatial attention and expectation engage partly overlapping neural systems via distinct mechanisms to guide perceptual inference in a multisensory world.SIGNIFICANCE STATEMENT In our natural environment the brain is exposed to a constant influx of signals through all our senses. How does the brain allocate attention and form spatial expectations in this multisensory environment? Because observers need to respond to stimuli regardless of their sensory modality, they may allocate attentional resources and encode the probability of events jointly across the senses. This psychophysics and neuroimaging study shows that the brain controls attentional resources interactively across the senses via a frontoparietal system but encodes the statistical structure of the environment independently for each sense in sensory and frontoparietal areas. Thus, spatial attention and expectation engage partly overlapping neural systems via distinct mechanisms to guide perceptual inference in a multisensory world.
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Affiliation(s)
- Arianna Zuanazzi
- Computational Cognitive Neuroimaging Laboratory, Computational Neuroscience and Cognitive Robotics Centre, University of Birmingham, B15 2TT Birmingham, United Kingdom
| | - Uta Noppeney
- Computational Cognitive Neuroimaging Laboratory, Computational Neuroscience and Cognitive Robotics Centre, University of Birmingham, B15 2TT Birmingham, United Kingdom
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82
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A division of labor between power and phase coherence in encoding attention to stimulus streams. Neuroimage 2019; 193:146-156. [PMID: 30877058 DOI: 10.1016/j.neuroimage.2019.03.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 02/20/2019] [Accepted: 03/08/2019] [Indexed: 11/22/2022] Open
Abstract
Both time-based (when) and feature-based (what) aspects of attention facilitate behavior, so it is natural to hypothesize additive effects. We tested this conjecture by recording response behavior and electroencephalographic (EEG) data to auditory pitch changes, embedded at different time lags in a continuous sound stream. Participants reacted more rapidly to larger rather than smaller feature change magnitudes (deviancy), as well as to changes appearing after longer rather than shorter waiting times (hazard rate of response times). However, the feature and time dimensions of attention separately contributed to response speed, with no significant interaction. Notably, phase coherence at low frequencies (delta and theta bands, 1-7 Hz) predominantly reflected attention capture by feature changes, while oscillatory power at higher frequency bands, alpha (8-12 Hz) and beta (13-25 Hz) reflected the orienting of attention in time. Power and phase coherence predicted different portions of response speed variance, suggesting a division of labor in encoding sensory attention in complex auditory scenes.
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83
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Reis C, Sharott A, Magill PJ, van Wijk BCM, Parr T, Zeidman P, Friston KJ, Cagnan H. Thalamocortical dynamics underlying spontaneous transitions in beta power in Parkinsonism. Neuroimage 2019; 193:103-114. [PMID: 30862535 PMCID: PMC6503152 DOI: 10.1016/j.neuroimage.2019.03.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 02/01/2019] [Accepted: 03/05/2019] [Indexed: 01/03/2023] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative condition in which aberrant oscillatory synchronization of neuronal activity at beta frequencies (15–35 Hz) across the cortico-basal ganglia-thalamocortical circuit is associated with debilitating motor symptoms, such as bradykinesia and rigidity. Mounting evidence suggests that the magnitude of beta synchrony in the parkinsonian state fluctuates over time, but the mechanisms by which thalamocortical circuitry regulates the dynamic properties of cortical beta in PD are poorly understood. Using the recently developed generic Dynamic Causal Modelling (DCM) framework, we recursively optimized a set of plausible models of the thalamocortical circuit (n = 144) to infer the neural mechanisms that best explain the transitions between low and high beta power states observed in recordings of field potentials made in the motor cortex of anesthetized Parkinsonian rats. Bayesian model comparison suggests that upregulation of cortical rhythmic activity in the beta-frequency band results from changes in the coupling strength both between and within the thalamus and motor cortex. Specifically, our model indicates that high levels of cortical beta synchrony are mainly achieved by a delayed (extrinsic) input from thalamic relay cells to deep pyramidal cells and a fast (intrinsic) input from middle pyramidal cells to superficial pyramidal cells. From a clinical perspective, our study provides insights into potential therapeutic strategies that could be utilized to modulate the network mechanisms responsible for the enhancement of cortical beta in PD. Specifically, we speculate that cortical stimulation aimed to reduce the enhanced excitatory inputs to either the superficial or deep pyramidal cells could be a potential non-invasive therapeutic strategy for PD. Coupling changes within and between circuit nodes lead to cortical beta enhancement. Input propagation delays play a crucial role in the up-regulation of cortical beta. Beta power could be modulated by altering lamina specific inputs.
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Affiliation(s)
- Carolina Reis
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Andrew Sharott
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK
| | - Peter J Magill
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK; Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Bernadette C M van Wijk
- Wellcome Centre for Human Neuroimaging, University College London, UK; Integrative Model-based Cognitive Neuroscience Research Unit, Department of Psychology, University of Amsterdam, the Netherlands
| | - Thomas Parr
- Wellcome Centre for Human Neuroimaging, University College London, UK
| | - Peter Zeidman
- Wellcome Centre for Human Neuroimaging, University College London, UK
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, University College London, UK
| | - Hayriye Cagnan
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK.
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84
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Attention promotes the neural encoding of prediction errors. PLoS Biol 2019; 17:e2006812. [PMID: 30811381 PMCID: PMC6411367 DOI: 10.1371/journal.pbio.2006812] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 03/11/2019] [Accepted: 02/05/2019] [Indexed: 11/20/2022] Open
Abstract
The encoding of sensory information in the human brain is thought to be optimised by two principal processes: 'prediction' uses stored information to guide the interpretation of forthcoming sensory events, and 'attention' prioritizes these events according to their behavioural relevance. Despite the ubiquitous contributions of attention and prediction to various aspects of perception and cognition, it remains unknown how they interact to modulate information processing in the brain. A recent extension of predictive coding theory suggests that attention optimises the expected precision of predictions by modulating the synaptic gain of prediction error units. Because prediction errors code for the difference between predictions and sensory signals, this model would suggest that attention increases the selectivity for mismatch information in the neural response to a surprising stimulus. Alternative predictive coding models propose that attention increases the activity of prediction (or 'representation') neurons and would therefore suggest that attention and prediction synergistically modulate selectivity for 'feature information' in the brain. Here, we applied forward encoding models to neural activity recorded via electroencephalography (EEG) as human observers performed a simple visual task to test for the effect of attention on both mismatch and feature information in the neural response to surprising stimuli. Participants attended or ignored a periodic stream of gratings, the orientations of which could be either predictable, surprising, or unpredictable. We found that surprising stimuli evoked neural responses that were encoded according to the difference between predicted and observed stimulus features, and that attention facilitated the encoding of this type of information in the brain. These findings advance our understanding of how attention and prediction modulate information processing in the brain, as well as support the theory that attention optimises precision expectations during hierarchical inference by increasing the gain of prediction errors.
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85
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Hsu YF, Waszak F, Hämäläinen JA. Prior Precision Modulates the Minimization of Auditory Prediction Error. Front Hum Neurosci 2019; 13:30. [PMID: 30828293 PMCID: PMC6385564 DOI: 10.3389/fnhum.2019.00030] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Accepted: 01/21/2019] [Indexed: 11/21/2022] Open
Abstract
The predictive coding model of perception proposes that successful representation of the perceptual world depends upon canceling out the discrepancy between prediction and sensory input (i.e., prediction error). Recent studies further suggest a distinction to be made between prediction error triggered by non-predicted stimuli of different prior precision (i.e., inverse variance). However, it is not fully understood how prediction error with different precision levels is minimized in the predictive process. Here, we conducted a magnetoencephalography (MEG) experiment which orthogonally manipulated prime-probe relation (for contextual precision) and stimulus repetition (for perceptual learning which decreases prediction error). We presented participants with cycles of tone quartets which consisted of three prime tones and one probe tone of randomly selected frequencies. Within each cycle, the three prime tones remained identical while the probe tones changed once at some point (e.g., from repetition of 123X to repetition of 123Y). Therefore, the repetition of probe tones can reveal the development of perceptual inferences in low and high precision contexts depending on their position within the cycle. We found that the two conditions resemble each other in terms of N1m modulation (as both were associated with N1m suppression) but differ in terms of N2m modulation. While repeated probe tones in low precision context did not exhibit any modulatory effect, repeated probe tones in high precision context elicited a suppression and rebound of the N2m source power. The differentiation suggested that the minimization of prediction error in low and high precision contexts likely involves distinct mechanisms.
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Affiliation(s)
- Yi-Fang Hsu
- Department of Educational Psychology and Counselling, National Taiwan Normal University, Taipei, Taiwan.,Institute for Research Excellence in Learning Sciences, National Taiwan Normal University, Taipei, Taiwan
| | - Florian Waszak
- Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,CNRS, Laboratoire Psychologie de la Perception, UMR 8242, Paris, France
| | - Jarmo A Hämäläinen
- Jyväskylä Centre for Interdisciplinary Brain Research, Department of Psychology, University of Jyväskylä, Jyväskylä, Finland
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86
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Focus of attention modulates the heartbeat evoked potential. Neuroimage 2019; 186:595-606. [DOI: 10.1016/j.neuroimage.2018.11.037] [Citation(s) in RCA: 88] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 11/13/2018] [Accepted: 11/21/2018] [Indexed: 01/23/2023] Open
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87
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Auditory predictions shape the neural responses to stimulus repetition and sensory change. Neuroimage 2019; 186:200-210. [DOI: 10.1016/j.neuroimage.2018.11.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Revised: 11/04/2018] [Accepted: 11/07/2018] [Indexed: 01/22/2023] Open
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88
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Predictive Processes and the Peculiar Case of Music. Trends Cogn Sci 2019; 23:63-77. [DOI: 10.1016/j.tics.2018.10.006] [Citation(s) in RCA: 185] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 10/23/2018] [Accepted: 10/24/2018] [Indexed: 12/18/2022]
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89
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The contemplative exercise through the lenses of predictive processing: A promising approach. PROGRESS IN BRAIN RESEARCH 2019; 244:299-322. [DOI: 10.1016/bs.pbr.2018.10.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
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90
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Structural and effective brain connectivity underlying biological motion detection. Proc Natl Acad Sci U S A 2018; 115:E12034-E12042. [PMID: 30514816 DOI: 10.1073/pnas.1812859115] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The perception of actions underwrites a wide range of socio-cognitive functions. Previous neuroimaging and lesion studies identified several components of the brain network for visual biological motion (BM) processing, but interactions among these components and their relationship to behavior remain little understood. Here, using a recently developed integrative analysis of structural and effective connectivity derived from high angular resolution diffusion imaging (HARDI) and functional magnetic resonance imaging (fMRI), we assess the cerebro-cerebellar network for processing of camouflaged point-light BM. Dynamic causal modeling (DCM) informed by probabilistic tractography indicates that the right superior temporal sulcus (STS) serves as an integrator within the temporal module. However, the STS does not appear to be a "gatekeeper" in the functional integration of the occipito-temporal and frontal regions: The fusiform gyrus (FFG) and middle temporal cortex (MTC) are also connected to the right inferior frontal gyrus (IFG) and insula, indicating multiple parallel pathways. BM-specific loops of effective connectivity are seen between the left lateral cerebellar lobule Crus I and right STS, as well as between the left Crus I and right insula. The prevalence of a structural pathway between the FFG and STS is associated with better BM detection. Moreover, a canonical variate analysis shows that the visual sensitivity to BM is best predicted by BM-specific effective connectivity from the FFG to STS and from the IFG, insula, and STS to the early visual cortex. Overall, the study characterizes the architecture of the cerebro-cerebellar network for BM processing and offers prospects for assessing the social brain.
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91
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Chao ZC, Takaura K, Wang L, Fujii N, Dehaene S. Large-Scale Cortical Networks for Hierarchical Prediction and Prediction Error in the Primate Brain. Neuron 2018; 100:1252-1266.e3. [DOI: 10.1016/j.neuron.2018.10.004] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 08/29/2018] [Accepted: 10/02/2018] [Indexed: 12/12/2022]
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92
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Ligneul R, Mermillod M, Morisseau T. From relief to surprise: Dual control of epistemic curiosity in the human brain. Neuroimage 2018; 181:490-500. [DOI: 10.1016/j.neuroimage.2018.07.038] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Revised: 07/13/2018] [Accepted: 07/15/2018] [Indexed: 12/29/2022] Open
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93
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Todd J, Cornwell R. The importance of precision to updating models of the sensory environment. Biol Psychol 2018; 139:8-16. [PMID: 30292784 DOI: 10.1016/j.biopsycho.2018.09.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Revised: 08/03/2018] [Accepted: 09/30/2018] [Indexed: 11/28/2022]
Abstract
The existence and updating of "sensory beliefs" or internal models can be studied using auditory evoked potentials (AEPs) when there is some form of predictable pattern in sound. Internal models are proposed to enable predictions about the most likely next sound-activation-state leading to small AEPs to standard sounds matching model predictions, and larger AEPs to sound that deviate. Internal models are precision-weighted with the standard-deviant difference being largest when precision is high (variability is low). Here we expose how order-effects determine whether a change in variability impacts model-precision estimates. Thirty participants heard 3000 t (30 ms standard p = 0.90 and 60 ms deviant p = 0.10) that either moved from a more precise stimulus onset asymmetry (n = 15, first 1000 tones 500 ms ± 10 ms) to a more variable one (n = 15, subsequent 2000 tones 500 ms ± 200 ms) or from variable (first 1000 t) to more precise (subsequent 2000 t). AEPs were equivalent between groups for the first 1000 tones but differed dramatically in the face of timing changes. Where timing precision decreased, the standard-deviant difference was impervious to the change but where precision increased, the standard-deviant difference increased dramatically after the timing change signalling a transient increase in model precision that subsided over the final 1000 tones. The results support contemporary models proposing that updates to an active internal model will be a function of the quality of the evidence upon which it has been built and the information value of subsequent errors in improving the predictive success of the active model.
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Affiliation(s)
- Juanita Todd
- School of Psychology, University of Newcastle, University Drive, Callaghan, NSW, 2308 Australia.
| | - Raymond Cornwell
- School of Psychology, University of Newcastle, University Drive, Callaghan, NSW, 2308 Australia
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94
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Not All Predictions Are Equal: "What" and "When" Predictions Modulate Activity in Auditory Cortex through Different Mechanisms. J Neurosci 2018; 38:8680-8693. [PMID: 30143578 DOI: 10.1523/jneurosci.0369-18.2018] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 07/22/2018] [Accepted: 07/26/2018] [Indexed: 11/21/2022] Open
Abstract
Using predictions based on environmental regularities is fundamental for adaptive behavior. While it is widely accepted that predictions across different stimulus attributes (e.g., time and content) facilitate sensory processing, it is unknown whether predictions across these attributes rely on the same neural mechanism. Here, to elucidate the neural mechanisms of predictions, we combine invasive electrophysiological recordings (human electrocorticography in 4 females and 2 males) with computational modeling while manipulating predictions about content ("what") and time ("when"). We found that "when" predictions increased evoked activity over motor and prefrontal regions both at early (∼180 ms) and late (430-450 ms) latencies. "What" predictability, however, increased evoked activity only over prefrontal areas late in time (420-460 ms). Beyond these dissociable influences, we found that "what" and "when" predictability interactively modulated the amplitude of early (165 ms) evoked responses in the superior temporal gyrus. We modeled the observed neural responses using biophysically realistic neural mass models, to better understand whether "what" and "when" predictions tap into similar or different neurophysiological mechanisms. Our modeling results suggest that "what" and "when" predictability rely on complementary neural processes: "what" predictions increased short-term plasticity in auditory areas, whereas "when" predictability increased synaptic gain in motor areas. Thus, content and temporal predictions engage complementary neural mechanisms in different regions, suggesting domain-specific prediction signaling along the cortical hierarchy. Encoding predictions through different mechanisms may endow the brain with the flexibility to efficiently signal different sources of predictions, weight them by their reliability, and allow for their encoding without mutual interference.SIGNIFICANCE STATEMENT Predictions of different stimulus features facilitate sensory processing. However, it is unclear whether predictions of different attributes rely on similar or different neural mechanisms. By combining invasive electrophysiological recordings of cortical activity with experimental manipulations of participants' predictions about content and time of acoustic events, we found that the two types of predictions had dissociable influences on cortical activity, both in terms of the regions involved and the timing of the observed effects. Further, our biophysical modeling analysis suggests that predictability of content and time rely on complementary neural processes: short-term plasticity in auditory areas and synaptic gain in motor areas, respectively. This suggests that predictions of different features are encoded with complementary neural mechanisms in different brain regions.
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95
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Generic dynamic causal modelling: An illustrative application to Parkinson's disease. Neuroimage 2018; 181:818-830. [PMID: 30130648 PMCID: PMC7343527 DOI: 10.1016/j.neuroimage.2018.08.039] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Revised: 08/15/2018] [Accepted: 08/16/2018] [Indexed: 12/26/2022] Open
Abstract
We present a technical development in the dynamic causal modelling of
electrophysiological responses that combines qualitatively different neural mass
models within a single network. This affords the option to couple various
cortical and subcortical nodes that differ in their form and dynamics. Moreover,
it enables users to implement new neural mass models in a straightforward and
standardized way. This generic framework hence supports flexibility and
facilitates the exploration of increasingly plausible models. We illustrate this
by coupling a basal ganglia-thalamus model to a (previously validated) cortical
model developed specifically for motor cortex. The ensuing DCM is used to infer
pathways that contribute to the suppression of beta oscillations induced by
dopaminergic medication in patients with Parkinson's disease.
Experimental recordings were obtained from deep brain stimulation electrodes
(implanted in the subthalamic nucleus) and simultaneous magnetoencephalography.
In line with previous studies, our results indicate a reduction of synaptic
efficacy within the circuit between the subthalamic nucleus and external
pallidum, as well as reduced efficacy in connections of the hyperdirect and
indirect pathway leading to this circuit. This work forms the foundation for a
range of modelling studies of the synaptic mechanisms (and pathophysiology)
underlying event-related potentials and cross-spectral densities.
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Rosch RE, Auksztulewicz R, Leung PD, Friston KJ, Baldeweg T. Selective Prefrontal Disinhibition in a Roving Auditory Oddball Paradigm Under N-Methyl-D-Aspartate Receptor Blockade. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2018; 4:140-150. [PMID: 30115499 PMCID: PMC6374982 DOI: 10.1016/j.bpsc.2018.07.003] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/03/2018] [Revised: 07/05/2018] [Accepted: 07/05/2018] [Indexed: 01/07/2023]
Abstract
BACKGROUND Disturbances in N-methyl-D-aspartate receptors (NMDARs)-as implicated in patients with schizophrenia-can cause regionally specific electrophysiological effects. Both animal models of NMDAR blockade and clinical studies in patients with schizophrenia have suggested that behavioral phenotypes are associated with reduction in inhibition within the frontal cortex. METHODS Here we investigate event-related potentials to a roving auditory oddball paradigm under ketamine in healthy human volunteers (N= 18; double-blind, placebo-controlled, crossover design). Using recent advances in Bayesian modeling of group effects in dynamic causal modeling, we fit biophysically plausible network models of the auditory processing hierarchy to whole-scalp event-related potential recordings. This allowed us to identify regionally specific effects of ketamine in a distributed network of interacting cortical sources. RESULTS We show that the effect of ketamine is best explained as a selective change in intrinsic inhibition, with a pronounced ketamine-induced reduction of inhibitory interneuron connectivity in frontal sources, compared with temporal sources. Simulations of these changes in an integrated microcircuit model shows that they are associated with a reduction in superficial pyramidal cell activity that can explain drug effects observed in the event-related potential. CONCLUSIONS These results are consistent with findings from invasive recordings in animal models exposed to NMDAR blockers, and provide evidence that inhibitory interneuron-specific NMDAR dysfunction may be sufficient to explain electrophysiological abnormalities induced by NMDAR blockade in human subjects.
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Affiliation(s)
- Richard E Rosch
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom; Developmental Neurosciences Programme, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom.
| | - Ryszard Auksztulewicz
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom; Department of Biomedical Sciences, City University of Hong Long, Hong Kong
| | - Pui Duen Leung
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
| | - Karl J Friston
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
| | - Torsten Baldeweg
- Developmental Neurosciences Programme, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
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97
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Fucci E, Abdoun O, Caclin A, Francis A, Dunne JD, Ricard M, Davidson RJ, Lutz A. Differential effects of non-dual and focused attention meditations on the formation of automatic perceptual habits in expert practitioners. Neuropsychologia 2018; 119:92-100. [PMID: 30040956 DOI: 10.1016/j.neuropsychologia.2018.07.025] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 07/15/2018] [Accepted: 07/20/2018] [Indexed: 10/28/2022]
Abstract
Non-dual meditation aims to undo maladaptive cognitive and affective patterns by recognizing their constructed and transient nature. We previously found high-amplitude spontaneous gamma (25-40 Hz) oscillatory activity during such practice. Nonetheless, it is unclear how this meditation state differs from other practices, in terms of perceptual information processing. Here, we hypothesized that non-dual meditation can downregulate the automatic formation of perceptual habits. To investigate this hypothesis, we recorded EEG from expert Buddhist meditation practitioners and matched novices to measure two components of the auditory evoked response: the Mismatch Negativity (MMN) and the Late Frontal Negativity (LFN), a potential observed at a latency sensitive to attentional engagement to the auditory environment, during the practices of Open Presence (OP) and Focused Attention (FA), as well as during a control state, in the context of a passive oddball paradigm. We found an increase in gamma oscillatory power during both meditation states in expert practitioners and an interaction between states and groups in the amplitude of the MMN. A further investigation identified the specific interplay between the MMN and the LFN as a possible marker to differentiate the two meditation states as a function of expertise. In experts, the MMN increased during FA, compared to OP, while the opposite pattern was observed at the LFN latency. We propose that the state of OP in experts is characterized by increased sensory monitoring and reduced perceptual inferences compared to FA. This study represents a first attempt to describe the impact of non-dual meditation states on the regulation of automatic brain predictive processes.
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Affiliation(s)
- E Fucci
- Lyon Neuroscience Research Centre, INSERM U1028, CNRS UMR5292, Lyon 1 University, Lyon, France
| | - O Abdoun
- Lyon Neuroscience Research Centre, INSERM U1028, CNRS UMR5292, Lyon 1 University, Lyon, France
| | - A Caclin
- Lyon Neuroscience Research Centre, INSERM U1028, CNRS UMR5292, Lyon 1 University, Lyon, France
| | - A Francis
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - J D Dunne
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - M Ricard
- Shechen Tennyi Dargyeling Monastery, Nepal
| | - R J Davidson
- University of Wisconsin, Madison, WI, USA; Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - A Lutz
- Lyon Neuroscience Research Centre, INSERM U1028, CNRS UMR5292, Lyon 1 University, Lyon, France; University of Wisconsin, Madison, WI, USA.
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98
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Amado C, Stoyanova P, Kovács G. Visual mismatch response and fMRI signal adaptation correlate in the occipital-temporal cortex. Behav Brain Res 2018. [PMID: 29524450 DOI: 10.1016/j.bbr.2018.03.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Several electrophysiological studies found response differences to a given stimulus when it is repeated frequently as compared to when it occurs rarely in oddball sequences. Initially defined in acoustic perception, such difference also exists in the visual modality and is referred to as visual mismatch negativity (vMMN). However, the repetition of a stimulus also leads to the reduction of the blood oxygen-level dependent (BOLD) signal (fMRI adaptation, fMRIa) when compared to alternating stimuli in fMRI experiments. So far no study compared the vMMN to fMRIa within the same paradigm and participants. Here we tested the possible connection between fMRIa and vMMN in a visual oddball paradigm in two separate sessions, acquiring electrophysiological and neuroimaging data for real and false characters from the same participants. We found significant visual mismatch response (vMM) as well as fMRIa for both character types. Importantly, the magnitude of the vMM over the CP1 electrode cluster showed a significant correlation with the fMRIa within the letter form area, for real characters. This finding suggests that similar neural mechanisms are responsible for the two phenomena.
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Affiliation(s)
- Catarina Amado
- Institute of Psychology, Friedrich Schiller University Jena, 07743 Jena, Germany
| | - Polina Stoyanova
- Institute of Psychology, Friedrich Schiller University Jena, 07743 Jena, Germany
| | - Gyula Kovács
- Institute of Psychology, Friedrich Schiller University Jena, 07743 Jena, Germany; Person Perception Research Unit, Friedrich Schiller University Jena, 07743 Jena, Germany; Brain Imaging Centre, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary.
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99
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Spriggs MJ, Sumner RL, McMillan RL, Moran RJ, Kirk IJ, Muthukumaraswamy SD. Indexing sensory plasticity: Evidence for distinct Predictive Coding and Hebbian learning mechanisms in the cerebral cortex. Neuroimage 2018; 176:290-300. [PMID: 29715566 DOI: 10.1016/j.neuroimage.2018.04.060] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Revised: 03/13/2018] [Accepted: 04/25/2018] [Indexed: 11/17/2022] Open
Abstract
The Roving Mismatch Negativity (MMN), and Visual LTP paradigms are widely used as independent measures of sensory plasticity. However, the paradigms are built upon fundamentally different (and seemingly opposing) models of perceptual learning; namely, Predictive Coding (MMN) and Hebbian plasticity (LTP). The aim of the current study was to compare the generative mechanisms of the MMN and visual LTP, therefore assessing whether Predictive Coding and Hebbian mechanisms co-occur in the brain. Forty participants were presented with both paradigms during EEG recording. Consistent with Predictive Coding and Hebbian predictions, Dynamic Causal Modelling revealed that the generation of the MMN modulates forward and backward connections in the underlying network, while visual LTP only modulates forward connections. These results suggest that both Predictive Coding and Hebbian mechanisms are utilized by the brain under different task demands. This therefore indicates that both tasks provide unique insight into plasticity mechanisms, which has important implications for future studies of aberrant plasticity in clinical populations.
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Affiliation(s)
- M J Spriggs
- School of Psychology, The University of Auckland, New Zealand; Brain Research New Zealand, New Zealand.
| | - R L Sumner
- School of Psychology, The University of Auckland, New Zealand
| | - R L McMillan
- School of Pharmacy, The University of Auckland, New Zealand
| | - R J Moran
- Department Engineering Mathematics, University of Bristol, BS8 1TH, UK; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - I J Kirk
- School of Psychology, The University of Auckland, New Zealand; Brain Research New Zealand, New Zealand
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100
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Additive and interactive effects of spatial attention and expectation on perceptual decisions. Sci Rep 2018; 8:6732. [PMID: 29712941 PMCID: PMC5928039 DOI: 10.1038/s41598-018-24703-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Accepted: 04/06/2018] [Indexed: 11/08/2022] Open
Abstract
Spatial attention and expectation are two critical top-down mechanisms controlling perceptual inference. Based on previous research it remains unclear whether their influence on perceptual decisions is additive or interactive. We developed a novel multisensory approach that orthogonally manipulated spatial attention (i.e. task-relevance) and expectation (i.e. signal probability) selectively in audition and evaluated their effects on observers' responses in vision. Critically, while experiment 1 manipulated expectation directly via the probability of task-relevant auditory targets across hemifields, experiment 2 manipulated it indirectly via task-irrelevant auditory non-targets. Surprisingly, our results demonstrate that spatial attention and signal probability influence perceptual decisions either additively or interactively. These seemingly contradictory results can be explained parsimoniously by a model that combines spatial attention, general and spatially selective response probabilities as predictors with no direct influence of signal probability. Our model provides a novel perspective on how spatial attention and expectation facilitate effective interactions with the environment.
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