Our research is theoretically driven by ideas of Predictive Coding, a computational framework that posits the brain is a predictive, efficient and adaptive machine. The main goal of the group is to understand how the brain’s circuitry implements these mechanisms, which enable us to make predictions about future events as well as learn about, and adapt to, the contingencies of a novel environment. Along with our work on typical cognition in healthy human individuals, our mission is to contribute to the understanding of mental illness, in particular to those conditions where predictive processes and brain circuitry are disrupted such as in schizophrenia and anxiety. To pursue this endeavour we use a combination of computational modelling, machine learning and brain imaging techniques such as magnetoencephalography (MEG), electroencephalography (EEG), and magnetic resonance imaging (MRI).

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RESEARCH PAPERS

Pre-prints

1. E.G. Rowe, Garrido, M.I., N. Tsuchiya. Do neural input patterns to the front of the brain contain information about the contents of consciousness? Registered Report (Stage 1, in revision)
2. I. Dzafic, C.D. Harris, L. Webber, Garrido, M.I.. Greater belief instability but lower volatility attuning in psychosis. Invited submission for Neuroimage special issue)
3. E. Rowe. Y. Zhang, Garrido, M.I. Evidence for adaptive myelination of subcortical shortcuts for visual motion perception in healthy adults. https://www.biorxiv.org/content/10.1101/2023.01.11.523655v1
4. A. Renton, ….Garrido, M.I., ….S. Bollmann. Neurodesk: An accessible, flexible, and portable data analysis environment for reproducible neuroimaging. https://www.biorxiv.org/content/10.1101/2022.12.23.521691v1
5. Isabella Goodwin, Joshua Kugel, Robert Hester, M.I. Garrido. Bayesian Accounts of Perceptual Decisions in the Nonclinical continuum of psychosis: Greater imprecision in both bottom-up and top-down processes. https://www.biorxiv.org/content/10.1101/2022.10.24.513606v1 Accepted/Published:
6. E.G. Rowe*, C.D. Harris*, I. Dzafic, Garrido, M.I.. Anxiety attenuates the behavioural and neuronal learning advantages conferred by statistical stability. Human Brain Mapping (in press) 2022

Published

7. R. Randeniya, I. Vilares. J.B. Mattingley. Garrido, M.I.. Increased functional activity, reduced adaptation and stronger top-down effective connectivity during visual learning in autism. Neuroimage: Clinical (accepted 13/12/22.
8. A. Putica, K.L. Felmingham, Garrido, M.I., M.L. O’Donnell, N.T. Van Dam. A Predictive Coding Account of Value-Based Learning in PTSD: Implications for Precision Treatments. Neuroscience and Biobehavioral Reviews.
9. R. Randeniya, J.B. Mattingley. Garrido, M.I.. Increased context adjustment is associated with auditory sensitivities but not with autistic traits. Autism Research
10. S. Kalhan, J. McFadyen, N. Tsuchiya, Garrido, M.I.. Neural and computational processes of accelerated perceptual awareness and decisions: A 7T fMRI Study. Human Brain Mapping.
11. J. McFadyen, C. Smout, N. Tsuchiya, J.B. Mattingley, Garrido, M.I.. Surprising threats accelerate conscious perception. Frontiers in Behavioural Neuroscience, Emotion Regulation and Processing.
12. S.C.H. Lin, Garrido, M.I.. Towards a cross-level understanding of Bayesian inference in the brain. Neuroscience and Biobehavioral Reviews.
13. R. Auksztulewicz, Garrido, M.I., M.S. Malmierca, A. Tavano, J. Todd, I. Winkler (2022) Editorial: Sensing the world through predictions and errors. Frontiers in Human Neuroscience, Cognitive Neuroscience.
14. S. Kalhan, E. Chen, Garrido, M.I.*, R. Hester* (2022) People with tobacco use disorder exhibit more prefrontal activity during preparatory control but reduced anterior cingulate activity during reactive control. Addiction Biology 27:e13159. 2021
15. R. Randeniya, I. Vilares. J.B. Mattingley. Garrido, M.I.. (2021) Reduced context updating but intact priors in autism. Computational Psychiatry 5(1), pp. 140–158.
16. M.S. Boord, D.D. Davis, P.J. Psaltis, S. Coussens, D. Feuerrieguel, Garrido, M.I., A. Bourke, H.A.D. Keage (2021) The DelIrium VULnerability in Geriatrics (DIVULGUE) Study: Protocol for a prospective observational study of electroencephalogram associations with incident delirium. BMJ Neurol Open 3(2):e000199.
17. A. Lacroix, L. Nalborczyk, F. Dutheil, Klara Kovarski, S. Chokron, Garrido, M.I., M. Gomot, M. Mermillod (2021) High spatial frequency information in primes hastens happy faces categorization in autistic adults. Brain and Cognition 155:105811.
18. Garrido, M.I., L.Y. Deouell (2021) Unilateral Neglect within the predictive processing framework. Brain Communications (commentary) 3(3)fcab193
19. J.A. Taylor, K.M. Larsen, I. Dzafic, Garrido, M.I.. (2021) Predicting sub-clinical psychotic-like experiences on a continuum using machine learning. Neuroimage 241:118329.
20. Kalhan S., Redish, D., Hester R., Garrido. M.I. (2021) A Salience Misattribution Model for Addictive-Like Behaviours. Neuroscience and Behavioral Reviews 125:466-477.
21. Dzafic I., Larsen M., Carter O., Sundram S., Garrido M.I. (2021) Stronger top-down and weaker bottomup frontotemporal connections during sensory learning are associated with severity of psychotic phenomena. Schizophrenia Bulletin 47:1039-1047.
22. M.J. Dietz, J.F. Nielsen, A. Roepstorff, Garrido, M.I.. (2021). Reduced effective connectivity between right parietal and inferior frontal cortex during audiospatial perception in neglect patients with a right-hemisphere lesion. Hearing Research 399:108052.
23. P.A. Pincheira, E. Martinez-Valdes, R. Martinez-Valdes, R. Guzman-Venegas, D. Falla, Garrido, M.I., A.G. Cresswell, G.A. Lichtwark. (2021) Regional changes in muscle activity do not underlie the repeated bout effect in the human gastrocnemius muscle. Scandinavian Journa of Medicine & Science in Sports 31:799- 812. 2020
24. E.G. Rowe, N. Tsuchiya*, Garrido, M.I. * (2020). Detecting (un)seen change: The neural underpinnings of (un)conscious prediction errors. Frontiers in Systems Neuroscience 14:541670.
25. F. Dark, E. Newman, V. Gore-Jones, V. de Monte, M.I Garrido, I. Dzafic (2020). Randomised controlled trial of Compensatory Cognitive Training and a Computerised Cognitive Remediation programme. Trials 21:810.
26. A. Taylor, K.M. Larsen, Garrido, M.I. (2020). Multidimension predictions of psychotic symptoms via machine learning. Human Brain Mapping 41:5151-5163.
27. I. Dzafic, R. Randeniya, C.D. Harris, M. Bammel, Garrido, M.I. (2020). Statistical learning and inference is impaired in the non-clinical continuum of psychosis. The Journal of Neuroscience 40:6759-6769.
28. C. Pernet, Garrido, M.I., …, A. Puce (2020) Issues and recommendations from the OHBM COBIDAS MEEG committee for reproducible EEG and MEG research. Nature Neuroscience 23: 1473-1483 (see also Best Practices in Data Analysis and Sharing in Neuroimaging using MEEG. https://osf.io/a8dhx/) Top 10% most cited worldwide
29. K. Garner, Garrido, M.I.*, P.E. Dux* (2020). Cognitive capacity limits are remediated by pratice-induced plasticity in a striatal-cortical network. eNeuro 7: ENEURO.0139-20.2020. Ranking it in the top 5% of all research outputs scored by Altmetric
30. K.M. Larsen, I. Dzafic, H. Darke, H. Pertile, O. Carter, S. Sundram, M.I Garrido. (2020) Aberrant connectivity in auditory precision encoding in schizophrenia spectrum disorder and across the continuum pf psychotic-like experiences. Schizophrenia Research 222:185-194.
31. C.A. Smout. Garrido, M.I., J.B. Mattingley. (2020) Global Effects of Feature-based Attention Depend on Surprise. Neuroimage.215:116785.
32. J. McFadyen. R.J. Dolan, Garrido, M.I.. (2020) The influence of subcortical shortcuts on disordered sensory and cognitive processing. Nature Reviews Neuroscience 21: 264-276.
33. J.A. Taylor, Garrido, M.I. (2020) Porthole and Stormcloud: Tools for visualisation of spatiotemporal M/EEG statistics. NeuroInformatics doi: 10.1007/s12021-019-09447-6
34. K. Garner, Garrido, M.I.*, P.E. Dux*. Cognitive capacity limits are remediated by practice-induced plasticity in a striatal-cortical network. https://www.biorxiv.org/content/10.1101/564450v1
35. C. Pernet, Garrido, M.I., A Gramfort, .... A. Puce. Best Practices in Data Analysis and Sharing in Neuroimaging using MEEG. https://osf.io/a8dhx/
36. Taylor, J., Garrido, M.I. (2019). Porthole and Stormcloud: Tools for visualisation of spatiotemporal M/EEG statistics. bioRxiv doi:org/10.1101/534784
37. McFadyen, J., Smout, C., Tsuchiya, N., Mattingley, J., Garrido, M.I. (2019). Surprising threats accelerate evidence accumulation for conscious perception. bioRxiv dio.org/10.1101/525519
38. Dietz, M., Nielsen, J., Roepstorff, A., Garrido, M.I. (2017). Dysconnection of right parietal and frontal cortex in neglect syndrome. bioRxiv doi: 10.1101/192583
39. Dzafic, I., Randeniya, R., Garrido, M.I. (2018). Reduced top-down connectivity as an underlying mechanism for psychotic experiences in healthy people. bioRxiv doi: 10.1101/296988
40. J.A. Taylor, K.M. Larsen, I. Dzafic, Garrido, M.I.. Predicting Individual Psychotic Experiences on a Continuum using machine learning. https://www.biorxiv.org/content/early/2018/07/30/380162
41. L.K.L. Oestreich*, R. Randeniya*, Garrido, M.I.. Auditory prediction errors and auditory white matter microstructure predict psychotic experiences in the healthy population. Brain Structure and Function
42. L.K.L Oestreich, R. Randenya, Garrido, M.I.. (2019) Structural connectivity facilitates functional connectivity of auditory prediction error generation within a fronto-temporal network. NeuroImage 195:454-462. Best paper of the month awarded by University of Queensland Centre for Clinical Research.
43. Larsen, K.M., Morup, M., Birknow, M.R., Fischer, E., Olsen, L., Didriksen, M., Baare, W.F.C., Werge, T.M.,Garrido, M.I*., Siebner, H.R*. Individuals with 22q11.2 deletion syndrome show intact prediction but reduced adaptation in responses to repeated sounds: evidence from Bayesian mapping. Neuroimage: Clinical *equal contribution
44. Smout, C., Tang, M., Garrido, M.I., Mattingley, M. (2019). Attention Promotes the Neural Encoding of Prediction Errors. PLOS Biology
45. McFadyen, J., Mattingley, J.,Garrido, M.I. (2019). An afferent white matter pathway from the pulvinar to the amygdala facilitates fear recognition. eLife 8:e40766
46. Harris, C.D., Rowe, E.G.,Randeniya, R., Garrido, M.I. (2018). Bayesian Model Selection Maps for group studies using M/EEG data.Frontiers in Neuroscience. 12: Article 598
47. Oestreich, L.K.L., Randenya, R., Garrido, M.I. (2018). White matter connectivity distruptions in the pre-clinical continuum of psychosis: A connectome study. Hum Brain Mapp. 40(2): 529-537
48. van Heusden, E., Harris, A., Garrido, M., Hogendoorn, H.(2019).Predictive coding of visual motion in both monocular and binocular visual processing. Journal of Vision. 19 (1):3, 1-12
49. Larsen, K.M., Dzafic, I., Siebner, H.R., Garrido, M. (2018). Alteration of functional brain architecture in 22q11.2 deletion syndrome - Insights into susceptibility for psychosis. NeuroImage 197: 328-336
50. Oestreich, L., Whitford, T.,  Garrido, M.I.  (2018). Prediction of speech sounds is facilitated by a functional fronto-temporal network. frontiers in Neural Circuits. 12:43
51. Larsen, K.M., Morup, M., Birknow, M., Fischer, E., Hulme, O., Vangkilde, A., Schmock., H., Baare, W.F.C., Didriksen, M., Olsen, L., Werge, T., Siebner, H.R., Garrido, M.I. (2018). Altered auditory processing and effective connectivity in 22q 11.2 deletion syndrome. Schizophrenia Research. 197: 328-336
52. Dzafic, I., Burianova, H., Periyasamy, S., Mowry, B. (2018). Association between schizophrenia polygenic risk and neural correlates of emotional perception. Psychiatry Research: Neuroimaging. 276:33-40
53. Cornwell, B., Garrido, M.I. Overstreet, C., Pine, D., Grillon, C.(2017). The un-predictive brain under threat: a neuro-computational account of anxious hypervigilance. Biological Psychiatry. 82: 447-454
54. Randeniya, R., Oestreich, L., Garrido, M.I.  (2018). Sensory prediction errors in the continuum of psychosis. Schizophrenia Research 191: 109-122
55. Garrido, M.I., Rowe, E., Halasz, V., Mattingley, J. (2017). Bayesian mapping reveals that attention boosts neural responses to predicted and unpredicted stimuli. Cerebral Cortex. 1-12
56. McFayden, J., Mermillod, M., Mattingley, J., Halasz. V., Garrido, M.I. (2017). A rapid subcortical amygdala route for faces irrespective of spatial frequency and emotion. J. Neurosci 37 (14) 3864-3874
57. Oestreich, L., Lyall, A., Pasternak, O., Kikinis, Z., Newell., Savadjiev, P., Bouix, S., Shenton, M., Kubicki, M. (2017). Characterizing white matter changes in chronic schizophrenia: A free-water imaging multi-site study. Schizophrenia Research, 189pp:153-161
58. Taylor, J.A., Matthews, N., Michie, P.T., Rosa, M.J., Garrido, M.I. (2017). Auditory prediction errors as individual biomarkers of schizophrenia. Neuroimage: Clinical. 15:264-273
59. Sherwell, C., Garrido, M.I. , Cunnington, R. (2016). Timing in predictive coding: The role of task relevance and global probability. Journal of Cognitive Neuroscience. 29 (5): 780-792
60. Oestreich,L.K.L., Pasternak,O., Shenton, M.E., Kubicki, M., Gong, X., Australian Schizophrenia Research Bank, McCarthy-Jones, S., Whitford, T.J. (2016). Abnormal white matter microstructure and increased extracellular free-water in the cingulul bundle associated with delusions in chronic schizophrenia. NeuroImage: Clinical, 12, pp: 405-414
61. Roberts, G., Lord, A.,Frankland, A., Wright, A., Lau, P., Levy, F., Lenroot, R.K., Mitchell, P.B., Breakspear, M. (2016). Functional dysconnection of the inferior frontal gyrus in young people with bipolar disorder or at genetic high risk. Biological Psychiatry.
62. Kaunitz, L.N., Rowe, E.G., Tsuchiya, N. (2016). Large Capacity of Conscious Access for Incidental Memories in Natural Scenes. PsychSci, 27(9) 1266-1277
63. Garrido, M.I., Teng, C.L.J., Taylor, J., Rowe, E.G. and Mattingley. J.B. (2016). Surprise responses in the human brain demonstrate statistical learning under high concurrent cognitive demand. npj Science of Learning. 1, 16006
64. Roberts, J.A., Perry, A., Lord, A.R., Roberts, G., Mitchell, P.B., Smith, R.E., Calamante, F. and Breakspear, M. (2016). The contribution of geometry to the human connectome. NeuroImage, 124, pp: 379-393.
65. Zavitz, E., Yu, H.H., Rowe, E.G., Rosa, M.G. and Price, N.S. (2016). Rapid Adaptation Induces Persistent Biases in Population Codes for Visual Motion. The Journal of Neuroscience, 36(16), pp: 4579-4590.
66. Cooray.G., Garrido, M.I., Brismar, T., Hyllienmark, L. (2016). The maturation of mismatch negativity networks in normal adolescence. Clinical Neurophysiology 127(1) pp: 520-529
67. Dürschmid, S., Zaehle, T., Hinrichs, H., Heinze, H., Voges, J., Garrido, M.I. Dolan, R.J., Knight, R. (2016). Sensory deviancy detection measured directly within the Human Nucleus Accumbens. Cerebral Cortex 26 pp: 1168-1175
68. Litvak, V., Garrido, M.I., Zeidman, P., Friston, K. (2015). Empirical Bayes for Group (DCM) Studies: A Reproducibility Study. Frontiers in Human Neuroscience.
69. Garrido, M.I. Barnes, G.R., Kumaran, D., Maguire, E.A., Dolan, R.J. (2015). Ventromedial prefrontal cortex drives hippocampal theta oscillations induced by mismatch computations. NeuroImage 120 pp: 362-370.
70. Poch, C., Garrido, M.I. Igoa, J.M., Belinchon, M., Morales-Morales,I., Campo, P. (2015).Time-varying effective connectivity during visual object naming as a function of semantic demands. Journal of Neuroscience 35(23) pp: 8768-8776
71. He, W., Garrido, M.I. Sowman, P.F, Brock, J., Johnson, B.W. (2015). Development of effective connectivity in the core network for face perception. Hum. Brain Mapp., 36 pp: 2161–2173
72. Rosa, M.J., Portugal, L., Hahn, T., Fallgatter, A.J., Garrido, M.I. Shawe-Taylor, J., Mourao-Miranda, J. (2015). Sparse network-based models for patient classification using fMRI. Neuroimage 105 pp: 493 506.
73. Dietz, M.J., Friston, J.B., Mattingley, J.B., Roepstorff, A., Garrido, M.I. (2014). Effective connectivity reveals right-hemisphere dominance in audiospatial perception: Implications for models of spatial neglect. The Journal of Neuroscience 34 pp: 5003 - 5011. Selected by Australian Life Scientist as some of the best Australian research published in May/June 2014.
74. Cooray, G.K., Garrido, M.I. Hyllienmark, L., Brismar, T. (2014). A mechaistic model of mismatch negativity in the aging brain. Clinical Neurophysiology 125 (9) pp: 1774 - 1782.
75. Garvert, M.M., Friston, K.J., Dolan R.J., Garrido, M.I. (2014). Subcortical amygdala pathways enable rapid face processing. Neuroimage 102 Pt 2 pp: 309 -316.
76. Lieder, F., Stephan, K.E., Daunizeau, J., Garrido, M.I. Friston. (2013). A neurocomputational model of the mismatch negativity. PLoS Computational Biology 9 (11):e1003288.
77. Garrido, M.I. Sahani, M., Dolan, R.J. (2013). Outlier responses reflect sensitivity to statistical structure in the human brain. PLoS Computational Biology 9 (3) e1002999
78. Lieder, F., Daunizeau, J., Garrido, M.I. Friston, K.J., Stephan, K.E. (2013). Modelling trial-by-trial changes in the mismatch negativity. PLoS Computational Biology 9(2): e1002911
79. Campo, P., Garrido, M.I. Moran, R.J., Garcia-Morales, I., Poch, C., Toledano, R., Gil-Nagel, A., Dolan, R., Friston, K. (2013). Network configuration and working memory impairment in mesial temporal lobe epilepsy. NeuroImage 72 pp:48-54
80. Boly, M., Massimini, M., Garrido, M.I. Gosseries, O., Noirhomme, Q., Laureys, S., Soddu, A. (2012). Brain connectivity in disorders of consciousness. Brain Connectivity 2 pp: 1 - 10.
81. Garrido, M.I. Barnes,G., Sahani, M., Dolan, R. (2012). Functional evidence for a dual route to amygdala. Current Biology 22 pp: 129 - 134.
82. Garrido, M.I. Brain connectivity: the feeling of blindsight. Current Biology 22: R599 - R600. Invited Dispatch.
83. Murta, T., Leal, A., Garrido, M.I. Figueiredo, P. (2012). Dynamic causal modelling of epileptic seizure propagation pathways: a combined EEG-fMRI study. NeuroImage 62 pp: 1634 - 1642. Awarded 2nd prize, "Liga Portuguesa contra a Epilepsia" 2013.
84. Campo, P., Garrido, M.I. Moran, R., Maestu, F., Garcia-Morales, I., Gil-Nagel., A., del Pozo, F., Dolan, R., Friston, K. (2012) Remote effects of hippocampal sclerosis on effective connectivity during working memory encoding: a case of connectional diaschisis? Cerebral Cortex 22 pp: 1225 -1235.
85. Garrido, M.I. Dolan, R., Sahani, M. (2011). Surprise leads to noiser perceptual decisions. iPerception 2 pp: 112 - 120.
86. Boly, M., Garrido, M.I. Gosseries, O., Bruno, M.A., Schnakers, C., Massimini, M., Litvak, V., Laureys, S., Friston, K. (2011). Preserved feedforward but impaired top-down processes in the vegetative state. Science 332 pp: 858 - 862. (Recommended in Faculty of 1000, article factor of 8 (must read) and 6 (recommended)). (see also: G. Miller (2011) Feedback From Frontal Cortex May Be a Signature of Consciousness. Science 332:779; J.R.King, T. Bekinschtein, S.M.Dehaene (2011) Comment on "Preserved feedforward but impaired top-down processesin the vegetative state". Science 334: 1203; L. Welberg (2011). Auditory processing: sounding out consciousness. Nat Rev Neurosci 12: 369)
87. Garrido, M.I. Kilner, J.M., Kiebel, S.J., Friston, K.J. (2009). Dynamic causal modelling of the response to frequency deviants. Journal of Neurophysiology 101 pp: 2620- 2631.
88. Garrido, M.I. Kilner, J.M., Stephan, K.E., Friston, K.J. (2009). The mismatch negativity: a review of the underlying mechanisms. Invited review. Clinical Neurophysiology 120 pp: 453 - 463. Issue cover.
89. Kiebel, S.J., Garrido, M.I. Moran, R.J., Chen, C.C., Friston, K.J. (2009). Dynamic causal modelling for EEG and MEG. Review. Human Brain Mapping 30 pp: 1866 - 1876.
90. Garrido, M.I. Kilner, J.M., Kiebel, S.J., Stephan, K.E., Baldeweg, T., Friston, K.J. (2009). Repetition suppression and cortico-cortical plasticity in the human brain. NeuroImage 48 pp: 269 - 279.
91. Garrido, M.I. Friston, K.J, Kiebel, S.J., Stephan, K.E., Baldeweg, T., Kilner, J.M. (2008). The functional anatomy of the MMN: A DCM study of the roving paradigm. NeuroImage 42 pp: 936 - 944.
92. Kiebel, S.J., Garrido, M.I. Moran, R.J., Friston, K.J. (2008). Dynamic causal modelling for EEG and MEG. Cogn Neurodyn 2 pp: 121 - 136.
93. Garrido, M.I. Kilner, J.M., Kiebel, S.J., Friston, K.J. (2007). Evoked brain responses are generated by feedback loops. Proceedings of the National Academy of Sciences of the USA 104 pp: 20961 - 20966.
94. Garrido, M.I. Kilner, J.M., Kiebel, S.J., Stephan, K.E., Friston, K.J. (2007). Dynamic causal modelling of evoked potentials: A reproducibility study. NeuroImage 36 pp: 571 - 580.
95. Kiebel, S.J., Garrido, M.I. Friston, K.J. (2007). Dynamic causal modelling of evoked responses: The role of intrinsic connections. NeuroImage 36 pp: 332 -345.

Book chapters

96. Kiebel, S.J., Garrido, M.I. Friston, K.J. (2010). Analysing functional and effective connectivity with EEG and MEG. In: Simultaneous EEG and fMRI: Recording, Analysis and Application. Markus Ullsperger & Stefan Deneber. Oxford University Press. Chapter 3.8 pp: 235 - 249.
97. Kiebel, S.J., Garrido, M.I. Friston, K.J. (2009). Dynamic causal modelling for evoked responses. In: Brain signal analysis: Advances in neurelectric and neuromagnetic methods. Todd Handy, The MIT Press. Chapter 6 pp: 141 - 169.
98. Friston, K., Kiebel, S., Garrido, M.I. David, O. (2007). Dynamic casual models for EEG. In: Statistical Parametric Mapping 2007. Eds: K. Friston, J. Ashburner, S. Kiebel, T. Nichols, W. Penny. Academic Press. Chapter 42 pp: 561 - 576