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Marsicano G, Bertini C, Ronconi L. Decoding cognition in neurodevelopmental, psychiatric and neurological conditions with multivariate pattern analysis of EEG data. Neurosci Biobehav Rev 2024; 164:105795. [PMID: 38977116 DOI: 10.1016/j.neubiorev.2024.105795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 06/21/2024] [Accepted: 07/03/2024] [Indexed: 07/10/2024]
Abstract
Multivariate pattern analysis (MVPA) of electroencephalographic (EEG) data represents a revolutionary approach to investigate how the brain encodes information. By considering complex interactions among spatio-temporal features at the individual level, MVPA overcomes the limitations of univariate techniques, which often fail to account for the significant inter- and intra-individual neural variability. This is particularly relevant when studying clinical populations, and therefore MVPA of EEG data has recently started to be employed as a tool to study cognition in brain disorders. Here, we review the insights offered by this methodology in the study of anomalous patterns of neural activity in conditions such as autism, ADHD, schizophrenia, dyslexia, neurological and neurodegenerative disorders, within different cognitive domains (perception, attention, memory, consciousness). Despite potential drawbacks that should be attentively addressed, these studies reveal a peculiar sensitivity of MVPA in unveiling dysfunctional and compensatory neurocognitive dynamics of information processing, which often remain blind to traditional univariate approaches. Such higher sensitivity in characterizing individual neurocognitive profiles can provide unique opportunities to optimise assessment and promote personalised interventions.
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Affiliation(s)
- Gianluca Marsicano
- Department of Psychology, University of Bologna, Viale Berti Pichat 5, Bologna 40121, Italy; Centre for Studies and Research in Cognitive Neuroscience, University of Bologna, Via Rasi e Spinelli 176, Cesena 47023, Italy.
| | - Caterina Bertini
- Department of Psychology, University of Bologna, Viale Berti Pichat 5, Bologna 40121, Italy; Centre for Studies and Research in Cognitive Neuroscience, University of Bologna, Via Rasi e Spinelli 176, Cesena 47023, Italy.
| | - Luca Ronconi
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
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Melcher D, Alaberkyan A, Anastasaki C, Liu X, Deodato M, Marsicano G, Almeida D. An early effect of the parafoveal preview on post-saccadic processing of English words. Atten Percept Psychophys 2024:10.3758/s13414-024-02916-4. [PMID: 38956003 DOI: 10.3758/s13414-024-02916-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/05/2024] [Indexed: 07/04/2024]
Abstract
A key aspect of efficient visual processing is to use current and previous information to make predictions about what we will see next. In natural viewing, and when looking at words, there is typically an indication of forthcoming visual information from extrafoveal areas of the visual field before we make an eye movement to an object or word of interest. This "preview effect" has been studied for many years in the word reading literature and, more recently, in object perception. Here, we integrated methods from word recognition and object perception to investigate the timing of the preview on neural measures of word recognition. Through a combined use of EEG and eye-tracking, a group of multilingual participants took part in a gaze-contingent, single-shot saccade experiment in which words appeared in their parafoveal visual field. In valid preview trials, the same word was presented during the preview and after the saccade, while in the invalid condition, the saccade target was a number string that turned into a word during the saccade. As hypothesized, the valid preview greatly reduced the fixation-related evoked response. Interestingly, multivariate decoding analyses revealed much earlier preview effects than previously reported for words, and individual decoding performance correlated with participant reading scores. These results demonstrate that a parafoveal preview can influence relatively early aspects of post-saccadic word processing and help to resolve some discrepancies between the word and object literatures.
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Affiliation(s)
- David Melcher
- Psychology Program, Division of Science, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, United Arab Emirates.
- Center for Brain and Health, NYUAD Research Institute, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, United Arab Emirates.
| | - Ani Alaberkyan
- Psychology Program, Division of Science, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, United Arab Emirates
| | - Chrysi Anastasaki
- Psychology Program, Division of Science, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, United Arab Emirates
| | - Xiaoyi Liu
- Psychology Program, Division of Science, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, United Arab Emirates
- Department of Psychology, Princeton University, Washington Rd, Princeton, NJ, 08540, USA
| | - Michele Deodato
- Psychology Program, Division of Science, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, United Arab Emirates
- Center for Brain and Health, NYUAD Research Institute, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, United Arab Emirates
| | - Gianluca Marsicano
- Department of Psychology, University of Bologna, Viale Berti Pichat 5, 40121, Bologna, Italy
- Centre for Studies and Research in Cognitive Neuroscience, University of Bologna, Via Rasi e Spinelli 176, 47023, Cesena, Italy
| | - Diogo Almeida
- Psychology Program, Division of Science, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, United Arab Emirates
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Mares I, Smith FW, Goddard EJ, Keighery L, Pappasava M, Ewing L, Smith ML. Effects of expectation on face perception and its association with expertise. Sci Rep 2024; 14:9402. [PMID: 38658575 PMCID: PMC11043383 DOI: 10.1038/s41598-024-59284-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 04/09/2024] [Indexed: 04/26/2024] Open
Abstract
Perceptual decisions are derived from the combination of priors and sensorial input. While priors are broadly understood to reflect experience/expertise developed over one's lifetime, the role of perceptual expertise at the individual level has seldom been directly explored. Here, we manipulate probabilistic information associated with a high and low expertise category (faces and cars respectively), while assessing individual level of expertise with each category. 67 participants learned the probabilistic association between a color cue and each target category (face/car) in a behavioural categorization task. Neural activity (EEG) was then recorded in a similar paradigm in the same participants featuring the previously learned contingencies without the explicit task. Behaviourally, perception of the higher expertise category (faces) was modulated by expectation. Specifically, we observed facilitatory and interference effects when targets were correctly or incorrectly expected, which were also associated with independently measured individual levels of face expertise. Multivariate pattern analysis of the EEG signal revealed clear effects of expectation from 100 ms post stimulus, with significant decoding of the neural response to expected vs. not stimuli, when viewing identical images. Latency of peak decoding when participants saw faces was directly associated with individual level facilitation effects in the behavioural task. The current results not only provide time sensitive evidence of expectation effects on early perception but highlight the role of higher-level expertise on forming priors.
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Affiliation(s)
- Inês Mares
- School of Psychological Sciences, Birkbeck College, University of London, London, UK.
- William James Center for Research, Ispa - Instituto Universitário, Lisbon, Portugal.
| | - Fraser W Smith
- School of Psychology, University of East Anglia, Norwich, UK
| | - E J Goddard
- School of Psychological Sciences, Birkbeck College, University of London, London, UK
| | - Lianne Keighery
- School of Psychological Sciences, Birkbeck College, University of London, London, UK
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, UK
| | - Michael Pappasava
- School of Psychological Sciences, Birkbeck College, University of London, London, UK
- Centre for Genomics and Child Health, Blizard Institute, Queen Mary University of London, London, UK
| | - Louise Ewing
- School of Psychology, University of East Anglia, Norwich, UK
| | - Marie L Smith
- School of Psychological Sciences, Birkbeck College, University of London, London, UK
- Centre for Brain and Cognitive Development, Birkbeck College, University of London, London, UK
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Marsicano G, Casartelli L, Federici A, Bertoni S, Vignali L, Molteni M, Facoetti A, Ronconi L. Prolonged neural encoding of visual information in autism. Autism Res 2024; 17:37-54. [PMID: 38009961 DOI: 10.1002/aur.3062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 10/30/2023] [Indexed: 11/29/2023]
Abstract
Autism spectrum disorder (ASD) is associated with a hyper-focused visual attentional style, impacting higher-order social and affective domains. The understanding of such peculiarity can benefit from the use of multivariate pattern analysis (MVPA) of high-resolution electroencephalography (EEG) data, which has proved to be a powerful technique to investigate the hidden neural dynamics orchestrating sensory and cognitive processes. Here, we recorded EEG in typically developing (TD) children and in children with ASD during a visuo-spatial attentional task where attention was exogenously captured by a small (zoom-in) or large (zoom-out) cue in the visual field before the appearance of a target at different eccentricities. MVPA was performed both in the cue-locked period, to reveal potential differences in the modulation of the attentional focus, and in the target-locked period, to reveal potential cascade effects on stimulus processing. Cue-locked MVPA revealed that while in the TD group the pattern of neural activity contained information about the cue mainly before the target appearance, the ASD group showed a temporally sustained and topographically diffuse significant decoding of the cue neural response even after the target onset, suggesting a delayed extinction of cue-related neural activity. Crucially, this delayed extinction positively correlated with behavioral measures of attentional hyperfocusing. Results of target-locked MVPA were coherent with a hyper-focused attentional profile, highlighting an earlier and stronger decoding of target neural responses in small cue trials in the ASD group. The present findings document a spatially and temporally overrepresented encoding of visual information in ASD, which can constitute one of the main reasons behind their peculiar cognitive style.
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Affiliation(s)
- Gianluca Marsicano
- Department of Psychology, University of Bologna, Bologna, Italy
- Centre for Studies and Research in Cognitive Neuroscience, University of Bologna, Cesena, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Luca Casartelli
- Child Psychopathology Department, Theoretical and Cognitive Neuroscience Unit, Scientific Institute IRCCS E.MEDEA, Bosisio Parini, Italy
| | | | - Sara Bertoni
- Department of Human and Social Sciences, University of Bergamo, Bergamo, Italy
- Developmental and Cognitive Neuroscience Lab, Department of General Psychology, University of Padua, Padova, Italy
| | | | - Massimo Molteni
- Child Psychopathology Department, Theoretical and Cognitive Neuroscience Unit, Scientific Institute IRCCS E.MEDEA, Bosisio Parini, Italy
| | - Andrea Facoetti
- Developmental and Cognitive Neuroscience Lab, Department of General Psychology, University of Padua, Padova, Italy
| | - Luca Ronconi
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy
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Mares I, Ewing L, Papasavva M, Ducrocq E, Smith FW, Smith ML. Face recognition ability is manifest in early dynamic decoding of face-orientation selectivity-Evidence from multi-variate pattern analysis of the neural response. Cortex 2023; 159:299-312. [PMID: 36669447 DOI: 10.1016/j.cortex.2022.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 09/20/2022] [Accepted: 11/07/2022] [Indexed: 12/23/2022]
Abstract
Although humans are considered to be face experts, there is a well-established reliable variation in the degree to which neurotypical individuals are able to learn and recognise faces. While many behavioural studies have characterised these differences, studies that seek to relate the neuronal response to standardised behavioural measures of ability remain relatively scarce, particularly so for the time-resolved approaches and the early response to face stimuli. In the present study we make use of a relatively recent methodological advance, multi-variate pattern analysis (MVPA), to decode the time course of the neural response to faces compared to other object categories (inverted faces, objects). Importantly, for the first time, we directly relate metrics of this decoding assessed at the individual level to gold-standard measures of behavioural face processing ability assessed in an independent task. Thirty-nine participants completed the behavioural Cambridge Face Memory Test (CFMT), then viewed images of faces and houses (presented upright and inverted) while their neural activity was measured via electroencephalography. Significant decoding of both face orientation and face category were observed in all individual participants. Decoding of face orientation, a marker of more advanced face processing, was earlier and stronger in participants with higher levels of face expertise, while decoding of face category information was earlier but not stronger for individuals with greater face expertise. Taken together these results provide a marker of significant differences in the early neuronal response to faces from around 100 ms post stimulus as a function of behavioural expertise with faces.
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Affiliation(s)
- Inês Mares
- School of Psychological Science, Birkbeck College, University of London, UK; William James Center for Research, Ispa - Instituto Universitário, Portugal.
| | - Louise Ewing
- School of Psychology, University of East Anglia, Norwich, UK
| | - Michael Papasavva
- School of Psychological Science, Birkbeck College, University of London, UK
| | - Emmanuel Ducrocq
- School of Psychological Science, Birkbeck College, University of London, UK
| | - Fraser W Smith
- School of Psychology, University of East Anglia, Norwich, UK
| | - Marie L Smith
- School of Psychological Science, Birkbeck College, University of London, UK; Centre for Brain and Cognitive Development, Birkbeck College, University of London, UK
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Ng B, Reh RK, Mostafavi S. A practical guide to applying machine learning to infant EEG data. Dev Cogn Neurosci 2022; 54:101096. [PMID: 35334336 PMCID: PMC8943418 DOI: 10.1016/j.dcn.2022.101096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 03/07/2022] [Accepted: 03/10/2022] [Indexed: 11/08/2022] Open
Abstract
Electroencephalography (EEG) has been widely adopted by the developmental cognitive neuroscience community, but the application of machine learning (ML) in this domain lags behind adult EEG studies. Applying ML to infant data is particularly challenging due to the low number of trials, low signal-to-noise ratio, high inter-subject variability, and high inter-trial variability. Here, we provide a step-by-step tutorial on how to apply ML to classify cognitive states in infants. We describe the type of brain attributes that are widely used for EEG classification and also introduce a Riemannian geometry based approach for deriving connectivity estimates that account for inter-trial and inter-subject variability. We present pipelines for learning classifiers using trials from a single infant and from multiple infants, and demonstrate the application of these pipelines on a standard infant EEG dataset of forty 12-month-old infants collected under an auditory oddball paradigm. While we classify perceptual states induced by frequent versus rare stimuli, the presented pipelines can be easily adapted for other experimental designs and stimuli using the associated code that we have made publicly available.
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