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Meyer GM, Riou M, Boulinguez P, Sescousse G. Mechanisms of Proactive Adaptation in a Rewarded Response Inhibition Task: Executive, Motor, or Attentional Effects? COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2025:10.3758/s13415-025-01269-1. [PMID: 39939462 DOI: 10.3758/s13415-025-01269-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/21/2025] [Indexed: 02/14/2025]
Abstract
A growing number of studies have demonstrated the effects of reward motivation on inhibitory control performance. However, the exact neurocognitive mechanisms supporting these effects are not fully elucidated. In this preregistered study, we test the hypothesis that changes in speed-accuracy trade-off across contexts that alternatively incentivize fast responses versus accurate inhibition rely on a modulation of proactive inhibitory control, a mechanism intended to lock movement initiation in anticipation of stimulus presentation. Thirty healthy participants performed a modified Go/NoGo task in which the motivation to prioritize Go vs. NoGo successes was manipulated using monetary rewards of different magnitudes. High-density EEG was recorded throughout the task. Source-space analyses were performed to track brain oscillatory activities consistent with proactive inhibitory control. We observed that participants adapted their behavior to the motivational context but found no evidence that this adaptation relied on a modulation of proactive inhibitory control, hence failing to provide support for our pre-registered hypothesis. Unplanned analyses of brain-behavior relationships suggested an association between faster reaction times and enhanced top-down attention to the stimuli associated with larger rewards, as well as between increased commission error rates and stronger motor activations when Go stimuli were associated with larger rewards. The latter was related to inter-individual differences in trait reward responsiveness. These results highlight the need to carefully parse the different contributing mechanisms when studying the influence of reward motivation on inhibitory performance in impulsivity disorders. Exploratory results suggest alternative mechanisms that may be directly tested in further studies.
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Affiliation(s)
- Garance M Meyer
- Université de Lyon, 69622, Lyon, France.
- Université Lyon 1, Villeurbanne, France.
- INSERM, U 1028, Lyon Neuroscience Research Center, 69000, Lyon, France.
- CNRS, UMR 5292, Lyon Neuroscience Research Center, 69000, Lyon, France.
- Brigham and Women's Hospital, Center for Brain Circuit Therapeutics, 60 Fenwood Rd, Boston, MA, 02115, USA.
- Harvard Medical School, Boston, MA, USA.
| | - Maëlle Riou
- Université de Lyon, 69622, Lyon, France
- Université Lyon 1, Villeurbanne, France
- INSERM, U 1028, Lyon Neuroscience Research Center, 69000, Lyon, France
- CNRS, UMR 5292, Lyon Neuroscience Research Center, 69000, Lyon, France
| | - Philippe Boulinguez
- Université de Lyon, 69622, Lyon, France
- Université Lyon 1, Villeurbanne, France
- INSERM, U 1028, Lyon Neuroscience Research Center, 69000, Lyon, France
- CNRS, UMR 5292, Lyon Neuroscience Research Center, 69000, Lyon, France
| | - Guillaume Sescousse
- Université de Lyon, 69622, Lyon, France
- Université Lyon 1, Villeurbanne, France
- INSERM, U 1028, Lyon Neuroscience Research Center, 69000, Lyon, France
- CNRS, UMR 5292, Lyon Neuroscience Research Center, 69000, Lyon, France
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2
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Lio G, Corazzol M, Fadda R, Doneddu G, Sirigu A. A neuronal marker of eye contact spontaneously activated in neurotypical subjects but not in autistic spectrum disorders. Cortex 2025; 183:87-104. [PMID: 39626467 DOI: 10.1016/j.cortex.2024.10.022] [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: 04/28/2023] [Revised: 07/23/2023] [Accepted: 10/25/2024] [Indexed: 02/21/2025]
Abstract
Attention to faces and eye contact are key behaviors for establishing social bonds in humans. In Autism Spectrum Disorders (ASD), a disturbance in neurodevelopment, impaired face processing and gaze avoidance are key clinical features for ASD diagnosis. The biological alterations underlying these impairments are not yet clearly established. Using high-density electroencephalography coupled with multi-variate pattern classification and group blind source separation methods we searched for face- and-face components-related neural signals that could best discriminate visual processing of neurotypical subjects (N = 38) from ASD participants (N = 27). We isolated a face-specific neural signal in the superior temporal sulcus peaking at 240 msec after face-stimulus onset. A machine learning algorithm applied on the extracted neural component reached 74% decoding accuracy at the same latencies, discriminating the neurotypical population from ASD subjects in whom this signal was weak. By manipulating attention on different parts of the face, we also found that the power of the evoked signal in neurotypical subjects varied depending on the region observed: it was strong when the eye region fell on the fovea to decrease on regions further away and outside the stimulus face. Such face and face-components selective neural modulations were not found in ASD, although they did show typical early face-related P100 and N170 signals. These results show that specialized cortical mechanisms for face perception show higher responses for eyes when attention is focused on gaze and that these mechanisms may be particularly affected in autism spectrum disorders.
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Affiliation(s)
- Guillaume Lio
- Institute of Cognitive Sciences Marc Jeannerod, CNRS, Bron, France; iMIND Center of Excellence for Autism, Le Vinatier Hospital, Bron, France
| | - Martina Corazzol
- Institute of Cognitive Sciences Marc Jeannerod, CNRS, Bron, France
| | - Roberta Fadda
- Department of Psychology, Philosophy, University of Cagliari, Italy
| | - Giuseppe Doneddu
- Centro per l'Autismo e Disturbi Correlati (CADc), Cagliari, Italy
| | - Angela Sirigu
- Institute of Cognitive Sciences Marc Jeannerod, CNRS, Bron, France; iMIND Center of Excellence for Autism, Le Vinatier Hospital, Bron, France; Aix-Marseille Université, CNRS, Institut de Neurosciences de la Timone UMR7289, Marseille, France.
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Meyer GM, Marco-Pallarés J, Boulinguez P, Sescousse G. Electrophysiological underpinnings of reward processing: Are we exploiting the full potential of EEG? Neuroimage 2021; 242:118478. [PMID: 34403744 DOI: 10.1016/j.neuroimage.2021.118478] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 06/21/2021] [Accepted: 08/14/2021] [Indexed: 11/27/2022] Open
Abstract
Understanding how the brain processes reward is an important and complex endeavor, which has involved the use of a range of complementary neuroimaging tools, including electroencephalography (EEG). EEG has been praised for its high temporal resolution but, because the signal recorded at the scalp is a mixture of brain activities, it is often considered to have poor spatial resolution. Besides, EEG data analysis has most often relied on event-related potentials (ERPs) which cancel out non-phase locked oscillatory activity, thus limiting the functional discriminative power of EEG attainable through spectral analyses. Because these three dimensions -temporal, spatial and spectral- have been unequally leveraged in reward studies, we argue that the full potential of EEG has not been exploited. To back up our claim, we first performed a systematic survey of EEG studies assessing reward processing. Specifically, we report on the nature of the cognitive processes investigated (i.e., reward anticipation or reward outcome processing) and the methods used to collect and process the EEG data (i.e., event-related potential, time-frequency or source analyses). A total of 359 studies involving healthy subjects and the delivery of monetary rewards were surveyed. We show that reward anticipation has been overlooked (88% of studies investigated reward outcome processing, while only 24% investigated reward anticipation), and that time-frequency and source analyses (respectively reported by 19% and 12% of the studies) have not been widely adopted by the field yet, with ERPs still being the dominant methodology (92% of the studies). We argue that this focus on feedback-related ERPs provides a biased perspective on reward processing, by ignoring reward anticipation processes as well as a large part of the information contained in the EEG signal. Finally, we illustrate with selected examples how addressing these issues could benefit the field, relying on approaches combining time-frequency analyses, blind source separation and source localization.
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Affiliation(s)
- Garance M Meyer
- Université de Lyon, F-69622, Lyon, France; Université Lyon 1, Villeurbanne, France; INSERM, U 1028, Lyon Neuroscience Research Center, Lyon, F-69000, France; CNRS, UMR 5292, Lyon Neuroscience Research Center, Lyon, F-69000, France
| | - Josep Marco-Pallarés
- Department of Cognition, Development and Educational Psychology, Institute of Neurosciences, University of Barcelona, Spain; Cognition and Brain Plasticity Unit, Bellvitge Biomedical Research Institute, Spain
| | - Philippe Boulinguez
- Université de Lyon, F-69622, Lyon, France; Université Lyon 1, Villeurbanne, France; INSERM, U 1028, Lyon Neuroscience Research Center, Lyon, F-69000, France; CNRS, UMR 5292, Lyon Neuroscience Research Center, Lyon, F-69000, France.
| | - Guillaume Sescousse
- Université de Lyon, F-69622, Lyon, France; Université Lyon 1, Villeurbanne, France; INSERM, U 1028, Lyon Neuroscience Research Center, Lyon, F-69000, France; CNRS, UMR 5292, Lyon Neuroscience Research Center, Lyon, F-69000, France
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4
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Meyer GM, Spay C, Beliakova A, Gaugain G, Pezzoli G, Ballanger B, Boulinguez P, Cilia R. Inhibitory control dysfunction in parkinsonian impulse control disorders. Brain 2021; 143:3734-3747. [PMID: 33320929 DOI: 10.1093/brain/awaa318] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 07/07/2020] [Accepted: 08/03/2020] [Indexed: 12/27/2022] Open
Abstract
Impulse control disorders (ICDs) in Parkinson's disease have been associated with dysfunctions in the control of value- or reward-based responding (choice impulsivity) and abnormalities in mesocorticolimbic circuits. The hypothesis that dysfunctions in the control of response inhibition (action impulsivity) also play a role in Parkinson's disease ICDs has recently been raised, but the underlying neural mechanisms have not been probed directly. We used high-resolution EEG recordings from 41 patients with Parkinson's disease with and without ICDs to track the spectral and dynamical signatures of different mechanisms involved in inhibitory control in a simple visuomotor task involving no selection between competing responses and no reward to avoid potential confounds with reward-based decision. Behaviourally, patients with Parkinson's disease with ICDs proved to be more impulsive than those without ICDs. This was associated with decreased beta activity in the precuneus and in a region of the medial frontal cortex centred on the supplementary motor area. The underlying dynamical patterns pinpointed dysfunction of proactive inhibitory control, an executive mechanism intended to gate motor responses in anticipation of stimulation in uncertain contexts. The alteration of the cortical drive of proactive response inhibition in Parkinson's disease ICDs pinpoints the neglected role the precuneus might play in higher order executive functions in coordination with the supplementary motor area, specifically for switching between executive settings. Clinical perspectives are discussed in the light of the non-dopaminergic basis of this function.
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Affiliation(s)
- Garance M Meyer
- Université de Lyon, F-69622, Lyon, France.,Université Lyon 1, Villeurbanne, France.,INSERM, U 1028, Lyon Neuroscience Research Center, Lyon, F-69000, France.,CNRS, UMR 5292, Lyon Neuroscience Research Center, Lyon, F-69000, France
| | - Charlotte Spay
- Université de Lyon, F-69622, Lyon, France.,Université Lyon 1, Villeurbanne, France.,INSERM, U 1028, Lyon Neuroscience Research Center, Lyon, F-69000, France.,CNRS, UMR 5292, Lyon Neuroscience Research Center, Lyon, F-69000, France
| | - Alina Beliakova
- Université de Lyon, F-69622, Lyon, France.,Université Lyon 1, Villeurbanne, France.,INSERM, U 1028, Lyon Neuroscience Research Center, Lyon, F-69000, France.,CNRS, UMR 5292, Lyon Neuroscience Research Center, Lyon, F-69000, France
| | - Gabriel Gaugain
- Université de Lyon, F-69622, Lyon, France.,Université Lyon 1, Villeurbanne, France.,INSERM, U 1028, Lyon Neuroscience Research Center, Lyon, F-69000, France.,CNRS, UMR 5292, Lyon Neuroscience Research Center, Lyon, F-69000, France
| | - Gianni Pezzoli
- Fondazione Grigioni per il Morbo di Parkinson, Milan, Italy.,Previous affiliation: Parkinson Institute, ASST "Gaetano Pini-CTO", Milan, Italy
| | - Bénédicte Ballanger
- Université de Lyon, F-69622, Lyon, France.,Université Lyon 1, Villeurbanne, France.,INSERM, U 1028, Lyon Neuroscience Research Center, Lyon, F-69000, France.,CNRS, UMR 5292, Lyon Neuroscience Research Center, Lyon, F-69000, France
| | - Philippe Boulinguez
- Université de Lyon, F-69622, Lyon, France.,Université Lyon 1, Villeurbanne, France.,INSERM, U 1028, Lyon Neuroscience Research Center, Lyon, F-69000, France.,CNRS, UMR 5292, Lyon Neuroscience Research Center, Lyon, F-69000, France
| | - Roberto Cilia
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Department of Clinical Neurosciences, Parkinson and Movement Disorders Unit, Milan, Italy.,Previous affiliation: Parkinson Institute, ASST "Gaetano Pini-CTO", Milan, Italy
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5
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Velasquez-Martinez LF, Zapata-Castano F, Castellanos-Dominguez G. Dynamic Modeling of Common Brain Neural Activity in Motor Imagery Tasks. Front Neurosci 2020; 14:714. [PMID: 33328839 PMCID: PMC7711077 DOI: 10.3389/fnins.2020.00714] [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: 09/27/2019] [Accepted: 06/12/2020] [Indexed: 12/17/2022] Open
Abstract
Evaluation of brain dynamics elicited by motor imagery (MI) tasks can contribute to clinical and learning applications. The multi-subject analysis is to make inferences on the group/population level about the properties of MI brain activity. However, intrinsic neurophysiological variability of neural dynamics poses a challenge for devising efficient MI systems. Here, we develop a time-frequency model for estimating the spatial relevance of common neural activity across subjects employing an introduced statistical thresholding rule. In deriving multi-subject spatial maps, we present a comparative analysis of three feature extraction methods: Common Spatial Patterns, Functional Connectivity, and Event-Related De/Synchronization. In terms of interpretability, we evaluate the effectiveness in gathering MI data from collective populations by introducing two assumptions: (i) Non-linear assessment of the similarity between multi-subject data originating the subject-level dynamics; (ii) Assessment of time-varying brain network responses according to the ranking of individual accuracy performed in distinguishing distinct motor imagery tasks (left-hand vs. right-hand). The obtained validation results indicate that the estimated collective dynamics differently reflect the flow of sensorimotor cortex activation, providing new insights into the evolution of MI responses.
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Affiliation(s)
| | - Frank Zapata-Castano
- Signal Processing and Recognition Group, Universidad Nacional de Colombia, Manizales, Colombia
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Spay C, Meyer G, Lio G, Pezzoli G, Ballanger B, Cilia R, Boulinguez P. Resting state oscillations suggest a motor component of Parkinson's Impulse Control Disorders. Clin Neurophysiol 2019; 130:2065-2075. [PMID: 31541984 DOI: 10.1016/j.clinph.2019.08.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 07/02/2019] [Accepted: 08/14/2019] [Indexed: 12/25/2022]
Abstract
OBJECTIVES Impulse control disorders (ICDs) in Parkinson's disease (PD) have been associated with cognitive impulsivity and dopaminergic dysfunction and treatment. The present study tests the neglected hypothesis that the neurofunctional networks involved in motor impulsivity might also be dysfunctional in PD-ICDs. METHODS We performed blind spectral analyses of resting state electroencephalographic (EEG) data in PD patients with and without ICDs to probe the functional integrity of all cortical networks. Analyses were performed directly at the source level after blind source separation. Discrete differences between groups were tested by comparing patients with and without ICDs. Gradual dysfunctions were assessed by means of correlations between power changes and clinical scores reflecting ICD severity (QUIP score). RESULTS Spectral signatures of ICDs were found in the medial prefrontal cortex, the dorsal anterior cingulate and the supplementary motor area, in the beta and gamma bands. Beta power changes in the supplementary motor area were found to predict ICDs severity. CONCLUSION ICDs are associated with abnormal activity within frequency bands and cortical circuits supporting the control of motor response inhibition. SIGNIFICANCE These results bring to the forefront the need to consider, in addition to the classical interpretation based on aberrant mesocorticolimbic reward processing, the issue of motor impulsivity in PD-ICDs and its potential implications for PD therapy.
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Affiliation(s)
- Charlotte Spay
- Université de Lyon, 92 rue Pasteur, 69007 Lyon, France; Université Lyon 1, 43 boulevard du 11 novembre 1918, 69622 Villeurbanne, France; INSERM, U 1028, Lyon Neuroscience Research Center, 95 boulevard Pinel, 69500 Bron, France; CNRS, UMR 5292, Lyon Neuroscience Research Center, 95 boulevard Pinel, 69500 Bron, France
| | - Garance Meyer
- Université de Lyon, 92 rue Pasteur, 69007 Lyon, France; Université Lyon 1, 43 boulevard du 11 novembre 1918, 69622 Villeurbanne, France; INSERM, U 1028, Lyon Neuroscience Research Center, 95 boulevard Pinel, 69500 Bron, France; CNRS, UMR 5292, Lyon Neuroscience Research Center, 95 boulevard Pinel, 69500 Bron, France
| | - Guillaume Lio
- Centre de Neuroscience Cognitive, UMR 5229, 67 boulevard Pinel, 69675 Bron, France
| | - Gianni Pezzoli
- Parkinson Institute, ASST Gaetano Pini-CTO, Via bignami 1, 20126 Milan, Italy
| | - Bénédicte Ballanger
- Université de Lyon, 92 rue Pasteur, 69007 Lyon, France; Université Lyon 1, 43 boulevard du 11 novembre 1918, 69622 Villeurbanne, France; INSERM, U 1028, Lyon Neuroscience Research Center, 95 boulevard Pinel, 69500 Bron, France; CNRS, UMR 5292, Lyon Neuroscience Research Center, 95 boulevard Pinel, 69500 Bron, France
| | - Roberto Cilia
- Parkinson Institute, ASST Gaetano Pini-CTO, Via bignami 1, 20126 Milan, Italy
| | - Philippe Boulinguez
- Université de Lyon, 92 rue Pasteur, 69007 Lyon, France; Université Lyon 1, 43 boulevard du 11 novembre 1918, 69622 Villeurbanne, France; INSERM, U 1028, Lyon Neuroscience Research Center, 95 boulevard Pinel, 69500 Bron, France; CNRS, UMR 5292, Lyon Neuroscience Research Center, 95 boulevard Pinel, 69500 Bron, France.
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7
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Spay C, Albares M, Lio G, Thobois S, Broussolle E, Lau B, Ballanger B, Boulinguez P. Clonidine modulates the activity of the subthalamic-supplementary motor loop: evidence from a pharmacological study combining deep brain stimulation and electroencephalography recordings in Parkinsonian patients. J Neurochem 2019; 146:333-347. [PMID: 29675956 DOI: 10.1111/jnc.14447] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Revised: 03/15/2018] [Accepted: 04/04/2018] [Indexed: 12/24/2022]
Abstract
Clonidine is an anti-hypertensive medication which acts as an alpha-adrenergic receptor agonist. As the noradrenergic system is likely to support cognitive functions including attention and executive control, other clinical uses of clonidine have recently gained popularity for the treatment of neuropsychiatric disorders like attention-deficit hyperactivity disorder or Tourette syndrome, but the mechanism of action is still unclear. Here, we test the hypothesis that the noradrenergic system regulates the activity of subthalamo-motor cortical loops, and that this influence can be modulated by clonidine. We used pharmacological manipulation of clonidine in a placebo-controlled study in combination with subthalamic nucleus-deep brain stimulation (STN-DBS) in 16 Parkinson's disease patients performing a reaction time task requiring to refrain from reacting (proactive inhibition). We recorded electroencephalographical activity of the whole cortex, and applied spectral analyses directly at the source level after advanced blind source separation. We found only one cortical source localized to the supplementary motor area (SMA) that supported an interaction of pharmacological and subthalamic stimulation. Under placebo, STN-DBS reduced proactive alpha power in the SMA, a marker of local inhibitory activity. This effect was associated with the speeding-up of movement initiation. Clonidine substantially increased proactive alpha power from the SMA source, and canceled out the benefits of STN-DBS on movement initiation. These results provide the first direct neural evidence in humans that the tonic inhibitory activity of the subthalamocortical loops underlying the control of movement initiation is coupled to the noradrenergic system, and that this activity can be targeted by pharmacological agents acting on alpha-adrenergic receptors.
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Affiliation(s)
- Charlotte Spay
- Université de Lyon, Lyon, France.,Université Lyon 1, Villeurbanne, France.,INSERM, U 1028, Lyon Neuroscience Research Center, Lyon, France.,CNRS, UMR 5292, Lyon Neuroscience Research Center, Lyon, France
| | - Marion Albares
- Université de Lyon, Lyon, France.,Université Lyon 1, Villeurbanne, France.,CNRS, UMR 5229, Institut des Sciences Cognitives Marc Jeannerod, Bron, France.,Sorbonne Universités, UPMC Université Pierre et Marie Curie Paris 06, UMR 7225, Paris, France.,INSERM UMR 1127, Institut du cerveau et de la moelle épinière, ICM, Paris, France.,CNRS, UMR 7225, Institut du cerveau et de la moelle épinière, ICM, Paris, France
| | - Guillaume Lio
- Université de Lyon, Lyon, France.,Université Lyon 1, Villeurbanne, France.,CNRS, UMR 5229, Institut des Sciences Cognitives Marc Jeannerod, Bron, France
| | - Stephane Thobois
- Université de Lyon, Lyon, France.,Université Lyon 1, Villeurbanne, France.,CNRS, UMR 5229, Institut des Sciences Cognitives Marc Jeannerod, Bron, France.,Hospices civils de Lyon, hôpital neurologique Pierre Wertheimer, Bron, France
| | - Emmanuel Broussolle
- Université de Lyon, Lyon, France.,Université Lyon 1, Villeurbanne, France.,CNRS, UMR 5229, Institut des Sciences Cognitives Marc Jeannerod, Bron, France.,Hospices civils de Lyon, hôpital neurologique Pierre Wertheimer, Bron, France
| | - Brian Lau
- Sorbonne Universités, UPMC Université Pierre et Marie Curie Paris 06, UMR 7225, Paris, France.,INSERM UMR 1127, Institut du cerveau et de la moelle épinière, ICM, Paris, France.,CNRS, UMR 7225, Institut du cerveau et de la moelle épinière, ICM, Paris, France
| | - Benedicte Ballanger
- Université de Lyon, Lyon, France.,Université Lyon 1, Villeurbanne, France.,INSERM, U 1028, Lyon Neuroscience Research Center, Lyon, France.,CNRS, UMR 5292, Lyon Neuroscience Research Center, Lyon, France
| | - Philippe Boulinguez
- Université de Lyon, Lyon, France.,Université Lyon 1, Villeurbanne, France.,INSERM, U 1028, Lyon Neuroscience Research Center, Lyon, France.,CNRS, UMR 5292, Lyon Neuroscience Research Center, Lyon, France
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Loberg O, Hautala J, Hämäläinen JA, Leppänen PHT. Semantic anomaly detection in school-aged children during natural sentence reading - A study of fixation-related brain potentials. PLoS One 2018; 13:e0209741. [PMID: 30589889 PMCID: PMC6307749 DOI: 10.1371/journal.pone.0209741] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Accepted: 12/11/2018] [Indexed: 11/19/2022] Open
Abstract
In this study, we investigated the effects of context-related semantic anomalies on the fixation-related brain potentials of 12-13-year-old Finnish children in grade 6 during sentence reading. The detection of such anomalies is typically reflected in the N400 event-related potential. We also examined whether the representation invoked by the sentence context extends to the orthographic representation level by replacing the final words of the sentence with an anomalous word neighbour of a plausible word. The eye-movement results show that the anomalous word neighbours of plausible words cause similar first-fixation and gaze duration reactions, as do other anomalous words. Similarly, we observed frontal negativity in the fixation-related potential of the unrelated anomalous words and in the anomalous word neighbours. This frontal negativity was larger in both anomalous conditions than in the response elicited by the plausible condition. We thus show that the brain successfully uses context to separate anomalous words from plausible words on a single letter level during free reading. From the P600 response of the scalp waveform, we observed that the P600 was delayed in the anomalous word neighbour condition. We performed group-level decomposition on the data with ICA (independent component analysis) and analysed the time course and source structure of the decomposed data. This analysis of decomposed brain signals not only confirmed the delay of the P600 response but also revealed that the frontal negativity concealed s more typical and separate N400 response, which was similarly delayed in the anomalous word neighbour condition, as was the P600 response. Source analysis of these independent components implicated the right frontal eye field as the cortical source for the frontal negativity and the middle temporal and parietal regions as cortical sources for the components resembling the N400 and P600 responses. We interpret the delays present in N400 and P600 responses to anomalous word neighbours to reflect competition with the representation of the plausible word just one letter different.
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Affiliation(s)
- Otto Loberg
- Department of Psychology, University of Jyväskylä, Jyväskylä, Finland
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9
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Spay C, Meyer G, Welter ML, Lau B, Boulinguez P, Ballanger B. Functional imaging correlates of akinesia in Parkinson's disease: Still open issues. NEUROIMAGE-CLINICAL 2018; 21:101644. [PMID: 30584015 PMCID: PMC6412010 DOI: 10.1016/j.nicl.2018.101644] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Revised: 12/13/2018] [Accepted: 12/15/2018] [Indexed: 11/19/2022]
Abstract
Akinesia is a major manifestation of Parkinson's disease (PD) related to difficulties or failures of willed movement to occur. Akinesia is still poorly understood and is not fully alleviated by standard therapeutic strategies. One reason is that the area of the clinical concept has blurred boundaries referring to confounded motor symptoms. Here, we review neuroimaging studies which, by providing access to finer-grained mechanisms, have the potential to reveal the dysfunctional brain processes that account for akinesia. It comes out that no clear common denominator could be identified across studies that are too heterogeneous with respect to the clinical/theoretical concepts and methods used. Results reveal, however, that various abnormalities within but also outside the motor and dopaminergic pathways might be associated with akinesia in PD patients. Notably, numerous yet poorly reproducible neural correlates were found in different brain regions supporting executive control by means of resting-state or task-based studies. This includes for instance the dorsolateral prefrontal cortex, the inferior frontal cortex, the supplementary motor area, the medial prefrontal cortex, the anterior cingulate cortex or the precuneus. This observation raises the issue of the multidimensional nature of akinesia. Yet, other open issues should be considered conjointly to drive future investigations. Above all, a unified terminology is needed to allow appropriate association of behavioral symptoms with brain mechanisms across studies. We adhere to a use of the term akinesia restricted to dysfunctions of movement initiation, ranging from delayed response to freezing or even total abolition of movement. We also call for targeting more specific neural mechanisms of movement preparation and action triggering with more sophisticated behavioral designs/event-related neurofunctional analyses. More work is needed to provide reliable evidence, but answering these still open issues might open up new prospects, beyond dopaminergic therapy, for managing this disabling symptom. No clear picture of the neural bases of PD akinesia can be drawn from the literature. Akinesia should be disentangled from bradykinesia and hypokinesia. Movement initiation dysfunctions may arise from both motor and executive disorders. Future neuroimaging studies should probe more specific neurocognitive processes. Future studies should look beyond the dopaminergic basal-ganglia circuitry.
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Affiliation(s)
- Charlotte Spay
- Université de Lyon, Université Claude Bernard Lyon 1, Lyon Neuroscience Resaerch Center, INSERM, U 1028, CNRS, UMR 5292, Action Control and Related Disorders team, F-69000, Lyon, France
| | - Garance Meyer
- Université de Lyon, Université Claude Bernard Lyon 1, Lyon Neuroscience Resaerch Center, INSERM, U 1028, CNRS, UMR 5292, Action Control and Related Disorders team, F-69000, Lyon, France
| | - Marie-Laure Welter
- Neurophysiology Department, CIC-CRB 1404, Rouen University Hospital, University of Rouen, F-76000 Rouen, France
| | - Brian Lau
- Sorbonne Universités, UPMC Univ Paris 06, UMR S 1127, CNRS UMR 7225, Institut du Cerveau et de la Moelle Epinière, F-75013 Paris, France
| | - Philippe Boulinguez
- Université de Lyon, Université Claude Bernard Lyon 1, Lyon Neuroscience Resaerch Center, INSERM, U 1028, CNRS, UMR 5292, Action Control and Related Disorders team, F-69000, Lyon, France
| | - Bénédicte Ballanger
- Université de Lyon, Université Claude Bernard Lyon 1, Lyon Neuroscience Research Center, INSERM, U 1028, CNRS, UMR 5292, Neuroplasticity and Neuropathology of Olfactory Perception team, F-69000, Lyon, France.
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Lio G, Thobois S, Ballanger B, Lau B, Boulinguez P. Removing deep brain stimulation artifacts from the electroencephalogram: Issues, recommendations and an open-source toolbox. Clin Neurophysiol 2018; 129:2170-2185. [PMID: 30144660 DOI: 10.1016/j.clinph.2018.07.023] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2014] [Revised: 07/23/2018] [Accepted: 07/28/2018] [Indexed: 12/30/2022]
Abstract
A major question for deep brain stimulation (DBS) research is understanding how DBS of one target area modulates activity in different parts of the brain. EEG gives privileged access to brain dynamics, but its use with implanted patients is limited since DBS adds significant high-amplitude electrical artifacts that can completely obscure neural activity measured using EEG. Here, we systematically review and discuss the methods available for removing DBS artifacts. These include simple techniques such as oversampling, antialiasing analog filtering and digital low-pass filtering, which are necessary but typically not sufficient to fully remove DBS artifacts when each is used in isolation. We also cover more advanced methods, including techniques tracking outliers in the frequency-domain, which can be effective, but are rarely used. The reason for that is twofold: First, it requires advanced skills in signal processing since no user friendly tool for removing DBS artifacts is currently available. Second, it involves fine-tuning to avoid over-aggressive filtering. We highlight an open-source toolbox incorporating most artifact removal methods, allowing users to combine different strategies.
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Affiliation(s)
- Guillaume Lio
- Université de Lyon, F-69622 Lyon, France; Université Lyon 1, Villeurbanne, France; CNRS, Centre de Neuroscience Cognitive, Bron, France
| | - Stéphane Thobois
- Université de Lyon, F-69622 Lyon, France; Université Lyon 1, Villeurbanne, France; CNRS, Centre de Neuroscience Cognitive, Bron, France; Hospices civils de Lyon, hôpital neurologique Pierre Wertheimer, Bron, France
| | - Bénédicte Ballanger
- Université de Lyon, F-69622 Lyon, France; Université Lyon 1, Villeurbanne, France; INSERM U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Lyon, France
| | - Brian Lau
- Sorbonne Universités, UPMC Univ Paris 06, UMR S 1127, CNRS UMR 7225, Institut du Cerveau et de la Moelle épinière, F-75013 Paris, France
| | - Philippe Boulinguez
- Université de Lyon, F-69622 Lyon, France; Université Lyon 1, Villeurbanne, France; INSERM U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Lyon, France.
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A Tutorial Review on Multi-subject Decomposition of EEG. Brain Topogr 2017; 31:3-16. [DOI: 10.1007/s10548-017-0603-x] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2017] [Accepted: 10/11/2017] [Indexed: 11/26/2022]
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Ochoa JF, Alonso JF, Duque JE, Tobón CA, Baena A, Lopera F, Mañanas MA, Hernández AM. Precuneus Failures in Subjects of the PSEN1 E280A Family at Risk of Developing Alzheimer's Disease Detected Using Quantitative Electroencephalography. J Alzheimers Dis 2017; 58:1229-1244. [PMID: 28550254 DOI: 10.3233/jad-161291] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Presenilin-1 (PSEN1) mutations are the most common cause of familial early onset Alzheimer's disease (AD). The PSEN1 E280A (E280A) mutation has an autosomal dominant inheritance and is involved in the production of amyloid-β. The largest family group of carriers with E280A mutation is found in Antioquia, Colombia. The study of mutation carriers provides a unique opportunity to identify brain changes in stages previous to AD. Electroencephalography (EEG) is a low cost and minimally invasiveness technique that enables the following of brain changes in AD. OBJECTIVE To examine how previous reported differences in EEG for Theta and Alpha-2 rhythms in E280A subjects are related to specific regions in cortex and could be tracked across different ages. METHODS EEG signals were acquired during resting state from non-carriers and carriers, asymptomatic and symptomatic subjects from E280A kindred from Antioquia, Colombia. Independent component analysis (ICA) and inverse solution methods were used to locate brain regions related to differences in Theta and Alpha-2 bands. RESULTS ICA identified two components, mainly related to the Precuneus, where the differences in Theta and Alpha-2 exist simultaneously at asymptomatic and symptomatic stages. When the ratio between Theta and Alpha-2 is used, significant correlations exist with age and a composite cognitive scale. CONCLUSION Theta and Alpha-2 rhythms are altered in E280A subjects. The alterations are possible to track at Precuneus regions using EEG, ICA, and inverse solution methods.
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Affiliation(s)
- John Fredy Ochoa
- Bioinstrumentation and Clinical Engineering Research Group, Bioengineering Program, Universidad de Antioquia, Medellín, Colombia
| | - Joan Francesc Alonso
- Department of Automatic Control (ESAII), Biomedical Engineering Research Center (CREB), Universitat Politènica de Catalunya (UPC), Barcelona, Spain.,Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain
| | - Jon Edinson Duque
- Bioinstrumentation and Clinical Engineering Research Group, Bioengineering Program, Universidad de Antioquia, Medellín, Colombia
| | - Carlos Andrés Tobón
- Neuroscience Group of Antioquia, Medical School, Universidad de Antioquia, Medellín, Colombia.,Neuropsychology and Behavior Group, Medical School, Universidad de Antioquia, Medellín, Colombia
| | - Ana Baena
- Neuroscience Group of Antioquia, Medical School, Universidad de Antioquia, Medellín, Colombia
| | - Francisco Lopera
- Neuroscience Group of Antioquia, Medical School, Universidad de Antioquia, Medellín, Colombia
| | - Miguel Angel Mañanas
- Department of Automatic Control (ESAII), Biomedical Engineering Research Center (CREB), Universitat Politènica de Catalunya (UPC), Barcelona, Spain.,Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain
| | - Alher Mauricio Hernández
- Bioinstrumentation and Clinical Engineering Research Group, Bioengineering Program, Universidad de Antioquia, Medellín, Colombia
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