1
|
Tatti E, Cacciola A, Carrara F, Luciani A, Quartarone A, Ghilardi MF. Movement-related ERS and connectivity in the gamma frequency decrease with practice. Neuroimage 2023; 284:120444. [PMID: 37926216 PMCID: PMC10758293 DOI: 10.1016/j.neuroimage.2023.120444] [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: 05/23/2023] [Revised: 10/30/2023] [Accepted: 11/03/2023] [Indexed: 11/07/2023] Open
Abstract
Previous work showed that movements are accompanied by modulation of electroencephalographic (EEG) activity in both beta (13-30 Hz) and gamma (>30 Hz) ranges. The amplitude of beta event-related synchronization (ERS) is not linked to movement characteristics, but progressively increases with motor practice, returning to baseline after a period of rest. Conversely, movement-related gamma ERS amplitude is proportional to movement distance and velocity. Here, high-density EEG was recorded in 51 healthy subjects to investigate whether i) three-hour practice in two learning tasks, one with a motor component and one without, affects gamma ERS amplitude and connectivity during a motor reaching test, and ii) 90-minutes of either sleep or quiet rest have an effect on gamma oscillatory activity. We found that, while gamma ERS was appropriately scaled to the target extent at all testing points, its amplitude decreased after practice, independently of the type of interposed learning, and after both quiet wake and nap, with partial correlations with subjective fatigue scores. During movement execution, connectivity patterns within fronto-parieto-occipital electrodes, over areas associated with attentional networks, decreased after both practice and after 90-minute rest. While confirming the prokinetic nature of movement-related gamma ERS, these findings demonstrated the preservation of gamma ERS scaling to movement velocity with practice, despite constant amplitude reduction. We thus speculate that such decreases, differently from the practice-related increases of beta ERS, are related to reduced attention or working memory mechanisms due to fatigue or a switch of strategy toward automatization of movement execution and do not specifically reflect plasticity phenomena.
Collapse
Affiliation(s)
- Elisa Tatti
- Department of Molecular, Cellular & Biomedical Sciences, CUNY, School of Medicine, New York, NY 10031, United States.
| | - Alberto Cacciola
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy; Center for Complex Network Intelligence (CCNI), Tsinghua Laboratory of Brain and Intelligence (THBI), Tsinghua University, Beijing, China; Department of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Federico Carrara
- Department of Mathematics, Polytechnic University of Milan, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
| | - Adalgisa Luciani
- Department of Molecular, Cellular & Biomedical Sciences, CUNY, School of Medicine, New York, NY 10031, United States; Section of Psychiatry, Department of Neuroscience, School of Medicine, University of Naples "Federico II", Naples, Italy
| | - Angelo Quartarone
- IRCCS-Centro Neurolesi Bonino-Pulejo, S.S. 113, Via Palermo, C. da Casazza, 98124 Messina, Italy.
| | - M Felice Ghilardi
- Department of Molecular, Cellular & Biomedical Sciences, CUNY, School of Medicine, New York, NY 10031, United States.
| |
Collapse
|
2
|
Strzelczyk D, Kelly SP, Langer N. Neurophysiological markers of successful learning in healthy aging. GeroScience 2023; 45:2873-2896. [PMID: 37171560 PMCID: PMC10643715 DOI: 10.1007/s11357-023-00811-8] [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: 01/16/2023] [Accepted: 04/26/2023] [Indexed: 05/13/2023] Open
Abstract
The capacity to learn and memorize is a key determinant for the quality of life but is known to decline to varying degrees with age. However, neural correlates of memory formation and the critical features that determine the extent to which aging affects learning are still not well understood. By employing a visual sequence learning task, we were able to track the behavioral and neurophysiological markers of gradual learning over several repetitions, which is not possible in traditional approaches that utilize a remember vs. forgotten comparison. On a neurophysiological level, we focused on two learning-related centro-parietal event-related potential (ERP) components: the expectancy-driven P300 and memory-related broader positivity (BP). Our results revealed that although both age groups showed significant learning progress, young individuals learned faster and remembered more stimuli than older participants. Successful learning was directly linked to a decrease of P300 and BP amplitudes. However, young participants showed larger P300 amplitudes with a sharper decrease during the learning, even after correcting for an observed age-related longer P300 latency and increased P300 peak variability. Additionally, the P300 amplitude predicted learning success in both age groups and showed good test-retest reliability. On the other hand, the memory formation processes, reflected by the BP amplitude, revealed a similar level of engagement in both age groups. However, this engagement did not translate into the same learning progress in the older participants. We suggest that the slower and more variable timing of the stimulus identification process reflected in the P300 means that despite the older participants engaging the memory formation process, there is less time for it to translate the categorical stimulus location information into a solidified memory trace. The results highlight the important role of the P300 and BP as a neurophysiological marker of learning and may enable the development of preventive measures for cognitive decline.
Collapse
Affiliation(s)
- Dawid Strzelczyk
- Methods of Plasticity Research, Department of Psychology, University of Zurich, Andreasstrasse 15, CH-8050, Zurich, Switzerland.
- University Research Priority Program (URPP) Dynamics of Healthy Aging, Zurich, Switzerland.
- Neuroscience Center Zurich (ZNZ), Zurich, Switzerland.
| | - Simon P Kelly
- School of Electrical and Electronic Engineering and UCD Centre for Biomedical Engineering, University College Dublin, Dublin, Ireland
| | - Nicolas Langer
- Methods of Plasticity Research, Department of Psychology, University of Zurich, Andreasstrasse 15, CH-8050, Zurich, Switzerland
- University Research Priority Program (URPP) Dynamics of Healthy Aging, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), Zurich, Switzerland
| |
Collapse
|
3
|
Salehinejad MA, Wischnewski M, Ghanavati E, Mosayebi-Samani M, Kuo MF, Nitsche MA. Cognitive functions and underlying parameters of human brain physiology are associated with chronotype. Nat Commun 2021; 12:4672. [PMID: 34344864 PMCID: PMC8333420 DOI: 10.1038/s41467-021-24885-0] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 07/08/2021] [Indexed: 01/03/2023] Open
Abstract
Circadian rhythms have natural relative variations among humans known as chronotype. Chronotype or being a morning or evening person, has a specific physiological, behavioural, and also genetic manifestation. Whether and how chronotype modulates human brain physiology and cognition is, however, not well understood. Here we examine how cortical excitability, neuroplasticity, and cognition are associated with chronotype in early and late chronotype individuals. We monitor motor cortical excitability, brain stimulation-induced neuroplasticity, and examine motor learning and cognitive functions at circadian-preferred and non-preferred times of day in 32 individuals. Motor learning and cognitive performance (working memory, and attention) along with their electrophysiological components are significantly enhanced at the circadian-preferred, compared to the non-preferred time. This outperformance is associated with enhanced cortical excitability (prominent cortical facilitation, diminished cortical inhibition), and long-term potentiation/depression-like plasticity. Our data show convergent findings of how chronotype can modulate human brain functions from basic physiological mechanisms to behaviour and higher-order cognition.
Collapse
Affiliation(s)
- Mohammad Ali Salehinejad
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
- International Graduate School of Neuroscience, Ruhr-University Bochum, Bochum, Germany
| | - Miles Wischnewski
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Elham Ghanavati
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
- Department of Psychology, Ruhr-University Bochum, Bochum, Germany
| | - Mohsen Mosayebi-Samani
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Min-Fang Kuo
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Michael A Nitsche
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany.
- Department of Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany.
| |
Collapse
|
4
|
Ricci S, Tatti E, Nelson AB, Panday P, Chen H, Tononi G, Cirelli C, Ghilardi MF. Extended Visual Sequence Learning Leaves a Local Trace in the Spontaneous EEG. Front Neurosci 2021; 15:707828. [PMID: 34335178 PMCID: PMC8322764 DOI: 10.3389/fnins.2021.707828] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 06/24/2021] [Indexed: 01/22/2023] Open
Abstract
We have previously demonstrated that, in rested subjects, extensive practice in a motor learning task increased both electroencephalographic (EEG) theta power in the areas involved in learning and improved the error rate in a motor test that shared similarities with the task. A nap normalized both EEG and performance changes. We now ascertain whether extensive visual declarative learning produces results similar to motor learning. Thus, during the morning, we recorded high-density EEG in well rested young healthy subjects that learned the order of different visual sequence task (VSEQ) for three one-hour blocks. Afterward, a group of subjects took a nap and another rested quietly. Between each VSEQ block, we recorded spontaneous EEG (sEEG) at rest and assessed performance in a motor test and a visual working memory test that shares similarities with VSEQ. We found that after the third block, VSEQ induced local theta power increases in the sEEG over a right temporo-parietal area that was engaged during the task. This local theta increase was preceded by increases in alpha and beta power over the same area and was paralleled by performance decline in the visual working memory test. Only after the nap, VSEQ learning rate improved and performance in the visual working memory test was restored, together with partial normalization of the local sEEG changes. These results suggest that intensive learning, like motor learning, produces local theta power increases, possibly reflecting local neuronal fatigue. Sleep may be necessary to resolve neuronal fatigue and its effects on learning and performance.
Collapse
Affiliation(s)
- Serena Ricci
- Department of Physiology, Pharmacology and Neuroscience, CUNY School of Medicine, New York, NY, United States.,Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy
| | - Elisa Tatti
- Department of Physiology, Pharmacology and Neuroscience, CUNY School of Medicine, New York, NY, United States
| | - Aaron B Nelson
- Department of Physiology, Pharmacology and Neuroscience, CUNY School of Medicine, New York, NY, United States
| | - Priya Panday
- Department of Physiology, Pharmacology and Neuroscience, CUNY School of Medicine, New York, NY, United States
| | - Henry Chen
- Department of Physiology, Pharmacology and Neuroscience, CUNY School of Medicine, New York, NY, United States
| | - Giulio Tononi
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - Chiara Cirelli
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - M Felice Ghilardi
- Department of Physiology, Pharmacology and Neuroscience, CUNY School of Medicine, New York, NY, United States
| |
Collapse
|
5
|
Horváth K, Kardos Z, Takács Á, Csépe V, Nemeth D, Janacsek K, Kóbor A. Error Processing During the Online Retrieval of Probabilistic Sequence Knowledge. J PSYCHOPHYSIOL 2021. [DOI: 10.1027/0269-8803/a000262] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Abstract. Adaptive behavior involves rapid error processing and action evaluation. However, it has not been clarified how errors contribute to automatic behaviors that can be retrieved to successfully adapt to our complex environment. Automatic behaviors strongly rely on the process of probabilistic sequence learning and memory. Therefore, the present study investigated error processing during the online retrieval of probabilistic sequence knowledge. Twenty-four healthy young adults acquired and continuously retrieved a repeating stimulus sequence reflected by reaction time (RT) changes on a rapid forced-choice RT task. Performance was compared with a baseline that denoted the processing of random stimuli embedded in the probabilistic sequence. At the neurophysiological level, event-related brain potentials synchronized to responses were measured. Error processing was tracked by the error negativity (Ne) and the error positivity (Pe). The mean amplitude of the Ne gradually decreased as the task progressed, similarly for the sequence retrieval and the embedded baseline process. The mean amplitude of the Pe increased over time, likewise, irrespective of the type of the stimuli. Accordingly, we propose that automatic error detection (Ne) and conscious error evaluation (Pe) are not sensitive to sequence learning and retrieval. Overall, the present study provides insight into how error processing takes place for the retrieval of sequence knowledge in a probabilistic environment.
Collapse
Affiliation(s)
- Kata Horváth
- Doctoral School of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- Brain, Memory and Language Research Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Zsófia Kardos
- Brain Imaging Centre, Research Centre for Natural Sciences, Budapest, Hungary
- Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary
| | - Ádám Takács
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Germany
| | - Valéria Csépe
- Brain Imaging Centre, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Modern Philology and Social Sciences, University of Pannonia, Veszprém, Hungary
| | - Dezso Nemeth
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- Brain, Memory and Language Research Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Lyon Neuroscience Research Center, INSERM, CNRS, Université de Lyon, France
| | - Karolina Janacsek
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- Brain, Memory and Language Research Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- School of Human Sciences, Faculty of Education, Health and Human Sciences, University of Greenwich, London, UK
| | - Andrea Kóbor
- Brain Imaging Centre, Research Centre for Natural Sciences, Budapest, Hungary
| |
Collapse
|
6
|
Tatti E, Ricci S, Nelson AB, Mathew D, Chen H, Quartarone A, Cirelli C, Tononi G, Ghilardi MF. Prior Practice Affects Movement-Related Beta Modulation and Quiet Wake Restores It to Baseline. Front Syst Neurosci 2020; 14:61. [PMID: 33013332 PMCID: PMC7462015 DOI: 10.3389/fnsys.2020.00061] [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: 06/11/2020] [Accepted: 07/24/2020] [Indexed: 12/30/2022] Open
Abstract
Beta oscillations (13.5−25 Hz) over the sensorimotor areas are characterized by a power decrease during movement execution (event-related desynchronization, ERD) and a sharp rebound after the movement end (event-related synchronization, ERS). In previous studies, we demonstrated that movement-related beta modulation depth (peak ERS-ERD) during reaching increases within 1-h practice. This increase may represent plasticity processes within the sensorimotor network. If so, beta modulation during a reaching test should be affected by previous learning activity that engages the sensorimotor system but not by learning involving other systems. We thus recorded high-density EEG activity in a group of healthy subjects performing three 45-min blocks of motor adaptation task to a visually rotated display (ROT) and in another performing three blocks of visual sequence-learning (VSEQ). Each block of either ROT or VSEQ was followed by a simple reaching test (mov) without rotation. We found that beta modulation depth increased with practice across mov tests. However, such an increase was greater in the group performing ROT over both the left and frontal areas previously involved in ROT. Importantly, beta modulation values returned to baseline values after a 90-min of either nap or quiet wake. These results show that previous practice leaves a trace in movement-related beta modulation and therefore such increases are cumulative. Furthermore, as sleep is not necessary to bring beta modulation values to baseline, they could reflect local increases of neuronal activity and decrease of energy and supplies.
Collapse
Affiliation(s)
- Elisa Tatti
- CUNY School of Medicine, The City University of New York, New York, NY, United States
| | - Serena Ricci
- CUNY School of Medicine, The City University of New York, New York, NY, United States
| | - Aaron B Nelson
- CUNY School of Medicine, The City University of New York, New York, NY, United States
| | - Dave Mathew
- CUNY School of Medicine, The City University of New York, New York, NY, United States
| | - Henry Chen
- CUNY School of Medicine, The City University of New York, New York, NY, United States
| | - Angelo Quartarone
- Department of Biomedical, Dental, Morphological and Functional Imaging Sciences, University of Messina, Messina, Italy
| | - Chiara Cirelli
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - Giulio Tononi
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - Maria Felice Ghilardi
- CUNY School of Medicine, The City University of New York, New York, NY, United States
| |
Collapse
|
7
|
Is learning scale-free? Chemistry learning increases EEG fractal power and changes the power law exponent. Neurosci Res 2019; 156:165-177. [PMID: 31722228 DOI: 10.1016/j.neures.2019.10.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 09/16/2019] [Accepted: 10/21/2019] [Indexed: 02/08/2023]
Abstract
Learning in chemistry and other areas of science involves developing one's mental models of invisible processes and manipulating temporal and spatial domains during visual information processing. While some aspects learning have been well studied by EEG (e.g., theta and gamma oscillations), the role of spontaneous and scale-free brain activity remains unclear. We used a continuous chemistry learning EEG paradigm to explore how scale-free brain activity is related learning. We found a learning effect in participants (N = 22) with an increase in test accuracy (learning gain) and decrease in test question response times in a counterbalanced pre/post-test experiment. In the brain we found increased overall (mixed) broadband power (1-50 Hz) during learning compared to rest. We then used the IRASA method to separate oscillatory and fractal (i.e. scale-free) spectral components and observed an increase in low-frequency oscillatory band powers during learning. More importantly, we found that fractal power increased during the learning sessions relative to oscillatory power. Finally, the structure of the fractal power spectra (PLE) correlated to the individual participants' learning gains. These findings support the importance of scale-free activity for learning from a complex visual paradigm. We tentatively hypothesize that this fractal component is involved in integrating the different time scales of the learning material with those of the spontaneous activity during learning and mental model shaping.
Collapse
|
8
|
Tinga AM, de Back TT, Louwerse MM. Non-invasive neurophysiological measures of learning: A meta-analysis. Neurosci Biobehav Rev 2019; 99:59-89. [PMID: 30735681 DOI: 10.1016/j.neubiorev.2019.02.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2018] [Revised: 12/22/2018] [Accepted: 02/04/2019] [Indexed: 01/09/2023]
Abstract
In a meta-analysis of 113 experiments we examined neurophysiological outcomes of learning, and the relationship between neurophysiological and behavioral outcomes of learning. Findings showed neurophysiology yielding large effect sizes, with the majority of studies examining electroencephalography and eye-related outcome measures. Effect sizes on neurophysiological outcomes were smaller than effect sizes on behavioral outcomes, however. Neurophysiological outcomes were, but behavioral outcomes were not, influenced by several modulating factors. These factors included the sensory system in which learning took place, number of learning days, whether feedback on performance was provided, and age of participants. Controlling for these factors resulted in the effect size differences between behavior and neurophysiology to disappear. The findings of the current meta-analysis demonstrate that neurophysiology is an appropriate measure in assessing learning, particularly when taking into account factors that could have an influence on neurophysiology. We propose a first model to aid further studies that are needed to examine the exact interplay between learning, neurophysiology, behavior, individual differences, and task-related aspects.
Collapse
Affiliation(s)
- Angelica M Tinga
- Department of Cognitive Science & Artificial Intelligence, Tilburg University, Dante Building, Room D 330, Warandelaan 2, 5037 AB Tilburg, The Netherlands.
| | - Tycho T de Back
- Department of Cognitive Science & Artificial Intelligence, Tilburg University, Dante Building, Room D 330, Warandelaan 2, 5037 AB Tilburg, The Netherlands
| | - Max M Louwerse
- Department of Cognitive Science & Artificial Intelligence, Tilburg University, Dante Building, Room D 330, Warandelaan 2, 5037 AB Tilburg, The Netherlands
| |
Collapse
|
9
|
Graser JV, Bastiaenen CHG, van Hedel HJA. The role of the practice order: A systematic review about contextual interference in children. PLoS One 2019; 14:e0209979. [PMID: 30668587 PMCID: PMC6342307 DOI: 10.1371/journal.pone.0209979] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 12/14/2018] [Indexed: 11/18/2022] Open
Abstract
Aim We aimed to identify and evaluate the quality and evidence of the motor learning literature about intervention studies regarding the contextual interference (CI) effect (blocked vs. random practice order) in children with brain lesions and typically developing (TD) children. Method Eight databases (Cinahl, Cochrane, Embase, PubMed, Pedro, PsycINFO, Scopus and Web of Knowledge) were searched systematically with predefined search terms. Controlled studies examining the CI effect in children (with brain lesions or TD) were included. Evidence level, conduct quality, and risk of bias were evaluated by two authors independently. A best evidence synthesis was performed. Results Twenty-five papers evaluating TD children were included. One of these studies also assessed children with cerebral palsy. Evidence levels were I, II, or III. Conduct quality was low and the risk of bias high, due to methodological issues in the study designs or poor description thereof. Best evidence synthesis showed mainly no or conflicting evidence. Single tasks showed limited to moderate evidence supporting the CI effect in TD children. Conclusion There is a severe limitation of good-quality evidence about the CI effect in children who practice different tasks in one session, especially in children with brain lesions.
Collapse
Affiliation(s)
- Judith V. Graser
- Paediatric Rehab Research Group, Rehabilitation Centre for Children and Adolescents, University Children’s Hospital Zurich, Affoltern am Albis, Switzerland
- Children’s Research Centre CRC, University Children’s Hospital Zurich, Zurich, Switzerland
- Research Line Functioning and Rehabilitation CAPHRI, Department of Epidemiology, Maastricht University, Maastricht, the Netherlands
- * E-mail:
| | - Caroline H. G. Bastiaenen
- Research Line Functioning and Rehabilitation CAPHRI, Department of Epidemiology, Maastricht University, Maastricht, the Netherlands
| | - Hubertus J. A. van Hedel
- Paediatric Rehab Research Group, Rehabilitation Centre for Children and Adolescents, University Children’s Hospital Zurich, Affoltern am Albis, Switzerland
- Children’s Research Centre CRC, University Children’s Hospital Zurich, Zurich, Switzerland
| |
Collapse
|
10
|
Langer N, Ho EJ, Alexander LM, Xu HY, Jozanovic RK, Henin S, Petroni A, Cohen S, Marcelle ET, Parra LC, Milham MP, Kelly SP. A resource for assessing information processing in the developing brain using EEG and eye tracking. Sci Data 2017; 4:170040. [PMID: 28398357 PMCID: PMC5387929 DOI: 10.1038/sdata.2017.40] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Accepted: 02/22/2017] [Indexed: 01/11/2023] Open
Abstract
We present a dataset combining electrophysiology and eye tracking intended as a resource for the investigation of information processing in the developing brain. The dataset includes high-density task-based and task-free EEG, eye tracking, and cognitive and behavioral data collected from 126 individuals (ages: 6–44). The task battery spans both the simple/complex and passive/active dimensions to cover a range of approaches prevalent in modern cognitive neuroscience. The active task paradigms facilitate principled deconstruction of core components of task performance in the developing brain, whereas the passive paradigms permit the examination of intrinsic functional network activity during varying amounts of external stimulation. Alongside these neurophysiological data, we include an abbreviated cognitive test battery and questionnaire-based measures of psychiatric functioning. We hope that this dataset will lead to the development of novel assays of neural processes fundamental to information processing, which can be used to index healthy brain development as well as detect pathologic processes.
Collapse
Affiliation(s)
- Nicolas Langer
- Center for the Developing Brain, Child Mind Institute, New York, New York 10022, USA.,Methods of Plasticity Research, Department of Psychology, University of Zurich, Zurich 8050, Switzerland
| | - Erica J Ho
- Center for the Developing Brain, Child Mind Institute, New York, New York 10022, USA.,Department of Psychology, Yale University, New Haven, Connecticut 06520, USA
| | - Lindsay M Alexander
- Center for the Developing Brain, Child Mind Institute, New York, New York 10022, USA
| | - Helen Y Xu
- Center for the Developing Brain, Child Mind Institute, New York, New York 10022, USA
| | - Renee K Jozanovic
- Center for the Developing Brain, Child Mind Institute, New York, New York 10022, USA
| | - Simon Henin
- Department of Biomedical Engineering, City College of New York, New York 10031, USA
| | - Agustin Petroni
- Department of Biomedical Engineering, City College of New York, New York 10031, USA
| | - Samantha Cohen
- Department of Biomedical Engineering, City College of New York, New York 10031, USA.,Department of Psychology, The Graduate Center of the City University of New York, New York, New York 10016, USA
| | - Enitan T Marcelle
- Center for the Developing Brain, Child Mind Institute, New York, New York 10022, USA.,Department of Psychology, University of California, California, Berkeley 94720, USA
| | - Lucas C Parra
- Department of Biomedical Engineering, City College of New York, New York 10031, USA
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, New York 10022, USA.,Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York 10962, USA
| | - Simon P Kelly
- Department of Biomedical Engineering, City College of New York, New York 10031, USA.,School of Electrical and Electronic Engineering, University College Dublin, Dublin D04 V1W8, Ireland
| |
Collapse
|