Longitudinal study of preterm and full-term infants: High-density EEG analyses of cortical activity in response to visual motion

Agyei, Seth B.; Weel, F. R. van der; Meer, Audrey L. H. van der

doi:10.1016/j.neuropsychologia.2016.02.001

Cited by 27 publications

(38 citation statements)

References 153 publications

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“…The more widespread and increased desynchronization found in the present study could indicate that a larger neural network is involved in information processing when drawing as opposed to describing the words, thereby facilitating and optimizing learning (Pfurtscheller, 1992). Proposed contributing factors to such improved desynchronization are: (1) increased task complexity (Vilhelmsen et al, 2015), (2) more efficient task performance (Boiten et al, 1992; Dujardin et al, 1993; Klimesch et al, 1996; Sterman et al, 1996; Agyei et al, 2015), and/or (3) more effort and attention as needed in patients and preterm infants (Agyei et al, 2016), the elderly, or participants with a lower IQ (Derambure et al, 1993; Neubauer et al, 1995; Defebvre et al, 1996; Neubauer et al, 1999). …”

Section: Discussionmentioning

confidence: 99%

Only Three Fingers Write, but the Whole Brain Works†: A High-Density EEG Study Showing Advantages of Drawing Over Typing for Learning

Meer

Weel

2017

Front. Psychol.

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Are different parts of the brain active when we type on a keyboard as opposed to when we draw visual images on a tablet? Electroencephalogram (EEG) was used in young adults to study brain electrical activity as they were typing or describing in words visually presented PictionaryTM words using a keyboard, or as they were drawing pictures of the same words on a tablet using a stylus. Analyses of temporal spectral evolution (time-dependent amplitude changes) were performed on EEG data recorded with a 256-channel sensor array. We found that when drawing, brain areas in the parietal and occipital regions showed event related desynchronization activity in the theta/alpha range. Existing literature suggests that such oscillatory neuronal activity provides the brain with optimal conditions for learning. When describing the words using the keyboard, upper alpha/beta/gamma range activity in the central and frontal brain regions were observed, especially during the ideation phase. However, since this activity was highly synchronized, its relation to learning remains unclear. We concluded that because of the benefits for sensory-motor integration and learning, traditional handwritten notes are preferably combined with visualizations (e.g., small drawings, shapes, arrows, symbols) to facilitate and optimize learning.

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Section: Discussionmentioning

confidence: 99%

Only Three Fingers Write, but the Whole Brain Works†: A High-Density EEG Study Showing Advantages of Drawing Over Typing for Learning

Meer

Weel

2017

Front. Psychol.

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“…Low-frequency activation in infants has been linked to signs of immaturity (Orekhova, Stroganova, Posikera, & Elam, 2006). Optic flow studies (Agyei et al, 2015;Agyei, Van der Weel, & Van der Meer, 2016b) found that during the first year of life infants show a decrease in amplitude in neuronal theta-band oscillations.…”

Section: Introductionmentioning

confidence: 99%

A high‐density EEG study of differentiation between two speeds and directions of simulated optic flow in adults and infants

et al. 2018

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A high-density EEG study was carried out to investigate cortical activity in response to forward and backward visual motion at two different driving speeds, simulated through optic flow. Participants were prelocomotor infants at the age of 4-5 months and infants with at least 3 weeks of crawling experience at the age of 8-11 months, and adults. Adults displayed shorter N2 latencies in response to forward as opposed to backward visual motion and differentiated significantly between low and high speeds, with shorter latencies for low speeds. Only infants at 8-11 months displayed similar latency differences between motion directions, and exclusively in response to low speed. The developmental differences in latency between infant groups are interpreted in terms of a combination of increased experience with self-produced locomotion and neurobiological development. Analyses of temporal spectral evolution (TSE, time-dependent amplitude changes) were also performed to investigate nonphase-locked changes at lower frequencies in underlying neuronal networks. TSE showed event-related desynchronization activity in response to visual motion for infants compared to adults. The poorer responses in infants are probably related to immaturity of the dorsal visual stream specialized in the processing of visual motion and could explain the observed problems in infants with differentiating high speeds of up to 50 km/h.

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“…being the EEG at sample time t k termed y(t k ) ∈ R d×1 , the lead field matrix M ∈ R d×n and the neural activity , beta-band (14-30 Hz) and gamma-band (30-150Hz) [3]. The aim was to simulate brain activity for three sources and five sources, these sources were randomly located in three (delta, alpha and beta bands) and five (delta, theta, alpha, beta and gamma bands) different frequency bands, they were also located randomly in different areas in the brain.…”

Section: Neuromagnetic Inverse Problemmentioning

confidence: 99%

“…Currently, some research have focused their studies to analyze the neural activity in frequency bands, in this way, they have found it e.g. some theta-band activities of low-amplitude desynchronised were associated to visual areas when they were compared among motion stimuli and static stimuli [3]. Besides, in [4], the authors focused the research in alpha-band oscillations because they are the main frequency components, associated to neural activity, present in EEG signals.…”

Section: Introduction Electroencephalographic (Eeg) Source Localizmentioning

confidence: 99%

Automatic Selection of Frequency Bands for Electroencephalographic Source Localization

Muñoz

Giraldo

López

et al. 2019

2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)

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This paper shows a method to locate actives sources from pre-processed electroencephalographic signals. These signals are processed using multivariate empirical mode decomposition (MEMD). The intrinsic mode functions are analyzed through the Hilbert-Huang spectral entropy. A cost function is proposed to automatically select the intrinsic mode functions associated with the lowest spectral entropy values and they are used to reconstruct the neural activity generated by the active sources. Multiple sparse priors are used to locate the active sources with and without multivariate empirical mode decomposition and the performance is estimated using the Wasserstein metric.

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Longitudinal study of preterm and full-term infants: High-density EEG analyses of cortical activity in response to visual motion

Cited by 27 publications

References 153 publications

Only Three Fingers Write, but the Whole Brain Works†: A High-Density EEG Study Showing Advantages of Drawing Over Typing for Learning

Only Three Fingers Write, but the Whole Brain Works†: A High-Density EEG Study Showing Advantages of Drawing Over Typing for Learning

A high‐density EEG study of differentiation between two speeds and directions of simulated optic flow in adults and infants

Automatic Selection of Frequency Bands for Electroencephalographic Source Localization

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