@article{KayhanMatthesMarriottHaresignetal.2022, author = {Kayhan, Ezgi and Matthes, Daniel and Marriott Haresign, Ira and B{\´a}nki, Anna and Michel, Christine and Langeloh, Miriam and Wass, Sam and Hoehl, Stefanie}, title = {DEEP: A dual EEG pipeline for developmental hyperscanning studies}, series = {Developmental Cognitive Neuroscience}, volume = {54}, journal = {Developmental Cognitive Neuroscience}, publisher = {Elsevier}, address = {Amsterdam, Niederlande}, issn = {1878-9307}, doi = {10.1016/j.dcn.2022.101104}, pages = {1 -- 11}, year = {2022}, abstract = {Cutting-edge hyperscanning methods led to a paradigm shift in social neuroscience. It allowed researchers to measure dynamic mutual alignment of neural processes between two or more individuals in naturalistic contexts. The ever-growing interest in hyperscanning research calls for the development of transparent and validated data analysis methods to further advance the field. We have developed and tested a dual electroencephalography (EEG) analysis pipeline, namely DEEP. Following the preprocessing of the data, DEEP allows users to calculate Phase Locking Values (PLVs) and cross-frequency PLVs as indices of inter-brain phase alignment of dyads as well as time-frequency responses and EEG power for each participant. The pipeline also includes scripts to control for spurious correlations. Our goal is to contribute to open and reproducible science practices by making DEEP publicly available together with an example mother-infant EEG hyperscanning dataset.}, language = {en} } @misc{KayhanMatthesMarriottHaresignetal.2022, author = {Kayhan, Ezgi and Matthes, Daniel and Marriott Haresign, Ira and B{\´a}nki, Anna and Michel, Christine and Langeloh, Miriam and Wass, Sam and Hoehl, Stefanie and Morales, Santiago}, title = {DEEP: A dual EEG pipeline for developmental hyperscanning studies}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {1866-8364}, doi = {10.25932/publishup-56689}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-566899}, pages = {1 -- 11}, year = {2022}, abstract = {Cutting-edge hyperscanning methods led to a paradigm shift in social neuroscience. It allowed researchers to measure dynamic mutual alignment of neural processes between two or more individuals in naturalistic contexts. The ever-growing interest in hyperscanning research calls for the development of transparent and validated data analysis methods to further advance the field. We have developed and tested a dual electroencephalography (EEG) analysis pipeline, namely DEEP. Following the preprocessing of the data, DEEP allows users to calculate Phase Locking Values (PLVs) and cross-frequency PLVs as indices of inter-brain phase alignment of dyads as well as time-frequency responses and EEG power for each participant. The pipeline also includes scripts to control for spurious correlations. Our goal is to contribute to open and reproducible science practices by making DEEP publicly available together with an example mother-infant EEG hyperscanning dataset.}, language = {en} } @article{JeschonekMarinovicHoehletal.2010, author = {Jeschonek, Susanna and Marinovic, Vesna and Hoehl, Stefanie and Elsner, Birgit and Pauen, Sabina}, title = {Do animals and furniture items elicit different brain responses in human infants?}, issn = {0387-7604}, year = {2010}, abstract = {One of the earliest categorical distinctions to be made by preverbal infants is the animate-inanimate distinction. To explore the neural basis for this distinction in 7-8-month-olds, an equal number of animal and furniture pictures was presented in an ERP-paradigm. The total of 118 pictures, all looking different from each other, were presented in a semi-randomized order for 1000 ms each. Infants' brain responses to exemplars from both categories differed systematically regarding the negative central component (Nc: 400-600 ms) at anterior channels. More specifically, the Nc was enhanced for animals in one subgroup of infants, and for furniture items in another subgroup of infants. Explorative analyses related to categorical priming further revealed category-specific differences in brain responses in the late time window (650-1550 ms) at right frontal channels: Unprimed stimuli (preceded by a different-category item) elicited a more positive response as compared to primed stimuli (preceded by a same-category item). In sum, these findings suggest that the infant's brain discriminates exemplars from both global domains. Given the design of our task, we conclude that processes of category identification are more likely to account for our findings than processes of on-line category formation during the experimental session.}, language = {en} } @misc{KoesterKayhanLangelohetal.2020, author = {K{\"o}ster, Moritz and Kayhan, Ezgi and Langeloh, Miriam and Hoehl, Stefanie}, title = {Making sense of the world}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe}, number = {3}, issn = {1866-8364}, doi = {10.25932/publishup-51371}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-513717}, pages = {12}, year = {2020}, abstract = {For human infants, the first years after birth are a period of intense exploration-getting to understand their own competencies in interaction with a complex physical and social environment. In contemporary neuroscience, the predictive-processing framework has been proposed as a general working principle of the human brain, the optimization of predictions about the consequences of one's own actions, and sensory inputs from the environment. However, the predictive-processing framework has rarely been applied to infancy research. We argue that a predictive-processing framework may provide a unifying perspective on several phenomena of infant development and learning that may seem unrelated at first sight. These phenomena include statistical learning principles, infants' motor and proprioceptive learning, and infants' basic understanding of their physical and social environment. We discuss how a predictive-processing perspective can advance the understanding of infants' early learning processes in theory, research, and application.}, language = {en} } @article{KoesterKayhanLangelohetal.2020, author = {K{\"o}ster, Moritz and Kayhan, Ezgi and Langeloh, Miriam and Hoehl, Stefanie}, title = {Making sense of the world}, series = {Perspectives on Psychological Science}, volume = {15}, journal = {Perspectives on Psychological Science}, number = {3}, publisher = {Sage}, address = {London}, issn = {1745-6916}, doi = {10.1177/1745691619895071}, pages = {562 -- 571}, year = {2020}, abstract = {For human infants, the first years after birth are a period of intense exploration-getting to understand their own competencies in interaction with a complex physical and social environment. In contemporary neuroscience, the predictive-processing framework has been proposed as a general working principle of the human brain, the optimization of predictions about the consequences of one's own actions, and sensory inputs from the environment. However, the predictive-processing framework has rarely been applied to infancy research. We argue that a predictive-processing framework may provide a unifying perspective on several phenomena of infant development and learning that may seem unrelated at first sight. These phenomena include statistical learning principles, infants' motor and proprioceptive learning, and infants' basic understanding of their physical and social environment. We discuss how a predictive-processing perspective can advance the understanding of infants' early learning processes in theory, research, and application.}, language = {en} }