Publications by authors named "Suzanne Dikker"

14 Publications

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Morning brain: real-world neural evidence that high school class times matter.

Soc Cogn Affect Neurosci 2020 12;15(11):1193-1202

Max Planck-NYU Center for Language, Music and Emotion, New York, NY, USA.

Researchers, parents and educators consistently observe a stark mismatch between biologically preferred and socially imposed sleep-wake hours in adolescents, fueling debate about high school start times. We contribute neural evidence to this debate with electroencephalogram data collected from high school students during their regular morning, mid-morning and afternoon classes. Overall, student alpha power was lower when class content was taught via videos than through lectures. Students' resting state alpha brain activity decreased as the day progressed, consistent with adolescents being least attentive early in the morning. During the lessons, students showed consistently worse performance and higher alpha power for early morning classes than for mid-morning classes, while afternoon quiz scores and alpha levels varied. Together, our findings demonstrate that both class activity and class time are reflected in adolescents' brain states in a real-world setting, and corroborate educational research suggesting that mid-morning may be the best time to learn.
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http://dx.doi.org/10.1093/scan/nsaa142DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7745151PMC
December 2020

Crowdsourcing neuroscience: Inter-brain coupling during face-to-face interactions outside the laboratory.

Neuroimage 2021 02 8;227:117436. Epub 2020 Oct 8.

Max Planck - NYU Center for Language, Music and Emotion, New York, USA; Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany; Department of Psychology, New York University, New York, USA.

When we feel connected or engaged during social behavior, are our brains in fact "in sync" in a formal, quantifiable sense? Most studies addressing this question use highly controlled tasks with homogenous subject pools. In an effort to take a more naturalistic approach, we collaborated with art institutions to crowdsource neuroscience data: Over the course of 5 years, we collected electroencephalogram (EEG) data from thousands of museum and festival visitors who volunteered to engage in a 10-min face-to-face interaction. Pairs of participants with various levels of familiarity sat inside the Mutual Wave Machine-an artistic neurofeedback installation that translates real-time correlations of each pair's EEG activity into light patterns. Because such inter-participant EEG correlations are prone to noise contamination, in subsequent offline analyses we computed inter-brain coupling using Imaginary Coherence and Projected Power Correlations, two synchrony metrics that are largely immune to instantaneous, noise-driven correlations. When applying these methods to two subsets of recorded data with the most consistent protocols, we found that pairs' trait empathy, social closeness, engagement, and social behavior (joint action and eye contact) consistently predicted the extent to which their brain activity became synchronized, most prominently in low alpha (~7-10 Hz) and beta (~20-22 Hz) oscillations. These findings support an account where shared engagement and joint action drive coupled neural activity and behavior during dynamic, naturalistic social interactions. To our knowledge, this work constitutes a first demonstration that an interdisciplinary, real-world, crowdsourcing neuroscience approach may provide a promising method to collect large, rich datasets pertaining to real-life face-to-face interactions. Additionally, it is a demonstration of how the general public can participate and engage in the scientific process outside of the laboratory. Institutions such as museums, galleries, or any other organization where the public actively engages out of self-motivation, can help facilitate this type of citizen science research, and support the collection of large datasets under scientifically controlled experimental conditions. To further enhance the public interest for the out-of-the-lab experimental approach, the data and results of this study are disseminated through a website tailored to the general public (wp.nyu.edu/mutualwavemachine).
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http://dx.doi.org/10.1016/j.neuroimage.2020.117436DOI Listing
February 2021

HyPyP: a Hyperscanning Python Pipeline for inter-brain connectivity analysis.

Soc Cogn Affect Neurosci 2021 01;16(1-2):72-83

Department of Neuroscience, Institut Pasteur, Paris, France.

The bulk of social neuroscience takes a 'stimulus-brain' approach, typically comparing brain responses to different types of social stimuli, but most of the time in the absence of direct social interaction. Over the last two decades, a growing number of researchers have adopted a 'brain-to-brain' approach, exploring similarities between brain patterns across participants as a novel way to gain insight into the social brain. This methodological shift has facilitated the introduction of naturalistic social stimuli into the study design (e.g. movies) and, crucially, has spurred the development of new tools to directly study social interaction, both in controlled experimental settings and in more ecologically valid environments. Specifically, 'hyperscanning' setups, which allow the simultaneous recording of brain activity from two or more individuals during social tasks, has gained popularity in recent years. However, currently, there is no agreed-upon approach to carry out such 'inter-brain connectivity analysis', resulting in a scattered landscape of analysis techniques. To accommodate a growing demand to standardize analysis approaches in this fast-growing research field, we have developed Hyperscanning Python Pipeline, a comprehensive and easy open-source software package that allows (social) neuroscientists to carry-out and to interpret inter-brain connectivity analyses.
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http://dx.doi.org/10.1093/scan/nsaa141DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812632PMC
January 2021

Inter-brain synchrony in teams predicts collective performance.

Soc Cogn Affect Neurosci 2021 01;16(1-2):43-57

Department of Psychology, New York University, New York, NY, USA.

Despite decades of research in economics and psychology attempting to identify ingredients that make up successful teams, neuroscientists have only just begun to study how multiple brains interact. Recent research has shown that people's brain activity becomes synchronized with others' (inter-brain synchrony) during social engagement. However, little is known as to whether inter-brain synchrony relates to collective behavior within teams. Here, we merge the nascent field of group neuroscience with the extant literature of team dynamics and collective performance. We recruited 174 participants in groups of 4 and randomly assigned them to complete a series of problem-solving tasks either independently or as a team, while simultaneously recording each person's brain activity using an electroencephalography hyperscanning setup. This design allowed us to examine the relationship between group identification and inter-brain synchrony in explaining collective performance. As expected, teammates identified more strongly with one another, cooperated more on an economic game, and outperformed the average individual on most problem-solving tasks. Crucially, inter-brain synchrony, but not self-reported group identification, predicted collective performance among teams. These results suggest that inter-brain synchrony can be informative in understanding collective performance among teams where self-report measures may fail to capture behavior.
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http://dx.doi.org/10.1093/scan/nsaa135DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812618PMC
January 2021

Magnetoencephalography and Language.

Neuroimaging Clin N Am 2020 May 1;30(2):229-238. Epub 2020 Apr 1.

Lyon Neuroscience Research Center (CRNL), CH Le Vinatier Bâtiment 452, 95, BD Pinel, Bron, Lyon 69675, France.

This article provides an overview of research that uses magnetoencephalography to understand the brain basis of human language. The cognitive processes and brain networks that have been implicated in written and spoken language comprehension and production are discussed in relation to different methodologies: we review event-related brain responses, research on the coupling of neural oscillations to speech, oscillatory coupling between brain regions (eg, auditory-motor coupling), and neural decoding approaches in naturalistic language comprehension.
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http://dx.doi.org/10.1016/j.nic.2020.01.004DOI Listing
May 2020

Instructor-learner brain coupling discriminates between instructional approaches and predicts learning.

Neuroimage 2020 05 15;211:116657. Epub 2020 Feb 15.

School of Psychology and Cognitive Science, Shanghai Changning-ECNU Mental Health Center, East China Normal University, Shanghai, China. Electronic address:

The neural mechanisms that support naturalistic learning via effective pedagogical approaches remain elusive. Here we used functional near-infrared spectroscopy to measure brain activity from instructor-learner dyads simultaneously during dynamic conceptual learning. Results revealed that brain-to-brain coupling was correlated with learning outcomes, and, crucially, appeared to be driven by specific scaffolding behaviors on the part of the instructors (e.g., asking guiding questions or providing hints). Brain-to-brain coupling enhancement was absent when instructors used an explanation approach (e.g., providing definitions or clarifications). Finally, we found that machine-learning techniques were more successful when decoding instructional approaches (scaffolding vs. explanation) from brain-to-brain coupling data than when using a single-brain method. These findings suggest that brain-to-brain coupling as a pedagogically relevant measure tracks the naturalistic instructional process during instructor-learner interaction throughout constructive engagement, but not information clarification.
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http://dx.doi.org/10.1016/j.neuroimage.2020.116657DOI Listing
May 2020

Are We Ready for Real-world Neuroscience?

J Cogn Neurosci 2019 03 19;31(3):327-338. Epub 2018 Jun 19.

University College London.

Real-world environments are typically dynamic, complex, and multisensory in nature and require the support of top-down attention and memory mechanisms for us to be able to drive a car, make a shopping list, or pour a cup of coffee. Fundamental principles of perception and functional brain organization have been established by research utilizing well-controlled but simplified paradigms with basic stimuli. The last 30 years ushered a revolution in computational power, brain mapping, and signal processing techniques. Drawing on those theoretical and methodological advances, over the years, research has departed more and more from traditional, rigorous, and well-understood paradigms to directly investigate cognitive functions and their underlying brain mechanisms in real-world environments. These investigations typically address the role of one or, more recently, multiple attributes of real-world environments. Fundamental assumptions about perception, attention, or brain functional organization have been challenged-by studies adapting the traditional paradigms to emulate, for example, the multisensory nature or varying relevance of stimulation or dynamically changing task demands. Here, we present the state of the field within the emerging heterogeneous domain of real-world neuroscience. To be precise, the aim of this Special Focus is to bring together a variety of the emerging "real-world neuroscientific" approaches. These approaches differ in their principal aims, assumptions, or even definitions of "real-world neuroscience" research. Here, we showcase the commonalities and distinctive features of the different "real-world neuroscience" approaches. To do so, four early-career researchers and the speakers of the Cognitive Neuroscience Society 2017 Meeting symposium under the same title answer questions pertaining to the added value of such approaches in bringing us closer to accurate models of functional brain organization and cognitive functions.
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http://dx.doi.org/10.1162/jocn_e_01276DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116058PMC
March 2019

Brain-to-Brain Synchrony and Learning Outcomes Vary by Student-Teacher Dynamics: Evidence from a Real-world Classroom Electroencephalography Study.

J Cogn Neurosci 2019 03 30;31(3):401-411. Epub 2018 Apr 30.

New York University.

How does the human brain support real-world learning? We used wireless electroencephalography to collect neurophysiological data from a group of 12 senior high school students and their teacher during regular biology lessons. Six scheduled classes over the course of the semester were organized such that class materials were presented using different teaching styles (videos and lectures), and students completed a multiple-choice quiz after each class to measure their retention of that lesson's content. Both students' brain-to-brain synchrony and their content retention were higher for videos than lectures across the six classes. Brain-to-brain synchrony between the teacher and students varied as a function of student engagement as well as teacher likeability: Students who reported greater social closeness to the teacher showed higher brain-to-brain synchrony with the teacher, but this was only the case for lectures-that is, when the teacher is an integral part of the content presentation. Furthermore, students' retention of the class content correlated with student-teacher closeness, but not with brain-to-brain synchrony. These findings expand on existing social neuroscience research by showing that social factors such as perceived closeness are reflected in brain-to-brain synchrony in real-world group settings and can predict cognitive outcomes such as students' academic performance.
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http://dx.doi.org/10.1162/jocn_a_01274DOI Listing
March 2019

Brain-to-Brain Synchrony Tracks Real-World Dynamic Group Interactions in the Classroom.

Curr Biol 2017 May 27;27(9):1375-1380. Epub 2017 Apr 27.

Department of Psychology, New York University, 6 Washington Place, New York, NY 10003, USA; Max Planck Institute for Empirical Aesthetics, Grüneburgweg 14, 60322 Frankfurt am Main, Germany. Electronic address:

The human brain has evolved for group living [1]. Yet we know so little about how it supports dynamic group interactions that the study of real-world social exchanges has been dubbed the "dark matter of social neuroscience" [2]. Recently, various studies have begun to approach this question by comparing brain responses of multiple individuals during a variety of (semi-naturalistic) tasks [3-15]. These experiments reveal how stimulus properties [13], individual differences [14], and contextual factors [15] may underpin similarities and differences in neural activity across people. However, most studies to date suffer from various limitations: they often lack direct face-to-face interaction between participants, are typically limited to dyads, do not investigate social dynamics across time, and, crucially, they rarely study social behavior under naturalistic circumstances. Here we extend such experimentation drastically, beyond dyads and beyond laboratory walls, to identify neural markers of group engagement during dynamic real-world group interactions. We used portable electroencephalogram (EEG) to simultaneously record brain activity from a class of 12 high school students over the course of a semester (11 classes) during regular classroom activities (Figures 1A-1C; Supplemental Experimental Procedures, section S1). A novel analysis technique to assess group-based neural coherence demonstrates that the extent to which brain activity is synchronized across students predicts both student class engagement and social dynamics. This suggests that brain-to-brain synchrony is a possible neural marker for dynamic social interactions, likely driven by shared attention mechanisms. This study validates a promising new method to investigate the neuroscience of group interactions in ecologically natural settings.
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http://dx.doi.org/10.1016/j.cub.2017.04.002DOI Listing
May 2017

On the same wavelength: predictable language enhances speaker-listener brain-to-brain synchrony in posterior superior temporal gyrus.

J Neurosci 2014 Apr;34(18):6267-72

Sackler Institute for Developmental Psychobiology, Weill Cornell Medical College, New York, New York 10065, Department of Psychology and Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey 08540, Haskins Laboratories, New Haven, Connecticut 06511, New York University, Department of Psychology, New York, New York 10003, and Utrecht University, Utrecht Institute of Linguistics OTS, 3512 JK Utrecht, The Netherlands.

Recent research has shown that the degree to which speakers and listeners exhibit similar brain activity patterns during human linguistic interaction is correlated with communicative success. Here, we used an intersubject correlation approach in fMRI to test the hypothesis that a listener's ability to predict a speaker's utterance increases such neural coupling between speakers and listeners. Nine subjects listened to recordings of a speaker describing visual scenes that varied in the degree to which they permitted specific linguistic predictions. In line with our hypothesis, the temporal profile of listeners' brain activity was significantly more synchronous with the speaker's brain activity for highly predictive contexts in left posterior superior temporal gyrus (pSTG), an area previously associated with predictive auditory language processing. In this region, predictability differentially affected the temporal profiles of brain responses in the speaker and listeners respectively, in turn affecting correlated activity between the two: whereas pSTG activation increased with predictability in the speaker, listeners' pSTG activity instead decreased for more predictable sentences. Listeners additionally showed stronger BOLD responses for predictive images before sentence onset, suggesting that highly predictable contexts lead comprehenders to preactivate predicted words.
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http://dx.doi.org/10.1523/JNEUROSCI.3796-13.2014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4004812PMC
April 2014

Predicting language: MEG evidence for lexical preactivation.

Brain Lang 2013 Oct 2;127(1):55-64. Epub 2012 Oct 2.

Sackler Institute for Developmental Psychobiology, Weill Cornell Medical College, NY, USA; New York University, Department of Psychology, NY, USA. Electronic address:

It is widely assumed that prediction plays a substantial role in language processing. However, despite numerous studies demonstrating that contextual information facilitates both syntactic and lexical-semantic processing, there exists no direct evidence pertaining to the neural correlates of the prediction process itself. Using magnetoencephalography (MEG), this study found that brain activity was modulated by whether or not a specific noun could be predicted, given a picture prime. Specifically, before the noun was presented, predictive contexts triggered enhanced activation in left mid-temporal cortex (implicated in lexical access), ventro-medial prefrontal cortex (previously associated with top-down processing), and visual cortex (hypothesized to index the preactivation of predicted form features), successively. This finding suggests that predictive language processing recruits a top-down network where predicted words are activated at different levels of representation, from more 'abstract' lexical-semantic representations in temporal cortex, all the way down to visual word form features. The same brain regions that exhibited enhanced activation for predictive contexts before the onset of the noun showed effects of congruence during the target word. To our knowledge, this study is one of the first to directly investigate the anticipatory stage of predictive language processing.
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http://dx.doi.org/10.1016/j.bandl.2012.08.004DOI Listing
October 2013

Before the N400: effects of lexical-semantic violations in visual cortex.

Brain Lang 2011 Jul 31;118(1-2):23-8. Epub 2011 Mar 31.

Sackler Institute for Developmental Psychobiology, Weill Cornell Medical College, New York, NY, United States.

There exists an increasing body of research demonstrating that language processing is aided by context-based predictions. Recent findings suggest that the brain generates estimates about the likely physical appearance of upcoming words based on syntactic predictions: words that do not physically look like the expected syntactic category show increased amplitudes in the visual M100 component, the first salient MEG response to visual stimulation. This research asks whether violations of predictions based on lexical-semantic information might similarly generate early visual effects. In a picture-noun matching task, we found early visual effects for words that did not accurately describe the preceding pictures. These results demonstrate that, just like syntactic predictions, lexical-semantic predictions can affect early visual processing around ∼100ms, suggesting that the M100 response is not exclusively tuned to recognizing visual features relevant to syntactic category analysis. Rather, the brain might generate predictions about upcoming visual input whenever it can. However, visual effects of lexical-semantic violations only occurred when a single lexical item could be predicted. We argue that this may be due to the fact that in natural language processing, there is typically no straightforward mapping between lexical-semantic fields (e.g., flowers) and visual or auditory forms (e.g., tulip, rose, magnolia). For syntactic categories, in contrast, certain form features do reliably correlate with category membership. This difference may, in part, explain why certain syntactic effects typically occur much earlier than lexical-semantic effects.
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http://dx.doi.org/10.1016/j.bandl.2011.02.006DOI Listing
July 2011

Early occipital sensitivity to syntactic category is based on form typicality.

Psychol Sci 2010 May 13;21(5):629-34. Epub 2010 Apr 13.

Department of Linguistics, New York University, 10 Washington Place, New York, NY 10003, USA.

Syntactic factors can rapidly affect behavioral and neural responses during language processing; however, the mechanisms that allow this rapid extraction of syntactically relevant information remain poorly understood. We addressed this issue using magnetoencephalography and found that an unexpected word category (e.g., "The recently princess . . . ") elicits enhanced activity in visual cortex as early as 120 ms after exposure, and that this activity occurs as a function of the compatibility of a word's form with the form properties associated with a predicted word category. Because no sensitivity to linguistic factors has been previously reported for words in isolation at this stage of visual analysis, we propose that predictions about upcoming syntactic categories are translated into form-based estimates, which are made available to sensory cortices. This finding may be a key component to elucidating the mechanisms that allow the extreme rapidity and efficiency of language comprehension.
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http://dx.doi.org/10.1177/0956797610367751DOI Listing
May 2010

Sensitivity to syntax in visual cortex.

Cognition 2009 Mar 3;110(3):293-321. Epub 2009 Jan 3.

Department of Linguistics, New York University, New York, NY 10003, USA.

One of the most intriguing findings on language comprehension is that violations of syntactic predictions can affect event-related potentials as early as 120 ms, in the same time-window as early sensory processing. This effect, the so-called early left-anterior negativity (ELAN), has been argued to reflect word category access and initial syntactic structure building (Friederici, 2002). In two experiments, we used magnetoencephalography to investigate whether (a) rapid word category identification relies on overt category-marking closed-class morphemes and (b) whether violations of word category predictions affect modality-specific sensory responses. Participants read sentences containing violations of word category predictions. Unexpected items varied in whether or not their word category was marked by an overt function morpheme. In Experiment 1, the amplitude of the visual evoked M100 component was increased for unexpected items, but only when word category was overtly marked by a function morpheme. Dipole modeling localized the generator of this effect to the occipital cortex. Experiment 2 replicated the main results of Experiment 1 and eliminated two non-morphology-related explanations of the M100 contrast we observed between targets containing overt category-marking and targets that lacked such morphology. Our results show that during reading, syntactically relevant cues in the input can affect activity in occipital regions at around 125 ms, a finding that may shed new light on the remarkable rapidity of language processing.
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http://dx.doi.org/10.1016/j.cognition.2008.09.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2709501PMC
March 2009
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