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Real-Life Neuroscience: An Ecological Approach To Brain and Behavior Research

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856350

research-article2019
PPSXXX10.1177/1745691619856350Shamay-Tsoory, MendelsohnEcological Approach

ASSOCIATION FOR
PSYCHOLOGICAL SCIENCE

Perspectives on Psychological Science

Real-Life Neuroscience: An Ecological 1­–19


© The Author(s) 2019
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DOI: 10.1177/1745691619856350
https://doi.org/10.1177/1745691619856350
www.psychologicalscience.org/PPS

Simone G. Shamay-Tsoory1,2 and Avi Mendelsohn2,3,4 


1
Department of Psychology, University of Haifa; 2The Integrated Brain and Behavior Research
Center (IBBR), University of Haifa; 3Department of Neurobiology, University of Haifa;
and 4Institute of Information Processing and Decision Making, University of Haifa

Abstract
Owing to advances in neuroimaging technology, the past couple of decades have witnessed a surge of research on
brain mechanisms that underlie human cognition. Despite the immense development in cognitive neuroscience, the
vast majority of neuroimaging experiments examine isolated agents carrying out artificial tasks in sensory and socially
deprived environments. Thus, the understanding of the mechanisms of various domains in cognitive neuroscience,
including social cognition and episodic memory, is sorely lacking. Here we focus on social and memory research as
representatives of cognitive functions and propose that mainstream, lab-based experimental designs in these fields
suffer from two fundamental limitations, pertaining to person-dependent and situation-dependent factors. The person-
dependent factor addresses the issue of limiting the active role of the participants in lab-based paradigms that may
interfere with their sense of agency and embodiment. The situation-dependent factor addresses the issue of the
artificial decontextualized environment in most available paradigms. Building on recent findings showing that real-
life as opposed to controlled experimental paradigms involve different mechanisms, we argue that adopting a real-
life approach may radically change our understanding of brain and behavior. Therefore, we advocate in favor of a
paradigm shift toward a nonreductionist approach, exploiting portable technology in semicontrolled environments, to
explore behavior in real life.

Keywords
Social interactions, memory, episodic memory, methodology, behavioral, neuroscience, social cognition

Human behavior is largely determined by complex of stimuli and naturally occurring responses (Fig. 1h).
interactions with our environment. Despite this fact, It is increasingly acknowledged that the field of cogni-
conventional experimental psychological approaches tive neuroscience may be hampered by the limited eco-
have mainly focused on investigating behavior of indi- logical validity that characterizes the bulk of paradigms
viduals as isolated agents situated in artificial, sensory, and settings in the field, resulting in a shift toward the
and socially deprived environments, limiting our under- study of human behaviors in natural environments
standing of naturalistic cognitive, emotional, and social (Dudai, 2002; Kingstone, Smilek, Ristic, Friesen, &
phenomena. Cognitive psychology and cognitive neu- Eastwood, 2002; Zaki & Ochsner, 2009).
roscience thereafter have traditionally addressed the In surveying the history of modern psychological
questions of how psychological functions are produced science, a boost in the discipline is apparent during the
by neural circuits by condensing complex naturalistic early 20th century. Until the late 19th century, philoso-
processes into reductionist forms of computerized tasks phers studied the mind and human behavior, largely
or questionnaires. Furthermore, functional neuroimag- on the basis of introspection and subjective experiences
ing methodologies largely rely on data collected from (D. P. Schultz & Schultz, 2015). Experimental psychol-
participants tested in highly restricted environments, ogy as a discipline detached from its philosophical
devoid of the contextual qualities and behavioral
actions that comprise our daily experiences (Fig. 1a).
Corresponding Author:
By real-life cognition or neuroscience, we refer to Simone G. Shamay-Tsoory, Department of Psychology, University of
behavioral and neural processes that are set in environ- Haifa, Aba-Hushi 199, Haifa 3498838, Israel
ments relevant to daily life and involve familiar types E-mail: sshamay@psy.haifa.ac.il
2 Shamay-Tsoory, Mendelsohn

a b c

d e f

g h

Fig. 1.  Experimental approaches in cognitive neuroscience. (a) A traditional lab-based approach for testing human cognition, depicting a
motionless participant presented with artificial stimuli such as a meaningless word list. The participant is limited in her responses and can-
not affect the situation (person-dependent limitation), and the stimulus is isolated from a real-life context (situation-dependent limitation).
(b) The participant is presented with meaningful stimuli (e.g., a story) but is unable to affect the situation (situation dependent). (c) The
participant can explore an object, introducing higher level of activity, but the context is limited, and the participant is unable to move freely.
(d) Depiction of the participant observing artificial social stimuli (the man protagonist) presented on a screen. (e and f) Lab-based unidirec-
tional and dyadic bidirectional interactions. In a bidirectional design, the woman (in this example) may exchange information and receive
feedback from the man, although the context is limited (situation-dependent limitation). (g) A multibrain interaction allows examination of
group dynamics in the lab. (h) Finally, a real-life multidirectional interaction is shown in which the participants are part of a group and the
situation is evaluated based on multiple interactions in natural surroundings. This final approach allows measuring of social interactions in
real-life situations and assessing real-life memory.

roots only when methodological tools that were applied to apply methodological techniques that were com-
at the time in biology and physics were combined with monplace in natural science, took the first steps toward
controlled observations and experimentation. Wilhelm establishing the modern psychology lab (Dhami et al.,
Wundt, who may be described as the founder of experi- 2004). By pushing away from the philosophical roots
mental psychology as an academic field, in attempting of psychology, he started the tradition of systematic
Ecological Approach 3

experimentation of human behavior and cognition, psychology (Fabes, Martin, Hanish, & Updegraff, 2000),
practices that still resonate by and large with today’s neuropsychology (Sbordone & Guilmette, 1999), and
experimental settings (D. P. Schultz & Schultz, 2015). social psychology (Koehler, 1996). Nonetheless, although
Cognitive science, initially established as a counter- the real-life approach is relevant to all fields of psychol-
movement to the absolute domination of behaviorism, ogy and cognitive neuroscience, the fields of social neu-
started to form during the middle of the 20th century roscience and episodic memory—the primary focuses
and matured to encompass a large fraction of experi- of the present review—are particularly relevant.
mental psychology, using experimental practices that A prominent aspect of everyday real-life behavior
emphasized highly reductionist, laboratory settings. The and cognitive functioning involves the interplay
disappointment from the sterile laboratory settings that between social cognition and episodic memory. These
do not represent naturally occurring behavior was mental processes, typically studied in isolation, perhaps
famously argued by Brunswik (1949), who introduced epitomize, better than any other, the crux of human
the term ecological validity to justify the opposition of experience. As highly developed social creatures,
representative design (i.e., the real-life approach) to humans allocate a significant proportion of their cogni-
systematic design (i.e., traditional approach). tive processing toward interpersonal interactions set
One notable exception to the reductionist approach within social settings. As stated by Hirst and Manier
was, ironically, one of the founders of cognitive psy- (1999), “we cannot divorce the act of remembering from
chology, Ulrich Neisser, who expressed a grave disap- the act of communication.” In fact, autobiographical
pointment in the observation that the field had memories are viewed by some as a key element of
succumbed to using experiments with extremely low social encounters (Hirst & Echterhoff, 2012). Thus, not
ecological validity (Neisser, 1991). The problem of low only is the content of autobiographical memory (AM)
ecological validity in cognitive psychology and later in filled with past episodes of social encounters (Spreng,
cognitive neuroscience was perhaps exacerbated by the 2013), but also AM often emerges in the context of
dramatic and complete dominance of the personal com- social interaction and may be crucial to the develop-
puter as a means to present experimental tasks. The ment of this cognitive function (Nelson & Fivush,
growing use of neuroimaging techniques such as func- 2004). Studying episodic memory and social interac-
tional MRI (fMRI) during the 1990s further boosted the tions in sterile laboratory paradigms may overlook the
development of computerized paradigms that restrict crux of the cognitive processes that underlie these
behavior to passive viewing of simple stimuli or button functions.
presses because these techniques are highly sensitive Indeed, because of the importance of understanding
to movement. Along with the obvious advantages in social behavior in natural settings, the fast-growing field
precision, controllability, and measurability, the abun- of social neuroscience recently took a step toward
dant usage of computers for managing experiments understanding real-life interactions, demonstrating that
fixated subjects as motionless participants in highly brains react differently to passive viewing of social
artificial tasks, with discrete, “clean” stimuli, situated in stimulations compared with active participation in
secluded environments, removing altogether most of the social exchange with others (e.g., Schilbach et  al.,
components found in natural, everyday behavior. Here 2013). The review by Schilbach et al. (2013) presented
we argue not only that such paradigms are removed compelling evidence showing the centrality of face-to-
from everyday experience but also that—similar to what face interaction and emotional engagement in facilitat-
Brunswik (1949) argued already more than a half cen- ing social understanding. The authors suggested that
tury ago—the systematic designs commonly used in social behavior differs fundamentally in multiple aspects
psychology disserve the very phenomena they investi- when it is examined from what they term a spectator
gate (Dhami et al., 2004). view (when participants observe a social interaction)
Although the need to shift toward real-world experi- compared with engagement in a real interaction.
mental settings has been acknowledged for decades, Schilbach et al. focused on discussing how emotional
this approach has gone through a period of rapid engagement in understanding other minds is a basic
expansion with the advent of portable neuroimaging part of social cognition, as opposed to merely reflecting
systems. Selective reviews of “real life” have been writ- on others’ behaviors. They emphasize interactions
ten in the past few years (e.g., Hasson & Honey, 2012; among minds-brains and the importance of studying
Schilbach et al., 2013), yet comprehensive reviews have social engagements in the presence of social occur-
yet to capture the breadth of the area. The importance rences (second-person neuroscience).
of designing ecologically valid paradigms in psychology Indeed, most paradigms in the field of social cogni-
and neuroscience has been addressed by numerous tion are based on computerized tasks in which partici-
commentators across fields, including developmental pants passively observe decontextualized social stimuli
4 Shamay-Tsoory, Mendelsohn

such as still pictures of facial expressions or an isolated typical tasks, individuals are limited in their ability to act
scene depicting a social interaction (e.g., Fig. 1d). In on the environment and participate or affect the events.
these types of tasks, participants are commonly required The prevention of action and influence over the situation
to make social judgments or emotional evaluations of may interfere with the participants’ sense of agency. Fur-
decontextualized social scenarios using forced-choice thermore, limiting participants’ movement may prevent
rating scales. Given that social interactions by their the sensation of embodiment. The second restricting ele-
nature require active participation in an interactive ment concerns situation-dependent limitations. In most
social exchange with social agents, measuring a response paradigms, cognitive abilities are measured in computer-
of an isolated passive observer may fail to capture the ized tasks with limited contextual cues that only remotely
core mechanisms of social interactions. resemble the richness of real-life experiences. Character-
Likewise, the study of human memory has tended to izing these person and context limitations could enable
examine retention of discrete elements of information, the development of real-life paradigms that allow partici-
devoid of context (G. Cohen, 2008). This practice is pants to behave more naturally in ecological settings.
particularly striking in the field of episodic memory, Whereas the review of Schilbach et  al. (2013)
defined as the uniquely human capacity to reinstate focused mainly on the field of social neuroscience, the
multisensory, content-rich information from the past, current review addresses two fields of study in psy-
typically characterized by meaningful, often socially chology: social cognition and memory. In addressing
mediated occurrences and contextual detail (Tulving, the field of episodic memory, we hold that removing
1985). Although many have advocated in favor of shift- naturalistic components of everyday experience as they
ing toward an ecological approach of memory research pertain to presented stimuli, contextual information,
(Neisser, 1991), it has largely been dominated by study- active participation, and bodily movement reduces eco-
ing “microevents,” consisting of discrete elements, such logical validity to the extent that we are not advancing
as words lists or pictures that are presented to a captive the understanding of behavioral and neural elements
audience of a single, passive participant (Cabeza & of memory in real life. By discussing how the same
Nyberg, 2000). Although such studies meet the dry cri- limitations are relevant to the field of memory, this
terion of episodic memory—the when and where of review makes a more general claim about ecological
the targeted events—the stimuli themselves lack the validity in cognitive neuroscience and demonstrates
contextual, emotional, interactive, and narrative nature how this approach is relevant to different (if not all)
of everyday-life events, which are key features of the fields of psychology.
original definition of episodic memory (Piolino, In the following sections, we characterize these two
Desgranges, & Eustache, 2009). Moreover, because the limitations and how they pertain to the research fields
information to be learned is context-free and often of social cognition and memory, focusing on the need
meaningless, memory in such experiments is typically to consider the key features—embodiment, agency, and
tested in time scales of minutes to hours after the stim- context. We then offer methodological suggestions for
uli were first presented, precluding the examination of devising practical research avenues, using state-of-the-
long-term memory mechanisms. Taken together, what art technology, that may provide valuable insights into
is conveniently referred to in the literature as episodic real-life behavioral and brain mechanisms of social cog-
memory is often actually the examination of memory nition and memory. We argue here that conclusions
for miniepisodes, or miniature events that contain lists drawn from controlled experimental designs with a
of items that have not yet been consolidated into long- limited number of variables may not be valid in real-life
term representations (Bruce, 1985). Here we argue that behavior. It is thus possible that incremental addition
removing naturalistic components of everyday experi- of complexity and context would not linearly correlate
ence as they pertain to presented stimuli, contextual with complexity of the mechanisms tested. For exam-
information, active participation, and bodily movement ple, the assumptions made in an experiment that tests
reduces ecological validity to the point that we are not emotion recognition in facial expression in a computer-
advancing the understanding of behavioral and neural ized task with an artificial, decontextualized, still pic-
elements of the uses of memory in real life. ture (Fig. 2a) may not be applicable to emotion
In the current review, we focus on social cognition and recognition in naturalistic settings (Fig. 2b). Thus, the
episodic memory as two separate (though related) repre- point to be made here is that by clinging to highly
sentatives of cognitive functions and suggest that the tra- reductionist experimental settings that are removed
ditional paradigms in these fields suffer from two key from our natural experiences, we might be inadver-
flaws that may potentially hinder advances in the field. tently investigating cognitive functions that are at the
The first flaw concerns person-dependent limitations. In fringe of human experience.
Ecological Approach 5

Fig. 2.  Illustration of nonlinearity in controlled versus real-life designs. (a) The participant views a decontextualized facial expression. (b)
The participant views the same face as part of a rich context that includes information regarding posture, environment, other people, and so
on. The shift from emotion recognition in the lab to real-life behavior does not represent merely a linear increase in processing demands,
because the underlying functions may be fundamentally different.

Person-Dependent Limitations: Not & Haggard, 2012). It is common practice in neuroscience


Being an Active Agent of social cognition and memory for participants to be
passively presented with stimuli to which they are
A considerable amount of knowledge in psychology is requested to judge or rate certain features. Although they
based on subjective reports of participants. Tradition- sometimes receive indications as to the success of their
ally, human behavior has been assessed with pencil- judgment, participants do not typically affect the stimuli
and-paper methods of administration and interviews. or the situation. That the actions of participants do not
Modern psychology has gradually moved toward testing have an effect on the experience may diminish the
behavior using computerized tasks. The development engagement of participants in the tasks, reduce their
of computerized methods for collecting data on a range sense of agency, and leave basic cognitive faculties dor-
of cognitive domains may also be related to the devel- mant. Higgins (2014) argued that individuals strive to be
opment of neuroimaging techniques that allow measur- effective in obtaining desired results and gaining control
ing behavior mainly in computerized tasks. Such over the environment. Indeed, research on the tendency
computerized tasks allow highly controlled and precise to possess a sense of agency indicates that it is a critical
presentation of stimuli across test sessions and partici- motivator of behavior. Accordingly, it has been shown
pants. Critically, data may be analyzed with automatic that manipulating one’s objective control over the envi-
scoring methods. A notable downside to such comput- ronment influences both the speed and the frequency
erized tasks, however, is that they limit the natural of performing an action associated with that control
behavior of the participant and restrict responses to (Karsh & Eitam, 2015), indicating that the mere sense of
button presses, which may interfere with basic cogni- control modifies behavior. How does the sense of agency
tive processes. Critically, although there are fundamen- interact with social cognition and memory functions?
tal differences between passive exposure and active According to Schilbach et al. (2013), merely observ-
exploration (e.g., Chrastil & Warren, 2012), many exper- ing a social agent devoid of actively engaging in social
imental paradigms in psychology involve passive view- interaction may affect the level of emotional engage-
ing of stimuli. Here we argue that based on frameworks ment in a social task. The authors argued that traditional
of agency and embodiment, limiting the participants’ studies in psychology are based on a spectatorial view,
active response may fundamentally impede the under- in which a detached observer reads out the mental
standing of basic cognitive functions. states of another person, who in turn is not affected
and cannot react to other people. Critically, the authors
claimed that social cognition is fundamentally different
Agency and cognition when individuals are emotionally engaged in a social
Interfering with the ability of participants to act on the situation compared with being a spectator of a social
environment may reduce their sense of control over the scenario. Thus, what is conveniently referred to as
environment, in turn affecting their sense of agency—the social cognition in numerous studies might be qualita-
experience of controlling one’s own actions (Chambon tively different from what the conceptual terms imply.
6 Shamay-Tsoory, Mendelsohn

In line with this framework, it was suggested that the social interactions, Phan et  al. (2010) used a “trust
fundamental differences between social observation game” task involving iterative exchanges and showed
and social interaction may predict the involvement of that reciprocity engages the ventral striatum. Likewise,
distinct brain regions in these two situations. Corrobo- real-time cooperation was shown to activate both the
rating this notion, Tylén, Allen, Hunter, and Roepstorff mentalizing network and the reward circuitry (Krill &
(2012) reported a distinction between social observa- Platek, 2012). Whereas Schilbach et al. (2013) addressed
tion and social interaction by demonstrating that per- the issue of agency and how it affects engagement, the
ceiving an interactive gesture (e.g., someone offering above findings demonstrate that providing the oppor-
or presenting an object) elicits activations in regions tunity to actively engage with one’s environment entails
corresponding to a model of coupled dynamics (joint a shift in the underlying supporting brain networks and
action). In contrast, perceiving someone “privately” not merely a linear change in the networks involved in
manipulating an object elicited activation in regions passive tasks of similar nature. One prominent brain
typically associated with theory of mind and the mirror structure that recurs in studies that involve strategic
neuron system. games is the ventral striatum, indicating the engage-
Although the study by Tylén et al. (2012) does not ment of reward-related learning when social interac-
involve a real-life social exchange, it is unique in that tions are involved. Nonetheless, although strategic
it exhibits dissociable activations during participatory games such as the ultimatum and trust games bring us
versus observational conditions, supporting the notion closer to understanding the behavioral and neural
that passive social cognition and interactive social mechanisms of cognition by enhancing the sense of
engagement are dissociable functions. agency, they only remotely resemble real-life, face-to-
Indeed, numerous paradigms in the field of social face interactions in which the range of responses and
neuroscience involve passive viewing of static images, the ability to act on the environment are far richer.
cartoons, video animations, or story reading (Molenberghs Being an active agent in an ongoing event is not only
et al., 2016). Conversely, paradigms of interactive games, significant for social interaction but can also affect
such as strategic decision making, allow participants to memory formation and future recollection of experi-
actively engage in live interactions, thus strengthening ences (Butler & James, 2013; Carassa, Geminiani,
subjects’ sense of agency. Employing strategic games Morganti, & Varotto, 2002; Plancher, Barra, Orriols, &
requires that participants engage in actively making Piolino, 2013). Memories of experiences are formed
decisions in light of incoming information associated whether the individual is a passive part of the occur-
with differential gains. Designing such experiments rence or an active agent (actively interacting with the
requires careful consideration of the processes relevant environment). The question at hand is whether the
to behaviors of interest and tasks that allow for model- degree of perceived control over the environment may
ing actions relevant to real-life behavior (Montague affect memory properties associated with relevant expe-
et al., 2012). Indeed, the increasing use of paradigms riences. There are now several lines of evidence sup-
adapted from behavioral economics can benefit the porting the notion that actively interacting with the
ecological validity if suitably applied to studying social environment can affect memory formation (Brandstatt
cognition. For example, Hampton, Bossaerts, and & Voss, 2014; Carassa et al., 2002; Murty, DuBrow, &
O’Doherty (2008) created a strategic game that assesses Davachi, 2015; Plancher et al., 2013; Rotem-Turchinski,
competitive interactions between “employer” and Ramaty, & Mendelsohn, 2019). For instance, spatial
“employee” and scanned participants with fMRI during memory in a virtual environment was found to be stron-
an online two-player strategy game. Whereas previous ger when individuals performed active rather than pas-
studies that used passive viewing of vignettes demon- sive exploration of the environment (Carassa et  al.,
strated equal activity in various components of the 2002). Likewise, memory for words that were generated
mentalizing network—for example, the medial prefron- by participants was somewhat superior to memory for
tal cortex (mPFC) and superior temporal sulcus (STS)— words that were passively assigned to subjects
during mental-state attribution (e.g., Jenkins & Mitchell, (Vinogradov et al., 2006). This latter study detected a
2009), Hampton et al. found that mentalizing-network different pattern of brain activity in the dorsomedial
components made dissociable contributions to the com- PFC and anterior cingulate cortex during correct
putations underlying competition. retrieval of self-generated words compared with
Note that in Hampton et  al. (2008), the activity of retrieval of passive words.
the mPFC was predicted by activity of the ventral stria- A recent study examined whether the act of a simple
tum, indicating that mentalizing during interaction choice opportunity affects declarative memory perfor-
involves activity in the reward circuitry. Pursuing the mance (Murty et al., 2015), emphasizing the involvement
idea that the reward mechanisms participate in “live” of the mesolimbic-dopaminergic system in enhancing
Ecological Approach 7

Emotions, Social Cognition


Embodiment
Memory Formation
Active vs.
Passive
Engagement
Memory Retrieval
Agency

Emotional Engagement

Fig. 3.  A schematic description of the influence of participants’ active versus passive
role in cognitive processes. Via the notion of embodiment, restricting activity may
affect different stages of memory as well as the way emotions and social interactions
are perceived. The level of activity can also engender a sense of agency, in turn again
affecting memory functions as well as emotional engagement in social encounters.

declarative memory encoding in humans (Murty & in the social and memory domains (Fig. 3). Social inter-
Adcock, 2014). This study is an example of memory actions are interpreted differently, and formation of
amplification in the absence of external reinforcement— memory as well as retrieval are boosted once individu-
in this case, the opportunity to choose even in the als engage in the encoding event. Specifically, it appears
absence of a correct answer. The working hypothesis that the striatal inputs to the mentalizing network dur-
was that by providing the opportunity to choose, indi- ing social interaction and to the hippocampus during
viduals generated a feeling of control and ability to active memory formation play a key role in mediating
affect the environment, which served in turn to enhance these effects. These links may provide a potential mech-
memory performance (Rotem-Turchinski et  al., 2019). anism that mediates the effect agency on cognition.
From the aspect of brain activity, the improvement in Having an active or passive role in a situation is sig-
memory performance was linked to interactions between nificant not only in participants’ sense of agency but also
striatum activation immediately before choice phases in their embodied cognition. In the following section,
and hippocampal activity thereafter during successful we highlight the effects that restricting the movement of
memory encoding of presented items. participants may exert on embodied cognition.
A rising notion in the field of interactive memory
systems is that dopaminergic inputs to the hippocam-
Embodied cognition
pus mediate a functional link between the reward-
related mesolimbic system and declarative memory Many paradigms that involve passive viewing of stimuli
formation (Shohamy & Adcock, 2010; Wittmann, Dolan, (instead of active participation in an event) also require
& Düzel, 2011; Wittmann et al., 2005). In light of the that the participant limit his or her body movement.
results of Murty and Adcock (2014), and particularly According to the embodied cognition theory, various
their finding that the striatum is involved in the active- cognitive abilities, including high-order ones (e.g., con-
induced memory effect, it can be argued that the act ceptualization, memory retrieval, empathy), are reliant
of choosing can serve as a reward. Gruber, Gelman, on and affected by environmental features surrounding
and Ranganath (2014) found that heightened states of the agent, taking into account such dimensions as sen-
curiosity benefit hippocampus-dependent learning via sory input processing, bodily interactions with the envi-
the dopaminergic circuit. These studies support the ronment, and action execution. The embodied cognition
notion that the opportunity to actively participate in an framework thus views cognitive processes as depen-
ongoing event and affect its consequences is perceived dent on bodily sensations and somatosensory and
as a positive occurrence in itself, generating a motiva- motor resources (Niedenthal, Barsalou, Winkielman,
tional signal that may affect diverse memory systems Krauth-Gruber, & Ric, 2005). According to this theory,
(Shohamy & Adcock, 2010). bodily experiences play an integral role in representa-
To summarize, a sense of agency entails a feeling tions such that not only bodily sensations but also
that one’s actions influence the environment. The above bodily postures, gestures, and expressions are inherent
literature survey indicates differential neurobiological components of cognition and can exert covert yet
underpinnings of passive versus active processing both potentially significant impacts on perception, memory,
8 Shamay-Tsoory, Mendelsohn

language, social cognition, and emotions (Barsalou, Limiting the ability to actively move during social inter-
1999). Schilbach et  al. (2013) discussed the issue of actions may therefore interfere with the way we per-
embodiment as affecting engagement in social interac- ceive and recognize emotional and social stimuli.
tion. Here we take a step forward and argue that not Bodily postures and signals seem to play an impor-
moving may affect basic emotional and cognitive pro- tant role in memory formation as well, particularly
cess. Indeed, it is increasingly acknowledged that body when manipulated during encoding. A set of studies
movements (e.g., Meier, Hauser, Robinson, Friesen, & that examined memory performance following either
Schjeldahl, 2007), gestures (Chandler & Schwarz, 2009), active or passive participation during encoding by
and facial-muscle contractions (Parzuchowski & employing a paradigm termed subjects-performed task
Szymkow-Sudziarska, 2008) influence emotions and concurred with this notion. In these experiments, par-
social cognition (see Barsalou, 2008; Niedenthal et al., ticipants are required to either actively perform the
2005). The close relationship between bodily motion behavior associated with a particular instruction (e.g.,
and emotion is evident in the fact that both words derive laugh, sharpen the pencil) or passively listen to the task
from the same Latin root word, movere (“to move”). instruction without performing it. Immediate and long-
Indeed, in social and emotional situations, people act, term recall tests are followed, in which participants are
react, and move their hands, torso, legs, and faces. instructed to write as many tasks as they can remember
It stands to reason that the tendency to use physical (R. L. Cohen, 1981). Indeed, actions that were actively
bodily movements during emotional experiences and carried out yielded higher levels of recall than their
social behavior is acquired from early stages of devel- passive counterparts (Engelkamp & Zimmer, 1989),
opment, when associations are made between emotions yielding a so-called enactment effect (Hainselin, Picard,
and bodily experiences. In adulthood, the link between Manolli, Vankerkore-Candas, & Bourdin, 2017). Further-
movement and mental representation becomes bidirec- more, it was demonstrated that merely imagining action
tional. Emotions trigger movements, and movements performance similarly leads to heightened recollection
may trigger emotions. For example, if during early levels (Dick, Kean, & Sands, 1989; Engelkamp &
social interactions we learn that interpersonal touch Zimmer, 1989; Steffens, von Stülpnagel, & Schult, 2015).
such as hugging or hand-holding involve physical In a similar vein, using an object while performing a
warmth, we may associate physical warmth with affec- task can promote memory performance for those
tion. As a result, merely holding a hot cup of coffee objects (Brooks, 1999; Engelkamp & Zimmer, 1997). It
may increase the evaluations of a protagonist’s levels seems that the involvement of motor sequences during
of psychological warmth (Williams & Bargh, 2008) or encoding benefits memory by forming multimodal asso-
friendliness (IJzerman & Semin, 2009), and higher oral ciations (Engelkamp & Cohen, 1991). Further support
temperature readings may be associated with greater for the boosting effect that action has on memory for-
feelings of social connection (Inagaki, Irwin, Moieni, mation comes from studies that afford participants the
Jevtic, & Eisenberger, 2016). possibility to actively navigate in a virtual environment.
Likewise, it has been shown repeatedly that bodily Here, active participants recall the spatial organization
actions and postures can influence emotional experi- of a virtual reality setting better than passive partici-
ences. Changing one’s body posture can affect perfor- pants. This finding suggests again that the motor system
mance on various tasks as well as the accompanying (moving a joystick) influenced the encoding of a spatial
feeling. For example, when asked to self-evaluate per- layout (Brooks, 1999).
formance outcome, participants express more pride Because memory performance can benefit from pro-
after sitting in an upright position than after slouching viding conditions that resemble those that were avail-
down (Stepper & Strack, 1993). Furthermore, it has able during encoding (Thomson & Tulving, 1970), it
been shown that, compared with reclining, leaning for- follows that adjusting bodily positions to resemble the
ward (associated with a heightened urge to approach encoding state should facilitate retrieval (Dijkstra,
stimuli) causes participants to generate heightened late Kaschak, & Zwaan, 2007; Dijkstra & Zwaan, 2014).
positive potential responses to appetitive but not neu- Indeed, participants’ autobiographical memory perfor-
tral pictures, suggesting that body postures may modify mance tends to profit from retrieval in positions similar
electrocortical responses (Price, Dieckman, & Harmon- to those in which the encoding took place (Dijkstra
Jones, 2012). These studies indicate that emotions can et al., 2007). Such findings were taken to indicate that
be reliably triggered or enhanced when corresponding bodily positions entail a sensorimotor component of
behaviors are produced. Critically, these reports imply the original experience, facilitating its reconstruction
that when movement is limited, one’s ability to repre- during retrieval. Bodily positions can also serve as cues
sent the associated emotion corresponding to the rel- to memories that seem appropriate to certain postures.
evant changes in bodily movement is diminished. For example, individuals tend to recall negative life
Ecological Approach 9

events when sitting in a slumped position, whereas an information, something that is not typically achieved in
upright position favors recollection of positive occur- laboratory settings (Steyvers & Hemmer, 2012). Thus,
rences (Riskind, 1989). Therefore, to fully understand very different conclusions can be drawn from memory
the mechanisms that enable episodic memory, it is use- studies that use naturalistic stimuli versus discrete items
ful to account not only for audiovisual information pre- as memoranda.
sented to a passive agent but also for aspects relating Controlled stimuli have been essential to elucidating
to kinesthetic and affective properties of the encoded the neural basis of distinct cognitive functions, includ-
experience (Wilson, 2002). ing complex ones such as social cognition properties
Although several studies on embodiment reported and memory formation. For example, in experiments
here were carried out in highly controlled environ- that examine face processing, faces are typically pre-
ments, the evidence described above provides a com- sented in isolation, separated from the body, and in
pelling showcase that restricting one’s body movement many cases with no hairline or color (i.e., in black and
may have direct influences on cognitive performance. white). A major strength of using simple stimuli is that
The effects of embodied cognition are apparent in emo- they are ideal for determining their relationship with a
tional experiences and social behaviors as well as mem- specific response of specific brain networks (e.g., the
ory encoding and retrieval. fusiform face area, or FFA, and face processing). None-
theless, such stimuli are deprived of their natural setting
Situation-Dependent Limitations: and are not representative of their appearance in their
natural setting. Our daily experience in real-life settings
Being Out of Context teaches us that interactions with human faces are rarely
Ample research implies that not only our bodies but presented as constant, stationary input. In fact, facial
also the physical environment and the social context motion and dynamics are critical for perceiving the
of cognition can influence cognitive processing (see identity of a person (Pilz, Thornton, & Bülthoff, 2006)
Barsalou, 2010). In natural environments, we perceive and his or her emotional state (Calvo, Avero, Fernández-
information in a vivid and dynamic context. Social situ- Martín, & Recio, 2016). It has been suggested that
ations in particular are characterized by their dynamic changeable dimensions of faces (e.g., emotional expres-
input, involving simultaneous processing of faces, bod- sions, eye gaze) are mediated by the STS (Blakemore
ies, vocalizations, and odors. Likewise, memories are & Decety, 2001; Grossman, Blake, & Kim, 2004),
encoded in complex and often unexpected combina- whereas static dimensions (e.g., face form) are pro-
tions of a multitude of physical features. Nevertheless, cessed by the FFA (Grill-Spector, Knouf, & Kanwisher,
the reductionist approach to scientific methodology and 2004; Haxby, Hoffman, & Gobbini, 2000; Kanwisher,
psychology research within it has dictated the division McDermott, & Chun, 1997; Kanwisher & Yovel, 2006).
of cognitive functions into tasks tested separately under Emerging data suggest that dynamic faces activate the
highly controlled conditions. By focusing on discrete face-processing network more consistently than static
components and avoiding confounding variables, psy- faces (Fox, Iaria, & Barton, 2009; J. Schultz, Brockhaus,
chologists have developed paradigms that use simple Bülthoff, & Pilz, 2013), implying a stronger interaction
stimuli devoid of their natural context. Whether under- between the neural pathways involved in processing
standing complex stimuli can necessarily be predicted changeable and invariant facial information than previ-
from responses to decontextualized settings is an open ously assumed. It is possible that the more natural form
question. of moving social stimuli draws more attentional
One of the defining features of real-life situations is resources than their static counterparts (Franconeri &
context. Items are not perceived in isolation because Simons, 2003) and therefore evoke increased neural
they are typically associated with background features, resources (Corbetta & Shulman, 2002).
together creating a continuous stream of spatial and In addition to moving and dynamically changing
temporal information to extract the bigger picture from stimuli, seldom are simple stimuli detached from their
the details. Studying contextual features of social situ- context in real life. We perceive faces while considering
ations such as group membership and group dynamics the body posture, the odors, the clothing, the social
is essential for understanding social processes. Like- situation, and the person identity (De Gelder, 2016).
wise, context is central to the understanding of real-life Indeed, recent evidence indicates that the context plays
memory processes. For example, studies suggest that an important role in determining how emotional facial
having prior (semantic) knowledge regarding tested expressions are recognized. For example, in contrast
stimuli enhances future retention, supporting the to the prevailing view that facial expressions are promi-
notion that encoding information in natural settings nent indicators of emotional states, the perception of
strengthens consolidation by assigning meaning to the basic facial expressions has been found to be highly
10 Shamay-Tsoory, Mendelsohn

dependent on body cues and can be categorically individual retrieves particular events from his or her past,
altered by context at early perceptual levels (Aviezer it is difficult to aggregate information across subjects;
et  al., 2008). In line with this, a recent event-related and finally, the accuracy of recollected memories cannot
potential (ERP) study has showed that body expressions be assessed (Cabeza & St Jacques, 2007; McDermott
affect the neural processing of facial expressions in et  al., 2009). These challenges can be overcome by
children as young as 8 months old (Rajhans, Jessen, importing real-life settings into the laboratory, specifically
Missana, & Grossmann, 2016). by staging experimental setups that enable experience
To increase the vividness of stimuli, researchers in documentation (and therefore accuracy determination)
social neuroscience have attempted to use cinema clips, and reproducibility across subjects.
which are multimodal in nature, engaging snapshots of Although rare, the real-life memory field has been
reality, and often describing human interactions in real- encouraged by research groups that devised ways to
istic conditions. Using clips from movies permits higher probe retrieval of ecological yet documented events,
ecological validity than short presentation of still pic- labeling them with terms such as autobiographical
tures (Haxby et al., 2011) and also enables analysis of memory (Cabeza et al., 2004; Henkel, 2014; St. Jacques,
intersubject correlation analysis (ISC; Hasson, Nir, Levy, Rubin, LaBar, & Cabeza, 2008), real-world episodic
Fuhrmann, & Malach, 2004). The ISC approach allows memory (Davidson, Cooper, & Taler, 2016; Griffiths,
the measurement of neural responses to extended natu- Mazaheri, Debener, & Hanslmayr, 2016), everyday rec-
ralistic stimuli (e.g., movies); the responses in one brain ognition memory (Milton, Muhlert, Butler, Benattayal-
are used to predict responses in another brain perceiv- lah, & Zeman, 2011), and personal memories (St. Jacques
ing the same stimulus. Although this method allows & Schacter, 2013). A growing trend in the field employs
examining coupling between brain activity of multiple the photograph paradigm (Cabeza et al., 2004). In these
participants, it does not measure real-time coupling studies, participants wear a camera that automatically
during real-life, face-to-face interactions. Critically, as takes pictures from their daily experiences. These pho-
much as the stimuli presented in movies are more tos are used as retrieval cues in recognition tests after
embedded in a natural context, having a participant participants encode material from daily events (Milton
passively view a scene from a movie is less engaging et al., 2011), campus outings (Cabeza et al., 2004; St.
than real social interaction that involves feedback. Jacques et al., 2008), and museum tours (St. Jacques,
Films of varying lengths have been used as learning Olm, & Schacter, 2013). Incidental memory brings us
material in memory research as well, attempting to bal- even closer to ecological validity such that by surprise
ance between controlled stimuli while maintaining its tests of memory for documented events, researchers
rich and contextual nature (Ben-Yakov & Dudai, 2011; can examine accuracy and subjective strength of memo-
Furman, Dorfman, Hasson, Davachi, & Dudai, 2007; ries for occurrences that were not suspected to be
Furman, Mendelsohn, & Dudai, 2012; Mendelsohn, tested thereafter (Davidson et al., 2016). It is notewor-
Chalamish, Solomonovich, & Dudai, 2008; Mendelsohn, thy that these experimental setups provide the oppor-
Furman, & Dudai, 2010; Mendelsohn, Furman, Navon, tunity to illuminate neural mechanisms involved in both
& Dudai, 2009). Whereas lists of words or pictures leave short- and long-term retrieval of such real-life docu-
only a short-lived trace, the content and details of mov- mented events.
ies can persist in memory for long and even remote Experiments with interactive avatars are perhaps bet-
periods (Furman et al., 2007; Furman et al., 2012). The ter at creating a seminatural vivid interactive environ-
brain network that corresponds with retrieval of movie ment. Artificial computer-generated environments offer
details appears to highly overlap the autobiographical the opportunity for participants to act and interact as
memory network (Mendelsohn et al., 2010), which can if in a real environment. A major advantage of virtual
be easily distinguished from networks associated with environments lies in the presentation of realistic stimuli.
lab-based memory retrieval (Burianova & Grady, 2007; Instead of passively watching a simple movie stimulus,
Cabeza et  al., 2004; McDermott, Szpunar, & Christ, subjects can interact actively within the environment.
2009). Although such paradigms bring us closer to For example, it is possible to examine memory by cre-
unveiling the behavioral and neural underpinnings of ating an artificial environment in which the participant
the different stages of long-term episodic memory, they can navigate and explore an arena (Mueller, Fagan, &
still lack a crucial aspect of memory for real-life events: Grimm, 2011). Although virtual reality (VR) allows mea-
the firsthand, egocentric experience of actual involve- suring behavior with an interactive environment, the
ment in an ongoing event. Studying real-life autobio- behavior of the participants is limited, and the sense of
graphical memory poses several challenges: First, the reality is typically weak. The sense of presence in an
experimenter typically lacks access to and control environment depends on input from some or all sen-
over the encoded occurrences; second, because each sory channels that are limited in the VR environment.
Ecological Approach 11

shift toward the study of human behaviors in natural


Dynamically Changing Stimuli environments (Dudai, 2002; Zaki & Ochsner, 2009). The
(Moving Faces) use of real-life complex, dynamic, naturalistic stimuli
provides a solid basis for understanding brain and
behavior. First, compared with basic computerized
tasks, real-life situations provide a natural context and
Multimodal Stimuli allow dynamic movement and feedback. Second, col-
Context (Visual, Auditory, Olfactory) lecting rich data from real-life experiments offers the
opportunity to evaluate multiple variables across exper-
iments possessing high ecological validity (Fig. 1h).
Finally, the sampling of real-life behaviors entails high-
level aspects of social behavior and memory that sel-
dom come into play in lab-based experiments. In recent
All Inclusive Stimuli (Face, Body) years, studies in the field of social neuroscience and
memory attempted to design paradigms that involve
real interactions and real-world experiences. Whereas
Fig. 4.  A schematic description of the different dimensions of con- traditional neuroimaging techniques including fMRI,
text. Cognitive neuroscience has made important steps toward the magnetoencephalography, and electroencephalography
implementation of context in experimental designs by using film
scenes, short stories, virtual environments, and real-life events. How- (EEG) are limited in their ability to examine freely mov-
ever, experimental paradigms in psychology should seek not only to ing individuals in natural context, attempts have been
incorporate a more elaborated context in experimental settings but made to create paradigms that allow investigating real
also to integrate contextual properties into their theoretical models.
social interactions (e.g., Dikker, Silbert, Hasson, &
For example, recent studies in social neuroscience use experimental
designs that enable measuring brain signals from two participants Zevin, 2014) and real-life memory (e.g., Cabeza & St
simultaneously during real, face-to-face interactions (hyperscanning; Jacques, 2007; St. Jacques et al., 2013) using these meth-
see next section). In these studies, providing naturalistic context not ods. The implementation of real-life experiments in
only increases the ecological validity of experimental settings but
also enables the investigation of new mechanistic questions regarding
neuroscience could be executed with traditional neu-
interbrain coupling and its contribution to social behavior. Combined roimaging techniques such as fMRI with paradigms
with state-of-the-art technology designed to record and manipulate designed to account for internal parameters such as
behavioral and neural responses (discussed in the next section), it sense of agency as well as external parameters such as
is now becoming possible to conceive experimental designs that
allow asking new questions about the effect of context on behavior,
context.
a feature that is discussed below. For example, Stephens, Silbert, and Hasson (2010)
applied fMRI to record brain activity from both speakers
and listeners during natural verbal communication and
A vivid visual display system might afford some indi- showed that the observed alignment of production- and
viduals a sense of “reality” but be unsuited for others comprehension-based processes is a potential mecha-
in the absence of sound (Slater, Usoh, & Steed, 1995). nism of communication. Designing experiments that
Indeed, recent VR studies with avatars show that beliefs allow active participation in a vivid environment neces-
about human agency of the avatar influence perfor- sitates systems that can reliably measure brain activity
mance in the task. For example, it has been shown that in natural environments while being sufficiently por-
specific brain responses (e.g., centroparietal P350 ERP) table. Newly developing portable neuroimaging tech-
are sensitive to whether participants realize that they niques—for example portable EEG and functional
interact with an avatar based on a computer algorithm near-infrared spectroscopy (fNIRS) systems—allow the
(Caruana, de Lissa, & McArthur, 2017). Collectively, it measurement brain activity of freely behaving individu-
appears that different social contexts may differentially als in natural settings. EEG is the most frequently used
affect social processing such that the artificial context portable technique (Scholkmann, Holper, Wolf, & Wolf,
activates social networks to a lesser extent to the point 2013), and one of its main advantages is its high tem-
in which certain networks will not activate when the poral resolution. However, it still suffers from the limited
context is limited (Fig. 4). ability to localize the epicenter of brain activation
(Huettel et  al., 2004). New fNIRS systems, which are
Measuring Brain and Behavior highly portable, enable measurement of changes in
cerebral blood flow (i.e., in oxyhemoglobin) during free
in Real Life
movement. Despite obvious shortcomings of fNIRS (e.g.,
Given the limited ecological validity that characterizes sensitivity to blood flow changes under the scalp that
the bulk of paradigms in neuroscience, there is a current are unrelated to brain activation, low spatial resolution;
12 Shamay-Tsoory, Mendelsohn

Gregg, White, Zeff, Berger, & Culver, 2010; Kirilina et al., level of analgesia during handholding. These studies
2012), it provides a promising way of localizing changes show that measures of brain-to-brain coupling along
in cerebral concentration of oxygenated and deoxygen- the EEG scale during live interactions allow understand-
ated hemoglobin in real-life situations. ing psychological questions in a way that was not pos-
To address the issue of decontextualized social envi- sible before.
ronments, researchers are increasingly shifting toward Studies on hyperscanning of dyads with fNIRS pro-
examining individuals during face-to-face social interac- vide further important evidence for brain-to-brain cou-
tions. Although traditional neuroimaging approaches are pling in cerebral blood flow of pairs of participants
limited to measuring individuals responding to social during social interactions. For example, studies using
stimuli presented on a screen (Fig. 1d), novel hyperscan- hyperscanning with fNIRS systems demonstrate
ning methods afford collecting data from individuals increases in brain-to-brain coupling in prefrontal
interacting with real social protagonists (Fig. 1f). The regions during various social behaviors, including
term hyperscanning, originally coined by Montague cooperation (Baker et al., 2016; Cheng, Li, & Hu, 2015;
et al. (2002), describes the measurement of brain activity Cui, Bryant, & Reiss, 2012; Funane et al., 2011; Liu et al.,
from two or more humans simultaneously, allowing the 2016), imitation (Holper, Scholkmann, & Wolf, 2012),
assessment of the bidirectional information flow between face-to-face dialogue ( Jiang et al., 2012), and coordi-
interacting individuals (Hari, Himberg, Nummenmaa, nated singing (Osaka et al., 2015).
Hämäläinen, & Parkkonen, 2013; Konvalinka & Roepstorff, Although these initial efforts allow measuring the
2012). Hyperscanning in dyads (Fig. 1f) enables the mea- behavior of dyads, there is little research on behavior
surement of interactive social interactions that include of humans in groups. Given that group living is a ubiq-
bidirectional flow of information between the protago- uitous biological phenomenon throughout the animal
nists, whereas hyperscanning in groups examines mul- kingdom (e.g., Alexander, 1974), studying the mecha-
tiple interactions (Fig. 1g). nisms underlying group processes and intergroup rela-
Hyperscanning enables creating a closed feedback tions is critical for understanding human behavior. As
loop across interacting individuals, and therefore it illustrated in Figure 1g, interaction in a context of a
lends itself easily to social neuroscience studies (for a group involves multibidirectional links between indi-
review, see Babiloni & Astolfi, 2014) but is similarly viduals. Only a handful of studies have focused on
applicable to various other cognitive domains, such as group behavior. Dikker et al. (2017) recently used por-
memory encoding and retrieval processes. Measure- table EEG to record the brains of 12 students simultane-
ments of coupling can include behavioral matching ously during regular classroom activities. Group-based
(coupled behavioral responses) as well as brain-to- neural coherence analysis demonstrated that the extent
brain coupling (Hasson & Frith, 2016). to which brain activity is synchronized across students
Most studies with hyperscanning have been per- predicts both student class engagement and social
formed with EEG. These studies mainly focus on mea- dynamics, suggesting that brain-to-brain synchrony is
surements of brain-to-brain coupling in the alpha-mu a possible neural marker for dynamic social interac-
band (8–12 Hz) during tasks that involve imitation tions. Likewise, Jiang et al. (2015) used fNIRS in groups
(Dumas, Nadel, Soussignan, Martinerie, & Garnero, of three participants in a paradigm that examined lead-
2010) or cooperation (Astolfi et al., 2010). In a pioneer- ership in groups. The authors reported that brain-to-
ing study, Sänger, Müller, and Lindenberger (2012) brain coupling for the leader-follower pairs was higher
examined brain-to-brain coupling during a guitar duet than that for the follower-follower pairs in the left tem-
performance. The authors reported brain-to-brain cou- poroparietal junction, an area important for mentaliz-
pling in the delta (1–4 Hz) and theta (4–8 Hz) ranges ing. Critically, leadership could be successfully predicted
measured by frontal and central electrodes during peri- on the basis of interbrain coupling. Finally, Nozawa,
ods that require musical coordination. Note that the Sasaki, Sakaki, Yokoyama, and Kawashima (2016)
inter- and intrabrain network associated with playing recently used fNIRS to study groups of four subjects
guitar in a duet differed significantly from that involved and showed frontopolar coupling during cooperative
in passive listening to a partner play the guitar (Müller, verbal communication. Given that single-brain-level
Sänger, & Lindenberger, 2013), further demonstrating analysis and paired-brain-level analysis may not fully
that being actively engaged in an interaction involves capture the complexity of group behavior, these studies
a different mechanism than passively viewing them. In demonstrated that it is becoming possible to measure
a recent study, Goldstein, Weissman-Fogel, Dumas, and brain signals from multiple participants to examine
Shamay-Tsoory (2018) linked brain-to-brain coupling group dynamics.
to the analgesic effect of social touch by showing that The main advantage of the hyperscanning approach
interbrain synchrony in the alpha-mu band predicts the is that it allows investigation of interbrain synchrony
Ecological Approach 13

between two or more brains. In addition, the experi- additional unconscious dimensions of behavior. For
mental setting of these types of experiments enables example, tracking the movement of two participants
real face-to-face interactions. However, it is not clear simultaneously allows measuring behavioral synchrony
what interbrain synchrony represents. Showing inter- in an objective automated and ecological manner. Non-
brain synchrony during social interaction adds new verbal synchrony can serve as an indicator of different
measurements to the traditional intrabrain activation aspects of social interaction (Hove & Risen, 2009;
measures, but it remains unclear what this synchrony Ramseyer & Tschacher, 2011; Yun, Watanabe, & Shimojo,
represents. A key question is how these coupling effects 2012). Bernieri and Rosenthal (1991) suggested that the
correlate with specific behaviors and how the activity degree of rapport between people is reflected by the
of one brain affects the behavior of a partner. Finally, behavioral synchrony between them.
it appears that the use of hyperscanning is still limited Ramseyer and Tschacher (2011) analyzed videos of
to studies in social neuroscience. Given the tight link therapist-client sessions using an automated and objec-
between episodic memory and social communication, tive video analysis method to calculate nonverbal syn-
it would be interesting to examine how brain-to-brain chrony. In their study, synchrony was shown to be
coupling underlies the formation of episodic memory positively correlated with the quality of the relationship
for information relevant to social interaction. A recent as rated by the patient as well as with the patient’s own
study that addressed this issue with fNIRS found that sense of high self-efficacy. Thus, measuring movements
interbrain synchrony between a learner and an instruc- in dyads provides interesting information regarding
tor in the inferior frontal gyrus (IFG) predicts song social interactions. Physical proximity to others has
learning, indicating that interbrain synchrony may be been shown to be a reliable indicator of underlying
a mechanism of social learning (Pan, Novembre, Song, affiliative relationships feelings of comfort and safety
Li, & Hu, 2018). with others (Cohen et al., 2017; Feeney, 1999). Thus,
The social and memory studies mentioned thus far the portable eye-tracking systems and motion-tracking
that used real-life strategies have mainly addressed the systems may be supplemented by other behavioral mea-
situation-dependent factor by using more contextual- sures (interview, rating scales, microcoding of observ-
ized environments or real interactions and daily events. ers), autonomic systems activity, and brain signals (EEG,
Yet studies that have addressed the person-dependent fNIRS). Combining multiple systems in real-life para-
limitation and the examination of freely moving par- digms may unveil the physiological and neural under-
ticipants are scarce. To address the issue of both mobil- pinnings of behaviors fundamental to the human
ity and context, Griffiths et al. (2016) recently examined experience-natural behaviors in real-life situations.
participants while they were presented with a series of It should be noted that although real-life paradigms
words to memorize along a predesignated route across enhance ecological validity, they pose serious chal-
campus while a mobile EEG system acquired ongoing lenges of controllability and reproducibility of involved
neural activity. The paradigm they used allowed both stimuli and experimental conditions. The obvious trade-
free movement and real-world context. In line with off between highly reductionist approaches that favor
previous lab-based studies, the authors identified sig- the fragmenting of everyday experiences to study the
nificant low- to mid-frequency power decreases (< 30 building blocks of cognitive functions and behavior ver-
Hz) over the left IFG. Critically, the authors reported sus the multidimensionality of real-life experiences is
that items strongly bound to spatial context exhibited emphasized in this sense. Naturally, to address research
significantly greater decreases in theta power than items questions studied in real-life settings, one should be
strongly bound to temporal context, further highlight- careful to remove or control for sources of noise that
ing the involvement of contextual factors in memory relate to the nature of the environment, which is typi-
formation. cally much richer and cluttered than in lab settings.
Note that newly available portable eye-tracking sys- To enable insights as to the neural mechanisms that
tems offer a cost-effective, easy to apply, and reliable underlie cognitive functions in naturalistic environ-
measure of eye gaze and saccades in an ecological ments such as movies, stories, and navigation, research-
environment. Portable eye-tracking systems allow mea- ers are proposing new analysis techniques for
suring numerous physiological markers that contain neuroimaging data. One such approach involves track-
covert information about the cognitive state of a freely ing the shared sources of variance in measured
moving participant, including pupil dilation, eye move- responses across participants, a method that is particu-
ments, and fixations (Grace, Stanford, Gentgall, & larly useful for stimuli that are not easily separable into
Rolan, 2010). Furthermore, tracking body motion by discrete segments, such as stories or movies (e.g., Hasson
assessing whole-body or specific organ movements et al., 2004). Analysis schemes that have recently gained
(e.g., head, shoulders, legs) may allow measuring popularity involve multivariate analysis algorithms. Such
14 Shamay-Tsoory, Mendelsohn

analyses, the most popular of which use machine- understanding neural mechanisms underlying social,
learning classifiers, aim to reveal spatial patterns of cognitive, and emotional effects within the context in
activity that uncover collective representations of infor- which these behaviors actually take place.
mation (Cohen et  al., 2017). The main advantage of
multivariate analysis methods over univariate tests that Action Editors
treat each spatial unit independently (e.g., voxels) is in Darby Saxbe and Laura King served as action editors for this
their ability to detect functional states of large-scale article.
areas by hidden patterns of activation across functional
units (Lewis-Peacock & Norman, 2013; Spiers & Maguire, Author Contributions
2007). Such methods, which can be applied to various Both authors contributed equally to this work, and both
imaging techniques ( Jafarpour, Barnes, Fuentemilla, authors approved the final version of the manuscript for
Duzel, & Penny, 2013; King & Dehaene, 2014), are submission.
particularly suitable for experiments involving rich,
naturalistic settings because they may detect activation ORCID iD
patterns that would not necessarily be revealed by
Avi Mendelsohn https://orcid.org/0000-0003-4582-2668
model-based approaches (Maguire, 2012; Naselaris,
Kay, Nishimoto, & Gallant, 2011).
Declaration of Conflicting Interests
To conclude, we show here that the amount of research
and the number of scientists conducting research with The author(s) declared that there were no conflicts of interest
real-life paradigms has significantly increased in recent with respect to the authorship or the publication of this
article.
years. Several exciting lines of studies in all fields of
neuroscience are providing new discoveries, generating
original ideas, and challenging longstanding conceptions References
of existing data collected from sterile lab settings. On Alexander, R. D. (1974). The evolution of social behavior.
the basis of these studies, we advocate in favor of a Annual Review of Ecology and Systematics, 5, 325–383.
paradigm shift toward combining ecological setups with Astolfi, L., Toppi, J., Fallani, F. D. V., Vecchiato, G., Salinari,
S., Mattia, D., . . . Babiloni, F. (2010). Neuroelectrical
advanced portable neuro-behavioral recording devices
hyperscanning measures simultaneous brain activity in
that will enable the exploration of fundamental issues humans. Brain Topography, 23, 243–256.
in naturalistic human behavior and cognition. We argue Aviezer, H., Hassin, R. R., Ryan, J., Grady, C., Susskind, J.,
that studying the brain in real-life settings while account- Anderson, A., . . . Bentin, S. (2008). Angry, disgusted, or
ing for person- and context-dependent issues may radi- afraid? Studies on the malleability of emotion perception.
cally update our research questions and derived working Psychological Science, 19, 724–732.
hypotheses while retaining high standards of controlla- Babiloni, F., & Astolfi, L. (2014). Social neuroscience and
bility and reproducibility. hyperscanning techniques: Past, present and future.
Already more than a half a century ago, Brunswik Neuroscience & Biobehavioral Reviews, 44, 76–93. doi:10
argued that behavior observed in a constrained environ- .1016/j.neubiorev.2012.07.006.
ment can speak only to behavior in that particular envi- Baker, J. M., Liu, N., Cui, X., Vrticka, P., Saggar, M., Hosseini,
S. H., & Reiss, A. L. (2016). Sex differences in neural
ronment. Nevertheless, real-life paradigms pose real
and behavioral signatures of cooperation revealed by
challenges in the analysis and interpretation of stimulus- fNIRS hyperscanning. Scientific Reports, 6, Article 26492.
response relationship, owing to the complex statistical doi:10.1038/srep26492
properties of natural stimuli. Prima facie testing cogni- Barsalou, L. W. (1999). Perceptions of perceptual symbols.
tive functions in real life is seemingly impossible. Behavioral and Brain Sciences, 22, 637–660.
Nonetheless, compared with simple stimuli, real-life Barsalou, L. W. (2008). Grounding symbolic operations in
paradigms require fewer a priori assumptions regarding the brain’s modal systems. In G. R. Semin & E. R. Smith
relevant stimulus parameters. To meet this challenge, (Eds.), Embodied grounding: Social, cognitive, affective,
it is necessary to establish suitable environmental set- and neuroscientific approaches (pp. 9–42). New York,
tings, apply portable measuring devices of movement NY: Cambridge University Press.
and eye gaze, and record autonomic responses and Barsalou, L. W. (2010). Grounded cognition: Past, present,
and future. Topics in Cognitive Sciences, 2, 716–724.
neural activity, collectively enabling the construction
Ben-Yakov, A., & Dudai, Y. (2011). Constructing realistic
of controlled and reproducible experimental designs engrams: Poststimulus activity of hippocampus and dorsal
for studying human cognition in natural settings. This striatum predicts subsequent episodic memory. Journal
approach puts forward exciting avenues for studying of Neuroscience, 31, 9032–9042.
psychological questions in an ecologically natural plat- Bernieri, F. J., & Rosenthal, R. (1991). Interpersonal coordi-
form that are necessary for making the next leap in nation: Behavior matching and interactional synchrony.
Ecological Approach 15

In R. S. Feldman & B. Rimé (Eds.), Studies in emotion & Chrastil, E. R., & Warren, W. H. (2012). Active and passive
social interaction. Fundamentals of nonverbal behavior contributions to spatial learning. Psychonomic Bulletin &
(pp. 401–432). New York, NY: Cambridge University Press. Review, 19, 1–23.
Blakemore, S. J., & Decety, J. (2001). From the perception of Cohen, D., Perry, A., Gilam, G., Mayseless, N., Gonen, T.,
action to the understanding of intention. Nature Reviews Hendler, T., & Shamay-Tsoory, S. G. (2017). The role
Neuroscience, 2, 561–567. of oxytocin in modulating interpersonal space: A phar-
Brandstatt, K. L., & Voss, J. L. (2014). Age-related impair- macological fMRI study. Psychoneuroendocrinology, 76,
ments in active learning and strategic visual exploration. 77–83.
Frontiers in Aging Neuroscience, 6, Article 19. doi:10.3389/ Cohen, G. (2008). The study of everyday memory. Memory
fnagi.2014.00019 in the Real World, 3, 1–20.
Brooks, B. M. (1999). The specificity of memory enhancement Cohen, J. D., Daw, N., Engelhardt, B., Hasson, U., Li, K., Niv,
during interaction with a virtual environment. Memory, Y., & Willke, T. L. (2017). Computational approaches to
7, 65–78. fMRI analysis. Nature Neuroscience, 20, 304–313.
Bruce, D. (1985). The how and why of ecological memory. Cohen, R. L. (1981). On the generality of some memory laws.
Journal of Experimental Psychology: General, 114, 78–90. Scandinavian Journal of Psychology, 22, 267–281.
Brunswik, E. (1949). Systematic and representative design of psy- Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed
chological experiments: With results in physical and social and stimulus-driven attention in the brain. Nature Reviews
perception. In J. Neyman (Ed.), Proceedings of the Berkeley Neuroscience, 3, 201–215.
Symposium on Mathematical Statistics and Probability (pp. Cui, X., Bryant, D. M., & Reiss, A. L. (2012). NIRS-based hyper-
143–202). Berkeley: University of California Press. scanning reveals increased interpersonal coherence in
Burianova, H., & Grady, C. L. (2007). Common and unique superior frontal cortex during cooperation. NeuroImage,
neural activations in autobiographical, episodic, and 59, 2430–2437.
semantic retrieval. Journal of Cognitive Neuroscience, Davidson, P. S., Cooper, L., & Taler, V. (2016). Remembering a
19, 1520–1534. visit to the psychology lab: Implications of Mild Cognitive
Butler, A. J., & James, K. H. (2013). Active learning of novel Impairment. Neuropsychologia, 90, 243–250.
sound-producing objects: Motor reactivation and enhance- De Gelder, B. (2016). Emotions and the body. Oxford,
ment of visuo-motor connectivity. Journal of Cognitive England: Oxford University Press.
Neuroscience, 25, 203–218. Dhami, M. K., Hertwig, R., & Hoffrage, U. (2004). The role of
Cabeza, R., & Nyberg, L. (2000). Imaging cognition II: An representative design in an ecological approach to cogni-
empirical review of 275 PET and fMRI studies. Journal of tion. Psychological Bulletin, 130, 959–988.
Cognitive Neuroscience, 12, 1–47. Dick, M. B., Kean, M. L., & Sands, D. (1989). Memory for action
Cabeza, R., Prince, S. E., Daselaar, S. M., Greenberg, D. L., events in Alzheimer-type dementia: Further evidence of an
Budde, M., Dolcos, F., . . . Rubin, D. C. (2004). Brain encoding failure. Brain and Cognition, 9, 71–87.
activity during episodic retrieval of autobiographical and Dijkstra, K., Kaschak, M. P., & Zwaan, R. A. (2007). Body
laboratory events: An fMRI study using a novel photo par- posture facilitates retrieval of autobiographical memories.
adigm. Journal of Cognitive Neuroscience, 16, 1583–1594. Cognition, 102, 139–149.
Cabeza, R., & St. Jacques, P. (2007). Functional neuroim- Dijkstra, K., & Zwaan, R. (2014). Memory and action. In L. A.
aging of autobiographical memory. Trends in Cognitive Shapiro (Ed.)., The Routledge handbook of embodied
Sciences, 11, 219–227. cognition (pp. 296–305). Abingdon, England: Taylor &
Calvo, M. G., Avero, P., Fernández-Martín, A., & Recio, G. Francis.
(2016). Recognition thresholds for static and dynamic Dikker, S., Silbert, L. J., Hasson, U., & Zevin, J. D. (2014).
emotional faces. Emotion, 16, 1186–1200. On the same wavelength: Predictable language enhances
Carassa, A., Geminiani, G., Morganti, F., & Varotto, D. (2002). speaker–listener brain-to-brain synchrony in posterior
Active and passive spatial learning in a complex virtual superior temporal gyrus. Journal of Neuroscience, 34,
environment: The effect of efficient exploration. Cognitive 6267–6272.
Processing, 3(4), 65–81. Dikker, S., Wan, L., Davidesco, I., Kaggen, L., Oostrik, M.,
Caruana, N., de Lissa, P., & McArthur, G. (2017). Beliefs about McClintock, J., . . . Poeppel, D. (2017). Brain-to-brain
human agency influence the neural processing of gaze synchrony tracks real-world dynamic group interactions
during joint attention. Social Neuroscience, 12, 194–206. in the classroom. Current Biology, 27, 1375–1380.
Chambon, V., & Haggard, P. (2012). Sense of control depends Dudai, Y. (2002). Memory from A to Z: Keywords, concepts and
on fluency of action selection, not motor performance. beyond. New York, NY: Oxford University Press.
Cognition, 125, 441–451. Dumas, G., Nadel, J., Soussignan, R., Martinerie, J., & Garnero, L.
Chandler, J., & Schwarz, N. (2009). How extending your (2010). Inter-brain synchronization during social interac-
middle finger affects your perception of others: Learned tion. PLOS ONE, 5(8), Article 12166. doi:10.1371/journal
movements influence concept accessibility. Journal of .pone.0012166
Experimental Social Psychology, 45, 123–128. Engelkamp, J., & Cohen, R. L. (1991). Current issues in mem-
Cheng, X., Li, X., & Hu, Y. (2015). Synchronous brain activity ory of action events. Psychological Research, 53, 175–182.
during cooperative exchange depends on gender of part- Engelkamp, J., & Zimmer, H. D. (1989). Memory for action
ner: A fNIRS-based hyperscanning study. Human Brain events: A new field of research. Psychological Research,
Mapping, 36, 2039–2048. 51, 153–157.
16 Shamay-Tsoory, Mendelsohn

Engelkamp, J., & Zimmer, H. D. (1997). Sensory factors in alone: Action is better for memory than reading. Frontiers
memory for subject-performed tasks. Acta Psychologica, in Psychology, 8, Article 325. doi:10.3389/fpsyg.2017.00325
96, 43–60. Hampton, A. N., Bossaerts, P., & O’Doherty, J. P. (2008).
Fabes, R. A., Martin, C. L., Hanish, L. D., & Updegraff, K. A. Neural correlates of mentalizing-related computations
(2000). Criteria for evaluating the significance of during strategic interactions in humans. Proceedings of
developmental research in the twenty-first century: Force the National Academy of Sciences, USA, 105, 6741–6746.
and counterforce. Child Development, 71, 212–221. Hari, R., Himberg, T., Nummenmaa, L., Hämäläinen, M.,
Feeney, J. A. (1999). Adult romantic attachment and couple & Parkkonen, L. (2013). Synchrony of brains and bod-
relationships. In J. Cassidy & P. R. Shaver (Eds.), Handbook ies during implicit interpersonal interaction. Trends in
of attachment: Theory, research, and clinical applications Cognitive Sciences, 17, 105–106.
(pp. 355–377). New York, NY: The Guilford Press. Hasson, U., & Frith, C. D. (2016). Mirroring and beyond:
Fox, C. J., Iaria, G., & Barton, J. J. (2009). Defining the face Coupled dynamics as a generalized framework for mod-
processing network: Optimization of the functional local- elling social interactions. Philosophical Transactions of
izer in fMRI. Human Brain Mapping, 30, 1637–1651. the Royal Society B: Biological Sciences, 371, 20150366.
Franconeri, S. L., & Simons, D. J. (2003). Moving and loom- Hasson, U., & Honey, C. J. (2012). Future trends in
ing stimuli capture attention. Perception & Psychophysics, Neuroimaging: Neural processes as expressed within real-
65, 999–1010. life contexts. NeuroImage, 62, 1272–1278.
Funane, T., Kiguchi, M., Atsumori, H., Sato, H., Kubota, K., & Hasson, U., Nir, Y., Levy, I., Fuhrmann, G., & Malach, R.
Koizumi, H. (2011). Synchronous activity of two people’s pre- (2004). Intersubject synchronization of cortical activity
frontal cortices during a cooperative task measured by simul- during natural vision. Science, 303, 1634–1640.
taneous near-infrared spectroscopy. Journal of Biomedical Haxby, J. V., Guntupalli, J. S., Connolly, A. C., Halchenko,
Optics, 16(7), Article 077011. doi:10.1117/1.3602853 Y. O., Conroy, B. R., Gobbini, M. I., . . . Ramadge, P. J.
Furman, O., Dorfman, N., Hasson, U., Davachi, L., & Dudai, (2011). A common, high-dimensional model of the rep-
Y. (2007). They saw a movie: Long-term memory for an resentational space in human ventral temporal cortex.
extended audiovisual narrative. Learning & Memory, 14, Neuron, 72, 404–416.
457–467. Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. (2000). The dis-
Furman, O., Mendelsohn, A., & Dudai, Y. (2012). The episodic tributed human neural system for face perception. Trends
engram transformed: Time reduces retrieval-related brain in Cognitive Sciences, 4, 223–233.
activity but correlates it with memory accuracy. Learning Henkel, L. A. (2014). Point-and-shoot memories: The influ-
& Memory, 19, 575–587. ence of taking photos on memory for a museum tour.
Goldstein, P., Weissman-Fogel, I., Dumas, G., & Shamay- Psychological Sciencesnd pain: How motivation works.
Tsoory, S. G. (2018). Brain-to-brain coupling during hand- New York, NY: Oxford University Press.
holding is associated with pain reduction. Proceedings of Hirst, W., & Echterhoff, G. (2012). Remembering in conver-
the National Academy of Sciences, USA, 115, E2528–E2537. sations: The social sharing and reshaping of memories.
Grace, P. M., Stanford, T., Gentgall, M., & Rolan, P. E. (2010). Annual Review of Psychology, 63, 55–79.
Utility of saccadic eye movement analysis as an objec- Hirst, W., & Manier, D. (1999). Remembering as communi-
tive biomarker to detect the sedative interaction between cation: A family recounts its past. In D. C. Rubin (Ed.),
opioids and sleep deprivation in opioid-naive and opioid- Remembering our past: Studies in autobiographical
tolerant populations. Journal of Psychopharmacology, 24, memory (pp. 271–290). Cambridge, England: Cambridge
1631–1640. University Press.
Gregg, N. M., White, B. R., Zeff, B. W., Berger, A. J., & Holper, L., Scholkmann, F., & Wolf, M. (2012). Between-
Culver, J. P. (2010). Brain specificity of diffuse optical brain connectivity during imitation measured by fNIRS.
imaging: Improvements from superficial signal regression NeuroImage, 63, 212–222.
and tomography. Frontiers in Neuroenergetics, 2, Article Hove, M. J., & Risen, J. L. (2009). It’s all in the timing: Interpersonal
14. doi:10.3389/fnene.2010.00014 synchrony increases affiliation. Social Cognition, 27, 949–
Griffiths, B., Mazaheri, A., Debener, S., & Hanslmayr, S. 960.
(2016). Brain oscillations track the formation of episodic Huettel, S. A., Song, A. W., & McCarthy, G. (2004). Functional
memories in the real world. NeuroImage, 143, 256–266. magnetic resonance imaging (Vol. 1). Sunderland, MA:
Grill-Spector, K., Knouf, N., & Kanwisher, N. (2004). The Sinauer Associates.
fusiform face area subserves face perception, not generic IJzerman, H., & Semin, G. R. (2009). The thermometer of
within-category identification. Nature Neuroscience, 7, social relations: Mapping social proximity on temperature.
555–562. Psychological Science, 20, 1214–1220.
Grossman, E. D., Blake, R., & Kim, C. Y. (2004). Learning to Inagaki, T. K., Irwin, M. R., Moieni, M., Jevtic, I., & Eisenberger,
see biological motion: Brain activity parallels behavior. N. I. (2016). A pilot study examining physical and
Journal of Cognitive Neuroscience, 16, 1669–1679. social warmth: Higher (non-febrile) oral temperature is
Gruber, M. J., Gelman, B. D., & Ranganath, C. (2014). States associated with greater feelings of social connection. PLOS
of curiosity modulate hippocampus-dependent learning ONE, 11(6), Article e0156873. doi:10.1371/journal.pone
via the dopaminergic circuit. Neuron, 84, 486–496. .0156873
Hainselin, M., Picard, L., Manolli, P., Vankerkore-Candas, S., Jafarpour, A., Barnes, G., Fuentemilla, L., Duzel, E., & Penny,
& Bourdin, B. (2017). Hey teacher, don’t leave them kids W. D. (2013). Population level inference for multivariate
Ecological Approach 17

MEG analysis. PLOS ONE, 8(8), e71305. doi:0.1371/jour- differ substantially in their neural substrates. Neuro­
nal.pone.0071305 psychologia, 47, 2290–2298.
Jenkins, A. C., & Mitchell, J. P. (2009). Mentalizing under Meier, B. P., Hauser, D. J., Robinson, M. D., Friesen, C. K.,
uncertainty: Dissociated neural responses to ambiguous & Schjeldahl, K. (2007). What’s “up” with God? Vertical
and unambiguous mental state inferences. Cerebral Cortex, space as a representation of the divine. Journal of
20, 404–410. Personality and Social Psychology, 93, 699–710.
Jiang, J., Chen, C., Dai, B., Shi, G., Ding, G., Liu, L., & Lu, C. Mendelsohn, A., Chalamish, Y., Solomonovich, A., & Dudai, Y.
(2015). Leader emergence through interpersonal neural (2008). Mesmerizing memories: Brain substrates of epi-
synchronization. Proceedings of the National Academy of sodic memory suppression in posthypnotic amnesia.
Sciences, USA, 112, 4274–4279. Neuron, 57, 159–170.
Jiang, J., Dai, B., Peng, D., Zhu, C., Liu, L., & Lu, C. (2012). Mendelsohn, A., Furman, O., & Dudai, Y. (2010). Signatures of
Neural synchronization during face-to-face communica- memory: Brain coactivations during retrieval distinguish
tion. Journal of Neuroscience, 32, 16064–16069. correct from incorrect recollection. Frontiers in Behavioral
Kanwisher, N., McDermott, J., & Chun, M. M. (1997). The Neuroscience, 4, Article 18. doi:10.3389/fnbeh.2010.00018
fusiform face area: A module in human extrastriate cortex Mendelsohn, A., Furman, O., Navon, I., & Dudai, Y. (2009).
specialized for face perception. Journal of Neuroscience, Subjective vs. documented reality: A case study of long-
17, 4302–4311. term real-life autobiographical memory. Learning &
Kanwisher, N., & Yovel, G. (2006). The fusiform face area: Memory, 16, 142–146.
A cortical region specialized for the perception of faces. Milton, F., Muhlert, N., Butler, C. R., Benattayallah, A., &
Philosophical Transactions of the Royal Society B: Biological Zeman, A. Z. (2011). The neural correlates of everyday
Sciences, 361, 2109–2128. recognition memory. Brain and Cognition, 76, 369–381.
Karsh, N., & Eitam, B. (2015). I control therefore I do: Molenberghs, P, Cunnington, R, & Mattingley, JB. (2012).
Judgments of agency influence action selection. Cognition, Brain regions with mirror properties: a meta-analysis of
138, 122–131. 125 human fMRI studies. Neuroscience & Biobehavioral
King, J. R., & Dehaene, S. (2014). Characterizing the dynamics Reviews, 36, 341-349.
of mental representations: The temporal generalization Montague, P. R., Berns, G. S., Cohen, J. D., McClure, S. M.,
method. Trends in Cognitive Sciences, 18, 203–210. Pagnoni, G., Dhamala, M., & Fisher, R. E. (2002). Hyper­
Kingstone, A., Smilek, D., Ristic, J., Friesen, C. K., & Eastwood, scanning: Simultaneous fMRI during linked social interac-
J. D. (2003). Attention, researchers! It is time to take a tions. NeuroImage, 16, 1159–1164.
look at the real world. Current Directions in Psychological Montague, P. R., Dolan, R. J., Friston, K. J., & Dayan, P.
Science, 12, 176–180. doi:10.1111/1467-8721.01255 (2012). Computational psychiatry. Trends in Cognitive
Kirilina, E., Jelzow, A., Heine, A., Niessing, M., Wabnitz, H., Sciences, 16, 72–80. doi:10.1016/j.tics.2011.11.018
Brühl, R., & Tachtsidis, I. (2012). The physiological ori- Mueller, T., Fagan, W. F., & Grimm, V. (2011). Integrating
gin of task-evoked systemic artefacts in functional near individual search and navigation behaviors in mechanistic
infrared spectroscopy. NeuroImage, 61, 70–81. movement models. Theoretical Ecology, 4, 341–355.
Koehler, J. J. (1996). The base rate fallacy reconsidered: Müller, V., Sänger, J., & Lindenberger, U. (2013). Intra-and
Descriptive, normative, and methodological challenges. inter-brain synchronization during musical improvisation
Behavioral and Brain Sciences, 19, 1–17. on the guitar. PLOS ONE, 8(9), Article 73852. doi:10.1371/
Konvalinka, I., & Roepstorff, A. (2012). The two-brain approach: journal.pone.0073852
How can mutually interacting brains teach us something Murty, V. P., & Adcock, R. A. (2014). Enriched encoding:
about social interaction? Frontiers in Human Neuroscience, Reward motivation organizes cortical networks for hippo-
6, Article 215. doi:10.3389/fnhum.2012.00215 campal detection of unexpected events. Cerebral Cortex,
Krill, A. L., & Platek, S. M. (2012). Working together may be 24, 2160–2168. doi:10.1093/cercor/bht063
better: Activation of reward centers during a cooperative Murty, V. P., DuBrow, S., & Davachi, L. (2015). The simple
maze task. PLOS ONE, 7(2), Article e30613. doi:10.1371/ act of choosing influences declarative memory. Journal
journal.pone.0030613 of Neuroscience, 35, 6255–6264.
Lewis-Peacock, J. A., & Norman, K. A. (2013). Multi-voxel Naselaris, T., Kay, K. N., Nishimoto, S., & Gallant, J. L. (2011).
pattern analysis of fMRI data. In M. S. Gazzaniga & G. R. Encoding and decoding in fMRI. NeuroImage, 56, 400–
Mangun (Eds.), The cognitive neurosciences (4th ed., pp. 410.
911–920). Cambridge, MA: MIT Press. Neisser, U. (1991). A case of misplaced nostalgia. American
Liu, N., Mok, C., Witt, E. E., Pradhan, A. H., Chen, J. E., & Psychologist, 46, 34–36. doi:10.1037/0003-066X.46.1.34
Reiss, A. L. (2016). NIRS-based hyperscanning reveals Nelson, K., & Fivush, R. (2004). The emergence of auto-
inter-brain neural synchronization during cooperative biographical memory: A social cultural developmental
Jenga game with face-to-face communication. Frontiers in theory. Psychological Review, 111, 486–511.
Human Neuroscience, 10, Article 82. doi:10.3389/fnhum Niedenthal, P. M., Barsalou, L. W., Winkielman, P., Krauth-
.2016.00082 Gruber, S., & Ric, F. (2005). Embodiment in attitudes,
Maguire, E. A. (2012). Studying the freely-behaving brain with social perception, and emotion. Personality and Social
fMRI. NeuroImage, 62, 1170–1176. Psychology Review, 9, 184–211.
McDermott, K. B., Szpunar, K. K., & Christ, S. E. (2009). Nozawa, T., Sasaki, Y., Sakaki, K., Yokoyama, R., & Kawashima, R.
Laboratory-based and autobiographical retrieval tasks (2016). Interpersonal frontopolar neural synchronization in
18 Shamay-Tsoory, Mendelsohn

group communication: An exploration toward fNIRS hyper- Scholkmann, F., Holper, L., Wolf, U., & Wolf, M. (2013). A new
scanning of natural interactions. NeuroImage, 133, 484–497. methodical approach in neuroscience: Assessing inter-
Osaka, N., Minamoto, T., Yaoi, K., Azuma, M., Shimada, Y. M., personal brain coupling using functional near-infrared
& Osaka, M. (2015). How two brains make one synchro- imaging (fNIRI) hyperscanning. Frontiers in Human Neuro­
nized mind in the inferior frontal cortex: fNIRS-based science, 7, Article 813. doi:10.3389/fnhum.2013.00813
hyperscanning during cooperative singing. Frontiers in Schultz, D. P., & Schultz, S. E. (2015). A history of modern
Psychology, 6, Article 1811. doi:10.3389/fpsyg.2015.01811 psychology. Boston, MA: Cengage Learning.
Pan, Y., Novembre, G., Song, B., Li, X., & Hu, Y. (2018). Schultz, J., Brockhaus, M., Bülthoff, H. H., & Pilz, K. S. (2013).
Interpersonal synchronization of inferior frontal cortices What the human brain likes about facial motion. Cerebral
tracks social interactive learning of a song. NeuroImage, Cortex, 23, 1167–1178.
183, 280–290. Shohamy, D., & Adcock, R. A. (2010). Dopamine and adap-
Parzuchowski, M., & Szymkow-Sudziarska, A. (2008). Well, tive memory. Trends in Cognitive Sciences, 14, 464–472.
slap my thigh: Expression of surprise facilitates memory Slater, M., Usoh, M., & Steed, A. (1995). Taking steps: The
of surprising material. Emotion, 8, 430–434. influence of a walking technique on presence in vir-
Phan, K. L., Sripada, C. S., Angstadt, M., & McCabe, K. (2010). tual reality. ACM Transactions on Computer-Human
Reputation for reciprocity engages the brain reward cen- Interaction (TOCHI), 2, 201–219.
ter. Proceedings of the National Academy of Sciences, USA, Spiers, H. J., & Maguire, E. A. (2007). Decoding human
107, 13099–13104. doi:10.1073/pnas.1008137107 brain activity during real-world experiences. Trends in
Pilz, K. S., Thornton, I. M., & Bülthoff, H. H. (2006). A search Cognitive Sciences, 11, 356–365.
advantage for faces learned in motion. Experimental Spreng, R. N. (2013). Examining the role of memory in
Brain Research, 171, 436–447. social cognition. Frontiers in Psychology, 4, Article 437.
Piolino, P., Desgranges, B., & Eustache, F. (2009). Episodic doi:10.3389/fpsyg.2013.00437
autobiographical memories over the course of time: Steffens, M. C., von Stülpnagel, R., & Schult, J. C. (2015).
Cognitive, neuropsychological and neuroimaging find- Memory recall after “learning by doing” and “learning
ings. Neuropsychologia, 47, 2314–2329. by viewing”: Boundary conditions of an enactment ben-
Plancher, G., Barra, J., Orriols, E., & Piolino, P. (2013). The influ- efit. Frontiers in Psychology, 6, Article 1907. doi:10.3389/
ence of action on episodic memory: A virtual reality study. fpsyg.2015.01907
Quarterly Journal of Experimental Psychology, 66, 895–909. Stephens, G. J., Silbert, L. J., & Hasson, U. (2010). Speaker–
Price, T. F., Dieckman, L. W., & Harmon-Jones, E. (2012). listener neural coupling underlies successful communi-
Embodying approach motivation: Body posture influences cation. Proceedings of the National Academy of Sciences,
startle eyeblink and event-related potential responses to USA, 107, 14425–14430.
appetitive stimuli. Biological Psychology, 90, 211–217. Stepper, S., & Strack, F. (1993). Proprioceptive determinants
Rajhans, P., Jessen, S., Missana, M., & Grossmann, T. (2016). of emotional and nonemotional feelings. Journal of
Putting the face in context: Body expressions impact facial Personality and Social Psychology, 64, 211–220.
emotion processing in human infants. Developmental Steyvers, M., & Hemmer, P. (2012). Reconstruction from
Cognitive Neuroscience, 19, 115–121. memory in naturalistic environments. In B. H. Ross (Ed.),
Ramseyer, F., & Tschacher, W. (2011). Nonverbal synchrony Psychology of learning and motivation (Vol. 56, pp. 125–
in psychotherapy: Coordinated body movement reflects 144). San Diego, CA: Academic Press.
relationship quality and outcome. Journal of Consulting St. Jacques, P., Olm, C., & Schacter, D. L. (2013). Neural mech-
and Clinical Psychology, 79, 284–295. anisms of reactivation-induced updating that enhance and
Riskind, J. H. (1989). The mediating mechanisms in mood distort memory. Proceedings of the National Academy of
and memory: A cognitive-priming formulation. Journal Sciences, USA, 110, 19671–19678.
of Social Behavior and Personality, 4, 173–184. St. Jacques, P., Rubin, D. C., LaBar, K. S., & Cabeza, R. (2008).
Rotem-Turchinski, N., Ramaty, A., & Mendelsohn, A. (2019). The short and long of it: Neural correlates of temporal-
The opportunity to choose enhances long-term episodic order memory for autobiographical events. Journal of
memory. Memory, 27, 431–440. Cognitive Neuroscience, 20, 1327–1341.
Sänger, J., Müller, V., & Lindenberger, U. (2012). Intra-and St. Jacques, P. L., & Schacter, D. L. (2013). Modifying memory:
interbrain synchronization and network properties when Selectively enhancing and updating personal memories
playing guitar in duets. Frontiers in Human Neuroscience, for a museum tour by reactivating them. Psychological
6, Article 312. doi:10.3389/fnhum.2012.00312 Science, 24, 537–543.
Sbordone, R. J., & Guilmette, T. J. (1999). Ecological validity: Thomson, D. M., & Tulving, E. (1970). Associative encod-
Prediction of everyday and vocational functioning from ing and retrieval: Weak and strong cues. Journal of
neuropsychological test data. In J. J. Sweet (Ed.), Studies Experimental Psychology, 86, 255–262.
on neuropsychology, development, and cognition. Forensic Tulving, E. (1985). Elements of episodic memory. Oxford,
neuropsychology: Fundamentals and practice (pp. 227– England: Oxford University Press.
254). Lisse, Netherlands: Swets & Zeitlinger Publishers. Tylén, K., Allen, M., Hunter, B. K., & Roepstorff, A. (2012).
Schilbach, L., Timmermans, B., Reddy, V., Costall, A., Bente, Interaction vs. observation: Distinctive modes of social
G., Schlicht, T., & Vogeley, K. (2013). Toward a second- cognition in human brain and behavior? A combined fMRI
person neuroscience. Behavioral and Brain Sciences, 36, and eye-tracking study. Frontiers in Human Neuroscience,
393–414. 6, Article 331. doi:10.3389/fnhum.2012.00331
Ecological Approach 19

Vinogradov, S., Luks, T. L., Simpson, G. V., Schulman, B. J., Wittmann, B. C., Schott, B. H., Guderian, S., Frey, J. U.,
Glenn, S., & Wong, A. E. (2006). Brain activation pat- Heinze, H. J., & Düzel, E. (2005). Reward-related FMRI
terns during memory of cognitive agency. NeuroImage, activation of dopaminergic midbrain is associated with
31, 896–905. enhanced hippocampus-dependent long-term memory
Williams, L. E., & Bargh, J. A. (2008). Experiencing physical formation. Neuron, 45, 459–467.
warmth promotes interpersonal warmth. Science, 322, Yun, K., Watanabe, K., & Shimojo, S. (2012). Interpersonal
606–607. body and neural synchronization as a marker of implicit
Wilson, M. (2002). Six views of embodied cognition. social interaction. Scientific Reports, 2, Article 959.
Psychonomic Bulletin & Review, 9, 625–636. doi:10.1038/srep00959
Wittmann, B. C., Dolan, R. J., & Düzel, E. (2011). Behavioral Zaki, J., & Ochsner, K. (2009). The need for a cognitive neu-
specifications of reward-associated long-term memory roscience of naturalistic social cognition. Annals of the
enhancement in humans. Learning & Memory, 18, 296–300. New York Academy of Sciences, 1167, 16–30.

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