Media Neuroscience
Media
Part of Media Neuroscience
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- Media Neuroscience
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Media Neuroscience
J. MICHAEL MANGUS, AUBRIE ADAMS, and RENE WEBER
Abstract
Media neuroscience offers a unique window into how the complexities of human
behavior emerge from the dynamic interaction of adaptive brain structures in
response to environmental inputs. Rather than treating these dynamics as a
black box or measuring them only indirectly through self-report or behavioral
observation, neuroimaging studies are uniquely able to provide theoretical insight
into underlying brain processes and their evolutionary basis. This essay provides an
overview of foundational research in the area of media neuroscience, evaluates key
critiques of that research, and provides an outlook for how emerging trends may
develop in the near future.
INTRODUCTION
Media neuroscience is emerging as a transdisciplinary research field. Scholars
from an expansive constellation of disciplines, including psychology, communication, pedagogy, and cognitive and computer sciences, are employing
the tools of neuroscience to cultivate a deeper understanding of media use,
its influence on individuals, and its implications for society at large. In some
of these disciplines, the integration of neuroscientific reasoning in the study
of the mind is long-established; in others, including the discipline of communication and media research, neuroscientific perspectives have emerged only
recently as a significant line of inquiry.
As with any transdisciplinary endeavor, the development of sophisticated
research and fruitful collaborations will require that researchers establish
common ground, interrogate latent assumptions, and craft programs of
research that can be mutually beneficial to scholars across disciplines. In
pursuit of these goals, this essay provides an overview of foundational
research in the area of media neuroscience, evaluates key critiques of that
research, and provides an outlook for how emerging trends may develop
in the near future. In the process, we attempted to address four major
questions: (i) What has extant media neuroscience research contributed to
scientific knowledge? (ii) How can tools from neuroscience be applied to the
Emerging Trends in the Social and Behavioral Sciences. Edited by Robert Scott and Stephen Kosslyn.
© 2015 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
study of media, and, conversely, how can media be useful in the study of
neuroscience? (iii) Why should we study media neuroscience—or, perhaps,
why not? (iv) What’s next for media neuroscience?
FOUNDATIONAL RESEARCH
Neuroscience has been well established as a field for decades, and an
overview of its foundational studies and major discoveries could easily
fill an entire textbook (see, e.g., Gazzaniga, 2009). Rather than attempt to
provide a comprehensive general overview, we instead concern ourselves
here with the emergence of media neuroscience as a specific area of study,
the development of which can be traced historically through the evolution
of research on mass communication. In particular, two major transitions
at different points in that history have laid the foundation for media
neuroscience.
The first inflection point was the development of mass communication
as a scientific discipline during the middle of the twentieth century. Of
course, scholarly interest in communication as the art of rhetoric is much
older—systematic approaches to rhetoric date back to at least ancient
Greece. However, the sweeping impact of new electronic media, as well
as the widespread use of propaganda during World War II, motivated a
substantial number of researchers to begin studies of mass communication
as a scientific, psychological, and social phenomenon in the 1940s and 1950s
(e.g., Hovland, Janis, & Kelley, 1953). The pioneering persuasion studies
of the Yale School initiated the bifurcation of communication science as a
field distinct from the humanistic art of rhetoric and established media as
a central focus of that field. This transition provided the basis for the media
and science components of media neuroscience.
This originary work arose during an era in which studies were heavily
influenced by positivism and environmental determinism. As a result, even
in the present day, many communication theories purport to explain behavioral and social outcomes as products of environmental stimuli only. However, such theories are necessarily incomplete because they fail to account
for the interaction between environmental inputs and the evolved physiological mechanisms that enable cognitive processes, traits, and behavior.
Recent attempts to address this shortcoming have provided the second key
transition toward media neuroscience: the development of a neurophysiological perspective, which incorporates theoretical ideas from evolutionary
psychology and methodological tools from cognitive science (Weber, Sherry,
& Mathiak, 2008). It is this body of research that has put the neuro in media
neuroscience.
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Media neuroscience is based on the belief that the brain is the center of cognition and must therefore play a pivotal role in processing media messages.
Philosophical questions about the nature of the mind notwithstanding, only
the physically observable world is amenable to scientific study, and mental processes can be most clearly explained through studying how physical
events in the brain are linked to attitudes and behaviors. Furthermore, media
neuroscientists subscribe to the view that the brain itself is a product of evolutionary processes, which have selected for modules that enable specific tasks
(e.g., motor control, understanding language, recognizing faces) and have
thereby yielded the emergence of complex cognitive phenomena (Barkow,
Cosmides, & Tooby, 1992).
The primary theoretical value of media neuroscience lies in the nested levels
of explanation demanded by a neurophysiological perspective on communication. Tinbergen (1963) famously argues that a complete explanation for
behavior must address four distinct questions: ontogeny, phylogeny, causation, and function. Ontogeny and phylogeny place a given behavior in
historical perspective, explaining how the trait develops during the life span
of an individual organism and how its evolutionary history has unfolded
at the species level, respectively. Both causation and function, on the other
hand, address the operation of that behavior at a given point in time: causation provides the proximate mechanism by which the behavior operates,
and function provides the adaptive utility of that behavior in evolutionary
terms. Given that communicative behavior is an evolved adaptation, media
neuroscience seeks to provide mechanistic explanations of how the behavior
operates and can facilitate improved functional explanations for why such
behavior is adaptive.
It is important to note that the rise of the neurophysiological perspective
is not about a shift from “nurture” to “nature” as the driving explanatory
force, but rather the dynamic interplay of both. This approach foregrounds
a process-driven view of communication. Media effects research has often
relied on static, population-level input–output models, which tacitly assume
that the impact of a message occurs as a singular event and frequently gloss
over the details of the individual differences and internal psychological
processes driving media effects. By contrast, a process-oriented perspective
argues that natural systems require a constant state of flux to adapt to
changing environments and therefore foregrounds the dynamical nature
of media effects (Lang, 2013). In keeping with this view, media neuroscience researchers aim to develop biologically driven explanations that
demonstrate how media selection and effects occur as a result of processes
that combine evolved physiological capacities with environmental inputs
over time.
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
All types of communication between individuals is necessarily mediated,
since the electrochemical signals in a sender’s brain must be encoded in a
format that can be transmitted to and processed by a receiver. At the most
basic level, this takes the form of bodily movement that manipulates the
local environment. Speech, for instance, uses the atmosphere as its medium:
the vocal tract generates vibrations in air, which can be heard and understood by others. Over time, humans have developed many mediation technologies capable of extending the spatial and temporal transmissibility of
a message. For example, writing encodes spoken language as symbols that
could be recorded on a particular physical object, such as indentations in a
clay tablet or ink on a sheet of paper, which can then circulate to other locations and persist over time. More recently, digital media have been developed
to encode messages as numbers that, using electromagnetic fields for storage and transmission, can reliably propagate almost instantaneously over
long distances and be broadcast to multiple receivers at minimal cost. Differences in how particular electronic media technologies—for example, text
messages versus video calls—are processed by the brain is an active area of
research with considerable value; however, this essay takes a broad perspective that foregrounds the content of mediated messages (e.g., auditory and
visual information) rather than a particular technology of transmission (e.g.,
broadcast television vs streaming video on the Internet). We focus on audiovisual electronic media such as video and virtual environments not because
other types of mediation are uninteresting, but rather because these media
are uniquely able to encode multimodal, dynamic stimuli that most closely
emulate the actual experience of reality.
Several studies exemplify early media neuroscience research and provide
the foundation for the area. These studies can be broadly divided into two
groups: those which use media to investigate neuroscience phenomena, and
those which use neuroscience to investigate media phenomena.
First, media can evoke naturalistic responses in studies, which might
otherwise struggle with ecological validity. A variety of brain imaging
experiments have used mediated stimuli to simulate actual reality for
participants during brain scans (Bartels & Zeki, 2004, 2005; Golland et al.,
2007; Hasson, Nir, Levy, Fuhrmann, & Malach, 2004; Mathiak & Weber, 2006;
Spiers & Maguire, 2006a, 2006b). There is good reason to believe that these
mediated stimuli can emulate real-world observations and interactions,
despite the fact that participants are alone inside a brain imaging scanner.
Research on the mapping principle suggests that individuals map virtual
worlds to their experiences with nonmediated reality and, therefore, tend to
behave in ways that parallel actual behavior (Reeves & Nass, 1996; Williams,
2010; Williams, Contractor, Poole, Srivastava, & Cai, 2011).
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Second, media neuroscience can be used to examine the brain systems that
are associated with particular media effects (Brefczynski-Lewis, 2011; Mathiak et al., 2011). The cognitive and behavioral effects of violence in media are
one highly studied example, with numerous studies using both interactive
(e.g., Klasen et al., 2013; Weber, Ritterfeld, & Mathiak, 2006) and noninteractive media (e.g., Mathews et al., 2005; Murray et al., 2006). Another major
line of research has examined the persuasiveness of health-related messages
(Falk, 2010; Ramsey, Yzer, Luciana, Vohs, & McDonald, 2013; Yzer, Vohs,
Luciana, Cuthbert, & McDonald, 2011). The application of neuroscience
to such questions can not only provide insight into the physical processes
underlying media effects, but also serve as an important theory-building
tool. For instance, the concept of flow has been used to explain media
selection and enjoyment (Sherry, 2004). Weber, Tamborini, Westcott-Baker,
and Kantor (2009) provide a neuroscientific reconceptualization of flow as
the synchronization of attentional and reward networks in the brain, which
has subsequently been tested using neuroimaging (Klasen, Weber, Kircher,
Mathiak, & Mathiak, 2011).
These few selected examples of foundational research in media neuroscience have demonstrated that this emerging research area is bidirectional.
Traditional cognitive neuroscientists stand to benefit from the increased
ecological validity of media stimuli, the methodological possibilities enabled
by virtual interactions, and the integration of solid media theory in neuroscientific investigations. Reciprocally, traditional media scientists stand to
benefit from the empirical sophistication of brain imaging methods and the
new theoretical trajectories that present themselves under an evolutionary
neurophysiological paradigm. The bidirectional relationship between media
science and neuroscience evinces the innate strengths of an abductive
approach where theory and method evolve together, with innovations in
one calling for further development of the other. In keeping with the notion
that “there is nothing so theoretical as a good method” (Greenwald, 2012),
media theory can drive new neuroscience methods, which can in turn
yield data that demand revisions to media theory, and so on, in a mutually
reinforcing cycle.
CHALLENGES AND CONTROVERSIES
While there seems to be a bright future for media neuroscience, this work
remains in its infancy and is not without its critics. In this section, we provide a brief primer on neuroimaging for social scientists and consider some
methodological, theoretical, and epistemological critiques of media neuroscience research.
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
Perhaps the biggest challenge for current work on media neuroscience is
that only a relatively small minority of media scientists have the training
necessary to execute or critically evaluate neuroscience research. Media
scholars need to develop a basic understanding of brain anatomy and
neuronal processes in order to design sound studies and engage in fruitful collaborations. Fortunately, there are a growing number of resources
available for researchers to develop these skills and a number of excellent
introductory textbooks (e.g., Frackowiak, Ashburner, Penny, & Zeki, 2004;
Gazzaniga, 2009; Harmon-Jones & Beer, 2009). One of the most common
technologies for neuroimaging is functional magnetic resonance imaging
(fMRI). As is so often the case in scientific measurement, this technology
has both advantages and disadvantages (Huettel, Song, & McCarthy, 2009).
However, fMRI serves as a common measurement to observe the brain’s
activity and its wide use facilitates easy replication and collaboration
(Brefczynski-Lewis, 2011).
One widely known methodological concern regarding neuroimaging is
the problem of reverse inference (Poldrack, 2006). Suppose that a researcher
observes that a certain stimulus tends to yield activation in a particular brain
region, and that prior studies have associated that brain region with some
well-known cognitive process. Frequently, the researcher will be drawn to
make a reverse inference and assert that the stimulus engages that cognitive
process. However, the available data can provide only limited support for
such a claim—a given brain region may be activated by multiple distinct
cognitive processes, so the fact that the region was active does not guarantee
that the purported cognitive process took place.
This problem can be ameliorated in two general ways (Poldrack, 2006).
First, certain brain regions exhibit highly selective responses that are consistently associated with one cognitive process but not others. Data sharing
and replication are crucial to establish the selectivity of a region by observing
trends across numerous studies. Though selectivity is beyond the direct control of the researcher, establishing high selectivity using prior research can
strengthen the justification for the reverse inference. Second, brain imaging
data can be combined with other behavioral measures, which can provide
further evidence to help triangulate relevant cognitive processes. Social scientists can provide particular insight here, given their expertise in the development of behavioral measures for psychological processes.
A related challenge for neuroimaging in social science research also
questions the ability to establish relationships between brain activity and
cognitive processes, but from a slightly different perspective. Consider a
distinction between research on encoding versus decoding brain states (Naselaris, Kay, Nishimoto, & Gallant, 2011). Traditionally, it has been generally
cautioned that brain imaging cannot be a “mind-reading” technology:
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experimenters present a stimulus designed to induce a given mental state
and then observe the brain activity that encodes that state, but rarely has
research reversed the procedure and used brain activity to decode mental
states. This approach limits the utility of brain imaging, since it uses mental
states to predict brain states, but not brain states to predict mental states.
However, there has been a recent groundswell of support for a new wave
of decoding research supported by sophisticated Bayesian classifiers. For
instance, the Gallant Lab at UC Berkeley has utilized a decoding approach
extensively (Huth, Nishimoto, Vu, & Gallant, 2012; Naselaris, Prenger,
Kay, Oliver, & Gallant, 2009; Naselaris, Kay, Nishimoto & Gallant, 2011),
including decoding visual features of movies from brain activity (Nishimoto
et al., 2011).
Similarly, Haynes and colleagues have conducted decoding studies focused
around free will and hidden intentions, using brain activity to predict attentional salience and decision-making behavior (Bogler, Bode, & Haynes, 2011;
Chen et al., 2010; Haynes et al., 2007; Soon, Brass, Heinze, & Haynes, 2008).
These results have been one of the most remarkable emerging trends in neuroscience generally and media neuroscience in particular: “mind-reading”
studies are now an extant, albeit nascent, area of research. It should be immediately evident that the ability to decode mental states using brain activity
represents a major avenue for theoretical advancement using neuroimaging.
An additional critique of media neuroscience is that neuroimaging studies
cannot predict real-world behaviors. This critique generally follows two
lines of reasoning. First, ecological validity is a concern—brain scanning
equipment is intrusive, and behavior during fMRI may not accord with
real-world behavior. As argued earlier, though, media neuroscience can
actually serve to enhance ecological validity by providing virtual environments within the experimental setting that can simulate actual experiences
(e.g., Mathiak & Weber, 2006). Furthermore, brain imaging technology is constantly improving, and fNIR (functional near-infrared) technology capable
of imaging prefrontal cortex is available in small, light, and comparatively
unobtrusive packages (see, inter alia, Izzetoglu et al., 2011).
The second prong of this critique questions whether neuroimaging data
can predict population-level effects. Given the time and expense associated
with brain imaging, studies typically use as small of a sample as reasonably
possible, often on the order of 10–20 participants. Moreover, the extensive
use of convenience sampling from undergraduate participant pools calls into
question the generalizability of research across the social sciences (Henrich,
Heine, & Norenzayan, 2010). This is essentially an empirical question: do
the results of neuroimaging studies allow us to predict behavior at the
population level or not? Though it is impossible to provide a definitive
answer to that question in its general form, recent publications (Berkman &
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
Falk, 2013; Falk et al., 2013) have persuasively argued for a framework that
combines neuroscience with population science, emphasizing representative
samples, longitudinal analysis, and transdisciplinary collaboration. In one
notable example, the application of neuroimaging using a brain-as-predictor
approach doubled the explained variance in real-world health behavior
compared to self-report measures (Falk, Berkman, Whalen, & Lieberman,
2011). Falk (2010) suggests that the future may bring “neural focus groups”
whose brain imaging data are used to fine-tune persuasive messages. We
believe that the use of the brain as a predictor of real-world behavior will be
a crucial avenue of development for media neuroscience.
A final critique of media neuroscience is that neuroimaging data are
innately misleading, increasing the confidence that researchers are willing
to place in research, even when the results are counter-intuitive or even
apparently absurd. A well-known study by McCabe and Castel (2008)
contends that images of the brain in and of themselves make research
findings more persuasive to their audiences—the exact same data presented
in text or chart form carry less persuasive force, they argue, because images
exaggerate a bias toward reductive physicalist explanations. We object
to this critique on three levels. First, methodological shortcomings and
failed attempts at replication call into question the empirical validity of the
supposed “seductive allure” of brain imaging (Farah & Hook, 2013). Second,
many researchers show due restraint in presenting their results, hedging the
implications of their work when appropriate, and including images of the
brain only when they contribute information above and beyond what can
be presented through other means. Third, if such a bias does exist, its impact
should be dampened over time as more scholars become familiar with
neuroscience research and develop the experience necessary to critically
evaluate that research. If anything, then this critique should be seen as a
call for more and better neuroscience research, not the abandonment of
neuroimaging.
OUTLOOK FOR THE FUTURE
Though it is currently in its early stages, we anticipate that media neuroscience research will grow tremendously in the coming years. In this concluding section, we provide an overview of research areas that are likely to
be core to media neuroscience going forward and offer general guidance for
how we believe this research can be most successful. The task of predicting where innovation is likely to occur always involves inherent uncertainty,
and there are innumerable lines of study that could generate valuable knowledge. Nonetheless, based on recent interest as well as practical and theoretical
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value, we choose to highlight three major areas of research that seem likely
to remain on the cutting edge of media neuroscience.
First, the effects of violent media seem likely to remain a central vein
of research for the foreseeable future. As one of the longest standing and
most studied topics in media neuroscience, the literature on media violence
is already considerable. Yet development has continued in recent years,
expanding research to consider not only the details of brain mechanisms
that might underlie direct effects of violent media on aggression (Guo et al.,
2013; Porges & Decety, 2013) but also better explanations of how different
individual traits might mediate that relationship (Swing & Anderson, 2014;
Valkenberg & Peter, 2013), and how violence effects psychological states
other than aggression (Madan, Mrug, & Wright, 2014). Future work in
this area also should include further examination of the contested link
between aggressive cognition during exposure to media violence and
subsequent aggressive behavior. The use of neuroimaging data to predict
population-level behavior could be especially valuable in addressing that
important ongoing controversy.
Second, media neuroscience will continue to provide great contributions
to the study of persuasion. The high-stakes area of health communication
will likely play a major role here. Falk (2010) argued that the contributions
of media neuroscience would likely proceed in three parts: identification of
neural mechanisms underlying persuasive health messages, translation of
brain imaging data examining those mechanisms into sound predictions
about population-level behavior, and integration of those mechanisms into
theories of persuasion. So far, this progression is well underway. The use of
brain imaging data to make predictions about the real-world effectiveness of
persuasive messages is an emerging trend with tremendous potential (Falk
et al., 2011).
Third, we anticipate an increasingly close relationship between research
on narratives as a means of communication and research on the neural substrates of moral reasoning. Hasson and colleagues have produced a fascinating program of media neuroscience research that examines communication
as a process of brain-to-brain coupling (Hasson et al., 2004; Hasson, Ghazanfar, Galantucci, Garrod, & Keysers, 2012; Stephens, Silbert, & Hasson, 2010).
A separate line of research has examined the evolutionary basis of moral
intuitions (de Waal, 2013; Haidt & Joseph, 2004) and sought to identify the
neural mechanisms of morality (Graham et al., 2011; Mikhail, 2007; Parkinson
et al., 2011). Narratives can serve to communicate culturally significant moral
norms, and future research on media neuroscience is poised to better understand how moral content promotes synchronous brain responses and affects
the salience and popularity of narratives (Tamborini, 2011; Weber et al., 2006,
2007; Weber, Popova, & Mangus, 2012).
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
The success of these research programs—and media neuroscience
overall—will demand innovation. Cross-disciplinary collaborations frequently suffer from differences in training and difficulties in communication.
Neuroimaging research requires extensive planning and resources. Without a culture of data sharing and replication, methods will be inconsistent,
predictions will be limited, and results will be uncertain. Students in communication and media science who intend to pursue this research will require
training that currently may not be available in many departments. Nevertheless, we believe that these challenges can—and ought to be—overcome
given the far-reaching benefits of media neuroscience research for revealing
how complex behavior emerges from dynamic processes in the brain.
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& Wheatley, T. (2011). Is morality unified? Evidence that distinct neural systems
underlie moral judgments of harm, dishonesty, and disgust. Journal of Cognitive
Neuroscience, 23, 3162–3180.
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J. MICHAEL MANGUS SHORT BIOGRAPHY
J. Michael Mangus, MA, MBD, is a fifth-year PhD student in the UCSB
Department of Communication and member of the Media Neuroscience Lab.
His scholarly interests include group coordination, morality, and collective
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
action; evolutionary and materialist approaches to communication theory;
and the philosophy of social science.
AUBRIE ADAMS SHORT BIOGRAPHY
Aubrie Adams, MA, is a PhD student in the Communication Department at
UCSB. She is interested in advancing media and computer-mediated communication research using neuroscientific methodologies. Her recent work
examines student perceptions of emoticons and her research has been featured on two top four paper panels at regional and national communication
conferences.
RENE WEBER SHORT BIOGRAPHY
Rene Weber, PhD, MD, is Professor in the Department of Communication at UCSB and lead researcher in the Media Neuroscience Lab
(http://medianeuroscience.org). His recent research focuses on cognitive
responses to mass communication and new technology media messages,
including video games. He develops and applies both traditional social
scientific and neuroscientific methodology (fMRI) to test media-related
theories.
-
Media Neuroscience
J. MICHAEL MANGUS, AUBRIE ADAMS, and RENE WEBER
Abstract
Media neuroscience offers a unique window into how the complexities of human
behavior emerge from the dynamic interaction of adaptive brain structures in
response to environmental inputs. Rather than treating these dynamics as a
black box or measuring them only indirectly through self-report or behavioral
observation, neuroimaging studies are uniquely able to provide theoretical insight
into underlying brain processes and their evolutionary basis. This essay provides an
overview of foundational research in the area of media neuroscience, evaluates key
critiques of that research, and provides an outlook for how emerging trends may
develop in the near future.
INTRODUCTION
Media neuroscience is emerging as a transdisciplinary research field. Scholars
from an expansive constellation of disciplines, including psychology, communication, pedagogy, and cognitive and computer sciences, are employing
the tools of neuroscience to cultivate a deeper understanding of media use,
its influence on individuals, and its implications for society at large. In some
of these disciplines, the integration of neuroscientific reasoning in the study
of the mind is long-established; in others, including the discipline of communication and media research, neuroscientific perspectives have emerged only
recently as a significant line of inquiry.
As with any transdisciplinary endeavor, the development of sophisticated
research and fruitful collaborations will require that researchers establish
common ground, interrogate latent assumptions, and craft programs of
research that can be mutually beneficial to scholars across disciplines. In
pursuit of these goals, this essay provides an overview of foundational
research in the area of media neuroscience, evaluates key critiques of that
research, and provides an outlook for how emerging trends may develop
in the near future. In the process, we attempted to address four major
questions: (i) What has extant media neuroscience research contributed to
scientific knowledge? (ii) How can tools from neuroscience be applied to the
Emerging Trends in the Social and Behavioral Sciences. Edited by Robert Scott and Stephen Kosslyn.
© 2015 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.
1
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
study of media, and, conversely, how can media be useful in the study of
neuroscience? (iii) Why should we study media neuroscience—or, perhaps,
why not? (iv) What’s next for media neuroscience?
FOUNDATIONAL RESEARCH
Neuroscience has been well established as a field for decades, and an
overview of its foundational studies and major discoveries could easily
fill an entire textbook (see, e.g., Gazzaniga, 2009). Rather than attempt to
provide a comprehensive general overview, we instead concern ourselves
here with the emergence of media neuroscience as a specific area of study,
the development of which can be traced historically through the evolution
of research on mass communication. In particular, two major transitions
at different points in that history have laid the foundation for media
neuroscience.
The first inflection point was the development of mass communication
as a scientific discipline during the middle of the twentieth century. Of
course, scholarly interest in communication as the art of rhetoric is much
older—systematic approaches to rhetoric date back to at least ancient
Greece. However, the sweeping impact of new electronic media, as well
as the widespread use of propaganda during World War II, motivated a
substantial number of researchers to begin studies of mass communication
as a scientific, psychological, and social phenomenon in the 1940s and 1950s
(e.g., Hovland, Janis, & Kelley, 1953). The pioneering persuasion studies
of the Yale School initiated the bifurcation of communication science as a
field distinct from the humanistic art of rhetoric and established media as
a central focus of that field. This transition provided the basis for the media
and science components of media neuroscience.
This originary work arose during an era in which studies were heavily
influenced by positivism and environmental determinism. As a result, even
in the present day, many communication theories purport to explain behavioral and social outcomes as products of environmental stimuli only. However, such theories are necessarily incomplete because they fail to account
for the interaction between environmental inputs and the evolved physiological mechanisms that enable cognitive processes, traits, and behavior.
Recent attempts to address this shortcoming have provided the second key
transition toward media neuroscience: the development of a neurophysiological perspective, which incorporates theoretical ideas from evolutionary
psychology and methodological tools from cognitive science (Weber, Sherry,
& Mathiak, 2008). It is this body of research that has put the neuro in media
neuroscience.
Media Neuroscience
3
Media neuroscience is based on the belief that the brain is the center of cognition and must therefore play a pivotal role in processing media messages.
Philosophical questions about the nature of the mind notwithstanding, only
the physically observable world is amenable to scientific study, and mental processes can be most clearly explained through studying how physical
events in the brain are linked to attitudes and behaviors. Furthermore, media
neuroscientists subscribe to the view that the brain itself is a product of evolutionary processes, which have selected for modules that enable specific tasks
(e.g., motor control, understanding language, recognizing faces) and have
thereby yielded the emergence of complex cognitive phenomena (Barkow,
Cosmides, & Tooby, 1992).
The primary theoretical value of media neuroscience lies in the nested levels
of explanation demanded by a neurophysiological perspective on communication. Tinbergen (1963) famously argues that a complete explanation for
behavior must address four distinct questions: ontogeny, phylogeny, causation, and function. Ontogeny and phylogeny place a given behavior in
historical perspective, explaining how the trait develops during the life span
of an individual organism and how its evolutionary history has unfolded
at the species level, respectively. Both causation and function, on the other
hand, address the operation of that behavior at a given point in time: causation provides the proximate mechanism by which the behavior operates,
and function provides the adaptive utility of that behavior in evolutionary
terms. Given that communicative behavior is an evolved adaptation, media
neuroscience seeks to provide mechanistic explanations of how the behavior
operates and can facilitate improved functional explanations for why such
behavior is adaptive.
It is important to note that the rise of the neurophysiological perspective
is not about a shift from “nurture” to “nature” as the driving explanatory
force, but rather the dynamic interplay of both. This approach foregrounds
a process-driven view of communication. Media effects research has often
relied on static, population-level input–output models, which tacitly assume
that the impact of a message occurs as a singular event and frequently gloss
over the details of the individual differences and internal psychological
processes driving media effects. By contrast, a process-oriented perspective
argues that natural systems require a constant state of flux to adapt to
changing environments and therefore foregrounds the dynamical nature
of media effects (Lang, 2013). In keeping with this view, media neuroscience researchers aim to develop biologically driven explanations that
demonstrate how media selection and effects occur as a result of processes
that combine evolved physiological capacities with environmental inputs
over time.
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
All types of communication between individuals is necessarily mediated,
since the electrochemical signals in a sender’s brain must be encoded in a
format that can be transmitted to and processed by a receiver. At the most
basic level, this takes the form of bodily movement that manipulates the
local environment. Speech, for instance, uses the atmosphere as its medium:
the vocal tract generates vibrations in air, which can be heard and understood by others. Over time, humans have developed many mediation technologies capable of extending the spatial and temporal transmissibility of
a message. For example, writing encodes spoken language as symbols that
could be recorded on a particular physical object, such as indentations in a
clay tablet or ink on a sheet of paper, which can then circulate to other locations and persist over time. More recently, digital media have been developed
to encode messages as numbers that, using electromagnetic fields for storage and transmission, can reliably propagate almost instantaneously over
long distances and be broadcast to multiple receivers at minimal cost. Differences in how particular electronic media technologies—for example, text
messages versus video calls—are processed by the brain is an active area of
research with considerable value; however, this essay takes a broad perspective that foregrounds the content of mediated messages (e.g., auditory and
visual information) rather than a particular technology of transmission (e.g.,
broadcast television vs streaming video on the Internet). We focus on audiovisual electronic media such as video and virtual environments not because
other types of mediation are uninteresting, but rather because these media
are uniquely able to encode multimodal, dynamic stimuli that most closely
emulate the actual experience of reality.
Several studies exemplify early media neuroscience research and provide
the foundation for the area. These studies can be broadly divided into two
groups: those which use media to investigate neuroscience phenomena, and
those which use neuroscience to investigate media phenomena.
First, media can evoke naturalistic responses in studies, which might
otherwise struggle with ecological validity. A variety of brain imaging
experiments have used mediated stimuli to simulate actual reality for
participants during brain scans (Bartels & Zeki, 2004, 2005; Golland et al.,
2007; Hasson, Nir, Levy, Fuhrmann, & Malach, 2004; Mathiak & Weber, 2006;
Spiers & Maguire, 2006a, 2006b). There is good reason to believe that these
mediated stimuli can emulate real-world observations and interactions,
despite the fact that participants are alone inside a brain imaging scanner.
Research on the mapping principle suggests that individuals map virtual
worlds to their experiences with nonmediated reality and, therefore, tend to
behave in ways that parallel actual behavior (Reeves & Nass, 1996; Williams,
2010; Williams, Contractor, Poole, Srivastava, & Cai, 2011).
Media Neuroscience
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Second, media neuroscience can be used to examine the brain systems that
are associated with particular media effects (Brefczynski-Lewis, 2011; Mathiak et al., 2011). The cognitive and behavioral effects of violence in media are
one highly studied example, with numerous studies using both interactive
(e.g., Klasen et al., 2013; Weber, Ritterfeld, & Mathiak, 2006) and noninteractive media (e.g., Mathews et al., 2005; Murray et al., 2006). Another major
line of research has examined the persuasiveness of health-related messages
(Falk, 2010; Ramsey, Yzer, Luciana, Vohs, & McDonald, 2013; Yzer, Vohs,
Luciana, Cuthbert, & McDonald, 2011). The application of neuroscience
to such questions can not only provide insight into the physical processes
underlying media effects, but also serve as an important theory-building
tool. For instance, the concept of flow has been used to explain media
selection and enjoyment (Sherry, 2004). Weber, Tamborini, Westcott-Baker,
and Kantor (2009) provide a neuroscientific reconceptualization of flow as
the synchronization of attentional and reward networks in the brain, which
has subsequently been tested using neuroimaging (Klasen, Weber, Kircher,
Mathiak, & Mathiak, 2011).
These few selected examples of foundational research in media neuroscience have demonstrated that this emerging research area is bidirectional.
Traditional cognitive neuroscientists stand to benefit from the increased
ecological validity of media stimuli, the methodological possibilities enabled
by virtual interactions, and the integration of solid media theory in neuroscientific investigations. Reciprocally, traditional media scientists stand to
benefit from the empirical sophistication of brain imaging methods and the
new theoretical trajectories that present themselves under an evolutionary
neurophysiological paradigm. The bidirectional relationship between media
science and neuroscience evinces the innate strengths of an abductive
approach where theory and method evolve together, with innovations in
one calling for further development of the other. In keeping with the notion
that “there is nothing so theoretical as a good method” (Greenwald, 2012),
media theory can drive new neuroscience methods, which can in turn
yield data that demand revisions to media theory, and so on, in a mutually
reinforcing cycle.
CHALLENGES AND CONTROVERSIES
While there seems to be a bright future for media neuroscience, this work
remains in its infancy and is not without its critics. In this section, we provide a brief primer on neuroimaging for social scientists and consider some
methodological, theoretical, and epistemological critiques of media neuroscience research.
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
Perhaps the biggest challenge for current work on media neuroscience is
that only a relatively small minority of media scientists have the training
necessary to execute or critically evaluate neuroscience research. Media
scholars need to develop a basic understanding of brain anatomy and
neuronal processes in order to design sound studies and engage in fruitful collaborations. Fortunately, there are a growing number of resources
available for researchers to develop these skills and a number of excellent
introductory textbooks (e.g., Frackowiak, Ashburner, Penny, & Zeki, 2004;
Gazzaniga, 2009; Harmon-Jones & Beer, 2009). One of the most common
technologies for neuroimaging is functional magnetic resonance imaging
(fMRI). As is so often the case in scientific measurement, this technology
has both advantages and disadvantages (Huettel, Song, & McCarthy, 2009).
However, fMRI serves as a common measurement to observe the brain’s
activity and its wide use facilitates easy replication and collaboration
(Brefczynski-Lewis, 2011).
One widely known methodological concern regarding neuroimaging is
the problem of reverse inference (Poldrack, 2006). Suppose that a researcher
observes that a certain stimulus tends to yield activation in a particular brain
region, and that prior studies have associated that brain region with some
well-known cognitive process. Frequently, the researcher will be drawn to
make a reverse inference and assert that the stimulus engages that cognitive
process. However, the available data can provide only limited support for
such a claim—a given brain region may be activated by multiple distinct
cognitive processes, so the fact that the region was active does not guarantee
that the purported cognitive process took place.
This problem can be ameliorated in two general ways (Poldrack, 2006).
First, certain brain regions exhibit highly selective responses that are consistently associated with one cognitive process but not others. Data sharing
and replication are crucial to establish the selectivity of a region by observing
trends across numerous studies. Though selectivity is beyond the direct control of the researcher, establishing high selectivity using prior research can
strengthen the justification for the reverse inference. Second, brain imaging
data can be combined with other behavioral measures, which can provide
further evidence to help triangulate relevant cognitive processes. Social scientists can provide particular insight here, given their expertise in the development of behavioral measures for psychological processes.
A related challenge for neuroimaging in social science research also
questions the ability to establish relationships between brain activity and
cognitive processes, but from a slightly different perspective. Consider a
distinction between research on encoding versus decoding brain states (Naselaris, Kay, Nishimoto, & Gallant, 2011). Traditionally, it has been generally
cautioned that brain imaging cannot be a “mind-reading” technology:
Media Neuroscience
7
experimenters present a stimulus designed to induce a given mental state
and then observe the brain activity that encodes that state, but rarely has
research reversed the procedure and used brain activity to decode mental
states. This approach limits the utility of brain imaging, since it uses mental
states to predict brain states, but not brain states to predict mental states.
However, there has been a recent groundswell of support for a new wave
of decoding research supported by sophisticated Bayesian classifiers. For
instance, the Gallant Lab at UC Berkeley has utilized a decoding approach
extensively (Huth, Nishimoto, Vu, & Gallant, 2012; Naselaris, Prenger,
Kay, Oliver, & Gallant, 2009; Naselaris, Kay, Nishimoto & Gallant, 2011),
including decoding visual features of movies from brain activity (Nishimoto
et al., 2011).
Similarly, Haynes and colleagues have conducted decoding studies focused
around free will and hidden intentions, using brain activity to predict attentional salience and decision-making behavior (Bogler, Bode, & Haynes, 2011;
Chen et al., 2010; Haynes et al., 2007; Soon, Brass, Heinze, & Haynes, 2008).
These results have been one of the most remarkable emerging trends in neuroscience generally and media neuroscience in particular: “mind-reading”
studies are now an extant, albeit nascent, area of research. It should be immediately evident that the ability to decode mental states using brain activity
represents a major avenue for theoretical advancement using neuroimaging.
An additional critique of media neuroscience is that neuroimaging studies
cannot predict real-world behaviors. This critique generally follows two
lines of reasoning. First, ecological validity is a concern—brain scanning
equipment is intrusive, and behavior during fMRI may not accord with
real-world behavior. As argued earlier, though, media neuroscience can
actually serve to enhance ecological validity by providing virtual environments within the experimental setting that can simulate actual experiences
(e.g., Mathiak & Weber, 2006). Furthermore, brain imaging technology is constantly improving, and fNIR (functional near-infrared) technology capable
of imaging prefrontal cortex is available in small, light, and comparatively
unobtrusive packages (see, inter alia, Izzetoglu et al., 2011).
The second prong of this critique questions whether neuroimaging data
can predict population-level effects. Given the time and expense associated
with brain imaging, studies typically use as small of a sample as reasonably
possible, often on the order of 10–20 participants. Moreover, the extensive
use of convenience sampling from undergraduate participant pools calls into
question the generalizability of research across the social sciences (Henrich,
Heine, & Norenzayan, 2010). This is essentially an empirical question: do
the results of neuroimaging studies allow us to predict behavior at the
population level or not? Though it is impossible to provide a definitive
answer to that question in its general form, recent publications (Berkman &
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
Falk, 2013; Falk et al., 2013) have persuasively argued for a framework that
combines neuroscience with population science, emphasizing representative
samples, longitudinal analysis, and transdisciplinary collaboration. In one
notable example, the application of neuroimaging using a brain-as-predictor
approach doubled the explained variance in real-world health behavior
compared to self-report measures (Falk, Berkman, Whalen, & Lieberman,
2011). Falk (2010) suggests that the future may bring “neural focus groups”
whose brain imaging data are used to fine-tune persuasive messages. We
believe that the use of the brain as a predictor of real-world behavior will be
a crucial avenue of development for media neuroscience.
A final critique of media neuroscience is that neuroimaging data are
innately misleading, increasing the confidence that researchers are willing
to place in research, even when the results are counter-intuitive or even
apparently absurd. A well-known study by McCabe and Castel (2008)
contends that images of the brain in and of themselves make research
findings more persuasive to their audiences—the exact same data presented
in text or chart form carry less persuasive force, they argue, because images
exaggerate a bias toward reductive physicalist explanations. We object
to this critique on three levels. First, methodological shortcomings and
failed attempts at replication call into question the empirical validity of the
supposed “seductive allure” of brain imaging (Farah & Hook, 2013). Second,
many researchers show due restraint in presenting their results, hedging the
implications of their work when appropriate, and including images of the
brain only when they contribute information above and beyond what can
be presented through other means. Third, if such a bias does exist, its impact
should be dampened over time as more scholars become familiar with
neuroscience research and develop the experience necessary to critically
evaluate that research. If anything, then this critique should be seen as a
call for more and better neuroscience research, not the abandonment of
neuroimaging.
OUTLOOK FOR THE FUTURE
Though it is currently in its early stages, we anticipate that media neuroscience research will grow tremendously in the coming years. In this concluding section, we provide an overview of research areas that are likely to
be core to media neuroscience going forward and offer general guidance for
how we believe this research can be most successful. The task of predicting where innovation is likely to occur always involves inherent uncertainty,
and there are innumerable lines of study that could generate valuable knowledge. Nonetheless, based on recent interest as well as practical and theoretical
Media Neuroscience
9
value, we choose to highlight three major areas of research that seem likely
to remain on the cutting edge of media neuroscience.
First, the effects of violent media seem likely to remain a central vein
of research for the foreseeable future. As one of the longest standing and
most studied topics in media neuroscience, the literature on media violence
is already considerable. Yet development has continued in recent years,
expanding research to consider not only the details of brain mechanisms
that might underlie direct effects of violent media on aggression (Guo et al.,
2013; Porges & Decety, 2013) but also better explanations of how different
individual traits might mediate that relationship (Swing & Anderson, 2014;
Valkenberg & Peter, 2013), and how violence effects psychological states
other than aggression (Madan, Mrug, & Wright, 2014). Future work in
this area also should include further examination of the contested link
between aggressive cognition during exposure to media violence and
subsequent aggressive behavior. The use of neuroimaging data to predict
population-level behavior could be especially valuable in addressing that
important ongoing controversy.
Second, media neuroscience will continue to provide great contributions
to the study of persuasion. The high-stakes area of health communication
will likely play a major role here. Falk (2010) argued that the contributions
of media neuroscience would likely proceed in three parts: identification of
neural mechanisms underlying persuasive health messages, translation of
brain imaging data examining those mechanisms into sound predictions
about population-level behavior, and integration of those mechanisms into
theories of persuasion. So far, this progression is well underway. The use of
brain imaging data to make predictions about the real-world effectiveness of
persuasive messages is an emerging trend with tremendous potential (Falk
et al., 2011).
Third, we anticipate an increasingly close relationship between research
on narratives as a means of communication and research on the neural substrates of moral reasoning. Hasson and colleagues have produced a fascinating program of media neuroscience research that examines communication
as a process of brain-to-brain coupling (Hasson et al., 2004; Hasson, Ghazanfar, Galantucci, Garrod, & Keysers, 2012; Stephens, Silbert, & Hasson, 2010).
A separate line of research has examined the evolutionary basis of moral
intuitions (de Waal, 2013; Haidt & Joseph, 2004) and sought to identify the
neural mechanisms of morality (Graham et al., 2011; Mikhail, 2007; Parkinson
et al., 2011). Narratives can serve to communicate culturally significant moral
norms, and future research on media neuroscience is poised to better understand how moral content promotes synchronous brain responses and affects
the salience and popularity of narratives (Tamborini, 2011; Weber et al., 2006,
2007; Weber, Popova, & Mangus, 2012).
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES
The success of these research programs—and media neuroscience
overall—will demand innovation. Cross-disciplinary collaborations frequently suffer from differences in training and difficulties in communication.
Neuroimaging research requires extensive planning and resources. Without a culture of data sharing and replication, methods will be inconsistent,
predictions will be limited, and results will be uncertain. Students in communication and media science who intend to pursue this research will require
training that currently may not be available in many departments. Nevertheless, we believe that these challenges can—and ought to be—overcome
given the far-reaching benefits of media neuroscience research for revealing
how complex behavior emerges from dynamic processes in the brain.
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J. MICHAEL MANGUS SHORT BIOGRAPHY
J. Michael Mangus, MA, MBD, is a fifth-year PhD student in the UCSB
Department of Communication and member of the Media Neuroscience Lab.
His scholarly interests include group coordination, morality, and collective
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action; evolutionary and materialist approaches to communication theory;
and the philosophy of social science.
AUBRIE ADAMS SHORT BIOGRAPHY
Aubrie Adams, MA, is a PhD student in the Communication Department at
UCSB. She is interested in advancing media and computer-mediated communication research using neuroscientific methodologies. Her recent work
examines student perceptions of emoticons and her research has been featured on two top four paper panels at regional and national communication
conferences.
RENE WEBER SHORT BIOGRAPHY
Rene Weber, PhD, MD, is Professor in the Department of Communication at UCSB and lead researcher in the Media Neuroscience Lab
(http://medianeuroscience.org). His recent research focuses on cognitive
responses to mass communication and new technology media messages,
including video games. He develops and applies both traditional social
scientific and neuroscientific methodology (fMRI) to test media-related
theories.