Neuroscience and Biobehavioral Reviews 35 (2011) 2026–2035
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Neuroscience and Biobehavioral Reviews
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Rethinking the cognitive revolution from a neural perspective: How
overuse/misuse of the term ‘cognition’ and the neglect of affective controls in
behavioral neuroscience could be delaying progress in understanding the
Howard Casey Cromwella,∗, Jaak Pankseppa,b
aDepartment of Psychology and J.P. Scott Center for Neuroscience, Mind and Behavior, Bowling Green State University, Bowling Green, OH 43402, United States
bDepartment of Veterinary Comparative Anatomy, Physiology, and Pharmacology, College of Veterinary Medicine, Washington State University, Pullman, WA 99163, United States
a r t i c l e i n f o
Received 19 August 2010
Received in revised form 13 February 2011
Accepted 14 February 2011
a b s t r a c t
Words such as cognition, motivation and emotion powerfully guide theory development and the overall
aspects of the brain, their influence can be pervasive and long lasting. Importantly, the choice of concep-
tual terms used to describe and study mental/neural functions can also constrain research by forcing the
results into seemingly useful ‘conceptual’ categories that have no discrete reality in the brain. Since the
popularly named ‘cognitive revolution’ in psychological science came to fruition in the early 1970s, the
term cognitive or cognition has been perhaps the most widely used conceptual term in behavioral neuro-
science. These terms, similar to other conceptual terms, have potential value if utilized appropriately. We
argue that recently the term cognition has been both overused and misused. This has led to problems in
developing a usable shared definition for the term and to promotion of possible misdirections in research
within behavioral neuroscience. In addition, we argue that cognitive-guided research influenced primar-
ily by top-down (cortical toward subcortical) perspectives without concurrent non-cognitive modes of
bottom-up developmental thinking, could hinder progress in the search for new treatments and medica-
to human psychology may be better served by bottom-up (subcortical to cortical) affective and motiva-
tional ‘state-control’ perspectives, simply because the lower networks of the brain are foundational for
the construction of higher ‘information-processing’ aspects of mind. Moving forward, rapidly expanding
guide the development of new therapeutics and hopefully more accurate ways to describe and explain
© 2011 Elsevier Ltd. All rights reserved.
Using cognition to describe and explain...........................................................................................................
Affective states as essential ingredients for cognitive information processing...................................................................
How overuse and misuse of the cognitive concept may harm behavioral neuroscience.........................................................
3.1.Needless battles among conceptual categories............................................................................................
3.2.The perennial battles between top-down cognitive and bottom-up neuroscientific approaches........................................
3.3.Holistic integrative network models.......................................................................................................
3.4. The role of affective valuation and evaluation in behavioral control......................................................................
3.5.Affective implication for mental health and psychiatric disorders........................................................................
Ideas for the future.................................................................................................................................
∗Corresponding author. Tel.: +1 419 372 9408.
E-mail address: email@example.com (H.C. Cromwell).
0149-7634/$ – see front matter © 2011 Elsevier Ltd. All rights reserved.
H.C. Cromwell, J. Panksepp / Neuroscience and Biobehavioral Reviews 35 (2011) 2026–2035
This essay seeks to unpack some of the potentially invidious
consequences of overutilization of “cognitive” concepts in a cross-
species behavioral neuroscience that is currently an increasingly
trol animal behaviors. Cognition can be defined as processing of
sory portals. Although this definition and its various other usages
do not typically include the most robust underlying ‘CTM’ vision
of modern cognitivism – the pervasive Computational Theory of
Mind in cognitive science – ‘cognition’ is widely used as a moniker
for practically all the interesting functions the brain performs to
facilitate behavioral adaptations and survival. We believe this wide
usage leads to conceptual confusions, arising from the conflating of
diverse types of brain functions under a universal label that fails to
recognize critically important distinctions, especially when exam-
ining the biopsychology of attention, emotions and motivations.
We will not specifically focus on the CTM, but would simply
highlight that there are increasing reasons for concern about the
degree to which the brain should be envisioned primarily as a
“computational device” (Panksepp, 2009). Clearly, the brain has
global attentional, emotional and motivational “state functions” –
widely ramifying neuropsychological processes that are not easily
captured in either strict computational or cognitive terms.
1. Using cognition to describe and explain
faculty and, at times, to the general public. If the work is on brain
activity related to learning and memory using rodent models, stu-
dents may be tempted to state, “Lesions to the brain impaired this
means by the term cognitive. The student replies “Those mecha-
nisms involved in learning and memory.” The audience member
is still puzzled and wants to know, “Are there mechanisms that
do not involve learning and memory?” The student replies, “Well
as far as I know everything involves learning and memory at some
point.” The student feels justified and actually empowered because
his research has such broad implications (i.e., an inclusive “Theory
of Everything”). In addition, non-critical audience members may
be content with such simplified analyzes, and be at peace with
logical inference that everything (at least related to this seminar)
is cognitive. Of course, if they used food or shock to serve as the
be hard-pressed to defend that the BrainMind features of those
banner. And the few spectators from the humanities may wonder
why emotional feelings are never discussed, but the rest implic-
itly understand that such subjective terms were tossed out from
rigorous behavioral research a long time ago.
A second example: a group of faculty gathers at an intimate
international conference to discuss novel ways to produce and uti-
lize animal models of mental illness. The behavioral paradigms are
discussed as ways to reveal cognitive deficits seen in human “men-
tal disease” states. The animal’s behavioral impairments include
alterations in choice behavior, object recognition and in the abil-
ity to utilize time appropriately to manipulate the environment.
The discussion begins to approach the topic for ‘how these deficits
decides that terms such as working memory and attention need to
be refined and possibly standardized in order to make the ‘trans-
lational’ leap to human work. Another scientist inquires about
stepping back one more notch in the conceptual chain and asking
about ‘standardizing the concept of cognitive processes’. Perhaps a
courageous soul may raise the issue whether we should or should
not consider emotional-experiential concepts in our discussions.
No substantive attempt to reply to these issues is made, but the
mini-conference moves forward in search of animal models with
orders. “Face” and “construct validity” fall by the wayside. We have
seen such passages at meetings we have attended, with relatively
uli and unconditioned responses that are routinely used to study
practically all aspects of learning, memory and attention. Should
we also place these critical unconditioned processes, so essential
for all learning tasks, within the subset of cognitive phenomena?
on what appear to be internal affective functions of animal expe-
rience, rather than externally arriving information to be processed
into learning by the brain. Somewhere, someone surely ponders
whether the learning “glue” that is commonly called “reinforce-
ment” is just a word for the how endogenously organized brain
affective processes regulate learning processes?
These two examples demonstrate situations in which scien-
tists have used the terms cognition and cognitive to describe what
the brain is doing and to develop a model to guide biomedical
research development commonly related to psychiatric disorders.
The examples illustrate the fact that in some cases when the term
cognition is used, it is used to describe a large and diverse set of
psychological processes and in the second example, the term may
be used by different people, each usage meaning something sub-
stantially different. This is just a symptom of a larger problem in
psychology. As Kurt Danziger (1997) noted a while ago in his Nam-
such as attitudes, emotions, intelligence, motivation, perception
and personality, to name a few – do not represent “real” entities in
history of psychological science. Such categories can easily become
obstacles to progress, and it seems to us that the term “cognition”
is growing into a whale of a problem in behavioral neuroscience.
Despite the fact that there are serious problems of overuse and
misuse with each and every complex concept – from attention to
temperament, so to speak – the many socially constructed cate-
gories used in psychological research tend to bleed willy-nilly into
behavioral neuroscience. This review chooses to ‘pick on’ cognition
for several reasons. These include the fact that cognition is proba-
research environments of cognitive and social neurosciences, but
learn about social cognition and cognitive regulation of emotion.
Throughout behavioral neuroscience research careers, individuals
can develop a deep-seated yet nonproductive reliance upon a con-
ceptual term such as cognition, while most of the primary-process
nitions’ have no disciplined way to be linked to such a concept.
One key point of the current review is that we believe the
increasing dependence on the term cognition, along with its
common overuse and misuse, especially in the field of behav-
ioral neuroscience often skews discussions in unproductive ways.
This is especially the case when considering the primary-process
(evolved) aspects of the neural apparatus and functions that have
typically been subsumed by classical concepts such as primal
drives, emotions and motivations. Another important reason to
that include dynamic neural networking that constructs organis-
mic coherence and brain–body communication. Finally, we think
H.C. Cromwell, J. Panksepp / Neuroscience and Biobehavioral Reviews 35 (2011) 2026–2035
that the mapping of ‘cognitive disabilities’ in psychiatric disorders
often misplaces the focus of what is actually leading to the behav-
ioral impairments in these illnesses. For instance, in depression
research, it might be the case that the most important question is
“Why does depression feel so bad?” (see the contribution by Zell-
ner et al., in this issue). In human addiction research, it is being
realized that a key issue to consider is how various drugs influ-
ence the affective feelings of human beings (Kassel, 2010), Thus,
in preclinical addiction research, should not a key question also be
ings are alleviated by various drugs when individuals are already
addicted? When we begin to think in these terms, we must begin
to wonder whether there might not be more appropriate nomen-
clatures than some kind of a global ‘Brain Reward System’ which
remains au courant even though abundant alternatives have been
suggested (Berridge, 2004; Panksepp and Moskal, 2008). Should
the great variety of affective state changes, that certainly occur in
nitive problem? We think not, even though aspects of learning and
memory formation may deserve this umbrella term.
This review briefly summarizes the historical and current def-
initions of “cognitive” and then provides an overview for specific
research progress. Finally, we complete the review by providing
possible ways to overcome the misuse of psychological terms in
animal models that may be impeding the search for etiological
roots of mental illness. Animal brains contain a variety of affective
functions, and we need specialized terms for the ones that are rea-
sonably well established, for instance perhaps capitalizations for
the primary-process emotional networks – e.g., SEEKING, RAGE,
FEAR, LUST, CARE, PANIC/GRIEF, PLAY – concentrated in subcorti-
cal somato-visceral networks of the brain (Panksepp, 1998, 2005,
ilar nomenclature conventions to discuss homeostatic imbalance
(drive) states as well as a host of sensory rewards and punishments
routinely used to promote learning.
Cognition originated from the Latin terms ‘cogitos’ and
‘cognoscere’ both being verbs meaning ‘to think’ or ‘to know’.
‘Descartes’ famous ‘Cogitos ergo sum’ meaning ‘I think therefore
I am’ is prescient in many ways for the heavy importance we
place on knowledge acquisition in behavioral neuroscience. In con-
trast “I feel therefore I am” never caught on in human research,
when the conversation of the nature of mind was re-energized
forty some years ago after enthusiasm for behavior-only analyzes
diminished. The ‘Cognitive Revolution’ sprouted in the 1950s and
60s, and in the decade of the 70s, displaced radical behavior-
ism, by beginning to focus on themes of information-processing
and underlying BrainMind computations (Gardner, 1985; Neisser,
1967). It was especially influential in transforming psychology,
linguistics, anthropology, philosophy, not to mention artificial
intelligence/computer science. Using cognition as a core set of pro-
cesses that defined intervening variables involved in mental states
also became a vital part of the growth of behavioral neuroscience,
especially in learning-theory, with many of the perspectives of
an earlier physiological psychology (e.g., Grossman, 1969) seem-
ingly discarded. A focus on ‘cognition’ presumably enabled a better
appreciation for brain functions engendering psychological states
and learned behavioral productions. Other terms did not seem
to foster this psychological to neuroscience linkage as well as
“cognition” – functional terms such as emotions and motivations
– presumably because of their reduced emphasis on informa-
tion processing (learning and memory) and their seemingly more
diffuse phenomenological relationships to central nervous sys-
tem activities (Richter, 1947). However, this left critical issues –
namely how the foundations of the BrainMind were constructed
early in brain evolution – little discussed in the behavioral neuro-
Prior to the formal advent of the Cognitive Revolution in the
1970s (Gardner, 1985), cognition was used mainly to denote a
sensory process that transformed input via perception to the gen-
eration of higher-order concepts (Heidbreder, 1945) or arrange
belief-value systems (Tolman, 1952). The utilization of sensory
inputs in the service of learned behavior patterns, in order to
engender adaptive behavioral strategies, was at the heart of many
definitions of cognition. However, the new, over-reaching TOE
concept has engendered a back-lash from certain leaders (e.g.,
Fodor, 1998) who have more recently focused on how traditional
human-centered cognitive science went wrong because of the
ways concepts are studied and inferred from other mental rep-
resentations. Still, Fodor hung on to the traditional computational
not explicitly acknowledging how ineffective that strategy might
be for elucidating more global, and more endogenous, informa-
tionally open-ended, BrainMind “state-control” processes such as
The term cognition also becomes difficult to tease apart from
the term perception, not to mention, as we will discuss, concepts
such as emotions and motivation. If cognition subsumes all of this
tinctions that need to be made. Neisser (1967, p. 6) provided this
view clearly “Whatever we know about reality has been mediated
pret and reinterpret sensory information ... The term ‘cognition’
refers to all the processes by which sensory input is transformed,
reduced, elaborated, stored, recovered and used.” At the heart of
how behavioral neuroscience has adopted the term is the idea of
computation and information processing, with a heavy reliance on
the important mental processes of life time learning and memory,
are built into our brain by our genetic heritage.
The cognitive neuroscience approach as detailed by Kosslyn
and Andersen (1992) is a three-pronged approach that includes
neuroscience, experimental psychology and computer science. The
textbook has five main sections that include (1) vision, (2) audi-
tory and somatosensory systems, (3) attention, (4) memory, and
reasoning. A more recent textbook, typical of one used by behav-
cognitive neuroscience as “investigations of all mental functions
that are linked to neural processes, ranging from investigations in
animals to humans and from experiments performed in the labo-
ratory to computer simulations” (Banich and Compton, 2011, p. 2).
Another new textbook by Baars and Gage (2010) emphasizes the
link between cognition and consciousness with cognitive neuro-
science including all the studies of the biology of the mind. Having
cognition be the sole purveyor of consciousness has been hotly
debated because computations can easily be shown to be com-
pleted without an intentional or conscious process (Searle, 1992)
and other psychological processes (e.g., affect) have been proposed
to have their own level of consciousness, one that can be separable
from the cognitive conscious process or even be dominant over the
cognitive outputs (Panksepp, 1998; Damasio, 1994).
These definitions and descriptions of ‘cognition’ highlight some
of the problems pervasive in the ways we think about complex
concepts. One major problem is the fact that many investigators
rely on one major concept like cognition to include everything. For
thought, whether conscious or unconscious, enters virtually every-
thing we do; we use it to pilot our lives and to be responsive to
feedback from the environment that could be relevant for survival”
H.C. Cromwell, J. Panksepp / Neuroscience and Biobehavioral Reviews 35 (2011) 2026–2035
(Richard Lazarus in Emotion & Adaptation p. 6). If cognition is pro-
vided this ubiquitous property, then it is a valid question to ask
what is the use of other psychological terms and what is the essen-
tial nature of a process that allows brains to be cognitive.
An alternative, data based view is that there exist a series of
ancient ‘state-control’ processes that deserve a more explicit con-
ceptual focus and research strategies that are in short supply in
cognitive science. For instance, internal affective processes surely
deserve to be brought to the forefront of thinking when we con-
sider the nature of decision making and ruminative thoughts. In
other words, the concept of ‘cognition’. even when used with
restraint, often remains untethered to the evolved ‘animal nature’
of our mind. As noted by an anonymous reviewer of this paper
“the promiscuous use of that word is a mere symptom of the
fact that so many theorists are seduced by the computational
model” which cannot be the whole story. Clearly, we also con-
neuroscience, which demands that we rethink our central theoret-
ical categories, and recognize that various bottom-up evolutionary
nitive processes. Although another reviewer of this paper noted
that we could also argue that the “bottom-up and top-down
dichotomy may be more related to us as observers and our lim-
ited capacities than to the brain itself.” This reviewer continued
that such a “dichotomy may be simply irrelevant” for brain func-
tioning “...being of methodological rather than neural origin.” We
where the more ancient functions are more medial and caudal in
the neuroaxis, but certainly interpenetrant with the more recently
evolved functions, which are generally more lateral and rostral.
Such brain organization suggests both robust bottom-up and top-
down nested hierarchies of neural regulations and controls (for
further elaboration of this point see Northoff et al., in this issue).
We would suggest that what is desperately needed are disci-
plined ways to distinguish cognitive from the many unconditional
making sense of what organisms do. One possible way to parse the
cognitive and many other brain processes is in the way they are
linked to incoming information from the external world (‘channel
functions’ as Marcel Mesulam (2000) called them), and the many
ways evolution prepared the brain and body to respond to the
exigencies of survival (the brain–body ‘state functions’ as distin-
psychologically meaningful within-brain functions (e.g., attention,
over their psychological functions than the external information-
linked channel functions of the brain (e.g., specific perceptions,
up distinction is in terms of the many conceptual distinctions
that can be made between the affective and cognitive aspects
of BrainMind functioning (see Table 1; Ciompi and Panksepp,
2004; Panksepp, 2003), with most primary-process affects (see
Panksepp’s lead essay in this issue) having a much deeper neu-
roevolutionary history than most cognitions.
cesses and our cognitive interpretations of events of the world
are massively blended (Lane and Nadel, 2000; Pessoa, 2008), and
in brain evolution, the complexities of the cognitive apparatus
many hierarchically embedded emotional and motivational state
functions that are initially unconditioned tools for living but can
rapidly become parts of classical- and operant-conditioning exten-
sions of the basic unconditional organismic abilities. These distinct
aspects of the brain differ in various characteristics that highlight
Some conceptual distinctions that can be made between the affective and cognitive
aspects of BrainMind functioning. These distinctions enable a separation between
these psychological processes. The distinct properties include neural and functional
processes that can guide how behavioral neuroscience research is completed and
used by others to develop new directions in the field.
Affective processes (values) vs. Cognitive processes (information)
Less computational (analog)
Action to perception controls
(e.g., more neuropeptidergic)
More computational (digital)
Perception to action controls
(e.g., more glutamatergic, etc.)
how insufficient the guiding metaphor of cognitive science may be
for understanding the brain. It is more than just an information-
processing device. The above distinctions are not well represented
in cognitive science, and we suspect that it is for this reason that
some of the esteemed fathers of computational cognitivism are
sharing their concerns that there is something profoundly miss-
ing from their information-only models of mind. In short, as Jerry
as already noted, Fodor did not back-down at all on the utility of
information-processing models of mind. We have no quarrel with
information-processing as being key to higher cognitive functions,
but we do not see it as a good descriptor of the evolutionar-
ily intrinsic primary-process affective functions. Attention, affects
and bodily drives, as well as hedonic responses to certain sen-
sory inputs, are largely inherited brain processes (Berridge, 2000;
Panksepp, 1998). As an example of the weakness of ‘pure cogni-
tivism’ we will briefly develop the more affective and motivational
view of mind that is essential for cognitivism to have a firmer
evolutionary ‘center of gravity’ around which animals abundant
information-processing revolves. However there are deep histori-
cal resistances within cognitive psychology for a fuller integration
with our animalian past.
2. Affective states as essential ingredients for cognitive
For the past three centuries, two views of mind have been vying
for supremacy. One view sees the conscious human mind as arising
from the brain’s symbol-manipulating abilities, not that dissimilar,
in principle, from modern computers. If that view is fundamen-
tally correct, then mind can be recreated through our ability to
fathom the underlying computations, and we should be able to
re-instantiate mind on non-biological platforms, such as digital
computers, that can perform the needed calculations (i.e., suppos-
cal cognitive-computational view, mind is independent of the type
of device on which the relevant information is processed, and we
should be able to construct minds symbolically without knowing
the details of brains. Of course, there is also the more moderate
school of “embodied cognitions” (e.g., Wilson, 2002) that strikes us
as one way in which affective and cognitive issues can be organ-
ically integrated, especially if one recognizes how the brain was
evolutionarily organized to control and regulate bodily functions.
science (Panksepp, 1998) that seeks to see BrainMind organization
from a very explicit bottom-up vantage, without any attempt to
marginalize developmentally emergent top-down controls.
In any event, adherents of computational neuro-mathematical
idealism in cognitive theorizing remain enticed by the possibil-
ity that minds are created “merely” from the capacities of brains
to process symbolic codes. Some extreme views of this type envi-
H.C. Cromwell, J. Panksepp / Neuroscience and Biobehavioral Reviews 35 (2011) 2026–2035
evolutionarily designed to extract important features such as
“chairness” from environmental stimuli that allow us to recognize
the infinite diversity of chairs in the world. According to certain
cognitive views, the capacity of the brain to generate Higher Order
Thoughts (HOTs) is a cardinal feature of consciousness (Matey,
2006; Rosenthal, 2002). Within that worldview, the capacity for
subjective phenomenal experience may, in fact, be largely unique
primates. This has long been a prevailing, if not predominant, view
in cognitive science. Of course, it is becoming clear that if we do not
deal with animal emotions, we will never understand their minds,
or for that matter, our own (Panksepp, 1998).
The minority position, ever increasing in influence, is a more
“embodied” organic view, which accepts that minds are integrally
linked to brains and bodies as well as the environments in which
they operate (Smith and Gasser, 2005). In this view, infants are
and explore and to affectively engage their environmental circum-
type of “naturalism” believe that we learn concepts such as “chair-
places in the world where we can rest our sometime weary bodies.
We learn language in part through our engagement with the ‘musi-
cal’ prosody of emotional sounds, allowing our affective-emotional
nature to promote language acquisition (Panksepp, 2009, 2010).
In the social realm, we learn to negotiate emotional complexi-
where we mutually create the social texture of our lives through
our ability to blend our affective desires with those who care
about us. This view acknowledges the deep nature of our sense
of agency, and our primordial desire, present in a rudimentary
form at birth, to live life actively as opposed to simply being
molded, as some still believe, by the ever-present reinforcement
contingencies of the environment. In this view, nature has given
us many tools to explore and confront the world and our capac-
ity to experience affect informs us about what is good, bad and
neutral in our environments. These feelings help guide our life
In this view of mind, the capacity of the brain to generate affective
feelings is the source of behavioral reinforcement and the primal
source of consciousness – capacities we share with many other
animals. In this view the efficacy of “rewards” and “punishments”
in establishing learned behavioral control is based fundamentally
on affectively guided learning processes, rather than just presently
poorly specified “reinforcement” processes, which is largely a con-
cept that covers over a great deal of our ignorance about how
lower brain affective processes help regulate higher brain func-
tions. Thus instead of ‘reinforcement’ creating emotions (Gray,
1990), affective-emotional changes may promote the process of
reinforcement (Panksepp, 1990).
Of course, to be fair to computationalism, robotic researchers
have recent returned to building more embodied insect-like archi-
tectures, and they are finding that when they in fact build in
some basic emotional and motivational systems into their “bugs”,
many of the perennial problems of artificial intelligence engineer-
convergences on basic life principles.
We also need to recognize that organismic BrainMinds are
fully embodied, unlike digital computers, and the internal states
of both body and brain are more than just informational con-
tent, but the substrates that create the coherence of organisms
“movie in the head.” Further, the “situated cognition” perspective
has informed us that much of animal intelligence is not simply an
intrinsic brain function, but also an outcome of dynamic percep-
tual linkages to ‘information’ already existing in the external world
(Gigerenzer, 2008; Makin et al., 2008). Likewise, it would be wise
to recognize that the brain’s potential for generating core affective
values, are not simply related to the objects of the world, but arise
substantially from inherited brain activities that allow us to be in
the world as coherent creatures (Panksepp, 1998, 2005). One of
the critical keys to MindBrain understanding that will not be pro-
vided by cognitive perspectives is why our bodies and our worlds
affectively feel the way they do.
Because of a vast neglect of affective-emotional processes dur-
ing the recent “cognitive revolution” (Panksepp, 1988) one of the
greatest remaining mysteries of the BrainMind is the fundamental
nature of affective experience. How do mental functions arise from
the higher order complexities of a fundamentally physiochemi-
cal world? How is it that animals experience the world in terms
varieties of good and bad feelings – in terms of ‘rewarding’ and
‘punishing’ brain and world events? Cognitive science has largely
remained silent about the many positive and negative feelings that
there is still much resistance to discussing or discriminating the
many distinct types of affects that help organisms control survival-
promoting behavioral outputs.
As far as certain lines of brain research inform us, certain
feelings of pleasure, pain and displeasure arise from our sensory-
perceptual connections with the world (Berridge, 2000; Young,
1959) and from neural sensing what is happening within the
body (Denton, 2006). There are yet other core affective feelings,
from RAGE networks that can promote anger to PLAY circuits
that can promote playful joy, to LUST filled sexual systems and
those that promote nurturant CARE as well as separation-distress
(PANIC/GRIEF). Unconditioned FEAR circuits may be essential for
fear conditioning, and the entire array of distinct emotional cir-
cuits link to general purpose SEEKING networks that allow animals
and humans to avoid harm and to harvest all the environmental
rewards needed for survival (Panksepp, 1998, 2005). Affective feel-
and affective body-sensing abilities of our brains interact with our
perceptions of the world. It would be a categorical error to call
the intrinsic primary-process affect of the brain ‘cognitive’. These
are fundamental “states” of mind that guide and regulate cognitive
Since such issues appear to be under-appreciated (perhaps
largely because of historical forces that are rarely openly dis-
cussed: the animal mind seems scientifically inscrutable), let us
re-emphasize: There are many distinct types of primitive affec-
tive experiences some linked to sensing the fruits and dangers
of the world (e.g., the pleasure of taste and the pain of bod-
ily injury), and clearly the affective and informational aspects of
such systems diverge at the thalamic level, with the affective
tone being integrated by subcortical neural functions while the
informational (cognitive) aspects are more dependent on thalamo-
cortical channel controls (Norgren, 1984). Some organic feelings
are related to homeostatic states of the body (hunger and thirst,
and their satisfactions) (Denton, 2006), while yet others seem to be
how such affective feelings are created in human brain, we have
no obvious empirical strategies other than to study correspond-
ing, evolutionarily related processes in animal models (Lieberman,
2007; Panksepp, 1998, 2005) This makes behavioral-affective-
social neuroscience an integrated discipline that has to consider
many non-cognitive aspects of both unconscious and experienced
mental processes. Behavioral neuroscientists should finally relax
their traditional guard against psychological concepts, and accept
that without the blending and integration of distinct cognitive,
affective and motivational perspectives, we cannot generate a
H.C. Cromwell, J. Panksepp / Neuroscience and Biobehavioral Reviews 35 (2011) 2026–2035
coherent understanding for brain control of organismic actions.
‘Cognitive’ and learning concepts alone will not suffice.
3. How overuse and misuse of the cognitive concept may
harm behavioral neuroscience
The previous sections highlighted ways in which cognition is
used and gave examples with definitions and potential defining
organisms as they truly are. An attempt was made to illustrate the
potential by using these definitions or set of properties to ‘overuse’
the term meaning over-extend the concept in order to have it
be all inclusive related to behavioral neuroscience goals. When
this occurs there can be a dramatic decrease in the worth of the
term because it becomes the same as the ‘study of brain-behavior
mechanisms’ – a shorthand way of saying something very general.
Likewise, ‘motivation’ is not a specific, single brain function but a
ily constancies as well as the shifting responsivities/sensitivities
of sensory systems that are linked to bodily needs. Using gen-
eral overarching conceptual terms is not necessarily harmful and
can surely boost communication and progress, if there is con-
sensus about what the terms actually mean. Our examples and
many key human experiences lead us to another view concerning
the debate among behavioral neuroscientists about what cognitive
and we suggest how the various types of brain functions should be
categorized and parsed to enable each concept to play a clearer and
more distinct roles in our visions of how brains produce minds and
Another harmful characteristic besides overuse of cognitive ter-
different types of misuse: These include (1) relegation of a minor
or subordinate role for other conceptually distinct psychological
processes; (2) an over-reliance on the framework of ‘top-down’
processing to define how evolutionary levels of brain function
interact; (3) Missing aspects of integration and an excessively
holistic approach to understanding the causal factors underlying
behavior; (4) Reducing the important influence of the properties
of brain affective outcomes in energizing and guiding behavior; (5)
Diverting attention away from brain-behavior relationships which
may constitute the core of the affectively imbalanced states and
impaired interpersonal relationships that characterize mental ill-
ness. Let us consider each of these in turn.
3.1. Needless battles among conceptual categories
One side effect of the tremendous emphasis on cognition and
cognitive functions has been the neglect of other concepts used to
as affects, emotions and motivation, once widely used in behav-
ioral science and psychology, need to be restored into the balanced
curriculum of behavioral controls. Emotion and affect have only
recently been seriously entertained, with increasing acceptance, in
2011). Despite the resurgence of psychological terms such as sen-
sory, emotional and homeostatic affects as a way of explaining
brain-behavior relationships (Berridge and Cromwell, 1990), there
remain the urgent problems concerning the manner in which cog-
nitions can be thought of as overriding thought-related process
that control the more basic, and with ontogenetic development,
increasingly subordinate processes. In our view, the bottom-up
view that emphasizes affective-emotional processes is a key to
early development, while the top-down view that emphasizes top-
down processes, provides us a richer view of adult mental life.
Much research is focused on regulation of emotion by cognition
and how inhibition of emotional behaviors is moderated by a cog-
nitive gating mechanism (Ochsner and Gross, 2005). Another way
of thinking about a function such as gating might be that there are
qualitatively different levels of gating that occur that include both
‘affective-emotional gating’ and ‘cognitive gating’ with no level
being more dominant than the other (Cromwell et al., 2008). Our
recent work demonstrating that inhibitory gating circuits related
sensory inputs is pervasive and located in established neural net-
works of emotion has supported this latter idea (Cromwell and
Woodward, 2007; Cromwell et al., 2007, 2005; Mears et al., 2009).
Of course, a case could be made that the above affect-emotion
focused research can be simply deemed to be an extension of
cognitive neuroscience (e.g., Lane and Nadel, 2000). For instance,
the vast amount of research focusing on emotional conditioning
(LeDoux, 1996) could be viewed as a ‘cognitive’ learning approach,
but much of this work could be improved by focussing on the con-
trol functions of the primary process emotional states themselves
(Panksepp, 2004), rather than just leaving them in a broad cate-
gory of unconditioned responses. For instance, it is possible that
the unconditioned responses (i.e., instinctual emotional arousals)
are critical for FEAR conditioning to occur in the amygdala.
The link between conditioning and cognition is powerful and
has been suggested to be an important cognitive process shared by
diverse organisms with clinical implications (Pickens and Holland,
ing was also major components of motivational theories of animal
and human behavior (Toates, 1986; McClelland, 1987). Thus, we
must welcome conditioning research that recognizes the vital con-
tribution of motivational and emotional mechanisms involved in
how animal’s learn to revalue stimuli following experiences with
cues that predict new affective outcomes (Dickinson and Balleine,
3.2. The perennial battles between top-down cognitive and
bottom-up neuroscientific approaches
issue, one that may have broad implications when attempting to
decipher new results of functional connectivity or activity coher-
ence of neural activity (Ochsner et al., 2009). This issue involves
‘top-down’ and ‘bottom-up’ directions. The bottom-up framework
has been extremely useful is building models of communication
networks and has provided useful insights into the important
processes involved in attention, learning, memory and other infor-
mation processing functions (Grossberg, 1999; Decety and Meyer,
2008). Thus, the bottom-up perspectives are not well accepted
by individuals involved in cognitive neurosciences and it is not
deemed a bona fide requirement as part of a cognitive model of
brain function where emotions are often largely envisioned in cog-
nitive terms (e.g., Lane and Nadel, 2000; Pessoa, 2008).
In our estimation, it is unwise to partition the models of mental
(and neural) function into just top (dominant) and down (sub-
ordinate) aspects as if these relationships are strong and static
(and persistent in the life-course). This type of implicit or explicit
top-down perspective is probably not useful in many cases, espe-
cially in realistic views of organismic maturation, and may actually
harm the development of more realistic models that incorporate
dynamic properties and bidirectional interactive multi-way com-
munications (Cisek and Kalaska, 2010). Recent data acquired using
multi-site single-unit recording or from broad neuroimaging tech-
niques supports the ideas that neural activity flows into multiple
regions and there is great overlap in terms of event-related activ-
ity in a broad range of neural regions (Woodward et al., 1999;
Gutierrez et al., 2010; Chow et al., 2009). It is probably fair to say
H.C. Cromwell, J. Panksepp / Neuroscience and Biobehavioral Reviews 35 (2011) 2026–2035
that the evoked consequences of many sensory signals (e.g., vision)
can be monitored, to some extent, in every region of the brain. The-
orists that take a more integrative approach to behavior such as
hunger and feeding have proposed that the neuroaxis communi-
cation is highly dynamic and bidirectional (Grill and Hayes, 2009;
Berthoud, 2004). It is hard to imagine it otherwise in any realistic
functions to operate.
3.3. Holistic integrative network models
Another key issue, highly related to previous one, is the need
to incorporate diverse factors into any model that provides possi-
bilities for interactions between the brain and other parts of the
nervous system. The ‘Neuron Doctrine’, important as it is, does
not yet allow us robust linkages to global brain and behavioral
functions, which require ‘Network Doctrines’ which recognize the
specializations inherent in certain neural pathway functions. Like-
wise, a holistic body-inclusive approach toward behavior should
include other systems besides the nervous system, in order to get
more accurate and useful integrative views than any limited men-
tal or brain model. The role of the body in emotional control is
generally well recognized (Fosha, 2009) but not as well studied,
and one has to see various psychological functions to have inte-
grated brain and bodily components. For instance, in the emerging
field of affective-fatigue studies, it is being recognized that there
are peripheral fatigue factors as well as central ones (Roelands and
In general then, cognition has been a conceptual term, often
limited by primarily focusing on the conceptual nervous system to
develop mental models of behavior. Other terms such as emotion
or motivation have made attempts at holistic approaches but have
been historically linked to specific aspects of general physiology,
peripheral signal transduction and homeostatic systems (James,
1894; Cooper, 2008). Extending explanatory concepts so that they
naturally include multiple systems will obviously enable more
complete explanations. For instance, recent work in the fields of
psychoneuroimmunology or psychoneuroendocrinology supports
the clear importance of understanding how immune cell signals
or hormone levels could be important parts for why behavior is
directed to potential outcomes. (Nelson, 2005; Graham et al., 2006,
2009). Cognition is not the term that naturally incorporates these
diverse systems and by restricting our explanations to cognitive
processes, there could be an undesirable neglect of such important
bodily variables not only in our modeling of mental ‘disorders’ but
also cognitive activities.
3.4. The role of affective valuation and evaluation in behavioral
The fourth area of misuse deals with the neglect of affec-
tive outcomes (or the various ‘rewarding’ and ‘punishing’ feelings
that exert behavioral control in both humans and animals) along
with their potential predictive properties in cognitive models.
Recent behavioral neuroscience work has shown that neural
activity in diverse brain regions encode and potentially utilize out-
come information (Watanabe et al., 2007; Cromwell and Schultz,
2003; Hollerman et al., 1998). The incentive motivational theory
of behavior combines incentive properties with a diverse array
of other properties including internal state information (Toates,
This type of diverse model that describes factors involved
in the production of behavior allows for the outcome and its
expectancy to be powerful mediators of choice behavior and goal-
directed action. Cognition with restricted emphases on sensory
transformations of input have relied primarily on higher-order
information-processing to associate and create a decision, while
the affective outcome has too often had a minor role in many
of these models (Taylor, 2004; Pitt et al., 2002). New areas of
study that include neuroeconomics have proposed novel ways
to incorporate incentive processing, yet they are commonly lim-
ited because of the neglect of affective state influences (Glimcher,
3.5. Affective implication for mental health and psychiatric
The final proposed misuse has significant implications for
biomedical research and the search for appropriate animal mod-
els of mental illness. Mental disorders have a broad spectrum of
symptoms that include alterations in learning, memory, attention,
emotion and behavior (DSM-IVR). The multitude of symptoms has
made it very difficult for professionals to agree on exact diagnos-
tic criteria and the relative importance of different symptoms. We
have previously made the case that it is imperative to focus on the
core neuro-emotional alterations in psychiatric illness (Panksepp,
tions such as learning or memory will not be enhanced. What are
these core processes? It is proposed that they are primary process
1998, 2004). This misuse of the term cognition can misdirect us
in the search for core affective symptoms of psychiatric disor-
ders as well as in that kind of translational approaches behavioral
neuroscience should take in attempting to discover new ways to
et al., 2011).
A most serious drawback of global use of cognitive terminology
may be that it restricts the development of potentially more use-
ful psychiatric models and may retard medication development in
harmful ways. For instance, in areas such as feeding research, a
focus on affective properties of appetite reducing drugs may be of
2010c). Many of these issues were highlighted in a recent overview
of current problems with research that is attempting to better cat-
egorize psychiatric disorders (Hyman, 2007). Steven Hyman, the
that the vast gaps between neurobiological and clinical approaches
to understanding emotional disorders remain enormous. Mani-
festing a cognitive bias, he suggested they arise largely from (1)
“the difficulty of characterizing the circuitry and mechanisms that
underlie higher brain functions” while failing to note that many
emotional difficulties may arise from imbalances in lower affec-
tive functions. He highlighted the evident (2) “complexity of the
genetic and developmental underpinning of normal and abnormal
behavioral variation” that prevents integration between diagnos-
tic labels and brain problems (a serious problem indeed, if one
does not consider the emerging bottom-up emotional features),
tal disorders” which we believe will remain the a case as long as
the underlying affective ones.
Still, Hyman recognizes, as should all of us, that practically all
the major advances in medicine have relied on the insightful use of
animal models to ferret out the biological sources of disease, and to
evaluate new potential therapies before they are used in humans.
Just consider the first modern medicine, insulin, introduced by
atic insulin production in canine models of diabetes, they rapidly
demonstrated that insulin supplementation could reverse the dis-
ease process. This knowledge rapidly saved and continues to save
millions of children who would otherwise have died prematurely.
H.C. Cromwell, J. Panksepp / Neuroscience and Biobehavioral Reviews 35 (2011) 2026–2035
of current animal models of mental disorders” is poignant from the
context we have been exploring here. Most of these models have
explicitly failed to even consider the changes in primary-process
emotionality that have long been waiting in the wings to be used
in preclinical research (Panksepp, 1998).
4. Ideas for the future
tive, cognitive and social neurosciences) is bright and there has
been abundant growth and success in diverse research endeav-
ors. Thinking about the brain and using terms such as cognition
and cognitive has certainly fertilized useful discussions in the field,
and has fostered understanding of memory formation and learn-
ing processes and how the brain can in some ways function like
a computing device (Berger et al., 2010). This progress is indebted
to the results of cognitive science and how various information-
brain activity. Now there is general acceptance for brain func-
tions as intervening variables that influence all behaviors, and a
mere input–output analysis is no longer sufficient. Indeed, some of
the evolutionarily designed “output” functions such as integration
of emotional unconditioned responses, may be more involved in
learning than most assume. Thus, it is periodically useful to reeval-
uate the ways we describe the factors that influence behavior in
order to promote major leaps forward in the conceptual infras-
tructure of behavioral neuroscience. A review of these ideas and
how cognitive concepts are currently used illustrate possible road-
blocks that could be envisioned as overuse and, at times, misuse.
Discussing these issues openly may provide greater clarity, cross-
disciplinary integration, and more effective research in general.
One path to change is a better recognition of how we use the
the idea of cognitive processing it may be now appropriate to
begin using narrower definitions, and better descriptions of pro-
cesses that actually exist in brains rather than relying too heavily
on concepts handed down to us from a pre-neuroscientific past.
Philosophy has endeavored to discuss broad versus narrow defi-
nitions for cognition – for instance, Green (1996) has argued that
cognitive is not as ambiguous as popularly thought and that the
term can be used in a rigorous fashion, as long as one is clear
about the domain of usage. His strict meaning is related to ethics in
philosophy and truth-evaluableness; this way of thinking harkens
back to the early usage of the term in psychology when belief
systems and value were part of a larger cognitive-emotive sys-
tem (Tolman, 1952; Asch, 1952; Festinger, 1957). Such a narrow
definition, based on the philosophical study of ethics, may not
be easily translated and applied to behavioral neuroscience, but
other narrower views of what cognition should be deemed to be,
could provide useful advances in conceptual clarity. For instance,
it has been proposed that cognition does not involve all infor-
mation processing but involves that information processing that
includes primarily flexible behaviors as an output (Greene et al.,
2004). This stricter vision of what cognition means entails a more
constrained vision of how cognition accesses and enables differ-
ent output paths to behavioral flexibility. Another way to develop
a stricter definition is to develop in parallel, definitions for related
psychological concepts. Previously, many researchers have divided
the mental/psychological space into those processes that are cog-
nitive and those that are affective. This partitioning could be made
more clear and take into consideration the various types of affects
(e.g., emotional, homeostatic and sensory), highlighting both the
overlapping and non-overlapping associated processes, that can be
dissociated and can interact (Ciompi and Panksepp, 2004).
Another important factor in the move toward a greater consen-
sus will be to use the information that the neural and behavioral
data provide to guide the development of terms and concepts
that come into general use. Novel methods involved in neural
and behavioral analysis have already uncovered the important
ways that functional connectivity can be understood (Sadaghiani
et al., 2010). Using higher resolution neuroimaging and more spe-
cific ways to probe multiple regions of the brain during behavior
(Pennartz et al., 2009; Goonawardena et al., 2009; Sanchez et al.,
2005) will open up new ways to think about how the brain com-
municate between regions and how it incorporates signals from
other systems. These new methods or new ways of using older
techniques may not be best described in older conceptual terms.
of a terminology that explicitly seeks to do that is the utilization
of capitalized vernacular terms for labeling the primary-process
emotional-affective networks of the brain – e.g., SEEKING, FEAR,
RAGE, LUST, CARE, PANIC/GRIEF and PLAY (Panksepp, 1998, 2005).
This can help minimize confusions with the vernacular meaning
of such words, while retaining the heuristic-generative aspects of
language needed for making novel predictions.
This review does not end with a the pronouncement of any new
term or terms in this regard but concludes by stressing the need
for a rethinking for the words that we use and how valuable and
harmful they can be depending on how well, and clearly, we use
them. For some, this argument may be about semantics or linguis-
tic development but the debate will be important not only for the
language chosen but what we actually mean by the words we use
to describe the complex relationships between body, brain and the
world, both genetically and epigenetically molded. Progress can be
promoted and new directions created if we find agreeable ways to
share language use patterns in ways that match the complexities
of the BrainMind functions we are privileged to study. Operational
Circle, were a great advance in establishing agreed-upon rules for
describing how we measured things in which we were interested.
Better agreement upon conceptual definitions, much harder to nail
down among all interested parties, are now needed to advance sci-
we ever expected. And if such projects succeed, we may even even-
occurred in the brain, as we know how well the procedure of ‘rein-
forcement’ allowed learning and cognition research to flourish in
5. In sum
Disparate views of mind have been battling for primacy ever
since Descartes divided mind and body, while his younger con-
temporary Spinoza pursued a rear-guard action, urging a more
unified, fully embodied view. Our goal in this paper has been
to promote such a rear-guard action that may better envision
the complexities we must face in order to understand the mam-
malian BrainMind, not to even mention the diverse ways of other
species. We feel confident, that our more recently evolved neu-
ral spaces for higher-order cognitive-conceptual abilities of an
expansive neocortex remain profoundly anchored to more ancient
affective state-control processes of the brain. Rather than having
top-down or bottom-up perspectives seeking to prevail over each
other, it is time to synthesize the best of each approach to bet-
ter understand how the whole BrainMind is integrated into an
adaptive-anticipatory organ that it is (for a fine development of
this theme, see Northoff et al., in this issue).
H.C. Cromwell, J. Panksepp / Neuroscience and Biobehavioral Reviews 35 (2011) 2026–2035
To do this well, we cannot leave the affective feelings of other
animals out of our discussions and cognitive equations, difficult
as they may be to study compared to learning and memory.
Convergent evidence indicates they are evolved processes of all
mammalian brains. To achieve a more integrated understand-
ing, we do need to parse brain and mind functions into various
affective, attentional, cognitive and motivational processes, and to
study how they interact. Just as many of us consider how ancient
forms of simple learning (classical and operant conditioning) were
antecedents for more recent cognitive developments, all of which
remain grounded in diverse earlier solutions that have been glob-
ally called unconditioned stimuli and responses – brain processes
essential for learning and more subtle higher cognitive processes
such as decision making – that have not received the experimental
attention they deserved in behavioral science.
Thus, our goal here was to facilitate a discussion that esteemed
neuroscientists have long recognized as problematic in our field.
Perhaps no one has said it better than Gyorgy Buzsaki (2005, p.
828): when he concluded from his studies of hippocampal theta
oscillations “that our behavioral-cognitive terms are simply work-
ing hypothetical constructs that do not necessarily correspond to
research is to reveal how the brain generates behavior..., most
behavioral-cognitive research, to date, seems to work in the oppo-
site direction. We take a man-created word or concept... and
search for brain mechanisms that may be responsible for the gen-
eration of this conceived behavior.” Thus, we have a long way to go
before we develop a lexicon that corresponds to the true functional
organization of the mammalian brain.
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