A system of ten parts in three movements. Ten agents improvise the ten parts at will through the interpretation of the diagram. Should be around 3 minutes. Agents can be musicians, harmonic or rhythmic components, sound grains, cells, or whatever. Whatever you want. Peptine.

Thesis continues:



When discussing the brain, neuroscientists modulate between expertise and simplicity. Their own topic of study-be it a neural nucleus, the biochemistry of bipolar disorder, the blood flow in brain structures during social behavior-is subject to rigorous and rich amounts of detail. Yet the areas on which the neuroscientist's expertise fails to cast light are numerous and present many interesting implications. I asked each of my participants about how they conceive of and think about the brain as a whole. Their responses were divergent. Some spoke freely about the brain, willingly exploring their conceptions of its totality without reservation. These researchers present a holistic approach. Others were careful not to stray far from their expertise. These individuals, the atomistic researchers, believe that moving too far away from their objects of research decreases their capacity for making meaningful statements. Yet, in their responses, both groups employed a nearly identical array of conceptual metaphors, consistently making sense of the concept of the whole brain in terms of other concepts. The conceptual metaphors referenced most often (and that form the basis for discussion in this section) include: brain-function localization and behavior, the brain as computational circuits, the integrated and irreducibly complex brain, and the brain as a mirror. The following analysis will explore the similarities and differences in the use and understanding of these metaphors in order to isolate certain implicit beliefs used in the neurosciences.
The constituent members of the atomistic and holistic research styles and their areas of study are listed below:
Atomistic
Aaron (Neurobiology of circadian rhythms)
Lauren (Brain imaging of bipolar disorder)
Holistic
Ian (Social neuroscience of autism and creativity; mirror neurons)
Albert (Mathematical modeling of brain development in songbirds)
Bill (Social cognitive neuroscience of subjective experience and reasoning)
Karen (Brain imaging of language development in humans)

Aaron represents the atomistic approach to research. When asked to discuss the whole brain concept he is skeptical of making far-reaching and unspecified claims, as is evidenced by this statement:

Aaron: If you poked somebody's orbital frontal cortex they might get moody or something like that, which, you know is kind of true, but it's like if you poked the 405 freeway you'd find that maybe the 10 would be free, but it's not because you poked the 405...you can't just say "this area is for that"...but some areas are, if you want to take that approach and you want to study something in great detail, you can say "this nucleus, in isolation from everything else, can act this way sometimes"...instead of attributing to the whole brain. To know the difference makes it so I'm pretty careful to say that.

In this excerpt Aaron touches on several dominant metaphors that are present in the field of neuroscience. First, to support his skepticism toward talking about the whole brain, he critically employs the "poke-effect" metaphor. The "poke-effect" metaphor combines several historical trends within brain research: phrenology, brain imaging, lesions, and neurosurgical research. Parallels have been drawn between the theory of phrenology of the eighteenth-century and modern brain imaging (PET, EEG, fMRI, etc.) in the their mapping of theorized faculties onto specific brain structures (Dumit 23). Likewise, brain lesions and accidental traumas have been used by humans for at least the past several centuries to analyze the effects of rough brain trauma on behavior. An example of this is ubiquitously taught in introductory-level neuroscience classes through the story of Phineas Gage. While Gage was working as a railroad foreman an explosion sent a tamping iron through his frontal lobes, forever changing his personality and behavior (Kandel et. al. 353). Much has been made of this common anecdote within the brain sciences, the most notable idea being the brain's ability to survive and be affected by harmful environmental stimuli. This stimuli can now be greatly refined by the practice of invasive neurosurgery, allowing surgeons to actually "poke" the brain and, as based on phrenological and image-faculty theory, perceive its effects.
Aaron derides any theory in which one can say "this area is for that", opting for a cautious and irreducibly integrated view of the brain. He claims that the best one can do in explaining the brain is to say that "this nucleus, when isolated from everything else, can do this sometimes". This is further supported by findings from his own research in circadian rhythms. By culturing his nucleus of interest, the suprachiasmatic nucleus of the hypothalamus, he can can alter its function by controlling its chemical and neural environments.

Aaron: Well just in a single nucleus that it is so small I think this is really interesting. Since obviously this is connected to other areas of the brain this makes me think that "okay these things are probably going to act differently in isolation than with each other and, even in isolation, there's a complex makeup for each of these different areas that are gonna function more like a circuit because you can take a single neuron out of anything and it's going to behave differently than it does in a population of other neurons and it's not just because one neuron is the same in every given environment and we don't know why. I don't know why.

By studying and understanding this tendency of his research object, Aaron has become weary of making claims about any emergent neural properties since, in varying environments, neurons can have divergent functions. He uses his personal visual and cognitive experiences with his nucleus to construct a theoretical stance toward the whole brain.
I found that all of my participants tend to adopt this approach. When asked about the brain in its totality, neuroscientists pull from predominantly visual experiences to make sense of their areas of ignorance. This is a process that is similar to what Lakoff describes as image schemas, wherein a source image (e.g. neurons in a petri dish) is mapped onto a target image (e.g. the whole brain) (222). There are differences as to how often this is done. Some researchers consistently relate their work to their whole brain concept, allowing both to mold and make meaning out of each other while others, as evidenced by Aaron, constrain themselves to their neural expertise.
A response given by Albert, a birdsong researcher interested in language evolution, represents the more holistic view:

Albert: I think to be a working neuroscientist, to be able to do hypothesis driven experiments, to be able to isolate variables and be able to make claims based on evidence you have to be working under the assumption that, well, to be a working neuroscientist who is interested in cognitive things, things that have to do with the mind, whatever that means, you have to be working under the assumption that the brain is the mind. Otherwise what are you doing?

Brain scientists like Albert who are concerned with biological and cognitive aspects of the mind have increased in number in the past twenty to thirty years due to the surge in genetic and imaging techniques that allow access to theoretical mental states, no matter how rough and intractable. Other researchers, such as those involved in behaviorist, cellular, biochemical, and biophysical analysis, approach the whole brain problem differently. They reflect a theoretical stance similar to that of the working neuroscientist presented in Patricia Churchland's now classic work Neurophilosophy (1986). These researchers believe, in one way or another, that: (1)"The time for theories has not yet arrived, since not enough is known about the structural detail," (2) "What is available by the way of theory is too abstract, is untestable, and is anyhow irrelevant to experimental neuroscience," (3) "You cannot get a grant for that sort of monkey-business". Furthermore, it often happens that a piece of research is undertaken, not in virtue of a larger program but instead because the researcher has mastered a certain technique, and there are always more measurements he can make (Churchland 403-404). Yet now, more than twenty years after Churchland's work, even these reductionist hard-liners are coming around to the cognitive approach, albeit often in non-explicit ways. Aaron's work is grounded in the study of neuropeptides and metabolic function but, interestingly, his motivation to do this work is grounded by the brain's observable output:

Aaron: I don't think (neurobiological research) is going to explain human existence and I don't personally look for that out of studying the brain. I think studying the kidneys could be interesting too. I think studying the digestive system could be interesting too. I find a little bit more fun in the brain because there is a behavior associated with it that is really complex and it's always in our face.

A jump is made from studying an anonymous group of neurons that theoretically produce the complex behaviors that are common to and known by all humans. This is done implicitly by Aaron for, even though he does not search for direct, existential meaning from his work, he does recognize a difference between it and studying the kidneys or the digestive system. By knowing and watching the behavior of himself and others, Aaron provides context for his work. It is in this way that a group of neurons can become conceptualized with a name and a function (e.g. the superchiasmatic nucleus that controls circadian rhythm).
Behavior, then, becomes a form of the visual representations and image schemas used to conduct and understand neuroscientific research. Yet many researchers call into question the importance of the visual, sometimes vehemently. In her study of brain imaging Beaulieu (2002) explains that "researchers insist they do not know the brain by seeing it, by making its activity visible" and that "denials of the importance of imaging, in a setting where visual representations are abundant, leave the analyst perplexed-and, indeed, at the heart of the claims about the contributions of brain mapping is a paradox" (56).
New fields that represent this paradox of the image are continuously being created within the brain sciences. Many seek to research aspects of mind and cognition by linking together cutting edge technologies with extant theories and methodologies. One such field that has gained attention, both in academic and lay circles, is social cognitive neuroscience (SCN). SCN combines the methodology of cognitive neuroscience with questions and theories from social scientific fields such as social psychology, economics, and political science (Lieberman 260). Due to its integration with functional neuroimaging, an infant scientific technology itself, the field has grown rapidly in the past five years. Its findings are diverse and hotly debated. The predominant imaging technology used in the field, functional magnetic resonance imaging (fMRI), has allowed experiment, data, and theory to be pushed to novel and unprecedented levels. FMRI allows researchers to locate brain functions and signals in three dimensions by studying the increased blood flow in neural structures (Kandel et. al 370). The logic says that the more blood a structure (e.g. auditory cortex) requires during a certain cognitive or behavioral task (e.g. listening to a Bach fugue), the more important that structure is to that task.
The use of fMRI in experiment design and data interpretation is a subject of ambivalence in the neurosciences. As Bill, a social cognitive neuroscientist, points out, when strongly controlled, fMRI provides the possibility for powerful correlations:

Bill: So it works out really well like when you analyze the brain data like sometimes you have things that are kind of like manipulation checks like when people are listening to things when you model it you want to show that your subjects are actually showing activity in their auditory cortex. If they are not then potentially there is something wrong with the auditory stimulus or potentially the subject wasn't listening because it is extremely reliable. Like in a study I am doing now 9 out of 10 subjects show activity in the bilateral auditory cortex and it's just nice that you did something psychological which is they are listening to sound but its very basic and nice that you have this really really reliable prediction about which pieces of the cortex are going to be lighting up in your analysis for that particular condition.

Bill perceives a capacity for fMRI to check itself and to provide controls. By introducing consistent and simple stimuli such as auditory signals, researchers can employ fMRI's imaging capacities to become convinced that their experimental environments (the fMRI machine, their cognitive and behavioral tasks, and the brain of the subject) are all static and in accordance with their notion of psychological reality. Bill recognizes the necessity of statistics in determining this. In his study "9 our of 10 subjects show activity" wherein the one subject who does not may simply not be listening. By controlling the fMRI environment and setting the experimental expectations, Bill is able to conclude that the statistical outliers must be involved in other non-related psychological tasks. Furthermore, Bill is not only able to conclude that their minds are elsewhere, he reserves the capacity to know which tasks the subject must be involved in. Bill's logic is backed up by a common sense understanding of psychological function: if a subject is not listening to what they are intended to, they must be listening to something else. It is a streamlined and simple approach to the mind, utilizing that most common form of reasoning: "if not A then B".
Yet the object that researchers like Bill are attempting to map the mind onto, the brain, is not seen by all to be streamlined and simple. Many neuroscientists, those working in SCN included, simultaneously recognize the power of fMRI while doubting certain aspects of its theoretical assumptions. Ian, for example, challenges the efficacy of comparative neuroimaging:

Ian: The experiment begins with thinking about behavior and then the mind…because the brain does one thing but the effect that that gives rise to in the mind is completely different. I don’t know, I feel like, and I don’t know if we know the answer to this yet, but I feel like similar brain activation patterns, and I’m not talking at the level of the cell because there need to be different firing patterns for different thoughts to come your mind, but at the level of the gross patterns we see in activation in terms of fMRI there’s probably very similar types of activation so you can look at two brains and they look lit up in very similar ways but the two people are doing completely different things.

Ian's conception of functional imaging allows for more theoretical uncertainty. He imagines a scenario in which the images of brain function may be identical while the behaviors and thoughts represented in those images may be widely divergent. Other researchers and authors have recognized this in different fashions. Steven Rose, for example, approaches this conundrum in terms of the individual. Rose writes that "imagers using PET and MRI have been able to develop algorithms by which they can transform and project the image derived from any individual into a 'standard' brain" and that "brains are so finely tuned to function, so limited by constraints, that anything more than relatively minor variation is simply lethal" (59). The "algorithms" Rose mentions are known as "average-brain models", computational devices used by neuroimagers to represent statistically normal brains, upon which research data can reflected and analyzed (Vul et al. 6). Average-brain models are products of technical convention wherein some models, the Talairach for example, have been used for over twenty years, dating back to the days before modern functional imaging. The idea being hinted at by both Ian and Rose, then, is that neuroimagers, in important ways, construct the brain and mind to fit their own expectations and assumptions.
Critics of SCN have argued along similar lines. A now famous 2008 paper by Vul et al. originally titled "Voodoo Correlations in Social Neuroscience" challenges the statistical and experimental designs used by SCN researchers. The authors argue that the reliability scores typically found in both psychological and neuroimaging tests are lower than certain outstanding scores found in SCN studies. SCN studies should, hypothetically, see scores that go no higher than the average of those of neuroimaging and psychology (around .74 out of 1.0 ) since methodologically SCN combines both approaches (4). Yet, time and again, SCN studies show scores well above .8 and higher, making some researchers, those in SCN included, skeptical of the claims coming from the field. Interestingly, while representing this skeptical camp in some ways, Ian is open to the holistic approach popular in fields such as this:

Ian: So I try to think of the whole brain, you know what I mean? Rather then thinking about necessarily when I design studies I don’t think about the brain so much as I think about myself and behavior. Because, I mentioned that a lot of my studies have to do with real life situations and I’m really interested in tangible things that people can relate to, I just think about my behavior.

Later in the interview he goes on to say that:

Ian: That’s one way to do it and it’s the not the most traditional way to do it nor the most methodical, you can see I do work in a lot of different areas so it’s a little bit like...what’s the expression…jack of all trades master of none kind of thing. But I am just fascinated by human behavior and so I think about it from that aspect of it first and then bring it back to the brain.

For researchers like Ian, and in certain ways for all neuroscientists, imaging is a simultaneously useful and problematic tool. It is challenging to read scientific meaning into an image, and even more difficult establishing a coherent, peer-accepted place for it within an established disciplinary paradigm. Furthermore, neuroscientists are notoriously ambivalent in their relationships with images, often attempting to fully degrade their use in formal talk and discussion. Yet, importantly, neuroscientists (along with other scientists and lay people alike) recognize and practice an innate ability to read cultural and social meaning into images. De Rijcke and Beaulieu (2007) explore the relationship between the scientific and cultural production of images. They write that once images are let loose into society, the "context of the subject's body, of the lab and of [the] high-tech expertise is removed and any concrete sense" and that "it is at best evoked, and what remains are rainbow colors superimposed on a floating brain" (737).
Conceptual metaphors are mapped onto visuals provided by imaging technologies such as fMRI and PET. The dominant image schema referenced by the participants is that of the computer, more specifically its constituent circuits and their characteristics. Turkle (1997) points out that the field of Artificial Intelligence has provided Western scientific culture with two major views of the computer: the computer as information-processor and the computer as an emergent intelligence (1094). While some of the participants spoke about ideas similar to the emergence concept, all of them touched upon the information-processing model where information is processed in a linear, input-memory-output system. This simpler model of modeling brain function, contingent upon the idea of interacting circuits, allows researchers to theoretically link various brain structures with functions, drawing lines between the groupings of colors found in brain images. To demonstrate the universality of the computer circuitry metaphor I provide the following quotes, one taken from each of the six interviews:

Aaron: I have also worked in an area where you have looked at it as a whole functioning working together brain and I think it's kind of a difference between looking at a macrosystems level of analysis like is this a major computer we are dealing with or is this just a specific circuit in the computer

Karen: ...all the neural circuitry that is involved with emotion regulation and those kinds of systems are able to wire up for maximum efficiency.

Bill: [Explaining motor control] Something like "when you pick up this spoon here, it seems very easy but there is all this complex crap going on in your motor cortex on the left side of your brain which sends signals down which eventually cross in your spinal cord which then go down fibers all the way to your fingers and contract the muscles around there but do so in very coordinated ways".
Ian: Stuff like that is really neat when you think about the brain, the way sounds come in, sights come in, and tastes and the front of the brain makes the decision of how to react to them or not react and then the motor system either executes or not.

Lauren: I suppose I see it as more of a computational machine that interacts with, takes in input from the environment and, trying to understand just the operating principles of the machine is the goal of many of the studies that I would be interested in doing.

Albert: So at a more abstract level you can conceive of each neuron as just a computational unit and you can conceive of the brain as just a vast network of nodes which is performing some computation and those nodes are arranged in groups and those groups are arranged in bigger groups and you have this hierarchical organization to a level that maybe other organisms don't have.

The participants speak of the brain in terms of hierarchies, circuits, computational units (neurons), wiring, and systems. These concepts are given agency through the participants' visual experience and knowledge. For example, the idea of a circuit, be it between electrical nodes or brain structures, is not a priori knowledge. An individual must have some form of practical or experiential relationship with a real circuit before they employ it conceptually. This is true for each of the constituent parts of the computer metaphor that were mentioned. I contend that this is due to the impact of imaging technology on neuroscientific knowledge and thinking, both expert and lay.
As mentioned before, decoding a brain image requires certain cognitive feats, some taken from cultural-at-large and some from statistical science. The ultimate goal in the decoding process is to create a holistic view of the image, to piece together the seeming chaos found in the pixels into a coherent and, hopefully, meaningful piece of data. Achieving this requires that each brain structure present in the image is provided a form of function, whether active or inactive, and a means of a connecting up with other structures. In response to this need a conceptual tool kit has been amassed. At its core is the concept of the circuited, information-processing brain. The brains circuits can be removed, as Aaron points out, and rewired in new ways. They can be manipulated by using pharmacological intervention, sensory input, and behavioral changes (as represented by the work of Karen, Bill, and Albert). Yet, in all cases, the circuits can only function and be studied if they are part of visualizable, integrated networks. The whole brain, in its modern form, only fully comes into being when visually captured at work, its highest forms of function caught in colors and pixels. It is in this sense that the increasing presence of brain images and their interpretations have influenced what, as part of the contemporary epistemological paradigm, neuroscientists can reasonably expect from their work and how they can understand it through language.
The discovery, and subsequent popularization, of mirror neurons has played a pivotal role in the construction of the dominant whole brain metaphors used today and are a prime example of how neuroscientists integrate structures and function in the brain. Through their investigation of macaque monkeys in the 1980's and 90's, Giacomo Rizzolatti and his team found that there are premotor neurons that fire when a monkey performs object-directed actions such as grasping, tearing, manipulating, holding, along with when the animal observes somebody else, either a conspecific or a human experimenter, performing the same class of actions (Iacoboni 529). These findings show that the cognition of the actions and intentions of others play a fundamental role in primate sociality. Making mirror neurons even more enticing is the fact that they demonstrably integrate the function of the premotor cortex, the inferior parietal cortex (a major area of sensory processing), and various aspects of cognition.
Neuroscientists, as evidenced by the response of my participants, construct various forms of meaning based on the existence of mirror neurons. For example, Albert perceives their role to be important to bird vocalization and, by extension, language.

Albert: So our birds actually have mirror neurons in their song system, mirror neurons seem to be, they are definitely in the parts of the brain that are important for language. Social interaction, imitation are definitely very important for language. One of the projects that I worked on as an undergrad was tracking infants and when they developed the ability to share attention with someone else with is kind of a pre-requisite for learning language.

Ian, a mirror neuron researcher himself, sees their existence as a defining feature of the human species and its connections with the external world.

Ian: Especially with the mirror neurons for example and the interconnectedness of everything and just that whole principle of everything being connected is so pervasive in yogic philosophy and now we know that maybe the neural basis of that is mirror neurons. And the reason we have such intimate connection with other people and less connection with a chimp, even though we do have a connection, and less of a connection with a chicken, and less with a cockroach is because these neurons modulate your firing depending on what is attracting them.

Popular pieces of research, such as mirror neurons, are theoretical open game for scientists and non-scientists alike. The most salient forms of popular research are those that integrate pre-existing fields of study, or at least show the potential to do so. Whether or not mirror neurons will be found to play a role in language evolution or confirm basic tenets of yogic philosophy does not matter as much as the belief that such findings are in fact possible. In this sense mirror neurons are a profound example of the ways in which neuroscientists create and use meanings and metaphors from the brain. They provide linguistic concepts that can be used to discuss the whole brain, validate dominant research technologies such as fMRI imaging, richly connect structure with function, and, as we will see, inform the nature of cultural identity and experience in important ways.

The following is a chunk of my thesis written for the UCLA Sociology department. I conducted six 30-45 minute interviews with UCLA neuroscientists asking them two main questions: 1. How do you conceive of the brain? and 2. How do you conceive of your own brain? The text below is a discussion of the responses to the second question.



Aaron: The thing that is special, maybe, about our brains is that we can perceive not only what is going on outside of our bodies, it can perceive the outside world, but it can perceive its own actions. It can keep track of itself. Basically it can be introspective and so when, when you ask me what comes to mind when you bring up the concept of brain perceiving itself the first that comes to mind is that maybe that's something that's very very important...Again it seems like the sociality is a very important thing but, yeah so, I remember being an undergrad and sitting in one of my first neuroscience/cog. sci. classes and thinking "man this is too crazy right now, I am learning about the thing that's in my head, that's doing the learning". There's this kind of infinite regress thing going on and that just kind of really fascinated me that we can really do that.

The knowledge provided by the life and social sciences allows individuals to perceive themselves as embodiments of the structures and processes these sciences outline through conceptual metaphors and image schemas, altering experience and identity in corresponding fashions. Nikolas Rose reflects upon this tendency with his concept of the neurochemical self: a fashioning of identity based on a model of brain neurotransmission that sees its means of intervention (psychiatric, psychopharmacological, therapeutic) as evolving in tandem with its research (10). Rose's model, along with those like it, explores the construction of self in terms of a lay scientific knowledge that is dispersed through forms of institutional influence and power (e.g. media, psychiatry, politics). Yet what about those who produce said knowledge, those right at the source? For these individuals, the neuroscientists, the achievement of brain embodiment is a system of complex interplay between self, culture, and one's vested interests in scientific knowledge.

Aaron's statement above is indicative of this interplay. He simultaneously references the functional efficacy of the brain (introspection, perception of the outside world), the role of sociality and culture in mediating brain function, and his own introspective cognitive experiences based on his intellectual and research interests. As an investigator of consciousness and language, Aaron perceives hierarchical levels of cognitive functions to be important in introspection. Specifically, he discusses the idea that, on one level, the brain's global function can produce a consciousness that, on another, can understand and reflect upon its embodiment in physical space and, on another still, intuit its own production as coming from its very physicality, all the while mediating this form of infinite regress through the concept of the self. This is a unique form of social relationship. The brain is provided with some form of anthropomorphic agency. It can "see" and "learn" in such a way that allows it to function as an actor in a social narrative. Yet, as Aaron notes, it is not given enough agency to constrain and make sensible the interaction. The brain does have the capability to provide the necessary social emotions and norms that dictate a normal interaction. Instead it is given a form of partial agency that, much like a broken faucet lever, allows its system of interactions to spiral out entropically until its space is filled with water or, in this case, an infinite regress of thought.

This more abstract form of brain embodiment is rooted in perceptions of consciousness popular in the brain and cognitive sciences, along with philosophy, wherein the highest levels of mind are related to the physical brain through an inhibited social relationship. Aaron's levels of introspection create a unique form of an infinite loop, an idea made popular by Hofstadter (2007), in that it can continue endlessly if it is not intentionally ended. This form of interaction is not found in the human social world but instead, as Evan Thompson argues, constitutes a phenomenological issue he deems the "body-body problem". The problem is part of "the relationship between oneself and the world, for one's living body is part of the world and one's body as one subjectively lives it is part of one's sense of self" (244). How then is the co-existence of the body (or brain) in one's subjective and physical experiences dealt with? Thompson points toward what is know as the dynamic sensorimotor hypothesis. It dictates "changes in qualitative expression to be explained not just in terms of properties of sensory inputs and of the brain region that receives them, but in terms of dynamic patterns of interdependence between sensory stimulation and embodied activity" (Thompson quoting Hurley and Noë 145-146).

This concept of interdependence between sensory stimulation and embodied activity brings us back to the mirror neuron and the metaphor of the brain-as-a-mirror as touched upon by several participants. Ian explores his understanding of mirror neurons in his personal experience through the visual comparison of two brains, one performing motor actions and one perceiving motor actions:

Ian: I mean we already know that because of the mirror neuron system seeing and doing overlap a lot. Essentially the difference is that one engages the motor system and the other does not. So those two brains would already look very similar especially if you are a seeing a part of the picture and not the entire brain.

The mirror metaphor encompasses several aspects of human psychological and physical experience that have been historically thought to be divergent and irreconcilable, making their use in meaning creation more tantalizing to the researcher. Through the incorporation of motor, sensory, and cognitive processes, mirror neurons offer an economical and systematic mode of interpreting the more salient and obvious aspects of human psychological experience: the behavior and cognition of one's self along with that of others. As explored in the previous section, even the more atomistic of neuroscientists rely on high level expressions of the brain's output to make sense of their work. Indeed, Aaron found interest in his circadian nucleus through its link to behavior and regulation, not through an intrinsic allure to its biochemical makeup.

If analyzed through Lakoff's model, mirror neurons provide a source concept through which the target concepts of behavior and sensory processing can be understood. These target concepts come to be used by the individual to understand not only his or her own experience but that of others aswell. Therefore, the mirror concept parses both phenomenological and social experience and offers a powerful tool for neuroscientists to understand themselves and their work.

Furthermore, conceptual metaphors such as the mirror are capable of bringing scientific theory and individual experience closer together in the embodied brain. Much of the literature within the social and mind sciences is concerned with explicating the norms and patterns of behavior that we intimately know yet have difficulty reflecting on. When these intimate aspects of human life are systematically studied, the results are often complex and require a technical, non-intuitive language for their explanation. For example, the process of having a ball thrown to you and your catching it requires no great feat of mind and, when done, seems coherent and fluid. Upon closer analysis, especially when looked at through, say, the computational model of mind, the series of actions become messy and disjunct. One is forced to intellectually negotiate several distinct computational processes, each with its own unique function. It is not obvious, even upon formal reflection, how the visual system recognizes the ball or how motor control achieves the catch. How then can this perspective be used to understand one's embodied behavior and experience in real life? It cannot. As a psychologically taxing process the model lacks the economy and allure of a successful conceptual framework. This highlights the tendency of individuals to shy away from highly complex concepts in their informal speech and thought. When describing aspects of the whole brain and its function, the participants opted to use speech that acknowledged the brain's complexity but, after doing such, left it alone:

Bill: Something like "when you pick up this spoon here, it seems very easy but there is all this complex crap going on in your motor cortex on the left side of your brain which sends signals down which eventually cross in your spinal cord which then go down fibers all the way to your fingers and contract the muscles around there but do so in very coordinated ways".
Albert: At that level, at the physical level, the brain is this ultra complex you know just a conglomeration of these specialized cells that have over the course of evolution arranged themselves in such a fashion that we are able to walk and talk and move around and eat and breathe and have emotions and all those things.
Aaron: I don't think it's like pill-cure form type thing and I think it's really complex and there are a ton of different factors including social factors that a lot of people tend to overlook.
Ian: What strikes me is just the intricacy of the brain and the way it evolved as an organ is absolutely amazing, but it is also something that evolved so there definitely is an order to things and there is a reason for why things are where they are.

To be successfully used by an individual in understanding their own embodiment, scientific conceptual metaphors must be robust enough to add understanding to phenomenological experience and simple enough to not overly tax psychological function. The embodied lives of neuroscientists reflect the knowledge and concepts they work to produce day in and day out. At times their research interests and expertise help construct their social and phenomenological experiences. During others, popular conceptual metaphors such as mirror neurons are employed to make sense of sometimes overwhelmingly complex processes and behaviors. It is through this inversion of brain knowledge that embodiment is achieved; by opening a dialogue between personal experience, metaphorical thought, and scientific inquiry, neuroscientists construct and understand their world, their bodies, their selves.

Sources:
Duden, B. & Samarski, S. "'Pop-Genes': The Symbolic Effects of the Release of 'Genes' into Ordinary Speech" in Women in Biotechnology ed. Molfino, F. & Zucco, F. Springer Science+Media B.V. (2008).
Lakoff, G. "Image Metaphors". Metaphor and Symbolic Activity 2:3 (1987): 219-222.
Lakoff, G. & Johnson, M. Metaphors We Live By. Chicago: The University of Chicago Press, (1980).
Rose, N. "Neurochemical selves". Society 41:1 (2003): 46-59.
Thompson, E. Mind in Life: Biology Phenomonology, and the Science of Mind. Cambridge: Harvard University Press, 2007.
Walter, W. The Living Brain. London: Penguin, 1953.

To begin, the data:

" As I breathe the sky anew
Lungs contract faintly white
(Body, scatter in the dust of the sky)
The top of a gingko tree glitters again
The zypressen darker
Sparks of the clouds pour down."
-Kenji Miyazawa "Spring and Asura"

" So the biosphere, it seems, in its persistent evolution, is doing something literally incalculable, nonalgorithmic, and outside our capacity to predict, not due to quantum uncertainty alone, nor deterministic chaos along, but for a different, equally, or more profound reason: Emergence and persistent creativity in the physical universe is real."
-Stuart Kauffman

"When you do something, you should burn yourself completely, like a good bonfire, leaving no trace of youself."
-Shunryu Suzuki

"Nested withing a nonlinear complexity that is unrivaled in the known Universe, Life combines all aspects of a creature's dynamics: its physiological, conceptual, motivational, and motor activities in an unsimulatable autopoietic network."
-Alwyn C. Scott

" He was a physicist and a computer-composer in his spare time. Why was he so stupid? Because he was of the opinion that the only thing that will engage the intellect is the measurement of relations between things. When told that his mind could change, his response was,'How? Why?'."
-John Cage

(A start to) discussion:

As the blanket of the natural universe unfolds into sheets of inquiry, exponentially highlighting vast areas of unknown complexity, causing even the most ardent physicists to shift their Newtonian assumptions (the scientific gold standard cum retro), and further pushing onto the horizon the "ultimate knowledge" of reality, why do we still bathe in the old philosophical concerns of time/no time, space/no time, self/no self, free will (if you want it), etc? If formal theorizing is receiving a major schoolyard quality flat-tire from REALITY itself, should humility not be the mode of course for the sciences of human social and mental life?

I propose that the new human scientist is an owner and applier of poetic awe-a protean mechanic of mind as it investigates, changes, and participates in reality. I propose that the new human cognition relies not on the physics of cause and effect but, rather, the incommunicable, immense systems of dynamic relationships that make up everything we know, from entangled particles to the humid breathe of H. Sapiens' history. How can one scientifically investigate so-called enlightenment itself? We may soon find out.

(Loaded words: search for new vocabulary commences....now)