Biopoiesis: Cybernetics, Art, and Ambiguity


Carlos Castellanos and Steven J. Barnes
DPrime Research, Vancouver, Canada
Email: dprime@dprime.org
Web: http://www.dprime.org
Reference this essay: Castellanos, Carlos and Steven Barnes. “Biopoiesis: Cybernetics, Art, and Ambiguity.” In Leonardo Electronic Almanac 22, no. 2, edited by Senior Editor Lanfranco Aceti, and Editors Candice Bancheri, Ashley Daugherty, and Michael Spicher. Cambridge, MA: LEA / MIT Press, 2017.
Published Online: January 15, 2018
Published in Print: To Be Announced
ISSN: 1071-4391
ISBN: Forthcoming
https://contemporaryarts.mit.edu/pub/biopoiesis

 

Abstract

We discuss Biopoiesis, a cybernetic art project that explores the relationships between structure, matter, and self-organization. Based on the work of cyberneticist Gordon Pask, the project features the construction of simple computational devices that harness an electrochemical reaction. We discuss the design and construction of the system and explore the relevance of Pask’s electrochemical work to the arts. We also put forth the notion of a “philosophy of open-ended ambiguity,” embedded within this work and discuss its resonance with the arts.

 Keywords

Cybernetics, art, self-organization, electrochemical, ambiguity, Gordon Pask, plasticity, dendrites

 

Introduction

Biopoiesis is a series of experiments exploring the relationships between structure, matter, and self-organization, in what might be described as a computational “primordial soup." This work builds on cyberneticist Gordon Pask’s research into electrochemical control systems that could adapt to certain aspects of their environment. [1] The present experiments, undertaken by members of DPrime Research, explore the artistic potential of Paskian-like systems. This work also examines the interactive and computational possibilities of natural processes, the potential for natural processes to serve as an alternative to the commonplace digital forms of computation—which might help (re)establish a dialogue among cybernetics, mainstream science, and the arts.

Besides being a laboratory for explorations into electrochemical computing, Biopoiesis has at least four additional purposes. First, we wish to feature and investigate alternative models of electronic arts practice. Second, in studying the growth and adaptation of an “inorganic” system, this project serves to question the traditional dichotomies of organic vs. inorganic and biological vs. non-biological. Third, by examining growth processes, this project makes inquiries into contemporary notions of “organic computing.” Finally, Biopoiesis may open up new ways of thinking about sensing, intelligence (including environmental and collective, not just cognitive), and memory (mutable electrochemical traces).

 

Biopoiesis

Biopoiesis entails the construction of several simple computational devices that are all based upon the process of electrochemical deposition: when an electrical current is passed through a metallic ion solution (e.g., ferrous sulfate, stannous chloride) metal is deposited on the electrode that is the source of electrons (i.e., the cathode). In our experiments, information (in the form of an electrical current) is fed to a chamber filled with a solution of stannous chloride and ethanol via an array of electrodes (see Figure 1, below). The resultant electrochemical reaction includes the growth and/or dissolution of metallic dendritic threads in the metallic ion solution—these dendrites contribute to a dynamic pattern of complex electrical and physical growth activity across the entire system.

 

Figure 1 - A typical Biopoiesis setup. In this iteration, an array of 13 electrodes was placed in the stannous chloride solution. Photograph by DPrime Research. © DPrime Research, 2012. Used with permission.
Figure 1 - A typical Biopoiesis setup. In this iteration, an array of 13 electrodes was placed in the stannous chloride solution. Photograph by DPrime Research. © DPrime Research, 2012. Used with permission.


The growth of the threads is predictable in one sense: thread growth will always be from a cathode to an anode. Yet even within a tank containing a single cathode and a single anode, such growth still constitutes a continuously shifting and dynamic signal network (comparable to the plasticity observed in neuronal and glial processes in a nervous system). The dendrites are fluid and unstable, bifurcating and dissolving in seemingly unpredictable ways. Thread bifurcation and dissolution, in turn, leads to resistance changes that modify the flow of information (current) through the network. If a subset of electrodes in the electrochemical solution receives input from an environmental sensor (or via some other method), and the electrochemical output can affect that sensor (or otherwise influence the growth of threads), then the network may move toward a dynamic equilibrium with its environment. The dendritic network also carries a decremental memory trace of its previous activities. When the environment changes, the system is perturbed but not immediately reset. Thus, the prior activity and configuration of the system affects how it handles a change in its environment. It can thus learn from its interactions. Furthermore, the system can be trained by providing reinforcement for certain sorts of conductance changes that are produced in response to a particular environmental perturbation. [2]

 

System Overview

As shown in Figure 2, the general Biopoiesis system consists of one or more input electrodes carrying information (i.e., electrical current changes) from an environmental sensor (e.g., a microphone, a video camera) into the electrochemical solution. The subsequent effects of that information on dendritic growth in the electrochemical solution can be fed back to the environment in any of several different ways. For example, several of our installations have focused on passing ongoing sound captured via a microphone from the environment through the system and then back out to the environment through a speaker. In this way, the system affects both the growth and/or dissolution (henceforth collectively referred to as “plasticity”) of dendritic threads, as well as the sound environment in which it is situated; a typical cybernetic feedback loop. As another example, we are currently building a system that employs video capture via a digital microscope of ongoing dendritic plasticity. Analysis of that video-recorded growth will be fed back to the environment in some form—completing the system feedback loop.

 

Figure 2 - The general characteristics of a Biopoiesis system. Information from the environment is fed into the stannous chloride solution, thus affecting growth of dendritic threads that, in turn, affect any outputs to the environment—a cybernetic feedback loop. In this system diagram, 13 electrodes (4 cathodes [black dots] and 9 anodes [red dots]) are placed in the stannous chloride solution, but different electrode numbers might be used depending on the goals of a particular implementation.
Figure 2 - The general characteristics of a Biopoiesis system. Information from the environment is fed into the stannous chloride solution, thus affecting growth of dendritic threads that, in turn, affect any outputs to the environment—a cybernetic feedback loop. In this system diagram, 13 electrodes (4 cathodes [black dots] and 9 anodes [red dots]) are placed in the stannous chloride solution, but different electrode numbers might be used depending on the goals of a particular implementation.


A notable strength of the project is the potential of the system, including its many potential sensors and effectors, to be easily “re-patched” and reconfigured, thus allowing for a wide variety of implementations and interaction modalities. We might compare it to an “open jam session.” Several participants are given the opportunity to simultaneously “patch” into the electrochemical network via a microcontroller to transform sound, video, computer graphics, or any other information source they want to provide into an electrochemical reaction. Electrical output from that reaction can then affect the participants’ data sources—and the feedback loop continues.

The general approach taken here can be employed in countless ways and with many different media. For example, dendritic plasticity patterns might be applied to the transformation of vertex data in computer graphics or gesture recognition in video tracking. The re-patchable nature of this project allows us (and participants) to explore the computational possibilities of natural processes that might serve as an alternative to more commonplace digital forms of computational processing, while the malleable nature of the medium allows for the exploration of virtually unbounded search spaces and implementation of open-ended evolutionary designs.

 

Implementation Strategies

To date, we have constructed several tanks to house the electrochemical solution—each made of either clear glass or plexiglass of differing dimensions (typically between 10x10 and 21x21 inches; see Figure 1 for an example of a tank). Some tanks have accommodated 11 electrodes, whereas others have allowed for up to 13 electrodes. In a typical setup, 8 or 9 of the electrodes serve as anodes while the remaining electrodes serve as cathodes. Currently, two types of Biopoiesis implementations have been developed. The first, dubbed Emergent Relations uses a relatively unmodulated feedback loop. It can be considered the “default” system since it has served as the template from which other implementations have been built. A second type of implementation, called Organic Learning, has been used to explore the electrochemical system’s ability to display properties of biological learning.

 

Emergent Relations

In this sort of implementation, a PC runs a simple Max/MSP sound synthesizer patch. Various parameters from this synthesizer patch, such as oscillator frequencies and modulation data, are sent to a microcontroller where they are transformed into lengths of electrical pulses and sent to the anodes in the tank. The cathodes are connected directly to the negative terminal of the electrical current source (which is typically set between five and nine volts DC). The length and variety of the electrical pulses (patterns of current gating) ultimately lead to a shifting pattern of plasticity and bifurcation. Currents at the cathodes are then measured by the microcontroller and used to alter the parameters of the sound synthesizer patch, thus completing the feedback loop. A simple variant of this system involves inserting the signal from a microphone directly into the solution. The dendritic threads that form can then affect a sonic output from a set of speakers. The sound from the speakers, as well as their vibrations and any other local environmental phenomena, establishes a continuous feedback loop that serves to affect ongoing dendritic plasticity.

As mentioned earlier, one variant of this system setup currently in development involves the use of a digital microscope along with video motion tracking software to measure the plasticity of the dendritic threads. Any plasticity of dendritic threads is captured by the motion tracker, which in turn changes the electrical pulse patterns—stimulating and affecting the pattern of ongoing dendritic plasticity in the solution.

 

Organic Learning

We recently conducted an experiment that explored the extent to which our electrochemical solution and electrode assembly could manifest features of associative learning. [3] Features of a gallery environment controlled the gating of currents through each of the individual electrodes. Nine electrodes (the anodes) were gated by motion in one zone near the test apparatus, while the remaining four electrodes (the cathodes) were each gated by the presence of sound within a particular frequency range (i.e., low, low-mid, high-mid, and high range) in the gallery (see Figure 3). In short, the circuit through the stannous chloride solution would only close when at least one anode and one cathode were active at the same time. This setup allows us to explore if and how dendritic thread plasticity might serve as a coincidence detector. [4] If our system does have such a capability, then it should manifest itself in the network as both a plasticity of the dendritic processes and a long-term potentiation or depression of current flow between the respective anode and cathode. [5] Thus, if there is sufficient simultaneous activation of motion-gated anodes and sound-gated cathodes, any resulting plasticity and current fluctuations would constitute a bioelectrical record of sensory-sensory learning.

 

Figure 3 - The Organic Learning setup. Coincident sound and motion information was fed into the stannous chloride solution.
Figure 3 - The Organic Learning setup. Coincident sound and motion information was fed into the stannous chloride solution.


The purpose of this particular experiment was not merely to demonstrate the presence of associative sensory learning in our system; our more general goal was to explore the classic dichotomies of inorganic vs. organic and non-biological vs. biological. Our system is, by standard scientific definitions, inorganic. Yet, we have commonly observed patterns of bifurcated growth and dissolution that have qualities classically reserved for organic biological systems. Accordingly, we wanted to test the boundaries of the inorganic and organic, the non- biological and the biological, by attempting to show that our “inorganic and non-biological” system could manifest properties comparable to those associated with a biological system that is learning about aspects of its environment (e.g., neuronal and glial plasticity or long-term potentiation/depression of synaptic communication).

This experiment, which was situated in the SIGGRAPH 2012 Art Gallery, ran for longer than our previous setups. It ran almost continuously for a period of four days (Figure 4). As predicted, plasticity that seemed to be related to the coincidence of particular sounds and motion in the environment was observed in the growth patterns of the dendritic threads. We also found something we hadn’t observed in earlier systems. At night, when the gallery was empty of visitors and largely devoid of any sound, the dendritic threads would begin to dissolve back into solution. This latter observation is remarkable (but not unprecedented—see the discussion of Pask’s assemblages below) in that it demonstrates that dendritic threads are activity dependent processes—further highlighting the system’s organic/biological qualities.

 

Figure 4 - A momentary result from day 2 of the Organic Learning experiment at SIGGRAPH 2012. A highly bifurcated dendritic growth pattern can be seen at the cathode in the foreground. Photograph by DPrime Research. © DPrime Research, 2012. Used with permission.
Figure 4 - A momentary result from day 2 of the Organic Learning experiment at SIGGRAPH 2012. A highly bifurcated dendritic growth pattern can be seen at the cathode in the foreground. Photograph by DPrime Research. © DPrime Research, 2012. Used with permission.


Dynamic Equilibrium

As mentioned at the beginning of this paper, Biopoeisis is based upon the work of cyberneticist Gordon Pask. In the 1950s, Pask experimented with the construction of electrochemical assemblages that were capable of growing their own sensors. These systems, which he referred to as “organic computers” (due to their quasi-organic properties), possessed emergent properties such that they were capable of developing their own “relevance criteria” (i.e., perceptual categories) in response to environmental inputs. In effect, the sensors and effectors of these Paskian systems were capable of adapting to changing environmental conditions.

Pask’s assemblages consisted of sets of electrodes inserted into a dish containing an aqueous metallic salt solution (i.e., ferrous sulfate or stannous chloride) and connected to a current-limited electrical source. By passing current through the electrode array, dendritic metallic threads were formed. These threads had low resistance relative to the solution, and thus their growth was reinforced if current was continuously applied. [6] Conversely, the threads would slow their growth or even dissolve if current was no longer provided. Over time, the assemblages would establish a dynamic equilibrium with their environments, [7] though it should be mentioned that Pask noted the patterns of thread growth were seemingly unpredictable. For example, in one of Pask’s experiments, he sent an assemblage sound from a microphone placed outside a window of his London flat. Within a few hours the assemblage had “grown an ear,” meaning the threads had adaptively grown to become sensitive to sound (and magnetic fields):


We have made an ear and we have made a magnetic receptor. The ear can discriminate two frequencies, one of the order of 50 cycles per second and the other on the order of one hundred cycles per second...The ear incidentally, looks rather like an ear. It is a gap in the thread structure in which you have fibrils which resonate at the excitation frequency. [8]


Pask pointed out that since the thread growth can itself influence current densities throughout the solution, any thread structures present at a given point in time will influence the plasticity of the assemblage. Thus, the prior activity and configuration of the system affected how it handled changes in its environment. In essence the system had the capacity to learn.

 

Relevance to the Arts

Several aspects of Biopoiesis are particularly relevant to the arts in a more general sense and merit further discussion here. In the broadest sense, Biopoiesis represents an exploration into alternative models of interactive arts practice, as well as a (re)integration of cybernetic methods into artmaking. [9] Specifically, there is the exploration of the underlying mediums employed in the interactive arts. Few would dispute that digital computation has pervaded most aspects of our existence and transformed our very thought processes. New media artists sometimes make the implicit assumption that digital forms are the only avenues for exploration. The digital is often taken as a given. Rarely is the underlying paradigm, which is embedded in the very material substrate on which the digital work exists, ever seriously questioned. Seen in this context, Biopoiesis represents an experimental approach to re-imagining cultural production with non-traditional (non-digital) computational methods as a medium by exploring alternative models of electronic arts practice. One of the appeals of interactivity and digital computation in the arts is the inclusion of the participant as co-creator of the work. In addition, computational techniques such as genetic algorithms, evolutionary robotics, and stochastic searches also have broad appeal (in both science and the arts) precisely because they seem to relax the (often rigid) engineering constraints inherent in traditional computational technologies. Though of course the implementation of randomness and indeterminacy in the arts predates digital technology, as exemplified by John Cage’s chance operations and the event scores of the Fluxus artists.

Biopoiesis and Pask’s electrochemical assemblages both serve to redirect our attention to the very material forms of the works and how they add a certain dimension of materiality as well as a sensuous presence that is often lacking in digital and even robotic works. Some of these works display at least a hint of a certain kind of agency that can only come from these non-symbolic (i.e., non-digital) material forms grounded in processes of organic or quasi-organic growth. Works inspired by Pask’s electrochemical experiments, such as Roman Kirchner’s Roots (2005-2006) and Andy Webster’s texts, System Generated by the Sound of its Own Making (2007) and Tuning Pask’s Ear (2002), [10] may be loosely related to “bio-art,” but can more properly be described as quasi-organic cybernetic systems. These works allow us to directly apprehend and experience self-organizing, emergent processes by virtue of their growth and sheer materiality.

 

Ambiguity

Pask was not interested in designing computational systems with the most efficient algorithms or statistical models, but rather in the harnessing of the complex self-organizing properties already inherent in nature:


Self-organizing systems lie all around us. There are quagmires, the fish in the sea, or intractable systems like clouds. Surely we can make these work things out for us, act as our control mechanisms, or perhaps most important of all, we can couple these seemingly uncontrollable entities together so that they control each other. Why not, for example, couple the traffic chaos in Chicago to the traffic chaos of New York in order to obtain an acceptably self-organizing whole? Why not associate individual brains to achieve a group intelligence? [11]


For Pask most complex problems require genuinely novel solutions that cannot be designed beforehand, but rather must be adaptively created via performative interactions with and through the dynamics of a system and more broadly within a complex environment that is not fully knowable in the classical scientific sense; a mathematical model of this is always crude and incomplete. Underlying Biopoiesis is what may be called a “Paskian” philosophy of open-ended ambiguity that we feel has a certain resonance with artistic approaches and lends itself to artistic interventions. We also believe that this quality is now lacking in most modern scientific endeavors.

By ambiguity we mean not so much something that is vague or confusingly idiosyncratic, as is the commonplace meaning of the term (at least in the arts). Rather, ambiguity in the sense put forth by philosopher Maurice Merleau-Ponty. We understand it to be anything that is undergoing development or is continuously open to determination. Moreover, it is something that cannot be objectively explained or subjectively understood except within the context of this continual emergence. Much of our experience of the arts and of nature can be said to have this quality of dynamic and flexible essences. This concept of ambiguity is similar to what Andrew Pickering refers to as a “nonmodern ontology of unknowability” when referring broadly to cybernetics, but more specifically to the work of Pask, his colleague Stafford Beer, and their experiments into self-organizing adaptive control systems. [12] Instead of seeing the world as a fully knowable place, through the detached “view from nowhere” that forms the ontology of classical science and engineering, Pickering argues that cybernetics offers us other ways to look at the world. It is not a place where there is a sharp dualist split between people and things, but where both occupy and constitute a lively dynamic place of performative interactions and endlessly emergent systems (of which we humans are just one sort).

For cyberneticists like Pask with his notion of control systems whose design parameters are purposely “ill-defined” and intended to evolve in response to environmental feedback, [13] and Beer with his notion of “exceedingly complex” systems, the world is viewed as ultimately unknowable, a world to which we constantly adapt through embodied action and displays of agency. [14] Pask pointed out the marked difference between a scientific observer, who minimizes interaction with an observed system and a participant observer, who maximizes it. [15] Not unlike artists who understand their materials through their manipulations of them and their subject through the artmaking process itself, Pask proposed that when we build and try to understand complex systems, we approach them as a natural historian would: through our interactions with them. [16] Much of mainstream science considers observer interaction as a source of confounding variables, and thus as something to be avoided. For Pask, however, constructing devices that adapt to environmental conditions and interacting with them adds to our knowledge in ways the scientific experimental method cannot.

 

Ambiguity as a Computational Method for Understanding the (Exceedingly) Complex

Pask’s electrochemical system demonstrated the rudimentary capability of evolving its own relevance criteria in part because of its ability to compel an observer to interact with it. Both of these attributes are intimately bound up with its “ill-defined” nature. For Pask, the construction of assemblages and the interaction with them was necessary for understanding complex phenomena such as learning, autonomy, and intelligence. He wanted to design a system that would evolve its own sensors to choose, independent of the designer, those aspects of its environment that were relevant to it and to which it would react. The malleable electrochemical medium is rich in structural possibilities, and thus allows for a complex self-organization that can be adaptively steered but not directed (in other words, it will still behave unpredictably, coming up with novel solutions that the designer may not have considered). In order to achieve this the system would have to be ill-defined—meaning no specification for components, construction details, or connectivity would be given. [17] While perhaps making his experiments difficult to replicate, this made sense from Pask’s point of view. If the system was to genuinely evolve its own environmental filters and its own means of influencing the world, then rigidly designing what the system was and how it behaved beforehand was antithetical to the very goals Pask wanted to achieve. Pask notes that unlike most control systems, whose parts and functions are well-defined ahead of time and do not change (and in fact are constructed so as to avoid any disturbances for which they were not designed), those built with elements that have no specified functions (such as an electrochemical assemblage) can exhibit novel behavior and adaptation that cannot be easily predicted (but can be steered). In essence, such a system can become sensitive to environmental stimuli that was not originally deemed relevant and not directly inserted into it.


The input connection may, however, be of any kind. True, there will be some electrical connections established at the outset, but it is not impossible that changes of temperature, chemical constitution, vibrations, magnetic fields, and so on, will affect the development of the assemblage and serve as inputs. [18]


If one of these arbitrary disturbances is reinforced, then the system may develop a continuous sensitivity to it. We have used this same approach by putting the tank on top of speakers that were playing back sound running through the solution. Physical vibrations then act as an additional input to the solution, adding a feedback loop that may encourage dendrites to physically resonate with particular frequencies or sonic patterns. We have also noticed how, for example, temperature changes in the gallery (e.g.,\y when they turn the air conditioners off) can affect the growth of the threads, and we often have to resist the urge to “fix” this problem by adjusting voltages or solution concentrations.

Pask notes that an assemblage like his “must force the observer to interact with it, in the sense that interaction yields benefits. It must be an assemblage for which the reference frame is badly specified.” [19] From this quote, one gets a sense of the different ontological space within which Pask operated (and which Pickering sketches out). All of this brings us back to our notion of ambiguity. For artists who design systems that interact in dynamic and complex environments (e.g., gallery spaces, outdoor spaces) and are interested in emergent phenomena, working with such “unstable” mediums that grow unpredictably cannot help but spark ideas about possible avenues of exploration in their artmaking processes. Likewise, for those scientists that seek to embrace real-world conditions as opposed to sterile control over experimental variables, such mediums also offer opportunities for experimentation and for the study of model systems. Furthermore, the evolution of sensors or relevance criteria that Pask’s assemblage demonstrated could only happen if the system was actually situated in a real-world context, with all the instability and variability that entails. Thus making an art gallery or a public space an almost ideal location and context for testing Paskian-like systems.

For many years now, artists have experimented with different mediums, techniques, and locations without knowing exactly what the results would be. Thus, to an artist, Pask’s approach might seem familiar and not that different from certain other artistic modes of experimentation. Pickering notes how in Pask and Beer’s work there is a belief in the agency and variability of matter. He notes how rather than marshaling, or dominating, “inert lumps of matter” (as the building of computers and industrial machinery entails), there are attempts to couple this variability to human concerns. [20] A Paskian electrochemical system such as Biopoiesis encourages us to view the world as full of co-emergent, co-evolving systems too complex to be fully apprehended or objectively explained. A world that is in a perpetual state of becoming, characterized and brought forth via emergent relations of complexity that adumbrate an experience of the world that we characterize here as open-endedly ambiguous. In other words, what we as artists who employ sophisticated technology in our work can learn from this Paskian philosophy is, in a sense, what we already know.

We would like to conclude by commenting on something we recently observed during our Organic Learning experiment at SIGGRAPH 2012, where we ran one of our electrochemical systems continuously for four days. By the end of the third day of the installation, we noticed that some white chalky material was building up on the bottom of the tank. We also noticed that the quality of the dendritic threads had changed. On the first few days of the installation, the threads were characteristically silver in color with clearly delineated branching patterns (see Figure 4). By the end of the third day, however, the dendritic threads were black and it was harder to discern branching—in some cases the growth constituted a shifting black clump of material focused at the electrode tip (see Figure 5). The system also seemed to be less plastic, in that it was harder to observe changes in the dendritic threads. All of this was an annoyance at first, and we were tempted to completely empty the solution and start anew. But upon further consideration we realized that this degradation of the solution and the dendritic threads only lent further weight to the assertion that this complex system was comparable to a biological nervous system: it had aged.

More information and documentation on Biopoiesis can be found on the web at biopoiesis.dprime.org.

 

Figure 5 - Growth from a cathode electrode of the Organic Learning experiment at SIGGRAPH 2012 after 3 days of growth; displaying signs of “aging.” Photograph by DPrime Research. © DPrime Research, 2012. Used with permission.
Figure 5 - Growth from a cathode electrode of the Organic Learning experiment at SIGGRAPH 2012 after 3 days of growth; displaying signs of “aging.” Photograph by DPrime Research. © DPrime Research, 2012. Used with permission.


References and Notes

[1] See Gordon Pask, “The Natural History of Networks,” in Self-Organizing Systems: Proceedings of an International Conference, 5 and 6 May, ed. M. C. Yovits and S. Cameron (New York: Pergamon Press, 1960) and Gordon Pask, “Physical Analogues to the Growth of a Concept,” in Mechanisation of Thought Processes: Proceedings of a Symposium Held at the National Physical Laboratory on 24th,25th, 26th and 27th November 1958 (London: H. M. Stationery Off, 1959).

[2] Pask spoke of “rewarding” the system if it generated desired outputs. This is not reward in the Pavlovian sense or in the sense used in standard reinforcement learning applications in computer science where a response is rewarded so as to obtain more of that specific response in the future. Rather, it is reward in the sense Pask described: to give “permission” for the system to continue to develop its thread structures, but develop them in an unspecified way. This reward usually entails sending more current to the solution. See Gordon Pask “The Natural History of Networks”, 251ff.; and Gordon Pask “Physical Analogues to the Growth of a Concept”, 920.

[3] Peter D. Balsam, Michael Drew, and C. R. Gallistel, “Time and Associative Learning,” Comparative Cognition and Behavior Reviews 5 (2010): 1-22.

[4] Greg J. Stuart and Michael Häusser, “Dendritic Coincidence Detection of EPSPs and Action Potentials,” Nature Neuroscience 4 (2001): 63-71.

[5] Wickliffe C. Abraham and Anthony Robins, “Memory Retention – The Synaptic Stability versus Plasticity Dilemna,” Trends in Neurosciences 28, no. 2 (2005): 73-78.

[6] Ibid., 251. See also Peter Cariani, “To Evolve an Ear: Epistemological Implications of Gordon Pask’s Electrochemical Devices,” Systems Research 10, no. 3 (1993): 22.

[7] Gordon Pask, “The Natural History of Networks,” 250.

[8] Ibid., 261.

[9] For artists employing cybernetic concepts and methods in their work, see Roy Ascott, Telematic Embrace: Visionary Theories of Art, Technology,and Consciousness, ed. Edward Shanken (Berkeley: University of California Press, 2003); Jack Burnham, “Systems Esthetics,” Artforum 7, no. 1 (1968): 30–35; Jack Burnham, “The Aesthetics of Intelligent Systems,” in On the Future of Art (New York: Viking Press, 1970), 95–122;, as well as the early work of Joel Slayton and C5 at the website of C5 Corporation, http://www.c5corp.com (accessed February 1, 2014).

[10] Roman Kirschner, "Roots," Roman Kirschner's website, 2005-2006, http://www.romankirschner.net/index.php?roots; Andy Webster, "Tuning Pask’s Ear," Andy Webster's website, 2002, http://www.andywebster.info/index.php?/projects/tuning-pasks-ear/; Andy Webster, "A System Generated By The Sound Of Its Own Making," Andy Webster's website, 2007, http://www.andywebster.info/index.php?/projects/system-generated-by-the-sound-of-its-own-making/ (accessed February 1, 2014).

[11] Gordon Pask, “The Natural History of Networks,” 258.

[12] Andrew Pickering, The Cybernetic Brain: Sketches of Another Future (Chicago: University of Chicago Press, 2010).

[13] Peter Cariani, “To Evolve an Ear,” 20.

[14] Beer even declared that the study and construction of such systems was the proper domain of cybernetics. See Andrew Pickering, The Cybernetic Brain, 223

[15] Gordon Pask, “Organic Control and the Cybernetic Method,” Cybernetica 1, no. 3 (1958): 172–173.

[16] Gordon Pask, “The Natural History of Networks.”

[17] Cariani, “To Evolve an Ear,” 20.

[18] Gordon Pask, “Physical Analogues to the Growth of a Concept,” 921.

[19] Ibid., 892.

[20] Andrew Pickering, The Cybernetic Brain, 236.

  

Author Biographies

Carlos Castellanos is an interdisciplinary artist and researcher with a wide array of interests such as embodiment, cybernetics and systems theory, networks, phenomenology and artificial intelligence. He is exploring the aesthetics of information technologies and their effects on lived embodied human experience. This has taken a variety of forms and include scholarly writing, net art, interactive installation, sound, performance and techno-conceptual systems. Castellanos is currently pursuing a Ph.D. at the School of Interactive Arts and Technology , Simon Fraser University and splits his time between Vancouver and San Francisco.


Steven Barnes holds a Ph.D. in Behavioural Neuroscience (Biopsychology) from the University of British Columbia (UBC) in Vancouver.He was a Postdoctoral Fellow in Neurophysiology in the Department of Epileptology at the University of Bonn, and a Postdoctoral Fellow in Interactive Arts and New Media at the School of Interactive Arts and Technology at Simon Fraser University.Initially trained as a visual artist, he currently teaches neuroscience and psychology at UBC. His academic expertise lies in the areas of learning and memory, psychiatric disorders, epilepsy, neuroplasticity and metaplasticity. Steven’s research interests currently shift between several topics including the history of neuroscience and psychology, biological mutualism, cybernetic systems and art-science collaboration. He continues to draw and paint.

 

DPrime Research is a nonprofit research and consultancy firm that specializes in cultural production informed by the intersection of technology, research and the arts. In addition to our core research, the DPrime approach is exemplified by the enhancement of collaboration, dialogue and knowledge sharing between local communities, academic research and cultural institutions, with the goal of showcasing alternatives to dominant ontological models.