1. Introduction

The often expressed, but usually trite cliché about history duplicating fiction, nonetheless, reflects a deeper reality, about the human penchant for mystery behind modern technological marvels like brain-computer interfacing (BCI). Indeed, by combining the elusiveness of mental representations with unseen links to motor movements, BCI seemingly appealed to fictional accounts of unlimited mobility and teleportation. This mystique behind the mechanism has lessened somewhat since Jacque Vidal first coined the term in the 1970s [1]. Nevertheless, there remains ongoing excitement over therapeutic prospects that continue to drive interest in advancing BCI applications. Recent domains for example have included the rehabilitation of stroke victims, improved learning with artificial sensory feedback, and real-time control over fine motor movements, as well as the traditional mobilization of external devices usually associated with BCI.

As a strategic response to cognitive and CNS impairments, BCI is a theoretical outgrowth of several generations of endogenous devices that have as a prime strategy the direct replacement of lost neural function. Devices like pacemakers, cochlear implants, and vagal stimulators for example have all been successfully deployed in the relatively simpler anatomical substrate of sensorial and motor nerves where nerve transmission is largely unidirectional and composed of sequences of transmitting signals [2, 3]. In these applications the premise of administering therapy by replacing lost function has been limited to the restoration of signal-generating capacity [4]. Cochlear implants, for instance, transduce pitch vibrations that occur outside the ear to coded electrical signals within the cochlea in order to elicit action potentials in the frequency to place receptors that form the auditory nerve. Implants sited more internally are similarly designed but require the presence of a bidirectional interface for nerve signals, that is, one that can both receive electrical impulses from the intact nerve tissue and yield an

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

equivalently spaced temporal output beyond the point of lesion. For these devices the replacement of action potentials is akin to the restoration of language syntax, here linearly related to temporal spiking sequences.

connectivities that possess reciprocal inhibitory and excitatory contributions [11–13]. The emphasis of this anatomical architecture is to create circumstances of signal stability, to enable information-bearing signals to persist, thereby minimizing any corruption of information content. Hence, the physical architecture of the brain is anatomically configured to create patterns of cyclical flow, where the pattern of the cycle contains the information representation. Current estimates indicate that nearly 95% of brain neurons exhibit some form of feedback, with some zones noted for especially dense innervation [14, 15]. The physiological consequence of this arrangement is the generation of energetically favored zones where signal propagation is retained. Such persistent activity is a necessity to enable the brain to monitor ongoing bodily activity. However, persistent activity also makes brain operation susceptible to the pervasive influence of a noisy background. This susceptibility is overcome by structuring flow within energetically favorable zones, which minimizes the influence of noise and maxi-

Introductory Chapter: Multilevel Representational Content in BCI Therapy - Extending Syntactic and Semantic…

http://dx.doi.org/10.5772/intechopen.80232

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The dynamical motifs that are generated adapt spiking activity to exhibit a periodicity that frees syntactical expression from its temporal dependence. This periodicity fundamentally restructures the representation of information content. Hence, basic elements of syntax in the

Critically, these stabilized patterns are unique outcomes determined by the resolution of numerous physical forces; that is, they emerge from a high-dimensional state space within the global activity of the brain. They can therefore potentially assume an indefinite number of mathematical configurations that are defined by these physical circumstances. In a simple model, like a fixed point attractor, the rate of change of the attractor back to its original configuration is linearly related to the brain state, which is typically represented by a signal feature related to that state. More complex models entail the continuous and repetitive traversal of brain states by the attractor, which are described mathematically by a second derivative function, while still other models are complex and multiparameterized [16, 17]. The result of this variation is a significant expansion of syntactical range that is likely to substantially differ from that in peripheral nerves. For BCI therapy the use of a different syntactical expression can be expected to have several consequences. The transposition of one syntax for another means, first, that an interfacial medium relying only on the original syntax introduces gaps in syntactical interpretation, with the immediate consequence of interpretive redundancy [18, 19]. That is, the mapping from one coding structure to the second is not one to one, but instead elicits multiple readouts. For a therapy premised on signal restoration, this overextends the intended output range and diminishes if not obviates therapeutic effectiveness. Hence, bidirectional interfacing premised on duplicating spiking sequences alone is likely to be inadequate for information transfer.

By acquiring temporal independence additionally, the manner in which syntactical elements are assembled is also altered. As cyclical patterns it is only through their modular assembly into larger architectures that they can yield representational variation, a feature that is seen, for instance, in cases of stable heteroclinic channels [20, 21]. Such variation is potentially amenable to exploitation for constructing extended symbolical architectures [22]. Rodrigues et al., for example, have shown that simple combinations of dynamical elements can be exploited to significantly expand the range of syntactical elements [23]. Using an attractor and repellor, they were able to demonstrate that networks generating these elements not only variably combine in specific ratios but also generalize from external inputs; that is, they learned to

mizes signal retention.

brain are not pulsed sequences, but blocked patterns.

In building on these earlier devices, BCI has appropriated not only a similar premise but also a similar design and has, therefore, been largely sequence based and output driven. One consequence of this approach, for example, has been the search for an electrical feature that can be used in a fashion analogous to that of spiking in implant devices for peripheral nerves, such as the local field potential [5]. The premise of a temporally defined syntax is increasingly challenged, however, as knowledge of the anatomical recurrency of the brain is made manifest and the need to distinguish transmitted signals from a dominant background of noise becomes evident [6–8]. How the brain resolves the challenges posed by its complex operation is now thought to occur through the structuring of temporally independent and cyclically repetitive activity, that is, nonlinear dynamical elements that, while using spiking activity as a fundamental mechanistic feature, nonetheless relate only indirectly to it for communication. This is to say that the brain employs a very different type of coding syntax from that of the peripheral nerves. Such fundamentally distinct conditions for communicating information in turn require a different premise on which to base BCI therapy.

Qualitatively different premises for technology, in fact, are hardly new in science, often exerting profound influences on the subsequent course a field may take. The difference in the way information content is represented, when transitioning from peripheral to central nervous tissue resembles, for example, the transition made in computational programming architectures before and after the introduction of autonomous robotic design [9]. Attempts to endow field-situated robotic agents with autonomous mobility initially employed basic program planning formats where decision-making points were encoded in a series of steps telling the robot how to respond. In the field however, it became apparent that programmed contingencies were incapable of responding to the vast array of circumstances that could act as input variables. The need to accommodate this nearly unlimited variability resulted in a new approach to program planning that adopted a more interactive format where plans comprised only one among several input resources that autonomous robots could call upon [10]. In their formatting, these plans adopted a parallel architecture to accommodate multiple and simultaneous inputs. World information was thus assimilated and assembled as blocks of knowledge rather than temporally consecutive incidents.

An analogous shift is now needed for conceiving of BCI as a therapeutic medium, that is, as one that no longer entails only the restoring of signal transmission capacity but also the repairing of processes that structure basic functions. The direction in which this shift will need to evolve, therefore, is not merely in duplicating how the brain transmits information but also in a larger grasp of organismal design that is mediated globally. This becomes apparent when analogized to a linguistic hierarchy, which is used to structure multilevel representational content.
