Towards Retina Implants for Improvement of Vision in Humans with Retinitis Pigmentosa - Challenges and First Results 1

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1 Towards Retina Implants for Improvement of Vision in Humans with Retinitis Pigmentosa - Challenges and First Results 1 R. Eckmiller Division of Neuroinformatics, Department of Computer Science University of Bonn, Römerstr. 164, D Bonn, FR Germany Tel.: FAX: eckmiller@nero.uni-bonn.de Abstract The concept of a retina implant for blind subjects with end-stage retinitis pigmentosa is being described. First results are being discussed. 1 Neurotechnology The emerging field of "Neurotechnology" deals with compensation of functional deficits of the human nervous system by means of novel computer and microsystems technologies. Accordingly, neurotechnology requires the development of adaptive BPNs, as well as novel multicontact neural interfaces (MNI) to allow for functional substitution of and bi-directional communication with specific parts of the nervous system in real time (Eckmiller, 1993). Thus, it is essential for technical neural systems (BPN) to be adjustable in response to signals from the implant-carrying patient as well as to encode and decode neural signals. The aim of neurotechnology is the development of a new generation of prosthetic devices, such as novel cochlea implants, functional electrical stimulation (FES) -systems, or retina implants as indicated in the two schemas of Fig. 1. The top schema depicts a BPN as adaptive neural encoder to map signals from a technical sensor array onto (several hundreds) separate neural impulse trains, which are being connected with single nerve fibres by means of a MNI. In contrast, the bottom schema in Fig. 1 indicates the reverse situation of another MNI for recording of (several hundreds) separate neural impulse trains from human nervous tissue and a subsequent BPN as adaptive neural decoder to map the spike trains onto appropriate control signals for technical devices (e.g.: prostheses or monitors). 1 Supported by the Federal Ministry for Education, Science, Research and Technology (BMBF) and by the Ministry for Science and Research (MWF in NRW)

2 Fig. 1 Two schemas for typical neuroprosthetic applications of neurotechnology Top: Technical sensor system (prosthesis) supplies an adaptive neural computer as BPN (which serves here as neural encoder) with sensory signals. BPN generates corresponding encoded impulse trains as input (stimulation) for a sensory nerve via a multi-contact neural interface (MNI). Bottom: Motor control signals, which are recorded as impulse trains from a motor nerve via a multicontact neural interface (MNI), are decoded by a BPN and fed into a technical motor system (prosthesis). 2 Concept of a Retina Implant A large portion of visually impaired human subjects suffers from retinal defects (especially: retinitis pigmentosa (RP)), which typically begins with night blindness (loss of rod photoreceptors), deteriorates into tunnel vision and finally leads to total blindness (additional loss of all cone photoreceptors).however, significant portions of retinal ganglion cells and subsequent parts of the visual system remain intact (Stone et al., 1992). In a recent pioneering study (Humayun et al., 1993) it could be demonstrated that local electrical stimulation of the retinal ganglion cell layer in blind RP-patients yields localized visual sensations (see also: May, 1993).

3 We are currently developing components for a retina implant for RP-patients in cooperation with several partners from microelectronics-, microsystems- and retina surgery research centers. The conceived retina implant (Fig. 2) consists of a retina stimulator for ganglion cell stimulation and a retina encoder designed as neural net with flexible antagonistic receptive field properties (RF- BPN). The currently developed RF-BPN module, handling both slow potentials and impulse events, allows for modification of ten spatial and/or temporal parameters in order to adjust the RF-BPN to the desired receptive field properties of a given ganglion cell (Dacey and Petersen, 1992; Wässle and Boycott, 1992). Specifically, each RF-BPN module can be tuned in a learning process to the receptive field properties of a retinal P-cell type (about 60 % of the total ganglion cell population in the primate retina) or a M-cell type (about 25 %) with regard to parameters such as RF center, time constants, etc. (Eckmiller, 1994). Fig. 2 Retina implant schema Top: RF-BPNs consisting of photo sensors, bipolar cells, and about 500 ganglion cells as well as an implanted ganglion cell stimulator with about 5000 microcontacts Bottom: Modifiable parameters of the receptive field properties of RF-BPNs

4 Fig. 3 Anatomical scheme of the human retina with schematic rendering of a retina stimulator as microcontact foil. Open triangles depict microcontacts for stimulation Fig. 3 indicates the possible position of a highly flexible implanted foil with embedded selectively addressable microcontacts close to the inner limiting membrane of the retina. Please, note that light reaches the retina from the top. The photoreceptor layer in the middle (tips pointing to the bottom) is mostly degenerated in end-stage retinitis pigmentosa. The electrical stimuli from the individual micro contacts have to elicit action potentials in the axons or cell bodies of the ganglion cells in the top layer.

5 Fig. 4 Recording episode of an electronic retina encoder with real time properties. For explanation of the recording traces, see text. Fig. 4 gives a recording episode of our first electronic version of a retina encoder with real time properties. The oblique trace (from upper left to lower right) indicates the movement time course of a light spot moving over the photosensor array (consisting of some 30 photosensors) with constant velocity. The middle trace gives the voltage time course of a simulated retinal ganglion cell of the retina encoder. The corresponding receptive field has an excitatory circular center and an inhibitory ring-shaped periphery (on-center receptive field with P-cell properties). The spatial and temporal receptive field parameters can be varied in a training phase. The bottom trace indicates the impulse train of the corresponding ganglion cell output (pulse duration is 1 ms). Beginning in spring 1995, a transdisciplinary consortium with 16 team partners from neural computation, microsystems technology, biology, and ophthalmology (especially surgery) starts its first four-year phase for the development of a retina implant in close cooperation with patients. The goal of this first phase is the development and experimental test of the components as well as the integrated retina implant system in various vertebrate species. The experimental tests will include continuous trials over several months in order to explore tissue responses and to test various alternative methods and designs.

6 3 References Dacey, D. M., Petersen, M. R. (1992) Dendritic field size and morphology of midget and parasol ganglion cells of the human retina. Proc. Natl. Acad. Sci. USA, 89, Eckmiller, R. (1993) Concerning the challenge of neurotechnology. In: Neurobionics, Bothe, M.-W., Samii, M., and Eckmiller, R. (eds.), Elsevier, Amsterdam, pp Eckmiller, R. (ed.) (1994) Final Report of the Feasibility Study for a Neurotechnology Program, BMFT, Bonn. Humayun, M. S., Propst, R. H., Hickingbotham, D., de Juan, E., Dagnelie, G. (1993) Visual sensations produced by electrical stimulation of the retinal surface in patients with end-stage retinitis pigmentosa (RP). Invest. Ophthal. & Vis. Sci., 34 (Suppl.), 835. May, M. (1993) The electric eye: A light-sensitive chip grafted to the human retina promises rudimentary vision for some people who cannot see. Popular Science, August 93, pp Stone, J. L., Barlow, W. E., Humayun, M. S., de Juan, E., Milam, A. H. (1992) Morphometric analysis of macular photoreceptors and ganglion cells in retinas with retinitis pigmentosa, Arch. Ophthalmol., 110, Wässle, H., Boycott, B. B. (1991) Functional architecture of the mammalian retina. Physiol. Rev. 71,