7 research outputs found
An Adaptive Neural Spike Processor With Embedded Active Learning for Improved Unsupervised Sorting Accuracy
There is a need for integrated spike sorting processors in implantable devices with low power consumption that have improved accuracy. Learning the characteristics of the variable input neural signals and adapting the functionality of the sorting process can improve the accuracy. An adaptive spike sorting processor is presented accounting for the variation in the input signal noise characteristics and the variable difficulty in the selection of the spike characteristics, which significantly improves the accuracy. The adaptive spike processor was fabricated in 180-nm CMOS technology for proof of concept. It performs conditional detection, alignment, adaptive feature extraction, and online clustering with sorting threshold self-tuning capability. The chip was tested under different input signal conditions to demonstrate its adaptation capability providing a median classification accuracy of 84.5 & #x0025; and consuming 148 & #x03BC;W from a 1.8 V supply voltage
Efficient Approximation of Action Potentials with High-Order Shape Preservation in Unsupervised Spike Sorting
This paper presents a novel approximation unit
added to the conventional spike processing chain which provides
an appreciable reduction of complexity of the high-hardware
cost feature extractors. The use of the Taylor polynomial is
proposed and modelled employing its cascaded derivatives to
non-uniformly capture the essential samples in each spike for
reliable feature extraction and sorting. Inclusion of the
approximation unit can provide 3X compression (i.e. from 66 to
22 samples) to the spike waveforms while preserving their
shapes. Detailed spike waveform sequences based on in-vivo
measurements have been generated using a customized neural
simulator for performance assessment of the approximation unit
tested on six published feature extractors. For noise levels σN
between 0.05 and 0.3 and groups of 3 spikes in each channel, all
the feature extractors provide almost same sorting performance
before and after approximation. The overall implementation
cost when including the approximation unit and feature
extraction shows a large reduction (i.e. up to 8.7X) in the
hardware costly and more accurate feature extractors, offering
a substantial improvement in feature extraction design
Accurate, Very Low Computational Complexity Spike Sorting Using Unsupervised Matched Subspace Learning
This paper presents an adaptable dictionary-based feature extraction approach for spike sorting offering high accuracy and low computational complexity for implantable applications. It extracts and learns identifiable features from evolving subspaces through matched unsupervised subspace filtering. To provide compatibility with the strict constraints in implantable devices such as the chip area and power budget, the dictionary contains arrays of {-1, 0 and 1} and the algorithm need only process addition and subtraction operations. Three types of such dictionary were considered. To quantify and compare the performance of the resulting three feature extractors with existing systems, a neural signal simulator based on several different libraries was developed. For noise levels between 0.05 and 0.3 and groups of 3 to 6 clusters, all three feature extractors provide robust high performance with average classification errors of less than 8% over five iterations, each consisting of 100 generated data segments. To our knowledge, the proposed adaptive feature extractors are the first able to classify reliably 6 clusters for implantable applications. An ASIC implementation of the best performing dictionary-based feature extractor was synthesized in a 65-nm CMOS process. It occupies an area of 0.09 mm2 and dissipates up to about 10.48 μW from a 1 V supply voltage, when operating with 8-bit resolution at 30 kHz operating frequency
An Accurate and Real-time Method for Resolving Superimposed Action Potentials in MultiUnit Recordings
Objective: Spike sorting of muscular and neural recordings requires separating action potentials that overlap in time (superimposed action potentials (APs)). We propose a new algorithm for resolving superimposed action potentials, and we test it on intramuscular EMG (iEMG) and intracortical recordings. Methods: Discrete-time shifts of the involved APs are first selected based on a heuristic extension of the peel-off algorithm. Then, the time shifts that provide the minimal residual Euclidean norm are identified (Discrete Brute force Correlation (DBC)). The optimal continuous-time shifts are then estimated (High-Resolution BC (HRBC)). In Fusion HRBC (FHRBC), two other cost functions are used. A parallel implementation of the DBC and HRBC algorithms was developed. The performance of the algorithms was assessed on 11,000 simulated iEMG and 14,000 neural recording superpositions, including two to eight APs, and eight experimental iEMG signals containing four to eleven active motor units. The performance of the proposed algorithms was compared with that of the Branch-and-Bound (BB) algorithm using the Rank-Product (RP) method in terms of accuracy and efficiency. Results: The average accuracy of the DBC, HRBC and FHRBC methods on the entire simulated datasets was 92.16\ub117.70, 93.65\ub116.89, and 94.90\ub115.15 (%). The DBC algorithm outperformed the other algorithms based on the RP method. The average accuracy and running time of the DBC algorithm on 10.5 ms superimposed spikes of the experimental signals were 92.1\ub121.7 (%) and 2.3\ub115.3 (ms). Conclusion and Significance: The proposed algorithm is promising for real-time neural decoding, a central problem in neural and muscular decoding and interfacing
An adaptive neural spike processor with embedded active learning for improved unsupervised sorting accuracy
There is a need for integrated spike sorting processors in implantable devices with low power consumption that have improved accuracy. Learning the characteristics of the variable input neural signals and adapting the functionality of the sorting process can improve the accuracy. An adaptive spike sorting processor is presented accounting for the variation in the input signal noise characteristics and the variable difficulty in the selection of the spike characteristics, which significantly improves the accuracy. The adaptive spike processor was fabricated in 180-nm CMOS technology for proof of concept. It performs conditional detection, alignment, adaptive feature extraction, and online clustering with sorting threshold self-tuning capability. The chip was tested under different input signal conditions to demonstrate its adaptation capability providing a median classification accuracy of 84.5% and consuming 148 μW from a 1.8 V supply voltage.</p
De animais a máquinas : humanos tecnicamente melhores nos imaginários de futuro da convergência tecnológica
Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Sociais, Departamento de Sociologia, 2020.O tema desta investigação é discutir os imaginários sociais de ciência e tecnologia que emergem
a partir da área da neuroengenharia, em sua relação com a Convergência Tecnológica de quatro
disciplinas: Nanotecnologia, Biotecnologia, tecnologias da Informação e tecnologias Cognitivas -
neurociências- (CT-NBIC). Estas áreas desenvolvem-se e são articuladas por meio de discursos
que ressaltam o aprimoramento das capacidades físicas e cognitivas dos seres humanos, com
o intuito de construir uma sociedade melhor por meio do progresso científico e tecnológico, nos
limites das agendas de pesquisa e desenvolvimento (P&D).
Objetivos:
Os objetivos nesse cenário, são discutir as implicações éticas, econômicas, políticas e sociais
deste modelo de sistema sociotécnico. Nos referimos, tanto as aplicações tecnológicas, quanto
as consequências das mesmas na formação dos imaginários sociais, que tipo de relações se
estabelecem e como são criadas dentro desse contexto.
Conclusão:
Concluímos na busca por refletir criticamente sobre as propostas de aprimoramento humano
mediado pela tecnologia, que surgem enquanto parte da agenda da Convergência Tecnológica
NBIC. No entanto, as propostas de melhoramento humano vão muito além de uma agenda de
investigação. Há todo um quadro de referências filosóficas e políticas que defendem o
aprimoramento da espécie, vertentes estas que se aliam a movimentos trans-humanistas e pós-
humanistas, posições que são ao mesmo tempo éticas, políticas e econômicas. A partir de nossa
análise, entendemos que ciência, tecnologia e política estão articuladas, em coprodução, em
relação às expectativas de futuros que são esperados ou desejados. Ainda assim, acreditamos
que há um espaço de diálogo possível, a partir do qual buscamos abrir propostas para o debate
público sobre questões de ciência e tecnologia relacionadas ao aprimoramento da espécie
humana.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)The subject of this research is to discuss the social imaginaries of science and technology that
emerge from the area of neuroengineering in relation with the Technological Convergence of four
disciplines: Nanotechnology, Biotechnology, Information technologies and Cognitive technologies
-neurosciences- (CT-NBIC). These areas are developed and articulated through discourses that
emphasize the enhancement of human physical and cognitive capacities, the intuition it is to build
a better society, through the scientific and technological progress, at the limits of the research
and development (R&D) agendas.
Objectives:
The objective in this scenery, is to discuss the ethic, economic, politic and social implications of
this model of sociotechnical system. We refer about the technological applications and the
consequences of them in the formation of social imaginaries as well as the kind of social relations
that are created and established in this context.
Conclusion:
We conclude looking for critical reflections about the proposals of human enhancement mediated
by the technology. That appear as a part of the NBIC technologies agenda. Even so, the
proposals of human enhancement go beyond boundaries that an investigation agenda. There is
a frame of philosophical and political references that defend the enhancement of the human
beings. These currents that ally to the transhumanism and posthumanism movements, positions
that are ethic, politic and economic at the same time. From our analysis, we understand that
science, technology and politics are articulated, are in co-production, regarding the expected and
desired futures. Even so, we believe that there is a space of possible dialog, from which we look
to open proposals for the public discussion on questions of science and technology related to
enhancement of human beings