2 research outputs found
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
Brain-Machine Interface for Reaching: Accounting for Target Size, Multiple Motor Plans, and Bimanual Coordination
<p>Brain-machine interfaces (BMIs) offer the potential to assist millions of people worldwide suffering from immobility due to loss of limbs, paralysis, and neurodegenerative diseases. BMIs function by decoding neural activity from intact cortical brain regions in order to control external devices in real-time. While there has been exciting progress in the field over the past 15 years, the vast majority of the work has focused on restoring of motor function of a single limb. In the work presented in this thesis, I first investigate the expanded role of primary sensory (S1) and motor (M1) cortex during reaching movements. By varying target size during reaching movements, I discovered the cortical correlates of the speed-accuracy tradeoff known as Fitts' law. Similarly, I analyzed cortical motor processing during tasks where the motor plan is quickly reprogrammed. In each study, I found that parameters relevant to the reach, such as target size or alternative movement plans, could be extracted by neural decoders in addition to simple kinematic parameters such as velocity and position. As such, future BMI functionality could expand to account for relevant sensory information and reliably decode intended reach trajectories, even amidst transiently considered alternatives.</p><p> The second portion of my thesis work was the successful development of the first bimanual brain-machine interface. To reach this goal, I expanded the neural recordings system to enable bilateral, multi-site recordings from approximately 500 neurons simultaneously. In addition, I upgraded the experiment to feature a realistic virtual reality end effector, customized primate chair, and eye tracking system. Thirdly, I modified the tuning function of the unscented Kalman filter (UKF) to conjointly represent both arms in a single 4D model. As a result of widespread cortical plasticity in M1, S1, supplementary motor area (SMA), and posterior parietal cortex (PPC), the bimanual BMI enabled rhesus monkeys to simultaneously control two virtual limbs without any movement of their own body. I demonstrate the efficacy of the bimanual BMI in both a subject with prior task training using joysticks and a subject naïve to the task altogether, which simulates a common clinical scenario. The neural decoding algorithm was selected as a result of a methodical comparison between various neural decoders and decoder settings. I lastly introduce a two-stage switching model with a classify step and predict step which was designed and tested to generalize decoding strategies to include both unimanual and bimanual movements.</p>Dissertatio