Os pesquisadores descrevem dois conjuntos de padraµes relacionados ao movimento no cortex visual que são baseados no movimento da cabea§a e se um animal estãona luz ou no escuro.
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)
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Para ter uma visão melhor do mundo ao seu redor, os animais estãoem movimento constante. Primatas e pessoas usam movimentos oculares complexos para focalizar sua visão (como os humanos fazem ao ler, por exemplo); pa¡ssaros, insetos e roedores fazem o mesmo movendo suas cabea§as e podem atéestimar distâncias dessa maneira. No entanto, como esses movimentos atuam nos circuitos elaborados de neura´nios que o cérebro usa para "ver" éamplamente desconhecido. E pode ser uma área de problema potencial, pois os cientistas criam redes neurais artificiais que imitam como a visão funciona em carros auta´nomos.
Para entender melhor a relação entre movimento e visão, uma equipe de pesquisadores de Harvard analisou o que acontece em uma das regiaµes prima¡rias do cérebro para analisar imagens quando os animais estãolivres para vagar naturalmente. Os resultados do estudo, publicado tera§a-feira na revista Neuron , sugerem que os circuitos de processamento de imagem no cortex visual prima¡rio não são são mais ativos quando os animais se movem, mas que recebem sinais de uma regia£o do cérebro que controla o movimento que éindependente da regia£o que processa o que o animal estãoolhando. Na verdade, os pesquisadores descrevem dois conjuntos de padraµes relacionados ao movimento no cortex visual que são baseados no movimento da cabea§a e se um animal estãona luz ou no escuro.
As descobertas relacionadas ao movimento foram inesperadas, uma vez que a visão tende a ser pensada como um sistema de computação feed-forward no qual a informação visual entra pela retina e viaja em circuitos neurais que operam em um caminho de ma£o única, processando a informação pea§a por pea§a . O que os pesquisadores viram aqui émais evidência de que o sistema visual tem muito mais componentes de feedback, onde a informação pode viajar em direções opostas do que se pensava.
Esses resultados oferecem um vislumbre de como a atividade neural funciona em uma regia£o sensorial do cérebro e se somam a um crescente corpo de pesquisas que estãoreescrevendo o modelo dida¡tico de visão no cérebro.
"Foi realmente surpreendente ver esse tipo de informação [relacionada ao movimento] no cortex visual porque tradicionalmente as pessoas pensavam no cortex visual como algo que apenas processa imagens", disse Grigori Guitchounts, pesquisador de pa³s-doutorado no Departamento de Neurobiologia de Harvard Faculdade de Medicina e principal autor do estudo. "Foi misterioso, a princapio, por que essa regia£o sensorial teria essa representação dos tipos específicos de movimentos que o animal estava fazendo."
Embora os cientistas não tenham sido capazes de dizer definitivamente por que isso acontece, eles acreditam que tem a ver com a forma como o cérebro percebe o que estãoao seu redor.
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"A explicação modelo para isso éque o cérebro de alguma forma precisa coordenar a percepção e a ação", disse Guitchounts. "Vocaª precisa saber quando uma entrada sensorial écausada por sua própria ação, ao contra¡rio de quando écausada por algo la¡ fora no mundo."
Para o estudo, Guitchounts se uniu ao ex-Professor do Departamento de Biologia Molecular e Celular David Cox, ex-aluno Javier Masis, MA '15, Ph.D. '18, e o pesquisador de pa³s-doutorado Steffen BE Wolff. O trabalho começou em 2017 e terminou em 2019, enquanto Guitchounts era um pesquisador graduado no laboratório de Cox. Uma versão pré-impressa do jornal publicada em janeiro.
A configuração tapica de experimentos anteriores de visão funcionava assim: animais, como ratos ou macacos, eram sedados, contidos de forma que suas cabea§as ficassem em posições fixas e recebiam estamulos visuais, como fotografias, para que os pesquisadores pudessem ver quais neura´nios no cérebro reagiram . A abordagem foi iniciada pelos cientistas de Harvard David H. Hubel e Torsten N. Wiesel na década de 1960 e, em 1981, eles ganharam um Praªmio Nobel de medicina por seus esforços. Muitos experimentos desde então seguiram seu modelo, mas ele não iluminou como o movimento afeta os neura´nios que analisam.
Os pesquisadores deste último experimento queriam explorar isso, então observaram 10 ratos andando por seus dias e noites. Os cientistas colocaram cada rato em um cercado, que também serviu de lar, e registraram continuamente os movimentos da cabea§a. Usando eletrodos implantados, eles mediram a atividade cerebral no cortex visual prima¡rio a medida que os ratos se moviam.
Metade das gravações foi feita com as luzes acesas. A outra metade foi gravada na escurida£o total. Os pesquisadores queriam comparar o que o cortex visual estava fazendo quando havia entrada visual e quando não havia. Para ter certeza de que o quarto estava escuro como breu, eles taparam qualquer fenda que pudesse permitir a entrada de luz, já que os ratos tem uma visão notoriamente boa a noite.
Os dados mostraram que, em média, os neura´nios do cortex visual dos ratos eram mais ativos quando os animais se moviam do que quando descansavam, mesmo no escuro. Isso pegou os pesquisadores desprevenidos: em uma sala totalmente escura, não hádados visuais para processar. Isso significava que a atividade vinha do cortex motor, não de uma imagem externa.
A equipe também notou que os padraµes neurais no cortex visual que disparavam durante o movimento diferiam no escuro e na luz, o que significa que não estavam diretamente conectados. Alguns neura´nios que estavam prontos para serem ativados no escuro estavam em uma espanãcie de modo de espera na luz.
Usando um algoritmo de aprendizado de ma¡quina, os pesquisadores codificaram os dois padraµes. Isso permitiu que eles não apenas soubessem para que lado um rato estava movendo sua cabea§a apenas olhando para a atividade neural em seu cortex visual, mas também previam o movimento várias centenas de milissegundos antes que o rato o fizesse.
Os pesquisadores confirmaram que os sinais de movimento vinham da área motora do cérebro, concentrando-se no cortex motor secunda¡rio. Eles o destruaram cirurgicamente em vários ratos e depois realizaram os experimentos novamente. Os ratos nos quais essa área do cérebro foi lesada não emitiram mais sinais no cortex visual. No entanto, os pesquisadores não foram capazes de determinar se o sinal se origina no cortex motor secunda¡rio . Sa³ pode ser por onde passa, disseram.
Além disso, os cientistas apontaram algumas limitações em suas descobertas. Por exemplo, eles mediram apenas o movimento da cabea§a e não mediram o movimento dos olhos . O estudo também ébaseado em roedores, que são noturnos. Seus sistemas visuais compartilham semelhanças com humanos e primatas, mas diferem em complexidade. Ainda assim, o artigo adiciona novas linhas de pesquisa e as descobertas podem ser potencialmente aplicadas a redes neurais que controlam a visão de ma¡quina, como aquelas em veaculos auta´nomos.
"a‰ tudo para entender melhor como a visão realmente funciona", disse Guitchounts. "A Neurociênciaestãoentrando em uma nova era onde entendemos que percepção e ação são loops entrelaa§ados ... Nãoháção sem percepção e não hápercepção sem ação. Agora temos a tecnologia para medir isso."