Gentileza gera Gentileza e computação dendrítica em neurônios críticos


Gentileza teria fundamentos genéticos, sugere estudo

AFPPor Rouf Bhat | AFP 

  • Homem ajuda idoso a atravessar uma ponte improvisada sobre a enxurrada que arrastou a estrada entre Leh e Srinagar, na Caxemira indianaHomem ajuda idoso a atravessar uma ponte improvisada sobre a enxurrada que arrastou …

Pessoas dotadas de um certo traço genético são mais gentis e carinhosas do que as demais e esta característica pode ser rapidamente identificada por estranhos, revelou um estudo publicado esta segunda-feira nos Estados Unidos.

Esta variação é relacionada com a ocitocina, gene receptor também conhecido como “hormônio do amor” porque costuma se manifestar nas relações sexuais e incita comportamentos sociais como união e empatia.

Cientistas da Universidade do estado do Oregon desenvolveram um experimento no qual 23 casais, cujos traços genéticos eram conhecidos dos pesquisadores mas não dos observadores, foram filmados.

Pediu-se a um dos membros do casal que contasse ao outro sobre um período de sofrimento de sua vida. Os observadores deviam abservar o ouvinte por 20 segundos, com o som desligado.

Na maior parte dos casos, os observadores conseguiram identificar quais ouvintes tinham o “gene da gentileza” e quais não, revelou a pesquisa, cujos resultados foram publicados na edição de 14 de novembro do periódico Proceedings of the National Academy of Sciences.

“Nossas descobertas sugerem que até mesmo a variação genética mais sutil pode ter impacto tangível no comportamento das pessoas e que estas diferenças comportamentais são rapidamente notadas pelos demais”, explicou o principal autor do estudo, Aleksandr Kogan, estudante de pós-doutorado da Universidade de Toronto.

Nove entre 10 pessoas, consideradas “menos confiáveis” pelos observadores neutros tinham a versão A do gene, enquanto 6 entre os 10 considerados os “mais pró-sociais” tinham o genótipo GG.

Os participantes da pesquisa foram testados antecipadamente e identificados como detentores dos genótipos GG, AG ou AA para a sequência de DNA do gene receptor deocitocina (OXTR).

As pessoas com duas cópias do alelo G foram geralmente consideradas mais empáticas, confiáveis e amorosas. As dotadas dos genótipos AG ou AA tenderam a dizer que se sentiam menos confiantes de modo geral e menor sensibilidade parental. Pesquisas anteriores demonstraram que estes indivíduos também apresentavam um risco mais elevado de desenvolver autismo.

“Nosso estudo questionou se estas diferenças se manifestam em comportamentos rapidamente detectáveis por estranhos e demonstrou que são”, explicou.

No entanto, nenhum traço genético pode prever totalmente o comportamento de uma pessoa e é necessário fazer mais pesquisas para descobrir como esta variação afeta a biologia comportamental.

Na vida acadêmica, você encontra certas situações onde é mais necessário inteligência social do que intelectual. Por exemplo, como tratar estudantes com geek syndrome? Bom, inspirado na notícia anterior, tentei a tática do Gentileza gera Gentileza e parece que deu certo.

Dear Osame,
Thank you for your explanation, my understanding about your paper improves much with your help. Your warm heart impresses me!
Be happy and healthy.
Z.

Dear Z., The model studied is a general one, that is, an excitable media with probabilistic couplings. The level where we can apply such model depends on the interest of the researcher: the elements could be persons in a epidemiological model (so, our model would be a probabilistic SIRS model), a neuronal network model (with excitatory couplings), a model of a glomerulus in the olfactory bulb (the particular application that we made in the paper), a mean field model of a dendritic arbor (see reference bellow) or even as a model of sensor networks of bacteria (to model bacterial chemotaxis). 

The particular level which you desire to apply the model will constrain and set the acceptable parameter ranges. If you are interested to model excitatory networks of neurons, you are right that one shoud use n=3 or n=4, so that the refractory period is similar to the spike width.

As you can see in Eq. (3), the refractory time governed by n affects the results only quantitatively, not qualitatively. We have studied all the cases from n=3 (that is, if spike = 1ms, then refractory period = 1ms) up to n = 10, but reported only the n=10 case because indeed we was interested in large refractory periods in the glomerulus (the particular application wich we made at the final part of the paper).

As stated in the pag. 349 of the paper, we have also studied the case with assymetrical p_ij and no difference is found. The reference to synchronization phenomena in the glomerulus is made as evidence of the presence of gap junctions in that system (More strong evidence is by now avaiable by the recent direct observation of such electrical synapses). If we apply external inputs to the system, synchronization appears, as can be seen in Fig.2c and 2d. This sinchronization under inputs is what is observed in the experimental papers. Only the spontaneous activity is in the form of avalanches, as found in experiments by Plenz. Our couplings are fast in the sense that there is no delay times at the couplings, when a site is excited, the neighbours could be excited at the following time step, without delay.

I hope that these observations coul be useful for your interests.

Presently we are working with dendritic computation, with a similar model in a tree structure, see here and here. In this model the refractory period is small and the couplings vary from the symmetric case to the full assymetric case.

Best regards,

Osame

Dear Osame,
I’m sorry I did not express myself clearly. My question is not about simulation, but about the physical meaning about your cellular automata model. It seems not so reasonable.

First, in your model, there is a very long refractory period for each cell, but in real neurons, the refractory period is usually very short. So I wonder what makes you do such an adventurous hypothesis.

Second, in your paper, you mentioned many times about the electrical synapse. The electrical synapses have two properties, it is fast and
symmetrical. But I cannot figure out what ingredient in your model represents the property of “fast”. As to the property of symmetrical, you assume that p_ij=p_ji; but I don’t know whether the network can still perform so well without such symmetrical property. Have you done such a simulation on your computer? How the result?

What’s more, still about the electrical synapse, you refer some articles about the electrical synapses and the synchronization of the network in
your paper. But I’m afraid I still cannot figure out what’s the relationship between the contents of the papers you mentioned and the content of your own paper. It seems that there is nothing about synchronization of the network in your paper.

Best wishes,
Z.

Dear Z.,
I am not sure about what is your question. The model is simply a generalized Greenberg-Hastings cellular automata in a random network where the conections p_ij are draw from a simple uniform distribution in [0,pmax]. Notice however that the mean field calculation assumes that p_ij = p (homogeneous network) and that this approximation seems to describe the behavior very well.

If you are having any difficulty to reproduce the results, I can send you more details about the exact procedure for the simulations.

Cheers,

Osame

—–Menssagem Original—–
De: “Z. B.”
Enviado 08/12/2011 07:20:43

Assunto: A question about your paper

Dear Prof. Kinouchi,

I’m a Chinese student, recently I’m reading your paper “Optimal dynamical range of excitable networks at criticality”  published in Nature Physics. However, I’m really puzzled by the model you proposed: where does it come from, how do you think out? Could you explain about it for me?

Thanks!

Besh wishes,

Z.

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