Redes cerebrales para el control mental

Cómo Red de Neurociencia ha creado una nueva era de Control Mental
MIT Technology Review


El cerebro humano es una red compleja. Es por eso que los neurocientíficos esperan usar la teoría de redes para controlar las mentes.

Al salir por la tecnología de la arXiv 19 de de octubre de, el año 2016

Las redes complejas forman la columna vertebral de la sociedad moderna: Internet, la red de aviación, el patrón de conexiones entre los individuos. Y ejemplos más complejos surgen constantemente, la forma en que interactúan los genes en las células, cómo la información fluye a través del sistema bancario y el ecosistema.

Cuanto más complejo es el sistema, más difícil es controlar. Sin embargo, los informáticos, médicos, economistas y el ejercicio como un mínimo de control sobre muchas de estas redes.

Y eso plantea una pregunta interesante: ¿es posible ejercer el mismo tipo de control sobre la red más compleja que conocemos: el cerebro humano?



Hoy en día tenemos una respuesta de tipo, gracias a la obra de John Medaglia en la Universidad de Pennsylvania en Filadelfia y algunos compañeros que evalúan la disciplina que está surgiendo en la intersección entre la neurociencia a la red y la teoría de control de la red. "Una cuestión fundamental ... es cómo modular una red cerebro humano para el tratamiento de los déficits cognitivos o mejorar las capacidades mentales", dicen. "Postulamos que el control de la red refiere fundamentalmente a control de la mente."

La idea básica detrás de este tipo de control es sencillo. La inyección de energía en una parte de una red debe influir en la actividad en otras partes de la red.

En el cerebro, este tipo de manipulación ya se utiliza en las técnicas de estimulación profunda del cerebro, tales como los utilizados para la enfermedad de Parkinson. Esto implica la inyección de energía en una parte del cerebro llamada ganglios basales, que está implicado en el movimiento. Esto luego reduce el deterioro del movimiento.

Una técnica similar se utiliza también para el trastorno obsesivo compulsivo, donde las personas experimentan impulsos abrumadores participar en un comportamiento repetitivo. Esto a menudo se asocia con la actividad eléctrica inusual en los circuitos fronto-estriado del cerebro. La estimulación cerebral profunda puede normalizar esta actividad y mejorar sustancialmente la calidad de vida.

A pesar del éxito de este tipo de técnicas, Medaglia y co señalan que existen retos significativos en el control de otros comportamientos. Un problema es que la estimulación no sólo influye en una parte del cerebro, pero tiende a cascada a través de muchas áreas en formas que son difíciles de caracterizar.

Es por eso que la comprensión de la conectividad en el cerebro es un importante objetivo futuro. Este es el objetivo de los diversos proyectos de "conectoma" en todo el mundo: al mapa de las vías estructurales en el cerebro.

Y es que ya está empezando a sugerir que el cerebro emplea diferentes estrategias de control. Cada una de estas estrategias son objetivos potenciales para el control de la mente.

Por ejemplo, los neurocientíficos piensan que el sistema fronto-parietal controla nuestra capacidad de cambiar entre tareas. Curiosamente, este sistema no está fuertemente ligada a otras partes del cerebro, pero el trabajo teórico ya ha demostrado que parece que funciona moviendo el cerebro en estados difíciles de llegar a lo largo de una especie de panorama energético. Así que una vía para el control de la mente podría ser el uso de inyecciones de energía para guiar el cerebro a través de este paisaje.

Apenas cómo se puede hacer esto no es del todo clara, pero hay varias tecnologías que tienen potencial. Estos incluyen la estimulación magnética transcraneal, que utiliza un campo magnético externo para inducir corrientes en partes del cerebro, junto con diversos estimuladores implantados, que inyectan directamente la energía. La mejora de la resolución de este tipo de inyección de energía es un importante objetivo futuro.

No hay discusión de control cerebral estaría completa sin una mención de la ética. Medaglia y co pasan algún tiempo esbozar las ideas actuales sobre este tema. Ellos basan sus argumentos en los cuatro principios básicos de la ética médica y de investigación: no maleficencia, la beneficencia, la justicia y el derecho a la libre determinación.

Esta es un área que tendrá que evolucionar a medida que surgen nuevas técnicas. "A medida que la ciencia de los avances de control mental, será importante para aclarar las prácticas de control aceptables con respecto a nuestra naturaleza fundamental y la propia identidad", dicen Medaglia y co.

Otro de los objetivos a la reflexión es comprender el vínculo entre el control neural y el control psicológico. "El mapeo entre la dinámica del cerebro y los procesos cognitivos específicos será fundamental para informar a control psicológico (es decir," mente ")," decir Medaglia y co.

Y ahí radica un punto ciego importante en este trabajo el papel de la información. Los procesos de la mente son claramente basada en la información. Y gran parte de la psicología se ha centrado en cómo la información puede cambiar los estados del cerebro. Por ejemplo, cambiar el estado emocional de una persona con un viaje al cine o leyendo un libro.

Este es el control mental basado en la información. Y, sin embargo Medaglia y co no mencionan este tipo de efectos basados ​​en la información.

Tal vez eso es comprensible. El papel de la información en los procesos cerebrales es poco conocida. Los neurólogos no entienden los códigos neuronales en el trabajo en nuestro cerebro.

Hasta que tienen que entender y más, las técnicas actuales parecerán crudo. En comparación, nadie intentaría solucionar el mal funcionamiento de un teléfono inteligente con el zapping con una corriente de un par de electrodos. Tampoco tendrían que reparar un sitio web chocado con un potente campo magnético externo.

De hecho, sólo una pequeña fracción de un posible mal funcionamiento de tecnologías de la información podría ser abordado de esta manera.

Y lo que es probable que sea con el cerebro humano. Un enfoque basado en la información es probable que sea mucho más potente.

El vínculo entre la información y la mente es hoy poco conocida. Si una mejor comprensión es una herencia de este tipo de trabajo, que habrá sido un importante paso adelante.

Ref: arxiv.org/abs/1610.04134: Mind Control: Frontiers in Guiding the Mind

Glattfelder: "¿Quien controla el Mundo?"

"When the crisis came, the serious limitations of existing economic and financial models immediately became apparent." "There is also a strong belief, which I share, that bad or oversimplistic and overconfident economics helped create the crisis."

Now, you've probably all heard of similar criticism coming from people who are skeptical of capitalism. But this is different. This is coming from the heart of finance. The first quote is from Jean-Claude Trichet when he was governor of the European Central Bank. The second quote is from the head of the U.K. Financial Services Authority. Are these people implyingthat we don't understand the economic systems that drive our modern societies? It gets worse. "We spend billions of dollars trying to understand the origins of the universe while we still don't understand the conditions for a stable society, a functioning economy, or peace."

What's happening here? How can this be possible? Do we really understand more about the fabric of reality than we do about the fabric which emerges from our human interactions?Unfortunately, the answer is yes. But there's an intriguing solution which is coming from what is known as the science of complexity.

To explain what this means and what this thing is, please let me quickly take a couple of steps back. I ended up in physics by accident. It was a random encounter when I was young, and since then, I've often wondered about the amazing success of physics in describing the reality we wake up in every day. In a nutshell, you can think of physics as follows. So you take a chunk of reality you want to understand and you translate it into mathematics. You encode it into equations. Then predictions can be made and tested.We're actually really lucky that this works, because no one really knows why the thoughts in our heads should actually relate to the fundamental workings of the universe. Despite the success, physics has its limits. As Dirk Helbing pointed out in the last quote, we don't really understand the complexity that relates to us, that surrounds us. This paradox is what got me interested in complex systems. So these are systems which are made up of many interconnected or interacting parts: swarms of birds or fish, ant colonies, ecosystems, brains, financial markets. These are just a few examples. Interestingly, complex systems are very hard to map into mathematical equations, so the usual physics approach doesn't really work here.

So what do we know about complex systems? Well, it turns out that what looks like complex behavior from the outside is actually the result of a few simple rules of interaction.This means you can forget about the equations and just start to understand the system by looking at the interactions, so you can actually forget about the equations and you just start to look at the interactions. And it gets even better, because most complex systems have this amazing property called emergence. So this means that the system as a wholesuddenly starts to show a behavior which cannot be understood or predicted by looking at the components of the system. So the whole is literally more than the sum of its parts. And all of this also means that you can forget about the individual parts of the system, how complex they are. So if it's a cell or a termite or a bird, you just focus on the rules of interaction.

As a result, networks are ideal representations of complex systems. The nodes in the network are the system's components and the links are given by the interactions. So what equations are for physics, complex networks are for the study of complex systems.

This approach has been very successfully applied to many complex systems in physics, biology, computer science, the social sciences, but what about economics? Where are economic networks? This is a surprising and prominent gap in the literature. The study we published last year called "The Network of Global Corporate Control" was the first extensive analysis of economic networks. The study went viral on the Internet and it attracted a lot of attention from the international media. This is quite remarkable, because, again, why did no one look at this before? Similar data has been around for quite some time.

What we looked at in detail was ownership networks. So here the nodes are companies, people, governments, foundations, etc. And the links represent the shareholding relations,so Shareholder A has x percent of the shares in Company B. And we also assign a value to the company given by the operating revenue. So ownership networks reveal the patterns of shareholding relations. In this little example, you can see a few financial institutions with some of the many links highlighted.

Now you may think that no one's looked at this before because ownership networks arereally, really boring to study. Well, as ownership is related to control, as I shall explain later,looking at ownership networks actually can give you answers to questions like, who are the key players? How are they organized? Are they isolated? Are they interconnected? And what is the overall distribution of control? In other words, who controls the world? I think this is an interesting question.

And it has implications for systemic risk. This is a measure of how vulnerable a system is overall. A high degree of interconnectivity can be bad for stability, because then the stress can spread through the system like an epidemic.

Scientists have sometimes criticized economists who believe ideas and concepts are more important than empirical data, because a foundational guideline in science is: Let the data speak. Okay. Let's do that.

So we started with a database containing 13 million ownership relations from 2007. This is a lot of data, and because we wanted to find out who rules the world, we decided to focus on transnational corporations, or TNCs for short. These are companies that operate in more than one country, and we found 43,000. In the next step, we built the network around these companies, so we took all the TNCs' shareholders, and the shareholders' shareholders, etc., all the way upstream, and we did the same downstream, and ended up with a network containing 600,000 nodes and one million links. This is the TNC network which we analyzed.

And it turns out to be structured as follows. So you have a periphery and a center which contains about 75 percent of all the players, and in the center there's this tiny but dominant core which is made up of highly interconnected companies. To give you a better picture,think about a metropolitan area. So you have the suburbs and the periphery, you have a center like a financial district, then the core will be something like the tallest high rise building in the center. And we already see signs of organization going on here. Thirty-six percent of the TNCs are in the core only, but they make up 95 percent of the total operating revenue of all TNCs.

Okay, so now we analyzed the structure, so how does this relate to the control? Well, ownership gives voting rights to shareholders. This is the normal notion of control. And there are different models which allow you to compute the control you get from ownership. If you have more than 50 percent of the shares in a company, you get control, but usually it depends on the relative distribution of shares. And the network really matters. About 10 years ago, Mr. Tronchetti Provera had ownership and control in a small company, which had ownership and control in a bigger company. You get the idea. This ended up giving him control in Telecom Italia with a leverage of 26. So this means that, with each euro he invested, he was able to move 26 euros of market value through the chain of ownership relations.

Now what we actually computed in our study was the control over the TNCs' value. This allowed us to assign a degree of influence to each shareholder. This is very much in the sense of Max Weber's idea of potential power, which is the probability of imposing one's own will despite the opposition of others.

If you want to compute the flow in an ownership network, this is what you have to do. It's actually not that hard to understand. Let me explain by giving you this analogy. So think about water flowing in pipes where the pipes have different thickness. So similarly, the control is flowing in the ownership networks and is accumulating at the nodes. So what did we find after computing all this network control? Well, it turns out that the 737 top shareholders have the potential to collectively control 80 percent of the TNCs' value. Now remember, we started out with 600,000 nodes, so these 737 top players make up a bit more than 0.1 percent. They're mostly financial institutions in the U.S. and the U.K. And it gets even more extreme. There are 146 top players in the core, and they together have the potential to collectively control 40 percent of the TNCs' value.

What should you take home from all of this? Well, the high degree of control you saw is very extreme by any standard. The high degree of interconnectivity of the top players in the core could pose a significant systemic risk to the global economy and we could easily reproduce the TNC network with a few simple rules. This means that its structure is probably the result of self-organization. It's an emergent property which depends on the rules of interaction in the system, so it's probably not the result of a top-down approach like a global conspiracy.

Our study "is an impression of the moon's surface. It's not a street map." So you should take the exact numbers in our study with a grain of salt, yet it "gave us a tantalizing glimpseof a brave new world of finance." We hope to have opened the door for more such research in this direction, so the remaining unknown terrain will be charted in the future. And this is slowly starting. We're seeing the emergence of long-term and highly-funded programs which aim at understanding our networked world from a complexity point of view. But this journey has only just begun, so we will have to wait before we see the first results.

Now there is still a big problem, in my opinion. Ideas relating to finance, economics, politics, society, are very often tainted by people's personal ideologies. I really hope that this complexity perspective allows for some common ground to be found. It would be really great if it has the power to help end the gridlock created by conflicting ideas, which appears to be paralyzing our globalized world. Reality is so complex, we need to move away from dogma. But this is just my own personal ideology.


Thank you.


(Applause)