[Paleopsych] Intelligent Bacteria

Eshel Ben-Jacob eshel at physics.ucsd.edu
Sat Apr 23 02:13:25 UTC 2005

Hi to all,
The new paper in trends in microibiology is quite interesting but is limited 
in scope (and references) it does not give a reference to our paper on 
Bacterial intelligence published in Trends just 8 months ago. He also does 
not give reference to any of Bassler papers.
Attached are both papers. All the best, Eshel

Eshel Ben-Jacob.
Professor of Physics
The Maguy-Glass Professor
in Physics of Complex Systems

eshel at tamar.tau.ac.il    ebenjacob at ucsd.edu
Home Page: http://star.tau.ac.il/~eshel/
Visit http://physicaplus.org.il - PhysicaPlus
the online magazine of the Israel Physical Society

School of Physics and Astronomy           10/2004 -10/2005
Tel Aviv University, 69978 Tel Aviv, Israel      Center for Theoretical 
Biological Physics
Tel 972-3-640 7845/7604 (Fax) -6425787      University of California San 
    La Jolla, CA 92093-0354 USA
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----- Original Message ----- 
From: "G. Reinhart-Waller" <waluk at earthlink.net>
To: "The new improved paleopsych list" <paleopsych at paleopsych.org>
Sent: Saturday, April 23, 2005 2:55 AM
Subject: Re: [Paleopsych] Intelligent Bacteria

> Bacteria live in groups, communicate and thus must possess intelligence. 
> Genes are on one level but by not including the meme portion of behavior, 
> one is only able to understand a portion of what intelligence actually is.
> Gerry Reinhart-Waller
> Steve Hovland wrote:
>>Our own intelligence is mediated by neuropeptides
>>and enzymes, so if we find those in bacteria,
>>we find intelligence...
>>Steve Hovland
>>-----Original Message-----
>>From: Buck, Ross [SMTP:ross.buck at uconn.edu]
>>Sent: Friday, April 22, 2005 8:28 AM
>>To: The new improved paleopsych list
>>Subject: RE: [Paleopsych] Intelligent Bacteria
>>  _____
>>From: paleopsych-bounces at paleopsych.org
>>[mailto:paleopsych-bounces at paleopsych.org] On Behalf Of
>>Thrst4knw at aol.com
>>Sent: Monday, April 18, 2005 3:14 PM
>>To: paleopsych at paleopsych.org
>>Cc: ToddStark at aol.com; HowlBloom at aol.com
>>Subject: [Paleopsych] Intelligent Bacteria
>>Intelligent bacteria?
>>For the most primitive beings in the web of life, some researchers
>>claim, "simple" might not mean "stupid."
>>Posted April 18, 2005
>>Special to World Science
>>Bacteria are by far the simplest things alive, at least among things
>>generally agreed on as being alive. Next to one of these single-celled
>>beings, one cell of our bodies looks about as complex as a human does
>>compared to a sponge.
>> <http://www.hometown.aol.com/scipage/images/plate-CT-docu0043b.jpg>
>>A colony of Paenibacillus dendritiformis bacteria, which some
>>researchers say can organize themselves into different types of
>>extravagant formations to maximize food intake for given conditions.
>>According to some, this reflects a bacterial intelligence. (Courtesy
>>Eshel Ben-Jacob <http://star.tau.ac.il/~inon/pictures/pictures.html> ,
>>Tel Aviv University, Israel)
>>  _____
>>Yet the humble microbes may have a rudimentary form of intelligence,
>>some researchers have found.
>>The claims seem to come as a final exclamation point to a long series of
>>increasingly surprising findings of sophistication among the microbes,
>>including apparent cases of cooperation and even altruism.
>>But there is no clear measurement or test that scientists can use, based
>>on the behavior alone, to determine whether it reflects intelligence.
>>Some researchers, though, have found a systematic way of addressing the
>>question and begun looking into it. This method involves focusing not so
>>much on the behavior itself as the nuts and bolts behind it-a complex
>>system of chemical "signals" that flit both within and among bacteria,
>>helping them decide what to do and where to go.
>>Researchers have found that this process has similarities to a type of
>>human-made machine designed to act as a sort of simplified brain. These
>>devices solve some simple problems in a manner more human-like than
>>The devices, called neural networks, also run on networks of signals
>>akin to those of the bacteria. The devices use the networks to "learn"
>>tasks such as distinguishing a male from a female in photographs-typical
>>sorts of problems that are easy for humans but hard for traditional
>>The similarities in the bacterial and neural network signaling systems
>>are far more than superficial, wrote one researcher, Klaas J.
>>Hellingwerf, in the April issue of the journal Trends in Microbiology.
>>He found that the bacterial system contains all the important features
>>that make neural networks work, leading to the idea that the bacteria
>>have "a minimal form of intelligence."
>>Bacterial signaling possesses all four of the key properties that neural
>>network experts have identified as essential to make such devices work,
>>Hellingwerf elaborated. The only weak link in the argument, he added, is
>>that for one of those properties, it's not clear whether bacteria
>>exhibit it to a significant extent. This may be where future research
>>should focus, he wrote.
>>Cooperation and altruism
>>The comparison of bacterial signaling with neural networks is not the
>>only evidence that has nudged researchers closer to the concept that
>>bacteria might possess a crude intelligence-though few scientists would
>>go as far as to use that word.
>>One of the other lines of evidence is a simple examination of bacterial
>>This behavior is strikingly versatile, researchers have found in recent
>>years; bacteria can cope with a remarkably wide range of situations by
>>taking appropriate actions for each. For instance, the deadly
>>Pseudomonas aeruginosa can make a living by infecting a wide variety of
>>animal and plant tissues, each of which is a very different type of
>>environment in which to live and find sustenance.
>>Furthermore, bacteria cooperate: they can group together to take on
>>tasks that would be difficult or impossible for one to handle alone. In
>>a textbook example, millions of individuals of the species Myxococcus
>>xanthus can bunch up to form a "predatory" colony that moves and changes
>>direction collectively toward possible food sources.
>>Some examples of bacterial cooperation have even led researchers to
>>propose that bacteria exhibit a form of altruism. For instance, some
>>strains of Escherichia coli commit suicide when infected by a virus,
>>thereby protecting their bacterial neighbors from infection.
>>But until recently, few or no scientists had seriously suggested these
>>behaviors reflected intelligence.
>>For instance, bacterial "altruism" may be a simple outcome of evolution
>>that has nothing to do with concern for the welfare of others, wrote the
>>University of Bonn's Jan-Ulrich Kreft in last August's issue of the
>>research journal Current Biology. Thus he didn't suggest that any
>>process akin to thinking was at work.
>>But one thing that ties these various behaviors together is that they
>>all operate as a result of signaling mechanisms like the ones studied by
>>Mousetraps, learning and language
>>These mechanisms work in a way somewhat akin to the American board game
>>Mousetrap. In this game, you try to catch your opponent's plastic mouse
>>using a rambling contraption that starts working when you turn a crank.
>>This rotates gears, that push a lever, that moves a shoe, that kicks a
>>bucket, that sends a ball down stairs and-after several more
>>hair-raising steps of the sort-drops a basket on the mouse.
>>Molecular signals inside cells work through somewhat similar chain
>>reactions, except the pieces involved are molecules.
>>A typical way these molecular chain reactions work is that small
>>clusters of atoms, called phosphate groups, are passed among various
>>molecules. One example of what such a system could accomplish: a bit of
>>food brushing against the cell could start a series of events that lead
>>inside the cell and activate genes that generate the chemicals that
>>digest the food.
>>A single bacterium can contain dozens of such systems operating
>>simultaneously for different purposes. And compared to the board game,
>>the cellular systems have additional features that make them more
>>complicated and versatile.
>>For instance, some of these bacterial contraptions, when set in motion,
>>lead to the formation of extra copies of themselves. These tricks can
>>lead to phenomena with aspects of learning and language.
>>For example, a shortage of a nutrient in a bacterium's neighborhood can
>>activate a system that makes the microbe attract the nutrient toward
>>itself more strongly. The system also produces extra copies of itself,
>>researchers have found. Thus if shortage recurs later, the bacterium is
>>better prepared. This is a form of "learning," Hellingwerf and
>>colleagues wrote in the August, 2001 issue of the Journal of
>>Brain cells can operate in an analogous way: a brain cell can grow more
>>sensitive to a signal that it receives repeatedly, resulting in a
>>reinforcement of signaling circuits and learning.
>>The bacterial versions of "mousetrap" have other tricks as well. For
>>instance, some of them seem to contain components influenced by not just
>>one stimulus, but by two or more. Thus the chain reactions merge. The
>>component receiving these stimuli adds the strength of each to give a
>>response whose strength is proportional to the sum.
>>Although the full complexities of bacterial signaling are far from
>>understood, many researchers believe the systems helps bacteria to
>>For instance, some bacteria, when starving, emit molecules that serve as
>>stress signals to their neighbors, write Eshel Ben-Jacob of Tel Aviv
>>University and colleagues in last August's issue of Trends in
>>Microbiology. The signals launch a process in which the group can
>>transform itself to create tough, walled structures that wait out tough
>>times to reemerge later.
>>This transformation involves a complex dialogue that reveals a "social
>>intelligence," the researchers added. Each bacterium uses the signals to
>>assess the group's condition, compares this with its own state, and
>>sends out a molecular "vote" for or against transformation. The majority
>>Collectively, the researchers wrote, "bacteria can glean information
>>from the environment and from other organisms, interpret the information
>>in a 'meaningful' way, develop common knowledge and learn from past
>>experience." Some can even collectively change their chemical "dialect"
>>to freeze out "cheaters" who exploit group efforts for their own selfish
>>interest, the researchers claimed.
>>Not everyone is convinced by these claims.
>>Rosemary J. Redfield of the University of British Columbia, Vancouver,
>>has argued that the supposed communication molecules actually exist
>>mainly to tell bacteria how closed-in their surroundings are, which is
>>useful information to them for various reasons.
>>To properly assess if bacterial signals constitute intelligence, whether
>>of a social or individual brand, Hellingwerf and some other researchers
>>work from the inside out.
>>Rather than focusing on the behaviors, which are open to differing
>>interpretations, they focus on the systems of interactions followed by
>>the molecules. These systems, it is hoped, have distinct properties that
>>can be measured and compared against similar interactions in known
>>intelligent beings.
>>For instance, if these bacterial systems operate similarly to networks
>>in the brain, it would provide a weighty piece of evidence in favor of
>>the bacterial intelligence.
>>Hellingwerf has set himself a more modest goal, comparing bacterial
>>signaling not to the brain, but to the brain-like, human-made neural
>>network devices. Such an effort has a simple motivation. Demonstrating
>>that bacterial signaling possesses every important feature of neural
>>networks would suggest at least that microbial capabilities rival those
>>of devices with proven ability to tackle simple problems using known
>>rules of brain function-rather than robot-like calculations, which are
>>very different.
>>To understand how one could do such a comparison requires a brief
>>explanation of how neural networks work, and how they differ from
>>traditional computers.
>>Computers are good at following precise instructions, but terrible at
>>even simple, common-sense tasks that lack definite rules, like the
>>recognition of the difference between male and female.
>>Neural networks, like humans, can do this because they are more
>>flexible, and they learn-even though they can be built using computers.
>>They are a set of simulated "brain cells" set to pass "signals" among
>>themselves through simulated "connections."
>>Some information that can be represented as a set of numbers, such as a
>>digitized photograph, is fed to a first set of "cells" in such a way
>>that each cell gets a number. Each cell is then set to "transmit" all,
>>part or none of that number to one or more other cells. How big a
>>portion of the number is passed on to each, depends on the simulated
>>"strength" of the connections that are programmed into the system.
>>Each of those cells, in turn, are set to do something with the numbers
>>they receive, such as add them or average them-and then transmit all or
>>part of them to yet another cell.
>>Numbers ricochet through the system this way until they arrive at a
>>final set of "output" cells. These cells are set to give out a final
>>answer-based on the numbers in them-in the form of yet another number.
>>For example, the answer could be 0 for male, 1 for female.
>>Such a system, when new, will give random answers, because the
>>connections are initially set at random. However, after each attempt at
>>the problem, a human "tells" the system whether it was right or wrong.
>>The system is designed to then change the strength of the connections to
>>improve the answer for the next try.
>>To do this, the system calculates to what extent a change in strength of
>>each connection previously contributed to giving a right or wrong
>>answer. This information tells the system how to change the strengths to
>>give better results. Over many attempts, the system's accuracy gradually
>>improves, often reaching nearly human-like performance on a given task.
>>Such systems not only work quite well for simple problems, many
>>researchers believed they capture all the key features of real brain
>>cells, though in a drastically simplified way.
>>The devices also have similarities to the messaging systems in bacteria.
>>But how deep are the resemblances? To answer this, Hellingwerf looked at
>>four properties that neural-network experts have identified as essential
>>for such devices to work. He then examined whether bacterial signaling
>>fits each of the criteria.
>>The four properties are as follows.
>>First, a neural network must have multiple sub-systems that work
>>simultaneously, or "in parallel." Neural networks do this, because
>>signals follow multiple pathways at once, in effect carrying out
>>multiple calculations at once. Traditional computers can't do this; they
>>conduct one at a time. Bacteria do fit the standard, though, because
>>they can contain many messaging networks acting simultaneously,
>>Hellingwerf observes.
>>Second, key components of the network must carry out logical operations.
>>This means, in the case of a neural network, that single elements of the
>>network combine signals from two or more other elements, and pass the
>>result on to a third according to some mathematical rule. Regular
>>computers also have this feature. Bacteria probably do too, Hellingwerf
>>argues, based on the way that parts of their signaling systems add up
>>inputs from different sources.
>>The third property is "auto-amplification." This describes the way some
>>network elements can boost the strength of their own interactions.
>>Hellingwerf maintains that bacteria show this property, as when, for
>>example, some of their signaling systems create more copies of
>>themselves as they run.
>>The fourth property is where the rub lies for bacteria. This feature,
>>called crosstalk, means that the system must not consist just of
>>separate chain reactions: rather, different chain reactions have to
>>connect, so that the way one operates can change the way another runs.
>>Crosstalk is believed to underlie an important form of memory called
>>associative memory, the ability to mentally connect two things with no
>>obvious relationship. A famous example is the Russian scientist Ivan
>>Pavlov's dog, who drooled at the ring of a bell because experience had
>>taught him food invariably followed the sound.
>>Crosstalk has been found many times in bacteria, Hellingwerf wrote-but
>>the strength of the crosstalk "signals" are hundreds or thousands of
>>times weaker than those that follow the main tracks of the chain
>>reactions. Moreover, "clear demonstrations of associative memory have
>>not yet been detected in any single bacterial cell," he added, and this
>>is an area ripe for further research. If bacteria can indeed
>>communicate, it seems they may be holding quite a bit back from us.
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