NeuroScience, entry directory

 

by Corry Shores
[Search Blog Here. Index-tags are found on the bottom of the left column.]

[Central Entry Directory]

Entry Directory for

NeuroScience

The NeuroScience of Memory

Sperling (1960) ‘The Information Available in Brief Visual Presentation’, notes

 

Sperling (1967) ‘Successive approximations to a model for short term memory’, notes

Levitt (1971) ‘Transformed up‐down methods in psychoacoustics’, notes


Fuster and Alexander. (1971) ‘Neuronal Activity Related to Short-Term Memory’, notes

Weichselgartner & Sperling (1985) ‘Continuous Measurement of Visible Persistence’, notes

Funahashi et al. (1989) ‘Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex,’ notes

 

Funahashi et al. (1993) ‘Prefrontal neuronal activity in rhesus monkeys performing a delayed anti-saccade task’, notes

Miller et al. (1996) ‘Neural Mechanisms of Visual Working Memory in Prefrontal Cortex of the Macaque’, notes

Rainer et al. (1999) ‘Prospective Coding for Objects in Primate Prefrontal Cortex’, notes

Heywood & Zihl (1999) Case Study of L.M.’s Inability to Perceive Motion, in their book chapter “Motion Blindness”, summary notes

 

 

 

 

Neurocomputation & Neural-network Computation

[Skip to subheading] Computation Entry Dirctory

Brain-Machine Interface Research

Some Recent Scientific Developments in Brain Machine Interface (for Robotic Prosthesis), Neuroplasticity, Neurocomputation, and Whole Brain Emulation

 

 

 

Funahashi et al. (1989) ‘Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex,’ notes

by Corry Shores
[Search Blog Here. Index-tags are found on the bottom of the left column.]

[Central Entry Directory]

[Neuro-Science, entry directory]

 

Funahashi S, Bruce CJ, Goldman-Rakic PS.

“Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex”

Brief summary:

This experiment suggests that we visually remember something because neurons used in our vision continue their activity even after the stimulus goes away.

 

Notes:

The authors are testing the activity of neurons used for vision during periods when the test subject needs to ‘remember’ what they saw, in absence of that stimulus. In their introduction they write:

Studies of single neuron activity in monkeys during performance of delayed-response tasks have also provided strong evidence of a prefrontal contribution to memory (4, 5, 15, 16,20,22, 37,4 1, 42, 46, 50-53). Although many types of neural activity have been found in the prefrontal cortex, neurons that show sustained activity during the delay period are particularly relevant to the issue of mnemonic processing. Usually these neurons increase their discharge rates following the brief cue presentation and continue firing tonically during the delay period until the response is executed (5, 15, 20, 22, 52, 53).
[p.331Bc]

The authors recorded activity from single neurons of monkeys. The monkeys were shown visual stimuli, and their eye moments were tracked. There is a fixation target, a small white spot in the middle of the screen. And there were peripheral visual cues, small filled white squares. The procedure went like this:

(1) 5s interval

(2) the fixation target appears at the center of the screen

(3) the monkey needed to be fixated for 0.75s (the fixation period)

(4) after those 0.75s, the peripheral visual cue was presented for 0.5s (the cue period) at one of many peripheral locations. The monkey was only rewarded if they maintained fixation in the center during the cue period and also during a subsequent delay period.

(5) delay period (monkey must stay fixated at center) of either 1.5, 3 or 6 (normally 3) seconds long.

(6) response period, within the next 0.5s after the delay, monkey must make saccadic eye movement to the cue’s location (to get reward). [332AB]

Our concern here lies with the neuronal activity. The measured the ‘discharge rate’ (p.334Aa) of 319 neurons in the prefrontal cortex (336Ba)

[Image from Funahashi et al., p.332.]

[The above diagrams show that during the delay period, when the monkey needs to visually ‘remember’ the cue’s location, there is heightened neuron activity.]

Findings: They find that of the 288 neurons (in the prefrontal cortex, within and surrounding the principal sulcus (PS)) “170 exhibited task-related activity during at least one phase of this task and, of these, 87 showed significant excitation or inhibition of activity during the delay period relative to activity during the intertrial interval,” and “For 50 of the 87 PS neurons, activity during the delay period was significantly elevated above the neuron’s spontaneous rate for at least one cue location.”

[331Bd]

S. Funahashi , C. J. Bruce , P. S. Goldman-Rakic. Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex. Journal of NeurophysiologyPublished 1 February 1989Vol. 61no. 331-349.
http://www.ncbi.nlm.nih.gov/pubmed/2918358

 

Some Recent Scientific Developments in Brain Machine Interface (for Robotic Prosthesis), Neuroplasticity, Neurocomputation, and Whole Brain Emulation

summary by Corry Shores
[Search Blog Here. Index-tags are found on the bottom of the left column.]
[Central Entry Directory]
[Posthumanism Entry Directory]

 

[All boldface is my own]

Some (mostly) Recent Scientific Developments in Brain Machine Interface (for Robotic Prosthesis), Neuroplasticity, Neurocomputation, and Whole Brain Emulation

Brief Summary: New scientific advances support the posthuman vision of robotically enhanced and reconstructed post-humans. Neuroplasticity and brain machine interface (also brain computer interface) empower brains to control robotic parts just like biological ones. Whole brain emulation and cognitive prosthetics could allow brain implanted chips to replace or enhance our brain functioning, perhaps even completely “uploading” our brain onto a computerized simulation. Progressive replacement of bodily and neural parts with robotic and computerized ones could enable one to make a complete and continuous transition from human to robot.

 

"Brain" In A Dish Acts As Autopilot Living Computer

Explore: Research at the University of Florida

Spring 2005 Vol. 10 No.1

http://www.research.ufl.edu/publications/explore/v10n1/extract2.html

Thomas DeMarse has created a miniature living brain on a dish. He placed neurons that grew connections to form a network, and it can perform tasks in a virtual world.

“It’s essentially a dish with 60 electrodes arranged in a grid at the bottom,” DeMarse said. “Over that we put the living cortical neurons from rats, which rapidly begin to reconnect themselves, forming a living neural network — a brain.”

The brain and the simulator establish a two-way connection, similar to how neurons receive and interpret signals from each other to control our bodies. By observing how the nerve cells interact with the simulator, scientists can decode how a neural network establishes connections and begins to compute, DeMarse said.

When DeMarse first puts the neurons in the dish, they look like little more than grains of sand sprinkled in water. However, individual neurons soon begin to extend microscopic lines toward each other, making connections that represent neural processes. “You see one extend a process, pull it back, extend it out — and it may do that a couple of times, just sampling who’s next to it, until over time the connectivity starts to establish itself,” he said. “(The brain is) getting its network to the point where it’s a live computation device.”

To control the simulated aircraft, the neurons first receive information from the computer about flight conditions: whether the plane is flying straight and level or is tilted to the left or to the right. The neurons then analyze the data and respond by sending signals to the plane’s controls. Those signals alter the flight path and new information is sent to the neurons, creating a feedback system.

“Initially when we hook up this brain to a flight simulator, it doesn’t know how to control the aircraft,” DeMarse
said. “So you hook it up and the aircraft simply drifts randomly. And as the data come in, it slowly modifies the (neural) network so over time, the network gradually learns to fly the aircraft.”

Although the brain currently is able to control the pitch and roll of the simulated aircraft in weather conditions ranging from blue skies to stormy, hurricane-force winds, the underlying goal is a more fundamental understanding of how neurons interact as a network, DeMarse said.

“There’s a lot of data out there that will tell you that the computation that’s going on here isn’t based on just one neuron. The computational property is actually an emergent property of hundreds or thousands of neurons cooperating to produce the amazing processing power of the brain.”

Monkeys Think, Moving Artificial Arm as Own

By Benedict Carey

New York Times

Published: May 29, 2008

http://www.nytimes.com/2008/05/29/science/29brain.html?_r=0

Two monkeys with brain-controlled prosthetics successfully use their robotic arms to reach for food and feed it to themselves.

Two monkeys with tiny sensors in their brains have learned to control a mechanical arm with just their thoughts, using it to reach for and grab food and even to adjust for the size and stickiness of morsels when necessary, scientists reported on Wednesday.

The report, released online by the journal Nature, is the most striking demonstration to date of brain-machine interface technology. Scientists expect that technology will eventually allow people with spinal cord injuries and other paralyzing conditions to gain more control over their lives.

ALSO reported at MIT Technology Review

Monkey Thinks Robot into Action

A monkey is able to feed itself with a robotic arm.

    By Emily Singer

MIT Technology Review

May 28, 2008

http://www.technologyreview.com/news/410189/monkey-thinks-robot-into-action/

“It’s the first time a monkey–or a human–is directly, with their brain, controlling a real prosthetic arm,” says Krishna Shenoy, a neuroscientist at Stanford University who was not involved in the research. (Singer)

TED

Henry Markram: A brain in a supercomputer
Filmed Jul 2009 • Posted Oct 2009 • TEDGlobal 2009

http://www.ted.com/talks/henry_markram_supercomputing_the_brain_s_secrets.html

Supercomputers are being used to simulate brain activity. They began with animals and are moving up to human brain. They first catalogued neurons and described their interactive behavior. They can simulate human neuronal activity on a small scale. Also see:

http://en.wikipedia.org/wiki/Blue_Brain_Project

Rat memory under computer simulation

Eric Mankin

Public release date: 17-Jun-2011

Restoring memory, repairing damaged brains
Biomedical engineers analyze -- and duplicate -- the neural mechanism of learning in rats

Eureka Alert

http://www.eurekalert.org/pub_releases/2011-06/uosc-rmr061211.php

Scientists have developed a way to turn memories on and off—literally with the flip of a switch.

Using an electronic system that duplicates the neural signals associated with memory, they managed to replicate the brain function in rats associated with long-term learned behavior, even when the rats had been drugged to forget.

"Flip the switch on, and the rats remember. Flip it off, and the rats forget," said Theodore Berger of the USC Viterbi School of Engineering's Department of Biomedical Engineering.” (Mankin)

ALSO reported in The New York Times

Memory Implant Gives Rats Sharper Recollection

By Benedict Carey

The New York Times

Published: June 17, 2011

http://www.nytimes.com/2011/06/17/science/17memory.html?_r=0

The authors said that with wireless technology and computer chips, the system could be easily fitted for human use. (Carey)

New horizons in auditory prostheses

Zeng, Fan-Gang PhD

Hearing Journal

November 2011 - Volume 64 - Issue 11 - pp 24,26,27

http://journals.lww.com/thehearingjournal/Fulltext/2011/11000/New_horizons_in_auditory_prostheses.5.aspx

There are many recent developments in cochlear implants.

All contemporary cochlear implants use similar signal processing that extracts temporal envelope information from a limited number of spectral bands, and delivers these envelopes successively to 12-22 electrodes implanted in the cochlea. As a result, these implants produce similarly good speech performance: 70-80 percent sentence recognition in quiet, which allows an average cochlear implant user to carry on a conversation over the telephone. Interestingly, though, sentence recognition in quiet has essentially remained at this same level since 1994. (Figure 1.)

Active tactile exploration using a brain–machine–brain interface

Joseph E. O’Doherty, Mikhail A. Lebedev, Peter J. Ifft, Katie Z. Zhuang, Solaiman Shokur, Hannes Bleuler & Miguel A. L. Nicolelis

Nature 479, 228–231 (10 November 2011)

http://www.nature.com/nature/journal/v479/n7372/full/nature10489.html

Monkeys operating virtual robotic arms had their brains given touch stimulations.

ALSO reported by The Huffington Post

Is It Possible To Feel Textures Using Just Brain Waves? New Study Shows How

The Huffington Post

Amanda Chan Posted: 10/07/11 11:49 AM ET

http://www.huffingtonpost.com/2011/10/07/brain-touch-texture-feelings-senses_n_996844.html

 

This is basically one of the holy grails of this field," study researcher Miguel Nicolelis, a neurobiology professor and co-director of the Duke Center for Neuroengineering, told Bloomberg. "No other study has provided an artificial sensory channel directly to the brain of animals. This is really needed to restore in patients that have a spinal cord injury not only their mobility, but their sense of touch." (Chan)

Going mental: Study highlights brain’s flexibility, gives hope for natural-feeling neuroprosthetics

By Sarah Yang, Media Relations

UC Berkeley News Center

March 4, 2012

http://newscenter.berkeley.edu/2012/03/04/brain-flexibility-gives-hope-for-neuroprosthetics/

Researchers at the University of California, Berkeley have shown that neurons used for physical tasks can be retrained for brain machine interface usage. This shows that neuro-prosthetics can feel natural.

“Their new study, to be published Sunday, March 4, in the advanced online publication of the journal Nature, shows that through a process called plasticity, parts of the brain can be trained to do something they normally do not do. The same brain circuits employed in the learning of motor skills, such as riding a bike or driving a car, can be used to master purely mental tasks, even arbitrary ones.

[…]

To clarify these issues, the scientists set up a clever experiment in which rats could only complete an abstract task if overt physical movement was not involved. The researchers decoupled the role of the targeted motor neurons needed for whisker twitching with the action necessary to get a food reward.

The rats were fitted with a brain-machine interface that converted brain waves into auditory tones. To get the food reward – either sugar-water or pellets – the rats had to modulate their thought patterns within a specific brain circuit in order to raise or lower the pitch of the signal.

Auditory feedback was given to the rats so that they learned to associate specific thought patterns with a specific pitch. Over a period of just two weeks, the rats quickly learned that to get food pellets, they would have to create a high-pitched tone, and to get sugar water, they needed to create a low-pitched tone.

If the group of neurons in the task were used for their typical function – whisker twitching – there would be no pitch change to the auditory tone, and no food reward.

“This is something that is not natural for the rats,” said Costa. “This tells us that it’s possible to craft a prosthesis in ways that do not have to mimic the anatomy of the natural motor system in order to work.”

Simulated brain scores top test marks

First computer model to produce complex behaviour performs almost as well as humans at simple number tasks.

    Ed Yong

Nature | News

29 November 2012

http://www.nature.com/news/simulated-brain-scores-top-test-marks-1.11914

A computer simulated brain with 2.5 million virtual neurons can perform simple mathematical calculations.

Mind-controlled robot arms show promise

People with tetraplegia use their thoughts to control robotic aids.

    Alison Abbott

Nature | News

16 May 2012

http://www.nature.com/news/mind-controlled-robot-arms-show-promise-1.10652

[AP Report here]

Two tetraplegics use brain machine interface to gain some lost abilities.

Neurosurgeons implanted tiny recording devices containing almost 100 hair-thin electrodes in the motor cortex of their brains, to record the neuronal signals associated with intention to move.” (Abbott)

Cathy can use her thoughts to direct the motion of a robotic arm. She is able to direct it to grab a bottle of coffee and lift it to her lips. Bob as well operates the arm successfully. There is also a subject who operates a computer cursor using this interface, as if operating a computer mouse. The subjects used the BrainGate2 brain implant system [image below from the BrainGate wiki page.]

(Thanks wiki)

Paralyzed Man Uses Thoughts Alone to Control Robot Arm, Touch Friend's Hand, After Seven Years

Science Daily

Feb. 8, 2013 —

http://www.sciencedaily.com/releases/2013/02/130208124818.htm

Based on this journal article

Wei Wang et al.

An Electrocorticographic Brain Interface in an Individual with Tetraplegia. PLoS ONE, 2013; 8 (2): e55344

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0055344

Researchers at the University of Pittsburgh School of Medicine and UPMC describe in PLoS ONE how an electrode array sitting on top of the brain enabled a 30-year-old paralyzed man to control the movement of a character on a computer screen in three dimensions with just his thoughts. It also enabled him to move a robot arm to touch a friend's hand for the first time in the seven years since he was injured in a motorcycle accident. (Science Daily)

ALSO reported by AP

Paralyzed Man Uses Mind-Powered Robot Arm To Touch
Tim Hemmes

By Lauran Neergaard  

10/10/11 10:04 AM ET  

AP

http://www.huffingtonpost.com/2011/10/10/mind-powered-robot-arm_n_1003204.html

"It wasn't my arm but it was my brain, my thoughts. I was moving something," Hemmes says. (Neergaard)

Bionic Eye Implant Approved by U.S. for Rare Disease
By Anna Edney

Bloomberg

Feb 15, 2013 7:01 AM GMT+0200

http://www.bloomberg.com/news/2013-02-14/bionic-eye-implant-approved-by-u-s-for-rare-disease.html

New neuroprosthetic eye implant restores some visual capabilities.

While the $100,000-plus system won’t restore sight, it gives patients the ability to perceive the difference between light and dark. The device consists of a video camera, a transmitter mounted on a pair of eyeglasses and a processing unit that transforms images into electronic data sent to an implanted retinal prosthesis, the FDA said.

[…]

Konstantopoulos, of Glen Burnie, Maryland, said he was diagnosed with retinitis pigmentosa when he was in his early 40s and became completely blind about six months ago. He can see shadows now with the device and tell if the sun is behind a tree. Argus II is comfortable and the surgery was painless, he said.

[…]

A clinical study of 30 people showed the eye device helped patients recognize large letters or words, detect street curbs, walk on a sidewalk without falling and match black, gray and white socks.

Rats With Linked Brains Work Together
Megan Gannon, News Editor

Live Science

Date: 28 February 2013 Time: 12:23 PM ET

http://www.livescience.com/27544-rats-with-linked-brains-work-together.html

Brain plasticity so great that brains can use information from other brains.

Scientists have engineered something close to a mind meld in a pair of lab rats, linking the animals' brains electronically so that they could work together to solve a puzzle. And this brain-to-brain connection stayed strong even when the rats were 2,000 miles apart.

The experiments were undertaken by Duke neurobiologist Miguel Nicolelis, who is best known for his work in making mind-controlled prosthetics.

"Our previous studies with brain-machine interfaces had convinced us that the brain was much more plastic than we had thought," Nicolelis explained. "In those experiments, the brain was able to adapt easily to accept input from devices outside the body and even learn how to process invisible infrared light generated by an artificial sensor. So, the question we asked was, if the brain could assimilate signals from artificial sensors, could it also assimilate information input from sensors from a different body?"

For the new experiments, Nicolelis and his colleagues trained pairs of rats to press a certain lever when a light went on in their cage. If they hit the right lever, they got a sip of water as a reward.

When one rat in the pair called the "encoder" performed this task, the pattern of its brain activity — something like a snapshot of its thought process — was translated into an electronic signal sent to the brain of its partner rat, the "decoder," in a separate enclosure. The light did not go off in the decoder's cage, so this animal had to crack the message from the encoder to know which lever to press to get the reward.

The decoder pressed the right lever 70 percent of the time, the researchers said.

[…]

"We saw that when the decoder rat committed an error, the encoder basically changed both its brain function and behavior to make it easier for its partner to get it right," Nicolelis explained in a statement. "

[…]

The connection was not lost even when the signals were sent over the Internet and the rats placed on two different continents, 2,000 miles (3,219 kilometers) apart.”

.

Andy Clark. 8.6 of Being There, “Continuous Reciprocal Causation”, summary

summary by Corry Shores
[Search Blog Here. Index-tags are found on the bottom of the left column.]
[Central Entry Directory]

[Posthumanism Entry Directory]

[Andy Clark, Being There, entry directory]

 

[My own commentary is in brackets. All boldface and underlining is my own.]

Andy Clark

Being There:

Putting Brain, Body, and World Together Again

Ch.8

Being, Computing, Representing

Part 8.6
Continuous Reciprocal Causation

Brief Summary:

Separate parts of a system can be in a state of continuous reciprocal causation, meaning that the behavior of each part simultaneously affects the behavior of the other parts. In such cases, it is not best to explain the whole system’s by analyzing the system into insulated parts. And also, representational accounts might not best explain how one part can be found internally affecting another part.

Summary

[Recall that a position is “representationalist if it depicts whole systems of identifiable inner states (local or distributed) or processes (temporal sequences of such states) as having the function of bearing specific types of information about external or bodily states of affairs”. (147a)] Clark will offer one last way to make a strong anti-representationalist argument. He will appeal to “the presence of continuous, mutually modulatory influences linking brain, body, and world.” (163b) Clark previously described the neuronal processes involved in vision, which had “hints of such mutually modulatory complexity in the interior workings of the brain itself.” (163b) Clark now wonders what if “something like this level of interactive complexity characterized some of the link among neural circuitry, physical bodies, and aspects of the local environment?” (163b)

 

[Consider if a radio and a transmitter were near one another, and the transmitter is broadcasting music from a turntable, also nearby. This means that low frequencies playing on the radio will disrupt the needle on the record, but the disruption of the needle on the record will change what the radio is playing.] Clark gives this example.

Consider a radio receiver, the input signal to which is best treated as a continuous modulator of the radio’s “behavior” (its sound output). Now imagine (here is where I adapt the analogy to press the point) that the radio’s output is also a continuous modulator of the external device (the transmitter) delivering the input signal. In such a case, we observe a truly complex and temporally dense interplay between the two system components – one which could lead to different overall dynamics (e.g. of positive feedback or stable equalibria) depending on the precise details of the interplay. The key fact is that, given the continuous nature of the mutual modulations, a common analytic strategy yields scant rewards. The common strategy is, of course, componential analysis, as described in chapter 6. To be sure, we can and should identify different components here. But the strategy breaks down if we then try to understand the behavior unfolding of one favored component (say, the receiver) by treating it as a unity insulated from its local environment by the traditional boundaries of transduction and action, for such boundaries, in view of the facts of continuous mutual modulation, look arbitrary with respect to this specific behavioral unfolding. They would not be arbitrary if, for example, the receiver unit displayed discrete time-stepped behaviors of signal | receiving and subsequent broadcast. Were that the case, we could reconceptualize the surrounding events as the world’s giving inputs to a device which then gives outputs (“actions”) which affect the world and hence help mold the next input down the line – for example, we could develop an interactive “catch and toss” version of the componential analysis, as predicted in chapter 6. (163-164)

[So if we were to analyze for example the component of the radio as if insulated from its environment, we would not know where to begin, assuming that the process had already begun. But if each causal event happened in temporal steps with gaps between, then we could analyze the components of the causal relation.]

Clark offers a second example (from Randy Beer). [First consider this description of oscillating or reverberating circuits in Marieb and Hoehn’s Human Anatomy & Physiology (quoting):

In reverberating, or oscillating, circuits, the incoming signal travels through a chain of neurons, each of which makes collateral synapses with neurons in a previous part of the pathway.

As a result of the positive feedback, the impulses reverberate (are sent through the circuit again and again), giving a continuous output signal until one neuron in the circuit fails to fire. Reverberating circuits are involved in control of rhythmic activities, such as the sleep-wake cycle, breathing, and certain motor activities (such as arm swinging when walking). Some researchers believe that such circuits underlie short-term memory. Depending on the specific circuit, reverberating circuits may continue to oscillate for seconds, hours, or (in the case of the circuit controlling the rhythm of breathing) a lifetime. (Marieb and Hoehn, 422d)

Andy Clark’s second example involves such oscillating neurons,] he writes:

Consider a simple two-neuron system. Suppose that neither neuron, in isolation, exhibits any tendency toward rhythmic oscillation. Nonetheless, it is sometimes the case that two such neurons, when linked by some process of continuous signaling, will modulate each other's behavior so as to yield oscillatory dynamics. Call neuron 1 "the brain" and neuron 2 "the environment." What concrete value would such a division have for understanding the oscillatory behavior? (164a.b)

[So the neurons mutually modify one another, because they have both inputs from and outputs to one another.]

When we are interested in the behavior of the two insofar as they are mutually affecting one another, it would not make sense to analyze the workings into insulated components, even though indeed the system is made of discrete parts.

in the case of biological brains and local environments it would indeed be perverse—as Butler (to appear) rightly insists—to pretend that we do not confront distinct components. The question, however, must be whether certain target phenomena are best explained by granting a kind of special status to one component (the brain) and treating the other as merely a source of inputs and a space for outputs. In cases where the target behavior involves continuous reciprocal causation between the components, such a strategy seems ill motivated. In such cases, we do not, I concede, confront a single undifferentiated system. But the target phenomenon is an emergent property of the coupling of the two (perfectly real) components, and should not be "assigned" to either alone. (164c.d)

Such continuous reciprocal causation is common in our everyday lives.

Nor, it seems to me, is continuous reciprocal causation a rare or exceptional case in human problem solving. The players in a jazz trio, when improvising, are immersed in just such a web of causal complexity. Each member's playing is continually responsive to the others' and at the same time exerts its own modulatory force. Dancing, playing interactive sports, and even having a group conversation all sometimes exhibit the kind of mutually modulatory dynamics which look to reward a wider perspective than one that focuses on one component and treats all the rest as mere inputs and outputs. Of course, these are all cases in which what counts is something like the social environment. But dense reciprocal interactions can equally well characterize our dealings with complex machinery (such as cars and airplanes) or even the ongoing interplay between musician and instrument. What matters is not whether the other component is itself a cognitive system but the nature of the causal coupling between components. Where that coupling provides for continuous and mutually modularity exchange, it will often be fruitful to consider the emergent dynamics of the overarching system. (165a.b)

[This is like Deleuze’s notion of rhythm in Spinoza’s affection, see the end of section 6 of my paper “Body and World in Merleau-Ponty and Deleuze”:

Our active self-affection and adaptive interaction with the world around us is what Deleuze here calls "rhythm." He also offers the example of swimming through a powerful wave. When we collide with the wave, its affection begins to decompose our body. Yet, by self-affectively altering the arrangements of our own body's parts, we may swim in conjunction with the wave and together form a larger composite body. Deleuze suggests another illustration to explain more clearly how affective rhythm involves couplings of continuous affective variations. He has us consider a dual improvisation of a violin and a piano. On the one hand, each one needs to improvisationally choose its own development. Yet, the musicians' decisions will influence how the other plays in concord with it. So, in order for both instruments to maintain their differential co-composition, they must make self-modifications that are differentially compatible with those of the other player. (Shores 203)

]

 

So when there is continuous reciprocal causation, there is little use for an analysis that looks at the parts of such systems as if they were separate.

Thus, to the extent that brain, body, and world can at times be joint participants in episodes of dense reciprocal causal influence, we will confront behavioral unfoldings that resist explanation in terms of inputs to and outputs from a supposedly insulated individual cognitive engine. (165c)

Clark thinks that there are then only two possibilities for the use of internal representation for cognitive scientific explanations. (165c)

To understand the first possibility, we consider a complex neural network, called ‘A’. It is coupled with its environment, and part of its dynamics is an ability to sense whether it the environmental processes it is coupled to are present. “Imagine a complex neural network, A, whose environmentally coupled dynamics include a specific spiking (firing) frequency which is used by other onboard networks as a source of information concerning the presence or absence of certain external environmental processes—the ones with which A is so closely coupled.” (165d) So internally we might say the system has patterns for when it is coupled to external processes. Now we are to consider those signals normally coming from outside to be produced from the inside, causing the system to ‘imagine’ being engaged with the environment rather than physically being so. This would be like internal representation.

The downstream networks thus use the response profiles of A as a stand-in for these environmental states of affairs. Imagine also that the coupled response profiles of A can sometimes be induced, in the absence of the environmental inputs, by top-down neural influences, and that when this happens the agent finds herself imagining engaging in the complex interaction in question (e.g., playing | in a jazz trio). In such circumstances, it seems natural and informative to treat A as a locus of internal representations, despite its involvement, at times, in episodes of dense reciprocal interaction with external events and processes.” (163-164)

The other possibility is that even such inner processes cannot operate unless they are coupled, and thus there are nonrepresentational dynamics at play.

A second possibility, however, is that the system simply never exhibits the kind of potentially decoupled inner evolution just described. This will be the case if, for example, certain inner resources participate only in densely coupled, continuous reciprocal environmental exchanges, and there seem to be no identifiable inner states or processes whose role in those interactions is to carry specific items of information about the outer events. Instead, the inner and the outer interact in adaptively valuable ways which simply fail to succumb to our attempts to fix determinate information processing roles to specific purely internal, components, states, or processes. In such a case the system displays what might be called nonrepresentational adaptive equilibrium. (A homely example is a tug of war: neither team is usefully thought of as a representation of the force being exerted by the other side, yet until the final collapse the two sets of forces influence and maintain each other in a very finely balanced way.) (166b.c)

Thus,

Where the inner and the outer exhibit this kind of continuous, mutually modulatory, non-decouplable coevolution, the tools of information processing decomposition are, I believe, at their weakest. What matters in such cases are the real, temporally rich properties of the ongoing exchange between organism and environment. (166c)

Such instances do not challenge the representational model, because they do not fall under the class of cases best suited for representational explanations. Clark will explain this in the next section. (166d)

 

 

Clark, Andy. Being There: Putting Brain, Body, and World Together Again. Cambridge, Massachusetts/London: MIT, 1997.

 

Marieb, Elaine N., & Katja Hoehn. Human Anatomy & Physiology. London: Pearson, 2007.

 

Shores, Corry. “Body and World in Merleau-Ponty and Deleuze” in Sudia Phaenomenologica, vol.12, 2012, pp.181-209.

https://cdn.anonfiles.com/1360747598945.pdf

Andy Clark. 7.3 of Being There, “Primate Vision: From Feature Detection to Tuned Filters,” summary

summary by Corry Shores
[Search Blog Here. Index-tags are found on the bottom of the left column.]
[Central Entry Directory]

[Posthumanism Entry Directory]

[Andy Clark, Being There, entry directory]

Andy Clark

Being There:

Putting Brain, Body, and World Together Again

Ch.7

The Neuroscientific Image

Part 7.3
Primate Vision: From Feature Detection to Tuned Filters

Brief Summary:

The neuronal visual systems in the brain have parts that are maximally tuned to process data for one visual parameter or another, meaning that rather than having cells responsible for dealing only with certain complex forms [like a spiral], many various cells in the system cooperatively play a role in understanding all the visual properties of something being seen [like something’s spirality, breadth, etc, perhaps].

Summary

Clark will discuss neuroscientific research into primate vision, especially work by David Van Essen. (133c.d)

Cognitive neuroscience examines neuronal responses.

Anatomically, the macaque monkey possesses at least 32 visual brain areas and over 300 connecting | pathways. Major areas include early cortical processing sites such as V1 and V2, intermediate sites such as V4 and MT, and higher sites such as IT (inferotemporal cortex) and PP (posterior parietal cortex) (plate 1). The connecting pathways tend to go both ways—e.g. from V1 to V2 and back again. In addition, there is some "sideways" connectivity—e.g. between subareas within VI. (133-134, boldface mine)

 

(From Clark p.170)

There are ten levels of cortical processing in the system, and we will look at some of the more important ones. There are three populations of sub-cortical cells from which the system receives input. One population is the magnocellular (M) and another is the Parvocellular (P). And there is a processing pathway for M, and another one for P. Each population specializes in a different type of low-level information. P cells “have high spatial and low temporal resolution”, while M cells have “high temporal resolution.” (134b) This means that M cells deal with rapid motion perception, while P cells deal with color discrimination (among other things). So when we selectively destroy a monkey’s P cells, it can no longer distinguish colors although it still recognizes motion. (134b)

So the magno M cells discern motion, and there is a magno-denominated (MD) stream of processing. This stream includes neuron populations that are sensitive to the direction of some motion, especially in area MT, which we said above was an intermediate cortical processing site. When we electrically stimulate a part of MT, the monkey might “perceive” left motion even if the target object is really moving to the right. There is a higher stage in the processing hierarchy, MSDT, where there are cells sensitive to spiral motion.

The MD stream is ultimately connected to the posterior parietal cortex, which appears to use spatial information to control such high level functions as deciding where objects are and planning eye movements. (134d)

There is also the task of object recognition, which is determining what things are. This is handled by a stream rooted in P inputs, moving through V1, V4, and posterior inferotemporal areas (PIT), and it leads into central and anterior inferotemporal areas. (134d) This pathway specializes in form and color. As we go up the hierarchy, we find sites capable of processing increasingly complex forms. At a high level, there are even cells that respond maximally to such complex geometrical visual stimuli as hands and faces. (135a). But although one cell responds maximally to one kind of form, like a spiral, it will also to a lesser extent respond to other sorts of patterns.

[This means that cells are not like yes-no sensors that detect the presence of one form or its absence, but rather each participate in contributing information about some property of what is being seen, with all working together cooperatively.]

Although a cell may respond maximally to (e.g.) a spiral pattern, the same cell will respond to some degree to multiple other patterns also. It is often the tuning of a cell to a whole set of stimuli that is most revealing. This overall tuning enables one cell to participate in a large number of distributed patterns of encoding, contributing information both by its being active and by its degree of activity. Such considerations lead Van Essen and others to treat cells not as simple feature detectors signaling the presence or absence of some fixed parameter but rather as filters tuned along several stimulus dimensions, so that differences in firing rate allow one cell to encode multiple types of information. There is also strong evidence that the responses of cells in the middle and upper levels of the processing hierarchy are dependent on attention and other shifting parameters (Motter 1994), and that even cells in VI have their response characteristics modulated by the effects of local context (Knierim and Van Essen 1992). Treating neurons as tunable and modulable filters provides a powerful framework in which to formulate and understand such complex profiles. (135a.b, boldface mine)

But even though visual systems are complex, they can still be analyzed. (135d)

Andy Clark. Being There: Putting Brain, Body, and World Together Again. Cambridge, Massachusetts/London: MIT, 1997.

Andy Clark. Being There: Putting Brain, Body, and World Together Again, entry directory

 

summary by Corry Shores
[Search Blog Here. Index-tags are found on the bottom of the left column.]
[Central Entry Directory]

[Posthumanism Entry Directory]

Entry Directory for

Andy Clark

Being There:

Putting Brain, Body, and World Together Again

Ch.2

The Situated Infant

Part 2.4
Soft Assembly and Decentralized Solutions

Ch.7

The Neuroscientific Image

Part 7.3
Primate Vision: From Feature Detection to Tuned Filters

 

Ch.8

Being, Computing, Representing

Part 8.2
What is this Thing Called Representation?

 

Part 8.6
Continuous Reciprocal Causation

Part 8.8
Roots

[this summary focuses on the Merleau-Ponty parts]

 

 

 

 

Kneading Friendship: Deleuze, Blanchot, and the Folding of Disciplines

by Corry Shores
[Search Blog Here. Index-tags are found on the bottom of the left column.]

[Central Entry Directory]
[Corry Shores, Entry Directory]

The following is Julie Van der Wielen's and my presentation at the Deleuze, Philosophy, Transdisciplinarity conference at Goldsmiths College, University of London in February of 2012. Thank you Masa Kosugi, Guillaume Collett, and Chryssa Sdrolia for all your help and for organizing the wonderful conference.

Julie Van der WielenCorry Shores

Kneading Friendship:Deleuze, Blanchot, and the Folding of Disciplines

[Corry Shores reads:]

We would like now to explain Deleuze’s appreciation for Blanchot’s idea that friendship is the condition for thought, and as well, how for both of them, friendship is as well philosophy’s path to transdisciplinarity.


[Julie Van Der Wielen reads:]

Friendship

When you have a friend who tries to get to close to you, or you try to get to close to a friend, either by trying to be the same or by trying to know his deepest thoughts, it will get uncomfortable. Also, we are all aware of the fact that it’s wrong to dispose of knowledge we have from a friend and to talk about the friend when this one is absent. Distance is needed, even between the closest friends. In his reflections about friendship, Blanchot takes the distance between friends as a necessary condition for their relation.

Because the other is irreducibly other and I am inevitably separated from him, a kind of collision takes place between me and the other wherein I’m confronted to a limit: I’m radically different from the other, I can’t posses him and even the possibility of really understanding the other person is questionable. This distance between me and the other, our being radically separated from each other is the precondition for a relation between us. The distance as an interval, an interruption of being or as a no man’s land, is where friendship takes place. In this openness of the interval the other is present and nearby, but this proximity hides and affirms the other as very far-off and belonging to no one. What I see of my friend when I talk to him, when I decipher his gestures or silence is an openness to his thought, nevertheless I will never really access this distant thought. Even in the closest moments, the infinite distance between friends remains.

This is why, in the last chapter of l’Amitie, Blanchot writes on the impossibility to write about his friend Georges Bataille. He doesn’t accept to write on Bataille’s character or on his thoughts because with his death, their relation as separation disappeared and all that is left are memories of that of Bataille which was close to people, not the distant reality where this proximity was the affirmation of. Without the presence of the friend, there is no possible openness to him and his thought. My relation with my friend preserves the openness to his thought. As the presence of my friend and our relation are a condition for me to find a possible openness to him, any grasp on him is out of the question, if without a relation or dialogue with him. Our relation follows an unpredictable course, where presence and dialogue are necessary to openness. For this reason I cannot know univocally who my friend is, and he will always be infinitely far from me. I can only find openness to his thought when we are present to each other, in an unpredictable movement of understanding which makes it impossible for me to get hold on him.

Another name Blanchot gives to the interval between friends, rising from the unpredictability of the other and his absolute strangeness, is discretion. This is not just the outright refusal to make assertions about the friend, or to dispose of knowledge I have of him, it is the pure interval as everything that is between us. The discretion doesn’t prevent communication, it links us up in difference, making communication possible through speech or silence. The interval or discretion is a necessary condition to communication. Real communication implies the acknowledgement of its limit, the distance between two parties. This limit shows it is impossible to talk about my friend but only to talk to him. It is an impossibility which opens up infinite possibility: impossibility of understanding by which we are driven to create new meaning, radical difference that pulls together.

We can see the interval operate in speech: talking together is never actually talking at the same time. Speech goes from one to the other, the talkers take turns. The impossibility to talk together opens up to the possibility of a dialogue. This dialogue follows an unpredictable course since there is always the possibility of contradiction, development or affirmation of my thought by the friend. The impossibility to predict the course of the conversation is a necessary condition to communication.

In a dialogue with a friend I should never claim comprehension of my friend or of fixed meaning. Communication and the relation with my friend is an unpredictable movement rising from the impossibility to get hold on the other. When Blanchot claims friendship is a necessary condition to thought, we should look at it this way: thought should be openness without pretention of fixed meaning, as in friendship communication should be a dialogue with the other as an unpredictable movement. In the Abecedaire, Deleuze paraphrases Blanchot saying friendship is a condition for thought, not because we need friends to think but because the category of friendship is a condition for the exercise of thought.


[Corry Shores reads:]

We also find Deleuze offering a strikingly similar account of friendship. Consider first his example of comedic friends, Laurel and Hardy.

Their cartoonish contrasts suggests they would regard one another as though from a great distance. One is fat, the other skinny; one more extroverted, the other more introverted. Yet, they always seem to be in communion with one another, despite their features that might normally push them apart. It is as if they are constantly together in communication. Even when one is physically distant from the other, we still never sense that there is a break in that continued communicative link that holds them together. But, what about when they seem to miscommunicate, like when Hardy says he is waiting for a streetcar, as if charmed rather than enraged by Laurel’s feigned innocence? Despite the disconnection and absurdity of their messages to one another, they do not break their constant bond of communicative contact.

Is it not as though they share a unique language that makes sense only to them? Would we really be surprised if Laurel and Hardy spent a whole day together without ever saying even one word, while the whole time, still conducting a sort of unspoken dialogue that unfolds without any need for conventional signs?


For Deleuze, our friendships form not on the basis of our explicit messages to one another, but rather on a more profound sort of reading of one another’s implicit and even inexplicable expressions to one another, or what Deleuze here calls signs.

Yet they are not signs in the sense of representations; they instead form a sort of prelanguage. But how are they read, if it is not by means of explicit interpretations? One reason is that they are sensed affectively. Friends are charmed by these implicit messages that reveal something slightly less than sane about the other, something that would only lose its meaning if it were clearly stated. These mutually-affective charming signs pull friends together even though there remains between them something mysterious and unspoken, something that might normally make people feel a distance to one another. And yet, it is not like a secret code that both can decipher. Friends do not share common ideas. They do not necessarily know what the other means, although they still know that they are saying something meaningful to one another.

Deleuze even discusses his own friendships to further illustrate. When he and his hypo-chondriac friend-converse, there might seem to be an absurd disconnect between what they say to one another. For example, if Deleuze asks him how he is doing, his friend replies “like a cork tossed by the sea.” But with Guattari, they may both just simply observe to one another that they have the same brand of hat. In the first case of communication, their explicit meanings did not need to cleanly match for them to read their deeper inexplicable signs. Yet, in the second case of noticing the same hats, it seems they say nothing important at all to one another; but nonetheless, something more profound transpired between them.

Now, to understand why Deleuze appreciates Blanchot’s point that friendship is the condition for thought, we will turn to Deleuze’s discussion of neurophysiology. What we will then suggest is that a friendship of disciplines happens not when they completely understand one another, but when they like friends are sensitive to each other’s inexplicable and charming signs.

We make this connection, because Deleuze talks in similar terms when discussing the brain activity at work in our thinking.

[Clips should be played and viewed simultaneously, if possible]

The brain’s production of ideas is a bit like the activities in a pinball machine. Neural electrical events often occur randomly, indeterminately, and probabilistically. Also, there are both continuous and discontinuous communications between neural circuits. Deleuze notes how very distant neurons can make a ‘jump’ over their gap in this probabilistic scheme.

To further illustrate, he describes a mathematical concept called the baker’s transformation. It gets its name from the procedure that bakers perform when kneading bread dough. They stretch it, which makes it flatter. Then they fold it back upon itself, which returns it to its thicker form. Here first is Deleuze showing the transformative motions with his hands.

(Animation above is my own, made with OpenOffice Draw and Unfreeze)

Likewise, in the Baker’s Transformation, a square is stretched and then folded back upon itself. This animation shows the geometrical rendition of the transformation.

(Animation above is my own, made with OpenOffice Draw and Unfreeze)

What Deleuze observes is how distant points will come together after some number of transformations.

Deleuze uses this example not only to illustrate neuro-biological activity during thinking, but also how he was able to connect ideas between disciplines that he had no training or background in. These illustrations might remind us of how friends communicate without knowing explicitly each other’s meanings. On the basis of charming signs that Deleuze detects in various disciplines, he is able to cross these disparate fields in order to understand ideas that connect them, even without him having the expertise normally needed for uncovering these concepts. He offers two examples.

(Animation above is my own, made with OpenOffice Draw and Unfreeze)

Delaunay image credits, in order
(Thanks spenceralley)
(Thanks leninimports)
(Thanks keepingupwithmyjoneses)
(Thanks joearevaloadam)
(Thanks 1artclub)

In one, he comes to understand an aspect of relativity theory through painting. He wanted to conceptualize regarding the Michelson experiment the way that a light beam expresses a form that is independent of the geometrical structure of the channel that the light beam moves through. In this moving diagram above, we observe the independent diagonal path that the vertical beam traverses, were it seen from an immobile point of reference.

Deleuze arrived at this concept not by working through the mathematics, but instead when he conjoined this scientific expression of the concept with the artistic one of Delaunay, who paints not the geometrical forms that the light shines on, but rather, he paints light itself as independently expressing forms in its own way. His other example is the way he came to understand Riemann space. He needed to grasp how each point is like a joint that varies the space in a non-predetermined way. He obtained this concept by juxtaposing the mathematical expression of this concept with these scenes in Bresson’s Pickpocket.

Deleuze further accounts how mathematicians tell him after reading the details of his mathematical writings that it fits together within what they know in their more specialized way, even though they and Deleuze would probably misunderstand each other in an intellectual conversation. He as well had such resonances with artists. In fact, Deleuze explains the importance also for philosophers to have a non-specialized reading of other philosophers, as if a philosopher for example would read Spinoza the way a merchant would.

For philosophical concepts to form, Deleuze explains, we need as well to have a non-philosophical reading of philosophical texts. So in this way, philosophers should alsoin a sense befriend other philosophers, as well as other non-philosophers, by dwelling below one other’s specialized terminology to instead produce concepts through non-representational communication.


[Julie Van der Wielen reads:]

Philosophy as friendship

Like Deleuze, Blanchot thinks friendship is a condition for thought. Philosophy should proceed in dialogue with the other, otherwise it strangles itself. Nothing is left then but thought thinking itself, scraping concepts until they’re empty. Blanchot himself oscillates between philosophy and literature, saying they’re both open to one another. He believes philosophy needs to be talked to from the outside, staying at her side we have to talk to her from outside, making a dialogue possible. As thought, philosophy needs to be in dialogue with a distant other in order to continue her unpredictable discourse.



Image credits

Delaunay

http://spenceralley.blogspot.com/2011/12/sonia-delaunay-again.html

http://joearevaloadam.blogspot.com/2009/08/robert-delaunay-1885-1941-hommage.htm

http://www.leninimports.com/robert_delaunay.html

http://keepingupwithmyjoneses.blogspot.com/2011/08/explore-art-projects-robert-delaunay.html

http://www.1artclub.com/tall-portuguese-woman-by-robert-delaunay/