Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

ASU advance could provide insight into human’s ability to recognize patterns

11.05.2004


Computers, for all of their computational muscle, do not hold a candle to humans in the ability to recognize patterns or images. This basic quandary in computational theory – why can computers crunch numbers but cannot efficiently process images – has stumped scientists for many years.



Now, researchers at Arizona State University have come up with a model that could help unlock some of the secrets of how humans process patterns and possibly lead to smarter robots. The advance concerns oscillatory associative memory networks, basically the ability to see a pattern, store it and then retrieve that pattern when needed. A good example is how humans can recognize faces.

"It is still a really big mystery as to how human beings can remember so many faces, but that it is extremely difficult for a computer to do," said Ying-Cheng Lai, an ASU professor of mathematics and a professor of electrical engineering in the Ira A. Fulton School of Engineering.


Lai, along with former post-doctoral fellow Takashi Nishikawa (now at Southern Methodist University), and former ASU professor Frank Hoppenstaedt (now at New York University), published their research, "Capacity of Oscillatory Associative Memory Networks with Error-Free Retrieval," in a recent issue of American Physical Society’s Physical Review Letters.

Although what the team developed is a mathematical and computational model for oscillatory networks that can be used associated memory devices, implementation of the model is possible by using electronic circuits as phase-locked loops.

"Computers can do very fast computation that humans cannot do, but humans can recognize patterns so much better than computers," Lai said. "The question is why. What is the fundamental mechanism that a biological system like us can make use of and try to memorize patterns."

A key to pattern recognition is the use of oscillatory associative memory networks. Lai said the human brain and its use of neurons have a great advantage over computer memory in that they employ oscillatory memory systems, systems where the individual components can oscillate or freely change between states. In contrast, digital computer memories operate on a binary number system (1 or 0).

An important advance was made in this area in the 1980s by John Hopfield, a Caltech researcher at the time, who developed the "Hopfield network" to help understand how biological memory works. But the main drawback of the Hopfield network is that while it represents how biological memory works, it employs discrete state memory units while most biological units are oscillatory.

"Our work is the first demonstration of the possibility for oscillatory networks to have the same memory capacity as for the discrete-state Hopfield network," Lai said. "When the Hopfield network was invented, it was considered a revolutionary step in understanding how biological memory works.

"A difficulty with the Hopfield network is that it consists of units (or artificial neurons) with two discrete states," he added. "It is therefore desirable to study oscillatory networks but this has been a struggle, as all previous work shows that the capacities of these networks are very low compared with that of the Hopfield network. In a sense, our work helps solve this difficulty."

Lai said that the most immediate application for this research is in artificial intelligence, where researchers try to get computers to reason as a human would. He adds that this advance could possibly allow the development of artificial memory devices that would use oscillators, which are robust and secure.

This could mean robots, or other electro-mechanical devices controlled by an electronic "brain" that could recognize patterns and do some form of reasoning on the fly -- basically respond to a much wider range of unanticipated situations -- to perform its task. This would be a big step towards smarter robots.

But the real payoff in Lai’s research could be what it may provide in terms of basic research into the human brain itself. Developing a good model of the human brain, one that could more closely replicate the actual function of the brain as it reasons, might help understand more of its operational basis and how it developed into the organ it is today.

"Biological systems, such as cells and neurons, are oscillators," Lai explained. "Demonstrating that oscillatory networks can have memories with high capacity is one more step toward understanding biological memory.

"Although the classical Hopfield network provides a plausible mechanism for memory, it has the drawback that it is too idealized as compared with real, oscillatory biological networks," he added. "We hope our work will stimulate further studies of the origin of memory based systems on a more realistic oscillatory network."


Source: Ying-Cheng Lai, (480) 965-6668

Skip Derra | EurekAlert!
Further information:
http://www.asu.edu/asunews/

More articles from Interdisciplinary Research:

nachricht A new method for the 3-D printing of living tissues
16.08.2017 | University of Oxford

nachricht Bergamotene - alluring and lethal for Manduca sexta
21.04.2017 | Max-Planck-Institut für chemische Ökologie

All articles from Interdisciplinary Research >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: The pyrenoid is a carbon-fixing liquid droplet

Plants and algae use the enzyme Rubisco to fix carbon dioxide, removing it from the atmosphere and converting it into biomass. Algae have figured out a way to increase the efficiency of carbon fixation. They gather most of their Rubisco into a ball-shaped microcompartment called the pyrenoid, which they flood with a high local concentration of carbon dioxide. A team of scientists at Princeton University, the Carnegie Institution for Science, Stanford University and the Max Plank Institute of Biochemistry have unravelled the mysteries of how the pyrenoid is assembled. These insights can help to engineer crops that remove more carbon dioxide from the atmosphere while producing more food.

A warming planet

Im Focus: Highly precise wiring in the Cerebral Cortex

Our brains house extremely complex neuronal circuits, whose detailed structures are still largely unknown. This is especially true for the so-called cerebral cortex of mammals, where among other things vision, thoughts or spatial orientation are being computed. Here the rules by which nerve cells are connected to each other are only partly understood. A team of scientists around Moritz Helmstaedter at the Frankfiurt Max Planck Institute for Brain Research and Helene Schmidt (Humboldt University in Berlin) have now discovered a surprisingly precise nerve cell connectivity pattern in the part of the cerebral cortex that is responsible for orienting the individual animal or human in space.

The researchers report online in Nature (Schmidt et al., 2017. Axonal synapse sorting in medial entorhinal cortex, DOI: 10.1038/nature24005) that synapses in...

Im Focus: Tiny lasers from a gallery of whispers

New technique promises tunable laser devices

Whispering gallery mode (WGM) resonators are used to make tiny micro-lasers, sensors, switches, routers and other devices. These tiny structures rely on a...

Im Focus: Ultrafast snapshots of relaxing electrons in solids

Using ultrafast flashes of laser and x-ray radiation, scientists at the Max Planck Institute of Quantum Optics (Garching, Germany) took snapshots of the briefest electron motion inside a solid material to date. The electron motion lasted only 750 billionths of the billionth of a second before it fainted, setting a new record of human capability to capture ultrafast processes inside solids!

When x-rays shine onto solid materials or large molecules, an electron is pushed away from its original place near the nucleus of the atom, leaving a hole...

Im Focus: Quantum Sensors Decipher Magnetic Ordering in a New Semiconducting Material

For the first time, physicists have successfully imaged spiral magnetic ordering in a multiferroic material. These materials are considered highly promising candidates for future data storage media. The researchers were able to prove their findings using unique quantum sensors that were developed at Basel University and that can analyze electromagnetic fields on the nanometer scale. The results – obtained by scientists from the University of Basel’s Department of Physics, the Swiss Nanoscience Institute, the University of Montpellier and several laboratories from University Paris-Saclay – were recently published in the journal Nature.

Multiferroics are materials that simultaneously react to electric and magnetic fields. These two properties are rarely found together, and their combined...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

“Lasers in Composites Symposium” in Aachen – from Science to Application

19.09.2017 | Event News

I-ESA 2018 – Call for Papers

12.09.2017 | Event News

EMBO at Basel Life, a new conference on current and emerging life science research

06.09.2017 | Event News

 
Latest News

Rainbow colors reveal cell history: Uncovering β-cell heterogeneity

22.09.2017 | Life Sciences

Penn first in world to treat patient with new radiation technology

22.09.2017 | Medical Engineering

Calculating quietness

22.09.2017 | Physics and Astronomy

VideoLinks
B2B-VideoLinks
More VideoLinks >>>