Showing posts with label foraging behavior. Show all posts
Showing posts with label foraging behavior. Show all posts

Wednesday, August 7, 2024

Every Move You Make


Network science is one of the most rapidly advancing fields of science, and looks more every day to be critical to plugging major holes in the most fundamental of physics, of sociology, of cognition, you name it.

Image credit: I use the same thumbnail every time, can't get more illustrative than that.

One phenomenon of network science that stands out as, well, common sense, is this thing that has a few different names. Most things, as they are only just beginning to be understood or to be useful, they have lots of different names for mostly the same thing. So for this reason, my shorthand for this is "Lévy things". A Lévy flight refers to the way our eyes jump around when we look at things, or the way animals forage. The pattern is one where you make small jumps in a limited area, then a long jump to another area, and small jumps in that new area, then a long jump to another, and so on.

"Lévy things" shows up in relation to many other word-forms - foraging behavior, foraging patterns, explore-exploit mode switching, random walks, Drunkard's walk, Brownian motion, chaos theory - and I'll use these sometimes interchangeably.

The thing that's most intriguing about this phenomenon is that it's making simple something we thought was really complicated. A "random walk" for example, sounds like it's mostly impossible to predict; that's the point of the word random, truly random. But lots of things that look random, especially in the biological world, they're really goverened by Lévy patterns, and if you plug a Lévy pattern into the behavior, it becomes way less random than you thought. And that means you can predict way more than you thought, like many aspects of seemingly unexplainable human behavior. This is also related to fractals, but because we know even less about fractals than we do Lévy flights, it's hard to say exactly how the two are related (for a non-expert). 

Startng with a simple example, from a long time ago - 


Tiny eye movements are under a surprising degree of cognitive control
Apr 2023, phys.org

A very subtle and seemingly random type of eye movement called ocular drift can be influenced by prior knowledge of the expected visual target, suggesting a surprising level of cognitive control over the eyes.

(I guess ocular drift is like a saccade but not)

Most studies of cognitive control over eye movement have covered more obvious movements, such as the "saccade" movements in which the eyes dart across large parts of the visual field. Ocular drift is tiny jitters of the eye that occur even when gaze seems fixed, and thought to improve detection of small, stationary details in a visual scene by scanning across them, effectively converting spatial details into trains of visual signals in time.

via Weill Cornell Medical College: Yen-Chu Lin et al, Cognitive influences on fixational eye movements, Current Biology (2023). DOI: 10.1016/j.cub.2023.03.026


Study shows same movement patterns used by wide range of organisms, with implications for cognition and robotics
Oct 2023, phys.org

While watching electric knifefish in an observation tank, the researchers noticed how when it was dark, the fish shimmied back and forth significantly more frequently. When lights were on, the fish swayed gently with only occasional bursts of rapid movement. Wiggling rapidly allows them to actively sense their surroundings, especially in dark water. In the light, they still make such rapid movements, just far less frequently. 

"We found that the best strategy is to briefly switch into explore mode when uncertainty is too high, and then switch back to exploit mode when uncertainty is back down." 

"If you go to a grocery store, you'll notice people standing in line will change between being stationary and moving around while waiting," Cowan said. "We think that's the same thing going on, that to maintain a stable balance you actually have to occasionally move around and excite your sensors like the knifefish. We found the statistical characteristics of those movements are ubiquitous across a wide range of animals, including humans." 

"Not a single study that we found in the literature violated the rules we discovered in the electric fish, not even single-celled organisms like amoeba sensing an electric field."

via Johns Hopkins University: Mode switching in organisms for solving explore-versus-exploit problems, Nature Machine Intelligence (2023). DOI: 10.1038/s42256-023-00745-y


Exploration—not work—could be key to a vibrant local economy
Mar 2024, phys.org

Suprise!

Infrequent trips to places like restaurants and sports facilities - not the everyday office visit or school drop-off - accounted for the majority of differences in economic outcomes between neighborhoods.

The activities with the strongest predictive power included French and New American restaurants, golf courses, hockey rinks, soccer games, and bagel shops. These kinds of activities accounted for just 2% of trips but explained more than 50% of the variation in economic outcomes between neighborhoods.

"Those irregular and infrequent activities are correlated with explorative behavior, the tendency of some groups to seek out opportunities, connect with different people, and create new businesses."

Again, trips to the office - where we earn our money - were not strongly associated with income or property values. Rather, it's how we spend our free time that drives the economic vibrancy of cities.

(Please don't tell the return-to-office people this or the people who run nyc).  

via University of Florida, MIT, and Northeastern: Shenhao Wang et al, Infrequent activities predict economic outcomes in major American cities, Nature Cities (2024). DOI: 10.1038/s44284-024-00051-7


Study uncovers neural mechanisms underlying foraging behavior in freely moving animals
Apr 2024, phys.org

They use an integrated wireless system for recording brain activity in the frontal areas of macaque brains to examine foraging tasks in real time.

Results indicate that foraging strategies are based on a cortical model of reward dynamics as animals freely explore their environment.

This research can potentially move in the direction of prosthetic devices to influence or bias choice, even noninvasively.

via Rice University Center for Neural Systems Restoration: Neda Shahidi et al, Population coding of strategic variables during foraging in freely moving macaques, Nature Neuroscience (2024). DOI: 10.1038/s41593-024-01575-w

Tuesday, February 28, 2023

Foraging for Behavior Patterns and Other Levy Things


Read a disappointing book recently called The Drunkard's Walk -- only disappointed because I thought it would be about the drunkard's walk but it was just about randomness in statistics and probability. Thought it would be about Levy flights, foraging behavior, random walks, saccades, etc. Something very fractal about the nature of these phenomena.


Explore or exploit: How our brains make choices
Apr 2022, phys.org

Basically, newer areas of the brain (evolutionarily speaking) such as the lateral prefrontal cortex, activated more when an unfamiliar choice was made while older brain systems including the amygdala and the orbitofrontal cortex showed increased activation while weighing the value of explorations vs. exploitation. This suggests that both the newer and older circuits in the brain worked together during the decision-making process rather than against each other as was previously thought.

via University of New Mexico: Jeremy Hogeveen et al, The neurocomputational bases of explore-exploit decision-making, Neuron (2022). DOI: 10.1016/j.neuron.2022.03.014


Typical movement behavior at large events increases risk of spreading infectious diseases
Sep 2022, phys.org

Burstiness (another word for foraging pattern behavior)

An earlier paper on this topic compared the movements of individuals in the crowd to the typical foraging patterns that were also present in our human hunter-gatherer ancestors.

The first author of the study, Ph.D. candidate Philip Rutten, says, "This [new study] shows that, if the infection probability is time-dependent, an intermittently moving but freely mixing crowd may present the highest level of transmission risk." 

Because infection is a probability game.

via University of Amsterdam: Philip Rutten et al, Modelling the dynamic relationship between spread of infection and observed crowd movement patterns at large scale events, Scientific Reports (2022). DOI: 10.1038/s41598-022-19081-z


Not-so private eyes: Eye movements hold clues to how we make decisions
Dec 2022, phys.org

"Unlike your arms or legs, the speed of eye movements is almost totally involuntary. It's a much more direct measurement of these unconscious processes happening in your brain."

In the study, the team asked 22 human subjects to walk on a treadmill then choose between different settings displayed on a computer screen: a brief walk up a steep grade or a longer walk on flat ground.

Researchers discovered that the subjects' eyes gave them away: Even before they made their choices, the treadmill users tended to move their eyes faster when they looked toward the options they ended up choosing. The more vigorously their eyes moved, the more they seemed to prefer their choice.

"Initially, the saccades to either option were similarly vigorous," Ahmed said. "Then, as time passed, that vigor increased and it increased even faster for the option they eventually chose."

via University of Colorado at Boulder: Colin C. Korbisch et al, Saccade vigor reflects the rise of decision variables during deliberation, Current Biology (2022). DOI: 10.1016/j.cub.2022.10.053

Image credit: A laser beam (orange) creates excitons (purple) that are trapped inside the semicondcutor material by electric fields. Credit: Puneet Murthy / ETH Zurich

Wednesday, May 11, 2022

Body Problems


Drunken solution to the chaotic three-body problem
Dec 2021, phys.org

This one is a real mind-bender.

Two objects orbiting each other like the Earth and Moon, can be precisely predicted. Newton helped with that one. Add a third, and all hell breaks loose. It's called the three-body problem, although it's also called chaos, and the best we can do is to say that the future trajectories of these bodies is essentially random. 

We know that at some point, the third body will be ejected into space. When, where, how fast, etc, we can't know; it's too chaotic. But these researchers model this using the theory of random walks (or the "drunkard's walk") --

This series of close encounters could be regarded as a drunkard's walk. Like a drunk's step, a star is ejected randomly, comes back, and another (or the same star) is ejected to a likely different random direction (similar to another step taken by the drunk) and comes back, and so forth, until a star is completely ejected and never returns (akin to a drunk falling into a ditch).

And --

Instead of predicting the actual outcome, they calculated the probability of any given outcome of each phase-1 [chaotic] interaction. While chaos implies that a complete solution is impossible, its random nature allows calculation of the probability that a triple interaction ends in one particular way rather than another. Then, the entire series of close approaches could be modeled by using the theory of random walks, sometimes called "drunkard's walk." 

So they use probability and work their way backwards from there?

via Technion - Israel Institute of Technology: Yonadav Barry Ginat et al, Analytical, Statistical Approximate Solution of Dissipative and Nondissipative Binary-Single Stellar Encounters, Physical Review X (2021). DOI: 10.1103/PhysRevX.11.031020

Image credit: On the Way to Paradise, Dainbramage on Fractal Forums, 2017

Post Script:
A three-qubit entangled state has been realized in a fully controllable array of spin qubits in silicon
Sep 2021, phys.org

via RIKEN: Kenta Takeda et al, Quantum tomography of an entangled three-qubit state in silicon, Nature Nanotechnology (2021). DOI: 10.1038/s41565-021-00925-0