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The situated HKB model: how sensorimotor spatial coupling can alter oscillatory brain dynamics

Overview of attention for article published in Frontiers in Computational Neuroscience, January 2013
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Title
The situated HKB model: how sensorimotor spatial coupling can alter oscillatory brain dynamics
Published in
Frontiers in Computational Neuroscience, January 2013
DOI 10.3389/fncom.2013.00117
Pubmed ID
Authors

Miguel Aguilera, Manuel G. Bedia, Bruno A. Santos, Xabier E. Barandiaran

Abstract

Despite the increase of both dynamic and embodied/situated approaches in cognitive science, there is still little research on how coordination dynamics under a closed sensorimotor loop might induce qualitatively different patterns of neural oscillations compared to those found in isolated systems. We take as a departure point the Haken-Kelso-Bunz (HKB) model, a generic model for dynamic coordination between two oscillatory components, which has proven useful for a vast range of applications in cognitive science and whose dynamical properties are well understood. In order to explore the properties of this model under closed sensorimotor conditions we present what we call the situated HKB model: a robotic model that performs a gradient climbing task and whose "brain" is modeled by the HKB equation. We solve the differential equations that define the agent-environment coupling for increasing values of the agent's sensitivity (sensor gain), finding different behavioral strategies. These results are compared with two different models: a decoupled HKB with no sensory input and a passively-coupled HKB that is also decoupled but receives a structured input generated by a situated agent. We can precisely quantify and qualitatively describe how the properties of the system, when studied in coupled conditions, radically change in a manner that cannot be deduced from the decoupled HKB models alone. We also present the notion of neurodynamic signature as the dynamic pattern that correlates with a specific behavior and we show how only a situated agent can display this signature compared to an agent that simply receives the exact same sensory input. To our knowledge, this is the first analytical solution of the HKB equation in a sensorimotor loop and qualitative and quantitative analytic comparison of spatially coupled vs. decoupled oscillatory controllers. Finally, we discuss the limitations and possible generalization of our model to contemporary neuroscience and philosophy of mind.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 2%
France 1 2%
Unknown 48 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 22%
Student > Doctoral Student 7 14%
Student > Bachelor 6 12%
Student > Master 5 10%
Professor > Associate Professor 4 8%
Other 7 14%
Unknown 10 20%
Readers by discipline Count As %
Psychology 8 16%
Neuroscience 6 12%
Agricultural and Biological Sciences 5 10%
Medicine and Dentistry 4 8%
Engineering 3 6%
Other 12 24%
Unknown 12 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 April 2022.
All research outputs
#13,176,719
of 23,571,271 outputs
Outputs from Frontiers in Computational Neuroscience
#460
of 1,377 outputs
Outputs of similar age
#155,142
of 284,650 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#37
of 132 outputs
Altmetric has tracked 23,571,271 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,377 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has gotten more attention than average, scoring higher than 65% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 284,650 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 132 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.