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Modeling habits as self-sustaining patterns of sensorimotor behavior.

Egbert MD, Barandiaran XE - Front Hum Neurosci (2014)

Bottom Line: In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation.We present various environments and the resulting habits that form in them.Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks.

View Article: PubMed Central - PubMed

Affiliation: Embodied Emotion, Cognition and (Inter-)Action Lab, School of Computer Science, University of Hertfordshire Hatfield, UK.

ABSTRACT
In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation. In this paper we use a computational model to present an alternative theoretical view (with some philosophical implications), where habits are seen as self-maintaining patterns of behavior that share properties in common with self-maintaining biological processes, and that inhabit a complex ecological context, including the presence and influence of other habits. Far from mechanical automatisms, this organismic and self-organizing concept of habit can overcome the dominating atomistic and statistical conceptions, and the high temporal resolution effects of situatedness, embodiment and sensorimotor loops emerge as playing a more central, subtle and complex role in the organization of behavior. The model is based on a novel "iterant deformable sensorimotor medium (IDSM)," designed such that trajectories taken through sensorimotor-space increase the likelihood that in the future, similar trajectories will be taken. We couple the IDSM to sensors and motors of a simulated robot, and show that under certain conditions, the IDSM conditions, the IDSM forms self-maintaining patterns of activity that operate across the IDSM, the robot's body, and the environment. We present various environments and the resulting habits that form in them. The model acts as an abstraction of habits at a much needed sensorimotor "meso-scale" between microscopic neuron-based models and macroscopic descriptions of behavior. Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks.

No MeSH data available.


Related in: MedlinePlus

Non-linear functions used to calculate the node-density of a SM-state, and to scale the influence of nodes by their proximity to the current SM-state (Plot A) and by their weight (Plot B). See main text for details.
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Figure 1: Non-linear functions used to calculate the node-density of a SM-state, and to scale the influence of nodes by their proximity to the current SM-state (Plot A) and by their weight (Plot B). See main text for details.

Mentions: New nodes are only added when the density of nodes near the current SM-state, as described by the function ϕ, is less than a threshold value, ϕ(x) < kt = 1. This density function, ϕ, can be thought of as a measure of how many nodes there are near to the SM-state x, and how heavily weighted those nodes are. It is calculated by summing a non-linear function of the distance from every node to the current SM-state d(Np, x), scaled by a sigmoidal function of the node's weight ω(Nw), as described in Equations (1–3) and Figure 1.


Modeling habits as self-sustaining patterns of sensorimotor behavior.

Egbert MD, Barandiaran XE - Front Hum Neurosci (2014)

Non-linear functions used to calculate the node-density of a SM-state, and to scale the influence of nodes by their proximity to the current SM-state (Plot A) and by their weight (Plot B). See main text for details.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4126554&req=5

Figure 1: Non-linear functions used to calculate the node-density of a SM-state, and to scale the influence of nodes by their proximity to the current SM-state (Plot A) and by their weight (Plot B). See main text for details.
Mentions: New nodes are only added when the density of nodes near the current SM-state, as described by the function ϕ, is less than a threshold value, ϕ(x) < kt = 1. This density function, ϕ, can be thought of as a measure of how many nodes there are near to the SM-state x, and how heavily weighted those nodes are. It is calculated by summing a non-linear function of the distance from every node to the current SM-state d(Np, x), scaled by a sigmoidal function of the node's weight ω(Nw), as described in Equations (1–3) and Figure 1.

Bottom Line: In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation.We present various environments and the resulting habits that form in them.Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks.

View Article: PubMed Central - PubMed

Affiliation: Embodied Emotion, Cognition and (Inter-)Action Lab, School of Computer Science, University of Hertfordshire Hatfield, UK.

ABSTRACT
In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation. In this paper we use a computational model to present an alternative theoretical view (with some philosophical implications), where habits are seen as self-maintaining patterns of behavior that share properties in common with self-maintaining biological processes, and that inhabit a complex ecological context, including the presence and influence of other habits. Far from mechanical automatisms, this organismic and self-organizing concept of habit can overcome the dominating atomistic and statistical conceptions, and the high temporal resolution effects of situatedness, embodiment and sensorimotor loops emerge as playing a more central, subtle and complex role in the organization of behavior. The model is based on a novel "iterant deformable sensorimotor medium (IDSM)," designed such that trajectories taken through sensorimotor-space increase the likelihood that in the future, similar trajectories will be taken. We couple the IDSM to sensors and motors of a simulated robot, and show that under certain conditions, the IDSM conditions, the IDSM forms self-maintaining patterns of activity that operate across the IDSM, the robot's body, and the environment. We present various environments and the resulting habits that form in them. The model acts as an abstraction of habits at a much needed sensorimotor "meso-scale" between microscopic neuron-based models and macroscopic descriptions of behavior. Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks.

No MeSH data available.


Related in: MedlinePlus