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Robust transient dynamics and brain functions.

Rabinovich MI, Varona P - Front Comput Neurosci (2011)

Bottom Line: In the last few decades several concepts of dynamical systems theory (DST) have guided psychologists, cognitive scientists, and neuroscientists to rethink about sensory motor behavior and embodied cognition.Specifically, we discuss a hierarchy of coarse-grain models of mental dynamics in the form of kinetic equations of modes.The analysis of the conditions for robustness, i.e., the structural stability of transient (sequential) dynamics, give us the possibility to explain phenomena like the finite capacity of our sequential working memory - a vital cognitive function -, and to find specific dynamical signatures - different kinds of instabilities - of several brain functions and mental diseases.

View Article: PubMed Central - PubMed

Affiliation: BioCircuits Institute, University of California San Diego La Jolla, CA, USA.

ABSTRACT
In the last few decades several concepts of dynamical systems theory (DST) have guided psychologists, cognitive scientists, and neuroscientists to rethink about sensory motor behavior and embodied cognition. A critical step in the progress of DST application to the brain (supported by modern methods of brain imaging and multi-electrode recording techniques) has been the transfer of its initial success in motor behavior to mental function, i.e., perception, emotion, and cognition. Open questions from research in genetics, ecology, brain sciences, etc., have changed DST itself and lead to the discovery of a new dynamical phenomenon, i.e., reproducible and robust transients that are at the same time sensitive to informational signals. The goal of this review is to describe a new mathematical framework - heteroclinic sequential dynamics - to understand self-organized activity in the brain that can explain certain aspects of robust itinerant behavior. Specifically, we discuss a hierarchy of coarse-grain models of mental dynamics in the form of kinetic equations of modes. These modes compete for resources at three levels: (i) within the same modality, (ii) among different modalities from the same family (like perception), and (iii) among modalities from different families (like emotion and cognition). The analysis of the conditions for robustness, i.e., the structural stability of transient (sequential) dynamics, give us the possibility to explain phenomena like the finite capacity of our sequential working memory - a vital cognitive function -, and to find specific dynamical signatures - different kinds of instabilities - of several brain functions and mental diseases.

No MeSH data available.


Related in: MedlinePlus

Irregular switching between firing and quiescent states in an inhibitory striatal network model of 500 neurons under a fixed excitatory input condition. Different colors correspond to randomly selected neurons in the network. Adapted with permission from Ponzi and Wickens (2010).
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Figure 4: Irregular switching between firing and quiescent states in an inhibitory striatal network model of 500 neurons under a fixed excitatory input condition. Different colors correspond to randomly selected neurons in the network. Adapted with permission from Ponzi and Wickens (2010).

Mentions: An interesting example of possible applications of the WLC principle for understanding cognitive processes has been presented in the context of the study of the striatum (Ponzi and Wickens, 2010). The striatum is the main input structure of the basal ganglia (BG), receiving excitatory inputs from the entire cerebral cortex (McGeorge and Faull, 1989). This neural system plays an important role in planning, decision making, and modulation of movement pathways, but is also involved in a variety of other cognitive processes (Forstmann et al., 2008; Kubota et al., 2009). In humans the striatum is activated, for example, by stimuli associated with reward. Medium spiny neurons (MSNs), which account for 90% of striatal neurons, form inhibitory synapses with each other. This anatomy has been interpreted in the past as a winner-take-all (WTA) network. However, several experimental findings argue against this interpretation (Czubayko and Plenz, 2002; Tunstall et al., 2002; Koos et al., 2004; Taverna et al., 2004; Ponzi and Wickens, 2010): sparse connectivity with weak interactions, predominant one-way connections, and the presence of irregular firing (Wilson, 1993). A simulation of a striatal inhibitory network model composed of spiking neurons has shown that cells form assemblies that fire in sequential coherent episodes and display complex identity-temporal spiking patterns even when cortical excitation is simply constant or fluctuating noisily (Ponzi and Wickens, 2010; see Figure 4). These modeling results demonstrate a good qualitative agreement with experimental studies and support a view of endogenously generated robust sequential dynamics in the striatum.


Robust transient dynamics and brain functions.

Rabinovich MI, Varona P - Front Comput Neurosci (2011)

Irregular switching between firing and quiescent states in an inhibitory striatal network model of 500 neurons under a fixed excitatory input condition. Different colors correspond to randomly selected neurons in the network. Adapted with permission from Ponzi and Wickens (2010).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3116137&req=5

Figure 4: Irregular switching between firing and quiescent states in an inhibitory striatal network model of 500 neurons under a fixed excitatory input condition. Different colors correspond to randomly selected neurons in the network. Adapted with permission from Ponzi and Wickens (2010).
Mentions: An interesting example of possible applications of the WLC principle for understanding cognitive processes has been presented in the context of the study of the striatum (Ponzi and Wickens, 2010). The striatum is the main input structure of the basal ganglia (BG), receiving excitatory inputs from the entire cerebral cortex (McGeorge and Faull, 1989). This neural system plays an important role in planning, decision making, and modulation of movement pathways, but is also involved in a variety of other cognitive processes (Forstmann et al., 2008; Kubota et al., 2009). In humans the striatum is activated, for example, by stimuli associated with reward. Medium spiny neurons (MSNs), which account for 90% of striatal neurons, form inhibitory synapses with each other. This anatomy has been interpreted in the past as a winner-take-all (WTA) network. However, several experimental findings argue against this interpretation (Czubayko and Plenz, 2002; Tunstall et al., 2002; Koos et al., 2004; Taverna et al., 2004; Ponzi and Wickens, 2010): sparse connectivity with weak interactions, predominant one-way connections, and the presence of irregular firing (Wilson, 1993). A simulation of a striatal inhibitory network model composed of spiking neurons has shown that cells form assemblies that fire in sequential coherent episodes and display complex identity-temporal spiking patterns even when cortical excitation is simply constant or fluctuating noisily (Ponzi and Wickens, 2010; see Figure 4). These modeling results demonstrate a good qualitative agreement with experimental studies and support a view of endogenously generated robust sequential dynamics in the striatum.

Bottom Line: In the last few decades several concepts of dynamical systems theory (DST) have guided psychologists, cognitive scientists, and neuroscientists to rethink about sensory motor behavior and embodied cognition.Specifically, we discuss a hierarchy of coarse-grain models of mental dynamics in the form of kinetic equations of modes.The analysis of the conditions for robustness, i.e., the structural stability of transient (sequential) dynamics, give us the possibility to explain phenomena like the finite capacity of our sequential working memory - a vital cognitive function -, and to find specific dynamical signatures - different kinds of instabilities - of several brain functions and mental diseases.

View Article: PubMed Central - PubMed

Affiliation: BioCircuits Institute, University of California San Diego La Jolla, CA, USA.

ABSTRACT
In the last few decades several concepts of dynamical systems theory (DST) have guided psychologists, cognitive scientists, and neuroscientists to rethink about sensory motor behavior and embodied cognition. A critical step in the progress of DST application to the brain (supported by modern methods of brain imaging and multi-electrode recording techniques) has been the transfer of its initial success in motor behavior to mental function, i.e., perception, emotion, and cognition. Open questions from research in genetics, ecology, brain sciences, etc., have changed DST itself and lead to the discovery of a new dynamical phenomenon, i.e., reproducible and robust transients that are at the same time sensitive to informational signals. The goal of this review is to describe a new mathematical framework - heteroclinic sequential dynamics - to understand self-organized activity in the brain that can explain certain aspects of robust itinerant behavior. Specifically, we discuss a hierarchy of coarse-grain models of mental dynamics in the form of kinetic equations of modes. These modes compete for resources at three levels: (i) within the same modality, (ii) among different modalities from the same family (like perception), and (iii) among modalities from different families (like emotion and cognition). The analysis of the conditions for robustness, i.e., the structural stability of transient (sequential) dynamics, give us the possibility to explain phenomena like the finite capacity of our sequential working memory - a vital cognitive function -, and to find specific dynamical signatures - different kinds of instabilities - of several brain functions and mental diseases.

No MeSH data available.


Related in: MedlinePlus