The dynamical hypothesis in cognitive science

Gelder, Tim van

doi:10.1017/s0140525x98001733

Cited by 699 publications

(315 citation statements)

References 77 publications

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“…Presumably, nervous systems have evolved slow dynamics to respond to such patterns in the environment. This neuroethological perspective is formalized in a theoretical approach (35)(36)(37)(38) that proposes that phenomena, such as intentions and expectations, traditionally viewed as cognitive, arise out of a continuous dynamic interaction between the animal and the environment and serve to stabilize appropriate coordinated patterns of behavior. In this dynamical formulation, the trajectory that the internal state of the nervous system traces as the animal continuously engages its environment gives rise to the history-dependence of behavior that we interpret as intentions and expectations.…”

Section: Discussionmentioning

confidence: 99%

Dynamical basis of intentions and expectations in a simple neuronal network

Proekt

Březina

Weiss

2004

Proc. Natl. Acad. Sci. U.S.A.

166

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Selection of behavioral responses to external stimuli is strongly influenced by internal states, such as intentions and expectations. These internal states are often attributed to higher-order brain functions. Yet here we show that even in the simple feeding network of Aplysia, external stimuli do not directly specify which motor output is expressed; instead, the motor output is specified by the state of the network at the moment of stimulation. The history-dependence of this network state manifests itself in the same way as do intentions and expectations in the behavior of higher animals. Remarkably, we find that activity-dependent plasticity of a synapse within the network itself, rather than some higher-order network, mediates one important aspect of the change in the network state. Through this mechanism, changes in the network state become an automatic consequence of the generation of behavior. Altogether, our findings suggest that intentions and expectations may emerge within behavior-generating networks themselves from the plasticity of the very processes that generate the behavior.A nimal behavior is not merely a passive response to external stimuli; rather, it expresses also the internal state of the animal. This internal state is presumably somehow embodied in the state of the nervous system. Here we study the manifestations and the neurophysiological basis of the internal state in the experimentally advantageous feeding network of the mollusk Aplysia.State-dependence of network function is not a new concept. In the neurophysiological literature, state-dependence is typically discussed as the ability of contextual cues to modify the response to a stimulus. This type of state-dependence has been demonstrated, for example, for locomotion by using stimulation of the mesencephalic locomotor region to elicit walking in the decerebrate cat. The speed of locomotion is determined by the speed of the treadmill on which the cat is placed (1). In another compelling example, stimulation of a command-like neuron in a leech immersed in water elicits swimming, whereas stimulation of the same neuron when the leech is placed on solid substrate elicits crawling (2). Similarly, stimulation of a command-like neuron in a cricket suspended in air elicits avoidance responses but it fails to do so when the cricket is placed on the ground (3). State-dependence of this type is also seen with neuromodulation. For instance, the ability of sensory stimulation to elicit stridulation in the grasshopper is critically dependent on the presence of a muscarinic agonist (4). The setting of network state by application of neuromodulators is a common phenomenon that has been well characterized in simple neuronal networks, such as the stomatogastric system of crustaceans (5-9).This type of state-dependence fails, however, to account for a fundamental feature of the state-dependence that is observed in animal behavior and human psychology. In the type of statedependence just discussed, the behavior is still unambiguously specified by the ext...

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Section: Discussionmentioning

confidence: 99%

Dynamical basis of intentions and expectations in a simple neuronal network

Proekt

Březina

Weiss

2004

Proc. Natl. Acad. Sci. U.S.A.

166

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“…Thus, dynamicism turns on a commitment to explanations of cognitive phenomena essentially involving (numerical) quantification of variables, a metric of time, analysis of the interdependence between variables, and focus on differential equations of change of those variables over time. In the literature, there are several features that can be emphasized or added to the picture: stability or self-organization (of behavior under certain conditions) (e.g., Kelso 1995), real time modeling (as opposed to 'ersatz' time modeling) (e.g., Van Gelder and Port 1995), continuity in state-space evolution (e.g., Calvo Garzón 2008), agent-environment coupling (e.g., Beer 1995;Chiel and Beer 1997) or quantitative character (of the variables and behavior in the system) (e.g., Van Gelder 1998). Careful delineation of all these related aspects goes clearly beyond the purposes of our discussion.…”

Section: Dynamicismmentioning

confidence: 99%

The systematicity challenge to anti-representational dynamicism

Verdejo

2014

Synthese

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After more than twenty years of representational debate in the cognitive sciences, anti-representational dynamicism may be seen as offering a rival and radically new kind of explanation of systematicity phenomena. In this paper, I argue that, on the contrary, anti-representational dynamicism must face a version of the old systematicity challenge: either it does not explain systematicity, or else, it is just an implementation of representational theories. To show this, I present a purely behavioral and representation-free account of systematicity. I then consider a case of insect sensorimotor systematic behavior: communicating behavior in honey bees. I conclude that anti-representational dynamicism fails to capture the fundamental trait of systematic behaviors qua systematic, i.e., their involving exercises of the same behavioral capacities. I suggest, finally, a collaborative strategy in pursuit of a rich and powerful account of this central phenomenon of high cognition at all levels of explanation, including the representational level.

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“…The dynamical systems approach to cognition claims that cognitive computation is essentially the transient behavior of nonlinear dynamical systems (Crutchfield 1994;Port and van Gelder 1995;van Gelder 1998;Beer 2000;). …”

Section: Dynamical System Modelsmentioning

confidence: 99%

Towards dynamical system models of language-related brain potentials

2008

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Event-related brain potentials (ERP) are important neural correlates of cognitive processes. In the domain of language processing, the N400 and P600 reflect lexicalsemantic integration and syntactic processing problems, respectively. We suggest an interpretation of these markers in terms of dynamical system theory and present two nonlinear dynamical models for syntactic computations where different processing strategies correspond to functionally different regions in the system's phase space.

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The dynamical hypothesis in cognitive science

Cited by 699 publications

References 77 publications

Dynamical basis of intentions and expectations in a simple neuronal network

Dynamical basis of intentions and expectations in a simple neuronal network

The systematicity challenge to anti-representational dynamicism

Towards dynamical system models of language-related brain potentials

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