A psycholinguistic model of natural language parsing implemented in simulated neurons

Huyck, Christian R.

doi:10.1007/s11571-009-9080-6

Cited by 22 publications

(22 citation statements)

References 47 publications

(42 reference statements)

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“…Later, Redish et al combined the two cognitive maps in 1998 to make symmetric and asymmetric connections coexist. There have been many promising works about neural coding and the cognitive map in the recent years (Han et al 2014; Duch and Dobosz 2011; Strauss et al 2010; Sato and Yamaguchi 2009; Huyck 2009; Wagatsuma and Yamaguchi 2007). And there are also many wonderful pioneering researches on neural dynamics model which set up a framework for the theory and application of neural system model (Adeli and Park 1998; Park and Adeli 1995, 1997; Adeli and Karim 1997; Senouci and Adeli 2001; Adeli and Kim 2001; Tashakori and Adeli 2002; Ahmadkhanlou and Adeli 2005).…”

Section: Introductionmentioning

confidence: 99%

Optimal path-finding through mental exploration based on neural energy field gradients

Wang

Zhu

2016

Cogn Neurodyn

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Rodent animal can accomplish self-locating and path-finding task by forming a cognitive map in the hippocampus representing the environment. In the classical model of the cognitive map, the system (artificial animal) needs large amounts of physical exploration to study spatial environment to solve path-finding problems, which costs too much time and energy. Although Hopfield’s mental exploration model makes up for the deficiency mentioned above, the path is still not efficient enough. Moreover, his model mainly focused on the artificial neural network, and clear physiological meanings has not been addressed. In this work, based on the concept of mental exploration, neural energy coding theory has been applied to the novel calculation model to solve the path-finding problem. Energy field is constructed on the basis of the firing power of place cell clusters, and the energy field gradient can be used in mental exploration to solve path-finding problems. The study shows that the new mental exploration model can efficiently find the optimal path, and present the learning process with biophysical meaning as well. We also analyzed the parameters of the model which affect the path efficiency. This new idea verifies the importance of place cell and synapse in spatial memory and proves that energy coding is effective to study cognitive activities. This may provide the theoretical basis for the neural dynamics mechanism of spatial memory.

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Section: Introductionmentioning

confidence: 99%

Optimal path-finding through mental exploration based on neural energy field gradients

Wang

Zhu

2016

Cogn Neurodyn

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“…This is a cognitive model of parsing implemented in neurons (Huyck, 2009). Context free parsing requires variable binding of some sort, and in this model, binding was done by short-term potentiation.…”

Section: Beyond Cabot1mentioning

confidence: 99%

A comparison of simple agents implemented in simulated neurons

Huyck

Evans

Mitchell

2015

Biologically Inspired Cognitive Architectures

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Neuromorphic embodied cell assembly agents that learn are one application being developed for the Human Brain Project (HBP). The HBP is building tools, available for all researchers, for building brain simulations. Existing simulated neural Cell Assembly agents are being translated to the platforms provided by the HBP; these agents run on neuromorphic chips in addition to von Neumann based computers. Whilst translation of the agents to the software technology demanded by the HBP platforms is relatively straightforward, porting to the neuromorphic chips is a non-trivial software engineering task. Versions of the simple agent, CABot1, have been developed in fatiguing leaky integrate and fire neurons, Izhikevich neurons and leaky integrate and fire neurons. These have been developed to run in Java, PyNN, NEST and Neuromorphic hardware. All variants are roughly equivalent. The agents view a picture, implement simple commands, and respond to a context sensitive directive involving the content of the picture. By running variants of these agents on different platforms, and with the different simulated neural models, implicit assumptions in these models can be revealed. Once these Cell Assembly agents have been translated and embodied in a virtual environment, they will be extended to learn more effectively. The use of neural hardware supports the real time simulation of many more neurons, providing a platform for exploration of more complex simulated neural systems.

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“…However, recent models show that neurally grounded approaches can parse linguistic streams (Huyck 2009) and embed symbolic parsing processes within temporally continuous neural dynamics (beim Graben et al 2008b). The conceptual mapping from these dynamics onto the DFT is therefore feasible.…”

Section: Limitationsmentioning

confidence: 99%

Swing it to the left, swing it to the right: enacting flexible spatial language using a neurodynamic framework

2009

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Research is continually expanding the empirical and theoretical picture of embodiment and dynamics in language. To date, however, a formalized neural dynamic framework for embodied linguistic processes has yet to emerge. To advance embodied theories of language, the present work develops a formalized neural dynamic framework of spatial language that explicitly integrates linguistic processes and dynamic sensory-motor systems. We then implement and test our spatial language architecture on a robotic platform continuously linked to real-time camera input. In a suite of tasks using everyday objects we demonstrate the framework's capacity for both contextuallydependent behavioral flexibility and the seamless integration of spatial, non-spatial, and symbolic representations. To our knowledge this is the first unified, neurally-grounded architecture integrating these processes and behaviors.

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A psycholinguistic model of natural language parsing implemented in simulated neurons

Cited by 22 publications

References 47 publications

Optimal path-finding through mental exploration based on neural energy field gradients

Optimal path-finding through mental exploration based on neural energy field gradients

A comparison of simple agents implemented in simulated neurons

Swing it to the left, swing it to the right: enacting flexible spatial language using a neurodynamic framework

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