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| 2. |
- Fransén, Erik, 1962-
(författare)
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Functional role of entorhinal cortex in working memory processing
- 2005
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Ingår i: Neural Networks. - : Elsevier BV. - 0893-6080 .- 1879-2782. ; 18:9, s. 1141-1149
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Tidskriftsartikel (refereegranskat)abstract
- Our learning and memory system has the challenge to work in a world where items to learn are dispersed in space and time. From the information extracted by the perceptual systems, the learning system must select and combine information. Both these operations may require a temporary storage where significance and correlations could be assessed. This work builds on the common hypothesis that hippocampus and subicular, entorhinal and parahippocampal/postrhinal areas are essential for the above-mentioned functions. We bring up two examples of models: the first one is modeling of in vivo and in vitro data from entorhinal cortex layer 11 of delayed match-to-sample working memory experiments, the second one studying mechanisms in theta rhythmicity in EC. In both cases, we discuss how cationic currents might be involved and relate their kinetics and pharmacology to behavioral and cellular experimental results.
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| 3. |
- Green, Michael, et al.
(författare)
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Exploring new possibilities for case based explanation of artificial neural network ensembles
- 2009
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Ingår i: Neural Networks. - : Elsevier BV. - 1879-2782 .- 0893-6080. ; 22:1, s. 75-81
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Tidskriftsartikel (refereegranskat)abstract
- Artificial neural network (ANN) ensembles have long suffered from a lack of interpretability. This has severely limited the practical usability of ANNs in settings where an erroneous decision can be disastrous. Several attempts have been made to alleviate this problem. Many of them are based on decomposing the decision boundary of the ANN into a set of rules. We explore and compare a set of new methods for this explanation process on two artificial data sets (Monks 1 and 3), and one acute coronary syndrome data set consisting of 861 electrocardiograms (ECG) collected retrospectively at the emergency department at Lund University Hospital. The algorithms managed to extract good explanations in more than 84% of the cases. More to the point, the best method provided 99% and 91% good explanations in Monks data 1 and 3 respectively. Also there was a significant overlap between the algorithms. Furthermore, when explaining a given ECG, the overlap between this method and one of the physicians was the same as the one between the two physicians in this study. Still the physicians were significantly, p-value <0.001, more similar to each other than to any of the methods. The algorithms have the potential to be used as an explanatory aid when using ANN ensembles in clinical decision support systems.
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| 4. |
- Hasselmo, Michael E., et al.
(författare)
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A phase code for memory could arise from circuit mechanisms in entorhinal cortex
- 2009
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Ingår i: Neural Networks. - : PERGAMON-ELSEVIER. - 0893-6080 .- 1879-2782. ; 22:8, s. 1129-1138
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Tidskriftsartikel (refereegranskat)abstract
- Neurophysiological data reveals intrinsic cellular properties that suggest how entorhinal cortical neurons could code memory by the phase of their firing. Potential cellular mechanisms for this phase coding in models of entorhinal function are reviewed. This mechanism for phase coding provides a substrate for modeling the responses of entorhinal grid cells, as well as the replay of neural spiking activity during waking and sleep. Efforts to implement these abstract models in more detailed biophysical compartmental simulations raise specific issues that could be addressed in larger scale population models incorporating mechanisms of inhibition.
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| 5. |
- Johansson, Christopher, et al.
(författare)
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Towards Cortex Sized Artificial Neural Systems
- 2007
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Ingår i: Neural Networks. - : Elsevier BV. - 0893-6080 .- 1879-2782. ; 20:1, s. 48-61
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Tidskriftsartikel (refereegranskat)abstract
- We propose, implement, and discuss an abstract model of the mammalian neocortex. This model is instantiated with a sparse recurrently connected neural network that has spiking leaky integrator units and continuous Hebbian learning. First we study the structure, modularization, and size of neocortex, and then we describe a generic computational model of the cortical circuitry. A characterizing feature of the model is that it is based on the modularization of neocortex into hypercolumns and minicolumns.Both a floating- and fixed-point arithmetic implementation of the model are presented along with simulation results. We conclude that an implementation on a cluster computer is not communication but computation bounded. A mouse and rat cortex sized version of our model executes in 44% and 23% of real-time respectively. Further, an instance of the model with 1.6 x 10(6) units and 2 x 10(11) connections performed noise reduction and pattern completion. These implementations represent the current frontier of large-scale abstract neural network simulations in terms of network size and running speed.
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| 6. |
- Morse, Anthony, et al.
(författare)
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Dynamic liquid association : Complex learning without implausible guidance
- 2009
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Ingår i: Neural Networks. - : Elsevier. - 0893-6080 .- 1879-2782. ; 22:7, s. 875-889
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Tidskriftsartikel (refereegranskat)abstract
- Simple associative networks have many desirable properties, but are fundamentally limited by their inability to accurately capture complex relationships. This paper presents a solution significantly extending the abilities of associative networks by using an untrained dynamic reservoir as an input filter. The untrained reservoir provides complex dynamic transformations, and temporal integration, and can be viewed as a complex non-linear feature detector from which the associative network can learn. Typically reservoir systems utilize trained single layer perceptrons to produce desired output responses. However given that both single layer perceptions and simple associative learning have the same computational limitations, i.e. linear separation, they should perform similarly in terms of pattern recognition ability. Further to this the extensive psychological properties of simple associative networks and the lack of explicit supervision required for associative learning motivates this extension overcoming previous limitations. Finally, we demonstrate the resulting model in a robotic embodiment, learning sensorimotor contingencies, and matching a variety of psychological data. (C) 2008 Elsevier Ltd. All rights reserved.
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| 7. |
- Smith, Christian, et al.
(författare)
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Teleoperation for a ball-catching task with significant dynamics
- 2008
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Ingår i: Neural Networks. - : Elsevier. - 0893-6080 .- 1879-2782. ; 21:4, s. 604-620
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we present ongoing work on how to incorporate human motion models into the design of a high performance teleoperation platform. A short description of human motion models used for ball-catching is followed by a more detailed study of a teleoperation platform on which to conduct experiments. Also, a pilot study using minimum jerk theory to explain user input behavior in teleoperated catching is presented.
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