The associative memory model is a typical neural network model, which can store discretely distributed fixed-point attractors as memory patterns. When the network stores the memory patterns extensively, however, the model has other attractors besides the memory patterns. These attractors are called spurious memories. Both spurious states and memory states are equilibrium, so there is little difference between their dynamics. Recent physiological experiments have shown that short-term dynamic synapse called synaptic depression decreases its transmission efficacy to postsynaptic neurons according to the activities of presynaptic neurons. Previous studies have shown that synaptic depression induces oscillation in the network and decreases the storage capacity at finite temperature. How synaptic depression affects spurious states, however, is still unclear. We investigate the effect of synaptic depression on spurious states through Monte Carlo simulation. The results demonstrate that synaptic depression does not affect the memory states but mainly destabilizes the spurious states and induces the periodic oscillations.
{"title":"Oscillations in Spurious States of the Associative Memory Model with Synaptic Depression","authors":"Shin Murata, Yosuke Otsubo, K. Nagata, M. Okada","doi":"10.7566/JPSJ.83.124004","DOIUrl":"https://doi.org/10.7566/JPSJ.83.124004","url":null,"abstract":"The associative memory model is a typical neural network model, which can store discretely distributed fixed-point attractors as memory patterns. When the network stores the memory patterns extensively, however, the model has other attractors besides the memory patterns. These attractors are called spurious memories. Both spurious states and memory states are equilibrium, so there is little difference between their dynamics. Recent physiological experiments have shown that short-term dynamic synapse called synaptic depression decreases its transmission efficacy to postsynaptic neurons according to the activities of presynaptic neurons. Previous studies have shown that synaptic depression induces oscillation in the network and decreases the storage capacity at finite temperature. How synaptic depression affects spurious states, however, is still unclear. We investigate the effect of synaptic depression on spurious states through Monte Carlo simulation. The results demonstrate that synaptic depression does not affect the memory states but mainly destabilizes the spurious states and induces the periodic oscillations.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129449825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-05-06DOI: 10.14704/NQ.2014.12.3.750
A. Khrennikov, Irina Basieva
Recently foundational issues of applicability of the formalism of quantum mechanics (QM) to cognitive psychology, decision making, and psychophysics attracted a lot of interest. In particular, in cite{DKBB} the possibility to use of the projection postulate and representation of "mental observables" by Hermitian operators was discussed in very detail. The main conclusion of the recent discussions on the foundations of "quantum(-like) cognitive psychology" is that one has to be careful in determination of conditions of applicability of the projection postulate as a mathematical tool for description of measurements of observables represented by Hermitian operators. To represent some statistical experimental data (both physical and mental) in the quantum(-like) way, one has to use generalized quantum observables given by positive operator-valued measures (POVMs). This paper contains a brief review on POVMs which can be useful for newcomers to the field of quantum(-like) studies. Especially interesting for cognitive psychology is a variant of the formula of total probability (FTP) with the interference term derived for incompatible observables given by POVMs. We present an interpretation of the interference term from the psychological viewpoint. As was shown before, the appearance of such a term (perturbing classical FTP) plays the important role in cognitive psychology, e.g., recognition of ambiguous figures and the disjunction effect. The interference term for observables given by POVMs has much more complicated structure than the corresponding term for observables given by Hermitian operators. We elaborate cognitive interpretations of different components of the POVMs-interference term and apply our analysis to a quantum(-like) model of decision making.
{"title":"Quantum model for psychological measurements: from the projection postulate to interference of mental observables represented as positive operator valued measures","authors":"A. Khrennikov, Irina Basieva","doi":"10.14704/NQ.2014.12.3.750","DOIUrl":"https://doi.org/10.14704/NQ.2014.12.3.750","url":null,"abstract":"Recently foundational issues of applicability of the formalism of quantum mechanics (QM) to cognitive psychology, decision making, and psychophysics attracted a lot of interest. In particular, in cite{DKBB} the possibility to use of the projection postulate and representation of \"mental observables\" by Hermitian operators was discussed in very detail. The main conclusion of the recent discussions on the foundations of \"quantum(-like) cognitive psychology\" is that one has to be careful in determination of conditions of applicability of the projection postulate as a mathematical tool for description of measurements of observables represented by Hermitian operators. To represent some statistical experimental data (both physical and mental) in the quantum(-like) way, one has to use generalized quantum observables given by positive operator-valued measures (POVMs). This paper contains a brief review on POVMs which can be useful for newcomers to the field of quantum(-like) studies. Especially interesting for cognitive psychology is a variant of the formula of total probability (FTP) with the interference term derived for incompatible observables given by POVMs. We present an interpretation of the interference term from the psychological viewpoint. As was shown before, the appearance of such a term (perturbing classical FTP) plays the important role in cognitive psychology, e.g., recognition of ambiguous figures and the disjunction effect. The interference term for observables given by POVMs has much more complicated structure than the corresponding term for observables given by Hermitian operators. We elaborate cognitive interpretations of different components of the POVMs-interference term and apply our analysis to a quantum(-like) model of decision making.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125196308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-01DOI: 10.1142/9789814525350_0018
Henning Dickten, C. Elger, K. Lehnertz
We advance our approach of analyzing the dynamics of interacting complex systems with the nonlinear dynamics of interacting nonlinear elements. We replace the widely used lattice-like connection topology of cellular neural networks (CNN) by complex topologies that include both short- and long-ranged connections. With an exemplary time-resolved analysis of asymmetric nonlinear interdependences between the seizure generating area and its immediate surrounding we provide first evidence for complex CNN connection topologies to allow for a faster network optimization together with an improved approximation accuracy of directed interactions.
{"title":"Measuring directed interactions using cellular neural networks with complex connection topologies","authors":"Henning Dickten, C. Elger, K. Lehnertz","doi":"10.1142/9789814525350_0018","DOIUrl":"https://doi.org/10.1142/9789814525350_0018","url":null,"abstract":"We advance our approach of analyzing the dynamics of interacting complex systems with the nonlinear dynamics of interacting nonlinear elements. We replace the widely used lattice-like connection topology of cellular neural networks (CNN) by complex topologies that include both short- and long-ranged connections. With an exemplary time-resolved analysis of asymmetric nonlinear interdependences between the seizure generating area and its immediate surrounding we provide first evidence for complex CNN connection topologies to allow for a faster network optimization together with an improved approximation accuracy of directed interactions.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125674822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-01DOI: 10.1142/9789814525350_0013
Christian Geier, Marie-Therese Kuhnert, C. Elger, K. Lehnertz
There is increasing evidence for specific cortical and subcortical large-scale human epileptic networks to be involved in the generation, spread, and termination of not only primary generalized but also focal onset seizures. The complex dynamics of such networks has been studied with methods of analysis from graph theory. In addition to investigating network-specific characteristics, recent studies aim to determine the functional role of single nodes---such as the epileptic focus---in epileptic brain networks and their relationship to ictogenesis. Utilizing the concept of betweenness centrality to assess the importance of network nodes, previous studies reported the epileptic focus to be of highest importance prior to seizures, which would support the notion of a network hub that facilitates seizure activity. We performed a time-resolved analysis of various aspects of node importance in epileptic brain networks derived from long-term, multi-channel, intracranial electroencephalographic recordings from an epilepsy patient. Our preliminary findings indicate that the epileptic focus is not consistently the most important network node, but node importance may drastically vary over time.
{"title":"On the Centrality of the Focus in Human Epileptic Brain Networks","authors":"Christian Geier, Marie-Therese Kuhnert, C. Elger, K. Lehnertz","doi":"10.1142/9789814525350_0013","DOIUrl":"https://doi.org/10.1142/9789814525350_0013","url":null,"abstract":"There is increasing evidence for specific cortical and subcortical large-scale human epileptic networks to be involved in the generation, spread, and termination of not only primary generalized but also focal onset seizures. The complex dynamics of such networks has been studied with methods of analysis from graph theory. In addition to investigating network-specific characteristics, recent studies aim to determine the functional role of single nodes---such as the epileptic focus---in epileptic brain networks and their relationship to ictogenesis. Utilizing the concept of betweenness centrality to assess the importance of network nodes, previous studies reported the epileptic focus to be of highest importance prior to seizures, which would support the notion of a network hub that facilitates seizure activity. We performed a time-resolved analysis of various aspects of node importance in epileptic brain networks derived from long-term, multi-channel, intracranial electroencephalographic recordings from an epilepsy patient. Our preliminary findings indicate that the epileptic focus is not consistently the most important network node, but node importance may drastically vary over time.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130962901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A stream of conscious experience is extremely contextual; it is impacted by sensory stimuli, drives and emotions, and the web of associations that link, directly or indirectly, the subject of experience to other elements of the individual's worldview. The contextuality of one's conscious experience both enhances and constrains the contextuality of one's behavior. Since we cannot know first-hand the conscious experience of another, it is by way of behavioral contextuality that we make judgements about whether or not, and to what extent, a system is conscious. Thus we believe that a deep understanding of contextuality is vital to the study of consciousness. Methods have been developed for handling contextuality in the microworld of quantum particles. Our goal has been to investigate the extent to which these methods can be used to analyze contextuality in conscious experience.
{"title":"Intrinsic contextuality as the crux of consciousness","authors":"Diederik Aerts, J. Broekaert, L. Gabora","doi":"10.1075/aicr.33.17aer","DOIUrl":"https://doi.org/10.1075/aicr.33.17aer","url":null,"abstract":"A stream of conscious experience is extremely contextual; it is impacted by sensory stimuli, drives and emotions, and the web of associations that link, directly or indirectly, the subject of experience to other elements of the individual's worldview. The contextuality of one's conscious experience both enhances and constrains the contextuality of one's behavior. Since we cannot know first-hand the conscious experience of another, it is by way of behavioral contextuality that we make judgements about whether or not, and to what extent, a system is conscious. Thus we believe that a deep understanding of contextuality is vital to the study of consciousness. Methods have been developed for handling contextuality in the microworld of quantum particles. Our goal has been to investigate the extent to which these methods can be used to analyze contextuality in conscious experience.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121762953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-24DOI: 10.6084/M9.FIGSHARE.868962.V1
Tommaso Furlanello, M. Cristoforetti, Cesare Furlanello, Giuseppe Jurman
The functional and structural representation of the brain as a complex network is marked by the fact that the comparison of noisy and intrinsically correlated high-dimensional structures between experimental conditions or groups shuns typical mass univariate methods. Furthermore most network estimation methods cannot distinguish between real and spurious correlation arising from the convolution due to nodes' interaction, which thus introduces additional noise in the data. We propose a machine learning pipeline aimed at identifying multivariate differences between brain networks associated to different experimental conditions. The pipeline (1) leverages the deconvolved individual contribution of each edge and (2) maps the task into a sparse classification problem in order to construct the associated "sparse deconvolved predictive network", i.e., a graph with the same nodes of those compared but whose edge weights are defined by their relevance for out of sample predictions in classification. We present an application of the proposed method by decoding the covert attention direction (left or right) based on the single-trial functional connectivity matrix extracted from high-frequency magnetoencephalography (MEG) data. Our results demonstrate how network deconvolution matched with sparse classification methods outperforms typical approaches for MEG decoding.
{"title":"Sparse Predictive Structure of Deconvolved Functional Brain Networks","authors":"Tommaso Furlanello, M. Cristoforetti, Cesare Furlanello, Giuseppe Jurman","doi":"10.6084/M9.FIGSHARE.868962.V1","DOIUrl":"https://doi.org/10.6084/M9.FIGSHARE.868962.V1","url":null,"abstract":"The functional and structural representation of the brain as a complex network is marked by the fact that the comparison of noisy and intrinsically correlated high-dimensional structures between experimental conditions or groups shuns typical mass univariate methods. Furthermore most network estimation methods cannot distinguish between real and spurious correlation arising from the convolution due to nodes' interaction, which thus introduces additional noise in the data. We propose a machine learning pipeline aimed at identifying multivariate differences between brain networks associated to different experimental conditions. The pipeline (1) leverages the deconvolved individual contribution of each edge and (2) maps the task into a sparse classification problem in order to construct the associated \"sparse deconvolved predictive network\", i.e., a graph with the same nodes of those compared but whose edge weights are defined by their relevance for out of sample predictions in classification. We present an application of the proposed method by decoding the covert attention direction (left or right) based on the single-trial functional connectivity matrix extracted from high-frequency magnetoencephalography (MEG) data. Our results demonstrate how network deconvolution matched with sparse classification methods outperforms typical approaches for MEG decoding.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133581578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-10DOI: 10.1017/CBO9780511761225.015
L. Gabora, Nancy Holmes
This chapter begins with an investigation into experiences of depression, alienation, and self-abuse amongst the highly creative. After this journey to the dark side, it may be uplifting to see that Mother Nature may have a few tricks up her sleeve to minimize the extent to which we succumb to the negative aspects of creativity while still benefiting from its riches. Finally, we discuss another sobering aspect of creativity--the fact that many of our inventions are dangerous to ourselves, our planet, and the other living things we share it with--and discuss how a creation intimately reflects the structure of the worldview(s) of its creators. Although the discussion focuses primarily on creative writers, we believe that it relevant to creativity in other domains, particularly the arts, and to a lesser extent science, engineering, and business.
{"title":"Dark Side of Creativity - Dangling from a Tassel on the Fabric of Socially Constructed Reality: Reflections on the Creative Writing Process","authors":"L. Gabora, Nancy Holmes","doi":"10.1017/CBO9780511761225.015","DOIUrl":"https://doi.org/10.1017/CBO9780511761225.015","url":null,"abstract":"This chapter begins with an investigation into experiences of depression, alienation, and self-abuse amongst the highly creative. After this journey to the dark side, it may be uplifting to see that Mother Nature may have a few tricks up her sleeve to minimize the extent to which we succumb to the negative aspects of creativity while still benefiting from its riches. Finally, we discuss another sobering aspect of creativity--the fact that many of our inventions are dangerous to ourselves, our planet, and the other living things we share it with--and discuss how a creation intimately reflects the structure of the worldview(s) of its creators. Although the discussion focuses primarily on creative writers, we believe that it relevant to creativity in other domains, particularly the arts, and to a lesser extent science, engineering, and business.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132529572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-10DOI: 10.1007/978-1-4614-5185-3_9
A. Ranjan, L. Gabora
{"title":"Creative Ideas for Actualizing Student Potential","authors":"A. Ranjan, L. Gabora","doi":"10.1007/978-1-4614-5185-3_9","DOIUrl":"https://doi.org/10.1007/978-1-4614-5185-3_9","url":null,"abstract":"","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131866856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-07DOI: 10.1007/978-3-642-54593-1_10
P. Graben, S. Rodrigues
{"title":"On the electrodynamics of neural networks","authors":"P. Graben, S. Rodrigues","doi":"10.1007/978-3-642-54593-1_10","DOIUrl":"https://doi.org/10.1007/978-3-642-54593-1_10","url":null,"abstract":"","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122649270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-30DOI: 10.1007/978-3-642-53734-9_3
C. Gros
{"title":"Generating Functionals for Guided Self-Organization","authors":"C. Gros","doi":"10.1007/978-3-642-53734-9_3","DOIUrl":"https://doi.org/10.1007/978-3-642-53734-9_3","url":null,"abstract":"","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132874484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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