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"https://www.zotero.org/groups/cbn/items/3U3BXMAY", "type": "text/html" } }, "meta": { "createdByUser": { "id": 20035, "username": "cjj", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/cjj", "type": "text/html" } } }, "lastModifiedByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "creatorSummary": "Zeng et al.", "parsedDate": "2024", "numChildren": 0 }, "data": { "key": "3U3BXMAY", "version": 69, "itemType": "journalArticle", "title": "Conjunctive encoding of exploratory intentions and spatial information in the hippocampus", "creators": [ { "creatorType": "author", "firstName": "Yi-Fan", "lastName": "Zeng" }, { "creatorType": "author", "firstName": "Ke-Xin", "lastName": "Yang" }, { "creatorType": "author", "firstName": "Yilong", "lastName": "Cui" }, { "creatorType": "author", "firstName": "Xiao-Na", "lastName": "Zhu" }, { "creatorType": "author", "firstName": "Rui", "lastName": "Li" }, { "creatorType": "author", "firstName": "Hanqing", "lastName": "Zhang" }, { "creatorType": "author", "firstName": "Dong Chuan", "lastName": "Wu" }, { "creatorType": "author", "firstName": "Raymond C", "lastName": "Stevens" }, { "creatorType": "author", "firstName": "Ji", "lastName": "Hu" }, { "creatorType": "author", "firstName": "Ning", "lastName": "Zhou" } ], "abstractNote": "", "publicationTitle": "Nature Communications", "publisher": "Nature Publishing Group UK London", "place": "", "date": "2024", "volume": "15", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "3221", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "", "citationKey": "zengConjunctiveEncodingExploratory2024", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [ "7HEPQMI4" ], "relations": {}, "dateAdded": "2025-09-13T03:46:17Z", "dateModified": "2025-09-13T03:46:17Z" } }, { "key": "N78MJVDD", "version": 68, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/N78MJVDD", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/N78MJVDD", "type": "text/html" } }, "meta": { "createdByUser": { "id": 20035, "username": "cjj", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/cjj", "type": "text/html" } } }, "lastModifiedByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "creatorSummary": "Lin et al.", "parsedDate": "2024", "numChildren": 0 }, "data": { "key": "N78MJVDD", "version": 68, "itemType": "journalArticle", "title": "Revealing intact neuronal circuitry in centimeter-sized formalin-fixed paraffin-embedded brain", "creators": [ { "creatorType": "author", "firstName": "Ya-Hui", "lastName": "Lin" }, { "creatorType": "author", "firstName": "Li-Wen", "lastName": "Wang" }, { "creatorType": "author", "firstName": "Yen-Hui", "lastName": "Chen" }, { "creatorType": "author", "firstName": "Yi-Chieh", "lastName": "Chan" }, { "creatorType": "author", "firstName": "Shang-Hsiu", "lastName": "Hu" }, { "creatorType": "author", "firstName": "Sheng-Yan", "lastName": "Wu" }, { "creatorType": "author", "firstName": "Chi-Shiun", "lastName": "Chiang" }, { "creatorType": "author", "firstName": "Guan-Jie", "lastName": "Huang" }, { "creatorType": "author", "firstName": "Shang-Da", "lastName": "Yang" }, { "creatorType": "author", "firstName": "Shi-Wei", "lastName": "Chu" }, { "creatorType": "author", "name": "others" } ], "abstractNote": "", "publicationTitle": "Elife", "publisher": "eLife Sciences Publications Limited", "place": "", "date": "2024", "volume": "13", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "RP93212", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "", "citationKey": "linRevealingIntactNeuronal2024", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [ "7HEPQMI4" ], "relations": {}, "dateAdded": "2025-09-13T03:46:17Z", "dateModified": "2025-09-13T03:46:17Z" } }, { "key": "XQDZ6P6Q", "version": 49, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/XQDZ6P6Q", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/XQDZ6P6Q", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "lastModifiedByUser": { "id": 20035, "username": "cjj", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/cjj", "type": "text/html" } } }, "creatorSummary": "Taillefumier and Magnasco", "parsedDate": "2014-02-20", "numChildren": 3 }, "data": { "key": "XQDZ6P6Q", "version": 49, "itemType": "journalArticle", "title": "A Transition to Sharp Timing in Stochastic Leaky Integrate-and-Fire Neurons Driven by Frozen Noisy Input", "creators": [ { "creatorType": "author", "firstName": "Thibaud", "lastName": "Taillefumier" }, { "creatorType": "author", "firstName": "Marcelo", "lastName": "Magnasco" } ], "abstractNote": "The firing activity of intracellularly stimulated neurons in cortical slices has been demonstrated to be profoundly affected by the temporal structure of the injected current (Mainen & Sejnowski, 1995). This suggests that the timing features of the neural response may be controlled as much by its own biophysical characteristics as by how a neuron is wired within a circuit. Modeling studies have shown that the interplay between internal noise and the fluctuations of the driving input controls the reliability and the precision of neuronal spiking (Cecchi et al., 2000; Tiesinga, 2002; Fellous, Rudolph, Destexhe, & Sejnowski, 2003). In order to investigate this interplay, we focus on the stochastic leaky integrate-and-fire neuron and identify the Hölder exponent H of the integrated input as the key mathematical property dictating the regime of firing of a single-unit neuron. We have recently provided numerical evidence (Taillefumier & Magnasco, 2013) for the existence of a phase transition when becomes less than the statistical Hölder exponent associated with internal gaussian white noise (H=1/2). Here we describe the theoretical and numerical framework devised for the study of a neuron that is periodically driven by frozen noisy inputs with exponent H>0. In doing so, we account for the existence of a transition between two regimes of firing when H=1/2, and we show that spiking times have a continuous density when the Hölder exponent satisfies H>1/2. The transition at H=1/2 formally separates rate codes, for which the neural firing probability varies smoothly, from temporal codes, for which the neuron fires at sharply defined times regardless of the intensity of internal noise.", "publicationTitle": "Neural Computation", "publisher": "", "place": "", "date": "February 20, 2014", "volume": "26", "issue": "5", "section": "", "partNumber": "", "partTitle": "", "pages": "819-859", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Neural Computation", "DOI": "10.1162/NECO_a_00577", "citationKey": "taillefumierTransitionSharpTiming2014", "url": "http://dx.doi.org/10.1162/NECO_a_00577", "accessDate": "2014-12-07T09:14:32Z", "PMID": "", "PMCID": "", "ISSN": "0899-7667", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "MIT Press Journals", "callNumber": "", "rights": "", "extra": "00004", "tags": [], "collections": [ "789AWISU" ], "relations": {}, "dateAdded": "2015-07-29T06:34:52Z", "dateModified": "2016-09-20T03:37:23Z" } }, { "key": "WRR2R7GR", "version": 50, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/WRR2R7GR", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/WRR2R7GR", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "creatorSummary": "Taillefumier and Magnasco", "parsedDate": "2013-04-16", "numChildren": 2 }, "data": { "key": "WRR2R7GR", "version": 50, "itemType": "journalArticle", "title": "A phase transition in the first passage of a Brownian process through a fluctuating boundary with implications for neural coding", "creators": [ { "creatorType": "author", "firstName": "Thibaud", "lastName": "Taillefumier" }, { "creatorType": "author", "firstName": "Marcelo O.", "lastName": "Magnasco" } ], "abstractNote": "Finding the first time a fluctuating quantity reaches a given boundary is a deceptively simple-looking problem of vast practical importance in physics, biology, chemistry, neuroscience, economics, and industrial engineering. Problems in which the bound to be traversed is itself a fluctuating function of time include widely studied problems in neural coding, such as neuronal integrators with irregular inputs and internal noise. We show that the probability p(t) that a Gauss–Markov process will first exceed the boundary at time t suffers a phase transition as a function of the roughness of the boundary, as measured by its Hölder exponent H. The critical value occurs when the roughness of the boundary equals the roughness of the process, so for diffusive processes the critical value is Hc = 1/2. For smoother boundaries, H > 1/2, the probability density is a continuous function of time. For rougher boundaries, H < 1/2, the probability is concentrated on a Cantor-like set of zero measure: the probability density becomes divergent, almost everywhere either zero or infinity. The critical point Hc = 1/2 corresponds to a widely studied case in the theory of neural coding, in which the external input integrated by a model neuron is a white-noise process, as in the case of uncorrelated but precisely balanced excitatory and inhibitory inputs. We argue that this transition corresponds to a sharp boundary between rate codes, in which the neural firing probability varies smoothly, and temporal codes, in which the neuron fires at sharply defined times regardless of the intensity of internal noise.", "publicationTitle": "Proceedings of the National Academy of Sciences", "publisher": "", "place": "", "date": "04/16/2013", "volume": "110", "issue": "16", "section": "", "partNumber": "", "partTitle": "", "pages": "E1438-E1443", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "PNAS", "DOI": "10.1073/pnas.1212479110", "citationKey": "taillefumierPhaseTransitionFirst2013", "url": "http://www.pnas.org/content/110/16/E1438", "accessDate": "2014-12-07T09:15:40Z", "PMID": "23536302", "PMCID": "", "ISSN": "0027-8424, 1091-6490", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.pnas.org", "callNumber": "", "rights": "", "extra": "00010", "tags": [ { "tag": "first-passage time", "type": 1 }, { "tag": "neural code", "type": 1 }, { "tag": "random walk", "type": 1 } ], "collections": [ "789AWISU" ], "relations": {}, "dateAdded": "2015-07-29T06:35:41Z", "dateModified": "2016-09-20T03:37:22Z" } }, { "key": "6VCXQW2A", "version": 51, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/6VCXQW2A", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/6VCXQW2A", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "lastModifiedByUser": { "id": 20035, "username": "cjj", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/cjj", "type": "text/html" } } }, "creatorSummary": "Hunsberger et al.", "parsedDate": "2014-05-30", "numChildren": 2 }, "data": { "key": "6VCXQW2A", "version": 51, "itemType": "journalArticle", "title": "The Competing Benefits of Noise and Heterogeneity in Neural Coding", "creators": [ { "creatorType": "author", "firstName": "Eric", "lastName": "Hunsberger" }, { "creatorType": "author", "firstName": "Matthew", "lastName": "Scott" }, { "creatorType": "author", "firstName": "Chris", "lastName": "Eliasmith" } ], "abstractNote": "Noise and heterogeneity are both known to benefit neural coding. Stochastic resonance describes how noise, in the form of random fluctuations in a neuron's membrane voltage, can improve neural representations of an input signal. Neuronal heterogeneity refers to variation in any one of a number of neuron parameters and is also known to increase the information content of a population. We explore the interaction between noise and heterogeneity and find that their benefits to neural coding are not independent. Specifically, a neuronal population better represents an input signal when either noise or heterogeneity is added, but adding both does not always improve representation further. To explain this phenomenon, we propose that noise and heterogeneity operate using two shared mechanisms: (1) temporally desynchronizing the firing of neurons in the population and (2) linearizing the response of a population to a stimulus. We first characterize the effects of noise and heterogeneity on the information content of populations of either leaky integrate-and-fire or FitzHugh-Nagumo neurons. We then examine how the mechanisms of desynchronization and linearization produce these effects, and find that they work to distribute information equally across all neurons in the population in terms of both signal timing (desynchronization) and signal amplitude (linearization). Without noise or heterogeneity, all neurons encode the same aspects of the input signal; adding noise or heterogeneity allows neurons to encode complementary aspects of the input signal, thereby increasing information content. The simulations detailed in this letter highlight the importance of heterogeneity and noise in population coding, demonstrate their complex interactions in terms of the information content of neurons, and explain these effects in terms of underlying mechanisms.", "publicationTitle": "Neural Computation", "publisher": "", "place": "", "date": "May 30, 2014", "volume": "26", "issue": "8", "section": "", "partNumber": "", "partTitle": "", "pages": "1600-1623", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Neural Computation", "DOI": "10.1162/NECO_a_00621", "citationKey": "hunsbergerCompetingBenefitsNoise2014", "url": "http://dx.doi.org/10.1162/NECO_a_00621", "accessDate": "2015-07-21T02:09:37Z", "PMID": "", "PMCID": "", "ISSN": "0899-7667", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "MIT Press Journals", "callNumber": "", "rights": "", "extra": "00014", "tags": [], "collections": [ "789AWISU" ], "relations": {}, "dateAdded": "2015-07-29T06:34:08Z", "dateModified": "2016-09-20T03:37:21Z" } }, { "key": "27RFBEA5", "version": 52, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/27RFBEA5", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/27RFBEA5", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "lastModifiedByUser": { "id": 20035, "username": "cjj", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/cjj", "type": "text/html" } } }, "creatorSummary": "Mejias and Longtin", "parsedDate": "2012-05-29", "numChildren": 2 }, "data": { "key": "27RFBEA5", "version": 52, "itemType": "journalArticle", "title": "Optimal Heterogeneity for Coding in Spiking Neural Networks", "creators": [ { "creatorType": "author", "firstName": "J. F.", "lastName": "Mejias" }, { "creatorType": "author", "firstName": "A.", "lastName": "Longtin" } ], "abstractNote": "The effect of cellular heterogeneity on the coding properties of neural populations is studied analytically and numerically. We find that heterogeneity decreases the threshold for synchronization, and its strength is nonlinearly related to the network mean firing rate. In addition, conditions are shown under which heterogeneity optimizes network information transmission for either temporal or rate coding, with high input frequencies leading to different effects for each coding strategy. The results are shown to be robust for more realistic conditions.", "publicationTitle": "Physical Review Letters", "publisher": "", "place": "", "date": "May 29, 2012", "volume": "108", "issue": "22", "section": "", "partNumber": "", "partTitle": "", "pages": "228102", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Phys. Rev. Lett.", "DOI": "10.1103/PhysRevLett.108.228102", "citationKey": "mejiasOptimalHeterogeneityCoding2012", "url": "http://link.aps.org/doi/10.1103/PhysRevLett.108.228102", "accessDate": "2015-01-23T13:25:25Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "APS", "callNumber": "", "rights": "", "extra": "00028", "tags": [], "collections": [ "789AWISU" ], "relations": {}, "dateAdded": "2015-07-29T06:33:30Z", "dateModified": "2016-09-20T03:37:20Z" } }, { "key": "V67RNIKJ", "version": 53, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/V67RNIKJ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/V67RNIKJ", "type": "text/html" } }, "meta": { "createdByUser": { "id": 20035, "username": "cjj", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/cjj", "type": "text/html" } } }, "creatorSummary": "Pikovsky et al.", "parsedDate": "2003-04-24", "numChildren": 1 }, "data": { "key": "V67RNIKJ", "version": 53, "itemType": "book", "title": "Synchronization: A Universal Concept in Nonlinear Sciences", "creators": [ { "creatorType": "author", "firstName": "Arkady", "lastName": "Pikovsky" }, { "creatorType": "author", "firstName": "Michael", "lastName": "Rosenblum" }, { "creatorType": "author", "firstName": "Jürgen", "lastName": "Kurths" } ], "abstractNote": "Systems as diverse as clocks, singing crickets, cardiac pacemakers, firing neurons and applauding audiences exhibit a tendency to operate in synchrony. These phenomena are universal and can be understood within a common framework based on modern nonlinear dynamics. The first half of this book describes synchronization without formulae, and is based on qualitative intuitive ideas. The main effects are illustrated with experimental examples and figures, and the historical development is also outlined. The second half of the book presents the main effects of synchronization in a rigorous and systematic manner, describing both classical results on synchronization of periodic oscillators, and recent developments in chaotic systems, large ensembles, and oscillatory media.", "series": "", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2003-04-24", "publisher": "Cambridge University Press", "place": "", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "numPages": "435", "ISBN": "978-0-521-53352-2", "DOI": "", "citationKey": "pikovskySynchronizationUniversalConcept2003", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "Synchronization", "language": "", "libraryCatalog": "Google Books", "callNumber": "", "rights": "", "extra": "05781", "tags": [ { "tag": "Mathematics / Linear & Nonlinear Programming", "type": 1 }, { "tag": "Science / Physics / General", "type": 1 }, { "tag": "Science / System Theory", "type": 1 } ], "collections": [ "ID8X7TXM" ], "relations": {}, "dateAdded": "2015-03-23T05:40:25Z", "dateModified": "2016-09-20T03:37:19Z" } }, { "key": "J2RPGUPC", "version": 54, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/J2RPGUPC", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/J2RPGUPC", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "lastModifiedByUser": { "id": 20035, "username": "cjj", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/cjj", "type": "text/html" } } }, "creatorSummary": "Karmarkar and Buonomano", "parsedDate": "2007-02-01", "numChildren": 2 }, "data": { "key": "J2RPGUPC", "version": 54, "itemType": "journalArticle", "title": "Timing in the Absence of Clocks: Encoding Time in Neural Network States", "creators": [ { "creatorType": "author", "firstName": "Uma R.", "lastName": "Karmarkar" }, { "creatorType": "author", "firstName": "Dean V.", "lastName": "Buonomano" } ], "abstractNote": "Summary\nDecisions based on the timing of sensory events are fundamental to sensory processing. However, the mechanisms by which the brain measures time over ranges of milliseconds to seconds remain unclear. The dominant model of temporal processing proposes that an oscillator emits events that are integrated to provide a linear metric of time. We examine an alternate model in which cortical networks are inherently able to tell time as a result of time-dependent changes in network state. Using computer simulations we show that within this framework, there is no linear metric of time, and that a given interval is encoded in the context of preceding events. Human psychophysical studies were used to examine the predictions of the model. Our results provide theoretical and experimental evidence that, for short intervals, there is no linear metric of time, and that time may be encoded in the high-dimensional state of local neural networks.", "publicationTitle": "Neuron", "publisher": "", "place": "", "date": "February 1, 2007", "volume": "53", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "427-438", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Neuron", "DOI": "10.1016/j.neuron.2007.01.006", "citationKey": "karmarkarTimingAbsenceClocks2007", "url": "http://www.sciencedirect.com/science/article/pii/S0896627307000256", "accessDate": "2015-01-23T15:21:12Z", "PMID": "", "PMCID": "", "ISSN": "0896-6273", "archive": "", "archiveLocation": "", "shortTitle": "Timing in the Absence of Clocks", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "00350", "tags": [ { "tag": "SYSBIO", "type": 1 }, { "tag": "SYSNEURO", "type": 1 } ], "collections": [ "ID8X7TXM" ], "relations": {}, "dateAdded": "2015-03-06T03:40:07Z", "dateModified": "2016-09-20T03:37:18Z" } }, { "key": "II2H2MVK", "version": 55, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/II2H2MVK", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/II2H2MVK", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "creatorSummary": "Goel and Buonomano", "parsedDate": "2014-03-05", "numChildren": 3 }, "data": { "key": "II2H2MVK", "version": 55, "itemType": "journalArticle", "title": "Timing as an intrinsic property of neural networks: evidence from in vivo and in vitro experiments", "creators": [ { "creatorType": "author", "firstName": "Anubhuti", "lastName": "Goel" }, { "creatorType": "author", "firstName": "Dean V.", "lastName": "Buonomano" } ], "abstractNote": "The discrimination and production of temporal patterns on the scale of hundreds of milliseconds are critical to sensory and motor processing. Indeed, most complex behaviours, such as speech comprehension and production, would be impossible in the absence of sophisticated timing mechanisms. Despite the importance of timing to human learning and cognition, little is known about the underlying mechanisms, in particular whether timing relies on specialized dedicated circuits and mechanisms or on general and intrinsic properties of neurons and neural circuits. Here, we review experimental data describing timing and interval-selective neurons in vivo and in vitro. We also review theoretical models of timing, focusing primarily on the state-dependent network model, which proposes that timing in the subsecond range relies on the inherent time-dependent properties of neurons and the active neural dynamics within recurrent circuits. Within this framework, time is naturally encoded in populations of neurons whose pattern of activity is dynamically changing in time. Together, we argue that current experimental and theoretical studies provide sufficient evidence to conclude that at least some forms of temporal processing reflect intrinsic computations based on local neural network dynamics.", "publicationTitle": "Philosophical Transactions of the Royal Society of London B: Biological Sciences", "publisher": "", "place": "", "date": "2014/03/05", "volume": "369", "issue": "1637", "section": "", "partNumber": "", "partTitle": "", "pages": "20120460", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1098/rstb.2012.0460", "citationKey": "goelTimingIntrinsicProperty2014", "url": "http://rstb.royalsocietypublishing.org/content/369/1637/20120460", "accessDate": "2015-01-23T15:22:55Z", "PMID": "24446494", "PMCID": "", "ISSN": "0962-8436, 1471-2970", "archive": "", "archiveLocation": "", "shortTitle": "Timing as an intrinsic property of neural networks", "language": "en", "libraryCatalog": "rstb.royalsocietypublishing.org", "callNumber": "", "rights": ". © 2014 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/, which permits unrestricted use, provided the original author and source are credited.", "extra": "00027 \nThe discrimination and production of temporal patterns on the scale of hundreds of milliseconds are critical to sensory and motor processing. Indeed, most complex behaviours, such as speech comprehension and production, would be impossible in the absence of sophisticated timing mechanisms. Despite the importance of timing to human learning and cognition, little is known about the underlying mechanisms, in particular whether timing relies on specialized dedicated circuits and mechanisms or on general and intrinsic properties of neurons and neural circuits. Here, we review experimental data describing timing and interval-selective neurons in vivo and in vitro . We also review theoretical models of timing, focusing primarily on the state-dependent network model, which proposes that timing in the subsecond range relies on the inherent time-dependent properties of neurons and the active neural dynamics within recurrent circuits. Within this framework, time is naturally encoded in populations of neurons whose pattern of activity is dynamically changing in time. Together, we argue that current experimental and theoretical studies provide sufficient evidence to conclude that at least some forms of temporal processing reflect intrinsic computations based on local neural network dynamics.", "tags": [], "collections": [ "ID8X7TXM" ], "relations": {}, "dateAdded": "2015-03-06T03:40:07Z", "dateModified": "2016-09-20T03:37:16Z" } }, { "key": "FHZAMUFI", "version": 56, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/FHZAMUFI", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/FHZAMUFI", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "creatorSummary": "Merchant et al.", "parsedDate": "2013", "numChildren": 1 }, "data": { "key": "FHZAMUFI", "version": 56, "itemType": "journalArticle", "title": "Neural Basis of the Perception and Estimation of Time", "creators": [ { "creatorType": "author", "firstName": "Hugo", "lastName": "Merchant" }, { "creatorType": "author", "firstName": "Deborah L.", "lastName": "Harrington" }, { "creatorType": "author", "firstName": "Warren H.", "lastName": "Meck" } ], "abstractNote": "Understanding how sensory and motor processes are temporally integrated to control behavior in the hundredths of milliseconds-to-minutes range is a fascinating problem given that the basic electrophysiological properties of neurons operate on a millisecond timescale. Single-unit recording studies in monkeys have identified localized timing circuits, whereas neuropsychological studies of humans who have damage to the basal ganglia have indicated that core structures, such as the cortico-thalamic-basal ganglia circuit, play an important role in timing and time perception. Taken together, these data suggest that a core timing mechanism interacts with context-dependent areas. This idea of a temporal hub with a distributed network is used to investigate the abstract properties of interval tuning as well as temporal illusions and intersensory timing. We conclude by proposing that the interconnections built into this core timing mechanism are designed to provide a form of degeneracy as protection against injury, disease, or age-related decline.", "publicationTitle": "Annual Review of Neuroscience", "publisher": "", "place": "", "date": "2013", "volume": "36", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "313-336", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Annu. Rev. Neurosci.", "DOI": "10.1146/annurev-neuro-062012-170349", "citationKey": "merchantNeuralBasisPerception2013", "url": "http://dx.doi.org/10.1146/annurev-neuro-062012-170349", "accessDate": "2015-03-06T03:20:45Z", "PMID": "23725000", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Annual Reviews", "callNumber": "", "rights": "", "extra": "00215", "tags": [ { "tag": "Temporal processing", "type": 1 }, { "tag": "cortico-thalamic-basal ganglia circuit", "type": 1 }, { "tag": "interval tuning", "type": 1 }, { "tag": "medial premotor cortex", "type": 1 }, { "tag": "striatal beat-frequency model", "type": 1 } ], "collections": [ "ID8X7TXM" ], "relations": {}, "dateAdded": "2015-03-06T03:40:07Z", "dateModified": "2016-09-20T03:37:15Z" } }, { "key": "DCXV2D5H", "version": 57, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/DCXV2D5H", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/DCXV2D5H", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "creatorSummary": "Dranias et al.", "parsedDate": "2013-01-30", "numChildren": 3 }, "data": { "key": "DCXV2D5H", "version": 57, "itemType": "journalArticle", "title": "Short-Term Memory in Networks of Dissociated Cortical Neurons", "creators": [ { "creatorType": "author", "firstName": "Mark R.", "lastName": "Dranias" }, { "creatorType": "author", "firstName": "Han", "lastName": "Ju" }, { "creatorType": "author", "firstName": "Ezhilarasan", "lastName": "Rajaram" }, { "creatorType": "author", "firstName": "Antonius M. J.", "lastName": "VanDongen" } ], "abstractNote": "Short-term memory refers to the ability to store small amounts of stimulus-specific information for a short period of time. It is supported by both fading and hidden memory processes. Fading memory relies on recurrent activity patterns in a neuronal network, whereas hidden memory is encoded using synaptic mechanisms, such as facilitation, which persist even when neurons fall silent. We have used a novel computational and optogenetic approach to investigate whether these same memory processes hypothesized to support pattern recognition and short-term memory in vivo, exist in vitro. Electrophysiological activity was recorded from primary cultures of dissociated rat cortical neurons plated on multielectrode arrays. Cultures were transfected with ChannelRhodopsin-2 and optically stimulated using random dot stimuli. The pattern of neuronal activity resulting from this stimulation was analyzed using classification algorithms that enabled the identification of stimulus-specific memories. Fading memories for different stimuli, encoded in ongoing neural activity, persisted and could be distinguished from each other for as long as 1 s after stimulation was terminated. Hidden memories were detected by altered responses of neurons to additional stimulation, and this effect persisted longer than 1 s. Interestingly, network bursts seem to eliminate hidden memories. These results are similar to those that have been reported from similar experiments in vivo and demonstrate that mechanisms of information processing and short-term memory can be studied using cultured neuronal networks, thereby setting the stage for therapeutic applications using this platform.", "publicationTitle": "The Journal of Neuroscience", "publisher": "", "place": "", "date": "01/30/2013", "volume": "33", "issue": "5", "section": "", "partNumber": "", "partTitle": "", "pages": "1940-1953", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "J. Neurosci.", "DOI": "10.1523/JNEUROSCI.2718-12.2013", "citationKey": "draniasShortTermMemoryNetworks2013", "url": "http://www.jneurosci.org/content/33/5/1940", "accessDate": "2015-03-13T02:10:42Z", "PMID": "23365233", "PMCID": "", "ISSN": "0270-6474, 1529-2401", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.jneurosci.org", "callNumber": "", "rights": "", "extra": "00032", "tags": [], "collections": [ "ID8X7TXM" ], "relations": {}, "dateAdded": "2015-03-13T03:22:45Z", "dateModified": "2016-09-20T03:37:14Z" } }, { "key": "ARUXCR7U", "version": 58, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/ARUXCR7U", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/ARUXCR7U", "type": "text/html" } }, "meta": { "createdByUser": { "id": 20035, "username": "cjj", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/cjj", "type": "text/html" } } }, "creatorSummary": "Coombes et al.", "parsedDate": "2014", "numChildren": 0 }, "data": { "key": "ARUXCR7U", "version": 58, "itemType": "book", "title": "Neural Fields", "creators": [ { "creatorType": "editor", "firstName": "Stephen", "lastName": "Coombes" }, { "creatorType": "editor", "firstName": "Peter", "lastName": "beim Graben" }, { "creatorType": "editor", "firstName": "Roland", "lastName": "Potthast" }, { "creatorType": "editor", "firstName": "James", "lastName": "Wright" } ], "abstractNote": "", "series": "", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2014", "publisher": "Springer Berlin Heidelberg", "place": "Berlin, Heidelberg", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "numPages": "", "ISBN": "978-3-642-54592-4 978-3-642-54593-1", "DOI": "", "citationKey": "coombesNeuralFields2014", "url": "http://link.springer.com/10.1007/978-3-642-54593-1", "accessDate": "2015-04-29T08:57:53Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "CrossRef", "callNumber": "", "rights": "", "extra": "00027", "tags": [], "collections": [ "ID8X7TXM" ], "relations": {}, "dateAdded": "2015-04-29T08:57:53Z", "dateModified": "2016-09-20T03:37:13Z" } }, { "key": "5NHDB9A4", "version": 59, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/5NHDB9A4", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/5NHDB9A4", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "creatorSummary": "Buhusi and Meck", "parsedDate": "2005-10", "numChildren": 3 }, "data": { "key": "5NHDB9A4", "version": 59, "itemType": "journalArticle", "title": "What makes us tick? Functional and neural mechanisms of interval timing", "creators": [ { "creatorType": "author", "firstName": "Catalin V.", "lastName": "Buhusi" }, { "creatorType": "author", "firstName": "Warren H.", "lastName": "Meck" } ], "abstractNote": "Time is a fundamental dimension of life. It is crucial for decisions about quantity, speed of movement and rate of return, as well as for motor control in walking, speech, playing or appreciating music, and participating in sports. Traditionally, the way in which time is perceived, represented and estimated has been explained using a pacemaker-accumulator model that is not only straightforward, but also surprisingly powerful in explaining behavioural and biological data. However, recent advances have challenged this traditional view. It is now proposed that the brain represents time in a distributed manner and tells the time by detecting the coincidental activation of different neural populations.", "publicationTitle": "Nature Reviews. Neuroscience", "publisher": "", "place": "", "date": "Oct 2005", "volume": "6", "issue": "10", "section": "", "partNumber": "", "partTitle": "", "pages": "755-765", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Nat. Rev. Neurosci.", "DOI": "10.1038/nrn1764", "citationKey": "buhusiWhatMakesUs2005", "url": "", "accessDate": "", "PMID": "16163383", "PMCID": "", "ISSN": "1471-003X", "archive": "", "archiveLocation": "", "shortTitle": "What makes us tick?", "language": "eng", "libraryCatalog": "NCBI PubMed", "callNumber": "", "rights": "", "extra": "01225", "tags": [ { "tag": "Animals", "type": 1 }, { "tag": "Brain", "type": 1 }, { "tag": "Humans", "type": 1 }, { "tag": "Models, Neurological", "type": 1 }, { "tag": "Time Perception", "type": 1 } ], "collections": [ "ID8X7TXM" ], "relations": {}, "dateAdded": "2015-03-06T03:40:07Z", "dateModified": "2016-09-20T03:37:12Z" } }, { "key": "2CQSQJXP", "version": 60, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/2CQSQJXP", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/2CQSQJXP", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "lastModifiedByUser": { "id": 20035, "username": "cjj", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/cjj", "type": "text/html" } } }, "creatorSummary": "Pham et al.", "parsedDate": "1998-09-01", "numChildren": 2 }, "data": { "key": "2CQSQJXP", "version": 60, "itemType": "journalArticle", "title": "Noise-induced coherent oscillations in randomly connected neural networks", "creators": [ { "creatorType": "author", "firstName": "J.", "lastName": "Pham" }, { "creatorType": "author", "firstName": "K.", "lastName": "Pakdaman" }, { "creatorType": "author", "firstName": "J.-F.", "lastName": "Vibert" } ], "abstractNote": "We study the dynamics of randomly connected excitatory networks of excitable spike-response neuron models. Large networks can exhibit a nonmonotonic collective response to a stimulation when the coupling strength between neurons lies within an appropriate range. With such a coupling, noise imposed upon neurons induces synchronization of the units and oscillations of the network activity, consisting of a succession of bursts. Furthermore, the regularity of this rhythmic activity goes through a maximum as the noise amplitude is increased. This nonmonotonic dependence on the noise amplitude relies on the fact that noise acts in two antagonistic ways. Noise of low amplitude shortens the interval between two successive bursts, leading to an increase of the dynamics regularity, whereas noise of strong amplitude deteriorates the regularity of the dynamics during a burst. In order to study the influence of the noise amplitude and the coupling on the generation of collective oscillations quantitatively, we consider a simpler network model of excitable units. We derive a discrete map, including the noise amplitude and the coupling strength as parameters, which describes the network dynamics in the limit of a large number of neurons. This map reproduces all characteristic features of the activity dynamics obtained with simulated networks. From the analysis of the bifurcation structure of this map, we obtain parameter regions where noise-induced oscillations occur. Using this map we also study the effect of the network connectivity on the generation of oscillations. We show that such noise-induced coherent oscillations in fully connected networks are related to special initial conditions, and are sensitive to perturbations, whereas they can be the only asymptotically stable regime in sparsely connected networks.", "publicationTitle": "Physical Review E", "publisher": "", "place": "", "date": "September 1, 1998", "volume": "58", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "3610-3622", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Phys. Rev. E", "DOI": "10.1103/PhysRevE.58.3610", "citationKey": "phamNoiseinducedCoherentOscillations1998", "url": "http://link.aps.org/doi/10.1103/PhysRevE.58.3610", "accessDate": "2015-04-22T16:49:44Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "APS", "callNumber": "", "rights": "", "extra": "00058", "tags": [], "collections": [ "ID8X7TXM" ], "relations": {}, "dateAdded": "2015-04-29T07:52:30Z", "dateModified": "2016-09-20T03:37:11Z" } }, { "key": "3RX3P9SD", "version": 61, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/3RX3P9SD", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/3RX3P9SD", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "creatorSummary": "Ju et al.", "parsedDate": "2015-03-04", "numChildren": 3 }, "data": { "key": "3RX3P9SD", "version": 61, "itemType": "journalArticle", "title": "Spatiotemporal Memory Is an Intrinsic Property of Networks of Dissociated Cortical Neurons", "creators": [ { "creatorType": "author", "firstName": "Han", "lastName": "Ju" }, { "creatorType": "author", "firstName": "Mark R.", "lastName": "Dranias" }, { "creatorType": "author", "firstName": "Gokulakrishna", "lastName": "Banumurthy" }, { "creatorType": "author", "firstName": "Antonius M. J.", "lastName": "VanDongen" } ], "abstractNote": "The ability to process complex spatiotemporal information is a fundamental process underlying the behavior of all higher organisms. However, how the brain processes information in the temporal domain remains incompletely understood. We have explored the spatiotemporal information-processing capability of networks formed from dissociated rat E18 cortical neurons growing in culture. By combining optogenetics with microelectrode array recording, we show that these randomly organized cortical microcircuits are able to process complex spatiotemporal information, allowing the identification of a large number of temporal sequences and classification of musical styles. These experiments uncovered spatiotemporal memory processes lasting several seconds. Neural network simulations indicated that both short-term synaptic plasticity and recurrent connections are required for the emergence of this capability. Interestingly, NMDA receptor function is not a requisite for these short-term spatiotemporal memory processes. Indeed, blocking the NMDA receptor with the antagonist APV significantly improved the temporal processing ability of the networks, by reducing spontaneously occurring network bursts. These highly synchronized events have disastrous effects on spatiotemporal information processing, by transiently erasing short-term memory. These results show that the ability to process and integrate complex spatiotemporal information is an intrinsic property of generic cortical networks that does not require specifically designed circuits.", "publicationTitle": "The Journal of Neuroscience", "publisher": "", "place": "", "date": "03/04/2015", "volume": "35", "issue": "9", "section": "", "partNumber": "", "partTitle": "", "pages": "4040-4051", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "J. Neurosci.", "DOI": "10.1523/JNEUROSCI.3793-14.2015", "citationKey": "juSpatiotemporalMemoryIntrinsic2015", "url": "http://www.jneurosci.org/content/35/9/4040", "accessDate": "2015-03-13T02:10:56Z", "PMID": "25740531", "PMCID": "", "ISSN": "0270-6474, 1529-2401", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.jneurosci.org", "callNumber": "", "rights": "", "extra": "00006", "tags": [ { "tag": "classification", "type": 1 }, { "tag": "multielectrode array", "type": 1 }, { "tag": "neuronal networks", "type": 1 }, { "tag": "optogenetics", "type": 1 } ], "collections": [ "ID8X7TXM" ], "relations": {}, "dateAdded": "2015-03-13T03:22:45Z", "dateModified": "2016-09-20T03:37:10Z" } }, { "key": "DU2WW2K9", "version": 62, "library": { "type": "group", "id": 311574, "name": "cbn", "links": { "alternate": { "href": "https://www.zotero.org/groups/cbn", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/311574/items/DU2WW2K9", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/cbn/items/DU2WW2K9", "type": "text/html" } }, "meta": { "createdByUser": { "id": 2181360, "username": "yingjenyang", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/yingjenyang", "type": "text/html" } } }, "lastModifiedByUser": { "id": 20035, "username": "cjj", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/cjj", "type": "text/html" } } }, "creatorSummary": "Arnal and Giraud", "parsedDate": "2012-07", "numChildren": 2 }, "data": { "key": "DU2WW2K9", "version": 62, "itemType": "journalArticle", "title": "Cortical oscillations and sensory predictions", "creators": [ { "creatorType": "author", "firstName": "Luc H.", "lastName": "Arnal" }, { "creatorType": "author", "firstName": "Anne-Lise", "lastName": "Giraud" } ], "abstractNote": "Many theories of perception are anchored in the central notion that the brain continuously updates an internal model of the world to infer the probable causes of sensory events. In this framework, the brain needs not only to predict the causes of sensory input, but also when they are most likely to happen. In this article, we review the neurophysiological bases of sensory predictions of “what’ (predictive coding) and ‘when’ (predictive timing), with an emphasis on low-level oscillatory mechanisms. We argue that neural rhythms offer distinct and adapted computational solutions to predicting ‘what’ is going to happen in the sensory environment and ‘when’.", "publicationTitle": "Trends in Cognitive Sciences", "publisher": "", "place": "", "date": "July 2012", "volume": "16", "issue": "7", "section": "", "partNumber": "", "partTitle": "", "pages": "390-398", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Trends in Cognitive Sciences", "DOI": "10.1016/j.tics.2012.05.003", "citationKey": "arnalCorticalOscillationsSensory2012", "url": "http://www.sciencedirect.com/science/article/pii/S1364661312001210", "accessDate": "2014-12-30T19:42:11Z", "PMID": "", "PMCID": "", "ISSN": "1364-6613", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "00215", "tags": [], "collections": [ "ID8X7TXM" ], "relations": {}, "dateAdded": "2014-12-31T02:43:38Z", "dateModified": "2016-09-20T03:37:09Z" } } ]