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            Noise in Human Cognition

Gilden, DL; Thornton, Thomas L.; Mallon, MW

doi:10.1126/science.7892611

Cited by 583 publications

(563 citation statements)

References 20 publications

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“…Earlier studies have indicated that the cortical evoked responses (32), as well as cognitive performance (24,33), oscillate at an infraslow rate. It may thus be that the ISO introduced in our study is not restricted to sleep states, but it may rather reflect a continuous oscillatory behavior of wide range of brain functions during both sleep and awakeness (see also ref.…”

Section: Discussionmentioning

confidence: 99%

Infraslow oscillations modulate excitability and interictal epileptic activity in the human cortex during sleep

Vanhatalo

Palva

Holmes

et al. 2004

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

435

397

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Human cortical activity has been intensively examined at frequencies ranging from 0.5 Hz to several hundred Hz. Recent studies have, however, reported also infraslow fluctuations in neuronal population activity, magnitude of electroencephalographic oscillations, discrete sleep events, as well as in the occurrence of interictal events. Here we use direct current electroencephalography to demonstrate large-scale infraslow oscillations in the human cortex at frequencies ranging from 0.02 to 0.2 Hz. These oscillations, which are not detectable in conventional electroencephalography because of its limited recording bandwidth (typical lower limit 0.5 Hz), were observed in widespread cortical regions. Notably, the infraslow oscillations were strongly synchronized with faster activities, as well as with the interictal epileptic events and K complexes. Our findings suggest that the infraslow oscillations represent a slow, cyclic modulation of cortical gross excitability, providing also a putative mechanism for the as yet enigmatic aggravation of epileptic activity during sleep.epilepsy ͉ slow cortical oscillations ͉ phase synchrony ͉ direct current electroencephalography ͉ full-band electroencephalography A large body of literature has characterized functional and clinical correlates of cortical oscillatory activity seen in the human electroencephalography (EEG) at frequencies ranging from 0.5 Hz to several hundred Hz (1). In addition to these relatively fast EEG oscillations, some studies have demonstrated infraslow fluctuations in, for instance, neuronal population activity (2-5), EEG power (5-9), discrete sleep events (arousals, spindles, K complexes) (9-12), as well as in the occurrence of epileptic events (4, 11, 13). These observations have raised the possibility that the human cortex may generate infraslow oscillations (ISOs) underlying such fluctuations. ISOs are not detectable in conventional EEG because of its limited recording bandwidth (typical lower limit, 0.5 Hz; ref. 1).In the present study, we used direct current (DC)-coupled EEG scalp recordings (14-16) to demonstrate that ISOs are, in fact, a salient, large-scale feature of the human EEG. They were tightly associated with a cyclic modulation of fast EEG activity as well as discrete EEG events such as K complexes and interictal activity. In analogy with recent studies demonstrating that slow delta oscillations (0.5-1 Hz) may modulate brain excitability (17, 18), our data points to a role of ISOs in the control of gross cortical excitability. Our findings also provide a window on the modulation of interictal epileptiform events (IIEs) and on sleep-epilepsy interactions in the human brain. MethodsSubjects and EEG Recording. We studied 16 subjects (four females; average age, 34.3 years; range, 16-51 years) during overnight (n ϭ 9) or daytime (n ϭ 7) sleep. This study was approved by the Human Subjects Committee of the University of Washington. Twelve subjects were recorded using a custom-made 16-channel DC-coupled EEG amplifier and Ag͞AgCl electrodes (refs....

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Section: Discussionmentioning

confidence: 99%

Infraslow oscillations modulate excitability and interictal epileptic activity in the human cortex during sleep

Vanhatalo

Palva

Holmes

et al. 2004

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

435

397

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“…Two types of context effects are considered in this section: context effects arising from between-trial dependencies and context effects that are constant over the course of the experiment. Sequential effects are nearly ubiquitous in cognitive science, with examples including representations of spatial or temporal intervals (Gilden, Thornton, & Mallon, 1995), serial position effects in free recall (e.g., Murdock, 1962;Raaijmakers & Shiffrin, 1981), and priming (Schooler, Shiffrin, & Raaijmakers, 2001;Howes & Osgood, 1954). However, MCMC was developed for the digital computer and assumes that decisions depend only on the current stimuli and are not influenced by any previous trials.…”

Section: Relaxing the Assumptionsmentioning

confidence: 99%

Uncovering mental representations with Markov chain Monte Carlo

Sanborn

Griffiths

Shiffrin

2010

Cognitive Psychology

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A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP URL' above for details on accessing the published version and note that access may require a subscription. Richard M. Shiffrin Indiana University, Bloomington Abstract A key challenge for cognitive psychology is the investigation of mental representations, such as object categories, subjective probabilities, choice utilities, and memory traces. In many cases, these representations can be expressed as a non-negative function defined over a set of objects. We present a behavioral method for estimating these functions. Our approach uses people as components of a Markov chain Monte Carlo (MCMC) algorithm, a sophisticated sampling method originally developed in statistical physics. Experiments 1 and 2 verified the MCMC method by training participants on various category structures and then recovering those structures. Experiment 3 demonstrated that the MCMC method can be used estimate the structures of the real-world animal shape categories of giraffes, horses, dogs, and cats. Experiment 4 combined the MCMC method with multidimensional scaling to demonstrate how different accounts of the structure of categories, such as prototype and exemplar models, can be tested, producing samples from the categories of apples, oranges, and grapes.

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“…in blood pressure dynamics, electroencephalographic potentials, stride intervals, center-of-pressure displacements, body temperature, respiration and human cognition [15,28,29,30,31]. Since the heart dynamics is the simplest physiological observable, it is also the best studied time series.…”

Section: More Than Romance: the Human Heart Has Memory!mentioning

confidence: 99%