MEG and EEG topography of frontal midline theta rhythm and source localization

Iramina, Keiji; Ueno, S.; Matsuoka, Shigeaki

doi:10.1007/bf01184793

Cited by 33 publications

(21 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this experiment, the peak power was noted at 4.9 -5.9 Hz. That is in accordance with the frequency in the self-initiated movement task in which the peak power was noted at 4.9 -5.9 Hz and also with the frequency of human Fm theta oscillations that has been reported at ϳ5-7 Hz Gevins et al 1997;Inouye et al 1988;Iramina et al 1996;McEvoy et al 2001;Mitchell et al 2008;Sasaki et al 1996a;Slobounov et al 2000;Smith et al 1999;Yamada 1998). …”

Section: Consistency As the Model For Fm Theta Oscillationssupporting

confidence: 86%

Theta Oscillations in Primate Prefrontal and Anterior Cingulate Cortices in Forewarned Reaction Time Tasks

Tsujimoto

Shimazu

Isomura

et al. 2010

Journal of Neurophysiology

View full text Add to dashboard Cite

we introduced a monkey model for human frontal midline theta oscillations as a possible neural correlate of attention. It was based on homologous theta oscillations found in the monkey's prefrontal and anterior cingulate cortices (areas 9 and 32) in a self-initiated handmovement task. However, it has not been confirmed whether theta activity in the monkey model consistently appears in other situations demanding attention. Here, we examined the detailed properties of theta oscillations in four variations of forewarned reaction time tasks with warning (S1) and imperative (S2) stimuli. We characterized the theta oscillations generated exclusively in areas 9 and 32, as follows: 1) in the S1-S2 interval where movement preparation and reward expectation were presumably involved, the theta power was higher than in the pre-S1 period; 2) in the no-go trials of go/no-go tasks instructed by S1, the theta power in the S1-S2 interval was lower than in the pre-S1 period in an asymmetrical reward condition, whereas it was moderately higher in a symmetrical condition; 3) the theta power after reward delivery was higher than in the unrewarded trials; 4) the theta power in the pre-S1 period was higher than in the resting condition; and 5) when the monkey had to guess the S1-S2 duration internally without seeing S2, the theta power in the pre-S1 period was higher than in the original S1-S2 experiment. These findings suggest that attentional loads associated with different causes can induce the same theta activity, thereby supporting the consistency of attentiondependent theta oscillations in our model.

show abstract

Section: Consistency As the Model For Fm Theta Oscillationssupporting

confidence: 86%

Theta Oscillations in Primate Prefrontal and Anterior Cingulate Cortices in Forewarned Reaction Time Tasks

Tsujimoto

Shimazu

Isomura

et al. 2010

Journal of Neurophysiology

View full text Add to dashboard Cite

show abstract

“…A speculative hypothesis then is that the DMN operates in theta mode (which is reflected in the scalp EEG by an increase in frontal theta) when it becomes less active (i.e., during engagement in a task). This would not only explain the observed BOLD decreases during engagement in a task Raichle et al, 2001), but it would also explain why frontal theta power has been shown to increase in a wide range of cognitive tasks, such as mental arithmetic Burgess and Gruzelier, 1997;Inanaga, 1998;Inouye et al, 1994;Iramina et al, 1996;Ishihara and Yoshii, 1972;Ishii et al, 1999;Lazarev, 1998;Mizuki et al, 1980;Sasaki et al, 1996;Smith et al, 1999), error detection tasks (Luu et al, 2003;Luu et al, 2004), language comprehension tasks (Bastiaansen et al, 2002;Hald et al, 2006) and working memory tasks (Gevins et al, 1997;Jensen and Tesche, 2002;Krause et al, 2000;Onton et al, 2005). However, although this suggestion would account for the observed pattern of theta power increases, it appears to contradict several previous functional interpretations that increased frontal theta oscillations reflect synchronous activity in brain regions that are involved in cognitively demanding tasks (Inanaga, 1998;Ishihara and Yoshii, 1972;Jensen and Tesche, 2002;Laukka et al, 1995;Onton et al, 2005;Smith et al, 1999).…”

Section: Discussionmentioning

confidence: 99%

“…This component has a frequency range of roughly 3-8 Hz, and is most prominent over midline fronto-central electrodes. Frontal theta has been observed during various cognitive activities that require attention or short term memory (Burgess and Gruzelier, 1997;Inanaga, 1998;Ishihara and Yoshii, 1972;Laukka et al, 1995;Lazarev, 1998;Smith et al, 1999), and is often studied during mental arithmetic Burgess and Gruzelier, 1997;Inanaga, 1998;Inouye et al, 1994;Iramina et al, 1996;Ishihara and Yoshii, 1972;Ishii et al, 1999;Lazarev, 1998;Mizuki et al, 1980;Sasaki et al, 1996;Smith et al, 1999). More recently, frontal theta power has been found to increase with working memory load (Gevins et al, 1997;Jensen and Tesche, 2002;Krause et al, 2000;Onton et al, 2005), indicating a possible role of theta oscillations in working memory maintenance.…”

Section: Introductionmentioning

confidence: 99%

Frontal theta EEG activity correlates negatively with the default mode network in resting state

Scheeringa¹,

Bastiaansen²,

Petersson³

et al. 2008

International Journal of Psychophysiology

367

295

View full text Add to dashboard Cite

We used simultaneously recorded EEG and fMRI to investigate in which areas the BOLD signal correlates with frontal theta power changes, while subjects were quietly lying resting in the scanner with their eyes open. To obtain a reliable estimate of frontal theta power we applied ICA on band-pass filtered (2-9 Hz) EEG data. For each subject we selected the component that best matched the mid-frontal scalp topography associated with the frontal theta rhythm. We applied a time-frequency analysis on this component and used the time course of the frequency bin with the highest overall power to form a regressor that modeled spontaneous fluctuations in frontal theta power. No significant positive BOLD correlations with this regressor were observed. Extensive negative correlations were observed in the areas that together form the default mode network. We conclude that frontal theta activity can be seen as an EEG index of default mode network activity.

show abstract

“…It has been suggested that this is accomplished by a "buffer" (Atkinson and Shiffrin, 1968), but the physiological mechanisms that would allow multiple items to be stored in a buffer are not known. We have proposed (Lisman and Idiart, 1995;Jensen et al, 1996) that a single brain network can separately maintain up to seven memories by a multiplexing mechanism that uses theta (Gundel and Wilson, 1992;Mecklinger et al, 1992;Nakamura et al, 1992;Iramina et al, 1996;Krause et al, 1996;Sasaki et al, 1996;Gevins et al, 1997;K limesch et al, 1997;Tesche, 1997) and gamma (Galambos et al, 1981;Pantev et al, 1991;Joliot et al, 1994;Tallon-Baudry et al, 1997 brain oscillations for clocking. A memory is represented by groups of neurons that fire in the same gamma cycle.…”

Section: Abstract: Theta; Gamma; Oscillations; Working Memory; Shortmentioning

confidence: 99%

An Oscillatory Short-Term Memory Buffer Model Can Account for Data on the Sternberg Task

1998

View full text Add to dashboard Cite

A limited number (7 Ϯ 2) of items can be held in human short-term memory (STM). We have previously suggested that observed dual (theta and gamma) oscillations could underlie a multiplexing mechanism that enables a single network to actively store up to seven memories. Here we have asked whether models of this kind can account for the data on the Sternberg task, the most quantitative measurements of memory search available. We have found several variants of the oscillatory search model that account for the quantitative dependence of the reaction time distribution on the number of items (S) held in STM. The models differ on the issues of (1) whether theta frequency varies with S and (2) whether the phase of ongoing oscillations is reset by the probe. Using these models the frequencies of dual oscillations can be derived from psychophysical data. The derived values (f ϭ 6-10 Hz; f ␥ ϭ 45-60 Hz) are in reasonable agreement with experimental values. The exhaustive nature of the serial search that has been inferred from psychophysical measurements can be plausibly explained by these oscillatory models. One argument against exhaustive serial search has been the existence of serial position effects. We find that these effects can be explained by short-term repetition priming in the context of serial scanning models. Our results strengthen the case for serial processing and point to experiments that discriminate between variants of the serial scanning process.

show abstract

MEG and EEG topography of frontal midline theta rhythm and source localization

Cited by 33 publications

References 2 publications

Theta Oscillations in Primate Prefrontal and Anterior Cingulate Cortices in Forewarned Reaction Time Tasks

Theta Oscillations in Primate Prefrontal and Anterior Cingulate Cortices in Forewarned Reaction Time Tasks

Frontal theta EEG activity correlates negatively with the default mode network in resting state

An Oscillatory Short-Term Memory Buffer Model Can Account for Data on the Sternberg Task

Contact Info

Product

Resources

About