The inhibition/excitation ratio related to task-induced oscillatory modulations during a working memory task: A multtimodal-imaging study using MEG and MRS

Takei, Yuichi; Fujihara, Kazuyuki; Tagawa, Minami; Hironaga, Naruhito; Near, Jamie; Kasagi, Masato; Takahashi, Yumiko; Motegi, Tomokazu; Suzuki, Yusuke; Aoyama, Yoshiyuki; Sakurai, Noriko; Yamaguchi, Miho; Tobimatsu, Shozó; Ujita, Koichi; Tsushima, Yoshito; Narita, Kosuke; Fukuda, Masato

doi:10.1016/j.neuroimage.2015.12.057

Cited by 33 publications

(26 citation statements)

References 57 publications

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“…In the beta-band, we found WM load-induced power decreases over bilateral mid-central regions. Although in contrast to some studies, reporting load-related increases of WM-relevant oscillatory activity in n-back tasks (Deiber et al, 2007;Larrouy-Maestri et al, 2013), our findings are consistent with the frequent reports of load-related beta-band desynchronizations, mainly at medial regions (along the anterior-posterior-axis) including the cingulate cortex (Pesonen et al, 2007;Brookes et al, 2011;Palomaki et al, 2012;Takei et al, 2016;Scharinger et al, 2017). Interestingly, Brookes et al (2011) stressed the largely overlapping spatial distribution of load-induced beta-band desynchronizations in WM processing with regions comprising the default mode network (DMN).…”

Section: Wm Load Effectssupporting

confidence: 83%

Post-training Load-Related Changes of Auditory Working Memory – An EEG Study

Gudi-Mindermann

Rimmele

Bruns

et al. 2020

Front. Hum. Neurosci.

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Working memory (WM) refers to the temporary retention and manipulation of information, and its capacity is highly susceptible to training. Yet, the neural mechanisms that allow for increased performance under demanding conditions are not fully understood. We expected that post-training efficiency in WM performance modulates neural processing during high load tasks. We tested this hypothesis, using electroencephalography (EEG) (N = 39), by comparing source space spectral power of healthy adults performing low and high load auditory WM tasks. Prior to the assessment, participants either underwent a modality-specific auditory WM training, or a modality-irrelevant tactile WM training, or were not trained (active control). After a modality-specific training participants showed higher behavioral performance, compared to the control. EEG data analysis revealed general effects of WM load, across all training groups, in the theta-, alpha-, and betafrequency bands. With increased load theta-band power increased over frontal, and decreased over parietal areas. Centro-parietal alpha-band power and central betaband power decreased with load. Interestingly, in the high load condition a tendency toward reduced beta-band power in the right medial temporal lobe was observed in the modality-specific WM training group compared to the modality-irrelevant and active control groups. Our finding that WM processing during the high load condition changed after modality-specific WM training, showing reduced beta-band activity in voice-selective regions, possibly indicates a more efficient maintenance of task-relevant stimuli. The general load effects suggest that WM performance at high load demands involves complementary mechanisms, combining a strengthening of task-relevant and a suppression of task-irrelevant processing.

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Section: Wm Load Effectssupporting

confidence: 83%

Post-training Load-Related Changes of Auditory Working Memory – An EEG Study

Gudi-Mindermann

Rimmele

Bruns

et al. 2020

Front. Hum. Neurosci.

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“…Lastly, n = 1 participant secretly watched movies on his smartphone during the experiment (all participants had been instructed to shut off their smartphones and put them away while the experimenters were watching to avoid potential interference with EEG recording, but this participant seems to have carried a second device that we were initially not aware of). On average, the n = 30 participants who remained in the sample were 23.43 ± 0.717 years old (range [18][19][20][21][22][23][24][25][26][27][28][29][30], had a height of 181.6 ± 1.3 cm (range 169-195), a weight of 76.8 ± 1.9 kg (range 56-100), and an AUDIT score of 6.8 ± 0.6 (range 3-14).…”

Section: Exclusion Of Participants and Sample Characterizationmentioning

confidence: 99%

“…However, it is important to consider that theta oscillations reflecting cognitive control are closely related to gamma-aminobutyric acid (GABA) and glutamate levels in the medial frontal cortex [30] and the striatum [19], which is anatomically well-connected to the medial frontal cortex [31]. Due to this close feed-forward connectivity, the functional contributions of these two brain regions to inhibition cannot be clearly separated.…”

Section: Introductionmentioning

confidence: 99%

Acute Alcohol Effects on Response Inhibition Depend on Response Automatization, but not on GABA or Glutamate Levels in the ACC and Striatum

Bensmann

Zink

Werner

et al. 2020

JCM

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Alcohol increases GABAergic signaling and decreases glutamatergic signaling in the brain. Variations in these neurotransmitter levels may modulate/predict executive functioning. Matching this, strong impairments of response inhibition are one of the most consistently reported cognitive/behavioral effects of acute alcohol intoxication. However, it has never been investigated whether baseline differences in these neurotransmitters allow to predict how much alcohol intoxication impairs response inhibition, and whether this is reflected in neurophysiological measures of cognitive control. We used MR spectroscopy to assess baseline (i.e., sober) GABA and glutamate levels in the anterior cingulate cortex (ACC) and striatum in n = 30 healthy young males, who were subsequently tested once sober and once intoxicated (1.01 permille). Inhibition was assessed with the sustained attention to response task (SART). This paradigm also allows to examine the effect of different degrees of response automatization, which is a known modulator for response inhibition, but does not seem to be substantially impaired during acute intoxication. As a neurophysiological correlate of response inhibition and control, we quantified EEG-derived theta band power and located its source using beamforming analyses. We found that alcohol-induced response inhibition deficits only occurred in the case of response automatization. This was reflected by decreased theta band activity in the left supplementary motor area (SMA), which may reflect modulations in the encoding of a surprise signal in response to inhibition cues. However, we did not find that differences in baseline (i.e., sober) GABA or glutamate levels significantly modulated differences in the size of alcohol-induced inhibition deficits.

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“…Indeed, associations between GABA, glutamate, BOLD signal ( 52 , 53 ), and functional connectivity ( 54 ) have been reported. A recent study found that the frontal GABA/Glx ratio (Glx is the sum of the glutamate and glutamine signals) is related to oscillatory modulations during a working memory task, showing that a low GABA/Glx ratio is needed for efficient inhibition of irrelevant neural activity in precise task performance ( 55 ). Changes in GABA and glutamate levels have been found in patients with schizophrenia, a disorder, which is known to affect cognitive functioning ( 22 , 30 , 56 ).…”

Section: Discussionmentioning

confidence: 99%

Intelligence and Brain Efficiency: Investigating the Association between Working Memory Performance, Glutamate, and GABA

et al. 2017

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Intelligence is a measure of general cognitive functioning capturing a wide variety of different cognitive functions. It has been hypothesized that the brain works to minimize the resources allocated toward higher cognitive functioning. Thus, for the intelligent brain, it may be that not simply more is better, but rather, more efficient is better. Energy metabolism supports both inhibitory and excitatory neurotransmission processes. Indeed, in glutamatergic and GABAergic neurons, the primary energetic costs are associated with neurotransmission. We tested the hypothesis that minimizing resources through the excitation–inhibition balance encompassing gamma-aminobutyric acid (GABA) and glutamate may be beneficial to general cognitive functioning using 7 T 1H-MRS in 23 healthy individuals (male/female = 16/7, 27.7 ± 5.3 years). We find that a higher working memory index is significantly correlated with a lower GABA to glutamate ratio in the frontal cortex and with a lower glutamate level in the occipital cortex. Thus, it seems that working memory performance is associated with the excitation–inhibition balance in the brain.

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The inhibition/excitation ratio related to task-induced oscillatory modulations during a working memory task: A multtimodal-imaging study using MEG and MRS

Cited by 33 publications

References 57 publications

Post-training Load-Related Changes of Auditory Working Memory – An EEG Study

Post-training Load-Related Changes of Auditory Working Memory – An EEG Study

Acute Alcohol Effects on Response Inhibition Depend on Response Automatization, but not on GABA or Glutamate Levels in the ACC and Striatum

Intelligence and Brain Efficiency: Investigating the Association between Working Memory Performance, Glutamate, and GABA

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