Neural Variability Is Quenched by Attention

Arazi, Ayelet; Yeshurun, Yaffa; Dinstein, Ilan

doi:10.1523/jneurosci.0355-19.2019

Cited by 35 publications

(31 citation statements)

References 58 publications

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“…Several studies have found that spatial attention lowers neural spiking variability [40,57,[59][60][61]. Here, we have shown that arousal lowers neural response variability as well, albeit when measured with hemodynamics rather than spikes.…”

Section: Relationship To Previous Studiessupporting

confidence: 52%

Task-related activity in human visual cortex

2020

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The brain exhibits widespread endogenous responses in the absence of visual stimuli, even at the earliest stages of visual cortical processing. Such responses have been studied in monkeys using optical imaging with a limited field of view over visual cortex. Here, we used functional MRI (fMRI) in human participants to study the link between arousal and endogenous responses in visual cortex. The response that we observed was tightly entrained to task timing, was spatially extensive, and was independent of visual stimulation. We found that this response follows dynamics similar to that of pupil size and heart rate, suggesting that task-related activity is related to arousal. Finally, we found that higher reward increased response amplitude while decreasing its trial-to-trial variability (i.e., the noise). Computational simulations suggest that increased temporal precision underlies both of these observations. Our findings are consistent with optical imaging studies in monkeys and support the notion that arousal increases precision of neural activity.

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Section: Relationship To Previous Studiessupporting

confidence: 52%

Task-related activity in human visual cortex

2020

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“…Interestingly, this effect was largely constant throughout the post-stimulus period, rather than peaking and decreasing as with the power-based results. In contradiction to this finding, however, we observed (as seen in previous studies 59,66,67 ) a reduction in TTV, occurring from 200 ms to 700 ms post-stimulus (p = 0.002), as well as an early increase in TTV (p = 0.006). This reduction in TTV, interpreted traditionally as in He (2013), should imply a negative interaction, in direct conflict with the results observed using the method of pseudotrials.…”

Section: Spontaneous-evoked Interaction In the Time Domain -Conflict contrasting

confidence: 99%

Bridging the gap – Spontaneous fluctuations shape stimulus-evoked spectral power

Wainio-Theberge

Wolff

Northoff

2020

Preprint

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Spontaneous fluctuations of neural activity have been shown to influence trial-by-trial variation in perceptual, cognitive, and behavioural outcomes. This implies that these fluctuations affect stimulus-related neural processes, and hence should affect stimulus-evoked neural activity. However, the mechanisms by which spontaneous neural activity shapes stimulus-evoked neural activity have rarely been examined. Employing a large-scale magnetoencephalographic dataset, as well as an electroencephalographic replication dataset, we observed that for high-frequency power, high pre-stimulus activity leads to greater evoked desynchronization (negative interaction); in contrast, for low-frequency power, high pre-stimulus activity induces greater event-related synchronization (positive interaction). We show that both positive and negative interactions are manifest primarily in cortical oscillations, rather than scale-free activity, and can also be observed in the time domain. In summary, we demonstrate positive and negative spontaneous-evoked interaction in multiple electrophysiological processes; these mechanisms "bridge the gap" between spontaneous and evoked activity and provide novel insights into how spontaneous activity influences behaviour and cognition.

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“…This trial-by-trial variability is relatively large before stimulus presentation, and strongly reduced (quenched) approximately 200 ms after stimulus presentation 7 . Neural variability quenching is a robust phenomenon that has been reported in intracellular membrane potential recordings in cats, extracellular recordings of spiking activity in monkeys 7,8 , and in human electroencephalography (EEG) 9–12 , electrocorticography (ECOG) 13 , magnetoencephalography (MEG) 11 , and functional magnetic resonance imaging (fMRI) recordings 14,15 . Furthermore, the phenomenon was reported during both awake and anaesthetized states, and in several cortical areas 7,15 using a variety of sensory stimuli 7,10 .…”

Section: Introductionmentioning

confidence: 99%

The Relationship between Trial-by-Trial Variability and Oscillations of Cortical Population Activity

Daniel

Meindertsma

Arazi

et al. 2019

Sci Rep

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Neural activity fluctuates over time, creating considerable variability across trials. This trial-by-trial neural variability is dramatically reduced (“quenched”) after the presentation of sensory stimuli. Likewise, the power of neural oscillations, primarily in the alpha-beta band, is also reduced after stimulus onset. Despite their similarity, these phenomena have so far been studied and discussed independently. We hypothesized that the two phenomena are tightly coupled in electrophysiological recordings of large cortical neural populations. To test this, we examined magnetoencephalography (MEG) recordings of healthy subjects viewing repeated presentations of a visual stimulus. The timing, amplitude, and spatial topography of variability-quenching and power-suppression were remarkably similar. Neural variability quenching was eliminated by excluding the alpha-beta band from the recordings, but not by excluding other frequency-bands. Moreover, individual magnitudes of alpha-beta band-power explained 86% of between-subject differences in variability quenching. An alternative mechanism that may generate variability quenching is increased phase alignment across trials. However, changes in inter-trial-phase-coherence (ITPC) exhibited distinct timing and no correlations with the magnitude of variability quenching in individual participants. These results reveal that neural variability quenching is tightly coupled with stimulus-induced changes in the power of alpha-beta band oscillations, associating two phenomena that have so far been studied in isolation.

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Neural Variability Is Quenched by Attention

Cited by 35 publications

References 58 publications

Task-related activity in human visual cortex

Task-related activity in human visual cortex

Bridging the gap – Spontaneous fluctuations shape stimulus-evoked spectral power

The Relationship between Trial-by-Trial Variability and Oscillations of Cortical Population Activity

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