Top-Down Beta Rhythms Support Selective Attention via Interlaminar Interaction: A Model

Lee, Jung H.; Whittington, Miles A.; Kopell, Nancy

doi:10.1371/journal.pcbi.1003164

Cited by 151 publications

(182 citation statements)

References 114 publications

(195 reference statements)

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“…This finding corresponds with laminar recordings in animals that find the strongest β-band synchronization in deep layers (8). Furthermore, β-activity in early visual regions has been associated with top-down streams of information from higher order regions (2,3,48,51).…”

Section: Discussionsupporting

confidence: 86%

The relationship between oscillatory EEG activity and the laminar-specific BOLD signal

Scheeringa

Koopmans

Mourik

et al. 2016

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

158

152

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Electrophysiological recordings in animals have indicated that visual cortex γ-band oscillatory activity is predominantly observed in superficial cortical layers, whereas α-and β-band activity is stronger in deep layers. These rhythms, as well as the different cortical layers, have also been closely related to feedforward and feedback streams of information. Recently, it has become possible to measure laminar activity in humans with high-resolution functional MRI (fMRI). In this study, we investigated whether these different frequency bands show a differential relation with the laminar-resolved blood-oxygen level-dependent (BOLD) signal by combining data from simultaneously recorded EEG and fMRI from the early visual cortex. Our visual attention paradigm allowed us to investigate how variations in strength over trials and variations in the attention effect over subjects relate to each other in both modalities. We demonstrate that γ-band EEG power correlates positively with the superficial layers' BOLD signal and that β-power is negatively correlated to deep layer BOLD and α-power to both deep and superficial layer BOLD. These results provide a neurophysiological basis for human laminar fMRI and link human EEG and high-resolution fMRI to systems-level neuroscience in animals.cortical layers | oscillations | high-resolution fMRI | EEG T he different cortical layers have distinct anatomical connections with subcortical, upstream, and downstream cortical regions (1). Intracranial electrophysiological recordings in animals have linked neuronal oscillations in different frequency bands to the cortical feedforward and feedback information flow and to cortico-subcortical interactions (2-5). In line with these findings, electrophysiological recordings in animals have also demonstrated that changes in α-, β-, and γ-bands can be localized to specific cortical layers (6-12).These findings are almost exclusively based on nonhuman animal research. Although a recent study explored the feasibility of measuring laminar-specific activity with magnetoencephalography (MEG) (13), most recent advances in measuring laminar activity in humans have been made using high-resolution functional MRI (fMRI) (14-18). In this study, we make use of these recent developments to investigate the relationship between electrophysiology and the laminar-specific blood oxygen level-dependent (BOLD) signal. By simultaneously measuring EEG and high-resolution fMRI in humans performing a visual attention task, we demonstrate that changes in specific frequency bands in the EEG can be related to changes in the BOLD signal measured at different cortical depths.The BOLD signal is thought to be closely related to variations in local field potentials (19-21). A wide variety of features in the local field potential (LFP) or EEG, related to several cognitive processes, have now been found to correlate with the BOLD signal (19,20,(22)(23)(24)(25)(26). Most relevant for this study, α-and β-power changes in EEG correlate negatively with the BOLD signal whereas γ-band...

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Section: Discussionsupporting

confidence: 86%

The relationship between oscillatory EEG activity and the laminar-specific BOLD signal

Scheeringa

Koopmans

Mourik

et al. 2016

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

158

152

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“…This mechanism may not account for beta at different recording scales or behavioral states [e.g., motor hold conditions (27,28) or up-states (47)] or in other brain networks, particularly those without spatially aligned PNs such as inhibitory networks in the striatum, where other mechanisms have been proposed (21). Prior modeling and experiments, primarily from slice recordings, have established that neocortical beta rhythms can emerge from the spiking interactions of local excitatory and inhibitory populations (22)(23)(24)(25)(26). Beta in the LFP of slice preparations, including those from somatosensory (22) and motor neocortex (24), operates in a similar 20-to 30-Hz range, dominated by the activity of layer V PNs.…”

Section: Discussionmentioning

confidence: 99%

“…These findings make several predictions about optimal states for perceptual and motor performance and guide causal interventions to modulate beta for optimal function. beta rhythm | magnetoencephalography | computational modeling | sensorimotor processing | Parkinson's disease B eta band rhythms (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29) are a commonly observed activity pattern in the brain. They are found with magnetoencephalography (MEG) (1)(2)(3)(4), EEG (5,6), and local field potential (LFP) recordings from neocortex (7)(8)(9) and are preserved across species (10).…”

mentioning

confidence: 99%

“…Consistent with the first view, beta has been robustly observed in LFP signals from basal ganglia nuclei including the subthalamic nucleus, striatum, and globus pallidus (18,19), and computational models have proposed mechanisms by which beta rhythms can emerge via interactions within and between these circuits (20,21). Other studies have suggested that the neocortex itself has unique properties that generate beta rhythms through spike-mediated synaptic and electrical interactions within local circuits (22)(23)(24)(25) or that beta in early-sensory neocortical areas could be driven in a top-down manner from frontal cortex during attentive states (26).…”

mentioning

confidence: 99%

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Neural mechanisms of transient neocortical beta rhythms: Converging evidence from humans, computational modeling, monkeys, and mice

Sherman

Lee

Law

et al. 2016

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

402

510

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Human neocortical 15-29-Hz beta oscillations are strong predictors of perceptual and motor performance. However, the mechanistic origin of beta in vivo is unknown, hindering understanding of its functional role. Combining human magnetoencephalography (MEG), computational modeling, and laminar recordings in animals, we present a new theory that accounts for the origin of spontaneous neocortical beta. In our MEG data, spontaneous beta activity from somatosensory and frontal cortex emerged as noncontinuous beta events typically lasting <150 ms with a stereotypical waveform. Computational modeling uniquely designed to infer the electrical currents underlying these signals showed that beta events could emerge from the integration of nearly synchronous bursts of excitatory synaptic drive targeting proximal and distal dendrites of pyramidal neurons, where the defining feature of a beta event was a strong distal drive that lasted one beta period (∼50 ms). This beta mechanism rigorously accounted for the beta event profiles; several other mechanisms did not. The spatial location of synaptic drive in the model to supragranular and infragranular layers was critical to the emergence of beta events and led to the prediction that beta events should be associated with a specific laminar current profile. Laminar recordings in somatosensory neocortex from anesthetized mice and awake monkeys supported these predictions, suggesting this beta mechanism is conserved across species and recording modalities. These findings make several predictions about optimal states for perceptual and motor performance and guide causal interventions to modulate beta for optimal function. beta rhythm | magnetoencephalography | computational modeling | sensorimotor processing | Parkinson's disease B eta band rhythms (15-29 Hz) are a commonly observed activity pattern in the brain. They are found with magnetoencephalography (MEG) (1-4), EEG (5, 6), and local field potential (LFP) recordings from neocortex (7-9) and are preserved across species (10). Local beta oscillations and their coordination between regions are implicated in numerous functions, including sensory perception, selective attention, and motor planning and initiation (2,3,6,7,9,(11)(12)(13)(14)(15). Neocortical beta oscillations are disrupted in various neuropathologies, most notably Parkinson's disease (PD), in which treatments that alleviate motor symptoms also reverse the neocortical beta disruption (16,17). Although associations between beta and performance suggest a crucial role in brain function, beta rhythmicity might not be important per se but instead may be an epiphenomenal consequence of other important processes. Discovering how beta emerges at the cellular and network levels is crucial to understanding why beta is such a clear predictor of performance in many domains.A major, unresolved point of debate concerns the locus of beta generation. One prominent view is that beta is generated in basal ganglia and thalamic structures and that neocortical beta is an entrained reflecti...

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“…At its target structure, an input might have differential effects solely due to the rhythm through which it has been transferred. For example, target cells and/or local circuits with resonant properties in particular frequency bands might be addressed differentially by inputs with different rhythms [24][25][26][27] . In that sense, the frequency band through which an input is mediated might functionally tag that input to trigger differential further processing.…”

Section: Cc-by-nc-nd 40 International License Not Peer-reviewed) Ismentioning

confidence: 99%

Visual areas exert feedforward and feedback influences through distinct frequency channels

Bastos

Vezoli

Bosman

et al. 2014

Preprint

178

284

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However, although these studies have revealed the anatomical paths and the neurophysiological consequences of influences in both directions, the neurophysiological mechanisms through which these influences are exerted remain largely elusive. Here we show that in the primate visual system, feedforward influences are carried by thetaband (~4 Hz) and gamma-band (~60-80 Hz) synchronization, and feedback influences by beta-band (~14-18 Hz) synchronization. These frequency-specific asymmetries in directed influences were revealed by simultaneous local field potential recordings from eight visual areas and an analysis of Granger-causal influences across all 28 pairs of areas. The asymmetries in directed influences correlated directly with asymmetries in anatomy and enabled us to build a visual cortical hierarchy from the influence asymmetries alone. Across different task periods, most areas stayed at their hierarchical position, whereas particularly frontal areas moved dynamically. Our results demonstrate that feedforward and feedback signalling use different frequency channels, which might subserve their differential communication requirements and lead to differential local consequences. The possibility to infer hierarchical relationships through functional data alone might make it possible to derive a cortical hierarchy in the living human brain.Many aspects of cognitive performance can only be explained through the concept of feedback influences. For example, reaction times are shortened when stimulus locations are pre-cued and attention can be pre-directed, an effect that cannot be explained if only constant feedforward input is considered 3 . Numerous neurophysiological studies have demonstrated the effects of feedback influences on neuronal activity 2 , yet the mechanisms through which feedback influences are exerted remain elusive. Anatomical studies have revealed that structural connections in the feedforward direction, i.e. from the primary sensory areas to higher order areas, are complemented by connections in the feedback direction 1,4 . In addition, it is well established that feedforward and feedback connections follow a characteristic pattern with regard to cortical layers: Feedforward connections target the granular layer 1 ; they originate preferentially in supragranular layers, and this preference is stronger for projections traversing more hierarchical levels, i.e. it is quantitatively related to the hierarchical distance 4 .Feedback connections avoid targeting the granular layer 1 ; they originate preferentially in the infragranular layers, and again, this preference is stronger for projections traversing more hierarchical levels and is thereby quantitatively related to hierarchical distance 4 . These asymmetries have been used to arrange the visual cortical areas into a hierarchy 1,4 , which has influenced many theories of cognition and brain function 5,6 .Recent studies have documented a neurophysiological asymmetry between cortical layers in visual cortex: While supragranular layers show local gam...

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Top-Down Beta Rhythms Support Selective Attention via Interlaminar Interaction: A Model

Cited by 151 publications

References 114 publications

The relationship between oscillatory EEG activity and the laminar-specific BOLD signal

The relationship between oscillatory EEG activity and the laminar-specific BOLD signal

Neural mechanisms of transient neocortical beta rhythms: Converging evidence from humans, computational modeling, monkeys, and mice

Visual areas exert feedforward and feedback influences through distinct frequency channels

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