Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory

Bastos, André M.; Loonis, Roman; Kornblith, Simon; Lundqvist, Mikael; Miller, Earl K.

doi:10.1073/pnas.1710323115

Cited by 259 publications

(309 citation statements)

References 37 publications

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“…It has been suggested that the key function of gamma synchrony is to regulate communication between groups of neurons in order to dynamically reconfigure circuits and generate diverse forms of behavior 7,9,12,13,30 . However, the functional significance of synchronization across neuronal structures, particularly at gamma-frequencies, has long remained one of the most controversial topics in systems neuroscience 31,11,32,18,33,7,8 .…”

Section: Discussionmentioning

confidence: 99%

“…Dynamic processes within the prefrontal cortex that facilitate this kind of behavioral adaptation remain unknown. Synchrony, particularly in the gamma-frequency range (~30-80 Hz), has been proposed to regulate how neurons interact with each other and their downstream targets [3][4][5][6][7][8][9][10][11][12][13] . Thus, by selectively enhancing interactions between neurons in specific brain regions at particular moments, synchrony could generate dynamic brain states to support behavioral adaptation.…”

Section: Introductionmentioning

confidence: 99%

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Interhemispheric gamma synchrony between parvalbumin interneurons supports behavioral adaptation

Cho

Davidson

Marshall

et al. 2019

Preprint

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Organisms must learn novel strategies to adapt to changing environments. Synchrony, which enhances neuronal communication, might create dynamic brain states, facilitating such adaptation. Although synchronization is common in neural systems, its functional significance remains controversial. We studied the role of gamma-frequency (~40 Hz) synchronization, promoted by parvalbumin interneurons, in mice learning multiple new cue-reward associations. Voltage imaging revealed cell type-specific increases of interhemispheric gamma synchrony within prefrontal parvalbumin interneurons, when mice received feedback that previously-learned associations were no longer valid. Disrupting this synchronization by delivering out-of-phase optogenetic stimulation caused mice to perseverate on outdated associations, an effect not reproduced by stimulating in-phase or out-of-phase at other frequencies. Gamma synchrony was specifically required when new associations utilized familiar cues that were previously irrelevant to behavioral outcomes, not when associations involved novel cues, or for reversing previously learned associations. Thus, gamma synchrony is indispensable for reappraising the behavioral salience of external cues.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Interhemispheric gamma synchrony between parvalbumin interneurons supports behavioral adaptation

Cho

Davidson

Marshall

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…These considerations might help to understand why those two sensorimotor rhythms are often aggregated into the same (mu-) rhythm category (Cuevas et al, 2014;Hari, 2006). Having shown that those two rhythms are anatomically and functionally distinct phenomena, it becomes relevant to know whether alpha and beta rhythms can also be systematically differentiated in other frontal brain regions (Bastos et al, 2018;Johnston et al, 2019).…”

Section: Interpretational Issuesmentioning

confidence: 99%

“…Yet, the neurophysiological characteristics of alpha-and beta-band rhythms have often been studied by aggregating these two rhythms into the same (mu-) rhythm category (Cuevas et al, 2014;Hari, 2006;Miller et al, 2010), an approach often justified by the partial overlap in their spatial and spectral distributions (Bressler and Richter, 2015;Haegens et al, 2014;Salmelin and Hari, 1994;Szurhaj et al, 2003) and by the temporal correlation of their power envelopes (Carlqvist et al, 2005;de Lange et al, 2008;Tiihonen et al, 1989). By aggregating those rhythms, it has been recently shown that 4-22 Hz activity modulates high-frequency broadband power in primates' frontal cortex (Bastos et al, 2018;Johnston et al, 2019), and that 10-40 Hz activity is spatially organized in traveling waves (Takahashi et al, 2015). It remains unclear, however, whether that aggregation could obscure differential contributions of those rhythms to movement selection.…”

Section: Introductionmentioning

confidence: 99%

Electrocorticographic dissociation of alpha and beta rhythmic activity in the human sensorimotor system

Stolk

Brinkman

Vansteensel

et al. 2019

Preprint

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Alpha-and beta-band rhythms over the sensorimotor cortex are prominent and functionally relevant for movement selection. However, it remains unclear whether these rhythms modulate excitability of the same neuronal ensembles in the same direction when a movement is selected across the sensorimotor cortex. Using electrocorticography in humans (N=11), we assessed the anatomical and functional specificity of alpha-and beta-band rhythms sampled around the central sulcus during the performance of a psychophysically-controlled movement imagery task. Both rhythms displayed effector-specific task-related modulations, tracked spectral markers of action potentials in the local neural population, and showed spatially systematic phase relationships (traveling waves). Yet, alpha-and beta-band rhythms were weakly correlated, differed in their anatomical and functional properties, and travelled along opposite directions across the sensorimotor cortex. Alpha was stronger at postcentral electrodes evoking somatosensory sensations. A relative increase in alpha power in the somatosensory cortex ipsilateral to the selected arm was associated with spatially unspecific inhibition. Beta was stronger at central electrodes evoking both movements and somatosensory sensations. A focal reduction in beta power over the somatomotor cortex contralateral to the selected arm was associated with a local shift in balance from relative inhibition to excitation. These observations indicate the relevance of both inhibition and disinhibition mechanisms for precise spatiotemporal coordination of movement-related neuronal populations, and illustrate how those mechanisms are implemented through the substantially different neurophysiological properties of sensorimotor alpha and beta rhythms.

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“…These types of short-lived prediction effects might seem surprising if one assumes that pre-activated mental representations are necessarily accompanied by sustained detectable neural activity. However, evidence from intracranial recordings of local neural activity (Mongillo et al, 2008;Stokes et al, 2013;Lundqvist et al, 2016;Bastos et al, 2018;Lundqvist et al, 2018b), and from noninvasive EEG and fMRI recordings of global brain activity (Sprague et al, 2016;Wolff et al, 2017), suggests that, instead of being persistent, neural activity over delays can be relatively sparse, especially when other information is concurrently activated from long term memory (Kaminski et al, 2017). During these delays, anticipated information remains accessible, but it can only be detected when perturbed or "pinged", e.g.…”

Section: The Time Course Of the Prediction Effectmentioning

confidence: 99%

Neural evidence for the prediction of animacy features during language comprehension: Evidence from MEG and EEG Representational Similarity Analysis

Lin

Wlotko

Alexander

et al. 2019

Preprint

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It has been proposed that people can generate probabilistic predictions at multiple levels of representation during language comprehension. We used Magnetoencephalography (MEG) and Electroencephalography (EEG), in combination with Representational Similarity Analysis (RSA), to seek neural evidence for the prediction of animacy features. In two studies, MEG and EEG activity was measured as human participants (both sexes) read three-sentence scenarios. Verbs in the final sentences constrained for either animate or inanimate semantic features of upcoming nouns, and the broader discourse context constrained for either a specific noun or for multiple nouns belonging to the same animacy category. We quantified the similarity between spatial patterns of brain activity following the verbs until just before the presentation of the nouns. The MEG and EEG datasets revealed converging evidence that the similarity between spatial patterns of neural activity following animate constraining verbs was greater than following inanimate constraining verbs. This effect could not be explained by lexical-semantic processing of the verbs themselves. We therefore suggest that it reflected the inherent difference in the semantic similarity structure of the predicted animate and inanimate nouns. Moreover, the effect was present regardless of whether a specific word could be predicted, providing strong evidence for the prediction of coarse-grained semantic features that goes beyond the prediction of individual words.Significance statementLanguage inputs unfold very quickly during real-time communication. By predicting ahead we can give our brains a “head-start”, so that language comprehension is faster and more efficient. While most contexts do not constrain strongly for a specific word, they do allow us to predict some upcoming information. For example, following the context, “they cautioned the…”, we can predict that the next word will be animate rather than inanimate (we can caution a person, but not an object). Here we used EEG and MEG techniques to show that the brain is able to use these contextual constraints to predict the animacy of upcoming words during sentence comprehension, and that these predictions are associated with specific spatial patterns of neural activity.

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Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory

Cited by 259 publications

References 37 publications

Interhemispheric gamma synchrony between parvalbumin interneurons supports behavioral adaptation

Interhemispheric gamma synchrony between parvalbumin interneurons supports behavioral adaptation

Electrocorticographic dissociation of alpha and beta rhythmic activity in the human sensorimotor system

Neural evidence for the prediction of animacy features during language comprehension: Evidence from MEG and EEG Representational Similarity Analysis

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