Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks

Hagen, Espen; Dahmen, David; Stavrinou, Maria L.; Lindén, Henrik; Tetzlaff, Tom; Albada, Sacha van; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T.

doi:10.1093/cercor/bhw237

Cited by 89 publications

(186 citation statements)

References 175 publications

(487 reference statements)

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“…Our data provide a first glimpse into the neural mechanisms of syntactic structure building in the brain. Theoretical models of the broadband high-gamma power signal that we measured here suggest that it increases linearly with the number of temporally uncorrelated inputs over a population of neurons near the recording site (54,55). Its increase with the number of open nodes therefore suggests a recruitment of increasingly larger pools of neurons as syntactic complexity increases.…”

Section: Discussionmentioning

confidence: 66%

Neurophysiological dynamics of phrase-structure building during sentence processing

Nelson

Karoui

Giber

et al. 2017

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

248

250

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Although sentences unfold sequentially, one word at a time, most linguistic theories propose that their underlying syntactic structure involves a tree of nested phrases rather than a linear sequence of words. Whether and how the brain builds such structures, however, remains largely unknown. Here, we used human intracranial recordings and visual word-by-word presentation of sentences and word lists to investigate how left-hemispheric brain activity varies during the formation of phrase structures. In a broad set of language-related areas, comprising multiple superior temporal and inferior frontal sites, high-gamma power increased with each successive word in a sentence but decreased suddenly whenever words could be merged into a phrase. Regression analyses showed that each additional word or multiword phrase contributed a similar amount of additional brain activity, providing evidence for a merge operation that applies equally to linguistic objects of arbitrary complexity. More superficial models of language, based solely on sequential transition probability over lexical and syntactic categories, only captured activity in the posterior middle temporal gyrus. Formal model comparison indicated that the model of multiword phrase construction provided a better fit than probabilitybased models at most sites in superior temporal and inferior frontal cortices. Activity in those regions was consistent with a neural implementation of a bottom-up or left-corner parser of the incoming language stream. Our results provide initial intracranial evidence for the neurophysiological reality of the merge operation postulated by linguists and suggest that the brain compresses syntactically wellformed sequences of words into a hierarchy of nested phrases.ost linguistic theories hold that the proper theoretical description of sentences is not a linear sequence of words, in the way we encounter it during reading or listening, but rather a hierarchical structure of nested phrases (1-4). Whether and how the brain encodes such nested structures during language comprehension, however, remains largely unknown. Brain-imaging studies of syntax have homed in on a narrow set of left-hemisphere areas (5-16), particularly the left superior temporal sulcus (STS) and inferior frontal gyrus (IFG), whose activation correlates with predictors of syntactic complexity (6,7,10,13,14). In particular, core syntax areas in left IFG and posterior STS (pSTS) show an increasing activation with the number of words that can be integrated into a well-formed phrase (10,14). Similarly, magneto-encephalography signals show increasing power in beta and theta bands during sentence-structure build-up (17) and a systematic phase locking to phrase structure in the low-frequency domain (18).These studies leave open the central question of whether and how neural populations in these brain areas create hierarchical phrase structures within each sentence. To address this question, intracranial recordings with more precise joint spatial and temporal resolution may be necess...

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Section: Discussionmentioning

confidence: 66%

Neurophysiological dynamics of phrase-structure building during sentence processing

Nelson

Karoui

Giber

et al. 2017

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

248

250

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“…A detailed ‘realistic’ model of cortical column 72,73 has recently become available because of a decade-long effort by the Blue Brain Project currently continuing under the umbrella of the Human Brain Project. These models of synaptically connected spiking neurons with realistic morphologies can be combined with the physical principles governing generation of the extracelluar potentials 74,75 for prediction of macroscopic electro- or magnetoencephalography signals resulting from complex circuit phenomena. These models may help bridge the cellular level biophysics to well-established neuronal deficits measured noninvasively in SCZ patients such as the lack of prepulse inhibition.…”

Section: Comprehensive Model Of Scz Pathophysiologymentioning

confidence: 99%

Genetic evidence for role of integration of fast and slow neurotransmission in schizophrenia

et al. 2017

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The most recent genome-wide association studies (GWAS) of schizophrenia (SCZ) identified hundreds of risk variants potentially implicated in the disease. Further, novel statistical methodology designed for polygenic architecture revealed more potential risk variants. This can provide a link between individual genetic factors and the mechanistic underpinnings of SCZ. Intriguingly, a large number of genes coding for ionotropic and metabotropic receptors for various neurotransmitters—glutamate, γ-aminobutyric acid (GABA), dopamine, serotonin, acetylcholine and opioids—and numerous ion channels were associated with SCZ. Here, we review these findings from the standpoint of classical neurobiological knowledge of neuronal synaptic transmission and regulation of electrical excitability. We show that a substantial proportion of the identified genes are involved in intracellular cascades known to integrate ‘slow’ (G-protein-coupled receptors) and ‘fast’ (ionotropic receptors) neurotransmission converging on the protein DARPP-32. Inspection of the Human Brain Transcriptome Project database confirms that that these genes are indeed expressed in the brain, with the expression profile following specific developmental trajectories, underscoring their relevance to brain organization and function. These findings extend the existing pathophysiology hypothesis by suggesting a unifying role of dysregulation in neuronal excitability and synaptic integration in SCZ. This emergent model supports the concept of SCZ as an ‘associative’ disorder—a breakdown in the communication across different slow and fast neurotransmitter systems through intracellular signaling pathways—and may unify a number of currently competing hypotheses of SCZ pathophysiology.

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“…R. Soc. B 371: 20150356 of LFP [155,156] for prediction of LFP/CSD/dipole signals resulting from complex circuit phenomena. These models also allow testing for potential non-additive effects resulting from active conductances (e.g.…”

Section: Bridging Across Spatial Scales: From Singlevessel Dilation Tmentioning

confidence: 99%

The roadmap for estimation of cell-type-specific neuronal activity from non-invasive measurements

Uhlířová

Kılıç

Tian

et al. 2016

Phil. Trans. R. Soc. B

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The computational properties of the human brain arise from an intricate interplay between billions of neurons connected in complex networks. However, our ability to study these networks in healthy human brain is limited by the necessity to use non-invasive technologies. This is in contrast to animal models where a rich, detailed view of cellular-level brain function with cell-type-specific molecular identity has become available due to recent advances in microscopic optical imaging and genetics. Thus, a central challenge facing neuroscience today is leveraging these mechanistic insights from animal studies to accurately draw physiological inferences from non-invasive signals in humans. On the essential path towards this goal is the development of a detailed ‘bottom-up’ forward model bridging neuronal activity at the level of cell-type-specific populations to non-invasive imaging signals. The general idea is that specific neuronal cell types have identifiable signatures in the way they drive changes in cerebral blood flow, cerebral metabolic rate of O 2 (measurable with quantitative functional Magnetic Resonance Imaging), and electrical currents/potentials (measurable with magneto/electroencephalography). This forward model would then provide the ‘ground truth’ for the development of new tools for tackling the inverse problem—estimation of neuronal activity from multimodal non-invasive imaging data. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’.

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Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks

Cited by 89 publications

References 175 publications

Neurophysiological dynamics of phrase-structure building during sentence processing

Neurophysiological dynamics of phrase-structure building during sentence processing

Genetic evidence for role of integration of fast and slow neurotransmission in schizophrenia

The roadmap for estimation of cell-type-specific neuronal activity from non-invasive measurements

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