Hierarchically nested networks optimize the analysis of audiovisual speech

Chalas, Nikos; Omigie, Diana; Poeppel, David; Wassenhove, Virginie van

doi:10.1016/j.isci.2023.106257

Cited by 7 publications

(6 citation statements)

References 86 publications

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“…DME was applied to pairwise functional connectivity measured as orthogonalized power envelope correlations [68] computed between recording sites in each participant. We focus on gamma band power envelope correlations because of its established role in feedforward information exchange in the auditory system [16][17][18][19] and use gamma band as a reference in presentation of data from other bands. The functional connectivity matrix was normalized and thresholded to yield a diffusion matrix P symm with an apparent community structure along the horizontal and vertical dimensions (Fig 2B).…”

Section: Dme Applied To Ieeg Datamentioning

confidence: 99%

“…First, canonical RS networks originally identified using RS BOLD fMRI data vary across band in the strength of within-network connectivity and in the relationship between electrophysiological-and fMRI-derived connectivity networks [10,82]. Second, detailed analyses of the relationship between anatomical projection patterns and functional or effective connectivity indicate that especially in auditory and visual cortical hierarchies, feedforward information streams rely on connectivity primarily in gamma and high-gamma bands, while lower frequency bands (alpha, beta) underlie feedback connectivity [11][12][13][14][15][16][17][18][19]. Based on these previous reports, we suggest that the gamma band organization that is the focus of the current report reflects feedforward connectivity.…”

Section: Frequency Band-specific Properties Of Cortical Networkmentioning

confidence: 99%

“…Compared to fMRI, intracranial electroencephalography (iEEG) offers superior spatiotemporal resolution, allowing for analyses that accommodate frequency-dependent features of information exchange in these networks [10,11]. For example, cortico-cortical feedforward versus feedback information exchange occurs via bandspecific communication channels (gamma band and beta/alpha bands, respectively) in both the visual [11][12][13][14][15] and auditory [16][17][18][19] systems. There are also important regions involved in speech and language processing for which iEEG can provide superior spatial resolution and signal characteristics compared to fMRI, including in the anterior temporal lobe [20,21] and the upper versus lower banks of the superior temporal sulcus (STS) [22,23].…”

Section: Introductionmentioning

confidence: 99%

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Functional geometry of auditory cortical resting state networks derived from intracranial electrophysiology

Banks,

Krause,

Berger

et al. 2023

PLoS Biol

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Understanding central auditory processing critically depends on defining underlying auditory cortical networks and their relationship to the rest of the brain. We addressed these questions using resting state functional connectivity derived from human intracranial electroencephalography. Mapping recording sites into a low-dimensional space where proximity represents functional similarity revealed a hierarchical organization. At a fine scale, a group of auditory cortical regions excluded several higher-order auditory areas and segregated maximally from the prefrontal cortex. On mesoscale, the proximity of limbic structures to the auditory cortex suggested a limbic stream that parallels the classically described ventral and dorsal auditory processing streams. Identities of global hubs in anterior temporal and cingulate cortex depended on frequency band, consistent with diverse roles in semantic and cognitive processing. On a macroscale, observed hemispheric asymmetries were not specific for speech and language networks. This approach can be applied to multivariate brain data with respect to development, behavior, and disorders.

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Section: Dme Applied To Ieeg Datamentioning

confidence: 99%

Section: Frequency Band-specific Properties Of Cortical Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Functional geometry of auditory cortical resting state networks derived from intracranial electrophysiology

Banks,

Krause,

Berger

et al. 2023

PLoS Biol

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“…One that arises not purely from experience from rhythmic sequences, but which is born out of biology: an evolutionary prior that relevant sequences often maintain regular temporal statistics. The notion of hard-coded expectations in time has recently been proposed to explain neural responses to natural delays in audiovisual speech [41]. Here we apply the notion to the rhythmic prediction of sequences themselves.…”

Section: Bayesian Modelingmentioning

confidence: 99%

Adaptive oscillators support Bayesian prediction in temporal processing

Doelling,

Arnal,

Assaneo

2023

PLoS Comput Biol

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Humans excel at predictively synchronizing their behavior with external rhythms, as in dance or music performance. The neural processes underlying rhythmic inferences are debated: whether predictive perception relies on high-level generative models or whether it can readily be implemented locally by hard-coded intrinsic oscillators synchronizing to rhythmic input remains unclear and different underlying computational mechanisms have been proposed. Here we explore human perception for tone sequences with some temporal regularity at varying rates, but with considerable variability. Next, using a dynamical systems perspective, we successfully model the participants behavior using an adaptive frequency oscillator which adjusts its spontaneous frequency based on the rate of stimuli. This model better reflects human behavior than a canonical nonlinear oscillator and a predictive ramping model–both widely used for temporal estimation and prediction–and demonstrate that the classical distinction between absolute and relative computational mechanisms can be unified under this framework. In addition, we show that neural oscillators may constitute hard-coded physiological priors–in a Bayesian sense–that reduce temporal uncertainty and facilitate the predictive processing of noisy rhythms. Together, the results show that adaptive oscillators provide an elegant and biologically plausible means to subserve rhythmic inference, reconciling previously incompatible frameworks for temporal inferential processes.

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“…When this is the case, understanding the structure and dynamics of interactions requires to identify clear boundaries that separate an ecosystem from its surroundings. While this idea and the resulting methods [9-12] have found promising initial applications in ecological [13][14][15][16], neural [17,18] and social networks [19,20], they have not yet been applied to economic systems where actors produce and export products. As for these systems, most studies assume that the ecosystem where a country operates is the entire world [21][22][23]: in principle, each country competes with all the others, and all products are considered.…”

mentioning

confidence: 99%

The different structure of economic ecosystems at the scales of companies and countries

et al. 2023

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A key element to understand complex systems is the relationship between the spatial scale of investigation and the structure of the interrelation among its elements. When it comes to economic systems, it is now well-known that the country-product bipartite network exhibits a nested structure, which is the foundation of diﬀerent algorithms that have been used to scientiﬁcally investigate countries’ development and forecast national economic growth. Changing the subject from countries to companies, a signiﬁcantly diﬀerent scenario emerges. Through the analysis of a unique dataset of Italian ﬁrms’ exports and a worldwide dataset comprising countries’ exports, here we ﬁnd that, while a globally nested structure is observed at the country level, a local, in-block nested structure emerges at the level of ﬁrms. This in-block nestedness is statistically signiﬁcant with respect to suitable null models and the algorithmic partitions of products into blocks correspond well with the UN-COMTRADE product classiﬁcation. These ﬁndings lay a solid foundation for developing a scientiﬁc approach based on the physics of complex systems to the analysis of companies, which has been lacking until now.

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Hierarchically nested networks optimize the analysis of audiovisual speech

Cited by 7 publications

References 86 publications

Functional geometry of auditory cortical resting state networks derived from intracranial electrophysiology

Functional geometry of auditory cortical resting state networks derived from intracranial electrophysiology

Adaptive oscillators support Bayesian prediction in temporal processing

The different structure of economic ecosystems at the scales of companies and countries

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