Information theoretic evidence for layer- and frequency-specific changes in cortical information processing under anesthesia

Pinzuti, Edoardo; Tüscher, Oliver; Wibral, Michael

doi:10.1371/journal.pcbi.1010380

Cited by 3 publications

(1 citation statement)

References 81 publications

(198 reference statements)

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“…Despite these difficulties, the analysis of cortico-cortical predictive coding using the proposed information-theoretic framework seems highly promising, as very explicit predictions on the type of predictive coding, the location of error-computing units in upper cortical layers, and the corresponding LFP-frequency signatures of error signal have been made [94,95]. Thus, we expect these hypotheses to be directly testable using frequency-resolved measures of information transfer [96,97].…”

Section: Considerations On Cortico-cortical Predictive Coding and On ...mentioning

confidence: 99%

Information-theoretic analyses of neural data to minimize the effect of researchers’ assumptions in predictive coding studies

Wollstadt,

Rathbun,

Usrey

et al. 2023

PLoS Comput Biol

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Studies investigating neural information processing often implicitly ask both, which processing strategy out of several alternatives is used and how this strategy is implemented in neural dynamics. A prime example are studies on predictive coding. These often ask whether confirmed predictions about inputs or predictions errors between internal predictions and inputs are passed on in a hierarchical neural system—while at the same time looking for the neural correlates of coding for errors and predictions. If we do not know exactly what a neural system predicts at any given moment, this results in a circular analysis—as has been criticized correctly. To circumvent such circular analysis, we propose to express information processing strategies (such as predictive coding) by local information-theoretic quantities, such that they can be estimated directly from neural data. We demonstrate our approach by investigating two opposing accounts of predictive coding-like processing strategies, where we quantify the building blocks of predictive coding, namely predictability of inputs and transfer of information, by local active information storage and local transfer entropy. We define testable hypotheses on the relationship of both quantities, allowing us to identify which of the assumed strategies was used. We demonstrate our approach on spiking data collected from the retinogeniculate synapse of the cat (N = 16). Applying our local information dynamics framework, we are able to show that the synapse codes for predictable rather than surprising input. To support our findings, we estimate quantities applied in the partial information decomposition framework, which allow to differentiate whether the transferred information is primarily bottom-up sensory input or information transferred conditionally on the current state of the synapse. Supporting our local information-theoretic results, we find that the synapse preferentially transfers bottom-up information.

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Section: Considerations On Cortico-cortical Predictive Coding and On ...mentioning

confidence: 99%

Information-theoretic analyses of neural data to minimize the effect of researchers’ assumptions in predictive coding studies

Wollstadt,

Rathbun,

Usrey

et al. 2023

PLoS Comput Biol

Self Cite

View full text Add to dashboard Cite

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Information theoretic evidence for layer- and frequency-specific changes in cortical information processing under anesthesia

2023

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Nature relies on highly distributed computation for the processing of information in nervous systems across the entire animal kingdom. Such distributed computation can be more easily understood if decomposed into the three elementary components of information processing, i.e. storage, transfer and modification, and rigorous information theoretic measures for these components exist. However, the distributed computation is often also linked to neural dynamics exhibiting distinct rhythms. Thus, it would be beneficial to associate the above components of information processing with distinct rhythmic processes where possible. Here we focus on the storage of information in neural dynamics and introduce a novel spectrally-resolved measure of active information storage (AIS). Drawing on intracortical recordings of neural activity in ferrets under anesthesia before and after loss of consciousness (LOC) we show that anesthesia- related modulation of AIS is highly specific to different frequency bands and that these frequency-specific effects differ across cortical layers and brain regions. We found that in the high/low gamma band the effects of anesthesia result in AIS modulation only in the supergranular layers, while in the alpha/beta band the strongest decrease in AIS can be seen at infragranular layers. Finally, we show that the increase of spectral power at multiple frequencies, in particular at alpha and delta bands in frontal areas, that is often observed during LOC (’anteriorization’) also impacts local information processing—but in a frequency specific way: Increases in isoflurane concentration induced a decrease in AIS in the alpha frequencies, while they increased AIS in the delta frequency range < 2Hz. Thus, the analysis of spectrally-resolved AIS provides valuable additional insights into changes in cortical information processing under anaesthesia.

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Information dynamics of in silico EEG Brain Waves: Insights into oscillations and functions

Menesse,

Torres

2024

PLoS Comput Biol

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The relation between electroencephalography (EEG) rhythms, brain functions, and behavioral correlates is well-established. Some physiological mechanisms underlying rhythm generation are understood, enabling the replication of brain rhythms in silico. This offers a pathway to explore connections between neural oscillations and specific neuronal circuits, potentially yielding fundamental insights into the functional properties of brain waves. Information theory frameworks, such as Integrated Information Decomposition (Φ-ID), relate dynamical regimes with informational properties, providing deeper insights into neuronal dynamic functions. Here, we investigate wave emergence in an excitatory/inhibitory (E/I) balanced network of integrate and fire neurons with short-term synaptic plasticity. This model produces a diverse range of EEG-like rhythms, from low δ waves to high-frequency oscillations. Through Φ-ID, we analyze the network’s information dynamics and its relation with different emergent rhythms, elucidating the system’s suitability for functions such as robust information transfer, storage, and parallel operation. Furthermore, our study helps to identify regimes that may resemble pathological states due to poor informational properties and high randomness. We found, e.g., that in silico β and δ waves are associated with maximum information transfer in inhibitory and excitatory neuron populations, respectively, and that the coexistence of excitatory θ, α, and β waves is associated to information storage. Additionally, we observed that high-frequency oscillations can exhibit either high or poor informational properties, potentially shedding light on ongoing discussions regarding physiological versus pathological high-frequency oscillations. In summary, our study demonstrates that dynamical regimes with similar oscillations may exhibit vastly different information dynamics. Characterizing information dynamics within these regimes serves as a potent tool for gaining insights into the functions of complex neuronal networks. Finally, our findings suggest that the use of information dynamics in both model and experimental data analysis, could help discriminate between oscillations associated with cognitive functions and those linked to neuronal disorders.

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Information theoretic evidence for layer- and frequency-specific changes in cortical information processing under anesthesia

Cited by 3 publications

References 81 publications

Information-theoretic analyses of neural data to minimize the effect of researchers’ assumptions in predictive coding studies

Information-theoretic analyses of neural data to minimize the effect of researchers’ assumptions in predictive coding studies

Information theoretic evidence for layer- and frequency-specific changes in cortical information processing under anesthesia

Information dynamics of in silico EEG Brain Waves: Insights into oscillations and functions

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