Local field potentials reflect cortical population dynamics in a region-specific and frequency-dependent manner

Gallego-Carracedo, Cecilia; Mg, Perich; Chowdhury, Raeed H.; Le, Miller; Gallego, Juan Álvaro

doi:10.1101/2021.05.31.446454

Cited by 7 publications

(10 citation statements)

References 104 publications

(239 reference statements)

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“…In particular, even frequencies as low as 20 Hz, which correspond to the beta band, were found to be almost always correlated to kHz range frequencies. This supports findings in many other works that show that the power in various LFP bands is associated with spike activity 14 – 16 , 18 – 24 , 29 , 79 . In fact, the continuous range of the significant power correlations suggests that spikes have power signatures in a continuous range of frequencies from kHz down to 20 Hz.…”

Section: Resultssupporting

confidence: 92%

The significance of neural inter-frequency power correlations

Savolainen

2021

Sci Rep

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It is of great interest in neuroscience to determine what frequency bands in the brain have covarying power. This would help us robustly identify the frequency signatures of neural processes. However to date, to the best of the author’s knowledge, a comprehensive statistical approach to this question that accounts for intra-frequency autocorrelation, frequency-domain oversampling, and multiple testing under dependency has not been undertaken. As such, this work presents a novel statistical significance test for correlated power across frequency bands for a broad class of non-stationary time series. It is validated on synthetic data. It is then used to test all of the inter-frequency power correlations between 0.2 and 8500 Hz in continuous intracortical extracellular neural recordings in Macaque M1, using a very large, publicly available dataset. The recordings were Current Source Density referenced and were recorded with a Utah array. The results support previous results in the literature that show that neural processes in M1 have power signatures across a very broad range of frequency bands. In particular, the power in LFP frequency bands as low as 20 Hz was found to almost always be statistically significantly correlated to the power in kHz frequency ranges. It is proposed that this test can also be used to discover the superimposed frequency domain signatures of all the neural processes in a neural signal, allowing us to identify every interesting neural frequency band.

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Section: Resultssupporting

confidence: 92%

The significance of neural inter-frequency power correlations

Savolainen

2021

Sci Rep

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“…We then ‘aligned’ the latent dynamics of each pair of experimental sessions from two different animals using Canonical Correlation Analysis (CCA 22 ), a method that finds linear transformations that maximise the correlations between two sets of signals (similar to Ref. 23 – 25 ; see Figure S1D).…”

Section: Resultsmentioning

confidence: 99%

Preserved neural population dynamics across animals performing similar behaviour

Safaie

Chang

Park

et al. 2022

Preprint

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Animals of the same species often exhibit similar behaviours that are advantageously adapted to their body and their environment. These behaviours are shaped by selection pressures over evolutionary timescales at the species level, yet each individual produces these behaviours using a different, uniquely constructed brain. It remains unclear how these common behavioural adaptations emerge from the idiosyncratic neural circuitry of a given individual. Here, we hypothesised that the adaptive behaviour of a species requires specific neural population 'latent dynamics'. These latent dynamics should thus be preserved and identifiable across individuals within a species, regardless of the idiosyncratic aspects of each individual's brain. Using recordings of neural populations from monkey and mouse motor cortex, we show that individuals from the same species share surprisingly similar neural dynamics when they perform the same behaviour. The similarity in neural population dynamics extends beyond cortical regions to the dorsal striatum, an evolutionarily older structure, and also holds when animals consciously plan future movements without overt behaviour. These preserved dynamics are behaviourally-relevant, allowing decoding of intended and ongoing movements across individuals. We posit that these emergent neural population dynamics result from evolutionarily-imposed constraints on brain development, and reflect a fundamental property of the neural basis of behaviour.

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“…A testable hypothesis arising from our observations is that SW-R should trigger state transitions in both the PFC and MTL to optimize inter-areal information reactivation and transfer. Here, we estimated high-frequency activity (120-200 Hz; HFA) as a surrogate marker of multi-unit population activity (Gallego-Carracedo et al, 2022; Leszczynski et al, 2020; Ray & Maunsell, 2011; Rich & Wallis, 2017). Note that we excluded the human ripple-band (80-120 Hz) from our HFA definition to avoid confounded estimates ( SI Appendix, Fig.…”

Section: Resultsmentioning

confidence: 99%

An evolutionary conserved division-of-labor between hippocampal and neocortical sharp-wave ripples organizes information transfer during sleep

Schalkwijk

Weber

Hahn

et al. 2022

Preprint

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The hippocampal sharp-wave ripple (SW-R) is the key substrate of the hippocampal-neocortical dialogue underlying memory formation. Recently, it became evident that SW-R are not unique to archicortex, but constitute a wide-spread neocortical phenomenon. To date, little is known about morphological and functional similarities between archi- and neocortical SW-R. Leveraging intracranial recordings from the human hippocampus and prefrontal cortex during sleep, our results reveal region-specific functional specializations, albeit a near-uniform morphology. While hippocampal SW-R trigger directional hippocampal-to-neocortical information flow, neocortical SW-R reduce information flow to minimize interference. At the population level, hippocampal SW-R confined population dynamics to a low-dimensional subspace, while neocortical SW-R diversified the population response; functionally uncoupling the hippocampal-neocortical network. Critically, our replication in rodents demonstrated the same division-of-labor between archi-and neocortical SW-R. These results uncover an evolutionary preserved mechanism where coordinated interplay between hippocampal and neocortical SW-R temporally segregates hippocampal information transfer from neocortical processing.

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Local field potentials reflect cortical population dynamics in a region-specific and frequency-dependent manner

Cited by 7 publications

References 104 publications

The significance of neural inter-frequency power correlations

The significance of neural inter-frequency power correlations

Preserved neural population dynamics across animals performing similar behaviour

An evolutionary conserved division-of-labor between hippocampal and neocortical sharp-wave ripples organizes information transfer during sleep

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