Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity

Zeraati, R; Shi, Yan-Liang; Steinmetz, Nicholas A.; Gieselmann, Marc Alwin; Thiele, Alexander; Moore, Tirin; Levina, Anna; Engel, Tatiana A.

doi:10.1038/s41467-023-37613-7

Cited by 32 publications

(8 citation statements)

References 81 publications

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“…(We note that the autocorrelation functions reported in Fig. 4 can also depend on whether connectivity is local or global (82).) These theoretical considerations suggest that we observed a low-dimensional critical subspace in our experiments because we measured neurons from a local patch of cortex (approximately one cortical column) using a single shank Neuropixels probe.…”

Section: Discussionmentioning

confidence: 81%

Low-dimensional criticality embedded in high-dimensional awake brain dynamics

Fontenele,

Sooter,

Norman

et al. 2024

Sci. Adv.

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Whether cortical neurons operate in a strongly or weakly correlated dynamical regime determines fundamental information processing capabilities and has fueled decades of debate. We offer a resolution of this debate; we show that two important dynamical regimes, typically considered incompatible, can coexist in the same local cortical circuit by separating them into two different subspaces. In awake mouse motor cortex, we find a low-dimensional subspace with large fluctuations consistent with criticality—a dynamical regime with moderate correlations and multi-scale information capacity and transmission. Orthogonal to this critical subspace, we find a high-dimensional subspace containing a desynchronized dynamical regime, which may optimize input discrimination. The critical subspace is apparent only at long timescales, which explains discrepancies among some previous studies. Using a computational model, we show that the emergence of a low-dimensional critical subspace at large timescales agrees with established theory of critical dynamics. Our results suggest that the cortex leverages its high dimensionality to multiplex dynamical regimes across different subspaces.

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Section: Discussionmentioning

confidence: 81%

Low-dimensional criticality embedded in high-dimensional awake brain dynamics

Fontenele,

Sooter,

Norman

et al. 2024

Sci. Adv.

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“…One context where biophysically interpretable multivariate methods such as GPLA hold potential is the analysis of cortical spatio-temporal dynamics. Horizontal connectivity is believed to endow many regions with distributed information processing capabilities [ 30 , 44 , 93 ]. However, how underlying connectivity properties relate to experimentally observed multi-channel recordings remains largely elusive.…”

Section: Resultsmentioning

confidence: 99%

Uncovering the organization of neural circuits with Generalized Phase Locking Analysis

et al. 2023

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Despite the considerable progress of in vivo neural recording techniques, inferring the biophysical mechanisms underlying large scale coordination of brain activity from neural data remains challenging. One obstacle is the difficulty to link high dimensional functional connectivity measures to mechanistic models of network activity. We address this issue by investigating spike-field coupling (SFC) measurements, which quantify the synchronization between, on the one hand, the action potentials produced by neurons, and on the other hand mesoscopic “field” signals, reflecting subthreshold activities at possibly multiple recording sites. As the number of recording sites gets large, the amount of pairwise SFC measurements becomes overwhelmingly challenging to interpret. We develop Generalized Phase Locking Analysis (GPLA) as an interpretable dimensionality reduction of this multivariate SFC. GPLA describes the dominant coupling between field activity and neural ensembles across space and frequencies. We show that GPLA features are biophysically interpretable when used in conjunction with appropriate network models, such that we can identify the influence of underlying circuit properties on these features. We demonstrate the statistical benefits and interpretability of this approach in various computational models and Utah array recordings. The results suggest that GPLA, used jointly with biophysical modeling, can help uncover the contribution of recurrent microcircuits to the spatio-temporal dynamics observed in multi-channel experimental recordings.

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“…To answer this question, we need to investigate the dynamics of neural timescales in the context of behavior 8 , 16 – 18 . There is currently scarce evidence about the behavioral dependence of neural timescales, their hierarchical organization, and general function in the context of behavior, and especially how these relate to one another.…”

Section: Introductionmentioning

confidence: 99%

Neural timescales reflect behavioral demands in freely moving rhesus macaques

Manea,

Maisson,

Voloh

et al. 2024

Nat Commun

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Previous work demonstrated a highly reproducible cortical hierarchy of neural timescales at rest, with sensory areas displaying fast, and higher-order association areas displaying slower timescales. The question arises how such stable hierarchies give rise to adaptive behavior that requires flexible adjustment of temporal coding and integration demands. Potentially, this lack of variability in the hierarchical organization of neural timescales could reflect the structure of the laboratory contexts. We posit that unconstrained paradigms are ideal to test whether the dynamics of neural timescales reflect behavioral demands. Here we measured timescales of local field potential activity while male rhesus macaques foraged in an open space. We found a hierarchy of neural timescales that differs from previous work. Importantly, although the magnitude of neural timescales expanded with task engagement, the brain areas’ relative position in the hierarchy was stable. Next, we demonstrated that the change in neural timescales is dynamic and contains functionally-relevant information, differentiating between similar events in terms of motor demands and associated reward. Finally, we demonstrated that brain areas are differentially affected by these behavioral demands. These results demonstrate that while the space of neural timescales is anatomically constrained, the observed hierarchical organization and magnitude is dependent on behavioral demands.

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Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity

Cited by 32 publications

References 81 publications

Low-dimensional criticality embedded in high-dimensional awake brain dynamics

Low-dimensional criticality embedded in high-dimensional awake brain dynamics

Uncovering the organization of neural circuits with Generalized Phase Locking Analysis

Neural timescales reflect behavioral demands in freely moving rhesus macaques

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