Exploring the role of dimensionality transformation in episodic memory

Trends in Cognitive Sciences, Год журнала: 2025, Номер unknown

Опубликована: Фев. 1, 2025

Episodic memory must accomplish two adversarial goals: encoding and storing a multitude of experiences without exceeding the finite neuronal structure brain, recalling memories in vivid detail. Dimensionality reduction expansion ('dimensionality transformation') enable brain to meet these demands. Reduction compresses sensory input into simplified, storable codes, while reconstructs details. Although processes are essential memory, their neural mechanisms for episodic remain unclear. Drawing on recent insights from cognitive psychology, systems neuroscience, neuroanatomy, we propose accounts how dimensionality transformation occurs brain: structurally (via corticohippocampal pathways) functionally (through oscillations). By examining cross-species evidence, highlight that may support identify crucial questions future research.

Язык: Английский

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Decoding the brain: From neural representations to mechanistic models

Cell, Год журнала: 2024, Номер 187(21), С. 5814 - 5832

Опубликована: Окт. 1, 2024

Язык: Английский

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Aging disrupts the link between network centrality and functional properties of prefrontal neurons during memory-guided behavior

Communications Biology, Год журнала: 2025, Номер 8(1)

Опубликована: Янв. 16, 2025

The prefrontal cortex (PFC) is vital for higher cognitive functions and displays neuronal heterogeneity, with activity varying significantly across individual neurons. Using calcium imaging in the medial PFC (mPFC) of mice, we investigate whether differences degree centrality-a measure connectivity strength within local circuits-could explain this diversity its functional implications. In young adults, neurons high centrality, inferred from resting-state activity, exhibit reliable stable action-plan selectivity during memory-guided tasks, suggesting that closely linked to heterogeneity. This relationship, however, deteriorates middle-aged older mice. A computational model simulating age-related declines synaptic plasticity reproduces these results. centrality also predicts cross-modal selectivity, but predictive power diminishes age. Furthermore, are spatially clustered, a pattern fades aging. These findings reveal significant aging impact on network properties parallel spatial organization mPFC.

Язык: Английский

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Multiscale organization of neuronal activity unifies scale-dependent theories of brain function

Cell, Год журнала: 2024, Номер unknown

Опубликована: Окт. 1, 2024

Язык: Английский

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Unifying community whole-brain imaging datasets enables robust neuron identification and reveals determinants of neuron position in C. elegans

Cell Reports Methods, Год журнала: 2025, Номер unknown, С. 100964 - 100964

Опубликована: Янв. 1, 2025

Язык: Английский

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The cortical critical power law balances energy and information in an optimal fashion

Proceedings of the National Academy of Sciences, Год журнала: 2025, Номер 122(21)

Опубликована: Май 23, 2025

A recent study has suggested that the stimulus responses of cortical neural populations follow a critical power law. More precisely, spectrum covariance matrix follows law with an exponent indicating manifold lies on edge differentiability. This criticality is hypothesized to balance expressivity and robustness in encoding, as population nondifferential fractal are thought be overly sensitive perturbations. However, contrary this hypothesis, we prove coding far more robust than previously assumed. We develop theoretical framework provides analytical expression for Fisher information under small noise assumption. Our results reveal that, due its intrinsic high dimensionality, maintains reliability even nondifferentiable manifold, despite sensitivity Furthermore, theory reveals trade-off between energetic cost makes power-law optimal encoding sensory wide range conditions. In derivation, highlight essential role correlation, known differential coding. By uncovering nontrivial nature high-dimensional coding, work deepens our understanding laws both biological artificial computation.

Язык: Английский

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Population coding under the scale-invariance of high-dimensional noise

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Авг. 26, 2024

Abstract High-dimensional neural activities exhibiting scale-invariant, power-law noise spectra are ubiquitously observed across various brain regions and species. However, their impact on information coding remains unclear. We provide the scaling conditions for covariance that clarify boundedness of establish a quantitative relation between capacity population size, based properties scale-invariant in stimulus-evoked mouse V1 neurons. Our analysis reveals sublinearly small components align sufficiently with signal direction, enabling neurons to convey stimulus unboundedly as size increases. These findings demonstrate quasi-universal lays foundation understanding codes, highlighting critical need consider full spectrum high-dimensional noise.

Язык: Английский

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Structure of activity in multiregion recurrent neural networks

Proceedings of the National Academy of Sciences, Год журнала: 2025, Номер 122(10)

Опубликована: Март 7, 2025

Neural circuits comprise multiple interconnected regions, each with complex dynamics. The interplay between local and global activity is thought to underlie computational flexibility, yet the structure of multiregion neural its origins in synaptic connectivity remain poorly understood. We investigate recurrent networks containing neurons random structured connections. Inspired by experimental evidence communication subspaces, we use low-rank regions enable selective routing. These exhibit high-dimensional fluctuations within low-dimensional signal transmission them. Using dynamical mean-field theory, cross-region currents as order parameters, show that act both generators transmitters activity-roles are often tension. Taming within-region can be crucial for effective Unlike previous models suppressed control flow, our model achieves routing exciting different patterns through nonlinear Our analysis this disordered system offers insights into data trained networks.

Язык: Английский

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Formation of brain-wide neural geometry during visual item recognition in monkeys

iScience, Год журнала: 2025, Номер 28(3), С. 111936 - 111936

Опубликована: Янв. 31, 2025

Neural dynamics are thought to reflect computations that relay and transform information in the brain. Previous studies have identified neural population many individual brain regions as a trajectory geometry, preserving common computational motif. However, whether these populations share particular geometric patterns across brain-wide remains unclear. Here, by mapping widely temporal/frontal/limbic cortical subcortical structures of monkeys, we show 10 populations, including 2,500 neurons, propagate visual item stochastic manner. We found inputs predominantly evoked rotational higher-order area, TE, its downstream striatum tail, while curvy/straight appeared frequently orbitofrontal/hippocampal network. These changes were not deterministic but rather according their respective emergence rates. Our meta-analysis results indicate propagates heterogeneous mixture signals

Язык: Английский

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A Sensitive Soma-localized Red Fluorescent Calcium Indicator for Multi-Modality Imaging of Neuronal Populations In Vivo

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Фев. 2, 2025

Abstract Recent advancements in genetically encoded calcium indicators, particularly those based on green fluorescent proteins, have optimized their performance for monitoring neuronal activities a variety of model organisms. However, progress developing red-shifted GECIs, despite advantages over has been slower, resulting fewer options end-users. In this study, we explored topological inversion and soma-targeting strategies, which are complementary to conventional mutagenesis, re-engineer red indicator, FRCaMP, enhanced vivo performance. The sensors, FRCaMPi soma-targeted (SomaFRCaMPi), exhibit up 2-fold higher dynamic range peak ΔF/F 0 per single AP compared widely used jRGECO1a neurons culture . Compared FRCaMPi, SomaFRCaMPi reduces erroneous correlation activity the brains mice zebrafish by two- four-fold due diminished neuropil contamination without compromising signal-to-noise ratio. Under wide-field imaging primary somatosensory visual cortex with high labeling density (80-90%), exhibits 40% SNR decreased artifactual across neurons. Altogether, improves accuracy scale at single-neuron resolution densely labeled brain tissues 2-3-fold automated segmentation, 50% fraction responsive cells, jRGECO1a. Our findings highlight potential SomaFRCaMPi, comparable most sensitive GCaMP, precise spatial recording populations using popular modalities organisms such as mice.

Язык: Английский

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