Multimodal subspace identification for modeling discrete-continuous spiking and field potential population activity DOI Creative Commons
Parima Ahmadipour, Omid G. Sani, Bijan Pesaran

et al.

Journal of Neural Engineering, Journal Year: 2023, Volume and Issue: 21(2), P. 026001 - 026001

Published: Nov. 29, 2023

Abstract Objective. Learning dynamical latent state models for multimodal spiking and field potential activity can reveal their collective low-dimensional dynamics enable better decoding of behavior through fusion. Toward this goal, developing unsupervised learning methods that are computationally efficient is important, especially real-time applications such as brain–machine interfaces (BMIs). However, remains elusive spike-field data due to heterogeneous discrete-continuous distributions different timescales. Approach. Here, we develop a multiscale subspace identification (multiscale SID) algorithm enables modeling dimensionality reduction data. We describe the combined Poisson Gaussian observations, which derive new analytical SID method. Importantly, also introduce novel constrained optimization approach learn valid noise statistics, critical statistical inference state, neural activity, behavior. validate method using numerical simulations with local population recorded during naturalistic reach grasp Main results. find accurately learned signals extracted from these signals. Further, it fused information, thus identifying modes predicting compared single modality. Finally, existing expectation-maximization Poisson–Gaussian had much lower training time while being in having or similar accuracy Significance. Overall, an accurate particularly beneficial when interest, online adaptive BMIs track non-stationary reducing offline neuroscience investigations.

Language: Английский

The population doctrine in cognitive neuroscience DOI Creative Commons
R. Becket Ebitz, Benjamin Y. Hayden

Neuron, Journal Year: 2021, Volume and Issue: 109(19), P. 3055 - 3068

Published: Aug. 19, 2021

Language: Английский

Citations

179
Preserved neural dynamics across animals performing similar behaviour DOI Creative Commons
Mostafa Safaie, Joanna Chang, Junchol Park

et al.

Nature, Journal Year: 2023, Volume and Issue: 623(7988), P. 765 - 771

Published: Nov. 8, 2023

Abstract Animals of the same species exhibit similar behaviours that are advantageously adapted to their body and environment. These shaped at level by selection pressures over evolutionary timescales. Yet, it remains unclear how these common behavioural adaptations emerge from idiosyncratic neural circuitry each individual. The overall organization circuits is preserved across individuals 1 because evolutionarily specified developmental programme 2–4 . Such circuit may constrain activity 5–8 , leading low-dimensional latent dynamics population 9–11 Accordingly, here we suggested shared circuit-level constraints within a would lead suitably individuals. We analysed recordings populations monkey mouse motor cortex demonstrate in surprisingly when they perform behaviour. Neural were also animals consciously planned future movements without overt behaviour 12 enabled decoding ongoing movement different Furthermore, found extend beyond cortical regions dorsal striatum, an older structure 13,14 Finally, used network models similarity necessary but not sufficient for this preservation. posit emergent result on brain development thus reflect fundamental properties basis

Language: Английский

Citations

59
Local field potentials reflect cortical population dynamics in a region-specific and frequency-dependent manner DOI Creative Commons
Cecilia Gallego-Carracedo, Matthew G. Perich, Raeed H. Chowdhury

et al.

eLife, Journal Year: 2022, Volume and Issue: 11

Published: Aug. 15, 2022

The spiking activity of populations cortical neurons is well described by the dynamics a small number population-wide covariance patterns, whose activation we refer to as ‘latent dynamics’. These latent are largely driven same correlated synaptic currents across circuit that determine generation local field potentials (LFPs). Yet, relationship between and LFPs remains unexplored. Here, characterised this for three different regions primate sensorimotor cortex during reaching. correlation was frequency-dependent varied regions. However, any given region, remained stable throughout behaviour: in each primary motor premotor cortices, LFP-latent profile remarkably similar movement planning execution. robust associations neural population help bridge wealth studies reporting correlates behaviour using either type recordings.

Language: Английский

Citations

43
Spatial transcriptomics reveals the distinct organization of mouse prefrontal cortex and neuronal subtypes regulating chronic pain DOI Creative Commons

Aritra Bhattacherjee,

Chao Zhang, Brianna R. Watson

et al.

Nature Neuroscience, Journal Year: 2023, Volume and Issue: 26(11), P. 1880 - 1893

Published: Oct. 16, 2023

Abstract The prefrontal cortex (PFC) is a complex brain region that regulates diverse functions ranging from cognition, emotion and executive action to even pain processing. To decode the cellular circuit organization of such functions, we employed spatially resolved single-cell transcriptome profiling adult mouse PFC. Results revealed PFC has distinct cell-type composition gene-expression patterns relative neighboring cortical areas—with neuronal excitability-regulating genes differently expressed. These molecular features are further segregated within subregions, alluding subregion-specificity several functions. projects major subcortical targets through combinations subtypes, which emerge in target-intrinsic fashion. Finally, based on these features, identified cell types circuits underlying chronic pain, an escalating healthcare challenge with limited understanding. Collectively, this comprehensive map will facilitate decoding discrete molecular, mechanisms specific health disease.

Language: Английский

Citations

30
Nonlinear manifolds underlie neural population activity during behaviour DOI Creative Commons
Cátia Fortunato,

Jorge Bennasar-Vázquez,

Junchol Park

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: July 19, 2023

There is rich variety in the activity of single neurons recorded during behaviour. Yet, these diverse neuron responses can be well described by relatively few patterns neural co-modulation. The study such low-dimensional structure population has provided important insights into how brain generates Virtually all studies have used linear dimensionality reduction techniques to estimate population-wide co-modulation patterns, constraining them a flat “neural manifold”. Here, we hypothesised that since nonlinear and make thousands distributed recurrent connections likely amplify nonlinearities, manifolds should intrinsically nonlinear. Combining recordings from monkey, mouse, human motor cortex, mouse striatum, show that: 1) are nonlinear; 2) their nonlinearity becomes more evident complex tasks require varied patterns; 3) manifold varies across architecturally distinct regions. Simulations using network models confirmed proposed relationship between circuit connectivity nonlinearity, including differences Thus, underlying generation behaviour inherently nonlinear, properly accounting for nonlinearities will critical as neuroscientists move towards studying numerous regions involved increasingly naturalistic behaviours.

Language: Английский

Citations

28
Subspace partitioning in the human prefrontal cortex resolves cognitive interference DOI Creative Commons
Jan Weber, Gabriela Yukari Iwama, Anne‐Kristin Solbakk

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2023, Volume and Issue: 120(28)

Published: July 3, 2023

The human prefrontal cortex (PFC) constitutes the structural basis underlying flexible cognitive control, where mixed-selective neural populations encode multiple task features to guide subsequent behavior. mechanisms by which brain simultaneously encodes task–relevant variables while minimizing interference from task-irrelevant remain unknown. Leveraging intracranial recordings PFC, we first demonstrate that competition between coexisting representations of past and present incurs a behavioral switch cost. Our results reveal this states in PFC is resolved through coding partitioning into distinct low-dimensional states; thereby strongly attenuating costs. In sum, these findings uncover fundamental mechanism central building block control.

Language: Английский

Citations

24
Theory of morphodynamic information processing: Linking sensing to behaviour DOI Creative Commons
Mikko Juusola, Jouni Takalo, Joni Kemppainen

et al.

Vision Research, Journal Year: 2025, Volume and Issue: 227, P. 108537 - 108537

Published: Jan. 4, 2025

The traditional understanding of brain function has predominantly focused on chemical and electrical processes.However, new research in fruit fly (Drosophila) binocular vision reveals ultrafast photomechanical photoreceptor movements significantly enhance information processing, thereby impacting a fly's perception its environment behaviour.The coding advantages resulting from these mechanical processes suggest that similar physical motion-based strategies may affect neural communication ubiquitously.The theory morphodynamics proposes rapid biomechanical microstructural changes at the level neurons synapses speed efficiency sensory intrinsic thoughts, actions by regulating phasic manner.We propose morphodynamic processing evolved to drive predictive coding, synchronising cognitive across networks match behavioural demands hand effectively.

Language: Английский

Citations

1
De novo motor learning creates structure in neural activity that shapes adaptation DOI Creative Commons
Joanna Chang, Matthew G. Perich, Lee E. Miller

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: May 14, 2024

Abstract Animals can quickly adapt learned movements to external perturbations, and their existing motor repertoire likely influences ease of adaptation. Long-term learning causes lasting changes in neural connectivity, which shapes the activity patterns that be produced during Here, we examined how a population’s patterns, acquired through de novo learning, affect subsequent adaptation by modeling cortical population dynamics with recurrent networks. We trained networks on different repertoires comprising varying numbers movements, they following various experiences. Networks multiple had more constrained robust dynamics, were associated defined ‘structure’—organization available patterns. This structure facilitated adaptation, but only when imposed perturbation congruent organization inputs learning. These results highlight trade-offs skill acquisition demonstrate experiences shape geometrical properties

Language: Английский

Citations

7
Generating realistic neurophysiological time series with denoising diffusion probabilistic models DOI Creative Commons
Julius Vetter, Jakob H. Macke, Richard Gao

et al.

Patterns, Journal Year: 2024, Volume and Issue: 5(9), P. 101047 - 101047

Published: Aug. 29, 2024

Language: Английский

Citations

6
Neuronal travelling waves explain rotational dynamics in experimental datasets and modelling DOI Creative Commons

Ekaterina Kuzmina,

Dmitrii Kriukov, Mikhail Lebedev

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Feb. 12, 2024

Spatiotemporal properties of neuronal population activity in cortical motor areas have been subjects experimental and theoretical investigations, generating numerous interpretations regarding mechanisms for preparing executing limb movements. Two competing models, representational dynamical, strive to explain the relationship between movement parameters activity. A dynamical model uses jPCA method that holistically characterizes oscillatory neuron populations by maximizing data rotational dynamics. Different dynamics revealed approach proposed. Yet, nature such remains poorly understood. We comprehensively analyzed several neuronal-population datasets found consistently accounted a traveling wave pattern. For quantifying rotation strength, we developed complex-valued measure, gyration number. Additionally, identified influencing extent data. Our findings suggest waves are typically same phenomena, so reevaluation previous where they were considered separate entities is needed.

Language: Английский

Citations

4