Article
Multidisciplinary Sciences
Itsuki Kanemura, Katsunori Kitano
Summary: Humans perceive the external world by integrating information from different modalities, but the mechanism behind this is still unclear. A model using two reservoir computing systems was able to detect stimulus patterns that repeatedly appear in a time series signal. The model was self-organized and could detect each fluctuation pattern. The original version of the model, which incorporated feedback from appropriately learned sensory modules, performed the best compared to alternative versions.
SCIENTIFIC REPORTS
(2023)
Article
Multidisciplinary Sciences
Richard J. Gardner, Erik Hermansen, Marius Pachitariu, Yoram Burak, Nils A. Baas, Benjamin A. Dunn, May-Britt Moser, Edvard Moser
Summary: The medial entorhinal cortex is part of a neural system that maps the position of an individual within a physical environment. Grid cells, a key component of this system, fire in a hexagonal pattern and collectively form a population code for the animal's position. The network dynamics of grid cells show on a toroidal manifold, with individual cells preferentially active at specific positions, which are maintained across environments and states.
Article
Multidisciplinary Sciences
Akihiro Shimbo, Ei-Ichi Izawa, Shigeyoshi Fujisawa
Summary: The study shows that neuronal assemblies encode elapsed time in time cells, displaying scalable features in temporal bisection tasks. Additionally, these neuronal assemblies can adjust according to different sets of time intervals, reflecting rats' time estimation, demonstrating that time cells may support the capability of flexible temporal representation for memory formation.
Article
Biology
Ching Fang, Dmitriy Aronov, L. F. Abbott, Emily L. Mackevicius
Summary: The hippocampus is believed to have predictive nature and is useful for memory-guided cognitive behaviors. Inspired by reinforcement learning literature, the concept is formalized as a predictive map called the successor representation (SR). The dynamics of a recurrent neural network naturally calculate the SR when synaptic weights match the transition probability matrix. The results suggest that SR is more accessible in neural circuits than previously thought and can support a broad range of cognitive functions.
Article
Acoustics
Shanwu Li, Yongchao Yang
Summary: This study presents a recurrent neural network (RNN) framework with an adaptive training strategy for long-time prediction of future states in nonlinear dynamical systems. By explicitly incorporating multi-step prediction and error accumulation into model training, the model robustness is improved. Experiments on Duffing oscillators demonstrate the advantages and limitations of this approach.
JOURNAL OF SOUND AND VIBRATION
(2021)
Article
Biology
Sebastian O. Andersson, Edvard Moser, May-Britt Moser
Summary: Research shows that OV cells respond to a variety of 2D surfaces using visual contrast as the most basic visual feature, allowing vector-guided navigation in environments with few free-standing landmarks.
COMMUNICATIONS BIOLOGY
(2021)
Article
Neurosciences
Shanshan Qin, Shiva Farashahi, David Lipshutz, Anirvan M. M. Sengupta, Dmitri B. B. Chklovskii, Cengiz Pehlevan
Summary: A computational model predicts coordinated drift of neural receptive fields during noisy representation learning and recapitulates experimental observations in the posterior parietal cortex and hippocampal CA1. Recent experiments have revealed that neural population codes in many brain areas continuously change even when animals have fully learned and stably perform their tasks. This representational 'drift' naturally leads to questions about its causes, dynamics and functions.
NATURE NEUROSCIENCE
(2023)
Article
Mathematics, Applied
Qinghua Zhou, Li Wan, Hongbo Fu, Qunjiao Zhang
Summary: This paper discusses the attractor problem of Hopfield neural networks with multiple time-varying delays. The existence conditions of the linear matrix inequality form of pullback attractor are derived using Lyapunov-Krasovskii functional and inequality techniques. Two examples are provided to demonstrate the effectiveness of the theoretical results and show that the conditions in linear matrix inequality form are superior to those in algebraic form.
Article
Engineering, Petroleum
Dung T. Phan, Chao Liu, Murtadha J. AlTammar, Yanhui Han, Younane N. Abousleiman
Summary: This paper presents an artificial intelligence solution for predicting time-dependent safe mud-weight windows and polar charts. The trained neural networks achieve accurate predictions with significantly faster computational speed compared to analytical solutions, making them suitable for real-time drilling operations.
Article
Mathematics, Interdisciplinary Applications
Li Wan, Qinghua Zhou
Summary: This paper investigates the pullback attractor of Cohen-Grossberg neural networks with multiple time-varying delays, deriving new sufficient criteria and demonstrating the effectiveness of the theoretical results through examples.
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
(2021)
Article
Multidisciplinary Sciences
Gily Ginosar, Ehud D. Karpas, Idan Weitzner, Nachum Ulanovsky
Summary: The perception of 3D space has been extensively studied, but there are conflicting reports on distortions. This study proposes that 3D perception consists of two processes: perception of traveled space and perception of surrounding space. By testing these two aspects on the same subjects, it was found that the perception of traveled space is experience-dependent, while the perception of surrounding space is not affected by experience. This suggests that these two aspects of 3D spatial perception emerge from distinct processes.
SCIENTIFIC REPORTS
(2023)
Article
Mathematics
Muyi Chen, Daling Wang, Shi Feng, Yifei Zhang
Summary: In this paper, the representation learning problem is studied from an out-of-distribution (OoD) perspective to identify the factors affecting representation quality. The concept of out-of-feature subspace (OoFS) noise is introduced, and its reduction is proven to be beneficial for better representation. A novel data-dependent regularizer is proposed to reduce noise in representations and achieve better performance in multiple tasks.
Review
Behavioral Sciences
Genela Morris, Dori Derdikman
Summary: Place cells and grid cells are essential for the hippocampal cognitive map. The traditional forward model suggests that grid cells are generated by a continuous attractor network, with a velocity signal moving entorhinal activity bumps during locomotion, and place cell activity being the sum of entorhinal grid cell modules. Experimental data support the first hypothesis but not the latter two. A modified model (spatial modulation continuous attractor network; SCAN) is proposed, where place cells are generated from spatially selective non-grid cells, and locomotion causes the movement of the hippocampal activity bump and the entorhinal manifolds. This inversion aligns with the shift of hippocampal function from navigation to more abstract processes.
TRENDS IN COGNITIVE SCIENCES
(2023)
Article
Multidisciplinary Sciences
Fahd Yazin, Moumita Das, Arpan Banerjee, Dipanjan Roy
Summary: This study demonstrates that prediction errors in different naturalistic contexts can lead to changes in the temporal ordering of event structures in complex episodic memories. Newer sequences with prediction errors have a lower decision threshold and faster recall speed, suggesting a distinct and adaptive role for prediction errors in learning and reorganizing episodic temporal sequences.
SCIENTIFIC REPORTS
(2021)
Article
Nanoscience & Nanotechnology
Zhaojie Xu, Fan Mo, Gucheng Yang, Penghui Fan, Yiding Wang, Botao Lu, Jingyu Xie, Yuchuan Dai, Yilin Song, Enhui He, Shihong Xu, Juntao Liu, Mixia Wang, Xinxia Cai
Summary: Grid cells in the medial entorhinal cortex play a crucial role in processing both spatial and social information. The study found that grid cells exhibit rate remapping in response to social conditions and undergo global remapping when the spatial landmarks change. Furthermore, the results suggest that grid cells respond to spatial and social information through different mechanisms.
MICROSYSTEMS & NANOENGINEERING
(2022)
Article
Physics, Multidisciplinary
Denis S. Goldobin, Matteo di Volo, Alessandro Torcini
Summary: The study addresses the entropy issue of Lorentzian distributions by introducing a pseudocumulants expansion, proposing a reduction method for heterogeneous neural networks, and obtaining a unified mean-field formulation.
PHYSICAL REVIEW LETTERS
(2021)
Review
Physiology
Rosa Cossart, Roustem Khazipov
Summary: This review focuses on the development and self-organized dynamics of hippocampal circuits, exploring their role in learning and memory. It is found that the development of hippocampal cells and circuits starts during embryonic neurogenesis, and later experiences are integrated onto this framework. The article reviews the development of hippocampal cells and circuits at anatomical and functional levels, and describes the emergence of network dynamics in the hippocampus. Finally, open questions are posed in the article.
PHYSIOLOGICAL REVIEWS
(2022)
Article
Mathematics, Applied
Matteo di Volo, Marco Segneri, Denis S. Goldobin, Antonio Politi, Alessandro Torcini
Summary: This study presents a detailed analysis of the dynamical regimes observed in a balanced network of identical quadratic integrate-and-fire neurons with sparse connectivity, identifying either asynchronous regime or periodic oscillations depending on parameter values. The comparison between numerical simulations and a mean-field model based on a self-consistent Fokker-Planck equation shows good reproduction of asynchronous dynamics in the homogeneous case. Additionally, in the limit of infinite in-degree, an exact self-consistent solution for the mean firing rate helps identify balanced regimes that can be either mean- or fluctuation-driven. In the heterogeneous situation, tuning connectivity or input DC current captures the emergence of periodic collective oscillations.
Article
Biochemical Research Methods
Walther Akemann, Sebastien Wolf, Vincent Villette, Benjamin Mathieu, Astou Tangara, Jozsua Fodor, Cathie Ventalon, Jean-Francois Leger, Stephane Dieudonne, Laurent Bourdieu
Summary: The 3D-CASH technology enables recording of neuronal activity at millisecond resolution in 3D microcircuits in vivo, offering insights into information flow in the brain. By eliminating motion artifacts, it improves data accuracy and provides a new approach for studying brain function.
Correction
Biochemical Research Methods
Walther Akemann, Sebastien Wolf, Vincent Villette, Benjamin Mathieu, Astou Tangara, Jozsua Fodor, Cathie Ventalon, Jean-Francois Leger, Stephane Dieudonne, Laurent Bourdieu
Review
Neurosciences
Rosa Cossart, Sonia Garel
Summary: The construction of cortical circuits is influenced by evolutionary mechanisms, changes in developmental programmes, and the need to adapt to the external world. Understanding the different stages of cortical construction and how cellular functions change over time is essential for studying cortical wiring in health and disease.
NATURE REVIEWS NEUROSCIENCE
(2022)
Editorial Material
Neurosciences
Joana Cabral, Viktor Jirsa, Oleksandr V. Popovych, Alessandro Torcini, Serhiy Yanchuk
FRONTIERS IN SYSTEMS NEUROSCIENCE
(2022)
Article
Biology
Robin F. Dard, Erwan Leprince, Julien Denis, Shrisha Rao Balappa, Dmitrii Suchkov, Richard Boyce, Catherine Lopez, Marie Giorgi-Kurz, Tom Szwagier, Theo Dumont, Herve Rouault, Marat Minlebaev, Agnes Baude, Rosa Cossart, Michel A. Picardo
Summary: Early electrophysiological brain oscillations in preterm babies and newborn rodents initially rely heavily on external inputs, but later detach and develop internal dynamics. The developmental timeline and circuit basis for this disengagement remains unknown. A study on mouse development reveals that there is an abrupt shift in the representation of self-motion in the hippocampal CA1 area at the end of the first postnatal week, indicating the emergence of internal hippocampal dynamics.
Article
Nanoscience & Nanotechnology
Fatima El Moussawi, Matthias Hofer, Damien Labat, Andy Cassez, Geraud Bouwmans, Siddharth Sivankutty, Rosa Cossart, Olivier Vanvincq, Herve Rigneault, Esben Ravn Andresen
Summary: This study presents a novel tapered multicore fiber (MCF) component for ultraminiaturized endoscopes, addressing the power delivery issue faced by MCF-based lensless endoscopes and achieving a significant increase in two-photon signal yield.
Article
Biochemistry & Molecular Biology
Zhuohe Liu, Xiaoyu Lu, Vincent Villette, Yueyang Gou, Kevin L. Colbert, Shujuan Lai, Sihui Guan, Michelle A. Land, Jihwan Lee, Tensae Assefa, Daniel R. Zollinger, Maria M. Korympidou, Anna L. Vlasits, Michelle M. Pang, Sharon Su, Changjia Cai, Emmanouil Froudarakis, Na Zhou, Saumil S. Patel, Cameron L. Smith, Annick Ayon, Pierre Bizouard, Jonathan Bradley, Katrin Franke, Thomas R. Clandinin, Andrea Giovannucci, Andreas S. Tolias, Jacob Reimer, Stephane Dieudonne, Francois St-Pierre
Summary: Researchers developed a high-throughput platform to optimize genetically encoded voltage indicators for two-photon microscopy. They identified a new indicator, JEDI-2P, which is faster, brighter, more sensitive, and more photostable than previous indicators. JEDI-2P can be used to monitor voltage dynamics in various applications.
Article
Mathematics, Applied
Gabriele Paolini, Marzena Ciszak, Francesco Marino, Simona Olmi, Alessandro Torcini
Summary: The study reports on collective excitatory events in a highly diluted random network of non-excitable nodes, driven by a local self-sustained adaptation mechanism that guides the system across a hysteric phase transition with different levels of synchronization. The research demonstrates that such collective phenomena remain remarkably robust against network diluteness.
Article
Neurosciences
Erwan Leprince, Robin F. Dard, Salome Mortet, Caroline Filippi, Marie Giorgi-Kurz, Romain Bourboulou, Pierre-Pascal Lenck-Santini, Michel A. Picardo, Marco Bocchio, Agnes Baude, Rosa Cossart
Summary: The adult CA1 region of the hippocampus produces coordinated neuronal dynamics with minimal reliance on its extrinsic inputs. Neonatal CA1, on the other hand, is tightly linked to externally generated sensorimotor activity, but the circuit mechanisms underlying early synchronous activity in CA1 remain unclear. In this study, researchers use a combination of in vivo and ex vivo circuit mapping, calcium imaging, and electrophysiological recordings in mouse pups to investigate the dynamics in the ventro-intermediate CA1. They find that these dynamics are influenced by both the entorhinal (EC) and thalamic (VMT) inputs, but movement-related population bursts are exclusively driven by the EC. The differential effects reflect the different intrahippocampal targets of these inputs, suggesting distinct contributions to the development of the hippocampal microcircuit and related cognitive maps.
Article
Cell Biology
Richard Boyce, Robin F. Dard, Rosa Cossart
Summary: A study found no difference in the structure of assembly activity in the sensorimotor cortex during awake, non-rapid eye movement sleep (NREMs), or rapid eye movement sleep (REMs), despite the latter two states being associated with reduced consciousness. However, there was a significant coordination between global electroencephalogram (EEG) microstate dynamics and local cortical assembly activity during periods of wakefulness, but not during sleep.
Article
Optics
Naveen Gajendra Kumar, Siddharth Sivankutty, Victor Tsvirkun, Andy Cassez, Damien Labat, Rosa Cossart, Geraud Bouwmans, Esben Ravn Andresen, Herve Rigneault
Summary: We present a modified fiber geometry for a bending-insensitive multi-core fiber (MCF) that allows optimal light coupling in and out of the individual cores, addressing the coupling complexity and potential degradation issues of previously reported twisted MCFs. By introducing a section with straight and parallel cores at the ends of the MCF, we rectify the coupling and output light problems, enabling the development of bend-insensitive lensless endoscopes.
Article
Physics, Fluids & Plasmas
Alberto Ferrara, David Angulo-Garcia, Alessandro Torcini, Simona Olmi
Summary: This study investigates the impact of spike-frequency adaptation (SFA) on the macroscopic dynamics of excitatory and inhibitory neural networks. Using an exact mean-field reduction method, synthetic neural mass models are employed to analyze the effects of SFA. The results demonstrate that SFA promotes population bursts in excitatory networks while inhibiting tonic spiking in inhibitory ones. Additionally, the symmetric coupling of two neural masses leads to the emergence of macroscopic solutions with broken symmetry, exhibiting cross-frequency coupling (CFC) between fast synaptic and slow adaptation timescales.