Article
Chemistry, Analytical
Madiah Binti Omar, Rosdiazli Ibrahim, Rhea Mantri, Jhanavi Chaudhary, Kaushik Ram Selvaraj, Kishore Bingi
Summary: This study aims to develop an enhanced forecasting model to predict the stability of a smart grid using neural networks to handle missing data. Four case studies are conducted to predict the missing data and a model is prepared to predict stability. The results demonstrate good performance and the models show the best training and prediction ability.
Article
Multidisciplinary Sciences
Sadegh Ebrahimi, Jerome Lecoq, Oleg Rumyantsev, Tugce Tasci, Yanping Zhang, Cristina Irimia, Jane Li, Surya Ganguli, Mark J. Schnitzer
Summary: This study investigated the process of neocortical sensory processing during visual discrimination tasks in mice. The results showed that the neocortex had a specific functional connectivity pattern at rest, which rearranged after the onset of sensory stimulus. A short-lived state with increased inter-area sensory data transmission and sensory encoding redundancy was observed, followed by a more stable visual representation that was robust to day-to-day variations in individual cell responses. In addition, a global fluctuation mode conveyed the upcoming response of the mouse to every area examined. These findings suggest that the neocortex supports sensory performance through dynamic changes in connectivity and robust population codes.
Article
Multidisciplinary Sciences
Chengcheng Huang, Alexandre Pouget, Brent Doiron
Summary: This study examines stimulus coding in networks of spiking neuron models with spatially ordered connectivity, and finds that correlations introduced by inhibitory feedback projections can limit the stimulus information available to a decoder. By using a spatial neural field model, the study relates the feedback circuit conditions to the spatiotemporal patterns of population-wide activity.
Article
Mathematics, Interdisciplinary Applications
Shiqi Dai, Lulu Lu, Zhouchao Wei, Yuan Zhu, Ming Yi
Summary: Temperature is an important factor that influences the propagation of subthreshold signals and the spontaneous activity of neural networks. This study reveals the mechanisms through which temperature and noise affect signal propagation.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Computer Science, Artificial Intelligence
Wenhao Lu, Zhengyuan Zhang, Feng Qin, Wenwen Zhang, Yuncheng Lu, Yue Liu, Yuanjin Zheng
Summary: In recent decades, there has been significant interest in the hardware implementation of feedforward neural networks. However, when implementing neural networks in analog circuits, the circuit-based model is sensitive to hardware nonidealities. This paper focuses on the presence of time-varying noise at the input of hidden neurons and proposes a noise-resilient network design to counteract its effects.
Article
Physics, Multidisciplinary
Cathelijne ter Burg, Felipe Bohn, Gianfranco Durin, Rubem Luis Sommer, Kay Jorg Wiese
Summary: We demonstrate the validity of the functional renormalization group by measuring force correlations in Barkhausen-noise experiments. Our results show that the force correlations have a universal form predicted by the functional renormalization group, with distinct characteristics for short-range and long-range elasticity. Additionally, we find that the correlations are mostly independent of eddy currents. These findings provide important insights into domain wall behavior in ferromagnetic materials.
PHYSICAL REVIEW LETTERS
(2022)
Article
Computer Science, Information Systems
Yan Hua, Lin Yang, Yingyun Yang
Summary: In this paper, a deep stereo matching model is proposed using multiple frequency inputs and an attention mechanism. The model achieves good performance in generating disparity maps, addressing the issues of blurred boundaries and inaccurate resolution restoration.
Article
Engineering, Multidisciplinary
MengYan Ge, GuoWei Wang, Ya Jia
Summary: Iterative methods were used to simulate in vitro feedforward neural networks in physiological experiments. The study investigated the effect of Gaussian colored noise and electromagnetic radiation on the propagation of subthreshold excitatory postsynaptic current signals. It was found that electromagnetic radiation slightly reduces the propagation of weak signals and an increase in feedback gain leads to longer propagation time. The feedforward neural network studied is a simple model, while more complex structures can be observed in real biological systems.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2021)
Article
Optics
Mohamed Touil, Rezki Becheker, Thomas Godin, Ammar Hideur
Summary: The study explores the potential of shaping spectral correlations by tuning parameters to track energy transfers within FOPO. By analyzing wavelength correlations, insights into spectrotemporal dynamics and correlation patterns are revealed, showcasing the versatility of fiber-optical sources in quantum optics applications.
Article
Multidisciplinary Sciences
Charlie S. Burlingham, Saghar Mirbagheri, David J. Heeger
Summary: The dilation and constriction of the pupil following task events can be explained by a model based on the common neural input driving saccades and pupil size. The estimates of arousal from this model are consistent with key predictions and offer a unified explanation for a wide range of phenomena.
Article
Neurosciences
Lu Wang, Zhenhao Zhang, Dan Han, Zhijun Zhang, Zhifang Liu, Wei Liu
Summary: Brain-computer interfaces (BCIs) help paralyzed individuals communicate with the outside world. A new concept of a one-to-two BCI was proposed to optimize existing problems by sharing the same location for target and other stimuli. The results showed that the BCI based on object-based attention achieved a recognition rate of 83.2% and an ITR of 12.5 bits per minute, demonstrating the feasibility of the one-to-two BCI design in simplifying keyboard layout and reducing user fatigue.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2021)
Article
Biochemical Research Methods
Oren Weiss, Hayley A. Bounds, Hillel Adesnik, Ruben Coen-Cagli
Summary: Divisive normalization is a widely used descriptive model of neural activity in various brain areas. However, the relationship between normalization and the statistics of neural responses beyond single neurons has not been thoroughly explored. In this study, a stochastic divisive normalization model is proposed to investigate the effects of normalization on noise correlations. The model is applied to calcium imaging data from mouse primary visual cortex (V1), and it accurately fits the data, outperforming alternative models. The analysis suggests that normalization signals are often shared between V1 neurons. This model provides a framework for quantifying the relation between normalization and covariability in neural systems, which is important for understanding circuit mechanisms of normalization and their role in information transmission and representation.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Multidisciplinary Sciences
Johan Nakuci, Jason Samaha, Dobromir Rahnev
Summary: Brain activity during a task shows significant variability. By using a data-driven clustering method, consistent EEG activity patterns across individual trials can be identified, revealing the different patterns associated with task characteristics. These findings highlight the across-trial variability in decision processes that are usually overlooked by experimenters, and provide a method for identifying endogenous brain state variability relevant to cognition and behavior.
Article
Multidisciplinary Sciences
Cheng Ly, Andrea K. Barreiro, Hari Gautam, Woodrow L. Shew
Summary: The onset of sensory input can cause an increase in the variability of neural activity in the mammalian olfactory bulb, contrary to previous beliefs. This sensory evoked increase in spiking variability is proposed as a viable alternative coding strategy.
Article
Computer Science, Hardware & Architecture
Yingya Guo, Yufei Peng, Run Hao, Xiang Tang
Summary: Network traffic prediction is crucial for network management and security, but current methods suffer from accuracy degradation. To address this issue, we propose an AGCN model that captures the temporal-spatial correlations in network traffic. Experimental results show that AGCN outperforms existing methods in terms of prediction accuracy and inference time.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2023)
Review
Neurosciences
Gerald Hahn, Adrian Ponce-Alvarez, Gustavo Deco, Ad Aertsen, Arvind Kumar
NATURE REVIEWS NEUROSCIENCE
(2019)
Article
Neurosciences
Marko Filipovic, Maya Ketzef, Ramon Reig, Ad Aertsen, Gilad Silberberg, Arvind Kumar
JOURNAL OF NEUROPHYSIOLOGY
(2019)
Article
Neurosciences
Orcun Orkan Ozcan, Xiaolu Wang, Francesca Binda, Kevin Dorgans, Chris I. De Zeeuw, Zhenyu Gao, Ad Aertsen, Arvind Kumar, Philippe Isope
JOURNAL OF NEUROSCIENCE
(2020)
Article
Biochemical Research Methods
Sebastian Spreizer, Ad Aertsen, Arvind Kumar
PLOS COMPUTATIONAL BIOLOGY
(2019)
Article
Neurosciences
Lars Hunger, Arvind Kumar, Robert Schmidt
JOURNAL OF NEUROSCIENCE
(2020)
Article
Biochemical Research Methods
Hedyeh Rezaei, Ad Aertsen, Arvind Kumar, Alireza Valizadeh
PLOS COMPUTATIONAL BIOLOGY
(2020)
Article
Neurosciences
Luiz Tauffer, Arvind Kumar
Summary: The brain's ability to differentiate spikes encoding specific stimuli is crucial for reliable information processing. Synaptic short-term plasticity (STP) and feedforward excitation followed by inhibition (FF-EI) mechanisms increase signal gain and allow discrimination between sparse signals and background activity changes, providing robustness to the brain. This STP-based distribution discrimination may be a latent function in regions like the cerebellum and hippocampus.
Review
Behavioral Sciences
Andrew B. Lehr, Arvind Kumar, Christian Tetzlaff, Torkel Hafting, Marianne Fyhn, Tristan M. Stober
Summary: CA2 in the hippocampal region is gaining increased attention for its role in social recognition memory, as well as its broader functions in memory processing. Recent research suggests that CA2 may play a fundamental role in hippocampus-dependent memory processing tasks.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2021)
Article
Neurosciences
Kingshuk Chakravarty, Sangheeta Roy, Aniruddha Sinha, Atsushi Nambu, Satomi Chiken, Jeanette Hellgren Kotaleski, Arvind Kumar
Summary: The basal ganglia is crucial for motor and cognitive functions. Persistent low-dopamine induces changes in steady-state population activity and transient response of the basal ganglia. This study used numerical simulations to identify key factors shaping the transient response in low-dopamine state.
Article
Multidisciplinary Sciences
Malin Sandstrom, Mathew Abrams, Jan G. Bjaalie, Mona Hicks, David N. Kennedy, Arvind Kumar, Jean-Baptiste Poline, Prasun K. Roy, Paul Tiesinga, Thomas Wachtler, Wojtek J. Goscinski
Summary: Repositories and science gateways are vital resources for the neuroscience community, but users struggle to find the most suitable services. INCF has developed recommendations and criteria for selecting, establishing, and running repositories or scientific gateways with a FAIR perspective.
Article
Biology
Gerald Hahn, Arvind Kumar, Helmut Schmidt, Thomas R. Knoesche, Gustavo Deco
Summary: The neocortex consists of layered microcircuits with various types of excitatory and inhibitory neurons, which perform computations based on firing rate and oscillations. Through modeling, researchers discovered that the superficial and deep layers of the mouse visual cortex have ultrasensitive and bistable switches, which toggle pyramidal neurons between high and low firing rate states. These switches are built on inhibitory connectivity motives between different types of cells. The findings also reveal layer-specific differences in oscillation frequency and power during state transitions.
Article
Biology
Movitz Lenninger, Mikael Skoglund, Pawel Andrzej Herman, Arvind Kumar
Summary: According to the efficient coding hypothesis, sensory neurons are adapted to provide maximal information about the environment, given some biophysical constraints. Tuning curves in early visual areas have predominantly single-peaked modulations of neural activity, while periodic tuning curves have been linked to increased decoding performance. The time scale at which neurons encode information is crucial to understand the advantages of single-peaked and periodic tuning curves. The presence of catastrophic errors creates a trade-off between decoding time and decoding ability, and this trade-off is reinforced by high stimulus dimensionality or ongoing activity. Overall, the normative arguments support the existence of the single-peaked tuning organization observed in early visual areas.
Article
Multidisciplinary Sciences
Emil Warnberg, Arvind Kumar
Summary: This article discusses the role of midbrain dopaminergic neurons in the basal ganglia and how to explain how dopamine supports learning of continuous outputs instead of discrete action values. The authors propose a model and demonstrate its validity through a learning rule.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Neurosciences
Katharina Heining, Antje Kilias, Philipp Janz, Ute Haeussler, Arvind Kumar, Carola A. Haas, Ulrich Egert
Article
Physics, Fluids & Plasmas
Christopher M. Kim, Ulrich Egert, Arvind Kumar