Article
Computer Science, Artificial Intelligence
Faramarz Faghihi, Siqi Cai, Ahmed A. Moustafa
Summary: This study introduces a spiking neural network model for auditory spatial attention detection, showing improved accuracy with the use of limited training data. The model leverages the role of sparse coding in cognitive tasks and brain-inspired machine learning.
Editorial Material
Biochemistry & Molecular Biology
Zane B. Andrews
Summary: Neural circuits play a role in regulating food intake by responding to internal hunger and hedonic cues. This study used a hunger discrimination task and genetic manipulation to identify circuits involved in driving food intake.
Article
Multidisciplinary Sciences
Ziqi Wang, Enrico Calzavarini, Chao Sun, Federico Toschi
Summary: Convective flows coupled with solidification or melting in water bodies have a significant impact on shaping geophysical landscapes. It is important to accurately quantify the dynamic interaction between water-body environments and ice formation or melting processes, considering factors such as water density anomaly. Thermal driving has major effects on the temporal evolution of the global icing process, with different flow-dynamics regimes influencing the coupling levels between ice front and water layers.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Multidisciplinary Sciences
Silvan Huerkey, Nelson Niemeyer, Jan-Hendrik Schleimer, Stefanie Ryglewski, Susanne Schreiber, Carsten Duch
Summary: This study identifies a miniaturized circuit solution for the central-pattern-generating (CPG) neural network underlying insect asynchronous flight. The network consists of motoneurons interconnected by electrical synapses that produce network activity splayed out in time instead of synchronized across neurons. This mechanism translates unpatterned premotor input into stereotyped neuronal firing with fixed sequences of cell activation, ensuring stable wingbeat power and is conserved across multiple species.
Article
Biology
Leor N. Katz, Gongchen Yu, James P. Herman, Richard J. Krauzlis
Summary: Correlated variability in neuronal activity can constrain information readout from populations of neurons. Traditionally, it is reported as a single value summarizing a brain area, but this may obscure underlying features. In the macaque superior colliculus, different functional classes of neurons exhibit distinct levels of correlated variability, with delay class neurons showing the highest levels during working memory tasks. Considering functional subpopulations is important for understanding population coding principles.
COMMUNICATIONS BIOLOGY
(2023)
Article
Audiology & Speech-Language Pathology
David Perez-Gonzalez, Gloria G. Parras, Camilo J. Morado-Diaz, Cristian Aedo-Sanchez, Guillermo V. Carbajal, Manuel S. Malmierca
Summary: This study investigated neuronal activities in the auditory cortex of animals under the oddball paradigm and found that both fast spiking and regular spiking neurons showed similar levels of deviance detection overall. However, in A1 area, fast spiking neurons exhibited significantly higher levels of deviance detection compared to regular spiking neurons.
Article
Astronomy & Astrophysics
J. M. Pittard, M. M. Kupilas, C. J. Wareing
Summary: We investigate the resolution dependence of H II regions expanding past their Stromgren spheres. We find that if the Stromgren radius is resolved with certain conditions, the structure, size, and radial momentum of the regions at a given time are in good agreement with analytical expectations. Otherwise, the radial momentum may be over- or underestimated by factors up to 10 or more. Our work is significant for understanding the amount of radial momentum and the relative importance of ionizing feedback from massive stars in numerical simulations.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2022)
Article
Mathematics, Applied
Qiang Lai, Shicong Guo
Summary: This paper aims to construct a class of memristive neural networks (MNNs) with a simple circular connection relationship and complex dynamics by introducing a generic memristor as synapse. One remarkable feature of the proposed MNNs is that they can yield complex dynamics, in particular, abundant coexisting attractors and large-scale parameter-relied amplitude control, by comparing with some existing MNNs. The complex dynamics and circuit implementation of one of the MNNs are studied, and a microcontroller-based hardware circuit is given to realize the network, which verifies the correctness of the numerical results and experimental results.
Review
Chemistry, Multidisciplinary
Hefei Liu, Yuan Qin, Hung-Yu Chen, Jiangbin Wu, Jiahui Ma, Zhonghao Du, Nan Wang, Jingyi Zou, Sen Lin, Xu Zhang, Yuhao Zhang, Han Wang
Summary: This paper reviews the progress of artificial neuronal devices based on emerging volatile switching materials, focusing on the demonstrated neuron models implemented in these devices and their utilization for computational and sensing applications. Furthermore, it discusses the inspirations from neuroscience and engineering methods to enhance the neuronal dynamics that are yet to be realized in artificial neuronal devices and networks towards achieving the full functionalities of biological neurons.
ADVANCED MATERIALS
(2023)
Article
Neurosciences
Scott S. Bolkan, Iris R. Stone, Lucas Pinto, Zoe C. Ashwood, Jorge M. Iravedra Garcia, Alison L. Herman, Priyanka Singh, Akhil Bandi, Julia Cox, Christopher A. Zimmerman, Jounhong Ryan Cho, Ben Engelhard, Jonathan W. Pillow, Ilana B. Witten
Summary: Opposing control of behavior by dorsomedial striatum pathways depends on task demands and changes in internal state.
NATURE NEUROSCIENCE
(2022)
Article
Mathematics, Applied
Hiroaki Uchida, Yuya Oishi, Toshimichi Saito
Summary: This paper investigates synchronization phenomena of spike-trains and approximation of target spike-trains in a simple network of digital spiking neurons. The network can exhibit multi-phase synchronization of various spike-trains and automatically approximate target spike-trains using a winner-take-all switching method. Experimental confirmation of typical synchronization phenomenon and spike-train approximation is provided through an FPGA based hardware prototype.
DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES S
(2021)
Article
Computer Science, Information Systems
Dhvani Shah, Ajit Narayanan, Josafath Israel Espinosa-Ramos
Summary: This paper presents a Spiking Neural Network (SNN) architecture for distinguishing piano and violin. The study investigates the behavior of spiking neurons and utilizes spike based statistics and a Gamma metric for classification and recognition. The research shows the potential of SNNs in temporal recognition and classification, and demonstrates that SNNs are more effective than conventional machine learning methods in capturing the acoustic characteristics of music.
Article
Engineering, Mechanical
Bruno Andre Santos, Rogerio Martins Gomes, Phil Husbands
Summary: The study suggests that the rebound spike of a neuron can sustain activity in a recurrent inhibitory neural circuit, with the neurons in the circuit firing at low frequencies. The occurrence of a rebound spike depends on factors such as synaptic weights, conductances, and neuron state. The developed model aims to raise theoretical issues for understanding neural mechanisms underlying self-sustained neural activity.
NONLINEAR DYNAMICS
(2021)
Article
Engineering, Multidisciplinary
Amel Ali Alhussan, Marwa M. Eid, S. K. Towfek, Doaa Sami Khafaga
Summary: According to the American Cancer Society, breast cancer is the second largest cause of mortality among women after lung cancer. Women's death rates can be decreased if breast cancer is diagnosed and treated early. Automated approach is necessary for early cancer identification. This research proposes a novel framework integrating metaheuristic optimization with deep learning and feature selection for robustly classifying breast cancer from ultrasound images.
Article
Health Care Sciences & Services
Fatih Demir, Kamran Siddique, Mohammed Alswaitti, Kursat Demir, Abdulkadir Sengur
Summary: This study proposes a new approach based on multi-level feature selection to detect Parkinson's disease by analyzing voice recordings. Feature selection was performed using the Chi-square, L1-Norm SVM, and ReliefF algorithms, and machine learning was done using the KNN classifier. The proposed approach achieved a classification accuracy of 95.4%.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Article
Virology
Michael Famulare, Stewart Chang, Jane Iber, Kun Zhao, Johnson A. Adeniji, David Bukbuk, Marycelin Baba, Matthew Behrend, Cara C. Burns, M. Steven Oberste
JOURNAL OF VIROLOGY
(2016)
Article
Multidisciplinary Sciences
Michael Famulare
Article
Public, Environmental & Occupational Health
Michael Famulare, Hao Hu
INTERNATIONAL HEALTH
(2015)
Article
Biochemistry & Molecular Biology
Michael Famulare, Christian Selinger, Kevin A. McCarthy, Philip A. Eckhoff, Guillaume Chabot-Couture
Article
Mathematical & Computational Biology
Brian Nils Lundstrom, Michael Famulare, Larry B. Sorensen, William J. Spain, Adrienne L. Fairhall
JOURNAL OF COMPUTATIONAL NEUROSCIENCE
(2009)
Article
Neurosciences
Rebecca A. Mease, Michael Famulare, Julijana Gjorgjieva, William J. Moody, Adrienne L. Fairhall
JOURNAL OF NEUROSCIENCE
(2013)
Correction
Physics, Fluids & Plasmas
Joshua H. Goldwyn, Nikita S. Imennov, Michael Famulare, Eric Shea-Brown
Article
Physics, Fluids & Plasmas
Joshua H. Goldwyn, Nikita S. Imennov, Michael Famulare, Eric Shea-Brown
Article
Multidisciplinary Sciences
Steve J. Kroiss, Maiwand Ahmadzai, Jamal Ahmed, Muhammad Masroor Alam, Guillaume Chabot-Couture, Michael Famulare, Abdirahman Mahamud, Kevin A. McCarthy, Laina D. Mercer, Salman Muhammad, Rana M. Safdar, Salmaan Sharif, Shahzad Shaukat, Hemant Shukla, Hil Lyons
Article
Multidisciplinary Sciences
Trevor Bedford, Alexander L. Greninger, Pavitra Roychoudhury, Lea M. Starita, Michael Famulare, Meei-Li Huang, Arun Nalla, Gregory Pepper, Adam Reinhardt, Hong Xie, Lasata Shrestha, Truong N. Nguyen, Amanda Adler, Elisabeth Brandstetter, Shari Cho, Danielle Giroux, Peter D. Han, Kairsten Fay, Chris D. Frazar, Misja Ilcisin, Kirsten Lacombe, Jover Lee, Anahita Kiavand, Matthew Richardson, Thomas R. Sibley, Melissa Truong, Caitlin R. Wolf, Deborah A. Nickerson, Mark J. Rieder, Janet A. Englund, James Hadfield, Emma B. Hodcroft, John Huddleston, Louise H. Moncla, Nicola F. Mueller, Richard A. Neher, Xianding Deng, Wei Gu, Scot Federman, Charles Chiu, Jeffrey S. Duchin, Romesh Gautom, Geoff Melly, Brian Hiatt, Philip Dykema, Scott Lindquist, Krista Queen, Ying Tao, Anna Uehara, Suxiang Tong, Duncan MacCannell, Gregory L. Armstrong, Geoffrey S. Baird, Helen Y. Chu, Jay Shendure, Keith R. Jerome