9 papers · ranked by Valyu relevance
Eliezer Masliah
How transient neural representations become integrated and stable enough to function as internal neural models remains incompletely understood. Grounded in efficient coding, Bayesian and predictive frameworks, recurrent and attractor dynamics, neural state-space models, and systems neuroscience, the Principle of…
Viktor Studenyak, Jürgen Jost, Christian F. Doeller, Andrej Bicanski
The Dentate Gyrus (DG) is a key part of the hippocampus, and damage to the DG produces a wide range of pathologies, including overgeneralization of contexts, affective dysregulation (4), and epileptogenic effects (60). The canonical model of the DG focuses on pattern separation for subsequent memory storage in the…
Henrique Reis Aguiar, Matthias H. Hennig
Predictive coding is a powerful normative framework for understanding cortical computation, but it is still an open question how biologically plausible networks with local plasticity support predictive inference and representation learning. In this work we show that a recurrent excitatory-inhibitory circuit with purely…
Eva Lemoine, Brendan Lenfesty, Umesh Kumar Naik Mudavath, Saugat Bhattacharyya + 1 more
Echo state networks (ESNs) are efficient, neuro-inspired computational frameworks well suited to time-series data. However, ESN decision confidence is typically quantified in limited ways. We propose an explicit decision-confidence readout neuron, trained from decision readout outputs, to continuously monitor…
Charles de Kergariou, Helmut Hauser, David Correa
Advances in novel materials science enable structures to function as intelligent machines by embedding memory and learning capabilities directly into materials. Our work introduces a physical adaptive material motor unit neural network, leveraging a new generation of controllable actuators composed of wood- and carbon…
Hayato Idei, Keisuke Suzuki, Yuichi Yamashita
Mindfulness has established psychological benefits, such as stress reduction and emotional regulation; however, the underlying computational mechanisms, particularly in relation to mind-wandering, remain unclear. This study aimed to present a hierarchical recurrent neural network-based agent model grounded in the free…
Yi Ren, Zimei Chen, Hayden Deans, Ying Nian Wu + 1 more
Extensive studies suggest the brain performs Bayesian inference to infer the latent world states. It is a fundamental neuroscience question that how canonical recurrent neural circuits in the brain implement Bayesian inference. Many existing theoretical studies focused on how the recurrent circuits compute the…
Yi Wang, Jin Shan, Chenglong Zhang, Zhenhu Jin + 3 more
Neuronal magnetic signal recording intrinsically provides vector information and tissue transparency, offering a potential route to overcome the spatial resolution limitations of conventional electrophysiological recordings. However, in situ detection of neuronal magnetic signals at the cellular level remains highly…
Hadeer Kamal, Amira Y. Haikal, Mahmoud M. Saafan
Traffic collisions and congestion represent significant challenges within intelligent transportation systems (ITS). Consequently, a vehicular ad-hoc network (VANET) has been established. Numerous architectures have been incorporated into VANETs to manage the extensive data generated by vehicles. Collaboration with fog…