Zobrazeno 1 - 10
of 298
pro vyhledávání: '"V Srinivasa Chakravarthy"'
Autor:
Azra Aziz, Bharat K. Patil, Kailash Lakshmikanth, Peesapati S. S. Sreeharsha, Ayan Mukhopadhyay, V. Srinivasa Chakravarthy
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Studies on the neural correlates of navigation in 3D environments are plagued by several issues that need to be solved. For example, experimental studies show markedly different place cell responses in rats and bats, both navigating in 3D en
Externí odkaz:
https://doaj.org/article/70677b75d6534dce949a46fe1bb38dfa
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)
Abstract We present a general, trainable oscillatory neural network as a large-scale model of brain dynamics. The model has a cascade of two stages - an oscillatory stage and a complex-valued feedforward stage - for modelling the relationship between
Externí odkaz:
https://doaj.org/article/a9498b81b7f24cd084f99b1192044d4f
Autor:
Sandeep Sathyanandan Nair, Vignayanandam Ravindernath Muddapu, C. Vigneswaran, Pragathi P. Balasubramani, Dhakshin S. Ramanathan, Jyoti Mishra, V. Srinivasa Chakravarthy
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract Human cognition is characterized by a wide range of capabilities including goal-oriented selective attention, distractor suppression, decision making, response inhibition, and working memory. Much research has focused on studying these indiv
Externí odkaz:
https://doaj.org/article/392b379b4e414816ac3d4abd638ac091
Publikováno v:
Journal of NeuroEngineering and Rehabilitation, Vol 19, Iss 1, Pp 1-21 (2022)
Abstract Background Restoring movement after hemiparesis caused by stroke is an ongoing challenge in the field of rehabilitation. With several therapies in use, there is no definitive prescription that optimally maps parameters of rehabilitation with
Externí odkaz:
https://doaj.org/article/8c568fc4b95c4f64b752e287b057ed18
Autor:
Sundari Elango, Amal Jude Ashwin Francis, Divya Darshini, Shabeera Hafsath, V. Srinivasa Chakravarthy, Raju S. Bapi, Pn Sylaja, Srijithesh Rajendran, Aniruddha Sinha, Lincy Philip, Sri Nithya
Publikováno v:
IBRO Neuroscience Reports, Vol 15, Iss , Pp S679- (2023)
Externí odkaz:
https://doaj.org/article/79e1c50c52a4461186a83072b64052d2
Publikováno v:
Frontiers in Neural Circuits, Vol 17 (2023)
We present a deep network-based model of the associative memory functions of the hippocampus. The proposed network architecture has two key modules: (1) an autoencoder module which represents the forward and backward projections of the cortico-hippoc
Externí odkaz:
https://doaj.org/article/7700c55f599b450c894c08ee56b7ab22
Publikováno v:
Frontiers in Neuroscience, Vol 17 (2023)
Although there is a plethora of modeling literature dedicated to the object recognition processes of the ventral (“what”) pathway of primate visual systems, modeling studies on the motion-sensitive regions like the Medial superior temporal area (
Externí odkaz:
https://doaj.org/article/edf7a9f8d6144b23be5afd4331b16913
Publikováno v:
Frontiers in Computational Neuroscience, Vol 16 (2022)
We propose a brain inspired attentional search model for target search in a 3D environment, which has two separate channels—one for the object classification, analogous to the “what” pathway in the human visual system, and the other for predict
Externí odkaz:
https://doaj.org/article/814da86a05d742d39b6d614f46bde05d
Publikováno v:
Frontiers in Computational Neuroscience, Vol 16 (2022)
We present a model of a tonotopic map known as the Oscillatory Tonotopic Self-Organizing Map (OTSOM). It is a 2-dimensional, self-organizing array of Hopf oscillators, capable of performing a Fourier-like decomposition of the input signal. While the
Externí odkaz:
https://doaj.org/article/90e6c99212be4bb0a342c5577f2891ee
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-19 (2021)
Abstract Artificial feedforward neural networks perform a wide variety of classification and function approximation tasks with high accuracy. Unlike their artificial counterparts, biological neural networks require a supply of adequate energy deliver
Externí odkaz:
https://doaj.org/article/134878b503b44fba9d6e4e37b5e40e55