A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Filters
Biophysical Neural Spiking, Bursting, and Excitability Dynamics in Reconfigurable Analog VLSI
2011
IEEE Transactions on Biomedical Circuits and Systems
Preserved Fulltext
Index Terms-Analog VLSI, biophysical neural dynamics, neuromorphic engineering, programmable channel kinetics, silicon neuron interfaces, spiking neuron models. ...
The extended models are implemented in NeuroDyn, a four neuron, twelve synapse continuous-time analog VLSI programmable neural emulation platform with generalized channel kinetics and biophysical membrane ...
Chi for help with the experimental setup, and the MOSIS Educational Program for fabricating the chip. ...
doi:10.1109/tbcas.2011.2169794
pmid:22227949
pmcid:PMC3251010
fatcat:fcjjxsuxwzcorocxj3t6ysjl6m
Controlling articulated robots in task-space with spiking silicon neurons
2014
5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2014; you can also visit the original URL.
The file type is application/pdf.
Factorizing the controller reduced the neural regression's complexity to cubic in the dynamic range of the robot's state and desired forces. ...
The controller is compliant and can draw shapes with a pen on a dynamically perturbed surface while remaining stable. ...
TASK-SPACE CONTROL WITH SPIKING NEURONS We mapped our task-space force controller on to Neurogrid using the Neural Engineering Framework [10] , which computes functions with pools of spiking neurons by ...
doi:10.1109/biorob.2014.6913773
dblp:conf/biorob/MenonFNKB14
fatcat:3axwjujjzbeord3ieorhprzuvi
Breaking the virtual barrier: real-time interactions with spiking neural models
2010
BMC Neuroscience
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Presented here is a toolkit, dubbed NCSTools, used for real-time interactions with large-scale neural simulations run on the NeoCortical Simulator (NCS). ...
The model information flow can be altered dynamically by NCSTools, as can model parameters ...
These programs can be used for control of defined NCSTools actions, monitoring specific neural information, or synchronization with the simulation. ...
doi:10.1186/1471-2202-11-s1-p73
pmcid:PMC3090963
fatcat:cmae5lh7mbax3dblcrncttrkpm
Neuromorphic implementations of neurobiological learning algorithms for spiking neural networks
2015
Neural Networks
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Unlike Von Neumann CPUs, these chips cannot be simply programmed with a standard programming language. ...
The paper thus gives an in-depth overview of neuromorphic implementations of basic mechanisms of synaptic plasticity which are required to realize advanced cognitive capabilities with spiking neural networks ...
The actual computation of neural dynamics is implemented in the Processing Core. ...
doi:10.1016/j.neunet.2015.07.004
pmid:26422422
fatcat:qbpqali565blfphyprdvy6o3lm
Neural dynamics in reconfigurable silicon
2010
Proceedings of 2010 IEEE International Symposium on Circuits and Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
Emphasis is placed on replicating the detailed dynamics of computational neural models. ...
The programmability is achieved using floating gate transistors with on-chip programming control. ...
CONCLUSION We presented a reconfigurable integrated circuit for accurately describing neural dynamics and computations. ...
doi:10.1109/iscas.2010.5536960
dblp:conf/iscas/BasuRH10
fatcat:2sp2qconqfdanetrpim4bp2fgy
Neural Dynamics in Reconfigurable Silicon
2010
IEEE Transactions on Biomedical Circuits and Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
Emphasis is placed on replicating the detailed dynamics of computational neural models. ...
The programmability is achieved using floating gate transistors with on-chip programming control. ...
CONCLUSION We presented a reconfigurable integrated circuit for accurately describing neural dynamics and computations. ...
doi:10.1109/tbcas.2010.2055157
pmid:23853376
fatcat:aazltzdporffle6brlldnpllu4
Biologically Sound Neural Networks for Embedded Systems Using OpenCL
[chapter]
2013
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2013; you can also visit the original URL.
The file type is application/pdf.
In this paper, we present an OpenCL implementation of a biologically sound spiking neural network with two goals in mind: First, applied neural dynamics should be accurate enough for bio-inspired training ...
We show that an optimized GPU kernel code can perform sufficiently fast to be used for future embedded neural processing. ...
Our results also compare to similar implementations of spiking neural networks with different neural dynamics [10] . ...
doi:10.1007/978-3-642-40148-0_18
fatcat:p4vdazof35cn7jnsq5qgzk7qyi
Data and Power Efficient Intelligence with Neuromorphic Learning Machines
2018
iScience
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The success of deep networks and recent industry involvement in brain-inspired computing is igniting a widespread interest in neuromorphic hardware that emulates the biological processes of the brain on ...
We find that (1) recent work in binary deep networks and approximate gradient descent learning are strikingly compatible with a neuromorphic substrate; (2) where real-time adaptability and autonomy are ...
Matching Neural and Synaptic Dynamics Several computational models of the brain argue that computational optimality hinges on plasticity dynamics and neural dynamics being matched (Lengyel et al., 2005 ...
doi:10.1016/j.isci.2018.06.010
pmid:30240646
pmcid:PMC6123858
fatcat:zo4dvtgo75c7pn6n7tal24fkly
Deep learning incorporating biologically-inspired neural dynamics
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Simultaneously, Spiking Neural Networks (SNNs) incorporating biologically-feasible spiking neurons have held great promise because of their rich temporal dynamics and high-power efficiency. ...
Here we show an alternative perspective on the spiking neuron that casts it as a particular ANN construct called Spiking Neural Unit (SNU), and a soft SNU (sSNU) variant that generalizes its dynamics to ...
The neuron N2 with a step activation function reproduces the spiking behaviour, whereas the neuron N2 with a sigmoid activation function generalizes the neural dynamics beyond the spiking case. c, SNUs ...
arXiv:1812.07040v2
fatcat:bbvknvrgzrcfzkge34nsapq5vy
Dynamic parallelism for synaptic updating in GPU-accelerated spiking neural network simulations
2018
Neurocomputing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Theoretical neuroscientists have exploited the use of general purpose computing on GPUs, in neural field model computations and spiking neural network simulations [2] . ...
The same problem exists in spiking neural network simulations on other parallel computing architectures [10]. ...
In terms of spiking neural network simulations, dynamic parallelism substantially accelerates the massive neural computations, by implementing the spike-triggered calculations at each synaptic updating ...
doi:10.1016/j.neucom.2018.04.007
pmid:30245550
pmcid:PMC6147227
fatcat:knhi4bij75b35m3ocnekjxtn4i
Modular Deconstruction Reveals the Dynamical and Physical Building Blocks of a Locomotion Motor Program
2015
Neuron
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
systems with richer, faster dynamics. ...
We computed an auto-correlogram A with 1 s bins up to a maximum lag of 20 s; the bin-size was chosen to be smaller than the characteristic timescale of the motor program in every recording ( Figure S1 ...
doi:10.1016/j.neuron.2015.03.005
pmid:25819612
pmcid:PMC6016739
fatcat:yfv53s2gqzcb3ntk74bv4io5oa
Programmable neuromorphic circuits for spike-based neural dynamics
2013
2013 IEEE 11th International New Circuits and Systems Conference (NEWCAS)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Hardware implementations of spiking neural networks offer promising solutions for a wide set of tasks, ranging from autonomous robotics to brain machine interfaces. ...
We propose a set of programmable hybrid analog/digital neuromorphic circuits than can be used to build compact low-power neural processing systems. ...
The chip implements a spiking neural network of 32 adaptive exponential Integrate-and-Fire (I&F) neuron circuits [16] with dynamic synapse circuits. ...
doi:10.1109/newcas.2013.6573600
dblp:conf/newcas/AzghadiMI13
fatcat:yh6dxsid2vfufe5kii445olehq
Recent Advances and New Frontiers in Spiking Neural Networks
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In recent years, spiking neural networks (SNNs) have received extensive attention in brain-inspired intelligence due to their rich spatially-temporal dynamics, various encoding methods, and event-driven ...
With the development of SNNs, brain-inspired intelligence, an emerging research field inspired by brain science achievements and aiming at artificial general intelligence, is becoming hot. ...
Acknowledgments This work was supported by the National Key R&D Program of China (2020AAA0104305), the Shanghai Municipal Science and Technology Major Project, and the Strategic Priority Research Program ...
arXiv:2204.07050v4
fatcat:zagxemwbtvdhtevycfdbie2r5q
Low-Power Neuromorphic Hardware for Signal Processing Applications
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Inspired by the time-encoding mechanism used by the brain, third generation spiking neural networks (SNNs) are being studied for building a new class of information processing engines. ...
Hence, novel computational architectures that address the von Neumann bottleneck are necessary in order to build systems that can implement SNNs with low energy budgets. ...
The chip has 128 neural cores, with each core having 1024 spiking neurons and 2 Mb SRAM to store the connectivity, configuration, and dynamic state of all neurons within the core. ...
arXiv:1901.03690v3
fatcat:34eavryprvdaxcvuteujwizeia
Large-scale spiking circuit simulation of spatio-temporal dynamics in superior colliculus
2014
BMC Neuroscience
Preserved Fulltext
The Internet Archive has a preservation copy of this work in our general collections.
The file type is application/pdf.
We present computational simulations of the intrinsic circuitry of the superior colliculus using large-scale spiking neural circuit models. ...
This contrasts with the motor-related intermediate layers ( Figure 1B) , whose response to stimulation was best explained by both spatial and temporal symmetry between inhibitory and excitatory neural ...
Acknowledgements R.V. is a GRF and IGERT; this research was supported by NSF GROW/JSPS Strategic Program. ...
doi:10.1186/1471-2202-15-s1-p4
pmcid:PMC4126475
fatcat:qt5ydrm73bhhfem3cahtt6ckse
« Previous
Showing results 1 — 15 out of 23,152 results