publication . Article . 2013

Anisotropic connectivity implements motion-based prediction in a spiking neural network

Kaplan B.A.; Lansner A.; Masson G.S.; Perrinet L.U.;
Open Access English
  • Published: 01 Jan 2013
  • Publisher: HAL CCSD
Abstract
International audience; Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the world. Although it is becoming generally accepted, it is not clear on which level spiking neural networks may implement predictive coding and what function their connectivity may have. We present a network model of conductance-based integrate-and-fire neurons inspired by the architecture of retinotopic cortical areas that assumes predictive coding is implemented through network connectivity, namely in the connection delays and in selectiveness for the tuning properties of source and target cells. We show tha...
Subjects
arXiv: Quantitative Biology::Neurons and Cognition
free text keywords: Bioinformatics (Computational Biology), Bioinformatik (beräkningsbiologi), Neurosciences, Neurovetenskaper, large-scale neuromorphic systems, motion detection, motion extrapolation, network of spiking neurons, predictive coding, probabilistic representation, [SHS]Humanities and Social Sciences, [SDV]Life Sciences [q-bio], [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neuroscience, Original Research Article, Cellular and Molecular Neuroscience, Neuroscience (miscellaneous), Decoding methods, Random neural network, Trajectory, Spiking neural network, Network model, Computer science, Probabilistic logic, Artificial intelligence, business.industry, business, Anisotropy, Machine learning, computer.software_genre, computer
Funded by
EC| BRAINSCALES
Project
BRAINSCALES
Brain-inspired multiscale computation in neuromorphic hybrid systems
  • Funder: European Commission (EC)
  • Project Code: 269921
  • Funding stream: FP7 | SP1 | ICT
,
EC| FACETS-ITN
Project
FACETS-ITN
Fast Analog Computing with Emergent Transient States - Initial Training Network (FACETS-ITN)
  • Funder: European Commission (EC)
  • Project Code: 237955
  • Funding stream: FP7 | SP3 | PEOPLE
Communities
FET FP7FET Proactive: FET proactive 8: Brain Inspired ICT
FET FP7FET Proactive: Brain-inspired multiscale computation in neuromorphic hybrid systems
73 references, page 1 of 5

Adams R. A.Perrinet L. U.Friston K. (2012). Smooth pursuit and visual occlusion: active inference and oculomotor control in schizophrenia. PLoS ONE 7:e47502 10.1371/journal.pone.0047502 23110076 [OpenAIRE] [PubMed] [DOI]

Albright T. D.Desimone R.Gross C. G. (1984). Columnar organization of directionally selective cells in visual area MT of the macaque. J. Neurophysiol. 51, 16–31 6693933 [OpenAIRE] [PubMed]

Allman J.Kaas J.Lane R. (1973). The middle temporal visual area (MT) in the bushbaby,Galago senegalensis. Brain Res. 57, 197–202 10.1016/0006-8993(73)90576-3 4197774 [OpenAIRE] [PubMed] [DOI]

Assad J. A.Maunsell J. H. R. (1995). Neuronal correlates of inferred motion in primate posterior parietal cortex. Nature 373, 518–521 10.1038/373518a0 7845463 [OpenAIRE] [PubMed] [DOI]

Baldo M. V. C.Caticha N. (2005). Computational neurobiology of the flash-lag effect. Vision Res. 45, 2620–2630 10.1016/j.visres.2005.04.014 15993457 [OpenAIRE] [PubMed] [DOI]

Beck J. M.Ma W. J.Kiani R.Hanks T.Churchland A. K.Roitman J. (2008). Probabilistic population codes for bayesian decision making. Neuron 60, 1142–1152 10.1016/j.neuron.2008.09.021 19109917 [OpenAIRE] [PubMed] [DOI]

Bennett S. J.Barnes G. R. (2003). Human ocular pursuit during the transient disappearance of a visual target. J. Neurophysiol. 90, 2504–2520 10.1152/jn.01145.2002 14534275 [OpenAIRE] [PubMed] [DOI]

Berry M. J.Brivanlou I. H.Jordan T. A.Meister M. (1999). Anticipation of moving stimuli by the retina. Nature 398, 334–338 10.1038/18678 10192333 [OpenAIRE] [PubMed] [DOI]

Bogadhi A. R.Montagnini A.Masson G. S. (2011). Interaction between retinal and extra retinal signals in dynamic motion integration for smooth pursuit. J. Vis. 11:533 10.1167/11.11.533 [OpenAIRE] [DOI]

Bosking W. H.Zhang Y.Schofield B.Fitzpatrick D. (1997). Orientation selectivity and the arrangement of horizontal connections in tree shrew striate cortex. J. Neurosci. 17, 2112–2127 9045738 [OpenAIRE] [PubMed]

Bressloff P. C. (2001). Traveling fronts and wave propagation failure in an inhomogeneous neural network. Physica D 155, 83–100 10.1016/S0167-2789(01)00266-4 14611379 [OpenAIRE] [PubMed] [DOI]

Bressloff P. C.Coombes S. (1998). Traveling waves in a chain of Pulse-Coupled oscillators. Phys. Rev. Lett. 80, 4815–4818 10.1103/PhysRevLett.80.4815 [OpenAIRE] [DOI]

Bringuier V.Chavane F.Glaeser L.Frégnac Y. (1999). Horizontal propagation of visual activity in the synaptic integration field of area 17 neurons. Science 283, 695–699 10.1126/science.283.5402.695 9924031 [OpenAIRE] [PubMed] [DOI]

Brüderle D.Petrovici M.Vogginger B.Ehrlich M.Pfeil T.Millner S. (2011). A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems. Biol. Cybern. 104, 263–296 10.1007/s00422-011-0435-9 21618053 [OpenAIRE] [PubMed] [DOI]

Brunel N. (2000). Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. J. Comput. Neurosci. 8, 183–208 10.1023/A:1008925309027 10809012 [PubMed] [DOI]

73 references, page 1 of 5
Abstract
International audience; Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the world. Although it is becoming generally accepted, it is not clear on which level spiking neural networks may implement predictive coding and what function their connectivity may have. We present a network model of conductance-based integrate-and-fire neurons inspired by the architecture of retinotopic cortical areas that assumes predictive coding is implemented through network connectivity, namely in the connection delays and in selectiveness for the tuning properties of source and target cells. We show tha...
Subjects
arXiv: Quantitative Biology::Neurons and Cognition
free text keywords: Bioinformatics (Computational Biology), Bioinformatik (beräkningsbiologi), Neurosciences, Neurovetenskaper, large-scale neuromorphic systems, motion detection, motion extrapolation, network of spiking neurons, predictive coding, probabilistic representation, [SHS]Humanities and Social Sciences, [SDV]Life Sciences [q-bio], [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neuroscience, Original Research Article, Cellular and Molecular Neuroscience, Neuroscience (miscellaneous), Decoding methods, Random neural network, Trajectory, Spiking neural network, Network model, Computer science, Probabilistic logic, Artificial intelligence, business.industry, business, Anisotropy, Machine learning, computer.software_genre, computer
Funded by
EC| BRAINSCALES
Project
BRAINSCALES
Brain-inspired multiscale computation in neuromorphic hybrid systems
  • Funder: European Commission (EC)
  • Project Code: 269921
  • Funding stream: FP7 | SP1 | ICT
,
EC| FACETS-ITN
Project
FACETS-ITN
Fast Analog Computing with Emergent Transient States - Initial Training Network (FACETS-ITN)
  • Funder: European Commission (EC)
  • Project Code: 237955
  • Funding stream: FP7 | SP3 | PEOPLE
Communities
FET FP7FET Proactive: FET proactive 8: Brain Inspired ICT
FET FP7FET Proactive: Brain-inspired multiscale computation in neuromorphic hybrid systems
73 references, page 1 of 5

Adams R. A.Perrinet L. U.Friston K. (2012). Smooth pursuit and visual occlusion: active inference and oculomotor control in schizophrenia. PLoS ONE 7:e47502 10.1371/journal.pone.0047502 23110076 [OpenAIRE] [PubMed] [DOI]

Albright T. D.Desimone R.Gross C. G. (1984). Columnar organization of directionally selective cells in visual area MT of the macaque. J. Neurophysiol. 51, 16–31 6693933 [OpenAIRE] [PubMed]

Allman J.Kaas J.Lane R. (1973). The middle temporal visual area (MT) in the bushbaby,Galago senegalensis. Brain Res. 57, 197–202 10.1016/0006-8993(73)90576-3 4197774 [OpenAIRE] [PubMed] [DOI]

Assad J. A.Maunsell J. H. R. (1995). Neuronal correlates of inferred motion in primate posterior parietal cortex. Nature 373, 518–521 10.1038/373518a0 7845463 [OpenAIRE] [PubMed] [DOI]

Baldo M. V. C.Caticha N. (2005). Computational neurobiology of the flash-lag effect. Vision Res. 45, 2620–2630 10.1016/j.visres.2005.04.014 15993457 [OpenAIRE] [PubMed] [DOI]

Beck J. M.Ma W. J.Kiani R.Hanks T.Churchland A. K.Roitman J. (2008). Probabilistic population codes for bayesian decision making. Neuron 60, 1142–1152 10.1016/j.neuron.2008.09.021 19109917 [OpenAIRE] [PubMed] [DOI]

Bennett S. J.Barnes G. R. (2003). Human ocular pursuit during the transient disappearance of a visual target. J. Neurophysiol. 90, 2504–2520 10.1152/jn.01145.2002 14534275 [OpenAIRE] [PubMed] [DOI]

Berry M. J.Brivanlou I. H.Jordan T. A.Meister M. (1999). Anticipation of moving stimuli by the retina. Nature 398, 334–338 10.1038/18678 10192333 [OpenAIRE] [PubMed] [DOI]

Bogadhi A. R.Montagnini A.Masson G. S. (2011). Interaction between retinal and extra retinal signals in dynamic motion integration for smooth pursuit. J. Vis. 11:533 10.1167/11.11.533 [OpenAIRE] [DOI]

Bosking W. H.Zhang Y.Schofield B.Fitzpatrick D. (1997). Orientation selectivity and the arrangement of horizontal connections in tree shrew striate cortex. J. Neurosci. 17, 2112–2127 9045738 [OpenAIRE] [PubMed]

Bressloff P. C. (2001). Traveling fronts and wave propagation failure in an inhomogeneous neural network. Physica D 155, 83–100 10.1016/S0167-2789(01)00266-4 14611379 [OpenAIRE] [PubMed] [DOI]

Bressloff P. C.Coombes S. (1998). Traveling waves in a chain of Pulse-Coupled oscillators. Phys. Rev. Lett. 80, 4815–4818 10.1103/PhysRevLett.80.4815 [OpenAIRE] [DOI]

Bringuier V.Chavane F.Glaeser L.Frégnac Y. (1999). Horizontal propagation of visual activity in the synaptic integration field of area 17 neurons. Science 283, 695–699 10.1126/science.283.5402.695 9924031 [OpenAIRE] [PubMed] [DOI]

Brüderle D.Petrovici M.Vogginger B.Ehrlich M.Pfeil T.Millner S. (2011). A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems. Biol. Cybern. 104, 263–296 10.1007/s00422-011-0435-9 21618053 [OpenAIRE] [PubMed] [DOI]

Brunel N. (2000). Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. J. Comput. Neurosci. 8, 183–208 10.1023/A:1008925309027 10809012 [PubMed] [DOI]

73 references, page 1 of 5
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publication . Article . 2013

Anisotropic connectivity implements motion-based prediction in a spiking neural network

Kaplan B.A.; Lansner A.; Masson G.S.; Perrinet L.U.;