| | Models |
| 1. |
Impact of Small Time Delays on the Onset of Oscillations and Synchrony (Al-Darabsah et al 2021)
|
| 2. |
A basal ganglia model of aberrant learning (Ursino et al. 2018)
|
| 3. |
A bistable model of Spike-Wave seizure and background activity (Taylor et al. 2014)
|
| 4. |
A Computational Model for the Binocular Vector Disparity Estimation (Chessa & Solari 2018)
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| 5. |
A computational model of a small DRG neuron to explore pain (Verma et al. 2019, 2020)
|
| 6. |
A computational model of action selection in the basal ganglia (Suryanarayana et al 2019)
|
| 7. |
A computational model of single-neuron perturbations (Sadeh and Clopath 2020)
|
| 8. |
A cortical sheet mesoscopic model for investigating focal seizure onset dynamics (Wang et al. 2014)
|
| 9. |
A detailed data-driven network model of prefrontal cortex (Hass et al 2016)
|
| 10. |
A generic MAPK cascade model for random parameter sampling analysis (Mai and Liu 2013)
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| 11. |
A kinetic model unifying presynaptic short-term facilitation and depression (Lee et al. 2009)
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| 12. |
A mathematical model of a neurovascular unit (Dormanns et al 2015, 2016) (Farrs & David 2011)
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| 13. |
A mathematical model of evoked calcium dynamics in astrocytes (Handy et al 2017)
|
| 14. |
A microcircuit model of the frontal eye fields (Heinzle et al. 2007)
|
| 15. |
A model of local field potentials generated by medial superior olive neurons (Goldwyn et al 2014)
|
| 16. |
A model of neurovascular coupling and the BOLD response (Mathias et al 2017, Kenny et al 2018)
|
| 17. |
A model of working memory for encoding multiple items (Ursino et al, in press)
|
| 18. |
A modified Morris-Lecar model with gM and gAHP (Yang et al., 2022)
|
| 19. |
A modified Morris-Lecar with TRPC4 & GIRK (Tian et al. 2022)
|
| 20. |
A multiphysics neuron model for cellular volume dynamics (Lee et al. 2011)
|
| 21. |
A Neural mass computational model of the Thalamocorticothalamic circuitry (Bhattacharya et al. 2011)
|
| 22. |
A neural mass model for critical assessment of brain connectivity (Ursino et al 2020)
|
| 23. |
A neural model of Parkinson`s disease (Cutsuridis and Perantonis 2006, Cutsuridis 2006, 2007)
|
| 24. |
A neuronal circuit simulator for non Monte Carlo analysis of neuronal noise (Kilinc & Demir 2018)
|
| 25. |
A simulation method for the firing sequences of motor units (Jiang et al 2006)
|
| 26. |
A spatially extended model for macroscopic spike-wave discharges (Taylor and Baier 2011)
|
| 27. |
A spiking model of cortical broadcast and competition (Shanahan 2008)
|
| 28. |
A state-space model to quantify common input to motor neurons (Feeney et al 2017)
|
| 29. |
A two-layer biophysical olfactory bulb model of cholinergic neuromodulation (Li and Cleland 2013)
|
| 30. |
Acetylcholine-modulated plasticity in reward-driven navigation (Zannone et al 2018)
|
| 31. |
ACh modulation in olfactory bulb and piriform cortex (de Almeida et al. 2013;Devore S, et al. 2014)
|
| 32. |
Activator protein 1(AP-1) transcriptional regulatory model in brainstem neurons (Makadia et al 2015)
|
| 33. |
Active intrinsic conductances in networks, transients, activity, plasticity (Akosy and Shouval 2021)
|
| 34. |
Activity dependent changes in dendritic spine density and spine structure (Crook et al. 2007)
|
| 35. |
Adaptation of Short-Term Plasticity parameters (Esposito et al. 2015)
|
| 36. |
Ambiguous Encoding and Distorted Perception (Carlson and Kawasaki 2006)
|
| 37. |
An oscillatory neural autoencoder based on frequency modulation and multiplexing (Soman et al 2018)
|
| 38. |
Artificial neuron model (Izhikevich 2003, 2004, 2007)
|
| 39. |
Astrocyte and Blood Vessel Calcium Imaging Tracking code (Haidey et al 2021)
|
| 40. |
Auditory nerve model for predicting performance limits (Heinz et al 2001)
|
| 41. |
Auditory nerve model with linear tuning (Heinz et al 2001)
|
| 42. |
Auditory nerve response model (Tan, Carney 2003)
|
| 43. |
Axon growth model (Diehl et al. 2016)
|
| 44. |
Axonal HH-model for temperature stimulation (Fribance et al 2016)
|
| 45. |
Balance of excitation and inhibition (Carvalho and Buonomano 2009)
|
| 46. |
Basal Ganglia and Levodopa Pharmacodynamics model for parameter estimation in PD (Ursino et al 2020)
|
| 47. |
Basal ganglia motor function and the inverse kinematics calculation (Salimi-Badr et al 2017)
|
| 48. |
Basal ganglia-corticothalamic (BGCT) network (Chen et al., 2014)
|
| 49. |
Basal ganglia-thalamic network model for deep brain stimulation (So et al. 2012)
|
| 50. |
Basal ganglia-thalamocortical loop model of action selection (Humphries and Gurney 2002)
|
| 51. |
Binocular energy model set for binocular neurons in optic lobe of praying mantis (Rosner et al 2019)
|
| 52. |
BK - CaV coupling (Montefusco et al. 2017)
|
| 53. |
Breakdown of accmmodation in nerve: a possible role for INAp (Hennings et al 2005)
|
| 54. |
Bump Attractor Models: Delayed Response & Recognition Span - spatial condition (Ibanez et al 2019)
|
| 55. |
Burst and tonic firing behaviour in subfornical organ (SFO) neurons (Medlock et al 2018)
|
| 56. |
Bursting and oscillations in RD1 Retina driven by AII Amacrine Neuron (Choi et al. 2014)
|
| 57. |
CA1 pyramidal cells, basket cells, ripples (Malerba et al 2016)
|
| 58. |
CA1 pyramidal neuron dendritic spine with plasticity (O`Donnell et al. 2011)
|
| 59. |
CA1 pyramidal: Stochastic amplification of KCa in Ca2+ microdomains (Stanley et al. 2011)
|
| 60. |
CA3 Radiatum/Lacunosum-Moleculare interneuron, Ih (Anderson et al. 2011)
|
| 61. |
Calyx of Held, short term plasticity (Yang Z et al. 2009)
|
| 62. |
Cancelling redundant input in ELL pyramidal cells (Bol et al. 2011)
|
| 63. |
Cardiac models of circadian rhythms in early afterdepolarizations & arrhythmias (Diekman & Wei 2021)
|
| 64. |
Cell signaling/ion channel variability effects on neuronal response (Anderson, Makadia, et al. 2015)
|
| 65. |
Central Nervous System tadpole model in Matlab and NEURON-Python (Ferrario et al, 2021)
|
| 66. |
Cholinergic and nicotinic regulation of DA neuron firing (Morozova et al 2020)
|
| 67. |
Circadian clock model based on protein sequestration (simple version) (Kim & Forger 2012)
|
| 68. |
Circadian clock model in mammals (detailed version) (Kim & Forger 2012)
|
| 69. |
Coding explains development of binocular vision and its failure in Amblyopia (Eckmann et al 2020)
|
| 70. |
Coincidence detection in MSO principal cells (Goldwyn et al. 2019)
|
| 71. |
Combination sensitivity and active conductances (Carlson and Kawasaki 2006)
|
| 72. |
Comparing correlation responses to motion estimation models (Salazar-Gatzimas et al. 2016)
|
| 73. |
Competing oscillator 5-cell circuit and Parameterscape plotting (Gutierrez et al. 2013)
|
| 74. |
Composite spiking network/neural field model of Parkinsons (Kerr et al 2013)
|
| 75. |
Computational endophenotypes in addiction (Fiore et al 2018)
|
| 76. |
Computational modeling of ultrasonic Subthalamic Nucleus stimulation (Tarnaud et al 2019)
|
| 77. |
Computational modelling of channelrhodopsin-2 photocurrent characteristics (Stefanescu et al. 2013)
|
| 78. |
Conditions for synaptic specificity in maintenance phase of synaptic plasticity (Huertas et al, '22)
|
| 79. |
CONFIGR: a vision-based model for long-range figure completion (Carpenter et al. 2007)
|
| 80. |
Continuous time stochastic model for neurite branching (van Elburg 2011)
|
| 81. |
Continuum model of tubulin-driven neurite elongation (Graham et al 2006)
|
| 82. |
Convergence regulates synchronization-dependent AP transfer in feedforward NNs (Sailamul et al 2017)
|
| 83. |
Core respiratory network organization: Insights from optogenetics and modeling (Ausborn et al 2018)
|
| 84. |
Cortex-Basal Ganglia-Thalamus network model (Kumaravelu et al. 2016)
|
| 85. |
Cortico - Basal Ganglia Loop (Mulcahy et al 2020)
|
| 86. |
Cortico-striatal plasticity in medium spiny neurons (Gurney et al 2015)
|
| 87. |
Decoding movement trajectory from simulated grid cell population activity (Bush & Burgess 2019)
|
| 88. |
Deep belief network learns context dependent behavior (Raudies, Zilli, Hasselmo 2014)
|
| 89. |
Dendritic Na inactivation drives a decrease in ISI (Fernandez et al 2005)
|
| 90. |
Dendritic properties control energy efficiency of APs in cortical pyramidal cells (Yi et al 2017)
|
| 91. |
Detailed analysis of trajectories in the Morris water maze (Gehring et al. 2015)
|
| 92. |
Development and Binocular Matching of Orientation Selectivity in Visual Cortex (Xu et al 2020)
|
| 93. |
Dipole Localization Kit (Mechler & Victor, 2012)
|
| 94. |
Direct recruitment of S1 pyramidal cells and interneurons via ICMS (Overstreet et al., 2013)
|
| 95. |
Disentangling astroglial physiology with a realistic cell model in silico (Savtchenko et al 2018)
|
| 96. |
Distributed cerebellar plasticity implements adaptable gain control (Garrido et al., 2013)
|
| 97. |
Distributed representation of perceptual categories in the auditory cortex (Kim and Bao 2008)
|
| 98. |
Distributed synaptic plasticity and spike timing (Garrido et al. 2013)
|
| 99. |
Distributed working memory in large-scale macaque brain model (Mejias and Wang, 2022)
|
| 100. |
Dopamine-modulated medium spiny neuron, reduced model (Humphries et al. 2009)
|
| 101. |
Drosophila 3rd instar larval aCC motoneuron (Gunay et al. 2015)
|
| 102. |
Drosophila circadian clock neurone model of essential tremor (Smith et al 2018)
|
| 103. |
Drosophila lateral ventral clock neuron (LNV) model (Smith et al 2019)
|
| 104. |
E-I balance modulates formation and dynamics of neuronal assemblies (Sadeh and Clopath, 2021)
|
| 105. |
Effect of circuit structure on odor representation in insect olfaction (Rajagopalan & Assisi 2020)
|
| 106. |
Effect of cortical D1 receptor sensitivity on working memory maintenance (Reneaux & Gupta 2018)
|
| 107. |
Effect of ionic diffusion on extracellular potentials (Halnes et al 2016)
|
| 108. |
Effects of the membrane AHP on the Lateral Superior Olive (LSO) (Zhou & Colburn 2010)
|
| 109. |
Efficient estimation of detailed single-neuron models (Huys et al. 2006)
|
| 110. |
Electrical activity of the suprachiasmatic nuclei (Stinchcombe et al. 2017)
|
| 111. |
Electrodiffusive astrocytic and extracellular ion concentration dynamics model (Halnes et al. 2013)
|
| 112. |
Elementary mechanisms producing facilitation of Cav2.1 (P/Q-type) channels
|
| 113. |
ELL pyramidal neuron (Simmonds and Chacron 2014)
|
| 114. |
Emergence of Connectivity Motifs in Networks of Model Neurons (Vasilaki, Giugliano 2014)
|
| 115. |
Entrainment and divisive inhibition in a neocortical neural mass model (Papasavvas et al 2020)
|
| 116. |
Ephaptic coupling in passive cable and MSO neuron models (Goldwyn & Rinzel 2016)
|
| 117. |
Epileptic seizure model with Morris-Lecar neurons (Beverlin and Netoff 2011)
|
| 118. |
Estimation of conductance in a conductance-based model of quadratic type (Vich & Guillamon 2015)
|
| 119. |
Exact mean-field models for Izhikevich networks (Chen and Campbell 2022)
|
| 120. |
Excessive beta oscillations in Parkinson's disease (Pavlides et al. 2015)
|
| 121. |
Excitability of DA neurons and their regulation by synaptic input (Morozova et al. 2016a, 2016b)
|
| 122. |
Excitation Properties of Computational Models of Unmyelinated Peripheral Axons (Pelot et al., 2021)
|
| 123. |
Excitation-contraction coupling in an integrative heart cell model (Greenstein et al 2006)
|
| 124. |
Excitotoxic loss of dopaminergic cells in PD (Muddapu et al 2019)
|
| 125. |
External Tufted Cell Model (Ryan Viertel, Alla Borisyuk 2019)
|
| 126. |
Extracellular Action Potential Simulations (Gold et al 2007)
|
| 127. |
Extraction and classification of three cortical neuron types (Mensi et al. 2012)
|
| 128. |
Failure of Deep Brain Stimulation in a basal ganglia neuronal network model (Dovzhenok et al. 2013)
|
| 129. |
Fast population coding (Huys et al. 2007)
|
| 130. |
Fast Spiking Basket cells (Tzilivaki et al 2019)
|
| 131. |
Feature integration drives probabilistic behavior in Fly escape response (von Reyn et al 2017)
|
| 132. |
FFV1MT: A V1-MT feedforward architecture for optical flow estimation (Solari et a., 2015)
|
| 133. |
Fisher and Shannon information in finite neural populations (Yarrow et al. 2012)
|
| 134. |
Fitting predictive coding to the neurophysiological data (Spratling 2019)
|
| 135. |
Fractional leaky integrate-and-fire model (Teka et al. 2014)
|
| 136. |
FRAT: An amygdala-centered model of fear conditioning (Krasne et al. 2011)
|
| 137. |
Function and energy constrain neuronal biophysics in coincidence detection (Remme et al 2018)
|
| 138. |
Gap junction coupled network of striatal fast spiking interneurons (Hjorth et al. 2009)
|
| 139. |
Generation of granule cell dendritic morphology (Schneider et al. 2014)
|
| 140. |
Generation of stable heading representations in diverse visual scenes (Kim et al 2019)
|
| 141. |
Generic Bi-directional Real-time Neural Interface (Zrenner et al. 2010)
|
| 142. |
Graph-theoretical Derivation of Brain Structural Connectivity (Giacopelli et al 2020)
|
| 143. |
Grid cell model with compression effects (Raudies & Hasselmo, 2015)
|
| 144. |
Grid cell oscillatory interference with noisy network oscillators (Zilli and Hasselmo 2010)
|
| 145. |
Grid cell spatial firing models (Zilli 2012)
|
| 146. |
Grid cells from place cells (Castro & Aguiar, 2014)
|
| 147. |
Hebbian learning in a random network for PFC modeling (Lindsay, et al. 2017)
|
| 148. |
Hebbian STDP for modelling the emergence of disparity selectivity (Chauhan et al 2018)
|
| 149. |
HH model neuron of the Suprachiasmatic Nucleus including a persistent Na+ channel (Paul et al 2016)
|
| 150. |
HH model of SCN neurons including a transient K+ channel (Bano-Otalora et al 2021)
|
| 151. |
Hierarchical anti-Hebbian network model for the formation of spatial cells in 3D (Soman et al 2019)
|
| 152. |
Hierarchical Gaussian Filter (HGF) model of conditioned hallucinations task (Powers et al 2017)
|
| 153. |
Hippocampal CA3 network and circadian regulation (Stanley et al. 2013)
|
| 154. |
Hippocampal spiking model for context dependent behavior (Raudies & Hasselmo 2014)
|
| 155. |
Hodgkin–Huxley model with fractional gating (Teka et al. 2016)
|
| 156. |
Homeostatic synaptic plasticity (Rabinowitch and Segev 2006a,b)
|
| 157. |
Hotspots of dendritic spine turnover facilitates new spines and NN sparsity (Frank et al 2018)
|
| 158. |
Human auditory periphery model: cochlea, IHC-AN, auditory brainstem responses (Verhulst et al 2018)
|
| 159. |
Human sleep-wake regulatory network model (Gleit et al 2013, Booth et al 2017)
|
| 160. |
Human tactile FA1 neurons (Hay and Pruszynski 2020)
|
| 161. |
Hybrid oscillatory interference / continuous attractor NN of grid cell firing (Bush & Burgess 2014)
|
| 162. |
Hyperbolic model (Daneshzand et al 2017)
|
| 163. |
Hyperconnectivity, slow synapses in PFC mental retardation and autism model (Testa-Silva et al 2011)
|
| 164. |
I&F recurrent networks with current- or conductance-based synapses (Cavallari et al. 2014)
|
| 165. |
IA and IT interact to set first spike latency (Molineux et al 2005)
|
| 166. |
Impact of dendritic size and topology on pyramidal cell burst firing (van Elburg and van Ooyen 2010)
|
| 167. |
INa and IKv4.3 heterogeneity in canine LV myocytes (Flaim et al 2006)
|
| 168. |
Inferring connection proximity in electrically coupled networks (Cali et al. 2007)
|
| 169. |
Inhibition perturbations reveals dynamical structure of neural processing (Sadeh & Clopath 2020)
|
| 170. |
Inhibitory control of motoneuron excitability (Venugopal et al 2011)
|
| 171. |
Inhibitory plasticity balances excitation and inhibition (Vogels et al. 2011)
|
| 172. |
Inner hair cell auditory nerve synapse model (Deligeorges, Mountain 1997)
|
| 173. |
Input strength and time-varying oscillation peak frequency (Cohen MX 2014)
|
| 174. |
Inverse stochastic resonance of cerebellar Purkinje cell (Buchin et al. 2016)
|
| 175. |
Investigation of different targets in deep brain stimulation for Parkinson`s (Pirini et al. 2009)
|
| 176. |
Irregular spiking in NMDA-driven prefrontal cortex neurons (Durstewitz and Gabriel 2006)
|
| 177. |
L5 cortical neurons with recreated synaptic inputs in vitro correlation transfer (Linaro et al 2019)
|
| 178. |
L5 pyr. cell spiking control by oscillatory inhibition in distal apical dendrites (Li et al 2013)
|
| 179. |
Laminar analysis of excitatory circuits in vibrissal motor and sensory cortex (Hooks et al. 2011)
|
| 180. |
Laminar connectivity matrix simulation (Weiler et al 2008)
|
| 181. |
Large-scale laminar model of macaque cortex (Mejias et al 2016)
|
| 182. |
Lateral dendrodenditic inhibition in the Olfactory Bulb (David et al. 2008)
|
| 183. |
Layer 5 Pyramidal Neuron (Shai et al., 2015)
|
| 184. |
Layer-specific pyramidal cell props underlie diverse ACC motor + limbic networks (Medalla et al '21)
|
| 185. |
Leaky integrate-and-fire model of spike frequency adaptation in the LGMD (Gabbiani and Krapp 2006)
|
| 186. |
Learning intrinsic excitability in Medium Spiny Neurons (Scheler 2014)
|
| 187. |
Learning spatiotemporal sequences using recurrent spiking NN that discretizes time (Maes et al 2020)
|
| 188. |
Leech Heart Interneuron model (Sharma et al 2020)
|
| 189. |
Levodopa-Induced Toxicity in Parkinson's Disease (Muddapu et al, 2022)
|
| 190. |
LGMD Variability and logarithmic compression in dendrites (Jones and Gabbiani, 2012, 2012B)
|
| 191. |
LGNcircuit: Minimal LGN network model of temporal processing of visual input (Norheim et al. 2012)
|
| 192. |
Lillie Transition: onset of saltatory conduction in myelinating axons (Young et al. 2013)
|
| 193. |
Linking STDP and Dopamine action to solve the distal reward problem (Izhikevich 2007)
|
| 194. |
Logarithmic distributions prove that intrinsic learning is Hebbian (Scheler 2017)
|
| 195. |
M1 and M4 intrinsically photosensitive retinal ganglion cells (Stinchcombe et al. 2021)
|
| 196. |
Macroscopic model of epilepsy (Fietkiewicz & Loparo 2016)
|
| 197. |
Markov Chain-based Stochastic Shielding Hodgkin Huxley Model (Schmandt, Galan 2012)
|
| 198. |
Mathematical model for windup (Aguiar et al. 2010)
|
| 199. |
Mathematical model of behavioral time scale plasticity (BTSP) of place fields (Shouval & Cone 2021)
|
| 200. |
Maximum entropy model to predict spatiotemporal spike patterns (Marre et al. 2009)
|
| 201. |
Mean Field Equations for Two-Dimensional Integrate and Fire Models (Nicola and Campbell, 2013)
|
| 202. |
Mean-field systems and small scale neural networks (Ferguson et al. 2015)
|
| 203. |
Mechanisms of magnetic stimulation of central nervous system neurons (Pashut et al. 2011)
|
| 204. |
Mechanisms underlying different onset patterns of focal seizures (Wang Y et al 2017)
|
| 205. |
Medial reticular formation of the brainstem: anatomy and dynamics (Humphries et al. 2006, 2007)
|
| 206. |
Memory savings through unified pre- and postsynaptic STDP (Costa et al 2015)
|
| 207. |
Method for deriving general HH neuron model`s spiking input-output relation (Soudry & Meir 2014)
|
| 208. |
Microglial cytokine network (Anderson et al., 2015)
|
| 209. |
Microsaccades and synchrony coding in the retina (Masquelier et al. 2016)
|
| 210. |
Midbrain torus semicircularis neuron model (Aumentado-Armstrong et al. 2015)
|
| 211. |
Model for concentration invariant odor coding based on primacy hypothesis (Wilson et al 2017)
|
| 212. |
Model of AngII signaling and membrane electrophysiology (Makadia, Anderson, Fey et al., 2015)
|
| 213. |
Model of calcium oscillations in olfactory cilia (Reidl et al. 2006)
|
| 214. |
Model of cerebellar parallel fiber-Purkinje cell LTD and LTP (Gallimore et al 2018)
|
| 215. |
Model of cochlear membrane adapted (Peterson, Bogert 1950)
|
| 216. |
Model of long range transmission of gamma oscillation (Murray 2007)
|
| 217. |
Model of the Xenopus tadpole swimming spinal network (Roberts et al. 2014)
|
| 218. |
Model of working memory based on negative derivative feedback (Lim and Goldman, 2013)
|
| 219. |
Model predictive control model for an isometric motor task (Ueyama 2017)
|
| 220. |
Modeling and MEG evidence of early consonance processing in auditory cortex (Tabas et al 2019)
|
| 221. |
Modeling extracellular electrical stimulation (Tahayori et al. 2012)
|
| 222. |
Modeling hebbian and homeostatic plasticity (Toyoizumi et al. 2014)
|
| 223. |
Modelling enteric neuron populations and muscle fed-state motor patterns (Chambers et al. 2011)
|
| 224. |
Modelling gain modulation in stability-optimised circuits (Stroud et al 2018)
|
| 225. |
Models for cortical UP-DOWN states in a bistable inhibitory-stabilized network (Jercog et al 2017)
|
| 226. |
Models of Vector Navigation with Grid Cells (Bush et al., 2015)
|
| 227. |
Motoneuron model of self-sustained firing after spinal cord injury (Kurian et al. 2011)
|
| 228. |
Motoneuron simulations for counting motor units (Major and Jones 2005)
|
| 229. |
Motor Cortex Connectivity & Event Related Desynchronization Based on Neural Mass Models (Ursino 21)
|
| 230. |
Multifunctional control of feeding in Aplysia (Webster-Wood et al. 2020)
|
| 231. |
Multiple mechanisms of short term plasticity at the calyx of Held (Hennig et al. 2008)
|
| 232. |
Multiple modes of inner hair cell stimulation (Mountain, Cody 1999)
|
| 233. |
Multiscale model of excitotoxicity in PD (Muddapu and Chakravarthy 2020)
|
| 234. |
Multisensory integration in the superior colliculus: a neural network model (Ursino et al. 2009)
|
| 235. |
Neocort. pyramidal cells subthreshold somatic voltage controls spike propagation (Munro Kopell 2012)
|
| 236. |
Network model of movement disorders (Yousif et al 2020)
|
| 237. |
Network models of frequency modulated sweep detection (Skorheim et al. 2014)
|
| 238. |
Neural mass model based on single cell dynamics to model pathophysiology (Zandt et al 2014)
|
| 239. |
Neural Mass Model for relationship between Brain Rhythms + Functional Connectivity (Ricci et al '21)
|
| 240. |
Neural mass model of the sleeping cortex (Weigenand et al 2014)
|
| 241. |
Neural model of frog ventilatory rhythmogenesis (Horcholle-Bossavit and Quenet 2009)
|
| 242. |
Neural transformations on spike timing information (Tripp and Eliasmith 2007)
|
| 243. |
Neural-field model of generalized seizures (Zhao et al., 2015)
|
| 244. |
Neurogenesis in the olfactory bulb controlled by top-down input (Adams et al 2018)
|
| 245. |
Non-Weak E-Fields Pyramidal Neurons (Reznik et. al.,2015)
|
| 246. |
Norns - Neural Network Studio (Visser & Van Gils 2014)
|
| 247. |
Numerical Integration of Izhikevich and HH model neurons (Stewart and Bair 2009)
|
| 248. |
Odor supported place cell model and goal navigation in rodents (Kulvicius et al. 2008)
|
| 249. |
Olfactory bulb juxtaglomerular models (Carey et al., 2015)
|
| 250. |
Olfactory Bulb mitral-granule network generates beta oscillations (Osinski & Kay 2016)
|
| 251. |
Olfactory bulb network: neurogenetic restructuring and odor decorrelation (Chow et al. 2012)
|
| 252. |
Olfactory receptor neuron model (Dougherty et al 2005)
|
| 253. |
Opponent-channel model of the cortical representation of auditory space (Briley et al., 2012)
|
| 254. |
Optimal Localist and Distributed Coding Through STDP (Masquelier & Kheradpisheh 2018)
|
| 255. |
Optimal spatiotemporal spike pattern detection by STDP (Masquelier 2017)
|
| 256. |
Origin of heterogeneous spiking patterns in spinal dorsal horn neurons (Balachandar & Prescott 2018)
|
| 257. |
Oscillating neurons in the cochlear nucleus (Bahmer Langner 2006a, b, and 2007)
|
| 258. |
Oscillation and coding in a proposed NN model of insect olfaction (Horcholle-Bossavit et al. 2007)
|
| 259. |
Oscillations emerging from noise-driven NNs (Tchumatchenko & Clopath 2014)
|
| 260. |
Oversampling method to extract excitatory and inhibitory conductances (Bedard et al. 2012)
|
| 261. |
Pancreatic Beta Cell signalling pathways (Fridlyand & Philipson 2016) (MATLAB)
|
| 262. |
Parallel cortical inhibition processing enables context-dependent behavior (Kuchibhotla et al. 2016)
|
| 263. |
Parameter estimation for Hodgkin-Huxley based models of cortical neurons (Lepora et al. 2011)
|
| 264. |
Patterns of synchronization in 2D networks of inhibitory neurons (Miller et al, 2022)
|
| 265. |
Peripheral nerve:Morris-Lecar implementation of (Schwarz et al 1995)
|
| 266. |
Phase oscillator models for lamprey central pattern generators (Varkonyi et al. 2008)
|
| 267. |
Phase plane reveals two slow variables in midbrain dopamine neuron bursts (Yu and Canavier, 2015)
|
| 268. |
Phase precession through acceleration of local theta rhythm (Castro & Aguiar 2011)
|
| 269. |
Phase response curves firing rate dependency of rat purkinje neurons in vitro (Couto et al 2015)
|
| 270. |
Phasic ACh promotes gamma oscillations in E-I networks (Lu et al, 2020)
|
| 271. |
Phasic dopamine changes, Hebbian mechs during reversal learning in striatum (Schirru et al in press)
|
| 272. |
Pipette and membrane patch geometry effects on GABAa currents patch-clamp exps (Moroni et al. 2011)
|
| 273. |
Plasticity forms non-overlapping adjacent ON and OFF RFs in cortical neurons (Sollini et al 2018)
|
| 274. |
Pleiotropic effects of SCZ-associated genes (Mäki-Marttunen et al. 2017)
|
| 275. |
Point process framework for modeling electrical stimulation of auditory nerve (Goldwyn et al. 2012)
|
| 276. |
Population-level model of the basal ganglia and action selection (Gurney et al 2001, 2004)
|
| 277. |
Prob. Inference of Short-Term Synaptic Plasticity in Neocort. Microcircuits (Costa et al. 2013)
|
| 278. |
Purkinje neuron network (Zang et al. 2020)
|
| 279. |
Pyramidal neurons with mutated SCN2A gene (Nav1.2) (Ben-Shalom et al 2017)
|
| 280. |
Pyramidal neurons: IKHT offsets activation of IKLT to increase gain (Fernandez et al 2005)
|
| 281. |
QIF method to estimate synaptic conductances (Vich et al 2017)
|
| 282. |
Reaching movements with robust or stochastic optimal control models (Crevecoeur et al 2019)
|
| 283. |
Realistic barrel cortical column - Matlab (Huang et al., 2022)
|
| 284. |
Reconstrucing sleep dynamics with data assimilation (Sedigh-Sarvestani et al., 2012)
|
| 285. |
Reconstructing cerebellar granule layer evoked LFP using convolution (ReConv) (Diwakar et al. 2011)
|
| 286. |
Reflected SDE Hodgkin-Huxley Model (Dangerfield et al. 2012)
|
| 287. |
Reichardt Model for Motion Detection in the Fly Visual System (Tuthill et al, 2011)
|
| 288. |
Reinforcement Learning with Forgetting: Linking Sustained Dopamine to Motivation (Kato Morita 2016)
|
| 289. |
Relative spike time coding and STDP-based orientation selectivity in V1 (Masquelier 2012)
|
| 290. |
Reliability of Morris-Lecar neurons with added T, h, and AHP currents (Zeldenrust et al. 2013)
|
| 291. |
Respiratory central pattern generator including Kolliker-Fuse nucleus (Wittman et al 2019)
|
| 292. |
Respiratory control model with brainstem CPG and sensory feedback (Diekman, Thomas, and Wilson 2017)
|
| 293. |
Response properties of neocort. neurons to temporally modulated noisy inputs (Koendgen et al. 2008)
|
| 294. |
Resurgent Na+ current offers noise modulation in bursting neurons (Venugopal et al 2019)
|
| 295. |
Reverse-time correlation analysis for idealized orientation tuning dynamics (Kovacic et al. 2008)
|
| 296. |
Revised opponent-channel model of auditory space cortical representation (Briley & Summerfield 2013)
|
| 297. |
Self-influencing synaptic plasticity (Tamosiunaite et al. 2007)
|
| 298. |
Sequence learning via biophysically realistic learning rules (Cone and Shouval 2021)
|
| 299. |
Sequential neuromodulation of Hebbian plasticity in reward-based navigation (Brzosko et al 2017)
|
| 300. |
SHOT-CA3, RO-CA1 Training, & Simulation CODE in models of hippocampal replay (Nicola & Clopath 2019)
|
| 301. |
Simple and accurate Diffusion Approximation algor. for stochastic ion channels (Orio & Soudry 2012)
|
| 302. |
Simulating ion channel noise in an auditory brainstem neuron model (Schmerl & McDonnell 2013)
|
| 303. |
Simulations of Reaching Adaptation and Control (Crevecoeur et al., 2022)
|
| 304. |
Single E-I oscillating network with amplitude modulation (Avella Gonzalez et al. 2012)
|
| 305. |
Single neuron with ion concentrations to model anoxic depolarization (Zandt et al. 2011)
|
| 306. |
Single-cell comprehensive biophysical model of SN pars compacta (Muddapu & Chakravarthy 2021)
|
| 307. |
Slow wave propagation in the guinea-pig gastric antrum (Hirst et al. 2006, Edwards and Hirst 2006)
|
| 308. |
Smoothing of, and parameter estimation from, noisy biophysical recordings (Huys & Paninski 2009)
|
| 309. |
Sound-evoked activity in peripheral axons of type I spiral ganglion neurons (Budak et al. 2021)
|
| 310. |
Sparse connectivity is required for decorrelation, pattern separation (Cayco-Gajic et al 2017)
|
| 311. |
Spatial coupling tunes NMDA receptor responses via Ca2+ diffusion (Iacobucci and Popescu 2019)
|
| 312. |
Spatially-varying glutamate diffusion coefficient at CA1 synaptic cleft space (Gupta et al. 2016)
|
| 313. |
Spectral method and high-order finite differences for nonlinear cable (Omurtag and Lytton 2010)
|
| 314. |
Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation (Luque et al 2019)
|
| 315. |
Spike frequency adaptation in the LGMD (Peron and Gabbiani 2009)
|
| 316. |
Spike Response Model simulator (Jolivet et al. 2004, 2006, 2008)
|
| 317. |
Spike timing detection in different forms of LTD (Doi et al 2005)
|
| 318. |
Spiking GridPlaceMap model (Pilly & Grossberg, PLoS One, 2013)
|
| 319. |
Spiking neuron model of the basal ganglia (Humphries et al 2006)
|
| 320. |
Spinal circuits controlling limb coordination and gaits in quadrupeds (Danner et al 2017)
|
| 321. |
State dependent drug binding to sodium channels in the dentate gyrus (Thomas & Petrou 2013)
|
| 322. |
Statistical Long-term Synaptic Plasticity (statLTSP) (Costa et al 2017)
|
| 323. |
Statistics of symmetry measure for networks of neurons (Esposito et al. 2014)
|
| 324. |
STDP allows fast rate-modulated coding with Poisson-like spike trains (Gilson et al. 2011)
|
| 325. |
Stochastic Hodgkin-Huxley Model: 14x28D Langevin Simulation (Pu and Thomas, 2020).
|
| 326. |
Stochastic model for pituitary corticotrophs (Duncan et al., 2022)
|
| 327. |
Stochastic versions of the Hodgkin-Huxley equations (Goldwyn, Shea-Brown 2011)
|
| 328. |
Stoney vs Histed: Quantifying spatial effects of intracortical microstims (Kumaravelu et al 2022)
|
| 329. |
Strategy for kinase transport by microtubules to nerve terminals (Koon et al. 2014)
|
| 330. |
Striatal dopamine ramping: an explanation by reinforcement learning with decay (Morita & Kato, 2014)
|
| 331. |
Striatal GABAergic microcircuit, dopamine-modulated cell assemblies (Humphries et al. 2009)
|
| 332. |
Striatal GABAergic microcircuit, spatial scales of dynamics (Humphries et al, 2010)
|
| 333. |
Structure-dynamics relationships in bursting neuronal networks revealed (Mäki-Marttunen et al. 2013)
|
| 334. |
Subiculum network model with dynamic chloride/potassium homeostasis (Buchin et al 2016)
|
| 335. |
Supervised learning in spiking neural networks with FORCE training (Nicola & Clopath 2017)
|
| 336. |
Supervised learning with predictive coding (Whittington & Bogacz 2017)
|
| 337. |
Surround Suppression in V1 via Withdraw of Balanced Local Excitation in V1 (Shushruth 2012)
|
| 338. |
Switching circuit for optimal context integration during static + moving contexts (Voina et al 2022)
|
| 339. |
Sympathetic neuron (Wheeler et al 2004)
|
| 340. |
Sympathetic Preganglionic Neurone (Briant et al. 2014)
|
| 341. |
Synaptic Impairment, Robustness of Excitatory NNs w/ Different Topologies (Mirzakhalili et al 2017)
|
| 342. |
Synaptic plasticity can produce and enhance direction selectivity (Carver et al, 2008)
|
| 343. |
Synchronized oscillations of clock gene expression in the choroid plexus (Myung et al 2018)
|
| 344. |
Synthesis of spatial tuning functions from theta cell spike trains (Welday et al., 2011)
|
| 345. |
Systems-level modeling of neuronal circuits for leech swimming (Zheng et al. 2007)
|
| 346. |
Temporal and spatial characteristics of vibrissa responses to motor commands (Simony et al. 2010)
|
| 347. |
Thalamic network model of deep brain stimulation in essential tremor (Birdno et al. 2012)
|
| 348. |
Thalamic transformation of pallidal input (Hadipour-Niktarash 2006)
|
| 349. |
Thalamo-cortical microcircuit (TCM) (AmirAli Farokhniaee and Madeleine M. Lowery 2021)
|
| 350. |
The activity phase of postsynaptic neurons (Bose et al 2004)
|
| 351. |
The role of network connectivity on epileptiform activity (Giacopelli et al 2021)
|
| 352. |
The ventricular AP and effects of the isoproterenol-induced cardiac hypertrophy (Sengul et al 2020)
|
| 353. |
Theoretical principles of DBS induced synaptic suppression (Farokhniaee & McIntyre 2019)
|
| 354. |
Theta phase precession in a model CA3 place cell (Baker and Olds 2007)
|
| 355. |
Towards a biologically plausible model of LGN-V1 pathways (Lian et al 2019)
|
| 356. |
TTX-R Na+ current effect on cell response (Herzog et al 2001) (MATLAB)
|
| 357. |
Understanding odor information segregation in the olfactory bulb by MC/TCs (Polese et al. 2014)
|
| 358. |
V1 and AL spiking neural network for visual contrast response in mouse (Meijer et al. 2020)
|
| 359. |
Vesicular pool simulations of synaptic depression (Aristizabal and Glavinovic 2004)
|
| 360. |
Vestibulo-Ocular Reflex model in Matlab (Clopath at al. 2014)
|
| 361. |
Voltage-based STDP synapse (Clopath et al. 2010)
|
| 362. |
Wilson-Cowan Network with Homeostatic Plasticity (Nicola and Campbell 2021)
|
| 363. |
Within movement adjustments of internal representations during reaching (Crevecoeur et al 2020)
|
| 364. |
Working memory circuit with branched dendrites (Morita 2008)
|
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