NEURON-related presentations at SFN 2010

Time & Place

Abstract Title
Session # & Title

Sat PM

1 - 2

B-H

46.17

H67

J. HA¹, *A. S. KUZNETSOV²; ¹Mathematical Sci. and Ctr. for Mathematical Biosci., IUPUI, Indianapolis, IN; ²Mathematical Sci. and Ctr. for Mathematical Biosci., IUPUI, INDIANAPOLIS, IN

An interlocked oscillator model for firing of the midbrain dopaminergic neuron

46.Neuronal Firing: Ion Channels

1 - 2

B-H

99.29

KKK15

*S. A. NEYMOTIN¹, A. A. FENTON^4,2, W. W. LYTTON³; ¹Biomed. Engin. Program, SUNY Downstate, BROOKLYN, NY; ²Physiol. & Pharmacol., SUNY Downstate, Brooklyn, NY; ³Biomed. Engineering, Physiol. & Pharmacology, Neurol., SUNY Downstate, BROOKLYN, NY; ⁴Ctr. for Neural Sci., New York Univ., New York, NY

Recurrence of correlation structure in hippocampal neuronal ensembles during spatial behavior

99.Learning and Memory Systems: Hippocampus I

1 - 2

B-H

108.5

MMM47

S. HONG¹, W. VAN GEIT^2,1, H. ANWAR^2,1, *E. DE SCHUTTER^2,1; ¹Computat. Neurosci. Unit, Okinawa Inst. of Sci. and Technol., Okinawa, Japan; ²Univ. Antwerp, Antwerp, Belgium

Computational modeling of cerebellar Purkinje neurons with complex and reduced morphologies

108.Simulations of Systems with Well-Described Substructure

1:15-1:30
Room 7B

230.2 Nano-symp.

*S. D. LARSON¹, C. APREA², J. MARTINEZ³, D. A. PETERSON⁴, R. CARLOZ⁵, D. LEE³, D. LITTLE³, V. ASTAKHOV⁵, H. S. KIM⁶, A. MEMON⁷, I. ZASLAVSKY⁷, H. POIZNER⁴, M. E. MARTONE³, M. E. ELLISMAN³;
¹Dept Neurosci, UC San Diego, CRBS 0446, LA JOLLA, CA; ²CRBS, UC San Diego, LA JOLLA, CA; ³CRBS, ⁴Inst. of Neural Computation, ⁶Computer Sci., ⁵UC San Diego, La Jolla, CA; ⁷San Diego Supercomputing Ctr., La Jolla, CA

The whole brain catalog and multiscale connectome browsing

230. Neuroinformatics and Connectomics

2 - 3

B-H

46.6

H56

C. DELEUZE¹, F. DAVID², R. C. LAMBERT², N. LERESCHE², S. BEHURET¹, A. DESTEXHE¹, H. S. SHIN³, V. N. UEBELE⁴, J. J. RENGER⁴, *T. BAL¹; ¹UNIC, CNRS UPR 3293, Gif-sur-Yvette, France; ²UPMC CNRS UMR 7102, Paris, France; ³Ctr. for Neural Science, KIST, Seoul, Korea, Republic of; ⁴Merck Res. Labs., West Point, PA

T-type calcium channels boost the thalamic relay of sensory inputs during cortical-like synaptic background

46.Neuronal Firing: Ion Channels

2 - 3

B-H

108.14

MMM56

*P. D. ROBERTS¹, H. GEERTS², A. SPIROS¹; ¹In Silico Biosci., Portland, OR; ²In Silico Biosci., Philadelphia, PA

A biophysically realistic computational model to predict human pharmaco-electroencephlograph

108.Simulations of Systems with Well-Described Substructure

3 - 4

B-H

25.15

OOO31

*S. OPRISAN; Physics & Astronomy, Col. of Charleston, CHARLESTON, SC

Interdisciplinary teaching methods and tools for biophysical modeling of excitable cells curriculum

25.Undergraduate Education: Experiments, Resources, and Simple Animal Models

3 - 4

B-H

25.27

OOO43

*T. S. MCTAVISH¹, G. M. SHEPHERD¹, M. L. HINES²; ¹Neurobio., Yale Univ. Sch. of Med., New Haven, CT; ²Computer Sci., Yale Univ., New Haven, CT

SAGE and NEURON: Theoretical neuroscience education and analysis over the web

25.Undergraduate Education: Experiments, Resources, and Simple Animal Models

3 - 4

B-H

106.15

MMM22

*T. J. FOUTZ^1,2, C. C. MCINTYRE^2,1; ¹Dept. of Biomed. Engin., Case Western Reserve Univ., Cleveland, OH; ²Dept of Biomed. Engin., Cleveland Clin., Cleveland, OH

Optical stimulation of multi-compartment cable neuron models with channelrhodopsin-2

106.Optogenetics I

4 - 5
B-H

46.8

H58

*M. HULL¹, D. WILLSHAW¹, C. WINLOVE², A. ROBERTS²; ¹Inst. For Adaptive and Neural Computation, Edinburgh, United Kingdom; ²Sch. of Biol. Sci., Univ. of Bristol, Bristol, United Kingdom

A roles for ratios? How ion channel densities could define neuronal firing properties

46.Neuronal Firing: Ion Channels

4 - 5

B-H

72.16

MM11

*H. WEI¹, D. S. DILLIHAY¹, H. M. PETRY², M. E. BICKFORD¹; ¹Dept Anatom. Sci. & Neurobiol, ²Dept Psychological and Brain Sci., Univ. Louisville, LOUISVILLE, KY

Thalamic burst firing propensity: A comparison of the dorsal lateral geniculate and pulvinar nuclei in the tree shrew

72.Subcortical Visual Pathways: Pulvinar and Superior Colliculus

Sun AM

9 - 10

B-H

208.2

LLL63

*S. L. ALLAM¹, E. Y. HU², B. D. OLIVEIRA³, T. ALBASH³, S. HAAS³, R. GREGET⁵, N. AMBERT⁵, M. SARMIS⁵, S. BISCHOFF⁵, J.-M. BOUTEILLER², M. BAUDRY⁴, T. W. BERGER²; ¹Biomed. Engin., Univ. of Southern California, LOS ANGELES, CA; ²Biomed. Engin., ³Physics and Astronomy, ⁴Biol. Sci., USC, Los Angeles, CA; ⁵Rhenovia Pharma, Mulhouse, France

Eons / Rhenoms modeling tool: Optimization framework for multi-scale neuronal parameter fitting

208.Data Analysis and Simulation Methodology

10 - 11

B-H

208.27

MMM18

*T. S. MCTAVISH¹, G. M. SHEPHERD¹, M. L. HINES²; ¹Neurobio., Yale Univ. Sch. of Med., New Haven, CT; ²Computer Sci., Yale Univ., New Haven, CT

NEURON simulations and model viewing over the web

208.Data Analysis and Simulation Methodology

11 - 12
B-H

203.20.

KKK63

A. C. WELDAY¹, I. G. SHLIFER², M. L. BLOOM², *H. T. BLAIR, IV³, K. ZHANG⁴; ¹Dept Psychology, UCLA, Los angeles, CA; ²Dept Psychology, UCLA, Los Angeles, CA; ³Dept Psychology, UCLA, LOS ANGELES, CA; ⁴Dept Biomed Engin., Johns Hopkins Univ., Baltimore, MD

Cosine directional tuning of theta cell burst frequencies in anterior thalamus: Evidence for an oscillatory path integration circuit in the rat brain

203.Learning and Memory: Gamma and Theta Activity

Sun PM

1 - 2

B-H

246.1

H24

*M. E. PETERSSON, E. A. FRANSEN; Sch. of Computer Sci. and Communication, Royal Inst. of Technol., Stockholm, Sweden

Role of TRPC channels in dendritic integration and subthreshold membrane potential plateaus

246.Dendritic Excitability and Synaptic Integration

1 - 2

B-H

246.9

H32

K. MIYAZAKI, S. MANITA, *W. N. ROSS; New York Med. Col., Valhalla, NY

Developmental profile of localized, spontaneous Ca²⁺ release events in the dendrites of hippocampal pyramidal neurons

246.Dendritic Excitability and Synaptic Integration

1 - 2

B-H

246.13

H36

*R. ZOMORRODI MOGHADDAM^1,2, H. KRÖGER², I. TIMOFEEV^1,3; ¹Le Ctr. de recherche Univ. Laval Robert-Giffard, Laval Univ., Quebec city, QC, Canada; ²Dept. of Physics, Quebec, QC, Canada; ³Dept of Psychiatry and Neurosci., Quebec, QC, Canada

Diversity in morphological features of dendritic tree of thalamocortical neuron controls the spatial pattern of signal propagation

246.Dendritic Excitability and Synaptic Integration

2 - 3

B-H

246.2.

H25

X. LI¹, K. MORITA², H. P. C. ROBINSON³, *M. SMALL¹; ¹Electronic and Information Engin., Hong Kong Polytechnic Univ., Hong Kong, Hong Kong; ²Dept. of Cognitive Neuroscience, Grad. Sch. of Med., The Univ. of Tokyo, Tokyo, Japan; ³Dept. of Physiology, Develop. and Neurosci., Univ. of Cambridge, Cambridge, United Kingdom

Frequency preference of a layer V pyramidal neuron in response to oscillatory inhibition at the apical tuft dendrites

246.Dendritic Excitability and Synaptic Integration

2 - 3

B-H

246.10.

H36

*J. M. POWER, P. CURBY, C. BOCKLISCH, P. SAH; Univ. of Queensland, St. Lucia, Australia

The slow afterhyperpolarization modulates the dendritic action potential evoked calcium rise

246.Dendritic Excitability and Synaptic Integration

2 - 3

B-H

246.14.

H37

*M. MIGLIORE¹, S. GASPARINI², V. MEDINILLA², G. A. ASCOLI³; ¹Natl. Res. Council, Palermo, Italy; ²Neurosci. Ctr., Louisiana State Univ. Hlth. Sci. Ctr., New Orleans, LA; ³Ctr. for Neural Informatics, Structures, & Plasticity and Mol. Neurosci. Dept., George Mason Univ., Fairfax, VA

Rebound spiking in CA1 pyramidal neuron dendrites can be locally modulated by the A-type K⁺ current

246.Dendritic Excitability and Synaptic Integration

3 - 4

B-H

246.3

H26

R. CAZE¹, M. HUMPHRIES², *B. S. GUTKIN²; ¹Group For Neural Theory, LNC INSERM U960, Ecole Normale Superieure, Paris, France; ²Group For Neural Theory, LNC U960, Ecole Normale Superieure, Paris, France

Local and non-linear dendritic integration is required for spiking responses that encode spatio-temporal patterns of EPSPs in pyramidal neurons

246.Dendritic Excitability and Synaptic Integration

3 - 4

B-H

276.15

QQ2

G. HALNES¹, S. AUGUSTINAITE², P. HEGGELUND², *G. T. EINEVOLL¹, M. MIGLIORE³; ¹Math, Sci, & Tech., Norwegian Univ. Life Sci., Aas, Norway; ²Univ. of Oslo, Oslo, Norway; ³Natl. Res. Council, Palermo, Italy

A compartmental model of an LGN interneuron

276.Subcortical Visual Pathways: LGN

4 - 5

B-H

246.12

H35

W.-L. ZHOU, *S. D. ANTIC; Neurosci, UConn Hlth. Ctr., FARMINGTON, CT

Action potential propagation in oblique dendrites of CA1 pyramidal cells

246.Dendritic Excitability and Synaptic Integration

4 - 5

B-H

246.20

H43

*S. M. ELBASIOUNY¹, R. K. POWERS², C. J. HECKMAN¹; ¹Dept Physiol, Northwestern Univ., CHICAGO, IL; ²Univ. of Washington, Seattle, WA

Quantitative evaluation of anatomically-detailed and reduced compartmental models in simulating spinal motoneurons firing behaviors

246.Dendritic Excitability and Synaptic Integration

Mon AM

8 - 9

B-H

339.1

E48

*Y. YU¹, D. MCCORMICK²; ²The Dept. of Neurobio., ¹Yale Univ. Sch. Med., NEW HAVEN, CT

An optimal proportion of sodium to potassium channel density in cortical neurons can account for energy-efficient action potentials

339.Sodium Channel Physiology I

8 - 9

B-H

339.21

F16

*C. GUNAY¹, F. SIELING^1,2, L. DHARMAR¹, W.-H. LIN³, R. MARLEY³, R. A. BAINES³, A. PRINZ¹; ¹Biol., Emory Univ., ATLANTA, GA; ²Biomed. Engin., Georgia Inst. of Technol., Atlanta, GA; ³Life Sci., Univ. of Manchester, Manchester, United Kingdom

Modeling larval Drosophila motoneurons to examine the functional effect of Na channel splice variants

339.Sodium Channel Physiology I

8 - 9

B-H

398.21

KKK47

G. WILKEN¹, *N. NAKAMURA²; ¹Mathematical Biol. Unit, Okinawa Inst. of Sci. and Technol., Onna, Japan; ²Okinawa Inst. Sci. Tech. IRP, Uruma-shi, Japan

Memory transfer from hippocampus to neocortex

398.Long-Term Memory: Medial Temporal Lobe Studies

9 - 10

B-H

341.6

F49

*M. OSANAI^1,2, A. TAMURA¹, I. MORI¹; ¹Tohoku Univ. Grad. Sch. of Med., Sendai, Japan; ²JST, CREST, Tokyo, Japan

Firing properties of medium spiny projection neuron in striatum could be modulated by the long-lasting spontaneous calcium rhythm

341.Calcium-Activated Potassium Channels

10 - 11

B-H

377.7

TT6

Q. WAN^1,2, C. KERR², D. PRITCHETT¹, M. HAMALAINEN³, *C. I. MOORE¹, S. R. JONES³; ¹McGovern Inst. Brain Res., MIT, CAMBRIDGE, MA; ²Osher Res. Ctr., Harvard Med. Sch., Boston, MA; ³Dept. of Radiology, Massachusetts Gen. Hosp., Charlestown, MA

Dynamics of dynamics: The within-session variability of human somatosensory neocortical oscillations and evoked responses

377.Cortical Reorganization and Plasticity

11 - 12

B-H

341.8

F51

*A. Y. KUZNETSOVA; Westfield, IN

Modeling study of BK potassium channel in midbrain DA neuron

341.Calcium-Activated Potassium Channels

11 - 12

B-H

362.12

Z9

*D. D. GEORGIEV¹, Y. MINABE¹, D. A. LEWIS^2,3, T. HASHIMOTO^1,2; ¹Dept. of Psychiatry and Neurobio., Kanazawa Univ. Grad. Sch. of Med. Sci., Ishikawa, Japan; ²Dept. of Psychiatry, ³Dept. of Neurosci., Univ. of Pittsburgh, Pittsburgh, PA

Identification of molecular markers for parvalbumin- or somatostatin-positive GABA neurons in the human dorsolateral prefrontal cortex

362.Molecular Mechanisms in Schizophrenia and Autism: Human Pathology

Mon PM

1 - 2

B-H

450.9

H31

*T. ABRAHAMSSON¹, L. CATHALA², D. DIGREGORIO¹; ¹Neurosci., Inst. Pasteur, Paris, France; ²Univ. Paris Descartes, Paris, France

Distance-dependent postsynaptic regulation of short-term plasticity along thin dendrites of aspiny interneurons

450.Synaptic Transmission: Synaptic Integration

1 - 2

B-H

459.3

N17

*P. J. HAHN, C. C. MCINTYRE; Biomed. Engr, Cleveland Clin. Lerner Resch Inst., CLEVELAND, OH

Algorithm sensitivity in analysis of experimental data and network models of deep brain stimulation

459.Deep Brain Stimulation

1 - 2

B-H

459.16

O12

*S. F. LEMPKA, C. C. MCINTYRE; Cleveland Clin., Cleveland, OH

Computational model of local field potential recordings in the subthalamic nucleus

459.Deep Brain Stimulation

1 - 2

B-H

494.1

GGG13

*B. A. SUTER¹, M. MIGLIORE², G. M. G. SHEPHERD¹; ¹Dept Physiology, Feinberg Sch. Med., Northwestern Univ., CHICAGO, IL; ²Natl. Res. Council, Palermo, Italy

Electrophysiological properties of corticospinal and corticostriatal neurons in mouse motor cortex

494.Motor Cortex and Voluntary Movement Control

2 - 3

B-H

494.2

GGG14

*W. W. LYTTON¹, G. M. G. SHEPHERD²; ¹SUNY Downstate, BROOKLYN, NY; ²Physiol., Northwestern Univ., Chicago, IL

Computer network model predicts dependence of neocortical laminar activation patterns on form of stimulation

494.Motor Cortex and Voluntary Movement Control

3 - 4

B-H

446.3

F57

*M. H. HIGGS¹, W. J. SPAIN^1,2; ¹Neurol., VA Puget Sound Hlth. Care Syst., SEATTLE, WA; ²Neurol. and Physiol. & Biophysics, Univ. of Washington, Seattle, WA

Kv1 channels control spike threshold dynamics in cortical pyramidal neurons

446.Potassium Channel Physiology II

3 - 4

B-H

450.11

H33

*F. LAJEUNESSE^1,2, H. KRÖGER², I. TIMOFEEV³; ¹CRULRG, ²Dept. of Physics, ³Dept. of Psychiatry and Neurosciences, Laval Univ., Quebec, QC, Canada

Cooperative action of excitatory synapses in thalamocortical cells

450.Synaptic Transmission: Synaptic Integration

3 - 4

B-H

453.7

I23

*W. R. HOLMES¹, L. M. GROVER²; ¹Biol. Sci., Ohio Univ., Athens, OH; ²Pharmacology, Physiol. & Toxicology, Marshall Univ. Sch. of Med., Huntington, WV

Modeling how the high frequency tetanus often used to induce long-term potentiation in CA1 hippocampal pyramidal cells works

453.Synaptic Plasticity: Presynaptic Mechanisms

4 - 5

B-H

450.8

H30

*Y. KUBOTA^1,2,3, F. KARUBE^1,2, M. NOMURA^4,2, A. T. GULLEDGE⁵, K. HASHIMOTO⁶, A. MOCHIZUKI⁶, Y. KAWAGUCHI^1,2,3; ¹Div. Cerebral Circuitry, Natl. Inst. Physiol Sci. (NIPS), Okazaki, Japan; ²JST, CREST, Tokyo, Japan; ³Dept. of Physiological Sci., SOKENDAI, Okazaki, Japan; ⁴Dept. of Mathematics, Kyoto Univ., Kyoto, Japan; ⁵Dept. of Physiol. and Neurobio., Dartmouth Med. Sch., Lebanon, NH; ⁶Theoretical Biol. Lab., RIKEN, Wako, Japan

Dendritic dimensions and signal conduction properties of cortical nonpyramidal cells

450.Synaptic Transmission: Synaptic Integration

4 - 5

B-H

450.12

H34

*M. UUSISAARI¹, B. TORBEN-NIELSEN¹, B. GUTKIN², K. M. STIEFEL¹; ¹Theoretical and Exptl. Neurosci. Unit, Okinawa Inst. of Sci. and Technol., Onna-Son, Okinawa, Japan; ²Ecole Normale Superieure, Paris, France

Stochastic resonance improves weak signal detection in the pyramidal neurons of mouse visual cortex

450.Synaptic Transmission: Synaptic Integration

Tue AM

8 - 9

B-H

552.5

H55

F. ZELDENRUST¹, P. CHAMEAU¹, *W. J. WADMAN²; ¹SILS-CNS, Univ. of Amsterdam, Amsterdam, Netherlands; ²Univ. Amsterdam, Amsterdam, Netherlands

Neural coding in thalamocortical relay cells

552.Signal Propagation

8 - 9

B-H

589.5

CCC18

H. KIM¹, *K. E. JONES^2,1; ¹Biomed. Engin., ²Fac Physical Educ. & Rec., Univ. Alberta, Edmonton, AB, Canada

Influence of the action potential width on the nonlinear dynamics of spinal motor neuron model

589.Motor Neurons: Activity and Sensory and Central Control

10 - 11

B-H

539.19

C32

R. G. YOUNG, D. K. HARTLINE, *A. M. CASTELFRANCO; Bekesy Lab. Neurobiol, PBRC, Univ. of Hawaii, HONOLULU, HI

The “Lillie Transition”: Modeling the onset of saltatory conduction in myelinating nerve

539.Neuron-Glia Interactions

10 - 11

B-H

616.15

OOO58

*S. G. CARVER, M. HINES; Neurobio., Yale Univ. Sch. of Med., New Haven, CT

Identifying macroscopic voltage clamp currents with bayesian filtering

616.Electrophysiological Data Analysis

11 - 12

B-H

552.4

H54

*M. SHEFFIELD¹, T. BEST², W. KATH², N. SPRUSTON²; ¹Northwestern Univ., CHICAGO, IL; ²Northwestern Univ., Evanston, IL

Persistent action potential firing generated in the distal axons of inhibitory interneurons

552.Signal Propagation

Tue PM

1 - 2

B-H

683.13

WW3

*S. R. JONES¹, M. HALASSA², D. L. PRITCHETT⁴, J. SIEGLE⁴, M. HAMALAINEN³, C. I. MOORE⁴; ¹Martinos Ctr. Biomed. Imaging, Mass Gen Hosp, CHARLESTOWN, MA; ²Neurol., ³Martinos Ctr. Biomed. Imaging, Mass Gen Hosp, Boston, MA; ⁴McGovern Inst., MIT, Cambridge, MA

A neocortical beta origin hypothesis: Computational modeling, electrophysiological, and optogenetic studies

683.Thalamocortical Processes

2 - 3

B-H

645.14

G8

C. FIETKIEWICZ¹, K. A. LOPARO¹, *C. G. WILSON²; ¹Electrical Engin. and Computer Sci., Case Western Reserve Univ., Cleveland, OH; ²Dept Pediatrics, CWRU, CLEVELAND, OH

Synchronization of hypoglossal motoneurons through correlated inputs in rat in vitro slices

645.Oscillations and Synchronization

2:30 - 2:45 Room 7B

635.7
Nano-symp.

*A. V. OLYPHER^1,2, W. W. LYTTON², A. A. PRINZ¹; ¹Dept. Biol., Emory Univ., ATLANTA, GA; ²Dept. of Physiol. and Pharmacol., SUNY, Downstate Med. Ctr., Brooklyn, NY

Transformation of inputs in a model of the rat hippocampal CA1 network

635.Cognitive Learning and Memory Systems

4 - 5

B-H

645.16

G10

*D. L. VIERLING-CLAASSEN^1,2, C. I. MOORE¹, J. A. CARDIN³, S. R. JONES²; ¹Brain and Cognitive Sci., MIT McGovern Inst. For Brain Res., Cambridge, MA; ²Radiology, MGH-MIT-HMS Martinos Ctr. for Biomed. Imaging, Charlestown, MA; ³Neurobio., Yale Univ. Sch. of Med., New Haven, CT

Computational modeling of distinct neocortical oscillations driven by cell-type selective optogenetic drive: Separable resonant circuits controlled by low-threshold spiking and fast-spiking interneurons

645.Oscillations and Synchronization

4 - 5

B-H

671.20

II8

*B. AUBIE, R. SAYEGH, P. A. FAURE; Psychology, Neurosci. & Behaviour, McMaster Univ., Hamilton, ON, Canada

Models of duration-tuned neurons predict a role in echolocation

671.Auditory Processing: Temporal and Spectral Factors II

4 - 5

B-H

673.4

JJ13

*L. E. MULLER, II¹, P.-O. POLACK², D. CONTRERAS², A. DESTEXHE¹; ¹Unité de Neurosciences, Information & Complexité (UNIC), Ctr. Natl. De La Recherche Scientifique (CNRS), Gif-sur-Yvette, France; ²Dept. of Neurosci., Univ. of Pennsylvania Sch. of Med., Philadelphia, PA

Analysis of voltage-sensitive dye imaging data during propagating cortical waves in mouse visual cortex reveals fine structure and state dependence

673.Striate Cortex: Activity Patterns and Visual Responses

4 - 5

B-H

685.20

YY9

*R. K. POWERS¹, P. NARDELLI², T. C. COPE²; ¹Dept Physiol & Biophysics, Univ. Washington, SEATTLE, WA; ²Dept. Neurosci., Cell Bio., Physiol., Wright State Univ., Dayton, OH

Frequency-dependent amplification of stretch-evoked EPSPs in spinal motoneurons

685."Motor Neuron Development, Identification, Intrinsic Properties, and Modulation"

Wed AM

9 - 10

B-H

745.6

F1

A. YADAV¹, *C. M. WEAVER², Y. Z. GAO¹, D. L. DICKSTEIN¹, J. I. LUEBKE³, P. R. HOF¹; ¹Dept. of Neurosci., Mount Sinai Sch. of Med., New York, NY; ²Mathematics and Computer Sci., Franklin & Marshall Col., Lancaster, PA; ³Dept. of Anat. and Neurobio., Boston Univ., Boston, MA

Aged model neurons of the prefrontal cortex fire faster to maintain functional robustness in response to morphological dystrophy

745.Modulation of Firing Properties

9 - 10

B-H

809.14

LLL23

*Y. CHEN¹, G. LI², G. J. QUIRK³, D. PARÉ⁴, S. S. NAIR¹; ¹Electrical Engin., Univ. of Missouri - Columbia, Columbia, MO; ²Psychology, Cornell Univ., Ithaca, NY; ³Departments of Psychiatry and Anat. and Neurobio., Univ. of Puerto Rico Sch. of Med., San Juan, PR; ⁴Ctr. for Mol. and Behavioral Neurosci., Rutgers State Univ., Newark, NJ

Modeling fear and extinction neurons in the basolateral nucleus of the amygdala

809.Fear and Aversive Learning and Memory: Extinction

10 - 11

B-H

820.11

PPP12

*H. LINDÉN¹, T. TETZLAFF¹, T. C. POTJANS^2,3, K. H. PETTERSEN¹, S. GRUEN⁴, M. DIESMANN^4,3, G. T. EINEVOLL¹; ¹Mathematical Sci. and Technol., Norwegian Univ. of Life Sci., Aas, Norway; ²Res. Ctr. Juelich, Juelich, Germany; ³RIKEN Computat. Sci. Res. Program, Wako, Japan; ⁴RIKEN Brain Sci. Inst., Wako, Japan

Estimating the spatial scale of local field potentials in a cortical population model

820.Data Acquisition and Brain-Machine Interface: Practice and Theory

11 - 12

B-H

745.12

F7

*J. S. COGGAN¹, S. A. PRESCOTT³, T. M. BARTOL², T. J. SEJNOWSKI²; ¹Computat. Neurobio. Lab., The Salk Inst., LA JOLLA, CA; ²Computat. Neurobio. Lab., The Salk Inst., La Jolla, CA; ³Dept. of Neurobio., Univ. of Pittsburgh, Pittsburgh, PA

Conductance imbalances link diverse symptoms of demyelination diseases

745.Modulation of Firing Properties

11 - 12

B-H

785.8

SS1

*F. M. SIMOES DE SOUZA¹, E. DE SCHUTTER^1,2; ¹Computat. Neurosci. Unit, Okinawa Inst. of Sci. and Technol., Okinawa, Japan; ²Theoretical Neurobio., Univ. of Antwerp, Antwerpen, Belgium

Robustness effect of gap junctions between Golgi cells on cerebellar oscillations

785.Cerebellum: Cortex and Nuclei

11 - 12

B-H

809.4

LLL13

*S. PENDYAM¹, A. BURGOS-ROBLES², G. J. QUIRK³, S. S. NAIR¹; ¹Univ. Missouri-Columbia, Columbia, MO; ²Brain and Cognitive Sci., MIT - McGovern Inst. for Brain Res., Cambridge, MA; ³Univ. of Puerto Rico Sch. of Med., San Juan, PR

The role of prelimbic prefrontal neurons in the expression of conditioned auditory fear - A computational study

809.Fear and Aversive Learning and Memory: Extinction

11 - 12

B-H

809.12

LLL21

*J. M. BALL¹, K. UPENDRAM¹, G. UNAL², D. PARɲ, S. S. NAIR¹; ¹Electrical & Computer Engin., Univ. of Missouri, COLUMBIA, MO; ²Rutgers State Univ., Newark, NJ

Biologically realistic computational model of perirhinal area 36

809.Fear and Aversive Learning and Memory: Extinction

11 - 12

B-H

820.8

PPP9

*S. L. GRATIY¹, A. DEVOR^1,2,3, G. T. EINEVOLL⁴, A. M. DALE^1,2; ¹Radiology, ²Neurosciences, UCSD, La Jolla, CA; ³MGH, Harvard Med. Sch., Charlestown, MA; ⁴Mathematical Sci. and Technol. and Ctr. for Integrative Genet., Norwegian Univ. of Life Sci., Ås, Norway

Estimation of synaptic currents from laminar multi-electrode recordings

820.Data Acquisition and Brain-Machine Interface: Practice and Theory

Wed PM

1 - 2

B-H

890.5

AAA18

*M. CEMBROWSKI¹, H. RIECKE¹, W. KATH², J. SINGER³; ¹Engin. Sci. and Applied Mathematics, ²Engin. Sci. and Applied Mathematics, Neurobio. and Physiol., Northwestern Univ., EVANSTON, IL; ³Ophthalmology and Physiol., Northwestern Univ., Chicago, IL

Burst firing in the AII amacrine interneuron of the mammalian retina

890.Retinal Circuitry: Synaptic Interactions

4 - 5

B-H

856.12

I18

*H. A. GEERTS, A. SPIROS, P. ROBERTS; In Silico Biosci., BERWYN, PA

Evaluating the clinical efficacy of symptomatic Alzheimer treatments using a mechanistic disease modeling & simulation approach

856."Alzheimer's Disease: Therapies Targeting Cell Signaling, Neurotransmitters, and Other Pathways"

4 - 5

B-H

892.12

CCC11

*B. F. BEHABADI¹, C. A. RAMACHANDRA², B. W. MEL²; ¹Biomed. Engin., Univ. So California, LOS ANGELES, CA; ²Biomed. Engin., Univ. So California, Los angeles, CA

Cue-combination, conjunctive, contextual and pooling interactions at natural images contours and their possible neural implementation

892.Vision: Processing of Form and Color