- -

Biased competition in the absence of input bias revealed through corticostriatal computation

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Biased competition in the absence of input bias revealed through corticostriatal computation

Mostrar el registro completo del ítem

Ardid-Ramírez, JS.; Sherfey, JS.; Mccarthy, MM.; Hass, J.; Pittman-Polletta, BR.; Kopell, N. (2019). Biased competition in the absence of input bias revealed through corticostriatal computation. Proceedings of the National Academy of Sciences. 116(17):8564-8569. https://doi.org/10.1073/pnas.1812535116

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/171332

Ficheros en el ítem

Metadatos del ítem

Título: Biased competition in the absence of input bias revealed through corticostriatal computation
Autor: Ardid-Ramírez, Joan Salvador Sherfey, Jason S. McCarthy, Michelle M. Hass, Joachim Pittman-Polletta, Benjamin R. Kopell, Nancy
Entidad UPV: Universitat Politècnica de València. Instituto de Investigación para la Gestión Integral de Zonas Costeras - Institut d'Investigació per a la Gestió Integral de Zones Costaneres
Fecha difusión:
Resumen:
[EN] Classical accounts of biased competition require an input bias to resolve the competition between neuronal ensembles driving downstream processing. However, flexible and reliable selection of behaviorally relevant ...[+]
Palabras clave: Rule-based decisions , Prefrontal cortex , Brain rhythms , Neural circuit modeling , Spiny projection neurons
Derechos de uso: Cerrado
Fuente:
Proceedings of the National Academy of Sciences. (issn: 0027-8424 )
DOI: 10.1073/pnas.1812535116
Editorial:
Proceedings of the National Academy of Sciences
Versión del editor: https://doi.org/10.1073/pnas.1812535116
Código del Proyecto:
info:eu-repo/grantAgreement/NSF//1042134/US/Cognitive Rhythms Collaborative: A Discovery Network/
info:eu-repo/grantAgreement/NIH//1R01N5081716/
info:eu-repo/grantAgreement/ARO//W911NF-12-R-0012-02/US/Event-Driven Game Theory for Predicting Dynamical Systems/
Agradecimientos:
We thank T. Womelsdorf for helpful suggestions on an earlier version of the manuscript. We also thank the two reviewers for the constructive comments that enhanced the quality of the manuscript. In particular, their question ...[+]
Tipo: Artículo

References

Desimone, R. (1998). Visual attention mediated by biased competition in extrastriate visual cortex. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 353(1373), 1245-1255. doi:10.1098/rstb.1998.0280

Deco, G., & Rolls, E. T. (2005). Neurodynamics of Biased Competition and Cooperation for Attention: A Model With Spiking Neurons. Journal of Neurophysiology, 94(1), 295-313. doi:10.1152/jn.01095.2004

Ardid, S., Wang, X.-J., & Compte, A. (2007). An Integrated Microcircuit Model of Attentional Processing in the Neocortex. Journal of Neuroscience, 27(32), 8486-8495. doi:10.1523/jneurosci.1145-07.2007 [+]
Desimone, R. (1998). Visual attention mediated by biased competition in extrastriate visual cortex. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 353(1373), 1245-1255. doi:10.1098/rstb.1998.0280

Deco, G., & Rolls, E. T. (2005). Neurodynamics of Biased Competition and Cooperation for Attention: A Model With Spiking Neurons. Journal of Neurophysiology, 94(1), 295-313. doi:10.1152/jn.01095.2004

Ardid, S., Wang, X.-J., & Compte, A. (2007). An Integrated Microcircuit Model of Attentional Processing in the Neocortex. Journal of Neuroscience, 27(32), 8486-8495. doi:10.1523/jneurosci.1145-07.2007

Börgers, C., Epstein, S., & Kopell, N. J. (2008). Gamma oscillations mediate stimulus competition and attentional selection in a cortical network model. Proceedings of the National Academy of Sciences, 105(46), 18023-18028. doi:10.1073/pnas.0809511105

Buia, C. I., & Tiesinga, P. H. (2008). Role of Interneuron Diversity in the Cortical Microcircuit for Attention. Journal of Neurophysiology, 99(5), 2158-2182. doi:10.1152/jn.01004.2007

Ardid, S., Wang, X.-J., Gomez-Cabrero, D., & Compte, A. (2010). Reconciling Coherent Oscillation with Modulationof Irregular Spiking Activity in Selective Attention:Gamma-Range Synchronization between Sensoryand Executive Cortical Areas. Journal of Neuroscience, 30(8), 2856-2870. doi:10.1523/jneurosci.4222-09.2010

Albin, R. L., Young, A. B., & Penney, J. B. (1989). The functional anatomy of basal ganglia disorders. Trends in Neurosciences, 12(10), 366-375. doi:10.1016/0166-2236(89)90074-x

Alexander, G. E., & Crutcher, M. D. (1990). Functional architecture of basal ganglia circuits: neural substrates of parallel processing. Trends in Neurosciences, 13(7), 266-271. doi:10.1016/0166-2236(90)90107-l

Gerfen, C. R., Engber, T. M., Mahan, L. C., Susel, Z., Chase, T. N., Monsma, F. J., & Sibley, D. R. (1990). D 1 and D 2 Dopamine Receptor-regulated Gene Expression of Striatonigral and Striatopallidal Neurons. Science, 250(4986), 1429-1432. doi:10.1126/science.2147780

Ballion, B., Mallet, N., Bézard, E., Lanciego, J. L., & Gonon, F. (2008). Intratelencephalic corticostriatal neurons equally excite striatonigral and striatopallidal neurons and their discharge activity is selectively reduced in experimental parkinsonism. European Journal of Neuroscience, 27(9), 2313-2321. doi:10.1111/j.1460-9568.2008.06192.x

Taverna, S., Ilijic, E., & Surmeier, D. J. (2008). Recurrent Collateral Connections of Striatal Medium Spiny Neurons Are Disrupted in Models of Parkinson’s Disease. Journal of Neuroscience, 28(21), 5504-5512. doi:10.1523/jneurosci.5493-07.2008

Tecuapetla, F., Carrillo-Reid, L., Bargas, J., & Galarraga, E. (2007). Dopaminergic modulation of short-term synaptic plasticity at striatal inhibitory synapses. Proceedings of the National Academy of Sciences, 104(24), 10258-10263. doi:10.1073/pnas.0703813104

Arias-García, M. A., Tapia, D., Flores-Barrera, E., Pérez-Ortega, J. E., Bargas, J., & Galarraga, E. (2013). Duration differences of corticostriatal responses in striatal projection neurons depend on calcium activated potassium currents. Frontiers in Systems Neuroscience, 7. doi:10.3389/fnsys.2013.00063

Gerfen, C. R., & Surmeier, D. J. (2011). Modulation of Striatal Projection Systems by Dopamine. Annual Review of Neuroscience, 34(1), 441-466. doi:10.1146/annurev-neuro-061010-113641

Cui, G., Jun, S. B., Jin, X., Pham, M. D., Vogel, S. S., Lovinger, D. M., & Costa, R. M. (2013). Concurrent activation of striatal direct and indirect pathways during action initiation. Nature, 494(7436), 238-242. doi:10.1038/nature11846

Oldenburg, I. A., & Sabatini, B. L. (2015). Antagonistic but Not Symmetric Regulation of Primary Motor Cortex by Basal Ganglia Direct and Indirect Pathways. Neuron, 86(5), 1174-1181. doi:10.1016/j.neuron.2015.05.008

Ardid, S., & Wang, X.-J. (2013). A Tweaking Principle for Executive Control: Neuronal Circuit Mechanism for Rule-Based Task Switching and Conflict Resolution. Journal of Neuroscience, 33(50), 19504-19517. doi:10.1523/jneurosci.1356-13.2013

Bogacz, R., Martin Moraud, E., Abdi, A., Magill, P. J., & Baufreton, J. (2016). Properties of Neurons in External Globus Pallidus Can Support Optimal Action Selection. PLOS Computational Biology, 12(7), e1005004. doi:10.1371/journal.pcbi.1005004

Asaad, W. F., Rainer, G., & Miller, E. K. (1998). Neural Activity in the Primate Prefrontal Cortex during Associative Learning. Neuron, 21(6), 1399-1407. doi:10.1016/s0896-6273(00)80658-3

White, I. M., & Wise, S. P. (1999). Rule-dependent neuronal activity in the prefrontal cortex. Experimental Brain Research, 126(3), 315-335. doi:10.1007/s002210050740

Wallis, J. D., Anderson, K. C., & Miller, E. K. (2001). Single neurons in prefrontal cortex encode abstract rules. Nature, 411(6840), 953-956. doi:10.1038/35082081

Freedman, D. J., Riesenhuber, M., Poggio, T., & Miller, E. K. (2001). Categorical Representation of Visual Stimuli in the Primate Prefrontal Cortex. Science, 291(5502), 312-316. doi:10.1126/science.291.5502.312

Wise, S. P., Murray, E. A., & Gerfen, C. R. (1996). The Frontal Cortex-Basal Ganglia System in Primates. Critical Reviews™ in Neurobiology, 10(3-4), 317-356. doi:10.1615/critrevneurobiol.v10.i3-4.30

Antzoulatos, E. G., & Miller, E. K. (2011). Differences between Neural Activity in Prefrontal Cortex and Striatum during Learning of Novel Abstract Categories. Neuron, 71(2), 243-249. doi:10.1016/j.neuron.2011.05.040

Marquand, A. F., Haak, K. V., & Beckmann, C. F. (2017). Functional corticostriatal connection topographies predict goal-directed behaviour in humans. Nature Human Behaviour, 1(8). doi:10.1038/s41562-017-0146

Buschman, T. J., Denovellis, E. L., Diogo, C., Bullock, D., & Miller, E. K. (2012). Synchronous Oscillatory Neural Ensembles for Rules in the Prefrontal Cortex. Neuron, 76(4), 838-846. doi:10.1016/j.neuron.2012.09.029

Cohen, J. D., Dunbar, K., & McClelland, J. L. (1990). On the control of automatic processes: A parallel distributed processing account of the Stroop effect. Psychological Review, 97(3), 332-361. doi:10.1037/0033-295x.97.3.332

Rougier, N. P., Noelle, D. C., Braver, T. S., Cohen, J. D., & O’Reilly, R. C. (2005). Prefrontal cortex and flexible cognitive control: Rules without symbols. Proceedings of the National Academy of Sciences, 102(20), 7338-7343. doi:10.1073/pnas.0502455102

Antzoulatos, E. G., & Miller, E. K. (2014). Increases in Functional Connectivity between Prefrontal Cortex and Striatum during Category Learning. Neuron, 83(1), 216-225. doi:10.1016/j.neuron.2014.05.005

Börgers, C., & Kopell, N. (2003). Synchronization in Networks of Excitatory and Inhibitory Neurons with Sparse, Random Connectivity. Neural Computation, 15(3), 509-538. doi:10.1162/089976603321192059

Wehr, M., & Zador, A. M. (2003). Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex. Nature, 426(6965), 442-446. doi:10.1038/nature02116

Bahuguna, J., Aertsen, A., & Kumar, A. (2015). Existence and Control of Go/No-Go Decision Transition Threshold in the Striatum. PLOS Computational Biology, 11(4), e1004233. doi:10.1371/journal.pcbi.1004233

Ott, T., Jacob, S. N., & Nieder, A. (2014). Dopamine Receptors Differentially Enhance Rule Coding in Primate Prefrontal Cortex Neurons. Neuron, 84(6), 1317-1328. doi:10.1016/j.neuron.2014.11.012

Sherfey, J. S., Ardid, S., Hass, J., Hasselmo, M. E., & Kopell, N. J. (2018). Flexible resonance in prefrontal networks with strong feedback inhibition. PLOS Computational Biology, 14(8), e1006357. doi:10.1371/journal.pcbi.1006357

Vogels, T. P., & Abbott, L. F. (2009). Gating multiple signals through detailed balance of excitation and inhibition in spiking networks. Nature Neuroscience, 12(4), 483-491. doi:10.1038/nn.2276

Sherfey JS Ardid S Miller EK Hasselmo ME Kopell N (2019) Prefrontal oscillations modulate the propagation of neuronal activity required for working memory. bioRxiv:10.1101/531574.

Akam, T., & Kullmann, D. M. (2010). Oscillations and Filtering Networks Support Flexible Routing of Information. Neuron, 67(2), 308-320. doi:10.1016/j.neuron.2010.06.019

Sherfey, J. S., Soplata, A. E., Ardid, S., Roberts, E. A., Stanley, D. A., Pittman-Polletta, B. R., & Kopell, N. J. (2018). DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation. Frontiers in Neuroinformatics, 12. doi:10.3389/fninf.2018.00010

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem