Abbott, L.F. (1997). Synaptic depression and cortical gain control. Science 275, 221–224.CrossRefGoogle ScholarPubMed

Abbott, L.F. (2008). Theoretical neuroscience rising. Neuron 60, 489–495.Google Scholar

Abbott, L.F., and Regehr, W.G. (2004). Synaptic computation. Nature 431, 796–803.Google Scholar

Ahissar, E., and Oram, T. (2013). Thalamic relay or cortico-thalamic processing? Old question, new answers. Cerebral Cortex 25, 845–848.Google Scholar

Ahrens, S., Jaramillo, S., Yu, K., Ghosh, S., Hwang, G.R., Paik, R., Lai, C., He, M., Huang, Z.J., and Li, B. (2015). ErbB4 regulation of a thalamic reticular nucleus circuit for sensory selection. Nature Neuroscience 18, 104–11.Google Scholar

Aizenberg, M., Rolón-Martínez, S., Pham, T., Rao, W., Haas, J.S., and Geffen, M.N. (2019). Projection from the amygdala to the thalamic reticular nucleus amplifies cortical sound responses. Cell Reports 28, 605–615.e4.Google Scholar

Alitto, H., Rathbun, D.L., Vandeleest, J.J., Alexander, P.C., and Usrey, W.M. (2019). The augmentation of retinogeniculate communication during thalamic burst mode. Journal of Neuroscience 39, 5697–5710.Google Scholar

Barthó, P., Slézia, A., Mátyás, F., Faradzs-Zade, L., Ulbert, I., Harris, K.D., and Acsády, L. (2014). Ongoing network state controls the length of sleep spindles via inhibitory activity. Neuron 82, 1367–1379.Google Scholar

Bastos, A.M., Briggs, F., Alitto, H.J., Mangun, G.R., and Usrey, W.M. (2014). Simultaneous recordings from the primary visual cortex and lateral geniculate nucleus reveal rhythmic interactions and a cortical source for gamma-band oscillations. Journal of Neuroscience 34, 7639–7644.Google Scholar

Bazhenov, M., Timofeev, I., Steriade, M., and Sejnowski, T.J. (2002). Model of thalamocortical slow-wave sleep oscillations and transitions to activated states. Journal of Neuroscience 22, 8691–8704.Google Scholar

Béhuret, S., Deleuze, C., and Bal, T. (2015). Corticothalamic synaptic noise as a mechanism for selective attention in thalamic neurons. Frontiers in Neural Circuits 9.Google Scholar

Bourjaily, M.A., and Miller, P. (2012). Dynamic afferent synapses to decision-making networks improve performance in tasks requiring stimulus associations and discriminations. Journal of Neurophysiology 108, 513–527.CrossRefGoogle ScholarPubMed

Brown, J.W., Taheri, A., Kenyon, R.V., Berger-Wolf, T.Y., and Llano, D.A. (2020). Signal propagation via open-loop intrathalamic architectures: A computational model. eNeuro 7, ENEURO.0441–19.2020.Google Scholar

Bruno, R.M. (2006). Cortex is driven by weak but synchronously active thalamocortical synapses. Science 312, 1622–1627.Google Scholar

Burt, J.B., Demirtas¸, M., Eckner, W.J., Navejar, N.M., Ji, J.L., Martin, W.J., Bernacchia, A., Anticevic, A., and Murray, J.D. (2018). Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography. Nature Neuroscience 21, 1251–1259.Google Scholar

Carandini, M., and Ferster, D. (2000). Membrane potential and firing rate in cat primary visual cortex. Journal of Neuroscience 20, 470–484.Google Scholar

Castro-Alamancos, M.A. (1997). Short-term plasticity in thalamocortical pathways: Cellular mechanisms and functional roles. Reviews in the Neurosciences 8.Google Scholar

Clemente-Perez, A., Makinson, S.R., Higashikubo, B., Brovarney, S., Cho, F.S., Urry, A., Holden, S.S., Wimer, M., Dávid, C., Fenno, L.E., Acsády, L., Deisseroth, K., and Paz, J.T. (2017). Distinct thalamic reticular cell types differentially modulate normal and pathological cortical rhythms. Cell Reports 19, 2130–2142.Google Scholar

Contreras, D., Destexhe, A., Sejnowski, T.J., and Steriade, M. (1996). Control of spatiotemporal coherence of a thalamic oscillation by corticothalamic feedback. Science 274, 771–774.Google Scholar

Contreras, D., and Steriade, M. (1995). Cellular basis of EEG slow rhythms: a study of dynamic corticothalamic relationships. Journal of Neuroscience 15, 604–622.Google Scholar

Cotillon-Williams, N., Huetz, C., Hennevin, E., and Edeline, J.M. (2008). Tonotopic control of auditory thalamus frequency tuning by reticular thalamic neurons. Journal of Neurophysiology 99, 1137–1151.Google Scholar

Coulon, P., and Landisman, C.E. (2017). The potential role of gap junctional plasticity in the regulation of state. Neuron 93, 1275–1295.Google Scholar

Crandall, S.R., Cruikshank, S.J., and Connors, B.W. (2015). A corticothalamic switch: controlling the thalamus with dynamic synapses. Neuron 86, 768–782.Google Scholar

Crick, F. (1984). Function of the thalamic reticular complex: the searchlight hypothesis. Proceedings of the National Academy of Sciences of the United States of America 81, 4586–4590.Google Scholar

Cueni, L., Canepari, M., Luján, R., Emmenegger, Y., Watanabe, M., Bond, C.T., Franken, P., Adelman, J.P., and Lüthi, A. (2008). T-type Ca²⁺ channels, SK2 channels and SERCAs gate sleep-related oscillations in thalamic dendrites. Nature Neuroscience 11, 683–692.Google Scholar

Destexhe, A., Babloyantz, A., and Sejnowski, T.J. (1993). Ionic mechanisms for intrinsic slow oscillations in thalamic relay neurons. Biophysical Journal 65, 1538–52.Google Scholar

Destexhe, A., Bal, T., McCormick, D.A., and Sejnowski, T.J. (1996). Ionic mechanisms underlying synchronized oscillations and propagating waves in a model of ferret thalamic slices. Journal of Neurophysiology 76, 2049–70.Google Scholar

Destexhe, A., Contreras, D., Sejnowski, T.J., and Steriade, M. (1994a). A model of spindle rhythmicity in the isolated thalamic reticular nucleus. Journal of Neurophysiology 72, 803–18.Google Scholar

Destexhe, A., Contreras, D., Sejnowski, T.J., and Steriade, M. (1994b). Modeling the control of reticular thalamic oscillations by neuromodulators. NeuroReport 5, 2217–2220.Google Scholar

Destexhe, A., Contreras, D., and Steriade, M. (1998). Mechanisms underlying the synchronizing action of corticothalamic feedback through inhibition of thalamic relay cells. Journal of Neurophysiology 79, 999–1016.CrossRefGoogle ScholarPubMed

Destexhe, A., Contreras, D., Steriade, M., Sejnowski, T.J., and Huguenard, J.R. (1996). In vivo, in vitro, and computational analysis of dendritic calcium currents in thalamic reticular neurons. Journal of Neuroscience 16, 169–185.Google Scholar

Destexhe, A., McCormick, D.A., and Sejnowski, T.J. (1993). A model for 8–10 Hz spindling in interconnected thalamic relay and reticularis neurons. Biophysical Journal 65, 2473–2477.Google Scholar

Diaz-Quesada, M., Martini, F.J., Ferrati, G., Bureau, I., and Maravall, M. (2014). Diverse thalamocortical short-term plasticity elicited by ongoing stimulation. Journal of Neuroscience 34, 515–526.CrossRefGoogle ScholarPubMed

Dittman, J.S., Kreitzer, A.C., and Regehr, W.G. (2000). Interplay between facilitation, depression, and residual calcium at three presynaptic terminals. Journal of Neuroscience 20, 1374–1385.CrossRefGoogle ScholarPubMed

Dong, P., Wang, H., Shen, X.F., Jiang, P., Zhu, X.T., Li, Y., Gao, J.H., Lin, S., Huang, Y., He, X.B., Xu, F.Q., Duan, S., Lian, H., Wang, H., Chen, J., and Li, X.M. (2019). A novel cortico-intrathalamic circuit for flight behavior. Nature Neuroscience 22, 941–949.Google Scholar

Fagerberg, L., Hallström, B.M., Oksvold, P., Kampf, C., Djureinovic, D., Odeberg, J., Habuka, M., Tahmasebpoor, S., Danielsson, A., Edlund, K., Asplund, A., Sjöstedt, E., Lundberg, E., Szigyarto, C.A.K., Skogs, M., Takanen, J.O., Berling, H., Tegel, H., Mulder, J., Nilsson, P., Schwenk, J.M., Lindskog, C., Danielsson, F., Mardinoglu, A., Sivertsson, A., von Feilitzen, K., Forsberg, M., Zwahlen, M., Olsson, I., Navani, S., Huss, M., Nielsen, J., Ponten, F., and Uhlén, M. (2014). Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics. Molecular & Cellular Proteomics 13, 397–406.Google Scholar

Fitzgibbon, T., Tevah, L.V., and Sefton, A.J. (1995). Connections between the reticular nucleus of the thalamus and pulvinar-lateralis posterior complex: A WGA-HRP study. Journal of Comparative Neurology 363, 489–504.CrossRefGoogle ScholarPubMed

Fortune, E.S., and Rose, G.J. (2001). Short-term synaptic plasticity as a temporal filter. Trends in Neurosciences 24, 381–385.CrossRefGoogle ScholarPubMed

Fuentealba, P., Crochet, S., Timofeev, I., Bazhenov, M., Sejnowski, T.J., and Steriade, M. (2004). Experimental evidence and modeling studies support a synchronizing role for electrical coupling in the cat thalamic reticular neurons in vivo. European Journal of Neuroscience 20, 111–119.Google Scholar

Fuhrmann, G., Segev, I., Markram, H., and Tsodyks, M. (2002). Coding of temporal information by activity-dependent synapses. Journal of Neurophysiology 87, 140–148.Google Scholar

Gabernet, L., Jadhav, S.P., Feldman, D.E., Carandini, M., and Scanziani, M. (2005). Somatosensory integration controlled by dynamic thalamocortical feed-forward inhibition. Neuron 48, 315–327.Google Scholar

Galvan, A., Hu, X., Smith, Y., and Wichmann, T. (2016). Effects of optogenetic activation of corticothalamic terminals in the motor thalamus of awake monkeys. Journal of Neuroscience 36, 3519–3530.Google Scholar

Gentet, L.J., and Ulrich, D. (2003). Strong, reliable and precise synaptic connections between thalamic relay cells and neurones of the nucleus reticularis in juvenile rats. Journal of Physiology 546, 801–811.Google Scholar

Goldman, M.S., Maldonado, P., and Abbott, L.F. (2002). Redundancy reduction and sustained firing with stochastic depressing synapses. Journal of Neuroscience 22, 584–591.Google Scholar

Golomb, D., Wang, X.J., and Rinzel, J. (1996). Propagation of spindle waves in a thalamic slice model. Journal of Neurophysiology 75, 750–769.Google Scholar

Gonzalo-Ruiz, A., and Lieberman, A. (1995). Topographic organization of projections from the thalamic reticular nucleus to the anterior thalamic nuclei in the rat. Brain Research Bulletin 37, 17–35.Google Scholar

Granseth, B., Ahlstrand, E., and Lindström, S. (2002). Paired pulse facilitation of corticogeniculate EPSCs in the dorsal lateral geniculate nucleus of the rat investigated in vitro. Journal of Physiology 544, 477–486.Google Scholar

Gu, Q.L., Lam, N.H., Halassa, M.M., and Murray, J.D. (2021). Computational circuit mechanisms underlying thalamic control of attention. bioRxiv 10.1101/2020.09.16.300749.Google Scholar

Halassa, M.M., and Acsády, L. (2016). Thalamic inhibition: diverse sources, diverse scales. Trends in Neurosciences 39, 680–693.CrossRefGoogle ScholarPubMed

Halassa, M.M., Chen, Z., Wimmer, R.D., Brunetti, P.M., Zhao, S., Zikopoulos, B., Wang, F., Brown, E.N., and Wilson, M.A. (2014). State-dependent architecture of thalamic reticular subnetworks. Cell 158, 808–821.Google Scholar

Halassa, M.M., and Kastner, S. (2017). Thalamic functions in distributed cognitive control. Nature Neuroscience 20, 1669–1679.Google Scholar

Halassa, M.M., and Sherman, S.M. (2019). Thalamocortical circuit motifs: a general framework. Neuron 103, 762–770.Google Scholar

Halassa, M.M., Siegle, J.H., Ritt, J.T., Ting, J.T., Feng, G., and Moore, C.I. (2011). Selective optical drive of thalamic reticular nucleus generates thalamic bursts and cortical spindles. Nature Neuroscience 14, 1118–1120.Google Scholar

Hale, P., Sefton, A., Baur, L., and Cottee, L. (1982). Interrelations of the rat’s thalamic reticular and dorsal lateral geniculate nuclei. Experimental Brain Research 45–45.Google Scholar

Hennig, M.H. (2013). Theoretical models of synaptic short term plasticity. Frontiers in Computational Neuroscience 7.Google Scholar

Hirai, D., Nakamura, K.C., ichi Shibata, K., Tanaka, T., Hioki, H., Kaneko, T., and Furuta, T. (2017). Shaping somatosensory responses in awake rats: cortical modulation of thalamic neurons. Brain Structure and Function 223, 851–872.Google Scholar

Hirsch, J.A., Wang, X., Sommer, F.T., and Martinez, L.M. (2015). How inhibitory circuits in the thalamus serve vision. Annual Review of Neuroscience 38, 309–329.Google Scholar

Hou, G., Smith, A.G., and Zhang, Z.W. (2016). Lack of intrinsic GABAergic connections in the thalamic reticular nucleus of the mouse. Journal of Neuroscience 36, 7246–52.Google Scholar

Huguenard, J., and Prince, D. (1992). A novel t-type current underlies prolonged Ca²⁺- dependent burst firing in GABAergic neurons of rat thalamic reticular nucleus. Journal of Neuroscience 12, 3804–3817.CrossRefGoogle ScholarPubMed

Huguenard, J.R., and McCormick, D.A. (2007). Thalamic synchrony and dynamic regulation of global forebrain oscillations. Trends in Neurosciences 30, 350–356.Google Scholar

Huntenburg, J.M., Bazin, P.L., and Margulies, D.S. (2018). Large-scale gradients in human cortical organization. Trends in Cognitive Sciences 22, 21–31.Google Scholar

Isaacson, J.S., and Scanziani, M. (2011). How inhibition shapes cortical activity. Neuron 72, 231–243.CrossRefGoogle ScholarPubMed

Jackman, S.L., and Regehr, W.G. (2017). The mechanisms and functions of synaptic facilitation. Neuron 94, 447–464.Google Scholar

Jahnsen, H., and Llinás, R. (1984). Electrophysiological properties of guinea-pig thalamic neurones: an in vitro study. Journal of Physiology 349, 205–226.Google Scholar

Jaramillo, J., Mejias, J.F., and Wang, X.J. (2019). Engagement of pulvino-cortical feedforward and feedback pathways in cognitive computations. Neuron 101, 321–336.e9.Google Scholar

Jones, E.G. (1975). Some aspects of the organization of the thalamic reticular complex. Journal of Comparative Neurology 162, 285–308.CrossRefGoogle ScholarPubMed

Jones, E.G. (2012). The thalamus (Springer Science & Business Media).Google Scholar

Katzner, S., Busse, L., and Carandini, M. (2011). GABA_A inhibition controls response gain in visual cortex. Journal of Neuroscience 31, 5931–5941.Google Scholar

Kim, U., Bal, T., and McCormick, D.A. (1995). Spindle waves are propagating synchronized oscillations in the ferret LGNd in vitro. Journal of Neurophysiology 74, 1301–1323.Google Scholar

Kimura, A. (2014). Diverse subthreshold cross-modal sensory interactions in the thalamic reticular nucleus: implications for new pathways of cross-modal attentional gating function. European Journal of Neuroscience 39, 1405–1418.Google Scholar

Kimura, A., Imbe, H., Donishi, T., and Tamai, Y. (2007). Axonal projections of single auditory neurons in the thalamic reticular nucleus: implications for tonotopy-related gating function and cross-modal modulation. European Journal of Neuroscience 26, 3524–3535.Google Scholar

Knudsen, E.I. (2018). Neural circuits that mediate selective attention: a comparative perspective. Trends in Neurosciences 41, 789–805.CrossRefGoogle ScholarPubMed

Krishnan, G.P., Chauvette, S., Shamie, I., Soltani, S., Timofeev, I., Cash, S.S., Halgren, E., and Bazhenov, M. (2016). Cellular and neurochemical basis of sleep stages in the thalamocortical network. eLife 5.Google Scholar

Krol, A., Wimmer, R.D., Halassa, M.M., and Feng, G. (2018). Thalamic reticular dysfunction as a circuit endophenotype in neurodevelopmental disorders. Neuron 98, 282–295.CrossRefGoogle ScholarPubMed

Lam, Y.W., and Sherman, S.M. (2015). Functional topographic organization of the motor reticulothalamic pathway. Journal of Neurophysiology 113, 3090–3097.Google Scholar

Landisman, C.E. (2005). Long-term modulation of electrical synapses in the mammalian thalamus. Science 310, 1809–1813.Google Scholar

Landisman, C.E., and Connors, B.W. (2007). VPM and PoM nuclei of the rat somatosensory thalamus: intrinsic neuronal properties and corticothalamic feedback. Cerebral Cortex 17, 2853–2865.Google Scholar

Landisman, C.E., Long, M.A., Beierlein, M., Deans, M.R., Paul, D.L., and Connors, B.W. (2002). Electrical synapses in the thalamic reticular nucleus. Journal of Neuroscience 22, 1002–1009.Google Scholar

Lee, J.H., Latchoumane, C.F.V., Park, J., Kim, J., Jeong, J., Lee, K.H., and Shin, H.S. (2019). The rostroventral part of the thalamic reticular nucleus modulates fear extinction. Nature Communications 10.Google Scholar

Lee, S.C., Cruikshank, S.J., and Connors, B.W. (2010). Electrical and chemical synapses between relay neurons in developing thalamus. Journal of Physiology 588, 2403–2415.Google Scholar

Lee, S.C., Patrick, S.L., Richardson, K.A., and Connors, B.W. (2014). Two functionally distinct networks of gap junction-coupled inhibitory neurons in the thalamic reticular nucleus. Journal of Neuroscience 34, 13170–13182.Google Scholar

Lee, S.H., Govindaiah, G., and Cox, C.L. (2007). Heterogeneity of firing properties among rat thalamic reticular nucleus neurons. Journal of Physiology 582, 195–208.Google Scholar

Lesica, N.A. (2004). Encoding of natural scene movies by tonic and burst spikes in the lateral geniculate nucleus. Journal of Neuroscience 24, 10731–10740.Google Scholar

Li, Y., Lopez-Huerta, V.G., Adiconis, X., Levandowski, K., Choi, S., Simmons, S.K., Arias-Garcia, M.A., Guo, B., Yao, A.Y., Blosser, T.R., Wimmer, R.D., Aida, T., Atamian, A., Naik, T., Sun, X., Bi, D., Malhotra, D., Hession, C.C., Shema, R., Gomes, M., Li, T., Hwang, E., Krol, A., Kowalczyk, M., Peça, J., Pan, G., Halassa, M.M., Levin, J.Z., Fu, Z., and Feng, G. (2020). Distinct subnetworks of the thalamic reticular nucleus. Nature 583, 819–824.Google Scholar

Litwin-Kumar, A., Rosenbaum, R., and Doiron, B. (2016). Inhibitory stabilization and visual coding in cortical circuits with multiple interneuron subtypes. Journal of Neurophysiology 115, 1399–1409.CrossRefGoogle ScholarPubMed

Liu, B.H., Li, Y.T., Ma, W.P., Pan, C.J., Zhang, L.I., and Tao, H.W. (2011). Broad inhibition sharpens orientation selectivity by expanding input dynamic range in mouse simple cells. Neuron 71, 542–554.Google Scholar

Lo, F.S., and Sherman, S.M. (1994). Feedback inhibition in the cat’s lateral geniculate nucleus. Experimental Brain Research 100.Google Scholar

Long, M.A. (2004). Small clusters of electrically coupled neurons generate synchronous rhythms in the thalamic reticular nucleus. Journal of Neuroscience 24, 341–349.Google Scholar

Lytton, W., Destexhe, A., and Sejnowski, T. (1996). Control of slow oscillations in the thalamocortical neuron: a computer model. Neuroscience 70, 673–684.Google Scholar

Marsat, G., and Maler, L. (2010). Neural heterogeneity and efficient population codes for communication signals. Journal of Neurophysiology 104, 2543–2555.Google Scholar

Martinez-Garcia, R.I., Voelcker, B., Zaltsman, J.B., Patrick, S.L., Stevens, T.R., Connors, B.W., and Cruikshank, S.J. (2020). Two dynamically distinct circuits drive inhibition in the sensory thalamus. Nature 583, 813–818.Google Scholar

Masson, G.L., Masson, S.R.L., Debay, D., and Bal, T. (2002). Feedback inhibition controls spike transfer in hybrid thalamic circuits. Nature 417, 854–858.Google Scholar

Matveev, V., and Wang, X.J. (2000). Differential short-term synaptic plasticity and transmission of complex spike trains: to depress or to facilitate?Cerebral Cortex 10, 1143–1153.Google Scholar

McAlonan, K., Cavanaugh, J., and Wurtz, R.H. (2008). Guarding the gateway to cortex with attention in visual thalamus. Nature 456, 391–394.CrossRefGoogle ScholarPubMed

McCormick, D.A., and Bal, T. (1997). Sleep and arousal: thalamocortical mechanisms. Annual Review of Neuroscience 20, 185–215.Google Scholar

McCormick, D.A., and Huguenard, J.R. (1992). A model of the electrophysiological properties of thalamocortical relay neurons. Journal of Neurophysiology 68, 1384–1400.Google Scholar

McCormick, D.A., and Pape, H.C. (1990). Properties of a hyperpolarization-activated cation current and its role in rhythmic oscillation in thalamic relay neurones. Journal of Physiology 431, 291–318.Google Scholar

Mease, R.A., Kuner, T., Fairhall, A.L., and Groh, A. (2017). Multiplexed spike coding and adaptation in the thalamus. Cell Reports 19, 1130–1140.Google Scholar

Mejías, J.F., and Torres, J.J. (2007). The role of synaptic facilitation in spike coincidence detection. Journal of Computational Neuroscience 24, 222–234.Google Scholar

Murray, J.D., and Anticevic, A. (2017). Toward understanding thalamocortical dysfunction in schizophrenia through computational models of neural circuit dynamics. Schizophrenia Research 180, 70–77.Google Scholar

Murray, J.D., Jaramillo, J., and Wang, X.J. (2017). Working memory and decision-making in a frontoparietal circuit model. Journal of Neuroscience 37, 12167–12186.Google Scholar

Nakajima, M., and Halassa, M.M. (2017). Thalamic control of functional cortical connectivity. Current Opinion in Neurobiology 44, 127–131.Google Scholar

Nakajima, M., Schmitt, L.I., and Halassa, M.M. (2019). Prefrontal cortex regulates sensory filtering through a basal ganglia-to-thalamus pathway. Neuron 103, 445–458.e10.Google Scholar

O’Connor, D.H., Fukui, M.M., Pinsk, M.A., and Kastner, S. (2002). Attention modulates responses in the human lateral geniculate nucleus. Nature Neuroscience 5, 1203–1209.Google Scholar

Ozeki, H., Finn, I.M., Schaffer, E.S., Miller, K.D., and Ferster, D. (2009). Inhibitory stabilization of the cortical network underlies visual surround suppression. Neuron 62, 578–592.CrossRefGoogle ScholarPubMed

Panzeri, S., Macke, J.H., Gross, J., and Kayser, C. (2015). Neural population coding: combining insights from microscopic and mass signals. Trends in Cognitive Sciences 19, 162–172.CrossRefGoogle ScholarPubMed

Pape, H.C. (1996). Queer current and pacemaker: the hyperpolarization-activated cation current in neurons. Annual Review of Physiology 58, 299–327.Google Scholar

Pham, T., and Haas, J.S. (2018). Electrical synapses between inhibitory neurons shape the responses of principal neurons to transient inputs in the thalamus: a modeling study. Scientific Reports 8.Google Scholar

Phillips, J.W., Schulmann, A., Hara, E., Winnubst, J., Liu, C., Valakh, V., Wang, L., Shields, B.C., Korff, W., Chandrashekar, J., Lemire, A.L., Mensh, B., Dudman, J.T., Nelson, S.B., and Hantman, A.W. (2019). A repeated molecular architecture across thalamic pathways. Nature Neuroscience 22, 1925–1935.Google Scholar

Pinault, D. (2004). The thalamic reticular nucleus: structure, function and concept. Brain Research Reviews 46, 1–31.Google Scholar

Pinault, D., and Deschênes, M. (1998a). Anatomical evidence for a mechanism of lateral inhibition in the rat thalamus. European Journal of Neuroscience 10, 3462–3469.Google Scholar

Pinault, D., and Deschênes, M. (1998b). Projection and innervation patterns of individual thalamic reticular axons in the thalamus of the adult rat: a three-dimensional, graphic, and morphometric analysis. Journal of Comparative Neurology 391, 180–203.3.0.CO;2-Z>CrossRefGoogle Scholar

Porter, J.T., Johnson, C.K., and Agmon, A. (2001). Diverse types of interneurons generate thalamus-evoked feedforward inhibition in the mouse barrel cortex. Journal of Neuroscience 21, 2699–2710.Google Scholar

Priebe, N.J., and Ferster, D. (2008). Inhibition, spike threshold, and stimulus selectivity in primary visual cortex. Neuron 57, 482–497.Google Scholar

Ramcharan, E.J., Gnadt, J.W., and Sherman, S.M. (2005). Higher-order thalamic relays burst more than first-order relays. Proceedings of the National Academy of Sciences of the United States of America 102, 12236–12241.Google Scholar

Reinagel, P., Godwin, D., Sherman, S.M., and Koch, C. (1999). Encoding of visual information by LGN bursts. Journal of Neurophysiology 81, 2558–2569.Google Scholar

Reinhold, K., Lien, A.D., and Scanziani, M. (2015). Distinct recurrent versus afferent dynamics in cortical visual processing. Nature Neuroscience 18, 1789–1797.Google Scholar

Rikhye, R.V., Wimmer, R.D., and Halassa, M.M. (2018). Toward an integrative theory of thalamic function. Annual Review of Neuroscience 41, 163–183.Google Scholar

Ritter-Makinson, S., Clemente-Perez, A., Higashikubo, B., Cho, F.S., Holden, S.S., Bennett, E., Chkhaidze, A., Rooda, O.H.E., Cornet, M.C., Hoebeek, F.E., Yamakawa, K., Cilio, M.R., Delord, B., and Paz, J.T. (2019). Augmented reticular thalamic bursting and seizures in Scn1a-Dravet syndrome. Cell Reports 26, 54–64.e6.Google Scholar

Roberts, J.A., and Robinson, P.A. (2012). Corticothalamic dynamics: structure of parameter space, spectra, instabilities, and reduced model. Physical Review E: Statistical, Nonlinear, and Soft Matter Physics 85, 011910.Google Scholar

Rodenkirch, C., Liu, Y., Schriver, B.J., and Wang, Q. (2019). Locus coeruleus activation enhances thalamic feature selectivity via norepinephrine regulation of intrathalamic circuit dynamics. Nature Neuroscience 22, 120–133.Google Scholar

Rosenbaum, R., Rubin, J., and Doiron, B. (2012). Short term synaptic depression imposes a frequency dependent filter on synaptic information transfer. PLoS Computational Biology 8, e1002557.Google Scholar

Rosenbaum, R., Rubin, J.E., and Doiron, B. (2013). Short-term synaptic depression and stochastic vesicle dynamics reduce and shape neuronal correlations. Journal of Neurophysiology 109, 475–484.Google Scholar

Rovó, Z., Ulbert, I., and Acsády, L. (2012). Drivers of the primate thalamus. Journal of Neuroscience 32, 17894–17908.Google Scholar

Saalmann, Y.B., and Kastner, S. (2011). Cognitive and perceptual functions of the visual thalamus. Neuron 71, 209–223.Google Scholar

Saleem, A.B., Lien, A.D., Krumin, M., Haider, B., Rosón, M.R., Ayaz, A., Reinhold, K., Busse, L., Carandini, M., and Harris, K.D. (2017). Subcortical source and modulation of the narrowband gamma oscillation in mouse visual cortex. Neuron 93, 315–322.CrossRefGoogle ScholarPubMed

Sanzeni, A., Akitake, B., Goldbach, H.C., Leedy, C.E., Brunel, N., and Histed, M.H. (2020). Inhibition stabilization is a widespread property of cortical networks. eLife 9.Google Scholar

Scheibel, A.B. (1997). The thalamus and neuropsychiatric illness. Journal of Neuropsychiatry and Clinical Neurosciences 9, 342–353.Google Scholar

Schmitt, L.I., Wimmer, R.D., Nakajima, M., Happ, M., Mofakham, S., and Halassa, M.M. (2017). Thalamic amplification of cortical connectivity sustains attentional control. Nature 545, 219–223.Google Scholar

Sherman, S. (2001). Tonic and burst firing: dual modes of thalamocortical relay. Trends in Neurosciences 24, 122–126.Google Scholar

Sherman, S.M. (2012). Thalamocortical interactions. Current Opinion in Neurobiology 22, 575–579.CrossRefGoogle ScholarPubMed

Sherman, S.M. (2016). Thalamus plays a central role in ongoing cortical functioning. Nature Neuroscience 19, 533–541.Google Scholar

Sherman, S.M., and Guillery, R.W. (1996). Functional organization of thalamocortical relays. Journal of Neurophysiology 76, 1367–1395.Google Scholar

Shosaku, A. (1986). Cross-correlation analysis of a recurrent inhibitory circuit in the rat thalamus. Journal of Neurophysiology 55, 1030–1043.CrossRefGoogle ScholarPubMed

Shosaku, A., Kayama, Y., Sumitomo, I., Sugitani, M., and Iwama, K. (1989). Analysis of recurrent inhibitory circuit in rat thalamus: neurophysiology of the thalamic reticular nucleus. Progress in Neurobiology 32, 77–102.Google Scholar

Sohal, V.S., and Huguenard, J.R. (1998). Long-range connections synchronize rather than spread intrathalamic oscillations: computational modeling and in vitro electrophysiology. Journal of Neurophysiology 80, 1736–1751.CrossRefGoogle ScholarPubMed

Soto-Sánchez, C., Wang, X., Vaingankar, V., Sommer, F.T., and Hirsch, J.A. (2017). Spatial scale of receptive fields in the visual sector of the cat thalamic reticular nucleus. Nature Communications 8, 800.Google Scholar

Steriade, M., Domich, L., Oakson, G., and Deschênes, M. (1987). The deafferented reticular thalamic nucleus generates spindle rhythmicity. Journal of Neurophysiology 57, 260–273.Google Scholar

Steriade, M., McCormick, D., and Sejnowski, T. (1993). Thalamocortical oscillations in the sleeping and aroused brain. Science 262, 679–685.Google Scholar

Steriade, M., Nunez, A., and Amzica, F. (1993). Intracellular analysis of relations between the slow (<1 Hz) neocortical oscillation and other sleep rhythms of the electroencephalogram. Journal of Neuroscience 13, 3266–3283.Google Scholar

Swadlow, H.A., and Gusev, A.G. (2001). The impact of “bursting” thalamic impulses at a neocortical synapse. Nature Neuroscience 4, 402–408.Google Scholar

Tarasenko, A.N., Kostyuk, P.G., Eremin, A.V., and Isaev, D.S. (1997). Two types of low-voltage-activated Ca²⁺ channels in neurones of rat laterodorsal thalamic nucleus. Journal of Physiology 499, 77–86.Google Scholar

Temereanca, S., Brown, E.N., and Simons, D.J. (2008). Rapid changes in thalamic firing synchrony during repetitive whisker stimulation. Journal of Neuroscience 28, 11153–11164.Google Scholar

Tian, Y., Margulies, D.S., Breakspear, M., and Zalesky, A. (2020). Topographic organization of the human subcortex unveiled with functional connectivity gradients. Nature Neuroscience 23, 1421–1432.Google Scholar

Timofeev, I., Bazhenov, M., Seigneur, J., and Sejnowski, T. (2012). Neuronal synchronization and thalamocortical rhythms in sleep, wake and epilepsy. In Noebels, J.L., Avoli, M., Rogawski, M.A., Olsen, R.W., and Delgado-Escueta, A.V., eds.,Jasper’s basic mechanisms of the epilepsies [Internet], 4th ed. (National Center for Biotechnology Information).Google Scholar

Timofeev, I., Bonjean, M.E., and Bazhenov, M. (2020).Cellular mechanisms of thalamocortical oscillations in the sleeping brain (Springer).Google Scholar

Timofeev, I., and Steriade, M. (1996). Low-frequency rhythms in the thalamus of intact-cortex and decorticated cats. Journal of Neurophysiology 76, 4152–4168.Google Scholar

Tottene, A., Favero, M., and Pietrobon, D. (2019). Enhanced thalamocortical synaptic transmission and dysregulation of the excitatory–inhibitory balance at the thalamocortical feedforward inhibitory microcircuit in a genetic mouse model of migraine. Journal of Neuroscience 39, 9841–9851.CrossRefGoogle Scholar

Traub, R.D., Contreras, D., Cunningham, M.O., Murray, H., LeBeau, F.E.N., Roopun, A., Bibbig, A., Wilent, W.B., Higley, M.J., and Whittington, M.A. (2005). Single-column thalamocortical network model exhibiting gamma oscillations, sleep spindles, and epileptogenic bursts. Journal of Neurophysiology 93, 2194–2232.Google Scholar

Tsodyks, M., Pawelzik, K., and Markram, H. (1998). Neural networks with dynamic synapses. Neural Computation 10, 821–835.Google Scholar

Tsodyks, M., and Wu, S. (2013). Short-term synaptic plasticity. Scholarpedia 8, 3153. Revision #182521.CrossRefGoogle Scholar

Urbain, N., Salin, P.A., Libourel, P.A., Comte, J.C., Gentet, L.J., and Petersen, C.C. (2015). Whisking-related changes in neuronal firing and membrane potential dynamics in the somatosensory thalamus of awake mice. Cell Reports 13, 647–656.Google Scholar

Usrey, W.M., and Sherman, S.M. (2018). Corticofugal circuits: communication lines from the cortex to the rest of the brain. Journal of Comparative Neurology 527, 640–650.Google Scholar

Vantomme, G., Rovó, Z., Cardis, R., Béard, E., Katsioudi, G., Guadagno, A., Perrenoud, V., Fernandez, L.M.J., and Lüthi, A. (2020). A thalamic reticular circuit for head direction cell tuning and spatial navigation. Cell Reports 31, 107747.Google Scholar

Viaene, A.N., Petrof, I., and Sherman, S.M. (2011). Synaptic properties of thalamic input to layers 2/3 and 4 of primary somatosensory and auditory cortices. Journal of Neurophysiology 105, 279–292.Google Scholar

Wang, X., Wei, Y., Vaingankar, V., Wang, Q., Koepsell, K., Sommer, F.T., and Hirsch, J.A. (2007). Feedforward excitation and inhibition evoke dual modes of firing in the cat’s visual thalamus during naturalistic viewing. Neuron 55, 465–478.Google Scholar

Wang, X.J. (2020).Macroscopic gradients of synaptic excitation and inhibition in the neocortex. Nature Reviews Neuroscience 21, 169–178.Google Scholar

Wang, X.J., Golomb, D., and Rinzel, J. (1995). Emergent spindle oscillations and intermittent burst firing in a thalamic model: specific neuronal mechanisms. Proceedings of the National Academy of Sciences of the United States of America 92, 5577–5581.Google Scholar

Wei, H., Bonjean, M., Petry, H.M., Sejnowski, T.J., and Bickford, M.E. (2011). Thalamic burst firing propensity: a comparison of the dorsal lateral geniculate and pulvinar nuclei in the tree shrew. Journal of Neuroscience 31, 17287–17299.Google Scholar

Wells, M.F., Wimmer, R.D., Schmitt, L.I., Feng, G., and Halassa, M.M. (2016). Thalamic reticular impairment underlies attention deficit in Ptchd1^Y/− mice. Nature 532, 58–63.Google Scholar

Wester, J.C., and Contreras, D. (2013). Differential modulation of spontaneous and evoked thalamocortical network activity by acetylcholine level in vitro. Journal of Neuroscience 33, 17951–17966.Google Scholar

Whitmire, C.J., Waiblinger, C., Schwarz, C., and Stanley, G.B. (2016). Information coding through adaptive gating of synchronized thalamic bursting. Cell Reports 14, 795–807.CrossRefGoogle ScholarPubMed

Willis, A.M., Slater, B.J., Gribkova, E.D., and Llano, D.A. (2015). Open-loop organization of thalamic reticular nucleus and dorsal thalamus: a computational model. Journal of Neurophysiology 114, 2353–2367.Google Scholar

Wimmer, R.D., Schmitt, L.I., Davidson, T.J., Nakajima, M., Deisseroth, K., and Halassa, M.M. (2015). Thalamic control of sensory selection in divided attention. Nature 526, 705–709.Google Scholar

Wolfart, J., Debay, D., Masson, G.L., Destexhe, A., and Bal, T. (2005). Synaptic background activity controls spike transfer from thalamus to cortex. Nature Neuroscience 8, 1760–1767.Google Scholar

Yang, S., Meng, Y., Li, J., Li, B., Fan, Y.S., Chen, H., and Liao, W. (2020). The thalamic functional gradient and its relationship to structural basis and cognitive relevance. NeuroImage 218, 116960.Google Scholar

Zeldenrust, F., Wadman, W.J., and Englitz, B. (2018). Neural coding with bursts—current state and future perspectives. Frontiers in Computational Neuroscience 12.Google Scholar

Zikopoulos, B., and Barbas, H. (2006). Prefrontal projections to the thalamic reticular nucleus form a unique circuit for attentional mechanisms. Journal of Neuroscience 26, 7348–7361.Google Scholar

Zikopoulos, B., and Barbas, H. (2012). Pathways for emotions and attention converge on the thalamic reticular nucleus in primates. Journal of Neuroscience 32, 5338–5350.Google Scholar

Arnsten, A. F. T., Wang, M. J., & Paspalas, C. D. (2012, October). Neuromodulation of thought: Flexibilities and vulnerabilities in prefrontal cortical network synapses. Neuron, 76(1), 223–239. doi: 10.1016/j.neuron.2012.08.038Google Scholar

Baars, B. J. (1988). A Cognitive Theory of Consciousness. New York: Cambridge University Press.Google Scholar

Badre, D., & Frank, M. J. (2012, March). Mechanisms of hierarchical reinforcement learning in corticostriatal circuits 2: Evidence from fMRI. Cerebral Cortex, 22(3), 527–536. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21693491Google Scholar

Bastos, A. M., Usrey, W. M., Adams, R. A., Mangun, G. R., Fries, P., & Friston, K. J. (2012, November). Canonical microcircuits for predictive coding. Neuron, 76(4), 695–711. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23177956Google Scholar

Bender, D. B., & Youakim, M. (2001, January). Effect of attentive fixation in macaque thalamus and cortex. Journal of Neurophysiology, 85, 219–234. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11152722Google Scholar

Bisley, J. W., & Goldberg, M. E. (2010). Attention, intention, and priority in the parietal lobe. Annual Review of Neuroscience, 33, 1–21. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/20192813Google Scholar

Bortone, D. S., Olsen, S. R., & Scanziani, M. (2014, April). Translaminar inhibitory cells recruited by layer 6 corticothalamic neurons suppress visual cortex. Neuron, 82(2), 474–485. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/24656931Google Scholar

Braver, T. S., & Cohen, J. D. (2000, December). On the control of control: The role of dopamine in regulating prefrontal function and working memory. In Monsell, S. & Driver, J. (Eds.), Control of Cognitive Processes: Attention and Performance XVIII (pp. 713–737). Cambridge, MA: MIT Press.Google Scholar

Braver, T. S., Paxton, J. L., Locke, H. S., & Barch, D. M. (2009, May). Flexible neural mechanisms of cognitive control within human prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America, 106(18), 7351–7356.CrossRefGoogle ScholarPubMed

Brown, R. G., & Marsden, C. D. (1990, February). Cognitive function in Parkinson’s disease: From description to theory. Trends in Neurosciences, 13, 21–29. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/1688671Google Scholar

Buffalo, E. A., Fries, P., Landman, R., Buschman, T. J., & Desimone, R. (2011, July). Laminar differences in gamma and alpha coherence in the ventral stream. Proceedings of the National Academy of Sciences of the United States of America, 108(27), 11262–11267. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21690410Google Scholar

Buschman, T. J., & Kastner, S. (2015, October). From behavior to neural dynamics: An integrated theory of attention. Neuron, 88(1), 127–144. doi: 10.1016/j.neuron.2015.09.017Google Scholar

Cavanagh, P., Hunt, A. R., Afraz, A., & Rolfs, M. (2010, April). Visual stability based on remapping of attention pointers. Trends in Cognitive Sciences, 14(4), 147–153. doi: 10.1016/j.tics.2010.01.007Google Scholar

Chatham, C. H., Frank, M., & Badre, D. (2014, January). Corticostriatal output gating during selection from working memory. Neuron, 81(4), 930–942.Google Scholar

Chatham, C. H., Herd, S. A., Brant, A. M., Hazy, T. E., Miyake, A., O’Reilly, R. C., & Friedman, N. P. (2011, November). From an executive network to executive control: A computational model of the n-back task. Journal of Cognitive Neuroscience, 23, 3598–3619. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21563882Google Scholar

Chen, H., Hua, S. E., Smith, M. A., Lenz, F. A., & Shadmehr, R. (2006, October). Effects of human cerebellar thalamus disruption on adaptive control of reaching. Cerebral Cortex, 16(10), 1462–1473. doi: 10.1093/cercor/bhj087Google Scholar

Clark, A. (2013, June). Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences, 36(3), 181–204. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23663408Google Scholar

Clascá, F., Rubio-Garrido, P., & Jabaudon, D. (2012). Unveiling the diversity of thalamocortical neuron subtypes. European Journal of Neuroscience, 35(10), 1524–1532. doi: 10.1111/j.1460-9568.2012.08033.xGoogle Scholar

Clayton, M. S., Yeung, N., & Kadosh, R. C. (2018). The many characters of visual alpha oscillations. European Journal of Neuroscience, 48(7), 2498–2508. doi: 10.1111/ejn.13747Google Scholar

Connors, B. W., Gutnick, M. J., & Prince, D. A. (1982, December). Electrophysiological properties of neocortical neurons in vitro. Journal of Neurophysiology, 48(6), 1302–1320. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/6296328Google Scholar

Crick, F. (1984, July). Function of the thalamic reticular complex: The searchlight hypothesis. Proceedings of the National Academy of Sciences of the United States of America, 81, 4586–4590. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/6589612Google Scholar

Crick, F. (1989, February). The recent excitement about neural networks. Nature, 337, 129–132. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/2911347Google Scholar

Dahlin, E., Neely, A. S., Larsson, A., Backman, L., & Nyberg, L. (2008, June). Transfer of learning after updating training mediated by the striatum. Science, 320(5882), 1510–1512. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/18556560Google Scholar

Dayan, P., Hinton, G. E., Neal, R. N., & Zemel, R. S. (1995, January). The Helmholtz machine. Neural Computation, 7(5), 889–904.Google Scholar

Dehaene, S., & Naccache, L. (2001, February). Towards a cognitive neuroscience of consciousness: Basic evidence and a workspace framework. Cognition, 79(1–2), 1–37. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11164022Google Scholar

Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18(1), 193–222. doi: 10.1146/annurev.ne.18.030195.001205Google Scholar

Dougherty, K., Cox, M. A., Ninomiya, T., Leopold, D. A., & Maier, A. (2017, February). Ongoing alpha activity in v1 regulates visually driven spiking responses. Cerebral Cortex, 27(2), 1113–1124. doi: 10.1093/cercor/bhv304Google Scholar

Duhamel, J. R., Colby, C. L., & Goldberg, M. E. (1992, April). The updating of the representation of visual space in parietal cortex by intended eye movements. Science, 255(5040), 90–92. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/1553535Google Scholar

Edelman, G. M., & Tononi, G. (2001). A Universe of Consciousness: How Matter Becomes Imagination. New York, NY: Basic Books.Google Scholar

Elman, J., Bates, E., Karmiloff-Smith, A., Johnson, M., Parisi, D., & Plunkett, K. (1996). Rethinking Innateness: A Connectionist Perspective on Development. Cambridge, MA: MIT Press.Google Scholar

Elman, J. L. (1990, January). Finding structure in time. Cognitive Science, 14(2), 179–211.Google Scholar

Elston, G. N. (2003). Cortex, cognition and the cell: New insights into the pyramidal neuron and prefrontal function. Cerebral Cortex, 13(11), 1124–1138. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/14576205Google Scholar

Farah, M. J. (1990). Visual Agnosia. Cambridge, MA: MIT Press.Google Scholar

Fiebelkorn, I. C., & Kastner, S. (2019, February). A rhythmic theory of attention. Trends in Cognitive Sciences, 23(2), 87–101. doi: 10.1016/j.tics.2018.11.009Google Scholar

Fiebelkorn, I. C., Pinsk, M. A., & Kastner, S. (2018, August). A dynamic interplay within the frontoparietal network underlies rhythmic spatial attention. Neuron, 99(4), 842–853.e8. doi: 10.1016/j.neuron.2018.07.038Google Scholar

Franceschetti, S., Guatteo, E., Panzica, F., Sancini, G., Wanke, E., & Avanzini, G. (1995, October). Ionic mechanisms underlying burst firing in pyramidal neurons: Intracellular study in rat sensorimotor cortex. Brain Research, 696(1–2), 127–139. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/8574660Google Scholar

Frandolig, J. E., Matney, C. J., Lee, K., Kim, J., Chevée, M., Kim, S.-J., … Brown, S. P. (2019, September). The synaptic organization of layer 6 circuits reveals inhibition as a major output of a neocortical sublamina. Cell Reports, 28(12), 3131–3143.e5. doi: 10.1016/j.celrep.2019.08.048Google Scholar

Frank, M. J. (2005, January). When and when not to use your subthalamic nucleus: Lessons from a computational model of the basal ganglia. In Seth, A. K., Prescott, T. J., & Bryson, J. J. (Eds.), Modelling Natural Action Selection: Proceedings of an International Workshop (pp. 53–60). Sussex: AISB.Google Scholar

Frank, M. J., Loughry, B., & O’Reilly, R. C. (2001, January). Interactions between the frontal cortex and basal ganglia in working memory: A computational model. Cognitive, Affective, and Behavioral Neuroscience, 1, 137–160. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/12467110Google Scholar

Friston, K. (2005, April). A theory of cortical responses. Philosophical Transactions of the Royal Society B, 360(1456), 815–836. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/15937014Google Scholar

Friston, K. (2010, February). The free-energy principle: A unified brain theory? Nature Reviews Neuroscience, 11(2), 127–138. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/20068583Google Scholar

Gerfen, C. R., & Surmeier, D. J. (2011). Modulation of striatal projection systems by dopamine. Annual Review of Neuroscience, 34, 441–466. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21469956CrossRefGoogle ScholarPubMed

Gers, F. A., Schmidhuber, J., & Cummins, F. (2000, November). Learning to forget: Continual prediction with LSTM. Neural Computation, 12, 2451–2471. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11032042Google Scholar

Giguere, M., & Goldman-Rakic, P. S. (1988). Mediodorsal nucleus: Areal, laminar, and tangential distribution of afferents and efferents in the frontal lobe of rhesus monkeys. Journal of Comparative Neurology, 277(2), 195–213. doi: 10.1002/cne.902770204Google Scholar

Graybiel, A. M. (1995). Building action repertoires: Memory and learning functions of the basal ganglia. Current Opinion in Neurobiology, 5(6), 733–741. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/8805417Google Scholar

Grossberg, S. (1999). How does the cerebral cortex work? Learning, attention, and grouping by the laminar circuits of visual cortex. Spatial Vision, 12. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/10221426Google Scholar

Guo, K., Yamawaki, N., Svoboda, K., & Shepherd, G. M. G. (2018, October). Anterolateral motor cortex connects with a medial subdivision of ventromedial thalamus through cell type-specific circuits, forming an excitatory thalamo-cortico-thalamic loop via layer 1 apical tuft dendrites of layer 5b pyramidal tract type neurons. Journal of Neuroscience, 38(41), 8787–8797. doi: 10.1523/JNEUROSCI.1333-18.2018Google Scholar

Guo, Z. V., Inagaki, H. K., Daie, K., Druckmann, S., Gerfen, C. R., & Svoboda, K. (2017, May). Maintenance of persistent activity in a frontal thalamocortical loop. Nature, 545(7653), 181–186. doi: 10.1038/nature22324Google Scholar

Halassa, M. M., & Kastner, S. (2017, December). Thalamic functions in distributed cognitive control. Nature Neuroscience, 20(12), 1669. doi: 10.1038/s41593-017-0020-1Google Scholar

Halassa, M. M., Siegle, J. H., Ritt, J. T., Ting, J. T., Feng, G., & Moore, C. I. (2011, September). Selective optical drive of thalamic reticular nucleus generates thalamic bursts and cortical spindles. Nature Neuroscience, 14(9), 1118–1120. doi: 10.1038/nn.2880Google Scholar

Harris, K. D., & Shepherd, G. M. G. (2015, February). The neocortical circuit: Themes and variations. Nature Neuroscience, 18(2), 170–181. doi: 10.1038/nn.3917Google Scholar

Hazy, T. E., Frank, M. J., & O’Reilly, R. C. (2006, April). Banishing the homunculus: Making working memory work. Neuroscience, 139, 105–118. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/16343792Google Scholar

Hazy, T. E., Frank, M. J., & O’Reilly, R. C. (2007, August). Towards an executive without a homunculus: Computational models of the prefrontal cortex/basal ganglia system. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 362(1485), 1601–1613. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/17428778Google Scholar

He, B. J., Snyder, A. Z., Vincent, J. L., Epstein, A., Shulman, G. L., & Corbetta, M. (2007, March). Breakdown of functional connectivity in frontoparietal networks underlies behavioral deficits in spatial neglect. Neuron, 53(6), 905–918. doi: 10.1016/j.neuron.2007.02.013Google Scholar

Herd, S. A., Krueger, K., Nair, A., Mollick, J., & O’Reilly, R. (2019). Neural mechanisms of human decision-making. Cognitive Affective and Behavioral Neuroscience. Retrieved from https://arxiv.org/abs/1912.07660Google Scholar

Herd, S. A., O’Reilly, R. C., Hazy, T. E., Chatham, C. H., Brant, A. M., & Friedman, N. P. (2014, April). A neural network model of individual differences in task switching abilities. Neuropsychologia, 62, 375–389. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/24791709Google Scholar

Hochreiter, S., & Schmidhuber, J. (1997, January). Long short-term memory. Neural Computation, 9, 1735–1780.Google Scholar

Houk, J. C. (2005, June). Agents of the mind. Biological Cybernetics, 92(6), 427–437. Retrieved from http://dx.doi.org/10.1007/s00422-005–0569-8Google Scholar

Ilinsky, I. A., Jouandet, M. L., & Goldman-Rakic, P. S. (1985). Organization of the nigrothalamocortical system in the rhesus monkey. Journal of Comparative Neurology, 236(3), 315–330. doi: 10.1002/cne.902360304Google Scholar

Jensen, O., Bonnefond, M., & VanRullen, R. (2012, April). An oscillatory mechanism for prioritizing salient unattended stimuli. Trends in Cognitive Sciences, 16(4), 200–206. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/22436764Google Scholar

Jones, E. G. (1998a). A new view of specific and nonspecific thalamocortical connections. Advances in Neurology, 77, 49–71. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/9709817Google Scholar

Jones, E. G. (1998b, April). Viewpoint: The core and matrix of thalamic organization. Neuroscience, 85(2), 331–345. doi: 10.1016/S0306-4522(97)00581-2Google Scholar

Jones, E. G. (2007). The Thalamus (2nd ed., Vol. 2). Cambridge: Cambridge University Press.Google Scholar

Karnath, H. O., Himmelbach, M., & Rorden, C. (2002, February). The subcortical anatomy of human spatial neglect: Putamen, caudate nucleus and pulvinar. Brain: A Journal of Neurology, 125, 350–360. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11844735Google Scholar

Kawato, M., Hayakawa, H., & Inui, T. (1993, January). A forward-inverse optics model of reciprocal connections between visual cortical areas. Network: Computation in Neural Systems, 4(4), 415–422. doi: 10.1088/0954-898X 4 4 001Google Scholar

Klimesch, W. (2011, August). Evoked alpha and early access to the knowledge system: The P1 inhibition timing hypothesis. Brain Research, 1408, 52–71. doi: 10.1016/j.brainres.2011.06.003Google Scholar

Kobatake, E., & Tanaka, K. (1994, January). Neuronal selectivities to complex object features in the ventral visual pathway. Journal of Neurophysiology, 71(3), 856–867.Google Scholar

Kohonen, T. (1989). Self-organization and associative memory.New York: Springer-Verlag.Google Scholar

Kok, P., & de Lange, F. P. (2015). Predictive coding in sensory cortex. In Forstmann, B. U. & Wagenmakers, E-J (Eds.),An Introduction to Model-Based Cognitive Neuroscience (pp. 221–244). New York: Springer. doi: 10.1007/978-1-4939-2236-9 11Google Scholar

Kok, P., Jehee, J. F. M., & de Lange, F. P. (2012, July). Less is more: Expectation sharpens representations in the primary visual cortex. Neuron, 75(2), 265–270. doi: 10.1016/j.neuron.2012.04.034Google Scholar

Kritzer, M. F., & Goldman-Rakic, P. S. (1995, August). Intrinsic circuit organization of the major layers and sublayers of the dorsolateral prefrontal cortex in the rhesus monkey. Journal of Comparative Neurology, 359(1), 131–143. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/8557842Google Scholar

Kuramoto, E., Furuta, T., Nakamura, K. C., Unzai, T., Hioki, H., & Kaneko, T. (2009, September). Two types of thalamocortical projections from the motor thalamic nuclei of the rat: A single neuron-tracing study using viral vectors. Cerebral cortex, 19(9), 2065–2077. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/19174446Google Scholar

Kuramoto, E., Ohno, S., Furuta, T., Unzai, T., Tanaka, Y. R., Hioki, H., & Kaneko, T. (2015, January). Ventral medial nucleus neurons send thalamocortical afferents more widely and more preferentially to layer 1 than neurons of the ventral anterior–ventral lateral nuclear complex in the rat. Cerebral Cortex, 25(1), 221–235. doi: 10.1093/cercor/bht216Google Scholar

LaBerge, D., & Buchsbaum, M. S. (1990, March). Positron emission tomographic measurements of pulvinar activity during an attention task. Journal of Neuroscience, 10, 613–619. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/2303863Google Scholar

Lamme, V. A. F. (2006, January). Towards a true neural stance on consciousness. Trends in Cognitive Sciences, 10(11), 494–501. doi: 10.1016/j.tics.2006.09.001Google Scholar

Larkum, M. E., Petro, L. S., Sachdev, R. N. S., & Muckli, L. (2018). A perspective on cortical layering and layer-spanning neuronal elements. Frontiers in Neuroanatomy, 12. doi: 10.3389/fnana.2018.00056Google Scholar

Larkum, M. E., Zhu, J. J., & Sakmann, B. (1999, March). A new cellular mechanism for coupling inputs arriving at different cortical layers. Nature, 398(6725), 338–341. doi: 10.1038/18686Google Scholar

LeCun, Y., Bengio, Y., & Hinton, G. (2015, May). Deep learning. Nature, 521(7553), 436–444. doi: 10.1038/nature14539Google Scholar

Lee, T. S., & Mumford, D. (2003, July). Hierarchical Bayesian inference in the visual cortex. Journal of the Optical Society of America, 20(7), 1434–1448. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/12868647/Google Scholar

Lewis, L. D., Voigts, J., Flores, F. J., Schmitt, L. I., Wilson, M. A., Halassa, M. M., & Brown, E. N. (2015, October). Thalamic reticular nucleus induces fast and local modulation of arousal state. eLife, 4, e08760. doi: 10.7554/eLife.08760Google Scholar

Lillicrap, T. P., Santoro, A., Marris, L., Akerman, C. J., & Hinton, G. (2020, June). Backpropagation and the brain. Nature Reviews Neuroscience, 21(6), 335–346. doi: 10.1038/s41583-020-0277-3Google Scholar

Lisman, J. E., Fellous, J. M., & Wang, X. J. (1999, April). A role for NMDA-receptor channels in working memory. Nature Neuroscience, 1, 273–275. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/10195158Google Scholar

Lotter, W., Kreiman, G., & Cox, D. (2016, May). Deep predictive coding networks for video prediction and unsupervised learning. arXiv:1605.08104 [cs, q-bio]. Retrieved from http://arxiv.org/abs/1605.08104Google Scholar

Luczak, A., Bartho, P., & Harris, K. D. (2009, May). Spontaneous events outline the realm of possible sensory responses in neocortical populations. Neuron, 62(3), 413–425. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/19447096Google Scholar

Luczak, A., Bartho, P., & Harris, K. D. (2013, January). Gating of sensory input by spontaneous cortical activity. Journal of Neuroscience, 33(4), 1684–1695. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23345241Google Scholar

Luo, Y., Boix, X., Roig, G., Poggio, T., & Zhao, Q. (2015, November). Foveation-based mechanisms alleviate adversarial examples. arXiv:1511.06292 [cs]. Retrieved from http://arxiv.org/abs/1511.06292Google Scholar

Makeig, S., Westerfield, M., Jung, T. P., Enghoff, S., Townsend, J., Courchesne, E., & Sejnowski, T. J. (2002, January). Dynamic brain sources of visual evoked responses. Science, 295, 690–693.Google Scholar

Manto, M. (2009, April). Mechanisms of human cerebellar dysmetria: Experimental evidence and current conceptual bases. Journal of NeuroEngineering and Rehabilitation, 6(1), 10. doi: 10.1186/1743-0003-6–10Google Scholar

Markov, N. T., Vezoli, J., Chameau, P., Falchier, A., Quilodran, R., Huissoud, C., … Kennedy, H. (2014, January). Anatomy of hierarchy: Feedforward and feedback pathways in macaque visual cortex: Cortical counterstreams. Journal of Comparative Neurology, 522(1), 225–259. doi: 10.1002/cne.23458Google Scholar

Mathewson, K., Gratton, G., Fabiani, M., Beck, D., & Ro, T. (2009). To see or not to see: Prestimulus alpha phase predicts visual awareness. Journal of Neuroscience, 29(9), 2725–2732.Google Scholar

Mathewson, K. E., Prudhomme, C., Fabiani, M., Beck, D. M., Lleras, A., & Gratton, G. (2012, August). Making waves in the stream of consciousness: Entraining oscillations in EEG alpha and fluctuations in visual awareness with rhythmic visual stimulation. Journal of Cognitive Neuroscience, 24(12), 2321–2333. doi: 10.1162/jocn a 00288Google Scholar

Middleton, F. A., & Strick, P. L. (2000, May). Basal ganglia and cerebellar loops: Motor and cognitive circuits. Brain Research, 31(2–3), 236–250. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/10719151Google Scholar

Mink, J. W. (1996, March). The basal ganglia: Focused selection and inhibition of competing motor programs. Progress in Neurobiology, 50(4), 381–425. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/9004351Google Scholar

Mumford, D. (1991, June). On the computational architecture of the neocortex. Biological Cybernetics, 65(2), 135–145. doi: 10.1007/BF00202389Google Scholar

Mumford, D. (1992). On the computational architecture of the neocortex. II. The role of cortico-cortical loops. Biological Cybernetics, 66(3), 241–251. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/1540675Google Scholar

Münkle, M. C., Waldvogel, H. J., & Faull, R. L. M. (2000, July). The distribution of calbindin, calretinin and parvalbumin immunoreactivity in the human thalamus. Journal of Chemical Neuroanatomy, 19(3), 155–173. doi: 10.1016/S0891-0618(00)00060-0Google Scholar

Nambu, A. (2008, December). Seven problems on the basal ganglia. Current Opinion in Neurobiology, 18(6), 595–604. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/19081243Google Scholar

Olsen, S., Bortone, D., Adesnik, H., & Scanziani, M. (2012, February). Gain control by layer six in cortical circuits of vision. Nature, 483(7387), 47–52.Google Scholar

O’Reilly, R. C. (1996, January). Biologically plausible error-driven learning using local activation differences: The generalized recirculation algorithm. Neural Computation, 8(5), 895–938. doi: 10.1162/neco.1996.8.5.895Google Scholar

O’Reilly, R. C. (2006, October). Biologically based computational models of high-level cognition. Science, 314(5796), 91–94. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/17023651Google Scholar

O’Reilly, R. C. (2020, April). Unraveling the mysteries of motivation. Trends in Cognitive Sciences, 24(6), 425–434. doi: 10.1016/j.tics.2020.03.001Google Scholar

O’Reilly, R. C., & Frank, M. J. (2006). Making working memory work: A computational model of learning in the prefrontal cortex and basal ganglia. Neural Computation, 18(2), 283–328. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/16378516Google Scholar

O’Reilly, R. C., Hazy, T. E., & Herd, S. A. (2016). The Leabra cognitive architecture: How to play 20 principles with nature and win! In Chipman, S. (Ed.), Oxford Handbook of Cognitive Science. Oxford: Oxford University Press. Retrieved from http://www.oxfordhandbooks.com/view/10.1093/oxfordhb/9780199842193.001.0001/oxfordhb-9780199842193-e-8Google Scholar

O’Reilly, R. C., & Munakata, Y. (2000). Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain. Cambridge, MA: MIT Press.Google Scholar

O’Reilly, R. C., Munakata, Y., Frank, M. J., Hazy, T. E., & Contributors. (2012). Computational Cognitive Neuroscience. Wiki Book, 1st Ed. Retrieved from http://ccnbook.colorado.eduGoogle Scholar

O’Reilly, R. C., Nair, A., Russin, J. L., & Herd, S. A. (2020, March). How Sequential interactive processing within frontostriatal loops supports a continuum of habitual to controlled processing. Frontiers in Psychology, 11, 380. doi: 10.3389/fpsyg.2020.00380Google Scholar

O’Reilly, R. C., Noelle, D. C., Braver, T. S., & Cohen, J. D. (2002, February). Prefrontal cortex and dynamic categorization tasks: Representational organization and neuromodulatory control. Cerebral Cortex, 12, 246–257. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11839599Google Scholar

O’Reilly, R. C., Russin, J. L., Zolfaghar, M., & Rohrlich, J. (2021). Deep predictive learning in neocortex and pulvinar. Journal of Cognitive Neuroscience, 33(6), 1158–1196.Google Scholar

O’Reilly, R. C., Wyatte, D., Herd, S. A., Mingus, B., & Jilk, D. J. (2013). Recurrent processing during object recognition. Frontiers in Psychology, 4(124). Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23554596Google Scholar

O’Reilly, R. C., Wyatte, D., & Rohrlich, J. (2014, July). Learning through time in the thalamocortical loops. arXiv:1407.3432 [q-bio]. Retrieved from http://arxiv.org/abs/1407.3432Google Scholar

O’Reilly, R. C., Wyatte, D. R., & Rohrlich, J. (2017, September). Deep predictive learning: A comprehensive model of three visual streams. arXiv:1709.04654 [q-bio]. Retrieved from http://arxiv.org/abs/1709.04654Google Scholar

Ouden, H. E. M., Kok, P., & Lange, F. P. (2012). How prediction errors shape perception, attention, and motivation. Frontiers in Psychology, 3(548). Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23248610Google Scholar

Pasupathy, A., & Miller, E. K. (2005, January). Different time courses for learning-related activity in the prefrontal cortex and striatum. Nature, 433, 873–876. Retrieved from http://www.nature.com/nature/journal/v433/n7028/full/nature03287.htmlGoogle Scholar

Petersen, S. E., Robinson, D. L., & Morris, J. D. (1987, January). Contributions of the pulvinar to visual spatial attention. Neuropsychologia, 25(1), 97–105. doi: 10.1016/0028-3932(87)90046-7Google Scholar

Phillips, J. W., Schulmann, A., Hara, E., Winnubst, J., Liu, C., Valakh, V., … Hantman, A. W. (2019, November). A repeated molecular architecture across thalamic pathways. Nature Neuroscience, 22(11), 1925–1935. doi: 10.1038/s41593-019-0483-3Google Scholar

Rac-Lubashevsky, R., & Frank, M. J. (2020, December). Analogous computations in working memory input, output and motor gating: Electrophysiological and computational modeling evidence. bioRxiv, 2020.12.21.423791. doi: 10.1101/2020.12.21.423791Google Scholar

Raizada, R. D. S., & Grossberg, S. (2003, January). Towards a theory of the laminar architecture of cerebral cortex: Computational clues from the visual system. Cerebral Cortex, 13(1), 100–113. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/12466221Google Scholar

Ramaswamy, S., & Markram, H. (2015). Anatomy and physiology of the thick-tufted layer 5 pyramidal neuron. Frontiers in Cellular Neuroscience, 9. doi: 10.3389/fncel.2015.00233Google Scholar

Rao, R. P., & Ballard, D. H. (1999, January). Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience, 2(1), 79–87. doi: 10.1038/4580Google Scholar

Redinbaugh, M. J., Phillips, J. M., Kambi, N. A., Mohanta, S., Andryk, S., Dooley, G. L., … Saalmann, Y. B. (2020, April). Thalamus modulates consciousness via layer-specific control of cortex. Neuron, 106(1), 66–75.e12. doi: 10.1016/j.neuron.2020.01.005Google Scholar

Reynolds, J. H., & Desimone, R. (2003, March). Interacting roles of attention and visual salience in V4. Neuron, 37, 853–863. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/12628175Google Scholar

Reynolds, J. H., & Heeger, D. J. (2009, January). The normalization model of attention. Neuron, 61(2), 168–185. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/19186161/Google Scholar

Richter, D., & de Lange, F. P. (2019, August). Statistical learning attenuates visual activity only for attended stimuli. eLife, 8, e47869. doi: 10.7554/eLife.47869Google Scholar

Rikhye, R. V., Gilra, A., & Halassa, M. M. (2018, December). Thalamic regulation of switching between cortical representations enables cognitive flexibility. Nature Neuroscience, 21(12), 1753–1763. doi: 10.1038/s41593-018-0269-zGoogle Scholar

Ringach, DL. Sparse thalamo cortical convergence. Current Biology. 2021 May 24;31(10):2199–202.Google Scholar

Robinson, D. L., & Petersen, S. E. (1992, June). The pulvinar and visual salience. Trends in Neurosciences, 15, 127–132. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/1374970Google Scholar

Rougier, N. P., & O’Reilly, R. C. (2002, January). Learning representations in a gated prefrontal cortex model of dynamic task switching. Cognitive Science, 26, 503–520. Retrieved from http://onlinelibrary.wiley.com/doi/abs/10.1207/s15516709cog26044Google Scholar

Rovó, Z., Ulbert, I., & Acsády, L. (2012, December). Drivers of the primate thalamus. Journal of Neuroscience, 32(49), 17894–17908. doi: 10.1523/JNEUROSCI.2815-12.2012Google Scholar

Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986, January). Learning representations by back-propagating errors. Nature, 323(9), 533–536.Google Scholar

Rumelhart, D. E., & Zipser, D. (1985, January). Feature discovery by competitive learning. Cognitive Science, 9(1), 75–112. doi: 10.1207/s15516709cog0901 5Google Scholar

Saalmann, Y. B., & Kastner, S. (2011, July). Cognitive and perceptual functions of the visual thalamus. Neuron, 71(2), 209–223. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21791281Google Scholar

Saalmann, Y. B., Pinsk, M. A., Wang, L., Li, X., & Kastner, S. (2012, August). The pulvinar regulates information transmission between cortical areas based on attention demands. Science, 337(6095), 753–756. doi: 10.1126/science.1223082Google Scholar

Sakata, S., & Harris, K. D. (2009, November). Laminar structure of spontaneous and sensory-evoked population activity in auditory cortex. Neuron, 64(3), 404–418. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/19914188Google Scholar

Sakata, S., & Harris, K. D. (2012). Laminar-dependent effects of cortical state on auditory cortical spontaneous activity. Frontiers in Neural Circuits, 6. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23267317Google Scholar

Sanders, H., Berends, M., Major, G., Goldman, M. S., & Lisman, J. E. (2013, January). NMDA and GABA_B (KIR) conductances: The “perfect couple” for bistability. Journal of Neuroscience, 33(2), 424–429. doi: 10.1523/JNEUROSCI.1854-12.2013Google Scholar

Schiff, N. D. (2008). Central thalamic contributions to arousal regulation and neurological disorders of consciousness. Annals of the New York Academy of Sciences, 1129(1), 105–118. doi: 10.1196/annals.1417.029Google Scholar

Shen, W., Flajolet, M., Greengard, P., & Surmeier, D. J. (2008, August). Dichotomous dopaminergic control of striatal synaptic plasticity. Science, 321(5890), 848–851. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/18687967Google Scholar

Sherman, S. M., & Guillery, R. W. (2006). Exploring the Thalamus and Its Role in Cortical Function. Cambridge, MA: MIT Press. Retrieved from http://www.scholarpedia.org/article/ThalamusGoogle Scholar

Shipp, S. (2003, October). The functional logic of cortico-pulvinar connections. Philosophical Transactions of the Royal Society of London B, 358(1438), 1605–1624. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/14561322CrossRefGoogle ScholarPubMed

Silva, L. R., Amitai, Y., & Connors, B. W. (1991, January). Intrinsic oscillations of neocortex generated by layer 5 pyramidal neurons. Science, 251(4992), 432–435. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/1824881Google Scholar

Sinz, F. H., Pitkow, X., Reimer, J., Bethge, M., & Tolias, A. S. (2019, September). Engineering a less artificial intelligence. Neuron, 103(6), 967–979. doi: 10.1016/j.neuron.2019.08.034Google Scholar

Snow, J. C., Allen, H. A., Rafal, R. D., & Humphreys, G. W. (2009, March). Impaired attentional selection following lesions to human pulvinar: Evidence for homology between human and monkey. Proceedings of the National Academy of Sciences, 106(10), 4054–4059. doi: 10.1073/pnas.0810086106Google Scholar

Spaak, E., de Lange, F. P., & Jensen, O. (2014, March). Local entrainment of alpha oscillations by visual stimuli causes cyclic modulation of perception. Journal of Neuroscience, 34(10), 3536–3544. doi: 10.1523/JNEUROSCI.4385-13.2014Google Scholar

Summerfield, C., & Egner, T. (2009, September). Expectation (and attention) in visual cognition. Trends in Cognitive Sciences, 13(9), 403–409. doi: 10.1016/j.tics.2009.06.003Google Scholar

Tanibuchi, I., Kitano, H., & Jinnai, K. (2009a, November). Substantia nigra output to prefrontal cortex via thalamus in monkeys. I. Electrophysiological identification of thalamic relay neurons. Journal of Neurophysiology, 102(5), 2933–2945. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/19692504Google Scholar

Tanibuchi, I., Kitano, H., & Jinnai, K. (2009b, November). Substantia nigra output to prefrontal cortex via thalamus in monkeys. II. Activity of thalamic relay neurons in delayed conditional go/no-go discrimination task. Journal of Neurophysiology, 102(5116), 2946–2954. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/19692503Google Scholar

Thomson, A. M. (2010). Neocortical layer 6, a review. Frontiers in Neuroanatomy, 4(13). Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/20556241Google Scholar

Tononi, G. (2004, November). An information integration theory of consciousness. BMC Neuroscience, 5, 42. doi: 10.1186/1471-2202-5-42Google Scholar

Treisman, A. (1993, January). The perception of features and objects. In Baddeley, A. & Weiskrantz, L. (Eds.), Attention: Selection, Awareness, and Control: A Tribute to Donald Broadbent (pp. 5–35). Oxford: Oxford University Press.Google Scholar

Tsumoto, T, Creutzfeldt OD, Legendy CR (1978) Functional organization of the cortifugal system from visual cortex to lateral geniculate nucleus in the cat. Exp Brain Res 32:345–364.Google Scholar

Usrey, W. M., & Sherman, S. M. (2018). Corticofugal circuits: Communication lines from the cortex to the rest of the brain. Journal of Comparative Neurology, 527(3), 640–650. doi: 10.1002/cne.24423Google Scholar

van Kerkoerle, T., Self, M. W., Dagnino, B., Gariel-Mathis, M.-A., Poort, J., van der Togt, C., & Roelfsema, P. R. (2014, October). Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex. Proceedings of the National Academy of Sciences of the United States of America, 111(40), 14332–14341. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/25205811Google Scholar

VanRullen, R., & Koch, C. (2003, May). Is perception discrete or continuous? Trends in Cognitive Sciences, 7(5), 207–213. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/12757822Google Scholar

von Helmholtz, H. (1867). Treatise on Physiological Optics, Vol III. Courier Corporation.Google Scholar

von Stein, A., Chiang, C., & König, P. (2000, December). Top-down processing mediated by interareal synchronization. Proceedings of the National Academy of Sciences of the United States of America, 97(26), 14748–14753. doi: 10.1073/pnas.97.26.14748Google Scholar

Voytek, B., & Knight, R. T. (2010, October). Prefrontal cortex and basal ganglia contributions to visual working memory. Proceedings of the National Academy of Sciences of the United States of America, 107(42), 18167–18172. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/20921401Google Scholar

Walsh, K. S., McGovern, D. P., Clark, A., & O’Connell, R. G. (2020, March). Evaluating the neurophysiological evidence for predictive processing as a model of perception. Annals of the New York Academy of Sciences, 1464(1), 242–268. doi: 10.1111/nyas.14321Google Scholar

Wang, M., Yang, Y., Wang, C.-J., Gamo, N. J., Jin, L. E., Mazer, J. A., … Arnsten, A. F. T. (2013, February). NMDA receptors subserve persistent neuronal firing during working memory in dorsolateral prefrontal cortex. Neuron, 77(4), 736–749. doi: 10.1016/j.neuron.2012.12.032Google Scholar

Ward, L. M. (2011, June). The thalamic dynamic core theory of conscious experience. Consciousness and Cognition, 20(2), 464–486. doi: 10.1016/j.concog.2011.01.007Google Scholar

Watanabe, Y., & Funahashi, S. (2012, January). Thalamic mediodorsal nucleus and working memory. Neuroscience & Biobehavioral Reviews, 36(1), 134–142. doi: 10.1016/j.neubiorev.2011.05.003Google Scholar

Watanabe, Y., Takeda, K., & Funahashi, S. (2009, June). Population vector analysis of primate mediodorsal thalamic activity during oculomotor delayed-response performance. Cerebral Cortex, 19, 1313–1321. Retrieved from http://cercor.oxfordjournals.org/cgi/content/abstract/19/6/1313Google Scholar

Whittington, J. C. R., & Bogacz, R. (2019, March). Theories of error back-propagation in the brain. Trends in Cognitive Sciences, 23(3), 235–250. doi: 10.1016/j.tics.2018.12.005Google Scholar

Wig, G. S. (2017). Segregated systems of human brain networks. Trends in Cognitive Sciences, 21(12), 981–996.Google Scholar

Wimmer, R. D., Schmitt, L. I., Davidson, T. J., Nakajima, M., Deisseroth, K., & Halassa, M. M. (2015, October). Thalamic control of sensory selection in divided attention. Nature, 526(7575), 705–709. doi: 10.1038/nature15398Google Scholar