Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-26T06:16:10.089Z Has data issue: false hasContentIssue false

Chapter 16 - The Thalamus in Cognitive Control

from Section 7: - Cognition

Published online by Cambridge University Press:  12 August 2022

By
Kai Hwang  and
Mark D’Esposito
Edited by
Michael M. Halassa
Michael M. Halassa
Affiliation:
Massachusetts Institute of Technology
Get access

Summary

Cognitive control refers to our ability to regulate thoughts and actions for adaptive, goal-directed behaviors. Traditionally, cognitive control is thought to be mediated by the prefrontal cortex; however, the thalamus likely plays an important yet underappreciated role. This chapter reviews the role of the human thalamus in cognitive control. We first review anatomical, human functional neuroimaging, and human neuropsychology findings that have investigated the role of the human thalamus in two cognitive control functions: working memory and top-down biasing. To understand how the human thalamus mechanistically supports cognitive control, we then summarize operational principles of thalamocortical circuits from anatomical and neurophysiological studies. Finally, we present an overarching conceptual framework to describe how thalamocortical circuits implement different components of information processing necessary for cognitive control. In conclusion, we refute the traditional view that the thalamus passively relays signals to the cortex for purposeful processing. Instead, emerging evidence suggests that the thalamus actively modulates cortical activity and cortical network interactions to shape and coordinate information processes underlying cognitive control.

Keywords

thalamusfrontal cortexcognitive controlworking memoryattentioninhibitioncognitive flexibilityfunctional connectivitybrain networks
Type
Chapter
Information
The Thalamus , pp. 307 - 323
Publisher: Cambridge University Press
Print publication year: 2022

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ährlund-Richter, S., Xuan, Y., van Lunteren, J. A., Kim, H., Ortiz, C., Pollak Dorocic, I., Meletis, K., & Carlén, M. (2019). A whole-brain atlas of monosynaptic input targeting four different cell types in the medial prefrontal cortex of the mouse. Nature Neuroscience, 22(4), 657–668.CrossRefGoogle ScholarPubMed
Alexander, G. E., DeLong, M. R., & Strick, P. L. (1986). Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annual Review of Neuroscience, 9, 357–381.Google Scholar
Alexander, W. H., & Brown, J. W. (2011). Medial prefrontal cortex as an action-outcome predictor. Nature Neuroscience, 14(10), 1338–1344.Google Scholar
Anderson, S. W., Damasio, H., Jones, R. D., & Tranel, D. (1991). Wisconsin Card Sorting Test performance as a measure of frontal lobe damage. Journal of Clinical and Experimental Neuropsychology, 13(6), 909–922.Google Scholar
Arend, I., Rafal, R., & Ward, R. (2008). Spatial and temporal deficits are regionally dissociable in patients with pulvinar lesions. Brain: A Journal of Neurology, 131(Pt 8), 2140–2152.CrossRefGoogle ScholarPubMed
Armstrong, K. M., Chang, M. H., & Moore, T. (2009). Selection and maintenance of spatial information by frontal eye field neurons. Journal of Neuroscience, 29(50), 15621–15629.Google Scholar
Aron, A. R., Behrens, T. E., Smith, S., Frank, M. J., & Poldrack, R. A. (2007). Triangulating a cognitive control network using diffusion-weighted magnetic resonance imaging (MRI) and functional MRI. Journal of Neuroscience, 27(14), 3743–3752.Google Scholar
Asanuma, C., Andersen, R. A., & Cowan, W. M. (1985). The thalamic relations of the caudal inferior parietal lobule and the lateral prefrontal cortex in monkeys: divergent cortical projections from cell clusters in the medial pulvinar nucleus. Journal of Comparative Neurology, 241(3), 357–381.Google Scholar
Baddeley, A. (2007). Working Memory, Thought, and Action. Oxford University Press.Google Scholar
Badre, D., & D’Esposito, M. (2007). Functional magnetic resonance imaging evidence for a hierarchical organization of the prefrontal cortex. Journal of Cognitive Neuroscience, 19(12), 2082–2099.Google Scholar
Badre, D., Hoffman, J., Cooney, J. W., & D’Esposito, M. (2009). Hierarchical cognitive control deficits following damage to the human frontal lobe. Nature Neuroscience, 12(4), 515–522.Google Scholar
Badre, D., Poldrack, R. A., Paré-Blagoev, E. J., Insler, R. Z., & Wagner, A. D. (2005). Dissociable controlled retrieval and generalized selection mechanisms in ventrolateral prefrontal cortex. Neuron, 47(6), 907–918.Google Scholar
Bastos, A. M., Vezoli, J., & Fries, P. (2015). Communication through coherence with inter-areal delays. Current Opinion in Neurobiology, 31, 173–180.Google Scholar
Behrens, T. E. J., Johansen-Berg, H., Woolrich, M. W., Smith, S. M., Wheeler-Kingshott, C. A. M., Boulby, P. A., Barker, G. J., Sillery, E. L., Sheehan, K., Ciccarelli, O., Thompson, A. J., Brady, J. M., & Matthews, P. M. (2003). Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. Nature Neuroscience, 6(7), 750–757.Google Scholar
Bertolero, M. A., Yeo, B. T. T., & D’Esposito, M. (2015). The modular and integrative functional architecture of the human brain. Proceedings of the National Academy of Sciences of the United States of America, 112(49), E6798–807.Google Scholar
Bolkan, S. S., Stujenske, J. M., Parnaudeau, S., Spellman, T. J., Rauffenbart, C., Abbas, A. I., Harris, A. Z., Gordon, J. A., & Kellendonk, C. (2017). Thalamic projections sustain prefrontal activity during working memory maintenance. Nature Neuroscience, 20(7), 987–996.Google Scholar
Bolkan, S. S., Stujenske, J. M., Parnaudeau, S., Spellman, T. J., Rauffenbart, C., Abbas, A. I., Harris, A. Z., Gordon, J. A., & Kellendonk, C. (2018). Publisher correction: thalamic projections sustain prefrontal activity during working memory maintenance. Nature Neuroscience, 21(8), 1138.CrossRefGoogle ScholarPubMed
Bowie, C. R., & Harvey, P. D. (2006). Administration and interpretation of the Trail Making Test. Nature Protocols, 1(5), 2277–2281.Google Scholar
Buckner, R. L., Krienen, F. M., & Yeo, B. T. T. (2013). Opportunities and limitations of intrinsic functional connectivity MRI. Nature Neuroscience, 16(7), 832–837.Google Scholar
Bullmore, E., & Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Reviews. Neuroscience, 10(3), 186–198.Google Scholar
Buschman, T. J., & Miller, E. K. (2007). Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science, 315(5820), 1860–1862.Google Scholar
Cai, W., Oldenkamp, C. L., & Aron, A. R. (2011). A proactive mechanism for selective suppression of response tendencies. Journal of Neuroscience, 31(16), 5965–5969.CrossRefGoogle ScholarPubMed
Callicott, J. H., Mattay, V. S., Bertolino, A., Finn, K., Coppola, R., Frank, J. A., Goldberg, T. E., & Weinberger, D. R. (1999). Physiological characteristics of capacity constraints in working memory as revealed by functional MRI. Cerebral Cortex, 9(1), 20–26.Google Scholar
Camperi, M., & Wang, X. J. (1998). A model of visuospatial working memory in prefrontal cortex: recurrent network and cellular bistability. Journal of Computational Neuroscience, 5(4), 383–405.Google Scholar
Cardin, J. A., Carlén, M., Meletis, K., Knoblich, U., Zhang, F., Deisseroth, K., Tsai, L.-H., & Moore, C. I. (2009). Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature, 459(7247), 663–667.CrossRefGoogle ScholarPubMed
Carlesimo, G. A., Lombardi, M. G., & Caltagirone, C. (2011). Vascular thalamic amnesia: a reappraisal. Neuropsychologia, 49(5), 777–789.Google Scholar
Chafee, M. V., & Goldman-Rakic, P. S. (1998). Matching patterns of activity in primate prefrontal area 8a and parietal area 7ip neurons during a spatial working memory task. Journal of Neurophysiology, 79(6), 2919–2940.Google Scholar
Chalupa, L. M., Coyle, R. S., & Lindsley, D. B. (1976). Effect of pulvinar lesions on visual pattern discrimination in monkeys. Journal of Neurophysiology, 39(2), 354–369.Google Scholar
Chatham, C. H., & Badre, D. (2015). Multiple gates on working memory. Current Opinion in Behavioral Sciences, 1, 23–31.Google Scholar
Child, N. D., & Benarroch, E. E. (2013). Anterior nucleus of the thalamus: functional organization and clinical implications. Neurology, 81(21), 1869–1876.CrossRefGoogle ScholarPubMed
Christophel, T. B., Klink, P. C., Spitzer, B., Roelfsema, P. R., & Haynes, J.-D. (2017). The distributed nature of working memory. Trends in Cognitive Sciences, 21(2), 111–124.Google Scholar
Clark, C. A. C., Pritchard, V. E., & Woodward, L. J. (2010). Preschool executive functioning abilities predict early mathematics achievement. Developmental Psychology, 46(5), 1176–1191.CrossRefGoogle ScholarPubMed
Clinton, S. M., & Meador-Woodruff, J. H. (2004). Thalamic dysfunction in schizophrenia: neurochemical, neuropathological, and in vivo imaging abnormalities. Schizophrenia Research, 69(2–3), 237–253.Google Scholar
Cohen, J. D. (2017). Cognitive control: core constructs and current considerations. In Egner, T. (Ed.), The Wiley Handbook of Cognitive Control (Vol. 50, pp. 1–28). John Wiley & Sons, Ltd.Google Scholar
Cohen, J. R., & D’Esposito, M. (2016). The segregation and integration of distinct brain networks and their relationship to cognition. Journal of Neuroscience, 36(48), 12083–12094.Google Scholar
Cole, M. W., Ito, T., Bassett, D. S., & Schultz, D. H. (2016). Activity flow over resting-state networks shapes cognitive task activations. Nature Neuroscience, 19(12), 1718–1726.Google Scholar
Cole, M. W., Reynolds, J. R., Power, J. D., Repovs, G., Anticevic, A., & Braver, T. S. (2013). Multi-task connectivity reveals flexible hubs for adaptive task control. Nature Neuroscience, 16(9), 1348–1355.Google Scholar
Cole, M. W., & Schneider, W. (2007). The cognitive control network: Integrated cortical regions with dissociable functions. NeuroImage, 37(1), 343–360.Google Scholar
Cronenwett, W. J., & Csernansky, J. (2010). Thalamic pathology in schizophrenia. Current Topics in Behavioral Neurosciences, 4, 509–528.CrossRefGoogle ScholarPubMed
Crosson, B., Parker, J. C., Kim, A. K., Warren, R. L., Kepes, J. J., & Tully, R. (1986). A case of thalamic aphasia with postmortem verification. Brain and Language, 29(2), 301–314.Google Scholar
Crowe, S. F. (1998). The differential contribution of mental tracking, cognitive flexibility, visual search, and motor speed to performance on parts A and B of the Trail Making Test. Journal of Clinical Psychology, 54(5), 585–591.Google Scholar
Cruikshank, S. J., Lewis, T. J., & Connors, B. W. (2007). Synaptic basis for intense thalamocortical activation of feedforward inhibitory cells in neocortex. Nature Neuroscience, 10(4), 462–468.Google Scholar
Curtis, C. E., & D’Esposito, M. (2003). Persistent activity in the prefrontal cortex during working memory. Trends in Cognitive Sciences, 7(9), 415–423.Google Scholar
Curtis, C. E., Rao, V. Y., & D’Esposito, M. (2004). Maintenance of spatial and motor codes during oculomotor delayed response tasks. Journal of Neuroscience, 24(16), 3944–3952.Google Scholar
Danziger, S., Ward, R., Owen, V., & Rafal, R. (1999). The effects of unilateral pulvinar damage in humans on reflexive orienting and filtering of irrelevant information. Behavioural Neurology, 13(3, 4), 95–104.Google Scholar
de Bourbon-Teles, J., Bentley, P., Koshino, S., Shah, K., Dutta, A., Malhotra, P., Egner, T., Husain, M., & Soto, D. (2014). Thalamic control of human attention driven by memory and learning. Current Biology: CB, 24(9), 993–999.Google Scholar
Dehaene, S., & Changeux, J. P. (1991). The Wisconsin Card Sorting Test: theoretical analysis and modeling in a neuronal network. Cerebral Cortex, 1(1), 62–79.Google Scholar
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.Google Scholar
D’Esposito, M. (2007). From cognitive to neural models of working memory. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 362(1481), 761–772.Google Scholar
D’Esposito, M., & Chen, A. J. W. (2013). Remediating frontal lobe dysfunction: from bench to bedside. In Stuss, D. T & Knight, R. T. (Eds.), Oxford Handbook of Frontal Lobe Function (pp. 726–741). Oxford University Press.Google Scholar
D’Esposito, M., Postle, B. R., Ballard, D., & Lease, J. (1999). Maintenance versus manipulation of information held in working memory: an event-related fMRI study. Brain and Cognition, 41(1), 66–86.Google Scholar
D’Esposito, M., Postle, B. R., & Rypma, B. (2000). Prefrontal cortical contributions to working memory: evidence from event-related fMRI studies. Experimental Brain Research. Experimentelle Hirnforschung. Experimentation Cerebrale, 133(1), 3–11.Google Scholar
Diamond, A., & Lee, K. (2011). Interventions shown to aid executive function development in children 4 to 12 years old. Science, 333(6045), 959–964.Google Scholar
Duncan, J. (2010). The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour. Trends in Cognitive Sciences, 14(4), 172–179.Google Scholar
Eickhoff, S. B., Bzdok, D., Laird, A. R., Kurth, F., & Fox, P. T. (2012). Activation likelihood estimation meta-analysis revisited. NeuroImage, 59(3), 2349–2361.Google Scholar
Ester, E. F., Sprague, T. C., & Serences, J. T. (2015). Parietal and frontal cortex encode stimulus-specific mnemonic representations during visual working memory. Neuron, 87(4), 893–905.Google Scholar
Everling, S., & Munoz, D. P. (2000). Neuronal correlates for preparatory set associated with pro-saccades and anti-saccades in the primate frontal eye field. Journal of Neuroscience, 20(1), 387–400.Google Scholar
Fellows, L. K. (2017). Cognitive control in the injured brain. In Egner, T. (Ed.), The Wiley Handbook of Cognitive Control (Vol. 67, pp. 513–538). John Wiley & Sons, Ltd.Google Scholar
Feredoes, E., Heinen, K., Weiskopf, N., Ruff, C., & Driver, J. (2011). Causal evidence for frontal involvement in memory target maintenance by posterior brain areas during distracter interference of visual working memory. Proceedings of the National Academy of Sciences of the United States of America, 108(42), 17510–17515.Google Scholar
Fischer, J., & Whitney, D. (2012). Attention gates visual coding in the human pulvinar. Nature Communications, 3, 1051.Google Scholar
Frank, M. J., Loughry, B., & O’Reilly, R. C. (2001). Interactions between frontal cortex and basal ganglia in working memory: a computational model. Cognitive, Affective & Behavioral Neuroscience, 1(2), 137–160.Google Scholar
Fries, P. (2015). Rhythms for cognition: communication through coherence. Neuron, 88(1): 220–235.Google Scholar
Funahashi, S. (2013). Thalamic mediodorsal nucleus and its participation in spatial working memory processes: comparison with the prefrontal cortex. Frontiers in Systems Neuroscience, 7, 36.CrossRefGoogle ScholarPubMed
Funahashi, S., Chafee, M. V., & Goldman-Rakic, P. S. (1993). Prefrontal neuronal activity in rhesus monkeys performing a delayed anti-saccade task. Nature, 365(6448), 753–756.Google Scholar
Fuster, J. M., & Alexander, G. E. (1971). Neuron activity related to short-term memory. Science, 173(3997), 652–654.Google Scholar
Gazzaley, A., Cooney, J. W., McEvoy, K., Knight, R. T., & D’Esposito, M. (2005). Top-down enhancement and suppression of the magnitude and speed of neural activity. Journal of Cognitive Neuroscience, 17(3), 507–517.Google Scholar
Gazzaley, A., & Nobre, A. C. (2012). Top-down modulation: bridging selective attention and working memory. Trends in Cognitive Sciences, 16(2), 129–135.Google Scholar
Gazzaley, A., Rissman, J., & D’Esposito, M. (2004). Functional connectivity during working memory maintenance. Cognitive, Affective & Behavioral Neuroscience, 4(4), 580–599.Google 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.Google Scholar
Gläscher, J., Adolphs, R., Damasio, H., Bechara, A., Rudrauf, D., Calamia, M., Paul, L. K., & Tranel, D. (2012). Lesion mapping of cognitive control and value-based decision making in the prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America, 109(36), 14681–14686.Google Scholar
Gläscher, J., Adolphs, R., & Tranel, D. (2019). Model-based lesion mapping of cognitive control using the Wisconsin Card Sorting Test. Nature Communications, 10(1), 20.Google Scholar
Goldman-Rakic, P. S., & Porrino, L. J. (1985). The primate mediodorsal (MD) nucleus and its projection to the frontal lobe. Journal of Comparative Neurology, 242(4), 535–560.Google Scholar
Gordon, E. M., Lynch, C. J., Gratton, C., Laumann, T. O., Gilmore, A. W., Greene, D. J., Ortega, M., Nguyen, A. L., Schlaggar, B. L., Petersen, S. E., Dosenbach, N. U. F., & Nelson, S. M. (2018). Three distinct sets of connector hubs integrate human brain function. Cell Reports, 24(7), 1687–1695.e4.Google Scholar
Graff-Radford, N. R., Eslinger, P. J., Damasio, A. R., & Yamada, T. (1984). Nonhemorrhagic infarction of the thalamus: behavioral, anatomic, and physiologic correlates. Neurology, 34(1), 14–23.Google Scholar
Graff-Radford, N. R., Tranel, D., Van Hoesen, G. W., & Brandt, J. P. (1990). Diencephalic amnesia. Brain: A Journal of Neurology, 113 (Pt 1), 1–25.Google Scholar
Greene, D. J., Marek, S., Gordon, E. M., Siegel, J. S., Gratton, C., Laumann, T. O., Gilmore, A. W., Berg, J. J., Nguyen, A. L., Dierker, D., Van, A. N., Ortega, M., Newbold, D. J., Hampton, J. M., Nielsen, A. N., McDermott, K. B., Roland, J. L., Norris, S. A., Nelson, S. M., … Dosenbach, N. U. F. (2020). Integrative and network-specific connectivity of the basal ganglia and thalamus defined in individuals. Neuron, 105(4), 742–758.e6.Google Scholar
Gregoriou, G. G., Rossi, A. F., Ungerleider, L. G., & Desimone, R. (2014). Lesions of prefrontal cortex reduce attentional modulation of neuronal responses and synchrony in V4. Nature Neuroscience, 17(7), 1003–1011.Google Scholar
Guillery, R. W., & Sherman, S. M. (2002). Thalamic relay functions and their role in corticocortical communication: generalizations from the visual system. Neuron, 33(2), 163–175.Google Scholar
Guimerà, R., & Nunes Amaral, L. A. (2005). Functional cartography of complex metabolic networks. Nature, 433(7028), 895–900.Google Scholar
Guo, Z. V., Inagaki, H. K., Daie, K., Druckmann, S., Gerfen, C. R., & Svoboda, K. (2017). Maintenance of persistent activity in a frontal thalamocortical loop. Nature, 545(7653), 181–186.Google Scholar
Halassa, M. M., & Kastner, S. (2017). Thalamic functions in distributed cognitive control. Nature Neuroscience, 20(12), 1669–1679.Google Scholar
Hazy, T. E., Frank, M. J., & O’Reilly, R. C. (2006). Banishing the homunculus: making working memory work. Neuroscience, 139(1), 105–118.Google Scholar
Hwang, K., Bertolero, M. A., Liu, W. B., & D’esposito, M. (2017). The human thalamus is an integrative hub for functional brain networks. Journal of Neuroscience, 37(23), 5594–5607.Google Scholar
Hwang, K., Bruss, J., Tranel, D., & Boes, A. D. (2020). Network localization of executive function deficits in patients with focal thalamic lesions. Journal of Cognitive Neuroscience, 32(12), 2303–2319.Google Scholar
Hwang, K., Ghuman, A. S., Manoach, D. S., Jones, S. R., & Luna, B. (2014). Cortical neurodynamics of inhibitory control. Journal of Neuroscience, 34(29), 9551–9561.Google Scholar
Hwang, K., Shine, J. M., & D’Esposito, M. (2019). Frontoparietal activity interacts with task-evoked changes in functional connectivity. Cerebral Cortex, 29(2), 802–813.Google Scholar
Isseroff, A., Rosvold, H. E., Galkin, T. W., & Goldman-Rakic, P. S. (1982). Spatial memory impairments following damage to the mediodorsal nucleus of the thalamus in rhesus monkeys. Brain Research, 232(1), 97–113.Google Scholar
Jiang, J., Beck, J., Heller, K., & Egner, T. (2015). An insula-frontostriatal network mediates flexible cognitive control by adaptively predicting changing control demands. Nature Communications, 6, 8165.Google Scholar
Jones, E. G. (1998). Viewpoint: the core and matrix of thalamic organization. Neuroscience, 85(2), 331–345.Google Scholar
Jones, E. G., & Leavitt, R. Y. (1974). Retrograde axonal transport and the demonstration of non‐specific projections to the cerebral cortex and striatum from thalamic intralaminar nuclei in the rat, cat and monkey. Journal of Comparative Neurology, 154(4), 349–377.Google Scholar
Kamiński, M., Ding, M., Truccolo, W. A., & Bressler, S. L. (2001). Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance. Biological Cybernetics, 85(2), 145–157.Google Scholar
Kastner, S., O’Connor, D. H., Fukui, M. M., Fehd, H. M., Herwig, U., & Pinsk, M. A. (2004). Functional imaging of the human lateral geniculate nucleus and pulvinar. Journal of Neurophysiology, 91(1), 438–448.Google Scholar
Koenigs, M., Barbey, A. K., Postle, B. R., & Grafman, J. (2009). Superior parietal cortex is critical for the manipulation of information in working memory. Journal of Neuroscience, 29(47), 14980–14986.Google Scholar
Kortte, K. B., Horner, M. D., & Windham, W. K. (2002). The Trail Making Test, Part B: cognitive flexibility or ability to maintain set? Applied Neuropsychology, 9(2), 106–109.Google Scholar
Krause, T., Brunecker, P., Pittl, S., Taskin, B., Laubisch, D., Winter, B., Lentza, M. E., Malzahn, U., Villringer, K., Villringer, A., & Jungehulsing, G. J. (2012). Thalamic sensory strokes with and without pain: differences in lesion patterns in the ventral posterior thalamus. Journal of Neurology, Neurosurgery, and Psychiatry, 83(8), 776–784.Google Scholar
Krauth, A., Blanc, R., Poveda, A., Jeanmonod, D., Morel, A., & Székely, G. (2010). A mean three-dimensional atlas of the human thalamus: generation from multiple histological data. NeuroImage, 49(3), 2053–2062.Google Scholar
Krol, A., Wimmer, R. D., Halassa, M. M., & Feng, G. (2018). Thalamic reticular dysfunction as a circuit endophenotype in neurodevelopmental disorders. Neuron, 98(2), 282–295.Google Scholar
Kubat-Silman, A. K., Dagenbach, D., & Absher, J. R. (2002). Patterns of impaired verbal, spatial, and object working memory after thalamic lesions. Brain and Cognition, 50(2), 178–193.Google Scholar
Kuljic-Obradovic, D. C. (2003). Subcortical aphasia: three different language disorder syndromes? European Journal of Neurology, 10(4), 445–448.Google Scholar
Laird, A. R., Lancaster, J. J., & Fox, P. T. (2005). BrainMap. Neuroinformatics, 3(1), 65–77.Google Scholar
Lee, T. G., & D’Esposito, M. (2012). The dynamic nature of top-down signals originating from prefrontal cortex: a combined fMRI–TMS study. Journal of Neuroscience, 32(44), 15458–15466.Google Scholar
Lesh, T. A., Niendam, T. A., Minzenberg, M. J., & Carter, C. S. (2011). Cognitive control deficits in schizophrenia: mechanisms and meaning. Neuropsychopharmacology, 36(1), 316–338.Google Scholar
Liebermann, D., Ploner, C. J., Kraft, A., Kopp, U. A., & Ostendorf, F. (2013). A dysexecutive syndrome of the medial thalamus. Cortex, 49(1), 40–49.Google Scholar
Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390(6657), 279–281.Google Scholar
Lundqvist, M., Rose, J., Herman, P., Brincat, S. L., Buschman, T. J., & Miller, E. K. (2016). Gamma and beta bursts underlie working memory. Neuron, 90(1), 152–164.Google Scholar
Luo, T. Z., & Maunsell, J. H. R. (2019). Attention can be subdivided into neurobiological components corresponding to distinct behavioral effects. Proceedings of the National Academy of Sciences of the United States of America, 116(52), 26187–26194. https://doi.org/10.1073/pnas.1902286116Google Scholar
Ma, W. J., Husain, M., & Bays, P. M. (2014). Changing concepts of working memory. Nature Neuroscience, 17(3), 347–356.Google Scholar
Mackey, W. E., Devinsky, O., Doyle, W. K., Golfinos, J. G., & Curtis, C. E. (2016). Human parietal cortex lesions impact the precision of spatial working memory. Journal of Neurophysiology, 116(3), 1049–1054.Google Scholar
Manoach, D. S., Greve, D. N., Lindgren, K. A., & Dale, A. M. (2003). Identifying regional activity associated with temporally separated components of working memory using event-related functional MRI. NeuroImage, 20(3), 1670–1684.Google Scholar
Miller, B. T., Vytlacil, J., Fegen, D., Pradhan, S., & D’Esposito, M. (2011). The prefrontal cortex modulates category selectivity in human extrastriate cortex. Journal of Cognitive Neuroscience, 23(1), 1–10.Google Scholar
Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167–202.Google Scholar
Miller, E. K., Erickson, C. A., & Desimone, R. (1996). Neural mechanisms of visual working memory in prefrontal cortex of the macaque. Journal of Neuroscience, 16(16), 5154–5167.CrossRefGoogle ScholarPubMed
Miyake, A., Friedman, N. P., Emerson, M. J., & Witzki, A. H. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: a latent variable analysis. Cognitive Psychology, 41(1), 49–100.Google Scholar
Morel, A., Magnin, M., & Jeanmonod, D. (1997). Multiarchitectonic and stereotactic atlas of the human thalamus. Journal of Comparative Neurology, 387(4), 588–630.Google Scholar
Morishima, Y., Akaishi, R., Yamada, Y., Okuda, J., Toma, K., & Sakai, K. (2009). Task-specific signal transmission from prefrontal cortex in visual selective attention. Nature Neuroscience, 12(1), 85–91.Google Scholar
Nasreddine, Z. S., & Saver, J. L. (1997). Pain after thalamic stroke: right diencephalic predominance and clinical features in 180 patients. Neurology, 48(5), 1196–1199.Google Scholar
Nee, D. E., & D’Esposito, M. (2016). The hierarchical organization of the lateral prefrontal cortex. eLife, 5. https://doi.org/10.7554/eLife.12112Google Scholar
Nobre, A., & Stokes, M. S. (2020). Memory and attention: the back and forth. In Gazzaniga, M. S. (Ed.), The Cognitive Neurosciences (6th ed., pp. 291–300). MIT Press.Google Scholar
Norman, D. A., & Shallice, T. (1986). Attention to action. In Davidson, R. J., Schwartz, G. E., & Shapiro, D. (Eds.), Consciousness and Self-Regulation: Advances in Research and Theory Volume 4 (pp. 1–18). Springer US.Google Scholar
O’Craven, K. M., Downing, P. E., & Kanwisher, N. (1999). fMRI evidence for objects as the units of attentional selection. Nature, 401(6753), 584–587.Google Scholar
Peräkylä, J., Sun, L., Lehtimäki, K., Peltola, J., Öhman, J., Möttönen, T., Ogawa, K. H., & Hartikainen, K. M. (2017). Causal evidence from humans for the role of mediodorsal nucleus of the thalamus in working memory. Journal of Cognitive Neuroscience, 29(12), 2090–2102.Google Scholar
Poldrack, R. A. (2006). Can cognitive processes be inferred from neuroimaging data? Trends in Cognitive Sciences, 10(2), 59–63.Google Scholar
Poldrack, R. A. (2011). Inferring mental states from neuroimaging data: from reverse inference to large-scale decoding. Neuron, 72(5), 692–697.Google Scholar
Poldrack, R. A., Baker, C. I., Durnez, J., Gorgolewski, K. J., Matthews, P. M., Munafò, M. R., Nichols, T. E., Poline, J.-B., Vul, E., & Yarkoni, T. (2017). Scanning the horizon: towards transparent and reproducible neuroimaging research. Nature Reviews. Neuroscience, 18(2), 115.Google Scholar
Posner, M. I., Snyder, C. R., & Solso, R. (2004). Attention and cognitive control. In Balota, D. & Marsh, E. (Eds.), Cognitive Psychology: Key Readings (pp. 55–85). Psychology Press.Google Scholar
Power, J. D., Cohen, A. L., Nelson, S. M., Wig, G. S., Barnes, K. A., Church, J. A., Vogel, A. C., Laumann, T. O., Miezin, F. M., Schlaggar, B. L., & Petersen, S. E. (2011). Functional network organization of the human brain. Neuron, 72(4), 665–678.Google Scholar
Power, J. D., Schlaggar, B. L., Lessov-Schlaggar, C. N., & Petersen, S. E. (2013). Evidence for hubs in human functional brain networks. Neuron, 79(4), 798–813.Google Scholar
Rafal, R. D., & Posner, M. I. (1987). Deficits in human visual spatial attention following thalamic lesions. Proceedings of the National Academy of Sciences of the United States of America, 84(20), 7349–7353.Google Scholar
Ranganath, C., DeGutis, J., & D’Esposito, M. (2004). Category-specific modulation of inferior temporal activity during working memory encoding and maintenance. Brain Research. Cognitive Brain Research, 20(1), 37–45.Google Scholar
Ratcliff, R., & McKoon, G. (2008). The diffusion decision model: theory and data for two-choice decision tasks. Neural Computation, 20(4), 873–922.Google Scholar
Rikhye, R. V., Gilra, A., & Halassa, M. M. (2018). Thalamic regulation of switching between cortical representations enables cognitive flexibility. Nature Neuroscience, 21(12), 1753–1763.Google Scholar
Rock, P. L., Roiser, J. P., Riedel, W. J., & Blackwell, A. D. (2014). Cognitive impairment in depression: a systematic review and meta-analysis. Psychological Medicine, 44(10), 2029–2040.Google Scholar
Romanski, L. M., Giguere, M., Bates, J. F., & Goldman-Rakic, P. S. (1997). Topographic organization of medial pulvinar connections with the prefrontal cortex in the rhesus monkey. Journal of Comparative Neurology, 379(3), 313–332.Google Scholar
Roux, F., Wibral, M., Mohr, H. M., Singer, W., & Uhlhaas, P. J. (2012). Gamma-band activity in human prefrontal cortex codes for the number of relevant items maintained in working memory. Journal of Neuroscience, 32(36), 12411–12420.Google Scholar
Ruff, C. C., Blankenburg, F., Bjoertomt, O., Bestmann, S., Freeman, E., Haynes, J.-D., Rees, G., Josephs, O., Deichmann, R., & Driver, J. (2006). Concurrent TMS-fMRI and psychophysics reveal frontal influences on human retinotopic visual cortex. Current Biology: CB, 16(15), 1479–1488.Google Scholar
Saalmann, Y. B., Pinsk, M. A., Wang, L., Li, X., & Kastner, S. (2012). The pulvinar regulates information transmission between cortical areas based on attention demands. Science, 337(6095), 753–756.Google Scholar
Schell, G. R., & Strick, P. L. (1984). The origin of thalamic inputs to the arcuate premotor and supplementary motor areas. Journal of Neuroscience, 4(2), 539–560.Google Scholar
Schmahmann, J. D. (2003). Vascular syndromes of the thalamus. Stroke, 34(9), 2264–2278.Google Scholar
Schmahmann, J. D., & Pandya, D. N. (1990). Anatomical investigation of projections from thalamus to posterior parietal cortex in the rhesus monkey: a WGA-HRP and fluorescent tracer study. Journal of Comparative Neurology, 295(2), 299–326.Google Scholar
Schmitt, L. I., Wimmer, R. D., Nakajima, M., Happ, M., Mofakham, S., & Halassa, M. M. (2017). Thalamic amplification of cortical connectivity sustains attentional control. Nature, 545(7653), 219–223.Google Scholar
Selemon, L. D., & Goldman-Rakic, P. S. (1988). Common cortical and subcortical targets of the dorsolateral prefrontal and posterior parietal cortices in the rhesus monkey: evidence for a distributed neural network subserving spatially guided behavior. Journal of Neuroscience, 8(11), 4049–4068.Google Scholar
Serences, J. T., Saproo, S., Scolari, M., Ho, T., & Muftuler, L. T. (2009). Estimating the influence of attention on population codes in human visual cortex using voxel-based tuning functions. NeuroImage, 44(1), 223–231.Google Scholar
Sherman, M. A., Lee, S., Law, R., Haegens, S., Thorn, C. A., Hämäläinen, M. S., Moore, C. I., & Jones, S. R. (2016). Neural mechanisms of transient neocortical beta rhythms: Converging evidence from humans, computational modeling, monkeys, and mice. Proceedings of the National Academy of Sciences of the United States of America, 113(33), E4885–94.Google Scholar
Sherman, S. M., & Guillery, R. W. (2002). The role of the thalamus in the flow of information to the cortex. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 357(1428), 1695–1708.Google Scholar
Sherman, S. M., & Guillery, R. W. (2006). Exploring the Thalamus and Its Role in Cortical Function (2nd ed.). MIT Press.Google Scholar
Sherman, S. M., & Guillery, R. W. (2013). Functional Connections of Cortical Areas: A New View from the Thalamus. MIT Press.Google Scholar
Shine, J. M., Bissett, P. G., Bell, P. T., Koyejo, O., Balsters, J. H., Gorgolewski, K. J., Moodie, C. A., & Poldrack, R. A. (2016). The dynamics of functional brain networks: integrated network states during cognitive task performance. Neuron, 92(2), 544–554.Google Scholar
Snow, J. C., Allen, H. A., Rafal, R. D., & Humphreys, G. W. (2009). Impaired attentional selection following lesions to human pulvinar: evidence for homology between human and monkey. Proceedings of the National Academy of Sciences of the United States of America, 106(10), 4054–4059.Google Scholar
Sohal, V. S., Zhang, F., Yizhar, O., & Deisseroth, K. (2009). Parvalbumin neurons and gamma rhythms enhance cortical circuit performance. Nature, 459(7247), 698–702.Google Scholar
Sporns, O., & Betzel, R. F. (2016). Modular brain networks. Annual Review of Psychology, 67, 613–640.Google Scholar
Sreenivasan, K. K., & D’Esposito, M. (2019). The what, where and how of delay activity. Nature Reviews. Neuroscience, 20(8), 466–481.Google Scholar
Stuss, D. T., & Alexander, M. P. (2000). Executive functions and the frontal lobes: a conceptual view. Psychological Research, 63(3–4), 289–298.CrossRefGoogle ScholarPubMed
Stuss, D. T., & Alexander, M. P. (2007). Is there a dysexecutive syndrome? Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 362(1481), 901–915.Google Scholar
Sutterer, M. J., & Tranel, D. (2017). Neuropsychology and cognitive neuroscience in the fMRI era: A recapitulation of localizationist and connectionist views. Neuropsychology, 31(8), 972–980.Google Scholar
Theyel, B. B., Llano, D. A., & Sherman, S. M. (2010). The corticothalamocortical circuit drives higher-order cortex in the mouse. Nature Neuroscience, 13(1), 84–88.Google Scholar
Trojanowski, J. Q., & Jacobson, S. (1976). Areal and laminar distribution of some pulvinar cortical efferents in rhesus monkey. Journal of Comparative Neurology, 169(3), 371–392.Google Scholar
Tsuchida, A., & Fellows, L. K. (2013). Are core component processes of executive function dissociable within the frontal lobes? Evidence from humans with focal prefrontal damage. Cortex, 49(7), 1790–1800.Google Scholar
Usrey, W. M., & Kastner, S. (2020). Functions of the visual thalamus in selective attention. In Gazzaniga, M. S., Mangun, G. R., & Poeppel, D. (Eds.), The Cognitive Neurosciences (6th ed., pp. 367–378). MIT Press.Google Scholar
van den Heuvel, M. P., & Sporns, O. (2013). Network hubs in the human brain. Trends in Cognitive Sciences, 17(12), 683–696.Google Scholar
Van der Werf, Y. D., Scheltens, P., Lindeboom, J., Witter, M. P., Uylings, H. B. M., & Jolles, J. (2003). Deficits of memory, executive functioning and attention following infarction in the thalamus; a study of 22 cases with localised lesions. Neuropsychologia, 41(10), 1330–1344.Google Scholar
Van der Werf, Y. D., Witter, M. P., & Groenewegen, H. J. (2002). The intralaminar and midline nuclei of the thalamus. Anatomical and functional evidence for participation in processes of arousal and awareness. Brain Research. Brain Research Reviews, 39(2–3), 107–140.Google Scholar
Varela, F., Lachaux, J. P., Rodriguez, E., & Martinerie, J. (2001). The brainweb: phase synchronization and large-scale integration. Nature Reviews. Neuroscience, 2(4), 229–239.Google Scholar
Verbruggen, F., McLaren, I. P. L., & Chambers, C. D. (2014). Banishing the control homunculi in studies of action control and behavior change. Perspectives on Psychological Science, 9(5), 497–524.Google Scholar
von Cramon, D. Y., Hebel, N., & Schuri, U. (1985). A contribution to the anatomical basis of thalamic amnesia. Brain: A Journal of Neurology, 108 (Pt 4), 993–1008.Google Scholar
Wang, X. J. (2001). Synaptic reverberation underlying mnemonic persistent activity. Trends in Neurosciences, 24(8), 455–463.Google Scholar
Watanabe, Y., & Funahashi, S. (2004a). Neuronal activity throughout the primate mediodorsal nucleus of the thalamus during oculomotor delayed-responses. I. Cue-, delay-, and response-period activity. Journal of Neurophysiology, 92(3), 1738–1755.Google Scholar
Watanabe, Y., & Funahashi, S. (2004b). Neuronal activity throughout the primate mediodorsal nucleus of the thalamus during oculomotor delayed-responses. II. Activity encoding visual versus motor signal. Journal of Neurophysiology, 92(3), 1756–1769.Google Scholar
Watanabe, Y., Takeda, K., & Funahashi, S. (2009). Population vector analysis of primate mediodorsal thalamic activity during oculomotor delayed-response performance. Cerebral Cortex, 19(6), 1313–1321.Google Scholar
Watson, R. T., & Heilman, K. M. (1979). Thalamic neglect. Neurology, 29(5), 690–694.Google Scholar
Wilke, M., Turchi, J., Smith, K., Mishkin, M., & Leopold, D. A. (2010). Pulvinar inactivation disrupts selection of movement plans. Journal of Neuroscience, 30(25), 8650–8659.Google Scholar
Willcutt, E. G., Doyle, A. E., Nigg, J. T., Faraone, S. V., & Pennington, B. F. (2005). Validity of the executive function theory of attention-deficit/hyperactivity disorder: a meta-analytic review. Biological Psychiatry, 57(11), 1336–1346.Google Scholar
Wimmer, R. D., Schmitt, L. I., Davidson, T. J., Nakajima, M., Deisseroth, K., & Halassa, M. M. (2015). Thalamic control of sensory selection in divided attention. Nature, 526(7575), 705–709.Google Scholar
Womelsdorf, T., Schoffelen, J.-M., Oostenveld, R., Singer, W., Desimone, R., Engel, A. K., & Fries, P. (2007). Modulation of neuronal interactions through neuronal synchronization. Science, 316(5831), 1609–1612.Google Scholar
Xiao, D., Zikopoulos, B., & Barbas, H. (2009). Laminar and modular organization of prefrontal projections to multiple thalamic nuclei. Neuroscience, 161(4), 1067–1081.Google Scholar
Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C., & Wager, T. D. (2011). Large-scale automated synthesis of human functional neuroimaging data. Nature Methods, 8(8), 665–670.Google Scholar
Yeo, B. T. T., Krienen, F. M., Eickhoff, S. B., Yaakub, S. N., Fox, P. T., Buckner, R. L., Asplund, C. L., & Chee, M. W. L. (2015). Functional specialization and flexibility in human association cortex. Cerebral Cortex, 25(10), 3654–3672.Google Scholar
Yeo, B. T. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., Roffman, J. L., Smoller, J. W., Zöllei, L., Polimeni, J. R., Fischl, B., Liu, H., & Buckner, R. L. (2011). The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106(3), 1125–1165.Google Scholar
Yu, Q., Panichello, M. F., Cai, Y., Postle, B. R., & Buschman, T. J. (2020). Delay-period activity in frontal, parietal, and occipital cortex tracks noise and biases in visual working memory. PLoS Biology, 18(9), e3000854.Google Scholar
Zanto, T. P., Rubens, M. T., Thangavel, A., & Gazzaley, A. (2011). Causal role of the prefrontal cortex in top-down modulation of visual processing and working memory. Nature Neuroscience, 14(5), 656–661.Google Scholar
Zhang, D., Snyder, A. Z., Fox, M. D., Sansbury, M. W., Shimony, J. S., & Raichle, M. E. (2008). Intrinsic functional relations between human cerebral cortex and thalamus. Journal of Neurophysiology, 100(4), 1740–1748.Google Scholar
Zhou, H., Schafer, R. J., & Desimone, R. (2016). Pulvinar-cortex interactions in vision and attention. Neuron, 89(1), 209–220.Google Scholar
Zikopoulos, B., & Barbas, H. (2006). Prefrontal projections to the thalamic reticular nucleus form a unique circuit for attentional mechanisms. Journal of Neuroscience, 26(28), 7348–7361.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×