1932

Abstract

Over the past two decades, neurophysiological responses in the lateral intraparietal area (LIP) have received extensive study for insight into decision making. In a parallel manner, inferred cognitive processes have enriched interpretations of LIP activity. Because of this bidirectional interplay between physiology and cognition, LIP has served as fertile ground for developing quantitative models that link neural activity with decision making. These models stand as some of the most important frameworks for linking brain and mind, and they are now mature enough to be evaluated in finer detail and integrated with other lines of investigation of LIP function. Here, we focus on the relationship between LIP responses and known sensory and motor events in perceptual decision-making tasks, as assessed by correlative and causal methods. The resulting sensorimotor-focused approach offers an account of LIP activity as a multiplexed amalgam of sensory, cognitive, and motor-related activity, with a complex and often indirect relationship to decision processes. Our data-driven focus on multiplexing (and de-multiplexing) of various response components can complement decision-focused models and provides more detailed insight into how neural signals might relate to cognitive processes such as decision making.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-neuro-072116-031508
2017-07-25
2024-06-15
Loading full text...

Full text loading...

/deliver/fulltext/neuro/40/1/annurev-neuro-072116-031508.html?itemId=/content/journals/10.1146/annurev-neuro-072116-031508&mimeType=html&fmt=ahah

Literature Cited

  1. Andersen RA, Asanuma C, Cowan WM. 1985. Callosal and prefrontal associational projecting cell populations in area 7A of the macaque monkey: a study using retrogradely transported fluorescent dyes. J. Comp. Neurol. 232:4443–55 [Google Scholar]
  2. Andersen RA, Asanuma C, Essick G, Siegel RM. 1990. Corticocortical connections of anatomically and physiologically defined subdivisions within the inferior parietal lobule. J. Comp. Neurol. 296165–113 [Google Scholar]
  3. Balan PF, Gottlieb J. 2009. Functional significance of nonspatial information in monkey lateral intraparietal area. J. Neurosci. 29:258166–76 [Google Scholar]
  4. Basso MA, Wurtz RH. 1998. Modulation of neuronal activity in superior colliculus by changes in target probability. J. Neurosci. 18:187519–34 [Google Scholar]
  5. Basso MA, Wurtz RH. 1997. Modulation of neuronal activity by target uncertainty. Nature 389:664666–69 [Google Scholar]
  6. Belmonte JCI, Callaway EM, Churchland P, Caddick SJ, Feng G. et al. 2015. Brains, genes, and primates. Neuron 86:3617–31 [Google Scholar]
  7. Ben Hamed S, Duhamel J-R, Bremmer F, Graf W. 2001. Representation of the visual field in the lateral intraparietal area of macaque monkeys: a quantitative receptive field analysis. Exp. Brain Res. 140:2127–44 [Google Scholar]
  8. Ben Hamed S, Duhamel J-R, Bremmer F, Graf W. 2002. Visual receptive field modulation in the lateral intraparietal area during attentive fixation and free gaze. Cereb. Cortex 12:3234–45 [Google Scholar]
  9. Bennur S, Gold JI. 2011. Distinct representations of a perceptual decision and the associated oculomotor plan in the monkey lateral intraparietal area. J. Neurosci. 31:3913–21 [Google Scholar]
  10. Bisley JW, Krishna BS, Goldberg ME. 2004. A rapid and precise on-response in posterior parietal cortex. J. Neurosci. 24:81833–38 [Google Scholar]
  11. Blatt GJ, Andersen RA, Stoner GR. 1990. Visual receptive field organization and cortico-cortical connections of the lateral intraparietal area (area LIP) in the macaque. J. Comp. Neurol. 299:4421–45 [Google Scholar]
  12. Britten KH, Newsome WT, Shadlen MN, Celebrini S, Movshon JA. 1996. A relationship between behavioral choice and the visual responses of neurons in macaque MT. Vis. Neurosci. 13:87–100 [Google Scholar]
  13. Britten KH, Shadlen MN, Newsome WT, Movshon JA. 1992. The analysis of visual motion: a comparison of neuronal and psychophysical performance. J. Neurosci. 12:124745–65 [Google Scholar]
  14. Britten KH, Shadlen MN, Newsome WT, Movshon JA. 1993. Responses of neurons in macaque MT to stochastic motion signals. Vis. Neurosci. 10:61157–69 [Google Scholar]
  15. Brody CD, Hanks TD. 2016. Neural underpinnings of the evidence accumulator. Curr. Opin. Neurobiol. 37:149–57 [Google Scholar]
  16. Brown EN, Frank LM, Tang D, Quirk MC, Wilson MA, Wilson MA. 1998. A statistical paradigm for neural spike train decoding applied to position prediction from ensemble firing patterns of rat hippocampal place cells. J. Neurosci. 18:187411–25 [Google Scholar]
  17. Brunton BW, Botvinick MM, Brody CD. 2013. Rats and humans can optimally accumulate evidence for decision-making. Science 340:612895–98 [Google Scholar]
  18. Carland MA, Marcos E, Thura D. 2016. Evidence against perfect integration of sensory information during perceptual decision making. J. Neurophysiol. 115:2915–30 [Google Scholar]
  19. Carpenter RH, Williams ML. 1995. Neural computation of log likelihood in control of saccadic eye movements. Nature 377:654459–62 [Google Scholar]
  20. Chichilnisky EJ. 2001. A simple white noise analysis of neuronal light responses. Network 12:2199–213 [Google Scholar]
  21. Chowdhury SA, DeAngelis GC. 2008. Fine discrimination training alters the causal contribution of macaque area MT to depth perception. Neuron 60:2367–77 [Google Scholar]
  22. Churchland AK, Kiani R, Chaudhuri R, Wang X-J, Pouget A, Shadlen MN. 2011. Variance as a signature of neural computations during decision making. Neuron 69:4818–31 [Google Scholar]
  23. Churchland AK, Kiani R, Shadlen MN. 2008. Decision-making with multiple alternatives. Nat. Neurosci. 11:6693–702 [Google Scholar]
  24. Cisek P, Puskas GA, El-Murr S. 2009. Decisions in changing conditions: the urgency-gating model. J. Neurosci. 29:3711560–71 [Google Scholar]
  25. Colby CL, Duhamel J-R, Goldberg ME. 1996. Visual, presaccadic, and cognitive activation of single neurons in monkey lateral intraparietal area. J. Neurophysiol. 76:52841–52 [Google Scholar]
  26. Cook EP, Maunsell JHR. 2004. Attentional modulation of motion integration of individual neurons in the middle temporal visual area. J. Neurosci. 24:367964–77 [Google Scholar]
  27. Cooke DF, Goldring A, Recanzone GH, Krubitzer L. 2014. The evolution of parietal areas associated with visuomanual behavior: from grasping to tool use. The New Visual Neurosciences JS Werner, LM Chalupa 1049–63 Cambridge, MA: MIT Press [Google Scholar]
  28. Cutrell EB, Marrocco RT. 2002. Electrical microstimulation of primate posterior parietal cortex initiates orienting and alerting components of covert attention. Exp. Brain Res. 144:1103–13 [Google Scholar]
  29. Dai J, Brooks DI, Sheinberg DL. 2014. Optogenetic and electrical microstimulation systematically bias visuospatial choice in primates. Curr. Biol. 24:163–69 [Google Scholar]
  30. de Lafuente V, Jazayeri M, Shadlen MN. 2015. Representation of accumulating evidence for a decision in two parietal areas. J. Neurosci. 35:104306–18 [Google Scholar]
  31. Ding L, Gold JI. 2010. Caudate encodes multiple computations for perceptual cecisions. J. Neurosci. 30:4715747–59 [Google Scholar]
  32. Ding L, Gold JI. 2012a. Neural correlates of perceptual decision making before, during, and after decision commitment in monkey frontal eye field. Cereb. Cortex 22:51052–67 [Google Scholar]
  33. Ding L, Gold JI. 2012b. Separate, causal roles of the caudate in saccadic choice and execution in a perceptual decision task. Neuron 75:5865–74 [Google Scholar]
  34. Ding L, Gold JI. 2013. The basal ganglia's contributions to perceptual decision making. Neuron 79:4640–49 [Google Scholar]
  35. Erlich JC, Brunton BW, Duan CA, Hanks TD, Brody CD. 2015. Distinct effects of prefrontal and parietal cortex inactivations on an accumulation of evidence task in the rat. eLife 4:e05457 [Google Scholar]
  36. Falkner AL, Krishna BS, Goldberg ME. 2010. Surround suppression sharpens the priority map in the lateral intraparietal area. J. Neurosci. 30:3812787–97 [Google Scholar]
  37. Fanini A, Assad JA. 2009. Direction selectivity of neurons in the macaque lateral intraparietal area. J. Neurophysiol. 101:1289–305 [Google Scholar]
  38. Felleman DJ, Van Essen DC. 1991. Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1:11–47 [Google Scholar]
  39. Fernandes HL, Stevenson IH, Phillips AN, Segraves MA, Körding KP. 2014. Saliency and saccade encoding in the frontal eye field during natural scene search. Cereb. Cortex 24:123232–45 [Google Scholar]
  40. Ferraina S, Paré M, Wurtz RH. 2002. Comparison of cortico-cortical and cortico-collicular signals for the generation of saccadic eye movements. J. Neurophysiol. 87:2845–58 [Google Scholar]
  41. Fetsch CR, Kiani R, Newsome WT, Shadlen MN. 2014. Effects of cortical microstimulation on confidence in a perceptual decision. Neuron 83:4797–804 [Google Scholar]
  42. Freedman DJ, Assad JA. 2006. Experience-dependent representation of visual categories in parietal cortex. Nature 443:710785–88 [Google Scholar]
  43. Freedman DJ, Assad JA. 2011. A proposed common neural mechanism for categorization and perceptual decisions. Nat. Neurosci. 14:2143–46 [Google Scholar]
  44. Freedman DJ, Assad JA. 2016. Neuronal mechanisms of visual categorization: an abstract view on decision making. Annu. Rev. Neurosci. 39:129–47 [Google Scholar]
  45. Fusi S, Miller EK, Rigotti M. 2016. Why neurons mix: high dimensionality for higher cognition. Curr. Opin. Neurobiol. 37:66–74 [Google Scholar]
  46. Ghose GM, Bearl DW. 2010. Attention directed by expectations enhances receptive fields in cortical area MT. Vis. Res. 50:4441–51 [Google Scholar]
  47. Ghose GM, Maunsell J. 2002. Attentional modulation in visual cortex depends on task timing. Nature 419:6907616–20 [Google Scholar]
  48. Gnadt JW, Andersen RA. 1988. Memory related motor planning activity in posterior parietal cortex of macaque. Exp. Brain Res. 70:1216–20 [Google Scholar]
  49. Gold JI, Shadlen MN. 2000. Representation of a perceptual decision in developing oculomotor commands. Nature 404:6776390–94 [Google Scholar]
  50. Gold JI, Shadlen MN. 2003. The influence of behavioral context on the representation of a perceptual decision in developing oculomotor commands. J. Neurosci. 23:2632–51 [Google Scholar]
  51. Gold JI, Shadlen MN. 2007. The neural basis of decision making. Annu. Rev. Neurosci. 30:535–74 [Google Scholar]
  52. Goldman-Rakic PS. 1995. Cellular basis of working memory. Neuron 14:3477–85 [Google Scholar]
  53. Gottlieb J, Balan P. 2010. Attention as a decision in information space. Trends Cogn. Sci. 14:6240–48 [Google Scholar]
  54. Hanes DP, Schall JD. 1995. Countermanding saccades in macaque. Vis. Neurosci. 12:5929–37 [Google Scholar]
  55. Hanes DP, Schall JD. 1996. Neural control of voluntary movement initiation. Science 274:5286427–30 [Google Scholar]
  56. Hanks TD, Ditterich J, Shadlen MN. 2006. Microstimulation of macaque area LIP affects decision-making in a motion discrimination task. Nat. Neurosci. 9:5682–89 [Google Scholar]
  57. Hanks TD, Kiani R, Shadlen MN. 2014. A neural mechanism of speed-accuracy tradeoff in macaque area LIP. eLife 3:e02260 [Google Scholar]
  58. Hanks TD, Kopec CD, Brunton BW, Duan CA, Erlich JC, Brody CD. 2015. Distinct relationships of parietal and prefrontal cortices to evidence accumulation. Nature 520:7546220–23 [Google Scholar]
  59. Hanks TD, Mazurek ME, Kiani R, Hopp E, Shadlen MN. 2011. Elapsed decision time affects the weighting of prior probability in a perceptual decision task. J. Neurosci. 31:176339–52 [Google Scholar]
  60. Hanks TD, Summerfield C. 2017. Perceptual decision making in rodents, monkeys, and humans. Neuron 93:115–31 [Google Scholar]
  61. Harvey CD, Coen P, Tank DW. 2013. Choice-specific sequences in parietal cortex during a virtual-navigation decision task. Nature 484:739262–68 [Google Scholar]
  62. Histed MH, Bonin V, Reid RC. 2009. Direct activation of sparse, distributed populations of cortical neurons by electrical microstimulation. Neuron 63:4508–22 [Google Scholar]
  63. Horwitz GD, Batista AP, Newsome WT. 2004. Representation of an abstract perceptual decision in macaque superior colliculus. J. Neurophysiol. 91:52281–96 [Google Scholar]
  64. Horwitz GD, Newsome WT. 1999. Separate signals for target selection and movement specification in the superior colliculus. Science 284:54171158–61 [Google Scholar]
  65. Huk AC, Shadlen MN. 2005. Neural activity in macaque parietal cortex reflects temporal integration of visual motion signals during perceptual decision making. J. Neurosci. 254510420–36 [Google Scholar]
  66. Ipata AE, Gee AL, Goldberg ME, Bisley JW. 2006. Activity in the lateral intraparietal area predicts the goal and latency of saccades in a free-viewing visual search task. J. Neurosci. 26:143656–61 [Google Scholar]
  67. Jacobs AL, Fridman G, Douglas RM, Alam NM, Latham PE. et al. 2009. Ruling out and ruling in neural codes. PNAS 106:145936–41 [Google Scholar]
  68. Janssen P, Shadlen MN. 2005. A representation of the hazard rate of elapsed time in macaque area LIP. Nat. Neurosci. 8:2234–41 [Google Scholar]
  69. Janssen P, Srivastava S, Ombelet S, Orban GA. 2008. Coding of shape and position in macaque lateral intraparietal area. J. Neurosci. 28:266679–90 [Google Scholar]
  70. Jazayeri M, Shadlen MN. 2015. A neural mechanism for sensing and reproducing a time interval. Curr. Biol. 25:202599–609 [Google Scholar]
  71. Joo SJ, Katz LN, Huk AC. 2016. Decision-related perturbations of decision-irrelevant eye movements. PNAS 113:71925–30 [Google Scholar]
  72. Katz LN, Yates JL, Pillow JW, Huk AC. 2016. Dissociated functional significance of decision-related activity in the primate dorsal stream. Nature 535:7611285–88 [Google Scholar]
  73. Kerkhoff G. 2001. Spatial hemineglect in humans. Prog. Neurobiol. 63:11–27 [Google Scholar]
  74. Kiani R, Hanks TD, Shadlen MN. 2008. Bounded integration in parietal cortex underlies decisions even when viewing duration is dictated by the environment. J. Neurosci. 28:123017–29 [Google Scholar]
  75. Kiani R, Shadlen MN. 2009. Representation of confidence associated with a decision by neurons in the parietal cortex. Science 324:5928759–64 [Google Scholar]
  76. Kim JN, Shadlen MN. 1999. Neural correlates of a decision in the dorsolateral prefrontal cortex of the macaque. Nat. Neurosci. 2:176–85 [Google Scholar]
  77. Kira S, Yang T, Shadlen MN. 2015. A neural implementation of Wald's sequential probability ratio test. Neuron 85:4861–73 [Google Scholar]
  78. Kubanek J, Li JM, Snyder LH. 2015. Motor role of parietal cortex in a monkey model of hemispatial neglect. PNAS 112:16E2067–72 [Google Scholar]
  79. Laming DRJ. 1968. Information Theory of Choice-Reaction Times New York: Acad. Press [Google Scholar]
  80. Latimer KW, Yates JL, Meister MLR, Huk AC, Pillow JW. 2015. Single-trial spike trains in parietal cortex reveal discrete steps during decision-making. Science 349:6244184–87 [Google Scholar]
  81. Law C-T, Gold JI. 2008. Neural correlates of perceptual learning in a sensory-motor, but not a sensory, cortical area. Nat. Neurosci. 11:4505–13 [Google Scholar]
  82. Lennie P. 1998. Single units and visual cortical organization. Perception 27:8889–935 [Google Scholar]
  83. Leon MI, Shadlen MN. 2003. Representation of time by neurons in the posterior parietal cortex of the macaque. Neuron 38:2317–27 [Google Scholar]
  84. Lewis JW, Van Essen DC. 2000a. Corticocortical connections of visual, sensorimotor, and multimodal processing areas in the parietal lobe of the macaque monkey. J. Comp. Neurol. 428:1112–37 [Google Scholar]
  85. Lewis JW, Van Essen DC. 2000b. Mapping of architectonic subdivisions in the macaque monkey, with emphasis on parieto‐occipital cortex. J. Comp. Neurol. 428:179–111 [Google Scholar]
  86. Li N, Daie K, Svoboda K, Druckmann S. 2016. Robust neuronal dynamics in premotor cortex during motor planning. Nature 532:7600459–64 [Google Scholar]
  87. Licata AM, Kaufman MT, Raposo D, Ryan MB. 2016. Posterior parietal cortex guides visual decisions in rats. bioRxiv 066639. https://dx.doi.org/10.1101/066639 [Crossref]
  88. Liu Y, Yttri EA, Snyder LH. 2010. Intention and attention: different functional roles for LIPd and LIPv. Nat. Neurosci. 13:4495–500 [Google Scholar]
  89. Louie K, LoFaro T, Webb R, Glimcher PW. 2014. Dynamic divisive normalization predicts time-varying value coding in decision-related circuits. J. Neurosci. 34:4816046–57 [Google Scholar]
  90. Mante V, Sussillo D, Shenoy KV, Newsome WT. 2013. Context-dependent computation by recurrent dynamics in prefrontal cortex. Nature 503:747478–84 [Google Scholar]
  91. Maunsell JH, Van Essen DC. 1983. Functional properties of neurons in middle temporal visual area of the macaque monkey. I. Selectivity for stimulus direction, speed, and orientation. J. Neurophysiol. 49:51127–47 [Google Scholar]
  92. Mayo JP, DiTomasso AR, Sommer MA, Smith MA. 2015. Dynamics of visual receptive fields in the macaque frontal eye field. J. Neurophysiol. 114:63201–10 [Google Scholar]
  93. Mayo JP, Morrison RM, Smith MA. 2016. A probabilistic approach to receptive field mapping in the frontal eye fields. Front. Syst. Neurosci. 10:25 [Google Scholar]
  94. Mazurek ME, Roitman JD, Ditterich J, Shadlen MN. 2003. A role for neural integrators in perceptual decision making. Cereb. Cortex 13:111257–69 [Google Scholar]
  95. Meister MLR, Hennig JA, Huk AC. 2013. Signal multiplexing and single-neuron computations in lateral intraparietal area during decision-making. J. Neurosci. 33:62254–67 [Google Scholar]
  96. Mountcastle VB, Lynch JC, Georgopoulos A, Sakata H, Acuna C. 1975. Posterior parietal association cortex of the monkey: command functions for operations within extrapersonal space. J. Neurophysiol. 38:4871–908 [Google Scholar]
  97. Murasugi CM, Salzman CD, Newsome WT. 1993. Microstimulation in visual area MT: effects of varying pulse amplitude and frequency. J. Neurosci. 13:41719–29 [Google Scholar]
  98. Newsome WT, Paré EB. 1988. A selective impairment of motion perception following lesions of the middle temporal visual area (MT). J. Neurosci. 8:62201–11 [Google Scholar]
  99. Pagan M, Rust NC. 2014. Quantifying the signals contained in heterogeneous neural responses and determining their relationships with task performance. J. Neurophysiol. 112:61584–98 [Google Scholar]
  100. Palmer J, Huk AC, Shadlen MN. 2005. The effect of stimulus strength on the speed and accuracy of a perceptual decision. J. Vis. 5:5376–404 [Google Scholar]
  101. Paninski L, Shoham S, Fellows MR, Hatsopoulos NG, Donoghue JP. 2004. Superlinear population encoding of dynamic hand trajectory in primary motor cortex. J. Neurosci. 24:398551–61 [Google Scholar]
  102. Pare M, Wurtz RH. 1997. Monkey posterior parietal cortex neurons antidromically activated from superior colliculus. J. Neurophysiol. 78:63493–97 [Google Scholar]
  103. Park IM, Meister MLR, Huk AC, Pillow JW. 2014. Encoding and decoding in parietal cortex during sensorimotor decision-making. Nat. Neurosci. 17:101395–403 [Google Scholar]
  104. Patel GH, Shulman GL, Baker JT, Akbudak E, Snyder AZ. et al. 2010. Topographic organization of macaque area LIP. PNAS 107:104728–33 [Google Scholar]
  105. Pesaran B, Freedman DJ. 2016. Where are perceptual decisions made in the brain. ? Trends Neurosci 39:10642–44 [Google Scholar]
  106. Pillow JW, Paninski L, Uzzell VJ, Simoncelli EP, Chichilnisky EJ. 2005. Prediction and decoding of retinal ganglion cell responses with a probabilistic spiking model. J. Neurosci. 25:4711003–13 [Google Scholar]
  107. Pillow JW, Shlens J, Paninski L, Sher A, Litke AM. et al. 2008. Spatio-temporal correlations and visual signalling in a complete neuronal population. Nature 454:7207995–99 [Google Scholar]
  108. Pisupati S, Chartarifsky L, Churchland AK. 2016. Decision activity in parietal cortex – leader or follower. ? Trends Cogn. Sci. 20:11788–89 [Google Scholar]
  109. Platt ML, Glimcher PW. 1997. Responses of intraparietal neurons to saccadic targets and visual distractors. J. Neurophysiol. 78:31574–89 [Google Scholar]
  110. Ramkumar P, Dekleva B, Cooler S, Miller L, Kording K. 2016. Premotor and motor cortices encode reward. PLOS ONE 11:8e0160851 [Google Scholar]
  111. Rao V, DeAngelis GC, Snyder LH. 2012. Neural correlates of prior expectations of motion in the lateral intraparietal and middle temporal areas. J. Neurosci. 32:2910063–74 [Google Scholar]
  112. Raposo D, Kaufman MT, Churchland AK. 2014. A category-free neural population supports evolving demands during decision-making. Nat. Neurosci. 17:121784–92 [Google Scholar]
  113. Ratcliff R. 1978. A theory of memory retrieval. Psychol. Rev. 85:259–108 [Google Scholar]
  114. Ratcliff R, Smith PL, Brown SD, McKoon G. 2016. Diffusion decision model: current issues and history. Trends Cogn. Sci. 20:4260–81 [Google Scholar]
  115. Rigotti M, Barak O, Warden MR, Wang X-J, Daw ND. et al. 2013. The importance of mixed selectivity in complex cognitive tasks. Nature 497:7451585–90 [Google Scholar]
  116. Rishel CA, Huang G, Freedman DJ. 2013. Independent category and spatial encoding in parietal cortex. Neuron 77:5969–79 [Google Scholar]
  117. Robinson DL, Goldberg ME, Stanton GB. 1978. Parietal association cortex in the primate: sensory mechanisms and behavioral modulations. J. Neurophysiol. 41:4910–32 [Google Scholar]
  118. Roitman JD, Shadlen MN. 2002. Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. J. Neurosci. 22:219475–89 [Google Scholar]
  119. Rorie AE, Gao J, McClelland JL, Newsome WT. 2010. Integration of sensory and reward information during perceptual decision-making in lateral intraparietal cortex (LIP) of the macaque monkey. PLOS ONE 5:2e9308 [Google Scholar]
  120. Salzman CD, Britten KH, Newsome WT. 1990. Cortical microstimulation influences perceptual judgements of motion direction. Nature 346:174–77 [Google Scholar]
  121. Salzman CD, Murasugi CM, Britten KH, Newsome WT. 1992. Microstimulation in visual area MT: effects on direction discrimination performance. J. Neurosci. 12:62331–55 [Google Scholar]
  122. Sarma A, Masse NY, Wang X-J, Freedman DJ. 2015. Task-specific versus generalized mnemonic representations in parietal and prefrontal cortices. Nat. Neurosci. 19:1143–49 [Google Scholar]
  123. Schall JD. 2001. Neural basis of deciding, choosing and acting. Nat. Rev. Neurosci. 2:133–42 [Google Scholar]
  124. Selen LPJ, Shadlen MN, Wolpert DM. 2012. Deliberation in the motor system: reflex gains track evolving evidence leading to a decision. J. Neurosci. 32:72276–86 [Google Scholar]
  125. Shadlen MN, Britten KH, Newsome WT, Movshon JA. 1996. A computational analysis of the relationship between neuronal and behavioral responses to visual motion. J. Neurosci. 16:41486–510 [Google Scholar]
  126. Shadlen MN, Kiani R. 2013. Decision making as a window on cognition. Neuron 80:3791–806 [Google Scholar]
  127. Shadlen MN, Kiani R, Hanks TD, Churchland AK. 2008. Neurobiology of decision making: an intentional framework. Better Than Conscious? Decision Making, the Human Mind, and Implications for Institutions C Engel, W Singer 71–101 Cambridge, MA: MIT Press [Google Scholar]
  128. Shadlen MN, Newsome WT. 1996. Motion perception: seeing and deciding. PNAS 93:2628–33 [Google Scholar]
  129. Shadlen MN, Newsome WT. 2001. Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. J. Neurophysiol. 86:41916–36 [Google Scholar]
  130. Snyder LH, Batista AP, Andersen RA. 2000. Intention-related activity in the posterior parietal cortex: a review. Vis. Res. 40:10–121433–41 [Google Scholar]
  131. Song J-H, Nakayama K. 2009. Hidden cognitive states revealed in choice reaching tasks. Trends Cogn. Sci. 13:8360–66 [Google Scholar]
  132. Spivey MJ, Grosjean M, Knoblich G. 2005. Continuous attraction toward phonological competitors. PNAS 102:2910393–98 [Google Scholar]
  133. Tehovnik EJ, Tolias AS, Slocum WM, Logothetis NK. 2006. Direct and indirect activation of cortical neurons by electrical microstimulation. J. Neurophysiol. 96:2512–21 [Google Scholar]
  134. Truccolo W, Eden UT, Fellows MR, Donoghue JP, Brown EN. 2005. A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects. J. Neurophysiol. 93:21074–89 [Google Scholar]
  135. Ungerleider LG, Desimone R. 1986. Projections to the superior temporal sulcus from the central and peripheral field representations of V1 and V2. J. Comp. Neurol. 248:2147–63 [Google Scholar]
  136. Wardak C, Olivier E, Duhamel J-R. 2002. Saccadic target selection deficits after lateral intraparietal area inactivation in monkeys. J. Neurosci. 22:229877–84 [Google Scholar]
  137. Wardak C, Olivier E, Duhamel J-R. 2004. A deficit in covert attention after parietal cortex inactivation in the monkey. Neuron 42:3501–8 [Google Scholar]
  138. Wilke M, Kagan I, Andersen RA. 2012. Functional imaging reveals rapid reorganization of cortical activity after parietal inactivation in monkeys. PNAS 109:218274–79 [Google Scholar]
  139. Wong K-F. 2007. Neural circuit dynamics underlying accumulation of time-varying evidence during perceptual decision making. Front. Comput. Neurosci. 1:6 [Google Scholar]
  140. Wurtz RH, Sommer MA, Pare M, Ferraina S. 2001. Signal transformations from cerebral cortex to superior colliculus for the generation of saccades. Vis. Res. 41:25–263399–412 [Google Scholar]
  141. Wyart V, De Gardelle V, Scholl J, Summerfield C. 2012. Rhythmic fluctuations in evidence accumulation during decision making in the human brain. Neuron 76:4847–58 [Google Scholar]
  142. Yang T, Shadlen MN. 2007. Probabilistic reasoning by neurons. Nature 447:71481075–80 [Google Scholar]
  143. Yates JL, Park IM, Katz LN, Pillow JP, Huk AC. 2017. Functional dissection of signal and noise in MT and LIP during decision making. Nat. Neurosci. In press [Google Scholar]
  144. Yu BM, Cunningham JP, Santhanam G, Ryu SI, Shenoy KV, Sahani M. 2009. Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity. J. Neurophysiol. 102:11881–88 [Google Scholar]
  145. Zirnsak M, Chen X, Lomber SG, Moore T. 2015. Effects of reversible inactivation of parietal cortex on the processing of visual salience in the frontal eye field Presented at Soc. Neurosci., Prog. No. 747.06, Oct. 21 Chicago: [Google Scholar]
/content/journals/10.1146/annurev-neuro-072116-031508
Loading
/content/journals/10.1146/annurev-neuro-072116-031508
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error