Kreiman Lab Publications

    2022

  1. Zhang M, Dellaferrera G, Sikarwar A, Armendariz M, Mudrik N, Agrawal P, Madan S, Barbu A, Yang H, Kumar T, Sadwani M, Dellaferrera S, Pizzochero M, Pfister H, Kreiman G (2022). Human or Machine? Turing Tests for Vision and Language. arXiv 2211.13087 PDF

  2. Li C, Kreiman G, Ramanathan S (2022). Integrating artificial and biological neural networks to improve animal task performance using deep reinforcement learning. bioRxiv 2022.09.19.508590 PDF

  3. Liu X, Sikarwar A, Lim JH, Kreiman G, Shi Z, Zhang M (2022). Reason from context with self-supervised learning. arXiv 2211.12817 PDF

  4. Zhang M, Xiao W, Rose O, Bendtz K, Livingstone M, Ponce CR, Kreiman G (2022). Look Twice: A Generalist Computational Model Predicts Return Fixations across Tasks and Species. PLoS Computational Biology, 18(11):e1010654 PDF | Supplementary Material | Resources

  5. Casper S, Nadeau M, Kreiman G (2022). One thing to fool them all: generating interpretable, universal, and physically-realizable adversarial features. NeurIPS. PDF

  6. Murugan R, Kreiman G (2022). Multiple transcription autoregulatory loops act as robust oscillators and decision making motifs   Computational and Structural Biotechnology Journal 20:5115-5135 PDF

  7. Bardon A, Xiao W, Ponce CR, Livingstone MS, Kreiman G (2022). Face neurons encode nonsemantic features. PNAS 119, e2118705119, doi:10.1073/pnas.2118705119 . PDF | Supplementary Material | Resources

  8. Zheng J, Schjetnan AGP, Yebra M, Mosher C, Kalia S, Valiante TA, Mamelak A, Kreiman G, Rutishauser U (2022). Cognitive boundary signals in the human medial temporal lobe shape episodic memory representation. Nature Neuroscience 25:358-368 . PDF | Resources

  9. Hoogsteen KMP, Szpiro S, Kreiman G, Peli E (2022). Beyond the Cane: Describing Urban Scenes to Blind People for Mobility Tasks. ACM Transactions on Accessible Computing 2022-09-3.  DOI: 10.1145/3522757. PDF

  10. Xiao Y, Chou C, Cosgrove GR, Crone NE, Stone S, Madsen JR, Reucroft I, Weisholtz D, Shih YC, Yu HY, Anderson WS, Kreiman G (2022) Cross-task specificity and within-task invariance og cognitive control processes. bioRxiv 2022.01.16.476535. Cell Reports, In Press. PDF | Supplementary Material | Resources

  11. Melloni L, Mudrik L, Pitts M, Bentz K, Ferrante O, Gorska U, Hirschhorn R, Khalaf A, Kozma C, Lepauvre A, Liu L, Mazumder D, Richter D, Zhou H, Blumenfeld H, Chalmers DJ, Devore S, Fallon F, de Lange F, Jensen O, Kreiman G, Luo H, Dehaene S, Koch C, Tononi G (2022). An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory. Scientific Reports, In Press. PDF

  12. Armendariz M, Xiao W, Vinken K, Kreiman G (2022). Do computational models of vision need shape-based representations? Evidence from an individual with intriguing visual perceptions. Cognitive Neuropsychology. In Press. PDF

  13. Dellaferrera G, Kreiman G (2022). Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass. International Conference on Machine Learning (ICML)   PDF

  14. Sikarwar, A, Kreiman G (2022). On the efficacy of co-attention transformer layers in visual question answering. arXiv 2201.03965. PDF

  15. Shaham N, Chandra J, Kreiman G, Sompolinsky H (2022). Stochastic consolidation of lifelong memory. Scientific Reports, 12: 13107 PDF

  16. 2021

  17. Gupta SK, Zhang M, Wu CC, Wolfe JM, Kreiman G (2021). Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases. NeurIPS. PDF | Supplementary Material | Resources

  18. Bricken T, Pehlevan C (2021). Attention approximates sparse distributed memory. NeurIPS. PDF

  19. Zhang Y, Aghajan ZM, Ison M, Lu Q, Tang H, Kalender G, Monsoor T, Zheng J, Kreiman G, Roychowdhury V, Fried I (2021). Decoding of human identity by computer vision and neuronal vision. bioRxiv 2021.10.10.463839 PDF

  20. Weisholtz, DS, Kreiman G, Silbersweig DA, Stern E, Cha B, Butler T (2021). Localized Task-Invariant Emotional Valence Encoding Revealed by Intracranial Recordings. Soc Cogn Affect Neurosci, doi:10.1093/scan/nsab134 PDF

  21. Wang J, Tao A, Anderson WS, Madsen JR, Kreiman G (2021). Mesoscopic physiological interactions in the human brain reveal small world properties. Cell Reports 36 (8) 109585. PDF | Supplementary Material | Resources

  22. Zhang M, Kreiman G (2021). Beauty is in the eye of the machine. Nature Human Behavior 5:1-2 PDF

  23. Bomatter P, Zhang M, Karev D, Madan S, Tseng C, Kreiman G (2021). When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes. International Conference on Computer Vision (ICCV) arXiv 2104.02215 PDF

  24. Zhang M, Badkundri R, Talbot M, Kreiman G (2021). Hypothesis-driven Stream Learning with Augmented Memory. arXiv 2104.02206 PDF

  25. Casper S, Boix X, D'Amario V, Guo L, Schrimpf M, Vinken K, Kreiman G. (2021). Frivolous Units: Wider Networks are not really that Wide. AAAI Conference on Artificial Intelligence. PDF

  26. 2020

  27. Yuan L, Xiao W, Kreiman G, Tay FEH, Feng, JL, Livingstone, M (2020). Adversarial images for the primate brain. arXiv. 2011.05623 PDF

  28. Kreiman G and Serre T (2020). Beyond the feedforward sweep: feedback computations in the visual cortex. Ann N Y Acad Sci. 1464:222-241. PDF

  29. Vinken K, Boix X, Kreiman G (2020). Incorporating intrinsic suppression in deep neural networks captures dynamics of adaptation in neurophysiology and perception. Science Advances, 6: eabd4205. PDF | Supplementary Material | Resources

  30. Olson J, Kreiman G. (2020). Simple learning rules generate complex cannonical circuits. arXiv:2009.06118 | PDF | Resources

  31. Xiao W. and Kreiman G. (2020). XDream: Finding preferred stimuli for visual neurons using generative networks and gradient-free optimization. PLoS Computational Biology 16(6): e1007973. PDF | Resources | arXiv 1905.00378

  32. Lotter W, Kreiman G, Cox D. (2020) A neural network trained to predict future video frames mimics critical properties of biological neuronal responses and perception. Nature Machine Intelligence, 2:210-219. PDF | Resources

  33. Zhang M, Tseng C, Kreiman G. (2020) Putting visual object recognition in context. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 12982-12991. arXiv:1911.07349 | Supplementary Material | Resources

  34. Jacquot V, Ying J, Kreiman G. (2020) Can Deep Learning Recognize Subtle Human Activities? Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 14244-14253. arXiv 2003.13852 | Resources

  35. Ben-Yosef G, Kreiman G, Ullman S. (2020) Minimal videos: Trade-off between spatial and temporal information in human and machine vision. Cognition 201:104263. PDF | Resources

  36. O'Connel TP, Chun MM, Kreiman G. (2020). Zero-shot neural decoding of visual categories without prior exemplars. bioRxiv 10.1101/700344. PDF

  37. 2019

  38. Ponce C.R., Xiao W., Schade P.F., Hartmann T.S., Kreiman G., Livingstone M. (2019). Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences. Cell, 177:999-1009. PDF | Supplementary Material | Resources | bioRxiv 10.1101/516484. PDF

  39. Zhang M, Tseng C, Montejo K, Kwon J, Kreiman G. Lift-the-flap: what, where and when for context reasoning. arXiv 1902.00163. PDF | Resources

  40. Kreiman G (2019). What do neurons really want? The role of semantics in cortical representations. In Psychology of Learning and Motivation, Volume 70. Chapter 8. PDF | Resources

  41. Kreiman G. (2019) It's a small dimensional world after all. Comment on The unreasonable effectiveness fo small neural ensembles in high-dimensional brains" by Gorban et al. Physics of Life Reviews. PDF

  42. Xiao W, Chen H, Liao Q, Poggio T. (2019). Biologically-plausible learning algorithms can scale to large datasets. ICLR. PDF

  43. Madhavan R, Bansal AK, Madsen JR, Golby AJ, Tierney TS, Eskandar EN, Anderson WS, Kreiman G (2019). Neural interactions underlying visuomotor associations in the human brain. Cerebral Cortex. 29:4551-4567. PDF | Supplementary Material | Resources

  44. 2018

  45. Tang H, Schrimpf M, Lotter W, Moerman C, Paredes A, Ortega Caro J, Hardesty W, Cox D, Kreiman G. (2018) Recurrent computations for visual pattern completion. PNAS, 115:8835-8840. PDF | Supplementary Material | GitHub | Resources. PMID: 30104363

  46. Misra P, Marconi A, Petterson M, Kreiman G. (2018) Minimal memory for details in real life events. Scientific Reports, 8, 16701. PDF | Supplementary Material | Resources

  47. Zhang M, Feng J, Ma KT, Lim JH, Zhao Q, Kreiman G. (2018) Finding any Waldo: zero-shot invariant and efficient visual search. Nature Communications, 9:3730. PDF | Supplementary Material | GitHub | Resources. PMID: 30213937

  48. Zhang M, Feng J, Lim JH, Zhao Q, Kreiman G. (2018) What am I searching for? arXiv version: arXiv 1807.11926

  49. Palepu A, Premananthan CS, Azhar F, Vendrame M, Loddenkemper T, Reinsberger C, Kreiman G, Parkerson K, Sarma VS, Anderson WS. (2018). Automating Interictal Spike Detection: Revisiting A Simple Threshold Rule. Conf Proc IEEE Eng Med Biol Soc. PDF

  50. Wu K, Wu E, Kreiman G (2018). Learning scene gist with convolutional neural networks to improve object recognition. IEEE Annual Conference on Information Sciences and Systems (CISS). arXiv version: arXiv:1803.01967v2 | Resources

  51. Isik I, Singer J, Madsen JR, Kanwisher N, Kreiman G. (2018) What is changing when: Decoding visual information in movies from human intracranial recordings. Neuroimage, 180:147-159. PDF | Supplementary Material | Resources. PMID: 28823828

  52. 2017

  53. Lotter W, Kreiman, G, Cox, D. (2017) Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. International Conference on Learning Representations (ICLR), Toulon, France. PDF | GitHub

  54. Cheney N, Schrimpf M, Kreiman G. On the Robustness of Convolutional Neural Networks to Internal Architecture and Weight Perturbations (2017). arXiv version: arXiv:1703.08245v1

  55. Tang H, Kreiman G. (2017). Recognition of occluded objects. In Computational and Cognitive Neuroscience of Vision. (ed Zhao, Q). Singapore: Springer-Verlag. PDF

  56. 2016

  57. Gomez-Laberge C, Smolyanskaya A, Nassi JJ, Kreiman G, Born R. (2016). Bottom-Up and Top-Down Input Augment the Variability of Cortical Neurons. Neuron, 91:540-547. PDF | Supplementary Material. PMID: 27427459

  58. Tang H, Singer J, Ison M, Pivazyan G, Romaine M, Frias R, Meller E, Boulin A, Carroll JD, Perron V, Dowcett S, Arlellano M, Kreiman G. (2016). Predicting episodic memory formation for movie events. Scientific Reports, 6:30175. PDF | Supplementary Material | Resources. PMID: 27686330

  59. Lotter, W, Kreiman, G, Cox, D. (2016.) Unsupervised representation learning using predictive generative works. International Conference on Learning Representations (ICLR), Puerto Rico. PDF

  60. Kreiman G. (2016). A null model for cortical representations with grandmothers galore. Language, Cognition and Neuroscience, 32, 274-285. PDF. PMID: 29204455

  61. Tang S, Hemberg M, Cansizoglu E, Belin S, Kosik K, Kreiman G, Steen H, Steen J. (2016). f-divergence Cutoff Index to Simultaneously Identify Differential Expression in the Integrated Transcriptome and Proteome. Nucleic Acids Research, 44:e97. PDF | Supplementary Material. PMID: 26980280

  62. Tang H, Yu H, Chou C, Crone N, Madsen J, Anderson W, Kreiman G. (2016). Cascade of neural processing orchestrates cognitive control in human frontal cortex. eLife, 5:e12352. PDF | Supplementary Material | Resources. PMID: 26888070

  63. Miconi T, Groomes L, Kreiman G. (2016). There's Waldo! A Normalization Model of Visual Search Predicts Single-Trial Human Fixations in an Object Search Task. Cerebral Cortex, 26:3064-3082. PDF | Supplementary Material | Resources. PMID: 26092221

  64. 2015

  65. Singer JM, Madsen JR, Anderson WS, Kreiman G. (2015). Sensitivity to Timing and Order in Human Visual Cortex. Journal of Neurophysiology, 113:1656-1669. PDF PMID: 25429116

  66. Madhavan R, Millman D, Tang H, Crone NE, Lenz F, Tierney T, Madsen JR, Kreiman G, Anderson WS. (2015). Decrease in gamma-band activity tracks sequence learning. Frontiers in Systems Neuroscience, 8:222. PDF | Supplementary Material. PMID: 25653598

  67. 2014

  68. Fried I, Rutishauser U, Cerf M, Kreiman G. (2014). Single Neuron Studies of the Human Brain, Probing Cognition. MIT Press. BOOK.

  69. Tang H, Buia C, Madhavan R, Madsen J, Anderson W, Crone N, Kreiman G. (2014). Spatiotemporal dynamics underlying object completion in human ventral visual cortex. Neuron, 83:736-748. PDF | Supplementary Material 1 | Supplementary Material 2. PMID: 25043420

  70. Bansal A. (2014). Human Single Unit Activity for Reach and Grasp Motor Prostheses. In Single Neuron Studies of the Human Brain. (eds Fried I, Rutishauser U, Cerf M, Kreiman, G). Ch 17, MIT Press. PDF

  71. Rutishauser U, Cerf M, Kreiman G. (2014). Data analysis techniques for human microwire recordings: spike detection and sorting, decoding, relation between units and local field potentials. In Single neuron studies of the human brain. Probing cognition (eds Fried I, Rutishauser U, Cerf M, Kreiman, G). Ch 6, MIT Press. PDF

  72. Mormann F, Ison M, Quiroga RQ, Koch C, Fried I, Kreiman G. (2014). Visual cognitive adventures of single neurons in the human medial temporal lobe. In Single neuron studies of the human brain. Probing cognition (eds Fried I, Rutishauser U, Cerf M, Kreiman, G). Ch. 8, MIT Press. PDF

  73. Kreiman G, Rutishauser U, Cerf M, Fried I. (2014). The next ten years and beyond. In Single neuron studies of the human brain. Probing cognition (eds Fried I, Rutishauser U, Cerf M, Kreiman, G). Ch. 19, MIT Press. PDF

  74. Kreiman G. (2014). Neural correlates of consciousness: perception and volition. In Cognitive Neuroscience, Vol. V (ed Gazzaniga M). Ch 68, MIT Press. PDF

  75. Malik A,Vierbuchen T, Hemberg M, Rubin A, Ling E, Couch C, Stroud H, Spiegel I, Farh K, Harmin D, Greenberg M. (2014).Genome-wide identification and characterization of functional neuronal activity–dependent enhancers. Nature Neuroscience, 17:1330-1339. PDF PMID: 25195102

  76. Prabakaran S, Hemberg M, Chauhan R, Winter D, Tweedie-Cullen R, Dittrich C, Hong E, Gunawardena J, Steen H, Kreiman G, Steen JA. (2014). Quantitative Profiling of Peptides from RNAs classified as non-coding. Nature Communications, 5:5429. PDF / SUPPLEMENTARY PDF PMID: 25403355

  77. Pinto A, Fernandez I, Peters J, Mananaro S, Singer J, Vendrame M, Prabhu S, Loddenkemper T, Kothare S. (2014). Localization of sleep spindles, k-complexes, and vertex waves with subdural electrodes in children. Clinical Neurophysiology 4:367-74. PDF PMID: 25083850

  78. Kim T, Hemberg M, Gray J. (2014). Enhancer RNAs: a class of long noncoding RNAs synthesized at enhancers. Invited essay for the Epigenetics textbook (2nd edition). Cold Spring Harbor Press. PDF PMID: 25561718

  79. Nassi J, Gomez-Laberge C, Kreiman G, Born R (2014). Corticocortical feedback increases the spatial extent of normalization. Frontiers in Systems Neuroscience, 8:105. PDF / SUPPLEMENTARY PDF PMID: 24910596

  80. Singer J, Kreiman G. (2014). Short Temporal Asynchrony Disrupts Visual Object Recognition. Journal of Vision, 12,14. PDF / Resources / PMID: 24819738

  81. Frost B, Hemberg M, Lewis J, Feany M. (2014). Tau promotes neurodegeneration through global chromatin relaxation. Nature Neuroscience, 17, 357-366. PDF PMID: 24464041

  82. Bansal A, Madhavan R, Agam Y, Golby A, Madsen J, Kreiman G. (2014). Neural Dynamics Underlying Target Detection in the Human Brain. Journal of Neuroscience, 34, 3042-3055. PDF PMID: 24553944

  83. 2013

  84. Kreiman G. (2013). Computational Models of Visual Object Recognition. In Principles of Neural Coding (eds Panzeri S, Quiroga R). Ch 29, CRC Press. PDF

  85. Kreiman G. (2013). Mind the quantum? Trends in Cognitive Science, 17(3),109. PDF
  86. 2012

  87. Murugan R, Kreiman G. (2012). Theory on the coupled stochastic dynamics of transcription and splice-site recognition. PLoS Computational Biology, 8, 1-13, e1002747. PDF PMID: 23133354

  88. Bansal A, Singer J, Anderson WS, Golby A, Madsen JR, Kreiman G. (2012). Temporal stability of visually selective responses in intracranial field potentials recorded from human occipital and temporal lobes. Journal of Neurophysiology, 108:3073-3086. PDF PMID: 22956795

  89. Hemberg M, Gray JM, Cloonan N, Kuersten S, Grimmond S, Greenberg ME, Kreiman G. (2012). Integrated genome analysis suggests that most conserved non-coding sequences are regulatory factor binding sites. Nucleic Acids Research, 40:7858-7869. PDF / SUPPLEMENTARY PDF / RESOURCES PMID: 2268462

  90. Burbank KS, Kreiman G. (2012). Depression-Biased Reverse Plasticity Rule Is Required for Stable Learning at Top-Down Connections. PLoS Computational Biology, 8:1-16. PDF PMID:22396630

  91. Bansal AK,Truccolo W, Vargas-Irwin CE, Donoghue J. (2012). Decoding 3D reach and grasp from hybrid signals in motor and premotor cortices: spikes, multiunit activity, and local field potentials. Journal of Neurophysiology, 107:1337-55. PDF PMID:22157115

  92. Ross SE, McCord AE, Jung C, Atan D, Mok SI, Hemberg M, Kim TK, Salogiannis J, Hu L, Cohen S, Lin Y, Harrar D, McInnes RR, Greenberg ME. (2012). Bhlhb5 and prdm8 form a repressor complex involved in neuronal circuit assembly. Neuron, 73:292-303. PDF PMID:22284184

  93. 2011

  94. Kriegeskorte N, Kreiman G. (2011). Visual Population Codes, Towards a Common Multivariate Framework for Cell Recording and Functional Imaging. MIT Press. BOOK / RESOURCES

  95. Burbank K, Kreiman G. (2011). Introduction to the Anatomy and Function of Visual Cortex. In Understanding Visual Population codes (eds Kriegeskorte N, Kreiman G). Ch 17, MIT Press. PDF

  96. Singer J, Kreiman G. (2011). Introduction to Statistical Learning and Pattern Classification. In Understanding Visual Population codes (eds Kriegeskorte N, Kreiman G). Ch 18, MIT Press. PDF

  97. Meyers E, Kreiman G. (2011). Tutorial on Pattern Classification in Cell Recording. In Understanding Visual Population Codes (eds Kriegeskorte N, Kreiman G). Ch 19, MIT Press. PDF

  98. Cohen S, Gabel HW, Hemberg M, Hutchinson AN, Sadacca LA, Ebert DH, Harmin DA, Greenberg RS, Verdine VK, Zhou Z, Wetsel WC, West AE, Greenberg ME. (2011). Genome-wide activity-dependent MeCP2 phosphorylation regulates nervous system development and function. Neuron, 72, 72-85. PDF PMID: 21982370

  99. Tang H, Kreiman G. (2011). Face Recognition: Vision and Emotions beyond the Bubble. Current Biology, 21:21. PDF PMID:22075428

  100. Kreiman G, Maunsell J. (2011). Nine criteria for a measure of scientific output. Frontiers in Computational Neuroscience, 5:48. PDF. PMID:22102840

  101. Kreiman G. (2011). Literary inspiration. Nature, 475:453-454. PDF

  102. Murugan R, Kreiman G. (2011). On the minimization of fluctuations in the response times of autoregulatory gene networks. Biophysical Journal, 101:1297-1306. PDF PMID:21943410

  103. Hemberg M, Kreiman G. (2011). Conservation of transcription factor binding events predicts gene expression across species. Nucleic Acids Research, 39:7092-7102 PDF PMID:21622661

  104. Fried I, Mukamel R, Kreiman G. (2011). Internally Generated Preactivation of Single Neurons in Human Medial Frontal Cortex Predicts Volition. Neuron, 69: 548-562. PDF | SUPPLEMENTARY PDF PMID: 21315264

  105. Anderson WS, Kreiman, G. (2011). Neuroscience: What We Cannot Model, We Do Not Understand. Current Biology, 21:R124-R125. PDF PMID:21315264

  106. Chen LL, Madhavan R, Rapoport B, Anderson WS. (2011). A method for real-time cortical oscillation detection and phase-locked stimulation. Conf Proc IEE Eng Med Biol Soc 2011, 3087-3090. PDF PMID:22254992

  107. 2010

  108. Kim TK*, Hemberg M*, Gray JM*, Costa A, Bear DM, Wu J, Harmin DA, Laptewicz, M, Barbara-Haley K, Kuersten S, Markenscoff-Papadimitriou E, Kuhl D, Bito H, Worley PF, Kreiman G, Greenberg ME. (2010). Widespread transcription at thousands of enhancers during activity-dependent gene expression in neurons. Nature, 465:182-187. (* = equal contribution) PDF / SUPPLEMENTARY PDF / RESOURCES PMID:20393465

  109. Agam Y, Liu H, Pappanastassiou A, Buia C, Golby AJ, Madsen JR, Kreiman G. (2010). Robust selectivity to two-object images in human visual cortex. Current Biology, 20:872-879. PDF / SUPPLEMENTARY PDF / RESOURCES PMID:20417105

  110. Pfenning AR, Kim TK, Spotts JM, Hemberg M, Su D, West AE. (2010). Genome-wide identification of calcium-response factor (CaRF) binding sites predicts a role in regulation of neuronal signaling pathways. PLoS One, 5:e10870. PDF PMID:20523734

  111. Blumberg J, Kreiman G. (2010). How cortical neurons help us see: visual recognition in the human brain. Journal of Clinical Investigation, 120:3054-3063. PDF PMID:20811161

  112. Singer JM, Sheinberg DL. (2010). Temporal cortex neurons encode articulated actions as slow sequences of integrated poses. Journal of Neuroscience, 30:3133-3145. PDF PMID:20181610

  113. Quian Quiroga R, Kreiman G. (2010). Measuring sparseness in the brain. Psychological Review, 11:291-297. PDF PMID:20063978

  114. 2009

  115. Stahlberg A, Bengtsson M, Hemberg M, Semb H. (2009). Quantitative transcription factor analysis of undifferentiated single human embryonic stem cells. Clinical Chemistry, 55: 2162-70. PDF PMID: 19815608.

  116. Liu H, Agam Y, Madsen J, Kreiman G. (2009). Timing, timing, timing: Fast decoding of object information from intracranial field potentials in human visual cortex. Neuron, 62:281-290. PDF / SUPPLEMENTARY PDF / RESOURCES PMID:19409272

  117. Rasch M, Logothetis NK, Kreiman G. (2009). From neurons to circuits: linear estimation of local field potentials. Journal of Neuroscience, 29:13785-13796. PDF / RESOURCES PMID:19889990

  118. Horng S, Kreiman G, Ellsworth C, Page D, Blank M, Milen K, Sur M. (2009). Differential Gene Expression in the Developing Lateral Geniculate Nucleus and Medial Geniculate Nucleus Reveals Novel Roles for Zic4 and Foxp2 in Visual and Auditory Pathway Development. Journal of Neuroscience, 29:13672-13683. PDF PMID:19864579

  119. Singer J, Kreiman G. (2009). Toward unmasking the dynamics of visual perception. Neuron, 64:446-447. PDF PMID:19945387

  120. 2008

  121. Meyers E, Freedman D, Kreiman G, Miller E, Poggio T. (2008). Dynamic Population Coding of Category Information in ITC and PFC. Journal of Neurophysiology, 100:1407-1419 PDF / SUPPLEMENTARY PDF / RESOURCES PMID:18562555

  122. Flavell SW, Kim TK, Gray JM, Harmin DA, Hemberg M, Hong EJ, Markenscoff-Papadimitriou E, Bear DM, Greenberg ME. (2008). Genome-wide analysis of MEF2 transcriptional program reveals synaptic target genes and neuronal activity-dependent polyadenylation site selection. Neuron, 60:1022-1038.PDF PMID:19109909

  123. Quian Quiroga R, Kreiman G, Koch C, Fried I. (2008). Sparse but not "Grandmother Cell" coding in the medial temporal lobe. Trends in Cognitive Science, 12:87-91. PDF PMID:18262826

  124. Leamey C, Glendining K, Kreiman G, Kang N, Kuan H, Fassler R, Sawatari A, Tonegawa S, Sur M. (2008). Differential Gene Expression between Sensory Neocortical Areas: Potential Roles for Ten_m3 and Bcl6 in Patterning Visual and Somatosensory Pathways. Cerebral Cortex, 18:53-66. PDF PMID:17478416

  125. 2007

  126. Kreiman G. (2007). Single neuron approaches to human vision and memories. Current Opinion in Neurobiology, 17:471-475. PDF PMID: 17703936

  127. Serre T, Kreiman G, Kouh M, Cadieu C, Knoblich U, Poggio T. (2007). A quantitative theory of immediate visual recognition. Progress In Brain Research, 165C:33-56. PDF / RESOURCES PMID:17925239

  128. Kreiman G. (2007). Brain science: from the very large to the very small. Current Biology, 17:R768-R770. PDF PMID:17803929

  129. 2006

  130. Tropea D, Kreiman G, Lyckman A, Mukherjee S, Yu H, Horng S, Sur M. (2006). Gene expression changes and molecular pathways mediating activity-dependent plasticity in visual cortex. Nature Neuroscience, 9:660-668 PDF / SUPPLEMENTARY PDF / RESOURCES PMID: 16633343

  131. Kreiman G*, Hung C*, Quiroga R, Kraskov A, Poggio T, DiCarlo J. (2006). Object selectivity of local field potentials and spikes in the macaque inferior temporal cortex Neuron, 49:433-445. (*=equal contribution) PDF / SUPPLEMENTARY PDF / RESOURCES PMID:16446146

  132. 2005

  133. Hung C*, Kreiman G*, Poggio T, DiCarlo J. (2005). Fast read-out of object identity from macaque inferior temporal cortex. Science, 310:863-866. (*=equal contribution) PDF / SUPPLEMENTARY PDF / RESOURCES PMID:16272124

  134. Quian Quiroga R, Reddy L, Kreiman G, Koch C, Fried I. (2005). Invariant visual representation by single neurons in the human brain. Nature, 435:1102-1107. PDF / SUPPLEMENTARY PDF PMID:15973409

  135. Kreiman G, Fried I, Koch C. (2005). Responses of single neurons in the human brain during flash suppression. In Binocular Rivalry (eds Blake R, Alais D). Ch 12, MIT Press. PDF

  136. 2004

  137. Crick F, Koch C, Kreiman G, Fried I. (2004). Consciousness and Neurosurgery. Neurosurgery, 55:272-282. PDF PMID: 15271233

  138. Yeo G, Holste D, Kreiman G, Burge C. (2004). Variation in alternative splicing across human tissues. Genome Biology, 5:R74. PDF / RESOURCES PMID: 15461793

  139. Kreiman G. (2004). Neural coding: computational and biophysical perspectives. Physics of Life Reviews, 2:71-102. PDF

  140. Kreiman G. (2004). Identification of sparsely distributed clusters of cis-regulatory elements in sets of co-expressed genes. Nucleic Acids Research, 32:2889-2900. PDF/ RESOURCES PMID: 15155858

  141. Su AI, Wiltshire T, Batalov S, Lapp H, Ching KA, Block D, Zhang J, Soden R, Hayakawa M, Kreiman G, Cooke MP, Walker JR, Hogenesch JB. (2004). A gene atlas of the mouse and human protein-encoding transcriptomes. Proceedings of the National Academy of Sciences USA, 101:6062-6067. PDF SUPPLEMENTARY PDF / RESOURCES PMID: 15075390

  142. 2002

  143. Kreiman G, Fried I, Koch C. (2002). Single neuron correlates of subjective vision in the human medial temporal lobe. Proceedings of the National Academy of Sciences USA, 99:8378-8383. PDF PMID: 12034865

  144. Rees G, Kreiman G, Koch C. (2002). Neural correlates of consciousness in humans. Nature Reviews Neuroscience, 3:261-270. PDF PMID: 11967556

  145. Krahe R, Kreiman G, Gabbiani F, Koch C, Metzner W. (2002). Stimulus encoding and feature extraction by multiple pyramidal cells in the hindbrain of weakly electric fish. Journal of Neuroscience, 22:2374-2382. PDF PMID: 11896176

  146. 2001

  147. Zirlinger M, Kreiman G, Anderson D. (2001). Amygdala-enriched genes identified by microarray technology are restricted to specific amygdaloid sub-nuclei. Proceedings of the National Academy of Sciences USA, 98:5270-5275. PDF / RESOURCES PMID: 11320257

  148. Kreiman G. (2001). Moveo ergo sum. BioEssays, 23:662. PDF

  149. 2000

  150. Kreiman G, Koch C, Fried I. (2000). Imagery neurons in the human brain. Nature, 408:357-361. PDF PMID: 11099042

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