Kreiman Lab Publications

All Reviews Conferences Comments Books Book Chapters Theses

    2024

  1. Xiao W, Sharma S, Kreiman G, Livingstone MS (2024) Feature-selective responses in macaque visual cortex follow eye movements during natural vision. Nature Neuroscience, 6:1157-1166. PDF | Supplement | Resources PMID: 38684892

  2. Li C, Kreiman G, Ramanathan S (2024). Discovering neural policies to drive behavior by integrating deep reinforcement learning agents with biological neural networks. Nature Machine Intelligence, PDF | Suppplement | Resources

  3. Djambazovska S, Zafer A, Ramezanpour H, Kreiman G, Kar K (2024). The impact of scene context on visual object recognition: comparing humans, monkeys, and computational models. bioRxiv, 2024.05.27.596127. PDF

  4. Madan S, Xiao W, Cao M, Pfister H, Livingstone M, Kreiman G. (2024). Benchmarking out-of-distribution generalization capabilities of DNN-based encoding models for the ventral visual cortex. NeurIPS PDF | Resources

  5. Wang C, Yaari A, Singh A, Subramaniam V, Rosenfarb D, Misra P, Madsen J, Stone S, Kreiman G, Katz B, Cases I, Barbu A (2024). Brain treebank: Large-scale intracranial recordings from naturalistic language stimuli. NeurIPS PDF | Resources

  6. Jain V, Alves Feitosa F, Kreiman G (2024). Is AI fun? HumorDB: a curated dataset and benchmark to investigate graphical humor. arXiv, 2406.13564. PDF

  7. Zheng J, Yebra M, Schjetnan AGP, Mosher C, Kalia A, Chung JM, Reed CM, Valiante TA, Mamelak A, Kreiman G, Rutishauser U (2024). Theta Phase Precession Supports Memory Formation and Retrieval of Naturalistic Experience in Humans. Nature Human Behavior, In Press. PDF | Resources

  8. Li C, Brenner JW, Boesky A, Ramanathan S, Kreiman G (2024). Neuron-level prediction and noise can implement flexible reward-seeking behavior. bioRxiv, 2024.05.22.595306. PDF

  9. Subramaniam V, Conwell C, Wang C, Kreiman G, Katz B, Cases I, Barbu A (2024). Revealing Vision-Language Integration in the Brain with Multimodal Networks.  International Conference on Machine Learning (ICML). PDF

  10. Bono S, Madan S, Grover I, Yasueda M, Breazeal C, Pfister H, Kreiman G (2024). Look Around! Unexpecetd gains from training on environments in the vicinity of the target. arXiv, 2401.15856. PDF

  11. Misra P, Shih Y, Yu H, Weisholtz D, Madsen J, Sceillig, S, Kreiman G (2024). Invariant neural representation of parts of speech in the human brain. bioRxiv, 2024.01.15.575788. PDF

  12. Srinivasan RF, Mignacco F, Sorboro M, Refinetti M, Cooper A, Kreiman G, Dellaferrera G. (2024). Forward learning with top-down feedback: empirical and analytical characterization.  International Conference on Learning Representations (ICLR), PDF

  13. Madan S, Li Y, Zhang M, Pfister H, Kreiman G. (2024). Improving generalization by mimicking the human visual diet. bioRxiv, 2206.07802. PDF | Resources

    14. 2023

  14. Singh P, Li Y, Sikarwar A, Lei W, Gao D, Talbot MB, Sun Y, Shou MZ, Kreiman G, Zhang M. (2023). Learning to Learn: How to Continuously Teach Humans and Machines. International Conference on Computer Vision (ICCV), PDF | Resources PMID: 38784111

  15. Talbot, MB, Zawar R, Badkundri R, Zhang M, Kreiman G. (2023). Tuned compositional feature replays for efficient stream learning. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), PDF | Supplement | Resources PMID: 38145511

  16. Aghajan Z, Kreiman G, Fried I (2023). Minute-scale periodicity of neuronal firing in the human entorhinal cortex. Cell Reports, 42, 113271. PDF | Resources PMID: 37906591

  17. Casper S, Killian T, Kreiman G, Hadfield-Mennell D (2023). White-box adversarial policies in deep reinforcement learning. arXiv, 2209.02167. PDF | Resources

  18. Xiao Y, Sanchez Lopez P, Wu R, Srinivasan R, Wei PH, Shan YZ, Weisholtz D, Cosgrove GR, Madsen JR, Stone S, Zhao GG, Kreiman G (2023). Neurophysiological and computational mechanisms of non-associative and associative memories during complex human behavior. bioRxiv, 2023.03.27.534384 PDF | Supplement| Resources

  19. Bricken T, Schaeffer R, Olshausen B, Kreiman G. (2023) Emergence of sparse representations from noise. International Conference on Machine Learning (ICML). PDF

  20. Bricken T, Davies A, Singh D, Krotov D, Kreiman G. (2023) Sparse distributed memory is a continual learner. International Conference on Learning Representations (ICLR), PDF | Supplementary Material | Resources

  21. Wang C, Subramaniam V, Yaari A, Kreiman G, Katz B, Cases I, Barbu A. (2023). BrainBERT: Self-supervised representation learning for intracranial electrodes. International Conference on Learning Representations (ICLR), PDF | Supplementary Material | Resources

  22. Xiao Y, Chou C, Cosgrove GR, Crone NE, Stone S, Madsen JR, Reucroft I, Weisholtz D, Shih YC, Yu HY, Anderson WS, Kreiman G (2023) Cross-task specificity and within-task invariance of cognitive control processes. Cell Reports, 42:111919. PDF | Supplementary Material | Resources PMID: 36640346

  23. Triggiani, AI, Kreiman G, Lewis C, Maoz U, Mele A, Mudrik L, Roskies A, Schurger A, Hallett M (2023). What is the intention to move and when does it occur? Neuroscience and Behavioral Reviews, 2023.105199 PDF PMID: 37119992

  24. Ferrante O, Gorska U, Henin S, Hirschhorn R, Khalaf A, Lepauvre A, Liu L, Richter D, Vidal Y, Bonacchi N, Brown T, Sripad P, Armendariz M, Bendtz K, Ghafari T, Hetenyi D, Jeschke J, Kozma C, Mazumder DR, Montenegro S, Seedat A, Sharafeldin A, Yang, S, Baillet S, Chalmers DJ, Cichy RM, Fallon F, Panagiotaropoulos TI, Blumenfeld H, de Lange FP, Devore S, Jensen O, Kreiman G, Luo H, Boly M, Dehaene S, Koch C, Tononi G, Pitts M, Mudrik L, Melloni L (2023). An adversarial collaboration to critically evaluate theories of consciousness. bioRxiv, 2023.06.23.546249 PDF

  25. Zhang Y, Aghajan ZM, Ison M, Lu Q, Tang H, Kalender G, Monsoor T, Zheng J, Kreiman G, Roychowdhury V, Fried I (2023). Decoding of human identity by computer vision and neuronal vision. Scientific Reports. 13:651 PDF | Supplementary Material PMID: 36635322

  26. Kreiman G (2023). Neural coding: Stimulating cortex to alter visual perception. 33, R117-R118. Current Biology, 33:R117-R118 PDF PMID: 36750025

  27. Xiao W, Zhang M, Kreiman G (2023). Artificial intelligence in neuroscience. Chater 10 in Neuroscience for Neurousrgeons, edited by Akter F, Emptage N, Engert F, and Berger M. Cambridge University Press, PDF

  28. 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 (2023). An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory. PLoS One, 18(2):e0268577 PDF PMID: 36763595

    29. 2022

  29. 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

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

  31. Ding Z, Ren X, David E, Vo Melissa, Kreiman G, Zhang M (2022). Efficient zero-shot visual search via target and context-aware transformer. arXiv, 2211.13470 PDF

  32. Zhang M, Armendariz 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 PMID: 36413523

  33. Casper S, Nadeau M, Hadfield-Menell D, Kreiman G (2022). Robust feature-level adversaries are interpretability tools. NeurIPS, 35, 33093-33106. PDF | Supplementary Material | Resources

  34. 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 PMID: 36187915

  35. 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 PMID: 35377737

  36. Zheng J, Schjetnan AGP, Yebra M, Mosher C, Kalia S, Valiante TA, Mamelak A, Kreiman G, Rutishauser U (2022). Neurons detect cognitive boundaries to structure episodic memories in humans. Nature Neuroscience 25:358-368. PDF | Resources PMID: 35260859

  37. 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, DOI: 10.1145/3522757. PDF PMID: 36148267

  38. 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, 39: 75-77. PDF PMID: 35193459

  39. Dellaferrera G, Kreiman G (2022). Error-driven input modulation: solving the credit assignment problem without a backward pass. Proceeedings of Machine Learning Research (International Conference on Machine Learning (ICML)), 162:4937-4955 PDF

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

  41. Shaham N, Chandra J, Kreiman G, Sompolinsky H (2022). Stochastic consolidation of lifelong memory. Scientific Reports, 12: 13107 PDF | Supplement PMID: 35907920

    42. 2021

  42. Gupta SK, Zhang M, Wu CC, Wolfe JM, Kreiman G (2021). Visual search asymmetry: deep nets and humans share similar inherent biases. Advances in Neural Information Processing Systems (NeurIPS) 34:6946-6959. PDF | Supplementary Material | Resources PMID: 36062138

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

  44. 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, 17 (6):549-558 PDF PMID: 34941992

  45. 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 PMID: 34433053

  46. Li C, Dezza, A (2021). What matters in branch specialization? Using a toy task to make predictions. Shared Visual Representations in Human and Machine Intelligence (SVRHM) Workshop at NeurIPS PDF

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

  48. 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), 255-264. PDF | Resources PMID: 36051852

  49. 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

    50. 2020

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

  51. 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 PMID: 32112444

  52. 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 PMID: 33055170

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

  54. Ben-Yosef G, Kreiman G, Ullman S. (2020). What can human minimal videos tells us about dynamic recognition models?. Workshop at International Conference on Learning Representations (ICLR) | PDF

  55. 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

  56. Lotter W, Kreiman G, Cox D. (2020) A neural network trained for prediction mimics diverse features of biological neuroms and perception. Nature Machine Intelligence, 2:210-219. PDF | Resources PMID: 34291193

  57. 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 PMID: 34566393

  58. 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 PMID: 34290902

  59. 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 PMID: 32325309

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

    61. 2019

  61. 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. PMID: 31051108

  62. 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

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

  64. 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

  65. Xiao W, Chen H, Liao Q, Poggio T. (2019). Biologically-plausible learning algorithms can scale to large datasets. International Conference on Learning Representations (ICLR). PDF

  66. 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. PMID: 30590542

    67. 2018

  67. 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

  68. 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

  69. 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

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

  71. 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

  72. 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), PDF | Resources

  73. 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

    74. 2017

  74. 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

  75. Cheney N, Schrimpf M, Kreiman G. (2017)  On the robustness of convolutional neural networks to internal architecture and weight perturbations arXiv, 1703.08245 PDF

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

    77. 2016

  77. 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

  78. 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

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

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

  81. 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

  82. 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

  83. 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

    84. 2015

  84. 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

  85. 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

    86. 2014

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

  87. 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

  88. 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

  89. 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

  90. 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

  91. 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

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

  93. 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

  94. 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 Material PMID: 25403355

  95. 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

  96. Kim T, Hemberg M, Gray J. (2014). Enhancer RNAs: a class of long noncoding RNAs synthesized at enhancers. Cold Spring Harbor Pesspectives in Biology. 5:a018622PDF PMID: 25561718

  97. 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 Material PMID: 24910596

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

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

  100. 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

    101. 2013

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

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

    103. 2012

  103. 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

  104. 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

  105. 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 Material | RESOURCES PMID: 2268462

  106. 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

  107. 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

  108. 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

    109. 2011

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

  110. 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

  111. 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

  112. 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

  113. 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

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

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

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

  117. 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

  118. 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

  119. 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 Material PMID: 21315264

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

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

    122. 2010

  122. 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 Material | RESOURCES PMID:20393465

  123. 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 Material | RESOURCES PMID:20417105

  124. 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

  125. 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

  126. 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

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

    128. 2009

  128. 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.

  129. 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 Material | RESOURCES PMID:19409272

  130. 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

  131. 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

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

    133. 2008

  133. 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 Material | Resources PMID:18562555

  134. 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

  135. 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

  136. 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

    137. 2007

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

  138. 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

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

    140. 2006

  140. 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 Material | RESOURCES PMID: 16633343

  141. 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 Material | RESOURCES PMID:16446146

    142. 2005

  142. 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 Material | RESOURCES PMID:16272124

  143. 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 MaterialF PMID:15973409

  144. 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

    145. 2004

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

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

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

  148. 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

  149. 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 Material | RESOURCES PMID: 15075390

    150. 2002

  150. 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

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

  152. 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

    153. 2001

  153. 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

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

    155. 2000

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

  156. Kreiman G, Koch C, Fried I. (2000). Category-specific visual responses of single neurons in the human medial temporal lobe. Nature Neuroscience, 3:946-953. PDF PMID: 10966627

  157. Kreiman G, Krahe R, Metzner W, Koch C, Gabbiani F. (2000). Robustness and Variability of Neuronal Coding by Amplitude Sensitive Afferents in the Weakly Electric Fish Eigenmannia. Journal of Neurophysiology, 84:189-204. PDF PMID: 10899196

    158. 1999

  158. Ouyang Y, Rosenstein A, Kreiman G, Schuman EM, Kennedy, MB. (1999). Tetanic stimulation leads to increased accumulation of Ca2+ calmodulin-dependent protein kinase II via dendritic protein synthesis in hippocampal neurons. Journal of Neuroscience, 19:7823-7833. PDF PMID: 1047968

  159. Inon de Iannino N, Briones G, Kreiman G, Ugalde, R. (1996). Characterization of the biosynthesis of betha(1-2) cyclc glucan in R. Freddii. Cellular and Molecular Biology, 42:617-629. PDF PMID: 8832091

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