2022
Bardon A, Xiao W, Ponce CR, Livingstone MS, Kreiman G (2022). Face neurons encode nonsemantic features. Proceedings of the National Academy of Sciences of the United States of America 119, e2118705119, doi:10.1073/pnas.2118705119
Supplementary Material | Resources
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. Resources
Hoogsteen K, Szpiro S, Kreiman G, Peli E (2022). Beyond the Cane: Describing Urban Scenes to Blind People for Mobility Tasks. ACM Transactions on Accessible Computing.
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). Task-specific neural processes underlying conflict resolution during cognitive control. bioRxiv 2022.01.16.476535. Resources
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
Dellaferrera G, Kreiman G (2022). Error-driven input modulation: solving the credit assignment problem without a backward pass. arXiv 2201.11665
Sikarwar A, Kreiman G (2022). On the efficacy of co-attention transformer layers in visual question answering. arXiv 2201.03965
2021
Gupta SK, Zhang M, Wu CC, Wolfe JM, Kreiman G (2021). Visual search asymmetry: deep nets and humans share similar inherent biases. NeurIPS | Supplementary Material | Resources
Bricken T, Pehlavan C (2021). Attention approximates sparse distributed memory. NeurIPS
Casper S, Nadeau M, Kreiman G (2021). One thing to fool them all: generating interpretable, universal, and physically-realizable adversarial features. arXiv, 2110.03605
Shaham N, Chandra J, Kreiman G, Sompolinsky H (2021). Stochastic consolidation of lifelong memory. bioRxiv 2021.08.24.457446
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
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. Supplementary Material | Resources
Zhang M, Kreiman G (2021). Beauty is in the eye of the machine. Nature Human Behaviour 5:1-2
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
Zhang M, Xiao W, Rose O, Bendtz K, Livingstone M, Ponce CR, Kreiman G (2021). Look Twice: A Computational Model of Return Fixations across Tasks and Species. arXiv 2101.01611
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 | Resources
Zhang M, Badkundri R, Talbot M, Kreiman G (2021). Hypothesis-driven Stream Learning with Augmented Memory.
arXiv 2104.02206
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. arXiv 1912.04783
2020
Yuan L, Xiao W, Kreiman G, Tay FEH, Feng, JL, Livingstone, M (2020). Adversarial images for the primate brain. arXiv. 2011.05623
Olson J, Kreiman G. (2020). Simple learning rules generate complex canonical circuits. arXiv:2009.06118 | Resources
Kreiman G, Serre T (2020). Beyond the feedforward sweep: feedback computations in the visual cortex. Ann NY Acad Sci 1464:222-241
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 Supplementary Material | Resources
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
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
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 | Resources
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 Learning, 2:210-219 | Resources
2019
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. Supplementary Material | Resources
O’Connel TP, Chun MM, Kreiman G. (2019) Zero-shot neural decoding of visual categories without prior exemplars. bioRxiv 10.1101/700344
Casper S, Boix X, D’Amario V, Guo L, Schrimpf M, Vinken K, Kreiman G. (2019) Removable and/or repeatable units emerge in overparametrized neural networks. arXiv 1912.047832
Zhang M, Tseng C, Montejo K, Kwon J, Kreiman G. (2019) Lift-the-flap: what, where and when for context reasoning. arXiv 1902.00163 | Resources
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 | Resources
Xiao W, Kreiman G. (2019) Finding preferred stimuli for visual neurons using generative networks and gradient-free optimization . arXiv 1905.00378 | Resources
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 29:96-97.
Xiao W, Chen H, Liao Q, Poggio T. (2019) Biologically-plausible learning algorithms can scale to large datasets. International Conference on Learning Representations (ICLR).
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. Supplementary Material | Resources
2018
Misra P, Marconi A, Petterson M, Kreiman G. (2018) Minimal memory for details in real life events. Scientific Reports 8, 16701. Supplementary Material | Resources
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, 115:8835-884. Supplementary Material | Resources | GitHub
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. Supplementary Material | Resources | GitHub
Zhang M, Feng J, Lim JH, Zhao Q, Kreiman G. (2018) What am I searching for? arXiv version: arXiv 1807.11926.
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. 2018:299-302.
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
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. Supplementary Material | Resources
2017
Cheney N, Schrimpf M, Kreiman G. (2017) On the Robustness of Convolutional Neural Networks to Internal Architecture and Weight Perturbations. arXiv version: arXiv:1703.08245v1
Lotter W, Kreiman, G, Cox, D. (2017) Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. International Conference on Learning Representations (ICLR). GitHub
Tang H, Kreiman G. (2017). Recognition of occluded objects. In Computational and Cognitive Neuroscience of Vision (ed Zhao, Q). Singapore: Springer-Verlag.
2016
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. Supplementary Material | Resources
Lotter, W, Kreiman, G, Cox, D. (2016.) Unsupervised representation learning using predictive generative works. International Conference on Learning Representations (ICLR). GitHub
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. Supplementary Material
Kreiman G. (2016). A null model for cortical representations with grandmothers galore. Language, Cognition and Neuroscience, 32, 274-285.
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. Supplementary Material
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. Supplementary Material | Resources
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. Supplementary Material | Resources
2015
Singer JM, Madsen JR, Anderson WS, Kreiman G. (2015). Sensitivity to Timing and Order in Human Visual Cortex. Journal of Neurophysiology, 113:1656-1669.
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. Supplementary Material | Resources
2014
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. Supplementary Material 1 | Supplementary Material 2
Fried I, Rutishauser U, Cerf M, Kreiman G. (2014). Single Neuron Studies of the Human Brain, Probing Cognition. MIT Press.
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.
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.
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.
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.
Kreiman G. (2014). Neural correlates of consciousness: perception and volition. In Cognitive Neuroscience, Vol. V (ed Gazzaniga M). Ch 68, MIT Press.
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.
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. Supplementary Material
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.
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.
Nassi J, Gomez-Laberge C, Kreiman G, Born R. (2014). Corticocortical feedback increases the spatial extent of normalization. Frontiers in Systems Neuroscience, 8:105. Supplementary Material
Singer J, Kreiman G. (2014). Short Temporal Asynchrony Disrupts Visual Object Recognition. Journal of Vision, 12,14. Resources
Frost B, Hemberg M, Lewis J, Feany M. (2014). Tau promotes neurodegeneration through global chromatin relaxation. Nature Neuroscience, 17, 357-366.
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.
2013
Kreiman G. (2013). Mind the quantum? Trends in Cognitive Science, 17(3), 109.
Kreiman G. (2013). Computational Models of Visual Object Recognition. In Principles of Neural Coding (eds Panzeri S, Quiroga R). Ch 29, CRC Press.
2012
Murugan R, Kreiman G. (2012). Theory on the coupled stochastic dynamics of transcription and splice-site recognition. PLoS Computational Biology, 8, 1-13, e1002747.
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.
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. Supplementary Material | Resources
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.
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.
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.
2011
Kriegeskorte N, Kreiman G. (2011). Visual Population Codes, Towards a Common Multivariate Framework for Cell Recording and Functional Imaging. MIT Press. Resources
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.
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.
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.
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.
Tang H, Kreiman G. (2011). Face Recognition: Vision and Emotions beyond the Bubble. Current Biology, 21:21.
Kreiman G, Maunsell J. (2011). Nine criteria for a measure of scientific output. Frontiers in Computational Neuroscience, 5:48.
Kreiman G. (2011). Literary inspiration. Nature, 475:453-454.
Murugan R, Kreiman G. (2011). On the minimization of fluctuations in the response times of autoregulatory gene networks. Biophysical Journal, 101:1297-1306.
Hemberg M, Kreiman G. (2011). Conservation of transcription factor binding events predicts gene expression across species. Nucleic Acids Research, 39:7092-7102.
Fried I, Mukamel R, Kreiman G. (2011). Internally Generated Preactivation of Single Neurons in Human Medial Frontal Cortex Predicts Volition. Neuron, 69: 548-562. Supplementary Material
Anderson WS, Kreiman, G. (2011). Neuroscience: What We Cannot Model, We Do Not Understand. Current Biology, 21:R124-R125.
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.
2010
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.
Blumberg J, Kreiman G. (2010). How cortical neurons help us see: visual recognition in the human brain. Journal of Clinical Investigation, 120:3054-3063.
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. Supplementary Material | Resources
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) Supplementary Material | Resources
Singer JM, Sheinberg DL. (2010). Temporal cortex neurons encode articulated actions as slow sequences of integrated poses. Journal of Neuroscience, 30:3133-3145.
Quian Quiroga R, Kreiman G. (2010). Measuring sparseness in the brain. Psychological Review, 11:291-297.
2009
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.
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. Supplementary Material | Resources
Rasch M, Logothetis NK, Kreiman G. (2009). From neurons to circuits: linear estimation of local field potentials. Journal of Neuroscience, 29:13785-13796. Resources
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.
Singer J, Kreiman G. (2009). Toward unmasking the dynamics of visual perception. Neuron, 64:446-447.
2008
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.
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 Supplementary Material | Resources
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.
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.
2007
Kreiman G. (2007). Single neuron approaches to human vision and memories. Current Opinion in Neurobiology, 17:471-475.
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. Resources
Kreiman G. (2007). Brain science: from the very large to the very small. Current Biology, 17:R768-R770.
2006
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 Supplementary Material | Resources
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) Supplementary Material | Resources
2005
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) Supplementary Material | Resources
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. Supplementary Material
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.
2004
Crick F, Koch C, Kreiman G, Fried I. (2004). Consciousness and Neurosurgery. Neurosurgery, 55:272-282.
Yeo G, Holste D, Kreiman G, Burge C. (2004). Variation in alternative splicing across human tissues. Genome Biology, 5:R74. Resources
Kreiman G. (2004). Neural coding: computational and biophysical perspectives. Physics of Life Reviews, 2:71-102.
Kreiman G. (2004). Identification of sparsely distributed clusters of cis-regulatory elements in sets of co-expressed genes. Nucleic Acids Research, 32:2889-2900. Resources
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. Supplementary Material | Resources
2002
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.
Rees G, Kreiman G, Koch C. (2002). Neural correlates of consciousness in humans. Nature Reviews Neuroscience, 3:261-270.
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.
2001
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.
Kreiman G. (2001). Moveo ergo sum. BioEssays, 23:662.
2000
Kreiman G, Koch C, Fried I. (2000). Imagery neurons in the human brain. Nature, 408:357-361.
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.
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.
1999
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.
1996
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.