Publications - Conference Abstracts

All Reviews Conferences Comments Books Book Chapters Theses

2021

• Zheng J, Schjetnan AGP, Yebra M, Mosher C, Kalia SK, Valiante TA, Mamelak AN, Kreiman G, Rutishauser U. (2021) Neurons detect cognitive boundaries to structure episodic memories in humans. NIH BRAIN Initiative PI Meeting. Bethesda, DC.
• Hoogsteen KMP, Szpiro S, Kreiman G, Peli E. (2021). Beyond the Cane: Describing Urban Street Scenes to Blind Travelers. Eye and the Chip. Detroit, MI
• Schaeffer R, Shaham N, Kreiman G, Sompolinsky H. (2021). Neural network model of amygdalar memory engram formation and function. Cosyne.

2020

• Shaham N, Chandra J, Kreiman G, Sompolinsky H. (2020) Continual learning, replay and consolidation in a forgetful memory network model. Cosyne.
• Kreiman G. (2020) What do neurons want? Using computational models to investigate neuronal tuning preferences in an unbiased manner. Cosyne workshop.
• Hashemil SA, Ebadil SA, Jahromy FZ, Treue S, Kreiman G, Esghaei M. (2020). Object information is differentially shared across short- and long-distance connections in the brain. Benstein Conference on Computational Neuroscience. Berlin, Germany.
• Zhang M, Kreiman G. (2020). Putting visual object recognition in context. Cognitive Neuroscience Annual Meeting.
• Tao A, Wang J, Kreiman G. (2020). Functional interactions in human cortex during sleep and wake states. Cognitive Neuroscience Society Annual Meeting.
• Szpiro S, Kreiman G, Peli E. (2020). Wayfinding without sight: do blind people ask the right questions? Conference on Cognition Research of the Israeli Society for Cognitive Psychology. Akko, Israel.
• Zhang Y, Aghajan2, ZM, Ison M, Lu Q, Tang H, Kalender G, Monsoor T, Zheng J, Kreiman G, Roychowdhury W, Fried I. (2020) Decoding of human identity by computer vision and neuronal vision. Society for Neuroscience Annual Meeting.

2019

• Xiao W, Schade P, Ponce C, Hartmann T, Kreiman G, Livingstone M. (2019). Automatically uncovering preferred stimuli of visual neurons using generative neural networks. Cosyne. Salt Lake City, UT.
• Kreiman G. (2019) What do visual neurons really like? Insights from joint computational modeling and neurophysiological experiments. Cosyne workshop. Salt Lake City, UT.
• Xiao Y, Yu HY, Chou CC, Shih YC, Madsen JR, Weisholtz D, Reucroft I, Crone NE, Anderson WS, Kreiman G. (2019). Task invariant and task dependent neural processes of conflict resolution during cognitive control. Society for Neuroscience Annual Meeting.
• Wang J, Kreiman G. (2019). Mesoscopic-scale functional interactions in the human brain. Brain Tweeter Conference.
• Zheng J, Schetnan AGP, Taufik VA, Mamelak A, Chung JM, Rutishauser U, Kreiman G. (2019). Event boundaries shape memory formation: evidence from single unit recordings in humans. Society for Neuroscience Annual Meeting.
• Kasper V, Kreiman G. (2019). Adaptation in visual object recognition. Visual Sciences Society Annual Meeting.
• Ponce C, Kreian G. (2019). What do neurons want? Society for Neuroscience Annual Meeting Miniymposum.
• Tao A, Wang J, Kreiman G. (2019). Functional interactions in human cortex during sleep and wake states. Association for the Scientific Study of Consciousness Annual Meeting.
• O'Connell TP, Chun MM, Kreiman G. (2019). Zero-shot neural decoding from rhesus macaque inferior temporal cortex. Visual Sciences Society Annual Meeting.
• Wick FA, Kreiamn G, Wolfe J. (2019). Computational strategies used during hybrid visual search. Visual Sciences Society Annual Meeting.

2018

• Aipfle F, Blumberg J, Kim JG, Reinacher P, Brandt A, Schulze-Bonhage A, Kreiman G. (2018). Single unit responses to visual stimuli in human occipital lobe neurons. Bernstein Conference on Computational Neuroscience.
• Kreiman G, Rutishauser U. (2018). Episodic memory formation: from neural circuits to behavior. Cognitive Neuroscience Society Annual Meeting Symposium.
• O'Connel TP, Chun MM, Kreiman G. (2018) Zero-shot neural decoding of basic-level object category. Cosyne
Zero-shot neural decoding of basic-level object category
• Weisholtz DS, Kreiman G, Stern E, Silbersweig D, Butler T. (2018). High Gamma Activity and Emotion. American Epilepsy Society Annual Meeting.
• Wang J, Kreiman G. (2018). Mesoscopic functional interactions in the human brain. Society for Neuroscience Annual Meeting.
• Kreiman G. (2018). Rapid learning of meaningful image interpretation. Visual Sciences Society Annual Meeting Workshop.
• Wick FA, Kreiman G, Wolfe JM. (2018). Two targets, held in memory, can guide search; four targets cannot. Visual Sciences Society Annual Meeting.

2017

• Lotter, W, Kreiman, G, Cox, D. (2017) Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. International Conference on Learning Representations, Toulon, France. PDF
• Isik L*, Lotter W*, Crone NE, Cox D, Kanwisher N, Anderson WS, Kreiman G (2017). Task dependent modulation before, during and after visually evoked responses in human intracranial recordings. Society for Neuroscience Annual Meeting. Washington, DC.
• Marconi A, Petterson M, Kreiman G (2017). Emmanuel College Thesis Presentation. Quantifying episodic memories from real-world experience.
• Aiple F, Blumberg J, Kim JG, Reinacher P, Brandt A, Schulze-Bonhage A, Kreiman G (2017). Neuronal response types to impoverished images in the human inferior and medial occipital lobe. European Conference on Visual Perception. Berlin, Germany.
  

2016

• Ortiz, A. J., Odejayi, A, Peterson, M, Kreiman, G. (2016). Episodic memory for real life events.
• Lotter, W, Kreiman, G, Cox, D. (2016.) Unsupervised representation learning using predictive generative works. International Conference on Learning Representations, Puerto Rico. PDF
• Krause, E. L., Tang, H, Ison, M, Fried, I, Kreiman, G. (2016). Investigation of episodic memory formation in the human brain with single-unit recordings. Society for Neuroscience Annual Meeting, San Diego, CA.
• Olson, J.W., Kreiman, G. (2016). Complex circuits from simple learning rules. Society for Neuroscience Annual Meeting, San Diego, CA.
• Isik, L, Singer, J, Madsen, J, Kanwisher, N, Kreiman, G. (2016). Probing human intracranial visual responses with commerical movies. Visual Science Society Annual Meeting, St. Pete Beach, FL.

2015

• Gomez-Laberge, C. (2015). Bottom up and top down inputs drive the variability of cortical neurons. Society for Neuroscience Annual Meeting, Chicago IL.
• Hemberg, M, Dattani, J, Barahona, M, Kreiman, G. (2015). Fundamental trade-off between estimation, detection, information rate and noise in gene regulatory networks. CSHL. Systems Biology: Global Regulation of Gene Expression. Cold Spring Harbor, NY.
• Kreiman, G. (2015). Neural signals underlying visual pattern completion. Computational and Systems Neuroscience, Salt Lake City, UT.

2014

• Hemberg, M, Prabakaran, S, Chauhan, R, Winter, D, Tweedie-Cullen, R, et al. (2014). Peptides from RNAs classified as non-coding.Computational RNA Biology. Cambridge, UK.
• Ross, C, Tang, H, Kreiman, G. (2014). Machine Learning to Quantify and Predict Episodic Memory Recall. Annual Biomedical Research Conference for Minority Students, San Antonio, Texas.
• Groomes, L, Madhavan, R, Tang, H, Crone, N, Madsen, J, Golby, A, Lenz, F, Kreiman, G, Anderson, W. (2014). Cognitive Consequences of Interictal Spikes. Epilepsy Society Annual Meeting, Seattle, WA.
• Hemberg, M, Prabakaran, S, Chauhan, R, Winter, D, Tweedie-Cullen, R, et al. (2014). Peptides from RNAs classified as non-coding. Regulation of Gene Expression, Cold Spring Harbor, NY.
• Kreiman, G. (2014). How neural circuits orchestrate the magic of human cognition. National Institute of Health,High-Risk High-Reward Symposium, Washington, D.C.
• Frias R, Kreiman, G. (2014). Formation of episodic memories for movie content. New England Science Symposium, Boston, MA.
• Tang, H, Madsen, J, Anderson, W, Kreiman, G. (2014). Dynamics of Human Anterior Cingulate Cortex Responses during Cognitive Control. Society for Neuroscience, Washington, D.C.
• Tang, H. (2014). Dynamics of human anterior cingulate cortex responses during cognitive control. Neuroscience 2014 Meeting, Washington, D.C.
• Miconi, T, Singer J, Kreiman, G. (2014). Normalized Hebbian learning develops both simple and complex receptive fields from naturalistic video. Computational and Systems Neuroscience, Salt Lake City, UT.

2013

• Tang, H, Kreiman, G. (2013). Computational mechanisms of object completion. Collaborative Research in Computational Neuroscience, Boston, MA.
• Gomez-Laberge, C, Smolyanskaya, A, Kreiman, G, Born, R. (2013). Silencing V2/V3 reduces spiking variability in MT: implications for excitatory/inhibitory balance. Collaborative Research in Computational Neuroscience, Boston, MA.
• Kreiman, G. (2013). On the representation of visual and cognitive information in the human brain.National Institute of Health, High-Risk High-Reward Symposium, Washington, D.C.
• Singer, J, Madsen, J, Anderson, W, Kreiman, G. (2013). Dynamic integration of information in human visual cortex. Collaborative Research in Computational Neuroscience, Boston, MA.
• Nassi, J.J., Gomez-Laberge, C, Kreiman, G, Born, R. (2013). Increasing the visuotopic extent of normalization through cortico-cortical feedback. Society for Neuroscience Annual Meeting, San Diego, CA.
• Gomez, C, Smolyanskaya, A, Kreiman, G, Born, R. (2013). Silencing V2/V3 reduces spiking variability in MT: implications for excitatory/inhibitory balance. Computational and Systems Neuroscience, Salt Lake City, UT.
• Madhavan, R, Tang, H, Millman, D, Crone, N, Madsen, J, Anderson, S.W., Kreiman, G.(2013). Gamma band activity in the human parahippocampal gyrus predicts performance in a sequence task. Computational and Systems Neuroscience, Salt Lake City, UT.
• Bansal, A, Golby, A, Madsen, J, Kreiman, G. (2013). Neural correlates of target detection in the human brain. Computational and Systems Neuroscience, Salt Lake City, UT.

2012

• Hemberg, M, Dattani, J, Barahoma, M. (2012). Analytical solution of separable Master Equations and applications to gene regulatory networks. QBio Conference, Santa Fe, NM. PDF
• Arslan, A. B., Cauchoix, M, Singer, J, Kreiman, G, Fize, D, Serre, T. (2012). A functional homology and monkey visual system through hyper-alignment of neural representations. Vision Sciences Soiciety, Naples, FL.
• Madhavan, R, Madsen, J, Eskandar, E, Cash, S, Kreiman, G, Anderson, W. (2012). Slow oscillations in the mesial temporal lobe predict successful short-term recall in a working memory task. American Epilepsy Society, San Deigo, CA.
• Wyatte, D, Tang, H, Buia, C, Madsen, J, O'Reilly, R, Kreiman, G. (2012). Object completion along the ventral visual stream: neural signatures and computational mechanisms. Computation and Systems Neuroscience, Salt Lake City, UT.

2011

• Arslan, A, Singer, J, Cauchoix, M, Maden, J, Kreiman, G, Serre, T. (2011). The neural basis of rapid visual recognition: neural decoding and Granger causality analysis of connectivity. Vision Sciences Soiciety, Naples, FL.
• Bansal, A. K., Singer J, Madsen, J, Kreiman, G. (2011). Temporal stability of visually selective repsonses in intracranial field potentials from the human occipital and temporal lobes. Society for Neuroscience, Washington, D.C. PDF
• Madhavan, R, Millman, D, Madsen, J, Golby, A.J., Kreiman, G, Anderson, W.S. (2011). Temporal theta oscillation enhancement predicts successful memory encoding. American Epilepsy Society and Society for Neuroscience, Baltimore and Washington, D.C. PDF
• Madhavan, R, Millman, D, Madsen, J, Golby, A, Kreiman, G, Anderson, W. (2011). Temporal theta oscillation enhancement predicts successful memory encoding. American Epilepsy Society, Washington, D.C.
• Burbank, K, Kreiman, G. (2011). Temporally reversed STDP is required for learning stable, diverse, weak feedback connections. Computation and Systems Neuroscience, Salt Lake City, UT.
• Kim, H. K., Hemberg, M, Gray, J. M, Costa, A.M., Harmin, D. A., Markenscoff-Papdimitriou, E, Bear, D. M., Kreiman, G, Greenberg, M. E. (2011). Widespread transcription at neuronal activity-regulated enhancersSystems Biology: Global Regulation of Gene Expression. Cold Spring Harbor, NY.
• Kreiman, G, Buia, C, Singer, J, Madsen, J. (2011). Top-down signals are needed for object completion in the human visual cortex. Vision Sciences Soiciety, Naples, FL.

2010

• Hemberg, M, Tobis, E, Ip, W, Kreiman, G. (2010). Histone modifications accurately predict RNAPII occupanc. Program in Quantitative Genomics, Boston, MA.
  
• Hemberg, M, Gray, M, J., Cloonan, N, Kim, T, MGrimmond, S, Greenberg, M.E., Kreiman, G (2010). Limited extragenic transcription suggests that most conserved non-coding sequences are regulatory factor binding sites. Beyond the Genome, Boston, MA.
  
• Kim, T, Hemberg, Gray, J. M., Costa ,A. M., Harmin, D. A., Markenscoff-Papadimitriou, E, Bear, D. M, Kreiman, G, Greenberg M. E. (2010). Histone Widespread transcription at neuronal activity-regulated enhancers. Systems Biology: Global Regulation of Gene Expression, Cold Spring Harbor, NY.
  
• Arslan, A.B., Cauchoix, M, Fize, D, Kreiman, G, Madsen, J.R., Serre, T, Singer, J. (2010). Neural decoding of natural object categories from intracranial field potentials: A comparison between human and monkey. Society for Neuroscience, San Diego, CA.
• Cauchoix, M, Serre, T, Kreiman, G, Fize, D. (2010). Fast decoding of natural object categories from intracranial field potentials in monkey’s visual cortex. Vision Sciences Soiciety, Naples, FL.
• Kreiman, G, Agam, Y, Liu, H, Buia, C, Papanastassiou, A, Golby, A, et al. (2010). Robustness to image clutter in human visual cortex. Vision Sciences Soiciety, Naples, FL.

2009

• Hemberg, M, Kreiman, G. (2009). Correlated conservation of tissue-specific gene expression and transcription factor binding sites in human and mouse. Cells, Circuits and Computation, Cambridge, MA.
  
• Hemberg, M, Kreiman, G. (2009). Conserved transcription factor binding sites predict tissue-specific gene expression and vice versa. Genome Informatics, Cold Spring Harbor, NY.
  
• Meyers, E, Freedman, D, Kreiman, G, Miller, E.K, Poggio T. (2009) Decoding dynamic patterns of neural activity using a 'biologically plausible' fixed set of weights. Computation and Systems Neuroscience, Salt Lake City, UT.
• Burbank, K, Kreiman, G.(2009). When can rates be reliably transmitted in feedforward networks? Computation and Systems Neuroscience, Salt Lake City, UT.
• Kreiman, G. (2009). Fast and robust decoding of visual information from intracranial field potentials in the human visual cortex. European Conference on Visual Perceptio, Regensburg, Germany.

2008

• Liu, H, Agam, Y, Madsen, J.R., Kreiman, G. (2008). Robust decoding of visual information from the human brain. Society for Neuroscience Annual Meeting, Washington, D.C.
  
• Blumberg, J, Singer, J, Liu, H, Agam, Y, Madsen, J.R., Kreiman, G. (2008). Stationarity of the neural code for vision. Society for Neuroscience Annual Meeting, Washington, D.C.
  
• Meyers, E, Embark, H, Freiwald, W, Serre, T, Kreiman, G, Poggio, T. (2008). Examining the neural representation of cluttered scenes in macaque ventral visual cortex. Society for Neuroscience Annual Meeting, Washington, D.C.
• Tan, C, Serre, T, Kreiman, G, Poggio, T. (2008). Implicit Location, Scale and Configural Information in Feedforward Hierarchical Models. Vision Sciences Soiciety, Naples, FL.

2007

• Rajamanickamm, M, Kreiman, G. (2007). Generalized dynamic theory of alternative splicing regulation. Research in Computational Molecular Biology, Satellite Meeting, Boston, MA.
  
• Kreiman, G, Serre, T, Poggio, T. (2007). The limits of feed-forward processing in visual object recognition. Vision Sciences Soiciety, Sarasota, FL.
• Kreiman, G, Serre, T, Poggio, T. (2007). The limits of feed-forward processing in visual object recognition. Computation and Systems Neuroscience, Salt Lake City, UT.
  
• Meyers, E, Freedman, D, Miller, E, Kreiman, G, Poggio, T. (2007). Reading out visual information from populations of neurons in inferior temporal cortex and prefrontal cortex. Computation and Systems Neuroscience, Salt Lake City, UT. Poster
  
• Kreiman, G, Hung, C, Quiroga, R, Kraskov, A, Poggio, T, DiCarlo, J. (2007). Object recognition by decoding spikes and local field potentials. Vision Sciences Soiciety, Sarasota, FL.
  
• Hung, C, Kreiman, G, Poggi,o T, DiCarlo, J. (2007). Decoding visual information from population of ITC neurons. Vision Sciences Soiciety, Sarasota, FL.
  

2006

• Tropea, D, Kreiman, G, Lyckman, A, Mukherjee, S, Yu, H, Horng, S, Sur, M. (2006. Role of insuling-like growth factor 1 in activity-dependent plasticity in visual cortex. Society for Neuroscience Annual Meeting, Atlanta, GA.
  

2005

• Hung, C, Kreiman, G, Poggio, T, DiCarlo, J. (2005). Using 'read-out' of object identity to understand object coding in the macaque inferior temporal cortex. Computation and Systems Neuroscience, Salt Lake City, UT.
• Kreiman, G, Nallasamy, N. (2005). Transcription factor binding: does order matter? Research in Computational Molecular Biology, Boston, MA.
• Horng, S, Kreiman, G, Ellsworth, C, Page, D, Blank, M, Milen, K, Sur, M. (2005). Differential gene expression in the developing lateral geniculate nucleus and medial geniculate nucleus. Society for Neuroscience Annual Meeting, Washington, D.C.

2004

• Kreiman, G, Hung, C, Shkolnik, A, Poggio, T, DiCarloJ. (2004). Object recognition by selective spike and LFP data in inferior temporal cortex. Society for Neuroscience Annual Meeting, San Diego, CA.
• Quiroga, Q, Reddy, L, Kreiman, G, Koch, C, Fried, I. (2004). Invariant visual representations in the human temporal lobe. Society for Neuroscience Annual Meeting, San Diego, CA.
• Tropea, D, Lyckman, A..W, Kreiman, G, Mukherjee, S, Sur, M. (2004). Gene expression in mouse visual cortex after visual input deprivation: gene systems mediating distinct effects of activity. Society for Neuroscience Annual Meeting, San Diego, CA.
  

2003

• Kreiman, G. (2003).Transcriptional regulation in higher eukaryotes. Computational Systems Biology Meeting, MIT, Maine, ME.
• Kreiman, G, Koch, C, Fried, I. (2003). Search for transcriptional regulatory signals in higher eukaryotes. Computational Biology: Function, Pathways, Phylogenies and Populations, Boston, MA.
• Kreiman, G, Koch, C, Fried, I. (2003). Dynamics of single neurons during perception and memory tasks in the human medial temporal lobe. 29th Gottingen Neurobiology Conference, Neuroscience Society Conference, Gottingen, Germany.
• Kreiman, G, Koch, C, Fried, I. (2003). In search of the NCC. Insights from single neuron recordings in the human brain. Association for the Scientific Study of Consciousness, Memphis, TN.
  

2002

 

• Kreiman, G. (2002). Computational search for differential gene expression and regulation in the medial temporal lobe. Society for Neuroscience, Orlando, FL.
• Krahe, R, Kreiman, G, Gabbiani, F, Koch, C, Metzner, W. (2002). Differences in feature extraction by electrosensory neurons for global and local stimuli. Society for Neuroscience, Orlando, FL.
• Kreiman, G, Koch, C, Fried, I. (2002). Sparse representation of visual information by single neurons in the human medial temporal lobe. Cognitive Neuroscience, Orlando, FL.
  

2001

• Staba, R. J., Kreiman, G, Wilson, C. L., Freid, I. (2001). Synchrony between single neurons in the human brain during sleep. Society for Neuroscience, San Diego, CA.
• Kreiman, G, Freid, I, Koch, C. (2001). Single neuron responses in humans during binocular rivalry and flash suppresion. Society for Neuroscience, San Diego, CA.
• Krahe, R, Kreiman, G, Gabbiani, F, Koch, C, Metzner, W.(2001).Information transmission by multiple pyramidal cells in the hindbrain of weakly electric fish. Society for Neuroscience, San Diego, CA.
• Fried, I, Kreiman, G, Koch, C. (2001).Imagery neurons in the human brain: a proposed substrate for visual experiential phenomena in epilepsy. American Epilepsy Society Annual Meeting, Los Angeles, CA.
  

2000

• Kreiman, G, Koch, C, Fried, I. (2000). Category-specific visual responses of single neurons in the human medial temporal lobe. Society for Neuroscience, New Orleans, LA.
• Kreiman, G, Koch, C, Fried, I. (2000). Feature extraction by multiple pyramidal cells in the hindbrain of weakly electric fish. European Neuroscience Societies Annual Meeting, Brighton, UK.
• Kreiman, G, Koch, C, Fried, I. (2000). Responses of single neurons in the human brain during visual presentation and imagery. Cognitive Neuroscience Society, San Francisco, CA.
• Fried, I, Kreiman, G, Koch, C. (2000). Responses of Single Neurons in the Human Brain During Vision and Visual Imagery. Annual Meeting of the Cognitive Neuroscience Society, San Francisc, CA.
  

1999

• Kreiman, G, Krahe, R, Metzner, W, Koch, C, Gabbian,i F. (1999). Robustness, variability and modeling of amplitude modulation encoding by P-receptor afferent spike trains of weakly electric fish. Neural Information and Coding Workshop, Big Sky, MT.
• Krahe, R, Kreiman, G, Gabbiani, F, Koch, C, Metzner, W. (1999). Stimulus encoding by multiple pyramidal cells in the ELL of weakly electric fish. Society for Neuroscience, Miami, FL.
• Kreiman, G, Koch, C. (1999). Flash Suppression: Competition between eyes or patterns? Association for Research in Vision and Opthalmology, Fort Lauderdale, FL.
  

1998

• Kreiman, G, Koch,C, Metzner, W, Gabbian, F. (1998). Robustness of amplitude modulation encoding by P-receptor afferent spike trains of weakly electric fish. Society for Neuroscience 1998, Los Angles, CA.
• Ouyang, Y, Rosenstein, A, Kreiman, G, Schuman, E. M., Kennedy, M. B. (1998). Tetanic Stimulation Increases Both Autophosphorylation and Synthesis of CaMKII in area CA1 of Hippocampal Slices Within 5 Minutes. Society for Neuroscience, Los Angles, CA.

1997

• Ouyang, Y, Kreiman, G, Kantor, D, Schuman, E. M., Kennedy, M. B. (1997). Tetanic stimulation produces a similar increase in both nonphosphorylated and autophosphorylated CaMKII in dendrites of hippocampal CA1 neurons. Society for Neuroscience, New Orleans, LA.