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Prof. dr. C.M.A. (Cyriel) Pennartz

Faculty of Science
Swammerdam Institute for Life Sciences

Visiting address
  • Science Park 904
  • Room number: C4.103
Postal address
  • Postbus 94246
    1090 GE Amsterdam
  • Research profile

    Neural mechanisms of perception and multisensory integration

    In our daily lives, we do not only process sensory information about single stimuli, but become consciously aware of many stimuli, perceive them as embedded in a context, and experience a rich diversity of sensations in multiple modalities. How is the brain able to perceive and to integrate or differentiate between sensory modalities? Here we apply techniques such as ensemble recordings (many-neuron recordings, using tetrodes, silicon probes and two-photon imaging) and optogenetics to examine how neurons and neuronal populations code sensory stimuli and make a difference between perceived versus unperceived stimuli, as gauged via behavioral report. Leading discoveries are that the visual cortex, seemingly dedicated to a single modality (vision) is susceptible to non-visual factors such as reward and auditory input.

    Two-photon imaging of multisensory interactions in primary visual cortex. (Left) Two-photon imaging of multi-neuron activity in primary visual cortex using the green fluorescent Calcium indicator GCaMP6. Numbers 1-4 indicate different neurons. (Middle) Relative changes in fluorescent activity of the same four neurons shown as a function of time. Vertical colored bars are visual stimuli with varying grating orientation, and bars marked by an ‘x’ at the top represent trials with co-presentation of an auditory tone. Tone presentations modulated visual responses. Right: polar plots showing orientation selectivity of the same four neurons (from: Meijer et al. 2017, J. Neurosci. 37: 8783-8796).

    Computational neuroscience of perception and cognition

    Empirical neuroscience data, although very intriguing on their own, are often too complicated to explain by intuitive models drafted with pen-and-paper. Therefore, computational models of networks performing cognitive and perceptual tasks are needed. In this research line we focus on neuronal models of predictive coding, wherein perception is built on the brain generating ‘predictions’ (or representations) about what causes the sensory inputs received through our senses. We have developed a novel, scalable model of a deep neural network relying on predictive coding with Hebbian learning. Next challenges are to make the model more neurobiologically realistic, endowing it with cortex-like circuitry, and expand the model to include cognitive capacities and multisensory integration.

    Predictive coding by multi-layer networks governed by Hebbian learning. The schematic illustrates the basic idea underlying predictive processing. On the left, a real-world horse causes patterns of photons to impinge on the retina, which gives rise to a low-level sensory representation (second picture from left). The network is trained to generate a representation of the cause of this low-level image, such that the image can be reconstructed from this representation once this is triggered in the absence of the actual image. Predictive coding enables this generative reconstruction by comparing top-down (feedback) predictions with bottom-up sensory inputs, resulting in an error signal that is fed forward to higher areas, thereby instructing inference and learning. Our computational model implements predictive coding in deep, cortex-like networks that learn based on Hebbian principles (from Dora, Pennartz & Bohte, 2018, Artificial Neural Networks and Machine Learning – ICANN 2018. Lecture Notes in Computer Science, Vol. 11141).

    Interactions between sensory neocortex and temporal lobe memory system

    How does the brain transmit sensory information to the temporal lobe memory system to direct the storage of hippocampus-dependent long-term memories? We understand some basics of sensory processing and hippocampal memory, but do not grasp how the two are connected and communicate. We focus on how the visual, auditory and somatosensory cortices interact with the hippocampus and an intermediate, parahippocampal structure: the perirhinal cortex. Using chemogenetics and ensemble recordings, we study the role of the sensory cortical-hippocampal hierarchy in navigation, discrimination between spatial patterns (pattern separation), object recognition and memory retrieval. Recently, we discovered perirhinal neurons with spatially extended firing fields – informally dubbed ‘neighborhood cells’ in analogy to hippocampal place cells.

    Spatially extended firing fields of perirhinal cortex neurons during task performance on a figure-8 shaped maze. For nine different neurons we display the firing rate of each neuron as a function of the subject’s position on a figure-8 maze. Subjects performed a visual discrimination task. Firing rate is coded both by color (red: high rate; blue: below baseline) and by the amplitude of each vertical bar, corresponding to the subject’s position on the maze. Some cells fire strongly and selectively for only one arm of the maze, or in the center lane. Other cells show a suppression for one arm or a bidirectional modulation (firing rate up on one arm, down on the other). These patterns could not be attributed to task variables such as reward, or environmental cues surrounding the maze. See Bos et al. (2017, Nature Communications 8:15602) for further details.

    Neural basis of consciousness and clinically related research

    How does brain activity give rise to consciousness? What in the brain makes the difference when we perceive or do not perceive an object? a key tenet of my neuropresentationalist theory holds that conscious experience essentially provides the subject with a multimodally rich and spatially encompassing survey of its situation in the world, including its body. This has a function: it enables the subject to make complex decisions and plan its behavior. The neural architecture required to construct this survey is rich, comprising phenomena such as hierarchical and lateral connectivity in the cortex, phase coding, predictive representations and a multi-level organization of representational systems. To better understand the conscious state, we also study neuronal ensembles and multi-area interactions during sleep and anesthesia. Thus, our theoretical research is translated into practical experiments on perception, multisensory integration as well as computational modelling. Complementary research with clinical relevance comprises data analysis to better characterize the conscious state and alleviate symptoms in patients who are behaviorally impaired and/or locked-in.

    The neurorepresentational account of conscious sensory processing. In 2015 I proposed that conscious processing is organized through low, intermediate and high representational levels. Here, representations correspond to hypotheses (rendered here as H(…)). A low-level hypothesis (green) pertains to a singular feature within a sensory modality, attributed to an object or location in the environment (e.g., H(color) is the hypothesis that a visual object is of a certain color). The intermediate level (blue) is exemplified by H(visual object), the hypothesis that a visual object has several properties integrated across low-level predictions. The highest level of representation (red) integrates across several sensory modalities and pertains to multimodal objects. For instance, grabbing a piece of paper in one’s hand generates a joint inference on its visual, tactile and auditory properties. Already at the lowest level, predictions are generated in a feedforward, recurrent and laterally connected multi-layer architecture which may well stretch across several connected cortical areas (e.g., V1, V2, V3 and V5 for visual motion). Motor or situational aspects are not taken into account here. From Olcese et al. (2018, Front. Syst. Neuroscience 12: 49).
  • Role in Cognitive and Systems Neuroscience group & collaborations

    Chairing the Cognitive and Systems Neuroscience group at the Swammerdam Institute for Life Sciences, I collaborate with staff members of the group, and many more scientists, to conduct the research as sketched above, coordinate teaching activities, support technical innovation, and guide PhD students in their projects. With Umberto Olcese I collaborate in several funded project

     (Neurotechnology: INTENSE project, Consciousness: Templeton Initiative on Accelerating Research on Consciousness, Human Brain Project). Dr Jorge Mejias, Prof. Dr Sander Bohte and I work together on computational modelling in the Human Brain Project and the NWA-ORC grant ‘Perceptive Acting under Uncertainty’. With Dr Conrado Bosman I collaborate on the emergent development of multisensory integration early in life. I also work closely with Gerjan Huis in ‘t Veld (biotechnician), Dr Angelica da Silva Lantyer (Scientific Integration Manager Human Brain Project) and data analyst and PhD candidate Pietro Marchesi.

    Nationally and internationally funded research projects

    • Trans-University Brain-Mind Research Grant of the Vrije Universiteit and University of Amsterdam. Processing multisensory evidence for decision-making (with Dr C. de Kock).
    • Templeton Initiative on Accelerating Research on Consciousness, grant from the Templeton World Charity Foundation for Pilot Experiments ‘Adversarial Research on Neural Mechanisms of Consciousness’ (with Umberto Olcese and others).
    • Human Brain Project grant, FET Flagship Core Project, Co-leader of Workpackage on Neural mechanisms of cognition and consciousness and Member of the Science and Infrastructure Board (SGA-3 phase; period 2020-2023).
    • NWO Crossover project INTENSE: Innovative Neurotechnology for Society (with Pieter Roelfsema, Umberto Olcese).
    • NWA-ORC grant, Perceptive Acting under Uncertainty, project on Computational Modelling (with Jorge Mejias and Sander Bohte).

    Main external collaborations

    • Katrin Amunts, Forschungszentrum Jülich (Germany)
    • Jan Bjaalie, University of Oslo (Norway)
    • Sander Bohte, Center of Mathematics and Computer Science (the Netherlands)
    • Melanie Boly, University of Wisconsin, Madison (U.S.A.)
    • Jeroen Bos, Radboud University Nijmegen (the Netherlands)
    • Michael Denker, Forschungszentrum Jülich (Germany)
    • Shirin Dora, Ulster University (United Kingdom)
    • Emrah Düzel, German Center for Neurodegenerative Diseases, Magdeburg (Germany)
    • Kathinka Evers, Uppsala University (Sweden)
    • Karl Friston, University College London/Wellcome Center (United Kingdom)
    • Sonja Grün, Forschungszentrum Jülich (Germany)
    • Jakob Hohwy, Monash University, Melbourne (Australia)
    • Marian Joëls, University Medical Center Groningen (the Netherlands)
    • Christiaan de Kock, Vrije Universiteit Amsterdam (the Netherlands)
    • Lars Muckli, University of Glasgow (United Kingdom)
    • Pepijn van den Munckhof, Amsterdam University Medical Center (the Netherlands)
    • Michael Okun, University of Leicester (United Kingdom)
    • Martin Pearson, University of the West of England, Bristol (United Kingdom)
    • Mihai Petrovici, University of Bern (Switzerland)
    • Giovanni Pezzulo, National Research Council of Italy, Rome (Italy)
    • Pieter Roelfsema, Netherlands Institute for Neuroscience (the Netherlands)
    • Matthew Self, Netherlands Institute for Neuroscience (the Netherlands)
    • Jonathan Coutinho, Amsterdam UMC (the Netherlands)
    • Walter Senn, University of Bern (Switzerland)
    • Giulio Tononi, University of Wisconsin-Madison (USA)
    • Paul Verschure, Institute for Bioengineering of Catalonia, Barcelona (Spain)
    • Martin Vinck, Ernst Strüngmann Institute, Frankfurt (Germany)
    • Menno Witter, NTNU University of Trondheim (Norway)
  • News

    On May 3, 2021, a new popular-science book from Pennartz was released by Publishing House Prometheus: De Code van het Bewustzijn. Hoe de hersenen onze werkelijkheid vormgeven. (The Code of Consciousness, in Dutch; paperback, 352 pages, ISBN: 978 90 446 3191 3)

  • Bio-sketch

    Cyriel Pennartz studied Biology at the Radboud University and University of Amsterdam with specializations in Neurobiology, Philosophy and Computational Neuroscience. He obtained his PhD degree in Neuroscience at the latter university. His PhD project examined the electrophysiology and plasticity of brain circuits involved in memory and motivation, focusing on the ventral striatum, and was partly conducted at the University of Tennessee (Memphis, U.S.A.). He next worked as Postdoctoral fellow in Computational Neuroscience at the Department of Physics of Computation of the California Institute of Technology with John Hopfield. Here he worked on neural network models of Reinforcement Learning. In 1994 he became tenured staff scientist and group leader at the Netherlands Institute for Brain Research, initially researching the physiology of the brain´s circadian clock. Working with Bruce McNaughton and Carol Barnes at the University of Arizona (Tucson, U.S.A.), he introduced in vivo ensemble recording techniques to the Netherlands and discovered replay of reward information in the ventral striatum during sleep.

          In 2003 he was appointed Full Professor in Cognitive and Systems Neuroscience at the University of Amsterdam, where he is currently leads the Cognitive and Systems Neuroscience group. He merges experimental neuroscience, computational models of brain function and theory on perception, memory and consciousness. His work in experimental neuroscience is paired with technological innovations in multi-area electrophysiology, pharmacological and optogenetic interventions, advanced data analytics and computer simulations. Chief characteristics of his work are its multidisciplinarity and integrative approach, in which theory and computer models drive in-depth experimentation. Recently his work has been ramifying into the clinical domain, studying disorders of consciousness and memory, and into neurotechnology, developing new methods to combat consequences of stroke.

  • Further information and contact

    For general information about our Master track Cognitive Neurobiology and Clinical Neurophysiology and internships, please contact:

    Are you seeking more specific information on Pennartz’ research lines or specific projects for internships or collaboration? Please contact me ( 

  • 10 key publications (past 10 years)
    • Vinck M, Oostenveld R, Van Wingerden M, Battaglia FP and Pennartz CMA (2011) An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias. Neuroimage 55: 1548-1565.
    • Van Wingerden M, Vinck MA, Tijms V, Rebelo da Silva I, Jonker AJ, Pennartz CMA (2012) NMDA receptors control cue-outcome selectivity and plasticity of orbitofrontal firing patterns during associative stimulus-reward learning. Neuron 76: 1-13.
    • Pezzulo G, van der Meer MAA, Lansink CS, Pennartz CMA (2014) Internally generated sequences in learning and executing goal-directed behavior. Trends in Cognitive Sciences 18: 647-657.
    • Pennartz CMA (2015) The Brain’s Representational Power – on consciousness and the integration of modalities. MIT press (382 pp.). ISBN: 9780262029315.
    • Montijn JS, Goltstein PM, Pennartz CMA (2015) Mouse V1 population correlates of visual detection rely on heterogeneity within neuronal response patterns. eLife 2015; 4: e10163. DOI: 10.7554/eLife.10163.
    • Bos JJ, Vinck M, Van Mourik-Donga LA, Jackson JC, Witter MP, Pennartz CMA (2017) Perirhinal firing patterns are sustained across large spatial segments of the task environment. Nature Communications 8:15602, DOI: 10.1038/ncomms15602.
    • Pennartz CMA (2018) Consciousness, representation, action: the importance of being goal-directed. Trends in Cognitive Sciences 22:137-153.
    • Goltstein PM, Meijer GT and Pennartz CMA (2018) Conditioning refines the spatial representation of rewarded stimuli in mouse primary visual cortex. ELife 7: e37683. DOI:
    • Pennartz CMA, Dora S, Muckli L, Lorteije JAM (2019) Towards a unified view on pathways and functions of neural recurrent processing. Trends in Neurosciences 42: 589-603. doi: 10.1016 /j.tins.2019.07.005.
    • Meijer GT, Mejias JF, Marchesi P, Montijn JS, Lansink CS, Pennartz CMA (2020) Neural correlates of multisensory detection behavior: comparison of primary and higher-order visual cortex of the mouse. Cell Reports 31: 107636. doi: 10.1016/j.celrep.2020.107636.
  • Publications








    • Aarts, E., Maroteaux, G., Loos, M., Koopmans, B., Kovačević, J., Smit, A. B., ... de Zeeuw, C. I. (2015). The light spot test: Measuring anxiety in mice in an automated home-cage environment. Behavioural Brain Research, 294, 123-130. [details]
    • Goltstein, P. M., Montijn, J. S., & Pennartz, C. M. A. (2015). Effects of isoflurane anesthesia on ensemble patterns of Ca2+ activity in mouse V1: reduced direction selectivity independent of increased correlations in cellular activity. PLoS ONE, 10(2), e0118277. [e0118277]. [details]
    • Lansink, C. S., & Pennartz, C. M. A. (2015). Associative Reactivation of Place-Reward Information in the Hippocampal-Ventral Striatal Circuitry. In M. Tatsuno, & J. Knierim (Eds.), Analysis and modeling of coordinated multi-neuronal activity (pp. 81-104). (Springer series in computational neuroscience; No. 12). New York: Springer. [details]
    • Loos, M., Koopmans, B., Aarts, E., Maroteaux, G., van der Sluis, S., Verhage, M., ... de Zeeuw, C. I. (2015). Within-strain variation in behavior differs consistently between common inbred strains of mice. Mammalian Genome, 26(7-8), 348-354. [details]
    • Montijn, J. S., Goltstein, P. M., & Pennartz, C. M. A. (2015). Mouse V1 population correlates of visual detection rely on heterogeneity within neuronal response patterns. eLife, 4, [e10163]. [details]
    • Pennartz, C. M. A. (2015). The brain’s representational power: on consciousness and the integration of modalities. Cambridge, MA: MIT Press. [details]
    • Remmelink, E., Loos, M., Koopmans, B., Aarts, E., van der Sluis, S., Smit, A. B., ... de Zeeuw, C. I. (2015). A 1-night operant learning task without food-restriction differentiates among mouse strains in an automated home-cage environment. Behavioural Brain Research, 283, 53-60. [details]
    • Vinck, M., Bos, J. J., van Mourik-Donga, L. A., Oplaat, K. T., Klein, G. A., Jackson, J. C., ... Pennartz, C. M. A. (2015). Cell-Type and State-Dependent Synchronization among Rodent Somatosensory, Visual, Perirhinal Cortex, and Hippocampus CA1. Frontiers in Systems Neuroscience, 9, [187]. [details]
    • Vinck, M., Huurdeman, L., Bosman, C. A., Fries, P., Battaglia, F. P., Pennartz, C. M. A., & Tiesinga, P. H. (2015). How to detect the Granger-causal flow direction in the presence of additive noise? NeuroImage, 108, 301-318. [details]



    • Goltstein, P. M., Coffey, E. B. J., Roelfsema, P. R., & Pennartz, C. M. A. (2013). In vivo two-photon Ca2+ imaging reveals selective reward effects on stimulus-specific assemblies in mouse visual cortex. The Journal of Neuroscience, 33(28), 11540-11555. [details]
    • Stănişor, L., van der Togt, C., Pennartz, C. M. A., & Roelfsema, P. R. (2013). A unified selection signal for attention and reward in primary visual cortex. Proceedings of the National Academy of Sciences of the United States of America, 110(22), 9136-9141. [details]


    • Huijbers, W., Vannini, P., Sperling, R. A., Pennartz, C. M. A., Cabeza, R., & Daselaar, S. M. (2012). Explaining the encoding/retrieval flip: memory-related deactivations and activations in the posteromedial cortex. Neuropsychologia, 50(14), 3764-3774. [details]
    • Lansink, C. S., Jackson, J. C., Lankelma, J. V., Ito, R., Robbins, T. W., Everitt, B. J., & Pennartz, C. M. A. (2012). Reward cues in space: commonalities and differences in neural coding by hippocampal and ventral striatal ensembles. The Journal of Neuroscience, 32(36), 12444-12459. [details]
    • Maroteaux, G., Loos, M., van der Sluis, S., Koopmans, B., Aarts, E., Gassen, K., ... Verhage, M. (2012). High-throughput phenotyping of avoidance learning in mice discriminates different genotypes and identifies a novel gene. Genes Brain and Behavior, 11(7), 772-784. [details]
    • Nagtegaal, A. P., Spijker, S., Crins, T. T. H., Brussaard, A. B., Borst, J. G. G., Elgersma, Y., ... de Zeeuw, C. I. (2012). A novel QTL underlying early-onset, low-frequency hearing loss in BXD recombinant inbred strains. Genes Brain and Behavior, 11(8), 911-920. [details]
    • Rietman, M. L., Sommeijer, J-P., Levelt, C. N., Heimel, J. A., Brussaard, A. B., Borst, J. G. G., ... de Zeeuw, C. I. (2012). Candidate genes in ocular dominance plasticity. Frontiers in Neuroscience, 6, [11]. [details]
    • Vinck, M., Battaglia, F. P., Balakirsky, V. B., Vinck, A. J. H., & Pennartz, C. M. A. (2012). Estimation of the entropy based on its polynomial representation. Physical Review E, 85(5-1), [051139]. [details]
    • Vinck, M., Battaglia, F. P., Womelsdorf, T., & Pennartz, C. (2012). Improved measures of phase-coupling between spikes and the Local Field Potential. Journal of Computational Neuroscience, 33(1), 53-75. [details]
    • Winstanley, C. A., Robbins, T. W., Balleine, B. W., Brown, J. W., Büchel, C., Cools, R., ... Seamans, J. K. (2012). Search, goals and the brain. In P. M. Todd, T. T. Hills, & T. W. Robbins (Eds.), Cognitive search: evolution, algorithms and the brain (pp. 125-156). (Strüngmann Forum reports). Cambridge, Massachusetts: MIT Press. [details]
    • van Wingerden, M., Vinck, M., Tijms, V., Ferreira, I. R. S., Jonker, A. J., & Pennartz, C. M. A. (2012). NMDA receptors control cue-outcome selectivity and plasticity of orbitofrontal firing patterns during associative stimulus-reward learning. Neuron, 76(4), 813-825. [details]


    • Battaglia, F. P., & Pennartz, C. M. A. (2011). The construction of semantic memory: grammar-based representations learned from relational episodic information. Frontiers in Computational Neuroscience, 5, 1-22. [details]
    • Battaglia, F. P., Benchenane, K., Sirota, A., Pennartz, C. M. A., & Wiener, S. I. (2011). The hippocampus: hub of brain network communication for memory. Trends in Cognitive Sciences, 15(7), 310-318. [details]
    • Guger, C., Gener, T., Pennartz, C. M. A., Brotons-Mas, J. R., Edlinger, G., Bermúdez i Badia, S., ... Sanchez-Vives, M. V. (2011). Real-time position reconstruction with hippocampal place cells. Frontiers in Neuroscience, 5, [85]. [details]
    • Huijbers, W., Pennartz, C. M. A., Cabeza, R., & Daselaar, S. M. (2011). The hippocampus is coupled with the default network during memory retrieval but not during memory encoding. PLoS ONE, 6(4). [details]
    • Huijbers, W., Pennartz, C. M. A., Rubin, D. C., & Daselaar, S. M. (2011). Imagery and retrieval of auditory and visual information: neural correlates of successful and unsuccessful performance. Neuropsychologia, 49, 1730-1740. [details]
    • Kalenscher, T., & Pennartz, C. M. A. (2011). Do intransitive choices reflect genuinely context-dependent preferences? In M. R. Delgado, E. A. Phelps, & T. W. Robbins (Eds.), Decision Making, Affect, and Learning: Attention and Performance XXIII (pp. 101-123). Oxford: Oxford University Press. [details]
    • Loos, M., Staal, J., Pattij, T., Brussaard, A. B., Borst, J. G., Elgersma, J. W., ... Spijker, S. (2011). Independent genetic loci for sensorimotor gating and attentional performance in BXD recombinant inbred strains. Genes Brain and Behavior, 11, 147-156. [details]
    • Malkki, H. A. I., Donga, L. A. B., de Groot, S. E., Brussaard, A. B., Borst, J. G. G., Elgersma, J. W., ... Battaglia, F. P. (2011). Towards mouse models of perseveration: a heritable component in extinction of operant behavior in fourteen standard and recombinant inbred mouse lines. Neurobiology of Learning and Memory, 96, 280-287. [details]
    • Pennartz, C. M. A., Ito, R., Verschure, P. F. M. J., Battaglia, F. P., & Robbins, T. W. (2011). The hippocampal-striatal axis in learning, prediction and goal-directed behavior. Trends in Neurosciences, 34(10), 548-559. [details]
    • Pennartz, C. M. A., van Wingerden, M., & Vinck, M. (2011). Population coding and neural rhythmicity in the orbitofrontal cortex. Annals of the New York Academy of Sciences, 1239, 149-161. [details]
    • Vinck, M., Oostenveld, R., van Wingerden, M., Battaglia, F., & Pennartz, C. M. A. (2011). An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias. NeuroImage, 55(4), 1548-1565. [details]


    • Daselaar, S. M., Huijbers, W., de Jonge, M., Goltstein, P. M., & Pennartz, C. M. A. (2010). Experience-dependent alterations in conscious resting state activity following perceptuomotor learning. Neurobiology of Learning and Memory, 93(3), 422-427. [details]
    • Daselaar, S. M., Porat, Y., Huijbers, W., & Pennartz, C. M. A. (2010). Modality-specific and modality-independent components of the human imagery system. NeuroImage, 52(2), 677-685. [details]
    • Huijbers, W., Pennartz, C. M. A., & Daselaar, S. M. (2010). Dissociating the "retrieval success" regions of the brain: Effects of retrieval delay. Neuropsychologia, 48(2), 491-497. [details]
    • Kalenscher, T., Lansink, C. S., Lankelma, J. V., & Pennartz, C. M. A. (2010). Reward-associated gamma oscillations in ventral striatum are regionally differentiated and modulate local firing activity. Journal of Neurophysiology, 103(3), 1658-1672. [details]
    • Kalenscher, T., Tobler, P. N., Huijbers, W., Daselaar, S. M., & Pennartz, C. M. A. (2010). Neural signatures of intransitive preferences. Frontiers in Human Neuroscience, 4, 49. [details]
    • Lansink, C. S., Goltstein, P. M., Lankelma, J. V., & Pennartz, C. M. A. (2010). Fast-spiking interneurons of the rat ventral striatum: temporal coordination of activity with principal cells and responsiveness to reward. European Journal of Neuroscience, 32(3), 494-508. [details]
    • Malkki, H. A. I., Donga, L. A. B., de Groot, S. E., Battaglia, F. P., Brussaard, A. B., Borst, J. G. G., ... de Zeeuw, C. I. (2010). Appetitive operant conditioning in mice: heritability and dissociability of training stages. Frontiers in Behavioral Neuroscience, 4, 171. [details]
    • Sanchez-Fibla, M., Bernardet, U., Wasserman, E., Pelc, T., Mintz, M., Jackson, J. C., ... Verschure, P. F. M. J. (2010). Allostatic control for robot behavior regulation: a comparative rodent-robot study. Advances in Complex Systems, 13(3), 377-403. [details]
    • Vinck, M., van Wingerden, M., Womelsdorf, T., Fries, P., & Pennartz, C. M. A. (2010). The pairwise phase consistency: A bias-free measure of rhythmic neuronal synchronization. NeuroImage, 51(1), 112-122. [details]
    • van Wingerden, M., Vinck, M., Lankelma, J. V., & Pennartz, C. M. A. (2010). Learning-associated gamma-band phase-locking of action-outcome selective neurons in orbitofrontal cortex. The Journal of Neuroscience, 30(30), 10025-10038. [details]
    • van Wingerden, M., Vinck, M., Lankelma, J., & Pennartz, C. M. A. (2010). Theta-band phase locking of orbitofrontal neurons during reward expectancy. The Journal of Neuroscience, 30(20), 7078-7087. [details]
    • van der Meer, M. A. A., Kalenscher, T., Lansink, C. S., Pennartz, C. M. A., Berke, J. D., & Redish, A. D. (2010). Integrating early results on ventral striatal gamma oscillations in the rat. Frontiers in Neuroscience, 4, [300]. [details]


    • Battaglia, F. P., Kalenscher, T., Cabral, H., Winkel, J., Bos, J., Manuputy, R., ... Pennartz, C. (2009). The Lantern: An ultra-light micro-drive for multi-tetrode recordings in mice and other small animals. Journal of Neuroscience Methods, 178(2), 291-300. [details]
    • Huijbers, W., Pennartz, C. M., Cabeza, R., & Daselaar, S. M. (2009). When learning and remembering compete: A functional MRI study. PLoS Biology, 7(1), [e1000011]. [details]
    • Lansink, C. S., Goltstein, P. M., Lankelma, J. V., McNaughton, B. L., & Pennartz, C. M. A. (2009). Hippocampus leads ventral striatum in replay of place-reward information. PLoS Biology, 7(8), e1000173. [details]
    • Lee, E., Oliveira-Ferreira, A. I., de Water, E., Gerritsen, H., Bakker, M. C., Kalwij, J. A. W., ... Pennartz, C. M. A. (2009). Ensemble recordings in awake rats: Achieving behavioral regularity during multimodal stimulus processing and discriminative learning. Journal of the Experimental Analysis of Behavior, 92(1), 113-129. [details]
    • Loos, M., van der Sluis, S., Bochdanovits, Z., van Zutphen, I. J., Pattij, T., Stiedl, O., ... Spijker, S. (2009). Activity and impulsive action are controlled by different genetic and environmental factors. Genes Brain and Behavior, 8(8), 817-828. [details]
    • Pennartz, C. M. A. (2009). Identification and integration of sensory modalities: Neural basis and relation to consciousness. Consciousness and Cognition, 18(3), 718-739. [details]
    • Pennartz, C. M. A., Berke, J. D., Graybiel, A. M., Ito, R., Lansink, C. S., van der Meer, M., ... Voorn, P. (2009). Corticostriatal interactions during learning, memory processing, and decision making. The Journal of Neuroscience, 29(41), 12831-12838. [details]
    • Taverna, S., & Pennartz, C. M. A. (2009). Intrinsic synaptic connectivity of the nucleus accumbens: Lateral inhibition, functions of fast-spiking interneurons and neuromodulation. In H. N. David (Ed.), The nucleus accumbens: Neurotransmitters & related behaviours (pp. 63-79). Trivandrum: Research Signpost. [details]
    • van Duuren, E., van der Plasse, G., Lankelma, J., Joosten, R. N. J. M. A., Feenstra, M. G. P., & Pennartz, C. M. A. (2009). Single-cell and population coding of expected reward probability in the orbitofrontal cortex of the rat. The Journal of Neuroscience, 29(28), 8965-8976. [details]


    • Heimel, J. A., Hermans, J. M., Sommeijer, J-P., Brussaard, A. B., Borst, J. G., Elgersma, Y., ... de Zeeuw, C. I. (2008). Genetic control of experience-dependent plasticity in the visual cortex. Genes Brain and Behavior, 7(8), 915-923. [details]
    • Ito, R., Robbins, T. W., Pennartz, C. M., & Everitt, B. J. (2008). Functional interaction between the hippocampus and nucleus accumbens shell is necessary for the acquisition of appetitive spatial context conditioning. The Journal of Neuroscience, 28(27), 6950-6959. [details]
    • Kalenscher, T., & Pennartz, C. M. A. (2008). Is a bird in the hand worth two in the future? The neuroeconomics of intertemporal decision-making. Progress in Neurobiology, 84(3), 284-315. [details]
    • Lansink, C. S., Goltstein, P. M., Lankelma, J. V., Joosten, R. N. J. M. A., McNaughton, B. L., & Pennartz, C. M. A. (2008). Preferential reactivation of motivationally relevant information in the ventral striatum. The Journal of Neuroscience, 28(25), 6372-6382. [details]
    • Nordquist, R. E., Vanderschuren, L. J. M. J., Jonker, A. J., Bergsma, M., de Vries, T. J., Pennartz, C. M. A., & Voorn, P. (2008). Expression of amphetamine sensitization is associated with recruitment of a reactive neuronal population in the nucleus accumbens core. Psychopharmacology, 198(1), 113-126. [details]
    • van Duuren, E., Lankelma, J., & Pennartz, C. M. A. (2008). Population coding of reward magnitude in the orbitofrontal cortex of the rat. The Journal of Neuroscience, 28(34), 8590-8603. [details]


    • Pennartz, C. M. A. (2016-). Member of National Science Agenda, preparatory group on Brain, Cognition and Behavior (organised by NWO), .

    Media appearance

    • Pennartz, C. (30-03-2013). Depressie bestrijden met geuren: interview door Joost Zonneveld [Print] Het Parool, Parool. Depressie bestrijden met geuren: interview door Joost Zonneveld.

    Journal editor

    • Pennartz, C. M. A. (editor) (2016-). eLife (Journal).
    • Pennartz, C. M. A. (editor) (2016-). Trends in Neurosciences (Journal).
    • Pennartz, C. M. A. (editor) (2016-). Behavioral and Brain Sciences (Journal).
    • Pennartz, C. M. A. (editor) (2016-). Neuron (Journal).
    • Pennartz, C. M. A. (editor) (2016-). Philosophical Transactions of the Royal Society B - Biological Sciences (Journal).
    • Pennartz, C. M. A. (editor) (2016-). Science (Journal).
    • Pennartz, C. M. A. (editor) (2016-). Proceedings of the National Academy of Sciences of the United States of America (Journal).
    • Pennartz, C. M. A. (editor) (2016-). Journal of Neuroscience Research (Journal).

    Talk / presentation

    • Pennartz, C. M. A. (speaker) (12-12-2016). Neuroscience Research in the Human Brain Project., 3rd Annual Meeting of the US BRAIN initiative, Bethesda.
    • Pennartz, C. M. A. (speaker) (30-11-2016). Systems Neurophysiology of multisensory and sensory-mnemonic integration., International HBP Systems and Cognitive Neuroscience Meeting. , Amsterdam.
    • Pennartz, C. M. A. (speaker) (14-10-2016). From plasticity to learning, perception and real-world behavior., Human Brain Project Summit meeting, Florence.
    • Pennartz, C. M. A. (invited speaker) (27-9-2016). Motivational influences on hippocampal rhythms and sequences, Workshop on Internally generated sequences in the hippocampus, Ariccia.
    • Pennartz, C. M. A. (speaker) (15-9-2016). Ensembles as intermediates between neurons and cognition., EBPS meeting, Amsterdam.
    • Pennartz, C. M. A. (invited speaker) (5-9-2016). Workshop to prepare Documentary on Children with Absence Epilepsy, Workshop to prepare Documentary on Children with Absence Epilepsy, Academy of the Arts, Trippenhuis, organized by M. Nevejan., Amsterdam.
    • Pennartz, C. M. A. (invited speaker) (4-8-2016). Neuroinformatics and the Human Brain Project: from neuron to consciousness’, Awesome IT; Student Conference in Informatics.
    • Pennartz, C. M. A. (invited speaker) (12-5-2016). Functional plasticity in large-scale systems: learning tasks, neurophysiology and computational issues., European Institute for Theoretical Neuroscience., Paris.
    • Pennartz, C. M. A. (speaker) (14-2-2016). Neural dynamics of memory, planning and motivated action., Haifa Forum for Brain and Behavior. The neuroscience of social interactions , Haifa.
    • Pennartz, C. M. A. (speaker) (3-2-2016). Systems Neuroscience of Episodic memory and multisensory integration, , European Institute for Theoretical Neuroscience, Paris.


    • Pennartz, C. M. A. (participant) (30-11-2016). International HBP Systems and Cognitive Neuroscience Meeting., Amsterdam. organizer (participating in a conference, workshop, ...).
    • Pennartz, C. M. A. (participant) (27-1-2016). Public Awareness Event (other).
    • Pennartz, C. M. A. (participant) (1-1-2016). Full Professorship promotion at Brown University, Providence RI, USA (other).


    • Arbab, T., Pennartz, C. M. A., & Battaglia, F. P. (2017). Impaired hippocampal representation of place in the Fmr1-knockout mouse model of Fragile-X syndrome. BioRxiv. [details]
    This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list.
  • Ancillary activities
    • No ancillary activities