Ph.D. University of Bern
Fax: (631) 632-6661
Life Sciences Building
Office: Room 513
Giancarlo La Camera studied Theoretical Physics at the University of Rome "La Sapienza" and received a Laurea (M. Sci.) in 1999. He went on to obtain a PhD in Neurobiology from the University of Bern in 2003. Between 2004 and 2008 he was a visiting fellow at the National Institute of Mental Health, where he performed research on the neural basis of cognitive functions. He then returned to the University of Bern where he focused on the topic of reinforcement learning in populations of spiking neurons. In early 2011 he joined the faculty of Stony Brook University as an Assistant Professor of Neurobiology & Behavior and was promoted to the rank of Associate Professor with tenure in 2017.
theoretical neuroscience / sensory and cognitive processes / learning and behavior
The laboratory is interested in the neural basis of sensory and cognitive processes. These include memory, decision making, and more recently taste processing and how it is affected by expectation (work in collaboration with A. Fontanini). The approach used in the lab is mainly theoretical. Priority is given to finding biologically plausible models, often in terms of populations of spiking neurons. Recently, with this approach we have characterized the metastable nature of ongoing and evoked activity in several cortical areas (most notably the primary gustatory cortex), and worked out some of its consequences for neural coding. We hope that uncovering the common basis of ongoing and evoked activity can tell us much about how cortical networks are organized and function. The investigation of what type of sensory and cognitive functions can be subserved by metastable (rather than stable) neural activity is also a central effort of the lab.
The lab is also interested in the theory of learning, and therefore in modeling synaptic plasticity and coming up with learning rules for neural circuits. Recently, we have obtained results on the compound problem of segmenting a sensory stream and making decisions based on the segmented input. This was achieved by reinforcement learning in a network of spiking neurons, and is a first step towards understanding how an agent learns to identify the 'features' of its environment that are relevant for making decisions. The long-term goal of this program is to understand how agents can learn to produce context-dependent representations of relevant events, and how the latter affect animal and human behavior. In addition to seeking a theoretical understanding of these issues, we team up with other research groups in the Department of Neurobiology and elsewhere to test our models against empirical data.
Undergraduate (U) and graduate (G) courses which I direct or co-direct:
- AMS/BIO 332 (U) – Computational Modeling of Physiological Systems
- NEU 536 (G) – Introduction to Computational Neuroscience
Undergraduate (U) and graduate (G) courses to which I contribute:- BIO 335 (U) – Neurobiology Laboratory
- BIO 338 (U) – From Synapse to Circuit: Self-organization of the Brain
- GRD 500 (G) – Integrity in Science (aka “Responsible Conduct of Research”)
- NEU 501 (G) – Introduction to Neuroscience Research
- BNB 562 (G) – Introduction to Neuroscience II: Systems Neuroscience
- BNB 597 (G) – Seminar Themes: Research Topics in Neuroscience
- PHY 687 (G) – Topics in Biological Physics: Introduction to Computational Neuroscience (2011)
- Representative Publications
- Laboratory Personnel
- G. La Camera, S. Bouret and B.J. Richmond, Contributions of laternal and orbitofrontal regions to abstract rule acquisition and reversal in monkeys, Front. Neurosci. 12:165, 2018
- L. Mazzucato, G. La Camera* and A. Fontanini*, Expectation-induced modulation of metastable activity underlies faster coding of sensory stimuli, bioRxiv 199380; doi: https://doi.org/10.1101/199380, 2017
- L. Le Donne, L. Mazzucato, R. Urbanczik, W. Senn* and G. La Camera*, Spike-based reinforcement learning for temporal stimulus segmentation and decision making, Computing with Spikes Workshop, NIPS 2016, Barcelona, Spain, 2016
- L. Mazzucato, A. Fontanini and G. La Camera, Stimuli reduce the dimensionality of cortical activity, Front Sys Neurosci 10:11, 2016. Pubmed entry
- L. Mazzucato, A. Fontanini* and G. La Camera*, Dynamics of multi-stable states during ongoing and evoked cortical activity, J Neurosci 35(21): 8214-8231, 2015. Pubmed entry
- G. La Camera, R. Urbanczik and W. Senn, Stimulus detection and decision making via spike-based reinforcement learning, Proceedings of the 1st Multidisciplinary Conference on Reinforcement Learning and Decision Making, pp. 183-187, Princeton NJ, 2013
- A. Jezzini*, L. Mazzucato*, G. La Camera and A. Fontanini, Processing of hedonic and chemosensory features of taste in medial prefrontal and insular networks, J Neurosci 33(48): 18966-18978, 2013
- T. Minamimoto, G. La Camera, and B.J. Richmond, Measuring and Modeling the Interaction Among Reward Size, Delay to Reward, and Satiation Level on Motivation in Monkeys, J Neurophysiol 101:437-447, 2009
- M. Giugliano, G. La Camera, S. Fusi and W. Senn, The response of cortical neurons to in vivo-like input current: theory and experiment II. Time-varying and spatially distributed inputs, Biol Cybern 99(4-5):303-18, 2008
- G. La Camera, M. Giugliano, W. Senn and S. Fusi, The response of cortical neurons to in vivo-like input current: theory and experiment I. Noisy inputs with stationary statistics, Biol Cybern 99(4-5):279-301, 2008
- G. La Camera and B.J. Richmond, Modeling the violation of reward maximization and invariance in reinforcement schedules, PLoS Comput Biol 4(8): e1000131, 2008
- G. La Camera*, A. Rauch*, D. Thurbon, H-R Lüscher, W. Senn and S. Fusi, Multiple time scales of temporal response in pyramidal and fast spiking cortical neurons, J Neurophysiol 96(6): 3448-3464, 2006
- E. Curti, G. Mongillo, G. La Camera and D.J. Amit, Mean-Field and capacity in realistic networks of spiking neurons storing sparsely coded random memories, Neural Comput 16(12): 2597-2637, 2004
- G. La Camera, A. Rauch, H-R Lüscher, W. Senn and S. Fusi, Minimal models of adapted neuronal response to in vivo-like input currents, Neural Comput 16(10): 2101-2124, 2004
- A. Rauch*, G. La Camera*, H-R Lüscher, W. Senn and S. Fusi, Neocortical pyramidal cells respond as integrate-and-fire neurons to in vivo-like input currents, J Neurophysiol 90(3): 1598-1612, 2003
- Luca Mazzucato, Ph.D. Physics, SISSA/ISAS Trieste: Sr. Postdoc (2012-13); Research Assistant Professor (2013-present) (in collaboration with Dr. A. Fontanini).
- Luisa Le Donne, M.Sc. Physics, Sapienza University of Rome: Graduate Student (2011-2017)
- Lucinda A. Davies, Ph.D. Biomedical Sciences, University of Leeds: Sr. Postdoc (2011-2015) -- now at ICON Clinical Research.