My research is in computational neuroscience - a field at the interface of neuro-biology, physics, and applied mathematics. I am most interested in the mechanisms of memory regulation, with an emphasis on the emerging field of neuro-glial interaction. I am also interested, on a more general level, in calcium excitability and calcium-regulated processes. In addition, I continue to work on issues in network dynamics. The different research venues are detailed below.
Theme 1: Modelling Hebbian reverberations as building blocks of short-term memory
One of the fundamental questions in neuroscience is how memories are formed, maintained, and recalled. In his seminal book, "Textbook of Psychology", Donald Hebb proposed that "...short-term memory may be a reverberation in the closed loops of the cell assembly and between cell assemblies, whereas long-term memory is a more structural, long lasting change of synaptic connections". Ever since Hebb, many attempts have been undertaken to find neurophysiological correlate of reverberating cell assembly and link it to higher brain functions. One example of experimental paradigm is shown in figure to the left (image). It shows a network of hippocampal neurons cultured on glial islands. Experimental studies have established that this system can serve as a good model of short-term memory - when stimulated with a brief pulse, a cultured network responds with reverberatory activity that lasts for several seconds (right, bottom). The ability of a network to maintain reverberatory response depends on the number of factors, among them asynchronous release of glutamate neurotransmitter from synaptic terminals.
We designed a neuro-computational model to study synaptic reverberations in hippocampal cultures. Using this model, we are able to reconstruct many salient features of network dynamics: reverberations originate in response to brief stimuli, are maintained by asynchronous release of neurotransmitter, and terminate due to the onset of slow depression. In addition, the model made a number of predictions (that were tested experimentally) as regards network's behavior following chemical manipulations. Thus, we showed that the model can be used as a neuro-computational parallel to neurophysiological experiments on hippocampal culture.
Our next research goal in this direction is to elucidate the effect of network's architecture and topological constraints on the properties of evoked and spontaneous reverberatory activity. These studies are likely to be of importance in investigating Hebb's idea of interacting cell assemblies.
Additional reading:
[1] P. Lau and G. Bi, "Synaptic mechanisms underlying reverberatory activity", Proc. Natl. Acad. Sci. USA, 2005
[2] V. Volman, R.C. Gerkin, P. Lau, E. Ben-Jacob, and G. Bi, "Calcium and synaptic dynamics underlie reverberatory activity in neuronal networks", Phys. Biol., 2007
[3] V. Volman and H. Levine, "Activity-dependent stochastic resonance in recurrent neuronal networks", Physical Review E, 2008
[4] V. Volman and H. Levine, "Signal processing in local neuronal circuits based on activity-dependent noise and competition", Chaos, 2009
[5] V. Volman, H. Levine, T.J. Sejnowski, "Shunting inhibition controls the gain modulation mediated by asynchronous neurotransmitter release in early development", PLoS Comp.Biol., 2010
[6] V. Volman and R.C. Gerkin, "Synaptic scaling stabilizes persistent activity driven by asynchronous neurotransmitter release", Neural Computation, 2010
Theme 2: Computational modelling of neuronal-glial interaction
Neurons are the most famous and well-studied brain cells, but they fill up only a small fraction of a brain. Glial cells can outnumber neurons by as large as factor of 9. For a long time, glia was thought to serve only a passive role in brain's functioning, mostly taking care of neuronal metabolism and keeping the extracellular space clean of "junk". The discovery that astrocytes, a cortical sub-type of glial cells, can "communicate" with neurons by sensing and secreting various transmitter molecules, boosted the experimental research in the direction of neuron-glial communication. As a result, we now have extensive evidence on the ways that astrocytes use to talk with neurons. In particular, hippocampal astrocytes were shown to modulate the characteristics of synaptic transmission and intrinsic neuronal excitability. From the morphological perspective, an intricate organization of neurons and astrocytes (image to the left) gives rise to the concept of "astrocyte syncytium", enabling these cells to coordinate the flow of sensory information through neuronal networks. The above findings call to assess the impact of neuron-astrocyte interaction on the computational capabilities of single neurons and neuronal cell assemblies.
Given the enormous complexity of neuro-glial organization, how do we approach the problem? Physicists' strategy is to start from the simple (approximate) case, with a hope that this will provide an insight into more complicated ones. To this end, we built a generic model that captures the existing empirical laws as regards the interaction of astrocytes with presynaptic terminals. The model of interaction was then applied to study the consequences of astrocytic feedback in a simplest possible neuro-glia network - one neuron with a self-synapse and one astrocyte adjacent to it. Even this simple model showed that introduction of an astrocyte brings about quite interesting behavior.
The next natural step is to extend the results of the simple "one synapse" model to the case when a single astrocyte coordinates the activity of several afferent synapses (see also next research theme).
Additional reading:
[1] V. Volman, E. Ben-Jacob, and H. Levine, "The astrocyte as a gatekeeper of synaptic information transfer", Neural Computation, 2007
[2] S. Nadkarni and P. Jung, Phys. Biol., 2007
[3] M. De Pitta, V. Volman, H. Berry, E. Beh-Jacob, "A tale of two stories: astrocyte regulation of synaptic depression and facilitation", PLoS Computational Biology, 2011
Theme 3: Processing of synaptic information by the active dendrites in the quantal limit of synaptic transmission
At any given instance of time, neurons are bombarded by synaptic stimuli that impinge on its dendrites through thousands of afferent channels. Understanding how this information is processed by neuronal dendritic trees is a crucial prerequisite for the construction of spatially extended computational model of neuro-glial interaction. Modelling of dendrites dates back to the days of Wilfrid Rall, and much work has been done to understand the connection between their structural features and function. Yet, those studies assume that synaptic events obey simple Poisson statistics. In reality, presynaptic plasticity transforms synaptic stimuli and imposes temporal structure on hitherto uncorrelated signals. This issue becomes significant at central synapses (such as CA3-CA1 Schaffer collaterals) that have small active zone and display heterogeneous pattern of presynaptic facilitation/depression.
We use multi-compartmental modelling techniques in order to study integrative properties of CA1 pyramidal neuron driven by plastic synapses in the quantal limit of synaptic transmission. Our main findings so far are that, notwithstanding the relatively large number of afferents, the spike trains of CA1 pyramidal neuron exhibit unusually high variability. This variability carries over from presynaptic terminals (where it arises due to the presynaptic plasticity and small active zone), and is preserved in pyramidal neurons due to the active mechanisms in their dendritic trees.
At present, we investigate the effect of ultrastructural characteristics of dendritic trees and presynaptic terminals on the variability of output spike trains, as well as implications of such variability for the activity of hippocampal place cells.
Additional reading:
[1] V. Volman, H. Levine, E. Ben-Jacob, T.J. Sejnowski, "Locally balanced dendritic integration by short-term synaptic plasticity and active dendritic conductances", J. Neurophysiology, Nov.2009
Theme 4: Mechanisms of calcium excitability and information encoding
Virtually all cells (including neurons and astrocytes) employ calcium signalling to carry information about the extracellular space to various points inside the cell. This information is encoded in spatio-temporal calcium patterns (most notably calcium waves) of bewildering complexity, and it is imperative to understand how such complexity relates to calcium excitability mechanisms. A traditional view had been that signals can translate to either amplitude- or frequency- variable calcium oscillations. We have discovered an additional, intermediate regime, in which amplitude and frequency modulations of calcium excitability can co-exist. This gives rise to more complicated patterns, and could serve as an explanation to some of the experimental results. This finding also opens up new prospects for information encoding in excitable systems.
Additional reading:
[1] M. De Pitta, V. Volman, H. Levine, G. Pioggia, D. De Rossi, and E. Ben-Jacob, "Coexistence of amplitude and frequency modulations in intracellular calcium dynamics", Physical Review E, 2008.
[2] M. Falcke, "Reading the patterns of calcium", Adv. Physics, 2001.
[3] M. De Pitta, V. Volman, H. Levine, E. Ben-Jacob, "Multi modal information encoding in a simplified model of calcium dynamics", Cognitive Processing, 2008.
[4] M. De Pitta, M. Goldberg, V. Volman, H.Berry, E. Ben-Jacob, "Glutamate regulation of calcium and IP3 oscillating and pulsating dynamics in astrocytes", J. Biological Physics, 2009.
[5] M. Goldberg, M. De Pitta, V. Volman, H. Berry, E. Ben-Jacob, "Nonlinear gap junctions enable long-distance propagation of pulsating calcium waves in astrocyte networks", PLoS Comp. Biol., 2010.
Theme 5: Computational modeling of trauma-induced epileptic activity
Mechanisms of post-traumatic epileptogenesis are studied using large-scale computational models of cortical networks. Topics of research include the relation between the trauma
spatial pattern and the rate of post-traumatic inter-ictal discharge, the role of network connectivity patterns in the emergence of post-traumatic epileptic activity, the spatio-temporal
mechanisms of glial (astrocyte) involvement in post-traumatic epileptogenesis. Particular attention is given to glial pathways of synaptic homeostatic regulation.
[1] V. Volman, T.J. Sejnowski, M. Bazhenov, "Topological basis of epileptogenesis in a model of severe cortical trauma", Journal of Neurophysiology, in press, 2011
[2] V. Volman, M. Bazhenov, T.J. Sejnowski, "Pattern of trauma determines the threshold for epileptic activity in the model of cortical deafferentation", PNAS, 2011
Theme 6: Patterns in complex excitable networks
[1] V. Volman, I. Baruchi, E. Ben-Jacob, "Manifestation of function-follow-form in cultured neuronal networks", Physical Biology, 2005.
[2] V. Volman, M. Perc. "Fast random rewiring and strong connectivity impair subthreshold signal detection in excitable networks", New Journal of Physics, 2010.
[3] V. Volman, M. Perc, M. Bazhenov, "Gap junctions and epileptic seizures - two sides of the same coin?", PLOS One, 2011.