פרופ' קורנגרין אלון
תואר ראשון בן-גוריון בנגב כימיה 1991
תואר שני בן-גוריון בנגב כימיה 1993
תואר שלישי בן-גוריון בנגב כימיה 1997
פוסט-דוקטורט מכון מקס פלנק פיזיולוגיה 1997-2001
מרצה אוניברסיטת בר-אילן 2001
מרצה-בכיר אוניברסיטת בר-אילן 2007
פרופ׳ חבר אוניברסיטת בר-אילן 2012
פרופ׳ מלא אוניברסיטת בר-אילן 2018
My research touches some of the basic yet still unresolved questions in neuroscience: How do neurons process information? What is the neuronal code at the cellular level? How does synaptic integration affect neuronal computation? To address these questions my lab combines electrophysiology of neurons in acute brain slices with techniques in computational neuroscience. Over the past decade we have developed several computational techniques aiming at constraining numerical models for complex cortical neurons. Thus, my research has aspects from computer science, neuronal computation, biophysics and neurophysiology. I am currently working on three primary projects that investigate various aspects of the general questions I am interested in.
Biophysics of dendritic excitability. We apply a combination of experiment and theory to provide a biophysically realistic model for the apical dendrite of L5 pyramidal neurons in the neocortex. Within the framework of this project, we have utilized genetic algorithms for constraining compartmental models of neurons with non-homogenous distributions of ion channels (Keren et al 2005, 2009) and voltage-gated channels (Gurkiewicz and Korngreen 2007, Gurkiewicz et al 2011). We have recently developed an experimental peeling procedure that greatly reduces the complexity of the numerical optimization problem (Keren et al 2009). This procedure allowed us to provide a reduced model for the apical dendrite of L5 pyramidal neurons (Keren et al 2009). This model predicted many of the properties of the back-propagating action potential. In the currnt stage of the project we are attempting, using similar peeling procedures, to constrain a biophysical model for the dendritic calcium spike in these neurons. For this end we have recently characterized the types and properties of voltage-gated calcium channels in L5 pyramidal neurons (Almog and Korngreen 2009). A substantial computational force is required in order to perform all these computations. Over the past decade I constructed several Linux clusters, the current one containing 160 CPUs. To increase our computation power even further we started using graphic cards as computing engines. I was fortunate to receive funding and equipment donation from the graphic card company NVIDIA. We just published a manuscript detailing a new numerical code for the GPU that sped the execution of part of our optimization algorithm by man orders of magnitude (Ben-Shalom et al 2012).
Magnetic stimulation of cortical neurons. Transcranial magnetic stimulation is a widely used stimulation tool applied both in research and in the clinic. A strong magnetic pulse is generated next to the skull and the resulting electric field in the brain activates neurons (mostly in the cortex). Surprisingly, the biophysical mechanisms responsible for this neuronal activation are far from understood. To provide a bottom-up mechanism for TMS we formed an interdisciplinary collaboration with Prof. Michal Lavidor (psychology), Dr. Izhar Bar-Gad (system neurophysiology) and Prof. Yosef Yeshurun (physics). This collaboration has proven to be extremely fruitful over the past four years producing (so far) two grant and four papers (two patents are in preparation). We built two recording setups combined with magnetic stimulation, one for primates and one for acute brain slices from rats. My student has developed a theoretical framework allowing for the first time to simulate the effect of magnetic stimulation on cortical neurons (Pashut et al 2011). This theoretical study predicted that the site of neuronal stimulation during TMS was somatic. This prediction contradicts the currently accepted hypothesis stating that TMS stimulates long axons in the cortex. We are currently testing our theoretical predictions using the novel recording system we have been developing.
Contribution of synaptic plasticity to network activity in the basal ganglia. The basal ganglia (BG) are a group of deep brain nuclei, strongly connected with the cerebral cortex, thalamus and other brain areas, that act as a cohesive functional unit. The basal ganglia are associated with a variety of functions, including voluntary motor control, procedural learning relating to routine behaviors or "habits" such as bruxism, eye movements, and cognitive, emotional functions. Many neurons in the BG display highly dynamic and rapid action potential firing. From my point of view, this makes them an interesting system in which to investigate the contribution of synaptic integration on network activity. I am collaborating with Dr. Bar-Gad and we are utilizing the similarities between the primate and rodent systems in our labs to try and bridge the gap between the integration at the cellular level to network function. Several joint manuscripts resulted from this close collaboration and we currently share one grant on this topic as well.