Detail

Keywords

Electrophysiology; Nociception; Optogenetics; Pain Perception

Research interests

Throughout my academic career I have been interested in the processing of aversive stimuli in the central neurvous system, how they are distinguished from benign stimuli, and how they influence the behavior of an organism. During my PhD studies, I focused on somatosensory inputs into the cerebellum, and their role in cerebellar classical conditioning. Since I have begun my postdoctoral research at the Center for Brain Research, I am looking to isolate different ascending pathways from the spinal cord to the brain, and to define the roles of these pathways in pain perception. To this aim, we are developing methods to selectively express genes in different populations of spinal cord projection neurons; this will allow for selective activation or inhibition of these neuronal populations using tools such as optogenetics and chemogenetics. With these methods, we could examine the involvement of specific pathways in shaping electrophysiological and behavioral responses to acute and chronic pain, with potential benefits to patients.

Techniques, methods & infrastructure

Genetic manipulations in wild-type rats using viral vectors, in vivo electrophysiology, intracranial and intraspinal injections

Selected publications

1. Hogri, R. et al., 2015. A neuro-inspired model-based closed-loop neuroprosthesis for the substitution of a cerebellar learning function in anesthetized rats. Scientific Reports, 5, p.8451. Available at: http://dx.doi.org/10.1038/srep08451.
2. Hogri, R., Segalis, E. & Mintz, M., 2014. Cerebellar Inhibitory Output Shapes the Temporal Dynamics of Its Somatosensory Inferior Olivary Input. The Cerebellum, 13(4), pp.452-461. Available at: http://dx.doi.org/10.1007/s12311-014-0558-3.
3. Bamford, S.A. et al., 2012. A VLSI Field-Programmable Mixed-Signal Array to Perform Neural Signal Processing and Neural Modeling in a Prosthetic System. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 20(4), pp.455-467. Available at: http://dx.doi.org/10.1109/TNSRE.2012.2187933.
4. Herreros, I. et al., 2014. A Cerebellar Neuroprosthetic System: Computational Architecture and in vivo Test. Frontiers in Bioengineering and Biotechnology, 2. Available at: http://dx.doi.org/10.3389/fbioe.2014.00014.
5. Taub, A.H. et al., 2012. Bioactive anti-inflammatory coating for chronic neural electrodes. J. Biomed. Mater. Res., 100A(7), pp.1854-1858. Available at: http://dx.doi.org/10.1002/jbm.a.34152.