Julie S. Haas, Ph.D.
Department of Biological Sciences
Iacocca Hall, Room D226
111 Research Drive
Bethlehem, PA 18015
Activity-dependent changes in the strengths of synaptic connections between neurons underlie the brain’s ability to develop and continuously refine its representations of the world throughout life. Synaptic learning rules and mechanisms of plasticity have been extensively characterized at excitatory synapses and examined to a lesser extent at inhibitory synapses but almost entirely unexplored at electrical synapses. My lab investigates activity-dependent plasticity at electrical synapses, a unique and underappreciated type of synapse that, unlike its neurotransmitter-based counterparts, forms a direct physical connection between neurons. Electrical synapses are expressed widely throughout the mammalian brain.
I am interested in determining the relationships between electrical synaptic strength, synchrony in circuits of coupled neurons, and the more abstract process of attention. These ideas coalesce within the thalamus, in a specific nucleus where electrical synapses are particularly dense; it is this nucleus that is thought to gate cortical attention to the sensory surround. I hypothesize that the strength of electrical synapses within this nucleus is a crucial component for the control of human attention.
To study electrical synapses, our main tool is dual whole-cell patch clamping. In the image above, two electrode tips are shown in preparation for patching the two cell bodies, which are connected by an electrical synapse (also known as a gap junction) where the ‘arms’ of the two neurons cross.
|Once two coupled cells have been patched, the electrical synapse is measured by injecting current into one cell (bottom square trace), measuring the resulting voltage deflection in the first cell (middle trace) and measuring the voltage deflection passed across the electrical synapse into the second cell (top trace).
Electrical synapses can share and cause spiking activity between coupled neurons. In the example above, the spikes in one cell (grey) of a coupled pair caused spikes in its coupled neighbor (black). With these methods, we measure strength of electrical synapses before and after the cells are active together.
Haas JS and Landisman CE (2012) Bursts modify electrical synaptic strength. Brain Research, special issue on Electrical Synapses, in press.
Haas JS, Zavala B and Landisman CE (2011) Activity-dependent long-term depression of electrical synapses.
Haas JS and Landisman CE (2011) State-dependent modulation of gap junction signaling by the persistent sodium current. Frontiers in Cellular Neuroscience 5:31.
Haas JS, Kreuz T, Torcini A, Politi A, Abarbanel HDI (2010) Rate maintenance in spiking neurons driving with strong inputs of varying speeds. European Journal of Neuroscience 32(11):1930-9.
Kreuz T, Chicharro D, Andrzejak RG, Haas JS, Abarbanel HDI, Politi A (2009). Measuring multiple spike train synchrony. J. Neurosci. Methods 182(2):287-299.
Kreuz T, Haas JS, Morelli A, Abarbanel HDI, Politi A (2007). Measuring spike train synchrony. J. Neurosci. Methods 165(1):151-61.
Haas JS, Dorval AD, White JA (2007). Contributions of Ih to feature selectivity in layer II stellate cells of the entorhinal cortex. J. Computational Neuroscience 22(2):161-71.
Haas JS, Nowotny TN, Abarbanel HDI (2006). Spike-timing-dependent plasticity at inhibitory synapses in the entorhinal cortex. J. Neurophysiol 96: 3305-3313.
Netoff TI, Banks MI, Dorval AD, Acker CD, Haas JS, Kopell N, White JA (2004). Synchronization in hybrid neuronal networks of the hippocampal formation. J. Neurophysiol. 93(3):1197-1208.
Haas JS and White JA (2002). Frequency selectivity of layer II stellate cells in the medial entorhinal cortex.
J. Neurophysiol. 88(5): 2422-2429.
Abarbanel HDI, Haas JS, Talathi SS (2007) Synapses and neurons: Basic properties and their use in the recognition of environmental signals. In Lecture Notes in Supercomputational Neuroscience, Springer-Verlag.
White JA and Haas JS (2001) Noise from voltage-gated ion channels: effects on dynamics and reliability in intrinsically oscillatory neurons. In Handbook of Biological Physics, Vol. 4, F Moss and S Gielen (eds.), Elsevier Press, Amsterdam.