Early postnatal exposure to lithium in vitro induces changes in AMPAR mEPSCs and vesicular recycling at hippocampal glutamatergic synapses.

Lithium is an effective mood stabilizer but its use is associated with many side effects. Electrophysiological recordings of miniature excitatory postsynaptic currents (mEPSCs) mediated by glutamate receptor AMPA-subtype (AMPARs) in hippocampal pyramidal neurons revealed that CLi (therapeutic concentration of 1 mM lithium, from days in vitro 4-10) decreased the mean amplitude and mean rectification index (RI) of AMPAR mEPSCs. Lowered mean RI indicate that contribution of Ca2+ -permeable AMPARs in synaptic events is higher in CLi neurons (supported by experiments sensitive to Ca2+ -permeable AMPAR modulation). Co-inhibiting PKA, GSK-3 beta and glutamate reuptake was necessary to bring about changes in AMPAR mEPSCs similar to that seen in CLi neurons. FM1-43 experiments revealed that recycling pool size was affected in CLi cultures. Results from minimum loading, chlorpromazine treatment and hyperosmotic treatment experiments indicate that endocytosis in CLi is affected while not much difference is seen in modes of exocytosis. CLi cultures did not show the high KCl associated presynaptic potentiation observed in control cultures. This study, by calling attention to long-term lithium-exposure-induced synaptic changes, might have implications in understanding the side effects such as CNS complications occurring in perinatally exposed babies and cognitive dulling seen in patients on lithium treatment.

Input coding for neuro-electronic hybrid systems.

Liquid State Machines have been proposed as a framework to explore the computational properties of neuro-electronic hybrid systems (Maass et al., 2002). Here the neuronal culture implements a recurrent network and is followed by an array of linear discriminants implemented using perceptrons in electronics/software. Thus in this framework, it is desired that the outputs of the neuronal network, corresponding to different inputs, be linearly separable. Previous studies have demonstrated this by either using only a small set of input stimulus patterns to the culture (Hafizovic et al., 2007), large number of input electrodes (Dockendorf et al., 2009) or by using complex schemes to post-process the outputs of the neuronal culture prior to linear discriminance (Ortman et al., 2011). In this study we explore ways to temporally encode inputs into stimulus patterns using a small set of electrodes such that the neuronal culture's output can be directly decoded by simple linear discriminants based on perceptrons. We demonstrate that network can detect the timing and order of firing of inputs on multiple electrodes. Based on this, we demonstrate that the neuronal culture can be used as a kernel to transform inputs which are not linearly separable in a low dimensional space, into outputs in a high dimension where they are linearly separable. Thus simple linear discriminants can now be directly connected to outputs of the neuronal culture and allow for implementation of any function for such a hybrid system.