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The pharmacological treatment of major depressive disorder with currently available antidepressant drugs is still unsatisfying as response to medication is delayed and in some patients even non-existent. To understand complex psychiatric diseases such as major depressive disorder and their treatment, research focus is shifting from investigating single neurons towards a view of the entire functional and effective neuronal network, because alterations on single synapses through antidepressant drugs may translate to alterations in the entire network. Here, we examined the effects of monoamine reuptake inhibitors on in vitro hippocampal network dynamics using calcium fluorescence imaging and analyzing the data with means of graph theoretical parameters. Hypothesizing that monoamine reuptake inhibitors operate through changes of effective connectivity on micro-scale neuronal networks, we measured the effects of the selective monoamine reuptake inhibitors GBR-12783, Sertraline, Venlafaxine, and Amitriptyline on neuronal networks. We identified a common pattern of effects of the different tested monoamine reuptake inhibitors. After treatment with GBR-12783, Sertraline, and Venlafaxine, the connectivity degree, measuring the number of existing connections in the network, was significantly decreased. All tested substances led to networks with more submodules and a reduced global efficiency. No monoamine reuptake inhibitor did affect network-wide firing rate, the characteristic path length, or the network strength. In our study, we found that monoamine reuptake inhibition in neuronal networks in vitro results in a sharpening of the network structure. These alterations could be the basis for the reorganization of a large-scale miswired network in major depressive disorder.

Analyzing the connectivity of neuronal networks, based on functional brain imaging data, has yielded new insight into brain circuitry, bringing functional and effective networks into the focus of interest for understanding complex neurological and psychiatric disorders. However, the analysis of network changes, based on the activity of individual neurons, is hindered by the lack of suitable meaningful and reproducible methodologies. Here, we used calcium imaging, statistical spike time analysis and a powerful classification model to reconstruct effective networks of primary rat hippocampal neurons in vitro. This method enables the calculation of network parameters, such as propagation probability, path length, and clustering behavior through the measurement of synaptic activity at the single-cell level, thus providing a fuller understanding of how changes at single synapses translate to an entire population of neurons. We demonstrate that our methodology can detect the known effects of drug-induced neuronal inactivity and can be used to investigate the extensive rewiring processes affecting population-wide connectivity patterns after periods of induced neuronal inactivity.

Effects of the antidepressant fluoxetine on stimulation-dependent synaptic vesicle exocytosis were examined in cultured primary hippocampal neurons. Synaptic vesicles were fluorescently labeled in vitro with FM1-43, washed and subsequently destained in two consecutive cycles. Exocytosis was triggered by electric field stimulation and imaged by fluorescence microscopy. In control preparations, the second staining-destaining cycle caused a significant reduction of relative fluorescence loss, number of active synapses and half-decay time (t(50)). These fatigue effects were largely prevented by short-term administration of 1 microM fluoxetine, which was present before and during the second stimulation cycle. Fluoxetine concentrations above 10 microM inhibited exocytosis almost completely but showed no other toxic effects on neurons. Stressed neurons, grown under hyperosmotic conditions, were even more fatigue-protected by fluoxetine. These observations support the idea that therapeutic concentrations of fluoxetine enhance the recovery of neurotransmission from exhausting stimuli in healthy and in hyperosmotically stressed neurons as well.