Dual synaptic plasticity in the hippocampus: Hebbian and spatiotemporal learning dynamics

Reactive Oxygen Species: Physiological and Physiopathological Effects on Synaptic Plasticity

In the mammalian central nervous system, reactive oxygen species (ROS) generation is counterbalanced by antioxidant defenses. When large amounts of ROS accumulate, antioxidant mechanisms become overwhelmed and oxidative cellular stress may occur. Therefore, ROS are typically characterized as toxic molecules, oxidizing membrane lipids, changing the conformation of proteins, damaging nucleic acids, and causing deficits in synaptic plasticity. High ROS concentrations are associated with a decline in cognitive functions, as observed in some neurodegenerative disorders and age-dependent decay of neuroplasticity. Nevertheless, controlled ROS production provides the optimal redox state for the activation of transductional pathways involved in synaptic changes. Since ROS may regulate neuronal activity and elicit negative effects at the same time, the distinction between beneficial and deleterious consequences is unclear. In this regard, this review assesses current research and describes the main sources of ROS in neurons, specifying their involvement in synaptic plasticity and distinguishing between physiological and pathological processes implicated.

Synaptic activity slows vesicular replenishment at excitatory synapses of rat hippocampus

Short-term synaptic depression mainly reflects the depletion of the readily releasable pool (RRP) of quanta. Its dynamics, and especially the replenishment rate of the RRP, are still not well characterized in spite of decades of investigation. Main reason is that the vesicular storage and release system is treated as time-independent. If it is time-dependent all parameters thus estimated become problematic. Indeed the reports about how prolonged stimulation affects the dynamics are contradictory. To study this, we used patterned stimulation on the Schaeffer collateral fiber pathway and model-fitting of the excitatory post-synaptic currents (EPSC) recorded from CA1 neurons in rat hippocampal slices. The parameters of a vesicular storage and release model with two pools were estimated by minimizing the squared difference between the ESPC amplitudes and simulated model output. This yields the 'basic' parameters (release coupling, replenishment coupling and RRP size) that underlie the 'derived' and commonly used parameters (fractional release and replenishment rate). The fractional release increases when [Ca(++)]o is raised, whereas the replenishment rate is [Ca(++)]o independent. Fractional release rises because release coupling increases, and the RRP becomes less able to contain quanta. During prolonged stimulation, the fractional release remains generally unaltered, whereas the replenishment rate decreases down to ~10 % of its initial value with a decay time of ~15 s, and this decrease in the replenishment rate significantly contributes to synaptic depression. In conclusion, the fractional release is [Ca(++)]o-dependent and stimulation-independent, whereas the replenishment rate is [Ca(++)]o-independent and stimulation-dependent.

A MODEL OF HIPPOCAMPAL MEMORY BASED ON AN ADAPTIVE LEARNING RULE OF SYNAPSES

We constructed a neural network of the hippocampus and proposed an adaptive learning rule of synapses to simulate the storing and retrieving processes of memory in the hippocampus by a mechanism of resonance. The hippocampus network consists of CA1, CA3 and DG, in particular, CA1 is a storage of memory, which receives inputs from both EC through perforant path (PP) and CA3 through Schaffer collaterals (SC). The stimulated results showed that the memory trace was unable to be encoded in CA1 when only a single subthreshold signal from EC or CA3 was inputted, of which the main reason might be lack of the resonance of the two signals. We calculated signal-to-noise ratio (SNR) of the network, and found it reached a peak value at appropriate SC connection strength, indicating that a typical stochastic resonance phenomenon appeared in PP signal detection. The inputs from EC and CA3 were able to enhance the memory representation in CA1, although still incomplete. We used a learning rule to modify synaptic weights by which the network could learn an external pattern. The hippocampus network tended to be stable after sufficient evolution. Some CA1 neurons show synchronized firings which are used to represent memory and are clearer than observed memory traces before learning. The model and results provide a good guidance to our understanding of the mechanism of the hippocampus memory.

Optical imaging of plastic changes induced by fear conditioning in the auditory cortex

The plastic changes in the auditory cortex induced by a fear conditioning, through pairing a sound (CS) with an electric foot-shock (US), were investigated using an optical recording method with voltage sensitive dye, RH795. In order to investigate the effects of association learning, optical signals in the auditory cortex in response to CS (12 kHz pure tone) and non-CS (4, 8, 16 kHz pure tone) were recorded before and after normal and sham conditioning. As a result, the response area to CS enlarged only in the conditioning group after the conditioning. Additionally, the rise time constant of the auditory response to CS significantly decreased and the relative peak value and the decay time constant of the auditory response to CS significantly increased after the conditioning. This study introduces an optical approach to the investigation of fear conditioning, representational plasticity, and the cholinergic system. The findings are synthesized in a model of the synaptic mechanisms that underlie cortical plasticity.