Local memory allocation recruits memory ensembles across brain regions.

Memories are thought to be stored in ensembles of neurons across multiple brain regions. However, whether and how these ensembles are coordinated at the time of learning remains largely unknown. Here, we combined CREB-mediated memory allocation with transsynaptic retrograde tracing to demonstrate that the allocation of aversive memories to a group of neurons in one brain region directly affects the allocation of interconnected neurons in upstream brain regions in a behavioral- and brain region-specific manner in mice. Our analysis suggests that this cross-regional recruitment of presynaptic neurons is initiated by downstream memory neurons through a retrograde mechanism. Together with statistical modeling, our results indicate that in addition to the anterograde flow of information between brain regions, the establishment of interconnected, brain-wide memory traces relies on a retrograde mechanism that coordinates memory ensembles at the time of learning.

CCR5 closes the temporal window for memory linking.

Real-world memories are formed in a particular context and are often not acquired or recalled in isolation1-5. Time is a key variable in the organization of memories, as events that are experienced close in time are more likely to be meaningfully associated, whereas those that are experienced with a longer interval are not1-4. How the brain segregates events that are temporally distinct is unclear. Here we show that a delayed (12-24 h) increase in the expression of C-C chemokine receptor type 5 (CCR5)-an immune receptor that is well known as a co-receptor for HIV infection6,7-after the formation of a contextual memory determines the duration of the temporal window for associating or linking that memory with subsequent memories. This delayed expression of CCR5 in mouse dorsal CA1 neurons results in a decrease in neuronal excitability, which in turn negatively regulates neuronal memory allocation, thus reducing the overlap between dorsal CA1 memory ensembles. Lowering this overlap affects the ability of one memory to trigger the recall of the other, and therefore closes the temporal window for memory linking. Our findings also show that an age-related increase in the neuronal expression of CCR5 and its ligand CCL5 leads to impairments in memory linking in aged mice, which could be reversed with a Ccr5 knockout and a drug approved by the US Food and Drug Administration (FDA) that inhibits this receptor, a result with clinical implications. Altogether, the findings reported here provide insights into the molecular and cellular mechanisms that shape the temporal window for memory linking.

A shared neural ensemble links distinct contextual memories encoded close in time.

Recent studies suggest that a shared neural ensemble may link distinct memories encoded close in time. According to the memory allocation hypothesis, learning triggers a temporary increase in neuronal excitability that biases the representation of a subsequent memory to the neuronal ensemble encoding the first memory, such that recall of one memory increases the likelihood of recalling the other memory. Here we show in mice that the overlap between the hippocampal CA1 ensembles activated by two distinct contexts acquired within a day is higher than when they are separated by a week. Several findings indicate that this overlap of neuronal ensembles links two contextual memories. First, fear paired with one context is transferred to a neutral context when the two contexts are acquired within a day but not across a week. Second, the first memory strengthens the second memory within a day but not across a week. Older mice, known to have lower CA1 excitability, do not show the overlap between ensembles, the transfer of fear between contexts, or the strengthening of the second memory. Finally, in aged mice, increasing cellular excitability and activating a common ensemble of CA1 neurons during two distinct context exposures rescued the deficit in linking memories. Taken together, these findings demonstrate that contextual memories encoded close in time are linked by directing storage into overlapping ensembles. Alteration of these processes by ageing could affect the temporal structure of memories, thus impairing efficient recall of related information.

Shaping Neuronal Network Activity by Presynaptic Mechanisms.

Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level.

StimDuino: an Arduino-based electrophysiological stimulus isolator.

BACKGROUND: Electrical stimulus isolator is a widely used device in electrophysiology. The timing of the stimulus application is usually automated and controlled by the external device or acquisition software; however, the intensity of the stimulus is adjusted manually. Inaccuracy, lack of reproducibility and no automation of the experimental protocol are disadvantages of the manual adjustment. To overcome these shortcomings, we developed StimDuino, an inexpensive Arduino-controlled stimulus isolator allowing highly accurate, reproducible automated setting of the stimulation current. NEW METHOD: The intensity of the stimulation current delivered by StimDuino is controlled by Arduino, an open-source microcontroller development platform. The automatic stimulation patterns are software-controlled and the parameters are set from Matlab-coded simple, intuitive and user-friendly graphical user interface. The software also allows remote control of the device over the network. RESULTS: Electrical current measurements showed that StimDuino produces the requested current output with high accuracy. In both hippocampal slice and in vivo recordings, the fEPSP measurements obtained with StimDuino and the commercial stimulus isolators showed high correlation. COMPARISON WITH EXISTING METHODS: Commercial stimulus isolators are manually managed, while StimDuino generates automatic stimulation patterns with increasing current intensity. The pattern is utilized for the input-output relationship analysis, necessary for assessment of excitability. In contrast to StimuDuino, not all commercial devices are capable for remote control of the parameters and stimulation process. CONCLUSIONS: StimDuino-generated automation of the input-output relationship assessment eliminates need for the current intensity manually adjusting, improves stimulation reproducibility, accuracy and allows on-site and remote control of the stimulation parameters.

DOC2B and Munc13-1 differentially regulate neuronal network activity.

Alterations in the levels of synaptic proteins affect synaptic transmission and synaptic plasticity. However, the precise effects on neuronal network activity are still enigmatic. Here, we utilized microelectrode array (MEA) to elucidate how manipulation of the presynaptic release process affects the activity of neuronal networks. By combining pharmacological tools and genetic manipulation of synaptic proteins, we show that overexpression of DOC2B and Munc13-1, proteins known to promote vesicular maturation and release, elicits opposite effects on the activity of the neuronal network. Although both cause an increase in the overall number of spikes, the distribution of spikes is different. While DOC2B enhances, Munc13-1 reduces the firing rate within bursts of spikes throughout the network; however, Munc13-1 increases the rate of network bursts. DOC2B's effects were mimicked by Strontium that elevates asynchronous release but not by a DOC2B mutant that enhances spontaneous release rate. This suggests for the first time that increased asynchronous release on the single-neuron level promotes bursting activity in the network level. This innovative study demonstrates the complementary role of the network level in explaining the physiological relevance of the cellular activity of presynaptic proteins and the transformation of synaptic release manipulation from the neuron to the network level.

Neuron-specific expression of tomosyn1 in the mouse hippocampal dentate gyrus impairs spatial learning and memory.

Tomosyn, a syntaxin-binding protein, is known to inhibit vesicle priming and synaptic transmission via interference with the formation of SNARE complexes. Using a lentiviral vector, we specifically overexpressed tomosyn1 in hippocampal dentate gyrus neurons in adult mice. Mice were then subjected to spatial learning and memory tasks and electrophysiological measurements from hippocampal slices. Tomosyn1-overexpression significantly impaired hippocampus-dependent spatial memory while tested in the Morris water maze. Further, tomosyn1-overexpressing mice utilize swimming strategies of lesser cognitive ability in the Morris water maze compared with control mice. Electrophysiological measurements at mossy fiber-CA3 synapses revealed impaired paired-pulse facilitation in the mossy fiber of tomosyn1-overexpressing mice. This study provides evidence for novel roles for tomosyn1 in hippocampus-dependent spatial learning and memory, potentially via decreased synaptic transmission in mossy fiber-CA3 synapses. Moreover, it provides new insight regarding the role of the hippocampal dentate gyrus and mossy fiber-CA3 synapses in swimming strategy preference, and in learning and memory.