Project description:Neurons fire at highly variable intrinsic rates and recent evidence suggests that low- and high-firing rate neurons display different plasticity and dynamics. Furthermore, recent publications imply possibly differing rate-dependent effects in hippocampus versus neocortex, but those analyses were carried out separately and with potentially important differences. To more effectively synthesize these questions, we analyzed the firing rate dynamics of populations of neurons in both hippocampal CA1 and frontal cortex under one framework that avoids the pitfalls of previous analyses and accounts for regression to the mean (RTM). We observed several consistent effects across these regions. While rapid eye movement (REM) sleep was marked by decreased hippocampal firing and increased neocortical firing, in both regions firing rate distributions widened during REM due to differential changes in high- versus low-firing rate cells in parallel with increased interneuron activity. In contrast, upon non-REM (NREM) sleep, firing rate distributions narrowed while interneuron firing decreased. Interestingly, hippocampal interneuron activity closely followed the patterns observed in neocortical principal cells rather than the hippocampal principal cells, suggestive of long-range interactions. Following these undulations in variance, the net effect of sleep was a decrease in firing rates. These decreases were greater in lower-firing hippocampal neurons but also higher-firing frontal cortical neurons, suggestive of greater plasticity in these cell groups. Our results across two different regions, and with statistical corrections, indicate that the hippocampus and neocortex show a mixture of differences and similarities as they cycle between sleep states with a unifying characteristic of homogenization of firing during NREM and diversification during REM.
Project description:Sleep is critical for memory consolidation, although the exact mechanisms mediating this process are unknown. Combining reduced network models and analysis of in vivo recordings, we tested the hypothesis that neuromodulatory changes in acetylcholine (ACh) levels during non-rapid eye movement (NREM) sleep mediate stabilization of network-wide firing patterns, with temporal order of neurons' firing dependent on their mean firing rate during wake. In both reduced models and in vivo recordings from mouse hippocampus, we find that the relative order of firing among neurons during NREM sleep reflects their relative firing rates during prior wake. Our modeling results show that this remapping of wake-associated, firing frequency-based representations is based on NREM-associated changes in neuronal excitability mediated by ACh-gated potassium current. We also show that learning-dependent reordering of sequential firing during NREM sleep, together with spike timing-dependent plasticity (STDP), reconfigures neuronal firing rates across the network. This rescaling of firing rates has been reported in multiple brain circuits across periods of sleep. Our model and experimental data both suggest that this effect is amplified in neural circuits following learning. Together our data suggest that sleep may bias neural networks from firing rate-based towards phase-based information encoding to consolidate memories.
Project description:Firing rate is an important means of encoding information in the nervous system. To reliably encode a wide range of signals, neurons need to achieve a broad range of firing frequencies and to move smoothly between low and high firing rates. This can be achieved with specific ionic currents, such as A-type potassium currents, which can linearize the frequency-input current curve. By applying recently developed mathematical tools to a number of biophysical neuron models, we show how currents that are classically thought to permit low firing rates can paradoxically cause a jump to a high minimum firing rate when expressed at higher levels. Consequently, achieving and maintaining a low firing rate is surprisingly difficult and fragile in a biological context. This difficulty can be overcome via interactions between multiple currents, implying a need for ion channel degeneracy in the tuning of neuronal properties.
Project description:Pre-clinical studies of fragile X syndrome (FXS) have focused on neurons, with the role of glia remaining largely underexplored. We examined the astrocytic regulation of aberrant firing of FXS neurons derived from human pluripotent stem cells. Human FXS cortical neurons, co-cultured with human FXS astrocytes, fired frequent short-duration spontaneous bursts of action potentials compared with less frequent, longer-duration bursts of control neurons co-cultured with control astrocytes. Intriguingly, bursts fired by FXS neurons co-cultured with control astrocytes are indistinguishable from control neurons. Conversely, control neurons exhibit aberrant firing in the presence of FXS astrocytes. Thus, the astrocyte genotype determines the neuronal firing phenotype. Strikingly, astrocytic-conditioned medium, and not the physical presence of astrocytes, is capable of determining the firing phenotype. The mechanistic basis of this effect indicates that the astroglial-derived protein, S100β, restores normal firing by reversing the suppression of a persistent sodium current in FXS neurons.
Project description:While hippocampal-dependent learning and memory are particularly vulnerable to traumatic brain injury (TBI), the functional status of individual hippocampal neurons and their interactions with oscillations are unknown following injury. Using the most common rodent TBI model and laminar recordings in CA1, we found a significant reduction in oscillatory input into the radiatum layer of CA1 after TBI. Surprisingly, CA1 neurons maintained normal firing rates despite attenuated input, but did not maintain appropriate synchronization with this oscillatory input or with local high-frequency oscillations. Normal synchronization between these coordinating oscillations was also impaired. Simultaneous recordings of medial septal neurons known to participate in theta oscillations revealed increased GABAergic/glutamatergic firing rates postinjury under anesthesia, potentially because of a loss of modulating feedback from the hippocampus. These results suggest that TBI leads to a profound disruption of connectivity and oscillatory interactions, potentially disrupting the timing of CA1 neuronal ensembles that underlie aspects of learning and memory.