Changes in the synaptic connection strengths between neurons are believed to play a role in memory formation. An important mechanism for changing synaptic strength is through movement of neurotransmitter receptors and regulatory proteins to and from the synapse. Several activity-triggered biochemical events control these movements. Here we use computer models to explore how these putative memory-related changes can be stabilised long after the initial trigger, and beyond the lifetime of synaptic molecules. We base our models on published biochemical data and experiments on the activity-dependent movement of a glutamate receptor, AMPAR, and a calcium-dependent kinase, CaMKII. We find that both of these molecules participate in distinct bistable switches. These simulated switches are effective for long periods despite molecular turnover and biochemical fluctuations arising from the small numbers of molecules in the synapse. The AMPAR switch arises from a novel self-recruitment process where the presence of sufficient receptors biases the receptor movement cycle to insert still more receptors into the synapse. The CaMKII switch arises from autophosphorylation of the kinase. The switches may function in a tightly coupled manner, or relatively independently. The latter case leads to multiple stable states of the synapse. We propose that similar self-recruitment cycles may be important for maintaining levels of many molecules that undergo regulated movement, and that these may lead to combinatorial possible stable states of systems like the synapse.

Tracking odour trails is a crucial behaviour for many animals, often leading to food, mates or away from danger. It is an excellent example of active sampling, where the animal itself controls how to sense the environment. Here we show that rats can track odour trails accurately with near-optimal sampling. We trained rats to follow odour trails drawn on paper spooled through a treadmill. By recording local field potentials (LFPs) from the olfactory bulb, and sniffing rates, we find that sniffing but not LFPs differ between tracking and non-tracking conditions. Rats can track odours within ~1 cm, and this accuracy is degraded when one nostril is closed. moreover, they show path prediction on encountering a fork, wide 'casting' sweeps on encountering a gap and detection of reappearance of the trail in 1-2 sniffs. We suggest that rats use a multi-layered strategy, and achieve efficient sampling and high accuracy in this complex task.

Many cellular signaling events occur in small subcellular volumes and involve low-abundance molecular species. This context introduces two major differences from mass-action analyses of nondiffusive signaling. First, reactions involving small numbers of molecules occur in a probabilistic manner which introduces scatter in chemical activities. Second, the timescale of diffusion of molecules between subcellular compartments and the rest of the cell is comparable to the timescale of many chemical reactions, altering the dynamics and outcomes of signaling reactions. This study examines both these effects on information flow through four protein kinase regulatory pathways. The analysis uses Monte Carlo simulations in a subcellular volume diffusively coupled to a bulk cellular volume. Diffusion constants and the volume of the subcellular compartment are systematically varied to account for a range of cellular conditions. Each pathway is characterized in terms of the probabilistic scatter in active kinase levels as a measure of "noise" on the pathway output. Under the conditions reported here, most signaling outcomes in a volume below one femtoliter are severely degraded. Diffusion and subcellular compartmentalization influence the signaling chemistry to give a diversity of signaling outcomes. These outcomes may include washout of the signal, reinforcement of signals, and conversion of steady responses to transients.

Excitation-inhibition (EI) balance controls excitability, dynamic range, and input gating in many brain circuits. Subsets of synaptic input can be selected or 'gated' by precise modulation of finely tuned EI balance, but assessing the granularity of EI balance requires combinatorial analysis of excitatory and inhibitory inputs. Using patterned optogenetic stimulation of mouse hippocampal CA3 neurons, we show that hundreds of unique CA3 input combinations recruit excitation and inhibition with a nearly identical ratio, demonstrating precise EI balance at the hippocampus. Crucially, the delay between excitation and inhibition decreases as excitatory input increases from a few synapses to tens of synapses. This creates a dynamic millisecond-range window for postsynaptic excitation, controlling membrane depolarization amplitude and timing via subthreshold divisive normalization. We suggest that this combination of precise EI balance and dynamic EI delays forms a general mechanism for millisecond-range input gating and subthreshold gain control in feedforward networks.

The olfactory system receives intermittent and fluctuating inputs arising from dispersion of odor plumes and active sampling by the animal. Previous work has suggested that the olfactory transduction machinery and excitatory-inhibitory olfactory bulb circuitry generate nonlinear population trajectories of neuronal activity that differ across odorants. Here we show that individual mitral/tufted (M/T) cells sum inputs linearly across odors and time. By decoupling odor sampling from respiration in anesthetized rats, we show that M/T cell responses to arbitrary odor waveforms and mixtures are well described by odor-specific impulse responses convolved with the odorant's temporal profile. The same impulse responses convolved with the respiratory airflow predict the classical respiration-locked firing of olfactory bulb neurons and several other reported response properties of M/T cells. These results show that the olfactory bulb linearly processes fluctuating odor inputs, thereby simplifying downstream decoding of stimulus identity and temporal dynamics.

The synaptic signaling network is capable of sophisticated cellular computations. These include the ability to respond selectively to different patterns of input, and to sustain changes in response over long periods. The small volume of the synapse complicates the analysis of signaling because the chemical environment is strongly affected by diffusion and stochasticity. This study is based on an updated version of a previously proposed synaptic signaling circuit (Bhalla and Iyengar, 1999) and analyzes three network computation properties in small volumes: bistability, thresholding, and pattern selectivity. Simulations show that although there are diffusive regimes in which bistability may persist, chemical noise at small volumes overwhelms bistability. In the deterministic situation, the network exhibits a sharp threshold for transition between lower and upper stable states. This transition is broadened and individual runs partition between lower and upper states, when stochasticity is considered. The third network property, pattern selectivity, is severely degraded at synaptic volumes. However, there are regimes in which a process similar to stochastic resonance operates and amplifies pattern selectivity. These results imply that simple scaling of signaling conditions to femtoliter volumes is unlikely, and microenvironments, such as reaction complex formation, may be essential for reliable small-volume signaling.

Stimulus reinforcement strengthens learning. Intervals between reinforcement affect both the kind of learning that occurs and the amount of learning. Stimuli spaced by a few minutes result in more effective learning than when massed together. There are several synaptic correlates of repeated stimuli, such as different kinds of plasticity and the amplitude of synaptic change. Here we study the role of signalling pathways in the synapse on this selectivity for spaced stimuli. Using the in vitro hippocampal slice technique we monitored long-term potentiation (LTP) amplitude in CA1 for repeated 100-Hz, 1-s tetani. We observe the highest LTP levels when the inter-tetanus interval is 5-10 min. We tested biochemical activity in the slice following the same stimuli, and found that extracellular signal-regulated kinase type II (ERKII) but not CaMKII exhibits a peak at about 10 min. When calcium influx into the slice is buffered using AM-ester calcium dyes, amplitude of the physiological and biochemical response is reduced, but the timing is not shifted. We have previously used computer simulations of synaptic signalling to predict such temporal tuning from signalling pathways. In the current study we consider feedback and feedforward models that exhibit temporal tuning consistent with our experiments. We find that a model incorporating post-stimulus build-up of PKM zeta acting upstream of mitogen-activated protein kinase is sufficient to explain the observed temporal tuning. On the basis of these combined experimental and modelling results we propose that the dynamics of PKM activation and ERKII signalling may provide a mechanism for functionally important forms of synaptic pattern selectivity.

Inositol phosphates function as second messengers for a variety of extracellular signals. Ins(1,4,5)P(3) generated by phospholipase C-mediated hydrolysis of phosphatidylinositol bisphosphate, triggers numerous cellular processes by regulating calcium release from internal stores. The Ins(1,4,5)P(3) signal is coupled to a complex metabolic cascade involving a series of phosphatases and kinases. These enzymes generate a range of inositol phosphate derivatives, many of which have signaling roles of their own. We have integrated published biochemical data to build a mass action model for InsP(3) metabolism. The model includes most inositol phosphates that are currently known to interact with each other. We have used this model to study the effects of a G-protein coupled receptor stimulus that activates phospholipase C on the inositol phosphates. We have also monitored how the metabolic cascade interacts with Ins(1,4,5)P(3)-mediated calcium release. We find temporal dynamics of most inositol phosphates to be strongly influenced by the elaborate networking. We also show that Ins(1,3,4,5)P(4) plays a key role in InsP(3) dynamics and allows for paired pulse facilitation of calcium release. Calcium oscillations produce oscillatory responses in parts of the metabolic network and are in turn temporally modulated by the metabolism of InsP(3).