Long term time-lapse imaging reveals that individual synapses undergo significant structural remodeling not only when driven by activity, but also when network activity is absent, raising questions about how reliably individual synapses maintain connections.

Long-term, repeated measurements of individual synaptic properties have revealed that synapses can undergo significant directed and spontaneous changes over time scales of minutes to weeks. These changes are presumably driven by a large number of activity-dependent and independent molecular processes, yet how these processes integrate to determine the totality of synaptic size remains unknown. Here we propose, as an alternative to detailed, mechanistic descriptions, a statistical approach to synaptic size dynamics. The basic premise of this approach is that the integrated outcome of the myriad of processes that drive synaptic size dynamics are effectively described as a combination of multiplicative and additive processes, both of which are stochastic and taken from distributions parametrically affected by physiological signals. We show that this seemingly simple model, known in probability theory as the Kesten process, can generate rich dynamics which are qualitatively similar to the dynamics of individual glutamatergic synapses recorded in long-term time-lapse experiments in ex-vivo cortical networks. Moreover, we show that this stochastic model, which is insensitive to many of its underlying details, quantitatively captures the distributions of synaptic sizes measured in these experiments, the long-term stability of such distributions and their scaling in response to pharmacological manipulations. Finally, we show that the average kinetics of new postsynaptic density formation measured in such experiments is also faithfully captured by the same model. The model thus provides a useful framework for characterizing synapse size dynamics at steady state, during initial formation of such steady states, and during their convergence to new steady states following perturbations. These findings show the strength of a simple low dimensional statistical model to quantitatively describe synapse size dynamics as the integrated result of many underlying complex processes.

Pomegranate oil (PGO) is a unique and quite rare edible oil produced from Punica granatum L. seeds. It is considered to be a powerful health-benefiting agent, due to its antioxidative, anticancer, and antilipidemic properties. The aim of this study was to achieve a comprehensive and detailed profile of the different components of PGO. The fatty acid profile and phytosterol composition were determined by GC-MS; the triacylglycerol (TAG) compositions were profiled by the mass spectrometry tool of MALDI-TOF/MS. Results showed linolenic acid (18:3) to be the predominant fatty acid in the PGO (64-83%), as previously reported. The linolenic acid fraction was composed of four different chromatographically separated peaks that are assumed, according to MS data (based on both FAME and DMOX derivatization), to be attributed to different geometric isomers of conjugated linolenic acid (CLNA), punicic acid (18:3: 9-cis,11-trans,13-cis) being the major isomer. The MALDI-TOF/MS finger printing results showed the different TAG compositions present in the PGO, the major ones being LnLnLn and LnLnP. This unique PGO TAG fingerprint enables it to be differentiated from most other common edible oils. Phytosterols were found in quite a high concentration in the PGO (4089-6205 mg/kg), about 3-4-fold higher than in soybean oil. A detailed profile of the phytosterols in the PGO showed a wide variety, the major phytosterols being beta-sitosterol, campesterol, and stigmasterol. This study depicts a new detailed analysis of PGO, showing great potential for further research regarding the physiological effects of specific valuable components in pomegranate oil.

Cholinergic neuromodulation plays key roles in the regulation of neuronal excitability, network activity, arousal, and behavior. On longer time scales, cholinergic systems play essential roles in cortical development, maturation, and plasticity. Presumably, these processes are associated with substantial synaptic remodeling, yet to date, long-term relationships between cholinergic tone and synaptic remodeling remain largely unknown. Here we used automated microscopy combined with multielectrode array recordings to study long-term relationships between cholinergic tone, excitatory synapse remodeling, and network activity characteristics in networks of cortical neurons grown on multielectrode array substrates. Experimental elevations of cholinergic tone led to the abrupt suppression of episodic synchronous bursting activity (but not of general activity), followed by a gradual growth of excitatory synapses over hours. Subsequent blockage of cholinergic receptors led to an immediate restoration of synchronous bursting and the gradual reversal of synaptic growth. Neither synaptic growth nor downsizing was governed by multiplicative scaling rules. Instead, these occurred in a subset of synapses, irrespective of initial synaptic size. Synaptic growth seemed to depend on intrinsic network activity, but not on the degree to which bursting was suppressed. Intriguingly, sustained elevations of cholinergic tone were associated with a gradual recovery of synchronous bursting but not with a reversal of synaptic growth. These findings show that cholinergic tone can strongly affect synaptic remodeling and synchronous bursting activity, but do not support a strict coupling between the two. Finally, the reemergence of synchronous bursting in the presence of elevated cholinergic tone indicates that the capacity of cholinergic neuromodulation to indefinitely suppress synchronous bursting might be inherently limited.

The prefrontal cortex (PFC) plays an important role in regulating social functions in mammals, and impairments in this region have been linked with social dysfunction in psychiatric disorders. Yet little is known of how the PFC encodes social information and of how social representations may be altered in such disorders. Here, we show that neurons in the medial PFC (mPFC) of freely behaving mice preferentially respond to socially-relevant sensory cues. Population activity patterns in the mPFC differed considerably between social and nonsocial stimuli and underwent experience-dependent refinement. In Cntnap2 knockout mice, a genetic model of autism, both the categorization of sensory stimuli and the refinement of social representations were impaired.Noise levels in spontaneous population activity were higher in Cntnap2 mice, and correlated strongly with the degree to which social representations were disrupted. Our findings elucidate the encoding of social sensory cues in the mPFC, and provide an important link between altered prefrontal dynamics and autism-associated social dysfunction.