An Emergent Neural Coactivity Code for Dynamic Memory

Coincidental spike discharge amongst distributed groups of neurons is thought to provide an efficient mechanism for encoding percepts, actions and cognitive processes1–3. Short timescale coactivity can indeed bind neurons with similar tuning, giving rise to robust representations congruent with those of the participating neurons4–6. Alternatively, coactivity may also play a role in information processing through encoding variables not represented by individual neurons. While this type of emergent coactivity-based coding has been described for physically well-defined variables, including percepts and actions7–10, its role in encoding abstract cognitive variables remains unknown. Coactivity-based representation could provide a flexible code in dynamic environments, where animals must regularly learn short-lived behavioural contingencies. Here, we tested this possibility by training mice to discriminate two new behavioural contingencies every day, while monitoring and manipulating neural ensembles in the hippocampal CA1. We found that, while the spiking of neurons within their place fields is organised into congruent coactivity patterns representing discrete locations during unsupervised exploration of the learning enclosure, additional neurons synchronised their activity into spatially-untuned patterns that discriminated opposing learning contingencies. This contingency discrimination was an emergent property of millisecond timescale coactivity rather than the tuning of individual neurons, and predicted trial-by-trial memory performance. Moreover, optogenetic suppression of plastic inputs from the upstream left CA3 region during learning selectively impaired the computation of contingency-discriminating, but not space-representing CA1 coactivity patterns. This manipulation, but not silencing the more stable right CA3 inputs, impaired memory of the contingency discrimination. Thus, the computation of an emergent, coactivity-based discrimination code necessitates plastic synapses and supports dynamic, two-contingency memory.

Synaptic and intrinsic plasticity coordinate spike output in cerebellar Purkinje cells

SummaryLearning has been thought to be implemented by activity-dependent modifications of synaptic weight and intrinsic excitability. Here, we highlight how long-term depression at parallel fiber to Purkinje cell synapses (PF-PC LTD) and intrinsic plasticity of PCs coordinate the postsynaptic spike discharge from C57BL/6 male mice. Intrinsic plasticity of PCs in the flocculus matched the timing rules and shared intracellular signaling for PF-PC LTD. Notably, the intrinsic plasticity was confined to the dendritic branches where the synaptic plasticity is formed. Besides, when either synaptic or intrinsic plasticity was impaired, the impact of PF inputs was less reflected by the spike output of PCs. In conclusion, synergies between synaptic and intrinsic plasticity may play a role in tuning the PC output, thereby achieving optimal ranges of output.

In vivo beta and gamma subthreshold oscillations in rat mitral cells: origin and gating by respiratory dynamics

In mammals, olfactory bulb (OB) dynamics are paced by slow and fast oscillatory rhythms at multiple levels: local field potential, spike discharge, and/or membrane potential oscillations. Interactions between these levels have been well studied for the slow rhythm linked to animal respiration. However, less is known regarding rhythms in the fast beta (10–35 Hz) and gamma (35–100 Hz) frequency ranges, particularly at the membrane potential level. Using a combination of intracellular and extracellular recordings in the OB of freely breathing rats, we show that beta and gamma subthreshold oscillations (STOs) coexist intracellularly and are related to extracellular local field potential (LFP) oscillations in the same frequency range. However, they are differentially affected by changes in cell excitability and by odor stimulation. This leads us to suggest that beta and gamma STOs may rely on distinct mechanisms: gamma STOs would mainly depend on mitral cell intrinsic resonance, while beta STOs could be mainly driven by synaptic activity. In a second study, we find that STO occurrence and timing are constrained by the influence of the slow respiratory rhythm on mitral and tufted cells. First, respiratory-driven excitation seems to favor gamma STOs, while respiratory-driven inhibition favors beta STOs. Second, the respiratory rhythm is needed at the subthreshold level to lock gamma and beta STOs in similar phases as their LFP counterparts and to favor the correlation between STO frequency and spike discharge. Overall, this study helps us to understand how the interaction between slow and fast rhythms at all levels of OB dynamics shapes its functional output. NEW & NOTEWORTHY In the mammalian olfactory bulb of a freely breathing anesthetized rat, we show that both beta and gamma membrane potential fast oscillation ranges exist in the same mitral and tufted (M/T) cell. Importantly, our results suggest they have different origins and that their interaction with the slow subthreshold oscillation (respiratory rhythm) is a key mechanism to organize their dynamics, favoring their functional implication in olfactory bulb information processing.

Spike discharge prediction based on Neuro-fuzzy system

This paper presents the development and evaluation of different versions of Neuro-Fuzzy model for prediction of spike discharge patterns. We aim to predict the spike discharge variation using first spike latency and frequency-following interval. In order to study the spike discharge dynamics, we analyzed the Cerebral Cortex data of the cat from [29]. Adaptive Neuro-Fuzzy Inference Systems (ANFIS), Wang and Mendel (WM), Dynamic evolving neural-fuzzy inference system (DENFIS), Hybrid neural Fuzzy Inference System (HyFIS), genetic for lateral tuning and rule selection of linguistic fuzzy system (GFS.LT.RS) and subtractive clustering and fuzzy c-means (SBC) algorithms are applied for data. Among these algorithms, ANFIS and GFS.LT.RS models have better performance. On the other hand, ANFIS and GFS.LT.RS algorithms can be used to predict the spike discharge dynamics as a function of first spike latency and frequency with a higher accuracy compared to other algorithms.

Electroencephalogram and clinical manifestations of Rett syndrome in children

Background Rett Syndrome (RS) is a severe neurodevelopmentaldisorder. Epileptic seizures occur in 80-90%; grandmal, psychomo-tor (complex partial), and focal motor seizures have been reported.The electroencephalogram(EEG) is almost always abnormal.Objective This study aimed to investigate the EEG and clinicalmanifestations of children with RSResults We investigated EEG on 5 patients with RS aged 30–66month. One patient was in clinical stage II and 4 patients in clini-cal stage III. Four patients had history of seizures, however onlytwo patients suffered from epilepsy. The EEG demonstrated slow-ing background activity in occipital region in two patients. In addi-tion, epileptic form activities were observed in 4 of 5 patients.Conclusion We concluded that epileptic spike discharge with orwithout clinical seizures were found in almost all of our RS pa-tients. These paroxysmal discharges suggested the process andthe sequences of cortical involvement. Compelling clinical, neuro-physiological evidences were very important to decide the stageof Rett disorder