Different responses of mice and rats hippocampus CA1 pyramidal neurons to in vitro and in vivo-like inputs.

The fundamental role of any neuron within a network is to transform complex spatiotemporal synaptic input patterns into individual output spikes. These spikes, in turn, act as inputs for other neurons in the network. Neurons must execute this function across a diverse range of physiological conditions, often based on species-specific traits. Therefore, it is crucial to determine the extent to which findings can be extrapolated between species and, ultimately, to humans. In this study, we employed a multidisciplinary approach to pinpoint the factors accounting for the observed electrophysiological differences between mice and rats, the two species most used in experimental and computational research. After analyzing the morphological properties of their hippocampal CA1 pyramidal cells, we conducted a statistical comparison of rat and mouse electrophysiological features in response to somatic current injections. This analysis aimed to uncover the parameters underlying these distinctions. Using a well-established computational workflow, we created ten distinct single-cell computational models of mouse CA1 pyramidal neurons, ready to be used in a full-scale hippocampal circuit. By comparing their responses to a variety of somatic and synaptic inputs with those of rat models, we generated experimentally testable hypotheses regarding species-specific differences in ion channel distribution, kinetics, and the electrophysiological mechanisms underlying their distinct responses to synaptic inputs during the behaviorally relevant Gamma and Sharp-Wave rhythms.

Engram cell connectivity as a mechanism for information encoding and memory function.

Information derived from experiences is incorporated into the brain as changes to ensembles of cells, termed engram cells, which allow memory storage and recall. The mechanism by which those changes hold specific information is unclear. Here, we test the hypothesis that the specific synaptic wiring between engram cells is the substrate of information storage. First, we monitor how learning modifies the connectivity pattern between engram cells at a monosynaptic connection involving the hippocampal ventral CA1 (vCA1) region and the amygdala. Then, we assess the functional significance of these connectivity changes by artificially activating or inhibiting its presynaptic and postsynaptic components, respectively. Finally, we identify a synaptic plasticity mechanism mediated by postsynaptic density protein 95 (PSD-95), which impacts the connectivity pattern among engram cells and contributes to the long-term stability of the memory. These findings impact our theory of learning and memory by helping us explain the translation of specific information into engram cells and how these connections shape brain function.

Engram cell connectivity as a mechanism for information encoding and memory function.

Information derived from experiences is incorporated into the brain as changes to ensembles of cells, termed engram cells, that allow memory storage and recall. The mechanism by which those changes hold specific information is unclear. Here we test the hypothesis that the specific synaptic wiring between engram cells is the substrate of information storage. First, we monitor how learning modifies the connectivity pattern between engram cells at a monosynaptic connection involving the hippocampal vCA1 region and the amygdala. Then, we assess the functional significance of these connectivity changes by artificially activating or inhibiting its presynaptic and postsynaptic components respectively. Finally, we identify a synaptic plasticity mechanism mediated by PSD-95, which impacts the connectivity pattern among engram cells and contributes to the long-term stability of the memory. These findings impact our theory of learning and memory by helping us explain the translation of specific information into engram cells and how these connections shape brain function.

Neuronal growth on high-aspect-ratio diamond nanopillar arrays for biosensing applications.

Monitoring neuronal activity with simultaneously high spatial and temporal resolution in living cell cultures is crucial to advance understanding of the development and functioning of our brain, and to gain further insights in the origin of brain disorders. While it has been demonstrated that the quantum sensing capabilities of nitrogen-vacancy (NV) centers in diamond allow real time detection of action potentials from large neurons in marine invertebrates, quantum monitoring of mammalian neurons (presenting much smaller dimensions and thus producing much lower signal and requiring higher spatial resolution) has hitherto remained elusive. In this context, diamond nanostructuring can offer the opportunity to boost the diamond platform sensitivity to the required level. However, a comprehensive analysis of the impact of a nanostructured diamond surface on the neuronal viability and growth was lacking. Here, we pattern a single crystal diamond surface with large-scale nanopillar arrays and we successfully demonstrate growth of a network of living and functional primary mouse hippocampal neurons on it. Our study on geometrical parameters reveals preferential growth along the nanopillar grid axes with excellent physical contact between cell membrane and nanopillar apex. Our results suggest that neuron growth can be tailored on diamond nanopillars to realize a nanophotonic quantum sensing platform for wide-field and label-free neuronal activity recording with sub-cellular resolution.

Engram cell connectivity: an evolving substrate for information storage.

Understanding memory requires an explanation for how information can be stored in the brain in a stable state. The change in the brain that accounts for a given memory is referred to as an engram. In recent years, the term engram has been operationalized as the cells that are activated by a learning experience, undergoes plasticity, and are sufficient and necessary for memory recall. Using this framework, and a growing toolbox of related experimental techniques, engram manipulation has become a central topic in behavioral, systems, and molecular neuroscience. Recent research on the topic has provided novel insights into the mechanisms of long-term memory storage, and its overlap with instinct. We propose that memory and instinct may be embodied as isomorphic topological structures within the brain's microanatomical circuitry.

The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow.

Every neuron is part of a network, exerting its function by transforming multiple spatiotemporal synaptic input patterns into a single spiking output. This function is specified by the particular shape and passive electrical properties of the neuronal membrane, and the composition and spatial distribution of ion channels across its processes. For a variety of physiological or pathological reasons, the intrinsic input/output function may change during a neuron's lifetime. This process results in high variability in the peak specific conductance of ion channels in individual neurons. The mechanisms responsible for this variability are not well understood, although there are clear indications from experiments and modeling that degeneracy and correlation among multiple channels may be involved. Here, we studied this issue in biophysical models of hippocampal CA1 pyramidal neurons and interneurons. Using a unified data-driven simulation workflow and starting from a set of experimental recordings and morphological reconstructions obtained from rats, we built and analyzed several ensembles of morphologically and biophysically accurate single cell models with intrinsic electrophysiological properties consistent with experimental findings. The results suggest that the set of conductances expressed in any given hippocampal neuron may be considered as belonging to two groups: one subset is responsible for the major characteristics of the firing behavior in each population and the other is responsible for a robust degeneracy. Analysis of the model neurons suggests several experimentally testable predictions related to the combination and relative proportion of the different conductances that should be expressed on the membrane of different types of neurons for them to fulfill their role in the hippocampus circuitry.

Anti-obesity and anti-hyperglycemic effects of cinnamaldehyde via altered ghrelin secretion and functional impact on food intake and gastric emptying.

Cinnamon extract is associated to different health benefits but the active ingredients or pathways are unknown. Cinnamaldehyde (CIN) imparts the characteristic flavor to cinnamon and is known to be the main agonist of transient receptor potential-ankyrin receptor 1 (TRPA1). Here, expression of TRPA1 in epithelial mouse stomach cells is described. After receiving a single-dose of CIN, mice significantly reduce cumulative food intake and gastric emptying rates. Co-localization of TRPA1 and ghrelin in enteroendocrine cells of the duodenum is observed both in vivo and in the MGN3-1 cell line, a ghrelin secreting cell model, where incubation with CIN up-regulates expression of TRPA1 and Insulin receptor genes. Ghrelin secreted in the culture medium was quantified following CIN stimulation and we observe that octanoyl and total ghrelin are significantly lower than in control conditions. Additionally, obese mice fed for five weeks with CIN-containing diet significantly reduce their cumulative body weight gain and improve glucose tolerance without detectable modification of insulin secretion. Finally, in adipose tissue up-regulation of genes related to fatty acid oxidation was observed. Taken together, the results confirm anti-hyperglycemic and anti-obesity effects of CIN opening a new approach to investigate how certain spice derived compounds regulate endogenous ghrelin release for therapeutic intervention.

Dampened neural activity and abolition of epileptic-like activity in cortical slices by active ingredients of spices.

Active ingredients of spices (AIS) modulate neural response in the peripheral nervous system, mainly through interaction with TRP channel/receptors. The present study explores how different AIS modulate neural response in layer 5 pyramidal neurons of S1 neocortex. The AIS tested are agonists of TRPV1/3, TRPM8 or TRPA1. Our results demonstrate that capsaicin, eugenol, menthol, icilin and cinnamaldehyde, but not AITC dampen the generation of APs in a voltage- and time-dependent manner. This effect was further tested for the TRPM8 ligands in the presence of a TRPM8 blocker (BCTC) and on TRPM8 KO mice. The observable effect was still present. Finally, the influence of the selected AIS was tested on in vitro gabazine-induced seizures. Results coincide with the above observations: except for cinnamaldehyde, the same AIS were able to reduce the number, duration of the AP bursts and increase the concentration of gabazine needed to elicit them. In conclusion, our data suggests that some of these AIS can modulate glutamatergic neurons in the brain through a TRP-independent pathway, regardless of whether the neurons are stimulated intracellularly or by hyperactive microcircuitry.

Electrical resonance in the θ frequency range in olfactory amygdala neurons.

The cortical amygdala receives direct olfactory inputs and is thought to participate in processing and learning of biologically relevant olfactory cues. As for other brain structures implicated in learning, the principal neurons of the anterior cortical nucleus (ACo) exhibit intrinsic subthreshold membrane potential oscillations in the θ-frequency range. Here we show that nearly 50% of ACo layer II neurons also display electrical resonance, consisting of selective responsiveness to stimuli of a preferential frequency (2-6 Hz). Their impedance profile resembles an electrical band-pass filter with a peak at the preferred frequency, in contrast to the low-pass filter properties of other neurons. Most ACo resonant neurons displayed frequency preference along the whole subthreshold voltage range. We used pharmacological tools to identify the voltage-dependent conductances implicated in resonance. A hyperpolarization-activated cationic current depending on HCN channels underlies resonance at resting and hyperpolarized potentials; notably, this current also participates in resonance at depolarized subthreshold voltages. KV7/KCNQ K+ channels also contribute to resonant behavior at depolarized potentials, but not in all resonant cells. Moreover, resonance was strongly attenuated after blockade of voltage-dependent persistent Na+ channels, suggesting an amplifying role. Remarkably, resonant neurons presented a higher firing probability for stimuli of the preferred frequency. To fully understand the mechanisms underlying resonance in these neurons, we developed a comprehensive conductance-based model including the aforementioned and leak conductances, as well as Hodgkin and Huxley-type channels. The model reproduces the resonant impedance profile and our pharmacological results, allowing a quantitative evaluation of the contribution of each conductance to resonance. It also replicates selective spiking at the resonant frequency and allows a prediction of the temperature-dependent shift in resonance frequency. Our results provide a complete characterization of the resonant behavior of olfactory amygdala neurons and shed light on a putative mechanism for network activity coordination in the intact brain.