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A lot of efforts have been made to understand the structure and function of neocortical circuits. In fact, a promising way to understand the functions of cortical circuits is the classification of the neural types, based on their different properties. Recent studies focused on applying modern computational methods to classify neurons based on molec...
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... were digitized using NI-DAQ board (PCI-MIO-16E-4, National Instruments) and acquired using custom-made LabVIEW software. The block diagram of our proposed method is shown in Figure 1. It consists of two procedures namely as the cluster analysis and the classification of cell types. ...
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Cortical representations underlying many cognitive abilities emerge from underlying circuits with several different cell types. However, cell type-specific contributions to rate and timing-based cortical coding are not well-understood. Here, we investigate the role of parvalbumin (PV) neurons in cortical complex scene analysis. Many complex scenes...
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... Two-step cluster analysis (Vaden et al. 2020) was performed on the dataset using eight electrophysiological parameters, including resting membrane potential (Vm), membrane capacitance (Cm), membrane input resistance (Rm), action potential (AP) rheobase, AP threshold, AP amplitude, AP width, and negative dV/dt peak, in addition to soma diameter and AP shape, which resulted in five clusters. Explorative factor analysis (principal component method) was then performed (David et al. 2007;Ghaderi et al. 2018) on the five clusters to identify which of the extracted electrophysiological parameters best clustered individual cells (Figure 1(c)-(e)). Factor analysis served as an independent measurement since the procedure is naïve to number of clusters and membership. ...
The role of Aβ-afferents in somatosensory function is often oversimplified as low threshold mechanoreceptors (LTMRs) with large omission of Aβ-afferent involvement in nociception. Recently, we have characterized Aβ-afferent neurons which have large diameter somas in the trigeminal ganglion (TG) and classified them into non-nociceptive and nociceptive-like TG afferent neurons based on their electrophysiological properties. Here, we extend our previous observations to further characterize electrophysiological properties of trigeminal Aβ-afferent neurons and investigate their mechanical and chemical sensitivity by patch-clamp recordings from large-diameter TG neurons in ex vivo TG preparations of adult male and female rats. Based on cluster analysis of electrophysiological properties, trigeminal Aβ-afferent neurons can be classified into five discrete types (type I, IIa, IIb, IIIa, and IIIb), which responded differentially to mechanical stimulation and sensory mediators including serotonin (5-HT), acetylcholine (ACh) and adenosine triphosphate (ATP). Notably, type I neuron action potential (AP) was small in amplitude, width was narrow in duration, and peak dV/dt repolarization was great with no deflection observed, whereas discretely graded differences were observed for type IIa, IIb, IIIa, and IIIb, as AP increased in amplitude, width broadened in duration, and peak dV/dt repolarization reduced with the emergence of increasing deflection. Type I, IIa, and IIb neurons were mostly mechanically sensitive, displaying robust and rapidly adapting mechanically activated current (IMA) in response to membrane displacement, while IIIa and IIIb, conversely, were almost all mechanically insensitive. Interestingly, mechanical insensitivity coincided with increased sensitivity to 5-HT and ACh. Together, type I, IIa and IIb display features of LTMR Aβ-afferent neurons while type IIIa and type IIIb show properties of nociceptive Aβ-afferent neurons.
... corticotropin releasing hormone | medial prefrontal cortex | novelty exploration | sexual dimorphic | circuit modulation Transcriptional and epigenetic profiling of cell types in mouse (1,2) and human brains (3,4) has refined our appreciation of the histological complexity of the cerebral cortex first documented more than a century ago (5). Although it has been demonstrated that the cortex is composed of scores of molecularly distinct cell classes with different electrophysiological properties (6)(7)(8)(9), our knowledge of the roles of these cell types in behavior is incomplete. For example, despite the facts that neuropeptides and their receptors are amongst the most diverse and cell-type restricted molecules in the cerebral cortex (10) and the fundamental roles of neuromodulation in all species (11,12), our knowledge of the cell types expressing these factors and of the functions of neuropeptides in the cerebral cortex are just beginning to emerge. ...
Neuromodulatory substances can be released from distal afferents for communication between brain structures or produced locally to modulate neighboring circuit elements. Corticotropin-releasing hormone (CRH) from long-range neurons in the hypothalamus projecting to the medial prefrontal cortex (mPFC) has been shown to induce anxiety-like behaviors. However, the role of CRH produced in the mPFC has not been investigated. Here we demonstrate that a specific class of mPFC interneurons that express CRH (CrhINs) releases CRH upon high-frequency stimulation to enhance excitability of layer 2/3 pyramidal cells (L2/3 PCs) expressing the CRH receptors. When stimulated at low frequency, CrhINs release GABA resulting in the inhibition of oxytocin receptor-expressing interneurons (OxtrINs) and L2/3 PCs. Conditional deletion of CRH in mPFC CrhINs and chemogenetic activation of CrhINs have opposite effects on novelty exploration in male but not in female mice, and do not affect anxiety-related behaviors in either males or females. Our data reveal that CRH produced by local interneurons in the mPFC is required for sex-specific novelty exploration and suggest that our understanding of complex behaviors may require knowledge of local and remote neuromodulatory action.
... Besides, the waveform cluster analysis showed that putative survival units were wider than despair ones (Figures 4B,C). It suggests the existence of PV+ subtypes in DRN, although this kind of studies is usually performed in the forebrain cortex (Helm et al., 2013;Ghaderi et al., 2018). In other words, there are more complicated neural networks of local inhibitory neurons' subtypes which participated in the balancing regulation in DRN, and thus further exploration needs to be conducted. ...
The dorsal raphe nucleus (DRN) is a major source of serotonin in the central nervous system, which is closely related to depression-like behaviors and is modulated by local GABAergic interneurons. Although serotonin neurons are known to be activated by struggling behavior in tail suspension test (TST), the exact electrophysiological characteristics are still unclear. Here, we combined in vivo electrode recording and behavioral test to explore the mice neuron electrophysiology in DRN during TST and observed that gamma oscillation was related to despair-like behaviors whereas burst fraction was crucial for survival-like behaviors. We reported the identification of a subpopulation of DRN neurons which change their firing rates when mice get into and during TST immobile states. Both increase (putative despair units, D units for short) and decrease (putative survival units, S units for short) in firing rate were observed. Furthermore, using optogenetics to identify parvalbumin-positive (PV+) and serotonin transporter-positive (SERT+) neurons, we found that SERT+ neurons were almost S units. Interestingly, those that have been identified PV+ neurons include ~20% of D units and ~50% of S units. These results suggest that electrophysiological characteristics incorporated in despair-like behavior studies can provide new insight into the study of anti-depression targets, and GABAergic interneuron is a complex key hub to the coding and regulation of local neural network.
... Planar lipid bilayer preparation and electrical measurements. The whole-cell patch-clamp technique was conducted by the methods of Ghaderi 13 . The whole-cell patch-clamp technique was employed at room temperature (23-25 °C) to measure ionic currents. ...
Peri-implantitis is a common reversible disease after tooth implantation, caused by a variety of pathogenic microorganisms. Based on non-surgical or surgical treatment principles, supplementation by local or systemic drugs might enhance treatment efficacy. Porphyromonas gingivalis (Pg) (ATCC 33,277) and Prevotella intermedius (Pi) (ATCC 25,611) were used as test strains. The effects of Pln 149 on the biofilm formation and growth of four periodontal pathogens were evaluated by RT-PCR, fluorescence microscopy, and scanning electron microscopy. The antibacterial mechanism was tested by the patch-clamp technique. The cytotoxicity of Pln 149 (125 µg/ml) to bone marrow stromal cell (BMSC) was assessed using an MTT assay. Pln 149 exhibited significant inhibitory effects on Pg and Pi (P < 0.05), with significant differences in the biofilm images of fluorescence microscope and scanning electron microscope (P < 0.05). Pln 149 could change the sodium channel currents and exerted no cytotoxicity on bone marrow stromal cell. Pln 149 could inhibit the biofilm formation and growth of periodontal pathogens. Considering the absence of antimicrobial resistance and cytotoxicity, we suggest that the Pln 149 from Lactobacillus plantarum 149 might be a promising option for managing peri-implantitis.
... Spike Sorting and cell-type classification are two of the most critical data analysis problems in neuroscience and have received a lot of attention in the literature. Some interesting references about Spike Sorting are [24,44,45], whereas [2,13,46] address cell-type classification. Besides, it is worth mentioning other more complex related problems such as multi-channel Spike Sorting and the function identification of neurons in brain circuits. ...
The Hodgkin-Huxley model, decades after its first presentation, is still a reference model in neuroscience as it has successfully reproduced the electrophysiological activity of many organisms. The primary signal in the model represents the membrane potential of a neuron. A simple representation of this signal is presented in this paper. The new proposal is an adapted Frequency Modulated Möbius multicomponent model defined as a signal plus error model in which the signal is decomposed as a sum of waves. The main strengths of the method are the simple parametric formulation, the interpretability and flexibility of the parameters that describe and discriminate the waveforms, the estimators’ identifiability and accuracy, and the robustness against noise. The approach is validated with a broad simulation experiment of Hodgkin-Huxley signals and real data from squid giant axons. Interesting differences between simulated and real data emerge from the comparison of the parameter configurations. Furthermore, the potential of the FMM parameters to predict Hodgkin-Huxley model parameters is shown using different Machine Learning methods. Finally, promising contributions of the approach in Spike Sorting and cell-type classification are detailed.
... from single RNA sequencing are presented. Electrophysiological taxonomies are predominantly based on patch-clamp recordings of neuron membrane potential signals that contain action potential curves (APs), as is done in Ghaderi et al. (2018) and Teeter et al. (2018). Furthermore, Gouwens et al. (2019) presents a taxonomy based on the combination of electrophysiological and morphological features, while part of this taxonomy is expanded with transcriptomic features in Gouwens et al. (2020). ...
... However, the features traditionally used in this type of taxonomy lack interpretability as they are not directly related to the observed potential difference signal. Most of these studies extract the features with dimensional reducing techniques (as is the case of Ghaderi et al., 2018or Gouwens et al., 2019 or the features are model parameters such as the leaky integrate and fire models (as in Teeter et al., 2018). A brief overview of the latter models can be found in Lynch and Houghton (2015). ...
The complete understanding of the mammalian brain requires exact knowledge of the function of each neuron subpopulation composing its parts. To achieve this goal, an exhaustive, precise, reproducible, and robust neuronal taxonomy should be defined. In this paper, a new circular taxonomy based on transcriptomic features and novel electrophysiological features is proposed. The approach is validated by analysing more than 1850 electrophysiological signals of different mouse visual cortex neurons proceeding from the Allen Cell Types database. The study is conducted on two different levels: neurons and their cell-type aggregation into Cre lines. At the neuronal level, electrophysiological features have been extracted with a promising model that has already proved its worth in neuronal dynamics. At the Cre line level, electrophysiological and transcriptomic features are joined on cell types with available genetic information. A taxonomy with a circular order is revealed by a simple transformation of the first two principal components that allow the characterization of the different Cre lines. Moreover, the proposed methodology locates other Cre lines in the taxonomy that do not have transcriptomic features available. Finally, the taxonomy is validated by Machine Learning methods which are able to discriminate the different neuron types with the proposed electrophysiological features.
... The internal solution had the osmolarity of 280-290 mOsm and adjusted its pH with KOH to 7.2-7.4, which is equivalent to the intracellular environment, and its compounds were (in mM): CaCl2, 0.1; MgATP, 4; K-Gluconate, 130; Na3GTP, 0.3; HEPES, 10; EGTA, 1; Na-Phosphocreatine, 10 and MgCl2, 2 (Safari et al., 2017) (Ghaderi et al., 2018). The resistance of these electrodes with the internal solution was 6-8 MΏ. we recorded neuronal membrane potentials in current-clamp mode using the Axopatch 200B amplifier. ...
Introduction: Sensory processing is profoundly regulated by brain neuromodulatory systems. One of the main neuromodulators is serotonin which influences higher cognitive functions such as different aspects of perceptual processing. So, malfunction in the serotonergic system may lead to visual illusion in psychiatric disorders such as autism and schizophrenia. In this work, we examined the serotonergic modulation of visual responses of neurons to stimulus orientation in the primary visual cortex. Methods: Eight-weeks old naive mice were anesthetized and craniotomy was done on the region of interest in primary visual cortex. Spontaneous and visual-evoked activities of neurons were recorded before and during the electrical stimulation of dorsal raphe nucleus using in vivo whole-cell patch-clamp recording. Square-wave grating of 12 orientations was presented. Data was analyzed and Wilcoxon signed-rank test, used in order to compare the data of two conditions that belong to the same neurons, with or without electrical stimulation. Results: The serotonergic system changed orientation tuning of about 60 % recorded neurons by decreasing the mean firing rate in two independent visual response components: gain and baseline response. It also increased mean firing rate in a small number of neurons (about 20%). Beyond that, it left the preferred orientation and sensitivity of neurons unchanged. Conclusion: However, serotonergic modulation showed a bi-directional effect; it seems to cause predominately divisive and subtractive decreases in the visual responses of the neurons in the primary visual cortex that can modify the balance between internal and external sensory signals and result in disorders.
... These summarized findings suggest that there are subtypes of narrow spiking neurons that are particularly important to regulate prefrontal circuit functions, raising the question to which subtypes they belong. Comparison of protein expression with spike-width have shown for prefrontal cortex that >95% of all PV and ~87% of all SOM interneurons show narrow spike width (Ghaderi et al., 2018;Torres-Gomez et al., 2020), while narrow spikes are also known to occur in ~20% of VIP interneurons (Torres-Gomez et al., 2020) among other GABAergic neurons (Krimer et al., 2005;Zaitsev et al., 2009), and in (at least in motor cortex) in a subgroup of pyramidal cells (Soares et al., 2017). In addition, electrophysiological characterization have shown at least three different types of firing patterns in narrow spiking neurons of monkeys during attention demanding task Dasilva et al., 2019;Trainito et al., 2019). ...
Interneurons are believed to realize critical gating functions in cortical circuits, but it has been difficult to ascertain the underlying type of interneuron and the content of gated information in primate cortex. Here, we address these questions by characterizing subclasses of interneurons in primate prefrontal and anterior cingulate cortex while monkeys engaged in attention demanding reversal learning. We find that subclasses of narrow spiking neurons exert a net suppressive influence on the local circuits indicating they are inhibitory. These putative interneurons encoded area-specific information showing in prefrontal cortex stronger encoding of choice probabilities, and in anterior cingulate cortex stronger encoding of reward prediction errors. These functional correlations were evident not in all putative interneurons but in one of three sub-classes of narrow spiking neuron. This same putative interneuron subclass also gamma - synchronized (35-45 Hz) while encoding choice probabilities in prefrontal cortex, and reward prediction errors in anterior cingulate cortex. These results suggest that a particular interneuron subtype forms networks in LPFC and in ACC that synchronize similarly but nevertheless realize a different area specific computation. In the reversal learning task, these interneuron-specific computations were (i) the gating of values into choice probabilities in LPFC and (ii) the gating of chosen values and reward into a prediction error in ACC. This finding implies that the same type of interneuron plays an important role for controlling local area transformations during learning in different brain areas of the nonhuman primate cortex.
... Traditional approaches differentiated putative interneurons and excitatory neurons based on characteristic shapes of the action potential waveform and interspike interval histograms. More recent work has taken this a step further, distinguishing functionally different cell types using data-driven approaches (Buccino et al., 2018;Ghaderi et al., 2018;Trainito et al., 2019;Mosher et al., 2020), although it remains to be seen whether these classifiers are helpful in distinguishing pathological microcircuit dynamics associated with diseases such as epilepsy. ...
With their ‘all-or-none’ action potential responses, single neurons (or units) are accepted as the basic computational unit of the brain. There is extensive animal literature to support the mechanistic importance of studying neuronal firing as a way to understand neuronal microcircuits and brain function. Although most studies have emphasized physiology, there is increasing recognition that studying single units provides novel insight into system level mechanisms of disease.
Microelectrode recordings are becoming more common in humans, paralleling the increasing use of intracranial electroencephalography recordings in the context of presurgical evaluation in focal epilepsy. In addition to single unit data, microelectrode recordings also record local field potentials and high frequency oscillations, some of which may be different to that recorded by clinical macroelectrodes. However, microelectrodes are being used almost exclusively in research contexts and there are currently no indications for incorporating microelectrode recordings into routine clinical care.
In this review, we summarise the lessons learnt from 65 years of microelectrode recordings in human epilepsy patients. We cover the electrode constructs that can be utilised, principles of how to record and process microelectrode data as well as insights into ictal dynamics, interictal dynamics and cognition. We end with a critique on the possibilities of incorporating single unit recordings into clinical care, with a focus on potential clinical indications, each with their specific evidence base and challenges.
... Spike width (NS and BS) has been used to classify macaque monkey neurons in several brain areas into putative interneurons and P cells (Mitchell et al. 2007;Hussar and Pasternak 2009) as well as mouse neurons into P cells, PV, and SST (Ghaderi et al. 2018). However, some studies have shown that some inhibitory interneurons are BS (Casale et al. 2015) and some P cells can be NS (Vigneswaran et al. 2011). ...
Neuronal spiking activity encoding working memory (WM) is robust in primate association cortices but weak or absent in early sensory cortices. This may be linked to changes in the proportion of neuronal types across areas that influence circuits' ability to generate recurrent excitation. We recorded neuronal activity from areas middle temporal (MT), medial superior temporal (MST), and the lateral prefrontal cortex (LPFC) of monkeys performing a WM task and classified neurons as narrow (NS) and broad spiking (BS). The ratio NS/BS decreased from MT > MST > LPFC. We analyzed the Allen Institute database of ex vivo mice/human intracellular recordings to interpret our data. Our analysis suggests that NS neurons correspond to parvalbumin (PV) or somatostatin (SST) interneurons while BS neurons are pyramidal (P) cells or vasoactive intestinal peptide (VIP) interneurons. We labeled neurons in monkey tissue sections of MT/MST and LPFC and found that the proportion of PV in cortical layers 2/3 decreased, while the proportion of CR cells increased from MT/MST to LPFC. Assuming that primate CR/CB/PV cells perform similar computations as mice VIP/SST/PV cells, our results suggest that changes in the proportion of CR and PV neurons in layers 2/3 cells may favor the emergence of activity encoding WM in association areas.
