Cellular Classes in the Human Brain Revealed In Vivo by Heartbeat-Related Modulation of the Extracellular Action Potential Waveform

Determining cell types is critical for understanding neural circuits but remains elusive in the living human brain. Current approaches discriminate units into putative cell classes using features of the extracellular action potential (EAP); in absence of ground truth data, this remains a problematic procedure. We find that EAPs in deep structures of the brain exhibit robust and systematic variability during the cardiac cycle. These cardiac-related features refine neural classification. We use these features to link bio-realistic models generated from in vitro human whole-cell recordings of morphologically classified neurons to in vivo recordings. We differentiate aspiny inhibitory and spiny excitatory human hippocampal neurons and, in a second stage, demonstrate that cardiac-motion features reveal two types of spiny neurons with distinct intrinsic electrophysiological properties and phase-locking characteristics to endogenous oscillations. This multi-modal approach markedly improves cell classification in humans, offers interpretable cell classes, and is applicable to other brain areas and species

Electrophysiological Heterogeneity of Fast-Spiking Interneurons: Chandelier versus Basket Cells

In the prefrontal cortex, parvalbumin-positive inhibitory neurons play a prominent role in the neural circuitry that subserves working memory, and alterations in these neurons contribute to the pathophysiology of schizophrenia. Two morphologically distinct classes of parvalbumin neurons that target the perisomatic region of pyramidal neurons, chandelier cells (ChCs) and basket cells (BCs), are generally thought to have the same "fast-spiking" phenotype, which is characterized by a short action potential and high frequency firing without adaptation. However, findings from studies in different species suggest that certain electrophysiological membrane properties might differ between these two cell classes. In this study, we assessed the physiological heterogeneity of fast-spiking interneurons as a function of two factors: species (macaque monkey vs. rat) and morphology (chandelier vs. basket). We showed previously that electrophysiological membrane properties of BCs differ between these two species. Here, for the first time, we report differences in ChCs membrane properties between monkey and rat. We also found that a number of membrane properties differentiate ChCs from BCs. Some of these differences were species-independent (e.g., fast and medium afterhyperpolarization, firing frequency, and depolarizing sag), whereas the differences in the first spike latency between ChCs and BCs were species-specific. Our findings indicate that different combinations of electrophysiological membrane properties distinguish ChCs from BCs in rodents and primates. Such electrophysiological differences between ChCs and BCs likely contribute to their distinctive roles in cortical circuitry in each species. © 2013 Povysheva et al

Specificity of Synaptic Connectivity between Layer 1 Inhibitory Interneurons and Layer 2/3 Pyramidal Neurons in the Rat Neocortex

Understanding the structure and function of the neocortical microcircuit requires a description of the synaptic connectivity between identified neuronal populations. Here, we investigate the electrophysiological properties of layer 1 (L1) neurons of the rat somatosensory neocortex (postnatal day 24–36) and their synaptic connectivity with supragranular pyramidal neurons. The active and passive properties of visually identified L1 neurons (n = 266) suggested division into 4 groups according to the Petilla classification scheme with characteristics of neurogliaform cells (NGFCs) (n = 72), classical-accommodating (n = 137), fast-spiking (n = 23), and burst-spiking neurons (n = 34). Anatomical reconstructions of L1 neurons supported the existence of 4 major neuronal groups. Multiparameter unsupervised cluster analysis confirmed the existence of 4 groups, revealing a high degree of similarity with the Petilla scheme. Simultaneous recordings between synaptically connected L1 neurons and L2/3 pyramidal neurons (n = 384) demonstrated neuronal class specificity in both excitatory and inhibitory connectivity and the properties of synaptic potentials. Notably, all groups of L1 neurons received monosynaptic excitatory input from L2/3 pyramidal neurons (n = 33), with the exception of NGFCs (n = 68 pairs tested). In contrast, NGFCs strongly inhibited L2/3 pyramidal neurons (n = 12 out 27 pairs tested). These data reveal a high specificity of excitatory and inhibitory connections in the superficial layers of the neocortex

Two-photon imaging and analysis of neural network dynamics

The glow of a starry night sky, the smell of a freshly brewed cup of coffee or the sound of ocean waves breaking on the beach are representations of the physical world that have been created by the dynamic interactions of thousands of neurons in our brains. How the brain mediates perceptions, creates thoughts, stores memories and initiates actions remains one of the most profound puzzles in biology, if not all of science. A key to a mechanistic understanding of how the nervous system works is the ability to analyze the dynamics of neuronal networks in the living organism in the context of sensory stimulation and behaviour. Dynamic brain properties have been fairly well characterized on the microscopic level of individual neurons and on the macroscopic level of whole brain areas largely with the help of various electrophysiological techniques. However, our understanding of the mesoscopic level comprising local populations of hundreds to thousands of neurons (so called 'microcircuits') remains comparably poor. In large parts, this has been due to the technical difficulties involved in recording from large networks of neurons with single-cell spatial resolution and near- millisecond temporal resolution in the brain of living animals. In recent years, two-photon microscopy has emerged as a technique which meets many of these requirements and thus has become the method of choice for the interrogation of local neural circuits. Here, we review the state-of-research in the field of two-photon imaging of neuronal populations, covering the topics of microscope technology, suitable fluorescent indicator dyes, staining techniques, and in particular analysis techniques for extracting relevant information from the fluorescence data. We expect that functional analysis of neural networks using two-photon imaging will help to decipher fundamental operational principles of neural microcircuits.Comment: 36 pages, 4 figures, accepted for publication in Reports on Progress in Physic

Target-selective GABAergic control of entorhinal cortex output.

The medial entorhinal cortex (MEC) is a major center for spatial navigation and memory. We found that cannabinoid type 1 receptor-expressing GABAergic basket cells selectively innervated principal cells in layer II of the rat MEC that projected outside the hippocampus but avoided neighboring cells that give rise to the perforant pathway to the dentate gyrus. These results indicate that the organization of GABAergic microcircuits reflects the long-distance axonal targets of principal neurons

Characterization of Type I and Type II nNOS-Expressing Interneurons in the Barrel Cortex of Mouse

In the neocortex, neuronal nitric oxide (NO) synthase (nNOS) is essentially expressed in two classes of GABAergic neurons: type I neurons displaying high levels of expression and type II neurons displaying weaker expression. Using immunocytochemistry in mice expressing GFP under the control of the glutamic acid decarboxylase 67k (GAD67) promoter, we studied the distribution of type I and type II neurons in the barrel cortex and their expression of parvalbumin (PV), somatostatin (SOM), and vasoactive intestinal peptide (VIP). We found that type I neurons were predominantly located in deeper layers and expressed SOM (91.5%) while type II neurons were concentrated in layer II/III and VI and expressed PV (17.7%), SOM (18.7%), and VIP (10.2%). We then characterized neurons expressing nNOS mRNA (n = 42 cells) ex vivo, using whole-cell recordings coupled to single-cell reverse transcription-PCR and biocytin labeling. Unsupervised cluster analysis of this sample disclosed four classes. One cluster (n = 7) corresponded to large, deep layer neurons, displaying a high expression of SOM (85.7%) and was thus very likely to correspond to type I neurons. The three other clusters were identified as putative type II cells and corresponded to neurogliaform-like interneurons (n = 19), deep layer neurons expressing PV or SOM (n = 9), and neurons expressing VIP (n = 7). Finally, we performed nNOS immunohistochemistry on mouse lines in which GFP labeling revealed the expression of two specific developmental genes (Lhx6 and 5-HT3A). We found that type I neurons expressed Lhx6 but never 5-HT3A, indicating that they originate in the medial ganglionic eminence (MGE). Type II neurons expressed Lhx6 (63%) and 5-HT3A (34.4%) supporting their derivation either from the MGE or from the caudal ganglionic eminence (CGE) and the entopeduncular and dorsal preoptic areas. Together, our results in the barrel cortex of mouse support the view that type I neurons form a specific class of SOM-expressing neurons while type II neurons comprise at least three classes