Complementary networks of cortical somatostatin interneurons enforce layer specific control

SummaryDefining the rules governing synaptic connectivity is key to formulating theories of neural circuit function. Interneurons can be connected by both electrical and chemical synapses, but the organization and interaction of these two complementary microcircuits is unknown. By recording from multiple molecular layer interneurons in the cerebellar cortex, we reveal specific, nonrandom connectivity patterns in both GABAergic chemical and electrical interneuron networks. Both networks contain clustered motifs and show specific overlap between them. Chemical connections exhibit a preference for transitive patterns, such as feedforward triplet motifs. This structured connectivity is supported by a characteristic spatial organization: transitivity of chemical connectivity is directed vertically in the sagittal plane, and electrical synapses appear strictly confined to the sagittal plane. The specific, highly structured connectivity rules suggest that these motifs are essential for the function of the cerebellar network.

GABAergic interneurons play an important role in shaping the activity of excitatory pyramidal cells (PCs). How the various inhibitory cell types contribute to neuronal information processing, however, is not resolved. Here, we propose a functional role for a widespread network motif consisting of parvalbumin- (PV), somatostatin- (SOM) and vasoactive intestinal peptide (VIP)-expressing interneurons. Following the idea that PV and SOM interneurons control the distribution of somatic and dendritic inhibition onto PCs, we suggest that mutual inhibition between VIP and SOM cells translates weak inputs to VIP interneurons into large changes of somato-dendritic inhibition of PCs. Using a computational model, we show that the neuronal and synaptic properties of the circuit support this hypothesis. Moreover, we demonstrate that the SOM-VIP motif allows transient inputs to persistently switch the circuit between two processing modes, in which top-down inputs onto apical dendrites of PCs are either integrated or cancelled.

Dependence of the inhibitory action of adenosine on the extracellular composite EPSP on the concentrations of Mg and Ca cations in the medium was investigated in isolated slices of rat hippocampusin vitro. Extracellular EPSPs were derived in the region of apical dendrites of pyramidal cells in area CA1 during stimulation of Schaffer's collaterals. The blocking action of bivalent cations (an increase in Mg++ or a decrease in Ca++) developed almost five times more slowly than the action of adenosine. An increase in the external Mg++ concentration potentiated whereas a decrease weakened the inhibitory action of adenosine. Ca++ ions had the opposite effect. Antagonistic relations were exhibited between Mg++ and Ca++ ions. Analysis of dose-response curves for adenosine showed that during a simultaneous increase in the extracellular Ca++ and decrease in Mg++ concentrations, not only was the maximal effect of adenosine reduced, but so also was its binding constant with the receptor. The results suggest that antagonism between Ca cations and adenosine is mixed in character — both competitive and noncompetitive. The possible mechanism of the inhibitory action of adenosine on synaptic transmission and the role of bivalent cations in this process are discussed.

Electroencephalogram(EEG)signals are mainly generated by postsynaptic potentials(EPSP)in the apical dendrites of pyramidal cells in the cortex. The mechanism of generation of interictal epileptiform discharges(IED)is paroxysmal depolarization shift(PDS). IEDs are negative towards the cortical surface and positive towards the white matter. To interpret EEG, readers should know normal EEG waveforms of wakefulness and sleep, normal variants such as wicket spikes or small sharp spikes, and artifacts such as eye movements or electromyography. Overinterpretation of EEG is a major cause of misdiagnosis; therefore, the accurate identification of IED is essential. The International Federation of Clinical Neurophysiology has proposed a criteria for the identification of IED. Long-term video-EEG is useful for correct diagnosis and localization of the epileptogenic zone in the setting of presurgical evaluation of intractable epilepsy and is also useful for the differential diagnosis of epileptic seizures and non-epileptic events. Clinical history and symptomatology are of utmost importance for correct diagnosis. Diagnosis should not be made using only EEG findings.

We prepared a monoclonal antibody to microtubule-associated protein 1 (MAP 1), one of the two major high molecular weight MAP found in microtubules isolated from brain tissue. We found that MAP 1 can be resolved by SDS PAGE into three electrophoretic bands, which we have designated MAP 1A, MAP 1B, and MAP 1C in order of increasing electrophoretic mobility. Our antibody recognized exclusively MAP 1A, the most abundant and largest MAP 1 polypeptide. To determine the distribution of MAP 1A in nervous system tissues and cells, we examined tissue sections from rat brain and spinal cord, as well as primary cultures of newborn rat brain by immunofluorescence microscopy. Anti- MAP 1A stained white matter and gray matter regions, while a polyclonal anti-MAP 2 antibody previously prepared in this laboratory stained only gray matter. This confirmed our earlier biochemical results, which indicated that MAP 1 is more uniformly distributed in brain tissue than MAP 2 (Vallee, R.B., 1982, J. Cell Biol., 92:435-442). To determine the identity of cells and cellular processes immunoreactive with anti-MAP 1A, we examined a variety of brain and spinal cord regions. Fibrous staining of white matter by anti-MAP 1A was generally observed. This was due in part to immunoreactivity of axons, as judged by examination of axonal fiber tracts in the cerebral cortex and of large myelinated axons in the spinal cord and in spinal nerve roots. Cells with the morphology of oligodendrocytes were brightly labeled in white matter. Intense staining of Purkinje cell dendrites in the cerebellar cortex and of the apical dendrites of pyramidal cells in the cerebral cortex was observed. By double-labeling with antibodies to MAP 1A and MAP 2, the presence of both MAP in identical dendrites and neuronal perikarya was found. In primary brain cell cultures anti-MAP 2 stained predominantly cells of neuronal morphology. In contrast, anti-MAP 1A stained nearly all cells. Included among these were neurons, oligodendrocytes and astrocytes as determined by double-labeling with anti-MAP 1A in combination with antibody to MAP 2, myelin basic protein or glial fibrillary acidic protein, respectively. These results indicate that in contrast to MAP 2, which is specifically enriched in dendrites and perikarya of neurons, MAP 1A is widely distributed in the nervous system.

The cytoarchitecture, topography, and cellular structure of the nucleus olfactorius anterior (NOA) in the hedgehog have been studied in Nissl-stained and Golgi preparations. The NOA is an important receptive allocortical formation for olfactory fibers and the major source of association fibers relating the main olfactory bulb with the rest of the olfactory brain. It was divided into a bulbar part; four subdivisions named lateral, dorsal, medial, and ventral; an external part; and a posterior part. Except for the external and posterior subdivisions, the NOA is relatively homogeneous and, in spite of the apparent lack of sublamination in Niss-stained material, four clearly defined cellular laminae were distinguished by the Golgi method. These layers were found to be strikingly similar to those in the piriform cortex. Layer I contains the terminal ramifications of apical dendrites of pyramidal cells and the collaterals of the lateral olfactory tract. The superficial part of layer II contains extraverted pyramidal cells with two or three apical dendrites ramifying in layer I. Most pyramidal cells in the deep part of layer II and layer III are typical pyramidal cells with axons entering the commissura anterior. Some pyramidal cell axons bifurcate into two branches running in opposite directions in the commissura anterior. The interstitial zone below layer III contains deep pyramidal cells and polymorphic cells with ascending branches. Cells with intrinsic axons were classified into four main categories according to the distribution of their axonal ramifications: 1) cells with very restricted axons, 2) cells with axons oriented tangentially in the superficial part of layer II, 3) cells with ascending axons located in the deep part, and 4) chandelierlike cells. Finally, some functional considerations are discussed.

HNN-core is a library for circuit and cellular level interpretation of non-invasive human magneto-/electro-encephalography (MEG/EEG) data. It is based on the Human Neocortical Neurosolver (HNN) software (Neymotin et al., 2020), a modeling tool designed to simulate multiscale neural mechanisms generating current dipoles in a localized patch of neocortex. HNN's foundation is a biophysically detailed neural network representing a canonical neocortical column containing populations of pyramidal and inhibitory neurons together with layer-specific exogenous synaptic drive (Figure 1 left). In addition to simulating network-level interactions, HNN produces the intracellular currents in the long apical dendrites of pyramidal cells across the cortical layers known to be responsible for macroscopic current dipole generation.

We investigated attentional guidance in early visual areas in the brain by recording event-related potentials directly from the surface of visual cortex. Patients performed a contextual cueing task in which attentive search to targets was guided by implicitly learned spatial context information. The earliest activity in striate cortex (area V1) was not modulated by contextual cueing, whereas later activity beginning at approximately 200 ms was enhanced by contextual cueing in V1, V2 and other portions of extrastriate cortex. These results suggest that context can enhance visual processing by temporally late top-down modulation of activity in anatomically early areas of visual cortex. Together with anatomical and neurophysiological studies in animals, these results suggest an excitatory feedback mechanism acting on apical dendrites of pyramidal cells in V1 and other areas of visual cortex.

The major target of the V4 projection in V2 is layer 1, where it forms a tangential spread of asymmetric (excitatory) synapses. This is characteristic of a "feedback" projection. Some axons formed discrete clusters of bouton terminaux between lengths of myelinated axon, while others were unbranched and formed a continuous distribution of en passant boutons with no intercalated myelin. Minor projections were found in layers 2/3 and 6. Dendritic spines were the most frequently encountered targets of the V4 projection (80% in layer 1 and layer 2/3, 94% in layer 6). The remaining targets were dendritic shafts. In layer 1, 69% of target dendrites (12% of all targets) had characteristics identifying them as smooth (GABAergic) cells. In layer 2/3 and layer 6 virtually all the shaft synapses were on smooth dendrites (86% and 100%, respectively). Multisynaptic boutons were rare (mean 1.1 synapses per bouton). Synapses formed in layer 6 were smaller than those of layer 1 (mean area 0.073 microm(2) vs. 0.117 microm(2)). Synapses formed with spines had a more complex postsynaptic density than those formed with dendritic shafts. With respect to targets and synaptic type and size and morphology of synapses, the feedback projection from V4 to V2 resembles those of feedforward projections. The principal difference between the feedforward and feedback projection is in the lamina location of their terminal boutons. The concentration of the V4 projection on layer 1, where it forms asymmetric synapses mainly with spines, suggests that it excites the distal apical dendrites of pyramidal cells.

Fifty years ago, Hubel & Wiesel (1962) proposed their hierarchical model to explain how the intricate response properties of Complex cells in cat visual cortex arose from multiple inputs from less complicated Simple cells. Although this model was perhaps an oversimplification already at the outset, the general concept of the repeated neocortical circuit motif has stood the test of time well. While inhibition has featured prominently in experiments, the interneuronal cell type has been conspicuously absent from many ideas about the repeated cortical circuit module. Maybe the sheer diversity of inhibitory interneuron classes in the neocortex has been too overwhelming. Amidst the disarray of neocortical interneuronal types, however, the Martinotti cell (MC) stands out as one that is relatively well demarcated. This ubiquitous inhibitory cell type, which is found across several neocortical layers, possesses a striking ascending axon that mainly arborizes in the top three layers, where it makes synaptic contacts onto the apical dendrites of pyramidal cells (PCs; Fig. 1). The MC also exhibits a characteristic slowly accommodating firing pattern with spikes triggered at low threshold and it also expresses the peptide somatostatin (Wang et al. 2004). A ubiquitous circuit motif in neocortex In several neocortical regions, around 1 in 7 of nearby PC pairs are connected, but the disynaptic PC–MC–PC motif that mediates FDDI is more than twice as prevalent (Berger et al. 2009). Whereas PC–PC connections are depressing (red trace), the PC–MC pathway is facilitating (blue trace), so PCs must fire at high frequency to drive MCs and generate FDDI (Silberberg & Markram, 2007). Dashed lines: axons; continuous lines: dendrites; scalebars: 1 mV, 50 ms. In an elegant study, Silberberg & Markram (2007) reported that high-frequency firing in PCs of the somatosensory cortex could readily trigger inhibitory responses in neighbouring PCs by activating intermediate MCs via a strongly facilitating synapse (Fig. 1), a concept here termed frequency-dependent disynaptic inhibition (FDDI). Interestingly, the prevalence of this disynaptic motif was more than twice that of the direct monosynaptic excitatory connection (Fig. 1, Silberberg & Markram, 2007). The omnipresence of this disynaptic motif seems to imply that it is important. But is it omnipresent across brain regions? In this issue of The Journal of Physiology, Berger et al. (2009) report that this disynaptic motif is indeed widespread. Using multiple simultaneous whole-cell recordings of layer-5 PCs, they examined the prevalence of this disynaptic circuit motif across a wide variety of neocortical areas: somatosensory, motor, auditory, secondary visual, and medial prefrontal cortices. They characterised the connectivity and properties of both monosynaptic and disynaptic connections, and found that the incidence of FDDI among PCs was consistently twice that of monosynaptic excitatory connections. The connectivity rate of FDDI scaled with the monosynaptic connectivity in different areas, with the highest connectivity in auditory cortex, and the lowest in medial prefrontal cortex. The authors also observed a higher than expected level of reciprocal FDDI and monosynaptic connections, especially in somatosensory cortex. Finally, FDDI was use dependent, and rapidly disappeared if PCs were stimulated too often, probably due to fatigue of the PC–MC synapse. Although FDDI remained stereotyped across regions, Berger et al. (2009) also observed some interesting area-specific differences. The auditory cortex stood out by having the highest FDDI connectivity, the largest amplitude, the fastest rise, and the most rapid decay of FDDI responses. The authors suggest that this may reflect the high temporal specificity requirements of auditory processing. To examine FDDI, Berger et al. (2009) used a prolonged 70 Hz spike train. Although this activity pattern is a good experimental probe, it does not necessarily reflect the in vivo activity of individual PCs. A recent in vivo study, however, indicates that bursts in PCs activate MCs and thereby hyperpolarize PC apical dendrites via FDDI (Murayama et al. 2009). Burst firing is therefore self-limiting, as it initiates in the distal PC dendrite, but more importantly, MCs can also dynamically reshape the stimulus–response curve of PC dendrites (Murayama et al. 2009). Another study shows that recruitment of MCs, or cells similar to them, increases supralinearly with the number of sparsely active PCs, thus efficiently limiting cortical excitability during more widespread synchronous PC activity (Kapfer et al. 2007). Both reports thus hint that one possible function of FDDI is to keep activity within bounds via negative feedback. But if this is true, then the finding of Berger et al. (2009) that FDDI disappears with increased use seems puzzling: during periods of increased activity, a mechanism that promotes stability should not fatigue but persist or up-regulate. An additional possible functional role for FDDI is that it serves to gate synaptic plasticity. It has been shown that excitatory inputs onto the distal apical PC dendrite undergo Hebbian long-term potentiation only when the dendrite is in a depolarized state (Sjöström & Häusser, 2006). PCs triggering FDDI would clamp apical dendrites of nearby PCs at hyperpolarized potentials, thus preventing potentiation. The functionality of FDDI thus remains uncertain and its possible role in plasticity needs to be investigated. It is also unclear if this disynaptic motif becomes more or less prevalent with development and maturity. Regardless, it is clear that FDDI is a new principle and that the disynaptic PC–MC–PC motif is generic and ubiquitous in neocortical microcircuits.

Synaptically activated postsynaptic [Ca2+]i increases occur through three main pathways: Ca2+ entry through voltage-gated Ca2+ channels, Ca2+ entry through ligand-gated channels, and Ca2+ release from internal stores. The first two pathways have been studied intensively; release from stores has been the subject of more recent investigations. Ca2+ release from stores in CNS neurons primarily occurs as a result of IP3 mobilized by activation of metabotropic glutamatergic and/or cholingergic receptors coupled to PLC. Ca2+ release is localized near spines in Purkinje cells and occurs as a wave in the primary apical dendrites of pyramidal cells in the hippocampus and cortex. The amplitude of the [Ca2+]i increase can reach several micromolar, significantly larger than the increase due to backpropagating spikes. The large amplitude, long duration, and unique location of the [Ca2+]i increases due to Ca2+ release from stores suggests that these increases can affect specific downstream signaling mechanisms in neurons.

Monoaminergic afferents to the neocortex: A developmental histofluorescence study in normal and reeler mouse embryos

We studied the influence of cocaine use on the structure of neurons in brain regions that contribute to its rewarding effects by allowing rats to self-administer cocaine (0.33 mg/infusion) for 1 h a day for 1 month. Control animals were left undisturbed or allowed to work for food for the same period of time. After an additional 1 month drug-free period the brains were processed for Golgi-Cox staining. In rats that self-administered cocaine, but not rats that worked for food, there was a significant increase in dendritic branching and in the density of dendritic spines on medium spiny neurons in the shell of the nucleus accumbens and on pyramidal cells in the prefrontal and parietal (but not occipital) cortex. There was also a 2.6-fold increase in the incidence of spines with multiple heads (branched spines) on medium spiny neurons. Finally, in the prefrontal cortex some of the apical dendrites of pyramidal cells appeared misshaped, having large bulbous structures on their terminal tips. We speculate that cocaine self-administration experience alters patterns of synaptic connectivity within limbocortical circuitry that is thought to contribute to cocaine's incentive motivational effects and may have neuropathological effects in frontal areas involved in decision making and judgment. Together, these two classes of drug-induced neuroadaptations may contribute to the development of addiction.

GABA-containing (GABAergic) interneurons comprise a very heterogeneous group of cells that are crucial for cortical function. Different classes of interneurons specialize in targeting specific subcellular domains of excitatory pyramidal cells or other interneurons, which provides cortical circuits with an enormous capability for information processing. As in other regions of the CNS, cortical interneuron diversity is thought to emerge from the genetic specification of different groups of progenitor cells within the subpallium. Most cortical interneurons originate from two main regions, the medial and the caudal ganglionic eminences (MGE and CGE, respectively). In addition, it has been shown that progenitors in the embryonic preoptic area (POA) also produce a small population of cortical GABAergic interneurons. Here, we show that the contribution of the POA to the complement of cortical GABAergic interneurons is larger than previously believed. Using genetic fate mapping and in utero transplantation experiments, we demonstrate that Dbx1-expressing progenitor cells in the POA give rise to a small but highly diverse cohort of cortical interneurons, with some neurochemical and electrophysiological characteristics that were previously attributed to MGE- or CGE-derived interneurons. There are, however, some features that seem to distinguish POA-derived interneurons from MGE- or CGE-derived cells, such as their preferential laminar location. These results indicate that the mechanisms controlling the specification of different classes of cortical interneurons might be more complex than previously expected. Together with earlier findings, our results also suggest that the POA generates nearly 10% of the GABAergic interneurons in the cerebral cortex of the mouse.

Cortical inhibitory interneurons form a broad spectrum of subtypes. This diversity suggests a division of labor, in which each cell type supports a distinct function. In the present era of optimisation-based algorithms, it is tempting to speculate that these functions were the evolutionary or developmental driving force for the spectrum of interneurons we see in the mature mammalian brain. In this study, we evaluated this hypothesis using the two most common interneuron types, parvalbumin (PV) and somatostatin (SST) expressing cells, as examples. PV and SST interneurons control the activity in the cell bodies and the apical dendrites of excitatory pyramidal cells, respectively, due to a combination of anatomical and synaptic properties. But was this compartment-specific inhibition indeed the function for which PV and SST cells originally evolved? Does the compartmental structure of pyramidal cells shape the diversification of PV and SST interneurons over development? To address these questions, we reviewed and reanalyzed publicly available data on the development and evolution of PV and SST interneurons on one hand, and pyramidal cell morphology on the other. These data speak against the idea that the compartment structure of pyramidal cells drove the diversification into PV and SST interneurons. In particular, pyramidal cells mature late, while interneurons are likely committed to a particular fate (PV vs. SST) during early development. Moreover, comparative anatomy and single cell RNA-sequencing data indicate that PV and SST cells, but not the compartment structure of pyramidal cells, existed in the last common ancestor of mammals and reptiles. Specifically, turtle and songbird SST cells also express the Elfn1 and Cbln4 genes that are thought to play a role in compartment-specific inhibition in mammals. PV and SST cells therefore evolved and developed the properties that allow them to provide compartment-specific inhibition before there was selective pressure for this function. This suggest that interneuron diversity originally resulted from a different evolutionary driving force and was only later co-opted for the compartment-specific inhibition it seems to serve in mammals today. Future experiments could further test this idea using our computational reconstruction of ancestral Elfn1 protein sequences.