Demonstration that sublinear dendrites enable linearly non-separable computations

Theory predicts that nonlinear summation of synaptic potentials within dendrites allows neurons to perform linearly non-separable computations (LNSCs). Using Boolean analysis approaches, we predicted that both supralinear and sublinear synaptic summation could allow single neurons to implement a type of LNSC, the feature binding problem (FBP), which does not require inhibition contrary to the exclusive-or function (XOR). Notably, sublinear dendritic operations enable LNSCs when scattered synaptic activation generates increased somatic spike output. However, experimental demonstrations of scatter-sensitive neuronal computations have not yet been described. Using glutamate uncaging onto cerebellar molecular layer interneurons, we show that scattered synaptic-like activation of dendrites evoked larger compound EPSPs than clustered synaptic activation, generating a higher output spiking probability. Moreover, we also demonstrate that single interneurons can indeed implement the FBP. Using a biophysical model to explore the conditions in which a neuron might be expected to implement the FBP, we establish that sublinear summation is necessary but not sufficient. Other parameters such as the relative sublinearity, the EPSP size, depolarization amplitude relative to action potential threshold, and voltage fluctuations all influence whether the FBP can be performed. Since sublinear synaptic summation is a property of passive dendrites, we expect that many different neuron types can implement LNSCs.

A dendritic substrate for temporal diversity of cortical inhibition

In the mammalian neocortex, GABAergic interneurons (INs) inhibit cortical networks in profoundly different ways. The extent to which this depends on how different INs process excitatory signals along their dendrites is poorly understood. Here, we reveal that the functional specialization of two major populations of cortical INs is determined by the unique association of different dendritic integration modes with distinct synaptic organization motifs. We found that somatostatin (SST)-INs exhibit NMDAR-dependent dendritic integration and uniform synapse density along the dendritic tree. In contrast, dendrites of parvalbumin (PV)-INs exhibit passive synaptic integration coupled with proximally enriched synaptic distributions. Theoretical analysis shows that these two dendritic configurations result in different strategies to optimize synaptic efficacy in thin dendritic structures. Yet, the two configurations lead to distinct temporal engagement of each IN during network activity. We confirmed these predictions with in vivo recordings of IN activity in the visual cortex of awake mice, revealing a rapid and linear recruitment of PV-INs as opposed to a long-lasting integrative activation of SST-INs. Our work reveals the existence of distinct dendritic strategies that confer distinct temporal representations for the two major classes of neocortical INs and thus dynamics of inhibition.

Transcranial alternating current stimulation (tACS) at gamma frequency: an up-and-coming tool to modify the progression of Alzheimer's Disease

The last decades have witnessed huge efforts devoted to deciphering the pathological mechanisms underlying Alzheimer's Disease (AD) and to testing new drugs, with the recent FDA approval of two anti-amyloid monoclonal antibodies for AD treatment. Beyond these drug-based experimentations, a number of pre-clinical and clinical trials are exploring the benefits of alternative treatments, such as non-invasive stimulation techniques on AD neuropathology and symptoms. Among the different non-invasive brain stimulation approaches, transcranial alternating current stimulation (tACS) is gaining particular attention due to its ability to externally control gamma oscillations. Here, we outline the current knowledge concerning the clinical efficacy, safety, ease-of-use and cost-effectiveness of tACS on early and advanced AD, applied specifically at 40 Hz frequency, and also summarise pre-clinical results on validated models of AD and ongoing patient-centred trials.

Spine plasticity of dentate gyrus parvalbumin-positive interneurons is regulated by experience

Experience-driven alterations in neuronal activity are followed by structural-functional modifications allowing cells to adapt to these activity changes. Structural plasticity has been observed for cortical principal cells. However, how GABAergic interneurons respond to experience-dependent network activity changes is not well understood. We show that parvalbumin-expressing interneurons (PVIs) of the dentate gyrus (DG) possess dendritic spines, which undergo behaviorally induced structural dynamics. Glutamatergic inputs at PVI spines evoke signals with high spatial compartmentalization defined by neck length. Mice experiencing novel contexts form more PVI spines with elongated necks and exhibit enhanced network and PVI activity and cFOS expression. Enhanced green fluorescent protein reconstitution across synaptic partner-mediated synapse labeling shows that experience-driven PVI spine growth boosts targeting of PVI spines over shafts by glutamatergic synapses. Our findings propose a role for PVI spine dynamics in regulating PVI excitation by their inputs, which may allow PVIs to dynamically adjust their functional integration in the DG microcircuitry in relation to network computational demands.

Physiological features of parvalbumin-expressing GABAergic interneurons contributing to high-frequency oscillations in the cerebral cortex

Parvalbumin-expressing (PV+) inhibitory interneurons drive gamma oscillations (30-80 Hz), which underlie higher cognitive functions. In this review, we discuss two groups/aspects of fundamental properties of PV+ interneurons. In the first group (dubbed Before Axon), we list properties representing optimal synaptic integration in PV+ interneurons designed to support fast oscillations. For example: [i] Information can neither enter nor leave the neocortex without the engagement of fast PV+ -mediated inhibition; [ii] Voltage responses in PV+ interneuron dendrites integrate linearly to reduce impact of the fluctuations in the afferent drive; and [iii] Reversed somatodendritic Rm gradient accelerates the time courses of synaptic potentials arriving at the soma. In the second group (dubbed After Axon), we list morphological and biophysical properties responsible for (a) short synaptic delays, and (b) efficient postsynaptic outcomes. For example: [i] Fast-spiking ability that allows PV+ interneurons to outpace other cortical neurons (pyramidal neurons). [ii] Myelinated axon (which is only found in the PV+ subclass of interneurons) to secure fast-spiking at the initial axon segment; and [iii] Inhibitory autapses - autoinhibition, which assures brief biphasic voltage transients and supports postinhibitory rebounds. Recent advent of scientific tools, such as viral strategies to target PV cells and the ability to monitor PV cells via in vivo imaging during behavior, will aid in defining the role of PV cells in the CNS. Given the link between PV+ interneurons and cognition, in the future, it would be useful to carry out physiological recordings in the PV+ cell type selectively and characterize if and how psychiatric and neurological diseases affect initiation and propagation of electrical signals in this cortical sub-circuit. Voltage imaging may allow fast recordings of electrical signals from many PV+ interneurons simultaneously.

Fast-spiking parvalbumin-positive interneurons in brain physiology and Alzheimer's disease

Fast-spiking parvalbumin (PV) interneurons are inhibitory interneurons with unique morphological and functional properties that allow them to precisely control local circuitry, brain networks and memory processing. Since the discovery in 1987 that PV is expressed in a subset of fast-spiking GABAergic inhibitory neurons, our knowledge of the complex molecular and physiological properties of these cells has been expanding. In this review, we highlight the specific properties of PV neurons that allow them to fire at high frequency and with high reliability, enabling them to control network oscillations and shape the encoding, consolidation and retrieval of memories. We next discuss multiple studies reporting PV neuron impairment as a critical step in neuronal network dysfunction and cognitive decline in mouse models of Alzheimer's disease (AD). Finally, we propose potential mechanisms underlying PV neuron dysfunction in AD and we argue that early changes in PV neuron activity could be a causal step in AD-associated network and memory impairment and a significant contributor to disease pathogenesis.

Structural and functional specializations of human fast-spiking neurons support fast cortical signaling

Fast-spiking interneurons (FSINs) provide fast inhibition that synchronizes neuronal activity and is critical for cognitive function. Fast synchronization frequencies are evolutionary conserved in the expanded human neocortex despite larger neuron-to-neuron distances that challenge fast input-output transfer functions of FSINs. Here, we test in human neurons from neurosurgery tissue, which mechanistic specializations of human FSINs explain their fast-signaling properties in human cortex. With morphological reconstructions, multipatch recordings, and biophysical modeling, we find that despite threefold longer dendritic path, human FSINs maintain fast inhibition between connected pyramidal neurons through several mechanisms: stronger synapse strength of excitatory inputs, larger dendrite diameter with reduced complexity, faster AP initiation, and faster and larger inhibitory output, while Na+ current activation/inactivation properties are similar. These adaptations underlie short input-output delays in fast inhibition of human pyramidal neurons through FSINs, explaining how cortical synchronization frequencies are conserved despite expanded and sparse network topology of human cortex.

The computational power of the human brain

At the end of the 20th century, analog systems in computer science have been widely replaced by digital systems due to their higher computing power. Nevertheless, the question keeps being intriguing until now: is the brain analog or digital? Initially, the latter has been favored, considering it as a Turing machine that works like a digital computer. However, more recently, digital and analog processes have been combined to implant human behavior in robots, endowing them with artificial intelligence (AI). Therefore, we think it is timely to compare mathematical models with the biology of computation in the brain. To this end, digital and analog processes clearly identified in cellular and molecular interactions in the Central Nervous System are highlighted. But above that, we try to pinpoint reasons distinguishing in silico computation from salient features of biological computation. First, genuinely analog information processing has been observed in electrical synapses and through gap junctions, the latter both in neurons and astrocytes. Apparently opposed to that, neuronal action potentials (APs) or spikes represent clearly digital events, like the yes/no or 1/0 of a Turing machine. However, spikes are rarely uniform, but can vary in amplitude and widths, which has significant, differential effects on transmitter release at the presynaptic terminal, where notwithstanding the quantal (vesicular) release itself is digital. Conversely, at the dendritic site of the postsynaptic neuron, there are numerous analog events of computation. Moreover, synaptic transmission of information is not only neuronal, but heavily influenced by astrocytes tightly ensheathing the majority of synapses in brain (tripartite synapse). At least at this point, LTP and LTD modifying synaptic plasticity and believed to induce short and long-term memory processes including consolidation (equivalent to RAM and ROM in electronic devices) have to be discussed. The present knowledge of how the brain stores and retrieves memories includes a variety of options (e.g., neuronal network oscillations, engram cells, astrocytic syncytium). Also epigenetic features play crucial roles in memory formation and its consolidation, which necessarily guides to molecular events like gene transcription and translation. In conclusion, brain computation is not only digital or analog, or a combination of both, but encompasses features in parallel, and of higher orders of complexity.

Associations between in vitro, in vivo and in silico cell classes in mouse primary visual cortex

The brain consists of many cell classes yet in vivo electrophysiology recordings are typically unable to identify and monitor their activity in the behaving animal. Here, we employed a systematic approach to link cellular, multi-modal in vitro properties from experiments with in vivo recorded units via computational modeling and optotagging experiments. We found two one-channel and six multi-channel clusters in mouse visual cortex with distinct in vivo properties in terms of activity, cortical depth, and behavior. We used biophysical models to map the two one- and the six multi-channel clusters to specific in vitro classes with unique morphology, excitability and conductance properties that explain their distinct extracellular signatures and functional characteristics. These concepts were tested in ground-truth optotagging experiments with two inhibitory classes unveiling distinct in vivo properties. This multi-modal approach presents a powerful way to separate in vivo clusters and infer their cellular properties from first principles.

Associations between in vitro , in vivo and in silico cell classes in mouse primary visual cortex

The brain consists of many cell classes yet in vivo electrophysiology recordings are typically unable to identify and monitor their activity in the behaving animal. Here, we employed a systematic approach to link cellular, multi-modal in vitro properties from experiments with in vivo recorded units via computational modeling and optotagging experiments. We found two one-channel and six multi-channel clusters in mouse visual cortex with distinct in vivo properties in terms of activity, cortical depth, and behavior. We used biophysical models to map the two one- and the six multi-channel clusters to specific in vitro classes with unique morphology, excitability and conductance properties that explain their distinct extracellular signatures and functional characteristics. These concepts were tested in ground-truth optotagging experiments with two inhibitory classes unveiling distinct in vivo properties. This multi-modal approach presents a powerful way to separate in vivo clusters and infer their cellular properties from first principles.

Spatial integration of dendrites in fast-spiking basket cells

Dendrites of fast-spiking basket cells (FS BCs) impact neural circuit functions in brain with both supralinear and sublinear integration strategies. Diverse spatial synaptic inputs and active properties of dendrites lead to distinct neuronal firing patterns. How the FS BCs with this bi-modal dendritic integration respond to different spatial dispersion of synaptic inputs remains unclear. In this study, we construct a multi-compartmental model of FS BC and analyze neuronal firings following simulated synaptic protocols from fully clustered to fully dispersed. Under these stimulation protocols, we find that supralinear dendrites dominate somatic firing of FS BC, while the preference for dispersing is due to sublinear dendrites. Moreover, we find that dendritic diameter and Ca2+-permeable AMPA conductance play an important role in it, while A-type K+ channel and NMDA conductance have little effect. The obtained results may give some implications for understanding dendritic computation.

Interneuronal network model of theta-nested fast oscillations predicts differential effects of heterogeneity, gap junctions and short term depression for hyperpolarizing versus shunting inhibition

Theta and gamma oscillations in the hippocampus have been hypothesized to play a role in the encoding and retrieval of memories. Recently, it was shown that an intrinsic fast gamma mechanism in medial entorhinal cortex can be recruited by optogenetic stimulation at theta frequencies, which can persist with fast excitatory synaptic transmission blocked, suggesting a contribution of interneuronal network gamma (ING). We calibrated the passive and active properties of a 100-neuron model network to capture the range of passive properties and frequency/current relationships of experimentally recorded PV+ neurons in the medial entorhinal cortex (mEC). The strength and probabilities of chemical and electrical synapses were also calibrated using paired recordings, as were the kinetics and short-term depression (STD) of the chemical synapses. Gap junctions that contribute a noticeable fraction of the input resistance were required for synchrony with hyperpolarizing inhibition; these networks exhibited theta-nested high frequency oscillations similar to the putative ING observed experimentally in the optogenetically-driven PV-ChR2 mice. With STD included in the model, the network desynchronized at frequencies above ~200 Hz, so for sufficiently strong drive, fast oscillations were only observed before the peak of the theta. Because hyperpolarizing synapses provide a synchronizing drive that contributes to robustness in the presence of heterogeneity, synchronization decreases as the hyperpolarizing inhibition becomes weaker. In contrast, networks with shunting inhibition required non-physiological levels of gap junctions to synchronize using conduction delays within the measured range.

Sharp-wave ripple doublets induce complex dendritic spikes in parvalbumin interneurons in vivo

Neuronal plasticity has been shown to be causally linked to coincidence detection through dendritic spikes (dSpikes). We demonstrate the existence of SPW-R-associated, branch-specific, local dSpikes and their computational role in basal dendrites of hippocampal PV+ interneurons in awake animals. To measure the entire dendritic arbor of long thin dendrites during SPW-Rs, we used fast 3D acousto-optical imaging through an eccentric deep-brain adapter and ipsilateral local field potential recording. The regenerative calcium spike started at variable, NMDA-AMPA-dependent, hot spots and propagated in both direction with a high amplitude beyond a critical distance threshold (~150 µm) involving voltage-gated calcium channels. A supralinear dendritic summation emerged during SPW-R doublets when two successive SPW-R events coincide within a short temporal window (~150 ms), e.g., during more complex association tasks, and generated large dSpikes with an about 2.5-3-fold amplitude increase which propagated down to the soma. Our results suggest that these doublet-associated dSpikes can work as a dendritic-level temporal and spatial coincidence detector during SPW-R-related network computation in awake mice.

Error correction and improved precision of spike timing in converging cortical networks

The brain propagates neuronal signals accurately and rapidly. Nevertheless, whether and how a pool of cortical neurons transmits an undistorted message to a target remains unclear. We apply optogenetic white noise signals to small assemblies of cortical pyramidal cells (PYRs) in freely moving mice. The directly activated PYRs exhibit a spike timing precision of several milliseconds. Instead of losing precision, interneurons driven via synaptic activation exhibit higher precision with respect to the white noise signal. Compared with directly activated PYRs, postsynaptic interneuron spike trains allow better signal reconstruction, demonstrating error correction. Data-driven modeling shows that nonlinear amplification of coincident spikes can generate error correction and improved precision. Over multiple applications of the same signal, postsynaptic interneuron spiking is most reliable at timescales ten times shorter than those of the presynaptic PYR, exhibiting temporal coding. Similar results are observed in hippocampal region CA1. Coincidence detection of convergent inputs enables messages to be precisely propagated between cortical PYRs and interneurons.

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PYR-to-interneuron spike transmission exhibits error correction and improved precision

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Interneuron precision is higher when a larger pool of presynaptic PYRs is recruited

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Error correction and improved precision are consistent with coincidence detection

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Interneurons activated by synaptic transmission act as temporal coders

Biophysical Kv3 channel alterations dampen excitability of cortical PV interneurons and contribute to network hyperexcitability in early Alzheimer's

In Alzheimer’s disease (AD), a multitude of genetic risk factors and early biomarkers are known. Nevertheless, the causal factors responsible for initiating cognitive decline in AD remain controversial. Toxic plaques and tangles correlate with progressive neuropathology, yet disruptions in circuit activity emerge before their deposition in AD models and patients. Parvalbumin (PV) interneurons are potential candidates for dysregulating cortical excitability as they display altered action potential (AP) firing before neighboring excitatory neurons in prodromal AD. Here, we report a novel mechanism responsible for PV hypoexcitability in young adult familial AD mice. We found that biophysical modulation of K_v3 channels, but not changes in their mRNA or protein expression, were responsible for dampened excitability in young 5xFAD mice. These K⁺ conductances could efficiently regulate near-threshold AP firing, resulting in gamma-frequency-specific network hyperexcitability. Thus, biophysical ion channel alterations alone may reshape cortical network activity prior to changes in their expression levels. Our findings demonstrate an opportunity to design a novel class of targeted therapies to ameliorate cortical circuit hyperexcitability in early AD.

Parvalbumin interneuron dendrites enhance gamma oscillations

Dendrites are essential determinants of the input-output relationship of single neurons, but their role in network computations is not well understood. Here, we use a combination of dendritic patch-clamp recordings and in silico modeling to determine how dendrites of parvalbumin (PV)-expressing basket cells contribute to network oscillations in the gamma frequency band. Simultaneous soma-dendrite recordings from PV basket cells in the dentate gyrus reveal that the slope, or gain, of the dendritic input-output relationship is exceptionally low, thereby reducing the cell's sensitivity to changes in its input. By simulating gamma oscillations in detailed network models, we demonstrate that the low gain is key to increase spike synchrony in PV basket cell assemblies when cells are driven by spatially and temporally heterogeneous synaptic inputs. These results highlight the role of inhibitory neuron dendrites in synchronized network oscillations.

The guide to dendritic spikes of the mammalian cortex in vitro and in vivo

Half a century since their discovery by Llinás and colleagues, dendritic spikes have been observed in various neurons in different brain regions, from the neocortex and cerebellum to the basal ganglia. Dendrites exhibit a terrifically diverse but stereotypical repertoire of spikes, sometimes specific to subregions of the dendrite. Despite their prevalence, we only have a glimpse into their role in the behaving animal. This article aims to survey the full range of dendritic spikes found in excitatory and inhibitory neurons, compare them in vivo versus in vitro, and discuss new studies describing dendritic spikes in the human cortex. We focus on dendritic spikes in neocortical and hippocampal neurons and present a roadmap to identify and understand the broader role of dendritic spikes in single-cell computation.

GABAergic Interneurons with Nonlinear Dendrites: From Neuronal Computations to Memory Engrams

GABAergic interneurons (INs) are a highly diverse class of neurons in the mammalian brain with a critical role in orchestrating multiple cognitive functions and maintaining the balance of excitation/inhibition across neuronal circuitries. In this perspective, we discuss recent findings regarding the ability of some IN subtypes to integrate incoming inputs in nonlinear ways within their dendritic branches. These recently discovered features may endow the specific INs with advanced computing capabilities, whose breadth and functional contributions remain an open question. Along these lines, we discuss theoretical and experimental evidence regarding the potential role of nonlinear IN dendrites in advancing single neuron computations and contributing to memory formation.

Developmental emergence of two-stage nonlinear synaptic integration in cerebellar interneurons

Synaptic transmission, connectivity, and dendritic morphology mature in parallel during brain development and are often disrupted in neurodevelopmental disorders. Yet how these changes influence the neuronal computations necessary for normal brain function are not well understood. To identify cellular mechanisms underlying the maturation of synaptic integration in interneurons, we combined patch-clamp recordings of excitatory inputs in mouse cerebellar stellate cells (SCs), three-dimensional reconstruction of SC morphology with excitatory synapse location, and biophysical modeling. We found that postnatal maturation of postsynaptic strength was homogeneously reduced along the somatodendritic axis, but dendritic integration was always sublinear. However, dendritic branching increased without changes in synapse density, leading to a substantial gain in distal inputs. Thus, changes in synapse distribution, rather than dendrite cable properties, are the dominant mechanism underlying the maturation of neuronal computation. These mechanisms favor the emergence of a spatially compartmentalized two-stage integration model promoting location-dependent integration within dendritic subunits.

Selective inhibition of gamma aminobutyric acid release from mouse hippocampal interneurone subtypes by the volatile anaesthetic isoflurane

BACKGROUND

The cellular and molecular mechanisms by which general anaesthesia occurs is poorly understood. Hippocampal interneurone subpopulations, which are critical regulators of cognitive function, have diverse neurophysiological and synaptic properties, but their responses to anaesthetics are unclear.

METHODS

We used live-cell imaging of fluorescent biosensors expressed in mouse hippocampal neurones to delineate interneurone subtype-specific effects of isoflurane on synaptic vesicle exocytosis. The role of voltage-gated sodium channel (Na_v) subtype expression in determining isoflurane sensitivity was probed by overexpression or knockdown of specific Na_v subtypes in identified interneurones.

RESULTS

Clinically relevant concentrations of isoflurane differentially inhibited synaptic vesicle exocytosis: to 83.1% (11.7%) of control in parvalbumin-expressing interneurones, and to 58.6% (13.3%) and 64.5% (8.5%) of control in somatostatin-expressing interneurones and glutamatergic neurones, respectively. The relative expression of Na_v1.1 (associated with lower sensitivity) and Na_v1.6 (associated with higher sensitivity) determined the sensitivity of exocytosis to isoflurane.

CONCLUSIONS

Isoflurane inhibits synaptic vesicle exocytosis from hippocampal glutamatergic neurones and GABAergic interneurones in a cell-type-specific manner depending on their expression of voltage-gated sodium channel subtypes.

Kcns3 deficiency disrupts Parvalbumin neuron physiology in mouse prefrontal cortex: Implications for the pathophysiology of schizophrenia

The unique fast spiking (FS) phenotype of cortical parvalbumin-positive (PV) neurons depends on the expression of multiple subtypes of voltage-gated potassium channels (Kv). PV neurons selectively express Kcns3, the gene encoding Kv9.3 subunits, suggesting that Kcns3 expression is critical for the FS phenotype. KCNS3 expression is lower in PV neurons in the neocortex of subjects with schizophrenia, but the effects of this alteration are unclear, because Kv9.3 subunit function is poorly understood. Therefore, to assess the role of Kv9.3 subunits in PV neuron function, we combined gene expression analyses, computational modeling, and electrophysiology in acute slices from the cortex of Kcns3-deficient mice. Kcns3 mRNA levels were ~ 50% lower in cortical PV neurons from Kcns3-deficient relative to wildtype mice. While silent per se, Kv9.3 subunits are believed to amplify the Kv2.1 current in Kv2.1-Kv9.3 channel complexes. Hence, to assess the consequences of reducing Kv9.3 levels, we simulated the effects of decreasing the Kv2.1-mediated current in a computational model. The FS cell model with reduced Kv2.1 produced spike trains with irregular inter-spike intervals, or stuttering, and greater Na+ channel inactivation. As in the computational model, PV basket cells (PVBCs) from Kcns3-deficient mice displayed spike trains with strong stuttering, which depressed PVBC firing. Moreover, Kcns3 deficiency impaired the recruitment of PVBC firing at gamma frequency by stimuli mimicking synaptic input observed during cortical UP states. Our data indicate that Kv9.3 subunits are critical for PVBC physiology and suggest that KCNS3 deficiency in schizophrenia could impair PV neuron firing, possibly contributing to deficits in cortical gamma oscillations in the illness.

Cholinergic Modulation of Dendritic Signaling in Hippocampal GABAergic Inhibitory Interneurons

Dendrites represent the "reception hub" of the neuron as they collect thousands of different inputs and send a coherent response to the cell body. A considerable portion of these signals, especially in vivo, arises from neuromodulatory sources, which affect dendritic computations and cellular activity. In this context, acetylcholine (ACh) exerts a coordinating role of different brain structures, contributing to goal-driven behaviors and sleep-wake cycles. Specifically, cholinergic neurons from the medial septum-diagonal band of Broca complex send numerous projections to glutamatergic principal cells and GABAergic inhibitory neurons in the hippocampus, differentially entraining them during network oscillations. Interneurons display abundant expression of cholinergic receptors and marked responses to stimulation by ACh. Nonetheless, the precise localization of ACh inputs is largely unknown, and evidence for cholinergic modulation of interneuronal dendritic signaling remains elusive. In this article, we review evidence that suggests modulatory effects of ACh on dendritic computations in three hippocampal interneuron subtypes: fast-spiking parvalbumin-positive (PV⁺) cells, somatostatin-expressing (SOM⁺) oriens lacunosum moleculare cells and vasoactive intestinal polypeptide-expressing (VIP⁺) interneuron-selective interneurons. We consider the distribution of cholinergic receptors on these interneurons, including information about their specific somatodendritic location, and discuss how the action of these receptors can modulate dendritic Ca²⁺ signaling and activity of interneurons. The implications of ACh-dependent Ca²⁺ signaling for dendritic plasticity are also discussed. We propose that cholinergic modulation can shape the dendritic integration and plasticity in interneurons in a cell type-specific manner, and the elucidation of these mechanisms will be required to understand the contribution of each cell type to large-scale network activity.

Efficient Low-Pass Dendro-Somatic Coupling in the Apical Dendrite of Layer 5 Pyramidal Neurons in the Anterior Cingulate Cortex

Signal propagation in the dendrites of many neurons, including cortical pyramidal neurons in sensory cortex, is characterized by strong attenuation toward the soma. In contrast, using dual whole-cell recordings from the apical dendrite and soma of layer 5 (L5) pyramidal neurons in the anterior cingulate cortex (ACC) of adult male mice we found good coupling, particularly of slow subthreshold potentials like NMDA spikes or trains of EPSPs from dendrite to soma. Only the fastest EPSPs in the ACC were reduced to a similar degree as in primary somatosensory cortex, revealing differential low-pass filtering capabilities. Furthermore, L5 pyramidal neurons in the ACC did not exhibit dendritic Ca2+ spikes as prominently found in the apical dendrite of S1 (somatosensory cortex) pyramidal neurons. Fitting the experimental data to a NEURON model revealed that the specific distribution of Ileak, Iir, Im , and Ih was sufficient to explain the electrotonic dendritic structure causing a leaky distal dendritic compartment with correspondingly low input resistance and a compact perisomatic region, resulting in a decoupling of distal tuft branches from each other while at the same time efficiently connecting them to the soma. Our results give a biophysically plausible explanation of how a class of prefrontal cortical pyramidal neurons achieve efficient integration of subthreshold distal synaptic inputs compared with the same cell type in sensory cortices.SIGNIFICANCE STATEMENT Understanding cortical computation requires the understanding of its fundamental computational subunits. Layer 5 pyramidal neurons are the main output neurons of the cortex, integrating synaptic inputs across different cortical layers. Their elaborate dendritic tree receives, propagates, and transforms synaptic inputs into action potential output. We found good coupling of slow subthreshold potentials like NMDA spikes or trains of EPSPs from the distal apical dendrite to the soma in pyramidal neurons in the ACC, which was significantly better compared with S1. This suggests that frontal pyramidal neurons use a different integration scheme compared with the same cell type in somatosensory cortex, which has important implications for our understanding of information processing across different parts of the neocortex.

The ins and outs of inhibitory synaptic plasticity: Neuron types, molecular mechanisms and functional roles

GABAergic interneurons are highly diverse, and their synaptic outputs express various forms of plasticity. Compelling evidence indicates that activity-dependent changes of inhibitory synaptic transmission play a significant role in regulating neural circuits critically involved in learning and memory and circuit refinement. Here, we provide an updated overview of inhibitory synaptic plasticity with a focus on the hippocampus and neocortex. To illustrate the diversity of inhibitory interneurons, we discuss the case of two highly divergent interneuron types, parvalbumin-expressing basket cells and neurogliaform cells, which support unique roles on circuit dynamics. We also present recent progress on the molecular mechanisms underlying long-term, activity-dependent plasticity of fast inhibitory transmission. Lastly, we discuss the role of inhibitory synaptic plasticity in neuronal circuits' function. The emerging picture is that inhibitory synaptic transmission in the CNS is extremely diverse, undergoes various mechanistically distinct forms of plasticity and contributes to a much more refined computational role than initially thought. Both the remarkable diversity of inhibitory interneurons and the various forms of plasticity expressed by GABAergic synapses provide an amazingly rich inhibitory repertoire that is central to a variety of complex neural circuit functions, including memory.

A Composite Sketch of Fast-Spiking Parvalbumin-Positive Neurons

Parvalbumin-positive neurons are inhibitory neurons that release GABA and are mostly represented by fast-spiking basket or chandelier cells. They constitute a minor neuronal population, yet their peculiar profiles allow them to react quickly to any event in the brain under normal or pathological conditions. In this review, we will summarize the current knowledge about the fundamentals of fast-spiking parvalbumin-positive neurons, focusing on their morphology and specific channel/protein content. Next, we will explore their development, maturation, and migration in the brain. Finally, we will unravel their potential contribution to the physiopathology of epilepsy.

Neurophotonics Approaches for the Study of Pattern Separation

Successful memory involves not only remembering over time but also keeping memories distinct. Computational models suggest that pattern separation appears as a highly efficient process to discriminate between overlapping memories. Furthermore, lesion studies have shown that the dentate gyrus (DG) participates in pattern separation. However, these manipulations did not allow identifying the neuronal mechanism underlying pattern separation. The development of different neurophotonics techniques, together with other genetic tools, has been useful for the study of the microcircuit involved in this process. It has been shown that less-overlapped information would generate distinct neuronal representations within the granule cells (GCs). However, because glutamatergic or GABAergic cells in the DG are not functionally or structurally homogeneous, identifying the specific role of the different subpopulations remains elusive. Then, understanding pattern separation requires the ability to manipulate a temporal and spatially specific subset of cells in the DG and ideally to analyze DG cells activity in individuals performing a pattern separation dependent behavioral task. Thus, neurophotonics and calcium imaging techniques in conjunction with activity-dependent promoters and high-resolution microscopy appear as important tools for this endeavor. In this work, we review how different neurophotonics techniques have been implemented in the elucidation of a neuronal network that supports pattern separation alone or in combination with traditional techniques. We discuss the limitation of these techniques and how other neurophotonic techniques could be used to complement the advances presented up to this date.

Gap Junctions Interconnect Different Subtypes of Parvalbumin-Positive Interneurons in Barrels and Septa with Connectivity Unique to Each Subtype

Parvalbumin (PV)-positive interneurons form dendritic gap junctions with one another, but the connectivity among gap junction-coupled dendrites remains uninvestigated in most neocortical areas. We visualized gap junctions in layer 4 of the mouse barrel cortex and examined their structural details. PV neurons were divided into 4 types based on the location of soma and dendrites within or outside barrels. Type 1 neurons that had soma and all dendrites inside a barrel, considered most specific to single vibrissa-derived signals, unexpectedly formed gap junctions only with other types but never with each other. Type 2 neurons inside a barrel elongated dendrites outward, forming gap junctions within a column that contained the home barrel. Type 3 neurons located outside barrels established connections with all types including Type 4 neurons that were confined inside the inter-barrel septa. The majority (33/38, 86.8%) of dendritic gap junctions were within 75 μm from at least 1 of 2 paired somata. All types received vesicular glutamate transporter 2-positive axon terminals preferentially on somata and proximal dendrites, indicating the involvement of all types in thalamocortical feedforward regulation in which proximal gap junctions may also participate. These structural organizations provide a new morphological basis for regulatory mechanisms in barrel cortex.

Shunting Inhibition Improves Synchronization in Heterogeneous Inhibitory Interneuronal Networks with Type 1 Excitability Whereas Hyperpolarizing Inhibition Is Better for Type 2 Excitability

All-to-all homogeneous networks of inhibitory neurons synchronize completely under the right conditions; however, many modeling studies have shown that biological levels of heterogeneity disrupt synchrony. Our fundamental scientific question is “how can neurons maintain partial synchrony in the presence of heterogeneity and noise?” A particular subset of strongly interconnected interneurons, the PV+ fast-spiking (FS) basket neurons, are strongly implicated in γ oscillations and in phase locking of nested γ oscillations to theta. Their excitability type apparently varies between brain regions: in CA1 and the dentate gyrus they have type 1 excitability, meaning that they can fire arbitrarily slowly, whereas in the striatum and cortex they have type 2 excitability, meaning that there is a frequency thresh old below which they cannot sustain repetitive firing. We constrained the models to study the effect of excitability type (more precisely bifurcation type) in isolation from all other factors. We use sparsely connected, heterogeneous, noisy networks with synaptic delays to show that synchronization properties, namely the resistance to suppression and the strength of theta phase to γ amplitude coupling, are strongly dependent on the pairing of excitability type with the type of inhibition. Shunting inhibition performs better for type 1 and hyperpolarizing inhibition for type 2. γ Oscillations and their nesting within theta oscillations are thought to subserve cognitive functions like memory encoding and recall; therefore, it is important to understand the contribution of intrinsic properties to these rhythms.

An axon-specific expression of HCN channels catalyzes fast action potential signaling in GABAergic interneurons

During high-frequency network activities, fast-spiking, parvalbumin-expressing basket cells (PV⁺-BCs) generate barrages of fast synaptic inhibition to control the probability and precise timing of action potential (AP) initiation in principal neurons. Here we describe a subcellular specialization that contributes to the high speed of synaptic inhibition mediated by PV⁺-BCs. Mapping of hyperpolarization-activated cyclic nucleotide-gated (HCN) channel distribution in rat hippocampal PV⁺-BCs with subcellular patch-clamp methods revealed that functional HCN channels are exclusively expressed in axons and completely absent from somata and dendrites. HCN channels not only enhance AP initiation during sustained high-frequency firing but also speed up the propagation of AP trains in PV⁺-BC axons by dynamically opposing the hyperpolarization produced by Na⁺-K⁺ ATPases. Since axonal AP signaling determines the timing of synaptic communication, the axon-specific expression of HCN channels represents a specialization for PV⁺-BCs to operate at high speed.

The precise subcellular location of ion channels is a key determinant of their functions. Here, subcellular patch-clamp recordings demonstrate that an axon-specific expression of HCN channels facilitates the initiation and propagation of action potentials in parvalbumin-expressing basket cells.

Dendritic inhibition differentially regulates excitability of dentate gyrus parvalbumin-expressing interneurons and granule cells

Fast-spiking parvalbumin-expressing interneurons (PVIs) and granule cells (GCs) of the dentate gyrus receive layer-specific dendritic inhibition. Its impact on PVI and GC excitability is, however, unknown. By applying whole-cell recordings, GABA uncaging and single-cell-modeling, we show that proximal dendritic inhibition in PVIs is less efficient in lowering perforant path-mediated subthreshold depolarization than distal inhibition but both are highly efficient in silencing PVIs. These inhibitory effects can be explained by proximal shunting and distal strong hyperpolarizing inhibition. In contrast, GC proximal but not distal inhibition is the primary regulator of their excitability and recruitment. In GCs inhibition is hyperpolarizing along the entire somato-dendritic axis with similar strength. Thus, dendritic inhibition differentially controls input-output transformations in PVIs and GCs. Dendritic inhibition in PVIs is suited to balance PVI discharges in dependence on global network activity thereby providing strong and tuned perisomatic inhibition that contributes to the sparse representation of information in GC assemblies.

Fast-spiking parvalbumin-expressing interneurons (PVIs) and granule cells of the dentate gyrus receive layer-specific dendritic inhibition. The authors show that distal and proximal dendritic inhibition differentially control input-output transformations in PVIs and granule cells.

Dendritic NMDA receptors in parvalbumin neurons enable strong and stable neuronal assemblies

Parvalbumin-expressing (PV+) GABAergic interneurons mediate feedforward and feedback inhibition and have a key role in gamma oscillations and information processing. The importance of fast synaptic recruitment and action potential initiation and repolarization, and rapid synchronous GABA release by PV+ cells, is well established. In contrast, the functional significance of PV+ cell NMDA receptors (NMDARs), which generate relatively slow postsynaptic currents, is unclear. Underlining their potential importance, several studies implicate PV+ cell NMDAR disruption in impaired network function and circuit pathologies. Here, we show that dendritic NMDARs underlie supralinear integration of feedback excitation from local pyramidal neurons onto mouse CA1 PV+ cells. Furthermore, by incorporating NMDARs at feedback connections onto PV+ cells in spiking networks, we show that these receptors enable cooperative recruitment of PV+ interneurons, strengthening and stabilising principal cell assemblies. Failure of this phenomenon provides a parsimonious explanation for cognitive and sensory gating deficits in pathologies with impaired PV+ NMDAR signalling.

Challenging the point neuron dogma: FS basket cells as 2-stage nonlinear integrators

Interneurons are critical for the proper functioning of neural circuits. While often morphologically complex, their dendrites have been ignored for decades, treating them as linear point neurons. Exciting new findings reveal complex, non-linear dendritic computations that call for a new theory of interneuron arithmetic. Using detailed biophysical models, we predict that dendrites of FS basket cells in both hippocampus and prefrontal cortex come in two flavors: supralinear, supporting local sodium spikes within large-volume branches and sublinear, in small-volume branches. Synaptic activation of varying sets of these dendrites leads to somatic firing variability that cannot be fully explained by the point neuron reduction. Instead, a 2-stage artificial neural network (ANN), with sub- and supralinear hidden nodes, captures most of the variance. Reduced neuronal circuit modeling suggest that this bi-modal, 2-stage integration in FS basket cells confers substantial resource savings in memory encoding as well as the linking of memories across time.

Global and Multiplexed Dendritic Computations under In Vivo-like Conditions

Dendrites integrate inputs nonlinearly, but it is unclear how these nonlinearities contribute to the overall input-output transformation of single neurons. We developed statistically principled methods using a hierarchical cascade of linear-nonlinear subunits (hLN) to model the dynamically evolving somatic response of neurons receiving complex, in vivo-like spatiotemporal synaptic input patterns. We used the hLN to predict the somatic membrane potential of an in vivo-validated detailed biophysical model of a L2/3 pyramidal cell. Linear input integration with a single global dendritic nonlinearity achieved above 90% prediction accuracy. A novel hLN motif, input multiplexing into parallel processing channels, could improve predictions as much as conventionally used additional layers of local nonlinearities. We obtained similar results in two other cell types. This approach provides a data-driven characterization of a key component of cortical circuit computations: the input-output transformation of neurons during in vivo-like conditions.

Complementary Tuning of Na+ and K+ Channel Gating Underlies Fast and Energy-Efficient Action Potentials in GABAergic Interneuron Axons

Fast-spiking, parvalbumin-expressing GABAergic interneurons (PV⁺-BCs) express a complex machinery of rapid signaling mechanisms, including specialized voltage-gated ion channels to generate brief action potentials (APs). However, short APs are associated with overlapping Na⁺ and K⁺ fluxes and are therefore energetically expensive. How the potentially vicious combination of high AP frequency and inefficient spike generation can be reconciled with limited energy supply is presently unclear. To address this question, we performed direct recordings from the PV⁺-BC axon, the subcellular structure where active conductances for AP initiation and propagation are located. Surprisingly, the energy required for the AP was, on average, only ∼1.6 times the theoretical minimum. High energy efficiency emerged from the combination of fast inactivation of Na⁺ channels and delayed activation of Kv3-type K⁺ channels, which minimized ion flux overlap during APs. Thus, the complementary tuning of axonal Na⁺ and K⁺ channel gating optimizes both fast signaling properties and metabolic efficiency.

Calcium Dynamics in Dendrites of Hippocampal CA1 Interneurons in Awake Mice

Hippocampal inhibitory interneurons exhibit a large diversity of dendritic Ca²⁺ mechanisms that are involved in the induction of Hebbian and anti-Hebbian synaptic plasticity. High resolution imaging techniques allowed examining somatic Ca²⁺ signals and, accordingly, the recruitment of hippocampal interneurons in awake behaving animals. However, little is still known about dendritic Ca²⁺ activity in interneurons during different behavioral states. Here, we used two-photon Ca²⁺ imaging in mouse hippocampal CA1 interneurons to reveal Ca²⁺ signal patterns in interneuron dendrites during animal locomotion and immobility. Despite overall variability in dendritic Ca²⁺ transients (CaTs) across different cells and dendritic branches, we report consistent behavior state-dependent organization of Ca²⁺ signaling in interneurons. As such, spreading regenerative CaTs dominated in dendrites during locomotion, whereas both spreading and localized Ca²⁺ signals were seen during immobility. Thus, these data indicate that while animal locomotion is associated with widespread Ca²⁺ elevations in interneuron dendrites that may reflect regenerative activity, local CaTs that may be related to synaptic activity become apparent during animal quiet state.

Flexible Nanopipettes for Minimally Invasive Intracellular Electrophysiology In Vivo

Intracellular recordings in vivo remains the best technique to link single-neuron electrical properties to network function. Yet existing methods are limited in accuracy, throughput, and duration, primarily via washout, membrane damage, and movement-induced failure. Here, we introduce flexible quartz nanopipettes (inner diameters of 10-25 nm and spring constant of ∼0.08 N/m) as nanoscale analogs of traditional glass microelectrodes. Nanopipettes enable stable intracellular recordings (seal resistances of 500 to ∼800 MΩ, 5 to ∼10 cells/nanopipette, and duration of ∼1 hr) in anaesthetized and awake head-restrained mice, exhibit minimal diffusional flux, and facilitate precise recording and stimulation. When combined with quantum-dot labels and microprisms, nanopipettes enable two-photon targeted electrophysiology from both somata and dendrites, and even paired recordings from neighboring neurons, while permitting simultaneous population imaging across cortical layers. We demonstrate the versatility of this method by recording from parvalbumin-positive (Pv) interneurons while imaging seizure propagation, and we find that Pv depolarization block coincides with epileptic spread. Flexible nanopipettes present a simple method to procure stable intracellular recordings in vivo.

Target Interneuron Preference in Thalamocortical Pathways Determines the Temporal Structure of Cortical Responses

Sensory processing relies on fast detection of changes in environment, as well as integration of contextual cues over time. The mechanisms by which local circuits of the cerebral cortex simultaneously perform these opposite processes remain obscure. Thalamic “specific” nuclei relay sensory information, whereas “nonspecific” nuclei convey information on the environmental and behavioral contexts. We expressed channelrhodopsin in the ventrobasal specific (sensory) or the rhomboid nonspecific (contextual) thalamic nuclei. By selectively activating each thalamic pathway, we found that nonspecific inputs powerfully activate adapting (slow-responding) interneurons but weakly connect fast-spiking interneurons, whereas specific inputs exhibit opposite interneuron preference. Specific inputs thereby induce rapid feedforward inhibition that limits response duration, whereas, in the same cortical area, nonspecific inputs elicit delayed feedforward inhibition that enables lasting recurrent excitation. Using a mean field model, we confirm that cortical response dynamics depends on the type of interneuron targeted by thalamocortical inputs and show that efficient recruitment of adapting interneurons prolongs the cortical response and allows the summation of sensory and contextual inputs. Hence, target choice between slow- and fast-responding inhibitory neurons endows cortical networks with a simple computational solution to perform both sensory detection and integration.

Multidimensional Connectomics and Treatment-Resistant Schizophrenia: Linking Phenotypic Circuits to Targeted Therapeutics

Schizophrenia is a very complex syndrome that involves widespread brain multi-dysconnectivity. Neural circuits within specific brain regions and their links to corresponding regions are abnormal in the illness. Theoretical models of dysconnectivity and the investigation of connectomics and brain network organization have been examined in schizophrenia since the early nineteenth century. In more recent years, advancements have been achieved with the development of neuroimaging tools that have provided further clues to the structural and functional organization of the brain and global neural networks in the illness. Neural circuitry that extends across prefrontal, temporal and parietal areas of the cortex as well as limbic and other subcortical brain regions is disrupted in schizophrenia. As a result, many patients have a poor response to antipsychotic treatment and treatment failure is common. Treatment resistance that is specific to positive, negative, and cognitive domains of the illness may be related to distinct circuit phenotypes unique to treatment-refractory disease. Currently, there are no customized neural circuit-specific and targeted therapies that address this neural dysconnectivity. Investigation of targeted therapeutics that addresses particular areas of substantial regional dysconnectivity is an intriguing approach to precision medicine in schizophrenia. This review examines current findings of system and circuit-level brain dysconnectivity in treatment-resistant schizophrenia based on neuroimaging studies. Within a connectome context, on-off circuit connectivity synonymous with excitatory and inhibitory neuronal pathways is discussed. Mechanistic cellular, neurochemical and molecular studies are included with specific emphasis given to cell pathology and synaptic communication in glutamatergic and GABAergic systems. In this review we attempt to deconstruct how augmenting treatments may be applied within a circuit context to improve circuit integration and treatment response. Clinical studies that have used a variety of glutamate receptor and GABA interneuron modulators, nitric oxide-based therapies and a variety of other strategies as augmenting treatments with antipsychotic drugs are included. This review supports the idea that the methodical mapping of system-level networks to both on (excitatory) and off (inhibitory) cellular circuits specific to treatment-resistant disease may be a logical and productive approach in directing future research toward the advancement of targeted pharmacotherapeutics in schizophrenia.

Hippocampal GABAergic Inhibitory Interneurons

In the hippocampus GABAergic local circuit inhibitory interneurons represent only ~10-15% of the total neuronal population; however, their remarkable anatomical and physiological diversity allows them to regulate virtually all aspects of cellular and circuit function. Here we provide an overview of the current state of the field of interneuron research, focusing largely on the hippocampus. We discuss recent advances related to the various cell types, including their development and maturation, expression of subtype-specific voltage- and ligand-gated channels, and their roles in network oscillations. We also discuss recent technological advances and approaches that have permitted high-resolution, subtype-specific examination of their roles in numerous neural circuit disorders and the emerging therapeutic strategies to ameliorate such pathophysiological conditions. The ultimate goal of this review is not only to provide a touchstone for the current state of the field, but to help pave the way for future research by highlighting where gaps in our knowledge exist and how a complete appreciation of their roles will aid in future therapeutic strategies.

Dendritic Properties Control Energy Efficiency of Action Potentials in Cortical Pyramidal Cells

Neural computation is performed by transforming input signals into sequences of action potentials (APs), which is metabolically expensive and limited by the energy available to the brain. The metabolic efficiency of single AP has important consequences for the computational power of the cell, which is determined by its biophysical properties and morphologies. Here we adopt biophysically-based two-compartment models to investigate how dendrites affect energy efficiency of APs in cortical pyramidal neurons. We measure the Na⁺ entry during the spike and examine how it is efficiently used for generating AP depolarization. We show that increasing the proportion of dendritic area or coupling conductance between two chambers decreases Na⁺ entry efficiency of somatic AP. Activating inward Ca²⁺ current in dendrites results in dendritic spike, which increases AP efficiency. Activating Ca²⁺-activated outward K⁺ current in dendrites, however, decreases Na⁺ entry efficiency. We demonstrate that the active and passive dendrites take effects by altering the overlap between Na⁺ influx and internal current flowing from soma to dendrite. We explain a fundamental link between dendritic properties and AP efficiency, which is essential to interpret how neural computation consumes metabolic energy and how biophysics and morphologies contribute to such consumption.

GABAergic Interneurons in the Neocortex: From Cellular Properties to Circuits

Cortical networks are composed of glutamatergic excitatory projection neurons and local GABAergic inhibitory interneurons that gate signal flow and sculpt network dynamics. Although they represent a minority of the total neocortical neuronal population, GABAergic interneurons are highly heterogeneous, forming functional classes based on their morphological, electrophysiological, and molecular features, as well as connectivity and in vivo patterns of activity. Here we review our current understanding of neocortical interneuron diversity and the properties that distinguish cell types. We then discuss how the involvement of multiple cell types, each with a specific set of cellular properties, plays a crucial role in diversifying and increasing the computational power of a relatively small number of simple circuit motifs forming cortical networks. We illustrate how recent advances in the field have shed light onto the mechanisms by which GABAergic inhibition contributes to network operations.

Synaptic integration in cortical inhibitory neuron dendrites

Cortical inhibitory interneurons have a wide range of important functions, including balancing network excitation, enhancing spike-time precision of principal neurons, and synchronizing neural activity within and across brain regions. All these functions critically depend on the integration of synaptic inputs in their dendrites. But the sparse number of inhibitory cells, their small caliber dendrites, and the problem of cell-type identification, have prevented fast progress in analyzing their dendritic properties. Despite these challenges, recent advancements in electrophysiological, optical and molecular tools have opened the door for studying synaptic integration and dendritic computations in molecularly defined inhibitory interneurons. Accumulating evidence indicates that the biophysical properties of inhibitory neuron dendrites differ substantially from those of pyramidal neurons. In addition to the supralinear dendritic integration commonly observed in pyramidal neurons, interneuron dendrites can also integrate synaptic inputs in a linear or sublinear fashion. In this comprehensive review, we compare the dendritic biophysical properties of the three major classes of cortical inhibitory neurons and discuss how these cell type-specific properties may support their functions in the cortex.

Differential Dendritic Integration of Synaptic Potentials and Calcium in Cerebellar Interneurons

Dendritic voltage integration determines the transformation of synaptic inputs into output firing, while synaptic calcium integration drives plasticity mechanisms thought to underlie memory storage. Dendritic calcium integration has been shown to follow the same synaptic input-output relationship as dendritic voltage, but whether similar operations apply to neurons exhibiting sublinear voltage integration is unknown. We examined the properties and cellular mechanisms of these dendritic operations in cerebellar molecular layer interneurons using dendritic voltage and calcium imaging, in combination with synaptic stimulation or glutamate uncaging. We show that, while synaptic potentials summate sublinearly, concomitant dendritic calcium signals summate either linearly or supralinearly depending on the number of synapses activated. The supralinear dendritic calcium triggers a branch-specific, short-term suppression of neurotransmitter release that alters the pattern of synaptic activation. Thus, differential voltage and calcium integration permits dynamic regulation of neuronal input-output transformations without altering intrinsic nonlinear integration mechanisms.

Developmental pruning of excitatory synaptic inputs to parvalbumin interneurons in monkey prefrontal cortex

Working memory requires efficient excitatory drive to parvalbumin-positive (PV) interneurons in the primate dorsolateral prefrontal cortex (DLPFC). Developmental pruning eliminates superfluous excitatory inputs, suggesting that working memory maturation during adolescence requires pruning of excitatory inputs to PV interneurons. Therefore, we tested the hypothesis that excitatory synapses on PV interneurons are pruned during adolescence. The density of excitatory synapses, defined by overlapping vesicular glutamate transporter 1-positive (VGlut1+) and postsynaptic density 95-positive (PSD95+) puncta, on PV interneurons was lower in postpubertal relative to prepubertal monkeys. In contrast, puncta levels of VGlut1 and PSD95 proteins were higher in postpubertal monkeys and positively predicted activity-dependent PV levels, suggesting a greater strength of the remaining synapses after pruning. Because excitatory synapse number on PV interneurons is regulated by erb-b2 receptor tyrosine kinase 4 (ErbB4), whose function is influenced by alternative splicing, we tested the hypothesis that pruning of excitatory synapses on PV interneurons is associated with developmental shifts in ErbB4 expression and/or splicing. Pan-ErbB4 expression did not change, whereas the minor-to-major splice variant ratios increased with age. In cell culture, the major, but not the minor, variant increased excitatory synapse number on PV interneurons and displayed greater kinase activity than the minor variant, suggesting that the effect of ErbB4 signaling in PV interneurons is mediated by alternative splicing. Supporting this interpretation, in monkey DLPFC, higher minor-to-major variant ratios predicted lower PSD95+ puncta density on PV interneurons. Together, our findings suggest that ErbB4 splicing may regulate the pruning of excitatory synapses on PV interneurons during adolescence.

Subcellular Patch-clamp Recordings from the Somatodendritic Domain of Nigral Dopamine Neurons

Dendrites of dopaminergic neurons receive and convey synaptic input, support action potential back-propagation and neurotransmitter release. Understanding these fundamental functions will shed light on the information transfer in these neurons. Dendritic patch-clamp recordings provide the possibility to directly examine the electrical properties of dendrites and underlying voltage-gated ion channels. However, these fine structures are not easily accessible to patch pipettes because of their small diameter. This report describes a step-by-step procedure to collect stable and reliable recordings from the dendrites of dopaminergic neurons in acute slices. Electrophysiological measurements are combined with post hoc recovery of cell morphology. Successful experiments rely on improved preparation of slices, solutions and pipettes, adequate adjustment of the optics and stability of the pipette in contact with the recorded structure. Standard principles of somatic patch-clamp recording are applied to dendrites but with a gentler approach of the pipette. These versatile techniques can be implemented to address various questions concerning the excitable properties of dendrites.

Firing Frequency Maxima of Fast-Spiking Neurons in Human, Monkey, and Mouse Neocortex

Cortical fast-spiking (FS) neurons generate high-frequency action potentials (APs) without apparent frequency accommodation, thus providing fast and precise inhibition. However, the maximal firing frequency that they can reach, particularly in primate neocortex, remains unclear. Here, by recording in human, monkey, and mouse neocortical slices, we revealed that FS neurons in human association cortices (mostly temporal) could generate APs at a maximal mean frequency (F_mean) of 338 Hz and a maximal instantaneous frequency (F_inst) of 453 Hz, and they increase with age. The maximal firing frequency of FS neurons in the association cortices (frontal and temporal) of monkey was even higher (F_mean 450 Hz, F_inst 611 Hz), whereas in the association cortex (entorhinal) of mouse it was much lower (F_mean 215 Hz, F_inst 342 Hz). Moreover, FS neurons in mouse primary visual cortex (V1) could fire at higher frequencies (F_mean 415 Hz, F_inst 582 Hz) than those in association cortex. We further validated our in vitro data by examining spikes of putative FS neurons in behaving monkey and mouse. Together, our results demonstrate that the maximal firing frequency of FS neurons varies between species and cortical areas.