Coding principles and mechanisms of serotonergic transmission modes

Zhu R.E., Diao X., Liu X., Ru Q., Wu Z., Zhang Z., Looger L., Zhu J.

Synaptic transmission mediated by various neurotransmitters influences a wide range of behaviors. However, understanding how neuromodulatory transmitters encode diverse behaviors and affect their functions remains challenging. Here, we introduce GESIAP3.0, an advanced, third-generation image analysis program based on genetically encoded sensors. This tool enables precise quantitative analysis of transmission in both awake, freely moving animals and immobilized subjects. GESIAP3.0 incorporates movement correction algorithms that effectively eliminate image displacement in behaving animals while optimizing synaptic information extraction and simplifying computations on commodity computers. Quantitative analysis of cholinergic, dopaminergic, and serotonergic transmission, corrected for tissue movement, revealed synaptic properties consistent with measurements fromex vivowide-field andin vivotwo-photon imaging under stable conditions. This validates the applicability of GESIAP3.0 for analyzing synaptic properties of neuromodulatory transmission in behaving animals.

Muir J., Anguiano M., Kim C.K.

To determine how neuronal circuits encode and drive behavior, it is often necessary to measure and manipulate different aspects of neurochemical signaling in awake animals. Optogenetics and calcium sensors have paved the way for these types of studies, allowing for the perturbation and readout of spiking activity within genetically defined cell types. However, these methods lack the ability to further disentangle the roles of individual neuromodulator and neuropeptides on circuits and behavior. We review recent advances in chemical biology tools that enable precise spatiotemporal monitoring and control over individual neuroeffectors and their receptors in vivo. We also highlight discoveries enabled by such tools, revealing how these molecules signal across different timescales to drive learning, orchestrate behavioral changes, and modulate circuit activity.

Wernersson E., Gelali E., Girelli G., Wang S., Castillo D., Mattsson Langseth C., Verron Q., Nguyen H.Q., Chattoraj S., Martinez Casals A., Blom H., Lundberg E., Nilsson M., Marti-Renom M.A., Wu C., et. al.

AbstractMicroscopy-based spatially resolved omic methods are transforming the life sciences. However, these methods rely on high numerical aperture objectives and cannot resolve crowded molecular targets, limiting the amount of extractable biological information. To overcome these limitations, here we develop Deconwolf, an open-source, user-friendly software for high-performance deconvolution of widefield fluorescence microscopy images, which efficiently runs on laptop computers. Deconwolf enables accurate quantification of crowded diffraction limited fluorescence dots in DNA and RNA fluorescence in situ hybridization images and allows robust detection of individual transcripts in tissue sections imaged with ×20 air objectives. Deconvolution of in situ spatial transcriptomics images with Deconwolf increased the number of transcripts identified more than threefold, while the application of Deconwolf to images obtained by fluorescence in situ sequencing of barcoded Oligopaint probes drastically improved chromosome tracing. Deconwolf greatly facilitates the use of deconvolution in many bioimaging applications.

Özçete Ö.D., Banerjee A., Kaeser P.S.

AbstractA wealth of neuromodulatory transmitters regulate synaptic circuits in the brain. Their mode of signaling, often called volume transmission, differs from classical synaptic transmission in important ways. In synaptic transmission, vesicles rapidly fuse in response to action potentials and release their transmitter content. The transmitters are then sensed by nearby receptors on select target cells with minimal delay. Signal transmission is restricted to synaptic contacts and typically occurs within ~1 ms. Volume transmission doesn’t rely on synaptic contact sites and is the main mode of monoamines and neuropeptides, important neuromodulators in the brain. It is less precise than synaptic transmission, and the underlying molecular mechanisms and spatiotemporal scales are often not well understood. Here, we review literature on mechanisms of volume transmission and raise scientific questions that should be addressed in the years ahead. We define five domains by which volume transmission systems can differ from synaptic transmission and from one another. These domains are (1) innervation patterns and firing properties, (2) transmitter synthesis and loading into different types of vesicles, (3) architecture and distribution of release sites, (4) transmitter diffusion, degradation, and reuptake, and (5) receptor types and their positioning on target cells. We discuss these five domains for dopamine, a well-studied monoamine, and then compare the literature on dopamine with that on norepinephrine and serotonin. We include assessments of neuropeptide signaling and of central acetylcholine transmission. Through this review, we provide a molecular and cellular framework for volume transmission. This mechanistic knowledge is essential to define how neuromodulatory systems control behavior in health and disease and to understand how they are modulated by medical treatments and by drugs of abuse.

Ligneul R., Mainen Z.F.

Serotonin, also known as 5-hydroxytryptamine or 5-HT, is a neuromodulator widely recognized for its role in various psychoactive drugs. These drugs can exhibit antidepressant, antipsychotic, anxiolytic, empathogenic, or psychedelic effects, depending on their specific interactions with the serotonin system as well as other neuromodulators such as noradrenaline, dopamine, and oxytocin. This has led to a widespread belief that the neurochemical processes taking place deep inside our brains affect our subjective experiences and mental health. However, a scientific understanding of how neuromodulators’ functions relate to drug effects remains elusive.

Connor S.A., Siddiqui T.J.

Synapse organizing proteins are multifaceted molecules that coordinate the complex processes of brain development and plasticity at the level of individual synapses. Their importance is demonstrated by the major brain disorders that emerge when their function is compromised. The mechanisms whereby the various families of organizers govern synapses are diverse, but converge on the structure, function, and plasticity of synapses. Therefore, synapse organizers regulate how synapses adapt to ongoing activity, a process central for determining the developmental trajectory of the brain and critical to all forms of cognition. Here, we explore how synapse organizers set the conditions for synaptic plasticity and the associated molecular events, which eventually link to behavioral features of neurodevelopmental and neuropsychiatric disorders. We also propose central questions on how synapse organizers influence network function through integrating nanoscale and circuit-level organization of the brain.

Marx W., Penninx B.W., Solmi M., Furukawa T.A., Firth J., Carvalho A.F., Berk M.

Major depressive disorder (MDD) is characterized by persistent depressed mood, loss of interest or pleasure in previously enjoyable activities, recurrent thoughts of death, and physical and cognitive symptoms. People with MDD can have reduced quality of life owing to the disorder itself as well as related medical comorbidities, social factors, and impaired functional outcomes. MDD is a complex disorder that cannot be fully explained by any one single established biological or environmental pathway. Instead, MDD seems to be caused by a combination of genetic, environmental, psychological and biological factors. Treatment for MDD commonly involves pharmacological therapy with antidepressant medications, psychotherapy or a combination of both. In people with severe and/or treatment-resistant MDD, other biological therapies, such as electroconvulsive therapy, may also be offered. This Primer summarizes the epidemiology, mechanisms, diagnosis and treatment of major depressive disorder (MDD). This Primer also reviews how this disorder affects patient quality of life, and provides an overview of future research.

Zhu J.J.

•Octuple-sexdecuple patch recordings enable architectonics of complex cortical circuits•Architectonics identifies modular L1 SBC-led disinhibitory circuits across cortices•Architectures of L1 SBC-led disinhibitory circuits construe principles of cortical operation•Architectonics reveals specific deficits at SBC-disinhibited synapses in an AD mouse model Acquisition of neuronal circuit architectures, central to understanding brain function and dysfunction, remains prohibitively challenging. Here I report the development of a simultaneous and sequential octuple-sexdecuple whole-cell patch-clamp recording system that enables architectural reconstruction of complex cortical circuits. The method unveils the canonical layer 1 single bouquet cell (SBC)-led disinhibitory neuronal circuits across the mouse somatosensory, motor, prefrontal, and medial entorhinal cortices. The ∼1,500-neuron modular circuits feature the translaminar, unidirectional, minicolumnar, and independent disinhibition and optimize cortical complexity, subtlety, plasticity, variation, and redundancy. Moreover, architectural reconstruction uncovers age-dependent deficits at SBC-disinhibited synapses in the senescence-accelerated mouse prone 8, an animal model of Alzheimer’s disease. The deficits exhibit the characteristic Alzheimer’s-like cortical spread and correlation with cognitive impairments. These findings decrypt operations of the elementary processing units in healthy and Alzheimer’s mouse cortices and validate the efficacy of octuple-sexdecuple patch-clamp recordings for architectural reconstruction of complex neuronal circuits. Acquisition of neuronal circuit architectures, central to understanding brain function and dysfunction, remains prohibitively challenging. Here I report the development of a simultaneous and sequential octuple-sexdecuple whole-cell patch-clamp recording system that enables architectural reconstruction of complex cortical circuits. The method unveils the canonical layer 1 single bouquet cell (SBC)-led disinhibitory neuronal circuits across the mouse somatosensory, motor, prefrontal, and medial entorhinal cortices. The ∼1,500-neuron modular circuits feature the translaminar, unidirectional, minicolumnar, and independent disinhibition and optimize cortical complexity, subtlety, plasticity, variation, and redundancy. Moreover, architectural reconstruction uncovers age-dependent deficits at SBC-disinhibited synapses in the senescence-accelerated mouse prone 8, an animal model of Alzheimer’s disease. The deficits exhibit the characteristic Alzheimer’s-like cortical spread and correlation with cognitive impairments. These findings decrypt operations of the elementary processing units in healthy and Alzheimer’s mouse cortices and validate the efficacy of octuple-sexdecuple patch-clamp recordings for architectural reconstruction of complex neuronal circuits. The sustained interest in neuronal circuits stems from the belief that intricately organized circuits provide the foundation for brain function.1Abbott L.F. Bock D.D. Callaway E.M. Denk W. Dulac C. Fairhall A.L. Fiete I. Harris K.M. Helmstaedter M. Jain V. et al.The mind of a mouse.Cell. 2020; 182: 1372-1376https://doi.org/10.1016/j.cell.2020.08.010Google Scholar,2Luo L. Architectures of neuronal circuits.Science. 2021; 373eabg7285https://doi.org/10.1126/science.abg7285Google Scholar In the past decade, significant progress has been made in our ability to decipher these circuits at the synaptic level with cell-type specificity, thanks to advancements in anatomic, neurophysiological, genetic, and functional imaging methods.3Kim C.K. Adhikari A. Deisseroth K. Integration of optogenetics with complementary methodologies in systems neuroscience.Nat. Rev. Neurosci. 2017; 18: 222-235https://doi.org/10.1038/nrn.2017.15Google Scholar,4Luo L. Callaway E.M. Svoboda K. Genetic dissection of neural circuits: a decade of progress.Neuron. 2018; 98: 256-281https://doi.org/10.1016/j.neuron.2018.03.040Google Scholar These technical advances have allowed for cell-type-specific circuit analysis, enabling researchers to decode hundreds of functional neuronal circuit motifs, consisting typically of a few different types of neurons, in various animal species. Among the various newly identified circuit motifs are the layer 1 (L1) single bouquet cell (SBC)-led disinhibitory neuronal circuit motifs (i.e., L1 interneurons ⏤⋅ L2/3 interneurons ⏤⋅ L2/3 and/or L5 pyramidal neurons) found in the cortex, which disclose a disinhibition scheme that governs the dendritic coincidence detection mechanism of excitatory neurons and their outputs.5Jiang X. Wang G. Lee A.J. Stornetta R.L. Zhu J.J. The organization of two new cortical interneuronal circuits.Nat. Neurosci. 2013; 16: 210-218https://doi.org/10.1038/nn.3305Google Scholar,6Lee A.J. Wang G. Jiang X. Johnson S.M. Hoang E.T. Lanté F. Stornetta R.L. Beenhakker M.P. Shen Y. Julius Zhu J. Canonical organization of layer 1 neuron-led cortical inhibitory and disinhibitory interneuronal circuits.Cerebr. Cortex. 2015; 25: 2114-2126https://doi.org/10.1093/cercor/bhu020Google Scholar This cortical disinhibition mechanism has been implicated in various high cognitive behaviors, such as perception, attention, learning, and memory.7Cichon J. Gan W.B. Branch-specific dendritic Ca2+ spikes cause persistent synaptic plasticity.Nature. 2015; 520: 180-185https://doi.org/10.1038/nature14251Google Scholar,8Takahashi N. Oertner T.G. Hegemann P. Larkum M.E. Active cortical dendrites modulate perception.Science. 2016; 354: 1587-1590https://doi.org/10.1126/science.aah6066Google Scholar,9Doron G. 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A disinhibitory microcircuit for associative fear learning in the auditory cortex.Nature. 2011; 480: 331-335https://doi.org/10.1038/nature10674Google Scholar However, understanding the higher-order circuit organization scheme and the overall architectural structure of complex circuits, which involve a large number of neurons and multiple circuit motifs, remains extremely challenging. For example, although optogenetics and functional imaging are effective in determining synaptic connections between neuronal groups, the methods are less suitable for zoom-in manipulation of compactly packed individual neurons to tease out the interconnections of neurons and to figure out the circuit architectural organization.3Kim C.K. Adhikari A. Deisseroth K. Integration of optogenetics with complementary methodologies in systems neuroscience.Nat. Rev. Neurosci. 2017; 18: 222-235https://doi.org/10.1038/nrn.2017.15Google Scholar,4Luo L. Callaway E.M. Svoboda K. Genetic dissection of neural circuits: a decade of progress.Neuron. 2018; 98: 256-281https://doi.org/10.1016/j.neuron.2018.03.040Google Scholar High-speed scanning electron microscopy permits high-resolution analysis of pre- and postsynaptic components, but the process of stitching and aligning miniature image sections to create a zoom-out interlinking diagram of individual neurons or circuit motifs and to see the circuit architectural design is still a daunting task.13Shapson-Coe A. Januszewski M. Berger D.R. Pope A. Wu Y. Blakely T. Schalek R.L. Li P. Wang S. Maitlin-Shepard J. et al.A connectomic study of a petascale fragment of human cerebral cortex.bioRxiv. 2021; (Preprint at) (10.1101/2021.05.29.446289)https://doi.org/10.1101/2021.1105.1129.446289v446281Google Scholar,14Schneider-Mizell C.M. Bodor A. Brittain D. Buchanan J. Bumbarger D.J. Elabbady L. Kapner D. Kinn S. Mahalingam G. Seshamani S. et al.Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex.bioRxiv. 2023; (Preprint at)https://doi.org/10.1101/2023.01.23.525290Google Scholar While these approaches evolve rapidly and become increasingly more powerful in illuminating the fine details of circuit motifs,14Schneider-Mizell C.M. Bodor A. Brittain D. Buchanan J. Bumbarger D.J. Elabbady L. Kapner D. Kinn S. Mahalingam G. Seshamani S. et al.Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex.bioRxiv. 2023; (Preprint at)https://doi.org/10.1101/2023.01.23.525290Google Scholar,15Fan L.Z. Kim D.K. Jennings J.H. Tian H. Wang P.Y. Ramakrishnan C. Randles S. Sun Y. Thadhani E. Kim Y.S. et al.All-optical physiology resolves a synaptic basis for behavioral timescale plasticity.Cell. 2023; 186: 543-559.e19https://doi.org/10.1016/j.cell.2022.12.035Google Scholar,16Turner N.L. Macrina T. Bae J.A. Yang R. Wilson A.M. Schneider-Mizell C. Lee K. Lu R. Wu J. Bodor A.L. et al.Reconstruction of neocortex: Organelles, compartments, cells, circuits, and activity.Cell. 2022; 185: 1082-1100.e24https://doi.org/10.1016/j.cell.2022.01.023Google Scholar they have yet to fully resolve the overall architectural structure of complex cortical circuits. As a result, we still have a paltry sense of architectural designs of complex cortical circuits, which are almost certainly at the heart of their operation and function.1Abbott L.F. Bock D.D. Callaway E.M. Denk W. Dulac C. Fairhall A.L. Fiete I. Harris K.M. Helmstaedter M. Jain V. et al.The mind of a mouse.Cell. 2020; 182: 1372-1376https://doi.org/10.1016/j.cell.2020.08.010Google Scholar,2Luo L. Architectures of neuronal circuits.Science. 2021; 373eabg7285https://doi.org/10.1126/science.abg7285Google Scholar This study describes the development of a simultaneous and sequential octuple-sexdecuple whole-cell patch-clamp recording system, which allows for direct manipulation and readout from individual neurons. The electrophysiology-based method offers the advantage of analyzing interconnections between a sufficient number of circuit elements (i.e., neurons and associated circuit motifs) to achieve the architectural reconstruction of complex cortical circuits. In the field of connectomics, many investigators use molecular markers to identify and classify neurons. This approach is convenient and genetically manipulable. However, it is important to consider that genetically defined cortical cell groups display a continuum of variability in morphology and electrophysiology, which means they may not represent biological or functional discrete entities.17Huang Z.J. Paul A. The diversity of GABAergic neurons and neural communication elements.Nat. Rev. Neurosci. 2019; 20: 563-572https://doi.org/10.1038/s41583-019-0195-4Google Scholar,18Scala F. Kobak D. Bernabucci M. Bernaerts Y. Cadwell C.R. Castro J.R. Hartmanis L. Jiang X. Laturnus S. Miranda E. et al.Phenotypic variation of transcriptomic cell types in mouse motor cortex.Nature. 2021; 598: 144-150https://doi.org/10.1038/s41586-020-2907-3Google Scholar In particular, caution should be exercised when analyzing cortical interneuronal circuits based on four coarse molecular subgroups, all of which consist of multiple overlapping types of interneurons. For example, parvalbumin-expressing neurons consist of at least baskets cells (BCs) and chandelier cells (ChCs).19Kubota Y. Karube F. Nomura M. Kawaguchi Y. The diversity of cortical inhibitory synapses.Front. Neural Circ. 2016; 10: 27https://doi.org/10.3389/fncir.2016.00027Google Scholar,20Rudy B. Fishell G. Lee S. Hjerling-Leffler J. Three groups of interneurons account for nearly 100% of neocortical GABAergic neurons.Dev. Neurobiol. 2011; 71: 45-61https://doi.org/10.1002/dneu.20853Google Scholar Somatostatin-expressing neurons comprise both Martinotti cells (MCs) and non-Martinotti cells.21Nigro M.J. Hashikawa-Yamasaki Y. Rudy B. Diversity and connectivity of layer 5 somatostatin-expressing interneurons in the mouse barrel cortex.J. Neurosci. 2018; 38: 1622-1633https://doi.org/10.1523/JNEUROSCI.2415-17.2017Google Scholar,22Ma Y. Hu H. Berrebi A.S. Mathers P.H. Agmon A. Distinct subtypes of somatostatin-containing neocortical interneurons revealed in transgenic mice.J. Neurosci. 2006; 26: 5069-5082https://doi.org/10.1523/JNEUROSCI.0661-06.2006Google Scholar,23McGarry L.M. Packer A.M. Fino E. Nikolenko V. Sippy T. Yuste R. Quantitative classification of somatostatin-positive neocortical interneurons identifies three interneuron subtypes.Front. 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Neurons immunoreactive for vasoactive intestinal polypeptide in the rat primary somatosensory cortex: morphology and spatial relationship to barrel-related columns.J. Comp. Neurol. 2000; 420: 291-304Google Scholar,27Kawaguchi Y. Kubota Y. Physiological and morphological identification of somatostatin- or vasoactive intestinal polypeptide-containing cells among GABAergic cell subtypes in rat frontal cortex.J. Neurosci. 1996; 16: 2701-2715https://doi.org/10.1523/JNEUROSCI.16-08-02701.1996Google Scholar Finally, newly designated Id2-expressing neurons correspond to elongated neurogliaform cells (ENGCs) in L1, and neurogliaform cells (NGCs) and a small number of diverse non-NGCs outside L1.28Machold R. Dellal S. Valero M. Zurita H. Kruglikov I. Meng J. Hanson J.L. Hashikawa Y. Schuman B. Buzsáki G. Rudy B. Id2 GABAergic interneurons: a neglected fourth major group of cortical inhibitory cells.bioRxiv. 2022; (Preprint at)https://doi.org/10.1101/2022.12.01.518752Google Scholar This study uses the established neuroanatomical cell classification scheme to identify cortical neurons because electrophysiology allows morphological reconstruction of >95% of neurons after patch-clamp recordings. In the case of inhibitory neurons, the scheme is based purely on their axonal morphology corresponding to their postsynaptic compartment targets and is thus presumably functionally relevant.5Jiang X. Wang G. Lee A.J. Stornetta R.L. Zhu J.J. The organization of two new cortical interneuronal circuits.Nat. Neurosci. 2013; 16: 210-218https://doi.org/10.1038/nn.3305Google Scholar,19Kubota Y. Karube F. Nomura M. Kawaguchi Y. The diversity of cortical inhibitory synapses.Front. Neural Circ. 2016; 10: 27https://doi.org/10.3389/fncir.2016.00027Google Scholar,29Markram H. Muller E. Ramaswamy S. Reimann M.W. 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The analysis disclosed the modular architectural structure of complex L1 SBC-led disinhibitory neuronal circuits across the cortical areas. The architectural structure indicates that the circuits are specifically designed to achieve the distinctive translaminar (engaging all cortical layers), unidirectional (creating 100% dominance), minicolumnar (enclosing area of ∼150 μm in diameter), and independent (forming 100% autonomy) disinhibition. The architectures immediately construe the principles underlying cortical operation. One key principle is that cortical operation utilizes canonical ∼1,500-neuron minicolumnar circuits as basic functional units to optimize complexity, subtlety, plasticity, variation, and redundancy. Additionally, the study investigated the senescence-accelerated mouse prone 8, an Alzheimer’s disease model, and validated the architectural design of the disinhibitory circuits. Interestingly, the architectural analysis of complex cortical circuits in Alzheimer’s mouse brains revealed age-dependent deficits. The deficits were circuit- and connection-specific and occurred selectively at SBC-disinhibited synapses. These synaptic deficits displayed the characteristic cortical spread observed in Alzheimer’s disease and showed correlations with cognitive impairments. The results suggest a disinhibition mechanism that may contribute to the development and progression of Alzheimer’s disease. To interrogate complex cortical circuits comprising ≥10 types of neurons and multiple circuit motifs, we developed a simultaneous and sequential octuple-sexdecuple whole-cell patch-clamp recording method. Our approach combined automated procedural algorithms for electrode positioning with manual operation to achieve precise gigasealing (see STAR Methods). By utilizing automatic algorithms, we achieved high-efficiency recordings, reducing the time to obtain individual cell recordings to ∼3–5 min (cf. Kodandaramaiah et al.32Kodandaramaiah S.B. Flores F.J. Holst G.L. Singer A.C. Han X. Brown E.N. Boyden E.S. Forest C.R. Multi-neuron intracellular recording in vivo via interacting autopatching robots.Elife. 2018; 7e24656https://doi.org/10.7554/eLife.24656Google Scholar). In the meantime, by making manual gigasealing procedure, we achieved high-quality recordings, preserving the high success rate of first-grade whole-cell recordings from interneurons (>95%), and stellate and pyramidal neurons (>99%) (cf. Jiang et al.5Jiang X. Wang G. Lee A.J. Stornetta R.L. Zhu J.J. The organization of two new cortical interneuronal circuits.Nat. Neurosci. 2013; 16: 210-218https://doi.org/10.1038/nn.3305Google Scholar,6Lee A.J. Wang G. Jiang X. Johnson S.M. Hoang E.T. Lanté F. Stornetta R.L. Beenhakker M.P. Shen Y. Julius Zhu J. Canonical organization of layer 1 neuron-led cortical inhibitory and disinhibitory interneuronal circuits.Cerebr. Cortex. 2015; 25: 2114-2126https://doi.org/10.1093/cercor/bhu020Google Scholar). The octuple-sexdecuple patch-clamp recording method allowed us to effectively study constituent neurons across six cortical layers in complex cortical circuits, as well as investigate synaptic connections among recorded neurons (see Figure 1 as an example). The initial application of octuple-sexdecuple patch-clamp recordings reconstructed sufficient elements, including neurons and their connections, leading to a connection diagram of the L1 SBC-led disinhibitory circuit in the mouse somatosensory cortex (Figures 1A–1C). Morphological reconstruction of recorded neurons revealed putative synaptic contacts under light microscopic examination, confirming the connection diagram disclosed by electrophysiological recordings (cf. Jiang et al.5Jiang X. Wang G. Lee A.J. Stornetta R.L. Zhu J.J. The organization of two new cortical interneuronal circuits.Nat. Neurosci. 2013; 16: 210-218https://doi.org/10.1038/nn.3305Google Scholar,6Lee A.J. Wang G. Jiang X. Johnson S.M. Hoang E.T. Lanté F. Stornetta R.L. Beenhakker M.P. Shen Y. Julius Zhu J. Canonical organization of layer 1 neuron-led cortical inhibitory and disinhibitory interneuronal circuits.Cerebr. Cortex. 2015; 25: 2114-2126https://doi.org/10.1093/cercor/bhu020Google Scholar). The analysis revealed that L1 SBCs inhibited interneurons in deeper cortical layers from L2 to L6, but none of stellate and pyramidal neurons in these layers (Figures 1C–1E). Moreover, the inhibited L2-6 interneurons inhibited a significant proportion of L2-6 stellate and pyramidal neurons (Figures 2A–2C ). These results indicate that L1 SBCs establish translaminar disinhibition on stellate and pyramidal neurons across the deeper cortical layers through L2-6 interneurons. Further analysis revealed the executing direction of L1 SBC-led disinhibitory circuits. While SBCs inhibited all groups of interneurons in L2-6, none of the L2-6 interneurons inhibited SBCs (Figures 2A–2C). In comparison, L1 ENGCs inhibited L1 SBCs (Figures 2A–2C), whereas none of SBCs inhibited ENGCs (Figures 1C–1E). These results indicate that L1 SBCs form unidirectional inhibition on L2-6 interneurons, without receiving any reciprocal inhibition back from L2-6 interneurons. These findings suggest that L1 SBC-led disinhibitory circuits, unlike VIP-containing interneuron-mediated more mutual inhibitory-like circuits,33Campagnola L. Seeman S.C. Chartrand T. Kim L. Hoggarth A. Gamlin C. Ito S. Trinh J. Davoudian P. Radaelli C. et al.Local connectivity and synaptic dynamics in mouse and human neocortex.Science. 2022; 375eabj5861https://doi.org/10.1126/science.abj5861Google Scholar predominantly execute dominative unidirectional disinhibition on excitatory neurons. The majority of L2-6 interneurons inhibited by L1 SBCs were found within small columnar regions surrounding the SBCs (Figures 1D and 1E). Mapping the location of SBC-inhibited L2-6 interneurons, as well as SBC-disinhibited L2-6 stellate and pyramidal neurons, revealed that these inhibitory and excitatory neurons were primarily confined to narrow circular columnar areas with a radius of ∼75 μm. The SBCs were positioned at the top centers of these columnar areas (Figures 1D, 1E, and 2D–2F). These findings demonstrate that L1 SBCs establish columnar or minicolumnar-like disinhibition on cortical L2-6 excitatory neurons through the involvement of L2-6 interneurons. The functional relationship between cortical minicolumns has not been previously explored in research.34Buxhoeveden D.P. Casanova M.F. The minicolumn hypothesis in neuroscience.Brain. 2002; 125: 935-951https://doi.org/10.1093/brain/awf110Google Scholar,35Sporns O. Tononi G. Kötter R. The human connectome: a structural description of the human brain.PLoS Comput. Biol. 2005; 1: e42https://doi.org/10.1371/journal.pcbi.0010042Google Scholar By employing octuple-sexdecuple patch-clamp recordings, we greatly increased the probability of obtaining simultaneous recordings from pairs of L1 SBC-led disinhibitory circuits. This allowed us to investigate whether minicolumnar circuits share common circuit elements (Figure 3). The results demonstrated that simultaneously recorded L1 SBCs inhibited L2-6 interneurons, which in turn inhibited L2-6 stellate and pyramidal neurons located within narrow columnar regions beneath the SBCs. These observations confirm the expected characteristics of translaminar, unidirectional, and minicolumnar disinhibitory circuits (Figures 3A–3F). Interestingly, L2-6 interneurons, stellate, and pyramidal neurons involved in one L1 SBC-led disinhibitory circuit participated into neither inhibition nor disinhibition of the other disinhibitory circuit (Figures 3G and 3H). Collectively, these results indicate that L1 SBCs establish translaminar, unidirectional, minicolumnar, and independent disinhibition on cortical L2-6 excitatory neurons through the involvement of L2-6 interneurons in the somatosensory cortex. The modular architecture of L1 SBC-led disinhibitory circuits in the somatosensory cortex provides the long-sought neuronal circuit basis supporting the “minicolumnar cortical architecture” theory, which purports the existence of translaminar and minicolumnar neuronal circuits in heterotypical cortical areas.36Mountcastle V.B. The columnar organization of the neocortex.Brain. 1997; 120: 701-722Google Scholar Previous studies report that L1 SBCs mediate disinhibition in the motor cortex5Jiang X. Wang G. Lee A.J. Stornetta R.L. Zhu J.J. The organization of two new cortical interneuronal circuits.Nat. Neurosci. 2013; 16: 210-218https://doi.org/10.1038/nn.3305Google Scholar,6Lee A.J. Wang G. Jiang X. Johnson S.M. Hoang E.T. Lanté F. Stornetta R.L. Beenhakker M.P. Shen Y. Julius Zhu J. Canonical organization of layer 1 neuron-led cortical inhibitory and disinhibitory interneuronal circuits.Cerebr. Cortex. 2015; 25: 2114-2126https://doi.org/10.1093/cercor/bhu020Google Scholar and disinhibition appears to exist in the other cortical areas, including the prefrontal cortex.37Anastasiades P.G. Collins D.P. Carter A.G. Mediodorsal and ventromedial thalamus engage distinct L1 circuits in the prefrontal cortex.Neuron. 2021; 109: 314-330.e4https://doi.org/10.1016/j.neuron.2020.10.031Google Scholar Octuple-sexdecuple patch-clamp recordings revealed that L1 SBCs inhibited interneurons in L2-6 without being inhibited by L2-6 interneurons in the motor and prefrontal cortex (Figures 4A–4C , 4E–4G, S1, and S2). Furthermore, while L1 SBCs did not inhibit any pyramidal neurons in L2-6, the L1 SBC-inhibited L2-6 interneurons inhibited pyramidal neurons in the motor and prefrontal cortex (Figures 4A–4C, 4E–4G, S1, and S2). Control experiments demonstrated that L1 ENGCs could inhibit SBCs, but SBCs did not inhibit ENGCs in the motor and prefrontal cortex (Figures 4A–4C, 4E–4G, S1, and S2). Additionally, L1 SBC-inhibited interneurons and -disinhibited L2-6 pyramidal neurons were largely confined within narrow columnar areas of ∼75 μm in radius (Figures 4C, 4D, 4G–4H, S1, and S2). These results indicate that L1 SBC-led disinhibitory circuits in the motor and prefrontal cortex exhibit the same translaminar, unidirectional, and minicolumnar disinhibition seen in the somatosensory cortex, suggesting a generalized architectural design for L1 SBC-led disinhibitory circuits across the neocortex. The medial entorhinal cortex, which acts as an interface between the hippocampus and neocortex, is involves in spatial navigation and memory.40Bellmund J.L.S. Gärdenfors P. Moser E.I. Doeller C.F. Navigating cognition: Spatial codes for human thinking.Science. 2018; 362eaat6766https://doi.org/10.1126/science.aat6766Google Scholar Interestingly, as with the neocortex, the medial entorhinal cortex also displays a minicolumnar-like anatomical structure,41Ray S. Naumann R. Burgalossi A. Tang Q. Schmidt H. Brecht M. Grid-layout and theta-modulation of layer 2 pyramidal neurons in medial entorhinal cortex.Science. 2014; 343: 891-896https://doi.org/10.1126/science.1243028Google Scholar employs two coincident mechanisms for the generation of grid cell firing patterns,42Zheng K. Wang G. Miao C. Murphy R. Simonsen Ø.W. Nilssen E.S. Miyazaki K. Ross W.N. Scott M.M. Deisseroth K. et al.A new commissural mechanism in the medial entorihinal cortex.Soc. Neurosci. Abstr. 2021; 23: P101-P108Google Scholar and possesses hallmark L1 SBCs and ENGCs (Figure S3, see also Shi et al.43Shi Y. Cui H. Li X. Chen L. Zhang C. Zhao X. Li X. Shao Q. Sun Q. Yan K. Wang G. Laminar and dorsoventral organization of layer 1 interneuronal microcircuitry in superficial layers of the medial entorhinal cortex.Cell Rep. 2023; 42: 112782Google Scholar). Octuple-sexdecuple patch-clamp recordings revealed the presence of L1 SBC-led disinhibitory circuits in the medial entorhinal cortex (Figures 4I–4K and S4). These circuits involved entorhinal L1 SBCs disinhibiting L2-6 stellate and pyramidal neurons through the participation of L2-6 interneurons, while no inhibitory feedback from L2-6 interneurons to SBCs was observed (Figures 4I–4K and S4). Moreover, all neuronal components of the entorhinal L1 SBC-led disinhibitory circuit were confined within columnar areas with a radius of ∼75 μm beneath the SBCs (Figures 4K–4L and S4). These results indicate that entorhinal L1 SBC-led disinhibitory circuits exhibit the translaminar, unidirectional, and minicolumnar disinhibition features identical to those in the neocortex. The findings support the idea that the modular organizational architecture is applicable across all cortical areas. Reconstructing sufficient elements, including both neurons and their connections, of L1 SBC-led disinhibitory circuits across somatosensory, motor, prefrontal, and entorhinal cortical areas yields several generalized architectural features (Figures 4M–4Q). First, L1 SBCs inhibit at least ∼30% interneurons and disinhibit at least ∼20% stellate and pyramidal neurons in L2-6 in the cortex (Figures 4M–4N), resulting in the translaminar disinhibition on excitatory neurons. Second, L1 SBCs exhibit 100% unidirectional inhibition on L2-6 interneurons, enabling disinhibition of L2-6 stellate and pyramidal neurons in the cortex (Figure 4O), effectively controlling the output of local pools of cortical excitatory neurons. Third, L1 SBCs inhibit L2-6 interneurons and disinhibit L2-6 stellate and pyramidal neurons within narrow columns of ∼75 μm in radius in the cortex, establis

Kayser C., Melkes B., Derieux C., Bock A.

G protein-coupled receptors (GPCRs) are ligand-activated cell membrane proteins and represent the most important class of drug targets. GPCRs adopt several active conformations that stimulate different intracellular G proteins (and other transducers) and thereby modulate second messenger levels, eventually resulting in receptor-specific cell responses. It is increasingly accepted that not only the type of active signaling protein but also the duration of its stimulation and the subcellular location from where receptors signal distinctly contribute to the overall cell response. However, the molecular principles governing such spatiotemporal GPCR signaling and their role in disease are incompletely understood. Genetically encoded, fluorescent biosensors—in particular for the GPCR/cAMP signaling axis—have been pivotal to the discovery and molecular understanding of novel concepts in spatiotemporal GPCR signaling. These include GPCR priming, location bias, and receptor-associated independent cAMP nanodomains. Here, we review such technologies that we believe will illuminate the spatiotemporal organization of other GPCR signaling pathways that define the complex signaling architecture of the cell.

Szuhany K.L., Simon N.M.

ImportanceAnxiety disorders have a lifetime prevalence of approximately 34% in the US, are often chronic, and significantly impair quality of life and functioning.ObservationsAnxiety disorders are characterized by symptoms that include worry, social and performance fears, unexpected and/or triggered panic attacks, anticipatory anxiety, and avoidance behaviors. Generalized anxiety disorder (6.2% lifetime prevalence), social anxiety disorder (13% lifetime prevalence), and panic disorder (5.2% lifetime prevalence) with or without agoraphobia are common anxiety disorders seen in primary care. Anxiety disorders are associated with physical symptoms, such as palpitations, shortness of breath, and dizziness. Brief screening measures applied in primary care, such as the Generalized Anxiety Disorder–7, can aid in diagnosis of anxiety disorders (sensitivity, 57.6% to 93.9%; specificity, 61% to 97%). Providing information about symptoms, diagnosis, and evidence-based treatments is a first step in helping patients with anxiety. First-line treatments include pharmacotherapy and psychotherapy. Selective serotonin reuptake inhibitors (SSRIs, eg, sertraline) and serotonin-norepinephrine reuptake inhibitors (SNRIs, eg, venlafaxine extended release) remain first-line pharmacotherapy for generalized anxiety disorder, social anxiety disorder, and panic disorder. Meta-analyses suggest that SSRIs and SNRIs are associated with small to medium effect sizes compared with placebo (eg, generalized anxiety disorder: standardized mean difference [SMD], −0.55 [95% CI, −0.64 to −0.46]; social anxiety disorder: SMD, −0.67 [95% CI, −0.76 to −0.58]; panic disorder: SMD, −0.30 [95% CI, −0.37 to −0.23]). Cognitive behavioral therapy is the psychotherapy with the most evidence of efficacy for anxiety disorders compared with psychological or pill placebo (eg, generalized anxiety disorder: Hedges g = 1.01 [large effect size] [95% CI, 0.44 to 1.57]; social anxiety disorder: Hedges g = 0.41 [small to medium effect] [95% CI, 0.25 to 0.57]; panic disorder: Hedges g = 0.39 [small to medium effect[ [95% CI, 0.12 to 0.65]), including in primary care. When selecting treatment, clinicians should consider patient preference, current and prior treatments, medical and psychiatric comorbid illnesses, age, sex, and reproductive planning, as well as cost and access to care.Conclusions and RelevanceAnxiety disorders affect approximately 34% of adults during their lifetime in the US and are associated with significant distress and impairment. First-line treatments for anxiety disorders include cognitive behavioral therapy, SSRIs such as sertraline, and SNRIs such as venlafaxine extended release.

Sun N., Qin Y., Xu C., Xia T., Du Z., Zheng L., Li A., Meng F., Zhang Y., Zhang J., Liu X., Li T., Zhu D., Zhou Q.

Major depressive disorder (MDD) is one of the most common mental disorders. We designed a fast-onset antidepressant that works by disrupting the interaction between the serotonin transporter (SERT) and neuronal nitric oxide synthase (nNOS) in the dorsal raphe nucleus (DRN). Chronic unpredictable mild stress (CMS) selectively increased the SERT-nNOS complex in the DRN in mice. Augmentation of SERT-nNOS interactions in the DRN caused a depression-like phenotype and accounted for the CMS-induced depressive behaviors. Disrupting the SERT-nNOS interaction produced a fast-onset antidepressant effect by enhancing serotonin signaling in forebrain circuits. We discovered a small-molecule compound, ZZL-7, that elicited an antidepressant effect 2 hours after treatment without undesirable side effects. This compound, or analogous reagents, may serve as a new, rapidly acting treatment for MDD.

Zheng W.S., Zhang Y., Zhu R.E., Zhang P., Gupta S., Huang L., Sahoo D., Guo K., Glover M.E., Vadodaria K.C., Li M., Qian T., Jing M., Feng J., Wan J., et. al.

Intercellular communication mediated by a large number of neuromodulators diversifies physiological actions, yet neuromodulation remains poorly understood despite the recent upsurge of genetically encoded transmitter sensors. Here, we report the development of a versatile genetically encoded sensor-based image analysis program (GESIAP) that utilizes MATLAB-based algorithms to achieve high-throughput, high-resolution processing of sensor-based functional imaging data. GESIAP enables delineation of fundamental properties (e.g., transmitter spatial diffusion extent, quantal size, quantal content, release probability, pool size, and refilling rate at single release sites) of transmission mediated by various transmitters (i.e., monoamines, acetylcholine, neuropeptides, and glutamate) at various cell types (i.e., neurons, astrocytes, and other non-neuronal cells) of various animal species (i.e., mouse, rat, and human). Our analysis appraises a dozen of newly developed transmitter sensors, validates a conserved model of restricted non-volume neuromodulatory synaptic transmission, and accentuates a broad spectrum of presynaptic release properties that variegate neuromodulation.

Yasuda R., Hayashi Y., Hell J.W.

Calcium–calmodulin (CaM)-dependent protein kinase II (CaMKII) is the most abundant protein in excitatory synapses and is central to synaptic plasticity, learning and memory. It is activated by intracellular increases in calcium ion levels and triggers molecular processes necessary for synaptic plasticity. CaMKII phosphorylates numerous synaptic proteins, thereby regulating their structure and functions. This leads to molecular events crucial for synaptic plasticity, such as receptor trafficking, localization and activity; actin cytoskeletal dynamics; translation; and even transcription through synapse–nucleus shuttling. Several new tools affording increasingly greater spatiotemporal resolution have revealed the link between CaMKII activity and downstream signalling processes in dendritic spines during synaptic and behavioural plasticity. These technologies have provided insights into the function of CaMKII in learning and memory. Calcium–calmodulin (CaM)-dependent protein kinase II (CaMKII) has a central role in synaptic plasticity, learning and memory. In this Review, Yasuda, Hayashi and Hell provide an overview of the postsynaptic regulation and function of CaMKII.

Paquelet G.E., Carrion K., Lacefield C.O., Zhou P., Hen R., Miller B.R.

The serotonin system modulates a wide variety of emotional behaviors and states, including reward processing, anxiety, and social interaction. To reveal the underlying patterns of neural activity, we visualized serotonergic neurons in the dorsal raphe nucleus (DRN5-HT) of mice using miniaturized microscopy during diverse emotional behaviors. We discovered ensembles of cells with highly correlated activity and found that DRN5-HT neurons are preferentially recruited by emotionally salient stimuli as opposed to neutral stimuli. Individual DRN5-HT neurons responded to diverse combinations of salient stimuli, with some preference for valence and sensory modality. Anatomically defined subpopulations projecting to either a reward-related structure (the ventral tegmental area) or an anxiety-related structure (the bed nucleus of the stria terminalis) contained all response types but were enriched in reward- and anxiety-responsive cells, respectively. Our results suggest that the DRN serotonin system responds to emotional salience using ensembles with mixed selectivity and biases in downstream connectivity.

Moncrieff J., Cooper R.E., Stockmann T., Amendola S., Hengartner M.P., Horowitz M.A.

The serotonin hypothesis of depression is still influential. We aimed to synthesise and evaluate evidence on whether depression is associated with lowered serotonin concentration or activity in a systematic umbrella review of the principal relevant areas of research. PubMed, EMBASE and PsycINFO were searched using terms appropriate to each area of research, from their inception until December 2020. Systematic reviews, meta-analyses and large data-set analyses in the following areas were identified: serotonin and serotonin metabolite, 5-HIAA, concentrations in body fluids; serotonin 5-HT1A receptor binding; serotonin transporter (SERT) levels measured by imaging or at post-mortem; tryptophan depletion studies; SERT gene associations and SERT gene-environment interactions. Studies of depression associated with physical conditions and specific subtypes of depression (e.g. bipolar depression) were excluded. Two independent reviewers extracted the data and assessed the quality of included studies using the AMSTAR-2, an adapted AMSTAR-2, or the STREGA for a large genetic study. The certainty of study results was assessed using a modified version of the GRADE. We did not synthesise results of individual meta-analyses because they included overlapping studies. The review was registered with PROSPERO (CRD42020207203). 17 studies were included: 12 systematic reviews and meta-analyses, 1 collaborative meta-analysis, 1 meta-analysis of large cohort studies, 1 systematic review and narrative synthesis, 1 genetic association study and 1 umbrella review. Quality of reviews was variable with some genetic studies of high quality. Two meta-analyses of overlapping studies examining the serotonin metabolite, 5-HIAA, showed no association with depression (largest n = 1002). One meta-analysis of cohort studies of plasma serotonin showed no relationship with depression, and evidence that lowered serotonin concentration was associated with antidepressant use (n = 1869). Two meta-analyses of overlapping studies examining the 5-HT1A receptor (largest n = 561), and three meta-analyses of overlapping studies examining SERT binding (largest n = 1845) showed weak and inconsistent evidence of reduced binding in some areas, which would be consistent with increased synaptic availability of serotonin in people with depression, if this was the original, causal abnormaly. However, effects of prior antidepressant use were not reliably excluded. One meta-analysis of tryptophan depletion studies found no effect in most healthy volunteers (n = 566), but weak evidence of an effect in those with a family history of depression (n = 75). Another systematic review (n = 342) and a sample of ten subsequent studies (n = 407) found no effect in volunteers. No systematic review of tryptophan depletion studies has been performed since 2007. The two largest and highest quality studies of the SERT gene, one genetic association study (n = 115,257) and one collaborative meta-analysis (n = 43,165), revealed no evidence of an association with depression, or of an interaction between genotype, stress and depression. The main areas of serotonin research provide no consistent evidence of there being an association between serotonin and depression, and no support for the hypothesis that depression is caused by lowered serotonin activity or concentrations. Some evidence was consistent with the possibility that long-term antidepressant use reduces serotonin concentration.