Journal of Neuroscience最新文献

The primary cilium, a single microtubule-based organelle protruding from the cell surface and critical for neural development, also functions in adult neurons. While some dorsal root ganglion neurons elaborate a primary cilium, whether it is expressed by and functional in nociceptors is unknown. Recent studies have shown the role of Hedgehog, whose canonical signaling is primary cilium dependent, in nociceptor sensitization. We establish the presence of primary cilia in soma of rat nociceptors, where they contribute to mechanical threshold, prostaglandin E₂ (PGE₂)-induced hyperalgesia, and chemotherapy-induced neuropathic pain (CIPN). Intrathecal administration of siRNA targeting Ift88, a primary cilium-specific intraflagellar transport (IFT) protein required for ciliary integrity, resulted in attenuation of Ift88 mRNA and nociceptor primary cilia. Attenuation of primary cilia was associated with an increase in mechanical nociceptive threshold in vivo and decrease in nociceptor excitability in vitro, abrogation of hyperalgesia, and nociceptor sensitization induced by both a prototypical pronociceptive inflammatory mediator PGE₂ and paclitaxel CIPN, in a sex-specific fashion. siRNA targeting Ift52, another IFT protein, and knockdown of NompB, the Drosophila Ift88 ortholog, also abrogated CIPN and reduced baseline mechanosensitivity, respectively, providing independent confirmation for primary cilia control of nociceptor function. Hedgehog-induced hyperalgesia is attenuated by Ift88 siRNA, supporting the role for primary cilia in Hedgehog-induced hyperalgesia. Attenuation of CIPN by cyclopamine (intradermal and intraganglion), which inhibits Hedgehog signaling, supports the role of Hedgehog in CIPN. Our findings support the role of the nociceptor primary cilium in control of mechanical nociceptive threshold and inflammatory and neuropathic pain, the latter Hedgehog-dependent.

Chronic pain remains a significant health challenge with limited effective treatments. This study investigates the metabolic changes underlying pain progression and resolution, uncovering a novel compensatory mechanism in sensory neurons. Using the hyperalgesic priming model in male mice, we demonstrate that nerve growth factor (NGF) initially disrupted mitochondrial pyruvate oxidation, leading to acute allodynia. Surprisingly, this metabolic disruption persisted even after the apparent resolution of allodynia. We discovered that during the resolution phase, sensory neurons exhibit increased glutamine oxidation and upregulation of the major glutamine transporter ASCT2 in dorsal root ganglia. This compensatory response plays a crucial role in pain resolution, as demonstrated by our experiments. Knockdown of ASCT2 prevents the resolution of NGF-induced allodynia and precipitates the transition to a chronic state. Furthermore, we show that the glutamine catabolite α-ketoglutarate attenuated glycolytic flux and alleviated allodynia in both acute and chronic phases of the hyperalgesic priming model. The importance of ASCT2 is further confirmed in a translational model, where its knockdown prevented the resolution of allodynia following plantar incision. These findings highlight the pivotal role of metabolic changes in pain resolution and identify ASCT2-mediated glutamine metabolism as a potential therapeutic target for chronic pain. Understanding these endogenous mechanisms that promote pain resolution can guide the development of novel interventions to prevent the transition pain from acute to chronic.

Sequential information permeates daily activities, such as when watching for the correct series of buildings to determine when to get off the bus or train. These sequences include periodicity (the spacing of the buildings), the identity of the stimuli (the kind of house), and higher-order more abstract rules that may not depend on the exact stimulus (e.g., house, house, house, business). Previously, we found that the posterior fundus of area 46 in the monkey lateral prefrontal cortex (LPFC) responds to rule changes in such abstract visual sequences. However, it is unknown if this region responds to other components of the sequence, i.e., image periodicity and identity, in isolation. Further, it is unknown if this region dissociates from other, more ventral LPFC subregions that have been associated with sequences and their components. To address these questions, we used awake functional magnetic resonance imaging in three male macaque monkeys during two no-report visual tasks. One task contained abstract visual sequences, and the other contained no visual sequences but maintained the same image periodicity and identities. We found the fundus of area 46 responded only to abstract sequence rule violations. In contrast, the ventral bank of area 46 responded to changes in image periodicity and identity, but not changes in the abstract sequence. These results suggest a functional specialization within anatomical substructures of LPFC to signal different kinds of stimulus regularities. This specialization may provide key scaffolding to identify abstract patterns and construct complex models of the world for daily living.

Dopaminergic neurotransmission plays a crucial role in motor function through the coordination of dopamine receptor (DRD) subtypes, such as DRD1 and DRD2, thus the functional imbalance of these receptors can lead to Parkinson's disease. However, due to the complexity of dopaminergic circuits in the brain, it is limited to investigating the individual functions of each DRD subtype in specific brain regions. Here, we developed a light-responsive chimeric DRD2, OptoDRD2, which can selectively activate DRD2-like signaling pathways with spatiotemporal resolution. OptoDRD2 was designed to include the light-sensitive component of rhodopsin and the intracellular signaling domain of DRD2. Upon illumination with blue light, OptoDRD2 triggered DRD2-like signaling pathways, such as Gαi/o subtype recruitment, a decrease in cAMP levels, and ERK phosphorylation. To explore unknown roles of DRD2 in glutamatergic cell populations of basal ganglia circuitry, OptoDRD2 was genetically expressed in excitatory neurons in lateral globus pallidus (LGP) of the male mouse brain. The optogenetic stimulation of OptoDRD2 in the LGP region affected a wide range of locomotion-related parameters, such as increased frequency of movement and decreased immobility time, resulting in the facilitation of motor function of living male mice. Therefore, our findings indicate a potential novel role for DRD2 in the excitatory neurons of the LGP region, suggesting that OptoDRD2 can be a valuable tool enabling the investigation of unknown roles of DRD2 at specific cell types or brain regions.Significance Statement We developed a light-responsive chimeric dopamine receptor type 2, OptoDRD2, by combining the blue-light sensing part of rhodopsin and intracellular functional regions of DRD2. OptoDRD2 can selectively trigger DRD2-like downstream signaling pathways upon illumination of blue light. To explore unknown roles of DRD2 in glutamatergic cell populations of basal ganglia circuitry, OptoDRD2 was genetically expressed in excitatory neurons at lateral globus pallidus (LGP) in the mouse brain. Optogenetic stimulation of OptoDRD2 in living mice suggested a potential novel function of DRD2 in the LGP that enhances motor outputs. Therefore, OptoDRD2 enabled the precise control of DRD2-like signaling in specific cell types and brain regions, allowing the exploration of potential novel DRD2 functions in living mice.

Macaque area V4 includes neurons that exhibit exquisite selectivity for visual form and surface texture, but their functional organization across laminae is unknown. We used high-density Neuropixels probes in two awake monkeys (one female and one male) to characterize shape and texture tuning of dozens of neurons simultaneously across layers. We found sporadic clusters of neurons that exhibit similar tuning for shape and texture: ∼20% exhibited similar tuning with their neighbors. Importantly, these clusters were confined to a few layers, seldom 'columnar' in structure. This was the case even when neurons were strongly driven, and exhibited robust contrast invariance for shape and texture tuning. We conclude that functional organization in area V4 is not columnar for shape and texture stimulus features and in general organization maybe at a coarser stimulus category scale (e.g. selectivity for stimuli with vs without 3D cues), and a coarser spatial scale (assessed by optical imaging), rather than at a fine scale in terms of similarity in single neuron tuning for specific features. We speculate that this may be a direct consequence of the great diversity of inputs integrated by V4 neurons to build variegated tuning manifolds in a high-dimensional space.Significance Statement In the primary visual cortex of the macaque monkey, studies have demonstrated columnar functional organization, i.e. shared tuning across layers for stimulus orientation, spatial frequency, ocular dominance, etc. In mid and higher level visual form processing stages, where neurons exhibit high-dimensional tuning, functional organization has been harder to evaluate. Here, leveraging the use of the high-density Neuropixels probes to record simultaneously from dozens of neurons across cortical layers, we demonstrate that functional organization is not columnar for shape and texture tuning in area V4, a midlevel stage critical for form processing. Our results contribute to the debate about the functional significance of cortical columns providing support to the idea that they emerge due to one-to-many representational expansion.

NMDA-type glutamate receptors are heterotetrameric complexes composed of two GluN1 and two GluN2 subunits. The precise composition of the GluN2 subunits determines the channel's biophysical properties and influences its interaction with postsynaptic scaffolding proteins and signaling molecules involved in synaptic physiology and plasticity. The precise regulation of NMDAR subunit composition at synapses is crucial for proper synaptogenesis, neuronal circuit development, and synaptic plasticity, a cellular model of memory formation.In the forebrain during early development, NMDARs contain solely the GluN2B subunit, which is necessary for proper synaptogenesis and synaptic plasticity. In rodents, GluN2A subunit expression begins in the second postnatal week, replacing GluN2B-containing NMDARs at synapses in an activity- or sensory experience-dependent process. This switch in NMDAR subunit composition at synapses alters channel properties and reduces synaptic plasticity. The molecular mechanism regulating the switch remains unclear.We have investigated the role of activity-dependent internalization of GluN2B-containing receptors in shaping synaptic NMDAR subunit composition. Using molecular, pharmacological, and electrophysiological approaches in cultured organotypic hippocampal slices from rats of both sexes, we show that the process of incorporating GluN2A-containing NMDARs receptors requires activity-dependent internalization of GluN2B-containing NMDARs. Interestingly, blockade of GluN2A synaptic incorporation was associated with impaired potentiation of AMPA-mediated synaptic transmission, suggesting a potential coupling between the trafficking of AMPARs into synapses and that of GluN2A-containing NMDARs.These insights contribute to our understanding of the molecular mechanisms underlying synaptic trafficking of glutamate receptors and synaptic plasticity. They may also have implications for therapeutic strategies targeting NMDAR function in neurological disorders.Significance statement NMDARs play a critical role in synaptogenesis, synaptic stability, and activity-dependent regulation of synaptic strength. The developmental switch in their GluN2 subunits composition is part of normal synapse development and crucial for proper synaptic physiology, plasticity, and the formation of functional neuronal circuits, though the mechanisms governing it remain unclear. We show that internalization of GluN2B-containing NMDARs is required for synaptic incorporation of GluN2A-containing receptors. This process can be induced by long-term potentiation and requires Ca⁺² Notably, GluN2A trafficking to synapses is linked to the incorporation of AMPA-type glutamate receptors, suggesting a shared pathway for synaptic incorporation. These findings provide greater insight into the molecular mechanisms behind glutamate receptor trafficking and synaptic plasticity, potentially informing therapeutic strategies for neurological disorders.

The cAMP-response element binding protein (CREB) transcription factor controls the expression of the neuronal immediate early genes c-Fos, Arc, and Bdnf and is essential for long-lasting synaptic plasticity underlying learning and memory. Despite this critical role, there is still ongoing debate regarding the synaptic excitation-transcription (E-T) coupling mechanisms mediating CREB activation in the nucleus. Here we employed optical uncaging of glutamate to mimic synaptic excitation of distal dendrites in conjunction with simultaneous imaging of intracellular Ca²⁺ dynamics and transcriptional reporter gene expression to elucidate CREB E-T coupling mechanisms in hippocampal neurons cultured from both male and female rats. Using this approach, we found that CREB-dependent transcription was engaged following dendritic stimulation of N-methyl, D-aspartate receptors (NMDARs) only when Ca²⁺ signals propagated to the soma via subsequent activation of L-type voltage-gated Ca²⁺ channels resulting in activation of Extracellular signal-Regulated Kinase (ERK) MAP kinase signaling to sustain CREB phosphorylation in the nucleus. In contrast, dendrite-restricted Ca²⁺ signals generated by NMDARs failed to stimulate CREB-dependent transcription. Furthermore, Ca²⁺-CaM-dependent kinase (CaMK)-mediated signaling pathways that may transiently contribute to CREB-phosphorylation following stimulation were ultimately dispensable for downstream CREB-dependent transcription and c-Fos induction. These findings emphasize the essential role that L-type Ca²⁺ channels play in rapidly relaying signals over long distances from synapses located on distal dendrites to the nucleus to control gene expression.Significance Statement The transcription factor CREB controls gene expression programs required for long-lasting synaptic plasticity and learning and memory, yet the synapse-to-nucleus signaling mechanisms mediating CREB activation are still unclear. Using glutamate uncaging to mimic synaptic input to dendrites, this study shows that Ca²⁺ signals propagated to the soma by L-type voltage-gated Ca²⁺ channels engage the ERK MAP kinase cascade to mediate CREB phosphorylation and CREB-dependent transcription. In contrast, dendrite-restricted Ca²⁺ signals generated primarily by NMDARs failed to effectively engage this signaling pathway or CREB-dependent transcription. In addition, we found that while ERK and CaMK pathways may both contribute to increased CREB phosphorylation immediately following neuronal stimulation, sustained ERK signaling to CREB was necessary to effectively drive CREB-dependent transcription.

To comprehend speech, human brains identify meaningful units in the speech stream. But whereas the English 'She believed him.' has 3 word-units, the Arabic equivalent 'ṣaddaqathu.' is a single word-unit with 3 meaningful sub-word units, called morphemes: a verb stem ('ṣaddaqa'), a subject suffix ('-t-'), and a direct object pronoun ('-hu'). It remains unclear whether and how the brain processes morphemes, above and beyond other language units, during speech comprehension. Here, we propose and test hierarchically-nested encoding models of speech comprehension: a naïve model with word-, syllable-, and sound-level information; a bottom-up model with additional morpheme boundary information; and predictive models that process morphemes before these boundaries. We recorded magnetoencephalography (MEG) data as 27 participants (16 female) listened to Arabic sentences like 'ṣaddaqathu.'. A temporal response function (TRF) analysis revealed that in temporal and left inferior frontal regions predictive models outperform the bottom-up model, which outperforms the naïve model. Moreover, verb stems were either length-ambiguous (e.g., 'ṣaddaqa' could initially be mistaken for the shorter stem 'ṣadda'='blocked') or length-unambiguous (e.g., 'qayyama'='evaluated' cannot be mistaken for a shorter stem), but shared a uniqueness point, beyond which stem identity is fully disambiguated. Evoked analyses revealed differences between conditions before the uniqueness point, suggesting that, rather than await disambiguation, the brain employs proactive predictive strategies, processing accumulated input as soon as any possible stem is identifiable, even if not uniquely. These findings highlight the role of morphemes in speech, and the importance of including morpheme-level information in neural and computational models of speech comprehension.Significance statement Many leading models of speech comprehension include information about words, syllables and sounds. But languages vary considerably in the amount of meaning packed into word units. This work proposes speech comprehension models with information about meaningful sub-word units, called morphemes (e.g., 'bake-' and '-ing' in 'baking'), and shows that they explain significantly more neural activity than models without morpheme information. We also show how the brain predictively processes morphemic information. These findings highlight the role of morphemes in speech comprehension and emphasize the contributions of morpheme-level information-theoretic metrics, like surprisal and entropy. Our findings can be used to update current neural, cognitive, and computational models of speech comprehension, and constitute a step towards refining those models for naturalistic, connected speech.

Learning occurs across multiple timescales, with fast learning crucial for adapting to sudden environmental changes, and slow learning beneficial for extracting robust knowledge from multiple events. Here we asked if miscalibrated fast vs slow learn-ing can lead to maladaptive decision-making in individuals with problem gambling. We recruited participants with problem gambling (PG; N=20; 9 female and 11 male) and a recreational gambling control group without any symptoms associated with problem gambling (N=20; 10 female and 10 male) from the community in Los Ange-les, CA. Participants performed a decision-making task involving reward-learning and loss-avoidance while being scanned with fMRI. Using computational model fitting, we found that individuals in the PG group showed evidence for an excessive dependence on slow timescales and a reduced reliance on fast timescales during learning. fMRI data implicated the putamen, an area associated with habit, and medial prefrontal cortex (PFC) in slow loss-value encoding, with significantly more robust encoding in medial PFC in the PG group compared to controls. The PG group also exhibited stronger loss prediction error encoding in the insular cortex. These findings suggest that individuals with PG have an impaired ability to adjust their predictions following losses, manifested by a stronger influence of slow value learning. This impairment could contribute to the behavioral inflexibility of problem gamblers, particularly the persistence in gambling behavior typically observed in those individuals after incur-ring loss outcomes.Significance Statement Over five million American adults are considered to experience problem gambling, leading to financial and social devastation. Yet the neural basis of problem gambling remains elusive, impeding the development of effective treatments. We apply computational modeling and neuroimaging to understand the mechanisms underlying problem gambling. In a decision-making task involving reward-learning and loss-avoidance, individuals with problem gambling show an impaired behavioral adjustment following losses. Computational model-driven analyses suggest that, while all participants relied on learning over both fast and slow timescales, individuals with problem gambling showed increased reliance on slow-learning from losses. Neuroimaging identified the putamen, medial prefrontal cortex, and insula as key brain regions in this learning disparity. This research offers new insights into the altered neural computations underlying problem gambling.

A key challenge in understanding the functional organisation of visual cortex stems from the fact that only a small proportion of the objects experienced during natural viewing can be presented in a typical experiment. This constraint often leads to experimental designs that compare responses to objects from experimenter-defined stimulus conditions, potentially limiting the interpretation of the data. To overcome this issue, we used images from the THINGS initiative, which provides a systematic sampling of natural objects. A data-driven analysis was then applied to reveal the functional organisation of the visual brain, incorporating both perceptual and neural responses to these objects. Perceptual properties of the objects were taken from an analysis of similarity judgements, and neural properties were taken from whole brain fMRI responses to the same objects. Partial least squares regression (PLSR) was then used to predict neural responses across the brain from the perceptual properties while simultaneously applying dimensionality reduction. The PLSR model accurately predicted neural responses across visual cortex using only a small number of components. These components revealed smooth, graded neural topographies, which were similar in both hemispheres, and captured a variety of object properties including animacy, real-world size, and object category. However, they did not accord in any simple way with previous theoretical perspectives on object perception. Instead, our findings suggest that visual cortex encodes information in a statistically efficient manner, reflecting natural variability among objects.Significance statement The ability to recognise objects is fundamental to how we interact with our environment, yet the organising principles underlying neural representations of visual objects remain contentious. In this study, we sought to address this question by analysing perceptual and neural responses to a large, unbiased sample of objects. Using a data-driven approach, we leveraged perceptual properties of objects to predict neural responses using a small number of components. This model predicted neural responses with a high degree of accuracy across visual cortex. The components did not directly align with previous explanations of object perception. Instead, our findings suggest the organisation of the visual brain is based on the statistical properties of objects in the natural world.