Production of rapid movement sequences relies on preparation before (pre-planning) and during (online planning) movement. Here, we compared these processes and asked whether they recruit different cortical areas. Human participants performed three single-finger and three multi-finger sequences in a delayed movement paradigm while undergoing 7T functional MRI. During preparation, primary motor (M1) and somatosensory (S1) areas showed pre-activation of the first movement, even without increases in overall activation. During production, the temporal summation of activity patterns corresponding to constituent fingers explained activity in these areas (M1 and S1). In contrast, the dorsal premotor cortex (PMd) and anterior superior parietal lobule (aSPL) showed substantial activation during the preparation (pre-planning) of multi-finger compared to single-finger sequences. These regions (PMd and aSPL) were also more active during production of multi-finger sequences, suggesting that pre- and online planning may recruit the same regions. However, we observed small but robust differences between the two contrasts, suggesting distinct contributions to pre- and online planning. Multivariate analysis revealed sequence-specific representations in both PMd and aSPL, which remained stable across both preparation and production phases. Our analyses show that these areas maintain a sequence-specific representation before and during sequence production, likely guiding the execution-related areas in the production of rapid movement sequences. Understanding how the brain orchestrates complex behavior remains a core challenge in human neuroscience. Here, we combine high-resolution neuroimaging and a carefully crafted design to study the neural control of rapid sequential finger movements, like typing or playing the piano. Advancing prior research, we show that the brain areas involved in planning these movements maintain those representations throughout the execution of the sequence. This representational stability across planning and execution suggests an intricate connection between these processes. Our results shed light on the nuanced contributions of different cortical areas to different aspects of coordinating skilled movement. This work is well placed to inform future research in animal models and the development of targeted interventions against movement disorders.

Understanding how heterogeneous neural populations represent sensory input to give rise to behavior remains a central problem in systems neuroscience. Here we investigated how midbrain neurons within the electrosensory system of code for object location in space. In vivo simultaneous recordings were achieved via Neuropixels probes, high-density electrode arrays, with the stimulus positioned at different locations relative to the animal. Midbrain neurons exhibited heterogeneous response profiles, with a significant proportion (65%) seemingly non-responsive to moving stimuli. Remarkably, we found that non-responsive neurons increased population coding of object location through synergistic interactions with responsive neurons by effectively reducing noise. Mathematical modeling demonstrated that increased response heterogeneity together with the experimentally observed correlations was sufficient to give rise to independent encoding by responsive neurons. Further, addition of non-responsive neurons in the model gave rise to synergistic population coding. Taken together, our findings reveal that non-responsive neurons, which are frequently excluded from analysis, can significantly improve population coding of object location through synergistic interactions with responsive neurons. Combinations of responsive and non-responsive neurons have been observed in sensory systems across taxa; it is likely that similar synergistic interactions improve population coding across modalities and behavioral tasks. Here we show that including the activities of non-responsive neurons with those of responsive neurons increases Fisher information about stimulus location. Further analysis revealed that this is because including non-responsive neurons led to reduced noise levels for responsive neurons. A combination of multi-unit recordings from neural populations and mathematical modeling reveals that response heterogeneity and spatially decaying correlations are necessary to observe this effect. It is likely that synergistic population coding by responsive and non-responsive neurons will be observed in other systems.

Cognitive models of reading assume that speech production occurs after visual and phonological processing of written words. This traditional view is at odds with more recent magnetoencephalography studies showing that the left posterior inferior frontal cortex (pIFC) classically associated with spoken production responds to print at 100-150 ms after word-onset, almost simultaneously with posterior brain regions for visual and phonological processing. Yet the theoretical significance of this fast neural response remains open to date. We used transcranial magnetic stimulation (TMS) to investigate how the left pIFC contributes to the early stage of reading. In Experiment 1, 23 adult participants (14 females) performed three different tasks about written words (oral reading, semantic judgment and perceptual judgment) while single-pulse TMS was delivered to the left pIFC, fusiform gyrus or supramarginal gyrus at different time points (50 to 200 ms after word-onset). A robust double dissociation was found between tasks and stimulation sites - oral reading, but not other control tasks, was disrupted only when TMS was delivered to pIFC at 100 ms. This task-specific impact of pIFC stimulation was further corroborated in Experiment 2, which revealed another double dissociation between oral reading and picture naming. These results demonstrate that the left pIFC specifically and causally mediates rapid computation of speech motor codes at the earliest stage of reading and suggest that this fast sublexical neural pathway for pronunciation, although seemingly dormant, is fully functioning in literate adults. Our results further suggest that these left-hemisphere systems for reading overall act faster than known previously. Recent neuroimaging data suggest that left posterior inferior frontal cortex, classically associated with spoken production, responds to print simultaneously with left fusiform and supramarginal gyri, each responsible for visual and phonological processing, contrary to traditional serial cascade models of reading. While the region is now known to mediate different aspects of cognitive processing, the functional significance of this fast neural response remains unclear. Using transcranial magnetic stimulation, we show that early inferior frontal activation plays a specific and causal role in speeded oral reading at 100 ms after word-onset. This fast sublexical neural pathway for pronunciation, although seemingly dormant, is fully functioning in literate adults. We also propose that the left-hemisphere reading systems act differently and faster than known previously.

Retinal ganglion cells (RGCs) are the neuronal connections between the eye and the brain conveying multiple features of the outside world through parallel pathways. While there is a large body of literature how these pathways arise in the retinal network, the process of converting presynaptic inputs into RGC spiking output is little understood. In this study, we show substantial differences in the spike generator across three types of alpha RGCs in female and male mice, the αON sustained, αOFF sustained and αOFF transient RGC. The differences in their intrinsic spiking responses match the differences of the light responses across RGC types. While sustained RGC types have spike generators that are able to generate sustained trains of action potentials at high rates, the transient RGC type fired shortest action potentials enabling it to fire high-frequency transient bursts. The observed differences were also present in late-stage photoreceptor-degenerated retina demonstrating long-term functional stability of RGC responses even when presynaptic circuitry is deteriorated for long periods of time. Our results demonstrate that intrinsic cell properties support the presynaptic retinal computation and are, once established, independent of them. Spiking output from retinal ganglion cells (RGCs) has long been thought to be solely determined by synaptic inputs from the retinal network. We show that the cell-intrinsic spike generator varies across RGC populations and therefore that postsynaptic processing shapes retinal spiking output in three types of mouse alpha RGCs (αRGCs). While sustained αRGC types have spike generators that are able to generate sustained trains of action potentials at high rates, the transient αRGC type fired shortest action potentials enabling them to fire high-frequency transient bursts. Computational modeling suggests that intrinsic response differences are not driven by dendritic morphology but by somatodendritc biophysics. After photoreceptor degeneration, the observed variability is preserved indicating stable physiology across the three αRGC types.

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. 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.

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. 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.

Anxiety elicits various physiological responses, including changes in respiratory rate and neuronal activity within specific brain regions such as the medial prefrontal cortex (mPFC). Previous research suggests that the olfactory bulb (OB) modulates the mPFC through respiration-coupled neuronal oscillations (RCOs), which have been linked to fear-related freezing behavior. Nevertheless, the impact of breathing on frontal brain networks during other negative emotional responses, such as anxiety-related states characterized by higher breathing rates, remains unclear. To address this, we subjected rats to the elevated plus maze (EPM) paradigm while simultaneously recording respiration and local field potentials in the OB and mPFC. Our findings demonstrate distinct respiratory patterns during EPM exploration: slower breathing frequencies prevailed in the closed arms, whereas faster frequencies were observed in the open arms, independent of locomotor activity, indicating that anxiety-like states are associated with increased respiratory rates. Additionally, we identified RCOs at different frequencies, mirroring the bimodal distribution of respiratory frequencies. RCOs exhibited higher power during open arm exploration, when they showed greater coherence with breathing at faster frequencies. Furthermore, we confirmed that nasal respiration drives RCOs in frontal brain regions, and found a stronger effect during faster breathing. Interestingly, we observed that the frequency of prefrontal gamma oscillations modulated by respiration increased with breathing frequency. Overall, our study provides evidence for a significant influence of breathing on prefrontal cortex networks during anxious states, shedding light on the complex interplay between respiratory physiology and emotional processing. Understanding how breathing influences brain activity during anxious states could pave the way for novel therapeutic interventions targeting respiratory control to alleviate anxiety symptoms. Our study uncovers a crucial link between respiratory patterns and anxiety-related neural activity in the brain. By investigating the interplay between breathing, neuronal oscillations, and emotional states, we reveal that anxiety induces distinct respiratory patterns, with higher breathing rates correlating with anxious behavior. Importantly, we demonstrate that respiration drives oscillatory activity in the prefrontal cortex, and this effect is potentiated during the fast breathing associated with anxiety. Furthermore, faster breathing modulates the emergence of faster prefrontal gamma oscillations. This discovery sheds new light on the intricate relationship between respiratory physiology and emotional processing.

The cAMP-response element binding protein (CREB) transcription factor controls the expression of the neuronal immediate early genes , , and 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 Ca 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 Ca signals propagated to the soma via subsequent activation of L-type voltage-gated Ca channels resulting in activation of Extracellular signal-Regulated Kinase (ERK) MAP kinase signaling to sustain CREB phosphorylation in the nucleus. In contrast, dendrite-restricted Ca signals generated by NMDARs failed to stimulate CREB-dependent transcription. Furthermore, Ca-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 Ca channels play in rapidly relaying signals over long distances from synapses located on distal dendrites to the nucleus to control gene expression. 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 Ca signals propagated to the soma by L-type voltage-gated Ca channels engage the ERK MAP kinase cascade to mediate CREB phosphorylation and CREB-dependent transcription. In contrast, dendrite-restricted Ca 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.

Protocadherins, a family of adhesion molecules with crucial role in cell-cell interactions, have emerged as key players in neurodevelopmental and psychiatric disorders. In particular, growing evidence links genetic alterations in Protocadherin 9 () gene with Autism Spectrum Disorder (ASD) and Major Depressive Disorder (MDD). Furthermore, deletion induces neuronal defects in the mouse somatosensory cortex, accompanied by sensorimotor and memory impairment. However, the synaptic and molecular mechanisms of in the brain remain largely unknown, particularly concerning its impact on brain pathology. To address this question, we conducted a comprehensive investigation of PCDH9 role in the male mouse hippocampus at the ultrastructural, biochemical, transcriptomic, electrophysiological and network level. We show that PCDH9 mainly localizes at glutamatergic synapses and its expression peaks in the first week after birth, a crucial time window for synaptogenesis. Strikingly, KO neurons exhibit oversized presynaptic terminal and postsynaptic density (PSD) in the CA1. Synapse overgrowth is sustained by the widespread up-regulation of synaptic genes, as revealed by single-nucleus RNA-seq (snRNA-seq), and the dysregulation of key drivers of synapse morphogenesis, including the SHANK2/CORTACTIN pathway. At the functional level, these structural and transcriptional abnormalities result into increased excitatory postsynaptic currents (mEPSC) and reduced network activity in the CA1 of KO mice. In conclusion, our work uncovers pivotal role in shaping the morphology and function of CA1 excitatory synapses, thereby modulating glutamatergic transmission within hippocampal circuits. Converging evidence indicates that genetic alterations in Protocadherin 9 () gene are associated with Autism Spectrum Disorder (ASD) and Major Depressive Disorder (MDD). However, our understanding of physiological role and molecular mechanisms in the brain, as well as its connection to synaptic dysfunction and brain pathology, remains limited. Here we demonstrate that regulates the transcriptional profile, morphology and function of glutamatergic synapses in the CA1, thereby tuning hippocampal network activity. Our results elucidate the molecular and synaptic mechanisms of a gene implicated in neurodevelopmental and psychiatric disorders, and suggest potential hippocampal alterations contributing to the cognitive deficits associated with these conditions.

To comprehend speech, human brains identify meaningful units in the speech stream. But whereas the English '' has 3 word-units, the Arabic equivalent '' is a single word-unit with 3 meaningful sub-word units, called morphemes: a verb stem (''), a subject suffix ('--'), and a direct object pronoun ('-'). 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 ''. 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., '' could initially be mistaken for the shorter stem ''='') or length-unambiguous (e.g., ''='' 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. 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., '' and '' in ''), 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.

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. 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. 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 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.

Predictive processing in parietal, temporal, frontal, and sensory cortex allows us to anticipate future meanings to maximize the efficiency of language comprehension, with the temporoparietal junction (TPJ) and inferior frontal gyrus (IFG) thought to be situated towards the top of a predictive hierarchy. Although the regions underpinning this fundamental brain function are well-documented, it remains unclear how they interact to achieve efficient comprehension. To this end we recorded functional magnetic resonance imaging (fMRI) in 22 participants (11 males) while they comprehended sentences presented part-by-part, in which we manipulated the constraint provided by sentential contexts on upcoming semantic information. Using this paradigm, we examined the connectivity patterns of bilateral TPJ and IFG during anticipatory phases (i.e., before the onset of targets) and integration phases (i.e., after the onset of targets). When upcoming semantic content was highly predictable in strong-constraint contexts, both left TPJ and bilateral IFG showed stronger visual coupling, while right TPJ showed stronger connectivity with regions within control, default mode, and visual networks, including IFG, parahippocampal gyrus, posterior cingulate, and fusiform gyrus. These connectivity patterns were weaker when predicted semantic content appeared, in line with predictive coding theory. Conversely, for less predictable content, these connectivity patterns were stronger during the integration phase. Overall, these results suggest that both top-down semantic prediction and bottom-up integration during predictive processing are supported by flexible coupling of frontoparietal regions with control, memory, and sensory systems. Recent work has revealed the neural basis of predictive language comprehension. However, it remains unclear how brain regions change their connectivity in a dynamic fashion to support comprehension in highly predictive and less predictive contexts. Here, we show that stronger frontoparietal connectivity with cognitive control, memory, and sensory areas supports top-down prediction generation in strong-constraint contexts; these connectivity patterns are reduced when the anticipated information appears. This pattern is reversed when upcoming sensory input is unpredictable; connectivity is stronger after word inputs have been presented, allowing semantic integration with preceding low-constraint context. Our findings suggest that both top-down semantic prediction and bottom-up semantic integration in language comprehension rely upon diverse functional coupling of higher-order frontoparietal regions with other brain systems.

Neuronal hyperexcitability is a hallmark of epilepsy. It has been recently shown in rodent models of seizures that microglia, the brain's resident immune cells, can respond to and modulate neuronal excitability. However, how human microglia interact with human neurons to regulate hyperexcitability mediated by an epilepsy-causing genetic mutation found in patients is unknown. The gene is responsible for encoding the voltage-gated sodium channel Nav1.2, one of the leading contributors to monogenic epilepsies. Previously, we demonstrated that the recurring Nav1.2-L1342P mutation leads to hyperexcitability in a male donor (KOLF2.1) hiPSC-derived cortical neuron model. Microglia originate from a different lineage (yolk sac) and are not naturally present in hiPSCs-derived neuronal cultures. To study how microglia respond to neurons carrying a disease-causing mutation and influence neuronal excitability, we established a co-culture model comprising hiPSC-derived neurons and microglia. We found that microglia display increased branch length and enhanced process-specific calcium signal when co-cultured with Nav1.2-L1342P neurons. Moreover, the presence of microglia significantly lowered the repetitive action potential firing and current density of sodium channels in neurons carrying the mutation. Additionally, we showed that co-culturing with microglia led to a reduction in sodium channel expression within the axon initial segment of Nav1.2-L1342P neurons. Furthermore, we demonstrated that Nav1.2-L1342P neurons release a higher amount of glutamate compared to control neurons. Our work thus reveals a critical role of human iPSCs-derived microglia in sensing and dampening hyperexcitability mediated by an epilepsy-causing mutation. Seizure studies in mouse models have highlighted the role of microglia in modulating neuronal activity, particularly in the promotion or suppression of seizures. However, a gap persists in comprehending the influence of human microglia on intrinsically hyperexcitable neurons carrying epilepsy-associated pathogenic mutations. This research addresses this gap by investigating human microglia and their impact on neuronal functions. Our findings demonstrate that microglia exhibit dynamic morphological alterations and calcium fluctuations in the presence of neurons carrying an epilepsy-associated mutation. Furthermore, microglia suppressed the excitability of hyperexcitable neurons, suggesting a potential beneficial role. This study underscores the role of microglia in the regulation of abnormal neuronal activity, providing insights into therapeutic strategies for neurological conditions associated with hyperexcitability.

How master splicing regulators crosstalk with each other and to what extent transcription regulators are differentially spliced remain unclear in the developing brain. Here, cell-type-specific RNA-Seq analyses of the developing neocortex uncover variable expression of the Rbfox1/2/3 genes and enriched splicing events in transcription regulators, altering protein isoforms or inducing nonsense-mediated mRNA decay. Transient expression of Rbfox proteins in radial glial progenitors induces neuronal splicing events preferentially in transcription regulators such as and Surprisingly, Rbfox proteins promote the inclusion of a mammal-specific alternative exon and a previously undescribed poison exon in Simultaneous ablation of in the neocortex downregulates neuronal isoforms and disrupts radial neuronal migration. Furthermore, the progenitor isoform of promotes transcription, while the neuron isoform promotes neuronal differentiation. These observations indicate that transcription regulators are differentially spliced between cell types in the developing neocortex. [The sex has not been reported to affect cortical neurogenesis in mice, and embryos of both sexes were studied without distinguishing one or the other.] How alternative splicing regulates cell-type-specific gene expression in the developing neocortex remains understudied. Here, analyses of sorted cell types and single-cell long-reads uncover cell-type-specific splicing that is enriched in transcription regulators. Rbfox proteins, including the pan-neuronal marker NeuN/Rbfox3, preferentially switch splice forms of transcription regulators and are required for radial neuronal migration. We further show that the progenitor and neuron isoforms of a transcription regulator function differently. Overall, this study suggests a cross-talk between alternative splicing and transcription for neuronal gene regulation.

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. 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.

The common marmoset () is known for its highly vocal nature, displaying a diverse range of calls. Functional imaging in marmosets has shown that the processing of conspecific calls activates a brain network that includes fronto-temporal areas. It is currently unknown whether different call types activate the same or different networks. In this study, nine adult marmosets (four females) were exposed to four common vocalizations (phee, chatter, trill, and twitter), and their brain responses were recorded using event-related fMRI at 9.4T. We found robust activations in the auditory cortices, encompassing core, belt, and parabelt regions, and in subcortical areas like the inferior colliculus, medial geniculate nucleus, and amygdala in response to these calls. Although a common network was engaged, distinct activity patterns were evident for different vocalizations that could be distinguished by a 3D convolution neural network, indicating unique neural processing for each vocalization. Our findings also indicate the involvement of the cerebellum and medial prefrontal cortex (mPFC) in distinguishing particular vocalizations from others. This study investigates the neural processing of vocal communications in the common marmoset (). Utilizing event-related fMRI at 9.4T, we demonstrate that different calls (phee, chatter, trill, and twitter) elicit distinct brain activation patterns, challenging the notion of a uniform neural network for all vocalizations. Each call type distinctly engages various regions within the auditory cortices and subcortical areas. These findings offer insights into the evolutionary mechanisms of primate vocal perception and provide a foundation for understanding the origins of human speech and language processing.

Human visual cortex contains regions selectively involved in perceiving and recognizing ecologically important visual stimuli such as people and places. Located in the ventral temporal lobe, these regions are organized consistently relative to cortical folding, a phenomenon thought to be inherited from how centrally or peripherally these stimuli are viewed with the retina. While this eccentricity theory of visual cortex has been one of the best descriptions of its functional organization, whether or not it accurately describes visual processing in all category-selective regions is not yet clear. Through a combination of behavioral and functional MRI measurements in 27 participants (17 females), we demonstrate that a limb-selective region neighboring well-studied face-selective regions shows tuning for the visual periphery in a cortical region originally thought to be centrally-biased. We demonstrate that the spatial computations performed by the limb-selective region are consistent with visual experience, and in doing so, make the novel observation that there may in fact be two eccentricity gradients, forming an eccentricity reversal across high-level visual cortex. These data expand the current theory of cortical organization to provide a unifying principle that explains the broad functional features of many visual regions, showing that viewing experience interacts with innate wiring principles to drive the location of cortical specialization. What is the organizing principle of high-level visual cortex? Visual stimuli experienced extensively during childhood, like faces or scenes, give rise to specialized regions in visual cortex. These regions emerge in consistent locations across individuals, thought to result from the retinotopic input of earlier visual cortex. The field has quantified this input as a medial-lateral gradient of retinotopic eccentricity in ventrotemporal cortex that has not yet been mapped beyond the fusiform gyrus. By performing receptive field mapping in limb-selective cortex for the first time we uncover a u-shaped eccentricity gradient which reverses near the lateral Fusiform. These findings produce a parsimonious model of cortical organization incorporating previously uncharacterized regions, offering a new organizing principle of high-level vision.