Journal of Neuroscience最新文献

The activation of autonomic and hypothalamo-pituitary-adrenal (HPA) systems occurs interdependently with behavioral adjustments under varying environmental demands. Nevertheless, laboratory rodent studies examining the neural bases of stress responses have generally attributed increments in these systems to be monolithic, regardless of whether an active or passive coping strategy is employed. Using the shock probe defensive burying test (SPDB) to measure stress-coping features naturalistically in male and female rats, we identify a neural pathway whereby activity changes may promote distinctive response patterns of hemodynamic and HPA indices typifying active and passive coping phenotypes. Optogenetic excitation of the rostral medial prefrontal cortex (mPFC) input to the ventrolateral periaqueductal gray (vlPAG) decreased passive behavior (immobility), attenuated the glucocorticoid hormone response, but did not prevent arterial pressure and heart rate increases associated with rats' active behavioral (defensive burying) engagement during the SPDB. In contrast, inhibition of the same pathway increased behavioral immobility and attenuated hemodynamic output but did not affect glucocorticoid increases. Further analyses confirmed that hemodynamic increments occurred preferentially during active behaviors and decrements during immobility epochs, whereas pathway manipulations, regardless of the directionality of effect, weakened these correlational relationships. Finally, neuroanatomical evidence indicated that the influence of the rostral mPFC→vlPAG pathway on coping response patterns is mediated predominantly through GABAergic neurons within vlPAG. These data highlight the importance of this prefrontal→midbrain connection in organizing stress-coping responses and in coordinating bodily systems with behavioral output for adaptation to aversive experiences.

The extent to which neural representations of fear experience depend on or generalize across the situational context has remained unclear. We systematically manipulated variation within and across three distinct fear-evocative situations including fear of heights, spiders, and social threats. Participants (n = 21; 10 females and 11 males) viewed ∼20 s clips depicting spiders, heights, or social encounters and rated fear after each video. Searchlight multivoxel pattern analysis was used to identify whether and which brain regions carry information that predicts fear experience and the degree to which the fear-predictive neural codes in these areas depend on or generalize across the situations. The overwhelming majority of brain regions carrying information about fear did so in a situation-dependent manner. These findings suggest that local neural representations of fear experience are unlikely to involve a singular pattern but rather a collection of multiple heterogeneous brain states.

Peripheral taste neurons exhibit functional, genetic, and morphological diversity, yet understanding how or if these attributes combine into taste neuron types remains unclear. In this study, we used male and female mice to relate taste bud innervation patterns to the function of a subset of proenkephalin-expressing (Penk+) taste neurons. We found that taste arbors (the portion of the axon within the taste bud) stemming from Penk+ neurons displayed diverse branching patterns and lacked stereotypical endings. The range in complexity observed for individual taste arbors from Penk+ neurons mirrored the entire population, suggesting that taste arbor morphologies are not primarily regulated by the neuron type. Notably, the distinguishing feature of arbors from Penk+ neurons was their propensity to come within 110 nm (in apposition with) different types of taste-transducing cells within the taste bud. This finding is contrary to the expectation of genetically defined taste neuron types that functionally represent a single stimulus. Consistently, further investigation of Penk+ neuron function revealed that they are more likely to respond to innately aversive stimuli-sour, bitter, and high salt concentrations-as compared with the full taste population. Penk+ neurons are less likely to respond to nonaversive stimuli-sucrose, umami, and low salt-compared with the full population. Our data support the presence of a genetically defined neuron type in the geniculate ganglion that is responsive to innately aversive stimuli. This implies that genetic expression might categorize peripheral taste neurons into hedonic groups, rather than simply identifying neurons that respond to a single stimulus.

Somatosensory coding in rodents has been mostly studied in the whisker system and hairy skin, whereas the function of low-threshold mechanoreceptors (LTMRs) in the rodent glabrous skin has received scant attention, unlike in primates where the glabrous skin has been the focus. The relative activation of different LTMR subtypes carries information about vibrotactile stimuli, as does the rate and temporal patterning of LTMR spikes. Rate coding depends on the probability of a spike occurring on each stimulus cycle (reliability), whereas temporal coding depends on the timing of spikes relative to the stimulus cycle (precision). Using in vivo extracellular recordings in male rats and mice of either sex, we measured the reliability and precision of LTMR responses to tactile stimuli including sustained pressure and vibration. Similar to other species, rodent LTMRs were separated into rapid-adapting (RA) or slow-adapting based on their response to sustained pressure. However, unlike the dichotomous frequency preference characteristic of RA1 and RA2/Pacinian afferents in other species, rodent RAs fell along a continuum. Fitting generalized linear models to experimental data reproduced the reliability and precision of rodent RAs. The resulting model parameters highlight key mechanistic differences across the RA spectrum; specifically, the integration window of different RAs transitions from wide to narrow as tuning preferences across the population move from low to high frequencies. Our results show that rodent RAs can support both rate and temporal coding, but their heterogeneity suggests that coactivation patterns play a greater role in population coding than for dichotomously tuned primate RAs.

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 Meis2 and Tead1 Surprisingly, Rbfox proteins promote the inclusion of a mammal-specific alternative exon and a previously undescribed poison exon in Ptbp1 Simultaneous ablation of Rbfox1/2/3 in the neocortex downregulates neuronal isoforms and disrupts radial neuronal migration. Furthermore, the progenitor isoform of Meis2 promotes Tgfb3 transcription, while the Meis2 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.]Significance Statement 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 Meis2 function differently. Overall, this study suggests a cross-talk between alternative splicing and transcription for neuronal gene regulation.

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.Significance Statement 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.

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.Significance Statement 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.

Cortical circuits contain multiple types of inhibitory neurons which shape how information is processed within neuronal networks. Here, we asked whether somatostatin-expressing (SST) and vasoactive intestinal peptide-expressing (VIP) inhibitory neurons have distinct effects on population neuronal responses to noise bursts of varying intensities. We optogenetically stimulated SST or VIP neurons while simultaneously measuring the calcium responses of populations of hundreds of neurons in the auditory cortex of male and female awake, head-fixed mice to sounds. Upon SST neuronal activation, noise bursts representations became more discrete for different intensity levels, relying on cell identity rather than strength. By contrast, upon VIP neuronal activation, noise bursts of different intensity level activated overlapping neuronal populations, albeit at different response strengths. At the single-cell level, SST and VIP neuronal activation differentially modulated the response-level curves of monotonic and nonmonotonic neurons. SST neuronal activation effects were consistent with a shift of the neuronal population responses toward a more localist code with different cells responding to sounds of different intensity. By contrast, VIP neuronal activation shifted responses towards a more distributed code, in which sounds of different intensity level are encoded in the relative response of similar populations of cells. These results delineate how distinct inhibitory neurons in the auditory cortex dynamically control cortical population codes. Different inhibitory neuronal populations may be recruited under different behavioral demands, depending on whether categorical or invariant representations are advantageous for the task.Significance Statement Information about sounds is represented in the auditory cortex by neuronal population activity that has a characteristic sparse structure. Cortical neuronal populations comprise multiple types of excitatory and inhibitory neurons. Here, we find that activating different types of inhibitory neurons differentially controls population neuronal representations, with one type of inhibitory neurons increasing the differences in the identity of the cells recruited to represent the different sounds, and another inhibitory neuron type changing the relative activity level of overlapping neuronal populations. Such transformations may be beneficial for different types of auditory behaviors, suggesting that these different types of inhibitory neurons may be recruited under different behavioral constraints in optimizing neuronal representations of sounds.

The common marmoset (Callithrix jacchus) 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.Significance Statement This study investigates the neural processing of vocal communications in the common marmoset (Callithrix jacchus). 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.

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.Significance Statement 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.