Current Research in Neurobiology

Pig vocalizations convey information about the emotional states of individuals, varying with arousal and valence. Studies show that different call types reflect distinct emotional contexts and social interactions for the receivers. However, little is known about the brain mechanisms behind the perception of conspecifics vocalizations. This study used BOLD fMRI to explore how pigs brains respond to emotionally varied vocalizations, with the aim to identify activity in regions linked to emotion, reward, and social processing. Eight healthy 2-month-old pigs underwent auditory brainstem response (ABR) testing and BOLD fMRI to assess brain responses to pig vocalizations with different hedonic valence. Sounds were delivered via MRI-compatible earphones, and imaging was performed on a 1.5T scanner. Data were analyzed using voxel-based and ROI-based statistics in SPM12 with small volume correction (SVC). Due to hearing anomalies or MRI artefacts, only 5 pigs were included in the final analysis. Functional MRI revealed that vocalizations activated regions of the auditory pathway and the left amygdala (pFWE at peak < 0.05 after SVC for all), with specific differences between positive and negative sounds. Clusters of activated voxels covering part of hippocampal areas, caudate nuclei and putamen were found with both positive and aversive vocal sounds. Limbic regions, including the amygdala and insula (p<0.05), as well as the right hippocampus after SVC (pFWE = 0.015) were uniquely engaged during the perception of negative conspecific vocalizations, indicating distinct processing based on emotional valence. This study shows for the first time that piglets brain can process and differentiate emotional vocalizations from other pigs, even under general anesthesia. Positive and negative vocal sound playbacks activated distinct brain regions related to hearing, emotion and reward. These findings highlight pigs cognitive and emotional processing of vocal cues. This study is part of a wider research program aimed at developing the fMRI protocol with acoustic stimulation in juvenile pigs.

When hearing fails, cochlear implants (CIs) partially restore auditory perception. Yet, poor coding of spectral information remains a bottleneck as each electrode broadly activates the auditory nerve. As light can be more conveniently confined, optical (o)CIs present a promising alternative. Here, we combined expression of the potent channelrhodopsin ChReef in spiral ganglion neurons (SGNs) and oCIs based on 5-10 green LED in gerbils. We characterized the oCI encoding of intensity and spectral information by ChReef-SGNs using recordings from the central nucleus of the inferior colliculus (ICC). ChReef aligned light sensitivity of SGNs well with the radiant fluxes provided by individual LEDs: ICC-activity had thresholds <200 nJ and reached a maximum close to that achieved with 46 dB tones. Multichannel oCIs enabled tonotopically ordered and spectrally distinct stimulation indistinguishable from acoustic stimulation for up to moderate activity levels. Some LEDs elicited >1 spectral peaks for stronger intensities. Representational Similarity Analysis and Linear Discriminant Analysis of ICC activity indicated improved channel discriminability of optical over electrical stimulation. In summary, {micro}J oCI stimulation achieves near-physiological spectral resolution. The Paper ExplainedO_ST_ABSProblemC_ST_ABSElectrical cochlear implants (eCIs) partially restore speech comprehension in most of >1 million otherwise deaf users, who still face challenges hearing in daily situations. This is primarily due to poor spectral selectivity of electrical sound encoding. Spatially more confined optogenetic activation of the auditory nerve by optical cochlear implants (oCI) promises to overcome this limitation. However, a thorough characterization of bionic coding of sound information by multichannel oCI is needed to evaluate the potential for improved hearing restoration. ResultsHere, we combine the potent channelrhodopsin ChReef and 10-channel oCI based on green LEDs in gerbils and characterize their utility for encoding of spectral and intensity information by multielectrode array recordings from the midbrain. ChReef enabled activation of the auditory pathway with nano-joule thresholds and up to high levels of midbrain activity with low {micro}J radiant energy. The cochlear spread of excitation and channel discriminability for low to medium activity levels were close to what we observed with acoustic stimulation. ImpactOur work demonstrates great potential of multichannel optogenetic stimulation for encoding sound frequency information.

Relapse after treatment for various mental health disorders has been linked to tendency for reductions in responding to increase over time or following re-exposure to motivating stimuli. Here we show that, in rats, responding reduced through non-contingent outcome delivery does not recover in these ways, and that this learning depends on an intact lateral orbitofrontal cortex. These findings suggest that contingency degradation overwrites original learning which may support the development of relapse-resistant behavioural interventions.

Many perceptual skills improve with a few days of training. However, weeks or months of practice may be required to reach a level of expertise on complex tasks (Watson, 1980). Here, we explored how gerbils attain expertise on a difficult task: amplitude modulation (AM) rate discrimination at very shallow AM depths, similar to the depths used during vocal communication. Using an appetitive Go-Nogo procedure, we first trained 6 gerbils to perform an AM discrimination task (Nogo: 4 Hz; Go: 4.25-10 Hz) at a depth of 0 dB (re: 100% depth). Animals were then trained to perform AM discrimination at successively shallower depths, from -3 to -18 dB, requiring an average of 5-10 days of practice to reach a performance metric of d[&ge;]1 for each depth. Finally, we determined that AM discrimination thresholds were nearly identical between 0 to -12 dB, and only slightly elevated at -15 dB. Improvements in performance were accompanied by a large reduction in response time during procedural learning, and a gradual reduction of response time during perceptual learning, even as AM depth became shallower (i.e., more difficult). The shallowest depth at which gerbils displayed peak performance on the AM discrimination task is similar to their lowest AM depth detection thresholds. These results suggest performance on challenging auditory perceptual tasks require prolonged practice, and is accompanied by increased automaticity (i.e., lower response time) that stabilizes once expertise is achieved.

When hearing fails, stimulation of the auditory nerve by electrical cochlear implants (eCIs) partially restores hearing, with most eCI users achieving open speech understanding. However, the broad current spread from each electrode limits frequency coding and speech understanding in daily situations with background noise. Spatially confined optogenetic stimulation by future optical cochlear implants (oCIs) improves frequency coding but millisecond closing kinetics of channelrhodopsins (ChRs) might limit temporal coding. Here, we evaluated the utility of fast-closing ChR f-Chrimson for processing temporal information in the auditory system of Mongolian gerbils. We recorded neural activity in the inferior colliculus evoked by f-Chrimson-mediated optogenetic stimulation of the cochlea. F-Chrimson enabled energy-efficient stimulation of the auditory pathway at rates [&ge;]150 Hz, outperforming the slower ChR variants CatCh (blue) and ChReef (green). Energy thresholds for activation of the auditory pathway were in the low {micro}J range, between ChReef (sub-{micro}J) and CatCh. Dynamic range and frequency selectivity were comparable to previous observations with CatCh and outperformed electrical stimulation. In conclusion, employing fast-gating ChRs harnesses improved spectral coding without degrading temporal coding. The Paper ExplainedO_ST_ABSProblemC_ST_ABSElectrical cochlear implants (eCIs) partially restore speech comprehension in most of 1 million otherwise severely deaf people. However, most CI-users face challenges hearing in daily situations. Spectrally more selective stimulation of the auditory nerve by optical cochlear implants (oCIs) promises to overcome this limitation. However, the closing kinetics of channelrhodopsins (ChR) limit the temporal bandwidth of bionic sound coding. Improving the ChR properties and evaluating temporal coding remain major objectives for developing hearing restoration by oCI. ResultsHere, we evaluate the utility of waveguide-based oCI using the fast-closing ChR Chrimson (f-Chrimson) for encoding of temporal, spectral and intensity information by multi-electrode-array (MEA) recordings from the midbrain. We compare f-Chrimson-mediated bionic coding to acoustic coding as well as to previous data acquired with optogenetic stimulation using other ChRs and with electrical stimulation. F-Chrimson enabled energy-efficient stimulation of the auditory pathway at rates [&ge;]150 Hz, outperforming the slower ChR variants CatCh (blue) and ChReef (green). Intensity and frequency coding were comparable to previous observations with CatCh and outperformed electrical stimulation. ImpactThis study demonstrates near physiological temporal coding with the fast-closing ChR f-Chrimson, indicating that improved spectral coding by oCI is not traded off by poor temporal fidelity.

Meditation has been associated with improvements in attention, emotional regulation, and mental well-being, motivating increasing interest in objective methods for assessing meditative states. In this study, we investigate whether EEG-based machine learning can reliably distinguish between multiple meditation styles and mind-wandering states. EEG data were recorded from experienced meditators performing three meditation styles, Shamatha, Vipassana, and Metta, together with an eyes-closed mind-wandering condition. EEG signals were preprocessed to remove artifacts, and features were extracted from frequency, time-frequency, and time domains. Classification was evaluated using both intra-subject and inter-subject strategies with multiple machine learning classifiers. Results demonstrate high intra-subject classification accuracy across meditation-versus-mind-wandering and meditation-style comparisons, indicating strongly discriminative subject-specific neural signatures. In contrast, inter-subject performance decreased substantially, particularly for distinguishing meditation styles, suggesting considerable inter-individual variability in meditation-related EEG patterns. Furthermore, temporal analysis revealed that classification performance increase over time, indicating that the neural distinctions between meditation states become increasingly pronounced over time. Additionally, t-SNE visualization showed clear within-subject clustering but increased overlap across subjects, explaining the reduced inter-subject generalization. Overall, these findings highlight the potential of EEG-based machine learning for personalized assessment and monitoring of meditative states while emphasizing the challenges of developing subject-independent meditation classification systems.

BackgroundResponding appropriately to threats is critical for survival. Dysregulated defensive responses are core features of psychiatric illnesses including panic disorder and post-traumatic stress disorder. Carbon dioxide (CO2) inhalation evokes defensive behaviors in both humans and mice. Here we investigated the role of acid-sensing ion channels (ASICs) in CO2-evoked jumping in mice. MethodsDefensive behaviors (jumping and freezing) were assessed in response to CO2 inhalation and basolateral amygdala (BLA) acidification. We tested the role of ASICs using global knockout mice and Asic1aloxP/loxP mice transduced with AAV-CMV-Cre or AAV-CaMKII-Cre in the BLA. Effects of CO2 on single neuron firing and local field potentials were studied via BLA microwire arrays. ResultsASIC1A disruption increased CO2-evoked jumping while reducing freezing, paralleled by increased BLA c-Fos induction. Acidification of the BLA recapitulated these effects. Virus-mediated ASIC1A disruption in BLA did not resolve the locus of ASIC1A action in jumping. CO2 inhalation suppressed firing in most BLA neurons, though a small number increased firing. ASIC1A disruption enhanced CO2-induced suppression of narrow waveform neurons (putative interneurons), and facilitated excitation of wide waveform neurons (putative principal neurons). Additionally, CO2 produced concentration-dependent broadband power suppression with selective theta enhancement, effects that were augmented by ASIC1A disruption. ConclusionsTogether, these findings suggest that ASIC1A promotes interneuron activity during acidosis and that its loss may reduce inhibition of principal neuron output, shifting defensive responses from freezing toward jumping. These results advance our understanding of how brain pH and ASICs regulate defensive behavior, with potential implications for understanding dysregulated defensive responses.

Interval timing (IT) is the ability to time events in the range from seconds to a few minutes, allowing animals to organize behavior in time at short durations. IT relies on two cognitive functions: 1) Measuring the passage of time; 2) Storing and retrieving temporal memories in a context appropriate manner. The hippocampus (HC) and medial prefrontal cortex (mPFC) have been shown critical to the accuracy and precision of time-contingent instrumental responses in IT. The anatomy supporting mPFC-HC interactions, required for memory encoding and retrieval, include projections from HC to mPFC, and indirect bidirectional connections through the ventral midline thalamus (VMT), most notably reuniens. Here, we explored VMTs role in retrieving fixed-interval (FI) temporal memories. Rats were trained on a 5s FI signaled by an auditory cue and demonstrated temporal memory by poking predominantly at the time of the expected reward. Timing responses on individual trials were classified into on-time, early, and random response. Across sessions, random response trials decreased following training. Next, we switched training to longer intervals (20s or 80s; daily sessions for weeks). To probe the role of the VMT in temporal memory retrieval, we infused the GABAA-agonist muscimol, or saline, before training sessions. Results show that VMT muscimol infusions decreased timing precision. Also, at both intervals, the number of on-time response trials decreased, and the number of random response trials significantly increased. The number of early response trials had no significant change at 20s, and significantly decreased at 80s. Overall, our results suggest that the VMT is critical for precise retrieval of temporal memories. We also describe per-trial response patterns with characteristics consistent across all trained intervals, suggesting multiple behavioral strategies at play during interval timing.

Flow, as defined by Mihalyi Csikszentmihalyi (1975), is a holistic sensation experienced when individuals are fully immersed in an activity, resulting in a mental state characterized by a diminished sense of self and altered perception of time. To investigate the global neural dynamics underlying flow, we employed EEG microstate analysis to capture the spatial and temporal properties of dominant transient global brain states (Lehmann et al., 1998). In a study involving 43 participants playing the video game Thumper for 25 minutes, we extracted three four-minute EEG segments from each session corresponding to reported experiences of flow, boredom, and frustration, as determined by self-reports and performance metrics. Across conditions, six distinct microstate topographies (A-F) accounted for most of the global variance. Given that reduced self-referential processing is a key feature of flow, we hypothesized that flow would modulate the properties of microstates C and E, which have been associated with brain regions resembling the default mode network (DMN). Compared to boredom and frustration, the flow condition showed significantly decreased global explained variance, mean duration, time coverage, and occurrence frequency of microstate E, as well as reduced mean duration and time coverage of microstate C. These findings suggest that microstates associated with self-referential processing are shorter and less frequent during flow than during boredom and frustration. This supports the notion that the flow experience modulates global brain dynamics, particularly within the DMN. Furthermore, our results align with previous research reporting reduced DMN activity during meditative and psychedelic states, reinforcing the idea of diminished self-awareness in such conditions.

The Mnemonic Similarity Task (MST) is highly sensitive to age-related cognitive decline in humans and has been adapted for rodents using 3D objects, where aged animals show deficits in discriminating similar lures. To improve translational alignment with human testing and increase automation, we developed a touchscreen-based rat analog using a morphed Object-Cued Spatial Choice (OCSC) task with 2D image stimuli. Young (4-month) and aged (21-month) male and female Fischer 344 x Brown Norway hybrid rats were trained in Bussey-Saksida touchscreen chambers and tested on discrimination performance using image pairs that varied parametrically in feature overlap. We also assessed perirhinal cortical engagement in a subset of animals using Arc expression as a readout of activity-related principal cell firing following low-and high-overlap task epochs. Across shaping and procedural training, aged rats required more errors to reach criterion on one stimulus set, but both age groups successfully acquired the task. During morph testing, performance declined systematically as stimulus similarity increased, confirming that the task manipulated discrimination difficulty. However, contrary to expectations, young and aged rats performed similarly across overlap conditions, with no significant age-related impairment. In the Arc experiment, discrimination accuracy was again reduced by greater stimulus overlap, but Arc expression in perirhinal cortex did not differ reliably by age or overlap condition, although expression was associated with behavioral accuracy and deep layers showed higher ensemble similarity than superficial layers. These findings indicate that, while the touchscreen morph OCSC task is sensitive to stimulus similarity, it does not detect the robust age-related mnemonic discrimination deficits previously observed with 3D object-based rodent MST paradigms, underscoring the importance of considering ethological relevance when designing translational cognitive assays.

Evidence suggests that information represented more reliably in neural activity patterns across repeated exposures is more likely to be remembered. However, this relationship varies across category-selective regions of the ventral visual cortex. Specifically, for house stimuli neural reliability has been robustly linked to memory outcomes in the parahippocampal place area (PPA), but less consistently for faces in the fusiform face area (FFA). The reason for this mismatch is unknown. To address this discrepancy, we implemented a novel within-category manipulation by presenting highly face-like and non-face-like house stimuli during fMRI, followed by a memory test. Non-face-like houses were more likely to be remembered than face-like houses. Although face-likeness did not elicit face-selective responses in the FFA, representational reliability in ventral visual cortices, particularly in the FFA, showed an association with individual differences in memory performance. Finally, symmetry emerged as a potential perceptual factor underlying differences in mnemonic outcomes.

Iconicity refers to systematic links between word form and meaning. Although evidence for iconicity in natural language continues to grow, its neural basis remains unclear. Using functional magnetic resonance imaging (fMRI) and multivariate pattern analysis (MVPA), we examined iconic shape associations of auditory real words and pseudowords. The pseudowords were matched to the real words in phonemic and phonotactic properties, while differing primarily in the absence of learned semantic representations. Participants listened to each item and judged whether it sounded rounded or pointed. Searchlight MVPA revealed significant decoding for both stimulus types. For real words, iconic shape associations were decoded above chance in regions associated with visual and haptic shape processing (left lateral occipital complex and left anterior intraparietal sulcus), visual imagery (bilateral precuneus), phonological processing (bilateral supramarginal gyri), and semantic processing (left middle frontal and right superior frontal gyri). For pseudowords, significant decoding was found in regions associated with multisensory feature organization (right posterior intraparietal sulcus) and language processing (left angular and inferior frontal gyri). Together, these findings provide evidence for neural mechanisms mediating iconic associations, with language-related areas involved for both real words and pseudowords, and visual processing for real words.

Aging and noise over-exposure lead to complex mixtures of cochlear degradation that impair the structure and function of outer hair cells, inner hair cells (IHCs), and the cochlear nerve. However, IHC damage and cochlear synaptopathy (CS) remain pathologies "hidden" from the audiogram. This study aimed to identify and differentiate the physiological signatures of these two distinct pathologies using promising non-invasive assays: Envelope Following Responses (EFRs), Auditory Brainstem Response (ABRs), Wideband middle-ear reflexes (WB-MEMRs), and Distortion Product Otoacoustic Emissions (DPOAEs). We utilized chinchilla models of carboplatin-induced (CA) IHC damage (N = 4) and temporary threshold shift (TTS) noise-induced CS (N = 4) to compare the physiological signatures of each pathology. While both groups showed unchanged ABR thresholds two weeks after exposure, EFRs, ABR Wave V/I ratios, and MEMRs showed distinct effects of exposure. Despite non-elevated ABR-derived audiometric thresholds after exposure, both CA and TTS exposure resulted in severe in EFR "peakiness", particularly for sharp, short-duty-cycle stimuli and significant elevations in ABR Wave V/I ratios. However, these findings were less-pronounced in the TTS-exposed animals. WB-MEMR amplitudes were decreased with elevated thresholds in both groups; this effect was more pronounced in the TTS group. Opposite trends in DPOAE amplitudes indicated that while both IHC damage and CS result in similar suprathreshold temporal coding deficits, effects on outer-hair-cell integrity and auditory efferent physiology may differ between the two pathologies. Future work and novel diagnostics should aim to distinguish these specific cochlear pathologies in clinical populations, or at the very least consider their overlap. HighlightsO_LIA multi-metric diagnostic approach was used with chinchilla models of inner-hair-cell (IHC) damage and cochlear synaptopathy (CS). C_LIO_LIIHC damage and synaptopathy both cause suprathreshold deficits "hidden" from the audiogram. C_LIO_LIIHC damage results in more severe temporal envelope coding degradation than does synaptopathy. C_LIO_LIA combination of EFR "peakiness", ABR Wave V/I ratio, and Wideband Middle Ear Muscle Reflex (WB-MEMR) appear to be useful measures for profiling IHC damage and CS. C_LI

This paper presents a six-stage methodological framework for Convolutional Neural Net-work (CNN)-based cetacean vocalization detection and classification in Passive Acoustic Monitoring (PAM), implemented as the open-source toolkit ai-pam-pipeline. The frame-work is generalizable across species and fully parameterised through a single configuration file, guaranteeing exact experimental reproducibility. Two experiments are reported. Experiment A examines the effect of FFT window length Nfft [isin] {256, 512, 1024} on binary Bottlenose dolphin (Tursiops truncatus) whistle detection using stratified 10-fold cross-validation on an in-domain dataset (Oltremare, 192 kHz) and a cross-domain benchmark (DCLDE 2022). In-domain performance is uniformly high (macro F1{approx} 0.98; Wilcoxon, all p > 0.05). Cross-domain results diverge substantially: Nfft = 256 is significantly superior (p = 0.006, rank-biserial r = 0.89). The mechanism is an upsampling amplification effect: coarser spectral bins produce wider, higher-contrast FM traces after bilinear resampling to fixed image dimensions. This superiority is threshold-invariant: precision equals 1.000 across all configurations and thresholds{theta} [isin] [0.1, 0.9], confirming that the advantage is not an artifact of threshold choice. These findings demonstrate that preprocessing choices -- often treated as secondary implementation details -- can significantly affect cross-domain generalisation. While Nfft serves here as a controlled case study, the framework is designed to enable systematic, reproducible evaluation of arbitrary preprocessing parameters within a unified experimental protocol. Experiment B demonstrates multiclass capability on five T. truncatus vocalization cate-gories (macro F1 = 0.843); inter-class confusion between click trains and burst-pulse sounds reflects biological signal overlap rather than classifier failure.

Homeostatic plasticity of intrinsic excitability (IE) in the visual system has been essentially shown at the cortical level but whether thalamic nuclei also express homeostatic plasticity of IE is unknown. We show here that 4 days of monocular deprivation (MD) at eye opening induces a homeostatic change in IE in dorsal lateral geniculate nucleus (dLGN) neurons. Neurons recorded in the dLGN region activated by the deprived eye are more excitable than neurons recorded in the dLGN region activated by the open eye. No significant changes were observed following 7 days of MD, however. Enhanced excitability in neurons from the deprived side after 4 days of MD was associated with a reduced Kv1-dependent LTP-IE, a smaller voltage ramp, and a reduced inter-spike interval, suggesting that Kv1 channels are down-regulated in deprived dLGN neurons. Furthermore, the ankyrin G signal of the axon initial segment was larger in deprived dLGN neurons compared with open ones, indicating that Nav1 channel number also undergoes homeostatic regulation, and Kv1.1 channel signals were lower in deprived neurons compared to open ones. In addition, electrical coupling was found to be strengthened in neurons displaying enhanced IE following either brief (4 days) or long (10 days) MD. These results suggest that homeostatic and Hebbian plasticity in the dLGN share common expression mechanisms involving the regulation of Kv1 channels, Nav1 channels and electrical coupling between relay neurons.

CaMKII promoter is widely used to label and manipulate hippocampal pyramidal neurons via transgenic mouse lines or viral approaches. While it targets most excitatory neurons, a small subset remains unlabeled and often overlooked. We present an AAV-based strategy combined with CaMKII-driven Cre expression to access and study this remaining population. Furthermore, we provide a detailed protocol for in-house AAV production, targeted stereotaxic delivery, and functional validation of targeted neurons through slice electrophysiology and behavior. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=194 HEIGHT=200 SRC="FIGDIR/small/723440v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@3a31ccorg.highwire.dtl.DTLVardef@9b7e90org.highwire.dtl.DTLVardef@92297borg.highwire.dtl.DTLVardef@1e159eb_HPS_FORMAT_FIGEXP M_FIG C_FIG

Cognitive maps encode spatial relationships between locations and support flexible navigation. However, how these mental representations form in the absence of visual experience remains unclear. Here, we introduce a multisensory virtual navigation paradigm that allows to track the temporal dynamics of non-visual cognitive map formation. Sixteen early blind (EB), 17 late blind (LB), and 29 sighted controls (SC) learned the layout of a tactile maze. Participants repeatedly performed virtual pointing (estimating directions between locations) and navigation (reaching locations) tasks, which measured cognitive maps across multiple stages of learning. This method also enabled algorithmic inference of cognitive maps, providing insights into how mental distortions are progressively corrected. Although there were no group differences in average navigation performance, EB showed slower knowledge accumulation compared to LB and SC. In addition, both EB and LB had difficulties translating cognitive maps into first-person perspectives, resulting in reduced pointing and cognitive map accuracy. Yet, cognitive map accuracy improved progressively in all groups and a subset of EB and LB achieved expert-level performance with high navigation and pointing precision. In sum, this study provides a scalable framework for tracking alterations in cognitive map formation in blindness and other neurological conditions. Importantly, it demonstrates that cognitive map formation in the absence of vision is experience-dependent and trainable. Spatial disadvantages often observed in EB and LB thus do not reflect cognitive deficits but result from adaptive behavioral strategies constraining the use of allocentric cognitive maps.

Apuschkin et al. (2024) proposed a GPCR-based transcriptomic atlas for midbrain dopamine (DA) neuron subpopulations, including candidates such as Nmur1, Cckar, and Ffar4. To guide genetic targeting, these markers must reflect functional expression in adult DA neurons. Using in situ hybridization, Cre-dependent reporter lines, and both intracranial and systemic viral approaches, we find no evidence of adult Nmur1-mediated recombination in DA neurons, while Cckar-driven recombination is consistent with developmental expression only. Notably, Ffar4 expression overlaps extensively with Ntsr1 midbrain populations, indicating that it does not define a distinct DA neuron class. Furthermore, analysis of independent spatial transcriptomic datasets together with our MERFISH data shows that many proposed GPCR markers are not detectably expressed in adult DA neurons. These findings demonstrate that transcriptomic enrichment does not always yield reliable adult markers and highlight the need for functional validation prior to use in circuit targeting.

To avoid image blurring, the vestibulo-ocular (VOR) and the optokinetic (OKR) reflexes stabilize gaze. In all vertebrates, the VOR is mediated via direct projections from the vestibular nuclei to the motor nuclei that control the extraocular muscles. Lampreys show three vestibular nuclei that are well characterized in terms of their projections and sensory inputs, but much less is known about their inputs from other brain regions and the connectivity between them. Using tracer injections and electrophysiological recordings, we show that the lamprey vestibular nuclei are largely interconnected, while their inputs from other brain regions are scarce. The main rostral areas projecting to the vestibular nuclei are the pretectum and the ventral tier of the thalamus, which send ipsilateral inputs to the three vestibular nuclei.

The human visual system segments images using both high-level recognition mechanisms and low-level mechanisms that are largely independent of specific prior experience. The low-level mechanisms are essential for initiating recognition processes, and for learning to recognize new materials, objects, and contexts. Here we describe a hierarchical Bayesian observer (HBO) model of texture segmentation that is biologically plausible, takes into account the statistics of natural scenes, and does not depend on prior experience. The HBO model consists of five steps: local similarity grouping with local normalization, mutual similarity grouping (local grouping is strengthened if the neighboring regions are similar to the same set of other regions), transitive grouping (good continuation), confidence grouping (neighboring regions far from the same-different decision boundary guide grouping of regions near the decision boundary), and region grouping (similarity grouping of the regions from the initial segmentation). We find that a local similarity grouping process, trained to maximize accuracy, predicts human texture discrimination accuracy. We then find that the four additional steps accurately segment images with randomly shaped regions containing arbitrary natural textures. The success of the model depends on all the steps, but especially on local-similarity and transitive grouping. We also find that the transitive grouping allows correct segmentation of non-stationary texture regions (e.g., textures slanted in depth). Further, we find that when illumination varies across the image, local normalization enables both correct texture segmentation and estimation of illumination change. Finally, we find that unlike our model large state-of-the-art deep networks often fail on these stimuli.