bioRxiv Subject Collection: Neuroscience's Journal

Validation of EEG data assimilation-based prefrontal excitation-inhibition balance estimation using TMS-EEG
The excitation and inhibition (E/I) balance of neural circuits is a crucial index reflecting neurophysiological homeostasis. Although several cutting-edge methods have been established to assess E/I balance in an intact brain, they have inherent limitations, such as difficulties in tracking changes in E/I balance over time. To tackle this issue, we have proposed neural-mass-model-based tracking of the brain states using a data assimilation (DA) scheme in our previous work. However, although we verified that sleep-dependent changes in E/I balance can be estimated from electroencephalography data, the neurophysiological validity of the method was not evaluated. Therefore, in the current study, we directly compared estimated E/I states based on the DA methods with the concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) based methods. The results showed that the E/I changes estimated by the DA-based method correlated significantly with E/I in the dorsolateral prefrontal cortex, as indexed by TMS-evoked EEG. These findings indicate that our proposed method can estimate neurophysiologically valid changes in E/I balance.

The representation and valuation of subgoals in the human brain during model-based hierarchical behavior
The human capacity to plan and perform long, complex sequences of behavior to achieve distant goals depends in part on a hierarchical organization that divides behavior into structured segments. Such a mechanism requires the internal designation of certain states as subgoals to mark the successful implementation of a behavioral segment. How the brain represents subgoals over time and computes decision values as a function of subgoals is unknown. While most characterizations of hierarchical behavior lack knowledge of the environment, human decision-making also relies on planning with an internal model of the world. Consequently, it remains to be determined how the brain computes values of subgoals using model-based planning in order to drive hierarchical, model-based decisions. Using a sequential-subgoal decision-making task designed to evoke hierarchical, model-based behavior in combination with fMRI, we decoded a representation of the current subgoal in insula and ventromedial prefrontal cortex during decision-making that persisted over time--a critical, latent representation for computing values and orienting behavior in the correct sequence. Using a model-based, hierarchical reinforcement learning model, we also found key decision signals based on values from the model in several regions of frontal cortex. These findings thereby shed light on the neural correlates of subgoal representation and illustrate how value signals can be computed on the basis of these subgoals and knowledge of the environment structure.

Coincident bursts of high frequency oscillations across the human cortex coordinate large-scale memory processing.
Oscillations in the high gamma and ripple frequency ranges are known to coordinate local hippocampal and neocortical neuronal assemblies during memory encoding and recall. Here, we explored spatiotemporal dynamics and the role of global coordination of these fast oscillatory discharges across the sensory and associational cortical areas in distinct phases of memory processing. Individual bursts of high frequency oscillations were detected in intracranial recordings from epilepsy patients remembering word lists for immediate free recall. We found constant coincident bursting across visual and higher order processing areas, peaking before recall and elevated during encoding of words. This global co-bursting was modulated by memory processing, engaged approximately half of the recorded electrode sites, and clustered into a sequence of multiple consecutive bursting discharges. Our results suggest a general role of global coincident high frequency oscillations in organizing large-scale information processing across the brain necessary especially, but not exclusively, for memory functions.

Head before heart: cognitive empathy emerges before affective empathy in the developing brain
Empathy is crucial for social interactions across all cultures, and is foundational to establishing social cooperation and group ties in human societies. Challenging the current predominant view, we recently proposed that understanding others' emotions (cognitive empathy) might emerge earlier than actually sharing those emotions (affective empathy) (Bulgarelli & Jones, 2023). Here we test this hypothesis by measuring which empathic component matures first during toddlerhood, a critical period for the development of broader social networks. Addressing this question is critical to understand the mechanisms through which caregivers scaffold empathy development. Traditional approaches are inadequate, as they rely on children's verbal skills or unfamiliar scenarios that lack ecological validity. In this preregistered study, we employed a novel toddler-appropriate task to dissociate neural and physiological correlates of cognitive and affective empathy in N=90 3-to-5-year-olds using functional near-infrared spectroscopy (fNIRS) and simultaneous heart rate monitoring to identify internal markers of empathy. We found that brain regions supporting affective and cognitive empathy in young children resemble those observed in adults. Importantly, we showed an effect of age on network specialisation with brain activations of cognitive empathy stronger in younger compared to older preschoolers, and brain activations of affective empathy stronger in older compared to younger preschoolers. These results provide the first evidence that cognitive empathy develops earlier than affective empathy in preschoolers, challenging existing models and suggesting a new framework for understanding the development of empathy.

Aligned representation of visual and tactile motion directions in hMT+/V5 and fronto- parietal regions
Moving events on the skin can be perceived through vision and touch. How does the brain create a unified multisensory representation of motion directions initially acquired in different coordinate systems? We show that the middle occipito-temporal region (hMT+/V5), along with a fronto-parietal network, encodes visual and tactile directions using a common external frame of reference independent of body posture. We characterized brain activity using fMRI in participants exposed to directional visual and tactile motion stimuli across different hand postures. We demonstrate that individually and functionally defined hMT+/V5 shows univariate preference for both visual and tactile motion and encodes motion directions in distributed activity patterns. Unlike somatosensory regions, information about tactile directions was enhanced in right hMT+/V5 when mapped using an external as compared to a somatotopic frame of reference. Crossmodal decoding showed that tactile directions defined using an externally centered coordinate system, but not a somatotopic one, align with the representation of visual directions in rhMT+/V5 (both MT and MST). A whole brain searchlight group analysis confirmed these individually defined regions-of-interest results and extended the presence of an aligned visuo-tactile code for directional motion in external space to the parietal and dorsal prefrontal cortex. Our findings reveal a brain network involving hMT+/V5 that encodes motion directions in vision and touch using a common external frame of reference.

Intellectual ability and cortical homotopy development in children and adolescents
Functional homotopy, defined as the similarity between the corresponding regions of the two hemispheres, is a critical feature of interhemispheric communication and cognitive integration. Throughout development, the brain transitions from broadly connected networks in early childhood to more specialized configurations in adolescence, accompanied by increased hemispheric differentiation and integration. Using longitudinal data and a novel metric of functional homotopy, homotopic functional affinity (HFA), we investigated the developmental patterns of functional homotopy and its relationship with intelligence. Our findings indicate a significant decrease in HFA with age, particularly in higher-order association networks. In addition, adolescents demonstrate stronger, predominantly negative correlations between HFA and intelligence, in contrast to younger children. In particular, individuals with superior intellectual ability experience accelerated decreases in HFA, indicating greater neural efficiency based on advanced hemispheric specialization and differentiation. These findings provide evidence of the neural mechanisms that underlie cognitive development, emphasizing the dynamic interaction between hemispheric organization and intelligence. Our work may have implications for the design of customized educational/clinical interventions to optimize individual developmental strategies.

A comparative transcriptomic analysis of mouse demyelination models and Multiple Sclerosis lesions
Demyelinating diseases, such as Multiple Sclerosis (MS), are debilitating conditions characterized by loss of the myelin sheaths, ultimately leading to neurodegeneration. Toxicity models are among the most commonly used mouse models to induce demyelination; however, it remains unclear whether different demyelination models elicit distinct glial responses, and how comparable these changes are to MS. To address this gap, we integrated new and published single cell transcriptomic data of the subcortical white matter from lysophosphatidylcholine (LPC) and cuprizone toxicity models, and compared them to an existing human MS dataset. We find that LPC and cuprizone treatments induce distinct oligodendrocyte (OL) states, but a highly conserved microglial response upon demyelination. Interestingly, remyelinating OLs converge on an altered maturation state in both LPC and cuprizone models, potentially due to persistent activation of microglia at remyelination stages. Comparison of the mouse models with MS tissue reveals that key OL gene signatures specific to LPC and cuprizone demyelination are observed in MS patients, while microglia appear more heterogeneous across the different types of MS lesions. Finally, cross-species analysis highlights a conserved phenotype shared between cuprizone and actively demyelinating MS lesions, with downregulation of genes required for stable myelin production and increased cellular stress pathways. Overall, this comparative analysis uncovers specific gene expression differences between mouse demyelination models and human MS lesions, providing a foundation for using the animal models effectively to advance remyelination therapies.

Revisiting Color Efficient Coding through Material Perception
An essential objective of early visual processing is to handle the redundant inputs from natural environments efficiently. For instance, cone signals from natural environments are highly correlated across cone types, indicating channel redundancy. Early visual processing transforms the signals into color and luminance information, such as principle component analysis, and thus achieves efficient and decorrelated representations of natural scenes. Building on these findings, previous research has investigated the effect of color on visual tasks such as object recognition using grayscale conversion, which separates luminance from color. However, recent work suggests that when focusing on object materials, color and luminance remain highly redundant due to complex optical properties. Although this finding indicates that there may be a more efficient decomposition of signals, the specific algorithms remain unknown. This study derives that a classic computer graphics algorithm, the median cut, offers a novel approach to enhance visual processing efficiency while capturing diagnostic features to separate material from object geometry information. Human behavioral experiments show that color reduction based on the algorithm disturbs material classification while preserving object recognition. These findings suggest that object geometric structures are available only from low-bit information. Finally, considering material information can be estimated from summary statistics of image sub-spaces, this study suggests an efficient decomposition of input color images.

MiR-7a-Klf4 axis as a regulator and therapeutic target of neuroinflammation and ferroptosis in Alzheimer's disease
Neuroinflammation and ferroptosis significantly contribute to neuronal death in Alzheimer's disease (AD) and other neurodegenerative disorders. MicroRNAs (miRNAs) are crucial regulators of these pathological processes. We employed transcriptomic analysis in an APP/PSEN1 Tg AD mouse model to identify dysregulated miRNAs and construct a miRNA-mRNA-pathway network. We discovered increased miR7a expression in the AD brain, targeting Kruppel-like factor 4 (Klf4), a transcriptional factor implicated in A{beta} oligomer-induced neuroinflammation and RSL3-induced neuronal ferroptosis. Elevated Klf4 levels in AD mice brains suggest its involvement in AD pathology. The miR-7a mediated silencing of Klf4 alleviates neuroinflammation by modulating NF-{kappa}B, iNOS, and NLRP3 pathways, and inhibition of ferroptosis by targeting labile iron levels, GPX4, Nrf2 pathway, and mitochondrial damage. These findings highlight the neuroprotective role of miR-7a and its potential as RNA therapeutic. Pharmacological targeting of the miR-7a-Klf4 axis with blood-brain-barrier (BBB)-permeable compound effectively mitigates neuroinflammation and ferroptosis, suggesting the miR-7a-Klf4 axis as a novel therapeutic target for AD.

Reaching vigor tracks learned prediction error
Movement vigor across multiple modalities increases with reward, suggesting that the neural circuits that represent value influence the control of movement. Dopaminergic neuron (DAN) activity in the basal ganglia has been suggested as the potential mediator of this response. If DAN activity is the bridge between value and vigor, then vigor should track canonical mediators of this activity, namely reward expectation and reward prediction error. Here we ask if a similar time-locked response is present in vigor of reaching movements. We explore this link by leveraging the known phasic dopaminergic response to stochastic rewards, where activity is modulated by both reward expectation at cue and the prediction error at feedback. We used probabilistic rewards to create a reaching task rich in reward expectation, reward prediction error, and learning. In one experiment, target reward probabilities were explicitly stated, and in the other, were left unknown and to be learned by the participants. We included two stochastic rewards (probabilities 33% and 66%) and two deterministic ones (probabilities 100% and 0%). Outgoing peak velocity in both experiments increased with increasing reward expectation. Furthermore, we observed a short-latency response in the vigor of the ongoing movement, that tracked reward prediction error: either invigorating or enervating velocity consistent with the sign and magnitude of the error. Reaching kinematics also revealed the value-update process in a trial-to-trial fashion, similar to the effect of prediction error signals typical in dopamine-mediated striatal phasic activity. Lastly, reach vigor increased with reward history over trials, mirroring the motivational effects often linked to fluctuating dopamine levels. Taken together, our results demonstrate and exquisite link between known short-latency reward signals and the invigoration of both discrete and ongoing movements.

Evolution of sensory systems underlies the emergence of predatory feeding behaviours in nematodes
Sensory systems are the primary interface between an organism and its environment with changes in selectivity or sensitivity representing key events in behavioural evolution. Here, we explored the molecular modifications influencing sensory perception across the nematode phyla. Pristionchus pacificus is a predatory species and has evolved contact-dependent sensing and teeth-like structures to attack prey. Using mutants defective for mechanosensory neuron function, we found an expanded role for this sensory modality in efficient predation alongside its canonical function in sensing aversive touch. To identify the precise mechanism involved in this tactile divergence we generated mutations in 26 canonical mechanosensory genes and tested their function using a combination of behavioural assays, automated behavioural tracking and machine learning. While mechanosensory defects were observed in several mutants, Ppa-mec-6 mutants specifically also induced predation deficiencies. Previously, a similar phenotype was observed in a chemosensory defective mutant and we found a synergistic influence on predation in mutants lacking both sensory inputs. Importantly, both chemosensory and mechanosensory receptor expression converge on the same environmentally exposed IL2 neurons revealing these as the primary mechanism for sensing prey. Thus, predation evolved through the co-option of both mechanosensory and chemosensory systems which act synergistically to shape the evolution of complex behavioural traits.

Combined MEG and EEG suggest a limbic source network of the P3 in retrosplenial cortex, insula, and hippocampus
Intracranial P3 activity in the hippocampus is a robust phenomenon, but it remains debated if this activity contributes to the extracranial P3. A second limbic P3 source was recently suggested in the retro-splenial cortex based on source analysis and fMRI. The present study tested if these sources could be confirmed by source modeling of a new data set. Combined magneto- and electroencephalography signals were recorded during a visual oddball paradigm. Observers were instructed to respond to rare targets of a deviant shape and ignore rare non-targets of a deviant color. Source analysis was based on noise-normalized minimum norm estimates in an individual, MRI-based cortical source space. Source analysis showed a strong P3 source in retrosplenial cortex. Further sources were observed in insular cortex and medial temporal lobe. The source configuration was similar for rare target and non-target stimuli. Simulations and further analyses show that the source in retrosplenial cortex is strongly attenuated in magnetoencephalography, whereas the source in medial temporal lobe and insula contribute to both recording modalities. These data further support a P3 generator in retrosplenial cortex. Moreover, previously suggested generators in insula and medial temporal lobe, most likely in the hippocampus, are confirmed. In summary, the source configuration presented here suggests that the P3 is confined to limbic circuits.

Breakthrough Percepts of Familiar Faces
In Rapid Serial Visual Presentation (RSVP), the vast majority of stimuli are not consciously perceived, but the salient ones breakthrough into awareness and can be reported. In addition, these breakthrough events are observable with EEG, since they generate a P3 or other distinguishing components. The Fringe-P3 method is based upon these characteristics. Concealed knowledge studies have successfully employed this Fringe-P3 method using own-name and own email-address, with the method being shown to be less vulnerable to counter-measures than other approaches. It has also been shown that famous faces presented in RSVP differentially break into awareness and generate a distinct evoked response component. In this paper, we further enhance the applicability of the Fringe-P3 concealed knowledge test by demonstrating the effectiveness of the method on personally-familiar faces. While salient, such stimuli do not have the exquisite salience of famous faces, being a better match to the level of salience that might be found in forensic applications. Our findings suggest that the Fringe-P3 method could be used to detect intrinsic salience of familiar faces, even when there was no task associated with these faces. We investigated the sensitivity of the ERP-based RSVP paradigm to infer recognition of familiar faces, and performed statistical inference in the Time and Frequency domains, to differentiate between known and unknown faces, at group and participant levels.

Slow wave sleep supports the reorganisation of episodic memory networks
Models of memory consolidation propose that newly acquired memory traces undergo reorganisation during sleep. To test this idea, we recorded high-density electroencephalography (EEG) during an evening session of word-image learning followed by immediate (pre-sleep) and delayed (post-sleep) recall. Polysomnography was employed throughout the intervening night, capturing time spent in different sleep stages. Using source-reconstructed time-frequency analysis, we first replicated the effect of alpha power decreases for successful relative to unsuccessful recall, emerging between 700 and 1500 ms after cue onset and spanning medial and lateral temporal lobe regions as well as posterior parietal cortex. Directly contrasting successful post-sleep vs. pre-sleep recall revealed a shift of alpha power decrease from parietal towards anterior temporal lobe (ATL) after sleep. Critically, time spent in slow wave sleep (SWS) during the intervening night not only predicted the extent of memory retention, but also correlated with the shift to ATL recall effects. Finally, brain-wide functional connectivity profiles during successful recall pointed to a marked overnight reorganisation of memory networks, with the extent of reorganisation again predicted by time spent in SWS. Together, these findings link SWS to the consolidation and functional reorganisation of episodic memory networks.

NeuroCarta: An Automated and Quantitative Approach to Mapping Cellular Networks in the Mouse Brain
Understanding the structural organization of the brain is essential for deciphering how complex functions emerge from neural circuits. The Allen Mouse Brain Connectivity Atlas (AMBCA) has revolutionized our ability to quantify anatomical connectivity at a mesoscale resolution, bridging the gap between microscopic cellular interactions and macroscopic network organization. To leverage AMBCA for automated network construction and analysis, here we introduce NeuroCarta, an open-source MATLAB toolbox designed to extract, process, and analyze brain-wide connectivity networks. NeuroCarta generates directed and weighted connectivity graphs, computes key network metrics, and visualizes topological features of brain circuits. As an application example, using NeuroCarta on viral tracer data from the AMBCA, we demonstrate that the mouse brain exhibits a densely connected architecture, with a degree of separation of approximately four synapses, suggesting an optimized balance between local specialization and global integration. We identify attractor nodes that may serve as key convergence points in brain-wide neural computations and show that NeuroCarta facilitates comparative network analyses, revealing regional variations in projection patterns. While the toolbox is currently constrained by the resolution and coverage of the AMBCA dataset, it provides a scalable and customizable framework for investigating brain network topology, interregional communication, and anatomical constraints on mesoscale circuit organization.

Dual targeting of transferrin receptor and CD98hc enhances brain exposure of large molecules
Targeting proteins highly expressed at the blood-brain barrier, including transferrin receptor (TfR) and CD98hc, is a transformative approach enabling more effective brain delivery of biotherapeutics for treatment of neurological diseases. TfR-mediated delivery promotes rapid, high brain uptake, while CD98hc-mediated delivery is slower with more prolonged exposure. Here, we engineer a huIgG Fc domain to bind both TfR and CD98hc to create a dual transport vehicle (TV) platform that drives distinct brain delivery properties. Dual TVs achieve significantly higher brain concentrations than TVs targeting either TfR or CD98hc alone. Modulation of TfR and CD98hc affinities shifts dual TV brain exposure kinetics and biodistribution. Stronger TfR affinity drives faster brain uptake and clearance, while stronger CD98hc affinity yields higher, more sustained concentrations, likely due to CD98hc affinity-dependent reduction in TfR-mediated neuronal internalization. This dual targeting strategy leverages the complementary properties of TfR and CD98hc-mediated brain exposure to increase optionality for brain delivery of biotherapeutics.

Parkinson's Paradox: Alpha-synuclein's Selective Strike on SNc Dopamine Neurons over VTA
In synucleinopathies, including Parkinson's disease (PD), dopamine neurons in the substantia nigra pars compacta (SNc) exhibit greater vulnerability to degeneration than those in the ventral tegmental area (VTA). While -synuclein (Syn) pathology is implicated in nigral dopamine neuron loss, the mechanisms by which Syn affects neuronal activity and midbrain dopamine network connectivity prior to cell death remain unclear. This study tested the hypothesis that elevated Syn expression induces pathophysiological changes in firing activity and disrupts network connectivity dynamics of dopamine neurons before neuronal loss. We employed two mouse models of synucleinopathy: preformed Syn fibril (PFF) injection and AAV-mediated expression of human Syn (hSyn) under the control of the tyrosine hydroxylase (TH) promoter, both targeting the VTA and SNc. Four weeks post-injection, brain sections underwent histological, electrophysiological, and network analyses. Immunohistochemistry for TH, hSyn, and phospho-Ser129 Syn assessed Syn expression and dopaminergic neuron alterations. Neuronal viability was evaluated using two complementary approaches: quantification of TH+ or FOX3+ and TUNEL labeling. Importantly, these analyses revealed no significant changes in neuronal counts or TUNEL+ cells at this time point, confirming that subsequent functional assessments captured pre-neurodegenerative, Syn-induced alterations rather than late-stage neurodegeneration. Electrophysiological recordings revealed a differential effect of hSyn expression. SNc dopamine neurons exhibited significantly increased baseline firing rates, whereas VTA dopamine neurons remained unchanged. These findings indicate a region-specific vulnerability to Syn-induced hyperactivity of dopamine neurons. Further analysis revealed impaired homeostatic firing rate regulation in SNc, but not VTA, dopamine neurons, demonstrated by a reduced capacity to recover baseline firing following hyperpolarization. Collectively, our results demonstrate that, prior to neurodegeneration, elevated Syn expression differentially disrupts both basal firing activity and network stability of SNc dopamine neurons, while sparing VTA dopamine neurons. By identifying neurophysiological changes preceding dopaminergic neuron loss, these findings provide critical insights into the pathophysiological mechanisms predisposing SNc neurons to degeneration in Parkinson's disease.

Qualitative and Quantitative Comparative Analysis of Common Normal Variants and Physiological Artifacts in MEG and EEG
Magnetoencephalography (MEG) and electroencephalography (EEG) provide complementary insights into brain activity, yet their distinct biophysical principles influence how normal neurophysiological patterns and artifacts are represented. This study presents a comprehensive qualitative and quantitative analysis of common physiological variants and artifacts in simultaneously recorded MEG and EEG data. We systematically examined patterns such as alpha spindles, sensorimotor rhythms, sleep-related waveforms (vertex waves, K-complexes, sleep spindles, and posterior slow waves of youth), as well as common artifacts including eye blinks, chewing, and movement-related interferences. By applying time-domain, time-frequency, and source-space analyses, we identified modality-specific differences in signal representation, source localization, and artifact susceptibility. Our results demonstrate that MEG provides a more spatially focal representation of physiological patterns, whereas EEG captures broader, radially oriented cortical activity. Mutual information analysis indicated that MEG-derived independent components exhibited greater topographical variability and higher information content for neurophysiological activity, while EEG components were more homogeneous. Signal-to-noise ratio (SNR) analysis confirmed that MEG gradiometers capture the highest total information, followed by magnetometers and then EEG. Notably, physiological signals such as vertex waves and K-complexes exhibited significantly higher total information in MEG, whereas EEG was more sensitive to high-amplitude artifacts, including swallowing and muscle activity. These findings highlight the distinct strengths and limitations of MEG and EEG, reinforcing the necessity of multimodal approaches in clinical and research applications to improve the accuracy of neurophysiological assessments.

Right-hemisphere frontoparietal oscillations precede conscious report of visual targets.
What neural events precede conscious reports? Hemisphere-asymmetric frontoparietal networks are causally related to conscious perception (Bartolomeo et al., 2025; Kaufmann et al., 2024), but their spectrotemporal dynamics remain unclear. Here, we examined frontoparietal gamma oscillations occurring before a near-threshold target during the understudied pre-target period. In 67% of trials, a supra-threshold visual cue appeared near the target placeholder box (cued condition), indicating a higher probability that the target would appear at that location. In the remaining 33% of trials (uncued condition), the target appeared at the opposite location. We measured whole-brain activity using magnetoencephalography and analyzed gamma-band oscillations, coherence, and amplitude coupling with theta-phase in 16 regions of interest involved in attentional and perceptual processes (Martin-Signes et al., 2024). Results revealed that: (1) Report of cued targets was preceded by gamma-band oscillations in the right-hemisphere (RH) superior frontal gyrus, and by theta-gamma phase-amplitude coupling in the RH superior parietal region, suggesting preparatory attention. (2) Report of uncued targets was preceded by RH inferior parietal gamma oscillations and by coherence between RH superior and middle frontal regions, supporting an anticipatory lookout mechanism involved in monitoring for unexpected stimuli and rapidly redirecting attention to them. (3) Unreported targets were preceded by gamma-band oscillations in the left-hemisphere superior parietal lobe and by higher coherence in the left-hemisphere frontoparietal networks, suggesting a pre-target bias contributing to omission errors (Bartolomeo et al., 2025). These spectrotemporal signatures of attention in hemisphere-asymmetric frontoparietal networks shape predictive processing and perceptual bias, and predict conscious reports or their absence.

The Distribution of Nitric Oxide-Synthesizing Neurons and Soluble Guanylate Cyclase in the Pigeon Brain
Nitric oxide (NO) is a diffusible neuromodulator with roles in synaptic plasticity and memory flexibility, exerting its primary effects via the enzyme soluble guanylate cyclase (sGC). Despite its well-documented functions in mammals and insects, little is known about the neuroanatomical distribution and functional relevance of NO in birds, particularly in relation to dopaminergic systems. This study used histochemical and immunohistochemical techniques to map the distribution of NO-synthesizing neurons - identified by NADPH-diaphorase (NADPH-d) and nNOS activity - and their relation to sGC and tyrosine hydroxylase (TH)-positive dopaminergic pathways in the pigeon brain. We found extensive NADPH-d labeling throughout forebrain, midbrain, and hindbrain regions. Among TH-positive midbrain structures, the locus coeruleus exhibited high colocalization with nNOS, while moderate colocalization was seen in the ventral tegmental area substantia grisea centralis and substantia nigra. Notably, a significant proportion of sGC-positive neurons was targeted by TH and NADPH-d positive fibres in the pigeon NCL. Our findings support the potential for NO-dopamine interactions in avian species, reminiscent of memory-related mechanisms in Drosophila melanogaster, and contribute to an understanding of conserved pathways that may underlie flexible learning and memory processing during navigation or related tasks across vertebrates. This work also offers insight into comparative NADPH-d distribution among avian species, with implications for aging, spatial learning, and memory formation.