bioRxiv Subject Collection: Neuroscience's Journal

Passive muscle forces in Drosophila are large but insufficient to support a flys weight
Movement of a limb is shaped by active forces generated by muscle contraction but also by passive forces within individual muscles and joints. In small animals such as insects, the contribution of passive forces to limb movement can match the active forces. However, most measurements of passive forces are limited to the femur-tibia joint in large insects. Here we take advantage of genetic tools in Drosophila to measure passive torques at multiple joints in the flys leg. We genetically inactivate all the motor neurons to assess passive forces. We find that the passive torques are well approximated by a linear spring, i.e., the passive torques linearly increase with angular deviation from the rest angle. The torques are much larger than the gravitational torque due to the leg itself. We estimate that the passive torques are seventy times smaller than necessary to support the weight of the animal. We also inactivated all the motor neurons in a freely standing fly and found that, as predicted from the model, the fly falls when the motor neurons are inactivated. We found that the height at which a fly stands, and, therefore the active forces vary. The flys height affects the time to initiate a fall. The time it takes for the fall is consistent with the active forces decaying with a time constant of ~100 ms. Thus, although passive forces are strong and will have a large effect on limb kinematics, they are not strong enough to support the weight of the fly.

High-resolution phenotypic screen in zebrafish identifies novel regulators of CNS axon diameter growth
Axon diameter varies up to 100-fold between distinct neurons in the central nervous system with larger axons exhibiting proportionally faster conduction velocity. Axon diameter influences myelination, can be dynamically regulated, which might help fine-tune neural circuit function, and is altered in several diseases. Despite its importance, mechanisms regulating axon diameter remain poorly understood. This gap in understanding is due in part to the limitations of fixed tissue analyses, such as electron microscopy, which cannot be scaled up to execute discovery screens. To address this, we developed a high-resolution, high-content imaging-based in vivo platform to identify pharmacological modulators of axon diameter in zebrafish. We focused on the Mauthner neuron, whose axon diameter growth can be monitored during development. To facilitate our high-content chemical screen, we developed an automated high-resolution imaging and image analysis pipeline to assess changes in Mauthner axon diameter in transgenic reporter animals. We screened 880 compounds and identified 33 that altered Mauthner axon diameter. Validating this discovery pipeline, we confirmed that compounds that affect beta-2 adrenoceptor and dopamine signaling increase axon diameter in separate follow-up studies. This represents the first discovery screen for axon diameter regulators, providing novel entry points to study the biology of axon diameter regulation.

3D multimodal histological atlas and coordinate framework for the mouse brain and head
Brain reference atlases are essential for neuroscience experiments and data integration. However, histological atlases of the mouse brain, crucial in biomedical research, have not kept pace. Autofluorescence-based volumetric brain atlases are increasingly used but lack microscopic histological contrast, cytoarchitectonic information, corresponding MRI datasets, and often have truncated brainstems. Here, we present a multimodal, multiscale atlas of the laboratory mouse brain and head. The new reference brains include the whole head with consecutive Nissl and myelin serial section histology in three planes of section with 0.46 m in-plane resolution, including intact brainstem, cranial nerves, and associated sensors and musculature. We provide reassembled histological volumes with 20 m isotropic resolution in stereotactic coordinates, determined using co-registered in vivo MRI and CT. In addition to conventional MRI contrasts, we provide diffusion MRI-based in vivo and ex vivo microstructural information, adding a valuable co-registered contrast modality that bridges MRI with cell-resolution histological data. We shift emphasis from compartmental annotations to stereotactic coordinates in the reference brains, offering a basis for evolving annotations over time and resolving conflicting neuroanatomical judgments by different experts. This new reference atlas facilitates integration of molecular cell type data and regional connectivity, serves as a model for similar atlases in other species, and sets a precedent for preserving extra-cranial nervous system structures.

Presynaptic vesicles supply membrane for axonal bouton enlargement during LTP
Long-term potentiation (LTP) induces presynaptic bouton enlargement and a reduction in the number of synaptic vesicles. To understand the relationship between these events, we performed 3D analysis of serial section electron micrographs in rat hippocampal area CA1, 2 hours after LTP induction. We observed a high vesicle packing density in control boutons, contrasting with a lower density in most LTP boutons. Notably, the summed membrane area of the vesicles lost in low-density LTP boutons is comparable to the surface membrane required for the observed bouton enlargement when compared to high-density control boutons. These novel findings suggest that presynaptic vesicle density provides a new structural indicator of LTP that supports a local mechanism of bouton enlargement.

Astrocyte-derived PTPRZ1 regulates astrocyte morphology and excitatory synaptogenesis
Protein tyrosine phosphatase receptor type Z1 (PTPRZ1) is one of the most abundantly expressed and enriched proteins in astrocytes during development, yet its function in astrocytes is unknown. Using an astrocyte-neuron co-culture system, we found that knockdown of Ptprz1 in astrocytes significantly impaired astrocyte branching morphogenesis. To investigate the function of PTPRZ1 in astrocytes during brain development, we generated a Ptprz1 conditional knockout mouse and deleted Ptprz1 from astrocytes postnatally, after the bulk of astrogenesis is complete. At postnatal day 21, we found defects in astrocyte morphology and a reduction in excitatory synapse number across multiple layers of the visual cortex, suggesting important functions for astrocytic PTPRZ1 in both astrocyte morphogenesis and synaptogenesis. PTPRZ1 is expressed in several neural cell types, including radial glial stem cells and oligodendrocyte progenitor cells (OPCs), and regulates critical aspects of neurodevelopment, including neurite outgrowth, neuronal differentiation, myelination, and extracellular matrix (ECM) development. Moreover, altered PTPRZ1 expression is associated with schizophrenia and glioblastoma. Therefore, this mouse model is a valuable resource for investigating cell-type-specific PTPRZ1 function in numerous neurodevelopmental and neuropathological mechanisms.

Cross-species Standardised Cortico-Subcortical Tractography
Despite their importance for brain function, cortico-subcortical white matter tracts are under-represented in diffusion MRI tractography studies. Their non-invasive mapping is more challenging and less explored compared to other major cortico-cortical bundles. We introduce a set of standardised tractography protocols for delineating tracts between the cortex and various deep subcortical structures, including the caudate, putamen, amygdala, thalamus and hippocampus.
To enable comparative studies, our protocols are designed for both human and macaque brains. We demonstrate how tractography reconstructions follow topographical principles obtained from tracers in the macaque and how these translate to humans. We show that the proposed protocols are robust against data quality and preserve aspects of individual variability stemming from family structure in humans. Lastly, we demonstrate the value of these species-matched protocols in mapping homologous grey matter regions in humans and macaques, both in cortex and subcortex.

HPDL is critical in human cortical development via regulation of mitochondrial functional properties
Human brain development is highly regulated by several spatiotemporal processes, which disruption can result in severe neurological disorders. Emerging evidence highlights the pivotal role of mitochondrial function as one of these fundamental pathways involved in neurodevelopment. Our study investigates the role of 4-hydroxyphenylpyruvate dioxygenase-like (HPDL) protein in cortical neurogenesis and mitochondrial activity, since mutations in the HPDL gene are associated with SPG83, a childhood-onset form of hereditary spastic paraplegia characterized by corticospinal tract degeneration and cortical abnormalities. Starting from mutant neuroblastoma cells, we demonstrated that HPDL is essential to mitochondrial respiratory chain supercomplex assembly and cellular redox balance. Moreover, transcriptomic analyses revealed dysregulated pathways related to neurogenesis, implicating HPDL role in early cortical development. To further elucidate the role of HPDL, we generated cortical neurons and organoids from SPG83 patient-derived induced pluripotent stem cells. Mutant cells exhibited premature neurogenesis at early differentiation stages, likely leading to depletion of cortical progenitors, as evidenced by decreased proliferation, slight increase of apoptosis, and unbalanced cortical type composition at later stages. Furthermore, cortical organoids derived from SPG83 patients showed impaired growth, reminding microcephaly observed in severe cases. In addition, mitochondrial morpho-functional characterization in mutant neurons confirmed disruption of OxPhos chain functionality and increased ROS generation rate. Treatment of cortical cells with two antioxidant compounds, could partially revert premature neurogenesis. In conclusion, our findings reveal a critical role for HPDL in coordinating cortical progenitor proliferation, neurogenesis, and mitochondrial function. These insights shed light on a mechanistical understanding of SPG83 pathology and underscore the therapeutic potential of targeting oxidative stress in this and related neurological disorders.

In-phase and anti-phase dual-site beta tACS differentially influence functional connectivity and motor inhibition
Inhibitory control relies on coordinated beta-band activity within a fronto-basal ganglia network, which implements inhibition via downstream effects on (pre)motor areas. In this study, we employed dual-site transcranial alternating current stimulation (tACS) targeting the right inferior frontal gyrus (rIFG) and primary motor cortex (M1) to directly manipulate phase relationships in the beta band and assess their effects on both functional connectivity and motor inhibition. Fifty-two healthy participants received in-phase, anti-phase and sham stimulation while performing a stop-signal task. The results revealed that connectivity between rIFG and lM1 increased following in-phase but decreased after anti-phase stimulation. Although no direct modulation of task performance was observed, the greater connectivity increase between the targets during in-phase stimulation was predictive of faster inhibitory performance. In contrast, greater connectivity decreases during anti-phase stimulation were related to faster go responses, suggesting a shift towards less inhibition on the motor system. These findings provide evidence that dual-site beta-tACS can both enhance and impair inhibitory control depending on phase alignment, highlighting its potential as a non-invasive intervention for disorders marked by impaired inhibition.

Perceptual prediction error supports implicit process in motor learning.
Error-based learning underlies motor learning, but what specific motor error drives implicit learning, the procedural component of motor skill, is unclear. A typical action consists of a movement and a performance outcome, e.g., grabbing a coffee cup involves a reaching movement and its actual landing of the hand relative to the target cup. While performance error is fundamental for the cognitive component of motor learning, what error, either performance or movement prediction error, underlies implicit motor learning has not been resolved. These two errors are hard to disentangle as the performance outcome is an integral part of the movement. Here we used the classical visuomotor adaptation paradigm, in which people learn to counter visual perturbations by deliberately aiming off the target, to dissociate the performance error from the prediction error. Using a series of behavioral experiments and model comparisons, we revealed that movement prediction error, but not performance error, can parsimoniously explain diverse learning effects. Importantly, despite the perturbation is visual, the movement prediction error is not specified in visual terms, but determined by a perceptual estimate of the hand kinematics. In other words, contrary to the widely-held concept of sensory prediction error, a perceptual prediction error drives implicit motor learning.

Neurogliaform cells mediate interhemispheric modulation of sensory-evoked activity in cortical pyramidal neurons
Integration of bilateral sensory inputs requires effective communication between brain hemispheres. This interhemispheric communication is essential for sensory perception and involves reciprocal connections between homotopic sensory areas. A key role in this process is attributed to interhemispheric inhibition which, owing to its long-lasting form, is posited to operate largely through neurogliaform cells (NGCs). However, direct evidence on the role of NGCs in interhemispheric inhibition is missing. Here we show that NGCs in the mouse barrel cortex (BC) are engaged by interhemispheric callosal projections to modulate pyramidal neuron (PN) activity and sensory perception. Using optogenetics, ex vivo whole-cell recordings, and in vivo calcium imaging, we found that layer 1 and layer 2/3 (L1-3) NGCs are strongly activated by the callosal and suppressed by the thalamocortical pathway, suggesting that NGCs encode ipsilateral rather than contralateral whisker stimuli. We also found that direct stimulation of L1-3 NGCs modulates whisker-evoked activity in L2/3 and L5b PNs, and increases the perceptual threshold in a whisker-deflection detection task. Furthermore, these effects were recapitulated by direct stimulation of callosal projections and deflection of the ipsilateral whiskers respectively, suggesting that the effect of the callosal pathway on sensory perception is mediated by NGCs. Our results not only prove that NGCs mediate interhemispheric inhibition, but also demonstrate their role in sensory perception via modulation of the main units involved in cortical input and output.

Sleep is associated with reduction of excitatory signaling in medial prefrontal cortex
Although many sleep medications enhance inhibitory signaling, it remains unclear whether inhibitory or excitatory neurotransmitters contribute to the natural transition from wakefulness to sleep in humans. Here, we show that changes in excitatory, rather than inhibitory, neurotransmitter levels are associated with this transition. Young, healthy participants underwent two nap sessions with polysomnography, during which glutamate and GABA concentrations in the medial prefrontal cortex were measured using magnetic resonance spectroscopy. Glutamate gradually decreased during deeper sleep stages compared to wakefulness in the second session, with better sleep quality. No such change occurred in the first session with poorer sleep, likely due to the first-night effect. Furthermore, reduced glutamate significantly mediated sleep-onset latency in both sessions. Conversely, GABA concentration did not change from wakefulness to sleep in either session. These findings provide the first evidence that reduced excitatory signaling is a key feature of natural good sleep onset in the human brain.

Gut transit and gut microbiome changes occur prior to the onset of motor impairment in a mouse model of Machado-Joseph disease
We previously identified microbial shifts prior to the onset of motor and neurological symptoms within a mouse model of the fatal neurodegenerative disease Machado-Joseph disease (MJD). Here, we aimed to explore possible mechanisms contributing to these changes within the microbiome-gut-brain axis, and whether it preceded or followed central neurodegeneration. Here, we report that pre-symptomatic male MJD mice present with significantly different microbiome communities as early as 5-weeks-old. Furthermore, we show that male MJD mice have faster total gut transit times by 9-weeks-old, prior to signs of impaired motor function by 11- weeks-old. To elucidate whether these microbial and colonic functional changes are due to the presence of pathological and morphological changes in the gut, we quantified the formation of ataxin-3 protein aggregates within the gut and examined morphological changes within the gut of pre- and early symptomatic MJD mice relative to proteinopathy in the brain. Interestingly, we observed ataxin-3 aggregates within the brains of pre-symptomatic MJD mice, with significantly more aggregates present in MJD than WT mice from 7-weeks-of-age, an earlier timepoint than previously reported, coinciding with changes within the microbiome. However, we observed no ataxin-3 protein aggregates and no changes in enteric neuron populations or morphology within the gut. Analysis of endocrine factors involved in gut motility and inflammatory markers within the small intestine of 13-week-old males revealed increased expression of genes encoding cholecystokinin (Cck), ghrelin (Ghrl), heme oxygenase (Ho1), interleukin-1 beta (Il1b), and decreased inducible nitric oxide synthase (Nos2). Together, we demonstrate for the first time that colonic dysfunction occurs after gut microbiome changes, but prior to the onset of motor impairments in male MJD mice. Our work suggests that whilst proteinopathy or morphological changes within the gut may not be involved in these changes, inflammation and related endocrine changes could have a role in the interplay between the gut and brain during MJD development, warranting further investigation.

Neurophysiological Markers of Cancer-Related Fatigue Derived from High-Density EEG
Cancer-related fatigue (CRF) significantly diminishes the quality of life of cancer survivors; however, objective diagnostic markers and the underlying neurophysiological mechanisms remain unclear. This study aimed to identify noninvasive EEG-based biomarkers of CRF by examining cortical activity and functional connectivity. We recorded resting-state and task-related [repetitive submaximal elbow flexion (EFs) until self-perceived exhaustion] high-density electroencephalography (EEG) from 10 cancer survivors with CRF and 14 healthy controls (HC). In our analysis, task-induced fatigue was categorized as mild, moderate, and severe, corresponding to the level of fatigue perceived at the beginning, middle, and end of the task period. Our study revealed the following significant findings: (1) Linear mixed-effects modeling of event-related desynchronization (ERD) EEG analysis during the EF task demonstrated significant effects of group and fatigue levels in the alpha band (8-12 Hz). (2) EF task-specific functional connectivity was estimated using the debiased weighted phase-lag index (dwPLI), which demonstrated reduced inter-regional connectivity in the M1 and prefrontal regions in the CRF group compared with the HC group. (3) The dwPLI analysis identified significantly reduced alpha-band connectivity strength in the CRF group, particularly between the right supramarginal gyrus and other brain regions during mild fatigue. (4) Additionally, resting-state EEG exhibited globally elevated delta band (1-4 Hz) activity in CRF survivors than HC, potentially reflecting chronic fatigue. These observations emphasize the clinical relevance of resting-state EEG, motor activity-related ERD and functional brain connectivity as potential CRF biomarkers. Future research should validate these findings in larger cohorts and provide insights into more objective CRF diagnosis and the development of personalized interventions for alleviating CRF.

Computational modeling-directed combination treatment with etanercept and mifepristone mitigates neuroinflammation in a mouse model of Gulf War Illness.
Gulf War Illness is a chronic multi-symptom disorder experienced by over 30% of veterans from the 1990-1991 Gulf War and is increasingly recognized to be driven by underlying persistent neuroinflammation resulting from chemical and physiological exposures experienced during deployment. Despite significant advances in identifying Gulf War-relevant exposures and underlying pathobiology, effective treatment strategies for Gulf War Illness are still largely lacking. Many studies that have evaluated potential therapies for Gulf War Illness have primarily focused on a single treatment. However, through a mechanistically informed computational evaluation of blood biomarkers and gene expression in veterans with Gulf War Illness, we identified that a combination of anti-inflammatory and anti-glucocorticoid treatment may prove effective in treating Gulf War Illness. Here, we have evaluated combined treatment with the anti-TNF drug, etanercept, and anti-glucocorticoid, mifepristone, in an established long-term mouse model of Gulf War Illness of combined physiological stress and nerve agent exposure. Supporting results from the computational modeling of this treatment, we found that this drug combination significantly alleviates the underlying neuroinflammation associated with Gulf War Illness. The fusion of computational and in vivo preclinical treatment evaluation may provide a highly useful and translationally relevant means by which to identify successful treatment paradigms for Gulf War Illness.

Is the whole the sum of its parts? Neural computation of consumer bundle valuation in humans
Humans are often tasked with making decisions about bundles of multiple items and very little is known about how the human brain aggregates, computes and represents value in such cases. We investigated how the human brain evaluates consumer items, both individually and in bundles, and how this activity relates to choice behavior. Participants underwent a deep-fMRI scanning protocol while we elicited behavioral valuations for single and bundled items. Behaviorally, we find that bundle values are sub-additively discounted compared to the sum of individual item values. Neurally, we find that the same distributed network in pre-frontal cortex computes the value of a bundle and its constituent individual items, but the value representation undergoes a normalization that actively re-scales across bundle and single item contexts. These findings suggest that generalized value regions contextually adapt within a valuation hierarchy, as opposed to utilizing an absolute value code.

Attention to a point in time causes a suppressive wake for subsequent time points
The Selective Tuning model proposed that attention to a visual stimulus suppresses interfering portions of the processing hierarchy. This has been shown in spatial and featural domains and the proposal extends to the temporal dimension. We investigated whether attending to a point in time leads to processing suppression of nearby time points. We presented a sequence of letters with an embedded target, and observers indicated the target's orientation. In the neutral condition, the target appeared randomly in one of the frames. In the informative condition, the target appeared in the same frame on most of the trials ('expected' trials), and the expected frame varied between blocks (Experiments 1-3) or groups (Experiment 4). On the remaining trials, it appeared before or after the most-probable frame ('unexpected' trials). Four different experiments were conducted to adjust the method and in the final one we found higher accuracy in expected trials than in neutral trials, indicating the allocation of temporal attention to the expected frame. When the target appeared after the expected frame, accuracy was lower than in the same neutral condition frame, suggesting an attentional suppressive wake in time (because the effect of attention cannot be observed until after stimulus onset).

Repeated blood-brain barrier opening using low-intensity pulsed ultrasound mitigates amyloid pathology
Background: The delivery of large molecules to the pathological brain is one of the main obstacles in the development of disease-modifying drugs. This is partly due to the presence of the blood-brain barrier (BBB), which blocks the free passage of lipophobic molecules and those larger than 400 Da. One strategy to bypass this natural barrier is to use low intensity pulsed ultrasound (LIPU) to oscillate circulating micro-sized microbubbles which then exert mechanical stress on the vessel walls. This procedure allows for temporary disruption of the BBB and enhanced local delivery of therapeutics from the blood to the brain parenchyma. In this study, the effect of repeated BBB opening on neuroinflammation in a healthy mouse model was first explored followed by the effect of repeated opening on amyloid pathology in a model for Alzheimer's disease. Methods: A cohort of wildtype mice was used to determine the effect of a single BBB opening mediated by ultrasound/microbubbles (US/MB) on the inflammatory profile, using RT-Q-PCR on brain extracts at 2-, 4-, 8- and 15-days post opening. A second cohort of ARTE10 mice, a mouse model for amyloid pathology, was treated with a different sequence of repeated US/MB mediated BBB opening to explore the effect on the pathology. Tissues were also analyzed for immune cell infiltration, microglia and astrocyte activation, and inflammatory response. Results: Our results demonstrate that the opening of the BBB leads to a mild inflammatory response in wild-type animals. However, repeated opening of the BBB in the ARTE10 model resulted in a decrease in amyloid pathology, along with a mild increase of growth factor. Conclusions: Altogether, this study suggests that sonication is not only a safe method to deliver therapeutics to the brain but could also have synergistic effects in the treatment of neurodegenerative diseases.

Changing cognitive chimera states in human brain networks with age: Variations in cognitive integration and segregation
The aging process profoundly impacts the human brain, leading to notable changes in cognitive abilities. Although the brains structural and functional alterations with age are individually well documented, how differences in cognitive abilities emerge from variations in the underlying spatio-temporal patterns of regional brain activity is largely unknown. Patterns of increased synchronization between brain regions are taken as enhanced cognitive integration, while decreased synchronization is indicative of cognitive segregation. The ability to dynamically switch between different levels of integration and segregation across different cognitive systems is believed to be crucial for overall cognitive performance. Building on a recently proposed cognitively informed, synchronization-based framework, we study here age-related variations in dynamical flexibility between segregation and integration, as captured by changes in the variable patterns of partial synchronization or chimera states. Leveraging personalized brain network models based on large-scale, multisite datasets of cross-sectional healthy cohorts, we systematically show how regional brain stimulation produces distinct patterns of synchronization. We find that chimera states play a crucial role in regulating the balance between cognitive integration and segregation as the brain ages, providing new insights into the mechanisms underlying cognitive decline and preservation in aging. Whereas the emergent synchronization behavior of brain regions belonging to the same cognitive system often show the same aging trends, different cognitive systems can demonstrate distinct trends. This supports the idea that aging affects cognitive systems differently and that understanding this variability is essential for a more comprehensive view of neuro-cognitive aging. At the same time, dynamical flexibility increases in the oldest age groups across most cognitive systems. This may reflect compensatory mechanisms to counteract age-related cognitive declines and points towards a phenomenon of dedifferentiation. Yet, the multiplicity of behaviors highlights that whereas dedifferentiation emerges in certain cognitive systems, differentiation can also occur in others. This illustrates that these processes, though seemingly oppositional, can coexist and unfold in parallel across different cognitive systems.

Interaction between Model-based and Model-free Mechanisms in Motor Learning
Motor learning can be driven by distinct mechanisms - habitual, model-free processes, and strategic, model-based processes-depending on the magnitude and context of movement errors. Although small and large errors are known to engage distinct motor learning mechanisms - model-free (implicit) or model-based (explicit), respectively - it remains unclear whether successfully deploying one mechanism might hamper the engagement of the other in subsequent learning tasks. Here, we investigated how prior engagement of a particular mechanism biases future adaptations, even when the new task context typically favours the alternative strategy. Across three experiments (N=82), participants performed reaching movements to targets that either remained fixed or jumped mid-movement by small (15{degrees}) or large (30{degrees}, 45{degrees}, or 60{degrees}) angles. When first exposed to small errors (15{degrees}), participants exhibited persistent aftereffects in subsequent catch trials and stable reaction times (RTs), hallmarks of a model-free, habitual process. Surprisingly, even when switching to larger error magnitudes later, these participants continued to show robust aftereffects and did not elevate RTs - indicating a carryover of model-free learning. Conversely, participants who initially experienced large errors showed minimal aftereffects and flexible RT modulation consistent with model-based strategies; this bias persisted in later sessions with smaller errors, leading to reduced habitual aftereffects. Notably, inserting a washout phase to reset baseline performance did not abolish these mechanistic biases, highlighting that the initial engagement of either model-free or model-based processes leaves a durable imprint on subsequent adaptations. Taken together, these findings demonstrate that motor learning is shaped not only by ongoing task demands (e.g., error magnitude) but also by an individual's prior learning history. Understanding how initial learning experiences constrain future adaptations has broad implications for designing interventions and training protocols in motor rehabilitation and skill acquisition.

Neural correlates of appetitive extinction learning: An fMRI study with actively participating pigeons
Extinction learning is an important learning process that enables adaptive and flexible behavior. Human neuroimaging studies show that the neural basis of extinction learning consists of a neural network that includes the hippocampus, amygdala, and subcomponents of the prefrontal cortex, but also extends beyond them. The limitations of applying fMRI to actively participating animals have so far restricted the identification of the entire extinction network in non-human animals. Here, we present the first fMRI study of extinction in awake and actively participating pigeons, using a Go/NoGo operant paradigm with a water reward. Our study revealed an extensive and largely left hemispheric telencephalic network of sensory, limbic, executive, and motor areas that slowly ceased to be active during the process of extinction learning. We propose that the onset of extinction ignites a neuronal updating of the associated consequences of own actions within a large telencephalic neural network until a new association is established which inhibits the previously acquired operant response.