Gamma activity temporally dissociates sensory encoding from perceptual decision-making in human olfactory circuits

Gamma activity temporally dissociates sensory encoding from perceptual decision-making in human olfactory circuits | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Biological Sciences - Article Gamma activity temporally dissociates sensory encoding from perceptual decision-making in human olfactory circuits Robert Richardson, Alan Bush, Yanming Zhu, Zack Lajoie, Amir Hadanny, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9107770/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Smell is intimately linked to emotion, memory, hazard detection, and social communication, yet the neural mechanisms by which human olfactory circuits encode chemosensory stimuli and transform them into conscious percepts remain poorly understood. We combined stereotactic electroencephalography (SEEG) with a passive, inspiration-triggered olfactometer that delivers odorized air without voluntary sniffing, attentional cuing, or motor engagement, enabling clean separation of sensory, perceptual, and motor contributions to chemosensory processing. Across 19 participants (two subjects had two study sessions), we identified two temporally and functionally distinct gamma-band components within human olfactory circuits. An early, stimulus-locked gamma response reflects primary olfactory encoding: it persists on trials in which participants fail to report odor detection, demonstrating that sensory processing proceeds independently of conscious awareness. A later gamma component is time-locked to behavioral report and emerges hierarchically across limbic structures, reflecting perceptual decision-making and response preparation. Gamma responses also encode odor intensity through two dissociable mechanisms: graded, dose-dependent modulation and switch-like, report-dependent dynamics, consistent with a signal-detection framework for perceptual threshold. These findings establish that gamma activity dissociates primary sensory encoding from higher-order perceptual decisions in human olfactory circuits, demonstrating that the computational principles governing sensory awareness in vision and touch extend to human olfaction. Biological sciences/Neuroscience/Olfactory system/Olfactory cortex Biological sciences/Physiology/Neurophysiology Biological sciences/Psychology/Human behaviour Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Despite the well-established associations of olfaction with emotion and memory, and its broader importance in hazard detection, social communication, and quality of life, the neural dynamics of human olfactory processing remain incompletely understood. This knowledge gap has significant clinical implications: an estimated 22% of the general population lives with smell disorders, a prevalence likely increased by the COVID-19 pandemic 1 . Olfactory dysfunction significantly impairs quality of life 2-4 , yet remains underappreciated relative to other sensory impairments. Translating insights from animal models to human olfactory physiology is challenging, as the ethological role, behavioral relevance, and cortical integration of olfaction differ substantially across species. Consequently, there is no coherent understanding of how human olfactory structures encode stimulus identity, intensity, and perceptual detection 5,6 . In rodents, olfactory-induced brain activity has been extensively studied using electrophysiological methods, revealing important roles for single-unit firing and oscillatory dynamics in the olfactory bulb and cortex 7-11 . Prior work has implicated gamma involvement in odor identification 12-14 , theta coupling to respiration, and beta involvement in feedback interactions 12,15,16 . The contributions of these rhythms across human chemosensory pathways, however, have not been systematically compared. Most human olfactory research has relied on noninvasive techniques such as functional magnetic resonance imaging, electroencephalography, and magnetoencephalography. While these approaches have provided important insights into large-scale network organization, they lack the spatial and temporal resolution necessary to study central olfactory circuits in detail. Stereotactic electroencephalography (SEEG), a diagnostic epilepsy surgery that provides local field potentials (LFP) along depth electrodes implanted throughout the brain, offers a unique opportunity to bridge this gap. Despite this potential, only a limited number of studies have examined human olfactory processing using intracranial recordings, reporting odor-evoked activity that reflects perception, memory, and behavioral relevance 12,13,15-26 . Access to millimeter-scale, time-resolved signals enables testing two outstanding questions about human chemosensory processing. First, how do olfactory and trigeminal pathways interact at the circuit level? Most odorants engage both systems, yet the neural mechanisms by which their signals converge or remain segregated in the human brain remain largely uncharacterized 27,28 . The two pathways overlap anatomically in the nasal epithelium and multiple brain structures 29,30 , and olfactory dysfunction has been associated with reduced trigeminal responsiveness 31,32 ; however, pure trigeminal processing and its interaction with olfactory circuits have received minimal investigation. Second, how are chemosensory representations transformed into perceptual decisions? In other sensory systems, perceptual report can diverge from early sensory encoding, and decision formation has been formalized within signal-detection and evidence-accumulation frameworks that distinguish continuous sensory evidence from categorical perceptual reports 33-36 . Whether similar computational principles govern human olfaction - and whether early sensory encoding can be dissociated from later decision-related activity within olfactory circuits - remains largely unexplored. Here, we address these gaps by combining SEEG with passive, inspiration-locked olfactometry that delivers odorized air without requiring sniffing, motor actions, or attentional cues. This approach isolates stimulus-evoked neural activity from respiration dynamics, enabling a clean dissociation of sensory, perceptual, and motor contributions to chemosensory processing. Across 19 participants, we analyzed LFP responses to phenyl ethyl alcohol (PEA), a pure olfactory stimulus, and CO₂, a selective trigeminal stimulus 37,38 . Passive Olfactory and Trigeminal Stimulation Elicits Artifact-Free Responses. To minimize task-related motion artifacts and isolate chemosensory neural circuitry, we developed a passive experimental paradigm for presenting olfactory stimuli (Figs. 1A and S2-3). Participants were patients with refractory epilepsy undergoing intracranial monitoring with SEEG depth electrodes for clinical purposes (Figs. S4). All participants underwent standardized olfactory screening with the Brief Smell Identification Test, which confirmed adequate odor identification before data collection (Table S1 and Fig. S5). A custom-built olfactometer delivered humidified air via a nasal cannula. Upon detecting inspiration onset, the system rapidly infused the airflow with odorized air from one of three reservoirs (PEA, CO₂, or odorless air) during natural inspiration (Figs. S6-7). We monitored respiration using a chest belt (Fig. S8) and a thermistor (Fig. S9) at the nasal opening, then trained a linear model for each participant to predict the onset of inspiration (Fig. S10). When the model output exceeded a predefined threshold, the olfactometer infused concentrated odorants into the airflow for a brief period (Fig. 1B). Participants wore noise-canceling headphones to mask acoustic noise generated by the olfactometer solenoid valves, minimizing attentional and auditory confounds. Offline photoionization detector (PID) calibration at the nasal cannula verified reliable, consistent odor delivery with ~250 ms latency and ~250 ms rise time to peak concentration after valve opening (Fig. 1B, bottom; Fig. S11), supporting use of a 250-ms pulse that was readily detected by normosmic subjects. Successful inspiratory delivery was achieved in 72% of trials overall (range 35–93% across participants, Figs. 1C and S12), with no requirement for active sniffing or task-related attention. A representative olfactory-responsive electrode localized to the amygdala (Fig. 1D) exhibited a transient increase in beta and gamma power immediately following stimulus onset, but we needed to determine whether this activity reflected genuine chemosensory processing. To disentangle odor-specific effects from respiration-related activity, we compared odor trials with two control conditions (Figs. 1E and S13): inspirations immediately preceding stimulus presentation and presentations of odorless air. Pre-stimulus inspirations evoked no significant deviation from baseline power (Fig. 1F, top right panel). Odorless air produced a weaker, temporally diffuse enhancement of theta-alpha power (Fig. 1F, bottom-left panel), likely due to mechanical effects or residual acoustic noise from valve switching that the noise-canceling headphones may not have fully masked, similar to observations from rodent studies 39,40 . In contrast, PEA (Fig. 1F, top-left panel) and CO 2 (Fig. 1F, bottom-right panel) evoked robust, time-locked increases in beta and gamma bands (Fig. S14, trial-by-trial activity in theta, beta, and gamma bands), with peak activity centered 0.5-2 s after valve opening, demonstrating that these responses reflect genuine chemosensory processing rather than respiratory or mechanical artifacts. Olfactory and Trigeminal Stimuli Elicit Dissociable Neural Signatures at Single-Electrode Resolution We compared responses to PEA, a pure olfactory stimulus, and CO₂, a selective trigeminal stimulus 37,38 , to determine whether these stimuli elicit functionally dissociable patterns across chemosensory pathways during the complete passive experiment. For each electrode, power changes were quantified from -0.5 to 1.5 s around stimulus onset. Fig. 2A shows representative electrodes that exhibited significant (one-way ANOVA corrected with the number of trials) encoding of either PEA alone (red, top row), CO₂ alone (blue, middle row), or both stimuli (lower row) when compared to odorless air (gray). We then examined the patterns that emerged across frequency bands. Using a cluster-based permutation test (CBPT), we quantified the number of electrodes that were significantly responsive to each stimulus across frequency bands (Figs. 2B, S15, and Table S2). For electrodes encoding for both PEA and CO 2 , the majority were in the gamma band (30-200 Hz). Among electrodes responsive to both PEA and CO 2 , more were significant in the theta and beta bands (γ vs β: Z = 7.24, p = 4.5 × 10⁻¹³; γ vs θ: Z = 6.51, p = 7.3 × 10⁻¹¹; β vs θ: Z = 0.49, p = 0.624). We also observed band-specific differences in activities selective for PEA (γ vs β: Z = -2.45, p = 0.014; γ vs θ: Z = 1.36, p = 0.175; β vs θ: Z = 3.79, p = 1.49 × 10⁻ 4 ), but not CO 2 (γ vs β: Z = -0.76, p = 0.448; γ vs θ: Z = 0.33, p = 0.743; β vs θ: Z = 1.09, p = 0.277). To further characterize these distinctions, we plotted each electrode’s median evoked power change to PEA against its response to CO₂ (Fig. 2C), categorized by stimulus selectivity. To test whether the spatial distribution of odorant-selective versus trigeminal-selective activity is anatomically organized, we plotted all significant contacts in MNI space (Montreal Neurological Institute, MNI152, and wrapped with HCP-MMP1 atlas) and labeled each by response class (PEA-only, CO₂-only, PEA∩CO₂). We mapped all electrodes showing significant power increases to PEA and CO₂ during the passive presentation task using a CBPT (Fig. 2D). Responsive electrodes were distributed bilaterally but concentrated within canonical chemosensory regions, including the amygdala, piriform cortex, and insula. When responses were stratified by frequency band, theta, beta, and gamma activity were substantially intermixed within each region, and no clear spatial organization was apparent (Figs. 2E, and S16). To quantify whether gamma-band convergence of olfactory and trigeminal responses was region-specific, we compared the observed number of jointly responsive electrodes to that expected by chance using χ² tests across brain regions. The amygdala, piriform cortex, and insula each exhibited a significant over-representation of joint (PEA∩CO₂) responsive electrodes, far exceeding chance levels when corrected for the number of contacts (amygdala: χ² = 58.49, p = 2.0×10⁻¹⁴; piriform: χ² = 34.17, p = 5.05×10⁻⁹; insula: χ² = 11.57, p = 6.7×10⁻⁴). Additionally, gamma activity accounted for the majority of PEA∩CO₂ electrodes. In contrast, beta and theta contained relatively few PEA∩CO₂ contacts but a larger share of stimulus-selective (PEA or CO₂) electrodes. Within the hippocampus, all significant contacts were stimulus-selective (Figs. 2E and S17). Stimulus-Locked and Report-Locked Gamma Activity Reveal Separable Stages of Olfactory Processing To determine whether gamma activity reflects primary olfactory encoding or higher-order processes (perceptual decision-making or motor preparation), we conducted a perceptual detection task in which participants pressed a button to report odor detection. We analyzed the temporal relationships among gamma activity, stimulus presentation, and behavioral response across electrodes. Here, although the participants were reporting their perceptions, their inspiration phase remains completely passive and locked to their natural inhalation. Two representative electrodes illustrate these distinct temporal profiles (Fig. 3A): one electrode showed gamma activity aligned to the onset of odor delivery (left, stimulus-locked, suggesting a sensory rather than motor or cognitive origin), and another showed gamma activity that preceded the button press (right, motor-locked). Critically, this stimulus-locked gamma activity was also present on trials in which participants failed to report odor detection (“missed” trials; Fig. 3A, green box). Despite the absence of an overt perceptual report, gamma onset remained tightly time-locked to odor presentation, indicating that neural processing of the odor stimulus occurred independently of conscious detection or behavioral reporting. To determine whether gamma-band activity was temporally associated with sensory input or behavioral report, we employed an interval-based timing analysis 41 . Specifically, for each trial, we quantified two complementary time intervals: (1) the latency from odor valve opening to gamma onset, indexing alignment to stimulus presentation, and (2) the latency from gamma onset to button-press response, indexing alignment to behavioral report (Fig. 3B). An electrode whose gamma onset is fixed relative to the valve opening will show no correlation between valve-to-gamma latency and total button-press latency, since the gamma timing is independent of how long the participant took to respond. We used a regression-based method to quantify the two electrode groups. An odor-locked electrode is operationally defined by the absence of correlation between valve-opening-to-gamma-onset latency and total button-press latency (Fig. 3C, left), while the button-press locked electrode is defined as no correlation between gamma modulation onset to button press with button-press latency (Fig. 3C, right). We applied this regression-based method to all electrodes (Fig. 3D). These findings demonstrate that human olfactory processing can be partitioned into an early component reflecting sensory olfactory encoding and a later component associated with perceptual decision-making and response-related processes underlying conscious detection, on the scale of milliseconds. We next asked whether stimulus-locked and report-locked activities were preferentially localized to distinct anatomical structures. We examined the distribution of response classifications across all sampled regions (Fig. 3E). Report-locked electrodes were located in the amygdala, insula, hippocampus, and orbitofrontal cortex (OFC). Amygdala electrodes tended to show gamma activity emerging earliest relative to the button press, whereas insular and hippocampal electrodes exhibited gamma onset closer to the behavioral response. OFC responses were largely time-locked to the button press, suggesting a direct role in late-stage decision commitment or motor execution, and the presence of a decision-related hierarchy within the olfactory circuit. Neural Responses Encode Odor Intensity Through Both Graded and Threshold-Based Mechanisms Having established that gamma activity comprises distinct stimulus-locked and report-locked components, we next asked whether these components also reflect the graded physical properties of the stimulus itself, specifically, whether olfactory regions encode odor intensity, perceptual detection, or both. We conducted a dose-response experiment in which participants received inspiration-locked PEA pulses at varying intensities. By varying the duration of solenoid valve opening, we modulated odorant intensity, as continuous airflow ensured that the inhaled odor dose scaled with valve open time (Figs. 4A and S18). In our hardware design, the latency for odorants to reach the nose was consistent (~0.5s; Fig. S18C) and did not depend on pulse duration. For this task, participants passively inhaled during each trial and pressed a button to report detection of an odor (Figs. 4B and S19). Across participants, the probability of detection increased monotonically with odorant dose (Figs. 4C and S20). Two representative electrodes showed distinct response profiles: one exhibited a monotonic increase in gamma power with increasing odor dosage, while the other showed a switch-like increase (Fig. 4D) with a dose-response relationship (Fig. 4E). For each electrode, we fitted a linear regression model relating trial-by-trial gamma activity to computed odorant dose, separately for detected and undetected trials. Electrodes were classified based on model parameters: those with a significant positive slope (graded response), those with a significant positive intercept (switch-like response), and those with no significant relationship (Figs. 4F, S21-22, and Table S3). These findings reveal two distinct neural components in the human olfactory cortex: a graded component that continuously encodes intensity and a switch-like component associated with perceptual awareness. Discussion Human olfactory circuits implement hierarchical computations that dissociate primary sensory encoding from perceptual decision-making, a computational organization previously characterized in vision and touch but not established in olfaction. Combining millimeter-scale intracranial recordings with passive olfactory stimulation, we demonstrate three key principles of this organization. First, olfactory and trigeminal information converges in gamma frequencies within the amygdala and piriform cortex while remaining segregated in the hippocampus, demonstrating hierarchical processing. Second, stimulus-locked gamma persists even without conscious detection, whereas report-locked gamma emerges hierarchically across limbic structures during perceptual decisions. Third, neural responses exhibit both graded intensity encoding and categorical threshold dynamics, paralleling signal detection frameworks in other sensory modalities 42,43 . These findings establish that human olfaction follows computational principles previously characterized only in vision and touch networks, with distinct mechanisms supporting sensory representation and perceptual awareness. Prior neuroimaging studies provide complementary evidence for this functional dissociation between the olfactory and trigeminal pathways. fMRI studies have shown that both odorant and trigeminal stimuli activate the ventral insular cortex, a known multisensory hub. However, trigeminal stimulation also recruits a broader network that includes the midbrain, superior temporal gyrus, anterior caudate nucleus, and dorsolateral orbitofrontal cortex, with responses typically more prominent in the right hemisphere 44 . Here, we showed that olfactory and trigeminal signals can be functionally dissociated at the single-electrode level, despite overlapping anatomical substrates. Theta- and beta-band responses largely segregated the two pathways, whereas gamma-band activity exhibited substantial convergence across piriform cortex, amygdala, and insula. This convergence was notably absent in the hippocampus, which maintained parallel, stimulus-selective representations. These findings argue against a purely anatomical model of chemosensory integration and instead support a frequency-based organizational principle, whereby the same anatomical region can support segregated or convergent processing depending on the oscillatory frequency engaged. In this framework, theta- and beta-band rhythms preferentially support modality-specific feedforward and feedback interactions, whereas gamma activity supports shared integrative processing across chemosensory inputs. Passive inspiration-locked delivery minimized motor artifacts and controlled for the confounding influence of respiration-entrained neural activity. Respiration has long been recognized as an intrinsic organizer of neural activity in the olfactory system, synchronizing oscillations in the olfactory bulb and cortex to optimize temporal sampling of incoming odors 45,46 . Aligning stimulus delivery with inspiration enabled us to isolate stimulus-evoked activities from those driven purely by breathing dynamics. This methodological advance strengthens the interpretation that the observed rhythmic activity reflects sensory and cognitive processing rather than respiratory entrainment. A previous study reported increased theta, beta, and gamma rhythms in the piriform cortex during an active odor-detection task 12 , but could not demonstrate a direct association between gamma activity and odor presence, in part because participants were cued to sniff at a specific time point 47 , a design that conflates sensory, motor, and attentional contributions to the neural response. Our fully passive paradigm eliminates this confound by delivering odorized air during natural inspiration without sniffing cues, attention, or motor preparation. Critically, this design enabled us to examine trials in which odor was delivered but went undetected, revealing that stimulus-locked gamma activity persists in the absence of conscious report, a dissociation that is inaccessible in paradigms requiring overt behavioral engagement with each stimulus. The piriform cortex and the amygdala are both parts of the primary olfactory cortex, and both receive projections from the olfactory bulb 15,26,48 . They are anatomically adjacent; for example, the periamygdaloid cortex is situated at the interface between the two structures and shares connections with the piriform cortex 49 . Although it can be assumed that their activity patterns are similar, the amygdala is a complex of multiple nuclei, and the piriform cortex is divided into anterior and posterior parts, each involved differently in olfactory processing 26,50 . Moreover, it appears that the amygdala maintains a distinct organization of olfactory bulb projections, whereas the piriform cortex does not 51 . Thus, they might be subject to differential influences, such as odorant characteristics (chemical or psychophysical) or the cognitive demands of the task 51 , a framework supported by our data, which show that the piriform cortex and amygdala share gamma-band convergence, whereas the hippocampus does not, instead exhibiting parallel representations of odorant and trigeminal inputs. Thus, the variability observed in prior studies may reflect subregional functional specialization, as revealed more clearly in our large-scale SEEG dataset. A key finding of this study is that gamma activity in human olfactory regions is not monolithic but instead comprises at least two temporally and functionally distinct components. Stimulus-locked gamma responses likely reflect early sensory encoding of chemosensory input, consistent with prior work implicating gamma oscillations in odor identity and intensity coding. In contrast, report-locked gamma responses appear to index later-stage processes related to perceptual decision-making and response preparation. The presence of these decision-related gamma activity within olfactory regions has not been previously reported in human intracranial studies. This finding suggests that the olfactory cortex participates not only in sensory representation but also in downstream computations that culminate in conscious detection. Critically, stimulus-locked gamma activity was also observed on trials in which participants failed to report odor detection. On these “missed” trials, gamma onset remained time-locked to odor delivery despite the absence of an overt perceptual report or behavioral response, indicating that this activity reflects primary olfactory processing driven directly by sensory input. Such dissociation between neural sensory encoding and perceptual report aligns with models in which olfactory information is processed at early cortical and limbic stages, even when it fails to reach awareness. Stimulus-locked gamma therefore may reflect a hierarchical functional distinction between a pre-decisional sensory component and later decision-related gamma activity. Although decision-locked gamma responses were observed across multiple regions, their timing relative to behavioral report varied systematically across structures. Amygdala locations tended to exhibit gamma onset earlier relative to the button press, whereas insular and hippocampal locations exhibited gamma activity closer to the behavioral response, and the orbitofrontal cortex was largely time-aligned with reporting. These findings suggest a process hierarchy in olfactory-limbic circuits, with earlier structures (amygdala) involved in evidence accumulation and later structures (OFC) involved in response execution. The presence of report-locked, switch-like gamma responses suggests that human olfactory perception can be interpreted within a signal detection theory framework. Early stimulus-locked gamma activity reflects the accumulation of sensory evidence, which varies continuously with stimulus intensity and is present even on trials lacking perceptual report. In contrast, switch-like and report-locked gamma activities are associated with decision-criterion crossing and motor preparation. Such a dissociation between sensory evidence and decision-related signals has been extensively described in visual and somatosensory systems but has not previously been demonstrated within human olfactory regions 52,53 . Together, these results establish signal-detection-like computation as a conserved organizational principle across sensory modalities, extending frameworks developed in vision and touch to the chemical senses. Beyond their basic science implications, these findings carry translational relevance: the dissociation between stimulus-locked and report-locked gamma provides candidate biomarkers for objective assessment of olfactory function in patients with smell disorders, a population affecting an estimated 22% of the general public and disproportionately impacted by COVID-19. 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A., Winston, J. S. & Dolan, R. J. Dissociable Codes of Odor Quality and Odorant Structure in Human Piriform Cortex. Neuron 49 , 467-479, doi:10.1016/j.neuron.2006.01.007 (2006). Shadlen, M. N. & Newsome, W. T. Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. Journal of neurophysiology 86 , 1916-1936 (2001). de Lafuente, V. & Romo, R. Neuronal correlates of subjective sensory experience. Nature neuroscience 8 , 1698-1703 (2005). Additional Declarations There is NO Competing Interest. Supplementary Files table1smelltest.xlsx Table 1 table2passivegrouplevel.docx Table 2 table3doseresponse.docx Table 3 table4subjectdemographics.xlsx Table 4 Gammatemporaldissociation12Mar2026Suppl.docx Manuscript supplementary material Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9107770","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Biological Sciences - Article","associatedPublications":[],"authors":[{"id":613470409,"identity":"96b2df9f-c262-48bd-b91b-335ffe2fc6aa","order_by":0,"name":"Robert Richardson","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0003-2620-7387","institution":"Massachusetts General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Robert","middleName":"","lastName":"Richardson","suffix":""},{"id":613470410,"identity":"4641666b-a76f-4863-b5d4-fb9f4ac8ed37","order_by":1,"name":"Alan Bush","email":"","orcid":"","institution":"Harvard Medical School; Department of Neurosurgery, Massachusetts General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Alan","middleName":"","lastName":"Bush","suffix":""},{"id":613470411,"identity":"41885c65-c0ed-41dd-9e6b-caf19bd29be1","order_by":2,"name":"Yanming Zhu","email":"","orcid":"https://orcid.org/0000-0002-6862-8123","institution":"Massachusetts General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yanming","middleName":"","lastName":"Zhu","suffix":""},{"id":613470412,"identity":"318990d4-a68c-4994-9b08-1465d84a9f1c","order_by":3,"name":"Zack Lajoie","email":"","orcid":"","institution":"Massachusetts General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zack","middleName":"","lastName":"Lajoie","suffix":""},{"id":613470413,"identity":"1eb7cb81-bab0-4c67-93e6-1f9acb8d8bc8","order_by":4,"name":"Amir Hadanny","email":"","orcid":"","institution":"Massachusetts General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Amir","middleName":"","lastName":"Hadanny","suffix":""},{"id":613470414,"identity":"1c1ce85a-4457-4c89-a770-538c133e6ed2","order_by":5,"name":"Zachary Kons","email":"","orcid":"","institution":"Massachusetts General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zachary","middleName":"","lastName":"Kons","suffix":""},{"id":613470415,"identity":"7006c8a5-08aa-44be-a005-5790e92e05dd","order_by":6,"name":"Coralie Mignot","email":"","orcid":"","institution":"Technische Universität Dresden","correspondingAuthor":false,"prefix":"","firstName":"Coralie","middleName":"","lastName":"Mignot","suffix":""},{"id":613470416,"identity":"0074e1ea-f962-4d65-b810-8207dafdc951","order_by":7,"name":"Thomas Hummel","email":"","orcid":"","institution":"Technische Universität Dresden","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Hummel","suffix":""},{"id":613470417,"identity":"fb28dcf4-d292-4c9e-a6f1-30df6415692a","order_by":8,"name":"Luis Boero","email":"","orcid":"https://orcid.org/0000-0003-1758-616X","institution":"Harvard University","correspondingAuthor":false,"prefix":"","firstName":"Luis","middleName":"","lastName":"Boero","suffix":""},{"id":613470418,"identity":"835278bf-e43b-4f9c-8ea5-9933ba4f7b85","order_by":9,"name":"Venkatesh Murthy","email":"","orcid":"https://orcid.org/0000-0003-2443-4252","institution":"Harvard University","correspondingAuthor":false,"prefix":"","firstName":"Venkatesh","middleName":"","lastName":"Murthy","suffix":""},{"id":613470419,"identity":"4f0d4461-7187-40e3-80a6-7b8ff78ba31c","order_by":10,"name":"Daniel Coelho","email":"","orcid":"","institution":"Virginia Commonwealth University","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Coelho","suffix":""},{"id":613470420,"identity":"39d8de23-03d6-496a-a5e0-49af2a2bf513","order_by":11,"name":"Eric Holbrook","email":"","orcid":"https://orcid.org/0000-0002-7632-2204","institution":"Massachusetts Eye and Ear","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"","lastName":"Holbrook","suffix":""},{"id":613470421,"identity":"a2f47b1c-f869-45e1-af19-1ea443aa34c8","order_by":12,"name":"Richard Costanzo","email":"","orcid":"","institution":"Virginia Commonwealth University","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"","lastName":"Costanzo","suffix":""}],"badges":[],"createdAt":"2026-03-12 19:00:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9107770/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9107770/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106962142,"identity":"65100562-9d3e-4800-9f19-50cb6de73411","added_by":"auto","created_at":"2026-04-15 09:34:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":812642,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOnline inspiration prediction enables passive and precise delivery of odorants, which elicit gamma and beta responses in the human olfactory-related region\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e Illustration of experimental setup in the epilepsy monitoring unit, featuring a subject with implanted intracranial sEEG electrodes and our custom-built olfactometer with online respiration tracking. \u003cstrong\u003e(B)\u003c/strong\u003e Sample signals from an implanted electrode and respiration-tracking devices, as well as the predicted respiration state from our online model. When the model output is above a given threshold (red line), it predicts inspiration (gray shaded regions), and it predicts expiration otherwise (white periods). The bottom panel represents the number of odorant molecules detected at the nasal cannula output by a photoionization detector in an offline benchmarking experiment. \u003cstrong\u003e(C)\u003c/strong\u003e Trial-wise model performance of our inspiration detection algorithm. Horizontal black lines separate individual subjects. The timing of the detected inspiration onset (and subsequent valve opening) is shown for each trial, sorted vertically by the length of the corresponding inspiration (shaded gray region). The amount of odorants delivered within the inspiration window was estimated by integrating the time-resolved odorant dose (measured by a photoionization detector) between the start and end times of inspiration. \u003cstrong\u003e(D)\u003c/strong\u003e Localization of a representative olfactory-responsive electrode (red) within the amygdala. \u003cstrong\u003e(E) \u003c/strong\u003eSchematic of a typical trial, showing a sample respiration and odorant delivery curve (measured by a PID in a separate calibration run). \u003cstrong\u003e(F) \u003c/strong\u003eTrial-averaged time-frequency plots for PEA presentations, inspirations preceding PEA presentations, presentations of an odorless blank, and CO\u003csub\u003e2\u003c/sub\u003e presentations. Time-frequency analyses of stimulus presentations were time-locked to the opening of the valve. The preceding inspirations were time-locked to the same phase of the inspiration as the following PEA presentation. Colored boxes show time windows of significant deviations (p\u0026lt;0.05) via a cluster-based permutation test (CBPT) in the time domain for the theta, alpha, beta, and gamma frequency bands. All time-frequency plots are aligned to the moment of valve opening (stimulus delivery onset).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9107770/v1/1c821a6293e4f0f3ca8f2203.png"},{"id":106962156,"identity":"b11efe85-076b-4cd5-8012-7ae83cba0381","added_by":"auto","created_at":"2026-04-15 09:34:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":880007,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistinct signatures differentiate olfactory and trigeminal processing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e Representative electrodes illustrating the diversity of response profiles across stimulus conditions. Example contacts showing selective responses to PEA, selective responses to CO₂, and joint responses to both odorants are plotted with blank trials. \u003cstrong\u003e(B) \u003c/strong\u003eNumber of electrodes that were significantly responsive to PEA and CO\u003csub\u003e2\u003c/sub\u003e presentation in the beta, theta, and gamma bands, via a cluster-based permutation test (CBPT) over the time domain in each frequency band. \u003cstrong\u003e(C)\u003c/strong\u003e Mean evoked power change to PEA and CO₂ post-stimulus for the beta, gamma, and theta. Points are color-coded by stimulus selectivity based on CBPT: electrodes responsive only to PEA (red), only to CO₂ (blue), or to both stimuli (purple). \u003cstrong\u003e(D)\u003c/strong\u003e Whole-brain distribution of all electrodes sampled in our entirely passive olfactory presentation task, colored by their responsiveness to PEA and CO\u003csub\u003e2\u003c/sub\u003e presentation (CBPT, p\u0026lt;0.05). \u003cstrong\u003e(E)\u003c/strong\u003e Spatial distribution of PEA and CO\u003csub\u003e2\u003c/sub\u003e responsive electrodes in the gamma bands in the amygdala, piriform cortex, and insula. Anatomical region titles are marked with an asterisk if they have a significantly greater proportion of responsive electrodes to both stimuli (purple) than either PEA (red) or CO2 (blue) via a Chi-squared test (p\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9107770/v1/c95695084d5d1472c221bcdc.png"},{"id":106962141,"identity":"03c056fc-0790-4d18-a2db-f4879eda6aeb","added_by":"auto","created_at":"2026-04-15 09:34:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":546974,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistinct gamma components reflect primary olfactory encoding and perceptual report.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A) \u003c/strong\u003eSingle-trial gamma traces of representative valve-locked and report-locked electrodes, separated by odor detection and sorted by button response latency. The onset and offset of gamma increases are identified using thresholding. \u003cstrong\u003e(B)\u003c/strong\u003e Schematic illustrating the thresholding algorithm used for gamma onset/offset determination. Upper orange right arrow indicates the button press latency, lower orange right arrow indicates the gamma response latency, and the grey left arrow indicates the gamma-to-button press latency. \u003cstrong\u003e(C)\u003c/strong\u003e To classify electrodes, the time between valve opening and gamma onset (orange) and the time between gamma onset and button press (black) are correlated with the time between valve opening and button press (red, button response latency). \u003cstrong\u003e(D) \u003c/strong\u003eSummary of the correlations and classification of all electrodes that had a significant increase in gamma power in the dose-response experiment. The exemplary electrodes from the prior subfigures are labeled. \u003cstrong\u003e(E)\u003c/strong\u003e Anatomical distribution of report-locked electrode response types across sampled brain regions. Boxes summarize the median and interquartile range for each category within each region.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9107770/v1/be4ff07c5adf3916dc729477.png"},{"id":106964814,"identity":"0f952055-89e5-419e-bfd0-989f7e087ff1","added_by":"auto","created_at":"2026-04-15 09:51:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":747734,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eElectrodes encoding olfactory intensity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A) \u003c/strong\u003eTo estimate single-trial odor intensity, we integrated the odorant delivery curve (measured offline by a photoionization detector) from the manually-marked inspiration start to the end time of each trial. \u003cstrong\u003e(B)\u003c/strong\u003e Behavioral detection performance during the dose–response task. For each subject, the probability of reporting odor detection is plotted as a function of PEA dose. \u003cstrong\u003e(C) \u003c/strong\u003eProbability of pressing the button as a function of the intensity of the presented odor for each subject. \u003cstrong\u003e(D)\u003c/strong\u003e Trial-averaged time-frequency plots for a representative dose-response electrode, separated by odorant pulse length (a direct correlate to odor intensity). The highlighted box (0.5-2.5 s, 30-200 Hz) was used as a window to average the gamma response over for a scalar estimate of the single-trial gamma response. \u003cstrong\u003e(E) \u003c/strong\u003eDose-amplitude curve of the representative electrode as shown in Fig. 3A.\u003cstrong\u003e (F) \u003c/strong\u003eFor each electrode, we separated trials in which the subject reported perceiving an odor from those in which they did not. For each group of trials, we fit a linear regression model to the single-trial gamma power and the computed odorant dose within the inspiration window. Electrodes were grouped based on the significance of the slope and y-intercept of this model being greater than zero (p\u0026lt;0.05). Trial data and regression models for representative electrodes of each group are shown.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9107770/v1/137bcc492e85ff97679d4899.png"},{"id":106967451,"identity":"de837e9a-a333-4cae-9e97-68051b4b9286","added_by":"auto","created_at":"2026-04-15 10:04:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3603354,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9107770/v1/ea35a746-4ab8-4d1b-8f2c-73613847d9aa.pdf"},{"id":106962109,"identity":"5373c3d0-833d-4ba2-8d49-0a048f166923","added_by":"auto","created_at":"2026-04-15 09:33:51","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":13197,"visible":true,"origin":"","legend":"Table 1","description":"","filename":"table1smelltest.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9107770/v1/bd2adea8ca4b810bceb99b40.xlsx"},{"id":106963475,"identity":"a3a6a631-d322-4b11-8ad2-e7980ed01009","added_by":"auto","created_at":"2026-04-15 09:44:42","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":49163,"visible":true,"origin":"","legend":"Table 2","description":"","filename":"table2passivegrouplevel.docx","url":"https://assets-eu.researchsquare.com/files/rs-9107770/v1/63235541f7a9973b64a3f6b7.docx"},{"id":106963224,"identity":"80d66a09-40ed-4bde-a2cc-044b0e107f0e","added_by":"auto","created_at":"2026-04-15 09:43:07","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":38522,"visible":true,"origin":"","legend":"Table 3","description":"","filename":"table3doseresponse.docx","url":"https://assets-eu.researchsquare.com/files/rs-9107770/v1/97f4342ff074d8f40d69f3cc.docx"},{"id":106962159,"identity":"5177b40a-e75c-4d70-9714-3232ba7951a8","added_by":"auto","created_at":"2026-04-15 09:34:51","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":9625,"visible":true,"origin":"","legend":"Table 4","description":"","filename":"table4subjectdemographics.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9107770/v1/fb8e130aea5c66341709353e.xlsx"},{"id":106963377,"identity":"018cbd9b-fee4-437e-94e0-266827129070","added_by":"auto","created_at":"2026-04-15 09:44:03","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":37415333,"visible":true,"origin":"","legend":"Manuscript supplementary material","description":"","filename":"Gammatemporaldissociation12Mar2026Suppl.docx","url":"https://assets-eu.researchsquare.com/files/rs-9107770/v1/ed8c77bc9d3d95be28e61cec.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Gamma activity temporally dissociates sensory encoding from perceptual decision-making in human olfactory circuits","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDespite the well-established associations of olfaction with emotion and memory, and its broader importance in hazard detection, social communication, and quality of life, the neural dynamics of human olfactory processing remain incompletely understood. This knowledge gap has significant clinical implications: an estimated 22% of the general population lives with smell disorders, a prevalence likely increased by the COVID-19 pandemic \u003csup\u003e1\u003c/sup\u003e. Olfactory dysfunction significantly impairs quality of life\u0026nbsp;\u003csup\u003e2-4\u003c/sup\u003e, yet remains underappreciated relative to other sensory impairments. Translating insights from animal models to human olfactory physiology is challenging, as the ethological role, behavioral relevance, and cortical integration of olfaction differ substantially across species. Consequently, there is no coherent understanding of how human olfactory structures encode stimulus identity, intensity, and perceptual detection\u0026nbsp;\u003csup\u003e5,6\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn rodents, olfactory-induced brain activity has been extensively studied using electrophysiological methods, revealing important roles for single-unit firing and oscillatory dynamics in the olfactory bulb and cortex \u003csup\u003e7-11\u003c/sup\u003e. Prior work has implicated gamma involvement in odor identification \u003csup\u003e12-14\u003c/sup\u003e, theta coupling to respiration, and beta involvement in feedback interactions \u003csup\u003e12,15,16\u003c/sup\u003e. The contributions of these rhythms across human chemosensory pathways, however, have not been systematically compared.\u003c/p\u003e\n\u003cp\u003eMost human olfactory research has relied on noninvasive techniques such as functional magnetic resonance imaging, electroencephalography, and magnetoencephalography. While these approaches have provided important insights into large-scale network organization, they lack the spatial and temporal resolution necessary to study central olfactory circuits in detail. Stereotactic electroencephalography (SEEG), a diagnostic epilepsy surgery that provides local field potentials (LFP) along depth electrodes implanted throughout the brain, offers a unique opportunity to bridge this gap. Despite this potential, only a limited number of studies have examined human olfactory processing using intracranial recordings, reporting odor-evoked activity that reflects perception, memory, and behavioral relevance \u003csup\u003e12,13,15-26\u003c/sup\u003e. Access to millimeter-scale, time-resolved signals enables testing two outstanding questions about human chemosensory processing.\u003c/p\u003e\n\u003cp\u003eFirst, how do olfactory and trigeminal pathways interact at the circuit level? Most odorants engage both systems, yet the neural mechanisms by which their signals converge or remain segregated in the human brain remain largely uncharacterized \u003csup\u003e27,28\u003c/sup\u003e. The two pathways overlap anatomically in the nasal epithelium and multiple brain structures \u003csup\u003e29,30\u003c/sup\u003e, and olfactory dysfunction has been associated with reduced trigeminal responsiveness \u003csup\u003e31,32\u003c/sup\u003e; however, pure trigeminal processing and its interaction with olfactory circuits have received minimal investigation.\u003c/p\u003e\n\u003cp\u003eSecond, how are chemosensory representations transformed into perceptual decisions? In other sensory systems, perceptual report can diverge from early sensory encoding, and decision formation has been formalized within signal-detection and evidence-accumulation frameworks that distinguish continuous sensory evidence from categorical perceptual reports \u003csup\u003e33-36\u003c/sup\u003e. Whether similar computational principles govern human olfaction - and whether early sensory encoding can be dissociated from later decision-related activity within olfactory circuits - remains largely unexplored.\u003c/p\u003e\n\u003cp\u003eHere, we address these gaps by combining SEEG with passive, inspiration-locked olfactometry that delivers odorized air without requiring sniffing, motor actions, or attentional cues. This approach isolates stimulus-evoked neural activity from respiration dynamics, enabling a clean dissociation of sensory, perceptual, and motor contributions to chemosensory processing. Across 19 participants, we analyzed LFP responses to phenyl ethyl alcohol (PEA), a pure olfactory stimulus, and CO₂, a selective trigeminal stimulus \u003csup\u003e37,38\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePassive Olfactory and Trigeminal Stimulation Elicits Artifact-Free Responses.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo minimize task-related motion artifacts and isolate chemosensory neural circuitry, we developed a passive experimental paradigm for presenting olfactory stimuli (Figs. 1A and S2-3).\u0026nbsp;Participants were patients with refractory epilepsy undergoing intracranial monitoring with SEEG depth electrodes for clinical purposes (Figs. S4). All participants underwent standardized olfactory screening with the Brief Smell Identification Test, which confirmed adequate odor identification before data collection (Table S1 and Fig. S5). A custom-built olfactometer delivered humidified air via a nasal cannula. Upon detecting inspiration onset, the system rapidly infused the airflow with odorized air from one of three reservoirs (PEA, CO₂, or odorless air) during natural inspiration (Figs. S6-7). We monitored respiration using a chest belt (Fig. S8) and a thermistor (Fig. S9) at the nasal opening, then trained a linear model for each participant to predict the onset of inspiration (Fig. S10). When the model output exceeded a predefined threshold, the olfactometer infused concentrated odorants into the airflow for a brief period (Fig. 1B). Participants wore noise-canceling headphones to mask acoustic noise generated by the olfactometer solenoid valves, minimizing attentional and auditory confounds.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOffline photoionization detector (PID) calibration at the nasal cannula verified reliable, consistent odor delivery with ~250 ms latency and ~250 ms rise time to peak concentration after valve opening (Fig. 1B, bottom; Fig. S11), supporting use of a 250-ms pulse that was readily detected by normosmic subjects. Successful inspiratory delivery was achieved in 72% of trials overall (range 35–93% across participants, Figs. 1C and S12), with no requirement for active sniffing or task-related attention.\u003c/p\u003e\n\u003cp\u003eA representative olfactory-responsive electrode localized to the amygdala (Fig. 1D) exhibited a transient increase in beta and gamma power immediately following stimulus onset, but we needed to determine whether this activity reflected genuine chemosensory processing. To disentangle odor-specific effects from respiration-related activity, we compared odor trials with two control conditions (Figs. 1E and S13): inspirations immediately preceding stimulus presentation and presentations of odorless air. Pre-stimulus inspirations evoked no significant deviation from baseline power (Fig. 1F, top right panel). Odorless air produced a weaker, temporally diffuse enhancement of theta-alpha power (Fig. 1F, bottom-left panel), likely due to mechanical effects or residual acoustic noise from valve switching that the noise-canceling headphones may not have fully masked, similar to observations from rodent studies \u003csup\u003e39,40\u003c/sup\u003e. In contrast, PEA (Fig. 1F, top-left panel) and CO\u003csub\u003e2\u003c/sub\u003e (Fig. 1F, bottom-right panel) evoked robust, time-locked increases in beta and gamma bands (Fig. S14, trial-by-trial activity in theta, beta, and gamma bands), with peak activity centered 0.5-2 s after valve opening, demonstrating that these responses reflect genuine chemosensory processing rather than respiratory or mechanical artifacts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eOlfactory and Trigeminal Stimuli Elicit Dissociable Neural Signatures at\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSingle-Electrode Resolution\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe compared responses to PEA, a pure olfactory stimulus, and CO₂, a selective trigeminal stimulus \u003csup\u003e37,38\u003c/sup\u003e, to determine whether these stimuli elicit functionally dissociable patterns across chemosensory pathways during the complete passive experiment. For each electrode, power changes were quantified from -0.5 to 1.5 s around stimulus onset. Fig. 2A shows representative electrodes that exhibited significant (one-way ANOVA corrected with the number of trials) encoding of either PEA alone (red, top row), CO₂ alone (blue, middle row), or both stimuli (lower row) when compared to odorless air (gray).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe then examined the patterns that emerged across frequency bands. Using a cluster-based permutation test (CBPT), we quantified the number of electrodes that were significantly responsive to each stimulus across frequency bands (Figs. 2B, S15, and Table S2). For electrodes encoding for both PEA and CO\u003csub\u003e2\u003c/sub\u003e, the majority were in the gamma band (30-200 Hz). Among electrodes responsive to both PEA and CO\u003csub\u003e2\u003c/sub\u003e, more were significant in the theta and beta bands (\u0026gamma; vs \u0026beta;: Z = 7.24, p = 4.5 \u0026times; 10⁻\u0026sup1;\u0026sup3;; \u0026gamma; vs \u0026theta;: Z = 6.51, p = 7.3 \u0026times; 10⁻\u0026sup1;\u0026sup1;; \u0026beta; vs \u0026theta;: Z = 0.49, p = 0.624). We also observed band-specific differences in activities selective for PEA (\u0026gamma; vs \u0026beta;: Z = -2.45, p = 0.014; \u0026gamma; vs \u0026theta;: Z = 1.36, p = 0.175; \u0026beta; vs \u0026theta;: Z = 3.79, p = 1.49 \u0026times; 10⁻\u003csup\u003e4\u003c/sup\u003e), but not CO\u003csub\u003e2\u003c/sub\u003e (\u0026gamma; vs \u0026beta;: Z = -0.76, p = 0.448; \u0026gamma; vs \u0026theta;: Z = 0.33, p = 0.743; \u0026beta; vs \u0026theta;: Z = 1.09, p = 0.277). To further characterize these distinctions, we plotted each electrode\u0026rsquo;s median evoked power change to PEA against its response to CO₂ (Fig. 2C), categorized by stimulus selectivity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo test whether the spatial distribution of odorant-selective versus trigeminal-selective activity is anatomically organized, we plotted all significant contacts in MNI space (Montreal Neurological Institute, MNI152, and wrapped with HCP-MMP1 atlas) and labeled each by response class (PEA-only, CO₂-only, PEA\u0026cap;CO₂). We mapped all electrodes showing significant power increases to PEA and CO₂ during the passive presentation task using a CBPT (Fig. 2D). Responsive electrodes were distributed bilaterally but concentrated within canonical chemosensory regions, including the amygdala, piriform cortex, and insula.\u003c/p\u003e\n\u003cp\u003eWhen responses were stratified by frequency band, theta, beta, and gamma activity were substantially intermixed within each region, and no clear spatial organization was apparent (Figs. 2E, and S16). To quantify whether gamma-band convergence of olfactory and trigeminal responses was region-specific, we compared the observed number of jointly responsive electrodes to that expected by chance using \u0026chi;\u0026sup2; tests across brain regions. The amygdala, piriform cortex, and insula each exhibited a significant over-representation of joint (PEA\u0026cap;CO₂) responsive electrodes, far exceeding chance levels when corrected for the number of contacts (amygdala: \u0026chi;\u0026sup2; = 58.49, p = 2.0\u0026times;10⁻\u0026sup1;⁴; piriform: \u0026chi;\u0026sup2; = 34.17, p = 5.05\u0026times;10⁻⁹; insula: \u0026chi;\u0026sup2; = 11.57, p = 6.7\u0026times;10⁻⁴). Additionally, gamma activity accounted for the majority of PEA\u0026cap;CO₂ electrodes. In contrast, beta and theta contained relatively few PEA\u0026cap;CO₂ contacts but a larger share of stimulus-selective (PEA or CO₂) electrodes. Within the hippocampus, all significant contacts were stimulus-selective (Figs. 2E and S17).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStimulus-Locked and Report-Locked Gamma Activity Reveal Separable\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStages of Olfactory Processing\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo determine whether gamma activity reflects primary olfactory encoding or higher-order processes (perceptual decision-making or motor preparation), we conducted a perceptual detection task in which participants pressed a button to report odor detection. We analyzed the temporal relationships among gamma activity, stimulus presentation, and behavioral response across electrodes. Here, although the participants were reporting their perceptions, their inspiration phase remains completely passive and locked to their natural inhalation.\u003c/p\u003e\n\u003cp\u003eTwo representative electrodes illustrate these distinct temporal profiles (Fig. 3A): one electrode showed gamma activity aligned to the onset of odor delivery (left, stimulus-locked, suggesting a sensory rather than motor or cognitive origin), and another showed gamma activity that preceded the button press (right, motor-locked). Critically, this stimulus-locked gamma activity was also present on trials in which participants failed to report odor detection (\u0026ldquo;missed\u0026rdquo; trials; Fig. 3A, green box). Despite the absence of an overt perceptual report, gamma onset remained tightly time-locked to odor presentation, indicating that neural processing of the odor stimulus occurred independently of conscious detection or behavioral reporting.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo determine whether gamma-band activity was temporally associated with sensory input or behavioral report, we employed an interval-based timing analysis \u003csup\u003e41\u003c/sup\u003e. Specifically, for each trial, we quantified two complementary time intervals: (1) the latency from odor valve opening to gamma onset, indexing alignment to stimulus presentation, and (2) the latency from gamma onset to button-press response, indexing alignment to behavioral report (Fig. 3B). An electrode whose gamma onset is fixed relative to the valve opening will show no correlation between valve-to-gamma latency and total button-press latency, since the gamma timing is independent of how long the participant took to respond.\u003c/p\u003e\n\u003cp\u003eWe used a regression-based method to quantify the two electrode groups. An odor-locked electrode is operationally defined by the absence of correlation between valve-opening-to-gamma-onset latency and total button-press latency (Fig. 3C, left), while the button-press locked electrode is defined as no correlation between gamma modulation onset to button press with button-press latency (Fig. 3C, right). We applied this regression-based method to all electrodes (Fig. 3D). These findings demonstrate that human olfactory processing can be partitioned into an early component reflecting sensory olfactory encoding and a later component associated with perceptual decision-making and response-related processes underlying conscious detection, on the scale of milliseconds.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe next asked whether stimulus-locked and report-locked activities were preferentially localized to distinct anatomical structures. We examined the distribution of response classifications across all sampled regions (Fig. 3E). Report-locked electrodes were located in the amygdala, insula, hippocampus, and orbitofrontal cortex (OFC). Amygdala electrodes tended to show gamma activity emerging earliest relative to the button press, whereas insular and hippocampal electrodes exhibited gamma onset closer to the behavioral response. OFC responses were largely time-locked to the button press, suggesting a direct role in late-stage decision commitment or motor execution, and the presence of a decision-related hierarchy within the olfactory circuit.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNeural Responses Encode Odor Intensity Through Both Graded and\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eThreshold-Based Mechanisms\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHaving established that gamma activity comprises distinct stimulus-locked and report-locked components, we next asked whether these components also reflect the graded physical properties of the stimulus itself, specifically, whether olfactory regions encode odor intensity, perceptual detection, or both. We conducted a dose-response experiment in which participants received inspiration-locked PEA pulses at varying intensities. By varying the duration of solenoid valve opening, we modulated odorant intensity, as continuous airflow ensured that the inhaled odor dose scaled with valve open time (Figs. 4A and S18). In our hardware design, the latency for odorants to reach the nose was consistent (~0.5s; Fig. S18C) and did not depend on pulse duration. For this task, participants passively inhaled during each trial and pressed a button to report detection of an odor (Figs. 4B and S19). Across participants, the probability of detection increased monotonically with odorant dose (Figs. 4C and S20). Two representative electrodes showed distinct response profiles: one exhibited a monotonic increase in gamma power with increasing odor dosage, while the other showed a switch-like increase (Fig. 4D) with a dose-response relationship (Fig. 4E).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor each electrode, we fitted a linear regression model relating trial-by-trial gamma activity to computed odorant dose, separately for detected and undetected trials. Electrodes were classified based on model parameters: those with a significant positive slope (graded response), those with a significant positive intercept (switch-like response), and those with no significant relationship (Figs. 4F, S21-22, and Table S3). These findings reveal two distinct neural components in the human olfactory cortex: a graded component that continuously encodes intensity and a switch-like component associated with perceptual awareness.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eHuman olfactory circuits implement hierarchical computations that dissociate primary sensory encoding from perceptual decision-making, a computational organization previously characterized in vision and touch but not established in olfaction. Combining millimeter-scale intracranial recordings with passive olfactory stimulation, we demonstrate three key principles of this organization. First, olfactory and trigeminal information converges in gamma frequencies within the amygdala and piriform cortex while remaining segregated in the hippocampus, demonstrating hierarchical processing. Second, stimulus-locked gamma persists even without conscious detection, whereas report-locked gamma emerges hierarchically across limbic structures during perceptual decisions. Third, neural responses exhibit both graded intensity encoding and categorical threshold dynamics, paralleling signal detection frameworks in other sensory modalities \u003csup\u003e42,43\u003c/sup\u003e. These findings establish that human olfaction follows computational principles previously characterized only in vision and touch networks, with distinct mechanisms supporting sensory representation and perceptual awareness.\u003c/p\u003e\n\u003cp\u003ePrior neuroimaging studies provide complementary evidence for this functional dissociation between the olfactory and trigeminal pathways. fMRI studies have shown that both odorant and trigeminal stimuli activate the ventral insular cortex, a known multisensory hub. However, trigeminal stimulation also recruits a broader network that includes the midbrain, superior temporal gyrus, anterior caudate nucleus, and dorsolateral orbitofrontal cortex, with responses typically more prominent in the right hemisphere \u003csup\u003e44\u003c/sup\u003e. Here, we showed that olfactory and trigeminal signals can be functionally dissociated at the single-electrode level, despite overlapping anatomical substrates. Theta- and beta-band responses largely segregated the two pathways, whereas gamma-band activity exhibited substantial convergence across piriform cortex, amygdala, and insula. This convergence was notably absent in the hippocampus, which maintained parallel, stimulus-selective representations. These findings argue against a purely anatomical model of chemosensory integration and instead support a frequency-based organizational principle, whereby the same anatomical region can support segregated or convergent processing depending on the oscillatory frequency engaged. In this framework, theta- and beta-band rhythms preferentially support modality-specific feedforward and feedback interactions, whereas gamma activity supports shared integrative processing across chemosensory inputs.\u003c/p\u003e\n\u003cp\u003ePassive inspiration-locked delivery minimized motor artifacts and controlled for the confounding influence of respiration-entrained neural activity. Respiration has long been recognized as an intrinsic organizer of neural activity in the olfactory system, synchronizing oscillations in the olfactory bulb and cortex to optimize temporal sampling of incoming odors \u003csup\u003e45,46\u003c/sup\u003e. Aligning stimulus delivery with inspiration enabled us to isolate stimulus-evoked activities from those driven purely by breathing dynamics. This methodological advance strengthens the interpretation that the observed rhythmic activity reflects sensory and cognitive processing rather than respiratory entrainment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA previous study reported increased theta, beta, and gamma rhythms in the piriform cortex during an active odor-detection task\u003csup\u003e12\u003c/sup\u003e, but could not demonstrate a direct association between gamma activity and odor presence, in part because participants were cued to sniff at a specific time point \u003csup\u003e47\u003c/sup\u003e, a design that conflates sensory, motor, and attentional contributions to the neural response. Our fully passive paradigm eliminates this confound by delivering odorized air during natural inspiration without sniffing cues, attention, or motor preparation. Critically, this design enabled us to examine trials in which odor was delivered but went undetected, revealing that stimulus-locked gamma activity persists in the absence of conscious report, a dissociation that is inaccessible in paradigms requiring overt behavioral engagement with each stimulus.\u003c/p\u003e\n\u003cp\u003eThe piriform cortex and the amygdala are both parts of the primary olfactory cortex, and both receive projections from the olfactory bulb \u003csup\u003e15,26,48\u003c/sup\u003e. They are anatomically adjacent; for example, the periamygdaloid cortex is situated at the interface between the two structures and shares connections with the piriform cortex \u003csup\u003e49\u003c/sup\u003e. Although it can be assumed that their activity patterns are similar, the amygdala is a complex of multiple nuclei, and the piriform cortex is divided into anterior and posterior parts, each involved differently in olfactory processing \u003csup\u003e26,50\u003c/sup\u003e. Moreover, it appears that the amygdala maintains a distinct organization of olfactory bulb projections, whereas the piriform cortex does not \u003csup\u003e51\u003c/sup\u003e. Thus, they might be subject to differential influences, such as odorant characteristics (chemical or psychophysical) or the cognitive demands of the task \u003csup\u003e51\u003c/sup\u003e, a framework supported by our data, which show that the piriform cortex and amygdala share gamma-band convergence, whereas the hippocampus does not, instead exhibiting parallel representations of odorant and trigeminal inputs. Thus, the variability observed in prior studies may reflect subregional functional specialization, as revealed more clearly in our large-scale SEEG dataset.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA key finding of this study is that gamma activity in human olfactory regions is not monolithic but instead comprises at least two temporally and functionally distinct components. Stimulus-locked gamma responses likely reflect early sensory encoding of chemosensory input, consistent with prior work implicating gamma oscillations in odor identity and intensity coding. In contrast, report-locked gamma responses appear to index later-stage processes related to perceptual decision-making and response preparation. The presence of these decision-related gamma activity within olfactory regions has not been previously reported in human intracranial studies. This finding suggests that the olfactory cortex participates not only in sensory representation but also in downstream computations that culminate in conscious detection.\u003c/p\u003e\n\u003cp\u003eCritically, stimulus-locked gamma activity was also observed on trials in which participants failed to report odor detection. On these “missed” trials, gamma onset remained time-locked to odor delivery despite the absence of an overt perceptual report or behavioral response, indicating that this activity reflects primary olfactory processing driven directly by sensory input. Such dissociation between neural sensory encoding and perceptual report aligns with models in which olfactory information is processed at early cortical and limbic stages, even when it fails to reach awareness. Stimulus-locked gamma therefore may reflect a hierarchical functional distinction between a pre-decisional sensory component and later decision-related gamma activity.\u003c/p\u003e\n\u003cp\u003eAlthough decision-locked gamma responses were observed across multiple regions, their timing relative to behavioral report varied systematically across structures. Amygdala locations tended to exhibit gamma onset earlier relative to the button press, whereas insular and hippocampal locations exhibited gamma activity closer to the behavioral response, and the orbitofrontal cortex was largely time-aligned with reporting. These findings suggest a process hierarchy in olfactory-limbic circuits, with earlier structures (amygdala) involved in evidence accumulation and later structures (OFC) involved in response execution.\u003c/p\u003e\n\u003cp\u003eThe presence of report-locked, switch-like gamma responses suggests that human olfactory perception can be interpreted within a signal detection theory framework. Early stimulus-locked gamma activity reflects the accumulation of sensory evidence, which varies continuously with stimulus intensity and is present even on trials lacking perceptual report. In contrast, switch-like and report-locked gamma activities are associated with decision-criterion crossing and motor preparation. Such a dissociation between sensory evidence and decision-related signals has been extensively described in visual and somatosensory systems but has not previously been demonstrated within human olfactory regions \u003csup\u003e52,53\u003c/sup\u003e. Together, these results establish signal-detection-like computation as a conserved organizational principle across sensory modalities, extending frameworks developed in vision and touch to the chemical senses. Beyond their basic science implications, these findings carry translational relevance: the dissociation between stimulus-locked and report-locked gamma provides candidate biomarkers for objective assessment of olfactory function in patients with smell disorders, a population affecting an estimated 22% of the general public and disproportionately impacted by COVID-19. More broadly, the identification of distinct gamma signatures for sensory encoding versus perceptual decision-making opens a path toward closed-loop neurostimulation strategies that could selectively augment deficient processing stages in olfactory dysfunction.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDesiato, V. M.\u003cem\u003e et al.\u003c/em\u003e The Prevalence of Olfactory Dysfunction in the General Population: A Systematic Review and Meta-analysis. \u003cem\u003eAm J Rhinol Allergy\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 195-205, doi:10.1177/1945892420946254 (2021).\u003c/li\u003e\n\u003cli\u003eHummel, T. \u0026amp; Nordin, S. Olfactory disorders and their consequences for quality of life. \u003cem\u003eActa Otolaryngol\u003c/em\u003e \u003cstrong\u003e125\u003c/strong\u003e, 116-121, doi:10.1080/00016480410022787 (2005).\u003c/li\u003e\n\u003cli\u003eBochicchio, V., Mezzalira, S., Maldonato, N. 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We combined stereotactic electroencephalography (SEEG) with a passive, inspiration-triggered olfactometer that delivers odorized air without voluntary sniffing, attentional cuing, or motor engagement, enabling clean separation of sensory, perceptual, and motor contributions to chemosensory processing. Across 19 participants (two subjects had two study sessions), we identified two temporally and functionally distinct gamma-band components within human olfactory circuits. An early, stimulus-locked gamma response reflects primary olfactory encoding: it persists on trials in which participants fail to report odor detection, demonstrating that sensory processing proceeds independently of conscious awareness. A later gamma component is time-locked to behavioral report and emerges hierarchically across limbic structures, reflecting perceptual decision-making and response preparation. Gamma responses also encode odor intensity through two dissociable mechanisms: graded, dose-dependent modulation and switch-like, report-dependent dynamics, consistent with a signal-detection framework for perceptual threshold. These findings establish that gamma activity dissociates primary sensory encoding from higher-order perceptual decisions in human olfactory circuits, demonstrating that the computational principles governing sensory awareness in vision and touch extend to human olfaction.","manuscriptTitle":"Gamma activity temporally dissociates sensory encoding from perceptual decision-making in human olfactory circuits","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-14 10:37:16","doi":"10.21203/rs.3.rs-9107770/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6d31fa5a-51b0-4bd4-a4c1-16f218bec1c1","owner":[],"postedDate":"April 14th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":65283340,"name":"Biological sciences/Neuroscience/Olfactory system/Olfactory cortex"},{"id":65283341,"name":"Biological sciences/Physiology/Neurophysiology"},{"id":65283342,"name":"Biological sciences/Psychology/Human behaviour"}],"tags":[],"updatedAt":"2026-04-14T10:37:16+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-14 10:37:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9107770","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9107770","identity":"rs-9107770","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}