Biology subjects

Lundqvist, M.

Publications and source records attributed to Lundqvist, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Recurrent beta-gamma interactions between olfactory bulb and piriform cortex support cross-sniff perceptual continuity in humans

Olfactory perception relies on active sampling, with successive inhalations providing discrete sensory inputs that in humans can be separated by several seconds. Yet odors are perceived as continuous and stable, raising the question of how the brain integrates sensory information across these temporal gaps. Here, we used electrobulbogram (EBG) recordings in 48 participants to demonstrate that successive sniffs are not processed independently but are linked through recurrent oscillatory dynamics between the olfactory bulb (OB) and piriform cortex (PC). Specifically, first-sniff alpha/beta activity in the OB and OB-PC functional connectivity predicted second-sniff gamma power, while transfer entropy indicated a directional temporal dependence from first-sniff alpha/beta to second-sniff gamma dynamics. In parallel, second-sniff gamma activity selectively tracked subjective odor valence prior to inhalation onset. At the network level, the PC exhibited stronger alpha/beta-band connectivity with orbitofrontal, insular, and prefrontal regions during the first sniff than during the second, suggesting that early evaluative processing provides a contextual signal that is carried forward to shape subsequent sensory representations. These results demonstrate that the human OB-PC circuit carries evaluative information across inhalations through directed alpha/beta-to-gamma interactions, providing a mechanism for maintaining perceptual continuity in a sensory system defined by temporally discrete sampling.

neuroscience↗

bioRxiv2026

Low-dimensional prefrontal representations of objects during working memory

There is an ongoing debate regarding the dimensionality of neural representations. Some accounts emphasize representation within low-dimensional subspaces or manifolds, while others suggest high-dimensional neural codes where neurons respond independently. Here, we investigate the dimensionality of prefrontal cortex (PFC) representations of visual objects held in working memory. We found that object representations are low-dimensional, occupying only 3-6 effective dimensions during both encoding and maintenance in working memory. Control analyses indicate this dimensionality was not limited by the number of objects tested (40) or neurons sampled ([~]100). We also compared PFC dimensionality to that of a well-established deep neural network model of its inferotemporal (IT) inputs and found an approximately 7-fold dimensionality reduction in PFC. These results suggest object representations are compressed into a low-dimensional manifold in PFC, which might be related to attractor dynamics for working memory, and might facilitate interaction with other variables and cognitive control. Author summaryCompeting accounts of cortical neural coding propose that neurons either activate in structured, coordinated patterns like schools of fish, or that they activate independently, like hunting sharks. A key metric discriminating these schemes is their effective dimensionality -- the number of independent activity patterns needed to characterize information conveyed in a neural population. To test this, we measured the dimensionality of primate prefrontal cortex during working memory for objects, a domain where the inputs are intrinsically complex and high-dimensional. We found that prefrontal dimensionality was surprisingly low, spanning only a handful of dimensions. Using convolutional neural network models of its visual cortex inputs, we found evidence for a substantial prefrontal compression of dimensionality. We hypothesize that this reformatting of high-dimensional sensory information into a compact code can facilitate flexible combination with information from other domains, as proposed by "mixed selectivity" theories of prefrontal coding.

neuroscience↗

bioRxiv2026

Capturing Spatially Organized Oscillatory Cliques as Signatures of Neuronal Assemblies

State-of-the-art neural recording technologies now enable dense sampling of neuronal activity, demonstrating meaningful spiking variability from moment to moment. Yet spiking activity is sparse by nature and allows only partial access to collective neuronal dynamics. Local field potentials (LFPs) provide complementary information by capturing coordinated activity from large neuronal populations, but methods to characterize the fine-scale spatio-temporal organization of LFPs are lacking. Starting from the notion that neural oscillations are brief and burst-like, we introduce a framework to detect and analyze SPatially Organized Oscillatory Cliques (SPOOCs), oscillatory events that are cohesive in space, time, and frequency. SPOOCs displayed diverse dynamics in space and frequency and were differentially modulated during stimulus processing. Linking SPOOCs to local spiking, we demonstrate that these events index rapid reconfigurations of neuronal assemblies. With SPOOChunter, we provide an open-source toolbox that enables systematic detection and analysis of transient, spatially organized population dynamics in high-density electrophysiological recordings.

neuroscience↗

bioRxiv2026

Emergent Traveling Waves in Neural Circuits

Artificial neural networks achieve striking performance but do not capture a prominent neural property. Cortical activity is organized by structured spatiotemporal dynamics, traveling waves (TW), which have been implicated in a wide range of functions. Existing computational models often rely on hand-crafted connectivity and imposed dynamics, offering insight into their impact but less into how the waves naturally emerge in biological circuits. Here, we found that TWs emerge in models under biologically plausible constraints (spatially organized, directionally biased connectivity). Under an empirical neural manifold constraint, these wiring principles naturally emerge to support traveling wave dynamics in the recurrent model. We further show that wave propagation provides a robust mechanism for maintaining working memory in the presence of visual distractors. We compared these model predictions to non-human primate prefrontal cortex recordings, revealing a similar mechanism. Together, these results advance our understanding of traveling waves as a substrate for cognition and offer a framework for mechanistic accounts of cortical computation.

neuroscience↗

bioRxiv2025

Neurodynamics of prefrontal areas in volitional contexts: a comparative study based on computational modelling and EEG/ERP data

Volitional action arises from the interaction between internal intentions and external stimuli, yet the neural dynamics distinguishing self-initiated from externally triggered actions remain unclear. Here, we combine human EEG/ERP data with simulations from a phenomenological neurocomputational model of prefrontal control to examine the neurodynamic principles underlying different types of volitional behaviors. Using an extended version of our previously developed model, we generated neural activity patterns corresponding to self-initiated and externally triggered actions by manipulating the balance between endogenous and exogenous inputs to lateral prefrontal subregions. We then qualitatively compared these simulated dynamics with empirical EEG data from a perceptual decision-making task involving voluntary and instructed skip actions. Across both datasets, self-initiated actions showed a gradual buildup of activity, marked reductions in cross-trial variability, sharper state transitions, and beta-gamma frequency shifts; in contrast, externally triggered actions exhibited minimal variability reduction, weaker transitions, and largely stable frequency content. These convergent results suggest that self-initiated actions are supported by distinct preparatory dynamics, characterized by internal competition and stabilization of neural states, whereas externally triggered actions rely primarily on externally driven input. Together, these findings identify candidate neurodynamic signatures of intention formation and highlight how simplified computational models can reproduce and help explain key features of volitional control observed in human electrophysiology.

neuroscience↗

bioRxiv2025

Methodological determinants of signal quality in electrobulbogram recordings

The electrobulbogram (EBG) is a new, non-invasive method for measuring the functional activity of the human olfactory bulb (OB). To date, the EBG has been used to assess how the OB process odor identity, valence, intensity, and it has shown promise as an early biomarker for Parkinsons disease. However, current implementation of the EBG method depends on several methodological components, including subject specific co-registration of electrode positions through neuronavigation and EEG source reconstruction, which may limit accessibility for many research groups. In this study, we test the quality and reliability of the OB signal under different configurations to potentially remedy this. Specifically, we compare six EBG setups that vary in the use of subject-specific T1 scans versus a template head model, co-registered versus template electrode positions, and individualized versus template-based OB location. Our results indicate that strongest EBG signals are obtained when using subject-specific T1 scans in combination with co-registered electrode positions. However, we obtained significant EBG activity even when using a fully template-based configuration. Our anatomical analysis of OB location of 941 individuals reveals that in 86% of cases, the OB is centered within the spatial resolution bounds of the EEG source dipole, supporting the feasibility of detecting olfactory bulb signals without precise individual anatomical mapping using template coordinates. These findings suggest that while subject-specific configurations enhance signal quality, the EBG method remains robust enough to yield meaningful results even with less complex setups. This enables a broader adoption of the EBG method in both clinical and research settings.

neuroscience↗

bioRxiv2025

Oscillatory Control of Cortical Space as a Computational Dimension

Flexible cognition depends on the ability to represent and apply relevant information to the current task at hand. This allows the brain to interpret sensory input and guide behavior in a context-dependent manner. Recent work has proposed Spatial Computing as a mechanism for this flexibility, suggesting that task-related signals organize information processing through spatial patterns of oscillatory activity across the cortical surface. These patterns are proposed to act as "inhibitory stencils" that constrain where sensory-related information (the "content" of cognition) can be expressed in spiking activity. Here, we provide a comprehensive empirical test of Spatial Computing using multi-electrode recordings from the lateral prefrontal cortex in non-human primates performing a range of cognitive tasks (object working memory, sequence working memory, categorization). We found that alpha/beta oscillations encoded task-related information, were organized into spatial patterns that changed with task conditions, and inversely correlated with the spatial expression of sensory-related spiking activity. Furthermore, we found that alpha/beta oscillations reflected misattributions of task conditions and correlated with subjects trial-by-trial decisions. These findings validate core predictions of Spatial Computing suggesting that oscillatory dynamics not only gate information in time but also shape where in the cortex cognitive content is represented. This framework offers a unifying principle for understanding how the brain flexibly coordinates cognition through structured population dynamics.

neuroscience↗

bioRxiv2025

Olfactory bulb and cortex activity reflects subjective odor intensity perception rather than concentration

Understanding stimulus intensity processing is fundamental in sensory science, yet this question remains largely unexplored in human olfaction. We investigated how the human olfactory bulb (OB) and piriform cortex (PC) process odor concentration versus subjective perceived intensity. We demonstrate that OB-PC network oscillatory dynamics are predominantly driven by perceived intensity, not physical concentration. The OB initially processes and communicates perceived intensity to the PC via early gamma-band oscillations (bottom-up feedback). The PC then refines and sends this percept back to the OB via later beta-band oscillations (top-down feedback), updating the OBs gamma activity for subsequent odorants. Critically, analyses of phase-amplitude coupling and beta burst activity demonstrate that transient beta patterns from the PC update OB gamma activity, providing the OB with an updated internal representation of the odor percept. These results reveal an oscillatory mechanism by which the olfactory system maintains perceptual constancy and adaptability despite fluctuations in environmental odor concentrations.

neuroscience↗

bioRxiv2024

The Respiratory-Pupillary Phase Effect: Pupils size is smallest around inhalation onset and largest during exhalation

The prevailing view in the study of animal and human pupillary function has been that pupils dilate and are largest during inhalation and constrict and are smallest during exhalation. However, this notion has recently been challenged. Here, we systematically address this question by conducting a study encompassing three experiments (two resting tasks and one visual perception task), with the latter two being pre-registered. Collectively, across nasal and oral breathing, resting, and task conditions, our experiments consistently and robustly demonstrate that pupil size is smallest around inhalation onset and largest around peak exhalation. This phenomenon, which we term the Respiratory-Pupillary Phase Effect (RPPE), directly contradicts the long-held notion that pupils are largest during inhalation and smallest during exhalation. Notably, the dilation and constriction processes overlap with both phases. The observed consistency and significance of the RPPE across various conditions underscore the need for further investigation into its underlying mechanisms and potential impact on human behavior.

physiology↗

bioRxiv2024

Working memory representations are spatially transferred in cortex during mental manipulations

Working Memory (WM) enables us to maintain and directly manipulate mental representations, yet we know little about the neural implementation of this privileged online format. We recorded electroencephalography data as human subjects engaged in a task requiring continuous updates to the locations of objects retained in WM as well as in a visually identical task with WM demands removed. Analysis of neural data suggested WM-related contralateral delay activity reversed polarity as objects held in WM moved to the opposite hemifield. This was partially but not fully explained by visual attention demands. Thus, the cortical location of activity related to both attention and WM was updated to meet behavioral demands as the spatial location of remembered objects changed.

neuroscience↗

bioRxiv2024

Stability from subspace rotations and traveling waves

Cortical activity shows the ability to recover from distractions. We analyzed neural activity from the prefrontal cortex (PFC) of monkeys performing working memory tasks with mid-memory-delay distractions (a cued gaze shift or an irrelevant visual input). After distraction there were state-space rotational dynamics that returned spiking to population patterns similar to those pre-disruption. In fact, rotations were fuller when the task was performed correctly versus when errors were made. We found a correspondence between state-space rotations and traveling waves across the surface of the PFC. This suggests a role for emergent dynamics like state-space rotations and traveling waves in recovery from distractions.

neuroscience↗

bioRxiv2023

Distinct Functions for Beta and Alpha Bursts in Gating of Human Working Memory

Multiple neural mechanisms underlying gating to and from working memory (WM) have been proposed, with divergent results obtained in human and animal studies. Previous results from non-human primate studies suggest information encoding and retrieval is regulated by high-power bursts in the beta frequency range, whereas human studies suggest that alpha power in sensory regions filters out unwanted stimuli from entering WM. Discrepancies between studies, whether due to differences in analysis, species, or cortical regions, remain unexplained. We addressed this by performing similar single-trial burst analysis we earlier deployed on non-human primates on human whole-brain electrophysiological activity. Participants performed a sequential working memory task that allowed us to track the distinct electrophysiological activity patterns associated with neural processing of targets and distractors. Intriguingly, our results reconcile earlier findings by demonstrating that both alpha and beta bursts are involved in the filtering and control of WM items, but with region and task-specific differences between the two rhythms. Occipital beta burst patterns regulate the transition from sensory processing to WM retention whereas prefrontal and parietal beta bursts track sequence order and proactively suppress retained information prior to upcoming target encoding. Occipital alpha bursts instead suppress unwanted sensory stimuli during their presentation. These results suggest that human working memory is regulated by multiple neural mechanisms that operate in different cortical regions and serve distinct computational roles.

neuroscience↗

bioRxiv2023

The how, when, and what of odor valence communication between the olfactory bulb and piriform cortex

A core function of the olfactory system is to determine an odors valence. The central processing of odor valence is initiated in the olfactory bulb, but the neural mechanisms by which this important information is communicated to, and from, the olfactory cortex (piriform cortex) in humans are not known. To assess communication between the two nodes, we simultaneously measured odor-dependent neural activity in the olfactory bulb and piriform cortex from human participants while obtaining trial-by-trial valence ratings. We determined when valence information was communicated, what kind of information was transferred, and how the information was transferred (i.e., in which frequency band). Support vector machine learning on the coherence spectrum and frequency-resolved Granger causality were used to identify valence-dependent differences in functional and effective connectivity between the olfactory bulb and piriform cortex. We found that the olfactory bulb communicates odor valence to the piriform cortex in the gamma band shortly after odor onset, while the piriform cortex subsequently feeds valence-related information back to the olfactory bulb in the beta band. Decoding accuracy was better for negative than positive valence, suggesting negative valence superiority. Critically, we replicated these findings in an independent dataset using other odors across a larger perceived valence range. Combined, these results demonstrate that the olfactory bulb and piriform cortex communicate levels of odor pleasantness across multiple frequencies, at specific time-points and in a direction-dependent pattern in accordance with the two-stage model of odor processing. It also provides further evidence that odor valence should be viewed as two perceptual dimensions and not one continuous.

neuroscience↗

bioRxiv2023

Propofol-mediated loss of consciousness disrupts predictive routing and local field phase modulation of neural activity

Predictive coding is a fundamental function of the cortex. The predictive routing model proposes a neurophysiological implementation for predictive coding. Predictions are fed back from deep-layer cortex via alpha/beta (8-30Hz) oscillations. They inhibit the gamma (40-100Hz) and spiking that feed sensory inputs forward. Unpredicted inputs arrive in circuits unprepared by alpha/beta, resulting in enhanced gamma and spiking. To test the predictive routing model and its role in consciousness, we collected data from intracranial recordings of macaque monkeys during passive presentation of auditory oddballs (e.g., AAAAB) before and after propofol-mediated loss of consciousness (LOC). In line with the predictive routing model, alpha/beta oscillations in the awake state served to inhibit the processing of predictable stimuli. Propofol-mediated LOC eliminated alpha/beta modulation by a predictable stimulus in sensory cortex and alpha/beta coherence between sensory and frontal areas. As a result, oddball stimuli evoked enhanced gamma power, late (> 200 ms from stimulus onset) period spiking, and superficial layer sinks in sensory cortex. Therefore, auditory cortex was in a disinhibited state during propofol-mediated LOC. However, despite these enhanced feedforward responses in auditory cortex, there was a loss of differential spiking to oddballs in higher order cortex. This may be a consequence of a loss of within-area and inter-area spike-field coupling in the alpha/beta and gamma frequency bands. These results provide strong constraints for current theories of consciousness. Significance statementNeurophysiology studies have found alpha/beta oscillations (8-30Hz), gamma oscillations (40-100Hz), and spiking activity during cognition. Alpha/beta power has an inverse relationship with gamma power/spiking. This inverse relationship suggests that gamma/spiking are under the inhibitory control of alpha/beta. The predictive routing model hypothesizes that alpha/beta oscillations selectively inhibit (and thereby control) cortical activity that is predictable. We tested whether this inhibitory control is a signature of consciousness. We used multi-area neurophysiology recordings in monkeys presented with tone sequences that varied in predictability. We recorded brain activity as the anesthetic propofol was administered to manipulate consciousness. Compared to conscious processing, propofol-mediated unconsciousness disrupted alpha/beta inhibitory control during predictive processing. This led to a disinhibition of gamma/spiking, consistent with the predictive routing model.

neuroscience↗

bioRxiv2022

Deciphering the determinants of recombinant protein yield across the human secretome

Mammalian cells are critical hosts for the production of most therapeutic proteins and many proteins for biomedical research. While cell line engineering and bioprocess optimization have yielded high protein titers of some recombinant proteins, many proteins remain difficult to express. Here, we decipher the factors influencing yields in Chinese hamster ovary (CHO) cells as they produce 2165 different proteins from the human secretome. We demonstrate that variation within our panel of proteins cannot be explained by transgene mRNA abundance. Analyzing the expression of the 2165 human proteins with machine learning, we find that protein features account for only 15% of the variability in recombinant protein yield. Meanwhile, transcriptomic signatures account for 75% of the variability across 95 representative samples. In particular, we observe divergent signatures regarding ER stress and metabolism among the panel of cultures expressing different recombinant proteins. Thus, our study unravels the factors underlying the variation on recombinant protein production in CHO and highlights transcriptomics signatures that could guide the rational design of CHO cell systems tailored to specific proteins.

systems biology↗

bioRxiv2022

Reduced variability of bursting activity during working memory

Working memories have long been thought to be maintained by persistent spiking. However, mounting evidence from multiple-electrode recording (and single-trial analyses) shows that the underlying spiking is better characterized by intermittent bursts of activity. A counterargument suggested this intermittent activity is at odds with observations that spike-time variability reduces during task performance. However, this counterargument rests on assumptions, such as randomness in the timing of the bursts, that may not be correct. Thus, we analyzed spiking and LFPs from the prefrontal cortex (PFC) of monkeys to determine if task-related reductions in variability can co-exist with intermittent spiking. We found that it does because both spiking and associated gamma bursts were task-modulated, not random. In fact, the task-related reduction in spike variability could be explained by a related reduction in gamma burst variability. Our results provide further support for the intermittent activity models of working memory as well as novel mechanistic insights into how spike variability is reduced during cognitive tasks.

neuroscience↗

bioRxiv2022

Oscillations without cortex: Working memory modulates brainwaves in the endbrain of crows

Complex cognition requires coordinated neuronal activity at the network level. In mammals, this coordination results in distinct dynamics of local field potentials (LFP) that have been central in many models of higher cognition. Because these models are based on mammalian data, they often implicitly assume a cortical organization. Higher associative regions of the brains of birds do not have cortical layering, yet these regions have neuronal single-cell correlates of higher cognition that are very similar to those found in mammals. Here we recorded LFP in the avian equivalent of prefrontal cortex while crows performed a highly controlled and cognitively demanding working memory task, adapted from monkeys. To further ensure that recordings reflected only cognitive processes detached from motor-related activities we trained and monitored the animals to keep their head still. We found signatures in local field potentials, modulated by working memory. Frequencies of a narrow gamma (30-59 Hz) and the beta band (13-19 Hz) contained information about the location of the target items on the screen and were modulated by working memory load. This indicates a critical involvement of these bands in ongoing cognitive processing. We also observed bursts in the beta and gamma frequencies, similar to those observed in monkeys. Such bursts are a vital part of activity silent models of working memory. Thus, despite the lack of a cortical organization the avian associative pallium can create LFP signatures reminiscent of those observed in primates. This points towards a critical cognitive function of oscillatory dynamics evolved through convergence in species capable of complex cognition. Relevance statementContemporary models of higher cognition, like those of working memory, often include temporal dynamics of neural activity such as gamma oscillations. Birds and mammals convergently evolved these cognitive functions and here we show that, despite the large evolutionary distance and largely different brain organization, crows share many of the oscillatory fingerprints reported in primates. This indicates that neural networks required for such LFP phenomena have evolved in parallel and may be critical to higher cognition.

neuroscience↗

bioRxiv2022

Robust Working Memory through Short-Term Synaptic Plasticity

Working memory has long been thought to arise from sustained spiking/attractor dynamics. However, recent work has suggested that short-term synaptic plasticity (STSP) may help maintain attractor states over gaps in time with little or no spiking. To determine if STSP endows additional functional advantages, we trained artificial recurrent neural networks (RNNs) with and without STSP to perform an object working memory task. We found that RNNs with and without STSP were able to maintain memories over distractors presented in the middle of the memory delay. However, RNNs with STSP showed activity that was similar to that seen in the cortex of a non-human primate (NHP) performing the same task. By contrast, RNNs without STSP showed activity that was less brain-like. Further, RNNs with STSP were more robust to noise and network degradation than RNNs without STSP. These results show that STSP can not only help maintain working memories, it also makes neural networks more robust and brain-like.

neuroscience↗