Biology subjects

Brincat, S. L.

Publications and source records attributed to Brincat, S. L..

At least 19 recordsLinked to original sources

bioRxiv2026

Disruption of interareal control during propofol anesthesia

Anesthetic-induced unconsciousness may arise partly from a change in how brain areas can manipulate each others activity. To quantify this change, we use control-theoretic tools that can precisely characterize how easily subsystems in complex networks can control each other. These tools rely on the Jacobian of the dynamics, an object that fully specifies how inputs to a function affect the outputs. We built on JacobianODE, a method for data-driven Jacobian learning, to enable its application to neural recordings. We developed a deep learning framework that recovers directional, nonlinear control from partially observed multi-area recordings by combining delay-coordinate embedding, a volume-preserving invertible encoder, and latent dynamics via JacobianODE. We validated our framework on the Lorenz system and a partially observed working-memory recurrent neural network. We then applied it to local field potential recordings from posterior parietal (PPC), superior temporal gyrus (STG), frontal eye fields (FEF), and ventrolateral prefrontal cortex (vlPFC) in two non-human primates, comparing wakefulness with propofol anesthesia. Anesthesia pervasively reduced the ability of areas to control each other, both in terms of driving towards novel states and stabilizing along existing trajectories. This change in ease of control was driven by a decrease in the magnitude of interareal coupling. Directional ease of driving control from PPC to vlPFC and FEF to vlPFC was increased under anesthesia, providing a potential mechanism for paradoxical excitation observed during propofol infusion. Together, these results recast anesthetic unconsciousness as a directional breakdown of cortical control.

neuroscience↗

bioRxiv2026

Mechanistic simulation identifies predictive dose-dependent biomarkers of propofol anesthesia

Understanding how receptor-level pharmacological modulation reorganizes large-scale brain circuits remains a central challenge in neuropharmacology. We introduce a multiscale mechanistic model with explicit core-matrix thalamocortical architecture, driven solely by GABA-A modulation without parameter fitting to any anesthesia data, to examine how propofol reorganizes brainwide activity from individual receptors to systems-level circuits. The model exhibits anesthetic effects spanning individual synaptic conductances to widespread changes in spiking, field potentials, and coherence. Without training on any task-specific data, our simulation of sensory processing in a standard auditory oddball paradigm matches independent macaque datasets. The same simulation, unmodified, also reproduces changes to functional connectivity in anesthetized humans, exhibiting selective attenuation of matrix thalamocortical loops relative to core loops. Most importantly, the simulation identified a dose-dependent biomarker of propofol concentration -- elevated residual inter-stimulus cortical activity -- that was subsequently confirmed in empirical macaque data where it had previously gone unnoticed. This simulation-first discovery, arising from mechanistic circuit dynamics rather than statistical comparison of clinical populations, illustrates a generative framework for translating receptor-level modulation into circuit-scale biomarkers with potential applications across predictive neuropharmacology.

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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.

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bioRxiv2026

Theta gates and routes information in the frontal cortex

Theta (4-10 Hz) oscillations seem well-suited for coordinating neural activity. Many studies have focused on thetas role in long-range coordination across brain regions (e.g., connectivity between the prefrontal cortex and the hippocampus). It remains unclear how theta coordinates neural activity more locally within prefrontal subareas. We examined neural activity in three frontal areas (i.e., dorsolateral prefrontal cortex (dlPFC), ventrolateral prefrontal cortex (vlPFC), and frontal eye fields (FEF)) as non-human primates categorized dot patterns. We found that theta flexibly coordinated spiking activity and higher-frequency oscillations within and between frontal areas. First, theta phase in all areas was coupled to spiking information in the FEF and seemed to gate information that was behaviorally relevant. Second, theta influences were routed in opposite directions depending on feedback. Theta flowed in a posterior direction to the FEF during choices and after correct outcomes. Theta influences reversed directionality and flowed in an anterior direction after incorrect outcomes. Third, theta organized nested cross-frequency, phase-amplitude interactions. Theta was coupled to beta (15-30Hz) oscillations, both within and between areas. Beta, in turn, was coupled to gamma (40-90Hz) oscillations, but mainly locally. Together, our results position theta as a critical mechanism that flexibly and dynamically coordinates neural activity within and across the frontal cortex. HIGHLIGHTS- Neural activity was recorded in three frontal areas as non-human primates categorized dot patterns. - Theta (4-10Hz) oscillations gated relevant information in spiking. - Theta influences were routed in opposite directions depending on feedback. - Theta organized nested cross-frequency interactions with beta (15-30Hz) and gamma (40-90Hz) oscillations. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/729810v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1b4a6a4org.highwire.dtl.DTLVardef@12886feorg.highwire.dtl.DTLVardef@1b6c08dorg.highwire.dtl.DTLVardef@11ba768_HPS_FORMAT_FIGEXP M_FIG C_FIG

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bioRxiv2026

Neural subspace reorganization reflects value-based decision making

Value-based decision making requires maintaining and comparing multiple option representations associated with different values. Then, the chosen option must be communicated to downstream regions to drive behavior. The neural circuits involved in value-based decisions are increasingly well understood, but less understood is how decisions shape option representations. We recorded from lateral prefrontal cortex (LPFC), a central hub for transforming options into actions, while non-human primates (NHPs) held two sequentially presented option-value pairs (spatial targets and abstract reward cues) in working memory, then chose the option with the higher value. This revealed how decisions dynamically reorganize option representations in LPFC. We found that, once decisions could be made, representations of chosen and unchosen options rotated into orthogonal subspaces and the chosen option representation was expanded. Before decisions, the first- and second-presented options were maintained separately. After decisions, the chosen option was rotated into a subspace with a consistent representation of the prescribed action, regardless of its presentation order. This suggests a mechanism for value-based decisions where the decision drives a neural subspace reorganization that facilitates selective and efficient readout of the chosen action.

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.

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bioRxiv2025

Similar destabilization of neural dynamics under different general anesthetics

Different classes of anesthetics can induce unconsciousness despite acting through distinct biological mechanisms. This raises the possibility that they produce a convergent effect on the dynamics or temporal evolution of neural population activity. To explore this, we analyzed intracortical electrophysiological recordings during infusions of propofol, ketamine, and dexmedetomidine, using a rigorous method to estimate dynamical stability. We found that all three anesthetics, despite their molecular differences, similarly affect cortical states by destabilizing their dynamics. This destabilization matched the slower recovery from sensory perturbations and longer stimulus-induced autocorrelation times observed during the anesthetic infusions. The destabilization was also reflected predominantly in lower-frequency ranges, linking it to the well-known increase in low-frequency power during anesthesia. Finally, destabilization closely tracked real-time fluctuations in consciousness. Together, these findings suggest that cortical destabilization may be a shared neural correlate of anesthetic-induced unconsciousness, offering a mechanistic explanation for low-frequency oscillations observed during anesthesia.

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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.

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bioRxiv2025

Recycling of prefrontal subspaces dynamically multiplexes information

Cortical spiking activity in areas like prefrontal cortex (PFC) encodes information only along a small number of dimensions, a subspace of the full space of population activity patterns. PFC often uses distinct subspaces to represent incoming sensory information and to maintain it in working memory. However, its generally assumed that a subspace carries specific information within a specific time frame. Here, in two datasets, we show that neither assumption is correct. The same subspace used during initial encoding was later reactivated during the behavioral response. We also found that subspaces ostensibly dedicated to processing sensory information were recycled to represent behavioral response information later in a trial. We further found a consistent spatial mapping between the original subspace usage and its later recycling. These results demonstrate previously unknown flexibility of PFC subspace coding, both in the deployment of subspaces across time and in their multiplexing of information. This flexibility suggests that PFC subspaces function more like "workspaces" into which different types of information can be written.

neuroscience↗

bioRxiv2025

Evidence for an active handoff between cerebral hemispheres during target tracking

The brain has somewhat separate cognitive resources for the left and right sides of our visual field. Despite this lateralization, we have a smooth and unified perception of our environment. This raises the question of how the cerebral hemispheres are coordinated to transfer information between them. We recorded neural activity in the lateral prefrontal cortex, bilaterally, as non-human primates covertly tracked a target that moved from one visual hemifield (i.e., from one hemisphere) to the other. Beta (15 to 30 Hz) power, gamma (30 to 80 Hz) power, and spiking information reflected sensory processing of the target. By contrast, alpha (10 to15 Hz) power, theta (4 to10 Hz) power, and spiking information seemed to reflect an active handoff of attention as target information was transferred between hemispheres. Specifically, alpha power and spiking information ramped up in anticipation of the hemifield cross. Theta power peaked after the cross, signaling its completion. Our results support an active hand-off of information between hemispheres. This handshaking operation may be critical for minimizing information loss, much like how mobile towers handshake when transferring calls between them.

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bioRxiv2025

Working memory readout varies with frontal theta rhythms

Increasing evidence suggests that attention varies rhythmically, phase-locked to ongoing cortical oscillations. Here, we report that the phase of theta oscillations (3-6 Hz) in the frontal eye field (FEF) is associated with temporal and spatial variation of the read-out of information from working memory (WM). Non-human primates were briefly shown a sample array of colored squares. A short time later, they viewed a test array and were rewarded for identifying which square changed color (the target). Better performance (accuracy and reaction time) varied systematically with the phase of local field potential (LFP) theta at the time of test array onset as well as the targets location. This is consistent with theta "scanning" across the FEF and thus visual space from top to bottom. Theta was coupled, on opposing phases, to both spiking and beta (12-20 Hz). These results could be explained by a wave of activity that moves across the FEF, modulating the readout of information from WM.

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bioRxiv2025

Quantifying Differences in Neural Population Activity With Shape Metrics

Quantifying differences across species and individuals is fundamental to many fields of biology. However, it remains challenging to draw detailed functional comparisons between large populations of interacting neurons. Here, we introduce a general framework for comparing neural population activity in terms of shape distances. This approach defines similarity in terms of explicit geometric transformations, which can be flexibly specified to obtain different measures of population-level neural similarity. Moreover, differences between systems are defined by a distance that is symmetric and satisfies the triangle inequality, enabling downstream analyses such as clustering and nearest-neighbor regression. We demonstrate this approach on datasets spanning multiple behavioral tasks (navigation, passive viewing of images, and decision making) and species (mice and non-human primates), highlighting its potential to measure functional variability across subjects and brain regions, as well as its ability to relate neural geometry to animal behavior.

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bioRxiv2024

Convergent effects of different anesthetics are due to changes in phase alignment of cortical oscillations

Many anesthetics cause loss of responsiveness despite having diverse underlying molecular and circuit actions. To explore the convergent effects of these drugs, we examined how anesthetic doses of ketamine and dexmedetomidine affected oscillations in the prefrontal cortex of nonhuman primates. Both anesthetics caused increases in phase locking in the ventrolateral and dorsolateral prefrontal cortex, within and across hemispheres. However, the nature of the phase locking varied. Activity in different subregions within a hemisphere became more anti-phase with both drugs. Local analyses within a region suggested that this finding could be explained by broad cortical distance-based effects, such as large traveling waves. By contrast, homologous areas across hemispheres became more in-phase. Our results suggest that both anesthetics induce strong patterns of cortical phase alignment that are markedly different from those in the awake state, and that these patterns may be a common feature driving loss of responsiveness from different anesthetic drugs.

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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.

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bioRxiv2023

Adaptive stretching of representations across brain regions and deep learning model layers

Prefrontal cortex (PFC) is known to modulate the visual system to favor goal-relevant information by accentuating task-relevant stimulus dimensions. Does the brain broadly re-configures itself to optimize performance by stretching visual representations along task-relevant dimensions? We considered a task that required monkeys to selectively attend on a trial-by-trial basis to one of two dimensions (color or motion direction) to make a decision. Except for V4 (color bound) and MT (motion bound), the brain radically re-configured itself to stretch representations along task-relevant dimensions in lateral PFC, frontal eye fields (FEF), lateral intraparietal cortex (LIP), and inferotemporal cortex (IT). Spike timing was crucial to this code. A deep learning model was trained on the same visual input and rewards as the monkeys. Despite lacking an explicit selective attention or other control mechanism, the model displayed task-relevant stretching as a consequence of error minimization, indicating that stretching is an adaptive strategy.

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bioRxiv2023

Propofol anesthesia destabilizes neural dynamics across cortex

Every day, hundreds of thousands of people undergo general anesthesia. One hypothesis is that anesthesia disrupts dynamic stability, the ability of the brain to balance excitability with the need to be stable and thus controllable. We tested this hypothesis using a new method for quantifying population-level dynamic stability in complex systems, Delayed Linear Analysis for Stability Estimation (DeLASE). Propofol was used to transition animals between the awake state and anesthetized unconsciousness. DeLASE was applied to macaque cortex local field potentials (LFPs). We found that neural dynamics were more unstable in unconsciousness compared to the awake state. Cortical trajectories mirrored predictions from destabilized linear systems. We mimicked the effect of propofol in simulated neural networks by increasing inhibitory tone. Paradoxically, increased inhibition also destabilized the networks. Our results suggest that anesthesia disrupts dynamical stability that is required for consciousness.

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bioRxiv2023

New learning principles emerge from biomimetic computational primitives

Although computational models have deepened our understanding of neuroscience, it is still highly challenging to link actual low-level physiological activity (spiking, field potentials) and biochemistry (transmitters and receptors) with high-level cognitive abilities (decision-making, working memory) nor with corresponding disorders. We introduce an anatomically-organized multi-scale model directly generating simulated physiology from which extended neural and cognitive phenomena emerge. The model produces spiking, fields, phase synchronies, and synaptic change, directly generating working memory, decisions, and categorization, all of which were then validated on extensive experimental macaque data from which the model received zero prior training of any kind. Moreover, the simulation uncovered a previously unknown neural code specifically predicting upcoming erroneous ("incongruous") behaviors, also subsequently confirmed in empirical data. The biomimetic model thus directly and predictively links novel decision and reinforcement signals, of computational interest, with novel spiking and field codes, of potential behavioral and clinical relevance.

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bioRxiv2023

Propofol Mediated Unconsciousness Disrupts Progression of Sensory Signals through the Cortical Hierarchy

A critical component of anesthesia is the loss sensory perception. Propofol is the most widely used drug for general anesthesia, but the neural mechanisms of how and when it disrupts sensory processing are not fully understood. We analyzed local field potential (LFP) and spiking recorded from Utah arrays in auditory cortex, associative cortex, and cognitive cortex of non-human primates before and during propofol mediated unconsciousness. Sensory stimuli elicited robust and decodable stimulus responses and triggered periods of stimulus-induced coherence between brain areas in the LFP of awake animals. By contrast, propofol mediated unconsciousness eliminated stimulus-induced coherence and drastically weakened stimulus responses and information in all brain areas except for auditory cortex, where responses and information persisted. However, we found stimuli occurring during spiking Up states triggered weaker spiking responses than in awake animals in auditory cortex, and little or no spiking responses in higher order areas. These results suggest that propofols effect on sensory processing is not just due to asynchronous down states. Rather, both Down states and Up states reflect disrupted dynamics.

neuroscience↗