Biology subjects

Heilbronner, S. R.

Publications and source records attributed to Heilbronner, S. R..

18 recordsLinked to original sources

bioRxiv2026

Individualized AI-driven Neuromodulation Selectively Enhances and Reorganizes Human Tongue Sensorimotor Networks.

Precise modulation of brain networks for tongue motor and sensory control (TMSC) is critical for neruorehabilitation. Existing neuromodulation approaches use fixed targets, ignoring individual network architecture. We present an AI-driven, individualized fMRI neuromodulation (iNM) platform adaptively targeting subject-specific TMSC networks in real-time. Using a neurofunctional twin built from each participant's anatomy and function, iNM reinforces targeted activity and suppresses competing states. Unsupervised machine learning and hidden Markov modeling showed iNM increased TMSC-state occupancy from 82% to 97% and suppressed swallow-state interference by 83%. The inferior parietal lobule emerged as a sensorimotor integration hub, with increased magnitude (d' 90.4 right, 84 left) and spatial expansion (134.8% right, 81.8% left). Cortico-subcortical connectivity strengthened 53% to 74% across motor, sensory, and attention networks and persisted into non-iNM blocks. Thus, iNM may offer precision neurorehabilitation for CNS or PNS disorders, such as amyotrophic lateral sclerosis, and treatment-induced cranial neuropathy in head-and-neck-cancer survivors, respectively.

neuroscience↗

bioRxiv2026

Electrophysiological dissociation of human posterior cingulate cortex contributions to value- and memory-based decision-making

The human posterior cingulate cortex (PCC) is routinely implicated in cognition and disease, yet its specific functional contributions remain unclear. Historically, human neuroimaging has linked the region to episodic memory and the default mode network, while a distinct non-human primate electrophysiology literature has focused on economic decision-making. Integrating anatomical evidence with these literatures, it has recently been proposed that this divergence reflects subregional organization, with dorsal PCC as a potential convergence site for value-based and memory-based decisions. Here, we recorded local field potentials (LFPs) and single units from human PCC while the same participants performed matched value- and memory-based decision tasks. LFPs in dorsal but not ventral PCC showed sustained engagement across both tasks, with risk sensitivity emerging only after the decision. In contrast, single-unit activity was more temporally circumscribed and could be grouped into response profiles active before or after the decision. Dorsal but not ventral PCC engagement further extended to memory encoding, recognition, and confidence judgments. Together, these findings reveal a consistent functional dissociation, identifying dorsal PCC as a domain-general interface between evaluative and mnemonic systems. In doing so, they align human and non-human primate accounts of PCC function and help orient future targeted studies of its role in cognition and disease.

neuroscience↗

bioRxiv2026

Electrophysiological features of signals recorded from white matter

Intracranial neurophysiology studies have typically ignored signals from electrodes located in white matter (WM), assuming that their information content is artifactual or related to nearby gray matter (GM). Here, we tested the electrophysiological and functional features of signals recorded from different WM locations. Signals were recorded from 19 patients undergoing intracranial monitoring for drug-resistant epilepsy by means of stereo-electroencephalography (sEEG). Each sEEG electrode was classified into WM or GM based on the surrounding tissue. We obtained recordings from a total of 1,717 sEEG electrode contacts, 36% in WM, while the patients were in awake resting state (5 minutes). For each sEEG electrode, we employed a model-based spectral decomposition to separate periodic and aperiodic components, and we computed signal complexity metrics. For a subset of participants, we computed WM structural information from diffusion-weighted magnetic resonance imaging and we evaluated functional signals during a cognitive control task. Our results show that signals recorded from WM have different spectral features and higher complexity than GM. Complexity correlates positively with fractional anisotropy, and modulations related to behavior during the task were detected in WM. Overall, this indicates that WM signals carry information that may reflect signal propagation across WM fiber tracts.

neuroscience↗

bioRxiv2026

Scaling up polarization-sensitive optical coherence tomography to image the whole macaque brain

Polarization-sensitive optical coherence tomography (PS-OCT) is a label-free imaging technique that exploits birefringence to visualize myelinated axons at micrometer resolution. However, serial PS-OCT imaging has been limited to small volumes, including tissue blocks from larger species, owing to constraints in acquisition speed, system stability, and data processing. These limitations have prevented its application to whole-brain mapping in large mammals. Here we present a scalable PS-OCT acquisition system and computational pipeline for whole-brain imaging in the rhesus macaque. The framework integrates high-throughput serial imaging with automated reconstruction and processing, enabling volumetric imaging at micrometer-scale resolution across decimeter-scale brain volumes. Using this approach, we acquired two complete macaque brains at a voxel size of 5.5 x 5.5 x 3.4 m and an effective resolution of approximately 10 x 10 x 5.5 m, generating multi-terabyte datasets consisting of multiple contrasts including fiber orientation information. The datasets and associated processing tools are made publicly available. This platform establishes a method for large-scale, high-resolution mapping of white matter architecture in primate brains. The resulting datasets provide a reference for validating MRI models and support the development of neurotechnological applications, including deep brain stimulation, where accurate characterization of axonal organization is required.

neuroscience↗

bioRxiv2026

Conserved fiber topography of the anterior limb of the internal capsule in treatment-resistant psychiatric patients

IntroductionThe anterior limb of the internal capsule (ALIC) is a major white matter highway connecting prefrontal cortical (PFC) regions to the thalamus, brainstem, and subthalamic nucleus. Structural and functional abnormalities within the ALIC circuit have been associated with many neuropsychiatric disorders, including obsessive-compulsive disorder (OCD) and depression, and deep brain stimulation (DBS) may provide effective treatment to some of these patients. However, it remains unclear whether the well-characterized topographic organization of the ALIC observed in healthy individuals and preclinical models is preserved in treatment-resistant psychiatric populations. MethodsWe first used diffusion tractography to evaluate the topography of PFC and subcortical fibers through the ALIC in patients with treatment-resistant OCD (n=18) and depression (n=5). In depression patients, we also evaluated ALIC topography using cerebro-cerebral evoked potentials (CCEPs) elicited by single-pulse electrical stimulation (SPES) of DBS leads in the ALIC and recordings in the ventral PFC (vPFC). ResultsThe topographic organization of PFC and subcortical projections is preserved in the ALIC among treatment-resistant psychiatric patients, consistent with patterns observed in healthy individuals and preclinical models. CCEP recordings in the ventral PFC showed a ventral ALIC to medial vPFC/dorsal ALIC to lateral vPFC response pattern in the left hemisphere, but not in the right. ConclusionOur findings confirm that topographic patterns within the ALIC previously identified using preclinical models and healthy controls are preserved in treatment-resistant psychiatric patients. Furthermore, by linking white matter topography to stimulation effects, this work supports more precise and individualized neuromodulatory strategies for neuropsychiatric disorders.

neuroscience↗

bioRxiv2026

A retinotopic wiring principle of the human brain

Summary paragraphA central challenge in neuroscience is to understand how anatomical connectivity links neural representations to behavior. In sensory systems, cortical areas encode structured maps of the external world, yet it remains unclear whether and how this representational geometry constrains long-range connectivity in the living human brain. Here, we show that structural connectivity in the human visual cortex preserves retinotopic organization, revealing a retinotopic wiring principle; cortical regions representing the same locations in visual space preferentially connect. Across more than 1,700 participants spanning ages 2 to 88 years, we further show that well-known perceptual asymmetries correspond to systematic asymmetries in connectivity within early visual cortex, but not in connections linking visual cortex to the rest of the brain. We introduce a scalable approach to map retinotopic connectivity when tractography alone is unreliable. Together, these findings demonstrate that anatomical connectivity preserves the geometry of neural representations, providing a general principle linking brain structure, function, and behavior.

neuroscience↗

bioRxiv2025

10.5 Tesla High-Resolution Macaque Brain MRI for Connectivity Studies

Mapping brain connectivity in primates remains a major challenge due to difficulties in resolving microscopic white matter architecture, while maintaining whole-brain coverage. Increasing imaging spatial resolution is key for disambiguating fibre configurations within smaller anatomical volumes. Here, we present novel developments that allow high-resolution diffusion MRI of the macaque brain using one of the world's highest-field human MRI scanners operating at 10.5 Tesla, allowing both in vivo and ex vivo macaque brain imaging. Our approach achieves very high spatial resolution across both tissue states, (up to 580 m)3 in vivo and (300 m)3 ex vivo, with diffusion weighting up to b = 6000 s/mm2. We detail methodological advances in data acquisition, image reconstruction, processing and whole-brain tractography that overcome critical challenges associated with ultra-high-field imaging. This work establishes a new framework for high-resolution in vivo and ex vivo neuroimaging of the NHP brain at 10.5 T using a human bore scanner, paving the way for subsequent analyses of brain connectivity across species and tissue states at unprecedented detail. The dataset, along with all processing pipelines, containerised workflows, and reusable web services, is openly shared to support reproducibility and future integration with microscopy for studying white matter microstructure and connections at the mesoscale.

neuroscience↗

bioRxiv2025

Convergent and divergent neural and behavioral responses to chronic cocaine use in macaques

Chronic cocaine use leads to physical dependence, psychological addiction, and various health problems such as cardiovascular issues and cognitive impairments. This condition continues to be extremely difficult to treat, as we grapple with its neural and behavioral complexities. What we are missing is a comprehensive account on how naive brains react to occasional and chronic cocaine use, abstinence and re-exposure within subject. We tracked naive macaques using precision functional mapping before, during and after chronic cocaine self-administration over a period of nine months. We analyzed the entire brain to illustrate the pervasive impact of chronic cocaine use on overall function. Although we set out to map the "addiction" connectome, we found that the neural correlates of chronic drug use and recovery are more complex that can be captured by a singular, canonical connectome. We provide a preclinical model that maps the progression of the macaque functional connectome from a naive state through chronic cocaine use, recovery and re-exposure. We demonstrate that the "addiction" connectome is dynamic and is characterized by the interaction of subject by drug by time. Occasional cocaine use, whether initial or re-exposure, overrides individual differences, leading to a strong homogenous effect across subjects, or convergence. However, the brains response to prolonged cocaine use becomes more individualized, resulting in the divergence of effects across subjects. This can be explained by heterogeneity in cocaine-induced effects and in their associated timescales. Abstinence-induced neural alterations converged across subjects after 1-month, but by 2 months, individual trajectories revealed heterogeneity, possibly indicating differences in recovery.

neuroscience↗

bioRxiv2025

16p11.2 duplication shows early male-biased impacts on reward learning, but NMDA receptor antagonism reduces optimal choice selection in both wildtypes and 16p11.2 duplication

Rationale16p11.2 duplication is associated with numerous neuropsychiatric conditions at a genome-wide level, including psychosis. Mice modeling 16p11.2 duplication may provide important insights into cognitive risk factors, in particular in reward-guided decision making. NMDAR function has also been implicated in psychosis phenotypes, but whether these phenotypes differ by genetic risk factor is unknown. ObjectivesWe aimed to: 1) identify sex and genotype differences in early operant training and two-arm spatial restless bandit task performance; 2) examine the effects of an NMDAR antagonist on task performance and strategy across genotypes. Methods16p11.2 duplication and wildtype mice completed a series of training schedules of escalating difficulty followed by bandit tasks. MK-801 and saline were administered in alternating sessions prior to later bandit task performance. ResultsLarge sex differences in early operant training revealed some male-biased impacts of 16p11.2 duplication, contingent on training schedule difficulty. Once on the two-arm spatial restless bandit task, 16p11.2 duplication was no longer a strong contributor to decision making. However, MK-801 decreased the tendency to stay with a rewarded choice, lowered the probability of selecting the highest rewarded option, and decreased the influence of prior outcomes on choice. ConclusionsThe male-biased vulnerability in early operant training suggests that strategies for learning early schemas or in novel environments may be impacted by 16p11.2 duplication in males. In contrast, NMDAR are influential in the ability to flexibly switch between choices, and disrupting this function significantly impairs decision making in all animals.

animal behavior and cognition↗

bioRxiv2025

Individualized AI-driven neuromodulation enhances tongue motor and sensory control: preliminary efficacy targeted towards the alleviation of chronic cranial neuropathies

Precise modulation of brain networks responsible for tongue motor and sensory control (TMSC) is critical for restoring functions, such as speech and swallowing in neurodegenerative disease or in treatment-induced chronic cranial neuropathy. We present an individualized, AI-driven fMRI neuromodulation (iNM) platform that adaptively targets subject-specific TMSC networks in real time. To enhance iNM precision and encodability --critical for neurorehabilitation--we mapped each healthy participants individualized TMSC selectivity network, creating a subject-specific TMSC digital twin. iNM increased signal strength, spatial expansion, and consistency across motor, sensory, and attention regions, while it reduced signal variability. The bilateral inferior parietal lobule emerged as key sensorimotor integration hub, as it exhibited exclusive activation under iNM along with highest discriminability, and largest spatial expansion. iNM also significantly strengthened and expanded motor, sensory, and attention-related networks -- medial-middle frontal areas, insula-claustrum, S1, M1, basal ganglia, motor cerebellum, and inferior temporal-- supporting interoceptive and proprioceptive-motor integration. Machine learning and unsupervised hidden Markov modeling revealed that iNM enhanced the decodability and stability of TMSC-neural states, while it suppressed competing swallow-neural state interference. Notably, the iNM effects extended beyond the neuromodulation window, indicating functional persistence--a key requirement for rehabilitation. iNM reconfigured TMSC networks by strengthening cortico-subcortical connectivity and adaptive circuit dynamics. Our findings show iNM as a non-invasive, personalized intervention capable of selectively enhancing sensorimotor control with high spatiotemporal specificity. By demonstrating mechanistic network-precision and functional carryover, iNM offers a promising intervention for individuals with limited treatment options, including head and neck cancer survivors and early-stage neurodegenerative disease patients.

neuroscience↗

bioRxiv2025

Learning and language in the unconscious human hippocampus

Consciousness is a fundamental component of cognition,1 but the degree to which higher-order pattern recognition relies on it remains disputed.2,3 Here we demonstrate the persistence of oddball discrimination, semantic processing, and online prediction in individuals under general anesthesia-induced loss of consciousness.4,5 Using high-density Neuropixels microelectrodes6 to record both single unit and local field potential neural activity in the human hippocampus while playing a series of tones to anesthetized patients, we found that hippocampal neurons and local oscillations retained some detection of oddball tones. This effect size grew over the course of the experiment ([~]10 minutes), demonstrating representational plasticity. A biologically plausible recurrent neural network model showed that learning and oddball representation are an emergent property of flexible tone discrimination. Moreover, when we played language stimuli, single units and local field potentials carried information about the semantic and grammatical features of natural speech, even predicting semantic information about upcoming words. Together these results indicate that in the hippocampus, which is anatomically and functionally distant from primary sensory cortices,7 complex processing of sensory stimuli occurs even in the unconscious state.

neuroscience↗

bioRxiv2024

Mapping polarization-sensitive optical coherence tomography and ultra-high-field diffusion MRI in the macaque brain

This paper provides comparisons between microstructure and two-dimensional fiber orientations measured optically using polarization sensitive optical coherence tomography (PS-OCT) and those estimated from ultra-high-field diffusion MRI (dMRI) at 10.5T in the macaque brain. The PS-OCT imaging is done at an in-plane resolution of [~]10 microns in and around the thalamus. Whole brain dMRI is acquired at an isotropic resolution of 0.75 mm. We provide comparisons between cross-polarization and optical orientation from PS-OCT with the fractional anisotropy and two-dimensional orientations extracted from dMRI using a diffusion tensor model. The orientations from PS-OCT are also extracted computationally using a structure tensor. Additionally, we demonstrate the utility of mesoscale, PS-OCT imaging in improving the MRI resolution by learning the mapping between these contrasts using a super-resolution Generative Adversarial Network.

neuroscience↗

bioRxiv2023

A biophysically constrained brain connectivity model based on stimulation-evoked potentials.

BackgroundSingle-pulse electrical stimulation (SPES) is an established technique used to map functional effective connectivity networks in treatment-refractory epilepsy patients undergoing intracranial-electroencephalography monitoring. While the connectivity path between stimulation and recording sites has been explored through the integration of structural connectivity, there are substantial gaps, such that new modeling approaches may advance our understanding of connectivity derived from SPES studies. New MethodUsing intracranial electrophysiology data recorded from a single patient undergoing sEEG evaluation, we employ an automated detection method to identify early response components, C1, from pulse-evoked potentials (PEPs) induced by SPES. C1 components were utilized for a novel topology optimization method, modeling 3D conductivity propagation from stimulation sites. Additionally, PEP features were compared with tractography metrics, and model results were analyzed with respect to anatomical features. ResultsThe proposed optimization model resolved conductivity paths with low error. Specific electrode contacts displaying high error correlated with anatomical complexities. The C1 component strongly correlates with additional PEP features and displayed stable, weak correlations with tractography measures. Comparison with existing methodsExisting methods for estimating conductivity propagation are imaging-based and thus rely on anatomical inferences. ConclusionsThese results demonstrate that informing topology optimization methods with human intracranial SPES data is a feasible method for generating 3D conductivity maps linking electrical pathways with functional neural ensembles. PEP-estimated effective connectivity is correlated with but distinguished from structural connectivity. Modeled conductivity resolves connectivity pathways in the absence of anatomical priors.

neuroscience↗

bioRxiv2022

Systematic evaluation of anatomical details on transcranial electric stimulation and transcranial magnetic stimulation induced electric fields in a non-human primate model

Non-human primates (NHPs) have become key for translational research in noninvasive brain stimulation (NIBS). However, in order to create comparable stimulation conditions to humans it is vital to evaluate and match electric fields across species. Numerical models to simulate electric fields are an important tool for experimental planning in NHPs and translation to human studies. It is thus essential to evaluate how anatomical details in NHP models affect NIBS electric fields. Here, we create a highly accurate head model of a non-human primate (NHP) from 10.5 T MR data. We systematically evaluate how muscle tissue and head size (due to different MRI fields of view) affect simulation results in transcranial electric and magnetic stimulation (TES and TMS). Our findings indicate that the inclusion of muscle can affect TES electric field strength up to 29.5% while TMS is largely unaffected. Additionally, comparing a full head model to a cropped head model illustrates the impact of head size on electric fields for both TES and TMS. We find opposing effects between TES and TMS with an increase up to 13.5% for TES and a decrease up to 21.5% for TMS for the cropped head model compared to the full head model. Our results provide important insights into the level of anatomical detail needed for NHP head models and can inform future translational efforts for NIBS studies. HighlightsO_LIWe created a high resolution non-human primate FEM head model from 10.5 T MR data. C_LIO_LIWe ran transcranial electric and magnetic stimulation (TES and TMS) simulations to evaluate the effects of muscle and head size on the induced electric field in the brain. C_LIO_LIWe simulated both isotropic and anisotropic muscle conductivities. C_LIO_LIMuscle tissue can greatly affect simulation results for TES (increase electric field strength by up to 29.5%), but not for TMS. C_LIO_LIThere are opposing, but large effects of using a full head model versus a cropped head model for both TES (increase up to 13.5%) and TMS (decrease of up to 21.5%) C_LI

neuroscience↗

bioRxiv2021

Intrinsic timescales as an organizational principle of neural processing across the whole rhesus macaque brain

Hierarchical temporal dynamics are a fundamental computational property of the brain; however, there are no whole-brain, noninvasive investigations into timescales of neural processing in animal models. To that end, we used the spatial resolution and sensitivity of ultrahigh field fMRI performed at 10.5 Tesla to probe timescales across the whole macaque brain. We uncovered within-species consistency between timescales estimated from fMRI and electrophysiology. Crucially, we extended existing electrophysiological hierarchies to whole brain topographies. Our results validate the complementary use of hemodynamic and electrophysiological intrinsic timescales, establishing a basis for future translational work. Further, with these results in hand, we were able to show that one facet of the high-dimensional functional connectivity topography of any region in the brain is closely related to hierarchical temporal dynamics. We demonstrated that intrinsic timescales are organized along spatial gradients that closely match functional connectivity gradient topographies across the whole brain. We conclude that intrinsic timescales are a unifying organizational principle of neural processing across the whole brain. Declaration of InterestsThe authors declare no competing interests.

neuroscience↗

bioRxiv2020

A functional hierarchy for choice in medial prefrontal cortex

Hierarchical approaches to functional neuroanatomy propose that choice-relevant brain regions have overlapping functions and can be organized into a series that progressively transforms information about options into choices. Here, we examined responses of neurons in four regions of the medial prefrontal cortex as macaques performed two-option risky choices. All four regions encoded economic variables in similar proportions and showed putative signatures of key choice-related computations. We found evidence for a hierarchical organization proceeding from areas 14[->]25[->]32[->]24. Specifically, we found that decodability of eight distinct task variables increased along that path, consistent with the idea that hierarchically later regions make these variables more separable. We also found longer intrinsic timescales in the same series, further supporting the idea of a hierarchy. Together these results highlight the importance of the medial wall in choice, endorse a specific hierarchical organization, and argue against a modular functional neuroanatomy of choice.

neuroscience↗

bioRxiv2020

Ultra-high field (10.5 T) resting state fMRI in the macaque

Resting state functional connectivity refers to the temporal correlations between spontaneous hemodynamic signals obtained using functional magnetic resonance imaging. This technique has demonstrated that the structure and dynamics of identifiable networks are altered in psychiatric and neurological disease states. Thus, resting state network organizations can be used as a diagnostic, or prognostic recovery indicator. However, much about the physiological basis of this technique is unknown. Thus, providing a translational bridge to an optimal animal model, the macaque, in which invasive circuit manipulations are possible, is of utmost importance. Current approaches to resting state measurements in macaques face unique challenges associated with signal-to-noise, the need for invasive contrast agents, and within-subject designs. These limitations can, in principle, be overcome through ultra-high magnetic fields. However, ultra-high field imaging has yet to be adapted for fMRI in macaques. Here, we demonstrate that the combination of high channel count transmitter and receiver arrays, optimized pulse sequences, and careful anesthesia regimens, allows for detailed within-subject resting state analysis at ultra-high resolutions. In this study, we uncover thirty spatially detailed resting state components that are highly robust across individual macaques and closely resemble the quality and findings of connectomes from large human datasets. This detailed map of the rsfMRI macaque connectome will be the basis for future neurobiological circuit manipulation work, providing valuable biological insights into human connectomics.

neuroscience↗

bioRxiv2019

A neural network for information seeking

Humans and other animals often show a strong desire to know the uncertain rewards their future has in store, even when they cannot use this information to influence the outcome. However, it is unknown how the brain predicts opportunities to gain information and motivates this information seeking behavior. Here we show that neurons in a network of interconnected subregions of primate anterior cingulate cortex and basal ganglia predict the moment of gaining information about uncertain rewards. Spontaneous increases in their information prediction signals are followed by gaze shifts toward objects associated with resolving uncertainty, and pharmacologically disrupting this network reduces the motivation to seek information. These findings demonstrate a cortico-basal ganglia mechanism responsible for motivating actions to resolve uncertainty by seeking knowledge about the future.

neuroscience↗