Biology subjects

Andersen, R. A.

Publications and source records attributed to Andersen, R. A..

At least 19 recordsLinked to original sources

bioRxiv2026

A Unified World Model in Human Posterior Parietal Cortex

How does the brain understand the physical world, predict future events, and plan actions? Are these problems solved by a unified world model, as hypothesized by cognitive scientists and artificial intelligence researchers? Posterior parietal cortex has been implicated in all these functions, but whether the same neurons support each of them is unknown. We recorded from the superior parietal lobule (SPL) of two tetraplegic participants implanted with microelectrode arrays. SPL units preferentially engaged by intuitive physics, judging block-tower stability and viewing naturalistic physical events, also predicted whether moving objects would collide hundreds of milliseconds before contact, generalizing between different physical scenarios. These populations also encoded which hand action the participant intended to perform. These findings identify SPL as a substrate for physical world modeling.

neuroscience↗

bioRxiv2026

Human single-neuron correlates of somatosensation

Understanding the neural correlates of consciousness poses a central challenge in neuroscience, with longstanding debate over which cortical areas underlie subjective sensory perception. In the tactile domain, posterior parietal cortex (PPC) and primary somatosensory cortex (S1) are candidate cortical substrates for neural correlates of consciousness due to their crucial roles in somatosensory processing. Yet whether and how these regions contribute to conscious tactile perception remains unclear. Here, to address this issue, we leveraged chronic intracortical recordings to simultaneously monitor large ensembles of single neurons in grasp related cortical areas from three participants with tetraplegia while natural vibrotactile stimuli were delivered to a sensate region of the upper limb. We demonstrate that an orchestration of neural activity emerged across the grasp-related parietal-frontal network at near-threshold perception. Within this distributed network, we then focused on PPC and S1. While S1 responses closely tracked the amplitude of the physical stimulus, PPC activity covaried more strongly with awareness and confidence. This single-neuron evidence reveals PPC and S1 have complementary neural codes with PPC transforming physical stimulation into conscious perception whereas S1 is more sensitive to stimulus amplitude.

neuroscience↗

bioRxiv2026

Neural encoding of grasp and object properties in the posterior parietal and motor cortices of the cortical grasping network in tetraplegic humans

The cortical grasping network (CGN) is responsible for the ability to physically interact with the world around us using our hands. For patients with motor impairments due to neurogenerative disease or traumatic injury, brain-machine interfaces (BMIs) offer a potential pathway towards restoration of dexterous hand control via recording neural activity throughout the CGN. However, grasping objects with robotic BMI devices has proved challenging, when utilizing neural signals from only motor cortex (MC, a subregion of the CGN). It is currently unclear how the presence of an object might compromise BMI performance; thus this work explores the interactive neural representation of grasp and objects throughout the CGN. Three tetraplegic human participants performed grasp motor imagery during imagined object manipulation while we recorded neural activity from the supramarginal gyrus (SMG), anterior intraparietal cortex (AIP), motor cortex (MC), and primary somatosensory cortex (S1). All regions within the CGN represented whole hand configuration of imagined grasps during motor planning and imaged execution. Additionally, grasp-related neural activity in each region was modulated by context (motor planning vs. imagined execution and object present vs. not present). SMG and AIP represented object shape during motor planning. PPC encoded both grasp and object properties simultaneously from mostly unique subpopulations of neurons. This separability in higher cortical regions could be a critical for stable BMI grasp performance.

neuroscience↗

bioRxiv2026

Evolution of multicellularity and reproductive strategies in yellow-green algae (Xanthophyceae, Heterokontophyta)

The evolution of multicellularity has long been linked to reproductive strategies. A long-standing debate concerns whether multicellular organisms are primarily stabilized by small single-cell propagules that minimize genetic heterogeneity or by larger multicellular and multinucleate propagules that may improve developmental success and survival of individuals. the Xanthophyceae provides an excellent model for investigating these questions, exhibiting transitions between unicellular to multicellular filamentous and coenocytic forms together with diverse reproductive modes, including single-cell zoospores and autospores, and multinucleate monospores and akinetes. However, a robust phylogenetic framework and systematic analyses of character evolution have remained lacking in this lineage. Here, we present a phylogenomic framework based on a nuclear dataset of 680 genes from 18 species, including 17 newly generated transcriptomes. Nuclear phylogenies robustly resolve all sampled inter-ordinal and inter-familial relationships with full concordance between concatenation and coalescent analyses, while plastid (141 genes) and mitochondrial (31 genes) datasets from 33 species recover identical topologies. Based on these results, we establish one new order (Pseudopleurochloridales), emend one order (Heterococcales), and propose five new families. Ancestral character reconstruction indicates at least four independent transitions from unicellular ancestors to simple multicellularity. Bayesian analyses of multicellularity and reproductive characters show that these transitions were consistently accompanied by shifts from multiple autospore-type propagules toward single monospore- and akinete-type propagules, whereas reversions to unicellularity were associated with the reappearance of autospore-based reproduction. These results provide a phylogenomic framework for understanding multicellular evolution in Xanthophyceae and shed light on the relationship between reproductive modes and the emergence of simple multicellularity.

evolutionary biology↗

bioRxiv2026

Functional ultrasound imaging through a human cranial window for mesoscopic mapping of motor effector encoding within the sensorimotor cortex

Understanding movement encoding within human cortical circuits has been essential for advancing brain computer interfaces (BCIs). However, there are limited minimally invasive, high resolution neurorecording methods sensitive enough to detect single-trial movement-correlated neural activity. Functional ultrasound imaging (fUSI) provides submillimeter spatial resolution of deep cortical tissue with high sensitivity and, when paired with acoustically transparent skull implants, enables transcutaneous recording of human neurovascular changes. Prior studies have used fUSI in participants with acoustically transparent skull implants for on-off task mapping and decoding. Here, we demonstrate fUSIs ability to reliably resolve multi-body-part and single digit movement encoding within the primary sensorimotor cortex in a participant with an acoustically transparent skull implant. We obtained fine-grained mappings of individual effector representation that were consistent with classic somatotopy for both multi-body-part and single digit movement. We were able to resolve single-trial event-related activity, enabling single-trial decoding of both conditions. Analysis of voxels important for decoding suggested differential encoding of single digit movement information across the different Brodmann areas. Finally, we show that these patterns can be approximated across different sessions, allowing for cross session decoding. These results establish that fUSI can reliably delineate somatotopically organized motor representations at submillimeter resolution, bridging a critical gap between invasive electrophysiology and noninvasive hemodynamic imaging in a human subject.

neuroscience↗

bioRxiv2026

The Compositional Encoding of Hand-Eye Coordinated Movements for Single Neurons in the Posterior Parietal Cortex

Human posterior parietal cortex (PPC) is thought to play an important role in hand-eye coordination, yet the underlying encoding mechanisms remain uncertain. We recorded 412 single neurons across 11 sessions from motor cortex (MC; n=251) and PPC (n=161) in a single human participant performing a hand-eye (H-E) coordinated center-out task. While MC neurons showed little to no modulation by eye movements, 79% of PPC neurons had neural representations that were additively separable into independent hand- and eye-movement tuning curves. Due to this separability, neural representations could be separated and additively recomposed while maintaining structure similarity. Consequently, compositional decoders trained solely on single-effector movements could match the performance of decoders trained on coordinated H-E movements (hand: 66% vs 69%; eye: 34% vs 36%). These results show that, during simple center-out tasks, MC hand movement codes are unaffected by eye movements and that compositionality can be used to modularly decode H-E coordinated movements in PPC.

neuroscience↗

bioRxiv2025

Hierarchical and Context-Dependent Encoding of Actions in Human Posterior Parietal and Motor Cortex

Action understanding requires internal models that link vision to motor goals. In monkeys, mirror neurons demonstrate motor resonance during observation, but single-unit evidence in humans is limited, leaving open whether such representations rely solely on motor resonance. We recorded neural activity from motor cortex (MC) and superior parietal lobule (SPL) in two tetraplegic participants implanted with Utah arrays while they intended or observed hand actions. MC strongly encoded intention but showed only weak, feature-specific overlap during observation, evident primarily at the population level. SPL, in contrast, supported shared models across intended movement and observation formats at both single-unit and population levels. In variants with incongruent instructed and observed actions, SPL encoded observed actions only when behaviorally relevant, whereas MC remained intention-dominant. Our results identify a context-dependent gating mechanism in SPL and suggest a hierarchical organization in which MC maintains intention-specific codes while SPL flexibly links observed input with internal goals to support action understanding.

neuroscience↗

bioRxiv2025

VARS-fUSI: Variable Sampling for Fast and Efficient Functional Ultrasound Imaging using Neural Operators

Functional ultrasound imaging (fUSI) is a promising neuroimaging method that infers neural activity by detecting cerebral blood volume changes. It offers high sensitivity and spatial resolution relative to fMRI and is an epidural alternative to electrophysiology for medical and neuroscience applications, including brain-computer interfaces. However, current fUSI methods require hundreds of compounded images and ultrasound pulse emissions, leading to high computational costs, memory demands, and potential probe heating. We propose VARiable Sampling fUSI (VARS-fUSI), the first deep learning fUSI method to allow for different sampling durations and rates during training and inference by using neural operators. VARS-fUSI reconstructs high-quality fUSI images using 10 - 15% of the time or sampling rate needed per image while preserving decodable behavior-correlated signals. Additionally, VARS-fUSI offers efficient finetuning for generalization to new animals and humans. Demonstrated across mouse, monkey, and human data, VARS-fUSI achieves state-of-the-art performance, enhancing imaging efficiency by significantly reducing storage and processing needs.

bioengineering↗

bioRxiv2024

Functional ultrasound neuroimaging reveals mesoscopic organization of saccades in the lateral intraparietal area of posterior parietal cortex

The lateral intraparietal cortex (LIP) located within the posterior parietal cortex (PPC) is an important area for the transformation of spatial information into accurate saccadic eye movements. Despite extensive research, we do not fully understand the functional anatomy of intended movement directions within LIP. This is in part due to technical challenges. Electrophysiology recordings can only record from small regions of the PPC, while fMRI and other whole-brain techniques lack sufficient spatiotemporal resolution. Here, we use functional ultrasound imaging (fUSI), an emerging technique with high sensitivity, large spatial coverage, and good spatial resolution, to determine how movement direction is encoded across PPC. We used fUSI to record local changes in cerebral blood volume in PPC as two monkeys performed memory-guided saccades to targets throughout their visual field. We then analyzed the distribution of preferred directional response fields within each coronal plane of PPC. Many subregions within LIP demonstrated strong directional tuning that was consistent across several months to years. These mesoscopic maps revealed a highly heterogenous organization within LIP with many small patches of neighboring cortex encoding different directions. LIP had a rough topography where anterior LIP represented more contralateral upward movements and posterior LIP represented more contralateral downward movements. These results address two fundamental gaps in our understanding of LIPs functional organization: the neighborhood organization of patches and the broader organization across LIP. These findings were achieved by tracking the same LIP populations across many months to years and developing mesoscopic maps of direction specificity previously unattainable with fMRI or electrophysiology methods.

neuroscience↗

bioRxiv2024

Visual context affects the perceived timing of tactile sensations elicited through intra-cortical microstimulation

Intra-cortical microstimulation (ICMS) is a technique to provide tactile sensations for a somatosensory brain-machine interface (BMI). A viable BMI must function within the rich, multisensory environment of the real world, but how ICMS is integrated with other sensory modalities is poorly understood. To investigate how ICMS percepts are integrated with visual information, ICMS and visual stimuli were delivered at varying times relative to one another. Both visual context and ICMS current amplitude were found to bias the qualitative experience of ICMS. In two tetraplegic participants, ICMS and visual stimuli were more likely to be experienced as occurring simultaneously when visual stimuli were more realistic, demonstrating an effect of visual context on the temporal binding window. The peak of the temporal binding window varied but was consistently offset from zero, suggesting that multisensory integration with ICMS can suffer from temporal misalignment. Recordings from primary somatosensory cortex (S1) during catch trials where visual stimuli were delivered without ICMS demonstrated that S1 represents visual information related to ICMS across visual contexts.

neuroscience↗

bioRxiv2023

A window to the brain: ultrasound imaging of human neural activity through a permanent acoustic window

Recording human brain activity is crucial for understanding normal and aberrant brain function. However, available recording methods are either highly invasive or have relatively low sensitivity. Functional ultrasound imaging (fUSI) is an emerging technique that offers sensitive, large-scale, high-resolution neural imaging. However, fUSI cannot be performed through adult human skull. Here, we use a polymeric skull replacement material to create an acoustic window allowing ultrasound to monitor brain activity in fully intact adult humans. We design the window through experiments in phantoms and rodents, then implement it in a participant undergoing reconstructive skull surgery. Subsequently, we demonstrate fully non-invasive mapping and decoding of cortical responses to finger movement, marking the first instance of high-resolution (200 m) and large-scale (50 mmx38 mm) brain imaging through a permanent acoustic window.

neuroscience↗

bioRxiv2022

Decoding Motor Plans Using a Closed-Loop Ultrasonic Brain-Machine Interface

Brain-machine interfaces (BMIs) can be transformative for people living with chronic paralysis. BMIs translate brain signals into computer commands, bypassing neurological impairments and enabling people with neurological injury or disease to control computers, robots, and more with nothing but thought. State-of-the-art BMIs have already made this future a reality in limited clinical trials. However, high performance BMIs currently require highly invasive electrodes in the brain. Device degradation limits longevity to about 5 years. Their field of view is small, restricting the number, and type, of applications possible. The next generation of BMI technology should include being longer lasting, less invasive, and scalable to sense activity from large regions of the brain. Functional ultrasound neuroimaging is a recently developed technique that meets these criteria. In this present study, we demonstrate the first online, closed-loop ultrasonic brain-machine interface. We used 2 Hz real-time functional ultrasound to measure the neurovascular activity of the posterior parietal cortex in two nonhuman primates (NHPs) as they performed memory-guided movements. We streamed neural signals into a classifier to predict the intended movement direction. These predictions controlled a behavioral task in real-time while the NHP did not produce overt movements. Both NHPs quickly succeeded in controlling up to eight independent directions using the BMI. Furthermore, we present a simple method to "pretrain" the BMI using data from previous sessions. This enables the BMI to work immediately from the start of a session without acquiring extensive additional training data. This work establishes, for the first time, the feasibility of an ultrasonic BMI and prepares for future work on a next generation of minimally invasive BMIs that can restore function to patients with neurological, physical, or even psychiatric impairments.

neuroscience↗

bioRxiv2022

Cognition through internal models: Mirror neurons as one manifestation of a broader mechanism

Cognition relies on transforming sensory inputs into a more generalizable understanding. Mirror neurons are proposed to underlie this process, yet they fail to explain many key features of human thinking and learning. Here we hypothesize that mirror-like responses are one limited view into a more general framework by which internal models of the world are built and used. We recorded populations of single neurons in the human posterior parietal cortex as a participant felt or observed diverse tactile stimuli. We found that mirror-like responses were fragile and embedded within a richer population response that encoded generalizable and compositional features of the stimuli. We speculate that populations of neurons support versatile understanding, not through mirroring, but instead by encoding representational building blocks of cognition. One-Sentence SummarySimilar neural responses during observed and experienced sensations are mediated by shared compositional building blocks, not mirror neurons.

neuroscience↗

bioRxiv2022

S1 represents multisensory contexts and somatotopic locations within and outside the bounds of the cortical homunculus

The responsiveness of primary somatosensory cortex (S1) to physical tactile stimuli is well documented but the extent to which it is modulated by vision is unresolved. Additionally, recent literature has suggested that tactile events are represented in S1 in a more complex, generalized manner than its long-established topographic organization. To better characterize S1 function, neural activity was recorded from a tetraplegic patient implanted with microelectrode arrays in S1 during 1s stroking touches to the forearm (evoking numb sensation) or finger (naturalistic sensation). Touch conditions included visually observed first person physical touches, physical touches without vision, and visual touches without physical contact which occurred either to a third person, an inanimate object, or the patients own body in virtual reality. Two major findings emerged from this dataset. The first was that vision strongly modulates S1 activity, but only if there is a physical element to the touch, suggesting that passive observation of touches is not sufficient to recruit S1 neurons. The second was that despite the location of the recording arrays in a putative arm area of S1, neural activity was able to represent both arm and finger touches in physical touch conditions. Arm touches were encoded more strongly and specifically, supporting the idea that S1 encodes tactile events primarily through its topographic organization, as well as in a more general manner encompassing larger areas of the body.

neuroscience↗

bioRxiv2021

Decoding grasp and speech signals from the cortical grasp circuit in a tetraplegic human

Tetraplegia from spinal cord injury leaves many patients paralyzed below the neck, leaving them unable to perform most activities of daily living. Brain-machine interfaces (BMIs) could give tetraplegic patients more independence by directly utilizing brain signals to control external devices such as robotic arms or hands. The cortical grasp network has been of particular interest because of its potential to facilitate the restoration of dexterous object manipulation. However, a network that involves such high-level cortical areas may also provide additional information, such as the encoding of speech. Towards understanding the role of different brain areas in the human cortical grasp network, neural activity related to motor intentions for grasping and performing speech was recorded in a tetraplegic patient in the supramarginal gyrus (SMG), the ventral premotor cortex (PMv), and the somatosensory cortex (S1). We found that in high-level brain areas SMG and PMv, grasps were well represented by firing rates of neuronal populations already at visual cue presentation. During motor imagery, grasps could be significantly decoded from all brain areas. At identical neuronal population sizes, SMG and PMv achieved similar highly-significant decoding abilities, demonstrating their potential for grasp BMIs. During speech, SMG encoded both spoken grasps and colors, in contrast to PMv and S1, which were not able to significantly decode speech.These findings suggest that grasp signals can robustly be decoded at a single unit level from the cortical grasping circuit in human. Data from PMv suggests a specialized role in grasping, while SMGs role is broader and extends to speech. Together, these results indicate that brain signals from high-level areas of the human cortex can be exploited for a variety of different BMI applications.

neuroscience↗

bioRxiv2021

Preserved motor representations after paralysis

AO_SCPLOWBSTRACTC_SCPLOWNeural plasticity allows us to learn skills and incorporate new experiences. What happens when our lived experiences fundamentally change, such as after a severe injury? To address this question, we analyzed intracortical population activity in a tetraplegic adult as she controlled a virtual hand through a brain-computer interface (BCI). By attempting to move her fingers, she could accurately drive the corresponding virtual fingers. Neural activity during finger movements exhibited robust representational structure and dynamics that matched the representational structure, previously identified in able-bodied individuals. The finger representational structure was consistent during extended use, even though the structure contributed to BCI decoding errors. Our results suggest that motor representations are remarkably stable, even after complete paralysis. BCIs re-engage these preserved representations to restore lost motor functions.

neuroscience↗

bioRxiv2020

NEURAL ENCODING OF FELT AND IMAGINED TOUCH WITHIN HUMAN POSTERIOR PARIETAL CORTEX

In the human posterior parietal cortex (PPC), single units encode high-dimensional information with partially mixed representations that enable small populations of neurons to encode many variables relevant to movement planning, execution, cognition, and perception. Here we test whether a PPC neuronal population previously demonstrated to encode visual and motor information is similarly selective in the somatosensory domain. We recorded from 1423 neurons within the PPC of a human clinical trial participant during objective touch presentation and during tactile imagery. Neurons encoded experienced touch with bilateral receptive fields, organized by body part, and covered all tested regions. Tactile imagery evoked body part specific responses that shared a neural substrate with experienced touch. Our results are the first neuron level evidence of touch encoding in human PPC and its cognitive engagement during tactile imagery which may reflect semantic processing, sensory anticipation, and imagined touch.

neuroscience↗

bioRxiv2020

Single Trial Decoding of Movement Intentions Using Functional Ultrasound Neuroimaging

Brain-machine interfaces (BMI) are powerful devices for restoring function to people living with paralysis. Leveraging significant advances in neurorecording technology, computational power, and understanding of the underlying neural signals, BMI have enabled severely paralyzed patients to control external devices, such as computers and robotic limbs. However, high-performance BMI currently require highly invasive recording techniques, and are thus only available to niche populations. Here, we show that a minimally invasive neuroimaging approach based on functional ultrasound (fUS) imaging can be used to detect and decode movement intention signals usable for BMI. We trained non-human primates to perform memory-guided movements while using epidural fUS imaging to record changes in cerebral blood volume from the posterior parietal cortex - a brain area important for spatial perception, multisensory integration, and movement planning. Using hemodynamic signals acquired during movement planning, we classified left-cued vs. right-cued movements, establishing the feasibility of ultrasonic BMI. These results demonstrate the ability of fUS-based neural interfaces to take advantage of the excellent spatiotemporal resolution, sensitivity, and field of view of ultrasound without breaching the dura or physically penetrating brain tissue.

neuroscience↗