Biology subjects

Pejsa, K.

Publications and source records attributed to Pejsa, K..

12 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

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↗

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

Neural subspaces of imagined movements in parietal cortex remain stable over several years in humans.

A crucial goal in brain-machine interfacing is long-term stability of neural decoding performance, ideally without regular retraining. Here we demonstrate stable neural decoding over several years in two human participants, achieved by latent subspace alignment of multi-unit intracortical recordings in posterior parietal cortex. These results can be practically applied to significantly expand the longevity and generalizability of future movement decoding devices.

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↗

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

Neural correlates of cognitive motor signals in primary somatosensory cortex.

Classical systems neuroscience positions primary sensory areas as early feed-forward processing stations for refining incoming sensory information. This view may oversimplify their role given extensive bi-directional connectivity with multimodal cortical and subcortical regions. Here we show that single units in human primary somatosensory cortex encode imagined reaches centered on imagined limb positions in a cognitive motor task. This result suggests a broader role of primary somatosensory cortex in cortical function than previously demonstrated.

neuroscience↗