Biology subjects

Christopoulos, V.

Publications and source records attributed to Christopoulos, V..

10 recordsLinked to original sources

bioRxiv2026

Distributed brain-spinal cord dynamics during micturition revealed by functional ultrasound imaging

Micturition relies on coordinated activity across distributed neural circuits spanning the brain and spinal cord, yet the spatiotemporal dynamics of these processes remain poorly understood. Disruption of these pathways in conditions such as spinal cord injury, Parkinson's disease, multiple sclerosis, and aging can lead to neurogenic bladder dysfunction. Here, we used functional ultrasound imaging (fUSI), a modality with high spatiotemporal resolution and single-trial sensitivity, to investigate central nervous system activity during micturition. In anesthetized rats undergoing controlled bladder filling and volitional voiding, we recorded power Doppler signals from either the brain or the lumbosacral spinal cord. We observed distinct, region-specific hemodynamic responses associated with micturition across multiple brain regions, including the thalamus, hypothalamus, midbrain, and neocortex - particularly sensorimotor and retrosplenial areas - as well as dorsal and ventral spinal cord circuits. Furthermore, population-level activity in these regions enabled accurate decoding of bladder pressure dynamics. These results provide a systems-level characterization of central nervous system activity during micturition and establish fUSI as a platform for developing neural interfaces to restore bladder control.

bioengineering↗

bioRxiv2025

An integrative computational approach for obstacle avoidance during action selection

Action selection in cluttered environments, where individuals must simultaneously pursue goals and avoid obstacles, presents a significant challenge for the brain. To understand the underlying mechanisms of action selection in such contexts, we propose a computational model that extends stochastic optimal control theory through a novel framework for obstacle avoidance. The model decomposes action selection as a weighted combination of individual control policies, each generated for either target approach or obstacle avoidance. By integrating value information from goals, obstacles, and actions into a unified measure of "relative desirability", the model dynamically determines the contribution of each policy to the overall action selection process. We evaluated the framework using simulated target-reaching tasks in cluttered environments based on previous human studies. The results showed that the model captures key features of human motor behavior, including the influence of obstacle properties on movement trajectories and the transient tendency to initiate movements toward obstacles before avoidance. This work offers new insights into the dynamic interaction between approach and avoidance behaviors, providing a comprehensive framework for understanding action selection in complex and naturalistic settings. Author SummaryEvery day, we make countless movements that require us to reach for something while avoiding obstacles--for example, grabbing a cup without knocking over nearby objects. How the brain selects such actions in cluttered environments remains poorly understood. In this study, we developed a computational model that explains how people plan and control movements when both goals and obstacles are present. Our model assumes that the brain prepares multiple potential actions at once--some for reaching the goal and others for avoiding obstacles--and then combines them based on how desirable each option is at any moment. Using computer simulations of reaching movements, we found that the model reproduced key patterns observed in human behavior, including the brief tendency to move toward an obstacle before steering away from it. By showing how the brain might continuously balance approach and avoidance drives, our work offers a new way to understand how people make rapid and flexible movement decisions in complex, everyday settings.

neuroscience↗

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↗

bioRxiv2023

Computational mechanism underlying switching of motor plans

Surviving in a constantly changing environment requires not only the ability to select actions, but also the flexibility to stop and switch actions when necessary. Extensive research has been devoted to understanding how the brain switches actions, yet the computations underlying switching and how it relates to selecting and stopping processes remain elusive. A central question is whether switching is an extension of the stopping process or involves different mechanisms. To address this question, we modeled action regulation tasks with a neurocomputational theory and evaluated its predictions on individuals performing reaches in a dynamic environment. Our findings suggest that, unlike stopping, switching does not necessitate a proactive pause mechanism to delay movement onset. However, switching engages a pause mechanism after movement onset, if the new target location is unknown prior to switch signal. These findings offer a new understanding of the action-switching computations, opening new avenues for future neurophysiological investigations.

neuroscience↗

bioRxiv2023

Comparison of image registration techniques in functional ultrasound imaging

Functional Ultrasound Imaging (fUSI) is an emerging hemodynamic-based functional neuroimaging technique that combines high spatiotemporal resolution and sensitivity, as well as extensive brain coverage, enabling a range of applications in both control and disease animal models. Based on power Doppler (pD) imaging, fUSI measures changes in cerebral blood volume (CBV) by detecting the back-scattered echoes from red blood cells moving within its field of view (FOV). However, the expansion of fUSI technology is partly limited by the challenge to co-register pD vascular maps acquired across different sessions or animals to one reference; an approach that could widen the scope of experimental paradigms and enable advanced data analysis tools. In this study, we seek to address this critical limitation. We evaluate six image registration techniques, predominantly used in other neuroimaging studies, using 2D sagittal whole-brain fUSI data from 82 anesthetized mice, and tested the quality of registration using multiple metrics. Our findings indicate a substantial enhancement in the alignment of fUSI images post registration. Among the tested techniques, the non-rigid registration algorithm Imregdeform yielded superior performance. We offer the first comparative study of image registration techniques for a 2D fUSI brain dataset, paving a way for improved utilization of fUSI in future pre-clinical research applications.

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↗

bioRxiv2023

Frequency- and circuit- specific effects of septohippocampal deep brain stimulation in mice as measured by functional ultrasound imaging.

BackgroundDeep brain stimulation (DBS) has shown remarkable success in treating neurological and psychiatric disorders such as Parkinsons disease, dystonia, epilepsy, and obsessive-compulsive disorder. Despite this success, the underlying mechanism of action remains unknown. DBS is now being explored to improve functional outcomes in other psychiatric conditions, such as those characterized by reduced N-methyl-D-aspartate (NMDA) function (i.e. schizophrenia). While DBS for movement disorders requires high-frequency continuous stimulation, there is evidence that intermittent low-frequency stimulation in neuropsychiatric conditions may have persisting cognitive benefits, necessitating a broader exploration of how DBS alters brain networks. ObjectiveWe characterize the effects of pharmacologic NMDA antagonism on the septohippocampal network and the impact of high- and low-frequency MSN DBS on cerebral blood volume (CBV) in brain structures within and outside of the septohippocampal network. MethodsIn this study, we utilize a novel technology, functional ultrasound imaging (fUSI), to characterize the cerebrovascular impact of medial septal nucleus (MSN) DBS under conditions of NMDA antagonism (pharmacologically using Dizocilpine [MK-801]) in anesthetized male mice. ResultsImaging from a sagittal plane across a variety of brain regions, we find that MSN theta-frequency (7.7Hz) DBS has a larger effect on hippocampal CBV after stimulation offset. This is observed following an intraperitoneal (i.p.) injection of either saline vehicle or MK-801 (1 mg/kg). This effect is not present using standard high-frequency DBS stimulation parameters (i.e. gamma [100Hz]). ConclusionThese results indicate the MSN DBS increases circuit-specific hippocampal neurovascular activity in a frequency-dependent manner that continues beyond the period of electrical stimulation.

neuroscience↗

bioRxiv2022

Functional Ultrasound Imaging of the Human Spinal Cord

The integration of functional responses in the human spinal cord into the nervous system is not well understood. Herein we demonstrate the first in-human functional ultrasound imaging (fUSI) of spinal cord response to epidural electrical stimulation. fUSI is a minimally invasive neuroimaging technique that can record blood flow at a level of spatial and temporal precision not previously achieved in the human spinal cord. By leveraging fUSI and epidural electrical spinal cord stimulation in patients who underwent surgery, we recorded and characterized for the first-time hemodynamic responses of the human spinal cord to an electrical neuromodulatory intervention commonly used for treating pain, and increasingly used for sensory-motor and autonomic functions. We found that the hemodynamic response to epidural stimulation reflects a spatiotemporal modulation of the spinal cord circuitry not previously recognized. The impact of this analytical capability is significant for several reasons. It offers a mechanism to assess blood flow changes with a new level of precision which can be obtained in real time under in vivo conditions. Additionally, we demonstrate that fUSI can successfully decode the spinal cord state in a single trial, which is of fundamental importance for developing real-time closed-loop neuromodulation systems. Also, we show that spinal cord hemodynamic changes due to epidural electrical stimulation occur primarily at the level of small vessels. Overall, our work is a critical step towards developing a vital technique to study spinal cord function and understand the potential effects of clinical neuromodulation for spinal cord and other neurological disorders. One Sentence SummaryThe first in-human quantitative evaluation of spinal cord hemodynamics using functional ultrasound imaging (fUSI).

bioengineering↗

bioRxiv2022

A neurocomputational theory of action regulation predicts motor behavior in neurotypical individuals and patients with Parkinsons disease

Surviving in an uncertain environment requires not only the ability to select the best action, but also the flexibility to withhold inappropriate actions when the environmental conditions change. Although selecting and withholding actions have been extensively studied in both human and animals, there is still lack of consensus on the mechanism underlying these action regulation functions, and more importantly, how they inter-relate. A critical gap impeding progress is the lack of a computational theory that will integrate the mechanisms of action regulation into a unified framework. The current study aims to advance our understanding by developing a neurodynamical computational theory that models the mechanism of action regulation that involves suppressing responses, and predicts how disruption of this mechanism can lead to motor deficits in Parkinsons disease (PD) patients. We tested the model predictions in neurotypical individuals and PD patients in three behavioral tasks that involve free action selection between two opposed directions, action selection in the presence of conflicting information and abandoning an ongoing action when a stop signal is presented. Our results and theory suggest an integrated mechanism of action regulation that affects both action initiation and inhibition. When this mechanism is disrupted, motor behavior is affected, leading to longer reaction times and higher error rates in action inhibition. Author SummaryHumans can rapidly regulate actions according to updated demands of the environment. A key component of action regulation is action inhibition, the failure of which contributes to various neuropsychiatric disorders. When faced with multiple choices, dealing with conflicting information, or current actions become inappropriate or unwanted, we should be able to pause or completely abandon actions. Despite extensive efforts to understand how the brain selects, pauses, and abandons actions based on environmental demands, the mechanisms underlying these action regulation functions and, perhaps more importantly, how they inter-relate remain elusive. Part of this challenge lies in the fact that these mechanisms were rarely explored together, making it difficult to develop a unified theory that explains the computational aspects of action regulation functions. The current study introduces a large-scale model that better characterizes the computations of action regulation functions, how they are implemented within brain networks that involve frontal, motor and basal ganglia (BG) circuits, and how disruption of these circuits can lead to deficits in motor behavior seen in Parkinsons disease (PD).The model was developed by studying the motor behavior of healthy individuals and PD patients in three motor tasks that involve action inhibition. Overall, the model explains many key aspects on how the brain regulates actions that involve inhibitory processes, opening new avenues for improving and developing therapeutic interventions for diseases that may involve these circuits.

neuroscience↗

bioRxiv2017

What if you are not certain? A common computation underlying action selection, reaction time and confidence judgment

From what to wear to a friends party, to whether to stay in academia or pursue a career in industry, nearly all of our decisions are accompanied by a degree of confidence that provides an assessment of the expected outcome. Although significant progress has been made in understanding the computations underlying confidence judgment, the preponderance of studies focuses on perceptual decisions, in which individuals sequentially sample noisy information and accumulate it as evidence until a threshold is exceeded. Once a decision is made, they initiate an action to implement the choice. However, we often have to make decisions during ongoing actions in dynamic environments where the value and the availability of the alternative options can change with time and previous actions. The current study aims to decipher the computations underlying confidence judgment in action decisions that are made in a dynamic environment. Using a reaching task in which movements are initiated to multiple potential targets, we show that action selection, reaction time and choice confidence all emerge from a common computation in which parallel prepared actions compete based on the overall desirability of targets and action plans.

neuroscience↗