About

Andrew G. Richardson, Ph.D., is a Research Assistant Professor of Neurosurgery at the University of Pennsylvania's Perelman School of Medicine. He is a member of the Institute for Translational Medicine and Therapeutics as well as the Penn Center for Musculoskeletal Disorders. His research expertise encompasses neuroengineering, neuroscience, and brain-machine interfaces. Dr. Richardson's work involves the development and application of advanced neural interfaces and neuromodulation techniques, contributing to the fields of neural dynamics, implantable devices, and closed-loop brain modulation systems. His educational background includes a B.S.E. in Biomedical Engineering from Case Western Reserve University, an S.M. in Mechanical Engineering, and a Ph.D. in Biomedical Engineering from the Massachusetts Institute of Technology. His research outputs include innovations in wireless neural devices, multimodal neural mapping, neuroprosthetic systems, and implantable tactile sensors, reflecting a focus on translating engineering solutions into clinical and experimental neuroscience applications.

Research topics

• Computer science
• Neuroscience
• Psychology
• Materials science
• Medicine

Selected publications

• Thalamus: a real-time system for synchronized, closed-loop multimodal behavioral and electrophysiological data capture

  Communications Engineering · 2026-03-26

  articleOpen access

  Precise and synchronized multimodal data capture in neurosurgical environments is essential for further understanding brain function and will be crucial to advancing the development of brain-computer interface technology. We have developed an open-source software platform named Thalamus, for multimodal data capture integrated with existing sensors and hardware commonly utilized in the operating room and other clinical environments such as pulse oximeters, inertial sensors, electromyography and neural electrophysiology. Thalamus facilitates synchronous recording of neural and behavioral data, enabling real-time computation for closed-loop experiments and detailed analysis of complex motor functions and neural activity. Thalamus uses a modular, configurable node-based pipeline with a tiered Python and C + + architecture. These design elements allow Thalamus to support a wide range of high-resolution sensors for diverse behavioral data types and enable robust closed-loop synchronization of various data streams. Validation experiments demonstrate that Thalamus is capable of data integration and concurrent analysis with up to sub-millisecond precision, offering great potential for enhancing neurosurgical research and clinical applications. By leveraging conventional sensors and hardware already in use, Thalamus supports adoption into the clinical environment, paving the way for more comprehensive, data-driven approaches to neurological care and improving the personalization and rigor of treatment strategies.

  PublisherDOI

• Optical transparent packages for implantable devices

  2025-03-19

  article

  We present a carbon dioxide (CO2) laser-assisted simultaneous localized fusion bonding and dicing technology on fused silica wafer. Direct bonding of fused silica wafer stacks results in an optically transparent package without introducing intermediate bonding layers. The temperature inside the package is maintained below 400 °C during the fabrication process to preserve complementary metal-oxide-semiconductor (CMOS)- compatibility. Such fused silica packages have many favorable features such as optical transparency for packaging micro-opto-electro-mechanical systems (MOEMS), biocompatibility and hermeticity for implantation applications, and transparency at radio frequencies for encapsulating electronics for wireless power and signal transmission. We applied this localized fusion bonding technology to encapsulate humidity sensors, evaluating the hermeticity and suggesting an implantation lifespan of over 70 years in the human body. Furthermore, we extended its application to vacuum packages and implantable tactile sensing systems to restore hand function for individuals with paralysis.

  PublisherDOI

• 1292 Circuitry of the Preparatory Period: A Role for Thalamocortical Circuit Dynamics in Optimizing Spontaneous Attentional Control Prior to Cognitive Engagement

  Neurosurgery · 2025-03-14

  article

  INTRODUCTION: Human cognition involves the complex coordination of interconnected networks, where pre-task spontaneous network states can prime brain performance. Thalamocortical communication is known to be a crucial element of attentional processes. METHODS: We employed a temporal expectancy task in 24 humans and 6 wild-type mice, consisting of an initial cue followed by a go cue separated by a variable time interval, and a response to the go cue. Human subjects were implanted with iEEG, and mice were injected with a fluorescent Ca2+ indicator (GCAMP6m) in the mediodorsal thalamus (MD), with neural activity subsequently recorded using fiber photometry in MD and prefrontal cortex (PFC). RESULTS: In humans, spectral power and graph communicability (Qexp) were calculated for each of four canonical frequency bands within 500 ms before the initial cue or the go cue. We streamlined the feature space by bootstrapping univariate linear regressions 1000 times, selecting features significantly correlated to reaction time (RT) in over 35% of iterations. A rank-sum test identified anatomical regions consistently predicting RT across subjects by comparing selected and non-selected features. Low frequency TC white matter Qexp predicted upcoming RT in the preparatory period while high frequency spectral activity predicted RT in the anticipatory period. In mice, activity in MD-PFC projections correlated strongly with RT. In trials with the fastest RTs (0-20ms), TC activity surged approximately 4s prior to initial cue onset as well prior to the go cue, compared to other trials (20-500ms) (p<0.001). When comparing the fastest vs. the slowest third of trials with RT<100ms, activity significantly increased for the fastest trials in the preparatory period but not the anticipatory period (p<0.001). CONCLUSIONS: These findings indicate that enhanced TC communication primes mammalian neural circuitry during the preparatory period for optimal performance.

  PublisherDOI

• 15.4 A Neuroprosthetic SoC with Sensory Feedback Featuring Frequency-Splitting-Based Wireless Power Transfer with 200Mb/s 0.67pJ/b Backscatter Data Uplink and Unsupervised Multi-Class Spike Sorting

  2025-02-16 · 4 citations

  article

  Neuroprosthetic technology has made significant strides in restoring movement for paralyzed individuals by decoding motor cortex signals into commands for prosthetic limbs or exoskeletons. Although high-channel neural implants have enhanced prosthetic control and freedom of movement, the benefits of channel scaling are restricted by the absence of feedback and the steep learning curves required for users. To address this, sensory feedback from prosthetic sensors has been used to modulate the sensory cortex for more stable and accurate prosthetic control [1]. However, latency in data transmission, decoding, and feedback mapping hinders the system's effectiveness as a true closed-loop. To overcome these challenges, a disruptive approach has emerged that introduces rapid local feedback between the motor and sensory cortices [2]. Instead of relying on external sensor inputs, this method derives sensory feedback directly from motor signals and modulates stimulation in the sensory cortex, reducing latency and simplifying learning (Fig. 15.4.1 top). Animal studies using optogenetic feedback have shown faster motor target acquisition with this internal feedback [3]. While optogenetics cannot be easily adopted for humans, electrical stimulation is a viable alternative, though it presents challenges such as rejecting stimulation artifacts to avoid false modulation or positive feedback loops.

  PublisherDOI

• Transparent MXene Microelectrode Arrays for Multimodal Mapping of Neural Dynamics (Adv. Healthcare Mater. 4/2025)

  Advanced Healthcare Materials · 2025-02-01 · 1 citations

  article
  PublisherDOI

• Subdermal Insertable Sensors: Characteristics and Applications

  2025-11-21

  articleOpen accessSenior author

  Continuous monitoring of chronic diseases with mobile health tools is rapidly advancing to improve patient care. Wearable sensors placed on or near the skin remain the dominant paradigm for collecting physiological data noninvasively during activities of daily living. However, wearable sensors have their limitations. Epidermal sensors are fundamentally limited by the information barrier that the skin presents. Furthermore, environmental factors impact stability and longevity of wearables. An alternative technology is the expanding class of minimallyinvasive subdermal sensors, also called insertables. Characteristics of insertable sensors are reviewed, emphasizing state-of-theart approaches for achieving biocompatibility, remote powering, and wireless data transmission from their location under the skin. Next, key applications for subdermal sensors are analyzed, including three current clinical devices: insertable cardiac monitors, insertable continuous glucose monitors, and sub-scalp epilepsy monitors. Finally, future directions for material and system innovations, addressing challenges such as fibrotic encapsulation and energy efficiency, are explored to suggest potential next-generation subdermal biosensors that address unmet needs in chronic disease monitoring.

  PublisherOA PDFDOI

• Human response times are governed by dual anticipatory processes with distinct neural signatures

  Communications Biology · 2025-01-26 · 4 citations

  articleOpen access

  Human behavior is strongly influenced by anticipation, but the underlying neural mechanisms are poorly understood. We obtained intracranial electrocephalography (iEEG) measurements in neurosurgical patients as they performed a simple sensory-motor task with variable (short or long) foreperiod delays that affected anticipation of the cue to respond. Participants showed two forms of anticipatory response biases, distinguished by more premature false alarms (FAs) or faster response times (RTs) on long-delay trials. These biases had distinct neural signatures in prestimulus neural activity modulations that were distributed and intermixed across the brain: the FA bias was most evident in preparatory motor activity immediately prior to response-cue presentation, whereas the RT bias was most evident in visuospatial activity at the beginning of the foreperiod. These results suggest that human anticipatory behavior emerges from a combination of motor-preparatory and attention-like modulations of neural activity, implemented by anatomically widespread and intermixed, but functionally identifiable, brain networks.

  PublisherOA PDFDOI

• Sensing Potential, Scientists Refine Thermal Imaging of Ecosystems

  Eos · 2025-02-07 · 1 citations

  articleOpen accessSenior author

  At a recent “bake-off,” researchers judged thermal infrared cameras and developed guidelines for their consistent use in studying vegetation temperatures, which illuminate vital ecosystem processes.

  PublisherDOI

• 33.4 A Multi-Loop Neuromodulation Chipset Network with Frequency-Interleaving Front-End and Explainable AI for Memory Studies in Freely Behaving Monkeys

  2024-02-18 · 4 citations

  article

  Alzheimer’s disease (AD), a common cause of dementia, affects over 30 million people worldwide and accounts for more than 1% of the global GDP [1]. Given that age is a significant risk factor, the number of AD patients is projected to double in the next two decades. While there is currently no cure for AD, increasing evidence suggests that electrical brain stimulation is a potential treatment [2]. The hippocampus (HC) is a critical brain region that exhibits specific rhythmic neural activities during memory encoding and consolidation. In-phase stimulation has the potential to entrain and amplify these rhythms, thereby enhancing memory formation and retrieval. Consequently, innovative stimulation protocols are being developed to treat AD by modulating the HC and its associated brain regions.

  PublisherDOI

• A Biocompatible Glass-Encapsulated Triaxial Force Sensor For Implantable Tactile Sensing Applications

  2024-01-21

  articleOpen access

  This paper reports a microfabricated triaxial capacitive force sensor. The sensor is fully encapsulated with inert and biocompatible glass (fused silica) material. The sensor comprises two glass plates, on which four capacitors are located. The sensor is intended for subdermal implantation in fingertips and palms and providing tactile sensing capabilities for patients with paralyzed hands. Additional electronic components, such as passives and IC chips, can also be integrated with the sensor in a hermetic glass package to achieve an implantable tactile sensing system. Through attachment to a human palm, the sensor has been shown to respond appropriately to typical hand actions, such as squeezing or picking up a bottle.

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: Continental-Scale Monitoring, Modeling and Forecasting of Phenological Responses to Climate Change

  NSF · $1.3M · 2011–2017

Frequent coauthors

• Timothy H. Lucas

  Neurotech (United States)

  89 shared

• Jan Van der Spiegel

  University of Pennsylvania

  41 shared

• Xilin Liu

  38 shared

• Flavia Vitale

  Translational Therapeutics (United States)

  27 shared

• Milin Zhang

  Tsinghua University

  24 shared

• Emilio Bizzi

  McGovern Institute for Brain Research

  22 shared

• Brendan B. Murphy

  Translational Therapeutics (United States)

  20 shared

• Brian Litt

  20 shared

Education

• PhD, Biomedical Engineering

  Massachusetts Institute of Technology

  2007

• SM, Mechanical Engineering

  Massachusetts Institute of Technology

  2003

• BSE, Biomedical Engineering

  Case Western Reserve University

  2000