Biology subjects

Hansma, P. K.

Publications and source records attributed to Hansma, P. K..

6 recordsLinked to original sources

bioRxiv2026

A recurrent neural network model of chronic pain development and recovery

Chronic pain presents a leading challenge in the world today for both clinicians and researchers. Because chronic pain is difficult to explain and treat, it is often managed with opioids despite providing limited relief and contributing to dependence and misuse. Persistent pain can be maintained by altered central nervous system processing even in the absence of distinct tissue damage or disease, which may limit the efficacy of conventional pharmacological therapies that target nociceptive signal transmission rather than maladaptive central nervous system dynamics often present in those with chronic pain. Although neuroimaging studies have identified this shift from nociceptive to emotional circuits during pain chronification, a quantitative framework linking these neural changes to longitudinal pain trajectories or recovery is lacking. We present a parsimonious firing-rate model that can account for the development of and recovery from chronic pain, which is based on the theoretical framework established by Wilson and Cowan. The model provides a quantitative explanation of how sensitization, anxiety, and fear maintain pain even after an injury has healed, and how calming stimulus downregulates these processes to facilitate recovery. A study applying the same principles as the model produced an average pain decrease of 3.5 on the Visual Analog Scale (VAS), with all subjects experiencing a reduction in pain. These results, coupled with our model and findings in prior studies, suggest that increasing calming stimulus can reduce pain without necessitating pharmacological or invasive, resource-intensive interventions.

neuroscience↗

bioRxiv2024

RT-Sort: an action potential propagation-based algorithm for real time spike detection and sorting with millisecond latencies

With the use of high density multi electrode recording devices, electrophysiological signals resulting from action potentials of individual neurons can now be reliably detected on multiple adjacent recording electrodes both in vivo and in vitro. Spike sorting assigns these signals to putative neural sources. However, until now, spike sorting can only be performed after completion of the recording, preventing true real time usage of spike sorting algorithms. Utilizing the unique propagation patterns of action potentials along axons detected as high fidelity sequential activations on adjacent electrodes, together with a convolutional neural network based spike detection algorithm, we introduce RT-Sort (Real Time Sorting), a spike sorting algorithm that enables the sorted detection of action potentials within 7.5ms{+/-}1.5ms (mean{+/-}STD) after the waveform trough while the recording remains ongoing. RT-Sorts true real-time spike sorting capabilities enable closed loop experiments with latencies comparable to synaptic delay times. We show RT-Sorts performance on both Multi-Electrode Arrays as well as Neuropixels probes to exemplify RT-Sorts functionality on different types of recording hardware and electrode configurations.

neuroscience↗

bioRxiv2023

Protosequences in human cortical organoids model intrinsic states in the developing cortex

Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human and murine brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human and murine brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development.

neuroscience↗

bioRxiv2021

Intrinsic network activity in human brain organoids

Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arrays (26,400 electrodes) and shank electrodes (960 electrodes), we probed broadband and three-dimensional extracellular field recordings generated by spontaneous activity of human brain organoids. These recordings simultaneously captured local field potentials (LFPs) and single-unit activity extracted through spike sorting. From spiking activity, we estimated a directed functional connectivity graph of synchronous neural network activity, which showed a large number of weak functional connections enmeshed within a network skeleton of significantly fewer strong connections. Treatment of the organoid with a benzodiazepine induced a reproducible signature response that shortened the inter-burst intervals, increased the uniformity of the firing pattern within each burst and decreased the population of weakly connected edges. Simultaneously examining the spontaneous LFPs and their phase alignment to spiking showed that spike bursts were coherent with theta oscillations in the LFPs. Our results demonstrate that human brain organoids have self-organized neuronal assemblies of sufficient size, cellular orientation, and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug mechanisms, and the effects of external stimuli upon neuronal networks.

neuroscience↗

bioRxiv2017

MEA Viewer: a High-performance Interactive Application for Visualizing Electrophysiological Data

Multi-electrode arrays (MEAs) have been used for many years to measure electrical activity in ensembles of many hundreds of neurons, and are used in research areas as diverse as neuronal connectivity and drug discovery. A high sampling frequency is required to adequately capture action potentials, also known as spikes, the primary electrical event associated with neuronal activity, and the resulting raw data files are large and difficult to visualize with traditional plotting tools. Many common approaches to deal with this issue, such as extracting spikes times and solely performing spike train analysis, significantly reduce data dimensionality. Unbiased data exploration benefits from the use of tools that minimize data transforms and such tools enable the development of heuristic perspective from data prior to any subsequent processing. Here we introduce MEA Viewer, a high-performance interactive application for the direct visualization of multi-channel electrophysiological data. MEA Viewer provides many high-performance visualizations of electrophysiological data, including an easily navigable overview of all recorded extracellular signals overlaid with spike timestamp data and an interactive raster plot. Beyond the fundamental data displays, MEA Viewer can signal average and spatially overlay the extent of action potential propagation within single neurons. This view extracts information below the spike detection threshold to directly visualize the propagation of action potentials across the plane of the MEA. This entirely new method of using MEAs opens up new and novel research applications for medium density arrays. MEA Viewer is licensed under the General Public License version 3, GPLv3, and is available at http://github.com/dbridges/mea-tools.

neuroscience↗

bioRxiv2017

Recording action potential propagation in single axons using multi-electrode arrays

The small caliber of central nervous system (CNS) axons makes routine study of axonal physiology relatively difficult. However, while recording extracellular action potentials from neurons cultured on planer multi-electrode arrays (MEAs) we found activity among groups of electrodes consistent with action potential propagation in single neurons. Action potential propagation was evident as widespread, repetitive cooccurrence of extracellular action potentials (eAPs) among groups of electrodes. These eAPs occurred with invariant sequences and inter-electrode latencies that were consistent with reported measures of action potential propagation in unmyelinated axons. Within co-active electrode groups, the inter-electrode eAP latencies were temperature sensitive, as expected for action potential propagation. Our data are consistent with these signals primarily reflecting axonal action potential propagation, from axons with a high density of voltage-gated sodium channels. Repeated codetection of eAPs by multiple electrodes confirmed these eAPs are from individual neurons and averaging these eAPs revealed sub-threshold events at other electrodes. The sequence of electrodes at which eAPs co-occur uniquely identifies these neurons, allowing us to monitor spiking of single identified neurons within neuronal ensembles. We recorded dynamic changes in single axon physiology such as simultaneous increases and decreases in excitability in different portions of single axonal arbors over several hours. Over several weeks, we measured changes in inter-electrode propagation latencies and ongoing changes in excitability in different regions of single axonal arbors. We recorded action potential propagation signals in human induced pluripotent stem cell-derived neurons which could thus be used to study axonal physiology in human disease models.\n\nSignificance StatementStudying the physiology of central nervous system axons is limited by the technical challenges of recording from axons with pairs of patch or extracellular electrodes at two places along single axons. We studied action potential propagation in single axonal arbors with extracellular recording with multi-electrode arrays. These recordings were non-invasive and were done from several sites of small caliber axons and branches. Unlike conventional extracellular recording, we unambiguously identified and labelled the neuronal source of propagating action potentials. We manipulated and quantified action potential propagation and found a surprisingly high density of axonal voltage-gated sodium channels. Our experiments also demonstrate that the excitability of different portions of axonal arbors can be independently regulated on time scales from hours to weeks.

neuroscience↗