Biology subjects

Clawson, W.

Publications and source records attributed to Clawson, W..

6 recordsLinked to original sources

bioRxiv2026

Goal directed closed-loop training of network bursts in cortical cultures produces improved performance and error correction over days

Dissociated neural cultures are living systems with no evolutionary history in their current form, which makes them a testbed for asking what goals neural tissue can learn to pursue once it is removed from its evolved body. It remains unclear which features of network activity such a culture can be trained to control, and whether that training is retained from one day to the next. We built an open-source closed-loop platform, the Holistic Agential Learning platform (HAL), that detects a network burst on a high-density microelectrode array, estimates its spatial origin in real time, and applies a minimal reinforcement rule. Here, a burst that originates off the goal side triggers global random stimulation that persists until the next burst. Over days of training, rat cortical cultures (n=10) increased the fraction of bursts that initiated on the goal side. This gain accrued between sessions, with little change within a session, a consolidation-like pattern that we interpret as a statement about timescale while the mechanism remains untested. The burst origin moved toward the goal side, while the burst peak and the repertoire of propagation directions were preserved. Trained cultures also recovered from incorrect states more reliably over days, while the rate at which they entered those states was unchanged, and this recovery effect was the most robust difference from unstimulated controls (n=6). Cultures that began on either side of chance converged to a similar level of performance. Damaged cultures (n=6) with comparable burst statistics showed neither the across-day gain nor the consolidation-like pattern. Training reweighted the activity patterns each culture already had, and we saw no new ones, which we read as a simple form of niche construction in which the tissue keeps a trace of its history that biases what it does next. These results identify burst initiation and error recovery as trainable variables in a novel living system, and they support training the tissue rather than engineering the machine.

bioengineering↗

bioRxiv2025

Ephaptic-Axonal Interactions Shape Radial Biases DuringNeural Self-Organization

Communication in the brain seems to not just be mediated by axonal action potential transmission resulting in post synaptic modulations, but also by electrical field effects of depolarizing neurons, i.e. ephaptic coupling. The significant role of ephaptic coupling in synchronizing neural ensembles has been conjectured to indirectly affect ontogenetic neural circuit development through sub threshold impacts on spike timing. We therefore hypothesized synchronously firing ensembles to emerge at spatial distances where ephaptic and axonal signals were most temporally correlated. To test our model of ephaptic axonal interactions during neural self-organization, we compared its predictions to developmental outcomes of cortical rat tissue on high-density multielectrode arrays in vitro. We observed a cosinusoidal variation of synchronous activity over radial distances that can be understood to result from the joint effects of ephaptic and axonal signals during gamma-band bursts. Recurrent amplification of this theorized interaction effect during ontogenetic differentiation appears to radially bias the spectral profile of neural activity in the spatial distribution of neural ensembles. While long- term plasticity has been conventionally attributed to synaptic action alone, we show that that the interaction effects with ephaptic waves deserve further investigation.

neuroscience↗

bioRxiv2025

Triple-Negative Breast Cancer Cells Activate Sensory Neurons via TRPV1 to Drive Nerve Outgrowth and Tumor Progression

The tumor microenvironment in triple-negative breast cancer (TNBC) is characterized by increased sensory nerve density, which contributes to cancer progression by promoting migration and metastasis. However, the origin of tumor-innervating nerves and the mechanisms driving sensory innervation into tumors remain poorly understood. Using in vivo retrograde labeling techniques, we show that mammary tumors are associated with an increase in nerves originating from the dorsal root ganglia. Additionally, we find that TNBC cells trigger stress and activation markers and induce neuronal firing in a transient receptor potential anilloid subtype 1 (TRPV1)-dependent manner. In both 2D and 3D cell culture models, TNBC cells promote outgrowth of sensory nerves that is abrogated with Trpv1 knockout. We identified c-Jun and IL-6 as an effector of neurite outgrowth that acts downstream of TRPV1 to promote outgrowth in vitro. Finally, in Trpv1 knockout mice, TNBC tumors exhibit delayed growth and reduced lung metastasis. These findings suggest that a critical role for TRPV1 in tumor-nerve crosstalk, offering a potential target to reduce metastatic disease.

cancer biology↗

bioRxiv2021

Disordered information processing dynamics in experimental epilepsy

Neurological disorders share common high-level alterations, such as cognitive deficits, anxiety, and depression. This raises the possibility of fundamental alterations in the way information conveyed by neural firing is maintained and dispatched in the diseased brain. Using experimental epilepsy as a model of neurological disorder we tested the hypothesis of altered information processing, analyzing how neurons in the hippocampus and the entorhinal cortex store and exchange information during slow and theta oscillations. We equate the storage and sharing of information to low level, or primitive, information processing at the algorithmic level, the theoretical intermediate level between structure and function. We find that these low-level processes are organized into substates during brain states marked by theta and slow oscillations. Their internal composition and organization through time are disrupted in epilepsy, loosing brain state-specificity, and shifting towards a regime of disorder in a brain region dependent manner. We propose that the alteration of information processing at an algorithmic level may be a mechanism behind the emergent and widespread co-morbidities associated with epilepsy, and perhaps other disorders.

neuroscience↗

bioRxiv2020

Dynamic core-periphery structure of information sharing networks in entorhinal cortex and hippocampus

Neural computation is associated with the emergence, reconfiguration and dissolution of cell assemblies in the context of varying oscillatory states. Here, we describe the complex spatio-temporal dynamics of cell assemblies through temporal network formalism. We use a sliding window approach to extract sequences of networks of information sharing among single units in hippocampus and enthorinal cortex during anesthesia and study how global and node-wise functional connectivity properties evolve along time and as a function of changing global brain state (theta vs slow-wave oscillations). First, we find that information sharing networks display, at any time, a core-periphery structure in which an integrated core of more tightly functionally interconnected units link to more loosely connected network leaves. However the units participating to the core or to the periphery substantially change across time-windows, with units entering and leaving the core in a smooth way. Second, we find that discrete network states can be defined on top of this continuously ongoing liquid core-periphery reorganization. Switching between network states results in a more abrupt modification of the units belonging to the core and is only loosely linked to transitions between global oscillatory states. Third, we characterize different styles of temporal connectivity that cells can exhibit within each state of the sharing network. While inhibitory cells tend to be central, we show that, otherwise, anatomical localization only poorly influences the patterns of temporal connectivity of the different cells. Furthermore, cells can change temporal connectivity style when the network changes state. Altogether, these findings reveal that the sharing of information mediated by the intrinsic dynamics of hippocampal and enthorinal cortex cell assemblies have a rich spatiotemporal structure, which could not have been identified by more conventional time- or state-averaged analyses of functional connectivity. AUTHOR SUMMARYIt is generally thought that computations performed by local brain circuits rely on complex neural processes, associated to the flexible waxing and waning of cell assemblies, i.e. ensemble of cells firing in tight synchrony. Although cell assembly formation is inherently and unavoidably dynamical, it is still common to find studies in which essentially "static" approaches are used to characterize this process. In the present study, we adopt instead a temporal network approach. Avoiding usual time averaging procedures, we reveal that hub neurons are not hardwired but that cells vary smoothly their degree of integration within the assembly core. Furthermore, our temporal network framework enables the definition of alternative possible styles of "hubness". Some cells may share information with a multitude of other units but only in an intermittent manner, as "activists" in a flash mob. In contrast, some other cells may share information in a steadier manner, as resolute "lobbyists". Finally, by avoiding averages over pre-imposed states, we show that within each global oscillatory state a rich switching dynamics can take place between a repertoire of many available network states. We thus show that the temporal network framework provides a natural and effective language to rigorously describe the rich spatiotemporal patterns of information sharing instantiated by cell assembly evolution.

neuroscience↗

bioRxiv2017

Visual Response Properties In The Three Layer Turtle Visual Cortex

Turtle dorsal cortex provides us with unique insights into cortical processing. It is known to share many features with the mammalian hippocampus and olfactory cortex as well as geniculo-cortical areas in stem amniotes from which mammals evolved. To this end, we have used data from extracellular recordings from microelectrode arrays to study spatial and temporal patterns of responses to visual stimuli as seen in both local field potential and action potentials. We discovered surprisingly large receptive fields, responsiveness to a broad range of stimuli, and high correlation between distant neural ensembles across recording array. Moreover, we found significant response variability regarding latency and strength in the presence of adaptation to both ongoing and visually evoked activity.

neuroscience↗