Biology subjects

Harland, B.

Publications and source records attributed to Harland, B..

3 recordsLinked to original sources

bioRxiv2024

Daily electric field treatment improves functional outcomes after thoracic contusion spinal cord injury in rats

Spinal cord injury (SCI) can result in permanent loss of sensory, motor, and autonomic functions, with limited therapeutic options to recover the loss. Low-frequency electric fields with changing polarity have shown promise in promoting axon regeneration and improving outcomes. However, the metal electrodes used previously were prone to corrosion, and their epidural placement limited the penetration of the electric field into the spinal cord. Here, we demonstrate that a thin-film implant with supercapacitive electrodes placed under the dura mater can safely and effectively deliver electric field treatment in rats with thoracic SCI. Subdural stimulation enhanced hind limb function and touch sensitivity compared to controls, without inducing a neuroinflammatory response in the spinal cord. While axon density around the lesion site remained unchanged after 12 weeks, in vivo monitoring and electrochemical testing of electrodes indicated that treatment was administered throughout the study. These results highlight the promise of electric field treatment as a viable therapeutic strategy for achieving long-term functional recovery in SCI.

neuroscience↗

bioRxiv2021

Dorsal CA1 Hippocampal Place Cells Form a Multi-Scale Representation of Megaspace

Spatially firing "place cells" within the hippocampal CA1 region form internal maps of the environment necessary for navigation and memory. In rodents, these neurons have been almost exclusively studied in small environments (<4 m2). It remains unclear how place cells encode a very large open 2D environment, which is more analogous to the natural environments experienced by rodents and other mammals. Such an ethologically realistic environment would require a more complex spatial representation, capable of simultaneously representing space at overlapping multiple fine to coarse informational scales. Here we show that in a megaspace (18.6 m2), the majority of dorsal CA1 place cells exhibited multiple place subfields of different sizes, akin to those observed along the septo-temporal axis. Furthermore, the total area covered by the subfields of each cell was not correlated with the number of subfields, and this total area increased with the scale of the environment. The multiple different-sized subfields exhibited by place cells in the megaspace suggest that the ensemble population of subfields form a multi-scale representation of space within the dorsal hippocampus. Our findings point to a new dorsal hippocampus ensemble coding scheme that simultaneously supports navigational processes at both fine- and coarse-grained resolutions.

neuroscience↗

bioRxiv2018

Prefrontal cortex creates novel navigation sequences from hippocampal place-cell replay with spatial reward propagation

As rats learn to search for multiple sources of food or water in a complex environment, they generate increasingly efficient trajectories between reward sites, across multiple trials. This optimization capacity has been characterized in the Traveling Salesrat Problem (TSP) (de Jong et al (2011). Such spatial navigation capacity involves the replay of hippocampal place-cells during awake states, generating small sequences of spatially related place-cell activity that we call \"snippets\". These snippets occur primarily during sharp-wave-ripple (SWR) events. Here we focus on the role of replay during the awake state, as the animal is learning across multiple trials. We hypothesize that snippet replay generates synthetic data that can substantially expand and restructure the experience available to make PFC learning more optimal. We developed a model of snippet generation that is modulated by reward, propagated in the forward and reverse directions. This implements a form of spatial credit assignment for reinforcement learning. We use a biologically motivated computational framework known as reservoir computing to model PFC in sequence learning, in which large pools of prewired neural elements process information dynamically through reverberations. This PFC model is ideal to consolidate snippets into larger spatial sequences that may be later recalled by subsets of the original sequences. Our simulation experiments provide neurophysiological explanations for two pertinent observations related to navigation. Reward modulation allows the system to reject non-optimal segments of experienced trajectories, and reverse replay allows the system to \"learn\" trajectories that is has not physically experienced, both of which significantly contribute to the TSP behavior.\n\nAuthor SummaryAs rats search for multiple sources of food in a complex environment, they generate increasingly efficient trajectories between reward sites, across multiple trials, characterized in the Traveling Salesrat Problem (TSP). This likely involves the coordinated replay of place-cell \"snippets\" between successive trials. We hypothesize that \"snippets\" can be used by the prefrontal cortex (PFC) to implement a form of reward-modulated reinforcement learning. Our simulation experiments provide neurophysiological explanations for two pertinent observations related to navigation. Reward modulation allows the system to reject non-optimal segments of experienced trajectories, and reverse replay allows the system to \"learn\" trajectories that it has not physically experienced, both of which significantly contribute to the TSP behavior.

neuroscience↗