Biology subjects

Hoyland, A.

Publications and source records attributed to Hoyland, A..

4 recordsLinked to original sources

bioRxiv2023

Reverse Correlation Characterizes More Complete Tinnitus Spectra in Patients

GoalWe validate a recent reverse correlation approach to tinnitus characterization by applying it to individuals with clinically-diagnosed tinnitus. MethodsTwo tinnitus patients assessed the subjective similarity of their non-tonal tinnitus percepts and random auditory stimuli. Regression of the responses onto the stimuli yielded reconstructions which were evaluated qualitatively by playing back resynthesized waveforms to the subjects and quantitatively by response prediction analysis. ResultsSubject 1 preferred their resynthesis to white noise; subject 2 did not. Response prediction balanced accuracies were significantly higher than chance across subjects: subject 1: 0.5963, subject 2: 0.6922. ConclusionReverse correlation can provide the foundation for reconstructing accurate representations of complex, non-tonal tinnitus in clinically diagnosed subjects. Further refinements may yield highly similar waveforms to individualized tinnitus percepts. Impact StatementCharacterization of tinnitus sounds can help clarify the heterogeneous nature of the condition and link etiology to subtypes and treatments.

bioengineering↗

bioRxiv2022

Reverse Correlation Uncovers More Complete Tinnitus Spectra

GoalThis study validates an approach to characterizing the sounds experienced by tinnitus patients via reverse correlation, with potential for characterizing a wider range of sounds than currently possible. MethodsTen normal-hearing subjects assessed the subjective similarity of random auditory stimuli and target tinnitus-like sounds ("buzzing" and "roaring"). Reconstructions of the targets were obtained by regressing subject responses on the stimuli, and were compared for accuracy to the frequency spectra of the targets using Pearsons r. ResultsReconstruction accuracy was significantly higher than chance across subjects: buzzing (M = 0.53, SD = 0.27): t(9) = 5.766, p < 0.001; roaring (M = 0.57, SD = 0.30): t(9) = 5.76, p < 0.001. ConclusionReverse correlation can accurately reconstruct nontonal tinnitus-like sounds in normal-hearing subjects, indicating its potential for characterizing the sounds experienced by patients with non-tonal tinnitus. Impact StatementCharacterization of tinnitus sounds can inform treatment by facilitating individualized sound therapies, leading to better outcomes for patients suffering from the cognitive and psychological effects of tinnitus.

bioengineering↗

bioRxiv2020

Effects of visual inputs on neural dynamics for coding of location and running speed in medial entorhinal cortex.

Neuronal representations of spatial location and movement speed in the medial entorhinal cortex during the "active" theta state of the brain are important for memory-guided navigation and rely on visual inputs. However, little is known about how visual inputs change neural dynamics as a function of running speed and time. By manipulating visual inputs in mice, we demonstrate that changes in spatial stability of grid cell firing as a function of time correlate with changes in a proposed speed signal by local field potential theta frequency. In contrast, visual inputs do not affect the speed modulation of firing rates. Moreover, we provide evidence that sensory inputs other than visual inputs can support grid cell firing, though less accurately, in complete darkness. Finally, changes in spatial accuracy of grid cell firing on a 10-s time scale suggest that grid cell firing is a function of velocity signals integrated over past time.

neuroscience↗

bioRxiv2018

Xolotl: An Intuitive and Approachable Neuron and Network Simulator for Research and Teaching

Conductance-based models of neurons are used extensively in computational neuroscience. Working with these models can be challenging due to their high dimensionality and large number of parameters. Here, we present a neuron and network simulator built on a novel automatic type system that binds object-oriented code written in C++ to objects in MATLAB. Our approach builds on the tradition of uniting the speed of languages like C++ with the ease-of-use and feature-set of scientific programming languages like MATLAB. Xolotl allows for the creation and manipulation of hierarchical models with components that are named and searchable, permitting intuitive high-level programmatic control over all parts of the model. The simulators architecture allows for the interactive manipulation of any parameter in any model, and for visualizing the effects of changing that parameter immediately. Xolotl is fully featured with hundreds of ion channel models from the electrophysiological literature, and can be extended to include arbitrary conductances, synapses, and mechanisms. Several core features like bookmarking of parameters and automatic hashing of source code facilitate reproducible and auditable research. Its ease of use and rich visualization capabilities make it an attractive option in teaching environments. Finally, xolotl is written in a modular fashion, includes detailed tutorials and worked examples, and is freely available at https://github.com/sg-s/xolotl, enabling seamless integration into the workflows of other researchers.

neuroscience↗