Peripheral Nerve Activation Evokes Machine-Learnable Signals in the Dorsal Column Nuclei

The brainstem dorsal column nuclei (DCN) are essential to inform the brain of tactile and proprioceptive events experienced by the body. However, little is known about how ascending somatosensory information is represented in the DCN. Our objective was to investigate the usefulness of high-frequency (HF) and low-frequency (LF) DCN signal features (SFs) in predicting the nerve from which signals were evoked. We also aimed to explore the robustness of DCN SFs and map their relative information content across the brainstem surface. DCN surface potentials were recorded from urethane-anesthetized Wistar rats during sural and peroneal nerve electrical stimulation. Five salient SFs were extracted from each recording electrode of a seven-electrode array. We used a machine learning approach to quantify and rank information content contained within DCN surface-potential signals following peripheral nerve activation. Machine-learning of SF and electrode position combinations was quantified to determine a hierarchy of information importance for resolving the peripheral origin of nerve activation. A supervised back-propagation artificial neural network (ANN) could predict the nerve from which a response was evoked with up to 96.8 ± 0.8% accuracy. Guided by feature-learnability, we maintained high prediction accuracy after reducing ANN algorithm inputs from 35 (5 SFs from 7 electrodes) to 6 (4 SFs from one electrode and 2 SFs from a second electrode). When the number of input features were reduced, the best performing input combinations included HF and LF features. Feature-learnability also revealed that signals recorded from the same midline electrode can be accurately classified when evoked from bilateral nerve pairs, suggesting DCN surface activity asymmetry. Here we demonstrate a novel method for mapping the information content of signal patterns across the DCN surface and show that DCN SFs are robust across a population. Finally, we also show that the DCN is functionally asymmetrically organized, which challenges our current understanding of somatotopic symmetry across the midline at sub-cortical levels

Peripheral nerve activation evokes machine-learnable signals in the dorsal column nuclei

The brainstem dorsal column nuclei (DCN) are essential to inform the brain of tactile and proprioceptive events experienced by the body. However, little is known about how ascending somatosensory information is represented in the DCN. Our objective was to investigate the usefulness of high-frequency (HF) and low-frequency (LF) DCN signal features (SFs) in predicting the nerve from which signals were evoked. We also aimed to explore the robustness of DCN SFs and map their relative information content across the brainstem surface. DCN surface potentials were recorded from urethane-anesthetized Wistar rats during sural and peroneal nerve electrical stimulation. Five salient SFs were extracted from each recording electrode of a seven-electrode array. We used a machine learning approach to quantify and rank information content contained within DCN surface-potential signals following peripheral nerve activation. Machine-learning of SF and electrode position combinations was quantified to determine a hierarchy of information importance for resolving the peripheral origin of nerve activation. A supervised back-propagation artificial neural network (ANN) could predict the nerve from which a response was evoked with up to 96.8 ± 0.8% accuracy. Guided by feature-learnability, we maintained high prediction accuracy after reducing ANN algorithm inputs from 35 (5 SFs from 7 electrodes) to 6 (4 SFs from one electrode and 2 SFs from a second electrode). When the number of input features were reduced, the best performing input combinations included HF and LF features. Feature-learnability also revealed that signals recorded from the same midline electrode can be accurately classified when evoked from bilateral nerve pairs, suggesting DCN surface activity asymmetry. Here we demonstrate a novel method for mapping the information content of signal patterns across the DCN surface and show that DCN SFs are robust across a population. Finally, we also show that the DCN is functionally asymmetrically organized, which challenges our current understanding of somatotopic symmetry across the midline at sub-cortical levels.The authors are extremely grateful to the Bootes Medical Research Foundation which funded this project. AL was supported by the Australian Government Research Training Program

Stimulation of a Suprachoroidal Retinal Prosthesis Drives Cortical Responses in a Feline Model of Retinal Degeneration

PURPOSE. Retinal prostheses have emerged as a promising technology to restore vision in patients with severe photoreceptor degeneration. To better understand how neural degeneration affects the efficacy of electronic implants, we investigated the function of a suprachoroidal retinal implant in a feline model. METHODS. Unilateral retinal degeneration was induced in four adult felines by intravitreal injection of adenosine triphosphate (ATP). Twelve weeks post injection, animals received suprachoroidal electrode array implants in each eye, and responses to electrical stimulation were obtained using multiunit recordings from the visual cortex. Histologic measurements of neural and glial changes in the retina at the implant site were correlated with cortical thresholds from individual stimulating electrodes. RESULTS. Adenosine triphosphate-injected eyes displayed changes consistent with mid-to-late stage retinal degeneration and remodeling. A significant increase in electrical charge was required to induce a cortical response from stimulation of the degenerated retina compared to that in the fellow control eye. Spatial and temporal characteristics of the electrically evoked cortical responses were no different between eyes. Individual electrode thresholds varied in both the control and the ATP-injected eyes and were correlated with ganglion cell density. In ATP-injected eyes, cortical threshold was also independently correlated with an increase in the extent of retinal gliosis. CONCLUSIONS. These data suggest that even when ganglion cell density remains unaffected, glial changes in the retina following degeneration can influence the efficacy of suprachoroidal electrical stimulation. A better understanding of how glial change impacts retinal prosthesis function may help to further the optimization of retinal implants

Maturation of Auditory Brainstem Projections and Calyces in the Congenitally deaf( dn/dn ) mouse

The deaf dn/dn mouse is a valuable model of human congenital deafness. In this study we used the lipophylic dye DiA to trace auditory nerve and cochlear nucleus projections in the dn/dn mouse. In both normal and deaf mice, the ipsilateral projections from the anteroventral cochlear nucleus (AVCN) to the lateral superior olive (LSO), and the contralateral projections from the AVCN to the medial nucleus of the trapezoid body (MNTB) were intact. With age, there was a noted increase in the fenestration of the endbulb and calyx of Held, and this morphological maturation was also observed in the deaf mice, although there was a significant difference in total endbulb volume at P20 between normal and deaf mice. However, total calyceal volume was not significantly different between normal and deaf mice. There was electrophysiological evidence of in vivo spontaneous ventral cochlear nucleus activity in normal and deaf animals, indicating that this activity may be responsible for the appropriate connectivity in the deaf mice. Our results indicate that congenital deafness caused by the dn/dn mutation does not result in aberrant projections between the AVCN and the ipsilateral MNTB and contralateral LSO but can cause abnormalities in endbulb size

Experiment 2 raw data

<p>Accuracy and motor reaction times (MRT) data for all participants on Novel-A (“NovelSounds”), Verbal-A (“VerbalSounds”), Shape-V (“RedShapes”), and three black shapes (BS) (LineSet1, 2, and 3) discrimination tasks. The values in each column denote:</p> <p>Stimulus type: 1 = target; 2, 3, 4 = non-target</p> <p>User Response: 1 = respond target; 2 = respond non-target; 999 = invalid response (both buttons pressed in response to the stimuli)</p> <p>Accuracy: 1 = correct; 0 = incorrect</p

Experiment 1 raw data

<p>Accuracy and motor reaction times (MRT) data for all participants on novel-AV (“AV”), shape-VV (“VV”), and verbal-AV (“Vver”) learning tasks. The values in each column denote:</p> <p>Stimulus type: 1-4 = target; 5-16 = non-target</p> <p>Response/Expected response: 1 = press; 0 = no press</p> <p>Accuracy: 0 = correct; 1 = incorrect</p

Susceptibility to the flash-beep illusion is increased in children compared to adults

Audio-visual integration was studied in children aged 8-17 (N = 30) and adults (N = 22) using the 'flash-beep illusion' paradigm, where the presentation of two beeps causes a single flash to be perceived as two flashes (fission illusion), and a single beep causes two flashes to be perceived as one flash (fusion illusion). Children reported significantly more fission illusions than adults, indicating that auditory and visual information was integrated more often, and less selectively, than in adults. Within either group, illusion reports did not correlate with either age or motor coordination measures. The current results show that the form of multisensory integration indexed by the illusion is slow to mature in normally developing children