Motor neurons generate pose-targeted movements via proprioceptive sculpting.

Motor neurons are the final common pathway1 through which the brain controls movement of the body, forming the basic elements from which all movement is composed. Yet how a single motor neuron contributes to control during natural movement remains unclear. Here we anatomically and functionally characterize the individual roles of the motor neurons that control head movement in the fly, Drosophila melanogaster. Counterintuitively, we find that activity in a single motor neuron rotates the head in different directions, depending on the starting posture of the head, such that the head converges towards a pose determined by the identity of the stimulated motor neuron. A feedback model predicts that this convergent behaviour results from motor neuron drive interacting with proprioceptive feedback. We identify and genetically2 suppress a single class of proprioceptive neuron3 that changes the motor neuron-induced convergence as predicted by the feedback model. These data suggest a framework for how the brain controls movements: instead of directly generating movement in a given direction by activating a fixed set of motor neurons, the brain controls movements by adding bias to a continuing proprioceptive-motor loop.

Transforming a head direction signal into a goal-oriented steering command.

To navigate, we must continuously estimate the direction we are headed in, and we must correct deviations from our goal1. Direction estimation is accomplished by ring attractor networks in the head direction system2,3. However, we do not fully understand how the sense of direction is used to guide action. Drosophila connectome analyses4,5 reveal three cell populations (PFL3R, PFL3L and PFL2) that connect the head direction system to the locomotor system. Here we use imaging, electrophysiology and chemogenetic stimulation during navigation to show how these populations function. Each population receives a shifted copy of the head direction vector, such that their three reference frames are shifted approximately 120° relative to each other. Each cell type then compares its own head direction vector with a common goal vector; specifically, it evaluates the congruence of these vectors via a nonlinear transformation. The output of all three cell populations is then combined to generate locomotor commands. PFL3R cells are recruited when the fly is oriented to the left of its goal, and their activity drives rightward turning; the reverse is true for PFL3L. Meanwhile, PFL2 cells increase steering speed, and are recruited when the fly is oriented far from its goal. PFL2 cells adaptively increase the strength of steering as directional error increases, effectively managing the tradeoff between speed and accuracy. Together, our results show how a map of space in the brain can be combined with an internal goal to generate action commands, via a transformation from world-centric coordinates to body-centric coordinates.

Converting an allocentric goal into an egocentric steering signal.

Neuronal signals that are relevant for spatial navigation have been described in many species1-10. However, a circuit-level understanding of how such signals interact to guide navigational behaviour is lacking. Here we characterize a neuronal circuit in the Drosophila central complex that compares internally generated estimates of the heading and goal angles of the fly-both of which are encoded in world-centred (allocentric) coordinates-to generate a body-centred (egocentric) steering signal. Past work has suggested that the activity of EPG neurons represents the fly's moment-to-moment angular orientation, or heading angle, during navigation2,11. An animal's moment-to-moment heading angle, however, is not always aligned with its goal angle-that is, the allocentric direction in which it wishes to progress forward. We describe FC2 cells12, a second set of neurons in the Drosophila brain with activity that correlates with the fly's goal angle. Focal optogenetic activation of FC2 neurons induces flies to orient along experimenter-defined directions as they walk forward. EPG and FC2 neurons connect monosynaptically to a third neuronal class, PFL3 cells12,13. We found that individual PFL3 cells show conjunctive, spike-rate tuning to both the heading angle and the goal angle during goal-directed navigation. Informed by the anatomy and physiology of these three cell classes, we develop a model that explains how this circuit compares allocentric heading and goal angles to build an egocentric steering signal in the PFL3 output terminals. Quantitative analyses and optogenetic manipulations of PFL3 activity support the model. Finally, using a new navigational memory task, we show that flies expressing disruptors of synaptic transmission in subsets of PFL3 cells have a reduced ability to orient along arbitrary goal directions, with an effect size in quantitative accordance with the prediction of our model. The biological circuit described here reveals how two population-level allocentric signals are compared in the brain to produce an egocentric output signal that is appropriate for motor control.

High-resolution EEG source localization in personalized segmentation-free head model with multi-dipole fitting.

Objective. Electroencephalograms (EEGs) are often used to monitor brain activity. Several source localization methods have been proposed to estimate the location of brain activity corresponding to EEG readings. However, only a few studies evaluated source localization accuracy from measured EEG using personalized head models in a millimeter resolution. In this study, based on a volume conductor analysis of a high-resolution personalized human head model constructed from magnetic resonance images, a finite difference method was used to solve the forward problem and to reconstruct the field distribution.Approach. We used a personalized segmentation-free head model developed using machine learning techniques, in which the abrupt change of electrical conductivity occurred at the tissue interface is suppressed. Using this model, a smooth field distribution was obtained to address the forward problem. Next, multi-dipole fitting was conducted using EEG measurements for each subject (N= 10 male subjects, age: 22.5 ± 0.5), and the source location and electric field distribution were estimated.Main results.For measured somatosensory evoked potential for electrostimulation to the wrist, a multi-dipole model with lead field matrix computed with the volume conductor model was found to be superior than a single dipole model when using personalized segmentation-free models (6/10). The correlation coefficient between measured and estimated scalp potentials was 0.89 for segmentation-free head models and 0.71 for conventional segmented models. The proposed method is straightforward model development and comparable localization difference of the maximum electric field from the target wrist reported using fMR (i.e. 16.4 ± 5.2 mm) in previous study. For comparison, DUNEuro based on sLORETA was (EEG: 17.0 ± 4.0 mm). In addition, somatosensory evoked magnetic fields obtained by Magnetoencephalography was 25.3 ± 8.5 mm using three-layer sphere and sLORETA.Significance. For measured EEG signals, our procedures using personalized head models demonstrated that effective localization of the somatosensory cortex, which is located in a non-shallower cortex region. This method may be potentially applied for imaging brain activity located in other non-shallow regions.

An adaptive h-refinement method for the boundary element fast multipole method for quasi-static electromagnetic modeling.

Objective.In our recent work pertinent to modeling of brain stimulation and neurophysiological recordings, substantial modeling errors in the computed electric field and potential have sometimes been observed for standard multi-compartment head models. The goal of this study is to quantify those errors and, further, eliminate them through an adaptive mesh refinement (AMR) algorithm. The study concentrates on transcranial magnetic stimulation (TMS), transcranial electrical stimulation (TES), and electroencephalography (EEG) forward problems.Approach.We propose, describe, and systematically investigate an AMR method using the boundary element method with fast multipole acceleration (BEM-FMM) as the base numerical solver. The goal is to efficiently allocate additional unknowns to critical areas of the model, where they will best improve solution accuracy. The implemented AMR method's accuracy improvement is measured on head models constructed from 16 Human Connectome Project subjects under problem classes of TES, TMS, and EEG. Errors are computed between three solutions: an initial non-adaptive solution, a solution found after applying AMR with a conservative refinement rate, and a 'silver-standard' solution found by subsequent 4:1 global refinement of the adaptively-refined model.Main results.Excellent agreement is shown between the adaptively-refined and silver-standard solutions for standard head models. AMR is found to be vital for accurate modeling of TES and EEG forward problems for standard models: an increase of less than 25% (on average) in number of mesh elements for these problems, efficiently allocated by AMR, exposes electric field/potential errors exceeding 60% (on average) in the solution for the unrefined models.Significance.This error has especially important implications for TES dosing prediction-where the stimulation strength plays a central role-and for EEG lead fields. Though the specific form of the AMR method described here is implemented for the BEM-FMM, we expect that AMR is applicable and even required for accurate electromagnetic simulations by other numerical modeling packages as well.

Comparison of head direction cell firing characteristics across thalamo-parahippocampal circuitry.

Head direction (HD) cells, which fire persistently when an animal's head is pointed in a particular direction, are widely thought to underlie an animal's sense of spatial orientation and have been identified in several limbic brain regions. Robust HD cell firing is observed throughout the thalamo-parahippocampal system, although recent studies report that parahippocampal HD cells exhibit distinct firing properties, including conjunctive aspects with other spatial parameters, which suggest they play a specialized role in spatial processing. Few studies, however, have quantified these apparent differences. Here, we performed a comparative assessment of HD cell firing characteristics across the anterior dorsal thalamus (ADN), postsubiculum (PoS), parasubiculum (PaS), medial entorhinal (MEC), and postrhinal (POR) cortices. We report that HD cells with a high degree of directional specificity were observed in all five brain regions, but ADN HD cells display greater sharpness and stability in their preferred directions, and greater anticipation of future headings compared to parahippocampal regions. Additional analysis indicated that POR HD cells were more coarsely modulated by other spatial parameters compared to PoS, PaS, and MEC. Finally, our analyses indicated that the sharpness of HD tuning decreased as a function of laminar position and conjunctive coding within the PoS, PaS, and MEC, with cells in the superficial layers along with conjunctive firing properties showing less robust directional tuning. The results are discussed in relation to theories of functional organization of HD cell tuning in thalamo-parahippocampal circuitry.

Biomechanical Response of Head Surrogate With and Without the Helmet.

Measurements of brain deformations under injurious loading scenarios are actively sought. In this work, we report experimentally measured head kinematics and corresponding dynamic, two-dimensional brain simulant deformations in head surrogates under a blunt impact, with and without a helmet. Head surrogates used in this work consisted of skin, skull, dura, falx, tentorium, and brain stimulants. The head surrogate geometry was based on the global human body models consortium's head model. A base head surrogate consisting of skin-skull-brain was considered. In addition, the response of two other head surrogates, skin-skull-dura-brain, and skin-skull-dura-brain-falx-tentorium, was investigated. Head surrogate response was studied for sagittal and coronal plane rotations for impactor velocities of 1 and 3 m/s. Response of head surrogates was compared against strain measurements in PMHS. The strain pattern in the brain simulant was heterogenous, and peak strains were established within ∼30 ms. The choice of head surrogate affect the spatiotemporal evolution of strain. For no helmet case, peak MPS of ∼50-60% and peak MSS of ∼35-50% were seen in brain simulant corresponding to peak rotational accelerations of ∼5000-7000 rad/s2. Peak head kinematics and peak MPS have been reduced by up to 75% and 45%, respectively, with the conventional helmet and by up to 90% and 85%, respectively, with the helmet with antirotational pads. Overall, these results provide important, new data on brain simulant strains under a variety of loading scenarios-with and without the helmets.

An easy-to-implement, non-invasive head restraint method for monkey fMRI.

Functional magnetic resonance imaging (fMRI) in behaving monkeys has a strong potential to bridge the gap between human neuroimaging and primate neurophysiology. In monkey fMRI, to restrain head movements, researchers usually surgically implant a plastic head-post on the skull. Although time-proven to be effective, this technique could create burdens for animals, including a risk of infection and discomfort. Furthermore, the presence of extraneous objects on the skull, such as bone screws and dental cement, adversely affects signals near the cortical surface. These side effects are undesirable in terms of both the practical aspect of efficient data collection and the spirit of "refinement" from the 3R's. Here, we demonstrate that a completely non-invasive fMRI scan in awake monkeys is possible by using a plastic head mask made to fit the skull of individual animals. In all of the three monkeys tested, longitudinal, quantitative assessment of head movements showed that the plastic mask has effectively suppressed head movements, and we were able to obtain reliable retinotopic BOLD signals in a standard retinotopic mapping task. The present, easy-to-make plastic mask has a strong potential to simplify fMRI experiments in awake monkeys, while giving data that is as good as or even better quality than that obtained with the conventional head-post method.

A fast direct solver for surface-based whole-head modeling of transcranial magnetic stimulation.

When modeling transcranial magnetic stimulation (TMS) in the brain, a fast and accurate electric field solver can support interactive neuronavigation tasks as well as comprehensive biophysical modeling. We formulate, test, and disseminate a direct (i.e., non-iterative) TMS solver that can accurately determine global TMS fields for any coil type everywhere in a high-resolution MRI-based surface model with ~ 200,000 or more arbitrarily selected observation points within approximately 5 s, with the solution time itself of 3 s. The solver is based on the boundary element fast multipole method (BEM-FMM), which incorporates the latest mathematical advancement in the theory of fast multipole methods-an FMM-based LU decomposition. This decomposition is specific to the head model and needs to be computed only once per subject. Moreover, the solver offers unlimited spatial numerical resolution. Despite the fast execution times, the present direct solution is numerically accurate for the default model resolution. In contrast, the widely used brain modeling software SimNIBS employs a first-order finite element method that necessitates additional mesh refinement, resulting in increased computational cost. However, excellent agreement between the two methods is observed for various practical test cases following mesh refinement, including a biophysical modeling task. The method can be readily applied to a wide range of TMS analyses involving multiple coil positions and orientations, including image-guided neuronavigation. It can even accommodate continuous variations in coil geometry, such as flexible H-type TMS coils. The FMM-LU direct solver is freely available to academic users.

Head trauma analysis of laboratory reconstructed headers using 1966 Slazenger Challenge and 2018 Telstar 18 soccer balls.

Retired soccer players are presenting with early onset neurodegenerative diseases, potentially from heading the ball. It has been proposed that the older composition of soccer balls places higher strains on brain tissues. The purpose of this research was to compare the dynamic head response and brain tissue strain of laboratory reconstructed headers using replicas of the 1966 Slazenger Challenge and 2018 Telstar 18 World Cup soccer balls. Head-to-ball impacts were physically conducted in the laboratory by impacting a Hybrid III head form at three locations and four velocities using dry and wet soccer ball conditions, and computational simulation was used to measure the resulting brain tissue strain. This research showed that few significant differences were found in head dynamic response and maximum principal strain between the dry 1966 and 2018 balls during reconstructed soccer headers. Headers using the wet 1966 soccer ball resulted in higher head form responses at low-velocity headers and lower head responses as velocities increased. This study demonstrates that under dry conditions, soccer ball construction does not have a significant effect on head and brain response during headers reconstructed in the laboratory. Although ball construction didn't show a notable effect, this study revealed that heading the ball, comparable to goalkeeper kicks and punts at 22 m/s, led to maximum principal strains exceeding the 50% likelihood of injury risk threshold. This has implications for the potential risks associated with repetitive heading in soccer for current athletes.

Angular Head Velocity Cells within Brainstem Nuclei Projecting to the Head Direction Circuit.

The sense of orientation of an animal is derived from the head direction (HD) system found in several limbic structures and depends on an intact vestibular labyrinth. However, how the vestibular system influences the generation and updating of the HD signal remains poorly understood. Anatomical and lesion studies point toward three key brainstem nuclei as key components for generating the HD signal-nucleus prepositus hypoglossi, supragenual nucleus, and dorsal paragigantocellularis reticular nuclei. Collectively, these nuclei are situated between the vestibular nuclei and the dorsal tegmental and lateral mammillary nuclei, which are thought to serve as the origin of the HD signal. To determine the types of information these brain areas convey to the HD network, we recorded neurons from these regions while female rats actively foraged in a cylindrical enclosure or were restrained and rotated passively. During foraging, a large subset of cells in all three nuclei exhibited activity that correlated with the angular head velocity (AHV) of the rat. Two fundamental types of AHV cells were observed; (1) symmetrical AHV cells increased or decreased their firing with increases in AHV regardless of the direction of rotation, and (2) asymmetrical AHV cells responded differentially to clockwise and counterclockwise head rotations. When rats were passively rotated, some AHV cells remained sensitive to AHV, whereas firing was attenuated in other cells. In addition, a large number of AHV cells were modulated by linear head velocity. These results indicate the types of information conveyed from the vestibular nuclei that are responsible for generating the HD signal.SIGNIFICANCE STATEMENT Extracellular recording of brainstem nuclei (nucleus prepositus hypoglossi, supragenual nucleus, and dorsal paragigantocellularis reticular nucleus) that project to the head direction circuit identified different types of AHV cells while rats freely foraged in a cylindrical environment. The firing of many cells was also modulated by linear velocity. When rats were restrained and passively rotated, some cells remained sensitive to AHV, whereas others had attenuated firing. These brainstem nuclei provide critical information about the rotational movement of the head of the rat in the azimuthal plane.

The Structural Response of the Human Head to a Vertex Impact.

In experimental models of cervical spine trauma caused by near-vertex head-first impact, a surrogate headform may be substituted for the cadaveric head. To inform headform design and to verify that such substitution is valid, the force-deformation response of the human head with boundary conditions relevant to cervical spine head-first impact models is required. There are currently no biomechanics data that characterize the force-deformation response of the isolated head supported at the occiput and compressed at the vertex by a flat impactor. The effect of impact velocity (1, 2 or 3 m/s) on the response of human heads (N = 22) subjected to vertex impacts, while supported by a rigid occipital mount, was investigated. 1 and 2 m/s impacts elicited force-deformation responses with two linear regions, while 3 m/s impacts resulted in a single linear region and skull base ring fractures. Peak force and stiffness increased from 1 to 2 and 3 m/s. Deformation at peak force and absorbed energy increased from 1 to 2 m/s, but decreased from 2 to 3 m/s. The data reported herein enhances the limited knowledge on the human head's response to a vertex impact, which may allow for validation of surrogate head models in this loading scenario.

Assessment of pediatric shoulder range of motion and loading response to evaluate the biofidelity of the Large Omni-directional Child (LODC) anthropomorphic test device (ATD) shoulder design.

The shoulder girdle complex, through engagement with the seat belt, influences motor vehicle occupant upper body movement during frontal impacts, affecting the movement of the head and spine. The recently developed Large Omni-directional Child (LODC) anthropomorphic test device (ATD) was designed with flexible shoulder girdle structures that capture the unique kinematics in pediatric occupants. However, the LODC shoulder has not been evaluated for biofidelity due to the lack of biomechanical data available on pediatric shoulder responses. This study evaluated quasi-static pediatric shoulder girdle complex responses through non-invasive displacement measurements. These data were obtained to evaluate, and, if necessary, improve the biofidelity of the LODC ATD. Shoulder range of motion and anthropometric measurements were obtained from 25 pediatric volunteers, ages 8-12 years old. Loads were applied bilaterally exclusively to the shoulder complexes in increments of 25 N up to 150 N per shoulder at 90 and 135 degrees of shoulder flexion. Still photos were used to determine shoulder displacement in the sagittal plane from images captured prior to and following the load applications. Data analysis consisted of motion tracking to evaluate the absolute and relative displacement of the right acromion and T1. The displacements for each volunteer were normalized based on the volunteer's shoulder width compared to the shoulder width of the LODC ATD. For the 90° load, the acromion moved relative to T1 an average of 28.1 mm forward and 3.1 mm downward at maximum displacement. For the 135° load, the acromion moved relative to T1 an average of 15.5 mm forward and 42.7 mm upward at maximum displacement. Similar displacements at higher loads indicated that the volunteers achieved their maximum range of motion. The results of this study will be compared to the LODC ATD, assessing the biofidelity of the shoulder complex.

Reconstruction of light absorption changes in the human head using analytically computed photon partial pathlengths in layered media.

Functional near infrared spectroscopy has been used in recent decades to sense and quantify changes in hemoglobin concentrations in the human brain. This noninvasive technique can deliver useful information concerning brain cortex activation associated with different motor/cognitive tasks or external stimuli. This is usually accomplished by considering the human head as a homogeneous medium; however, this approach does not explicitly take into account the detailed layered structure of the head, and thus, extracerebral signals can mask those arising at the cortex level. This work improves this situation by considering layered models of the human head during reconstruction of the absorption changes in layered media. To this end, analytically calculated mean partial pathlengths of photons are used, which guarantees fast and simple implementation in real-time applications. Results obtained from synthetic data generated by Monte Carlo simulations in two- and four-layered turbid media suggest that a layered description of the human head greatly outperforms typical homogeneous reconstructions, with errors, in the first case, bounded up to ∼20% maximum, while in the second case, the error is usually larger than 75%. Experimental measurements on dynamic phantoms support this conclusion.

Neurophysiological Effects of Repeated Soccer Heading in Youth.

Repeated head loading in sports is associated with negative long-term brain health, and there is growing evidence of short-term neurophysiological changes after repeated soccer heading. The objective of this study was to quantify the head kinematics and effects of repetitive soccer headers in adolescents using an instrumented mouthguard. Adolescent soccer players aged 13-18 years were randomly assigned to a kicking control, frontal heading, or oblique heading group. Participants completed neurophysiological assessments at three-time points: immediately prior to, immediately after, and approximately 24 h after completing 10 headers or kicks. The suite of assessments included the Post-Concussion Symptom Inventory, visio-vestibular exam, King-Devick test, modified Clinical Test of Sensory Interaction and Balance with force plate sway measurement, pupillary light reflex, and visual evoked potential. Data were collected for 19 participants (17 male). Frontal headers resulted in significantly higher peak resultant linear acceleration (17.4 ± 0.5 g) compared to oblique headers (12.1 ± 0.4 g, p < 0.001), and oblique headers resulted in significantly higher peak resultant angular acceleration (frontal: 1147 ± 45 rad/s2, oblique: 1410 ± 65 rad/s2, p < 0.001). There were no neurophysiological deficits for either heading group or significant differences from controls at either post-heading timepoint, and therefore, a bout of repeated headers did not result in changes in the neurophysiological measures evaluated in this study. The current study provided data regarding the direction of headers with the goal to reduce the risk of repetitive head loading for adolescent athletes.

Evaluating the Intracranial Pressure Biofidelity and Response Repeatability of a Physical Head-Brain Model in Frontal Impacts.

Headforms are widely used in head injury research and headgear assessment. Common headforms are limited to replicating global head kinematics, although intracranial responses are crucial to understanding brain injuries. This study aimed to evaluate the biofidelity of intracranial pressure (ICP) and the repeatability of head kinematics and ICP of an advanced headform subjected to frontal impacts. Pendulum impacts were performed on the headform using various impact velocities (1-5 m/s) and impactor surfaces (vinyl nitrile 600 foam, PCM746 urethane, and steel) to simulate a previous cadaveric experiment. Head linear accelerations and angular rates in three axes, cerebrospinal fluid ICP (CSFP), and intraparenchymal ICP (IPP) at the front, side, and back of the head were measured. The head kinematics, CSFP, and IPP demonstrated acceptable repeatability with coefficients of variation generally being less than 10%. The BIPED front CSFP peaks and back negative peaks were within the range of the scaled cadaver data (between the minimum and maximum values reported by Nahum et al.), while side CSFPs were 30.9-92.1% greater than the cadaver data. CORrelation and Analysis (CORA) ratings evaluating the closeness of two time histories demonstrated good biofidelity of the front CSFP (0.68-0.72), while the ratings for the side (0.44-0.70) and back CSFP (0.27-0.66) showed a large variation. The BIPED CSFP at each side was linearly related to head linear accelerations with coefficients of determination greater than 0.96. The slopes for the BIPED front and back CSFP-acceleration linear trendlines were not significantly different from cadaver data, whereas the slope for the side CSFP was significantly greater than cadaver data. This study informs future applications and improvements of a novel head surrogate.

A current assessment of the THOR 50M in rear impacts.

OBJECTIVE: This study presents a comparison of the Test Device for Human Occupant Restraint (THOR) 50M and Hybrid III (HIII) 50M anthropomorphic test device (ATD) geometries and rear impact head and neck biofidelity to each other and to postmortem human surrogate (PMHS) data to evaluate the usefulness of the THOR in rear impact testing. METHODS: Both ATDs were scanned in a seated position on a rigid bench seat. A series of rear impact sled tests with the rigid bench seat with no head restraint support were conducted with a HIII-50M at 16 and 24 kph. Tests at each speed were performed twice with the THOR-50M to allow an assessment of the repeatability of the THOR-50M. A comparison of the test results from THOR-50M testing were made to the results of a previous study that included PMHS. Rear impact sled tests with both ATDs in a modern seat were then conducted at 40 kph. RESULTS: The THOR-50M head was 48.4 mm rearward and 60.1 mm higher than the HIII-50M head when seated in the rigid bench seat. In the repeated rigid bench testing at 16 and 24 kph, the THOR-50M head longitudinal and vertical accelerations, upper neck moment, and overall kinematics showed good test-to-test repeatability. In the rigid bench tests, the THOR-50M neck experienced flexion prior to extension in the 16 kph tests, where the neck of the HIII only experienced extension. At 24 kph both ATDs only experienced extension. The THOR-50M head displaced more rearward at both test velocities. The rigid bench tests show that the THOR-50M neck allows for more extension motion or articulation than the HIII-50M neck. The rigid bench test also shows that the head longitudinal and vertical accelerations, angular head kinematics, and upper neck moments were reasonably comparable between the ATDs. The THOR-50M results were closer to the average of the PMHS results than the HIII-50-M results, with the exception of the upper neck. In the 40 kph tests, with a modern seat design, the THOR-50M resulted in more deformation of the seatback with greater head restraint loading than the HIII-50M. The THOR-50M head backset distance was less. CONCLUSION: This study provides insight into the differences and similarities between the THOR and the HIII-50M ATD geometries, instrumentation responses, and kinematics, as well as the repeatability of the THOR-50M in rear impacts testing. The overall geometries of the THOR-50M and the HIII-50M are similar. The seated head position of the THOR-50M is slightly further rearward and higher than the HIII-50M. The results indicate that the THOR-50M matches the PMHS results more closely than the HIII-50M and may have improved neck biofidelity in rear impact testing. The results indicate that the studied THOR-50M responses are repeatable within expected test-to-test variations in rear impacts. Early data suggest that the THOR-50M can be used in rear impact testing, though a more complete understanding of the THOR-50M differences to the HIII ATDs will allow for better correlation to the existing body of HIII rear impact testing.

Population dynamics of head-direction neurons during drift and reorientation.

The head direction (HD) system functions as the brain's internal compass1,2, classically formalized as a one-dimensional ring attractor network3,4. In contrast to a globally consistent magnetic compass, the HD system does not have a universal reference frame. Instead, it anchors to local cues, maintaining a stable offset when cues rotate5-8 and drifting in the absence of referents5,8-10. However, questions about the mechanisms that underlie anchoring and drift remain unresolved and are best addressed at the population level. For example, the extent to which the one-dimensional description of population activity holds under conditions of reorientation and drift is unclear. Here we performed population recordings of thalamic HD cells using calcium imaging during controlled rotations of a visual landmark. Across experiments, population activity varied along a second dimension, which we refer to as network gain, especially under circumstances of cue conflict and ambiguity. Activity along this dimension predicted realignment and drift dynamics, including the speed of network realignment. In the dark, network gain maintained a 'memory trace' of the previously displayed landmark. Further experiments demonstrated that the HD network returned to its baseline orientation after brief, but not longer, exposures to a rotated cue. This experience dependence suggests that memory of previous associations between HD neurons and allocentric cues is maintained and influences the internal HD representation. Building on these results, we show that continuous rotation of a visual landmark induced rotation of the HD representation that persisted in darkness, demonstrating experience-dependent recalibration of the HD system. Finally, we propose a computational model to formalize how the neural compass flexibly adapts to changing environmental cues to maintain a reliable representation of HD. These results challenge classical one-dimensional interpretations of the HD system and provide insights into the interactions between this system and the cues to which it anchors.

Cerebellar control of a unitary head direction sense.

The head-direction (HD) system, a key neural circuit for navigation, consists of several anatomical structures containing neurons selective to the animal's head direction. HD cells exhibit ubiquitous temporal coordination across brain regions, independently of the animal's behavioral state or sensory inputs. Such temporal coordination mediates a single, stable, and persistent HD signal, which is essential for intact orientation. However, the mechanistic processes behind the temporal organization of HD cells are unknown. By manipulating the cerebellum, we identify pairs of HD cells recorded from two brain structures (anterodorsal thalamus and retrosplenial cortex) that lose their temporal coordination, specifically during the removal of the external sensory inputs. Further, we identify distinct cerebellar mechanisms that participate in the spatial stability of the HD signal depending on sensory signals. We show that while cerebellar protein phosphatase 2B-dependent mechanisms facilitate the anchoring of the HD signal on the external cues, the cerebellar protein kinase C-dependent mechanisms are required for the stability of the HD signal by self-motion cues. These results indicate that the cerebellum contributes to the preservation of a single and stable sense of direction.

Bayesian inference in ring attractor networks.

Working memories are thought to be held in attractor networks in the brain. These attractors should keep track of the uncertainty associated with each memory, so as to weigh it properly against conflicting new evidence. However, conventional attractors do not represent uncertainty. Here, we show how uncertainty could be incorporated into an attractor, specifically a ring attractor that encodes head direction. First, we introduce a rigorous normative framework (the circular Kalman filter) for benchmarking the performance of a ring attractor under conditions of uncertainty. Next, we show that the recurrent connections within a conventional ring attractor can be retuned to match this benchmark. This allows the amplitude of network activity to grow in response to confirmatory evidence, while shrinking in response to poor-quality or strongly conflicting evidence. This "Bayesian ring attractor" performs near-optimal angular path integration and evidence accumulation. Indeed, we show that a Bayesian ring attractor is consistently more accurate than a conventional ring attractor. Moreover, near-optimal performance can be achieved without exact tuning of the network connections. Finally, we use large-scale connectome data to show that the network can achieve near-optimal performance even after we incorporate biological constraints. Our work demonstrates how attractors can implement a dynamic Bayesian inference algorithm in a biologically plausible manner, and it makes testable predictions with direct relevance to the head direction system as well as any neural system that tracks direction, orientation, or periodic rhythms.