Theoretical principles explain the structure of the insect head direction circuit.

To navigate their environment, insects need to keep track of their orientation. Previous work has shown that insects encode their head direction as a sinusoidal activity pattern around a ring of neurons arranged in an eight-column structure. However, it is unclear whether this sinusoidal encoding of head direction is just an evolutionary coincidence or if it offers a particular functional advantage. To address this question, we establish the basic mathematical requirements for direction encoding and show that it can be performed by many circuits, all with different activity patterns. Among these activity patterns, we prove that the sinusoidal one is the most noise-resilient, but only when coupled with a sinusoidal connectivity pattern between the encoding neurons. We compare this predicted optimal connectivity pattern with anatomical data from the head direction circuits of the locust and the fruit fly, finding that our theory agrees with experimental evidence. Furthermore, we demonstrate that our predicted circuit can emerge using Hebbian plasticity, implying that the neural connectivity does not need to be explicitly encoded in the genetic program of the insect but rather can emerge during development. Finally, we illustrate that in our theory, the consistent presence of the eight-column organisation of head direction circuits across multiple insect species is not a chance artefact but instead can be explained by basic evolutionary principles.

Insects, including fruit flies and locusts, move throughout their environment to find food, interact with each other or escape danger. To navigate their surroundings, insects need to be able to keep track of their orientation. This tracking is achieved through visual cues and integrating information about their movements whilst flying so they know which direction their head is facing. The set of neurons responsible for relaying information about the direction of the head (also known as heading) are connected together in a ring made up of eight columns of cells. Previous studies showed that the level of activity across this ring of neurons resembles a sinusoid shape: a smooth curve with one peak which encodes the animal's heading. Neurons downstream from this eight-column ring, which relay velocity information, also display this sinusoidal pattern of activation. Aceituno, Dall'Osto and Pisokas wanted to understand whether this sinusoidal pattern was an evolutionary coincidence, or whether it offers a particular advantage to insects. To answer this question, they established the mathematical criteria required for neurons in the eight-column ring to encode information about the heading of the animal. This revealed that these conditions can be satisfied by many different patterns of activation, not just the sinusoidal shape. However, Aceituno, Dall'Osto and Pisokas show that the sinusoidal shape is the most resilient to variations in neuronal activity which may impact the encoded information. Further experiments revealed that this resilience only occurred if neurons in the circuit were connected together in a certain pattern. Aceituno, Dall'Osto and Pisokas then compared this circuit with experimental data from locusts and fruit flies and found that both insects exhibit the predicted connection pattern. They also discovered that animals do not have to be born with this neuronal connection pattern, but can develop it during their lifetime. These findings provide fresh insights into how insects relay information about the direction of their head as they fly. They suggest that the structure of the neuronal circuit responsible for encoding head direction was not formed by chance but instead arose due to the evolutionary benefits it provided.

Phonetic differences between affirmative and feedback head nods in German Sign Language (DGS): A pose estimation study.

This study investigates head nods in natural dyadic German Sign Language (DGS) interaction, with the aim of finding whether head nods serving different functions vary in their phonetic characteristics. Earlier research on spoken and sign language interaction has revealed that head nods vary in the form of the movement. However, most claims about the phonetic properties of head nods have been based on manual annotation without reference to naturalistic text types and the head nods produced by the addressee have been largely ignored. There is a lack of detailed information about the phonetic properties of the addressee's head nods and their interaction with manual cues in DGS as well as in other sign languages, and the existence of a form-function relationship of head nods remains uncertain. We hypothesize that head nods functioning in the context of affirmation differ from those signaling feedback in their form and the co-occurrence with manual items. To test the hypothesis, we apply OpenPose, a computer vision toolkit, to extract head nod measurements from video recordings and examine head nods in terms of their duration, amplitude and velocity. We describe the basic phonetic properties of head nods in DGS and their interaction with manual items in naturalistic corpus data. Our results show that phonetic properties of affirmative nods differ from those of feedback nods. Feedback nods appear to be on average slower in production and smaller in amplitude than affirmation nods, and they are commonly produced without a co-occurring manual element. We attribute the variations in phonetic properties to the distinct roles these cues fulfill in turn-taking system. This research underlines the importance of non-manual cues in shaping the turn-taking system of sign languages, establishing the links between such research fields as sign language linguistics, conversational analysis, quantitative linguistics and computer vision.

Using your head - cranial steering in pterosaurs.

The vast majority of pterosaurs are characterized by relatively large, elongate heads that are often adorned with large, elaborate crests. Projecting out in front of the body, these large heads and any crests must have had an aerodynamic effect. The working hypothesis of the present study is that these oversized heads were used to control the left-right motions of the body during flight. Using digital models of eight non-pterodactyloids ("rhamphorhyncoids") and ten pterodactyloids, the turning moments associated with the head + neck show a close and consistent correspondence with the rotational inertia of the whole body about a vertical axis in both groups, supporting the idea of a functional relationship. Turning moments come from calculating the lateral area of the head (plus any crests) and determining the associated lift (aerodynamic force) as a function of flight speed, with flight speeds being based on body mass. Rotational inertias were calculated from the three-dimensional mass distribution of the axial body, the limbs, and the flight membranes. The close correlation between turning moment and rotational inertia was used to revise the life restorations of two pterosaurs and to infer relatively lower flight speeds in another two.

Efficacy of posture correction band vs. McKenzie's exercises on pulmonary function and chest expansion in asymptomatic population with forward head posture.

BACKGROUND: Poor posture and sedentary lifestyle cause Forward Head Posture (FHP). To correct this, a Posture Correction Band (PCB) is commonly used. However, the efficacy of PCB vs. McKenzie's Exercises on pulmonary function and chest expansion in asymptomatic individuals with FHP was not known. OBJECTIVE: This study aimed to determine the efficacy of PCB vs. McKenzie's Exercises on the Pulmonary function and chest expansion in asymptomatic population with FHP. METHODOLOGY: A Randomized control trial was conducted on forty-two subjects with FHP. Subjects were divided in two groups. G1 group was educated as per McKenzie's exercises to perform once daily for a month. The Pulmonary function test and chest expansion of this group was performed before and after the McKenzie exercises. G2 group wore PCB for 2 h daily for a month and their PFT and chest expansion was recorded before and after the trial. FVC, FEV1, FEV1/FVC ratio, PEFR and Chest expansion were measured. RESULTS: The P-value of FVC, FEV1, FEV1/FVC ratio and PEFR between the groups (treatment group) was significant as 0.000, 0.000, 0.000 and 0.02 respectively. The chest expansion was non-significant between the groups (treatment group) with P-value as 0.553, 0.493 and 0.699 at axillary, 4th intercostal and xiphisternum level respectively. The P-value of FVC, FEV1, FEV1/FVC ratio and PEFR between the groups (control group) was non-significant as 0.682, 0.149, 0.424 and 0.414 respectively. The chest expansion was also non-significant between the groups (control group) with P-value as 0.853, 0.651 and 0.763 at axillary, 4th intercostal and xiphisternum level. CONCLUSION: The study concluded that there were significant effects of both Posture Correction Band and Mc'Kenzie exercises on pulmonary function with greater difference seen with PCB and non-significant effects on chest expansion in terms of P-values in treatment group.

Efficacy of head postural correction program on craniovertebral angle, scapular position, and dominant hand grip strength in forward head posture subjects: A randomized controlled trial.

OBJECTIVE: Forward head posture (FHP) is a common postural disorder that alters shoulder function. This study examined the efficacy of a corrective program involving postural correction exercises (PCEs), scapular stabilization exercises (SSEs), and kinesiotaping (KT) on improving craniovertebral angle (CVA), scapular position, and dominant hand grip strength (HGS) in individuals with FHP. METHODS: Sixty subjects (8 males and 52 females, 18-40 years old) were randomly allocated into four equal groups: Group A: received PCEs only, Group B: received PCEs and SSEs, Group C: received PCEs and KT, Group D: received PCEs, SSEs and KT. All subjects received treatment for 4 weeks (4 times/week) and postural advice. Outcome measures included cranio-vertebral angle (CVA), scapular position using Lateral Scapular Slide Test and dominant HGS using a CAMRY dynamometer that were assessed at baseline and 4 weeks post intervention. RESULTS: Comparing all groups post training revealed that there were statistically significant increases (p < 0.05) in all measured variables (CVA, scapular position and dominant HGS) in favor of group (D). CONCLUSION: Combination of PCEs, SSEs and KT interventions has achieved the best gains in terms of CVA, dominant HGS and regaining optimal scapular position in FHP subjects.

Influence of aging on the relation between head control and hip joint kinematics during crossover stepping.

Falls in older individuals are a serious health issue in super-aged societies. The stepping reaction is an important postural strategy for preventing falls. This study aimed to reveal the characteristics of lateral stepping in response to mechanical disturbance by means of an analysis of the hip joint kinematics in the stepping leg and head stability during crossover steps. The participants included 11 healthy older and 13 younger individuals. An electromagnet-controlled disturbance-loading device induced crossover steps due to lateral disturbance. Responses were measured using a motion capture system and force plates. The righting reaction of the head was quantified by lateral displacement (sway), neck joint kinematics (angle displacement, angular velocity), and neck joint moment during crossover stepping. Moreover, the relationship between the neck lateral bending moment and angular velocity of hip flexion/adduction of the stepping leg was examined. The lateral head sway was significantly larger in the older participants (1.13±0.7 m/s2) than in the younger individuals (0.54±0.3 m/s2); whereas, the angle displacement (older -14.1±7.1 degree, young -8.3±4.5 degree) and angular velocity (older 9.9±6.6 degree/s, 41.2±27.7 degree/s) of the head were significantly lower in the older than in the younger participants. In both groups, the moment of neck lateral bending exhibited a significant negative correlation with the hip flexion angular velocity of the stepping leg. Correlation analysis also showed a significant negative correlation between the neck lateral bending moment and hip adduction angular velocity only in the older group (r = 0.71, p<0.01). In conclusion, older individuals increased instability in the lateral direction of the head and decreased righting angle displacement and angular velocity of the head during crossover steps. The correlation between neck moment and hip flexion/adduction angular velocity suggested a decrease in step speed due to increased neck muscle tone, which could be influenced by vestibulospinal reflexes.

Effect of sound-induced vibrations of the pinna on head-related transfer functions: Experimental and numerical investigations.

Numerical simulations of head-related transfer functions (HRTFs) conventionally assume a rigid boundary condition for the pinna. The human pinna, however, is an elastic deformable body that can vibrate due to incident acoustic waves. This work investigates how sound-induced vibrations of the pinna can affect simulated HRTF magnitudes. The work will motivate the research question by measuring the sound-induced vibrational patterns of an artificial pinna with a high-speed holographic interferometric system. Then, finite element simulations are used to determine HRTFs for a tabletop model of the B&K 5128 head and torso simulator for a number of directions. Two scenarios are explored: one where the pinna is modeled as perfectly rigid, and another where the pinna is modeled as linear elastic with material properties close to that of auricular cartilage. The findings suggest that pinna vibrations have negligible effects on HRTF magnitudes up to 5 kHz. The same conclusion, albeit with less certainty, is drawn for higher frequencies. Finally, the importance of the elastic domain's material properties is emphasized and possible implications for validation studies on dummy heads 1as well as the limitations of the present work are discussed in detail.

User experience with ultrawide curved displays: A mixed methods analysis.

Due to the trend of replacing dual displays with ultrawide (UW) curved displays, we used a mixed methods analysis to investigate the user experience with UW curved displays. We conducted an experimental laboratory study that quantified user self-selected positions for three displays - 24 in. flat panel, and 34 in. and 40 in. UW curved displays. Participants were first provided with a familiarization protocol, and they then positioned the display. The self-selected UW display viewing distances were within current recommendations; however, viewing distance increased with display size, potentially challenging small work surface depths and may have been in response to feeling "overwhelmed" by larger displays. Head twist range of motion increased with display width. While all displays were within recommendations, participants commented that less head twisting was a factor in choosing the 34 in. over the 40 in. display. Practitioners should assess potential workstation limitations and the potential impact on neck twist angles when installing ultrawide displays.

Evaluating Intraocular Pressure Alterations during Large Muscle Group Isometric Exercises with Varying Head and Body Positions.

Performing physical exercise affects intraocular pressure, and its elevation and fluctuations are the main risk factors for glaucoma development or progression. The aim of this study was to examine the acute alterations in intraocular pressure (IOP) during four unweighted isometric exercises and to determine whether the different head and body positions taken during exercise additionally affect IOP. Twelve healthy volunteers between the ages of 25 and 33 performed four isometric exercises: wall sit in neutral head and body position, elbow plank in prone head and body position, reverse plank in supine head and body position for 1 min, and right-side plank in lateral head and body position for 30 s. Intraocular pressure was measured by applanation portable tonometry, before performing the exercise, immediately after exercise completion, and after five minutes of rest. A significant acute increase in intraocular pressure was found as a response to the performance of the elbow plank (p < 0.01), the reverse plank (p < 0.001), and the right-side plank (p < 0.001). The wall sit exercise did not reveal a statistically significant IOP elevation (p = 0.232). Different head and body positions had no significant additional influence on IOP (F (3,33) = 0.611; p = 0.613), even though the alteration in IOP was found to be greater in exercises with a lower head and body position. Our data revealed that IOP elevation seems to be affected by the performance of the elbow plank, the reverse plank, and the right-side plank; and not by the wall sit exercise. More different isometric exercises should be examined to find ones that are safe to perform for glaucoma patients.

Measurement proprieties of the CROM instrument for assessing head posture, neck retraction and protraction.

BACKGROUND: The CROM instrument is widely used clinically and in research to measure neck range of motion. However, its measurement proprieties during the assessment of protraction and retraction movements were not examined so far. OBJECTIVE: To analyse the intra- and inter-rater reliability, the concurrent validity of the CROM for measuring head posture, retraction and protraction in healthy subjects. METHODS: Thirty-three asymptomatic subjects were recruited and assigned in a random order to one of two raters. After a 10-min break, they were examined by a second rater (Assessment 1). After a 30-min break, both raters repeated the examination (Assessment 2). The examination consisted of measuring the head posture, maximum head protraction and maximum retraction. Each movement was repeated 3 times and measured simultaneously with the CROM and with a 3D capture system laboratory. RESULTS: The intra-rater reliability of the CROM was excellent for both raters for head posture and all head movements (ICC>0.9, 95% CI: 0.82-0.99, p < 0.01). The inter-rater reliability was excellent for head posture (ICC>0.95, 95% CI: 0.92-0.98, p < 0.01) and good-to-excellent for all movements at both time-points (ICC = 0.73-0.98, 95%CI: 0.45-0.99, p < 0.01). The validity analysis showed moderate-to-strong correlation between instruments for the head posture and head movements [(r) = -0.47 to -0.78), 95% CI: 0.99 to -0.24, p < 0.01]. CONCLUSION: The CROM instrument has good-to-excellent reliability and adequate validity for measuring cervical position and displacement in the sagittal plane.

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.

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.

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.

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.

Transmission of fore-and-aft floor vibration to the spine and head of standing people.

Sixteen standing male participants were subjected to fore-and-aft sinusoidal vibration with peak magnitude and frequency in the range 0.44-4.431 ms-2 and 2-6 Hz, respectively. The fore-and-aft, lateral and vertical transmissibilities to the first dorsal vertebra (T1), eighth dorsal vertebra (T8), twelfth dorsal vertebra (T12), fourth lumbar vertebra (L4) and head were measured. Large inter-participant variability was observed in the transmissibilities at all locations. Nevertheless, peaks in the range 3-4.5 Hz were identified at all locations, implying a whole-body resonance in this frequency range. The response was found dominant in the mid-sagittal plane as the lateral transmissibility showed low values. Below 4.5 Hz, the fore-and-aft transmissibility increased with moving from caudal to cranial locations of the upper body. However, at higher frequencies, the opposite trend was observed. The results can be used for developing models that may help understand how vibration affects health and comfort.

Brain Deformation Estimation With Transfer Learning for Head Impact Datasets Across Impact Types.

OBJECTIVE: The machine-learning head model (MLHM) to accelerate the calculation of brain strain and strain rate, which are the predictors for traumatic brain injury (TBI), but the model accuracy was found to decrease sharply when the training/test datasets were from different head impacts types (i.e., car crash, college football), which limits the applicability of MLHMs to different types of head impacts and sports. Particularly, small sizes of target dataset for specific impact types with tens of impacts may not be enough to train an accurate impact-type-specific MLHM. METHODS: To overcome this, we propose data fusion and transfer learning to develop a series of MLHMs to predict the maximum principal strain (MPS) and maximum principal strain rate (MPSR). RESULTS: The strategies were tested on American football (338), mixed martial arts (457), reconstructed car crash (48) and reconstructed American football (36) and we found that the MLHMs developed with transfer learning are significantly more accurate in estimating MPS and MPSR than other models, with a mean absolute error (MAE) smaller than 0.03 in predicting MPS and smaller than [Formula: see text] in predicting MPSR on all target impact datasets. High performance in concussion detection was observed based on the MPS and MPSR estimated by the transfer-learning-based models. CONCLUSION: The MLHMs can be applied to various head impact types for rapidly and accurately calculating brain strain and strain rate. SIGNIFICANCE: This study enables developing MLHMs for the head impact type with limited availability of data, and will accelerate the applications of MLHMs.

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.

Dynamic strain fields of the mouse brain during rotation.

Mouse models are used to better understand brain injury mechanisms in humans, yet there is a limited understanding of biomechanical relevance, beginning with how the murine brain deforms when the head undergoes rapid rotation from blunt impact. This problem makes it difficult to translate some aspects of diffuse axonal injury from mouse to human. To address this gap, we present the two-dimensional strain field of the mouse brain undergoing dynamic rotation in the sagittal plane. Using a high-speed camera with digital image correlation measurements of the exposed mid-sagittal brain surface, we found that pure rotations (no direct impact to the skull) of 100-200 rad/s are capable of producing complex strain fields that evolve over time with respect to rotational acceleration and deceleration. At the highest rotational velocity tested, the largest tensile strains (≥ 21% elongation) in selected regions of the mouse brain approach strain thresholds previously associated with axonal injury in prior work. These findings provide a benchmark to validate the mechanical response in biomechanical computational models predicting diffuse axonal injury, but much work remains in correlating tissue deformation patterns from computational models with underlying neuropathology.