Activity Patterns Research Articles

Hearing Impairment and Physical Activity and Physical Functioning in Older Adults: Baseline Results From the ACHIEVE Trial.

Hearing loss is associated with restricted physical activity (PA) and impaired physical functioning, yet the relationship between severity of hearing impairment (HI) and novel PA measures in older adults with untreated HI is not well understood. Analyses included 845 participants aged ≥70 years (mean = 76.6 years) with a better-hearing ear pure-tone average (PTA) ≥30 and <70 dB in the Aging and Cognitive Health Evaluation in Elders (ACHIEVE) study who wore an ActiGraph accelerometer for 7 days. Physical functioning measures included grip strength and the Short Physical Performance Battery (SPPB). Linear regression models estimated the association by HI level (moderate or greater [PTA ≥ 40 dB] vs mild [PTA < 40 dB]) and continuous hearing with total daily activity counts, active minutes/day, activity fragmentation, grip strength, and gait speed. Logistic regression models estimated odds ratios (ORs) and 95% confidence intervals (CIs) of poor performance on the SPPB (≤6) and its subtests (≤2). Mixed-effects models estimated differences by HI level in activity by time of day. Participants with moderate or greater HI had poorer physical functioning, particularly balance (OR = 2.17, 95% CI = 1.29-3.67), versus those with mild impairment. There was no association of HI level with activity quantities or fragmentation. For diurnal patterns of activity, participants with moderate or greater HI had fewer activity counts in the afternoon (12:00 pm -05:59 pm). Older adults with worse hearing had shifted diurnal patterns and poorer balance performance. Exercise programs should be tailored to older adults with different levels of HI to maintain PA and physical functioning, particularly balance control.

Spatiotemporal Properties of Common Semantic Categories for Words and Pictures.

The timing of semantic processing during object recognition in the brain is a topic of ongoing discussion. One way of addressing this question is by applying multivariate pattern analysis to human electrophysiological responses to object images of different semantic categories. However, although multivariate pattern analysis can reveal whether neuronal activity patterns are distinct for different stimulus categories, concerns remain on whether low-level visual features also contribute to the classification results. To circumvent this issue, we applied a cross-decoding approach to magnetoencephalography data from stimuli from two different modalities: images and their corresponding written words. We employed items from three categories and presented them in a randomized order. We show that if the classifier is trained on words, pictures are classified between 150 and 430 msec after stimulus onset, and when training on pictures, words are classified between 225 and 430 msec. The topographical map, identified using a searchlight approach for cross-modal activation in both directions, showed left lateralization, confirming the involvement of linguistic representations. These results point to semantic activation of pictorial stimuli occurring at ≈150 msec, whereas for words, the semantic activation occurs at ≈230 msec.

Intrinsic dynamics of randomly clustered networks generate place fields and preplay of novel environments.

During both sleep and awake immobility, hippocampal place cells reactivate time-compressed versions of sequences representing recently experienced trajectories in a phenomenon known as replay. Intriguingly, spontaneous sequences can also correspond to forthcoming trajectories in novel environments experienced later, in a phenomenon known as preplay. Here, we present a model showing that sequences of spikes correlated with the place fields underlying spatial trajectories in both previously experienced and future novel environments can arise spontaneously in neural circuits with random, clustered connectivity rather than pre-configured spatial maps. Moreover, the realistic place fields themselves arise in the circuit from minimal, landmark-based inputs. We find that preplay quality depends on the network's balance of cluster isolation and overlap, with optimal preplay occurring in small-world regimes of high clustering yet short path lengths. We validate the results of our model by applying the same place field and preplay analyses to previously published rat hippocampal place cell data. Our results show that clustered recurrent connectivity can generate spontaneous preplay and immediate replay of novel environments. These findings support a framework whereby novel sensory experiences become associated with preexisting "pluripotent" internal neural activity patterns.

Stereotypical Hippocampal Clustering Predicts Navigational Success in Virtualized Real-World Environments.

Structural differences along the hippocampal long axis are believed to underlie meaningful functional differences. Yet, recent data-driven parcellations of the hippocampus subdivide the hippocampus into a 10-cluster map with anterior-medial, anterior-lateral, and posteroanterior-lateral, middle, and posterior components. We tested whether task and experience could modulate this clustering using a spatial learning experiment where male and female participants were trained to virtually navigate a novel neighborhood in a Google Street View-like environment. Participants were scanned while navigating routes early in training and after a 2 week training period. Using the 10-cluster map as the ideal template, we found that participants who eventually learn the neighborhood well have hippocampal cluster maps consistent with the ideal-even on their second day of learning-and their cluster mappings do not deviate over the 2 week training period. However, participants who eventually learn the neighborhood poorly begin with hippocampal cluster maps inconsistent with the ideal template, though their cluster mappings may become more stereotypical after the 2 week training. Interestingly this improvement seems to be route specific: after some early improvement, when a new route is navigated, participants' hippocampal maps revert back to less stereotypical organization. We conclude that hippocampal clustering is not dependent solely on anatomical structure and instead is driven by a combination of anatomy, task, and, importantly, experience. Nonetheless, while hippocampal clustering can change with experience, efficient navigation depends on functional hippocampal activity clustering in a stereotypical manner, highlighting optimal divisions of processing along the hippocampal anterior-posterior and medial-lateral axes.

Mnemonics for the use and interpretation of amplitude-integrated electroencephalography in newborn infants.

An electroencephalography (EEG) has always been considered a specialized field, whose use and interpretation requires training. For this reason, access to these monitoring studies has been restricted to neurologists and neurophysiologists. Newborn infants admitted to the neonatal intensive care unit (NICU) require neurophysiological monitoring to establish their diagnosis and prognosis, so a simple and accessible tool is required for NICU staff. Such features have been covered by amplitude-integrated electroencephalography (aEEG), which, through simple visual patterns of brain activity, allows to approach neurological conditions. The objective of this study is to help with the management of mnemonics that facilitate the identification of normal and pathological visual patterns in an aEEG. Although simple in appearance, this nomenclature is intended to create an easy-to-understand idea of basic concepts for the use and interpretation of neurophysiological monitoring with aEEG.

General mechanisms of task engagement in the primate frontal cortex

Staying engaged is necessary to maintain goal-directed behaviors. Despite this, engagement exhibits continuous, intrinsic fluctuations. Even in experimental settings, animals, unlike most humans, repeatedly and spontaneously move between periods of complete task engagement and disengagement. We, therefore, looked at behavior in male macaques (macaca mulatta) in four tasks while recording fMRI signals. We identified consistent autocorrelation in task disengagement. This made it possible to build models capturing task-independent engagement. We identified task general patterns of neural activity linked to impending sudden task disengagement in mid-cingulate gyrus. By contrast, activity centered in perigenual anterior cingulate cortex (pgACC) was associated with maintenance of performance across tasks. Importantly, we carefully controlled for task-specific factors such as the reward history and other motivational effects, such as response vigor, in our analyses. Moreover, we showed pgACC activity had a causal link to task engagement: transcranial ultrasound stimulation of pgACC changed task engagement patterns.

Functional Dynamics and Selectivity of Two Parallel Corticocortical Pathways from Motor Cortex to Layer 5 Circuits in Somatosensory Cortex.

In the rodent whisker system, active sensing and sensorimotor integration are mediated in part by the dynamic interactions between the motor cortex (M1) and somatosensory cortex (S1). However, understanding these dynamic interactions requires knowledge about the synapses and how specific neurons respond to their input. Here, we combined optogenetics, retrograde labeling, and electrophysiology to characterize the synaptic connections between M1 and layer 5 (L5) intratelencephalic (IT) and pyramidal tract (PT) neurons in S1 of mice (both sexes). We found that M1 synapses onto IT cells displayed modest short-term depression, whereas synapses onto PT neurons showed robust short-term facilitation. Despite M1 inputs to IT cells depressing, their slower kinetics resulted in summation and a response that increased during short trains. In contrast, summation was minimal in PT neurons due to the fast time course of their M1 responses. The functional consequences of this reduced summation, however, were outweighed by the strong facilitation at these M1 synapses, resulting in larger response amplitudes in PT neurons than IT cells during repetitive stimulation. To understand the impact of facilitating M1 inputs on PT output, we paired trains of inputs with single backpropagating action potentials, finding that repetitive M1 activation increased the probability of bursts in PT cells without impacting the time dependence of this coupling. Thus, there are two parallel but dynamically distinct systems of M1 synaptic excitation in L5 of S1, each defined by the short-term dynamics of its synapses, the class of postsynaptic neurons, and how the neurons respond to those inputs.

Pain and subjective well-being among older adults in the developing world : A comprehensive assessment based on the WHO Study on Global Ageing and Adult Health

This paper studies the association of pain with subjective well-being (SWB) and time use among older adults in five low- and middle-income countries using data from the first wave of the WHO Study on Global Ageing and Adult Health. We suggest a novel use of anchoring vignettes as direct control functions to account for potentially correlated reporting behaviors such as correlated response scales when analyzing the relationship between subjective variables such as self-reported pain and SWB. Exploiting detailed data on individual time use and several complementary measures of SWB, including fine-grained activity-specific affective experiences derived from an abbreviated version of the Day Reconstruction Method, we find that both evaluative and experienced well-being are markedly lower for people living with pain compared to those without pain. These disparities persist even after controlling for possible confounding from reporting behaviors through the use of anchoring vignettes. Differences in experienced utility by pain status appear to be exclusively due to worse affective experiences during daily activities for those with pain, which seem to be partially mediated through changes in their functional limitations. Pain-related differences in time use, in turn, seem to provide only small compensating effects, underscoring important challenges to the use of changed activity patterns as a viable coping strategy for individuals enduring pain.

Representations of imaginary scenes and their properties in cortical alpha activity

Imagining natural scenes enables us to engage with a myriad of simulated environments. How do our brains generate such complex mental images? Recent research suggests that cortical alpha activity carries information about individual objects during visual imagery. However, it remains unclear if more complex imagined contents such as natural scenes are similarly represented in alpha activity. Here, we answer this question by decoding the contents of imagined scenes from rhythmic cortical activity patterns. In an EEG experiment, participants imagined natural scenes based on detailed written descriptions, which conveyed four complementary scene properties: openness, naturalness, clutter level and brightness. By conducting classification analyses on EEG power patterns across neural frequencies, we were able to decode both individual imagined scenes as well as their properties from the alpha band, showing that also the contents of complex visual images are represented in alpha rhythms. A cross-classification analysis between alpha power patterns during the imagery task and during a perception task, in which participants were presented images of the described scenes, showed that scene representations in the alpha band are partly shared between imagery and late stages of perception. This suggests that alpha activity mediates the top-down re-activation of scene-related visual contents during imagery.

Circadian pattern in attendance of aphid colonies by ants

Ant-attendance of aphids is one of the subjects of interest in ecological studies as a reciprocal service providing benefits to both groups involved. The behavioural patterns in this relation depend on many factors, e.g. biology of the species involved, aphid host plants, activity of natural enemies and abiotic factors. In this respect, the circadian pattern of ant-attendance was almost unknown. The paper presents the results of the pattern of such circadian activity of ants Lasius niger and L. emarginatus attending six aphid species (Panaphis juglandis, Aphis grossulariae, A. urticata, A. umbrella, Myzus persicae and Aphis fabae) feeding on various types of plants and having various dependence of trophobiosis. The highest number of ant workers in aphid colonies was observed at night and dawn, while the lowest was just after solar noon. The circadian pattern of ant activity strongly depends on the weather, especially temperature and relative humidity, with the highest abundance of ants during humid and cool weather. The possible interconnection between the temperature-dependent activity of ants and the water-dependent physiological condition of certain plants is discussed and indicated as an explanation. The issue of possible work division among ant workers attending aphids as an explanation of the observed pattern of activity remains open.

Natural scenes reveal diverse representations of 2D and 3D body pose in the human brain

Human pose, defined as the spatial relationships between body parts, carries instrumental information supporting the understanding of motion and action of a person. A substantial body of previous work has identified cortical areas responsive to images of bodies and different body parts. However, the neural basis underlying the visual perception of body part relationships has received less attention. To broaden our understanding of body perception, we analyzed high-resolution fMRI responses to a wide range of poses from over 4,000 complex natural scenes. Using ground-truth annotations and an application of three-dimensional (3D) pose reconstruction algorithms, we compared similarity patterns of cortical activity with similarity patterns built from human pose models with different levels of depth availability and viewpoint dependency. Targeting the challenge of explaining variance in complex natural image responses with interpretable models, we achieved statistically significant correlations between pose models and cortical activity patterns (though performance levels are substantially lower than the noise ceiling). We found that the 3D view-independent pose model, compared with two-dimensional models, better captures the activation from distinct cortical areas, including the right posterior superior temporal sulcus (pSTS). These areas, together with other pose-selective regions in the LOTC, form a broader, distributed cortical network with greater view-tolerance in more anterior patches. We interpret these findings in light of the computational complexity of natural body images, the wide range of visual tasks supported by pose structures, and possible shared principles for view-invariant processing between articulated objects and ordinary, rigid objects.

The COMBO window: A chronic cranial implant for multiscale circuit interrogation in mice.

Neuroscientists studying the neural correlates of mouse behavior often lack access to the brain-wide activity patterns elicited during a specific task of interest. Fortunately, large-scale imaging is becoming increasingly accessible thanks to modalities such as Ca2+ imaging and functional ultrasound (fUS). However, these and other techniques often involve challenging cranial window procedures and are difficult to combine with other neuroscience tools. We address this need with an open-source 3D-printable cranial implant-the COMBO (ChrOnic Multimodal imaging and Behavioral Observation) window. The COMBO window enables chronic imaging of large portions of the brain in head-fixed mice while preserving orofacial movements. We validate the COMBO window stability using both brain-wide fUS and multisite two-photon imaging. Moreover, we demonstrate how the COMBO window facilitates the combination of optogenetics, fUS, and electrophysiology in the same animals to study the effects of circuit perturbations at both the brain-wide and single-neuron level. Overall, the COMBO window provides a versatile solution for performing multimodal brain recordings in head-fixed mice.

Ultrasonic cerebrospinal fluid clearance improves outcomes in hemorrhagic brain injury models.

Impaired clearance of the byproducts of aging and neurologic disease from the brain exacerbates disease progression and severity. We have developed a noninvasive, low intensity transcranial focused ultrasound protocol that facilitates the removal of pathogenic substances from the cerebrospinal fluid (CSF) and the brain interstitium. This protocol clears neurofilament light chain (NfL) - an aging byproduct - in aged mice and clears red blood cells (RBCs) from the central nervous system in two mouse models of hemorrhagic brain injury. Cleared RBCs accumulate in the cervical lymph nodes from both the CSF and interstitial compartments, indicating clearance through meningeal lymphatics. Treating these hemorrhagic brain injury models with this ultrasound protocol reduced neuroinflammatory and neurocytotoxic profiles, improved behavioral outcomes, decreased morbidity and, importantly, increased survival. RBC clearance efficacy was blocked by mechanosensitive channel antagonism and was effective when applied in anesthetized subjects, indicating a mechanosensitive channel mediated mechanism that does not depend on sensory stimulation or a specific neural activity pattern. Notably, this protocol qualifies for an FDA non-significant risk designation given its low intensity, making it readily clinically translatable. Overall, our results demonstrate that this low-intensity transcranial focused ultrasound protocol clears hemorrhage and other harmful substances from the brain via the meningeal lymphatic system, potentially offering a novel therapeutic tool for varied neurologic disorders.

Noise or signal? Spontaneous activity of dorsal horn neurons: patterns and function in health and disease.

Spontaneous activity refers to the firing of action potentials by neurons in the absence of external stimulation. Initially considered an artifact or "noise" in the nervous system, it is now recognized as a potential feature of neural function. Spontaneous activity has been observed in various brain areas, in experimental preparations from different animal species, and in live animals and humans using non-invasive imaging techniques. In this review, we specifically focus on the spontaneous activity of dorsal horn neurons of the spinal cord. We use a historical perspective to set the basis for a novel classification of the different patterns of spontaneous activity exhibited by dorsal horn neurons. Then we examine the origins of this activity and propose a model circuit to explain how the activity is generated and transmitted to the dorsal horn. Finally, we discuss possible roles of this activity during development and during signal processing under physiological conditions and pain states. By analyzing recent studies on the spontaneous activity of dorsal horn neurons, we aim to shed light on its significance in sensory processing. Understanding the different patterns of activity, the origins of this activity, and the potential roles it may play, will contribute to our knowledge of sensory mechanisms, including pain, to facilitate the modeling of spinal circuits and hopefully to explore novel strategies for pain treatment.

Artificial light at night drives diel activity patterns of synanthropic pipistrelle bats and their prey

The use of artificial light at night (ALAN) has increased drastically worldwide over the last decades. ALAN can have major effects on nocturnal communities, including insects and bats. Insects are attracted to street lights and few bat species take advantage of this by foraging on the attracted insects. ALAN potentially affects the temporal patterns of insect abundance and thereby bat foraging behaviour. In a natural dark environment, these patterns are usually bimodal, with an activity peak in the early evening and the morning. Little is known about how ALAN affects insect presence throughout the night, and whether the light spectrum plays a role. This is important, as these temporal changes may be a key driver of disturbances in bat-insect interactions. Here, we studied how white and red light affect insects' and bats' nightly activity patterns. The activity of insects and bats (Pipistrellus spp.) was recorded throughout the night at seven experimentally illuminated sites in a forest-edge ecosystem. ALAN disrupted activity patterns, with both insects and bats being more active throughout the night. ALAN facilitated all-night foraging in bats especially near white light, but these effects were attenuated near red light. The ability to forage throughout the night may be a key advantage causing synanthropic bats to dominate in illuminated environments, but this could also prove detrimental in the long term. As red light reduced disturbing effects of ALAN on insects and bats diel activity pattern, it opens the possibility of using spectral composition as a mitigation measure.

Topology of surface electromyogram signals: hand gesture decoding on Riemannian manifolds

Objective. Decoding gestures from the upper limb using noninvasive surface electromyogram (sEMG) signals is of keen interest for the rehabilitation of amputees, artificial supernumerary limb augmentation, gestural control of computers, and virtual/augmented realities. We show that sEMG signals recorded across an array of sensor electrodes in multiple spatial locations around the forearm evince a rich geometric pattern of global motor unit (MU) activity that can be leveraged to distinguish different hand gestures. Approach. We demonstrate a simple technique to analyze spatial patterns of muscle MU activity within a temporal window and show that distinct gestures can be classified in both supervised and unsupervised manners. Specifically, we construct symmetric positive definite covariance matrices to represent the spatial distribution of MU activity in a time window of interest, calculated as pairwise covariance of electrical signals measured across different electrodes. Main results. This allows us to understand and manipulate multivariate sEMG timeseries on a more natural subspace—the Riemannian manifold. Furthermore, it directly addresses signal variability across individuals and sessions, which remains a major challenge in the field. sEMG signals measured at a single electrode lack contextual information such as how various anatomical and physiological factors influence the signals and how their combined effect alters the evident interaction among neighboring muscles. Significance. As we show here, analyzing spatial patterns using covariance matrices on Riemannian manifolds allows us to robustly model complex interactions across spatially distributed MUs and provides a flexible and transparent framework to quantify differences in sEMG signals across individuals. The proposed method is novel in the study of sEMG signals and its performance exceeds the current benchmarks while being computationally efficient.

Nonfrontal Control of Working Memory.

Items held in visual working memory can be quickly updated, replaced, removed, and even manipulated in accordance with current behavioral goals. Here, we use multivariate pattern analyses to identify the patterns of neuronal activity that realize the executive control processes supervising these flexible stores. We find that portions of the middle temporal gyrus and the intraparietal sulcus represent what item is cued for continued memorization independently of representations of the item itself. Importantly, this selection-specific activity could not be explained by sensory representations of the cue and is only present when control is exerted. Our results suggest that the selection of memorized items might be controlled in a distributed and decentralized fashion. This evidence provides an alternative perspective to the notion of "domain general" central executive control over memory function.

Irregular optogenetic stimulation waveforms can induce naturalistic patterns of hippocampal spectral activity

Objective. Therapeutic brain stimulation is conventionally delivered using constant-frequency stimulation pulses. Several recent clinical studies have explored how unconventional and irregular temporal stimulation patterns could enable better therapy. However, it is challenging to understand which irregular patterns are most effective for different therapeutic applications given the massively high-dimensional parameter space. Approach. Here we applied many irregular stimulation patterns in a single neural circuit to demonstrate how they can enable new dimensions of neural control compared to conventional stimulation, to guide future exploration of novel stimulation patterns in translational settings. We optogenetically excited the septohippocampal circuit with constant-frequency, nested pulse, sinusoidal, and randomized stimulation waveforms, systematically varying their amplitude and frequency parameters. Main results. We first found equal entrainment of hippocampal oscillations: all waveforms provided similar gamma-power increase, whereas no parameters increased theta-band power above baseline (despite the mechanistic role of the medial septum in driving hippocampal theta oscillations). We then compared each of the effects of each waveform on high-dimensional multi-band activity states using dimensionality reduction methods. Strikingly, we found that conventional stimulation drove predominantly ‘artificial’ (different from behavioral activity) effects, whereas all irregular waveforms induced activity patterns that more closely resembled behavioral activity. Significance. Our findings suggest that irregular stimulation patterns are not useful when the desired mechanism is to suppress or enhance a single frequency band. However, novel stimulation patterns may provide the greatest benefit for neural control applications where entraining a particular mixture of bands (e.g. if they are associated with different symptoms) or behaviorally-relevant activity is desired.

Proactive cursorial and ambush predation risk avoidance in four African herbivore species.

Most herbivores must balance demands to meet nutritional requirements, maintain stable thermoregulation and avoid predation. Species-specific predator and prey characteristics determine the ability of prey to avoid predation and the ability of predators to maximize hunting success. Using GPS collar data from African wild dogs, lions, impala, tsessebes, wildebeest and zebra in the Okavango Delta, Botswana, we studied proactive predation risk avoidance by herbivores. We considered predator activity level in relation to prey movement, predator and prey habitat selection, and preferential use of areas by prey. We compared herbivore behaviour to lion and wild dog activity patterns and determined the effect of seasonal resource availability and prey body mass on anti-predator behaviour. Herbivore movement patterns were more strongly correlated with lion than wild dog activity. Habitat selection by predators was not activity level dependent and, while prey and predators differed to some extent in their habitat selection, there were also overlaps, probably caused by predators seeking habitats with high prey abundance. Areas favoured by lions were used by herbivores more when lions were less active, whereas wild dog activity level was not correlated with prey use. Prey body mass was not a strong predictor of the strength of proactive predation avoidance behaviour. Herbivores showed stronger anti-predator behaviours during the rainy season when resources were abundant. Reducing movement when top predators are most active and avoiding areas with a high likelihood of predator use during the same periods appear to be common strategies to minimize predation risk. Such valuable insights into predator-prey dynamics are only possible when using similar data from multiple sympatric species of predator and prey, an approach that should become more prevalent given the ongoing integration of technological methods into ecological studies.

Reconstruction of Population-Level Migration Trajectories of Black-Faced Spoonbill (Platalea minor) Based on Citizen Science Data.

Migration is a critical ecological process for birds. Understanding avian migratory routes is essential for identifying important stopover sites and key foraging areas to ensure high-quality stopovers for birds. The Black-faced Spoonbill (Platalea minor), a national Grade I protected wild animal in China, is classified as endangered on the IUCN Red List of Threatened Species. Studying the migratory routes of the Black-faced Spoonbill and identifying critical stopover sites across different life histories is vital for its conservation. However, research on the migratory routes of this species has been very limited. This study, utilizing citizen science data and the Level-order-Minimum-cost-Traversal (LoMcT) algorithm, reconstructs the migratory trajectories of the Black-faced Spoonbill from 2018 to 2022. The results show that Wenzhou, Xiamen, Shantou, Shanwei, Hsinchu, Chiayi, and Tainan are significant stopovers for this species. The Black-faced Spoonbill is actively migratory during the migration season across the southeastern coastal region of China. The simulation results of this study reveal the migratory routes and activity patterns of the Black-faced Spoonbill, providing critical support for its conservation.