scholarly journals A hybrid versatile method for state estimation and feature extraction from the trajectory of animal behavior

2017 ◽  
Author(s):  
Shuhei J. Yamazaki ◽  
Kazuya Ohara ◽  
Kentaro Ito ◽  
Nobuo Kokubun ◽  
Takuma Kitanishi ◽  
...  

ABSTRACTAnimal behavior is the final and integrated output of the brain activity. Thus, recording and analyzing behavior is critical to understand the underlying brain function. While recording animal behavior has become easier than ever with the development of compact and inexpensive devices, detailed behavioral data analysis requires sufficient previous knowledge and/or high content data such as video images of animal postures, which makes it difficult for most of the animal behavioral data to be efficiently analyzed to understand brain function. Here, we report a versatile method using a hybrid supervised/unsupervised machine learning approach to efficiently estimate behavioral states and to extract important behavioral features only from low-content animal trajectory data. As proof of principle experiments, we analyzed trajectory data of worms, fruit flies, rats, and bats in the laboratories, and penguins and flying seabirds in the wild, which were recorded with various methods and span a wide range of spatiotemporal scales—from mm to 1000 km in space and from sub-seconds to days in time. We estimated several states during behavior and comprehensively extracted characteristic features from a behavioral state and/or a specific experimental condition. Physiological and genetic experiments in worms revealed that the extracted behavioral features reflected specific neural or gene activities. Thus, our method provides a versatile and unbiased way to extract behavioral features from simple trajectory data to understand brain function.

2020 ◽  
Author(s):  
Jonathan Wirsich ◽  
João Jorge ◽  
Giannina R Iannotti ◽  
Elhum A Shamshiri ◽  
Frédéric Grouiller ◽  
...  

AbstractBoth electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are non-invasive methods that show complementary aspects of human brain activity. Despite their differences in probing brain activity, both electrophysiology and BOLD signal can map the underlying functional connectivity structure at the whole brain scale at different timescales. Previous work demonstrated a moderate but significant correlation between resting-state functional connectivity of both modalities, however there is a wide range of technical setups to measure simultaneous EEG-fMRI and the reliability of those measures between different setups remains unknown. This is true notably with respect to different magnetic field strengths (low and high field) and different spatial sampling of EEG (medium to high-density electrode coverage).Here, we investigated the reliability of the bimodal EEG-fMRI functional connectome in the most comprehensive resting-state simultaneous EEG-fMRI dataset compiled to date including a total of 72 subjects from four different imaging centers. Data was acquired from 1.5T, 3T and 7T scanners with simultaneously recorded EEG using 64 or 256 electrodes. We demonstrate that the whole-brain monomodal connectivity reliably correlates across different datasets and that the crossmodal correlation between EEG and fMRI connectivity of r≈0.3 can be reliably extracted in low and high-field scanners. The crossmodal correlation was strongest in the EEG-β frequency band but exists across all frequency bands. Both homotopic and withing intrinsic connectivity network (ICN) connections contributed the most to the crossmodal relationship.This study confirms, using a considerably diverse range of recording setups, that simultaneous EEG-fMRI offers a consistent estimate of multimodal functional connectomes in healthy subjects being organized into reliable ICNs across different timescales. This opens new avenues for estimating the dynamics of brain function and provides a better understanding of interactions between EEG and fMRI measures. Alterations of this coupling could be explored as a potential clinical marker of pathological brain function.


2009 ◽  
Vol 23 (4) ◽  
pp. 191-198 ◽  
Author(s):  
Suzannah K. Helps ◽  
Samantha J. Broyd ◽  
Christopher J. James ◽  
Anke Karl ◽  
Edmund J. S. Sonuga-Barke

Background: The default mode interference hypothesis ( Sonuga-Barke & Castellanos, 2007 ) predicts (1) the attenuation of very low frequency oscillations (VLFO; e.g., .05 Hz) in brain activity within the default mode network during the transition from rest to task, and (2) that failures to attenuate in this way will lead to an increased likelihood of periodic attention lapses that are synchronized to the VLFO pattern. Here, we tested these predictions using DC-EEG recordings within and outside of a previously identified network of electrode locations hypothesized to reflect DMN activity (i.e., S3 network; Helps et al., 2008 ). Method: 24 young adults (mean age 22.3 years; 8 male), sampled to include a wide range of ADHD symptoms, took part in a study of rest to task transitions. Two conditions were compared: 5 min of rest (eyes open) and a 10-min simple 2-choice RT task with a relatively high sampling rate (ISI 1 s). DC-EEG was recorded during both conditions, and the low-frequency spectrum was decomposed and measures of the power within specific bands extracted. Results: Shift from rest to task led to an attenuation of VLFO activity within the S3 network which was inversely associated with ADHD symptoms. RT during task also showed a VLFO signature. During task there was a small but significant degree of synchronization between EEG and RT in the VLFO band. Attenuators showed a lower degree of synchrony than nonattenuators. Discussion: The results provide some initial EEG-based support for the default mode interference hypothesis and suggest that failure to attenuate VLFO in the S3 network is associated with higher synchrony between low-frequency brain activity and RT fluctuations during a simple RT task. Although significant, the effects were small and future research should employ tasks with a higher sampling rate to increase the possibility of extracting robust and stable signals.


2020 ◽  
Vol 19 (7) ◽  
pp. 509-526
Author(s):  
Qin Huang ◽  
Fang Yu ◽  
Di Liao ◽  
Jian Xia

: Recent studies implicate microbiota-brain communication as an essential factor for physiology and pathophysiology in brain function and neurodevelopment. One of the pivotal mechanisms about gut to brain communication is through the regulation and interaction of gut microbiota on the host immune system. In this review, we will discuss the role of microbiota-immune systeminteractions in human neurological disorders. The characteristic features in the development of neurological diseases include gut dysbiosis, the disturbed intestinal/Blood-Brain Barrier (BBB) permeability, the activated inflammatory response, and the changed microbial metabolites. Neurological disorders contribute to gut dysbiosis and some relevant metabolites in a top-down way. In turn, the activated immune system induced by the change of gut microbiota may deteriorate the development of neurological diseases through the disturbed gut/BBB barrier in a down-top way. Understanding the characterization and identification of microbiome-immune- brain signaling pathways will help us to yield novel therapeutic strategies by targeting the gut microbiome in neurological disease.


Studies of animal behavior often assume that all members of a species exhibit the same behavior. Geographic Variation in Behavior shows that, on the contrary, there is substantional variation within species across a wide range of taxa. Including work from pioneers in the field, this volume provides a balanced overview of research on behavioral characteristics that vary geographically. The authors explore the mechanisms by which behavioral differences evolve and examine related methodological issues. Taken together, the work collected here demonstrates that genetically based geographic variation may be far more widespread than previously suspected. The book also shows how variation in behavior can illuminate both behavioral evolution and general evolutionary patterns. Unique among books on behavior in its emphasis on geographic variation, this volume is a valuable new resource for students and researchers in animal behavior and evolutionary biology.


Author(s):  
Belden C. Lane

Carrying only basic camping equipment and a collection of the world's great spiritual writings, Belden C. Lane embarks on solitary spiritual treks through the Ozarks and across the American Southwest. For companions, he has only such teachers as Rumi, John of the Cross, Hildegard of Bingen, Dag Hammarskjöld, and Thomas Merton, and as he walks, he engages their writings with the natural wonders he encounters--Bell Mountain Wilderness with Søren Kierkegaard, Moonshine Hollow with Thich Nhat Hanh--demonstrating how being alone in the wild opens a rare view onto one's interior landscape, and how the saints' writings reveal the divine in nature. The discipline of backpacking, Lane shows, is a metaphor for a spiritual journey. Just as the wilderness offered revelations to the early Desert Christians, backpacking hones crucial spiritual skills: paying attention, traveling light, practicing silence, and exercising wonder. Lane engages the practice not only with a wide range of spiritual writings--Celtic, Catholic, Protestant, Buddhist, Hindu, and Sufi Muslim--but with the fascination of other lovers of the backcountry, from John Muir and Ed Abbey to Bill Plotkin and Cheryl Strayed. In this intimate and down-to-earth narrative, backpacking is shown to be a spiritual practice that allows the discovery of God amidst the beauty and unexpected terrors of nature. Adoration, Lane suggests, is the most appropriate human response to what we cannot explain, but have nonetheless learned to love. An enchanting narrative for Christians of all denominations, Backpacking with the Saints is an inspiring exploration of how solitude, simplicity, and mindfulness are illuminated and encouraged by the discipline of backcountry wandering, and of how the wilderness itself becomes a way of knowing-an ecology of the soul.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kaicheng Li ◽  
Xiao Luo ◽  
Qingze Zeng ◽  
Yerfan Jiaerken ◽  
Shuyue Wang ◽  
...  

AbstractThough sleep disturbance constitutes the risk factor for Alzheimer’s disease (AD), the underlying mechanism is still unclear. This study aims to explore the interaction between sleep disturbances and AD on brain function. We included 192 normal controls, 111 mild cognitive impairment (MCI), and 30 AD patients, with either poor or normal sleep (PS, NS, respectively). To explore the strength and stability of brain activity, we used static amplitude of low-frequency fluctuation (sALFF) and dynamic ALFF (dALFF) variance. Further, we examined white matter hyperintensities (WMH) and amyloid PET deposition, representing the vascular risk factor and AD-related hallmark, respectively. We observed that sleep disturbance significantly interacted with disease severity, exposing distinct effects on sALFF and dALFF variance. Interestingly, PS groups showed the dALFF variance trajectory of initially increased, then decreased and finally increased along the AD spectrum, while showing the opposite trajectory of sALFF. Further correlation analysis showed that the WMH burden correlates with dALFF variance in PS groups. Conclusively, our study suggested that sleep disturbance interacts with AD severity, expressing as effects of compensatory in MCI and de-compensatory in AD, respectively. Further, vascular impairment might act as important pathogenesis underlying the interaction effect between sleep and AD.


2021 ◽  
Vol 9 (7_suppl3) ◽  
pp. 2325967121S0013
Author(s):  
Manish Anand ◽  
Jed A. Diekfuss ◽  
Dustin R. Grooms ◽  
Alexis B. Slutsky-Ganesh ◽  
Scott Bonnette ◽  
...  

Background: Aberrant frontal and sagittal plane knee motor control biomechanics contribute to increased anterior cruciate ligament (ACL) injury risk. Emergent data further indicates alterations in brain function may underlie ACL injury high risk biomechanics and primary injury. However, technical limitations have limited our ability to assess direct linkages between maladaptive biomechanics and brain function. Hypothesis/Purpose: (1) Increased frontal plane knee range of motion would associate with altered brain activity in regions important for sensorimotor control and (2) increased sagittal plane knee motor control timing error would associate with altered activity in sensorimotor control brain regions. Methods: Eighteen female high-school basketball and volleyball players (14.7 ± 1.4 years, 169.5 ± 7 cm, 65.8 ± 20.5 kg) underwent brain functional magnetic resonance imaging (fMRI) while performing a bilateral, combined hip, knee, and ankle flexion/extension movements against resistance (i.e., leg press) Figure 1(a). The participants completed this task to a reference beat of 1.2 Hz during four movement blocks of 30 seconds each interleaved in between 5 rest blocks of 30 seconds each. Concurrent frontal and sagittal plane range of motion (ROM) kinematics were measured using an MRI-compatible single camera motion capture system. Results: Increased frontal plane ROM was associated with increased brain activity in one cluster extending over the occipital fusiform gyrus and lingual gyrus ( p = .003, z > 3.1). Increased sagittal plane motor control timing error was associated with increased brain activity in multiple clusters extending over the occipital cortex (lingual gyrus), frontal cortex, and anterior cingulate cortex ( p < .001, z > 3.1); see Figure 1 (b). Conclusion: The associations of increased knee frontal plane ROM and sagittal plane timing error with increased activity in regions that integrate visuospatial information may be indicative of an increased propensity for knee injury biomechanics that are, in part, driven by reduced spatial awareness and an inability to adequately control knee abduction motion. Increased activation in these regions during movement tasks may underlie an impaired ability to control movements (i.e., less neural efficiency), leading to compromised knee positions during more complex sports scenarios. Increased activity in regions important for cognition/attention associating with motor control timing error further indicates a neurologically inefficient motor control strategy. [Figure: see text]


Author(s):  
Francisco Arcas-Tunez ◽  
Fernando Terroso-Saenz

The development of Road Information Acquisition Systems (RIASs) based on the Mobile Crowdsensing (MCS) paradigm has been widely studied for the last years. In that sense, most of the existing MCS-based RIASs focus on urban road networks and assume a car-based scenario. However, there exist a scarcity of approaches that pay attention to rural and country road networks. In that sense, forest paths are used for a wide range of recreational and sport activities by many different people and they can be also affected by different problems or obstacles blocking them. As a result, this work introduces SAMARITAN, a framework for rural-road network monitoring based on MCS. SAMARITAN analyzes the spatio-temporal trajectories from cyclists extracted from the fitness application Strava so as to uncover potential obstacles in a target road network. The framework has been evaluated in a real-world network of forest paths in the city of Cieza (Spain) showing quite promising results.


2017 ◽  
Vol 24 (3) ◽  
pp. 277-293 ◽  
Author(s):  
Selen Atasoy ◽  
Gustavo Deco ◽  
Morten L. Kringelbach ◽  
Joel Pearson

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at “rest.” Here, we introduce the concept of harmonic brain modes—fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.


1982 ◽  
Vol 57 (3) ◽  
pp. 309-315
Author(s):  
Mortimer J. Adler

✓ In his 1982 Cushing oration, a distinguished philosopher, author, and discerning critic presents a distillate of his phenomenally wide range of personal experience and his familiarity with the great books and teachers of the present and the past. He explores the differences and relationships between human beings, brute animals, and machines. Knowledge of the brain and nervous system contribute to the explanation of all aspects of animal behavior, intelligence, and mentality, but cannot completely explain human conceptual thought.


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