scholarly journals Post-weaning stroking stimuli induce affiliative behavior toward humans and influence brain activity in female rats

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shota Okabe ◽  
Yuki Takayanagi ◽  
Masahide Yoshida ◽  
Tatsushi Onaka
Keyword(s):  
Neural Activity ◽  
Positive Emotion ◽  
Brain Activity ◽  
Brain Regions ◽  
Female Rats ◽  
Control Group ◽  
Affiliative Behavior ◽  
Hypothalamic Neurons ◽  
Affiliative Behaviors

AbstractGentle touch contributes to affiliative interactions. We investigated the effects of gentle stroking in female rats on the development of affiliative behaviors toward humans and we exploratively examined brain regions in which activity was influenced by stroking. Rats that had received stroking stimuli repeatedly after weaning emitted 50-kHz calls, an index of positive emotion, and showed affiliative behaviors toward the experimenter. Hypothalamic paraventricular oxytocin neurons were activated in the rats after stroking. The septohypothalamic nucleus (SHy) in the post-weaningly stroked rats showed decreased activity in response to stroking stimuli compared with that in the non-stroked control group. There were negative correlations of neural activity in hypothalamic regions including the SHy with the number of 50-kHz calls. These findings revealed that post-weaning stroking induces an affiliative relationship between female rats and humans, possibly via activation of oxytocin neurons and suppression of the activity of hypothalamic neurons.

Abstract WMP117: Regional Homogeneity Changes In Patients With Transient Ischemic Attack: A Resting-state Functional Magnetic Resonance Imaging Study

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Jian Guo ◽  
Ning Chen ◽  
Muke Zhou ◽  
Pian Wang ◽  
Li He
Keyword(s):  
Transient Ischemic Attack ◽  
Neural Activity ◽  
Resting State ◽  
Right Hemisphere ◽  
Brain Activity ◽  
Imaging Study ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
Anterior Cingulate ◽  
Ischemic Attack

Background: Transient ischemic attack (TIA) can increase the risk of some neurologic dysfunctions, of which the mechanism remains unclear. Resting-state functional MRI (rfMRI) is suggested to be a valuable tool to study the relation between spontaneous brain activity and behavioral performance. However, little is known about whether the local synchronization of spontaneous neural activity is altered in TIA patients. The purpose of this study is to detect differences in regional spontaneous activities throughout the whole brain between TIAs and normal controls. Methods: Twenty one TIA patients suffered an ischemic event in the right hemisphere and 21 healthy volunteers were enrolled in the study. All subjects were investigated using cognitive tests and rfMRI. The regional homogeneity (ReHo) was calculate and compared between two groups. Then a correlation analysis was performed to explore the relationship between ReHo values of brain regions showing abnormal resting-state properties and clinical variables in TIA group. Results: Compared with controls, TIA patients exhibited decreased ReHo in right dorsolateral prefrontal cortex (DLPFC), right inferior prefrontal gyrus, right ventral anterior cingulate cortex and right dorsal posterior cingular cortex. Moreover, the mean ReHo in right DLPFC and right inferior prefrontal gyrus were significantly correlated with MoCA in TIA patients. Conclusions: Neural activity in the resting state is changed in patients with TIA. The positive correlation between regional homogeneity of rfMRI and cognition suggests that ReHo may be a promising tool to better our understanding of the neurobiological consequences of TIA.

Reconstruction of Neural Activity from EEG Data Using Dynamic Spatiotemporal Constraints

2016 ◽  
Vol 26 (07) ◽  
pp. 1650026 ◽  
Author(s):  
E. Giraldo-Suarez ◽  
J. D. Martinez-Vargas ◽  
G. Castellanos-Dominguez
Keyword(s):  
Spatial Resolution ◽  
Neural Activity ◽  
Focal Epilepsy ◽  
Experimental Testing ◽  
Brain Activity ◽  
Brain Regions ◽  
Basis Set ◽  
Eeg Signals ◽  
Reconstruction Performance ◽  
Eeg Data

We present a novel iterative regularized algorithm (IRA) for neural activity reconstruction that explicitly includes spatiotemporal constraints, performing a trade-off between space and time resolutions. For improving the spatial accuracy provided by electroencephalography (EEG) signals, we explore a basis set that describes the smooth, localized areas of potentially active brain regions. In turn, we enhance the time resolution by adding the Markovian assumption for brain activity estimation at each time period. Moreover, to deal with applications that have either distributed or localized neural activity, the spatiotemporal constraints are expressed through [Formula: see text] and [Formula: see text] norms, respectively. For the purpose of validation, we estimate the neural reconstruction performance in time and space separately. Experimental testing is carried out on artificial data, simulating stationary and non-stationary EEG signals. Also, validation is accomplished on two real-world databases, one holding Evoked Potentials and another with EEG data of focal epilepsy. Moreover, responses of functional magnetic resonance imaging for the former EEG data have been measured in advance, allowing to contrast our findings. Obtained results show that the [Formula: see text]-based IRA produces a spatial resolution that is comparable to the one achieved by some widely used sparse-based estimators of brain activity. At the same time, the [Formula: see text]-based IRA outperforms other similar smooth solutions, providing a spatial resolution that is lower than the sparse [Formula: see text]-based solution. As a result, the proposed IRA is a promising method for improving the accuracy of brain activity reconstruction.

scholarly journals Representation of real-world event schemas during narrative perception

2018 ◽  
Author(s):  
Christopher Baldassano ◽  
Uri Hasson ◽  
Kenneth A. Norman
Keyword(s):  
Human Subjects ◽  
Brain Activity ◽  
Temporal Structure ◽  
Animal Experiments ◽  
Situation Model ◽  
Brain Regions ◽  
Control Group ◽  
Daily Lives ◽  
High Level ◽  
Almost All

AbstractUnderstanding movies and stories requires maintaining a high-level situation model that abstracts away from perceptual details to describe the location, characters, actions, and causal relationships of the currently unfolding event. These models are built not only from information present in the current narrative, but also from prior knowledge about schematic event scripts, which describe typical event sequences encountered throughout a lifetime. We analyzed fMRI data from 44 human subjects presented with sixteen three-minute stories, consisting of four schematic events drawn from two different scripts (eating at a restaurant or going through the airport). Aside from this shared script structure, the stories varied widely in terms of their characters and storylines, and were presented in two highly dissimilar formats (audiovisual clips or spoken narration). One group was presented with the stories in an intact temporal sequence, while a separate control group was presented with the same events in scrambled order. Regions including the posterior medial cortex, medial prefrontal cortex (mPFC), and superior frontal gyrus exhibited schematic event patterns that generalized across stories, subjects, and modalities. Patterns in mPFC were also sensitive to overall script structure, with temporally scrambled events evoking weaker schematic representations. Using a Hidden Markov Model, patterns in these regions can predict the script (restaurant vs. airport) of unlabeled data with high accuracy, and can be used to temporally align multiple stories with a shared script. These results extend work on the perception of controlled, artificial schemas in human and animal experiments to naturalistic perception of complex narrative stimuli.Significance StatementIn almost all situations we encounter in our daily lives, we are able to draw on our schematic knowledge about what typically happens in the world to better perceive and mentally represent our ongoing experiences. In contrast to previous studies that investigated schematic cognition using simple, artificial associations, we measured brain activity from subjects watching movies and listening to stories depicting restaurant or airport experiences. Our results reveal a network of brain regions that is sensitive to the shared temporal structure of these naturalistic situations. These regions abstract away from the particular details of each story, activating a representation of the general type of situation being perceived.

Default-Mode Activity during a Passive Sensory Task: Uncoupled from Deactivation but Impacting Activation

2004 ◽  
Vol 16 (9) ◽  
pp. 1484-1492 ◽  
Author(s):  
Michael D. Greicius ◽  
Vinod Menon
Keyword(s):  
Episodic Memory ◽  
Cognitive Processing ◽  
Neural Activity ◽  
Default Mode Network ◽  
Brain Activity ◽  
Block Design ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
High Demand ◽  
Default Mode

Deactivation refers to increased neural activity during low-demand tasks or rest compared with high-demand tasks. Several groups have reported that a particular set of brain regions, including the posterior cingulate cortex and the medial prefrontal cortex, among others, is consistently deactivated. Taken together, these typically deactivated brain regions appear to constitute a default-mode network of brain activity that predominates in the absence of a demanding external task. Examining a passive, block-design sensory task with a standard deactivation analysis (rest epochs vs. stimulus epochs), we demonstrate that the default-mode network is undetectable in one run and only partially detectable in a second run. Using independent component analysis, however, we were able to detect the full default-mode network in both runs and to demonstrate that, in the majority of subjects, it persisted across both rest and stimulus epochs, uncoupled from the task waveform, and so mostly undetectable as deactivation. We also replicate an earlier finding that the default-mode network includes the hippocampus suggesting that episodic memory is incorporated in default-mode cognitive processing. Furthermore, we show that the more a subject's default-mode activity was correlated with the rest epochs (and “deactivated” during stimulus epochs), the greater that subject's activation to the visual and auditory stimuli. We conclude that activity in the default-mode network may persist through both experimental and rest epochs if the experiment is not sufficiently challenging. Time-series analysis of default-mode activity provides a measure of the degree to which a task engages a subject and whether it is sufficient to interrupt the processes—presumably cognitive, internally generated, and involving episodic memory—mediated by the default-mode network.

scholarly journals Mindfulness Improves Brain Computer Interface Performance by Increasing Control over Neural Activity in the Alpha Band

2020 ◽  
Author(s):  
James R. Stieger ◽  
Stephen Engel ◽  
Haiteng Jiang ◽  
Christopher C. Cline ◽  
Mary Jo Kreitzer ◽  
...  
Keyword(s):  
Neural Activity ◽  
Resting State ◽  
Brain Activity ◽  
Large Population ◽  
Body Awareness ◽  
Mindfulness Practice ◽  
Control Group ◽  
Alpha Band ◽  
Attention Task ◽  
Band Activity

AbstractBrain-computer interfaces (BCIs) are promising tools for assisting patients with paralysis, but suffer from long training times and variable user proficiency. Mind-body awareness training (MBAT) can improve BCI learning, but how it does so remains unknown. Here we show that MBAT allows participants to learn to volitionally increase alpha band neural activity during BCI tasks that incorporate intentional rest. We trained individuals in mindfulness-based stress reduction (MBSR; a standardized MBAT intervention) and compared performance and brain activity before and after training between randomly assigned trained and untrained control groups. The MBAT group showed reliably faster learning of BCI than the control group throughout training. Alpha-band activity in EEG signals, recorded in the volitional resting state during task performance, showed a parallel increase over sessions, and predicted final BCI performance. The level of alpha-band activity during the intentional resting state correlated reliably with individuals’ mindfulness practice as well as performance on a sustained attention task. Collectively, these results show that MBAT modifies a specific neural signal used by BCI. MBAT, by increasing patients’ control over their brain activity during rest, may increase the effectiveness of BCI in the large population who could benefit from alternatives to direct motor control.

scholarly journals A spatiotemporal complexity architecture of human brain activity

2021 ◽  
Author(s):  
Stephan Krohn ◽  
Nina von Schwanenflug ◽  
Leonhard Waschke ◽  
Amy Romanello ◽  
Martin Gell ◽  
...  
Keyword(s):  
Human Brain ◽  
Neural Activity ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Organization ◽  
Functional Connections ◽  
Signal Complexity ◽  
The Brain

The human brain operates in large-scale functional networks, collectively subsumed as the functional connectome1-13. Recent work has begun to unravel the organization of the connectome, including the temporal dynamics of brain states14-20, the trade-off between segregation and integration9,15,21-23, and a functional hierarchy from lower-order unimodal to higher-order transmodal processing systems24-27. However, it remains unknown how these network properties are embedded in the brain and if they emerge from a common neural foundation. Here we apply time-resolved estimation of brain signal complexity to uncover a unifying principle of brain organization, linking the connectome to neural variability6,28-31. Using functional magnetic resonance imaging (fMRI), we show that neural activity is marked by spontaneous "complexity drops" that reflect episodes of increased pattern regularity in the brain, and that functional connections among brain regions are an expression of their simultaneous engagement in such episodes. Moreover, these complexity drops ubiquitously propagate along cortical hierarchies, suggesting that the brain intrinsically reiterates its own functional architecture. Globally, neural activity clusters into temporal complexity states that dynamically shape the coupling strength and configuration of the connectome, implementing a continuous re-negotiation between cost-efficient segregation and communication-enhancing integration9,15,21,23. Furthermore, complexity states resolve the recently discovered association between anatomical and functional network hierarchies comprehensively25-27,32. Finally, brain signal complexity is highly sensitive to age and reflects inter-individual differences in cognition and motor function. In sum, we identify a spatiotemporal complexity architecture of neural activity — a functional "complexome" that gives rise to the network organization of the human brain.

scholarly journals Late Frontal Negativity Discriminates Outcomes and Intentions in Trust-Repayment Behavior

2020 ◽  
Vol 11 ◽  
Author(s):  
Mauricio Aspé-Sánchez ◽  
Paola Mengotti ◽  
Raffaella Rumiati ◽  
Carlos Rodríguez-Sickert ◽  
John Ewer ◽  
...  
Keyword(s):  
Social Interaction ◽  
Cognitive Control ◽  
Neural Activity ◽  
Brain Activity ◽  
Brain Regions ◽  
Cortical Sources ◽  
Negative Reciprocity ◽  
Frontal Negativity ◽  
Neurophysiological Activity ◽  
Economic Interactions

Altruism (a costly action that benefits others) and reciprocity (the repayment of acts in kind) differ in that the former expresses preferences about the outcome of a social interaction, whereas the latter requires, in addition, ascribing intentions to others. Interestingly, an individual’s behavior and neurophysiological activity under outcome- versus intention-based interactions has not been compared directly using different endowments in the same subject and during the same session. Here, we used a mixed version of the Dictator and the Investment games, together with electroencephalography, to uncover a subject’s behavior and brain activity when challenged with endowments of different sizes in contexts that call for an altruistic (outcome-based) versus a reciprocal (intention-based) response. We found that subjects displayed positive or negative reciprocity (reciprocal responses greater or smaller than that for altruism, respectively) depending on the amount of trust they received. Furthermore, a subject’s late frontal negativity differed between conditions, predicting responses to trust in intentions-based trials. Finally, brain regions related with mentalizing and cognitive control were the cortical sources of this activity. Thus, our work disentangles the behavioral components present in the repayment of trust, and sheds light on the neural activity underlying the integration of outcomes and perceived intentions in human economic interactions.

scholarly journals TMS alters multivoxel patterns in the absence of overall activity changes

2020 ◽  
Author(s):  
Farshad Rafiei ◽  
Martin Safrin ◽  
Martijn E. Wokke ◽  
Hakwan Lau ◽  
Dobromir Rahnev
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Neural Activity ◽  
Magnetic Stimulation ◽  
Human Subjects ◽  
Brain Activity ◽  
Blood Oxygen Level Dependent ◽  
Brain Regions ◽  
Motor Threshold ◽  
Promising Tool ◽  
Site Of Stimulation

AbstractTranscranial magnetic stimulation (TMS) has become one of the major tools for establishing the causal role of specific brain regions in perceptual, motor, and cognitive processes. Nevertheless, a persistent limitation of the technique is the lack of clarity regarding its precise effects on neural activity. Here, we examined the effects of TMS intensity and frequency on concurrently recorded blood-oxygen level-dependent (BOLD) signals at the site of stimulation. In two experiments, we delivered TMS to the dorsolateral prefrontal cortex in human subjects of both sexes. In Experiment 1, we delivered a series of pulses at high (100% of motor threshold) or low (50% of motor threshold) intensity, whereas in Experiment 2, we always used high intensity but delivered stimulation at four different frequencies (5, 8.33, 12.5, and 25 Hz). We found that the TMS intensity and frequency could be reliably decoded using multivariate analysis techniques even though TMS had no effect on overall BOLD activity at the site of stimulation in either experiment. These results provide important insight into the mechanisms through which TMS influences neural activity.SignificanceTranscranial magnetic stimulation (TMS) is a promising tool for the treatment of a number of neuropsychiatric disorders. However, its effectiveness is still impeded by an incomplete understanding of its neural effects. One fundamental unresolved issue is whether TMS leads to local changes in overall neural activity in the absence of a task. Here we performed two experiments where TMS was delivered inside an MRI scanner while brain activity was continuously monitored. We found converging evidence for the notion that TMS affects the pattern of local activity changes but does not lead to an overall increase in activity. These results help clarify the mechanisms of how TMS affects local neural activity.

scholarly journals Modality-independent coding of scene categories in prefrontal cortex

2017 ◽  
Author(s):  
Yaelan Jung ◽  
Bart Larsen ◽  
Dirk B. Walther
Keyword(s):  
Prefrontal Cortex ◽  
Neural Activity ◽  
Brain Activity ◽  
Sensory Modality ◽  
Brain Regions ◽  
Complex Scene ◽  
Healthy Human ◽  
Sensory Inputs ◽  
Sensory Modalities ◽  
Scene Information

AbstractNatural environments convey information through multiple sensory modalities, all of which contribute to people’s percepts. Although it has been shown that visual or auditory content of scene categories can be decoded from brain activity, it remains unclear where and how humans integrate different sensory inputs and represent scene information beyond a specific sensory modality domain. To address this question, we investigated how categories of scene images and sounds are represented in several brain regions. A mixed gender group of healthy human subjects participated the present study, where their brain activity was measured with fMRI while viewing images or listening to sounds of different places. We found that both visual and auditory scene categories can be decoded not only from modality-specific areas, but also from several brain regions in the temporal, parietal, and prefrontal cortex. Intriguingly, only in the prefrontal cortex, but not in any other regions, categories of scene images and sounds appear to be represented in similar activation patterns, suggesting that scene representations in the prefrontal cortex are modality-independent. Furthermore, the error patterns of neural decoders indicate that category-specific neural activity patterns in the middle and superior frontal gyri are tightly linked to categorization behavior. Our findings demonstrate that complex scene information is represented at an abstract level in the prefrontal cortex, regardless of the sensory modality of the stimulus.Statement of SignificanceOur experience in daily life requires the integration of multiple sensory inputs such as images, sounds, or scents from the environment. Here, for the first time, we investigated where and how in the brain information about the natural environment from multiple senses is merged to form modality-independent representations of scene categories. We show direct decoding of scene categories across sensory modalities from patterns of neural activity in the prefrontal cortex. We also conclusively tie these neural representations to human categorization behavior based on the errors from the neural decoder and behavior. Our findings suggest that the prefrontal cortex is a central hub for integrating sensory information and computing modality-independent representations of scene categories.

Neuroticism and Its Associated Brain Activation in Women With PTSD

2016 ◽  
Vol 35 (1-2) ◽  
pp. 341-363
Author(s):  
Nicholas Brown ◽  
Jessica A. Wojtalik ◽  
Melissa Turkel ◽  
Tessa Vuper ◽  
David Strasshofer ◽  
...  
Keyword(s):  
Neural Activity ◽  
Interpersonal Violence ◽  
Neural Correlates ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Control Group ◽  
Stress Model ◽  
Conflict Task ◽  
Increased Risk ◽  
Diathesis Stress Model

Previous research suggests a diathesis-stress model of posttraumatic stress disorder (PTSD), wherein individuals with high levels of neuroticism who are exposed to traumatic events subsequently develop PTSD. Although studies have established relationships between neuroticism and neurological functioning in various brain regions for healthy and depressed individuals, the specific neural correlates of neuroticism for individuals with PTSD are yet unknown. This relationship is particularly relevant for women, given that their increased risk for PTSD is partially accounted for by their higher baseline levels of neuroticism. The current study examined previously established neural correlates of neuroticism in 61 women (48 women with interpersonal violence [IPV]/PTSD and 13 healthy controls). A specific region of interest map, including the amygdala, hippocampus, parahippocampus, anterior cingulate cortex (ACC), and dorsal medial prefrontal cortex (dmPFC), was examined while participants completed an emotional conflict task. Results showed that the PTSD group had significantly higher neuroticism scores than the healthy control group ( t = 6.90, p < .001). Higher neuroticism scores were associated with increased neural activity in the right dmPFC when participants were instructed to directly attend to faces with negative emotional valences. Significant trends between higher neuroticism scores and greater right amygdala and right ACC activation also emerged for this condition. Finally, neuroticism was found to be associated with right amygdala and right parahippocampal activity when participants were instructed to ignore faces with negative emotional valences. The results of this study lend further evidence to the proposed diathesis-stress model of neuroticism and PTSD. Moreover, findings suggest a significant association between neuroticism and neural activity in brain regions associated with fear and emotion regulation for women with IPV and subsequent PTSD.

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