Steady state-evoked potentials of subjective beat perception in musical rhythms

2021 ◽  
Author(s):  
Karli M Nave ◽  
Erin Hannon ◽  
Joel S. Snyder
Keyword(s):  
Brain Activity ◽  
Spectral Amplitude ◽  
Conscious Perception ◽  
Neural Responses ◽  
Musical Excerpt ◽  
Beat Pattern ◽  
Preceding Context ◽  
Trial Basis ◽  
Stimulus Features ◽  
Musical Rhythms

Synchronization of movement to music is a seemingly universal human capacity that depends on sustained beat perception. Previous research shows that the frequency of the beat can be observed in the neural activity of the listener. However, the extent to which these neural responses reflect concurrent, conscious perception of musical beat versus stimulus-driven activity is a matter of debate. We investigated whether this kind of periodic brain activity, measured using electroencephalography (EEG), reflects perception of beat, by holding the stimulus constant while manipulating the listener’s perception. Listeners with minimal music training heard a musical excerpt that strongly supported one of two beat patterns (context), followed by a rhythm consistent with either beat pattern (ambiguous phase). During the final phase, listeners indicated whether or not a superimposed drum matched the perceived beat (probe phase). Participants were more likely to indicate that the probe matched the music when that probe matched the original context, suggesting an ability to maintain the beat percept through the ambiguous phase. Likewise, we observed that the spectral amplitude during the ambiguous phase was higher at frequencies corresponding to the beat of the preceding context, and the EEG amplitude at the beat-related frequency predicted performance on the beat induction task on a single-trial basis. Together, these findings provide evidence that auditory cortical activity reflects conscious perception of musical beat and not just stimulus features or effortful attention.

scholarly journals Neural and Behavioral Evidence for Frequency-Selective Context Effects in Rhythm Processing in Humans

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Tomas Lenc ◽  
Peter E Keller ◽  
Manuel Varlet ◽  
Sylvie Nozaradan
Keyword(s):  
Auditory Processing ◽  
Sensory Input ◽  
Context Effects ◽  
Brain Activity ◽  
Acoustic Cues ◽  
Neural Responses ◽  
Passive Tracking ◽  
Behavioral Evidence ◽  
Stimulus Features ◽  
Stimulus Degradation

Abstract When listening to music, people often perceive and move along with a periodic meter. However, the dynamics of mapping between meter perception and the acoustic cues to meter periodicities in the sensory input remain largely unknown. To capture these dynamics, we recorded the electroencephalography while nonmusician and musician participants listened to nonrepeating rhythmic sequences, where acoustic cues to meter frequencies either gradually decreased (from regular to degraded) or increased (from degraded to regular). The results revealed greater neural activity selectively elicited at meter frequencies when the sequence gradually changed from regular to degraded compared with the opposite. Importantly, this effect was unlikely to arise from overall gain, or low-level auditory processing, as revealed by physiological modeling. Moreover, the context effect was more pronounced in nonmusicians, who also demonstrated facilitated sensory-motor synchronization with the meter for sequences that started as regular. In contrast, musicians showed weaker effects of recent context in their neural responses and robust ability to move along with the meter irrespective of stimulus degradation. Together, our results demonstrate that brain activity elicited by rhythm does not only reflect passive tracking of stimulus features, but represents continuous integration of sensory input with recent context.

Acetaminophen Reduces Social Pain

2010 ◽  
Vol 21 (7) ◽  
pp. 931-937 ◽  
Author(s):  
C. Nathan DeWall ◽  
Geoff MacDonald ◽  
Gregory D. Webster ◽  
Carrie L. Masten ◽  
Roy F. Baumeister ◽  
...  
Keyword(s):  
Brain Activity ◽  
Brain Regions ◽  
Daily Basis ◽  
Social Rejection ◽  
Neural Mechanisms ◽  
Anterior Cingulate ◽  
Neural Responses ◽  
Physical Pain ◽  
Social Pain ◽  
Dorsal Anterior Cingulate Cortex

Pain, whether caused by physical injury or social rejection, is an inevitable part of life. These two types of pain—physical and social—may rely on some of the same behavioral and neural mechanisms that register pain-related affect. To the extent that these pain processes overlap, acetaminophen, a physical pain suppressant that acts through central (rather than peripheral) neural mechanisms, may also reduce behavioral and neural responses to social rejection. In two experiments, participants took acetaminophen or placebo daily for 3 weeks. Doses of acetaminophen reduced reports of social pain on a daily basis (Experiment 1). We used functional magnetic resonance imaging to measure participants’ brain activity (Experiment 2), and found that acetaminophen reduced neural responses to social rejection in brain regions previously associated with distress caused by social pain and the affective component of physical pain (dorsal anterior cingulate cortex, anterior insula). Thus, acetaminophen reduces behavioral and neural responses associated with the pain of social rejection, demonstrating substantial overlap between social and physical pain.

scholarly journals Prefrontal High Gamma in ECoG tags periodicity of musical rhythms in perception and imagination

2019 ◽  
Author(s):  
S. A. Herff ◽  
C. Herff ◽  
A. J. Milne ◽  
G. D. Johnson ◽  
J. J. Shih ◽  
...  
Keyword(s):  
Auditory Processing ◽  
Right Hemisphere ◽  
Brain Activity ◽  
Activity Patterns ◽  
Superior Temporal Gyrus ◽  
Gamma Activity ◽  
Rhythm Perception ◽  
High Gamma ◽  
The Right ◽  
Musical Rhythms

AbstractRhythmic auditory stimuli are known to elicit matching activity patterns in neural populations. Furthermore, recent research has established the particular importance of high-gamma brain activity in auditory processing by showing its involvement in auditory phrase segmentation and envelope-tracking. Here, we use electrocorticographic (ECoG) recordings from eight human listeners, to see whether periodicities in high-gamma activity track the periodicities in the envelope of musical rhythms during rhythm perception and imagination. Rhythm imagination was elicited by instructing participants to imagine the rhythm to continue during pauses of several repetitions. To identify electrodes whose periodicities in high-gamma activity track the periodicities in the musical rhythms, we compute the correlation between the autocorrelations (ACC) of both the musical rhythms and the neural signals. A condition in which participants listened to white noise was used to establish a baseline. High-gamma autocorrelations in auditory areas in the superior temporal gyrus and in frontal areas on both hemispheres significantly matched the autocorrelation of the musical rhythms. Overall, numerous significant electrodes are observed on the right hemisphere. Of particular interest is a large cluster of electrodes in the right prefrontal cortex that is active during both rhythm perception and imagination. This indicates conscious processing of the rhythms’ structure as opposed to mere auditory phenomena. The ACC approach clearly highlights that high-gamma activity measured from cortical electrodes tracks both attended and imagined rhythms.

Influence of trait anxiety on brain activity during the acquisition and extinction of aversive conditioning

2008 ◽  
Vol 39 (2) ◽  
pp. 255-265 ◽  
Author(s):  
J. Barrett ◽  
J. L. Armony
Keyword(s):  
Trait Anxiety ◽  
Conditioned Response ◽  
Brain Activity ◽  
Aversive Conditioning ◽  
Anterior Cingulate ◽  
Neural Responses ◽  
Conditioning Paradigm ◽  
Subgenual Anterior Cingulate Cortex ◽  
Anxiety Response ◽  
Echo Planar

BackgroundWe examined how individual differences in trait anxiety (TA) influence the neural responses associated with the acquisition and extinction of anticipatory anxiety elicited through a context conditioning paradigm, with particular focus on the amygdala and the subgenual anterior cingulate cortex (sgACC).MethodDuring two sessions of echo-planar functional magnetic resonance imaging (fMRI), 18 healthy volunteers completed a decision-making task with two randomly alternating 28-s to 32-s background screen colour blocks. One of the colours was associated with the presentation of an aversive noise (CTX+) and the other colour was ‘safe’ (CTX−). In the first session (Acquisition), 33% of CTX+ colour blocks were paired with noise and in the second session (Extinction) no noise was presented.ResultsThe amygdala displayed an increased response to CTX+ compared to CTX− colour blocks during the Acquisition and Extinction sessions and the ACC displayed an increased response to CTX+ compared to CTX− colour blocks during Extinction only. In addition, a greater conditioned response (CTX+ minus CTX−) was observed in the ACC when comparing the Extinction and Acquisition sessions. Correlation analyses further showed that higher levels of TA were associated with a higher conditioned response in the amygdala during Extinction as well as a greater differential conditioned response (i.e. Extinction>Acquisition) in the ACC.ConclusionsOur results support the idea that individuals with high levels of anxiety-relevant traits and vulnerable to developing an anxiety disorder display a more resilient anxiety response during extinction that is characterized by hyper-responsivity in the amygdala.

scholarly journals Neural Responses to Infant Emotions and Emotional Self-Awareness in Mothers and Fathers during Pregnancy

2020 ◽  
Vol 17 (9) ◽  
pp. 3314 ◽  
Author(s):  
Cristina Trentini ◽  
Marco Pagani ◽  
Marco Lauriola ◽  
Renata Tambelli
Keyword(s):  
Mental Imagery ◽  
Spatial Information ◽  
Brain Activity ◽  
Post Partum ◽  
High Order ◽  
Self Awareness ◽  
Neural Responses ◽  
Mothers And Fathers ◽  
Visual Mental Imagery ◽  
Affective Processes

Neuroscientific research has largely investigated the neurobiological correlates of maternal and (to a much lesser extent) paternal responsiveness in the post-partum period. In contrast, much less is known about the neural processing of infant emotions during pregnancy. Twenty mothers and 19 fathers were recruited independently during the third trimester of pregnancy. High-density electroencephalography (hdEEG) was recorded while expectant parents passively viewed images representing distressed, ambiguous, happy, and neutral faces of unknown infants. Correlational analyses were performed to detect a link between neural responses to infant facial expressions and emotional self-awareness. In response to infant emotions, mothers and fathers showed similar cerebral activity in regions involved in high-order socio-affective processes. Mothers and fathers also showed different brain activity in premotor regions implicated in high-order motor control, in occipital regions involved in visuo-spatial information processing and visual mental imagery, as well as in inferior parietal regions involved in attention allocation. Low emotional self-awareness negatively correlated with activity in parietal regions subserving empathy in mothers, while it positively correlated with activity in temporal and occipital areas implicated in mentalizing and visual mental imagery in fathers. This study may enlarge knowledge on the neural response to infant emotions during pregnancy.

scholarly journals Allelic variation in 5-HTTLPR and the effects of citalopram on the emotional neural network

2015 ◽  
Vol 206 (5) ◽  
pp. 385-392 ◽  
Author(s):  
Yina Ma ◽  
Bingfeng Li ◽  
Chenbo Wang ◽  
Wenxia Zhang ◽  
Yi Rao ◽  
...  
Keyword(s):  
Serotonin Transporter ◽  
Selective Serotonin Reuptake Inhibitors ◽  
Allelic Variation ◽  
Brain Activity ◽  
Negative Emotions ◽  
Healthy Adults ◽  
Acute Administration ◽  
Neural Responses ◽  
Acute Effects ◽  
Imaging Results

BackgroundSelective serotonin reuptake inhibitors (SSRIs), such as citalopram, which selectively block serotonin transporter (5-HTT) activity, are widely used in the treatment of depression and anxiety disorders. Numerous neuroimaging studies have examined the effects of SSRIs on emotional processes. However, there are considerable inter-individual differences in SSRI effect, and a recent meta-analysis further revealed discrepant effects of acute SSRI administration on neural responses to negative emotions in healthy adults.AimsWe examined how a variant of the serotonin-transporter polymorphism (5-HTTLPR), which affects the expression and function of 5-HTT, influenced the acute effects of an SSRI (citalopram) on emotion-related brain activity in healthy adults.MethodCombining genetic neuroimaging, pharmacological technique and a psychological paradigm of emotion recognition, we scanned the short/short (s/s) and long/long (l/l) variants of 5-HTTLPR during perception of fearful, happy and neutral facial expressions after the acute administration of an SSRI (i.e. 30mg citalopram administered orally) or placebo administration.ResultsWe found that 5-HTTLPR modulated the acute effects of citalopram on neural responses to negative emotions. Specifically, relative to placebo, citalopram increased amygdala and insula activity in l/l but not s/s homozygotes during perception of fearful faces. Similar analyses of brain activity in response to happy faces did not show any significant effects.ConclusionsOur combined pharmacogenetic and functional imaging results provide a neurogenetic mechanism for discrepant acute effects of SSRIs.

scholarly journals Subjective visual perception: from local processing to emergent phenomena of brain activity

2014 ◽  
Vol 369 (1641) ◽  
pp. 20130534 ◽  
Author(s):  
Theofanis I. Panagiotaropoulos ◽  
Vishal Kapoor ◽  
Nikos K. Logothetis
Keyword(s):  
Visual Perception ◽  
Visual Stimulation ◽  
Brain Activity ◽  
Sensory Information ◽  
Brain Regions ◽  
Intrinsic Activity ◽  
Subjective Perception ◽  
Conscious Perception ◽  
Perceptual Awareness ◽  
Sensory Stimuli

The combination of electrophysiological recordings with ambiguous visual stimulation made possible the detection of neurons that represent the content of subjective visual perception and perceptual suppression in multiple cortical and subcortical brain regions. These neuronal populations, commonly referred to as the neural correlates of consciousness , are more likely to be found in the temporal and prefrontal cortices as well as the pulvinar, indicating that the content of perceptual awareness is represented with higher fidelity in higher-order association areas of the cortical and thalamic hierarchy, reflecting the outcome of competitive interactions between conflicting sensory information resolved in earlier stages. However, despite the significant insights into conscious perception gained through monitoring the activities of single neurons and small, local populations, the immense functional complexity of the brain arising from correlations in the activity of its constituent parts suggests that local, microscopic activity could only partially reveal the mechanisms involved in perceptual awareness. Rather, the dynamics of functional connectivity patterns on a mesoscopic and macroscopic level could be critical for conscious perception. Understanding these emergent spatio-temporal patterns could be informative not only for the stability of subjective perception but also for spontaneous perceptual transitions suggested to depend either on the dynamics of antagonistic ensembles or on global intrinsic activity fluctuations that may act upon explicit neural representations of sensory stimuli and induce perceptual reorganization. Here, we review the most recent results from local activity recordings and discuss the potential role of effective, correlated interactions during perceptual awareness.

scholarly journals Performance-optimized hierarchical models only partially predict neural responses during perceptual decision making

2017 ◽  
Author(s):  
Laura Gwilliams ◽  
Jean-Rémi King
Keyword(s):  
Decision Making ◽  
Human Subjects ◽  
Brain Activity ◽  
Hand Movement ◽  
Temporal Organization ◽  
Natural Image ◽  
Neural Responses ◽  
Perceptual Decision Making ◽  
Healthy Human ◽  
Perceptual Decision

AbstractModels of perceptual decision making have historically been designed to maximally explain behaviour and brain activity independently of their ability to actually perform tasks. More recently, performance-optimized models have been shown to correlate with brain responses to images and thus present a complementary approach to understand perceptual processes. In the present study, we compare how these approaches comparatively account for the spatio-temporal organization of neural responses elicited by ambiguous visual stimuli. Forty-six healthy human subjects performed perceptual decisions on briefly flashed stimuli constructed from ambiguous characters. The stimuli were designed to have 7 orthogonal properties, ranging from low-sensory levels (e.g. spatial location of the stimulus) to conceptual (whether stimulus is a letter or a digit) and task levels (i.e. required hand movement). Magneto-encephalography source and decoding analyses revealed that these 7 levels of representations are sequentially encoded by the cortical hierarchy, and actively maintained until the subject responds. This hierarchy appeared poorly correlated to normative, drift-diffusion, and 5-layer convolutional neural networks (CNN) optimized to accurately categorize alpha-numeric characters, but partially matched the sequence of activations of 3/6 state-of-the-art CNNs trained for natural image labeling (VGG-16, VGG-19, MobileNet). Additionally, we identify several systematic discrepancies between these CNNs and brain activity, revealing the importance of single-trial learning and recurrent processing. Overall, our results strengthen the notion that performance-optimized algorithms can converge towards the computational solution implemented by the human visual system, and open possible avenues to improve artificial perceptual decision making.

scholarly journals Dissociable Neural Representations of Adversarially Perturbed Images in Convolutional Neural Networks and the Human Brain

2021 ◽  
Vol 15 ◽  
Author(s):  
Chi Zhang ◽  
Xiao-Han Duan ◽  
Lin-Yuan Wang ◽  
Yong-Li Li ◽  
Bin Yan ◽  
...  
Keyword(s):  
Neural Networks ◽  
Human Brain ◽  
Convolutional Neural Networks ◽  
Brain Activity ◽  
Neural Responses ◽  
Neural Representations ◽  
Artificial Neurons ◽  
Visual Areas ◽  
Two Systems ◽  
Visual Tasks

Despite the remarkable similarities between convolutional neural networks (CNN) and the human brain, CNNs still fall behind humans in many visual tasks, indicating that there still exist considerable differences between the two systems. Here, we leverage adversarial noise (AN) and adversarial interference (AI) images to quantify the consistency between neural representations and perceptual outcomes in the two systems. Humans can successfully recognize AI images as the same categories as their corresponding regular images but perceive AN images as meaningless noise. In contrast, CNNs can recognize AN images similar as corresponding regular images but classify AI images into wrong categories with surprisingly high confidence. We use functional magnetic resonance imaging to measure brain activity evoked by regular and adversarial images in the human brain, and compare it to the activity of artificial neurons in a prototypical CNN—AlexNet. In the human brain, we find that the representational similarity between regular and adversarial images largely echoes their perceptual similarity in all early visual areas. In AlexNet, however, the neural representations of adversarial images are inconsistent with network outputs in all intermediate processing layers, providing no neural foundations for the similarities at the perceptual level. Furthermore, we show that voxel-encoding models trained on regular images can successfully generalize to the neural responses to AI images but not AN images. These remarkable differences between the human brain and AlexNet in representation-perception association suggest that future CNNs should emulate both behavior and the internal neural presentations of the human brain.

scholarly journals Deep learning: Using machine learning to study biological vision

2017 ◽  
Author(s):  
Najib J. Majaj ◽  
Denis G. Pelli
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Deep Learning ◽  
Deep Neural Networks ◽  
Brain Activity ◽  
Neural Responses ◽  
Statistical Tool ◽  
Biological Vision ◽  
Vision Science ◽  
Living Organisms

ABSTRACTToday many vision-science presentations employ machine learning, especially the version called “deep learning”. Many neuroscientists use machine learning to decode neural responses. Many perception scientists try to understand how living organisms recognize objects. To them, deep neural networks offer benchmark accuracies for recognition of learned stimuli. Originally machine learning was inspired by the brain. Today, machine learning is used as a statistical tool to decode brain activity. Tomorrow, deep neural networks might become our best model of brain function. This brief overview of the use of machine learning in biological vision touches on its strengths, weaknesses, milestones, controversies, and current directions. Here, we hope to help vision scientists assess what role machine learning should play in their research.

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