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What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology
Stochastic resonance is said to be observed when increases in levels of unpredictable fluctuations--e.g., random noise--cause an increase in a metric of the quality of signal transmission or detection performance, rather than a decrease. This counterintuitive effect relies on system nonlinearities and on some parameter ranges being \"suboptimal\". Stochastic resonance has been observed, quantified, and described in a plethora of physical and biological systems, including neurons. Being a topic of widespread multidisciplinary interest, the definition of stochastic resonance has evolved significantly over the last decade or so, leading to a number of debates, misunderstandings, and controversies. Perhaps the most important debate is whether the brain has evolved to utilize random noise in vivo, as part of the \"neural code\". Surprisingly, this debate has been for the most part ignored by neuroscientists, despite much indirect evidence of a positive role for noise in the brain. We explore some of the reasons for this and argue why it would be more surprising if the brain did not exploit randomness provided by noise--via stochastic resonance or otherwise--than if it did. We also challenge neuroscientists and biologists, both computational and experimental, to embrace a very broad definition of stochastic resonance in terms of signal-processing \"noise benefits\", and to devise experiments aimed at verifying that random variability can play a functional role in the brain, nervous system, or other areas of biology.
Journal Article
The Rewarding Aspects of Music Listening Are Related to Degree of Emotional Arousal
Listening to music is amongst the most rewarding experiences for humans. Music has no functional resemblance to other rewarding stimuli, and has no demonstrated biological value, yet individuals continue listening to music for pleasure. It has been suggested that the pleasurable aspects of music listening are related to a change in emotional arousal, although this link has not been directly investigated. In this study, using methods of high temporal sensitivity we investigated whether there is a systematic relationship between dynamic increases in pleasure states and physiological indicators of emotional arousal, including changes in heart rate, respiration, electrodermal activity, body temperature, and blood volume pulse.
Twenty-six participants listened to self-selected intensely pleasurable music and \"neutral\" music that was individually selected for them based on low pleasure ratings they provided on other participants' music. The \"chills\" phenomenon was used to index intensely pleasurable responses to music. During music listening, continuous real-time recordings of subjective pleasure states and simultaneous recordings of sympathetic nervous system activity, an objective measure of emotional arousal, were obtained.
Results revealed a strong positive correlation between ratings of pleasure and emotional arousal. Importantly, a dissociation was revealed as individuals who did not experience pleasure also showed no significant increases in emotional arousal.
These results have broader implications by demonstrating that strongly felt emotions could be rewarding in themselves in the absence of a physically tangible reward or a specific functional goal.
Journal Article
Causal Inference in Multisensory Perception
Perceptual events derive their significance to an animal from their meaning about the world, that is from the information they carry about their causes. The brain should thus be able to efficiently infer the causes underlying our sensory events. Here we use multisensory cue combination to study causal inference in perception. We formulate an ideal-observer model that infers whether two sensory cues originate from the same location and that also estimates their location(s). This model accurately predicts the nonlinear integration of cues by human subjects in two auditory-visual localization tasks. The results show that indeed humans can efficiently infer the causal structure as well as the location of causes. By combining insights from the study of causal inference with the ideal-observer approach to sensory cue combination, we show that the capacity to infer causal structure is not limited to conscious, high-level cognition; it is also performed continually and effortlessly in perception.
Journal Article
Quantification of inter-brain coupling: A review of current methods used in haemodynamic and electrophysiological hyperscanning studies
•215 hyperscanning publications were found from 2000-2022 computing inter-brain coupling.•Throughout these 27 different methods used to compute IBC.•fNIRS and Wavelet coherence were the most commonly neuroimaging modality and method.
Hyperscanning is a form of neuroimaging experiment where the brains of two or more participants are imaged simultaneously whilst they interact. Within the domain of social neuroscience, hyperscanning is increasingly used to measure inter-brain coupling (IBC) and explore how brain responses change in tandem during social interaction. In addition to cognitive research, some have suggested that quantification of the interplay between interacting participants can be used as a biomarker for a variety of cognitive mechanisms aswell as to investigate mental health and developmental conditions including schizophrenia, social anxiety and autism. However, many different methods have been used to quantify brain coupling and this can lead to questions about comparability across studies and reduce research reproducibility. Here, we review methods for quantifying IBC, and suggest some ways moving forward. Following the PRISMA guidelines, we reviewed 215 hyperscanning studies, across four different brain imaging modalities: functional near-infrared spectroscopy (fNIRS), functional magnetic resonance (fMRI), electroencephalography (EEG) and magnetoencephalography (MEG). Overall, the review identified a total of 27 different methods used to compute IBC. The most common hyperscanning modality is fNIRS, used by 119 studies, 89 of which adopted wavelet coherence. Based on the results of this literature survey, we first report summary statistics of the hyperscanning field, followed by a brief overview of each signal that is obtained from each neuroimaging modality used in hyperscanning. We then discuss the rationale, assumptions and suitability of each method to different modalities which can be used to investigate IBC. Finally, we discuss issues surrounding the interpretation of each method.
Journal Article
The Natural Statistics of Audiovisual Speech
Humans, like other animals, are exposed to a continuous stream of signals, which are dynamic, multimodal, extended, and time varying in nature. This complex input space must be transduced and sampled by our sensory systems and transmitted to the brain where it can guide the selection of appropriate actions. To simplify this process, it's been suggested that the brain exploits statistical regularities in the stimulus space. Tests of this idea have largely been confined to unimodal signals and natural scenes. One important class of multisensory signals for which a quantitative input space characterization is unavailable is human speech. We do not understand what signals our brain has to actively piece together from an audiovisual speech stream to arrive at a percept versus what is already embedded in the signal structure of the stream itself. In essence, we do not have a clear understanding of the natural statistics of audiovisual speech. In the present study, we identified the following major statistical features of audiovisual speech. First, we observed robust correlations and close temporal correspondence between the area of the mouth opening and the acoustic envelope. Second, we found the strongest correlation between the area of the mouth opening and vocal tract resonances. Third, we observed that both area of the mouth opening and the voice envelope are temporally modulated in the 2-7 Hz frequency range. Finally, we show that the timing of mouth movements relative to the onset of the voice is consistently between 100 and 300 ms. We interpret these data in the context of recent neural theories of speech which suggest that speech communication is a reciprocally coupled, multisensory event, whereby the outputs of the signaler are matched to the neural processes of the receiver.
Journal Article