Temporal Dynamics of Brain Activity Predicting Sense of Agency over Muscle Movements.

Our muscles are the primary means through which we affect the external world, and the sense of agency (SoA) over the action through those muscles is fundamental to our self-awareness. However, SoA research to date has focused almost exclusively on agency over action outcomes rather than over the musculature itself, as it was believed that SoA over the musculature could not be manipulated directly. Drawing on methods from human-computer interaction and adaptive experimentation, we use human-in-the-loop Bayesian optimization to tune the timing of electrical muscle stimulation so as to robustly elicit a SoA over electrically actuated muscle movements in male and female human subjects. We use time-resolved decoding of subjects' EEG to estimate the time course of neural activity which predicts reported agency on a trial-by-trial basis. Like paradigms which assess SoA over action consequences, we found that the late (post-conscious) neural activity predicts SoA. Unlike typical paradigms, however, we also find patterns of early (sensorimotor) activity with distinct temporal dynamics predicts agency over muscle movements, suggesting that the "neural correlates of agency" may depend on the level of abstraction (i.e., direct sensorimotor feedback versus downstream consequences) most relevant to a given agency judgment. Moreover, fractal analysis of the EEG suggests that SoA-contingent dynamics of neural activity may modulate the sensitivity of the motor system to external input.SIGNIFICANCE STATEMENT The sense of agency, the feeling of "I did that," when directing one's own musculature is a core feature of human experience. We show that we can robustly manipulate the sense of agency over electrically actuated muscle movements, and we investigate the time course of neural activity that predicts the sense of agency over these actuated movements. We find evidence of two distinct neural processes: a transient sequence of patterns that begins in the early sensorineural response to muscle stimulation and a later, sustained signature of agency. These results shed light on the neural mechanisms by which we experience our movements as volitional.

Permutation-based group sequential analyses for cognitive neuroscience.

Cognitive neuroscientists have been grappling with two related experimental design problems. First, the complexity of neuroimaging data (e.g. often hundreds of thousands of correlated measurements) and analysis pipelines demands bespoke, non-parametric statistical tests for valid inference, and these tests often lack an agreed-upon method for performing a priori power analyses. Thus, sample size determination for neuroimaging studies is often arbitrary or inferred from other putatively but questionably similar studies, which can result in underpowered designs - undermining the efficacy of neuroimaging research. Second, when meta-analyses estimate the sample sizes required to obtain reasonable statistical power, estimated sample sizes can be prohibitively large given the resource constraints of many labs. We propose the use of sequential analyses to partially address both of these problems. Sequential study designs - in which the data is analyzed at interim points during data collection and data collection can be stopped if the planned test statistic satisfies a stopping rule specified a priori - are common in the clinical trial literature, due to the efficiency gains they afford over fixed-sample designs. However, the corrections used to control false positive rates in existing approaches to sequential testing rely on parametric assumptions that are often violated in neuroimaging settings. We introduce a general permutation scheme that allows sequential designs to be used with arbitrary test statistics. By simulation, we show that this scheme controls the false positive rate across multiple interim analyses. Then, performing power analyses for seven evoked response effects seen in the EEG literature, we show that this sequential analysis approach can substantially outperform fixed-sample approaches (i.e. require fewer subjects, on average, to detect a true effect) when study designs are sufficiently well-powered. To facilitate the adoption of this methodology, we provide a Python package "niseq" with sequential implementations of common tests used for neuroimaging: cluster-based permutation tests, threshold-free cluster enhancement, t-max, F-max, and the network-based statistic with tutorial examples using EEG and fMRI data.

Absolute pitch judgments of familiar melodies generalize across timbre and octave.

Most listeners can determine when a familiar recording of music has been shifted in musical key by as little as one semitone (e.g., from B to C major). These findings appear to suggest that absolute pitch memory is widespread in the general population. However, the use of familiar recordings makes it unclear whether these findings genuinely reflect absolute melody-key associations for at least two reasons. First, listeners may be able to use spectral cues from the familiar instrumentation of the recordings to determine when a familiar recording has been shifted in pitch. Second, listeners may be able to rely solely on pitch height cues (e.g., relying on a feeling that an incorrect recording sounds "too high" or "too low"). Neither of these strategies would require an understanding of pitch chroma or musical key. The present experiments thus assessed whether listeners could make accurate absolute melody-key judgments when listening to novel versions of these melodies, differing from the iconic recording in timbre (Experiment 1) or timbre and octave (Experiment 2). Listeners in both experiments were able to select the correct-key version of the familiar melody at rates that were well above chance. These results fit within a growing body of research supporting the idea that most listeners, regardless of formal musical training, have robust representations of absolute pitch - based on pitch chroma - that generalize to novel listening situations. Implications for theories of auditory pitch memory are discussed.

Going beyond ourselves: the role of self-transcendent experiences in wisdom.

Having good moral character often involves shifting one's focus of attention from the self to others and the world. Across three studies (N = 605 adults), we found converging evidence that self-transcendent experiences, specifically awe and flow, enabled the expression of wisdom, as captured by wise reasoning and epistemic humility measures. Study 1 found that dispositionally awe- and flow-prone people have stronger wise reasoning and epistemic humility abilities, over and above dispositional happiness. Consistent with Study 1, Study 2 found that, across diverse recalled experiences, individuals who experienced more awe showed greater wise reasoning, and those who experienced more flow showed greater epistemic humility. In Study 3, using situated interventions, we induced awe (watching a video involving vast nature scenes) and flow (composing a song using an online music maker) and compared them with neutral and amusement experiences. Compared to these control conditions, eliciting awe and flow facilitated one's (1) ability to address interpersonal conflicts with wise reasoning, (2) ability to acknowledge one's epistemic gaps, and (3) willingness to improve those aspects and one's general moral character. Altogether, these findings reveal the promising role of self-transcendent experiences in motivating people to appreciate others' perspectives beyond one's own.

Going Beyond Rote Auditory Learning: Neural Patterns of Generalized Auditory Learning.

The ability to generalize across specific experiences is vital for the recognition of new patterns, especially in speech perception considering acoustic-phonetic pattern variability. Indeed, behavioral research has demonstrated that listeners are able via a process of generalized learning to leverage their experiences of past words said by difficult-to-understand talker to improve their understanding for new words said by that talker. Here, we examine differences in neural responses to generalized versus rote learning in auditory cortical processing by training listeners to understand a novel synthetic talker. Using a pretest-posttest design with EEG, participants were trained using either (1) a large inventory of words where no words were repeated across the experiment (generalized learning) or (2) a small inventory of words where words were repeated (rote learning). Analysis of long-latency auditory evoked potentials at pretest and posttest revealed that rote and generalized learning both produced rapid changes in auditory processing, yet the nature of these changes differed. Generalized learning was marked by an amplitude reduction in the N1-P2 complex and by the presence of a late negativity wave in the auditory evoked potential following training; rote learning was marked only by temporally later scalp topography differences. The early N1-P2 change, found only for generalized learning, is consistent with an active processing account of speech perception, which proposes that the ability to rapidly adjust to the specific vocal characteristics of a new talker (for which rote learning is rare) relies on attentional mechanisms to selectively modify early auditory processing sensitivity.

Visual cortex entrains to sign language.

Despite immense variability across languages, people can learn to understand any human language, spoken or signed. What neural mechanisms allow people to comprehend language across sensory modalities? When people listen to speech, electrophysiological oscillations in auditory cortex entrain to slow ([Formula: see text]8 Hz) fluctuations in the acoustic envelope. Entrainment to the speech envelope may reflect mechanisms specialized for auditory perception. Alternatively, flexible entrainment may be a general-purpose cortical mechanism that optimizes sensitivity to rhythmic information regardless of modality. Here, we test these proposals by examining cortical coherence to visual information in sign language. First, we develop a metric to quantify visual change over time. We find quasiperiodic fluctuations in sign language, characterized by lower frequencies than fluctuations in speech. Next, we test for entrainment of neural oscillations to visual change in sign language, using electroencephalography (EEG) in fluent speakers of American Sign Language (ASL) as they watch videos in ASL. We find significant cortical entrainment to visual oscillations in sign language <5 Hz, peaking at [Formula: see text]1 Hz. Coherence to sign is strongest over occipital and parietal cortex, in contrast to speech, where coherence is strongest over the auditory cortex. Nonsigners also show coherence to sign language, but entrainment at frontal sites is reduced relative to fluent signers. These results demonstrate that flexible cortical entrainment to language does not depend on neural processes that are specific to auditory speech perception. Low-frequency oscillatory entrainment may reflect a general cortical mechanism that maximizes sensitivity to informational peaks in time-varying signals.

Trading experience modulates anterior insula to reduce the endowment effect.

People often demand a greater price when selling goods that they own than they would pay to purchase the same goods-a well-known economic bias called the endowment effect. The endowment effect has been found to be muted among experienced traders, but little is known about how trading experience reduces the endowment effect. We show that when selling, experienced traders exhibit lower right anterior insula activity, but no differences in nucleus accumbens or orbitofrontal activation, compared with inexperienced traders. Furthermore, insula activation mediates the effect of experience on the endowment effect. Similar results are obtained for inexperienced traders who are incentivized to gain trading experience. This finding indicates that frequent trading likely mitigates the endowment effect indirectly by modifying negative affective responses in the context of selling.

Differential development of retroactive and proactive interference during post-learning wakefulness.

Newly encoded, labile memories are prone to disruption during post-learning wakefulness. Here we examine the contributions of retroactive and proactive interference to daytime forgetting on an auditory classification task in a songbird. While both types of interference impair performance, they do not develop concurrently. The retroactive interference of task-B on task-A developed during the learning of task-B, whereas the proactive interference of task-A on task-B emerged during subsequent waking retention. These different time courses indicate an asymmetry in the emergence of retroactive and proactive interference and suggest a mechanistic framework for how different types of interference between new memories develop.

The effects of acoustic variability on absolute pitch categorization: Evidence of contextual tuning.

Absolute pitch (AP) is defined as the ability to label a musical note without the aid of a reference note. Despite the large amounts of acoustic variability encountered in music, AP listeners generally experience perceptual constancy for different exemplars within note categories (e.g., recognizing that a C played on a tuba belongs to the same category as a C played on a piccolo). The present studies investigate whether AP possessors are sensitive to context variability along acoustic dimensions that are not inherently linked to the typical definition of a note category. In a speeded target recognition task, AP participants heard a sequence of notes and pressed a button whenever they heard a designated target note. Within a trial the sequence of notes was either blocked according to note-irrelevant variation or contained a mix of different instruments (Experiment 1), amplitude levels (Experiment 2), or octaves (Experiment 3). Compared to the blocked trials, participants were significantly slower to respond in the mixed-instrument and mixed-octave trials, but not the mixed-amplitude trials. Importantly, this performance difference could not be solely attributed to initial performance differences between instruments, amplitudes, or octaves. These results suggest that AP note identification is contextually sensitive.

Sleep consolidation of interfering auditory memories in starlings.

Memory consolidation has been described as a process to strengthen newly formed memories and to stabilize them against interference from similar learning experiences. Sleep facilitates memory consolidation in humans, improving memory performance and protecting against interference encountered after sleep. The European starling, a songbird, has also manifested sleep-dependent memory consolidation when trained on an auditory-classification task. Here, we examined how memory for two similar classification tasks is consolidated across waking and sleep in starlings. We demonstrated for the first time that the learning of each classification reliably interferes with the retention of the other classification across waking retention but that sleep enhances and stabilizes the memory of both classifications even after performance is impaired by interference. These observations demonstrate that sleep consolidation enhances retention of interfering experiences, facilitating opportunistic daytime learning and the subsequent formation of stable long-term memories.

Absolute pitch may not be so absolute.

Most people cannot name the musical note that corresponds to a particular pitch without being provided a reference note, but those people with absolute pitch (AP) can do this accurately. Early experience during a developmental period is often thought to convey identity and stability of the note categories in people with AP, but the plasticity of these categories has not been investigated. Here we provide the first evidence that the note categories of adults with AP can change with listening experience. Participants with AP showed shifts in perception in direct accord with prior exposure to music detuned by a fraction of a semitone. This suggests that the apparent stability of AP categories is conferred not by early experience but rather by the cultural norms adopted for tuning music.

Brain mechanisms of valuable scientific problem finding inspired by heuristic knowledge.

Heuristics through the application of heuristic knowledge to the creation of imitation devices may be one of the most common processes in scientific innovation. In particular, heuristics suggests that innovation includes the automatic activation of heuristic knowledge and formation of novel associations between heuristic knowledge and problem situations. In this study, 76 scientific innovation problem situations were selected as materials. Among these, 36 contain related heuristic knowledge and 40 have no such information. Through functional magnetic resonance imaging, the learning-testing paradigm was used to explore the brain mechanisms of scientific problem finding inspired by heuristic knowledge. Participants were asked to find a problem on the basis of a given innovation problem situation. Two scenarios were presented: finding scientific problems with related heuristic knowledge and finding conventional problems without related heuristic knowledge. The authors assumed that the regions in the brain significantly activated by the finding scientific problems with related heuristic knowledge condition compared with the finding normal problems without related heuristic knowledge condition are relevant to the brain mechanisms of scientific problem finding inspired by heuristic knowledge. The first scenario more significantly activated the left precuneus and left angular gyrus than did the second scenario. These findings suggest that the precuneus is relevant to the successful storage and retrieval of heuristic knowledge and that the left angular gyrus is involved in the formation of novel associations between heuristic knowledge and problem situations for finding scientific problems.

Single-trial visually evoked potentials predict both individual choice and market outcomes.

A central assumption in the behavioral sciences is that choice behavior generalizes enough across individuals that measurements from a sampled group can predict the behavior of the population. Following from this assumption, the unit of behavioral sampling or measurement for most neuroimaging studies is the individual; however, cognitive neuroscience is increasingly acknowledging a dissociation between neural activity that predicts individual behavior and that which predicts the average or aggregate behavior of the population suggesting a greater importance of individual differences than is typically acknowledged. For instance, past work has demonstrated that some, but not all, of the neural activity observed during value-based decision-making is able to predict not just individual subjects' choices but also the success of products on large, online marketplaces-even when those two behavioral outcomes deviate from one another-suggesting that some neural component processes of decision-making generalize to aggregate market responses more readily across individuals than others do. While the bulk of such research has highlighted affect-related neural responses (i.e. in the nucleus accumbens) as a better predictor of group-level behavior than frontal cortical activity associated with the integration of more idiosyncratic choice components, more recent evidence has implicated responses in visual cortical regions as strong predictors of group preference. Taken together, these findings suggest a role of neural responses during early perception in reinforcing choice consistency across individuals and raise fundamental scientific questions about the role sensory systems in value-based decision-making processes. We use a multivariate pattern analysis approach to show that single-trial visually evoked electroencephalographic (EEG) activity can predict individual choice throughout the post-stimulus epoch; however, a nominally sparser set of activity predicts the aggregate behavior of the population. These findings support an account in which a subset of the neural activity underlying individual choice processes can scale to predict behavioral consistency across people, even when the choice behavior of the sample does not match the aggregate behavior of the population.

Generalizing across tonal context, timbre, and octave in rapid absolute pitch training.

Absolute pitch (AP) is the rare ability to name any musical note without the use of a reference note. Given that genuine AP representations are based on the identification of isolated notes by their tone chroma, they are considered to be invariant to (1) surrounding tonal context, (2) changes in instrumental timbre, and (3) changes in octave register. However, there is considerable variability in the literature in terms of how AP is trained and tested along these dimensions, making recent claims about AP learning difficult to assess. Here, we examined the effect of tonal context on participant success with a single-note identification training paradigm, including how learning generalized to an untested instrument and octave. We found that participants were able to rapidly learn to distinguish C from other notes, with and without feedback and regardless of the tonal context in which C was presented. Participants were also able to partly generalize this skill to an untrained instrument. However, participants displayed the weakest generalization in recognizing C in a higher octave. The results indicate that participants were likely attending to pitch height in addition to pitch chroma - a conjecture that was supported by analyzing the pattern of response errors. These findings highlight the complex nature of note representation in AP, which requires note identification across contexts, going beyond the simple storage of a note fundamental. The importance of standardizing testing that spans both timbre and octave in assessing AP and further implications on past literature and future work are discussed.

Recursive syntactic pattern learning by songbirds.

Humans regularly produce new utterances that are understood by other members of the same language community. Linguistic theories account for this ability through the use of syntactic rules (or generative grammars) that describe the acceptable structure of utterances. The recursive, hierarchical embedding of language units (for example, words or phrases within shorter sentences) that is part of the ability to construct new utterances minimally requires a 'context-free' grammar that is more complex than the 'finite-state' grammars thought sufficient to specify the structure of all non-human communication signals. Recent hypotheses make the central claim that the capacity for syntactic recursion forms the computational core of a uniquely human language faculty. Here we show that European starlings (Sturnus vulgaris) accurately recognize acoustic patterns defined by a recursive, self-embedding, context-free grammar. They are also able to classify new patterns defined by the grammar and reliably exclude agrammatical patterns. Thus, the capacity to classify sequences from recursive, centre-embedded grammars is not uniquely human. This finding opens a new range of complex syntactic processing mechanisms to physiological investigation.

Task-dependent organization of brain regions active during rest.

The human brain demonstrates complex yet systematic patterns of neural activity at rest. We examined whether functional connectivity among those brain regions typically active during rest depends on ongoing and recent task demands and individual differences. We probed the temporal coordination among these regions during periods of language comprehension and during the rest periods that followed comprehension. Our findings show that the topography of this "rest network" varies with exogenous processing demands. The network encompassed more highly interconnected regions during rest than during listening, but also when listening to unsurprising vs. surprising information. Furthermore, connectivity patterns during rest varied as a function of recent listening experience. Individual variability in connectivity strength was associated with cognitive function: more attentive comprehenders demonstrated weaker connectivity during language comprehension, and a greater differentiation between connectivity during comprehension and rest. The regions we examined have generally been thought to form an invariant physiological and functional network whose activity reflects spontaneous cognitive processes. Our findings suggest that their function extends beyond the mediation of unconstrained thought, and that they play an important role in higher-level cognitive function.

Abstract coding of audiovisual speech: beyond sensory representation.

Is there a neural representation of speech that transcends its sensory properties? Using fMRI, we investigated whether there are brain areas where neural activity during observation of sublexical audiovisual input corresponds to a listener's speech percept (what is "heard") independent of the sensory properties of the input. A target audiovisual stimulus was preceded by stimuli that (1) shared the target's auditory features (auditory overlap), (2) shared the target's visual features (visual overlap), or (3) shared neither the target's auditory or visual features but were perceived as the target (perceptual overlap). In two left-hemisphere regions (pars opercularis, planum polare), the target invoked less activity when it was preceded by the perceptually overlapping stimulus than when preceded by stimuli that shared one of its sensory components. This pattern of neural facilitation indicates that these regions code sublexical speech at an abstract level corresponding to that of the speech percept.

Sleep-dependent consolidation of auditory discrimination learning in adult starlings.

Memory consolidation is widely believed to benefit from sleep. Sleep-dependent memory consolidation has been established broadly in humans, appearing in declarative and procedural tasks. Animal studies have indicated a variety of mechanisms that could potentially serve as the neural basis of sleep-dependent consolidation, such as the offline replay of waking neural activity and the modulation of specific sleep parameters or synaptic strength during sleep. Memory consolidation, however, cannot be inferred from neuronal events alone, and the behavioral demonstration of sleep-dependent consolidation has been limited in animals. Here we investigated whether adult animals undergo sleep-dependent memory consolidation comparable to that of humans. European starlings (Sturnus vulgaris) were trained to discriminate between segments of novel starling song and retested after retention periods that included a regular night of sleep or consisted only of wakefulness. Auditory discrimination performance improved significantly after retention periods that included sleep but not after time spent awake, and the performance changes following sleep were significantly greater than after comparable periods of wakefulness. Thus, sleep produces a pattern of memory benefits in adult starlings that is fundamentally similar to the patterns of sleep-dependent consolidation observed in humans, suggesting a common sleep-dependent mechanism works across many vertebrate species to consolidate memories and establishing a robust animal model for this phenomenon.

Consolidating the effects of waking and sleep on motor-sequence learning.

Sleep is widely believed to play a critical role in memory consolidation. Sleep-dependent consolidation has been studied extensively in humans using an explicit motor-sequence learning paradigm. In this task, performance has been reported to remain stable across wakefulness and improve significantly after sleep, making motor-sequence learning the definitive example of sleep-dependent enhancement. Recent work, however, has shown that enhancement disappears when the task is modified to reduce task-related inhibition that develops over a training session, thus questioning whether sleep actively consolidates motor learning. Here we use the same motor-sequence task to demonstrate sleep-dependent consolidation for motor-sequence learning and explain the discrepancies in results across studies. We show that when training begins in the morning, motor-sequence performance deteriorates across wakefulness and recovers after sleep, whereas performance remains stable across both sleep and subsequent waking with evening training. This pattern of results challenges an influential model of memory consolidation defined by a time-dependent stabilization phase and a sleep-dependent enhancement phase. Moreover, the present results support a new account of the behavioral effects of waking and sleep on explicit motor-sequence learning that is consistent across a wide range of tasks. These observations indicate that current theories of memory consolidation that have been formulated to explain sleep-dependent performance enhancements are insufficient to explain the range of behavioral changes associated with sleep.