Retrieving the structure of probabilistic sequences of auditory stimuli from EEG data

Using a new probabilistic approach we model the relationship between sequences of auditory stimuli generated by stochastic chains and the electroencephalographic (EEG) data acquired while 19 participants were exposed to those stimuli. The structure of the chains generating the stimuli are characterized by rooted and labeled trees whose leaves, henceforth called contexts, represent the sequences of past stimuli governing the choice of the next stimulus. A classical conjecture claims that the brain assigns probabilistic models to samples of stimuli. If this is true, then the context tree generating the sequence of stimuli should be encoded in the brain activity. Using an innovative statistical procedure we show that this context tree can effectively be extracted from the EEG data, thus giving support to the classical conjecture.

The longer the better? General skill but not probabilistic learning improves with the duration of short rest periods

Memory consolidation has mainly been investigated for extended periods, from hours to days. Recent studies suggest that memory consolidation can also occur within shorter periods, from minutes to seconds. Our study aimed at determining (1) whether short rest periods lead to improvements in implicit probabilistic sequence learning and (2) whether length of rest duration influences such offline improvements. Participants performed an implicit probabilistic sequence learning task throughout 45 blocks. Between blocks, participants were allowed to rest and then to continue the task in their pace. The overall reaction times (general skill learning) shortened from pre- to post-rest periods, and this improvement was increased for longer rest durations. However, probabilistic sequences knowledge decreased in these periods, and this decrement was not related to the length of rest duration. These results suggest that (1) general skill learning but not probabilistic sequence knowledge benefits from short rest periods and, possibly, from memory consolidation, (2) ultra-fast offline improvements in general skills, but not forgetting in probabilistic sequence knowledge, are time-dependent. Overall, our findings highlight that ultra-fast consolidation differently affects distinct cognitive processes.

Sequence Structure Has a Differential Effect on Underlying Motor Learning Processes

Current methods to understand implicit motor sequence learning inadequately assess motor skill acquisition in daily life. Using fixed sequences in the serial reaction time task is not ideal as participants may become aware of the sequence, thereby changing the learning from implicit to explicit. Probabilistic sequences, in which stimuli are linked by statistical, rather than deterministic, associations can ensure that learning remains implicit. Additionally, the processes underlying the learning of motor sequences may differ based on sequence structure. Here, the authors compared the learning of fixed and probabilistic sequences to randomly ordered stimuli using a modified serial reaction time task. Both the fixed and probabilistic sequence groups exhibited learning as indicated by decreased response time and variability. In the initial stage of learning, fixed sequences exhibited both online and offline gains in response time; however, only the offline gain was observed during the learning of probabilistic sequences. These results indicated that probabilistic structures may be learned differently from fixed structures and have important implications for our current understanding of motor learning. Probabilistic sequences more accurately reflect motor skill acquisition in daily life, offer ecological validity to the serial reaction time framework, and advance our understanding of motor learning.

Timing during transitions in Bengalese finch song: implications for motor sequencing

To investigate mechanisms of action sequencing, we examined the relationship between timing and sequencing of syllables in Bengalese finch song. An individual’s song comprises acoustically distinct syllables organized into probabilistic sequences: a given syllable potentially can transition to several different syllables (divergence points), and several different syllables can transition to a given syllable (convergence points). In agreement with previous studies, we found that more probable transitions at divergence points occur with shorter intersyllable gaps. One intuition for this relationship is that selection between syllables reflects a competitive branching process, in which stronger links to one syllable lead to both higher probabilities and shorter latencies for transitions to that syllable vs. competing alternatives. However, we found that simulations of competitive race models result in overlapping winning-time distributions for competing outcomes and fail to replicate the strong negative correlation between probability and gap duration found in song data. Further investigation of song structure revealed strong positive correlation between gap durations for transitions that share a common convergent point. Such transitions are not related by a common competitive process, but instead reflect a common terminal syllable. In contrast to gap durations, transition probabilities were not correlated at convergence points. Together, our data suggest that syllable selection happens early during the gap, with gap timing determined chiefly by the latency to syllable initiation. This may result from a process in which probabilistic sequencing is first stabilized, followed by a shortening of the latency to syllables that are sung more often. NEW & NOTEWORTHY Bengalese finch songs consist of probabilistic sequences of syllables. Previous studies revealed a strong negative correlation between transition probability and the duration of intersyllable gaps. We show here that the negative correlation is inconsistent with previous suggestions that timing at syllable transitions is governed by a race between competing alternatives. Rather, the data suggest that syllable selection happens early during the gap, with gap timing determined chiefly by the latency to syllable initiation.

Preliminary Study on Risk-Informed LBLOCA of CPR1000

The safety assessment approach of nuclear power plants (NPPs) has been evolved with the technological progress and the lessons learned from the major events. Recently, the risk-informed analysis methodology combined probabilistic safety assessment (PSA) and traditional deterministic methodology has been a hot topic. Following the Risk-Informed Analysis Methodology, the PCT margin of CPR1000 Nuclear Power Plant was re-evaluated in this paper. In the PSA analysis, 162 probabilistic sequences had been identified after LBLOCA occurs. Then 18 probabilistically significant sequences were selected for the deterministic methodology analysis with deterministic realistic method (DRM) for CPR1000 NPP. With calculated PCT of each dominant sequence, a load spectrum of PCT for LBLOCA was generated. Then the risk-informed PCT margin can be evaluated by two different methods, namely the expecting value estimation method and the sequence probability coverage method. In conclusion, it was found that the PCT margin evaluated by the Risk-Informed Analysis Methodology can be greater than that of the deterministic DRM methodology by 16∼34°C.

Auditory-induced neural dynamics in sensory-motor circuitry predict learned temporal and sequential statistics of birdsong

Predicting future events is a critical computation for both perception and behavior. Despite the essential nature of this computation, there are few studies demonstrating neural activity that predicts specific events in learned, probabilistic sequences. Here, we test the hypotheses that the dynamics of internally generated neural activity are predictive of future events and are structured by the learned temporal–sequential statistics of those events. We recorded neural activity in Bengalese finch sensory-motor area HVC in response to playback of sequences from individuals’ songs, and examined the neural activity that continued after stimulus offset. We found that the strength of response to a syllable in the sequence depended on the delay at which that syllable was played, with a maximal response when the delay matched the intersyllable gap normally present for that specific syllable during song production. Furthermore, poststimulus neural activity induced by sequence playback resembled the neural response to the next syllable in the sequence when that syllable was predictable, but not when the next syllable was uncertain. Our results demonstrate that the dynamics of internally generated HVC neural activity are predictive of the learned temporal–sequential structure of produced song and that the strength of this prediction is modulated by uncertainty.

Implicit Learning of Second-, Third-, and Fourth-Order Adjacent and Nonadjacent Sequential Dependencies

Serial reaction time (SRT) task studies have established that people can implicitly learn first- and second-order adjacent dependencies. Sequential confounds have made it impossible to draw conclusions regarding learning of nonadjacent dependencies and learning of third- and fourth-order adjacent dependencies. Addressing the confounds, the present study shows that people can implicitly learn second-, third-, and fourth-order adjacent and nonadjacent dependencies embedded in probabilistic sequences of target locations.