scholarly journals Distinct roles of cognitive and sensory information in musical expectancy

2020 ◽  
Author(s):  
Vincent K.M. Cheung ◽  
Peter M. C. Harrison ◽  
Stefan Koelsch ◽  
Marcus Thomas Pearce ◽  
Angela D. Friederici ◽  
...  
Keyword(s):  
Model Comparison ◽  
Short Term Memory ◽  
Predictive Accuracy ◽  
Sensory Information ◽  
Current Debate ◽  
Short Term ◽  
Term Memory ◽  
Bayesian Model Comparison ◽  
Music Structure ◽  
Probabilistic Knowledge

Expectation is crucial for our enjoyment of music, yet the underlying generative mechanism remains contested. While sensory–acoustic models derive predictions based on the short-term auditory input alone, cognitive models assume the use of abstract knowledge of music structure acquired over the long-term. To evaluate these two contrasting mechanisms, we compared simulations from computational models of musical expectancy against subjective surprise ratings of chords sampled from US Billboard pop songs in musicians and non-musicians. Bayesian model comparison revealed that probabilistic knowledge of music structure and auditory short-term memory both explained unique behavioural variance without mediation. However, probabilistic knowledge accounted for nearly four times as much variance in musicians, and over twice as much in non-musicians. Incorporating both probabilistic knowledge and auditory short-term memory together furthermore improved predictive accuracy over the individual models. Our findings thus motivate an alternative to the current debate by emphasising the distinct, albeit complementary, roles of cognitive and sensory information in forming expectations during music-listening in humans.

scholarly journals PM2.5 concentration forecasting using Long Short-Term Memory Neural Network and Multi-Level Additive Model

2019 ◽  
Author(s):  
Lixin Tao ◽  
Feifei Tian ◽  
Lijuan Wu ◽  
Mengyang Liu ◽  
Yuan Ma ◽  
...  
Keyword(s):  
Neural Network ◽  
Short Term Memory ◽  
Predictive Accuracy ◽  
Additive Model ◽  
Percentage Error ◽  
Short Term ◽  
Term Memory ◽  
Pm 2.5 ◽  
Multi Level ◽  
Long Short Term Memory

Abstract Background PM 2.5 concentration predication can provide an effective way to protect public health by early warning. Though there are many methods available, the comparison between multi-level additive model (AM) and long short-term memory (LSTM) neural network in predicting PM 2.5 concentration is limited. This study aimed to compare the performance of multi-level AM and LSTM in predicting hourly and daily PM 2.5 concentration.Methods Air pollution data from Jul 1, 2016 to Dec 31, 2017 were obtained from Beijing Municipal Environmental Monitoring Center, and meteorological data were derived from the National Meteorological Science Data Sharing Service. Multi-level AM and LSTM were developed to estimate the regional hourly and daily concentration of PM 2.5 .Results In the prediction of hourly PM 2.5 concentrations, LSTM achieved a better performance than multi-level AM (range of R 2 : 0.76-0.92 for LSTM, 0.59-0.78 for multi-level AM; range of root mean square error (RMSE): 6.20-17.58μg/m 3 for LSTM, 19.19-30.81μg/m 3 for multi-level AM; range of mean absolute error (MAE): 4.50-13.42μg/m 3 for LSTM, 13.55-22.35μg/m 3 for multi-level AM; range of mean absolute percentage error (MAPE): 0.18%-0.55% for LSTM, 0.50%-0.87% for multi-level AM). While in the prediction of daily PM 2.5 concentrations, multi-level AM showed a higher predictive accuracy than LSTM (range of R 2 : 0.43-0.93 for LSTM, 0.74-0.98 for multi-level AM; range of RMSE: 32.46-46.82μg/m 3 for LSTM, 4.83-20.98μg/m 3 for multi-level AM; range of MAE: 24.32-34.89μg/m 3 for LSTM, 3.67-16.33μg/m 3 for multi-level AM; range of MAPE: 0.92%-1.74% for LSTM, 0.11%-0.45% for multi-level AM).Conclusion LSTM showed better performance than the multi-level AM when there is a large amount of data, while multi-level AM showed better performance than LSTM when the amount of data is relatively small.

scholarly journals A Deep Learning Integrated Lee–Carter Model

Risks ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 33 ◽  
Author(s):  
Andrea Nigri ◽  
Susanna Levantesi ◽  
Mario Marino ◽  
Salvatore Scognamiglio ◽  
Francesca Perla
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Predictive Accuracy ◽  
Mortality Rates ◽  
Short Term ◽  
Term Memory ◽  
The Future ◽  
Long Short Term Memory ◽  
Carter Model ◽  
Over Time

In the field of mortality, the Lee–Carter based approach can be considered the milestone to forecast mortality rates among stochastic models. We could define a “Lee–Carter model family” that embraces all developments of this model, including its first formulation (1992) that remains the benchmark for comparing the performance of future models. In the Lee–Carter model, the κ t parameter, describing the mortality trend over time, plays an important role about the future mortality behavior. The traditional ARIMA process usually used to model κ t shows evident limitations to describe the future mortality shape. Concerning forecasting phase, academics should approach a more plausible way in order to think a nonlinear shape of the projected mortality rates. Therefore, we propose an alternative approach the ARIMA processes based on a deep learning technique. More precisely, in order to catch the pattern of κ t series over time more accurately, we apply a Recurrent Neural Network with a Long Short-Term Memory architecture and integrate the Lee–Carter model to improve its predictive capacity. The proposed approach provides significant performance in terms of predictive accuracy and also allow for avoiding the time-chunks’ a priori selection. Indeed, it is a common practice among academics to delete the time in which the noise is overflowing or the data quality is insufficient. The strength of the Long Short-Term Memory network lies in its ability to treat this noise and adequately reproduce it into the forecasted trend, due to its own architecture enabling to take into account significant long-term patterns.

Binary Mapping of Cortical Spike Trains in Short-Term Memory

1997 ◽  
Vol 77 (4) ◽  
pp. 2219-2222 ◽  
Author(s):  
Mark Bodner ◽  
Yong-Di Zhou ◽  
Joaquín M. Fuster
Keyword(s):  
Cortical Neurons ◽  
Short Term Memory ◽  
Memory Task ◽  
Sensory Information ◽  
Spatial Summation ◽  
Spike Trains ◽  
Short Term ◽  
Cortical Cells ◽  
Term Memory ◽  
Wide Range

Bodner, Mark, Yong-Di Zhou, and Joaquı́n M. Fuster. Binary mapping of cortical spike trains in short-term memory. J. Neurophysiol. 77: 2219–2222, 1997. Microelectrode studies in monkeys performing short-term memory tasks show the sustained elevated discharge of cortical neurons during the retention of recalled sensory information. Cortical cells that are part of memory networks are assumed to receive numerous inputs of excitatory as well as inhibitory nature and local as well as remote. Thus it is reasonable to postulate that the temporal and spatial summation of diverse inputs on any cell in an activated network will result in temporally discrete groups of spikes in its firing. The activation of a network in active memory supposedly increases the magnitude and diversity of those inputs and thus increases the discontinuities and frequency fluctuations in the firing of cells in the network. In this study we use a new method of analysis that allows the quantification of firing discontinuities in a spike train. We apply it to parietal cells recorded from monkeys during the performance of a tactile short-term memory task. In our method, time is divided into bins of equal duration and the measure of discontinuities is the total count of the number of transitions between consecutive time bins with and without spikes. The results of the analysis show that in many of the cells studied, discontinuities (transitions between spiking and nonspiking) reflect memory-related activity obscured in the measures of raw spike frequency over a wide range of frequencies. These cells show more firing transitions in active short-term memory than in baseline (intertrial) conditions.

Conceptual short-term memory (CSTM) supports core claims of Christiansen and Chater

2016 ◽  
Vol 39 ◽  
Author(s):  
Mary C. Potter
Keyword(s):  
Working Memory ◽  
Rapid Serial Visual Presentation ◽  
Language Comprehension ◽  
Short Term Memory ◽  
Visual Presentation ◽  
Long Term Memory ◽  
Short Term ◽  
Term Memory ◽  
Use Of Knowledge

AbstractRapid serial visual presentation (RSVP) of words or pictured scenes provides evidence for a large-capacity conceptual short-term memory (CSTM) that momentarily provides rich associated material from long-term memory, permitting rapid chunking (Potter 1993; 2009; 2012). In perception of scenes as well as language comprehension, we make use of knowledge that briefly exceeds the supposed limits of working memory.

Working, Declarative, and Procedural Memory in Children With Developmental Language Disorder

2020 ◽  
Vol 63 (12) ◽  
pp. 4162-4178
Author(s):  
Emily Jackson ◽  
Suze Leitão ◽  
Mary Claessen ◽  
Mark Boyes
Keyword(s):  
Working Memory ◽  
Short Term Memory ◽  
Language Disorder ◽  
Declarative Memory ◽  
Memory Systems ◽  
Procedural Memory ◽  
Typically Developing ◽  
Short Term ◽  
Term Memory ◽  
Visual Spatial

Purpose Previous research into the working, declarative, and procedural memory systems in children with developmental language disorder (DLD) has yielded inconsistent results. The purpose of this research was to profile these memory systems in children with DLD and their typically developing peers. Method One hundred four 5- to 8-year-old children participated in the study. Fifty had DLD, and 54 were typically developing. Aspects of the working memory system (verbal short-term memory, verbal working memory, and visual–spatial short-term memory) were assessed using a nonword repetition test and subtests from the Working Memory Test Battery for Children. Verbal and visual–spatial declarative memory were measured using the Children's Memory Scale, and an audiovisual serial reaction time task was used to evaluate procedural memory. Results The children with DLD demonstrated significant impairments in verbal short-term and working memory, visual–spatial short-term memory, verbal declarative memory, and procedural memory. However, verbal declarative memory and procedural memory were no longer impaired after controlling for working memory and nonverbal IQ. Declarative memory for visual–spatial information was unimpaired. Conclusions These findings indicate that children with DLD have deficits in the working memory system. While verbal declarative memory and procedural memory also appear to be impaired, these deficits could largely be accounted for by working memory skills. The results have implications for our understanding of the cognitive processes underlying language impairment in the DLD population; however, further investigation of the relationships between the memory systems is required using tasks that measure learning over long-term intervals. Supplemental Material https://doi.org/10.23641/asha.13250180

Comparison of Auditory, Language, Memory, and Attention Abilities in Children With and Without Listening Difficulties

2020 ◽  
Vol 29 (4) ◽  
pp. 710-727
Author(s):  
Beula M. Magimairaj ◽  
Naveen K. Nagaraj ◽  
Alexander V. Sergeev ◽  
Natalie J. Benafield
Keyword(s):  
Auditory Processing ◽  
Short Term Memory ◽  
Group Differences ◽  
Long Term Memory ◽  
Short Term ◽  
Significant Group ◽  
Term Memory ◽  
Memory And Attention ◽  
Speed And Accuracy

Objectives School-age children with and without parent-reported listening difficulties (LiD) were compared on auditory processing, language, memory, and attention abilities. The objective was to extend what is known so far in the literature about children with LiD by using multiple measures and selective novel measures across the above areas. Design Twenty-six children who were reported by their parents as having LiD and 26 age-matched typically developing children completed clinical tests of auditory processing and multiple measures of language, attention, and memory. All children had normal-range pure-tone hearing thresholds bilaterally. Group differences were examined. Results In addition to significantly poorer speech-perception-in-noise scores, children with LiD had reduced speed and accuracy of word retrieval from long-term memory, poorer short-term memory, sentence recall, and inferencing ability. Statistically significant group differences were of moderate effect size; however, standard test scores of children with LiD were not clinically poor. No statistically significant group differences were observed in attention, working memory capacity, vocabulary, and nonverbal IQ. Conclusions Mild signal-to-noise ratio loss, as reflected by the group mean of children with LiD, supported the children's functional listening problems. In addition, children's relative weakness in select areas of language performance, short-term memory, and long-term memory lexical retrieval speed and accuracy added to previous research on evidence-based areas that need to be evaluated in children with LiD who almost always have heterogenous profiles. Importantly, the functional difficulties faced by children with LiD in relation to their test results indicated, to some extent, that commonly used assessments may not be adequately capturing the children's listening challenges. Supplemental Material https://doi.org/10.23641/asha.12808607

The Link Between Verbal Short-Term Memory and Anomia Treatment Gains

2019 ◽  
Vol 28 (3) ◽  
pp. 1039-1052
Author(s):  
Reva M. Zimmerman ◽  
JoAnn P. Silkes ◽  
Diane L. Kendall ◽  
Irene Minkina
Keyword(s):  
Short Term Memory ◽  
Controlled Trial ◽  
Treatment Success ◽  
Linear Regression Models ◽  
Language Performance ◽  
Short Term ◽  
Term Memory ◽  
Treatment Gains ◽  
Post Hoc

Purpose A significant relationship between verbal short-term memory (STM) and language performance in people with aphasia has been found across studies. However, very few studies have examined the predictive value of verbal STM in treatment outcomes. This study aims to determine if verbal STM can be used as a predictor of treatment success. Method Retrospective data from 25 people with aphasia in a larger randomized controlled trial of phonomotor treatment were analyzed. Digit and word spans from immediately pretreatment were run in multiple linear regression models to determine whether they predict magnitude of change from pre- to posttreatment and follow-up naming accuracy. Pretreatment, immediately posttreatment, and 3 months posttreatment digit and word span scores were compared to determine if they changed following a novel treatment approach. Results Verbal STM, as measured by digit and word spans, did not predict magnitude of change in naming accuracy from pre- to posttreatment nor from pretreatment to 3 months posttreatment. Furthermore, digit and word spans did not change from pre- to posttreatment or from pretreatment to 3 months posttreatment in the overall analysis. A post hoc analysis revealed that only the less impaired group showed significant changes in word span scores from pretreatment to 3 months posttreatment. Discussion The results suggest that digit and word spans do not predict treatment gains. In a less severe subsample of participants, digit and word span scores can change following phonomotor treatment; however, the overall results suggest that span scores may not change significantly. The implications of these findings are discussed within the broader purview of theoretical and empirical associations between aphasic language and verbal STM processing.

Symptomvalidierungstests in der neuropsychologischen Diagnostik: eine Analogstudie

2004 ◽  
Vol 15 (2) ◽  
pp. 81-90 ◽  
Author(s):  
Thomas Merten ◽  
Matthias Henry ◽  
Robin Hilsabeck
Keyword(s):  
Short Term Memory ◽  
Memory Test ◽  
Short Term ◽  
Term Memory ◽  
Word Memory Test ◽  
Word Memory ◽  
Complex Figure ◽  
Trail Making ◽  
Figure Test ◽  
Word Completion

Zusammenfassung: In der neuropsychologischen Diagnostik, mehr noch aber in der Begutachtung gewinnen Symptomvalidierungstests (SVT) zur Untersuchung der Leistungsmotivation zunehmend an Bedeutung. In einer Analogstudie wurde die Güte zweier international bekannter Verfahren (Word Memory Test; Amsterdam Short Term Memory Test) sowie einer Neuentwicklung (Word Completion Memory Test) untersucht. Zusätzlich wurden Leistungstests eingesetzt: der Trail Making Test (TMT), der Complex Figure Test sowie die Standard Progressive Matrices (SPM). Eine Gruppe von 10 experimentellen Simulanten wurde spezifisch auf die Vortäuschung von Gedächtnisstörungen vorbereitet, während eine Kontrollgruppe (n = 10) optimale Testanstrengung zeigen sollte. Alle SVT führten im Gegensatz zu den Simulationsmarkern des TMT und der SPM zu einer ausgezeichneten Klassifikationsgüte (95-100 %). Die neuropsychologischen Leistungsmaße wiesen zwar signifikante Gruppenunterschiede aus, zeigten aber auch eine nicht unbedeutende Überlappung der Verteilungen. Mehr Studien sind notwendig, um den SVT in den deutschsprachigen Ländern den Platz zu sichern, den sie international aktuell in der klinisch-neuropsychologischen Forschung und Praxis einnehmen.

Dynamic Visual Noise Affects Visual Short-Term Memory for Surface Color, but not Spatial Location

2010 ◽  
Vol 57 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Kevin Dent
Keyword(s):  
Short Term Memory ◽  
Spatial Location ◽  
Visual Noise ◽  
Dynamic Visual Noise ◽  
Short Term ◽  
Surface Color ◽  
Term Memory ◽  
Visual Short Term Memory ◽  
Experimental Tool ◽  
Spatial Locations

In two experiments participants retained a single color or a set of four spatial locations in memory. During a 5 s retention interval participants viewed either flickering dynamic visual noise or a static matrix pattern. In Experiment 1 memory was assessed using a recognition procedure, in which participants indicated if a particular test stimulus matched the memorized stimulus or not. In Experiment 2 participants attempted to either reproduce the locations or they picked the color from a whole range of possibilities. Both experiments revealed effects of dynamic visual noise (DVN) on memory for colors but not for locations. The implications of the results for theories of working memory and the methodological prospects for DVN as an experimental tool are discussed.

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