scholarly journals When less is more: Enhanced statistical learning of non-adjacent dependencies after disruption of bilateral DLPFC

2017 ◽  
Author(s):  
Géza Gergely Ambrus ◽  
Teodóra Vékony ◽  
Karolina Janacsek ◽  
Anna B. C. Trimborn ◽  
Gyula Kovács ◽  
...  
Keyword(s):  
Statistical Learning ◽  
Learning Performance ◽  
Less Is More ◽  
Prefrontal Cortical ◽  
Model Free ◽  
Dorsolateral Prefrontal ◽  
Statistical Regularities ◽  
Left And Right ◽  
Qualitative Changes

AbstractBrain networks related to human learning can interact in cooperative but also competitive ways to optimize performance. The investigation of such interactive processes is rare in research on learning and memory. Previous studies have shown that manipulations reducing the engagement of prefrontal cortical areas could lead to improved statistical learning performance. However, no study has investigated how disruption of the dorsolateral prefrontal cortex (DLPFC) affects the acquisition and consolidation of non-adjacent second-order dependencies. The present study aimed to test the role of the DLPFC, more specifically, the Brodmann 9 area in implicit temporal statistical learning of non-adjacent dependencies. We applied 1 Hz inhibitory transcranial magnetic stimulation or sham stimulation over both the left and right DLPFC intermittently during the learning. The DLPFC-stimulated group showed better performance compared to the sham group after a 24-hour consolidation period. This finding suggests that the disruption of DLPFC during learning induces qualitative changes in the consolidation of non-adjacent statistical regularities. A possible mechanism behind this result is that the stimulation of the DLPFC promotes a shift to model-free learning by weakening the access to model-based processes.

scholarly journals What drives individual differences in statistical learning? The role of perceptual fluency and familiarity

2018 ◽  
Author(s):  
Amy Perfors ◽  
Evan Kidd
Keyword(s):  
Individual Differences ◽  
Statistical Learning ◽  
Learning Task ◽  
Perceptual Fluency ◽  
Learning Performance ◽  
Visual Modality ◽  
Learning Skills ◽  
Domain Specific ◽  
Different Levels

Humans have the ability to learn surprisingly complicated statistical information in a variety of modalities and situations, often based on relatively little input. These statistical learning (SL) skills appear to underlie many kinds of learning, but despite their ubiquity, we still do not fully understand precisely what SL is and what individual differences on SL tasks reflect. Here we present experimental work suggesting that at least some individual differences arise from variation in perceptual fluency — the ability to rapidly or efficiently code and remember the stimuli that statistical learning occurs over. We show that performance on a standard SL task varies substantially within the same (visual) modality as a function of whether the stimuli involved are familiar or not, independent of stimulus complexity. Moreover, we find that test-retest correlations of performance in a statistical learning task using stimuli of the same level of familiarity (but distinct items) are stronger than correlations across the same task with different levels of familiarity. Finally, we demonstrate that statistical learning performance is predicted by an independent measure of stimulus-specific perceptual fluency which contains no statistical learning component at all. Our results suggest that a key component of SL performance may be unrelated to either domain-specific statistical learning skills or modality-specific perceptual processing.

An Exploratory TMS Study on Prefrontal Lateralization in Valence Categorization of Facial Expressions

2017 ◽  
Vol 64 (4) ◽  
pp. 282-289 ◽  
Author(s):  
Chiara Ferrari ◽  
Lucile Gamond ◽  
Marcello Gallucci ◽  
Tomaso Vecchi ◽  
Zaira Cattaneo
Keyword(s):  
Facial Expressions ◽  
Emotional Processing ◽  
Right Hemisphere ◽  
Control Site ◽  
Emotional Facial Expressions ◽  
Left Dlpfc ◽  
Dorsolateral Prefrontal ◽  
Left And Right ◽  
The Right

Abstract. Converging neuroimaging and patient data suggest that the dorsolateral prefrontal cortex (DLPFC) is involved in emotional processing. However, it is still not clear whether the DLPFC in the left and right hemisphere is differentially involved in emotion recognition depending on the emotion considered. Here we used transcranial magnetic stimulation (TMS) to shed light on the possible causal role of the left and right DLPFC in encoding valence of positive and negative emotional facial expressions. Participants were required to indicate whether a series of faces displayed a positive or negative expression, while TMS was delivered over the right DLPFC, the left DLPFC, and a control site (vertex). Interfering with activity in both the left and right DLPFC delayed valence categorization (compared to control stimulation) to a similar extent irrespective of emotion type. Overall, we failed to demonstrate any valence-related lateralization in the DLPFC by using TMS. Possible methodological limitations are discussed.

scholarly journals What drives individual differences in statistical learning? The role of perceptual fluency and familiarity

2020 ◽  
Author(s):  
Andrew Perfors ◽  
Evan Kidd
Keyword(s):  
Individual Differences ◽  
Statistical Learning ◽  
Learning Task ◽  
Perceptual Processing ◽  
Perceptual Fluency ◽  
Learning Performance ◽  
Visual Modality ◽  
Stimulus Familiarity ◽  
Different Levels

Humans have the ability to learn surprisingly complicated statistical information in avariety of modalities and situations, often based on relatively little input. These statistical learning (SL) skills appear to underlie many kinds of learning, but despite their ubiquity, we still do not fully understand precisely what SL is and what individual differences on SL tasks reflect. Here we present experimental work suggesting that at least some individual differences arise from variation in perceptual fluency — the ability to rapidly or efficiently code and remember the stimuli that statistical learning occurs over – and that perceptual fluency is driven at least in part by stimulus familiarity: performance on a standard SL task varies substantially within the same (visual) modality as a function of whether the stimuli involved are familiar or not, independent of stimulus complexity. Moreover, we find that test-retest correlations of performance in a statistical learning task using stimuli of the same level of familiarity (but distinct items) are stronger than correlations across the same task with stimuli of different levels of familiarity. Finally, we demonstrate that statistical learning performance is predicted by an independent measure of stimulus-specific perceptual fluency that contains no statistical learning component at all. Our results suggest that a key component of statistical learning performance may be related to stimulus-specific perceptual processing and familiarity.

Executive function deficit in betel-quid-dependent chewers: Mediating role of prefrontal cortical thickness

2018 ◽  
Vol 32 (12) ◽  
pp. 1362-1368 ◽  
Author(s):  
Xueling Zhu ◽  
Shaohui Liu ◽  
Weihua Liao ◽  
Lingyu Kong ◽  
Canhua Jiang ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Executive Function ◽  
Cortical Thickness ◽  
Dorsolateral Prefrontal Cortex ◽  
Betel Quid ◽  
Prefrontal Cortical ◽  
Betel Quid Chewing ◽  
Dorsolateral Prefrontal ◽  
Brain Structure And Function

Background: Betel quid is the fourth most popular psychoactive agent worldwide. Neuroimaging studies have suggested betel-quid dependence is accompanied by abnormality in brain structure and function. However, the neural correlates of executive function deficit and prefrontal cortical thickness associated with betel-quid chewing still remain unclear. Objective: The present study aimed to examine the relationship between executive function deficit and prefrontal cortical thickness in chronic betel-quid chewers. Methods: Twenty-three betel-quid-dependent chewers and 26 healthy controls were recruited to participate in this study. Executive function was tested using three tasks. Cortical thickness analysis was analyzed with the FreeSurfer software package. Results: Behavioral results suggested a profound deficit of executive function in betel-quid-dependent chewers. Cortical thickness analysis revealed thinner cortex in the bilateral dorsolateral prefrontal cortex in betel-quid-dependent chewers. Further analysis suggested that cortical thickness of the bilateral dorsolateral prefrontal cortex mediated the correlation of betel-quid chewing and executive function. Conclusions: These results suggest the important role of executive function and cortical thickness of the dorsolateral prefrontal cortex with betel-quid chewing. Our findings provide evidence that executive function deficit may be mediated by the cortical thickness of the dorsolateral prefrontal cortex. These results could potentially help us develop novel ways to diagnose and prevent betel-quid dependence.

scholarly journals Linguistic entrenchment: prior knowledge impacts statistical learning performance

2019 ◽  
Author(s):  
Noam Siegelman ◽  
Louisa Bogaerts ◽  
Amit Elazar ◽  
Joanne Arciuli ◽  
Ram Frost
Keyword(s):  
Prior Knowledge ◽  
Statistical Learning ◽  
Native Language ◽  
Learning Task ◽  
Individual Performance ◽  
Learning Performance ◽  
General Mechanism ◽  
Verbal Tasks ◽  
Statistical Regularities ◽  
Fourth Experiment

Statistical Learning (SL) is typically considered to be a domain-general mechanism by which cognitive systems discover the underlying statistical regularities in the input. Recent findings, however, show clear differences in processing regularities across modalities and stimuli as well as low correlations between performance on visual and auditory tasks. Why does a presumably domain-general mechanism show distinct patterns of modality and stimulus specificity? Here we claim that the key to this puzzle lies in the prior knowledge brought upon by learners to the learning task. Specifically, we argue that learners’ already entrenched expectations about speech co-occurrences from their native language impacts what they learn from novel auditory verbal input. In contrast, learners are free of such entrenchment when processing sequences of visual material such as abstract shapes. We present evidence from three experiments supporting this hypothesis by showing that auditory-verbal tasks display distinct item-specific effects resulting in low correlations between test items. In contrast, non-verbal tasks – visual and auditory – show high correlations between items. Importantly, we also show that individual performance in visual and auditory SL tasks that do not implicate prior knowledge regarding co-occurrence of elements, is highly correlated. In a fourth experiment, we present further support for the entrenchment hypothesis by showing that the variance in performance between different stimuli in auditory-verbal statistical learning tasks can be traced back to their resemblance to participants' native language. We discuss the methodological and theoretical implications of these findings, focusing on models of domain generality/specificity of SL.

scholarly journals Impaired Statistical Learning in Developmental Dyslexia

2015 ◽  
Vol 58 (3) ◽  
pp. 934-945 ◽  
Author(s):  
Yafit Gabay ◽  
Erik D. Thiessen ◽  
Lori L. Holt
Keyword(s):  
Statistical Learning ◽  
Developmental Dyslexia ◽  
Phonological Processing ◽  
Sine Wave ◽  
Procedural Learning ◽  
Learning Performance ◽  
Test Items ◽  
Learning Impairments ◽  
Continuous Stream ◽  
Statistical Regularities

Purpose Developmental dyslexia (DD) is commonly thought to arise from phonological impairments. However, an emerging perspective is that a more general procedural learning deficit, not specific to phonological processing, may underlie DD. The current study examined if individuals with DD are capable of extracting statistical regularities across sequences of passively experienced speech and nonspeech sounds. Such statistical learning is believed to be domain-general, to draw upon procedural learning systems, and to relate to language outcomes. Method DD and control groups were familiarized with a continuous stream of syllables or sine-wave tones, the ordering of which was defined by high or low transitional probabilities across adjacent stimulus pairs. Participants subsequently judged two 3-stimulus test items with either high or low statistical coherence as being the most similar to the sounds heard during familiarization. Results As with control participants, the DD group was sensitive to the transitional probability structure of the familiarization materials as evidenced by above-chance performance. However, the performance of participants with DD was significantly poorer than controls across linguistic and nonlinguistic stimuli. In addition, reading-related measures were significantly correlated with statistical learning performance of both speech and nonspeech material. Conclusion Results are discussed in light of procedural learning impairments among participants with DD.

Prior real-world experience influences non-linguistic statistical learning

2020 ◽  
Author(s):  
Stephen Charles Van Hedger ◽  
Ingrid Johnsrude ◽  
Laura Batterink
Keyword(s):  
Statistical Learning ◽  
Real World ◽  
Language Experience ◽  
Pitch Range ◽  
Test Items ◽  
Instrument Measuring ◽  
Statistical Regularities ◽  
Context Free ◽  
Specific Learning

Listeners are adept at extracting regularities from the environment, a process known as statistical learning (SL). SL has been generally assumed to be a form of “context-free” learning that occurs independently of prior knowledge, and SL experiments typically involve exposing participants to presumed novel regularities, such as repeating nonsense words. However, recent work has called this assumption into question, demonstrating that learners’ previous language experience can considerably influence SL performance. In the present experiment, we tested whether previous knowledge also shapes SL in a non-linguistic domain, using a paradigm that involves extracting regularities over tone sequences. Participants learned novel tone sequences, which consisted of pitch intervals not typically found in Western music. For one group of participants, the tone sequences used artificial, computerized instrument sounds. For the other group, the same tone sequences used familiar instrument sounds (piano or violin). Knowledge of the statistical regularities was assessed using both trained sounds (measuring specific learning) and sounds that differed in pitch range and/or instrument (measuring transfer learning). In a follow-up experiment, two additional testing sessions were administered to gauge retention of learning (one day and approximately one-week post-training). Compared to artificial instruments, training on sequences played by familiar instruments resulted in reduced correlations among test items, reflecting more idiosyncratic performance. Across all three testing sessions, learning of novel regularities presented with familiar instruments was worse compared to unfamiliar instruments, suggesting that prior exposure to music produced by familiar instruments interfered with new sequence learning. Overall, these results demonstrate that real-world experience influences SL in a non-linguistic domain, supporting the view that SL involves the continuous updating of existing representations, rather than the establishment of entirely novel ones.

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