scholarly journals Prediction of Successful Memory Encoding Based on Lateral Temporal Cortical Gamma Power

2021 ◽  
Vol 15 ◽  
Author(s):  
Soyeon Jun ◽  
June Sic Kim ◽  
Chun Kee Chung
Keyword(s):  
Verbal Memory ◽  
Memory Performance ◽  
Recognition Task ◽  
Memory Formation ◽  
Gamma Activity ◽  
Support Vector ◽  
Svm Classifier ◽  
Memory Encoding ◽  
Gamma Frequency ◽  
Gamma Power

Prediction of successful memory encoding is important for learning. High-frequency activity (HFA), such as gamma frequency activity (30–150 Hz) of cortical oscillations, is induced during memory tasks and is thought to reflect underlying neuronal processes. Previous studies have demonstrated that medio-temporal electrophysiological characteristics are related to memory formation, but the effects of neocortical neural activity remain underexplored. The main aim of the present study was to evaluate the ability of gamma activity in human electrocorticography (ECoG) signals to differentiate memory processes into remembered and forgotten memories. A support vector machine (SVM) was employed, and ECoG recordings were collected from six subjects during verbal memory recognition task performance. Two-class classification using an SVM was performed to predict subsequently remembered vs. forgotten trials based on individually selected frequencies (low gamma, 30–60 Hz; high gamma, 60–150 Hz) at time points during pre- and during stimulus intervals. The SVM classifier distinguished memory performance between remembered and forgotten trials with a mean maximum accuracy of 87.5% using temporal cortical gamma activity during the 0- to 1-s interval. Our results support the functional relevance of ECoG for memory formation and suggest that lateral temporal cortical HFA may be utilized for memory prediction.

EXPRESS: Bored, distracted and forgetful – The impact of mind wandering and boredom on memory encoding

2021 ◽  
pp. 174702182110263
Author(s):  
Philippe Blondé ◽  
Marco Sperduti ◽  
Dominique Makowski ◽  
Pascale Piolino
Keyword(s):  
Working Memory ◽  
Memory Load ◽  
Memory Performance ◽  
Load Condition ◽  
Recognition Task ◽  
Mind Wandering ◽  
Memory Encoding ◽  
Working Memory Load ◽  
Thought Probes ◽  
The Impact

Mind wandering, defined as focusing attention toward task unrelated thoughts, is a common mental state known to impair memory encoding. This phenomenon is closely linked to boredom. Very few studies, however, have tested the potential impact of boredom on memory encoding. Thus, the present study aimed at manipulating mind wandering and boredom during an incidental memory encoding task, to test their differential impact on memory encoding. Thirty-two participants performed a variant of the n-back task in which they had to indicate if the current on-screen object was the same as the previous one (1-back; low working memory load) or the one presented three trials before (3-back; high working memory load). Moreover, thought probes assessing either mind wandering or boredom were randomly presented. Afterward, a surprise recognition task was delivered. Results showed that mind wandering and boredom were highly correlated, and both decreased in the high working memory load condition, while memory performance increased. Although both boredom and mind wandering predicted memory performance taken separately, we found that mind wandering was the only reliable predictor of memory performance when controlling for boredom and working memory load. Model comparisons also revealed that a model with boredom only was outperformed by a model with mind wandering only and a model with both mind wandering and boredom, suggesting that the predictive contribution of boredom in the complete model is minimal. The present results confirm the high correlation between mind wandering and boredom and suggest that the hindering effect of boredom on memory is subordinate to the effect of mind wandering.

scholarly journals Tonic resting-state hubness supports high-frequency activity defined verbal-memory encoding network in epilepsy

2019 ◽  
Author(s):  
Chaitanya Ganne ◽  
Walter Hinds ◽  
James Kragel ◽  
Xiaosong He ◽  
Noah Sideman ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Verbal Memory ◽  
Resting State ◽  
High Frequency ◽  
Cognitive Networks ◽  
Gamma Activity ◽  
List Type ◽  
Healthy Controls ◽  
Memory Encoding ◽  
Memory Network

AbstractHigh-frequency gamma activity of verbal-memory encoding using invasive-electroencephalogram coupled has laid the foundation for numerous studies testing the integrity of memory in diseased populations. Yet, the functional connectivity characteristics of networks subserving these HFA-memory linkages remains uncertain. By integrating this electrophysiological biomarker of memory encoding from IEEG with resting-state BOLD fluctuations, we estimated the segregation and hubness of HFA-memory regions in drug-resistant epilepsy patients and matched healthy controls. HFA-memory regions express distinctly different hubness compared to neighboring regions in health and in epilepsy, and this hubness was more relevant than segregation in predicting verbal memory encoding. The HFA-memory network comprised regions from both the cognitive control and primary processing networks, validating that effective verbal-memory encoding requires multiple functions, and is not dominated by a central cognitive core. Our results demonstrate a tonic intrinsic set of functional connectivity, which provides the necessary conditions for effective, phasic, task-dependent memory encoding.HighlightsHigh frequency memory activity in IEEG corresponds to specific BOLD changes in resting-state data.HFA-memory regions had lower hubness relative to control brain nodes in both epilepsy patients and healthy controls.HFA-memory network displayed hubness and participation (interaction) values distinct from other cognitive networks.HFA-memory network shared regional membership and interacted with other cognitive networks for successful memory encoding.HFA-memory network hubness predicted both concurrent task (phasic) and baseline (tonic) verbal-memory encoding success.

scholarly journals A real-time drowsiness and fatigue recognition using support vector machine

2020 ◽  
Vol 9 (4) ◽  
pp. 584
Author(s):  
Nur Nabilah Abu Mangshor ◽  
Iylia Ashiqin Abdul Majid ◽  
Shafaf Ibrahim ◽  
Nurbaity Sabri
Keyword(s):  
Support Vector Machine ◽  
Real Time ◽  
Recognition Task ◽  
Support Vector ◽  
Svm Classifier ◽  
Face Expression ◽  
Exact Position ◽  
Sobel Edge Detection ◽  
Processing Techniques ◽  
Current Accuracy

<p>A drowsiness and fatigue problems among the drivers are the main factor that contributes to road accidents. These problems are vital to be resolved as they could contribute to damage of road facilities, vehicles and most importantly the loss of lives. In avoiding these matters, a proper mechanism is needed to alert the driver to stay awake throughout the driving journey. Thus, this study proposed a real-time prototype for recognizing the drowsiness and fatigue face expression of the driver. The methodology of this study involves facial features detection using Viola-Jones algorithm to detect the exact position of both left and right eyes and mouth. Next, based on the detected eyes and mouth beforehand, the segmentation processes performed on both eyes and mouth using Sobel edge detection to obtain facial regions. The feature extraction phase is conducted using shape-based feature to obtain the extraction values. Support vector machine (SVM) classifier is deployed for the recognition task. A total of 100 images are used during the testing stages. This study achieved a competetive result of 90.00% of accuracy. Yet, hybridization or integration of more image processing techniques will be performed in the future to improve the current accuracy obtained.</p>

scholarly journals The genomic underpinnings of oscillatory biomarkers supporting successful memory encoding in humans

2019 ◽  
Author(s):  
Stefano Berto ◽  
Miles Fontenot ◽  
Sarah Seger ◽  
Fatma Ayhan ◽  
Emre Caglayan ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Memory Performance ◽  
Temporal Cortex ◽  
Memory Task ◽  
Memory Formation ◽  
Inhibitory Neurons ◽  
Patient Specific ◽  
Memory Encoding ◽  
Brain Oscillations ◽  
Resected Tissue

AbstractIn humans, brain oscillations are thought to support critical features of memory formation such as coordination of activity across regions, consolidation, and temporal ordering of events. However, understanding the molecular mechanisms underlining this activity in humans remains a major challenge. Here, we measured memory-sensitive oscillations using direct intracranial electroencephalography recordings from the temporal cortex of patients performing an episodic memory task. By then employing transcriptomics on the resected tissue from the same patients, we linked gene expression with brain oscillations, identifying genes correlated with oscillatory signatures of memory formation across six frequency bands. A co-expression analysis isolated biomarker-specific modules associated with neuropsychiatric disorders as well as ion channel activity. Using single-nuclei transcriptomic data from this resected tissue, we further revealed that biomarker-specific modules are enriched for both excitatory and inhibitory neurons. This unprecedented dataset of patient-specific brain oscillations coupled to genomics unlocks new insights into the genetic mechanisms that support memory encoding. By linking brain expression of these genes to oscillatory patterns, our data help overcome limitations of phenotypic methods to uncover genetic links to memory performance.

scholarly journals Sensory suppression and increased neuromodulation during actions disrupt memory encoding of unpredictable self-initiated stimuli

2021 ◽  
Author(s):  
Nadia Paraskevoudi ◽  
Iria SanMiguel
Keyword(s):  
Sensory Processing ◽  
Pupil Diameter ◽  
Memory Performance ◽  
Recognition Task ◽  
Pupil Dilation ◽  
Memory Bias ◽  
Memory Encoding ◽  
Differential Processing ◽  
Sensory Suppression ◽  
Sensory Attenuation

Actions modulate sensory processing by attenuating responses to self- compared to externally-generated inputs, which is traditionally attributed to stimulus-specific motor predictions. Yet, suppression has been also found for stimuli merely coinciding with actions, pointing to unspecific processes that may be driven by neuromodulatory systems. Meanwhile, the differential processing for self-generated stimuli raises the possibility of producing effects also on memory for these stimuli, however, evidence remains mixed as to the direction of the effects. Here, we assessed the effects of actions on sensory processing and memory encoding of concomitant, but unpredictable sounds, using a combination of self-generation and memory recognition task concurrently with EEG and pupil recordings. At encoding, subjects performed button presses that half of the time generated a sound (motor-auditory; MA) and listened to passively presented sounds (auditory-only; A). At retrieval, two sounds were presented and participants had to respond which one was present before. We measured memory bias and memory performance by having sequences where either both or only one of the test sounds were presented at encoding, respectively. Results showed worse memory performance — but no differences in memory bias — and attenuated responses and larger pupil diameter for MA compared to A sounds. Critically, the larger the sensory attenuation and pupil diameter, the worse the memory performance for MA sounds. Nevertheless, sensory attenuation did not correlate with pupil dilation. Collectively, our findings suggest that sensory attenuation and neuromodulatory processes coexist during actions, and both relate to disrupted memory for concurrent, albeit unpredictable sounds.

scholarly journals Aberrant prefrontal beta oscillations predict episodic memory encoding deficits in schizophrenia

2016 ◽  
Author(s):  
Federica Meconi ◽  
Sarah Anderl-Straub ◽  
Heidelore Raum ◽  
Michael Landgrebe ◽  
Berthold Langguth ◽  
...  
Keyword(s):  
Episodic Memory ◽  
Verbal Memory ◽  
Semantic Processing ◽  
Memory Performance ◽  
Oscillatory Activity ◽  
Healthy Controls ◽  
Memory Encoding ◽  
Brain Oscillations ◽  
Beta Power ◽  
Pattern Similarity

AbstractVerbal episodic memory is one of the core cognitive functions affected in patients suffering from schizophrenia (SZ). Although this verbal memory impairment in SZ is a well-known finding, our understanding about its underlying neurophysiological mechanisms is rather scarce. Here we address this issue by recording brain oscillations during a memory task in a sample of healthy controls and patients suffering from SZ. Brain oscillations represent spectral fingerprints of specific neurocognitive operations and are therefore a promising tool to identify neurocognitive mechanisms that are affected by SZ. Healthy controls showed a prominent suppression of left prefrontal beta oscillatory activity during successful memory formation, which replicates several previous oscillatory memory studies. In contrast, patients failed to exhibit such left prefrontal beta power suppression. Utilizing a new topographical pattern similarity approach, we further demonstrate that the degree of similarity between a patient's beta power decrease to that of the controls reliably predicted memory performance. This relationship between beta power decreases and memory was such that the patients' memory performance improved as they showed a more similar topographical beta desynchronization pattern compared to that of healthy controls. These findings suggest that left prefrontal beta power suppression (or lack thereof) during memory encoding is a possible biomarker for the observed encoding impairments in SZ in verbal memory. This lack of left prefrontal beta power decreases might indicate a specific semantic processing deficit of verbal material in patients with schizophrenia.

scholarly journals Gamma Oscillatory Activity Related to Language Prediction

2018 ◽  
Vol 30 (8) ◽  
pp. 1075-1085 ◽  
Author(s):  
Lin Wang ◽  
Peter Hagoort ◽  
Ole Jensen
Keyword(s):  
Gamma Activity ◽  
Oscillatory Activity ◽  
Final Word ◽  
Gamma Frequency ◽  
Power Difference ◽  
Gamma Power ◽  
Activation Intervals

Using magnetoencephalography, the current study examined gamma activity associated with language prediction. Participants read high- and low-constraining sentences in which the final word of the sentence was either expected or unexpected. Although no consistent gamma power difference induced by the sentence-final words was found between the expected and unexpected conditions, the correlation of gamma power during the prediction and activation intervals of the sentence-final words was larger when the presented words matched with the prediction compared with when the prediction was violated or when no prediction was available. This suggests that gamma magnitude relates to the match between predicted and perceived words. Moreover, the expected words induced activity with a slower gamma frequency compared with that induced by unexpected words. Overall, the current study establishes that prediction is related to gamma power correlations and a slowing of the gamma frequency.

A Preliminary Study of the Association Among Metacognition and Resting State EEG in Schizophrenia

2016 ◽  
Vol 30 (2) ◽  
pp. 47-54 ◽  
Author(s):  
Jenifer L. Vohs ◽  
Bethany L. Leonhardt ◽  
Michael M. Francis ◽  
Daniel Westfall ◽  
Josselyn Howell ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Gamma Activity ◽  
Multiple Perspectives ◽  
Behavioral Correlates ◽  
Form Complex ◽  
Gamma Frequency ◽  
Gamma Range ◽  
The World ◽  
Gamma Power

Abstract. Metacognition refers to a spectrum of activities that range from the consideration of discrete mental experiences, such as a specific thought or emotion, to the synthesis of discrete perceptions into integrated representations of the self and others as unique agents in the world. Metacognitive deficits have been observed in schizophrenia and linked with a number of behavioral correlates and outcomes. Less is known however about the neural systems associated with such processes. Establishing the link between brain activity and metacognition therefore is an essential next step. Resting state electroencephalography (EEG) provides one possible avenue for investigating this link. EEG studies in schizophrenia suggest that the gamma frequency range may have functional significance and be related to the disturbed information processing often observed in the disorder. In the present investigation, we assessed metacognition among 20 individuals with prolonged schizophrenia using the Metacognition Assessment Scale Abbreviated, who also participated in resting state EEG recording. We hypothesized that gamma activity would be associated with those domains of metacognition that require the most integration to perform, Decentration and Mastery. We then examined the association among gamma power and each metacognitive domain. Additional exploratory analyses were conducted across a spectrum of EEG activity. We found that increased gamma activity at rest was linked with decreased decentration. This suggests that hyperactivity in the gamma range may index disrupted processing and integration, and ultimately the metacognitive processes needed to form complex ideas about oneself and others and to see the world from multiple perspectives. This link provides additional evidence of how the biological roots of schizophrenia may culminate in a disrupted life.

scholarly journals Slow rTMS to the left DLPFC enhances verbal memory formation

2021 ◽  
Author(s):  
Mircea van der Plas ◽  
Verena Braun ◽  
Benjamin Johannes Stauch ◽  
Simon Hanslmayr
Keyword(s):  
Prefrontal Cortex ◽  
Verbal Memory ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Incidental Finding ◽  
Memory Performance ◽  
Memory Formation ◽  
Control Group ◽  
Specific Information ◽  
Left Dlpfc ◽  
Beta Power

AbstractEncoding of episodic memories relies on stimulus-specific information processing and involves the left prefrontal cortex. We here present an incidental finding from a simultaneous EEG-TMS experiment as well as a replication of this unexpected effect. Our results reveal that stimulating the left dorsolateral prefrontal cortex (DLPFC) with slow repetitive transcranial magnetic stimulation (rTMS) leads to enhanced word memory performance. 40 healthy human participants engaged in a list learning paradigm. Half of the subjects (N=20) received 1 Hz rTMS to the left DLPFC while the other half (N=20) received 1 Hz rTMS to the vertex and served as a control group. Subjects receiving left DLPFC stimulation demonstrated enhanced memory performance compared to the control group. This effect was replicated in a double-blind within-subjects experiment where 24 participants received 1 Hz rTMS to the left DLPFC and vertex. In this second experiment, DLPFC stimulation also induced better memory performance compared to vertex stimulation. In addition to these behavioural effects, we found that 1 Hz rTMS to DLPFC induced stronger beta power modulation in posterior areas, a state which is known to be beneficial for memory encoding. Further analysis indicated, that beta modulations did not have an oscillatory origin. Instead, the observed beta modulations were a result of a spectral tilt, suggesting inhibition of these parietal regions. These results show that applying 1 Hz rTMS to DLPFC, an area involved in episodic memory formation, improves memory performance via modulating neural activity in parietal regions.

scholarly journals Impaired Desynchronization of Beta Activity Underlies Memory Deficits in People with Parkinson’s Disease

2019 ◽  
Author(s):  
Hayley J. MacDonald ◽  
John-Stuart Brittain ◽  
Bernhard Spitzer ◽  
Simon Hanslmayr ◽  
Ned Jenkinson
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Brain Activity ◽  
Memory Performance ◽  
Memory Formation ◽  
Motor Deficits ◽  
Beta Activity ◽  
Memory Encoding ◽  
Concomitant Reduction ◽  
Non Motor Symptoms

AbstractThere is a pressing need to better understand the mechanisms underpinning the increasingly recognised non-motor deficits in Parkinson’s disease. Brain activity during Parkinson’s disease is excessively synchronized within the beta range (12–30Hz). However, relatively little is known about how the abnormal beta rhythms impact on non-motor symptoms. In healthy adults, beta desynchronization is necessary for successful episodic memory formation. We investigated whether there was a direct relationship between decreased beta modulation and memory formation in Parkinson’s disease. Electroencephalography recordings were made during an established memory-encoding paradigm. Parkinson’s participants showed impaired memory strength (P = 0.023) and reduced beta desynchronization (P = 0.014) relative to controls. Longer disease duration was correlated with a larger reduction in beta desynchronization, and a concomitant reduction in memory performance. These novel results extend the notion that pathological beta activity is causally implicated in the motor and (lesser appreciated) non-motor deficits inherent to Parkinson’s disease.

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