Neural Mechanisms of Memory Enhancement and Impairment Induced by Visual Statistical Learning

2020 ◽  
Vol 32 (9) ◽  
pp. 1749-1763
Author(s):  
Sachio Otsuka ◽  
Jun Saiki
Keyword(s):  
Statistical Learning ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
Neural Mechanisms ◽  
Fmri Data ◽  
Precentral Gyrus ◽  
Memory Enhancement ◽  
Visual Statistical Learning ◽  
Mechanisms Of Memory ◽  
The Brain

Prior research has reported that the medial temporal, parietal, and frontal brain regions are associated with visual statistical learning (VSL). However, the neural mechanisms involved in both memory enhancement and impairment induced by VSL remain unknown. In this study, we examined this issue using event-related fMRI. fMRI data from the familiarization scan showed a difference in the activation level of the superior frontal gyrus (SFG) between structured triplets, where three objects appeared in the same order, and pseudorandom triplets. More importantly, the precentral gyrus and paracentral lobule responded more strongly to Old Turkic letters inserted into the structured triplets than to those inserted into the random triplets, at the end of the familiarization scan. Furthermore, fMRI data from the recognition memory test scan, where participants were asked to decide whether the objects or letters shown were old (presented during familiarization scan) or new, indicated that the middle frontal gyrus and SFG responded more strongly to objects from the structured triplets than to those from the random triplets, which overlapped with the brain regions associated with VSL. In contrast, the response of the lingual gyrus, superior temporal gyrus, and cuneus was weaker to letters inserted into the structured triplets than to those inserted into the random triplets, which did not overlap with the brain regions associated with observing the letters during the familiarization scan. These findings suggest that different brain regions are involved in memory enhancement and impairment induced by VSL.

scholarly journals Mean deviation based identification of activated voxels from time-series fMRI data of schizophrenia patients

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1615 ◽  
Author(s):  
Indranath Chatterjee
Keyword(s):  
Time Series ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
Medical Intervention ◽  
Fmri Data ◽  
Mean Deviation ◽  
Functional Changes ◽  
Statistical Measures ◽  
The Brain ◽  
Over Time

Background: Schizophrenia is a serious mental illness affecting different regions of the brain, which causes symptoms such as hallucinations and delusions. Functional magnetic resonance imaging (fMRI) is the most popular technique to study the functional activation patterns of the brain. The fMRI data is four-dimensional, composed of 3D brain images over time. Each voxel of the 3D brain volume is associated with a time series of signal intensity values. This study aimed to identify the distinct voxels from time-series fMRI data that show high functional activation during a task. Methods: In this study, a novel mean-deviation based approach was applied to time-series fMRI data of 34 schizophrenia patients and 34 healthy subjects. The statistical measures such as mean and median were used to find the functional changes in each voxel over time. The voxels that show significant changes for each subject were selected and thus used as the feature set during the classification of schizophrenia patients and healthy controls. Results: The proposed approach identifies a set of relevant voxels that are used to distinguish between healthy and schizophrenia subjects with high classification accuracy. The study shows functional changes in brain regions such as superior frontal gyrus, cuneus, medial frontal gyrus, middle occipital gyrus, and superior temporal gyrus. Conclusions: This work describes a simple yet novel feature selection algorithm for time-series fMRI data to identify the activated brain voxels that are generally affected in schizophrenia. The brain regions identified in this study may further help clinicians to understand the illness for better medical intervention. It may be possible to explore the approach to fMRI data of other psychological disorders.

scholarly journals Mean deviation based identification of activated voxels from time-series fMRI data of schizophrenia patients

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1615 ◽  
Author(s):  
Indranath Chatterjee
Keyword(s):  
Time Series ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
Medical Intervention ◽  
Fmri Data ◽  
Mean Deviation ◽  
Functional Changes ◽  
Statistical Measures ◽  
The Brain ◽  
Over Time

Background: Schizophrenia is a serious mental illness affecting different regions of the brain, which causes symptoms such as hallucinations and delusions. Functional magnetic resonance imaging (fMRI) is the most popular technique to study the functional activation patterns of the brain. The fMRI data is four-dimensional, composed of 3D brain images over time. Each voxel of the 3D brain volume is associated with a time series of signal intensity values. This study aimed to identify the distinct voxels from time-series fMRI data that show high functional activation during a task. Methods: In this study, a novel mean-deviation based approach was applied to time-series fMRI data of 34 schizophrenia patients and 34 healthy subjects. The statistical measures such as mean and median were used to find the functional changes in each voxel over time. The voxels that show significant changes for each subject were selected and thus used as the feature set during the classification of schizophrenia patients and healthy controls. Results: The proposed approach identifies a set of relevant voxels that are used to distinguish between healthy and schizophrenia subjects with high classification accuracy. The study shows functional changes in brain regions such as superior frontal gyrus, cuneus, medial frontal gyrus, middle occipital gyrus, and superior temporal gyrus. Conclusions: This work describes a simple yet novel feature selection algorithm for time-series fMRI data to identify the activated brain voxels that are generally affected in schizophrenia. The brain regions identified in this study may further help clinicians to understand the illness for better medical intervention. It may be possible to explore the approach to fMRI data of other psychological disorders.

Use of 64-Channel Electroencephalography to Study Neural Otolith-Evoked Responses

2011 ◽  
Vol 22 (03) ◽  
pp. 143-155 ◽  
Author(s):  
Kathleen M. McNerney ◽  
Alan H. Lockwood ◽  
Mary Lou Coad ◽  
David S. Wack ◽  
Robert F. Burkard
Keyword(s):  
Source Localization ◽  
Statistical Parametric Mapping ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
Precentral Gyrus ◽  
Evoked Responses ◽  
Vestibular Evoked Myogenic Potential ◽  
Eeg Recordings ◽  
Otolith Stimulation ◽  
The Brain

Background: The vestibular evoked myogenic potential (VEMP) is a myogenic response that can be used clinically to evaluate the function of the saccule. However, to date, little is known about the thalamo-cortical representation of saccular activation. It is important to understand all aspects of the VEMP, as this test is currently used clinically in the evaluation of saccular function. Purpose: To identify the areas of the brain that are activated in response to stimuli used clinically to evoke the VEMP. Research Design: Electroencephalography (EEG) recordings combined with current density analyses were used to identify the areas of the brain that are activated in response to stimuli presented above VEMP threshold (500 Hz, 120 dB peak SPL [pSPL] tone bursts), as compared to stimuli presented below VEMP threshold (90 dB pSPL, 500 Hz tone bursts). Ten subjects without any history of balance or hearing impairment participated in the study. Results: The neural otolith-evoked responses (NOERs) recorded in response to stimuli presented below VEMP threshold were absent or smaller than NOERs that were recorded in response to stimuli presented above VEMP threshold. Subsequent analyses with source localization techniques, followed by statistical analysis with SPM5 (Statistical Parametric Mapping), revealed several areas that were activated in response to the 120 dB pSPL tone bursts. These areas included the primary visual cortex, the precuneus, the precentral gyrus, the medial temporal gyrus, and the superior temporal gyrus. Conclusions: The present study found a number of specific brain areas that may be activated by otolith stimulation. Given the findings and source localization techniques (which required limited input from the investigator as to where the sources are believed to be located in the brain) used in the present study as well as the similarity in findings between studies employing galvanic stimuli, fMRI (functional magnetic resonance imaging), and scalp-recorded potentials in response to VEMP-eliciting stimuli, our study provides additional evidence that these brain regions are activated in response to stimuli that can be used clinically to evoke the VEMP.

scholarly journals Antagonism between brain regions relevant for cognitive control and emotional memory facilitates the generation of humorous ideas

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Florian Bitsch ◽  
Philipp Berger ◽  
Andreas Fink ◽  
Arne Nagels ◽  
Benjamin Straube ◽  
...  
Keyword(s):  
Cognitive Control ◽  
Positive Emotions ◽  
Emotional Memory ◽  
Brain Regions ◽  
Neural Mechanisms ◽  
Functional Magnetic Resonance ◽  
Frontal Brain ◽  
Successful Resolution ◽  
Neural Underpinnings ◽  
The Brain

AbstractThe ability to generate humor gives rise to positive emotions and thus facilitate the successful resolution of adversity. Although there is consensus that inhibitory processes might be related to broaden the way of thinking, the neural underpinnings of these mechanisms are largely unknown. Here, we use functional Magnetic Resonance Imaging, a humorous alternative uses task and a stroop task, to investigate the brain mechanisms underlying the emergence of humorous ideas in 24 subjects. Neuroimaging results indicate that greater cognitive control abilities are associated with increased activation in the amygdala, the hippocampus and the superior and medial frontal gyrus during the generation of humorous ideas. Examining the neural mechanisms more closely shows that the hypoactivation of frontal brain regions is associated with an hyperactivation in the amygdala and vice versa. This antagonistic connectivity is concurrently linked with an increased number of humorous ideas and enhanced amygdala responses during the task. Our data therefore suggests that a neural antagonism previously related to the emergence and regulation of negative affective responses, is linked with the generation of emotionally positive ideas and may represent an important neural pathway supporting mental health.

Neural Mechanisms of Negative Symptoms

1989 ◽  
Vol 155 (S7) ◽  
pp. 93-98 ◽  
Author(s):  
Nancy C. Andreasen
Keyword(s):  
Frontal Cortex ◽  
Negative Symptoms ◽  
Neural Mechanism ◽  
Brain Regions ◽  
Brain Dysfunction ◽  
Neural Mechanisms ◽  
Dementia Praecox ◽  
Intellectual Abilities ◽  
The Brain ◽  
Psychic Mechanisms

When Kraepelin originally defined and described dementia praecox, he assumed that it was due to some type of neural mechanism. He hypothesised that abnormalities could occur in a variety of brain regions, including the prefrontal, auditory, and language regions of the cortex. Many members of his department, including Alzheimer and Nissl, were actively involved in the search for the neuropathological lesions that would characterise schizophrenia. Although Kraepelin did not use the term ‘negative symptoms', he describes them comprehensively and states explicitly that he believes the symptoms of schizophrenia can be explained in terms of brain dysfunction:“If it should be confirmed that the disease attacks by preference the frontal areas of the brain, the central convolutions and central lobes, this distribution would in a certain measure agree with our present views about the site of the psychic mechanisms which are principally injured by the disease. On various grounds, it is easy to believe that the frontal cortex, which is specially well developed in man, stands in closer relation to his higher intellectual abilities, and these are the faculties which in our patients invariably suffer profound loss in contrast to memory and acquired ability.” Kraepelin (1919, p. 219)

scholarly journals Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training

2021 ◽  
Author(s):  
Takashi Nakano ◽  
Masahiro Takamura ◽  
Haruki Nishimura ◽  
Maro Machizawa ◽  
Naho Ichikawa ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Fmri Data ◽  
Independent Test ◽  
The Individual ◽  
The Brain

AbstractNeurofeedback (NF) aptitude, which refers to an individual’s ability to change its brain activity through NF training, has been reported to vary significantly from person to person. The prediction of individual NF aptitudes is critical in clinical NF applications. In the present study, we extracted the resting-state functional brain connectivity (FC) markers of NF aptitude independent of NF-targeting brain regions. We combined the data in fMRI-NF studies targeting four different brain regions at two independent sites (obtained from 59 healthy adults and six patients with major depressive disorder) to collect the resting-state fMRI data associated with aptitude scores in subsequent fMRI-NF training. We then trained the regression models to predict the individual NF aptitude scores from the resting-state fMRI data using a discovery dataset from one site and identified six resting-state FCs that predicted NF aptitude. Next we validated the prediction model using independent test data from another site. The result showed that the posterior cingulate cortex was the functional hub among the brain regions and formed predictive resting-state FCs, suggesting NF aptitude may be involved in the attentional mode-orientation modulation system’s characteristics in task-free resting-state brain activity.

scholarly journals Neuronal Graphs: A Graph Theory Primer for Microscopic, Functional Networks of Neurons Recorded by Calcium Imaging

2021 ◽  
Vol 15 ◽  
Author(s):  
Carl J. Nelson ◽  
Stephen Bonner
Keyword(s):  
Graph Theory ◽  
Fluorescence Microscopy ◽  
Calcium Imaging ◽  
Neural Mechanisms ◽  
Fmri Data ◽  
Functional Networks ◽  
Large Bank ◽  
Fundamental Structure ◽  
Formal Study ◽  
The Brain

Connected networks are a fundamental structure of neurobiology. Understanding these networks will help us elucidate the neural mechanisms of computation. Mathematically speaking these networks are “graphs”—structures containing objects that are connected. In neuroscience, the objects could be regions of the brain, e.g., fMRI data, or be individual neurons, e.g., calcium imaging with fluorescence microscopy. The formal study of graphs, graph theory, can provide neuroscientists with a large bank of algorithms for exploring networks. Graph theory has already been applied in a variety of ways to fMRI data but, more recently, has begun to be applied at the scales of neurons, e.g., from functional calcium imaging. In this primer we explain the basics of graph theory and relate them to features of microscopic functional networks of neurons from calcium imaging—neuronal graphs. We explore recent examples of graph theory applied to calcium imaging and we highlight some areas where researchers new to the field could go awry.

scholarly journals Algebra dissociates from arithmetic in the brain semantic network

2021 ◽  
Author(s):  
Dazhi Cheng ◽  
Mengyi Li ◽  
Naiyi Wang ◽  
Liangyuan Ouyang ◽  
Xinlin Zhou
Keyword(s):  
Supplementary Motor Area ◽  
Semantic Network ◽  
Brain Activation ◽  
Brain Regions ◽  
Motor Area ◽  
Angular Gyrus ◽  
Precentral Gyrus ◽  
Single Trial ◽  
Brain Behavior ◽  
The Brain

Abstract Background Mathematical expressions mainly include arithmetic (such as 8 − (1 + 3)) and algebraic expressions (such as a − (b + c)). Previous studies shown that both algebraic processing and arithmetic involved the bilateral parietal brain regions. Although behavioral and neuropsychological studies have revealed the dissociation between algebra and arithmetic, how algebraic processing is dissociated from arithmetic in brain networks is still unclear. Methods Using functional magnetic resonance imaging (fMRI), this study scanned 30 undergraduates and directly compared the brain activation during algebra and arithmetic. Brain activations, single-trial (item-wise) interindividual correlation and mean-trial interindividual correlation related to algebra processing were compared with those related to arithmetic. Results Brain activation analyses showed that algebra elicited greater activation in the angular gyrus and arithmetic elicited greater activation in the bilateral supplementary motor area, left insula, and left inferior parietal lobule. Interindividual single-trial brain-behavior correlation revealed significant brain-behavior correlations in the semantic network, including the middle temporal gyri, inferior frontal gyri, dorsomedial prefrontal cortices, and left angular gyrus, for algebra. For arithmetic, the significant brain-behavior correlations were located in the phonological network, including the precentral gyrus and supplementary motor area, and in the visuospatial network, including the bilateral superior parietal lobules. Conclusion These findings suggest that algebra relies on the semantic network and arithmetic relies on the phonological and visuospatial networks.

scholarly journals Region-specific complexity of the intracranial EEG in the sleeping human brain

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Elzbieta Olejarczyk ◽  
Jean Gotman ◽  
Birgit Frauscher
Keyword(s):  
Sleep Stage ◽  
Brain Regions ◽  
Sleep Stages ◽  
Precentral Gyrus ◽  
Self Similarity ◽  
Intracranial Eeg ◽  
Brain Signals ◽  
Cortical Regions ◽  
The Brain

AbstractAs the brain is a complex system with occurrence of self-similarity at different levels, a dedicated analysis of the complexity of brain signals is of interest to elucidate the functional role of various brain regions across the various stages of vigilance. We exploited intracranial electroencephalogram data from 38 cortical regions using the Higuchi fractal dimension (HFD) as measure to assess brain complexity, on a dataset of 1772 electrode locations. HFD values depended on sleep stage and topography. HFD increased with higher levels of vigilance, being highest during wakefulness in the frontal lobe. HFD did not change from wake to stage N2 in temporo-occipital regions. The transverse temporal gyrus was the only area in which the HFD did not differ between any two vigilance stages. Interestingly, HFD of wakefulness and stage R were different mainly in the precentral gyrus, possibly reflecting motor inhibition in stage R. The fusiform and parahippocampal gyri were the only areas showing no difference between wakefulness and N2. Stages R and N2 were similar only for the postcentral gyrus. Topographical analysis of brain complexity revealed that sleep stages are clearly differentiated in fronto-central brain regions, but that temporo-occipital regions sleep differently.

Common and distinct neural mechanisms of visual and tactile extinction: A large scale VBM study in sub-acute stroke

2012 ◽  
Vol 25 (0) ◽  
pp. 17
Author(s):  
Magdalena Chechlacz ◽  
Anna Terry ◽  
Pia Rotshtein ◽  
Wai-Ling Bickerton ◽  
Glyn Humphreys
Keyword(s):  
Large Scale ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
Neural Mechanisms ◽  
Middle Temporal Gyrus ◽  
Visual Modality ◽  
Voxel Based Morphometry ◽  
White Matter Damage ◽  
Sensory Modalities ◽  
Middle Occipital Gyrus

Extinction is diagnosed when patients respond to a single contralesional item but fail to detect this item when an ipsilesional item is present concurrently. It is considered to be a disorder of attention characterized by a striking bias for the ipsilesional stimulus at the expense of the contralesional stimulus. Extinction has been studied mainly in the visual modality but it occurs also in other sensory modalities (touch, audition) and hence can be considered a multisensory phenomenon. The functional and neuroanatomical relations between extinction in different modalities are poorly understood. It could be hypothesised that extinction deficits in different modalities emerge after damage to both common (attention specific) and distinct (modality specific) brain regions. Here, we used voxel-based morphometry to examine the neuronal substrates of visual versus tactile extinction in a large group of stroke patients (). We found that extinction deficits in the two modalities were significantly correlated (; ). Lesions to inferior parietal lobule and middle frontal gyrus were linked to visual extinction, while lesions involving the superior temporal gyrus were associated with tactile extinction. Damage within the middle temporal gyrus was linked to both types of deficits but interestingly these lesions extended into the middle occipital gyrus in patients with visual but not tactile extinction. White matter damage within the temporal lobe was associated with both types of deficits, including lesions within long association pathways involved in spatial attention. Our findings indicate both common and distinct neural mechanisms of visual and tactile extinction.

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