scholarly journals Amygdala to hippocampal volume ratio is associated with negative memory bias in healthy subjects

2011 ◽  
Vol 42 (2) ◽  
pp. 335-343 ◽  
Author(s):  
L. Gerritsen ◽  
M. Rijpkema ◽  
I. van Oostrom ◽  
J. Buitelaar ◽  
B. Franke ◽  
...  
Keyword(s):  
Cognitive Vulnerability ◽  
Automatic Segmentation ◽  
Volume Ratio ◽  
Neural Substrates ◽  
Emotional Memory ◽  
Hippocampal Volume ◽  
Memory Bias ◽  
Cognitive Risk ◽  
Negative Memory ◽  
Magnetic Resonance Imaging Mri

BackgroundNegative memory bias is thought to be one of the main cognitive risk and maintenance factors for depression, but its neural substrates are largely unknown. Here, we studied whether memory bias is related to amygdala and hippocampal volume, two structures that are critical for emotional memory processes and that show consistent volume alterations in depression.MethodStructural magnetic resonance imaging (MRI) was carried out in 272 healthy participants (62% female, 18–50 years old). All images were acquired on 1.5 T Siemens MRI scanners. Automatic segmentation of amygdala and hippocampus was performed using the FIRST module of FSL. Negative memory bias was assessed by the self-referent encoding/evaluation test.ResultsNegative memory bias was associated with larger amygdala (p=0.042) and smaller hippocampal (p=0.029) volumes. In additional analyses, we found that, compared with the associations found with hippocampus and amygdala volume separately, a stronger association was found between negative memory bias and the ratio of amygdala:hippocampus volume (p=0.021).ConclusionsIn non-depressed subjects we found that larger amygdala and smaller hippocampal volumes are associated with negative memory bias. This suggests that an increased amygdala:hippocampus volume ratio plays a role in cognitive vulnerability often seen in individuals with high risk for depression and that these structural brain differences may pre-date the onset of depression.

Neuroimaging and the Neuroanatomy of Posttraumatic Stress Disorder

CNS Spectrums ◽  
1998 ◽  
Vol 3 (S2) ◽  
pp. 30-41 ◽  
Author(s):  
Scott L. Rauch ◽  
Lisa M. Shin ◽  
Paul J. Whalen ◽  
Roger K. Pitman
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Stress Disorder ◽  
Neural Substrates ◽  
Hippocampal Volume ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Imaging Studies ◽  
Neuroimaging Data ◽  
Magnetic Resonance Imaging Mri

AbstractContemporary neuroimaging methods have been used to gather initial data regarding the neural substrates of posttraumatic stress disorder (PTSD). Morphometric magnetic resonance imaging (MRI) studies have reliably shown reduced hippocampal volume in subjects with PTSD vs control cohorts. Functional imaging studies have implicated a network of brain regions in PTSD, comprising the amygdala, hippocampus, and anterior paralimbic territories (including anterior cingulate cortex), as well as Broca's area and visual cortex. Extant relevant neuroimaging data are reviewed, and a tentative heuristic neuroanatomical model of PTSD is provided. In conclusion, emerging strategies for advancement in this field are outlined.

Depression, self-focused attention, and the negative memory bias.

1989 ◽  
Vol 57 (2) ◽  
pp. 351-357 ◽  
Author(s):  
Tom Pyszczynski ◽  
James C. Hamilton ◽  
Fred H. Herring ◽  
Jeff Greenberg
Keyword(s):  
Memory Bias ◽  
Focused Attention ◽  
Negative Memory

scholarly journals A deep learning method for automatic segmentation of the bony orbit in MRI and CT images

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jared Hamwood ◽  
Beat Schmutz ◽  
Michael J. Collins ◽  
Mark C. Allenby ◽  
David Alonso-Caneiro
Keyword(s):  
Deep Learning ◽  
Human Performance ◽  
Automatic Segmentation ◽  
Ct Images ◽  
Human Observer ◽  
In Series ◽  
Magnetic Resonance Imaging Mri ◽  
High Degree ◽  
Orbital Region ◽  
Ct And Mri

AbstractThis paper proposes a fully automatic method to segment the inner boundary of the bony orbit in two different image modalities: magnetic resonance imaging (MRI) and computed tomography (CT). The method, based on a deep learning architecture, uses two fully convolutional neural networks in series followed by a graph-search method to generate a boundary for the orbit. When compared to human performance for segmentation of both CT and MRI data, the proposed method achieves high Dice coefficients on both orbit and background, with scores of 0.813 and 0.975 in CT images and 0.930 and 0.995 in MRI images, showing a high degree of agreement with a manual segmentation by a human expert. Given the volumetric characteristics of these imaging modalities and the complexity and time-consuming nature of the segmentation of the orbital region in the human skull, it is often impractical to manually segment these images. Thus, the proposed method provides a valid clinical and research tool that performs similarly to the human observer.

Childhood Emotional Maltreatment, Cognitive Vulnerability to Depression, and Self-Referent Information Processing in Adulthood: Reciprocal Relations

2003 ◽  
Vol 17 (4) ◽  
pp. 347-358 ◽  
Author(s):  
Jennifer A. Steinberg ◽  
Brandon E. Gibb ◽  
Lauren B. Alloy ◽  
Lyn Y. Abramson
Keyword(s):  
Information Processing ◽  
Cognitive Vulnerability ◽  
Reciprocal Relations ◽  
Emotional Maltreatment ◽  
Current Information ◽  
Information Processing Biases ◽  
Cognitive Risk ◽  
Alternate Model ◽  
The Relationship ◽  
Risk For Depression

Previous work has established a relationship between reports of childhood emotional maltreatment and cognitive vulnerability to depression, as well as an association between cognitive vulnerability and self-referent information-processing biases. Findings from this study of individuals at low (LR) and high (HR) cognitive risk for depression revealed a relationship between reports of childhood emotional maltreatment and current information processing biases. Specifically, individuals with greater childhood emotional maltreatment exhibited more negative self-referent information processing. Moreover, cognitive risk mediated the relationship between childhood emotional maltreatment and these information-processing biases. Testing an alternate model, information-processing biases also mediated the relationship between childhood emotional maltreatment and cognitive risk.

051 Is Working Memory Associated with Ag- related Emotional Memory Bias?

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A21-A22
Author(s):  
Negin Sattari ◽  
Lauren Whitehurst ◽  
Sara Mednick
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Emotional Reactivity ◽  
Emotional Memory ◽  
Negative Word ◽  
Memory Bias ◽  
Long Term Memory ◽  
Sleep Condition ◽  
Valence And Arousal ◽  
Positive Memories

Abstract Introduction Aging is accompanied by deterioration in both working memory (WM) and long-term memory (LTM), though the reason is not well understood. Sleep may play a role in young adults, but the findings in older adults are not as clear. In addition, older adults show better memory for positive memories, whereas youngers tend to hold on to negative memories. The prefrontal cortex has been implicated in this emotional memory bias. The current study investigated the role of working memory (a prefrontal task) on emotional memory consolidation across sleep and wake in young and older adults. Methods In the morning, 93 younger (18–39) and 121 older (60–85) adults took a WM task and encoded neutral or negative word pairs, and gave valence and arousal ratings for each pair. After a wake or polysomnography-recorded sleep condition, memory for the word pairs was tested plus valence and arousal ratings. Results Youngers had better overall memory (p<.001), with older adults showing better memory for neutral compared to negative word pairs (p=.04), as well as increased positivity (p=.02), which was correlated with LTM performance (p=.009). In contrast, youngers performed better on the negative word pairs (p=.01), but no change in ratings and no association between emotional reactivity and LTM. Further, WM was positively related to memory in youngers (r=.38, p=.02), but not in older adults. Lastly, no role for sleep likely due to the lack of an immediate test. Conclusion we found that the positivity bias in aging in both memory and valence, with increasing positivity associated with better memory. We found a robust relation between WM and LTM in youngers but not older adults. Our findings are consistent with the socioemotional-selectivity theory that posits that aging is associated with a relative suppression of negative information while WM may play a role. Support (if any):

scholarly journals Evaluation of secondary dentin formation for forensic age assessment by means of semi-automatic segmented ultrahigh field 9.4 T UTE MRI datasets

2020 ◽  
Vol 134 (6) ◽  
pp. 2283-2288
Author(s):  
Maximilian Timme ◽  
Jens Borkert ◽  
Nina Nagelmann ◽  
Andreas Schmeling
Keyword(s):  
Dental Pulp ◽  
Automatic Segmentation ◽  
Tooth Pulp ◽  
Human Teeth ◽  
Age Assessment ◽  
Ultrahigh Field ◽  
Tooth Structure ◽  
Pulp Cavity ◽  
Magnetic Resonance Imaging Mri ◽  
Dentin Formation

Abstract Dental methods are an important element of forensic age assessment of living persons. After the development of all the teeth, including third molars, is completed, degenerative characteristics can be used to assess age. The radiologically detectable reduction of the dental pulp cavity has been described as such a feature. We investigated the suitability of ultrahigh field 9.4 T ultrashort time echo (UTE) magnetic resonance imaging (MRI) for the evaluation of pulp cavity volume in relation to the total tooth volume in 4 extracted human teeth. The volume calculations were performed after semi-automatic segmentation by software AMIRA using the different intensities of the structures in the MRI dataset. The automatically selected intensity range was adjusted manually to the structures. The visual distinction of pulp and tooth structure was possible in all cases with in-plane resolution < 70 μm. Ratios of tooth/pulp volume were calculated, which could be suitable for age estimation procedures. Intensity shifts within the pulp were not always correctly assigned by the software in the course of segmentation. 9.4 T UTE-MRI technology is a forward-looking, radiation-free procedure that allows the volume of the dental pulp to be determined at high spatial resolution and is thus potentially a valuable instrument for the age assessment of living persons.

scholarly journals The BDNF Val66Met polymorphism affects negative memory bias in civilian women with PTSD

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hiroaki Hori ◽  
Mariko Itoh ◽  
Fuyuko Yoshida ◽  
Mingming Lin ◽  
Madoka Niwa ◽  
...  
Keyword(s):  
Memory Bias ◽  
Val66met Polymorphism ◽  
Negative Memory ◽  
Bdnf Val66met Polymorphism ◽  
Civilian Women

scholarly journals Examining Sex Differences in Markers of Cognition and Neurodegeneration in Autosomal Dominant Alzheimer’s Disease: Preliminary Findings from the Colombian Alzheimer’s Prevention Initiative Biomarker Study

2020 ◽  
Vol 77 (4) ◽  
pp. 1743-1753
Author(s):  
Clara Vila-Castelar ◽  
Edmarie Guzmán-Vélez ◽  
Enmanuelle Pardilla-Delgado ◽  
Rachel F. Buckley ◽  
Yamile Bocanegra ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Sex Differences ◽  
Autosomal Dominant ◽  
Volume Ratio ◽  
Word List ◽  
Hippocampal Volume ◽  
Delayed Recall ◽  
List Learning ◽  
Age Range ◽  
Female Carriers

Background: Growing evidence suggests that there may be a sex-specific biological risk for Alzheimer’s disease (AD). Individuals with autosomal dominant AD due to a mutation (E280A) in Presenilin-1 (PSEN1) are genetically determined to develop early-onset dementia and thus, have few age-related risk factors for AD that are known to vary by sex (i.e., cardiovascular disease, menopause, life expectancy). Objective: Investigate sex differences in markers of cognition and neurodegeneration in autosomal dominant AD. Methods: We conducted a retrospective study in 19 cognitively-unimpaired PSEN1 mutation carriers (age range 20–44; 11 females), 11 symptomatic carriers (age range 42–56; 8 females), and 23 matched non-carriers family members (age range 20–50; 13 females). We examined hippocampal volume ratio, CERAD Total Score, and CERAD Word List (i.e., Learning, Delayed Recall, and Recognition). Mann-Whitney U tests, Spearman correlations and regression models were conducted. Results: There were no differential associations between age, CERAD Total Score, CERAD Word List–Learning, Delayed Recall, Recognition, and hippocampal volume ratio in male and female carriers and non-carriers. Cognitively-unimpaired female carriers showed better CERAD Total scores and CERAD Word List-Learning than cognitively-unimpaired male carriers, despite having similar hippocampal volume ratios. The interaction of sex and hippocampal volume ratio did not predict cognitive performance across groups. Conclusion: Our preliminary findings suggest that cognitively-unimpaired female carriers showed a verbal memory reserve, and as disease progresses, female carriers did not exhibit a cognitive susceptibility to AD-related neurodegeneration. Future studies with larger samples of autosomal dominant AD are warranted to further understand sex differences in AD-related clinical and pathological markers.

scholarly journals Transcranial Magnetic Stimulation of the Medial Prefrontal Cortex Decreases Emotional Memory Schemas

2020 ◽  
Vol 30 (6) ◽  
pp. 3608-3616 ◽  
Author(s):  
Leonore Bovy ◽  
Ruud M W J Berkers ◽  
Julia C M Pottkämper ◽  
Rathiga Varatheeswaran ◽  
Guillén Fernández ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Transcranial Magnetic Stimulation ◽  
Medial Prefrontal Cortex ◽  
Magnetic Stimulation ◽  
Mood Induction ◽  
Recognition Performance ◽  
Memory Task ◽  
Emotional Memory ◽  
Memory Bias

Abstract Mood-congruent memory bias is a critical characteristic of depression, but the underlying neural mechanism is largely unknown. Negative memory schemas might enhance encoding and consolidation of negative experiences, thereby contributing to the genesis and perpetuation of depressive pathology. To investigate this relationship, we aimed to perturb medial prefrontal cortex (mPFC) processing, using neuronavigated transcranial magnetic stimulation (TMS) targeting the mPFC. Forty healthy volunteers first underwent a negative mood induction to activate negative schema processing after which they received either active inhibitory (N = 20) or control (N = 20) stimulation to the mPFC. Then, all participants performed the encoding of an emotional false memory task. Recall and recognition performance was tested the following morning. Polysomnographic data were recorded continuously during the night before and after encoding. We observed a significantly lower false recognition of negative critical lures following mPFC inhibition, but no differences in veridical memory. These findings were supported by reaction time data, showing a relative slower response to negative compared with positive critical lures. The current findings support previous causal evidence for a role of the mPFC in schema memory processing and further suggest a role of the mPFC in memory bias.

scholarly journals Automatic Segmentation of the Dorsal Claustrum in Humans Using in vivo High-Resolution MRI

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Shai Berman ◽  
Roey Schurr ◽  
Gal Atlan ◽  
Ami Citri ◽  
Aviv A Mezer
Keyword(s):  
High Resolution ◽  
Automatic Segmentation ◽  
Thin Sheet ◽  
Brain Regions ◽  
Reproducible Research ◽  
Human Connectome Project ◽  
High Resolution Mri ◽  
Magnetic Resonance Imaging Mri ◽  
And Function

Abstract The claustrum is a thin sheet of neurons enclosed by white matter and situated between the insula and the putamen. It is highly interconnected with sensory, frontal, and subcortical regions. The deep location of the claustrum, with its fine structure, has limited the degree to which it could be studied in vivo. Particularly in humans, identifying the claustrum using magnetic resonance imaging (MRI) is extremely challenging, even manually. Therefore, automatic segmentation of the claustrum is an invaluable step toward enabling extensive and reproducible research of the anatomy and function of the human claustrum. In this study, we developed an automatic algorithm for segmenting the human dorsal claustrum in vivo using high-resolution MRI. Using this algorithm, we segmented the dorsal claustrum bilaterally in 1068 subjects of the Human Connectome Project Young Adult dataset, a publicly available high-resolution MRI dataset. We found good agreement between the automatic and manual segmentations performed by 2 observers in 10 subjects. We demonstrate the use of the segmentation in analyzing the covariation of the dorsal claustrum with other brain regions, in terms of macro- and microstructure. We identified several covariance networks associated with the dorsal claustrum. We provide an online repository of 1068 bilateral dorsal claustrum segmentations.

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