Seminar Papers

[Article] Canonical Correlation Analysis of Imaging Genetics Data Based on Statistical Independence and Structural Sparsity.

Summary: They proposed Independence and Structural sparsity canonical correlation analysis (ISCCA) for imaging genetics study. They combined ICA and CCA to reduce the collinear effects, which also incorporate graph structure of the data into the model to improve the accuracy of feature selection. This method helps identify risk genes and abnormal brain regions in schizophrenia.

Zhang, Yipu, et al. “Canonical Correlation Analysis of Imaging Genetics Data Based on Statistical Independence and Structural Sparsity.” IEEE journal of biomedical and health informatics 24.9 (2020): 2621-2629.

[Article] Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder.

Summary: Using deep neural networks(DNN) to classify diseases using genetic data is popular these days. In this article, they hypothesized that disease-relevant modules of genes can be discovered within the autoencoder (AE) representations. They compared shallow and deep AE with various node sizes, and showed deep AE works better. Also, they also showed that each different layer captures gradients of biology. By overlapping top 1000 genes for each disease with GWAS, they found a highly significant association for at least one layer in all tested diseases.

Dwivedi, S. K., Tjärnberg, A., Tegnér, J., & Gustafsson, M. (2020). Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder. Nature communications, 11(1), 1-10.

[Article] Concept Representation Reflects Multimodal Abstraction: A Framework for Embodied Semantics.

Summary: This paper showed the relationship between the activation of brain regions and sensory-motor semantic features. They defined five semantic features (sound, color, motion, shape, manipulation - which are related to sensory-motor experiences) for each word and observed brain regions which are associated with each of the semantic attributes. They found that four of the five attributes were related to the activation in corresponding sensory-motor regions.

Fernandino, Leonardo, et al. “Concept representation reflects multimodal abstraction: A framework for embodied semantics.” Cerebral cortex 26.5 (2016): 2018-2034.

[Article] Identification of the brain networks that contribute to the interaction between physical function and working memory: an fMRI investigation with over 1,000 healthy adults

Summary: The study into the relationship between physical function and working memory is actively underway. In this paper, they tried to find the relationships between cardiorespiratory fitness, gait speed, hand dexterity, muscular strength with N-back performance as a working memory task. The results illustrate that FPN and DMN are activated by task-evoked functional activity and the cardiorespiratory fitness and hand dexterity contribute to enhance this activation.

Ishihara, Toru, et al. “Identification of the brain networks that contribute to the interaction between physical function and working memory: an fMRI investigation with over 1,000 healthy adults.” NeuroImage 221 (2020): 117152.

[Article] Neurofeedback of core language network nodes modulates connectivity with the default-mode network:a double-blind fMRI neurofeedback study on auditory verbal hallucinations.

Summary: The auditory-verbal hallucination by change of brain network function has been reported from schizophrenia patients. The goal of the paper is to investigate the modulation by neurofeedback in resting-state connectivity. They demonstrated the coupling increased between language and DMN node after the down-regulation NF. Also, they showed the possibility of NF as a therapeutic intervention

Zweerings, Jana, et al. (2019) “Neurofeedback of core language network nodes modulates connectivity with the default-mode network: a double-blind fMRI neurofeedback study on auditory verbal hallucinations.” NeuroImage 189 : 533-542.

[Article] natomical and functional properties of the foot and leg representation in areas 3b, 1 and 2 of primary somatosensory cortex in humans: A 7T fMRI study

Summary: In this paper, lower limb somatotopy mapping was investigated whether each mapped representation also responded to the stimulation of other body parts (i.e., response selectivity) and conducted dissimilarity analysis relating these anatomical and functional properties of S1 to the physical structure of the lower limbs. They found only minor differences between the properties of the three BAs of somasensory areas (i.e., BA 3,1,2), suggesting that S1 maps for the lower limbs differ from those described for the hand. Furthermore, this paper suggested a possible homology between the first digit of upper and lower extremity in humans, and report different patterns of selectivity in the foot representations (i.e. lower selectivity) compared to the other leg representations (i.e. greater selectivity)

Akselrod, Michel, et al. (2017) Anatomical and functional properties of the foot and leg representation in areas 3b, 1 and 2 of primary somatosensory cortex in humans: A 7T fMRI study. Neuroimage 159, 473-487.

How sex differences play a role in neurological diseases

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Separating vascular cell data based on sex helps researchers make new discoveries about why males and females are affected by neurodegenerative* diseases differently. Findings point to differences in the blood-brain barrier between males and females.

*neurodegenerative : the progressive loss of structure or function of neurons, including their death

Weber, Callie M., and Alisa Morss Clyne. “Sex differences in the blood–brain barrier and neurodegenerative diseases.” APL Bioengineering 5.1 (2021): 011509.

Study links genes with function across the human brain

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A new study, that utilized machine learning tools, provides a new map that links genetic signatures to functions across the human brain!

Interestingly, they found a clear genetic signal that separated cognitive processes, like attention, from more affective processes, like fear. This separation can be traced to gene expression in specific cell types and molecular pathways, offering key insights for future research into psychiatric disorders.

Cognition, for example, was linked more to the gene signatures of inhibitory or excitatory neurons. Affective processes, however, were linked to support cells such as microglia and astrocytes, supporting a theory that inflammation of these cells is a risk factor in mental illness. The genetic signature related to affect was centred on a brain region called the anterior cingulate cortex, which has been shown to be vulnerable in mental illness.

See the https://www.nature.com/articles/s41562-021-01082-z
Published in the journal Nature Human Behaviour on March 25, 2021
(this study draws a direct link between gene expression and higher brain function, by mapping gene signatures to functional processes across the human brain.)

The evolution of overconfidence

Johnson, D. D., & Fowler, J. H. (2011). The evolution of overconfidence. Nature, 477(7364), 317-320.

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Interestingly, the authors found that overconfidence maximizes individual fitness and populations tend to become overconfident.