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Shaping Neural Circuits, Human Brain Region Development, and Predicting the Future: the PLOS Comp Biol August Issue

bchadwick Community Computational biology Genomics Image Neuroscience

Check out our highlights from the PLOS Computational Biology August issue:

 

Shaping Neural Circuits by High Order Synaptic Interactions

Illustration of connectivity matrices: Left—random connectivity, A. Synfire chain connectivity, B. Self connected assemblies. In all panels horizontal (vertical) axes represent the pre (post) synaptic neuron. Image Credit: Ravid Tannenbaum, Burak.
Illustration of connectivity matrices: Left—random connectivity, A. Synfire chain connectivity, B. Self connected assemblies. In all panels horizontal (vertical) axes represent the pre (post) synaptic neuron. Image Credit: Ravid Tannenbaum, Burak.

 

Plasticity between neural connections plays a key role in our ability to process and store information. One of the fundamental questions regarding plasticity is the extent to which local processes – affecting individual synapses – are responsible for large-scale structures of neural connectivity. To investigate this, Neta Ravid Tannenbaum and Yoram Burak focus on two types of structure: synfire chains and self-connected assemblies. They show that an important plasticity mechanism – spike timing-dependent plasticity – can lead to autonomous emergence of these large-scale structures in the brain.

 

 

Gene Expression Patterns and Human Brain Regions

Genome-wide measurements of gene expression across the human brain can reveal new principles of brain organization and function. Lior Kirsch and Gal Chechik aim to discover which genes are differentially expressed and in what brain regions. They find that almost all genes in the adult human brain bear a developmental ‘footprint’ which determines their areal expression pattern based on the developmental ontology of brain regions, while at the same time their spatial expression pattern changes during life.

 

Prediction Error in Auditory Cortex

A crucial aspect of all life is the ability to use past events in order to guide future behaviour. To do that, creatures need the ability to predict future events. Predictability has been shown to affect neuronal responses in many animals and under many conditions. The quality of predictions should depend on the amount and detail of the past information used to generate them. By using a basic principle from information theory, Jonathan Rubin and colleagues show how to derive the trade-off between the quality of prediction and the complexity of the representation of past information.

 

Information flow between the organism and the environment. Image Credit: Rubin et al.
      Information flow between the organism and the environment. Image Credit: Rubin et al.

Header Image Credit: Lior Kirsch

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