Dup15q 2015
Recent articles
Brain-wave patterns distinguish dup15q syndrome
Children with an extra copy of the 15q11-13 chromosomal region, the second most common genetic abnormality in people with autism, have unusually strong brain waves called beta oscillations. The preliminary findings, presented Friday at the Dup15q Alliance Scientific Meeting in Orlando, Florida, suggest that beta oscillations could distinguish children with dup15q syndrome from those with other forms of autism.
Brain-wave patterns distinguish dup15q syndrome
Children with an extra copy of the 15q11-13 chromosomal region, the second most common genetic abnormality in people with autism, have unusually strong brain waves called beta oscillations. The preliminary findings, presented Friday at the Dup15q Alliance Scientific Meeting in Orlando, Florida, suggest that beta oscillations could distinguish children with dup15q syndrome from those with other forms of autism.
Dispatches from the 2015 Dup15q Alliance Scientific Meeting
These short reports from our reporter, Nicholette Zeliadt, give you the inside scoop on developments at the 2015 Dup15q Alliance Scientific Meeting.
Dispatches from the 2015 Dup15q Alliance Scientific Meeting
These short reports from our reporter, Nicholette Zeliadt, give you the inside scoop on developments at the 2015 Dup15q Alliance Scientific Meeting.
Explore more from The Transmitter
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Single-gene systems-level effects, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 6 April.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
Computational neuroscientist Keith Hengen explains his work through illustrations
The images help him communicate the “big-picture ideas” behind the mathematical principles of neuronal networks.
Computational neuroscientist Keith Hengen explains his work through illustrations
The images help him communicate the “big-picture ideas” behind the mathematical principles of neuronal networks.