Area:
cellular, computational neuroscience, central pattern generation
We are testing a new system for linking grants to scientists.
The funding information displayed below comes from the
NIH Research Portfolio Online Reporting Tools and the
NSF Award Database.
The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
You can help! If you notice any innacuracies, please
sign in and mark grants as correct or incorrect matches.
Sign in to see low-probability grants and correct any errors in linkage between grants and researchers.
High-probability grants
According to our matching algorithm, Rachel G. Grashow is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2007 — 2009 |
Grashow, Rachel G |
F31Activity Code Description: To provide predoctoral individuals with supervised research training in specified health and health-related areas leading toward the research degree (e.g., Ph.D.). |
Can Modulators Act Consistently On Intrinsically Variable Neural Networks?
[unreadable] DESCRIPTION (provided by applicant): Small networks of neurons can produce rhythmic behaviors such as breathing, walking, and chewing. However, these simple behaviors often need to be modified to suit environmental circumstances, such as breathing more quickly during exertion, and more slowly during rest. One of the ways that these small networks can produce a variety of behaviors is through neuromodulation. Neurotransmitters and hormones act on cellular and synaptic properties to alter the output of a neural network. Recent experimental work, however, has shown that functionally identical networks can have variable underlying cellular and synaptic properties. This raises the following conundrum: Are the effects of neuromodulators consistent if the underlying structure of each network is different? By building artificial networks out of biological and model neurons with controlled synaptic and cellular properties, it may be possible to understand if neuromodulators alter neural network output in a similar way regardless of variable underlying structure. While neuromodulation can confer a larger behavioral repertoire on a simple network, neuromodulator imbalances have been implicated as one of the underlying causes of schizophrenia, epilepsy, mood disorders and drug addiction. In extreme cases of mental illness, drugs are used to modify neuromodulator pathways and networks in the brain. This research should provide insight into whether we can expect a drug or treatment that impacts neuromodulator pathways to do so consistently in different patients and pathologies. [unreadable] [unreadable] [unreadable]
|
1 |