Tag: Brain Science

Research has shown that babies do an incredible amount of language processing even before they reach their first birthday. The review “Brain Mechanisms in Early Language Acquisition” published September 9, 2010 in Neuron summarizes some of these data.

The auditory sensory areas in brains of newborns are activated by speech and a number of studies have shown that they are already acquiring language skills and their neural circuitry is influenced. However, the 0 to about 3 month old infant’s motor speech areas are not yet activated.

Speech directed to babies about 3 months old activates their motor speech areas in addition to their auditory sensory areas. At this point the infant begins acquiring sensory and motor language skills.

Social interaction is necessary to acquiring language skills in addition to hearing speech and using motor skills to make speech sounds. An infant exposed to a new language through social interaction shows robust learning. In contrast, infants exposed to the same material but through video or audio tapes show no learning at all.

An infant’s social behavior can be linked to their ability to learn new language material. Babies that are more actively engaged in the learning experience as measured by their gaze progress faster.

Very young babies (less than 1 year old) can seem like they’re doing very little. Don’t be fooled! They’re very active and are counting on you to baby-talk to them.

Since at least the 1960s brain scientists have thought that nerve cell dendrites may discriminate amongst sequences of signal inputs that vary across time and space but experimental methods were not able to control and measure signals at the very small time (submillisecond) and space (submicron) precision necessary to test the idea.

New experimental techniques using two-photon glutamate uncaging in identified dendritic spines now enable the idea to be directly investigated. The paper “Dendritic Discrimination of Temporal Input Sequences in Cortical Neurons” published September 24, 2010 issue of Science tests to see if dendrites discriminate between different temporal and spacial input sequences.

Indeed, the result is yes and some of the specific mechanisms underlying the discrimination are exposed. Impedance along the dendritic shaft was shown to be important and NMDA receptors were shown to be crucial. In fact, the research showed that a large dynamic range provided by NMDA receptor activation enabled high fidelity discrimination between different spatial-temporal sequences whether the input was all on the same dendritic branch or dispersed across the dendritic tree.

As neuroscientists demonstrate the computational complexity of axon terminals and dendritic trees I expect the focus for those interested in how signal processing is carried out in the brain to move from the neuron to the microstructure known as the neuropil.

Wouldn’t it be great if a physician could accurately assess and predict an individual’s brain maturity and development on the basis of a single fMRI scan?

That’s what researchers set out to provide tools for in the study “Prediction of Individual Brain Maturity Using fMRI” published September 10, 2010 in Science.

The result was a functional connectivity maturation curve derived from 238 brain scans of healthy 7 to 30 year old people. A physician can know where a patient fits on this curve by computing a functional connectivity maturation index number using the curve’s associated parametric equation from 5 minutes of resting state fcMRI data.

Overall, the data showed that as a person matures there is a weakening of short range functional connections and a strengthening in long range functional connections. Interestingly, the region with the greatest predictive power for brain maturity was the right anterior prefrontal cortex (see blog post “Are you right? Introspective Accuracy and Individual Differences in Brain Structure“).

The data predicts that a human brain is fully mature at around 22 years.

Other related blog posts:

Are you right? Introspective Accuracy and Individual Differences in Brain Structure