rochester NIRS workshop

It’s been a long time since my last post (tisk tisk!) so here I am, catching up.

Last week one of my advisors, Lauren Emberson, hosted a NIRS workshop at the University of Rochester. NIRS (near-infrared spectroscopy) is a non-invasive imaging technique used to measure the metabolic activity in the cortex. (For a great review, see Aslin, 2012.) Basically, when areas of the cortex are more active, this requires additional metabolic support, so more oxygenated hemoglobin is transferred to the location of activation. Light is absorbed differentially for oxygenated hemoglobin and deoxygenated hemoglobin, so our measure is essentially how much light the cortex in an approximate area is absorbing during x measurement time. (Note: I say “approximate” because one of the downsides of current NIRS systems is low spatial resolution, as compared to fMRI, so we can’t make super exact claims about cortical areas.) NIRS is an excellent method to use with infants, because the imaging doesn’t require rigid head stabilization. Infants wear a cap (similar to EEG) and can sit on their parent’s lap while watching+/listening to audio+/visual stimuli.

This was a great opportunity – both to learn more about the NIRS methodology and recent literature, but also to bond with my future labmates. Here are a few pictures from the trip:

IMG_6900  IMG_6935

SES ranges

Lately, I’ve been thinking more about SES (socioeconomic status) ranges for participants in cognitive and developmental psychology research. I’d like to know more about SES-based differences in language and cognitive development, but I’ve only begun to scratch the surface with a literature review in this regard. In the long-term, I’d really like to do a review paper on this topic.

It seems likely that we usually draw upon “convenience samples.” These are families who live near a major research institution, and who have time to volunteer. Working at Harvard, I found it difficult to get a normal distribution on a number of standardized assessments of verbal and nonverbal abilities (e.g., MCDI, PPVT, CELF, TROG, KBIT). This raises the important question as to whether our results are generalizable to a broader population. Moreover, small samples from low-SES populations might make it a bit difficult to interpret SES effects.

For example, I was reading this article this morning that described large SES effects:

“Toddlers came from a range of socioeconomic backgrounds, as indexed by mother’s education level gathered by parent report. Participants’ mothers’ educational attainment fell into the following ordered categories: 1) less than high school degree (n = 1), 2) high school diploma (10), 3) some college (8), 4) college degree (16), and 5) advanced degree (41). One parent declined to provide this information.” (Bergelson & Swingley, 2013).

Here’s what that range looks like:

ses1ses2

The authors found: “Mother’s education has a significant and graded effect on toddlers’ overall word-comprehension performance. These effects were large, as Figure 4 shows.” However, discussing why these effects exist is outside the scope of this particular paper: “Our data do not speak to the origins of performance differences correlated with socioeconomic status; based on the work of previous authors, differences in the children’s language environment are plausible causes.”

These effects were indeed very large, and the pattern is strikingly clear, but I do wonder what would happen if more children from low-SES groups were included in the sample. In this study, 75% of the mothers had a college degree or a graduate-level degree. More research is surely needed to better understand SES effects and their origins.

For now, back to literature review!