Predicting learning and achievement using GABA and glutamate concentrations in human development

Abstract

Previous research has highlighted the role of glutamate and gamma-aminobutyric acid (GABA) in learning and plasticity. What is currently unknown is how this knowledge translates to real-life complex cognitive abilities that emerge slowly and how the link between these neurotransmitters and human learning and plasticity is shaped by development. While some have suggested a generic role of glutamate and GABA in learning and plasticity, others have hypothesized that their involvement shapes sensitive periods during development. Here we used a cross-sectional longitudinal design with 255 individuals (spanning primary school to university) to show that glutamate and GABA in the intraparietal sulcus explain unique variance both in current and future mathematical achievement (approximately 1.5 years). Furthermore, our findings reveal a dynamic and dissociable role of GABA and glutamate in predicting learning, which is reversed during development, and therefore provide novel implications for models of learning and plasticity during childhood and adulthood.

Fig 1. Information about the scanning and cognitive sessions and neurochemical spectra plots.

(A) Scanning and (B) cognitive sessions were completed both during Time 1 and Time 2 (approximately 1.5 years later) in each of the 5 age groups (6-year-olds, 10-year-olds, 14-year-olds, 16-year-olds, and 18+-year-olds). The mean spectra from our sample at Time 1 for the (C) MFG and the (D) IPS. The thickness corresponds to ±1 SD from the mean (chemical shift expressed in ppm, in x-axis). (E) Fit spectra for glutamate (black) and GABA (red) (For the spectra for each of the age groups separately, see S1 Fig). The data underlying this figure can be found in S1 Data. GABA, gamma-aminobutyric acid; IPS, intraparietal sulcus; MFG, middle frontal gyrus; ppm, parts per million; SD, standard deviation.

Fig 2

The moderating role of age in the relation between neurotransmitter concentration and MA at Time 1 (A–D) and at Time 2 (E–H). To depict the interaction between the continuous variables (age and neurotransmitter concentration), we plotted the regression lines for ± 1 SD from the mean age [53]. Dark color concerns +1 SD above the mean, while light color concerns −1 SD below the mean. The average color represents the mean. (A) Glutamate*age and (B) GABA*age in the left IPS at Time 1. (C) Glutamate*age and (D) GABA*age in the left MFG at Time 1. (E) Glutamate*age and (F) GABA*age in the left IPS at Time 2. (G) Glutamate*age and (H) GABA*age in the left MFG at Time 2. The shaded area represents 95% confidence intervals. The data underlying this figure can be found in S2 Data. GABA, gamma-aminobutyric acid; IPS, intraparietal sulcus; MA, mathematical achievement; MFG, middle frontal gyrus; SD, standard deviation.

Fig 3. Predicting MA at Time 2 from the interaction between age neurotransmitter concentration at Time 1.

To depict the interaction between the continuous variables, we plotted the regression lines for ± 1 SD from the mean age [53]. Dark color concerns +1 SD above the mean, while light color concerns −1 SD below the mean. The average color represents the mean. (A) Glutamate and (B) GABA in the left IPS; (C) glutamate and (D) GABA in the left MFG. The shaded area represents 95% confidence intervals. For visualization purposes, the effect of age at Time 2 was not included when generated the panels of this figure. The data underlying this figure can be found in S3 Data. GABA, gamma-aminobutyric acid; IPS, intraparietal sulcus; MA, mathematical achievement; MFG, middle frontal gyrus; SD, standard deviation.