Psychobiological factors of resilience and depression in late life.

In contrast to traditional perspectives of resilience as a stable, trait-like characteristic, resilience is now recognized as a multidimentional, dynamic capacity influenced by life-long interactions between internal and environmental resources. We review psychosocial and neurobiological factors associated with resilience to late-life depression (LLD). Recent research has identified both psychosocial characteristics associated with elevated LLD risk (e.g., insecure attachment, neuroticism) and psychosocial processes that may be useful intervention targets (e.g., self-efficacy, sense of purpose, coping behaviors, social support). Psychobiological factors include a variety of endocrine, genetic, inflammatory, metabolic, neural, and cardiovascular processes that bidirectionally interact to affect risk for LLD onset and course of illness. Several resilience-enhancing intervention modalities show promise for the prevention and treatment of LLD, including cognitive/psychological or mind-body (positive psychology; psychotherapy; heart rate variability biofeedback; meditation), movement-based (aerobic exercise; yoga; tai chi), and biological approaches (pharmacotherapy, electroconvulsive therapy). Additional research is needed to further elucidate psychosocial and biological factors that affect risk and course of LLD. In addition, research to identify psychobiological factors predicting differential treatment response to various interventions will be essential to the development of more individualized and effective approaches to the prevention and treatment of LLD

The Neuroscience of Mathematical Cognition and Learning

The synergistic potential of cognitive neuroscience and education for efficient learning has attracted considerable interest from the general public, teachers, parents, academics and policymakers alike. This review is aimed at providing 1) an accessible and general overview of the research progress made in cognitive neuroscience research in understanding mathematical learning and cognition, and 2) understanding whether there is sufficient evidence to suggest that neuroscience can inform mathematics education at this point. We also highlight outstanding questions with implications for education that remain to be explored in cognitive neuroscience. The field of cognitive neuroscience is growing rapidly. The findings that we are describing in this review should be evaluated critically to guide research communities, governments and funding bodies to optimise resources and address questions that will provide practical directions for short- and long-term impact on the education of future generations

Transcranial random noise stimulation mitigates increased difficulty in an arithmetic learning task

Proficiency in arithmetic learning can be achieved by using a multitude of strategies, the most salient of which are procedural learning (applying a certain set of computations) and rote learning (direct retrieval from long-term memory). Here we investigated the effect of transcranial random noise stimulation (tRNS), a non-invasive brain stimulation method previously shown to enhance cognitive training, on both types of learning in a 5-day sham-controlled training study, under two conditions of task difficulty, defined in terms of item repetition. On the basis of previous research implicating the prefrontal and posterior parietal cortex in early and late stages of arithmetic learning, respectively, sham-controlled tRNS was applied to bilateral prefrontal cortex for the first 3 days and to the posterior parietal cortex for the last 2 days of a 5-day training phase. The training involved learning to solve arithmetic problems by applying a calculation algorithm; both trained and untrained problems were used in a brief testing phase at the end of the training phase. Task difficulty was manipulated between subjects by using either a large (“easy” condition) or a small (“difficult” condition) number of repetition of problems during training. Measures of attention and working memory were acquired before and after the training phase. As compared to sham, participants in the tRNS condition displayed faster reaction times and increased learning rate during the training phase; as well as faster reaction times for both trained and untrained (new) problems, which indicated a transfer effect after the end of training. All stimulation effects reached significance only in the “difficult” condition when number of repetition was lower. There were no transfer effects of tRNS on attention or working memory. The results support the view that tRNS can produce specific facilitative effects on numerical cognition – specifically, on arithmetic learning. They also highlight the importance of task difficulty in the neuromodulation of learning, which in the current study due to the manipulation of item repetition might have being mediated by the memory system

From cortical excitation to cognition: the case of mathematics

Excitatory and inhibitory neurons have important roles in learning and skill acquisition in the brain. Glutamate and gamma-aminobutyric acid (GABA) are the brain’s major excitatory and inhibitory neurotransmitters in the brain, respectively. Until recently, the link between such neurochemicals and higher-order cognition could not be directly observed in the living human brain. With the advent of magnetic resonance spectroscopy (MRS), an MRI-based method to measure regional concentrations of a whole range of neurochemicals, it has become possible to link behavioral measures with glutamate and GABA. Here I investigated whether glutamate and GABA in a fronto-parietal mathematical brain network were associated with mathematical abilities in children, adults, and expert calculators, including an individual with prodigious calculation abilities. I found that the relationship differs as a function of the brain area (e.g. the hemisphere), age, gender, and ability. Furthermore, regional levels of glutamate and GABA can be artificially modulated by transcranial electrical stimulation (tES), a non-invasive method to affect cortical excitability and increase the potential for plastic changes in the brain. As a possible neuro-enhancement tool, I investigated whether tES to frontal and parietal cortices during mathematical task execution can reliably improve complex arithmetic training effects, and whether such effects were accompanied by changes in regional concentrations in glutamate and GABA. In two double-blind, sham-controlled studies involving a five-day training paradigm, I could not replicate the exact results from a previous study. The previous study found beneficial effects of stimulation to bilateral dorsolateral prefrontal (DLPFCs), but not posterior parietal cortices (PPCs) on learning and transfer to novel task material using the same training paradigm. In a counter-balanced, sham-controlled, within-subjects design, I found that certain sub-tests improved when stimulating DLPFCs, while others improved when stimulating PPCs. In a subsequent between-subjects study, I found impairments in the group that received stimulation to PPCs. Moreover, I could not find changes in glutamate and GABA in the groups that received real, compared to sham stimulation. In a different paradigm, I also investigated whether an individual with exceptional calculation abilities, the 'lightning calculator' G.M., could benefit from tES. In a sham-controlled within-subject single-case study across six testing sessions on two separate days, I found no improvement of G.M.'s calculation abilities. In order to test whether other expert calculators would show the same lack of an effect, I tested six postgraduate students in mathematics fields in an adapted but similar tES paradigm. These experts showed impairment in calculation performance under tES compared to sham. The failure to replicate previous results and the impairments observed in two different samples suggest that the effects of tES on cognition are currently relatively unpredictable. Therefore, positive outcomes of individual tES studies should be interpreted with caution. MRS can be a useful tool to investigate brain-behavior relationships at a neuro-biological level and ideally, further research will demonstrate whether glutamate and GABA can be used as neural markers for poor cognitive abilities. Ideally, MRS will aid the diagnosis of cognitive difficulties at the neurochemical level, such that neuro-intervention can be targeted to enhance cognitive plasticity accordingly.</p