Sensorimotor network segregation declines with age and is linked to GABA and to sensorimotor performance

Highlights

• Older age is associated with reduced segregation in the sensorimotor network and reduced GABA levels in sensorimotor cortex.

• Reduced segregation in the sensorimotor network is associated with lower sensorimotor GABA levels.

• Individual differences in sensorimotor GABA levels correlate with sensorimotor performance.

• This relationship between sensorimotor GABA and sensorimotor behavior is mediated by sensorimotor network segregation.

Abstract

Aging is typically associated with declines in sensorimotor performance. Previous studies have linked some age-related behavioral declines to reductions in network segregation. For example, compared to young adults, older adults typically exhibit weaker functional connectivity within the same functional network but stronger functional connectivity between different networks. Based on previous animal studies, we hypothesized that such reductions of network segregation are linked to age-related reductions in the brain's major inhibitory transmitter, gamma aminobutyric acid (GABA). To investigate this hypothesis, we conducted graph theoretical analyses of resting state functional MRI data to measure sensorimotor network segregation in both young and old adults. We also used magnetic resonance spectroscopy to measure GABA levels in the sensorimotor cortex and collected a battery of sensorimotor behavioral measures. We report four main findings. First, relative to young adults, old adults exhibit both less segregated sensorimotor brain networks and reduced sensorimotor GABA levels. Second, less segregated networks are associated with lower GABA levels. Third, less segregated networks and lower GABA levels are associated with worse sensorimotor performance. Fourth, network segregation mediates the relationship between GABA and performance. These findings link age-related differences in network segregation to age-related differences in GABA levels and sensorimotor performance. More broadly, they suggest a neurochemical substrate of age-related dedifferentiation at the level of large-scale brain networks.

Introduction

Advanced age is typically associated with declines in sensorimotor functioning. Such declines affect the ability of older adults to perform activities of daily living and maintain their functional independence (Seidler et al., 2010). Part of this decline is associated with impairments in the peripheral sensorimotor system, including motor unit reorganization (Galganski et al., 1993) or reduced functioning of cutaneous afferents. But evidence also suggests that some of these age-related declines in behavior are related to changes in the brain, including alterations in neurochemistry, gray matter atrophy, and changes in the functional organization of large-scale brain networks (Seidler et al, 2010, 2015; Langan et al., 2010; Raz and Rodrigue, 2006; Goh, 2011; Ferreira and Busatto, 2013). Understanding these brain-behavior relationships is important for our efforts to prolong the functional independence of older adults as our society continues to age.

Studies in young adults have demonstrated the existence of multiple segregated functional brain networks. Regions within these networks exhibit spontaneous yet correlated activity, and thus are thought to be functionally connected (Biswal et al., 1995; Buckner et al., 2013). Studies have found that connections within these functional networks are quite dense, whereas connections between different networks are more sparse. This organization is considered to benefit specialized or segregated information processing in different brain systems (Bullmore and Sporns, 2012). Several studies have investigated the effect of age on functional connectivity by measuring differences in correlated brain activity within and between brain networks at rest. Many of these studies have found that older adults exhibit weaker functional connectivity between brain regions within the same functional network but stronger functional connectivity between regions belonging to different networks. In other words, their functional networks are less segregated (i.e., a type of age-related dedifferentiation) (Chan et al., 2014; Geerligs et al., 2015; Damoiseaux, 2017).

Many studies have also found that less segregated brain networks are associated with worse cognitive performance, independent of age (Chan et al., 2014; Geerligs et al., 2015; Wang et al., 2010; Damoiseaux et al., 2008). Only a few studies have investigated the relationship between network segregation and sensorimotor behavior, but one such study found that reduced segregation of several large-scale resting state brain networks was associated with poorer bimanual motor performance (King et al., 2018). In sum, the evidence to date suggests that age-related changes in functional connectivity may contribute to age-related declines in cognitive and sensorimotor performance.

An important open question is what causes age-related reductions in network segregation, or neural dedifferentiation. Previous animal studies have linked neural dedifferentiation to changes at the neurotransmitter level. In particular, studies by Leventhal and colleagues suggested that age differences in the brain's major inhibitory neurotransmitter, gamma-aminobutyric acid (GABA), may play an important and potentially causal role in age-related dedifferentiation (i.e., reductions in the specificity of neural activity). More specifically, they demonstrated that manipulations of GABA levels led to changes in the orientation-selectivity of neurons in the visual cortex (Leventhal et al., 2003). The application of GABA or a GABA agonist made visual cortex neurons in old monkeys more orientation-selective, thereby making them similar to neurons in young monkeys. In contrast, the application of a GABA antagonist reduced the orientation-selectivity of visual cortex neurons in young monkeys, thereby making them similar to neurons in old monkeys. These results demonstrate that manipulations of GABA cause changes in neural selectivity in animals, raising the possibility that age declines in GABA might contribute to age-related neural dedifferentiation and associated behavioral declines in humans.

Consistent with this hypothesis, more recent studies in humans have linked individual differences in GABA levels to performance variations across healthy young adults (Edden et al., 2009; Boy et al., 2010; Puts et al., 2011). For example, Edden et al. found that orientation discrimination performance is predicted by GABA levels in primary visual cortex (Edden et al., 2009). In addition, Puts et al. demonstrated that GABA levels in sensorimotor cortex correlate with tactile discrimination thresholds (Puts et al., 2011). Previous work has also found that reactivity in the GABA system plays an important role in motor learning and learning-related brain activity. For instance, Stagg et al. (2011) demonstrated that participants in whom motor cortex (M1) GABA levels decreased the most following transcranial direct current stimulation (i.e., greatest GABA reactivity), also exhibited the most learning in a motor task (Stagg et al., 2011).

Studies have also observed a relationship between functional connectivity within specific resting state networks and GABA levels in young adults. For example, Stagg and colleagues demonstrated that functional connectivity strength within the motor resting state network is related to GABA levels in primary motor cortex (Stagg et al., 2014). A similar relationship was also reported between GABA levels in the posteromedial cortex and the strength of default mode network connectivity (Kapogiannis et al., 2013). While these studies linked individual differences in functional connectivity to differences in GABA levels, no studies have investigated whether this relationship varies with age. Moreover, no studies have examined GABA levels, network segregation, and sensorimotor behavior within the same participants in order to explore the potential links between all three levels.

In the present study, we specifically addressed these gaps. We performed graph theoretical analysis of resting state functional MRI data to measure sensorimotor network segregation and used magnetic resonance spectroscopy (MRS) to measure GABA levels in the sensorimotor cortex. We also collected a battery of sensorimotor behavioral measures to determine whether network segregation and/or GABA levels are associated with individual differences in performance. All three datasets were collected within the same participants, making it possible to examine associations between all the measures.

We tested three hypotheses: 1) The sensorimotor resting state brain network would be less segregated and sensorimotor cortex GABA levels would be reduced in older compared to young adults; 2) lower levels of GABA would be associated with less segregated networks, independent of age; and 3) lower levels of GABA and less segregated networks would be associated with worse sensorimotor performance, independent of age.