Michigan Neural Distinctiveness (MiND) project: Investigating the scope, causes, and consequences of age-related neural dedifferentiation

Background Aging is often associated with behavioral impairments, but some people age more gracefully than others. Why? One factor that may play a role is individual differences in the distinctiveness of neural representations. Previous research has found that neural activation patterns in visual cortex in response to different visual stimuli are often more similar (i.e., less distinctive) in older vs. young participants, a phenomenon referred to as age-related neural dedifferentiation. Furthermore, older people whose neural representations are less distinctive tend to perform worse on a wide range of behavioral tasks. The Michigan Neural Distinctiveness (MiND) project aims to investigate the scope of neural dedifferentiation (e.g., does it also occur in auditory, motor, and somatosensory cortex?), one potential cause (age-related reductions in the inhibitory neurotransmitter gamma-aminobutyric acid (GABA)), and the behavioral consequences of neural dedifferentiation. This protocol paper describes the study rationale and methods being used in complete detail, but not the results (data collection is currently underway). Methods/Design The MiND project consists of two studies: the main study and a drug study. In the main study, we are recruiting 60 young and 100 older adults to perform behavioral tasks that measure sensory and cognitive function. They also participate in functional MRI (fMRI), MR spectroscopy (MRS), and diffusion weighted imaging (DWI) sessions, providing data on neural distinctiveness and GABA concentrations. In the drug study, we are recruiting 25 young and 25 older adults to compare neural distinctiveness, measured with fMRI, after participants take (1) a benzodiazepine (lorazepam) that should increase GABA activity or (2) a placebo. Discussion By collecting multimodal imaging measures (fMRI, MRS, DWI) along with extensive behavioral measures from the same subjects, we are linking individual differences in neurochemistry, neural representation, and behavioral performance, rather than focusing solely on group differences between young and old participants. Our findings have the potential to inform new interventions for age-related declines.

Main study exclusion criteria • Hearing problems or use of a hearing aid • Color blindness • Motor control problems • Psychotropic medication • Current depression or anxiety, or occurrence of depression/anxiety within 5 years • Concussion with unconsciousness for 5 minutes or more • Pregnancy or attempting to become pregnant • More than 4 alcoholic drinks per week for women, more than 6 for men • History of drug or alcohol abuse or addiction • Weight greater than 250 pounds • MRI incompatibility (claustrophobic, foreign metallic objects, pacemaker, etc.) 118 Power Calculations 119 Carp, Park, Polk, et al. [2] found that the neural representations of visual stimuli are less 120 distinct in older adults than in young adults (d = 1.06). To achieve 80% power to detect an effect 121 of this size, a sample of approximately 15 subjects per group would be required. Park et al. [4] 122 reported correlations between neural distinctiveness and fluid intelligence among older adults 123 ranging from r = 0.275 to r = 0.59. To achieve 80% power to detect a correlation of r = 0.275, 124 approximately 100 subjects would be required per group; to detect a correlation of r = 0.59, 125 approximately 30 subjects would be required. Thus, to provide sufficient power to detect both 126 between-group neural differences and brain-behavior correlations within the older group, we are 127 targeting a sample of 100 older adults and 60 young adults.  any. The software automatically calculates a LogMAR score (a modified version 155 of a Snellen visual acuity score) and converts it to a standard score. The stimulus picture is either a house (50% of trials) or an apartment (50% 173 of trials). Participants are asked to press "1" on the keyboard with their left 174 index finger if they think the picture was a house and to press "0" with 175 their right index finger if they think the picture was an apartment building. presented using over-the-ear noise cancelling headphones, and participants adjust 220 the volume to a comfortable level before beginning the task.

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This task assesses how well participants can hear sentences presented in noise.

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The task is administered on a

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Participants are instructed to place as many pegs as they can until they are told to 326 stop. The number of pairs of pegs placed in 30 seconds is recorded.

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In the "Assembly" task, participants use both hands to create assemblies     The specific sequence of scans is described below.

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The localizer is generated with a 2D Gradient Echo pulse sequence with FOV = 320 x 486 320 mm and slice thickness = 10 mm with no spacing; acquisition time = 30 seconds.

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The overlay is generated with a 2D T1-weighted Fluid-Attenuated Inversion Recovery The localizer is collected using the same parameters as in the fMRI session.

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The structural image is collected using the same parameters as in the fMRI session. hemisphere voxel to capture activations from the right hand motor task and the right hand 595 somatosensory task. We place the right hemisphere voxel using the left hand activations.

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The goal of the drug study is to explore whether GABA plays a role in age-related neural 599 dedifferentiation. To do so, we manipulate GABA activity pharmacologically using lorazepam (a 600 benzodiazepine) and investigate the effect on neural distinctiveness assessed with fMRI.

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Lorazepam is an allosteric modulator of the GABA receptor, potentiating its inhibitory function. 602 We hypothesize that increasing GABA activity experimentally will increase neural 603 distinctiveness.  analog scale and psychomotor vigilance task just before and immediately following the fMRI 638 scans to assess potential drowsiness. Participants are randomly assigned to one of four session 639 orders as depicted in Table 3. These session orders are used to counterbalance the lorazepam   We use surface-based methods as implemented in FreeSurfer to construct a cortical 653 surface for each participant from their high-resolution T1-weighted anatomical image. Fixel-based analysis 775 We are performing fixel based analyses (FBA) of fiber density (FD), fiber bundle cross-776 section (FC), and fiber density and cross section (FDC investigates group differences between young and older subjects and ignores individual 810 differences between subjects in the same age group. However, some older subjects experience 811 significantly greater behavioral declines than others, and these individual differences could 812 provide important insights into the underlying causes of age-related behavioral declines.

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Finally, the proposed research offers the potential to inspire a new approach to therapy

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Consent for publication 873 Not applicable.

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Availability of data and material 875 Data sharing is not applicable to this article as no datasets were generated or analyzed during the 876 current study.

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Competing interests 878 The authors declare no competing interests. TP is the PI of the study and received the grant funding the project.

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HG and MS were the main authors of the manuscript.

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HG and EF were major contributors to the coordination of the project and data collection.

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MS, BF, and MP were the main contributors to MRS design and analyses.

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HG, MS, KC, JC, PL, DP, RDS, and DHW contributed to task design and data analyses.

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SFT contributed to drug-related components of the study.
SK contributed to DWI analyses.

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All authors read and approved the final manuscript.