Key PointsQuestion
Is dorsolateral prefrontal cortex plasticity impaired in Alzheimer disease?
Findings
In this cross-sectional study of 32 participants with early Alzheimer disease and 16 healthy control participants, significant deficits in dorsolateral prefrontal cortex plasticity were found in participants with Alzheimer disease compared with controls. Working memory performance was also significantly impaired in participants with Alzheimer disease and was associated with dorsolateral prefrontal cortex plasticity across both groups.
Meaning
Dorsolateral prefrontal cortex plasticity is impaired in Alzheimer disease and is associated with impaired working memory.
Importance
The extent of dorsolateral prefrontal cortex (DLPFC) plasticity in Alzheimer disease (AD) and its association with working memory are not known.
Objectives
To determine whether participants with AD had impaired DLPFC plasticity compared with healthy control participants, to compare working memory between participants with AD and controls, and to determine whether DLPFC plasticity was associated with working memory.
Design, Setting, and Participants
This cross-sectional study included 32 participants with AD who were 65 years or older and met diagnostic criteria for dementia due to probable AD with a score of at least 17 on the Mini-Mental State Examination and 16 age-matched control participants. Participants were recruited from a university teaching hospital from May 2013 to October 2016.
Main Outcomes and Measures
Plasticity of the DLPFC measured as potentiation of cortical-evoked activity using paired associative stimulation (a combination of peripheral nerve electrical stimulation and transcranial magnetic stimulation) combined with electroencephalography. Working memory was assessed with the n-back task (1- and 2-back) and measured using the A’ statistic.
Results
Among the 32 participants with AD, 17 were women and 15 were men (mean [SD] age, 76.3 [6.3] years); among the 16 controls, 8 were men and 8 were women (mean [SD] age, 76.4 [5.1] years). Participants with AD had impaired DLPFC plasticity (mean [SD] potentiation, 1.18 [0.25]) compared with controls (mean [SD] potentiation, 1.40 [0.35]; F1,44 = 5.90; P = .02; between-group comparison, Cohen d = 0.77; P = .01). Participants with AD also had impaired performances on the 1-back condition (mean [SD] A′ = 0.47 [0.30]) compared with controls (mean [SD] A′ = 0.96 [0.01]; Cohen d = 1.86; P < .001), with similar findings for participants with AD on the 2-back condition (mean [SD] A’ = 0.29 [0.2]) compared with controls (mean [SD], A′ = 0.85 [0.18]; Cohen d = 2.83; P < .001). Plasticity of DLPFC was positively associated with working memory performance on the 1-back A′ (parameter estimate B [SE] = 0.32 [0.13]; standardized β = 0.29; P = .02) and 2-back A′ (B [SE] = 0.43 [0.15]; β = 0.39; P = .006) across both groups after controlling for age, education, and attention.
Conclusions and Relevance
This study demonstrated impaired in vivo DLPFC plasticity in patients with AD. The findings support the use of DLPFC plasticity as a measure of DLPFC function and a potential treatment target to enhance DLPFC function and working memory in patients with AD.
Pathologic change and dysfunction in the frontal lobes are common in Alzheimer disease (AD) and are present from an early stage of the illness.1-3 In particular, patients with early AD experience dorsolateral prefrontal cortex (DLPFC) dysfunction.4 Dysfunction of the DLPFC is manifested by impairment of working memory and specifically its executive component in early AD.5,6 Furthermore, the DLPFC provides neural substrate for cognitive reserve in individuals at risk for developing AD.7-9 The DLPFC is able to compensate for neuropathologic changes and dysfunction in other regions owing to its ability to experience neuroplasticity.10-13 Thus, understanding the mechanisms that underlie DLPFC dysfunction is important to design effective interventions in patients with AD.
Neuroplasticity refers to the ability of the brain to modify its function or structure in response to experience, use, or pathologic change.14-18 Long-term potentiation (LTP) is a prototype of functional neuroplasticity and refers to use- and time-dependent strengthening of synapses.15,19-21 Paired associative stimulation (PAS) is a transcranial magnetic stimulation (TMS) paradigm that is considered to be a standard in the field to assess LTP-like activity in the human cortex.22-25 Paired associative stimulation induces LTP-like activity (hereafter referred to as PAS-LTP) through the pairing of peripheral nerve electrical stimulation (eg, median nerve at the wrist) with TMS of the contralateral cerebral cortex.26,27 Through this pairing, these 2 stimulations occur contemporaneously in the cortex and activate presynaptic and postsynaptic neurons to induce PAS-LTP.26,27 Paired associative stimulation was originally applied to the human motor cortex, and PAS-LTP was assessed through changes in motor-evoked potentials.26 Subsequently, PAS-LTP was shown to be induced in the human DLPFC by combining median nerve stimulation at the wrist with TMS to the contralateral DLPFC and recording changes in the cortical-evoked activity over the DLPFC using scalp electroencephalography (EEG).28,29 The rationale for using median nerve stimulation in combination with DLPFC is based on extensive evidence of connectivity between frontal and somatosensory cortices in rodents30-32 and primates33 and the ability of median nerve stimulation to induce N24 somatosensory-evoked potential in the human DLPFC.34,35
The DLPFC is critical for working memory,36-39 and DLPFC activation correlates with working memory load.40 Working memory is supported by reentrant circuits between the DLPFC and posterior cortices.38 Robust neuroplasticity within the DLPFC is essential to maintain these networks.41,42 Thus, studying DLPFC plasticity is essential for understanding the mechanisms underlying working memory deficits in AD. A few studies have shown impaired motor cortex plasticity in mild to moderate AD.43-46 Some studies showed impaired motor cortex plasticity using PAS,43,44 whereas others used theta burst stimulation.45,46 However, plasticity changes in the DLPFC of patients with AD have not been reported. Thus, we conducted the first study, to our knowledge, to investigate DLPFC plasticity in AD and its association with working memory. The primary aim of this study was to compare PAS-LTP in the DLPFC between participants with AD and age-matched healthy control participants. We hypothesized that PAS-LTP (ie, plasticity) in the DLPFC would be impaired in participants with AD. The secondary aim was to compare working memory between controls and participants with AD and to determine whether PAS-LTP in the DLPFC is associated with working memory performance. We hypothesized that working memory would be significantly associated with PAS-LTP.
The study was conducted at the Centre for Addiction and Mental Health, Toronto, Ontario, Canada. The study was approved by the research ethics board of the center, and all participants provided written informed consent.
Participants with AD were recruited based on referrals from memory clinics in Toronto or in response to advertisements. They were included if they met (1) the core criteria for probable AD according to the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer Disease and Related Disorders Association (NINCDS-ADRDA)47 and (2) the diagnostic criteria for dementia due to probable AD according to the DSM-IV-TR.48 Other key inclusion criteria were a score of 17 or above on the Mini-Mental State Examination (MMSE; range, 0-30, with higher scores indicating better performance)49; age of 65 years or older; and treatment with a stable dose of a cognitive enhancer (ie, donepezil hydrochloride, galantamine hydrobromide, memantine hydrochloride, or rivastigmine tartrate) for at least 3 months. Age-matched, right-handed controls were recruited using advertisements and from a database (further eligibility criteria are given in eMethods in the Supplement). On the basis of a previous study of PAS at our center,28 a sample of 32 participants with AD and 16 controls was determined to be needed to provide 80% power at α = .05 to detect a significant difference in DLPFC plasticity between the 2 groups.
Data were collected from May 2013 to October 2016. Participants were assessed using the NINCDS-ADRDA criteria,47 the Structured Clinical Interview for DSM-IV-TR,50 Cornell Scale for Depression in Dementia,51 MMSE,49 Repeatable Battery for the Assessment of Neuropsychological Status,52 and Executive Interview.53 Working memory performance was assessed using the n-back54,55 following previously published methods.56 In this study, n was 1 or 2 because participants with AD could not generate meaningful data with the 3-back condition. The n-back task was performed immediately before PAS and on the same day. To assess performance accuracy, we used the A′ statistic, which takes into account true-positive and false-positive findings57,58 (eMethods in the Supplement).
Brodmann area 9/46 in the DLPFC was localized through neuronavigation techniques as previously described.59 The DLPFC site of stimulation corresponded to the F3 or F5 EEG electrode (eMethods in the Supplement).
EEG Recording and Data Analysis
The EEG was recorded during the PAS protocol (TMS-EEG) using 64 channels per 10-20 system60 as previously described.59 The EEG data were cleaned using the EEGLAB toolbox (Matlab) and referenced to the mean for further analyses (eMethods in the Supplement).
PAS Administration and Assessment of DLPFC Plasticity
Paired associative stimulation was administered using a published protocol.28 The protocol involved electrical stimulation of the right median nerve at the wrist followed by TMS of the left DLPFC after a 25-millisecond delay. During the procedure, participants were intermittently asked to report their current count of sensory stimuli, which was recorded against the actual count. The absolute difference between the participant’s count and the actual count (count difference) was used as an index of attention during the PAS procedure because attention is known to be critical for PAS-LTP.26,28 Pre-PAS cortical-evoked activity at the DLPFC was indexed using a train of 100 monophasic TMS pulses at 0.1 Hz administered to the left DLPFC using a 7-cm figure-8 coil and a commercially available module (BiStim; Magstim Company Ltd). We used a rectified area under the curve for TMS-evoked potential to calculate cortical-evoked activity, in line with previous publications on TMS-EEG59,61 and DLPFC plasticity.28,29 At 0, 17, and 34 minutes after PAS, cortical-evoked activity was indexed using the same procedures. These times were chosen on the basis of previous research showing the maximum likelihood of potentiation during this interval for motor cortex62,63 and the DLPFC.28,29 We defined PAS-LTP (ie, DLPFC plasticity) as the maximum potentiation of cortical-evoked activity at 1 of these 3 times and measured using the ratio of post-PAS to pre-PAS cortical-evoked activity as in several previous publications on PAS.28,29,64,65 Finally, to show the changes in TMS-evoked response potential before and after PAS in both groups, we plotted the TMS-evoked response potential before and after PAS at the time of maximum potentiation of cortical-evoked activity for each group of participants (eMethods in the Supplement).
First, we compared the demographic and baseline cognitive and neurophysiological variables between participants with AD and controls by using an independent-samples paired t test or χ2 test. Second, to test our primary hypothesis, we performed an analyses of covariance (ANCOVA) with PAS-LTP as the dependent variable, group (AD vs control) as the independent fixed factor, the count difference as a covariate accounting for the potential confounding effect of attention during PAS, and pre-PAS cortical-evoked activity as another covariate accounting for baseline excitability (which can affect response to PAS). Then, we performed 2 additional ANCOVAs, one using the 1-back A′ and the second using the 2-back A′ as dependent variables, group (AD vs control) as the independent fixed factor, and educational attainment as a covariate potentially confounding differences in working memory performance between participants with AD and controls. Finally, we performed 2 multivariable regression models, the first using the 1-back A′ and the second using the 2-back A′ as dependent variables, with age, educational attainment, count difference, and PAS-LTP entered simultaneously as the independent variables. The Cohen d statistic was used to estimate effect sizes when appropriate. All analyses were performed using SPSS Statistical software for Windows (version 24.0; IBM).
Demographic and Baseline Characteristics
Thirty-two participants with AD (17 women and 15 men; mean [SD] age, 76.3 [6.3] years) and 16 controls (8 men and 8 women; mean [SD] age, 76.4 [5.1] years) completed the assessments and were included in the analysis. We found no statistically significant differences between the 2 groups in age or sex. Participants with AD had lower educational attainment, MMSE scores, and Repeatable Battery for the Assessment of Neuropsychological Status scores and a higher count difference during PAS than did controls. The 2 groups did not differ in baseline neurophysiologic measures, including resting motor threshold and baseline pre-PAS cortical-evoked activity (Table).
Paired Associative Stimulation–Long-term Potentiation
Increases in cortical-evoked activity (ie, PAS-LTP) in the left DLPFC as demonstrated by a mean (SD) post-PAS to pre-PAS cortical-evoked activity ratio of greater than 1.00 were experienced by participants with AD (1.18 [0.25]; t31 = 3.95; P < .001) and controls (1.40 [0.35]; t15 = 4.7; P < .001). We found a significant association of group with PAS-LTP (F1,44 = 5.90; P = .02); when controlling for pre-PAS cortical-evoked activity (F1,44 = 0.28; P = .60) and count difference (F1,44 = 0.02; P = .88), both of which had no influence on PAS-LTP, participants with AD experienced significantly less PAS-LTP than did controls (Cohen d = 0.77; P = .01). This finding was also revealed when plotting the TMS-evoked response potential before and after PAS for participants with AD and controls (Figure 1 and Figure 2).
As expected, we found a significant association of presence of AD with working memory using the 1-back A′ (F1,45 = 32.6; P < .001) and the 2-back A′ (F1,41 = 69.9; P < .001); controlling for educational attainment had no influence on the 1-back A′ (F1,45 = 1.7; P = .19) or the 2-back A′ (F1,41 = 0.36; P = .55). Participants with AD had impaired working memory performance on the 1-back condition (mean [SD] A′ = 0.47 [0.30]) compared with controls (mean [SD] A′ = 0.96 [0.01]; Cohen d = 1.86; P < .001), with similar findings for participants with AD on the 2-back condition (mean [SD] A′ = 0.29 [0.20]) compared with controls (mean [SD] A′ = 0.85 [0.18]; Cohen d = 2.83; P < .001).
Association Between PAS-LTP and Working Memory Performance
Finally, PAS-LTP was associated with working memory performance in both groups on the 1-back A′ (parameter estimate B [SE] = 0.32 [0.13]; standardized β = 0.29; P = .02) and the 2-back A′ (B [SE] = 0.43 [0.15]; β = 0.39; P = .006) after controlling for age, educational attainment, and count difference. Figure 3 shows the raw data demonstrating the correlation between working memory and PAS-LTP. Educational attainment was associated with working memory performance on the 1-back A′ (B [SE] = 0.04 [0.01]; β = 0.38; P = .002) and 2-back A′ (B [SE] = 0.03 [0.01]; β = 0.31; P = .03). Attention was also associated with working memory performance on the 1-back A′ (B [SE] = −0.006 [0.002]; β = −0.46; P < .001) and 2-back A′ (B [SE] = −0.004 [0.002]; β = −0.28; P = .04), but age was not.
This study is the first, to our knowledge, to provide evidence of DLPFC plasticity deficits in patients with AD using TMS-EEG to assess PAS-LTP. To our knowledge, this study also demonstrates for the first time, to our knowledge, an association between DLPFC plasticity and working memory. These findings extend current knowledge on neuroplasticity deficits in AD.43,45,66 Assessing plasticity directly from the DLPFC using TMS-EEG has several advantages. First and notwithstanding the possibility that deficits in DLPFC plasticity may be an upstream effect of subcortical pathologic changes in regions such as the locus ceruleus and dorsal raphe nuclei,67 TMS-EEG allows the development of a direct marker of DLPFC plasticity rather than more peripheral markers (eg, motor-evoked potential or serum markers of neuroplasticity). Second, the feasibility of this procedure in patients with AD makes it possible to study mechanisms underlying cognitive dysfunction in AD. Robust synaptic plasticity is critical for cognitive processes such as learning and memory,68-70 and impaired plasticity could be the final common neurophysiologic mechanism for cognitive deficits of AD. Third, DLPFC plasticity could be a potential target to enhance cognition with interventions such as transcranial direct-current or magnetic stimulation.71-73 Noninvasive DLPFC stimulation may also positively affect plasticitylike phenomena in the motor cortex and have positive effects beyond cognition separate from plasticity.74
The mechanisms by which AD pathologic changes could specifically impair neuroplasticity remain unclear. A reciprocal association between DLPFC plasticity and brain pathologic features in AD may exist.75-78 Furthermore, synaptic dysfunction could lead to a vicious cycle of aberrant neuroplasticity and amyloid deposition, resulting in progression of AD.18 In contrast, several studies have shown a positive role of low levels of endogenous amyloid in maintaining neuroplasticity79,80; thus, the interaction between amyloid and neuroplasticity is complex. Impaired neuroplasticity could also be associated with network dysfunction in AD.81,82 Impairment of default mode network activity is well known in AD and is associated with increased amyloid deposition and cognitive decline.83,84 Thus, future studies should assess the association of neuroplasticity with network dysfunction in AD using techniques such as corticocortical PAS.85-87 The effect of synaptic and neuronal loss on neuroplasticity should be investigated by combining studies of neuroplasticity with markers of neural integrity in vivo or by studying the association between neuroplasticity and postmortem brain pathologic changes in AD.
Long-term potentiation depends on intact glutamate signaling at the synapses.69,88 However, the association between glutamate receptor dysfunction and neuroplasticity in AD is not well understood. Similarly, the association of other neurotransmitters, such as dopamine, with neuroplasticity in AD is not well understood.89 Deficits in acetylcholine signaling are considered to be a hallmark of AD, but the association of acetylcholine with neuroplasticity in AD is not fully known.90-92 Thus, future studies should use magnetic resonance spectroscopy or positron emission tomographic imaging to study neurotransmitter systems in conjunction with PAS.
We also found an association between DLPFC plasticity and working memory in participants with AD and controls. This association seems to be partially driven by differences in distributions of working memory performance and DLPFC plasticity in participants with AD and controls. Although this finding supports the association between DLPFC plasticity and working memory, future research should include participants with mild cognitive impairment whose performance and DLPFC plasticity would be expected to range between that of AD and control groups. In addition, future studies could assess the association between DLPFC plasticity and other cognitive or functional measures in AD. Finally, noninvasive brain stimulation has been shown to enhance motor cortex plasticity93 and cognitive function in AD.71-73,94-96 A recent meta-analysis of 7 studies including 94 patients with mild to moderate AD72 showed that repetitive TMS of the bilateral DLPFC was associated with improved cognitive function. These studies did not investigate the effect of repetitive TMS on DLPFC plasticity. Notwithstanding an overall positive effect, some studies97,98 have shown variability in results for DLPFC noninvasive brain stimulation to enhance working memory. Thus, future studies should consider assessment of DLPFC plasticity and working memory before and after the intervention.
Some differences between the existing literature and the results of our study should be noted. Several studies99-101 have found decreased resting motor threshold and increased cortical excitability in AD. We found no differences in resting motor threshold between the AD and control groups in our study. This finding could be attributable to the relatively milder illness in the participants with AD in our study.99,100,102 One study99 reported an association between motor threshold and severity of illness in AD. We did not find any difference in baseline DLPFC cortical-evoked activity between the AD and control groups in our study. Furthermore, cortical excitability was not associated with PAS-LTP in our study, which suggests that DLPFC plasticity deficits may occur before changes in cortical excitability.
This study has several limitations. First, although the sample size was defined a priori, it was relatively small, which limited our ability to conduct subgroup analyses (eg, based on sex or medications). However, the sample size was sufficient to detect DLPFC plasticity deficits because of the moderate to large effect size that we observed. One study has shown that combined treatment with acetylcholinesterase inhibitors and memantine may restore motor cortex plasticity in AD,66 whereas another study103 has shown that memantine may block motor cortex plasticity in healthy individuals. Only 2 participants with AD in our study were using memantine, and thus it is unlikely to have caused a meaningful effect on our results. Second, the diagnosis of AD in our study was based on clinical assessment and did not incorporate pathologic markers of AD (eg, amyloid or tau imaging). However, a clinical diagnosis of AD based on the NINCDS-ADRDA criteria has been shown to be highly reliable.104,105 Third, we did not correct for coil-to-cortex distance in determining TMS intensity of stimulation. However, we individualized the intensity of stimulation by assessing resting motor threshold and TMS intensity required to produce a 1-mV motor-evoked potential; this procedure is expected to adjust for cortical atrophy. Furthermore, our measure of plasticity (ie, PAS-LTP) is a ratio of post-PAS to pre-PAS cortical-evoked activity, which controls for baseline cortical-evoked activity. Fourth, to remove the TMS artifact, we excluded early TMS-evoked activity (first 50 milliseconds), which could have excluded early glutamate-mediated activity.106,107
We found that older patients with AD have impaired DLPFC plasticity compared with healthy older individuals, and impaired DLPFC plasticity is associated with impairment in working memory. Improving our understanding of the association between DLPFC plasticity and working memory may advance our understanding of neurophysiologic mechanisms underlying working memory deficits in AD. Ultimately, this process may lead to novel treatment interventions to treat or prevent the cognitive deficits of AD. Future studies are now needed to further define the association of DLPFC plasticity with other biomarkers from functional brain imaging, amyloid and tau brain imaging, peripheral and central neurotransmitter studies, and postmortem pathologic studies. Finally, longitudinal studies of DLPFC plasticity in response to treatment interventions are required to demonstrate its relevance as a treatment target in AD and related disorders.
Corresponding Author: Tarek K. Rajji, MD, Centre for Addiction and Mental Health, Geriatric Psychiatry Division, 80 Workman Way, Toronto, ON M6J 1H4, Canada (tarek.rajji@camh.ca).
Accepted for Publication: September 4, 2017.
Published Online: October 25, 2017. doi:10.1001/jamapsychiatry.2017.3292
Author Contributions: Drs Kumar and Rajji had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Kumar, Blumberger, Daskalakis, Mulsant, Rajji.
Acquisition, analysis, or interpretation of data: Kumar, Zomorrodi, Ghazala, Goodman, Blumberger, Cheam, Fischer, Mulsant, Pollock, Rajji.
Drafting of the manuscript: Kumar, Rajji.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Kumar, Ghazala, Goodman, Cheam, Daskalakis, Rajji.
Obtained funding: Pollock, Rajji.
Administrative, technical, or material support: Kumar, Zomorrodi, Ghazala, Goodman, Blumberger, Daskalakis, Pollock, Rajji.
Study supervision: Blumberger, Fischer, Rajji.
Conflict of Interest Disclosures: Dr Blumberger reports receiving research support and in-kind equipment support for an investigator-initiated study from Brainsway, Ltd; serving as the site principal investigator for 3 sponsor-initiated studies for Brainsway, Ltd; receiving in-kind equipment support from Magventure, Inc, for an investigator-initiated study; and receiving medication supplies for an investigator-initiated trial from Indivior. Dr Fischer reports participating in peer-reviewed research involving a commercial device designed to treat Alzheimer disease manufactured by Vieight. Dr Daskalakis reports receiving research and equipment in-kind support for an investigator-initiated study through Brainsway, Ltd, and Magventure, Inc, in the past 3 years and receiving monies for participation on an advisory board from Sunovion, Inc. Dr Mulsant reports receiving current research support from HAPPYneuron (software used in a study funded by Brain Canada); receiving research support from Bristol-Myers Squibb (medications for a National Institutes of Health [NIH]–funded clinical trial), Eli Lilly and Company (medications for an NIH-funded clinical trial), and Pfizer (medications for an NIH-funded clinical trial) within the past 5 years; and directly owning stocks of General Electric (less than $5000). No other disclosures were reported.
Funding/Support: This study was supported by grant RR120070 from Weston Brain Institute (Dr Rajji); in part by the Canada Research Chairs program (Dr Rajji); research support from Canada Foundation for Innovation (Dr Rajji); a fellowship award from the Centre for Addiction and Mental Health (CAMH) (Dr Kumar); and in kind support from Temerty Centre for Therapeutic Brain Intervention at CAMH.
Role of the Funder/Sponsor: The sponsors did not have any role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
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