Type 2 diabetes mellitus (T2DM) alters brain function and manifests as brain atrophy. Intranasal insulin has emerged as a promising intervention for treatment of cognitive impairment. We evaluated the acute effects of intranasal insulin on resting-state brain functional connectivity in older adults with T2DM. This proof-of-concept, randomized, double-blind, placebo-controlled study evaluated the effects of a single 40 IU dose of insulin or saline in 14 diabetic and 14 control subjects. Resting-state functional connectivity between the hippocampal region and default mode network (DMN) was quantified using functional MRI (fMRI) at 3Tesla. Following insulin administration, diabetic patients demonstrated increased resting-state connectivity between the hippocampal regions and the medial frontal cortex (MFC) as compared with placebo (cluster size: right, P = 0.03) and other DMN regions. On placebo, the diabetes group had lower connectivity between the hippocampal region and the MFC as compared with control subjects (cluster size: right, P = 0.02), but on insulin, MFC connectivity was similar to control subjects. Resting-state connectivity correlated with cognitive performance. A single dose of intranasal insulin increases resting-state functional connectivity between the hippocampal regions and multiple DMN regions in older adults with T2DM. Intranasal insulin administration may modify functional connectivity among brain regions regulating memory and complex cognitive behaviors.

Type 2 diabetes mellitus (T2DM) accelerates brain aging that manifests as a widespread generalized atrophy (1) and earlier onset of dementia and Alzheimer disease (AD) (2). Aging, diabetes, and AD alter insulin transport and utilization in the brain (3). Central insulin is a neuromodulator involved in the key processes underlying cognition (4,5), energy homeostasis (6), synapse formation, and neuronal survival (7).

Intranasal insulin administration delivers insulin directly to the brain (8), and therefore intranasal insulin administration is emerging as a promising tool to deliver therapeutics to the brain tissue (9). Intranasal insulin increases regional perfusion (10,11) and improves cognition and memory (hippocampal function) in healthy young and older people (12,13), as well as in patients with cognitive impairment or mild AD (14).

Our proof-of-concept pilot study demonstrated that a single intranasal insulin dose of 40 IU acutely improved visuospatial memory in older people with T2DM and healthy control subjects (10). In patients with diabetes, better cognitive performance following intranasal insulin administration correlated with regional vasodilatation in the middle cerebral artery territory and in the insular cortex. Still, the mechanisms for insulin-related improvement of memory (hippocampal function) remain unclear. Functional MRI (fMRI) studies have led to the characterization of a network, termed the default mode network (DMN), that is activated during wakeful rest and deactivated during the performance of cognitive tasks (15,16). Numerous brain regions within the DMN have been linked to higher cognitive processes (i.e., language and memory), including the medial temporal lobe, the medial prefrontal cortex, anterior (ACC) and posterior cingulate cortex (PCC), and the medial, lateral, and inferior parietal cortex (IPC) (16,17). Older people with diabetes have worse functional connectivity among these regions, as compared with healthy control subjects, and the abnormal neuronal connectivity may precede clinical manifestations of brain atrophy and cognitive impairment (1820).

We hypothesized that intranasal insulin may acutely modify signaling between the hippocampus and the DMN regions that have been implicated in memory and cognitive processing. We acquired resting-state fMRI to identify functional connectivity between the hippocampus and DMN regions following the administration of intranasal insulin or placebo in older adults with and without T2DM.

Design

We conducted a pilot, randomized, double-bind, placebo-controlled study with crossover design of a single dose of intranasal insulin or sterile saline in T2DM and healthy older adults (FDA-IND 107690; www.clinicaltrials.gov NCT01206322). Details of the study protocol have been reported, and intranasal insulin administration was safe without affecting systemic glucose levels (10).

Subjects

The study was conducted at the Syncope and Falls in the Elderly (SAFE) Laboratory, the Center for Advanced MR Imaging, and the Clinical Research Center (CRC) at the Beth Israel Deaconess Medical Center (BIDMC). The protocol was approved by the BIDMC Committee on Clinical Investigation. Participants were recruited prospectively via advertisements in the local community. Diabetic participants were required to be diagnosed with T2DM for at least 5 years and treated with oral antidiabetic agents. Control subjects were required to be normotensive, have fasting blood glucose <100 mg/dL, and not be treated for any systemic disease. Of 262 participants who completed the phone screen, 64 were eligible and provided written informed consent. Twenty-nine participants completed the protocol, and data from 28 participants were included in the analyses: 14 diabetic (7 females, 61.7 ± 8.1 years) and 14 healthy subjects (10 females, 60.1 ± 9.9 years) (Table 1).

Table 1

Demographic characteristics of the diabetes and control groups

Diabetes (n = 14)Control (n = 14)P
Age (years) 61.7 ± 8.1 60.1 ± 9.9 0.7 
Sex (male/female) 8/6 4/10 NS 
Race (white/AA/Asian) 9/3/2 13/1/0  
Education (years) 14.1 ± 3.9 17.1 ± 3.2 0.03 
Diabetes duration (years) 11.6 ± 4.8   
HbA1c (%) 7.4 ± 1.5 5.6 ± 0.2 <0.0001 
HbA1c (mmol/mol) 58.4 ± 16.8 38 ± 1.95 <0.0001 
Fasting glucose 131.8 ± 30.1 87.9 ± 9.7 0.0004 
Systolic blood pressure (mmHg) 126.69 ± 13.8 125.5 ± 14.3 NS 
Diastolic blood pressure (mmHg) 73.2 ± 8.92 72.1 ± 10.9 NS 
Hyperlipidemia (yes/no) 9/5 2/12 0.005* 
Total cholesterol (mg/dL) 160.7 ± 37.0 213.1 ± 45.6 0.003 
Hypertension, n (%) 6 (8) N/A* 
MMSE 28.2 ± 1.7 28.8 ± 1.6 0.6* 
Hopkins Verbal Learning-Delayed Recall T Score 41.8 ± 9.1 54.5 ± 8.5 0.0018 
Trail-Making Part B T Score 37.6 ± 12.9 52.1 ± 11.5 0.004 
Global gray matter volume (cm3635.5 ± 29.0 691.3 ± 27.5 0.03 
Left hippocampus volume (cm35.92 ± 0.45 5.76 ± 0.47 0.59 
Right hippocampus volume (cm35.69 ± 0.43 5.62 ± 0.42 0.55 
Left MFC volume (cm321.2 ± 0.7 22.9 ± 1.0 0.08 
Right MFC volume (cm321.8 ± 0.9 23.3 ± 1.3 0.18 
Diabetes (n = 14)Control (n = 14)P
Age (years) 61.7 ± 8.1 60.1 ± 9.9 0.7 
Sex (male/female) 8/6 4/10 NS 
Race (white/AA/Asian) 9/3/2 13/1/0  
Education (years) 14.1 ± 3.9 17.1 ± 3.2 0.03 
Diabetes duration (years) 11.6 ± 4.8   
HbA1c (%) 7.4 ± 1.5 5.6 ± 0.2 <0.0001 
HbA1c (mmol/mol) 58.4 ± 16.8 38 ± 1.95 <0.0001 
Fasting glucose 131.8 ± 30.1 87.9 ± 9.7 0.0004 
Systolic blood pressure (mmHg) 126.69 ± 13.8 125.5 ± 14.3 NS 
Diastolic blood pressure (mmHg) 73.2 ± 8.92 72.1 ± 10.9 NS 
Hyperlipidemia (yes/no) 9/5 2/12 0.005* 
Total cholesterol (mg/dL) 160.7 ± 37.0 213.1 ± 45.6 0.003 
Hypertension, n (%) 6 (8) N/A* 
MMSE 28.2 ± 1.7 28.8 ± 1.6 0.6* 
Hopkins Verbal Learning-Delayed Recall T Score 41.8 ± 9.1 54.5 ± 8.5 0.0018 
Trail-Making Part B T Score 37.6 ± 12.9 52.1 ± 11.5 0.004 
Global gray matter volume (cm3635.5 ± 29.0 691.3 ± 27.5 0.03 
Left hippocampus volume (cm35.92 ± 0.45 5.76 ± 0.47 0.59 
Right hippocampus volume (cm35.69 ± 0.43 5.62 ± 0.42 0.55 
Left MFC volume (cm321.2 ± 0.7 22.9 ± 1.0 0.08 
Right MFC volume (cm321.8 ± 0.9 23.3 ± 1.3 0.18 

Between-group comparisons, ANOVA, unadjusted. Data are mean ± SD.

*Pearson χ2 test, inclusion criteria: normotensive control subjects. AA, African American.

*LS model adjusted for education years, race.

Thirty-six participants were excluded for the following reasons: consent withdrawal (n = 7), diagnosis of DM <5 years (n = 3), insulin treatment (n = 1), intranasal medication (n = 1), abnormal laboratory results (n = 3), control subjects with HbA1c >6% (n = 4), uncontrolled hypertension (n = 4), subthreshold Mini–Mental State Exam (MMSE) scores (≤24 on age-adjusted norms) (n = 2), psychiatric disorder (n = 1), brain biopsy surgery (n = 1), substance abuse (n = 1), MRI-incompatible stents (n = 1), hypoglycemic episodes during home monitoring (n = 2), health care provider disapproval (n = 1), lost to follow-up (n = 3), and poor fMRI data quality due to motion artifacts (n = 1).

On-site screening included the following: fasting laboratory chemistries, electrocardiogram, vital signs, detailed medical history and medication review, and anthropometric measurements. One control participant was excluded after randomization because of high blood pressure, and one subject’s data were excluded from analyses due to motion artifacts on the MRI scan. All other exclusions occurred before randomization during the screening phase. Glycemic control and other prescribed medications were taken during the study but were held in the morning before the intervention, MRI, and cognitive testing. Medications were administered at a usual dose after the completion of these procedures on days 2 and 3. Participants had current prescriptions of one or more medications: glycemic control agents (biguanides [metformin, n = 11], sulfonylureas [glyburide, n = 4; glipizide, n = 2], and thiazolidinediones [pioglitazone, n = 2]), antihypertensives (β blockers, n = 5), angiotensin II receptor blockers (n = 3), ACE inhibitors (n = 4), statins (n = 10; control subjects, n = 0), and hormone replacement (control subjects, n = 1). Women were required to be postmenopausal.

Protocol

Studies were conducted at the BIDMC CRC. On CRC admission day 1, participants completed a baseline cognitive assessment. On days 2 and 3, protocols included safety monitoring for glucose and cardiovascular vital signs, insulin/placebo administration, anatomical and resting-state fMRI, and cognitive assessment. Resting-state fMRI was performed 26.5 ± 9.3 min after intranasal insulin administration. Vitals signs were also monitored during MRI using a Medrad Veris MR Vital Signs Monitor (Warrendale, PA).

Insulin/Placebo Administration

Each participant was treated with 40 IU insulin (Novolin; Novo Nordisk) or sterile saline in a random order on days 2 and 3 using a ViaNase device (Kurve Technologies, Inc.). Insulin administration contained 40 IU insulin mixed with 0.4 mL saline and an additional residual volume of 0.66 mL (30 IU insulin mixed with 0.33 mL saline). The placebo contained an equivalent volume of sterile saline.

Anatomical and fMRI

Anatomical and functional studies were performed on a 3Tesla GE HDx MRI scanner (GE Medical Systems, Milwaukee, WI) using the three-dimensional magnetization-prepared rapid gradient echo (MP-RAGE) (repetition time = 6.6 ms, echo time = 2.8 ms, flip angle = 15°, bandwidth = 31.25 kHz, field of view = 24, slice thickness = 3 mm, 52 slices, matrix = 192 × 256). Resting-state functional images were collected over a 5-min period using a gradient-echo planar imaging pulse sequence sensitive to blood oxygenation level–dependent (BOLD) contrast (repetition time = 3,000 ms, echo time = 27 ms, flip angle = 60°, field of view = 25, slice thickness = 5 mm, 30 slices, matrix = 64 × 64, number of excitations = 1).

Neuropsychological Assessment

Baseline assessment (day 1) included the MMSE and measures of verbal learning (Hopkins Verbal Learning Test [HVLT]-Revised) and executive function (Trail-Making Tests A and B, Digit Span). Cognitive assessment on insulin versus placebo (days 2 and 3) was performed after MRI scan and had to be completed within 2 h after drug administration because of insulin pharmacokinetics (8,21,22). These assessments included a brief battery of parallel versions of the Brief Visuospatial Memory Test-Revised (BVMT-R) and the Verbal Fluency Task (timed word generation using letters [FAS], category, and switching conditions) of the Delis-Kaplan Executive Function System assessment (23,24).

Statistical Analyses

Statistical parametric mapping (SPM8, Wellcome Department of Cognitive Neurology, London, U.K., www.fil.ion.ucl.ac.uk/spm) was used to preprocess the raw fMRI data, and resting-state fMRI data analysis (REST V1.8, www.restfmri.net) was used for the network correlation analysis.

The first two volumes of the scanning session were discarded to allow for T1 equilibration effects. The remaining images were corrected for timing differences between each slice using Fourier interpolation. The images were then corrected for motion effects, where the first volume of the scanning session was designated as the reference volume. One participant with head motion >2.0 mm maximum displacement in any direction of x, y, and z or 2.0 degree of any angular motion throughout the course of the scan was excluded from the analyses. The mean EPI images were coregistered to the T1 images. Coregistered T1 images were normalized to the Montreal Neurological Institute Atlas via SPM 8 tools. The resulting images were smoothed with a Gaussian kernel of 6 mm × 6 mm × 6 mm (full-width half-maximum). Linear trends were removed from the image time series, and data were band-pass filtered at 0.01–0.08 Hz.

A hypothesis-driven regions of interest approach was used to investigate the hippocampus and parahippocampus (hippocampal region) using the regions of interest from the Wake Forest University PickAtlas (25). Bilateral hippocampus and parahippocampus were selected as seed regions, and the correlations of time course between seed regions and the whole brain were calculated in a voxel-wise manner for each subject and condition (e.g., DM-insulin, DM-placebo, control-insulin, control-placebo). The Fisher transformation (r-to-z transformation) was used to normalize distribution of the Pearson correlation coefficient values (r) to standard z scores to represent the strength of connectivity (26). One-sample Student t tests (uncorrected, voxels with P < 1 × 10−9 and cluster size ≥270 mm3) were used to determine brain regions with significant connectivity to the seed regions in each state. Connectivity maps were compared between the insulin and placebo condition for each subject using a paired Student t test. Two-sample Student t tests were used to compare the diabetes and control groups. The threshold was corrected with Alphasim (AFNI, Bethesda, MD, http://afni.nimh.nih.gov/afni/) in paired and two-sample Student t tests (P < 0.05; minimum cluster size was set to 270 mm3).

Performances on the BVMT-R were reported as age-adjusted T scores for the total learning score across the three immediate recall trials (Total Recall) and delayed recall (Delayed Recall). Performances on the FAS, category, and switching verbal fluency trials were also reported as age- and education-adjusted T scores. Composite general cognitive function scores were calculated as average T scores.

Least square (LS) models were used to evaluate the relationships between fMRI measures (regional z scores) and cognitive measures (verbal fluency and BVMT-R, as dependent variables) with age and sex as model effects. A LS model for MMSE was adjusted for education years and race. LS models were calculated separately within group and condition (e.g., diabetes group on insulin) for each variable to minimize the effects of multiple comparisons. Conservatively, we selected models with R2 >0.25 and P < 0.05, and we present R2adj adjusted for model covariates. Nominal observed P values are reported without adjustment for multiple testing in this small proof-of-concept study.

Demographic and Baseline Characteristics

Demographic group characteristics were similar (Table 1), but diabetic subjects had lower global gray matter volume (P = 0.03), fewer years of education (P = 0.03), and worse executive function (P = 0.004) and verbal memory (P = 0.002). Hippocampal volumes were similar between the groups.

Resting-State Connectivity

Multiple regions within the DMN exhibited functional connectivity to the right and left hippocampal regions. Figure 1A–F depicts a summary of the DMN regions that were significantly correlated (voxels with |t| ≥15.4, cluster size ≥270 mm3) to bilateral hippocampal regions following intranasal insulin and placebo administration in the diabetes group (Fig. 1A and B) and control subjects (Fig. 1D and E).

Figure 1

Resting-state functional network regions (MFC, PCC, IPC, and ACC) with significant connectivity (voxels with |t| ≥15.4, cluster size ≥270 mm3, and P < 1 × 10−9) to the right and left hippocampus in the diabetes and the control groups after intranasal insulin and placebo administration. A: Diabetes group, intranasal insulin administration. B: Diabetes group, placebo administration. C: Diabetes group, differences in functional connectivity between insulin and placebo administration. Intranasal insulin administration was associated with increased connectivity between hippocampal regions and MFC, R-IPC, and PCC, as compared with placebo (paired Student t test, voxel corrected within subject comparisons, cluster size ≥270 mm3, P < 0.05). D: Age-matched healthy control subjects, intranasal insulin administration. E: Control group, placebo administration. F: Control group, differences in functional connectivity between insulin and placebo administration.

Figure 1

Resting-state functional network regions (MFC, PCC, IPC, and ACC) with significant connectivity (voxels with |t| ≥15.4, cluster size ≥270 mm3, and P < 1 × 10−9) to the right and left hippocampus in the diabetes and the control groups after intranasal insulin and placebo administration. A: Diabetes group, intranasal insulin administration. B: Diabetes group, placebo administration. C: Diabetes group, differences in functional connectivity between insulin and placebo administration. Intranasal insulin administration was associated with increased connectivity between hippocampal regions and MFC, R-IPC, and PCC, as compared with placebo (paired Student t test, voxel corrected within subject comparisons, cluster size ≥270 mm3, P < 0.05). D: Age-matched healthy control subjects, intranasal insulin administration. E: Control group, placebo administration. F: Control group, differences in functional connectivity between insulin and placebo administration.

In the diabetes group, insulin increased connectivity between the medial frontal cortex (MFC), right (R)-IPC, PCC, and ACC and hippocampal regions, as compared with placebo (Fig. 1A–C and Table 2). The threshold was set at P < 0.05, voxel corrected; a minimum cluster size = 270 mm3.

Table 2

Insulin vs. placebo connectivity within diabetes and control groups

Brain regionBrodmann areaCluster size (mm3)
Average t value
Peak t value
DiabetesControlDiabetesControlDiabetesControl
MFC 8//9 8,073 3,321 3.33 3.17 6.78 5.85 
R-IPC 40 2,214 NS 3.33 NS 5.85 NS 
PCC 23//31 1,404 1,188 3.49 2.84 5.53 4.17 
ACC 24 4,752 972 3.22 3.13 6.34 5.28 
Brain regionBrodmann areaCluster size (mm3)
Average t value
Peak t value
DiabetesControlDiabetesControlDiabetesControl
MFC 8//9 8,073 3,321 3.33 3.17 6.78 5.85 
R-IPC 40 2,214 NS 3.33 NS 5.85 NS 
PCC 23//31 1,404 1,188 3.49 2.84 5.53 4.17 
ACC 24 4,752 972 3.22 3.13 6.34 5.28 

Comparisons of connectivity between hippocampal regions and DMN regions in both hemispheres between insulin and placebo conditions in the diabetes and the control groups. Paired Student t tests were used to compare insulin vs. placebo conditions within the diabetes and control groups, |t| >2.16 (Alphasim corrected P < 0.05).

Similarly, in the control group, insulin increased connectivity in the MFC, PCC, and ACC (Fig. 1D–F and Table 2). Table 2 shows all regions connected to the right or left hippocampal regions.

In addition, we calculated the strength of ipsilateral connections and an average regional cluster size for each subject, and compared the insulin and placebo conditions within each group (Table 3). In the diabetes group, insulin administration increased the average cluster size within the MFC that was functionally connected to the right hippocampal region, as compared with placebo (P = 0.03). Following insulin administration, as compared with placebo, we also observed a trend toward an increase in cluster size within the left MFC that was functionally connected to the left hippocampal region (P = 0.06). The correlation between the right hippocampal region and the R-IPC also increased on insulin as compared with placebo (z value P = 0.03). The group average peak z value range for all regions was 0.76–1.69 following insulin administration and 0.71–1.55 following administration of the placebo.

Table 3

Insulin vs. placebo connectivity within diabetes and control groups

Diabetes groupBrodmann areaCluster size (mm3)Peak z valueP value Insulin vs. placeboInsulin P value DM vs. control
InsulinPlaceboInsulinPlaceboCluster sizez valueCluster sizez value
Brain region          
 Left hippocampal regions          
  MFC 8//9 4,900.5 ± 3,617.6 3,276.6 ± 2,703.2 0.97 ± 0.17 0.91 ± 0.23 0.06 0.16 0.18 0.48 
  L-IPC 39 345.2 ± 249.3 403.1 ± 318.8 1.65 ± 0.58 1.55 ± 0.78 0.21 0.3 0.11 0.47 
  R-IPC 40 779.8 ± 736.9 509.1.3 ± 636.0 0.76 ± 0.21 0.68 ± 0.21 0.095 0.096 0.31 0.29 
  PCC 23//31 1,824.4 ± 744.3 1,419.4 ± 1,060.3 1.07 ± 0.27 0.94 ± 0.33 0.32 0.38 0.49 0.27 
  ACC 24 2,009.6 ± 1,664.0 1,492.7 ± 1,289.3 0.91 ± 0.22 0.87 ± 0.24 0.24 0.40 0.35 0.26 
 Right hippocampal regions          
  MFC 8//9 4,142.6 ± 3,857.0 2,684.6 ± 2,675.1 0.95 ± 0.24 0.90 ± 0.24 0.03 0.24 0.42 0.46 
  L-IPC 39 331.7 ± 278.9 435.9 ± 299.5 1.61 ± 0.85 1.69 ± 0.89 0.13 0.36 0.13 0.39 
  R-IPC 40 935.4 ± 825.5 779.1 ± 682.6 0.82 ± 0.25 0.71 ± 0.19 0.17 0.033 0.23 0.33 
  PCC 23//31 1,982.6 ± 809.8 1,776.2 ± 830.9 1.21 ± 0.27 1.11 ± 0.28 0.44 0.46 0.22 0.12 
  ACC 24 1,776.2 ± 1,496.8 1,018.3 ± 1,247.0 0.91 ± 0.23 0.79 ± 0.21 0.17 0.15 0.39 0.48 
Control group        Placebo 
       DM vs. control 
Brain region          
 Left hippocampal regions          
  MFC 8//9 6,665.1 ± 5,254.0 5,575.5 ± 4,496.5 0.97 ± 0.24 0.97 ± 0.22 0.10 0.16 0.058 0.24 
  L-IPC 39 439.7 ± 131.6 468.6 ± 99.3 1.67 ± 0.65 1.64 ± 0.47 0.21 0.44 0.24 0.35 
  R-IPC 40 636.4 ± 764.0 501.4 ± 734.9 0.71 ± 0.29 0.64 ± 0.28 0.31 0.29 0.33 0.28 
  PCC 23//31 1,695.2 ± 923.4 1,147.5 ± 1,026.2 0.98 ± 0.27 0.87 ± 0.30 0.017 0.052 0.099 0.17 
  ACC 24 2,131.1 ± 1,670.4 1,886.1 ± 1,925.9 0.95 ± 0.23 0.90 ± 0.25 0.24 0.056 0.40 0.42 
 Right hippocampal regions          
  MFC 8//9 5,402.0 ± 4,961.7 5,691.2 ± 4,349.1 0.93 ± 0.25 0.94 ± 0.23 0.23 0.44 0.019 0.31 
  L-IPC 39 428.1 ± 131.4 459 ± 100.0 1.69 ± 0.69 1.65 ± 0.46 0.2 0.42 0.39 0.44 
  R-IPC 40 709.7 ± 784.4 692.4 ± 778.9 0.78 ± 0.24 0.73 ± 0.26 0.24 0.24 0.19 0.38 
  PCC 23//31 1,675.9 ± 755.6 1,373.1 ± 1,008.9 1.06 ± 0.29 1.00 ± 0.31 0.19 0.29 0.047 0.09 
  ACC 24 1,807.1 ± 1,690.2 1,940.1 ± 1,786.3 0.88 ± 0.22 0.88 ± 0.28 0.40 0.098 0.15 0.33 
Diabetes groupBrodmann areaCluster size (mm3)Peak z valueP value Insulin vs. placeboInsulin P value DM vs. control
InsulinPlaceboInsulinPlaceboCluster sizez valueCluster sizez value
Brain region          
 Left hippocampal regions          
  MFC 8//9 4,900.5 ± 3,617.6 3,276.6 ± 2,703.2 0.97 ± 0.17 0.91 ± 0.23 0.06 0.16 0.18 0.48 
  L-IPC 39 345.2 ± 249.3 403.1 ± 318.8 1.65 ± 0.58 1.55 ± 0.78 0.21 0.3 0.11 0.47 
  R-IPC 40 779.8 ± 736.9 509.1.3 ± 636.0 0.76 ± 0.21 0.68 ± 0.21 0.095 0.096 0.31 0.29 
  PCC 23//31 1,824.4 ± 744.3 1,419.4 ± 1,060.3 1.07 ± 0.27 0.94 ± 0.33 0.32 0.38 0.49 0.27 
  ACC 24 2,009.6 ± 1,664.0 1,492.7 ± 1,289.3 0.91 ± 0.22 0.87 ± 0.24 0.24 0.40 0.35 0.26 
 Right hippocampal regions          
  MFC 8//9 4,142.6 ± 3,857.0 2,684.6 ± 2,675.1 0.95 ± 0.24 0.90 ± 0.24 0.03 0.24 0.42 0.46 
  L-IPC 39 331.7 ± 278.9 435.9 ± 299.5 1.61 ± 0.85 1.69 ± 0.89 0.13 0.36 0.13 0.39 
  R-IPC 40 935.4 ± 825.5 779.1 ± 682.6 0.82 ± 0.25 0.71 ± 0.19 0.17 0.033 0.23 0.33 
  PCC 23//31 1,982.6 ± 809.8 1,776.2 ± 830.9 1.21 ± 0.27 1.11 ± 0.28 0.44 0.46 0.22 0.12 
  ACC 24 1,776.2 ± 1,496.8 1,018.3 ± 1,247.0 0.91 ± 0.23 0.79 ± 0.21 0.17 0.15 0.39 0.48 
Control group        Placebo 
       DM vs. control 
Brain region          
 Left hippocampal regions          
  MFC 8//9 6,665.1 ± 5,254.0 5,575.5 ± 4,496.5 0.97 ± 0.24 0.97 ± 0.22 0.10 0.16 0.058 0.24 
  L-IPC 39 439.7 ± 131.6 468.6 ± 99.3 1.67 ± 0.65 1.64 ± 0.47 0.21 0.44 0.24 0.35 
  R-IPC 40 636.4 ± 764.0 501.4 ± 734.9 0.71 ± 0.29 0.64 ± 0.28 0.31 0.29 0.33 0.28 
  PCC 23//31 1,695.2 ± 923.4 1,147.5 ± 1,026.2 0.98 ± 0.27 0.87 ± 0.30 0.017 0.052 0.099 0.17 
  ACC 24 2,131.1 ± 1,670.4 1,886.1 ± 1,925.9 0.95 ± 0.23 0.90 ± 0.25 0.24 0.056 0.40 0.42 
 Right hippocampal regions          
  MFC 8//9 5,402.0 ± 4,961.7 5,691.2 ± 4,349.1 0.93 ± 0.25 0.94 ± 0.23 0.23 0.44 0.019 0.31 
  L-IPC 39 428.1 ± 131.4 459 ± 100.0 1.69 ± 0.69 1.65 ± 0.46 0.2 0.42 0.39 0.44 
  R-IPC 40 709.7 ± 784.4 692.4 ± 778.9 0.78 ± 0.24 0.73 ± 0.26 0.24 0.24 0.19 0.38 
  PCC 23//31 1,675.9 ± 755.6 1,373.1 ± 1,008.9 1.06 ± 0.29 1.00 ± 0.31 0.19 0.29 0.047 0.09 
  ACC 24 1,807.1 ± 1,690.2 1,940.1 ± 1,786.3 0.88 ± 0.22 0.88 ± 0.28 0.40 0.098 0.15 0.33 

Comparisons of connectivity between right and left hippocampal regions and DMN regions in both hemispheres between insulin and placebo conditions within each group, and between the groups. Paired and two-tailed Student t test. L-IPC, left inferior parietal cortex.

In the control group, insulin administration increased the average cluster size within the left PCC that was functionally connected to the left hippocampal region, as compared with placebo (P = 0.017; z value P = 0.056). Correlations between the left ACC and the left hippocampus also tended to be stronger (z value P = 0.056). The group average peak z value range for all regions was for insulin 0.71–1.69 and for placebo 0.73–1.64.

Figure 2 maps the differences between the diabetes and the control groups after insulin (Fig. 2A) and placebo (Fig. 2B) administration. After insulin administration, the diabetes group still had worse functional connectivity in the MFC as compared with healthy control subjects (Fig. 2A), but these differences were less prominent than after the placebo administration (Fig. 2B) (the threshold was set as Alphasim corrected P < 0.05; a minimum cluster extent = 270 mm3).

Figure 2

Differences in connectivity between the diabetes and the control groups after insulin (A) and placebo administration (B). After insulin administration, diabetic subjects had lower functional connectivity only in MFC as compared with control subjects. B: After placebo administration, diabetic subjects had larger areas or lower functional connectivity in multiple regions; the threshold was set as P < 0.05, a minimum cluster extent = 270 mm3 (corrected).

Figure 2

Differences in connectivity between the diabetes and the control groups after insulin (A) and placebo administration (B). After insulin administration, diabetic subjects had lower functional connectivity only in MFC as compared with control subjects. B: After placebo administration, diabetic subjects had larger areas or lower functional connectivity in multiple regions; the threshold was set as P < 0.05, a minimum cluster extent = 270 mm3 (corrected).

Ipsilateral comparisons indicated that after placebo administration, the diabetes group had a smaller cluster of voxels within the MFC that was functionally connected with the right hippocampus, as compared with control subjects (47% decrease; P = 0.019; z value P = 0.31). A similar trend was also observed for the connectivity between the MFC and the left hippocampus (58% reduction; P = 0.058; z value P = 0.24). However, the diabetes group had a larger cluster of connectivity between the right hippocampus and the PCC as compared with control subjects (29% increase; P = 0.047; z value P = 0.09), and a similar trend was observed for increased connectivity between the PCC and the left hippocampus (23% increase; P = 0.1; z value P = 0.17).

After insulin administration, the cluster size differences between the diabetes and the control groups decreased by 44% in the MFC and by 95% in the ACC.

Resting-State Connectivity and Cognition

Performances on verbal fluency and visuospatial memory (BVMT-R) tasks after insulin administration tended to be higher than on-placebo performances, and control subjects on insulin performed better than diabetic participants on insulin on FAS, switching, and composite verbal fluency, and BVMT-R T1–T3 trials and Total Recall (10).

In diabetic subjects on insulin, better performance on the verbal fluency category (naming all words in the same semantic category) was associated with stronger average connectivity (z value) between the right hippocampal region and the ACC (R2adj = 0.28; P = 0.02) (Fig. 3A and B). Verbal fluency category switching was associated with lower connectivity coefficient between the left hippocampal region and the MFC (R2adj = 0.43; P = 0.04) but not with cluster size. In control subjects on insulin, better scores on BVMT-R Delayed Recall tended to be associated with stronger average connectivity between the left hippocampal region and the PCC (R2adj = 0.41; P = 0.07).

Figure 3

The relationship between functional connectivity measures and cognitive performance in the diabetes group after insulin and placebo administration. After insulin administration (A), the average coefficient of connectivity between the right hippocampus and ACC was associated with better verbal fluency score, but not after placebo administration (B). Brief visuospatial memory learning T score showed a positive trend with coefficient connectivity between right hippocampus and R-IPC after insulin administration (C) and a strong negative association after placebo administration (D).

Figure 3

The relationship between functional connectivity measures and cognitive performance in the diabetes group after insulin and placebo administration. After insulin administration (A), the average coefficient of connectivity between the right hippocampus and ACC was associated with better verbal fluency score, but not after placebo administration (B). Brief visuospatial memory learning T score showed a positive trend with coefficient connectivity between right hippocampus and R-IPC after insulin administration (C) and a strong negative association after placebo administration (D).

In diabetic subjects on placebo, BVMT-R Total Recall scores were associated with lower average coefficients of connectivity between the left hippocampal region and the ACC (R2adj = 0.45; P = 0.04), and the lower connectivity with the R-IPC (R2adj = 0.44; P = 0.03) (LS models were adjusted for age and sex). BVMT-R learning T scores were also associated with lower average coefficients of connectivity between the right hippocampal region and the IPC (R2adj = 0.60; P = 0.01) (Fig. 3C and D).

In control subjects on placebo, composite general cognitive function scores were also associated with lower average coefficients of connectivity between the right hippocampal region and the IPC (R2adj = 0.74; P = 0.007) (LS models adjusted for age and sex). HVLT-Recall T score was negatively associated with average connectivity (R2adj = 0.84; P = 0.01) and voxel size (R2adj = 0.84; P = 0.01) between the right hippocampus and the MFC and also between the left hippocampus and the MFC (R2adj = 0.81; P = 0.02), PCC (R2adj = 0.73; P = 0.04), and R-IPC (R2adj = 0.72; P = 0.04). These relationships were not observed after insulin administration in the diabetes and control groups.

Resting-State Connectivity and Glycemic Control

There was no significant relationship between HbA1c and resting-state connectivity after insulin administration. In the control group, after placebo administration, HbA1c was associated with stronger connectivity between the right and the left hippocampus and R-IPC (R2adj = 0.76; P = 0.03).

This study demonstrated that in diabetic and age-matched healthy subjects, intranasal administration of a single dose of insulin acutely increased resting-state functional connectivity between the hippocampal regions and multiple regions within the DMN (i.e., MFC, IPC, ACC, and PCC) that are linked to integrative higher cognitive functions. After placebo administration, connectivity between hippocampal regions and these DMN regions was lower in diabetic subjects as compared with healthy control subjects in several brain regions. After insulin administration, the cluster size differences between the diabetes and the control groups decreased by 44% in the MFC and by 95% in the ACC. After administration of intranasal insulin, the differences in functional connectivity between the diabetes and control groups were no longer significant.

These findings suggest that acute administration of insulin via intranasal delivery route may improve functional connections between brain regions involved in memory and cognitive processing in other domains.

The insulin resistance syndrome is associated with reduced brain insulin levels and sensitivity in age-related memory impairment and AD (5,2729). Brain insulin plays an important role as a neuromodulator in cognition (4,5), energy homeostasis, food intake, sympathetic activity, neuron-astrocyte signaling, synapse formation, and neuronal survival (7,30). Insulin has been shown to reinforce signaling in the dopamine-mediated brain reward system and modulate food intake and responses to reward stimuli (3133). Intranasal insulin increases rapidly in cerebrospinal fluid and binds to insulin receptors (34,35) in the olfactory bulb, several regions in the cerebral cortex including the autonomic network (e.g., insular cortex, dorsal root ganglia, nigro-striatal neurons), cerebellum (3638), hypothalamus, and hippocampus (34,35,39).

T2DM is associated with impairment of hippocampus-dependent memory, and these effects are proportional to diabetes severity (2). Resting-state functional connectivity is also altered in T2DM subjects, and the severity of impairment correlates with the degree of insulin resistance (18,19). The effects of intranasal insulin on resting-state connectivity have not been studied. Diabetic subjects had worse baseline cognitive performance, especially in the memory and executive function domains. We have previously shown, in this cohort, that intranasal insulin may acutely improve visuospatial memory in older diabetic and healthy adults, and that this improvement of memory and verbal learning may be dependent upon vasodilation response in the middle cerebral artery territory and in particular insular cortex (10). In diabetic subjects on insulin, better performance on the verbal fluency naming task was associated with stronger coefficient of connectivity between the right hippocampal region and ACC and lesser connectivity between the left hippocampal regions and the MFC for a more difficult category switching task. In control subjects on insulin, better performance on the visuospatial memory task (BVMT-R) tended to correlate with stronger connectivity between the left hippocampal region and PCC. Differences in relationships between cognition and connectivity between the right and left hippocampal regions are intriguing and reflect a complexity of the large-scale verbal fluency network that comprises of verbal fluency and orthographic discrimination subnetworks (40). Set switching is a complex operation involving a number of different brain structures that usually include various parts of the dorsolateral and dorsomedial prefrontal cortex, as well as temporal regions where hippocampus is located (41). Functional integration within the verbal fluency network declines with age and task difficulty. Low productive-difficult tasks are associated with significant decreases in connectivity. Therefore, the decreased connectivity between the left hippocampus and DMN regions may reflect inhibition of the left hippocampus as a result of the complex category switching process (42). After placebo administration, we have observed a “deactivation pattern” (15,16) that is characterized by task-related decreases in activity and connectivity among several DMN regions. In other words, during a task, a better task-related performance is associated with a decrease in functional connectivity within DMN.

In diabetic subjects, the worse performance on BVMT-R task was associated with stronger functional connectivity between the hippocampal regions and the ACC and IPC. Similarly in the control groups, negative associations were found between the general cognitive score and verbal learning performance and connectivity between the hippocampal regions and the MFC, PCC, and IPC. It has been demonstrated using magnetoencephalography and a two-step hyperinsulimic clamp that resting-state activity correlates with insulin disposal (43). Furthermore, intranasal insulin may improve peripheral insulin sensitivity; insulin sensitization was associated with increased hypothalamic blood flow and parasympathetic heart rate variability (44,45). Intranasal insulin also diminished saliva cortisol and stress-induced responsiveness along the hypothalamus-pituitary axis (46,47). These findings may suggest that intranasal insulin administration may enhance functional connectivity between DMN and other brain regions and may modulate central autonomic responses to stress.

This pilot study has several limitations. The small sample size may have limited the ability to observe the full extent of functional connectivity. Cognitive testing was performed after completion of fMRI scan, and therefore we could not assess acute responses in functional connectivity to different cognitive tasks that may involve different brain regions and range of difficulty. Eleven of 14 diabetic participants were treated with metformin, which may be associated with worse cognitive performance (48). Women were required to be postmenopausal, and only one participant received hormone replacement therapy, which minimized potential effects of estrogen levels on functional connectivity (49). Furthermore, the optimal dose of intranasal insulin to modulate brain function remains unknown, as no dose-response studies have been completed to date within this population. Larger and/or more frequent doses may thus optimize the effects of intranasal insulin on brain function. Longer-term studies are also warranted to evaluate the potential for intranasal insulin for neuroprotection and improvement of cortical connectivity.

Conclusion

This study provided preliminary evidence that intranasal insulin may acutely increase functional connectivity between the hippocampal regions and the DMN in older adults with T2DM and age-matched healthy subjects. Furthermore, differences in postinsulin connectivity between diabetic and control subjects diminished. Cognitive performance on insulin was associated with regional changes in functional connectivity. Our findings provide insights into how intranasal insulin acutely modulates resting-state brain activity and its relationship to performance on higher cognitive tasks. Therefore, enhancement of functional connectivity may serve as a potential mechanism of acute intranasal insulin effect in the brain. However, larger prospective studies are needed to determine long-term safety and efficacy for prevention of cognitive decline in older people with T2DM.

See accompanying article, p. 687.

Clinical trial reg. no. NCT01206322, clinicaltrials.gov.

The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University and its affiliated academic health care centers, or the National Institutes of Health.

Acknowledgments. The authors acknowledge the contributions of the CRC nursing and MRI staffs.

Funding. Y.H. received grant support from China Scholarship Council (201206010220). B.M. received a KL2 Medical Research Investigator Training award (1KL2RR025757-04) from the Harvard Clinical and Translational Science Center (National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health award 8KL2-TR-000168-05). W.M. was also supported by the Translational Research Center for TBI and Stress Disorders (TRACTS), the VA Rehabilitation Research and Development Traumatic Brain Injury Center of Excellence (B6796-C), and VA Merit Review Award to Regina McGlinchey. V.N. has received grants from the National Institute of Diabetes and Digestive and Kidney Diseaseshttp://dx.doi.org/10.13039/100000062 (5R21-DK-084463-02) and the National Institute on Aginghttp://dx.doi.org/10.13039/100000049 (1R01-AG-0287601-A2) related to this study, and V.N., B.M., P.N., and W.M. received salaries from these grants. This work was conducted with support from Harvard Catalyst, the Harvard Clinical and Translational Science Center (National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health award 8UL1-TR-000170-05, and financial contributions from Harvard University and its affiliated academic health care centers). This work was also supported by the National Natural Science Foundation of China (NSFC 11372013).

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. H.Z. and Y.H. performed MRI analyses and contributed to manuscript preparation. B.M. contributed to study conduct and manuscript preparation. P.N. oversaw clinical aspects of the study. W.M. designed and oversaw cognitive testing and contributed to manuscript preparation. J.Z. and J.F. oversaw MRI analyses. V.N. designed the study and oversaw study conduct, data collection, analyses, and manuscript preparation. V.N. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation. This study was presented in poster form at the Annual Meeting of the International Society for Magnetic Resonance in Medicine, Milan, Italy, 10–16 May 2014, and at the 73rd Scientific Sessions of the American Diabetes Association, Chicago, IL, 21–25 June 2013.

1.
Franke
K
,
Gaser
C
,
Manor
B
,
Novak
V
.
Advanced BrainAGE in older adults with type 2 diabetes mellitus
.
Front Aging Neurosci
2013
;
5
:
90
[PubMed]
2.
Xu
WL
,
Qiu
CX
,
Wahlin
A
,
Winblad
B
,
Fratiglioni
L
.
Diabetes mellitus and risk of dementia in the Kungsholmen project: a 6-year follow-up study
.
Neurology
2004
;
63
:
1181
1186
[PubMed]
3.
Banks
WA
.
Brain meets body: the blood-brain barrier as an endocrine interface
.
Endocrinology
2012
;
153
:
4111
4119
[PubMed]
4.
Shemesh
E
,
Rudich
A
,
Harman-Boehm
I
,
Cukierman-Yaffe
T
.
Effect of intranasal insulin on cognitive function: a systematic review
.
J Clin Endocrinol Metab
2012
;
97
:
366
376
[PubMed]
5.
Freiherr
J
,
Hallschmid
M
,
Frey
WH
 2nd
, et al
.
Intranasal insulin as a treatment for Alzheimer’s disease: a review of basic research and clinical evidence
.
CNS Drugs
2013
;
27
:
505
514
[PubMed]
6.
Jauch-Chara
K
,
Friedrich
A
,
Rezmer
M
, et al
.
Intranasal insulin suppresses food intake via enhancement of brain energy levels in humans
.
Diabetes
2012
;
61
:
2261
2268
[PubMed]
7.
Plum
L
,
Belgardt
BF
,
Brüning
JC
.
Central insulin action in energy and glucose homeostasis
.
J Clin Invest
2006
;
116
:
1761
1766
[PubMed]
8.
Born
J
,
Lange
T
,
Kern
W
,
McGregor
GP
,
Bickel
U
,
Fehm
HL
.
Sniffing neuropeptides: a transnasal approach to the human brain
.
Nat Neurosci
2002
;
5
:
514
516
[PubMed]
9.
Chapman
CD
,
Frey
WH
 2nd
,
Craft
S
, et al
.
Intranasal treatment of central nervous system dysfunction in humans
.
Pharm Res
2013
;
30
:
2475
2484
[PubMed]
10.
Novak
V
,
Milberg
W
,
Hao
Y
, et al
.
Enhancement of vasoreactivity and cognition by intranasal insulin in type 2 diabetes
.
Diabetes Care
2014
;
37
:
751
759
[PubMed]
11.
Schilling
TM
,
Ferreira de Sá
DS
,
Westerhausen
R
, et al
.
Intranasal insulin increases regional cerebral blood flow in the insular cortex in men independently of cortisol manipulation
.
Hum Brain Mapp
2014
;
35
:
1944
1956
[PubMed]
12.
Benedict
C
,
Hallschmid
M
,
Hatke
A
, et al
.
Intranasal insulin improves memory in humans
.
Psychoneuroendocrinology
2004
;
29
:
1326
1334
[PubMed]
13.
Benedict
C
,
Hallschmid
M
,
Schultes
B
,
Born
J
,
Kern
W
.
Intranasal insulin to improve memory function in humans
.
Neuroendocrinology
2007
;
86
:
136
142
[PubMed]
14.
Craft
S
,
Baker
LD
,
Montine
TJ
, et al
.
Intranasal insulin therapy for Alzheimer disease and amnestic mild cognitive impairment: a pilot clinical trial
.
Arch Neurol
2012
;
69
:
29
38
[PubMed]
15.
Greicius
MD
,
Krasnow
B
,
Reiss
AL
,
Menon
V
.
Functional connectivity in the resting brain: a network analysis of the default mode hypothesis
.
Proc Natl Acad Sci U S A
2003
;
100
:
253
258
[PubMed]
16.
Greicius
MD
,
Supekar
K
,
Menon
V
,
Dougherty
RF
.
Resting-state functional connectivity reflects structural connectivity in the default mode network
.
Cereb Cortex
2009
;
19
:
72
78
[PubMed]
17.
Anticevic
A
,
Cole
MW
,
Murray
JD
,
Corlett
PR
,
Wang
XJ
,
Krystal
JH
.
The role of default network deactivation in cognition and disease
.
Trends Cogn Sci
2012
;
16
:
584
592
[PubMed]
18.
Musen
G
,
Jacobson
AM
,
Bolo
NR
, et al
.
Resting-state brain functional connectivity is altered in type 2 diabetes
.
Diabetes
2012
;
61
:
2375
2379
[PubMed]
19.
Chen
YC
,
Jiao
Y
,
Cui
Y
, et al
.
Aberrant brain functional connectivity related to insulin resistance in type 2 diabetes: a resting-state fMRI study
.
Diabetes Care
2014
;
37
:
1689
1696
[PubMed]
20.
Hoogenboom
WS
,
Marder
TJ
,
Flores
VL
, et al
.
Cerebral white matter integrity and resting-state functional connectivity in middle-aged patients with type 2 diabetes
.
Diabetes
2014
;
63
:
728
738
[PubMed]
21.
Benedict
C
,
Dodt
C
,
Hallschmid
M
, et al
.
Immediate but not long-term intranasal administration of insulin raises blood pressure in human beings
.
Metabolism
2005
;
54
:
1356
1361
[PubMed]
22.
Benedict
C
,
Kern
W
,
Schultes
B
,
Born
J
,
Hallschmid
M
.
Differential sensitivity of men and women to anorexigenic and memory-improving effects of intranasal insulin
.
J Clin Endocrinol Metab
2008
;
93
:
1339
1344
[PubMed]
23.
Benedict
RHB
,
Schretlen
D
,
Groninger
L
,
Dobraski
M
,
Sphritz
B
.
Revision of the Brief Visuospatial Memory Test: studies of normal performance, reliability and validity
.
Psychol Assess
1996
;
8
:
145
153
24.
Yeudall
LT
,
Fromm
D
,
Reddon
JR
,
Stefanyk
WO
.
Normative data stratified by age and sex for 12 neuropsychological tests
.
J Clin Psychol
1986
;
42
:
918
946
25.
Maldjian
JA
,
Laurienti
PJ
,
Kraft
RA
,
Burdette
JH
.
An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets
.
Neuroimage
2003
;
19
:
1233
1239
[PubMed]
26.
van Duinkerken
E
,
Schoonheim
MM
,
Sanz-Arigita
EJ
, et al
.
Resting-state brain networks in type 1 diabetic patients with and without microangiopathy and their relation to cognitive functions and disease variables
.
Diabetes
2012
;
61
:
1814
1821
[PubMed]
27.
Craft
S
.
Insulin resistance and cognitive impairment: a view through the prism of epidemiology
.
Arch Neurol
2005
;
62
:
1043
1044
[PubMed]
28.
Craft
S
.
Insulin resistance syndrome and Alzheimer’s disease: age- and obesity-related effects on memory, amyloid, and inflammation
.
Neurobiol Aging
2005
;
26
(
Suppl. 1
):
65
69
[PubMed]
29.
Messier
C
,
Teutenberg
K
.
The role of insulin, insulin growth factor, and insulin-degrading enzyme in brain aging and Alzheimer’s disease
.
Neural Plast
2005
;
12
:
311
328
[PubMed]
30.
Plum
L
,
Schubert
M
,
Brüning
JC
.
The role of insulin receptor signaling in the brain
.
Trends Endocrinol Metab
2005
;
16
:
59
65
[PubMed]
31.
Figlewicz
DP
.
Insulin, food intake, and reward
.
Semin Clin Neuropsychiatry
2003
;
8
:
82
93
[PubMed]
32.
Figlewicz
DP
,
Benoit
SC
.
Insulin, leptin, and food reward: update 2008
.
Am J Physiol Regul Integr Comp Physiol
2009
;
296
:
R9
R19
[PubMed]
33.
Stice
E
,
Figlewicz
DP
,
Gosnell
BA
,
Levine
AS
,
Pratt
WE
.
The contribution of brain reward circuits to the obesity epidemic
.
Neurosci Biobehav Rev
2013
;37:2047–2058
[PubMed]
34.
Thorne
RG
,
Pronk
GJ
,
Padmanabhan
V
,
Frey
WH
 2nd
.
Delivery of insulin-like growth factor-I to the rat brain and spinal cord along olfactory and trigeminal pathways following intranasal administration
.
Neuroscience
2004
;
127
:
481
496
[PubMed]
35.
Hanson
LR
,
Frey
WH
 2nd
.
Intranasal delivery bypasses the blood-brain barrier to target therapeutic agents to the central nervous system and treat neurodegenerative disease
.
BMC Neurosci
2008
;
9
(
Suppl. 3
):
S5
[PubMed]
36.
Hopkins
DF
,
Williams
G
.
Insulin receptors are widely distributed in human brain and bind human and porcine insulin with equal affinity
.
Diabet Med
1997
;
14
:
1044
1050
[PubMed]
37.
Albrecht
J
,
Wróblewska
B
,
Mossakowski
MJ
.
The binding of insulin to cerebral capillaries and astrocytes of the rat
.
Neurochem Res
1982
;
7
:
489
494
[PubMed]
38.
Banks
WA
.
The source of cerebral insulin
.
Eur J Pharmacol
2004
;
490
:
5
12
[PubMed]
39.
Abbott
MA
,
Wells
DG
,
Fallon
JR
.
The insulin receptor tyrosine kinase substrate p58/53 and the insulin receptor are components of CNS synapses
.
J Neurosci
1999
;
19
:
7300
7308
[PubMed]
40.
Marsolais
Y
,
Perlbarg
V
,
Benali
H
,
Joanette
Y
.
Age-related changes in functional network connectivity associated with high levels of verbal fluency performance
.
Cortex
2014
;
58
:
123
138
[PubMed]
41.
Baldo
JV
,
Schwartz
S
,
Wilkins
D
,
Dronkers
NF
.
Role of frontal versus temporal cortex in verbal fluency as revealed by voxel-based lesion symptom mapping
.
J Int Neuropsychol Soc
2006
;
12
:
896
900
[PubMed]
42.
Koch
I
,
Gade
M
,
Schuch
S
,
Philipp
AM
.
The role of inhibition in task switching: a review
.
Psychon Bull Rev
2010
;
17
:
1
14
[PubMed]
43.
Tschritter
O
,
Preissl
H
,
Hennige
AM
, et al
.
The cerebrocortical response to hyperinsulinemia is reduced in overweight humans: a magnetoencephalographic study
.
Proc Natl Acad Sci U S A
2006
;
103
:
12103
12108
[PubMed]
44.
Heni
M
,
Kullmann
S
,
Ketterer
C
, et al
.
Nasal insulin changes peripheral insulin sensitivity simultaneously with altered activity in homeostatic and reward-related human brain regions
.
Diabetologia
2012
;
55
:
1773
1782
[PubMed]
45.
Heni M, Wagner R, Kullmann S, et al. Central insulin administration improves whole-body insulin sensitivity via hypothalamus and parasympathetic outputs in men. Diabetes
2014
;
63
:
4083
4088
46.
Veer
IM
,
Oei
NY
,
Spinhoven
P
,
van Buchem
MA
,
Elzinga
BM
,
Rombouts
SA
.
Endogenous cortisol is associated with functional connectivity between the amygdala and medial prefrontal cortex
.
Psychoneuroendocrinology
2012
;
37
:
1039
1047
[PubMed]
47.
Bohringer
A
,
Schwabe
L
,
Richter
S
,
Schachinger
H
.
Intranasal insulin attenuates the hypothalamic-pituitary-adrenal axis response to psychosocial stress
.
Psychoneuroendocrinology
2008
;
33
:
1394
1400
[PubMed]
48.
Moore
EM
,
Mander
AG
,
Ames
D
, et al.;
AIBL Investigators
.
Increased risk of cognitive impairment in patients with diabetes is associated with metformin
.
Diabetes Care
2013
;
36
:
2981
2987
[PubMed]
49.
Ottowitz
WE
,
Siedlecki
KL
,
Lindquist
MA
,
Dougherty
DD
,
Fischman
AJ
,
Hall
JE
.
Evaluation of prefrontal-hippocampal effective connectivity following 24 hours of estrogen infusion: an FDG-PET study
.
Psychoneuroendocrinology
2008
;
33
:
1419
1425
[PubMed]