Sex similarities and dopaminergic differences in interval timing.

Rodent behavioral studies have largely focused on male animals, which has limited the generalizability and conclusions of neuroscience research. Working with humans and rodents, we studied sex effects during interval timing that requires participants to estimate an interval of several seconds by making motor responses. Interval timing requires attention to the passage of time and working memory for temporal rules. We found no differences between human females and males in interval timing response times (timing accuracy) or the coefficient of variance of response times (timing precision). Consistent with prior work, we also found no differences between female and male rodents in timing accuracy or precision. In female rodents, there was no difference in interval timing between estrus and diestrus cycle stages. Because dopamine powerfully affects interval timing, we also examined sex differences with drugs targeting dopaminergic receptors. In both female and male rodents, interval timing was delayed after administration of sulpiride (D2-receptor antagonist), quinpirole (D2-receptor agonist), and SCH-23390 (D1-receptor antagonist). By contrast, after administration of SKF-81297 (D1-receptor agonist), interval timing shifted earlier only in male rodents. These data illuminate sex similarities and differences in interval timing. Our results have relevance for rodent models of both cognitive function and brain disease by increasing representation in behavioral neuroscience. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Resting-state EEG measures cognitive impairment in Parkinson's disease.

Cognitive dysfunction is common in Parkinson's disease (PD). We developed and evaluated an EEG-based biomarker to index cognitive functions in PD from a few minutes of resting-state EEG. We hypothesized that synchronous changes in EEG across the power spectrum can measure cognition. We optimized a data-driven algorithm to efficiently capture these changes and index cognitive function in 100 PD and 49 control participants. We compared our EEG-based cognitive index with the Montreal cognitive assessment (MoCA) and cognitive tests across different domains from National Institutes of Health (NIH) Toolbox using cross-validations, regression models, and randomization tests. Finally, we externally validated our approach on 32 PD participants. We observed cognition-related changes in EEG over multiple spectral rhythms. Utilizing only 8 best-performing electrodes, our proposed index strongly correlated with cognition (MoCA: rho = 0.68, p value < 0.001; NIH-Toolbox cognitive tests: rho ≥ 0.56, p value < 0.001) outperforming traditional spectral markers (rho = -0.30-0.37). The index showed a strong fit in regression models (R2 = 0.46) with MoCA, yielded 80% accuracy in detecting cognitive impairment, and was effective in both PD and control participants. Notably, our approach was equally effective (rho = 0.68, p value < 0.001; MoCA) in out-of-sample testing. In summary, we introduced a computationally efficient data-driven approach for cross-domain cognition indexing using fewer than 10 EEG electrodes, potentially compatible with dynamic therapies like closed-loop neurostimulation. These results will inform next-generation neurophysiological biomarkers for monitoring cognition in PD and other neurological diseases.

Evoked mid-frontal activity predicts cognitive dysfunction in Parkinson's disease.

BACKGROUND: Cognitive dysfunction is a major feature of Parkinson's disease (PD), but the pathophysiology remains unknown. One potential mechanism is abnormal low-frequency cortical rhythms which engage cognitive functions and are deficient in PD. We tested the hypothesis that mid-frontal delta/theta rhythms predict cognitive dysfunction in PD. METHOD: We recruited 100 patients with PD and 49 demographically similar control participants who completed a series of cognitive control tasks, including the Simon, oddball and interval-timing tasks. We focused on cue-evoked delta (1-4 Hz) and theta (4-7 Hz) rhythms from a single mid-frontal EEG electrode (cranial vertex (Cz)) in patients with PD who were either cognitively normal, with mild-cognitive impairments (Parkinson's disease with mild-cognitive impairment) or had dementia (Parkinson's disease dementia). RESULTS: We found that PD-related cognitive dysfunction was associated with increased response latencies and decreased mid-frontal delta power across all tasks. Within patients with PD, the first principal component of evoked electroencephalography features from a single electrode (Cz) strongly correlated with clinical metrics such as the Montreal Cognitive Assessment score (r=0.34) and with National Institutes of Health Toolbox Executive Function score (r=0.46). CONCLUSIONS: These data demonstrate that cue-evoked mid-frontal delta/theta rhythms directly relate to cognition in PD. Our results provide insight into the nature of low-frequency frontal rhythms and suggest that PD-related cognitive dysfunction results from decreased delta/theta activity. These findings could facilitate the development of new biomarkers and targeted therapies for cognitive symptoms of PD.

Effects of Very Low- and High-Frequency Subthalamic Stimulation on Motor Cortical Oscillations During Rhythmic Lower-Limb Movements in Parkinson's Disease Patients.

BACKGROUND: Standard high-frequency deep brain stimulation (HF-DBS) at the subthalamic nucleus (STN) is less effective for lower-limb motor dysfunctions in Parkinson's disease (PD) patients. However, the effects of very low frequency (VLF; 4 Hz)-DBS on lower-limb movement and motor cortical oscillations have not been compared. OBJECTIVE: To compare the effects of VLF-DBS and HF-DBS at the STN on a lower-limb pedaling motor task and motor cortical oscillations in patients with PD and with and without freezing of gait (FOG). METHODS: Thirteen PD patients with bilateral STN-DBS performed a cue-triggered lower-limb pedaling motor task with electroencephalography (EEG) in OFF-DBS, VLF-DBS (4 Hz), and HF-DBS (120-175 Hz) states. We performed spectral analysis on the preparatory signals and compared GO-cue-triggered theta and movement-related beta oscillations over motor cortical regions across DBS conditions in PD patients and subgroups (PDFOG-and PDFOG+). RESULTS: Both VLF-DBS and HF-DBS decreased the linear speed of the pedaling task in PD, and HF-DBS decreased speed in both PDFOG-and PDFOG+. Preparatory theta and beta activities were increased with both stimulation frequencies. Both DBS frequencies increased motor cortical theta activity during pedaling movement in PD patients, but this increase was only observed in the PDFOG + group. Beta activity was not significantly different from OFF-DBS at either frequency regardless of FOG status. CONCLUSION: Results suggest that VL and HF DBS may induce similar effects on lower-limb kinematics by impairing movement speed and modulating motor cortical oscillations in the lower frequency band.

A Pilot Study of Ex Vivo Human Prefrontal RNA Transcriptomics in Parkinson's Disease.

Parkinson's disease (PD) can dramatically change cortical neurophysiology. The molecular basis for PD-related cortical changes is unclear because gene expression data are usually derived from postmortem tissue collected at the end of a complex disease and they profoundly change in the minutes after death. Here, we studied cortical changes in tissue from the prefrontal cortex of living PD patients undergoing deep-brain stimulation implantation surgery. We examined 780 genes using the NanoString nCounter platform and found that 40 genes were differentially expressed between PD (n = 12) and essential tremor (ET; n = 9) patients. One of these 40 genes, STAT1, correlated with intraoperative 4-Hz rhythms and intraoperative performance of an oddball reaction-time task. Using a pre-designed custom panel of 780 targets, we compared these intraoperative data with those from a separate cohort of fresh-frozen tissue from the same frontal region in postmortem human PD donors (n = 6) and age-matched neurotypical controls (n = 6). This cohort revealed 279 differentially expressed genes. Fifteen of the 40 intraoperative PD-specific genes overlapped with postmortem PD-specific genes, including CALB2 and FOXP2. Transcriptomic analyses identified pathway changes in PD that had not been previously observed in postmortem cases. These molecular signatures of cortical function and dysfunction may help us better understand cognitive and neuropsychiatric aspects of PD.

A pilot study of machine learning of resting-state EEG and depression in Parkinson's disease.

Introduction: Depression is a non-motor symptom of Parkinson's disease (PD). PD-related depression is difficult to diagnose, and the neurophysiological basis is poorly understood. Depression can markedly affect cortical function, which suggests that scalp electroencephalography (EEG) may be able to distinguish depression in PD. We conducted a pilot study of depression and resting-state EEG in PD. Methods: We recruited 18 PD patients without depression, 18 PD patients with depression, and 12 demographically similar non-PD patients with clinical depression. All patients were on their usual medications. We collected resting-state EEG in all patients and compared cortical brain signal features between patients with and without depression. We used a machine learning algorithm that harnesses the entire power spectrum (linear predictive coding of EEG Algorithm for PD: LEAPD) to distinguish between groups. Results: We found differences between PD patients with and without depression in the alpha band (8-13 Hz) globally and in the beta (13-30 Hz) and gamma (30-50 Hz) bands in the central electrodes. From two minutes of resting-state EEG, we found that LEAPD-based machine learning could robustly distinguish between PD patients with and without depression with 97 % accuracy and between PD patients with depression and non-PD patients with depression with 100 % accuracy. We verified the robustness of our finding by confirming that the classification accuracy gracefully declines as data are randomly truncated. Conclusions: Our results suggest that resting-state EEG power spectral analysis has the potential to distinguish depression in PD accurately. We demonstrated the efficacy of the LEAPD algorithm in identifying PD patients with depression from PD patients without depression and controls with depression. Our data provide insight into cortical mechanisms of depression and could lead to novel neurophysiological markers for non-motor symptoms of PD.

Novelty-induced frontal-STN networks in Parkinson's disease.

Novelty detection is a primitive subcomponent of cognitive control that can be deficient in Parkinson's disease (PD) patients. Here, we studied the corticostriatal mechanisms underlying novelty-response deficits. In participants with PD, we recorded from cortical circuits with scalp-based electroencephalography (EEG) and from subcortical circuits using intraoperative neurophysiology during surgeries for implantation of deep brain stimulation (DBS) electrodes. We report three major results. First, novel auditory stimuli triggered midfrontal low-frequency rhythms; of these, 1-4 Hz "delta" rhythms were linked to novelty-associated slowing, whereas 4-7 Hz "theta" rhythms were specifically attenuated in PD. Second, 32% of subthalamic nucleus (STN) neurons were response-modulated; nearly all (94%) of these were also modulated by novel stimuli. Third, response-modulated STN neurons were coherent with midfrontal 1-4 Hz activity. These findings link scalp-based measurements of neural activity with neuronal activity in the STN. Our results provide insight into midfrontal cognitive control mechanisms and how purported hyperdirect frontobasal ganglia circuits evaluate new information.

Neuromodulation of cognition in Parkinson's disease.

Neuromodulation is a widely used treatment for motor symptoms of Parkinson's disease (PD). It can be a highly effective treatment as a result of knowledge of circuit dysfunction associated with motor symptoms in PD. However, the mechanisms underlying cognitive symptoms of PD are less well-known, and the effects of neuromodulation on these symptoms are less consistent. Nonetheless, neuromodulation provides a unique opportunity to modulate motor and cognitive circuits while minimizing off-target side effects. We review the modalities of neuromodulation used in PD and the potential implications for cognitive symptoms. There have been some encouraging findings with both invasive and noninvasive modalities of neuromodulation, and there are promising advances being made in the field of therapeutic neuromodulation. Substantial work is needed to determine which modulation targets are most effective for the different types of cognitive deficits of PD.

Hippocampal acidity and volume are differentially associated with spatial navigation in older adults.

The hippocampus is negatively affected by aging and is critical for spatial navigation. While there is evidence that wayfinding navigation tasks are especially sensitive to preclinical hippocampal deterioration, these studies have primarily used volumetric hippocampal imaging without considering microstructural properties or anatomical variation within the hippocampus. T1ρ is an MRI measure sensitive to regional pH, with longer relaxation rates reflecting acidosis as a marker of metabolic dysfunction and neuropathological burden. For the first time, we investigate how measures of wayfinding including landmark location learning and delayed memory in cognitively normal older adults (N = 84) relate to both hippocampal volume and T1ρ in the anterior and posterior hippocampus. Regression analyses revealed hippocampal volume was bilaterally related to learning, while right lateralized T1ρ was related to delayed landmark location memory and bilateral T1ρ was related to the delayed use of a cognitive map. Overall, results suggest hippocampal volume and T1ρ relaxation rate tap into distinct mechanisms involved in preclinical cognitive decline as assessed by wayfinding navigation, and laterality influenced these relationships more than the anterior-posterior longitudinal axis of the hippocampus.

Timing variability and midfrontal ~4 Hz rhythms correlate with cognition in Parkinson's disease.

Patients with Parkinson's disease (PD) can have significant cognitive dysfunction; however, the mechanisms for these cognitive symptoms are unknown. Here, we used scalp electroencephalography (EEG) to investigate the cortical basis for PD-related cognitive impairments during interval timing, which requires participants to estimate temporal intervals of several seconds. Time estimation is an ideal task demand for investigating cognition in PD because it is simple, requires medial frontal cortical areas, and recruits basic executive processes such as working memory and attention. However, interval timing has never been systematically studied in PD patients with cognitive impairments. We report three main findings. First, 71 PD patients had increased temporal variability compared to 37 demographically matched controls, and this variability correlated with cognitive dysfunction as measured by the Montreal Cognitive Assessment (MOCA). Second, PD patients had attenuated ~4 Hz EEG oscillatory activity at midfrontal electrodes in response to the interval-onset cue, which was also predictive of MOCA. Finally, trial-by-trial linear mixed-effects modeling demonstrated that cue-triggered ~4 Hz power predicted subsequent temporal estimates as a function of PD and MOCA. Our data suggest that impaired cue-evoked midfrontal ~4 Hz activity predicts increased timing variability that is indicative of cognitive dysfunction in PD. These findings link PD-related cognitive dysfunction with cortical mechanisms of cognitive control, which could advance novel biomarkers and neuromodulation for PD.

Frontal theta and beta oscillations during lower-limb movement in Parkinson's disease.

OBJECTIVES: Patients with Parkinson's disease (PD) have deficits in lower-limb functions such as gait, which involves both cognitive and motor dysfunction. In PD, theta and beta brain rhythms are associated with cognitive and motor functions, respectively. We tested the hypothesis that PD patients with lower-limb abnormalities would exhibit abnormal theta and beta rhythms in the mid-frontal cortical region during lower-limb action. METHODS: This study included thirty-nine participants; 13 PD patients with FOG (PDFOG+), 13 without FOG (PDFOG-), and 13 demographically-matched controls. We recorded scalp electroencephalograms (EEG) during a lower-limb pedaling motor task, which required intentional initiation and stopping of a motor movement. RESULTS: FOG scores were correlated with disease severity and cognition. PDFOG+ patients pedaled with reduced speed and decreased acceleration compared to PDFOG- patients and controls. PDFOG+ patients exhibited attenuated theta-band (4-8 Hz) power and increased beta-band (13-30 Hz) power at mid-frontal electrode Cz during pedaling. Frontal theta- and beta-band oscillations also correlated with motor and cognitive deficits. CONCLUSION: Frontal theta and beta oscillations are predictors of lower-limb motor symptoms in PD and could be used to design neuromodulation for PD-related lower-limb abnormalities. SIGNIFICANCE: These data provide insight into mechanisms of lower-limb dysfunction in PD with FOG.

Cardiorespiratory fitness and hippocampal volume predict faster episodic associative learning in older adults.

Declining episodic memory is common among otherwise healthy older adults, in part due to negative effects of aging on hippocampal circuits. However, there is significant variability between individuals in severity of aging effects on the hippocampus and subsequent memory decline. Importantly, variability may be influenced by modifiable protective physiological factors such as cardiorespiratory fitness (CRF). More research is needed to better understand which aspects of cognition that decline with aging benefit most from CRF. The current study evaluated the relation of CRF with learning rate on the episodic associative learning (EAL) task, a task designed specifically to target hippocampal-dependent relational binding and to evaluate learning with repeated occurrences. Results show higher CRF was associated with faster learning rate. Larger hippocampal volume was also associated with faster learning rate, though hippocampal volume did not mediate the relationship between CRF and learning rate. Furthermore, to support the distinction between learning item relations and learning higher-order sequences, which declines with aging but is largely reliant on extra-hippocampal learning systems, we found learning rate on the EAL task was not related to motor sequence learning on the alternating serial reaction time task. Motor sequence learning was also not correlated with hippocampal volume. Thus, for the first time, we show that both higher CRF and larger hippocampal volume in healthy older adults are related to enhanced rate of relational memory acquisition.

Acute Exercise Effects Predict Training Change in Cognition and Connectivity.

PURPOSE: Previous studies report memory and functional connectivity of memory systems improve acutely after a single aerobic exercise session or with training, suggesting that the acute effects of aerobic exercise may reflect initial changes that adapt over time. In this trial, for the first time, we test the proof-of-concept of whether the acute and training effects of aerobic exercise on working memory and brain network connectivity are related in the same participants. METHODS: Cognitively normal older participants (N = 34) were enrolled in a randomized clinical trial (NCT02453178). Participants completed fMRI resting state and a face working memory N-back task acutely after light- and moderate-intensity exercises and after a 12-wk aerobic training intervention. RESULTS: Functional connectivity did not change more after moderate-intensity training compared with light-intensity training. However, both training groups showed similar changes in cardiorespiratory fitness (CRF) (maximal exercise oxygen uptake, V˙O2peak), limiting group-level comparisons. Acute effects of moderate-intensity aerobic exercise on connections primarily in the default network predicted training enhancements in the same connections. Working memory also improved acutely, especially after moderate-intensity, and greater acute improvements predicted greater working memory improvement with training. Exercise effects on functional connectivity of right lateralized frontoparietal connections were related to both acute and training gains in working memory. CONCLUSIONS: Our data support the concept of acute aerobic exercise effects on functional brain systems and performance as an activity-evoked biomarker for exercise training benefits in the same outcomes. These findings may lead to new insights and methods for improving memory outcomes with aerobic exercise training.