Electrophysiological Signature of Mild Cognitive Impairment and Its Relationship with Parkinson's Disease: a High-density EEG Investigation
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Parkinson Disease
- Sponsor
- IRCCS San Camillo, Venezia, Italy
- Enrollment
- 42
- Locations
- 1
- Primary Endpoint
- Power Spectrum Density Analysis profile for hdEEG resting state data
- Status
- Recruiting
- Last Updated
- last year
Overview
Brief Summary
The study aims to investigate neural correlate of Mild Cognitive Impairment (MCI) in Parkinson's disease (PD) and to identify a link between functional impairment (in both cognitive and motor domains) and electrophysiological cortical sing of MCI in PD. A sample of 42 subjects will be divide into three subgroup: healthy control, PD with MCI (PD-MCI) and PD without MCI (PD-ctrl). Those subjects will undergo a specific neuropsychological evaluation and, to measure the electro-cortical activity, high-density electroencephalography (hdEEG) will be record during both resting state and cognitive tasks. Furthermore, hdEEG data will be combine with structural magnetic resonance to obtain information about network connectivity.
Detailed Description
Parkinson's disease (PD) is a neurodegenerative disorder, characterized by a degeneration of dopaminergic neurons at the level of the pars compacta of the substantia nigra, which results in impaired control of the nigrostriatal pathway. This degeneration is manifested by both motor and non-motor symptoms such bradykinesia, tremor, rigidity, and cognitive disorders. Particularly, patients with PD might be affected by Mild Cognitive Impairment (MCI), dementia, and related behavioral disorders including apathy and depressive syndromes. However, while motor disturbances are more evident, it is difficult to evaluate the onset of cognitive symptoms, especially in the prodromal phases of the disease. Indeed, it seems that the onset of cognitive deficits in PD occurs in a high prevalence in the earlier stages of the disease. PD patients can often be associated with MCI, a preclinical condition characterized by the presence of deficits in memory and executive functions as well as, to a lesser extent, in language- and visuospatial- related functions. Dual-syndrome hypothesis posit the existence of two subtypes of MCI one fronto-striatal, characterised by executive and attentional deficits, and a posterior cortical one, characterised by deficits in memory visuo-spatial and language deficits. Recent studies described alterations in brain rhythm, measured with high-density EEG (HDEEG) in terms of frequency domain analysis, at the level of fronto-striatal regions only in patients with the fronto-striatal subtype. Moreover, fMRI studies have shown that the presence of MCI in PD causes a reduction in activity at the level of the cognitive cortico-striatal loop, which includes the caudate nucleus (CN) and prefrontal cortex (PFC). Although the use of neurophysiological and neuroimaging techniques have substantially grown, the available data highlight the lack of detailed descriptions of functional connectivity in relation whit the onset and extent of the cognitive deficit itself. Therefore, the aim of the present study is to characterise MCI in PD from a neurophysiological and clinical point of view. First, all patients undergo a neuropsychological assessment to identify PD patients with MCI (PD-MCI) and those without MCI (PD-nMCI). Then, to investigate the functional connectivity of cortical areas underpinning cognitive decline, HDEEG will be record, during both resting state and cognitive tasks. Furthermore, for each participant will be collect MRI (Magnetic resonance imaging), to combine structural data with electrodes position over the scalp. This would allow obtaining a realistic model of the head for source analysis. Identification of alterations in functional connectivity between specific cortical areas in MCI-PD patients, and a possible direct relationship between these and clinical impairment, could lead to improve therapeutic interventions and prevent cognitive disorders in PD patients.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Upper score \>24 MMSE or \>15.5 Moca
- •If taking medications, taking stable doses for at least 4 weeks prior to the inclusion visit - of anticholinesterase drugs (donepezil, memantine, rivastigmine, ...) or antidepressants (SSRIs, tricyclics, SNARI, ...) or Levodopa.
- •Having signed the informed consent
Exclusion Criteria
- •Subjects with severe dementia ( MMSE \< 24 )
- •Lower score \<15.5 Moca
- •Subjects on antipsychotic treatment for less than 3 months
- •Subjects with uncontrolled comorbidities
- •Subjects with metal prostheses or dentures and in general conditions for which MRI examinations are prevented.
- •Subjects with an inability to walk independently.
Outcomes
Primary Outcomes
Power Spectrum Density Analysis profile for hdEEG resting state data
Time Frame: at baseline
For all the groups, starting from the hdEEG data, brain oscillation will be studied by performing the Power Spectral Analysis (PSD). The PSD aims to investigate the spectral properties in the delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz), and gamma (\>30Hz) frequencies bands. PSD will be performed for each electrode, for each subject, and then averaged across subjects, obtaining a value of PSD for each electrode, separately for each group (PD-ctrl vs PD-MCI). Then the PSD value will be displayed over the scalp with a topological representation.
Power Spectrum Density Analysis profile for hdEEG during cognitive task data
Time Frame: at baseline
For all the groups, starting from the hdEEG data, brain oscillation will be studied by performing the Power Spectral Analysis (PSD). The PSD aims to investigate the spectral properties in the delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz), and gamma (\>30 Hz) frequencies bands. PSD will be performed for each electrode, for each subject, and then averaged across subject obtaining value of PSD for each electrode, separately for each group (PD-ctrl vs PD-MCI). Then the PSD value will be displayed over the scalp with a topological representation.
Functional connectivity - seed based analysis for hdEEG resting state data
Time Frame: at baseline
To study the temporal correlation of cortical signals generated in spatially distributed regions of interest (ROI), the collected hdEEG data will be analyzed using the seed-based functional connectivity analysis (FC-SBA). FC-SBA will measures the time course activation of specific resting state networks (RSNs). Specifically, the DMN (default mode network), SN (Salience Network), FPN1 and FNP2 (Fronto-parietal Network). This approach allows to obtain the functional connectivity matrices that will show the activation pattern of different RSNs and frequency bands (delta 1-4Hz; theta 4-8Hz; alpha 8-13 Hz, beta 13-30Hz; gamma \>30Hz).
Functional connectivity - seed based analysis for hdEEG during cognitive task data
Time Frame: at baseline
To study the temporal correlation of cortical signals generated in spatially distributed regions of interest (ROI), the collected hdEEG data will be analyzed using the seed-based functional connectivity analysis (FC-SBA). FC-SBA will measures the time course activation of specific resting state networks (RSNs). Specifically, the DMN (default mode network), SN (Salience Network), FPN1 and FNP2 (Fronto-parietal Network). This approach allows to obtain the functional connectivity matrices that will show the activation pattern of different RSNs and frequency bands (delta 1-4Hz; theta 4-8Hz; alpha 8-13 Hz, beta 13-30Hz; gamma \>30Hz).
Secondary Outcomes
- Performances at neuropsychological evaluation(at baseline)
- Fraility assessment(at baseline)
- Accuracy during cognitive task(at baseline)