Biology subjects

Farina, F. R.

Publications and source records attributed to Farina, F. R..

3 recordsLinked to original sources

bioRxiv2019

Hyperactive/impulsive and inattention symptoms are associated with reduced ERP activity during different reward processing stages: Evidence from the electrophysiological Monetary Incentive Delay Task in adult ADHD

Hyperactivity/impulsivity and inattention are core symptoms dimensions in attention-deficit/hyperactivity disorder. Some approaches suggest that these symptoms arise from deficits in the ability to anticipate and process rewards. However, evidence is equivocal with regard to ADHD-related differences in brain activity during reward processing. The aim of this study was to investigate when, and how, reward-related ERP activity was associated with hyperactive/impulsive symptoms and inattention symptoms. Adults with ADHD (n=34) and matched comparison participants (n=36) completed an electrophysiological version of the Monetary Incentive Delay task. This task separates reward processing into two stages-namely, an anticipation stage and a delivery stage. During the anticipation stage, visual cues signalled a possible monetary incentive (i.e. a reward or loss). After a brief delay, the delivery stage began, and incentives were delivered contingent on a speeded button-press. Electroencephalogram activity was simultaneously sampled and incentive-related event relate potentials (ERPs) calculated. These data were then analysed by calculating multiple regression models, at each sample point, wherein the correlation between incentive-related ERPs and ADHD symptoms was estimated. Linear and curvilinear associations between ERP activity and ADHD symptoms were tested in each regression mode. Findings suggest that ADHD symptoms were associated ERP activity at different reward processing stages. Hyperactive/impulsive symptoms were associated with reduced ERP activity during the initial anticipation of rewards from 224-329 ms post-reward cue. Inattention symptoms were associated with reduced ERP activity during the initial delivery of rewards from 251-280 ms post-reward onset. Finally, extreme ends of hyperactive/impulsive and inattention symptoms were associated with reduced ERP activity towards the end of the anticipation stage from 500 ms post-reward cue onwards. These results support the idea that reward processing is disrupted in ADHD while also shedding new light on the dynamic relationship between ADHD symptom dimensions and the neurological mechanisms of reward processing.

neuroscience↗

bioRxiv2019

Contralateral Delay Activity is not sensitive to cognitive decline in older adults at risk of Mild Cognitive Impairment.

Contralateral delay activity (CDA) has been proposed as a pre-clinical marker for Mild Cognitive Impairment (MCI). However, existing evidence is limited to one study with a small sample size (n=12 per group). Our aim was to compare CDA amplitudes in a larger sample of low- and high-risk older adult groups (n=35 per group). As expected, behavioural performance decreased as the number of memory items increased, and the low-risk group out-performed the high-risk group. However, we found no differences in CDA amplitudes across groups, indicating that WM capacity increased irrespective of risk-level. These findings suggest that the CDA is not a sensitive marker of MCI risk. More broadly, our results highlight the difficulty in identifying at-risk individuals, particularly as MCI is a heterogeneous, unstable condition. Future research should prioritise longitudinal approaches in order to track the progression of the CDA and its association with cognitive decline in later life.

neuroscience↗

bioRxiv2019

A comparison of resting state EEG and structural MRI for classifying Alzheimer’s disease and mild cognitive impairment

Alzheimers disease (AD) is a neurodegenerative disorder characterised by severe cognitive decline and loss of autonomy. AD is the leading cause of dementia. AD is preceded by mild cognitive impairment (MCI). By 2050, 68% of new dementia cases will occur in low- and middle-income countries. In the absence of objective biomarkers, psychological assessments are typically used to diagnose MCI and AD. However, these require specialist training and rely on subjective judgements. The need for low-cost, accessible and objective tools to aid AD and MCI diagnosis is therefore crucial. Electroencephalography (EEG) has potential as one such tool: it is relatively inexpensive (cf. magnetic resonance imaging; MRI) and is portable. In this study, we collected resting state EEG, structural MRI and rich neuropsychological data from older adults (55+ years) with AD, with MCI and from healthy controls (n~60 per group). Our goal was to evaluate the utility of EEG, relative to MRI, for the classification of MCI and AD. We also assessed the performance of combined EEG and behavioural (Mini-Mental State Examination; MMSE) and structural MRI classification models. Resting state EEG classified AD and HC participants with moderate accuracy (AROC=0.76), with lower accuracy when distinguishing MCI from HC participants (AROC=0.67). The addition of EEG data to MMSE scores had no additional value compared to MMSE alone. Structural MRI out-performed EEG (AD vs HC, AD vs MCI: AROCs=1.00; HC vs MCI: AROC=0.73). Resting state EEG does not appear to be a suitable tool for classifying AD. However, EEG classification accuracy was comparable to structural MRI when distinguishing MCI from healthy aging, although neither were sufficiently accurate to have clinical utility. This is the first direct comparison of EEG and MRI as classification tools in AD and MCI participants.

neuroscience↗