Kieran Mohr

Kieran Mohr
University College Dublin | UCD · Department of Cognitive Neuroscience, School of Electrical, Electronic and Mechanical Engineering

BA, MSc

About

21
Publications
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207
Citations

Publications

Publications (21)
Article
Full-text available
Amyotrophic lateral sclerosis (ALS) is a devastating disease characterised primarily by motor system degeneration, with clinical evidence of cognitive and behavioural change in up to 50% of cases. ALS is both clinically and biologically heterogeneous. Subgrouping is currently undertaken using clinical parameters, such as site of symptom onset (bulb...
Article
Full-text available
Spatial attention modulations of initial afferent activity in area V1, indexed by the first component ‘C1’ of the human visual evoked potential, are rarely found. It has thus been suggested that early modulation is induced only by special task conditions, but what these conditions are remains unknown. Recent failed replications—findings of no C1 mo...
Poster
Full-text available
Typically, the initial afferent activity of V1 has been measured in VEPs via the C1 component, which peaks 70-90 ms post-stimulus and is canonically associated with a V1 source due to its polarity reversal across the horizontal meridian, reflecting the opposing faces of the Calcarine banks along which V1 lies. Below, we demonstrate a related signal...
Poster
Full-text available
Here, we demonstrate that topography shifts as a function of visual field location are highly consistent across three common visual evoked potentials (C1 component of the discrete VEP, the SSVEP, and the pattern pulse multifocal visual evoked potential), which in turn are highly consistent with a source in V1 due to its cortical geometry with respe...
Article
Full-text available
Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease primarily affecting motor function, with additional evidence of extensive nonmotor involvement. Despite increasing recognition of the disease as a multisystem network disorder characterised by impaired connectivity, the precise neuroelectric characteristics of impaired c...
Article
Full-text available
Objective: To localise and characterise changes in cognitive networks in Amyotrophic Lateral Sclerosis (ALS) using source analysis of mismatch negativity (MMN) waveforms. Rationale: The MMN waveform has an increased average delay in ALS. MMN has been attributed to change detection and involuntary attention switching. This therefore indicates pat...
Article
Amyotrophic lateral sclerosis (ALS) is a terminal progressive adult-onset neurodegeneration of the motor system. Although originally considered a pure motor degeneration, there is increasing evidence of disease heterogeneity with varying degrees of extra-motor involvement. How the combinedmotor and nonmotor degeneration occurs in the context of bro...
Article
Slotnick (this issue) provided a selective review of studies on the attentional modulation of the C1 component of the visual evoked potential, and offers a number of guidelines to maximize the likelihood of observing such modulation in terms of electrode choice, stimulus placement, and types of attentional cue and target stimulus. However, the broa...
Article
In Kelly, Gomez-Ramirez and Foxe (2008), we demonstrated strong spatial attentional modulation of initial afferent activity in human area V1 reflected in the C1 visual evoked potential (VEP) component. Using the same task and analysis strategy, Baumgartner and colleagues provide compelling evidence that there is no such modulation in their data. He...
Article
Full-text available
Objective: To evaluate the utility of mismatch negativity (MMN), a neurophysiologic marker of non-motor cognitive processing, in amyotrophic lateral sclerosis (ALS). Methods: 89 patients, stratified into 4 different phenotypic presentations of ALS (67 spinal-onset, 15 bulbar-onset, 7 ALS-FTD, 7 C9ORF72 gene careers), and 19 matched controls unde...
Conference Paper
Coherence is a mathematical measure of correlation in the frequency domain, commonly used to quantify the oscillatory synchrony of bio-signals such as the electroencephalogram (EEG). In biomedical applications, such as assessment of functional connectivity, reliable estimation of coherence is of paramount importance for studying the function of com...
Preprint
A wide range of studies in human neuroscience rely on the analysis of electrophysiological bio-signals such as electroencephalogram (EEG) where customized data analysis may require supervised artefact rejection, binary marking through visual inspection, selection of noise and artefact samples for pre-processing algorithms, and selection of clinical...
Article
Full-text available
A fundamental problem faced by humans is learning to select motor actions based on noisy sensory information and incomplete knowledge of the world. Recently, a number of authors have asked whether this type of motor learning problem might be very similar to a range of higher-level decision-making problems. If so, participant behaviour on a high-lev...
Data
Representative participant learning curves for each target with model prediction (average over 100 runs). One participant’s learning curves for all 24 targets in both the DM (red) and the MO task (green), against model predictions (black; average over 100 runs). Each panel represents a specific target. (TIF)
Data
Representative participant learning curves for each target with model prediction (one single run). One participant’s learning curves for all 24 targets in both the DM (red) and the MO task (green), against model predictions (black; one single run). Each panel represents a specific target. (TIF)
Data
Learning curve predictions for different target cells (the DM task). The model’s predictions of the learning curves (black) for all the 24 targets used in the experiment, against participant performance (red). Each panel is for a specific target, indicated by blue asterisk plotted against the rectangle in the bottom right of each panel. Red error b...
Data
Comparison of the error reduction (Experiment 1). Two-way repeated measures ANOVA results on the three parameters (a,b and c in y = ae−bx + c). (TIF)
Data
Comparison of the error reduction (Experiment 2). Two-way repeated measures ANOVA results on the three parameters (a,b and c in y = ae−bx + c). (TIF)
Data
Learning curve predictions for different target trajectories (the MO task). The model’s predictions of the learning curves (black) for all the 24 targets used in the experiment, against participant performance (green). Each panel is for a specific target trajectory, indicated by blue trajectory plotted against the rectangle in the bottom right of e...
Data
Likelihood implementation details. (DOCX)

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