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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A Neurocomputational Model of the Effect of Cognitive Load on Freezing of Gait in Parkinson's Disease
|
|---|---|
| Published in |
Frontiers in Human Neuroscience, January 2017
|
| DOI | 10.3389/fnhum.2016.00649 |
| Pubmed ID | |
| Authors |
Vignesh Muralidharan, Pragathi P. Balasubramani, V. Srinivasa Chakravarthy, Moran Gilat, Simon J. G. Lewis, Ahmed A. Moustafa |
| Abstract |
Experimental data show that perceptual cues can either exacerbate or ameliorate freezing of gait (FOG) in Parkinson's Disease (PD). For example, simple visual stimuli like stripes on the floor can alleviate freezing whereas complex stimuli like narrow doorways can trigger it. We present a computational model of the cognitive and motor cortico-basal ganglia loops that explains the effects of sensory and cognitive processes on FOG. The model simulates strong causative factors of FOG including decision conflict (a disagreement of various sensory stimuli in their association with a response) and cognitive load (complexity of coupling a stimulus with downstream mechanisms that control gait execution). Specifically, the model simulates gait of PD patients (freezers and non-freezers) as they navigate a series of doorways while simultaneously responding to several Stroop word cues in a virtual reality setup. The model is based on an actor-critic architecture of Reinforcement Learning involving Utility-based decision making, where Utility is a weighted sum of Value and Risk functions. The model accounts for the following experimental data: (a) the increased foot-step latency seen in relation to high conflict cues, (b) the high number of motor arrests seen in PD freezers when faced with a complex cue compared to the simple cue, and (c) the effect of dopamine medication on these motor arrests. The freezing behavior arises as a result of addition of task parameters (doorways and cues) and not due to inherent differences in the subject group. The model predicts a differential role of risk sensitivity in PD freezers and non-freezers in the cognitive and motor loops. Additionally this first-of-its-kind model provides a plausible framework for understanding the influence of cognition on automatic motor actions in controls and Parkinson's Disease. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 138 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 25 | 18% |
| Student > Master | 21 | 15% |
| Student > Bachelor | 14 | 10% |
| Researcher | 11 | 8% |
| Lecturer | 6 | 4% |
| Other | 17 | 12% |
| Unknown | 44 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 17 | 12% |
| Psychology | 13 | 9% |
| Engineering | 12 | 9% |
| Nursing and Health Professions | 7 | 5% |
| Computer Science | 7 | 5% |
| Other | 28 | 20% |
| Unknown | 54 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 January 2017.
All research outputs
#18,148,462
of 23,314,015 outputs
Outputs from Frontiers in Human Neuroscience
#5,779
of 7,266 outputs
Outputs of similar age
#296,540
of 423,405 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#145
of 179 outputs
Altmetric has tracked 23,314,015 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,266 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 423,405 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 179 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.