The phrase "accumulator model" is correct and usable in written English.
It can be used in contexts related to computing, mathematics, or psychology, where a model accumulates data or information over time.
Example: "The accumulator model helps in understanding how information is gathered and processed in cognitive tasks."
Alternatives: "cumulative model" or "aggregation model".
In the leaky competing accumulator model, noisy evidence for each alternative is accumulated over time in each accumulator.
We present a mechanistic account of participants' performance within the framework of the leaky competing accumulator model [1], in which accumulators for each alternative accumulate noisy information subject to leakage and mutual inhibition.
To demonstrate that subjects accumulated the sensory evidence provided by the auditory clicks, we fit an accumulator model using the individual click times and the rats' choices on each trial.
We implemented two independent race models: the well-known Linear Ballistic Accumulator (LBA; Brown & Heathcote, 2008) and a discrete accumulator model with varying thresholds (DAVT), a suitable model for demonstration purposes.
The accumulator model can be used to explain normal developmental changes in voluntary saccade control that are present in normal development as well as in attention deficit hyperactivity disorder (ADHD), Parkinson's disease (PD), and Tourette syndrome (TS).
The model consists of Izhikevich neurons and conductance-based synapses for realistic approximation of neuronal dynamics, a spike-timing-dependent plasticity (STDP) synaptic learning rule with additional synaptic dynamics for memory encoding, and an accumulator model for memory retrieval and categorization.
By contrast, several computational models of decision-making, particularly random walk and accumulator models, explicitly incorporate a theoretical framework for SATs [31] [34].
A related class of models, called accumulator models, invokes separate accumulators to model forced-choice tasks with two or more alternatives [6], [7], and recent versions of such models allow for the possibility of competition among the accumulators and decay or leakage of accumulated information (e.g. [8], [9], [10]).
Shadlen and colleagues opened a particularly rich vein of research by applying accumulator models to study neural mechanisms underlying the workhorse task of psychophysics the two-alternative, forced-choice (2AFC) sensory discrimination.
This model is one of a broad class of accumulator models of decision-making (See [4] for a review), incorporating leakage or decay of accumulated information, as well as competition among accumulators, factors motivated both by behavioral and neurophysiological considerations, in the context of a stochastic information integration process.
These results are not only consistent with accumulator models of decision-making [32], [39], [40], [51], but also with neurophysiological evidence that accumulation of activity occurs in 'central' stages rather than in early sensory or late motor stages of information processing [16], [20], [26], [30], [52].
