arXiv subjects

Sajjad Zabbah

Publications and source records attributed to Sajjad Zabbah.

5 recordsLinked to original sources

arXiv2025

Recency effect disappears when information is integrated from independent perceptual sources

Decision-making often involves integrating discrete pieces of information from distinct sources over time, yet the cognitive mechanisms underlying this integration remain unclear. In this study, we examined how individuals accumulate and integrate discrete sensory evidence. Participants performed a task involving random dot motion stimuli presented in single- and double-pulse trials. These stimuli varied in motion coherence, source consistency of pulses (either the same or orthogonal directions), and temporal gaps between pulses. We found that participants effectively integrated information regardless of source type or temporal gaps. As expected, when both pulses originated from the same source, performance showed a sequence-dependent effect-accuracy was influenced by the order of pulse presentation. However, this effect disappeared when the pulses came from orthogonal sources. Confidence judgments were similarly unaffected by temporal gaps or pulse sequence but were higher when information originated from orthogonal sources. These findings highlight the specific role of perceptual independency on information integration and consequently, on decision-making.

q-bio.NC↗

arXiv2024

Choice confidence bridges credit assignment to levels of decision hierarchy

Everyday decisions often involve many different levels. What connects these higher and lower level decisions hierarchy to one another determines how the cause(s) of failures are interpreted. It is hypothesized that decision confidence guides the assignment of blame to the correct level of hierarchy but this hypothesis has only been tested by manipulation of sensory evidence itself. We examined the consequences of modulating subjective confidence in hierarchical decision making via extra-sensory, social influence. Participants who made hierarchical, motion-plus-bandit decisions also received social information from a partner that advised the participant in the motion task. The strength of social advice -- independently from sensory signals -- modulated the likelihood of strategy change after negative feedback. Our findings therefore provide strong empirical evidence that subjective confidence per se acts as the bridge in assignment of credit and blame to various levels of decision hierarchy.

q-bio.NC↗

arXiv2018

A temporal neural network model for object recognition using a biologically plausible decision making layer

Brain can recognize different objects as ones that it has experienced before. The recognition accuracy and its processing time depend on task properties such as viewing condition, level of noise and etc. Recognition accuracy can be well explained by different models. However, less attention has been paid to the processing time and the ones that do, are not biologically plausible. By extracting features temporally as well as utilizing an accumulation to bound decision making model, an object recognition model accounting for both recognition time and accuracy is proposed. To temporally extract informative features in support of possible classes of stimuli, a hierarchical spiking neural network, called spiking HMAX is modified. In the decision making part of the model the extracted information accumulates over time using accumulator units. The input category is determined as soon as any of the accumulators reaches a threshold, called decision bound. Results show that not only does the model follow human accuracy in a psychophysics task better than the classic spiking HMAX model, but also it predicts human response time in each choice. Results provide enough evidence that temporal representation of features are informative since they can improve the accuracy of a biological plausible decision maker over time. This is also in line with the well-known idea of speed accuracy trade-off in decision making studies.

q-bio.NC↗

arXiv2018

Sequence-dependent sensitivity explains the accuracy of decisions when cues are separated with a gap

Most decisions require information gathering from a stimulus presented with different gaps. Indeed, the brain process of this integration is rarely ambiguous. Recently, it has been claimed that humans can optimally integrate the information of two discrete pulses independent of the temporal gap between them. Interestingly, subjects' performance on such a task, with two discrete pulses, is superior to what a perfect accumulator can predict. Although numerous neuronal and descriptive models have been proposed to explain the mechanism of perceptual decision-making, none can explain human behavior in this two-pulse task. In order to investigate the mechanism of decision-making on the noted tasks, a set of modified drift-diffusion models based on different hypotheses were used. Model comparisons clarified that, in a sequence of information arriving at different times, the accumulated information of earlier evidence affects the process of information accumulation of later evidence. It was shown that the rate of information extraction depends on whether the pulse is the first or the second one. The proposed model can also explain the stronger effect of the second pulse as shown by Kiani et al. 2013.

q-bio.NC↗

arXiv2017

Residual Information of Previous Decision Affects Evidence Accumulation in Current Decision

Bias in perceptual decisions comes to pass when the advance knowledge colludes with the current sensory evidence in support of the final choice. The literature on decision making suggests two main hypotheses to account for this kind of bias: internal bias signals are derived from (a) the residual of motor response-related signals, and (b) the sensory information residues of the decisions that we made in the past. Beside these hypotheses, a credible hypothesis proposed by this study to explain the cause of decision biasing, suggests that the decision-related neuron can make use of the residual information of the previous decision for the current decision. We demonstrate the validity of this assumption, first by performing behavioral experiments based on the two-alternative forced-choice (TAFC) discrimination of motion direction paradigms and then, we modified the pure drift-diffusion model (DDM) based on accumulation to the bound mechanism to account for the sequential effect. In both cases, the trace of the previous trial influences the current decision. Results indicate that the probability of being correct in a current decision increases if it is in line with the previously made decision. Also, the model that keeps the previous decision information provides a better fit to the behavioral data. Our findings suggest that the state of a decision variable which is represented in the activity of decision-related neurons after crossing the bound (in the previous decision) can accumulate with the decision variable for the current decision in consecutive trials.

q-bio.NC↗