Browsing by Subject "reaction times"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Cognitive/Neural Compensatory Mechanisms in Schizophrenia: Reaction Times-Brain Activity Correlates
    (2016-12) Elshikh, Ansam
    Abstract Cognitive deficiency in schizophrenia (SZ) was found to be associated with decreased PFC activity compared to healthy controls (HC). Other studies referred to increased / intact patterns of PFC activity. Parallel to those inconsistent neuroimaging findings, schizophrenia patients also showed increased intra-individual reaction times variability (RT_IIV). In the current work, we suggested that inconsistent findings in schizophrenia neuroimaging literature are driven by their increased RT-IIV. We hypothesized that performance with increased reaction times in SZ patients reflects compensatory cognitive/neural mechanisms. To address that general hypothesis, we conducted three studies as follow: 1. Activation likelihood Estimation (ALE) meta analysis of (90 fMRI studies in SZ); In that study we were first concerned with extracting the most consistent neuroimaging findings in the previous SZ literature. Second, we conducted ALE analyses within two categories: experiment with impaired RT (effect sizes > 0.3) vs. experiments with unimpaired RT (effect sizes <0.3); 2. In the second study, we investigated RT_IIV coefficients during AX task performance in four groups, SZ patients (N= 20), SZ.R (N= 33), HC subjects (N =21), HC.R (N= 23). We hypothesized that SZ patients and their relatives would show increased RT_IIV relative to HC within the probe and the cue conditions. 3. In our main study, fMRI study, we tested BOLD response across three levels of RT (slow, medium and fast). We hypothesized that SZ patients and their relatives will show more VLPFC activity during the slow trials than the faster trials relative to HC- reflecting slow reactive compensatory mechanisms.
  • Thumbnail Image
    Item
    Information-theoretic Bounded Rationality: Timing Laws and Cognitive Costs Emerge from Rational Bounds on Information Coding and Transmission
    (2019-10) Christie, Scott
    Cognitive models are used to characterize and understand task performance in humans. Human behavior often deviates from predictions made by models that assume perfect rationality. Imposing constraints on cognitive resources, time, and/or information, while still assuming optimal function within those bounds, produces better characterizations of behavior. However, many of the proposed constraints and costs are ad-hoc and are not derived from fundamental limitations on computation. We suggest that behavioral performance is limited by the necessity of encoding and transmitting information about the world in the brain. Encoding information imposes a set of intrinsic bounds, defined by signal power, noise power, and knowledge of environmental statistics, that can be understood and quantified using concepts from information theory. In this dissertation, we investigate the patterns of behavior that should arise if cognition is subject to these bounds. Using an information transmission mechanism built using stochastic processes and Bayesian inference, we show that known `laws' of human behavior, including the Hick-Hyman law and the Power Law of Learning, are direct consequences of unavoidable limitations on the efficiency of information transmission. By instantiating constraints on information transmission in a working system, we are able to quantify transmission costs induced by task performance. This provides a unifying and principled explanation of cognitive costs and mental effort: effort arises in tasks that require expensive information transmission and is reduced through practice as learned task statistics are exploited to improve efficiency. To test the extent to which humans exploit task statistics to improve efficiency, we measured behavior on a version of the N-back task modified to include a predictable structure in target responses. We found that human data closely matches model predictions, suggesting that humans integrate information about both task structure and past images to produce responses. This finding is an experimental validation of our model, and suggests that the N-back task is more complex than is normally assumed. In sum, we show that treating cognition as a process constrained by fundamental bounds on information transmission provides a unified explanation of a wide range of behavioral phenomena.