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Dual mechanisms of cognitive control

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Presentation on theme: "Dual mechanisms of cognitive control"— Presentation transcript:

1 Dual mechanisms of cognitive control
Todd Braver Cognitive Control and Psychopathology Lab, Washington University Plus: Jeremy Reynolds Josh Brown Stefan van der Stigchel First, I would like to take a moment to thank my collaborators As a psychopathologist, my primary interest is in schizophrenia Understanding the relationships between the observable signs and symptoms of schizophrenia, and the underlying cognitive and neural mechanisms

2 Cognitive Control What is cognitive control? The problem: Interference
formation, maintenance and realization of internal goals structuring thoughts and actions in accordance with these goals The problem: Interference the environment often provides conflicting or distracting information perceptually salient information or default action tendencies are often incongruent with intended goals Examples: Action capture errors, RED A major function of control processes is to successfully manage interference What are the underlying neural & cognitive mechanisms?

3 Dual mechanisms of control
Our hypothesis => Dual mechanisms Reactive control: Detection and resolution of interference Proactive control: Anticipation and prevention of interference Reactive control Transient, stimulus-driven activation of lateral prefrontal cortex (PFC) and other areas due to: Spreading activation processes Detection of conflict (anterior cingulate cortex) Late correction mechanism: suppression of goal-irrelevant information when needed or just-in-time Example: remember to stop at store after work (e.g. prospective memory); event-based triggering Proactive control: Sustained active maintenance of goal-related information in lateral PFC dependent upon phasic dopamine (DA) activity Early selection mechanism: top-down attentional biases enhance access to goal-relevant information or prepare appropriate actions Example: Remembering your point in a conversation while others are speaking

4 Why dual mechanisms? Cost-benefit analysis A mixture model
Proactive control: More effective, but More energetically demanding More vulnerable to disruption (precise DA dynamics required) Reactive control More susceptible to interference effects (late correction), but Less demanding, more robust A mixture model Both control strategies are used but weightings can differ: Across task situations: Opportunity & Impact Across individuals: May be dependent upon biases and capabilities May even be trial-to-trial variability (e.g,. natural fluctuations) Task-switching

5 Research Strategy A cognitive neuroscience approach Domains
Cognitive Experiments: Manipulation of control strategy, look for behavioral markers Brain Imaging: Dynamics of activity in lateral PFC, ACC, other regions Special populations: Effects due to normal individual differences (personality, intelligence), impaired functions (older adults, schizophrenia) Computational Modeling: Mechanistic explanations, bridging brain & behavior Domains Working memory (e.g., Sternberg task) Controlled attention (e.g., Stroop) Task-switching

6 Task-switching Key Issues Accounts Problem
Switch costs imply interference from other task sets Preparatory interval effects on switch cost implies proactive control is being used (Meiran) Task-set (goals) are actively maintained and used to bias attention Residual switch costs with long preparatory intervals suggest this can’t be full account Accounts Task-set inertia (Allport): Emphasis on unresolved interference rather than proactive control Exogenous cuing (Monsell): Proactive control is incomplete until target presented Failure-to-engage (DeJong): Probabilistic proactive control; intermittent failures Problem If no proactive control, how come interference effects are not catastrophic? Ambiguous targets (bivalent, incongruent) can only be performed appropriately if task-set information is accesssible (e.g., actively maintained) In the last decade there has been an explosion of research on task-switching. Out of this research it has become very clear that one of the most robust behavioral findings in the literature is the switch cost. When subjects switch to a new task on a trial rather than repeat the task performed on the previous trial they incur a fairly substantial decrement in performance, primarily in reaction time. It is also clear that providing an advance instruction cue, as shown on the previous trial, along with a preparatory period before the target stimulus is presented, causes a significant reduction in the switch cost. This has been taken as clear evidence that individuals are able to engage cognitive control, by preparing for the next task through task-set updating. Moreover, the idea is that task-set updating requires time to complete, and that this is an important cause of the switch cost. Yet a remarkable finding has also been clearly observed -- which is the residual switch cost. Even given advance cues and long preparatory intervals, there is still a substantial performance decrement associated with switching task. The residual switch cost has been a considerable source of controversy within the literature, because it is so theoretically challenging. That is, it is not immediately clear what mechanisms prevent full preparation to occur prior to the onset of a new task, even when the appropriate information and time is provided. In recent years, a number of neuroimaging studies have been conducted to investigate the neural basis of task-switching but these too have often produced surprising results. The expectation in these studies would be that task-switching, because it is so clearly demanding of cognitive control, would be associated with reliable activation in prefrontal cortex. And although this hypothesis has sometimes been borne out, there have been some mixed results, especially in event-related studies directly contrasting task-switch and task-repeat trials.

7 Our hypothesis Prepared trials = proactive control
Actively maintained PFC representations lead to preparatory biasing prior to target stimuli Updating and maintenance in PFC triggered by phasic dopamine burst occurring during task cue presentation Unprepared trials = reactive control Transient activation of PFC during cue presentation, but no updating and maintenance Dopamine system is noisy; no phasic response on some trials Target-driven reactivation of cue leads to late biasing of relevant task pathways Goal Develop computational model to demonstrate mechanisms Demonstrate that model can capture task-switching behavioral phenomena Switch costs, congruency costs, etc. De Jong mixture analysis: prepared (fast) trials show no switch costs, unprepared (slow) trials show maximal switch costs Demonstrate that model can capture task-switching brain activity dynamics Our hypothesis is that prepared vs. unprepared trials actually reflect the cognitive system operating in two distinct modes of control that we term proactive and reactive control. We hypothesize that the proactive control mode is one in which PFC representations are activated and maintained during delay intervals prior to the time in which control must be exerted. Proactive control enables optimal top-down configuration of attention, perception and response selection to be achieved. In contrast, reactive control is a control mode characterized by transient stimulus-driven activation of PFC representations in just enough time to override potential sources of interference before errors occur. In our theoretical model, advance contextual cues can lead to updating and active maintenance within PFC only if accompanied by a phasic burst of dopamine activity. Based upon our previous modelling work, we have suggested that phasic dopamine responses can serve as a gating signal enabling afferent information to access and update state of PFC activity. Without such phasic dopamine activity, relevant task cues can only transiently activate PFC and will not lead to updating or active maintenance of cue information. Because the dopamine system is noisy, this situation might occur quite frequently. Under such situations, when faced with a target stimulus the relevant task-set information must be re-activated since it had not been maintained. This cue re-activation is driven by bottom-up associative priming between the target information and task-set representation. This late activation of the task-set then leads to biasing of task-pathways, but the biasing occurs late rather than early in the course of a trial.

8 Experimental Paradigm
Unpredictable (trial-by-trial) cueing, letter-digit task Long preparatory interval (1500 msec) Cons Vowel TASK A Odd Even TASK B LETTER X 9 Time NUMBER The work I’ll be talking about comes from the domain of task-switching. And this is a very nice domain for investigating cognitive control, because task-switching paradigmsallow for a direct examination of the notion of internal “task-set” representations and how these become rapidly activated and updated as task conditions changes. [ADVANCE SLIDE] This diagram illustrates a typical task-switching paradigm, using the well-known letters-digit task popularized by Rogers & Monsell. Here across a series of trials the subject is asked to perform either the letter task, in which a decision must be made as to whether the letter is a vowel or consonant, and the number task, in which a decision must be made as to whether the number is odd or even. There are two important characteristics of the task which make it a challenge for control processes. First, in most task-switching paradigms, all stimuli are “bivalent” that is having both task dimensions present on every trial. This makes each stimulus ambiguous, since the same stimulus could be present for either task and even require different responses in each task. This characteristic is shown here where in both trials the stimulus is “X 9”. But given a particular response button mapping, in one task the stimulus requires a right button response, and in the other task a left button response. A second important feature of task-switching paradigms is that one is rapidly asked to switch from one task to another, with almost no pause between them. So here, the first trial requires the letter task, but then the second trial, immediately afterwards, asks for the number task to be performed. In this case, as I have shown it, each task trial is preceded by an instruction cue that indicates the task to be performed on the next trial. And this will be an important feature in the work I will be discussing.

9 Neural network model

10 Simulations Proactive control (prepared) Reactive control (unprepared)

11 Simulation Mechanisms
DA-based updating is probabilistic (50% of trials) Results in mixture of unprepared and prepared trials DA gating enables active maintenance Co-Activation leads to associative (Hebbian) strengthening (priming) Prepared trials (proactive control) Task set information is actively maintained during preparatory interval (in PFC module) Biases appropriate task-pathway Local competition leads to suppression of irrelevant task set and pathway Reduced interference effects (e.g., switch costs) Unprepared trials (reactive control) Task-set information transiently activated with cue, leads to associative strengthening (priming) with task pathway Task-set decays during preparatory interval Target presentation causes reactivation of appropriate task-set Task-set interference is greater on switch trials and incongruent trials Increased interference effects (congruency & switch costs)

12 Error Rate Data

13 RT data

14 RT distribution data

15 Mixture Analysis Switch-all trials Nonswitch (plus switch -gating)
Switch-no gating

16 Preparation & Errors Unprepared Prepared

17 Simulated PFC Activity

18 Actual PFC Activity Braver, Reynolds, and Donaldson (2003) Neuron

19 Summary Task-switching effects might reflect dual mechanisms of cognitive control Proactive control: Active maintenance of task-set and preparatory biasing Reactive control: Reactivation of task-set following target This theory provides resolution of key questions Residual switch costs due to probabilistic preparation Performance on non-prepared trials aided by reactive control Task-set interference only present on unprepared trials PFC activity associated with task-cues may be variable Framework may account for other issues as well Mixing costs: Anterior vs. dorsolateral PFC; proactive biasing of eligible tasks Sequential effects: Conflict (Incongruency)-based strengthening of active task (e.g. Goschke, 2000) Asymmetric switch costs: no repetition benefits for weaker task w/o proactive control Other domains: WM, selective attention, individual differences

20 Future Directions Asymmetric Switch Costs (van der Stigchel)
Mixing Costs (Neuron) Conflict Effects (Brown)


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