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ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
ADHD as a model for understanding neural network dynamics
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ADHD as a model for understanding neural network dynamics

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  • Blue: pay attention there’s something unique going on here, what do I do?
    Yellow: transforming senses into actions
    Red: Executive Control and Working Memory
  • motor system activation was functionally integrated with prefrontal and parietal
    regions frequently observed during goal-directed behavior involving motor attention and working memory.
  • Striatal regions typically recruited in response execution were not engaged
    This may reflect a breakdown of higher-order control on error trials.
    functional interpretation of mesiotemporal activity is that it could represent internal speech [Ryding et al., 1996], a literal or figurative sub-vocal ‘whoops!’ response made to errors.
  • which likely contributes affective salience to No-Go target stimuli [Holroyd and
    Coles, 2002]. Activity in these frontotemporal areas has been linked to internally-generated emotional response
    [Reiman et al., 1997], awareness of errors [Hester et al., 2005], and self-referential thinking [Vogeley et al., 2001],
    suggesting these regions may underlie awareness of and emotional reaction to errors.

    Specifically, affective responses might signal the failure to reinforce stimulus-action-reward associations.
  • Transcript

    • 1. Using ADHD as a model for understanding neural networks Dr. Laura Jansons 02/22/2014
    • 2. ADHD • Diagnosis made by behavior observation: DSM-V – 18 symptoms of ADHD, need to meet a percentage of them to be diagnosed – Diagnosed using behavioral checklists – Problem for neuropsychologists: • DSM-V is not based on NP test data • DSM-V not based on Neuroanatomy • DSM-V is based on “lesion” or disease model.
    • 3. – Old: ADHD is dysfunction of frontal lobe – New: abnormally functioning brain circuitry – New: Several etiological influences, “common disease- common variant model” – New: ADHD is not one thing, there is not one place on the brain we can map.
    • 4. • Based on what we’ve learned from neuroimaging, we should be thinking in terms of loops and connections, and not land marks. • Those loops recruited in ADHD: –Cerebro-cortical –Cortical-basal ganglia –Cerebo-cerebellar –Basal ganglia-cerebellar
    • 5. 7 brain networks involved in ADHD Yeo and colleagues (2011) • Frontal Parietal network: effortful cognitive tasks, esp. novel. • Ventral attentional network : directs attn. to salient objects. “What” you are seeing or “what” an object is used for. • Dorsal attentional network : Where and How of spatial attn. “Where” is object located and “how” do I use it. • Visual Network: interacts with dorsal and ventral route • Limbic network: anticipation of rewards, monitors errors and conflict resolution. • Sensory-motor network: motor skills • Default mode network: What you are imagining at rest.
    • 6. • What this means for neuropsychologists is that it is no longer appropriate to think of ADHD as a simple ‘‘frontal-lobe disorder’’ • Need to replace the localizationist view, ADHD is not just one thing from one place in the brain with one trajectory. • This is why there is no NP test available, ADHD is heterogeneous, the symptoms are heterogeneous.
    • 7. Functionally mapping ONE symptom of ADHD using one type of test • Stevens and colleagues, 2007, provided the first description of how multiple neural network dynamics are associated with response inhibition in normal control adolescent and adult subjects in the performance of a “Go-No-Go” task.
    • 8. • There is not one region in the brain responsible for inhibiting response. • There are “loops” of communication that leads to disinhibition, in fact there are three. • We are always “idling” and anticipating. When the light is red, the car is not “off”. • There is a lot going on when you inhibit a response.
    • 9. Withholding response These loops can be mapped on the brain via fMRI. The following is the “blue”, “yellow” and “red” circuit. Correctly rejected No-Go stimuli involved with successful response inhibition:
    • 10. 13 Stevens, et al, 2007 Blue: pay attention there’s something unique going on here, what do I do? Yellow: transforming senses into actions. Object recognition, salience/reward value Red: Executive Control and Working Memory
    • 11. Fig. 1. Brain regions in each component associated with successful response inhibition. (A) Fronto-striatal-thalamic indirect pathway engagement consistent with modulation of motor function (Blue); (B) precentral gyri deactivation concurrent with prefrontal and inferotemporal activation (Yellow); (C) frontoparietal circuit activity consistent with higher-order presentations of No-Go’ response contingencies (Red). Statistical results are thresholded at a low of p < .001, corrected for searching the whole brain.
    • 12. Summary Stevens 2007 • Causal relationships among ensembles of different brain regions. • May help understand that there is no one linear cause for disinhibition, alterations in specific connections or brain region could impact psychopathological conditions.
    • 13. Stevens 2009 • Network dynamics supporting correct responses and errors of commission • NCs between 11 and 37 • Go/No-Go task
    • 14. Stevens 2009 • The analysis found five distinct functional networks related to correct hits and errors.
    • 15. Go XRapidly presented (1000 ms intervals) 85% Go stimuli right index finger taps
    • 16. Go X
    • 17. Go X
    • 18. No Go K
    • 19. Correct Button Pushes A: a motor-execution neural circuit integrated with frontal, parietal, and striatal regions (Orange), B: the ‘default mode’ neural network (imagining a task as if you were doing it)
    • 20. Errors A A: a motor- execution neural circuit showing absent or decreased activity in brain regions engaged for higher-order control (things are going on implicitly—without thought) “whoops” Car’s going down the road without a driver, disturbance in intention program, start, stay stop. Connection between working memory and Impulsivity—environment , stimulus, triggers behavior not thought
    • 21. Errors B B: a low-probability stimulus processing functional circuit that has a greater response amplitude to errors
    • 22. Errors C C: the pregenual cingulate-temporal lobe network possibly reflecting an affective response to errors (bilateral amygdala activation)
    • 23. • Why are NP task so inadequate? Behaviorally defined criteria in ADHD do not easily ‘‘map’’ on to functional brain networks. • With the advent of functional neuroimaging, it was seen conclusively that these sorting and planning tasks should not fairly be considered ‘‘frontal’’ tests.
    • 24. • assessment instruments were never designed to evaluate the networks and interactions in question. • CPT’S are not ADHD tests: they measure a range of impulses and don’t correlate with one another. • Current: widely accepted belief of causal heterogeneity in ADHD. ADHD is not one thing with one cause.
    • 25. • the challenge to functional neuroimaging is to find a way to effectively ‘‘diagnose’’ ADHD.
    • 26. • Neuropsychology can establish itself at the ‘‘ground floor’’ in developing methodologies to explore these different dimensions of behavior. • Challenge in the field today seems to need a way to bring these two worlds together.

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