Y P O Brain Network Imaging and Brain C Stimulation T O N O - - PowerPoint PPT Presentation

Brain Network Imaging and Brain Stimulation

Michael D. Fox, MD, PhD

Director, Laboratory for Brain Network Imaging and Visualization Associate Director, Berenson-Allen Center for Noninvasive Brain Stimulation Associate Director, Deep Brain Stimulation Program Beth Israel Deaconess Medical Center, Harvard Medical School Neuroscientist, Department of Neurology and Martinos Center for Biomedical Imaging Massachusetts General Hospital, Harvard Medical School

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Disclosures

• Intellectual property using connectivity

imaging to guide brain stimulation (no royalties)

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Outline

• Intro to brain network imaging
• What can network imaging do for brain

stimulation?

• What can brain stimulation do for brain

networks?

P L E A S E D O N O T C O P Y

Outline

• Intro to brain network imaging
• What can network imaging do for brain

stimulation?

• What can brain stimulation do for brain

networks?

P L E A S E D O N O T C O P Y

Types of Brain Network Imaging

• Co-activation Patterns
• Resting state functional connectivity MRI

(Rs-fcMRI)

• Diffusion tensor imaging (DTI)

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Open Open Open Open Closed Closed Closed Closed

Open – Closed =

Classical Neuroimaging

% BOLD Change Time (s)

Fox and Raichle (2007) Nat. Rev. Neuro.

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Open – Closed =

BOLD Data Is Very “Noisy”

% BOLD Change

Open Open Open Open Closed Closed Closed Closed

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Fox and Raichle (2007) Nat. Rev. Neuro.

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Spontaneous Fluctuations (“Noise”) in the BOLD Signal

Left Motor Cortex

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Left Motor Cortex Right Motor Cortex

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Spontaneous Fluctuations are Specifically Correlated

After Bharat Biswal and colleagues (1995) Magnetic Resonance in Medicine

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Generation of Resting State Functional Connectivity Maps

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Fox and Raichle (2007) Nat. Rev. Neuro.

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Z score, fixed effects, N = 10 Fox and Raichle (2007) Nat. Rev. Neuro.

Generation of Resting State Functional Connectivity Maps

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Fox et al. (2005) PNAS

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Fox et al. (2005) PNAS

positive negative Task-induced changes

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Diffusion Tractography

Fox et al. 2014 PNAS

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Results match anatomical connectivity relevant to DBS response

Fox et al. PNAS In Press

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DTI Network Rs-fcMRI Network

Honey et al. 2009 PNAS

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Research Applications of Rs-fcMRI

• Trial to trial variability in behavior

– (Fox et al. 2007 Neuron)

• Thalamic and cerebellar connections

– (Zhang et al. 2009 J. Neurophys , Buckner et al. 2011 J. Neurophys.)

• Individual differences in performance

– (Hampson et al. 2006 J. Neurosci, Koyama et al. 2009 J. Neurosci.)

• Correlates of learning

– (Lewis et al. 2009 PNAS)

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Clinical Applications of Rs-fcMRI

• Understanding disease pathophysiology
• Biomarkers / Diagnosis
• Guiding treatment

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Understanding Peduncular Hallucinosis

Boes et al. 2015 Brain

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Understanding Peduncular Hallucinosis

Boes et al. 2015 Brain

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Disease/Condition References Findings

Alzheimer’s (Allen et al. 2007; Greicius et al. 2004; Li et al. 2002; Supekar et al. 2008; Wang et al. 2006a; Wang et al. 2007; Wang et al. 2006b) Decreased correlations within the default mode network including hippocampi and decreased anticorrelations between the DMN and TPN PIB positive (Hedden et al. 2009; Sheline et al. 2009) Decreased correlations within the default mode network Mild Cognitive Impairment (Li et al. 2002; Sorg et al. 2007) Decreased correlations within the default mode network and decreased anticorrelations between the DMN and TPN Fronto-Temporal Dementia (Seeley et al. 2007a; Seeley et al. 2008) Decreased correlations within the salience network Healthy Aging (Andrews-Hanna et al. 2007; Damoiseaux et al. 2007) Decreased correlations within the default mode network Multiple Sclerosis (De Luca et al. 2005; Lowe et al. 2002) Decreased correlations within the somatomotor network ALS (Mohammadi et al. 2009) Decreased connectivity in DMN and premotor cortex Depression (Anand et al. 2009; Anand et al. 2005a; b; Bluhm et al. 2009a; Greicius et al. 2007) Variable: Decreased connectivity between dACC and limbic regions (amygdala, medial thalamus, pallidostriatum) increased connectivity within the DMN (esp. subgenual prefrontal cortex), decreased connectivity between DMN and caudate Bipolar (Anand et al. 2009) Decreased corticolimbic connectivity PTSD (Bluhm et al. 2009c) Decreased connectivity in the DMN Schizophrenia (Bluhm et al. 2007; Bluhm et al. 2009b; Jafri et al. 2008; Liang et al. 2006; Liu et al. 2006; Liu et al. 2008; Salvador et al. 2007; Whitfield-Gabrieli et al. 2009; Zhou et al. 2007) Variable: Decreased or increased DMN connectivity Schizophrenia 1 relatives (Whitfield-Gabrieli et al. 2009) Increased connectivity in the DMN ADHD (Cao et al. 2006; Castellanos et al. 2008; Tian et al. 2006; Wang et al. 2008; Zang et al. 2007; Zhu et al. 2008; Zhu et al. 2005) Variable: reduced connectivity within the DMN, reduced anticorrelations, increased connectivity in salience Autism (Cherkassky et al. 2006; Kennedy and Courchesne 2008; Monk et al. 2009; Weng et al. 2009) Decreased connectivity within the DMN (although hippocampus is variable and connectivity may be increased in younger patients) Tourette Syndrome (Church et al. 2009) Delayed maturation of task-control and cingulo-opercular networks Epilepsy (Bettus et al. 2009; Lui et al. 2008; Waites et al. 2006; Zhang et

• al. 2009a; Zhang et al. 2009b)

Variable: decreased connectivity in mult. networks including medial temporal lobe, decreased connectivity in DMN with generalized seizure Blindness (Liu et al. 2007; Yu et al. 2008) decreased connectivity within the visual cortices and between visual cortices and somatosensory, frontal motor and temporal multisensory cortices Chronic Pain (Cauda et al. 2009a; Cauda et al. 2009c; Cauda et al. 2009d; Greicius et al. 2008) Variable: Increased/decreased connectivity within the salience network, decreased connectivity in attention networks Neglect (He et al. 2007) Decreased connectivity within the dorsal and ventral attention networks Vegetative State (Boly et al. 2009; Cauda et al. 2009b) Progressively decreased DMN connectivity with progressive states of impaired consciousness

Fox and Greicius (2010) Frontiers Sys Neurosci

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Outline

• Intro to brain network imaging
• What can network imaging do for brain

stimulation?

• What can brain stimulation do for brain

networks?

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Therapeutic Brain Stimulation

Transcranial Magnetic Stimulation (TMS) Deep Brain Stimulation (DBS)

• Implanted by Neurosurgeon
• Constant stimulation
• 130-180 Hz
• FDA approved for Parkinson’s,

essential tremor, dystonia, OCD

• Noninvasive
• Repeated sessions of stimulation
• 10 Hz (excitatory), 1Hz (inhibitory)
• FDA approved for depression

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Therapeutic Brain Stimulation

Transcranial Magnetic Stimulation (TMS) Deep Brain Stimulation (DBS) Both are showing early signs of utility in many of the same disorders

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Disease Invasive (DBS) Noninvasive (TMS, tDCS) Addiction NA DLPFC (laterality unclear) Alzheimer’s Fornix Bilateral DLPFC (+/- parietal, temporal) Anorexia NA, Subgenual L DLPFC Depression Subgenual, VC/VS, NA, MFB, habenula Left DLPFC, R DLPFC Dystonia GPi SMA/ACC, Premotor Epilepsy Thalamus (AN, CM), MTL Active EEG focus Cerebellum Essential Tremor VIM Midline Cerebellum, Lateral Cerebellum, M1 Gait Dysfunction PPN M1 (leg area) Huntington’s GPi SMA Minimally Conscious Thalamus (intralaminar/CL, CM/Pf) R DLPFC, M1 Obsessive Compulsive Disorder VC/VS, NA, ALIC, STN L orbitofrontal, Pre-SMA Pain PAG, Thalamus (VPL/VPM) M1 Parkinson’s STN, GPi M1, SMA Tourette’s Thalamus (CM/Pf), GPi, NA, ALIC SMA

Fox et al. 2014 PNAS

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Therapeutic Brain Stimulation

Transcranial Magnetic Stimulation (TMS) Deep Brain Stimulation (DBS) Both propagate beyond the site of stimulation to impact a distributed network of brain regions

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TMS propagates trans-synaptically

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TMS propagates trans-synaptically

Fox et al. 2012 Neuroimage

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TMS propagates trans-synaptically

Fox et al. 2012 Neuroimage

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Fox et al. 2012 Neuroimage

TMS propagates trans-synaptically

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Guiding Logic

• 1. Both techniques are useful in many of the

same diseases

• 2. Both techniques propagate through

anatomical connections to impact distributed brain networks

P L E A S E D O N O T C O P Y

Guiding Logic

• 1. Both techniques are useful in many of the

same diseases

• 2. Both techniques propagate through

anatomical connections to impact distributed brain networks

• Are both techniques targeting the same

network?

P L E A S E D O N O T C O P Y

Disease Invasive (DBS) Noninvasive (TMS, tDCS) Addiction NA DLPFC (laterality unclear) Alzheimer’s Fornix Bilateral DLPFC (+/- parietal, temporal) Anorexia NA, Subgenual L DLPFC Depression Subgenual, VC/VS, NA, MFB, habenula Left DLPFC, R DLPFC Dystonia GPi SMA/ACC, Premotor Epilepsy Thalamus (AN, CM), MTL Active EEG focus Cerebellum Essential Tremor VIM Midline Cerebellum, Lateral Cerebellum, M1 Gait Dysfunction PPN M1 (leg area) Huntington’s GPi SMA Minimally Conscious Thalamus (intralaminar/CL, CM/Pf) R DLPFC, M1 Obsessive Compulsive Disorder VC/VS, NA, ALIC, STN L orbitofrontal, Pre-SMA Pain PAG, Thalamus (VPL/VPM) M1 Parkinson’s STN, GPi M1, SMA Tourette’s Thalamus (CM/Pf), GPi, NA, ALIC SMA

Fox et al. 2014 PNAS

P L E A S E D O N O T C O P Y

Disease Invasive (DBS) Noninvasive (TMS, tDCS) Addiction NA DLPFC (laterality unclear) Alzheimer’s Fornix Bilateral DLPFC (+/- parietal, temporal) Anorexia NA, Subgenual L DLPFC Depression Subgenual, VC/VS, NA, MFB, habenula Left DLPFC, R DLPFC Dystonia GPi SMA/ACC, Premotor Epilepsy Thalamus (AN, CM), MTL Active EEG focus Cerebellum Essential Tremor VIM Midline Cerebellum, Lateral Cerebellum, M1 Gait Dysfunction PPN M1 (leg area) Huntington’s GPi SMA Minimally Conscious Thalamus (intralaminar/CL, CM/Pf) R DLPFC, M1 Obsessive Compulsive Disorder VC/VS, NA, ALIC, STN L orbitofrontal, Pre-SMA Pain PAG, Thalamus (VPL/VPM) M1 Parkinson’s STN, GPi M1, SMA Tourette’s Thalamus (CM/Pf), GPi, NA, ALIC SMA

Fox et al. 2014 PNAS

P L E A S E D O N O T C O P Y

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Subgenual Seed Fox et al. 2012 Biol Psych.

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Subgenual Seed Fox et al. 2012 Biol Psych.

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Disease Invasive (DBS) Noninvasive (TMS, tDCS) Addiction NA DLPFC (laterality unclear) Alzheimer’s Fornix Bilateral DLPFC (+/- parietal, temporal) Anorexia NA, Subgenual L DLPFC Depression Subgenual, VC/VS, NA, MFB, habenula Left DLPFC, R DLPFC Dystonia GPi SMA/ACC, Premotor Epilepsy Thalamus (AN, CM), MTL Active EEG focus Cerebellum Essential Tremor VIM Midline Cerebellum, Lateral Cerebellum, M1 Gait Dysfunction PPN M1 (leg area) Huntington’s GPi SMA Minimally Conscious Thalamus (intralaminar/CL, CM/Pf) R DLPFC, M1 Obsessive Compulsive Disorder VC/VS, NA, ALIC, STN L orbitofrontal, Pre-SMA Pain PAG, Thalamus (VPL/VPM) M1 Parkinson’s STN, GPi M1, SMA Tourette’s Thalamus (CM/Pf), GPi, NA, ALIC SMA

Fox et al. 2014 PNAS

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Fox et al. 2014 PNAS Invasive and Noninvasive Brain Stimulation Sites are Linked Across 14 Diseases

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Invasive and Noninvasive Brain Stimulation Sites are Linked Across 14 Diseases

0.02 0.04 0.06 0.08 0.1 DBS Correlation (r) Best Noninvasive Stimulation Site Random Noninvasive Stimulation Sites

P < 0.005 Fox et al. 2014 PNAS

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Ineffective sites are characterized by an absence of functional connectivity

Parkinson’s Disease Pain Essential Tremor Depression Fox et al. 2014 PNAS

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The sign of the correlation (positive vs negative) relates to the reported utility of excitatory vs inhibitory stimulation

Fox et al. 2014 PNAS

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The sign of the correlation (positive vs negative) relates to the reported utility of excitatory vs inhibitory stimulation

Fox et al. 2014 PNAS

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• Can we take advantage of network

imaging to improve brain stimulation?

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Herwig et al. 2001 BIOL PSYCHIATRY 50:58–61

Targeting TMS in Depression: The 5 cm method

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Herwig et al. 2001 BIOL PSYCHIATRY 50:58–61

Targeting TMS in Depression: The 5 cm method

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Herwig et al. 2001 BIOL PSYCHIATRY 50:58–61

Targeting TMS in Depression: The 5 cm method

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Targeting TMS in Depression: The 5 cm method

Herwig et al. 2001 BIOL PSYCHIATRY 50:58–61 Only hit the “DLPFC” ~40% of the time

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TMS targets vary in their efficacy

Herbsman et al. 2009

Effective Ineffective

Fitzgerald et al. 2009

42% responders 18% responders

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Hypothesis:

• More effective TMS targets show stronger

connectivity to the subgenual than less effective targets

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• Avg. 5cm Target

Fitzgerald Target Less Effective 5cm More Effective 5cm

• 0.15
• 0.10
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0.00

Subgenual Correlation (r)

P < 0.005

• 0.30
• 0.20
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0.00

Subgenual Correlation (r)

P < 5 x 10-8 vs vs

Effective vs. Ineffective TMS Targets

Fox et al. 2012 Biol Psych.

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• Avg. 5cm Target

Fitzgerald Target Less Effective 5cm More Effective 5cm

vs vs

6

• 6

15

• 15

Effective vs. Ineffective TMS Targets

Fox et al. 2012 Biol Psych.

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Effective vs. Ineffective TMS Targets

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Optimizing the TMS target for depression

Subgenual Seed Efficacy-based Seed Map Fox et al. 2012 Biol Psych.

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0.53 0.73

DLPFC

Left DLPFC connectivity is highly variable between subjects

Mueller and Liu et al. Neuron 2013

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Individualized TMS targets for depression

Subgenual Seed Efficacy- based Seed Map Fox et al. 2012 Neuroimage

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Individualized TMS targets for depression

Subgenual Seed Efficacy- based Seed Map Fox et al. 2012 Neuroimage

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Subgenual Seed Efficacy- based Seed Map

Individual differences in functional connectivity are reproducible across days

Fox et al. 2012 Neuroimage

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Can we predict individual patient responses to TMS?

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(+) (-)

Why pick just one site?

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Why pick just one site?

Ruffini, Fox et al. 2014 Neuroimage

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Outline

• Intro to brain network imaging
• What can network imaging do for brain

stimulation?

• What can brain stimulation do for brain

networks?

P L E A S E D O N O T C O P Y

Disease/Condition References Findings

Alzheimer’s (Allen et al. 2007; Greicius et al. 2004; Li et al. 2002; Supekar et al. 2008; Wang et al. 2006a; Wang et al. 2007; Wang et al. 2006b) Decreased correlations within the default mode network including hippocampi and decreased anticorrelations between the DMN and TPN PIB positive (Hedden et al. 2009; Sheline et al. 2009) Decreased correlations within the default mode network Mild Cognitive Impairment (Li et al. 2002; Sorg et al. 2007) Decreased correlations within the default mode network and decreased anticorrelations between the DMN and TPN Fronto-Temporal Dementia (Seeley et al. 2007a; Seeley et al. 2008) Decreased correlations within the salience network Healthy Aging (Andrews-Hanna et al. 2007; Damoiseaux et al. 2007) Decreased correlations within the default mode network Multiple Sclerosis (De Luca et al. 2005; Lowe et al. 2002) Decreased correlations within the somatomotor network ALS (Mohammadi et al. 2009) Decreased connectivity in DMN and premotor cortex Depression (Anand et al. 2009; Anand et al. 2005a; b; Bluhm et al. 2009a; Greicius et al. 2007) Variable: Decreased connectivity between dACC and limbic regions (amygdala, medial thalamus, pallidostriatum) increased connectivity within the DMN (esp. subgenual prefrontal cortex), decreased connectivity between DMN and caudate Bipolar (Anand et al. 2009) Decreased corticolimbic connectivity PTSD (Bluhm et al. 2009c) Decreased connectivity in the DMN Schizophrenia (Bluhm et al. 2007; Bluhm et al. 2009b; Jafri et al. 2008; Liang et al. 2006; Liu et al. 2006; Liu et al. 2008; Salvador et al. 2007; Whitfield-Gabrieli et al. 2009; Zhou et al. 2007) Variable: Decreased or increased DMN connectivity Schizophrenia 1 relatives (Whitfield-Gabrieli et al. 2009) Increased connectivity in the DMN ADHD (Cao et al. 2006; Castellanos et al. 2008; Tian et al. 2006; Wang et al. 2008; Zang et al. 2007; Zhu et al. 2008; Zhu et al. 2005) Variable: reduced connectivity within the DMN, reduced anticorrelations, increased connectivity in salience Autism (Cherkassky et al. 2006; Kennedy and Courchesne 2008; Monk et al. 2009; Weng et al. 2009) Decreased connectivity within the DMN (although hippocampus is variable and connectivity may be increased in younger patients) Tourette Syndrome (Church et al. 2009) Delayed maturation of task-control and cingulo-opercular networks Epilepsy (Bettus et al. 2009; Lui et al. 2008; Waites et al. 2006; Zhang et

• al. 2009a; Zhang et al. 2009b)

Variable: decreased connectivity in mult. networks including medial temporal lobe, decreased connectivity in DMN with generalized seizure Blindness (Liu et al. 2007; Yu et al. 2008) decreased connectivity within the visual cortices and between visual cortices and somatosensory, frontal motor and temporal multisensory cortices Chronic Pain (Cauda et al. 2009a; Cauda et al. 2009c; Cauda et al. 2009d; Greicius et al. 2008) Variable: Increased/decreased connectivity within the salience network, decreased connectivity in attention networks Neglect (He et al. 2007) Decreased connectivity within the dorsal and ventral attention networks Vegetative State (Boly et al. 2009; Cauda et al. 2009b) Progressively decreased DMN connectivity with progressive states of impaired consciousness

Fox and Greicius (2010) Frontiers Sys Neurosci

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Eldaief et al. 2012 PNAS

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Conclusions

• Brain stimulation propagates through brain

networks

• Network imaging can help us understand

and guide brain stimulation

• Brain stimulation might be used to modify

connectivity in brain networks altered by disease

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Acknowledgements

Marc Raichle, Avi Snyder Mike Greicius Randy Buckner, Hesheng Liu, Justin Vincent, Tianyi Qian, Sophia Mueller, Verne Caviness Alvaro Pascual-Leone, Aaron Boes, Anne Weigand, Simon Laganiere, David Fischer

Funding

NINDS (R25, K23) NIMH (R21) AAN / ABF Sidney Baer Foundation

Giulio Ruffini Andres Lozano Mallar Chakravarty Sashank Prasad

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Questions?

Contact: foxmdphd@gmail.com

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