Volume 89, Issue 6, Pages (March 2016)

Slides:



Advertisements
Similar presentations
Soyoun Kim, Jaewon Hwang, Daeyeol Lee  Neuron 
Advertisements

Volume 63, Issue 3, Pages (August 2009)
Volume 60, Issue 4, Pages (November 2008)
Volume 73, Issue 3, Pages (February 2012)
Neuronal Correlates of Metacognition in Primate Frontal Cortex
Volume 77, Issue 5, Pages (March 2013)
Volume 63, Issue 6, Pages (September 2009)
Effective Connectivity between Hippocampus and Ventromedial Prefrontal Cortex Controls Preferential Choices from Memory  Sebastian Gluth, Tobias Sommer,
Medial Prefrontal Cortex Predicts Internally Driven Strategy Shifts
Volume 15, Issue 7, Pages (April 2005)
Differential Dynamics of Activity Changes in Dorsolateral and Dorsomedial Striatal Loops during Learning  Catherine A. Thorn, Hisham Atallah, Mark Howe,
Volume 72, Issue 4, Pages (November 2011)
Caspar M. Schwiedrzik, Winrich A. Freiwald  Neuron 
Daphna Shohamy, Anthony D. Wagner  Neuron 
Dynamic Nigrostriatal Dopamine Biases Action Selection
Huan Luo, Xing Tian, Kun Song, Ke Zhou, David Poeppel  Current Biology 
Learning to Simulate Others' Decisions
Volume 87, Issue 1, Pages (July 2015)
Perirhinal-Hippocampal Connectivity during Reactivation Is a Marker for Object-Based Memory Consolidation  Kaia L. Vilberg, Lila Davachi  Neuron  Volume.
Volume 63, Issue 4, Pages (August 2009)
Volume 63, Issue 3, Pages (August 2009)
Sheng Li, Stephen D. Mayhew, Zoe Kourtzi  Neuron 
Perceptual Learning and Decision-Making in Human Medial Frontal Cortex
Scale-Invariant Movement Encoding in the Human Motor System
Volume 93, Issue 2, Pages (January 2017)
Reversible Silencing of the Frontopolar Cortex Selectively Impairs Metacognitive Judgment on Non-experience in Primates  Kentaro Miyamoto, Rieko Setsuie,
Vincent B. McGinty, Antonio Rangel, William T. Newsome  Neuron 
Roman F. Loonis, Scott L. Brincat, Evan G. Antzoulatos, Earl K. Miller 
Feature- and Order-Based Timing Representations in the Frontal Cortex
Volume 79, Issue 4, Pages (August 2013)
Hedging Your Bets by Learning Reward Correlations in the Human Brain
CA3 Retrieves Coherent Representations from Degraded Input: Direct Evidence for CA3 Pattern Completion and Dentate Gyrus Pattern Separation  Joshua P.
Caspar M. Schwiedrzik, Winrich A. Freiwald  Neuron 
Volume 82, Issue 5, Pages (June 2014)
Selective Entrainment of Theta Oscillations in the Dorsal Stream Causally Enhances Auditory Working Memory Performance  Philippe Albouy, Aurélien Weiss,
Aryeh Hai Taub, Rita Perets, Eilat Kahana, Rony Paz  Neuron 
Consolidation Promotes the Emergence of Representational Overlap in the Hippocampus and Medial Prefrontal Cortex  Alexa Tompary, Lila Davachi  Neuron 
Volume 73, Issue 3, Pages (February 2012)
Dynamic Coding for Cognitive Control in Prefrontal Cortex
Volume 74, Issue 3, Pages (May 2012)
Between Thoughts and Actions: Motivationally Salient Cues Invigorate Mental Action in the Human Brain  Avi Mendelsohn, Alex Pine, Daniela Schiller  Neuron 
Volume 97, Issue 3, Pages e8 (February 2018)
Human Orbitofrontal Cortex Represents a Cognitive Map of State Space
Independent Category and Spatial Encoding in Parietal Cortex
BOLD fMRI Correlation Reflects Frequency-Specific Neuronal Correlation
Volume 50, Issue 3, Pages (May 2006)
John T. Arsenault, Koen Nelissen, Bechir Jarraya, Wim Vanduffel  Neuron 
Uma R. Karmarkar, Dean V. Buonomano  Neuron 
Ethan S. Bromberg-Martin, Masayuki Matsumoto, Okihide Hikosaka  Neuron 
Sharon C. Furtak, Omar J. Ahmed, Rebecca D. Burwell  Neuron 
Volume 89, Issue 6, Pages (March 2016)
Neural Mechanisms Underlying Human Consensus Decision-Making
Serial, Covert Shifts of Attention during Visual Search Are Reflected by the Frontal Eye Fields and Correlated with Population Oscillations  Timothy J.
Volume 59, Issue 5, Pages (September 2008)
Normal Movement Selectivity in Autism
Volume 76, Issue 4, Pages (November 2012)
Learning to Simulate Others' Decisions
Brain Mechanisms for Extracting Spatial Information from Smell
Sébastien Marti, Jean-Rémi King, Stanislas Dehaene  Neuron 
Michael J. Frank, Brion S. Woroch, Tim Curran  Neuron 
Jude F. Mitchell, Kristy A. Sundberg, John H. Reynolds  Neuron 
Megan E. Speer, Jamil P. Bhanji, Mauricio R. Delgado  Neuron 
Temporal Specificity of Reward Prediction Errors Signaled by Putative Dopamine Neurons in Rat VTA Depends on Ventral Striatum  Yuji K. Takahashi, Angela J.
Attention Samples Stimuli Rhythmically
Encoding of Stimulus Probability in Macaque Inferior Temporal Cortex
Medial Prefrontal Cortex Predicts Internally Driven Strategy Shifts
John D.E. Gabrieli, Satrajit S. Ghosh, Susan Whitfield-Gabrieli  Neuron 
Volume 99, Issue 1, Pages e4 (July 2018)
Volume 61, Issue 6, Pages (March 2009)
Volume 63, Issue 6, Pages (September 2009)
Presentation transcript:

Volume 89, Issue 6, Pages 1331-1342 (March 2016) Cognitive Neurostimulation: Learning to Volitionally Sustain Ventral Tegmental Area Activation  Jeff J. MacInnes, Kathryn C. Dickerson, Nan-kuei Chen, R. Alison Adcock  Neuron  Volume 89, Issue 6, Pages 1331-1342 (March 2016) DOI: 10.1016/j.neuron.2016.02.002 Copyright © 2016 Elsevier Inc. Terms and Conditions

Figure 1 Task Design Pre-test and Post-test: all groups completed identical test runs. During ACTIVATE trials, participants tried to increase motivation using only internally generated thoughts and imagery, without reward cues or rt-fMRI neurofeedback. During COUNT baseline trials, participants counted backward. Training: during ACTIVATE trials, participants in VTA and NAcc Feedback groups tried to increase motivation and received veridical neurofeedback from either VTA or NAcc. FF participants received noise neurofeedback they were told was veridical. VC participants viewed predictable patterns indicating the duration of the ACTIVATE period. During REST trials, each group’s thermometer display presented a random (VTA Feedback, NAcc Feedback, FF groups) or predictable (VC group) pattern. COUNT trials were identical across all runs. An inter-trial interval ranging from 3.5–5.5 s separated all trials. Neuron 2016 89, 1331-1342DOI: (10.1016/j.neuron.2016.02.002) Copyright © 2016 Elsevier Inc. Terms and Conditions

Figure 2 Significant VTA Activation and Group Differences at Post-Test following Feedback Training (A) VTA ROI defined in an independent sample of 50 participants. Color scale denotes probabilistic weighting of the ROI. (B) Test run × group interaction plot (p < 0.05) representing percentage signal difference for mean ACTIVATE > COUNT values. Pre-test: no significant activations or group differences. Post-test: VTA Feedback group self-activated the VTA relative to baseline (p < 0.005) and to Control (p < 0.0005) and FF (p < 0.05) groups. Neuron 2016 89, 1331-1342DOI: (10.1016/j.neuron.2016.02.002) Copyright © 2016 Elsevier Inc. Terms and Conditions

Figure 3 Consistent VTA Activation and Group Differences Emerged during Feedback Training ERA time courses for ACTIVATE > COUNT during Test and Training trials. Waveforms represent percentage signal difference from baseline (shading, ± SEM). The time course for both ACTIVATE and COUNT is calculated relative to the preceding 3-s inter-trial interval. To compare the time series, we subtracted COUNT from the ACTIVATE time series. Time courses were segmented at 10 s to examine sustained activation (solid horizontal bars represent means). Pre-test: no significant positive activations or group differences. Training: VTA Feedback group showed greater VTA activation than the VC group in both early (p < 0.0001) and late phases of trials (p < 0.05; i.e., across the entire 20 s), but did not significantly differ from FF group (p > 0.1). Post-test: the VTA Feedback group sustained greater activation relative to baseline (early, late, and overall p < 0.05), relative to the VC group (early, late, and overall p < 0.005), and relative to FF group (late and overall p < 0.05). Post hoc t tests (p < 0.05) are denoted by the keys below the time courses. Center white circle, baseline; orange, VTA Feedback; blue, VC; gray, FF; black line, a significant difference. Neuron 2016 89, 1331-1342DOI: (10.1016/j.neuron.2016.02.002) Copyright © 2016 Elsevier Inc. Terms and Conditions

Figure 4 No Significant NAcc Activation or Group Differences in Test Runs (A) NAcc ROI defined by Greer et al. (2014). (B) Non-significant test run × group interaction plot (p > 0.1) representing percentage signal difference for mean ACTIVATE > COUNT values. Pre-test: No significant corrected positive activations or group differences were observed. Both control groups were significantly deactivated relative to baseline (p < 0.05). Post-test: The groups did not significantly differ from each other (p ≥ 0.09) and no group self-activated the NAcc relative to baseline (p ≥ 0.1). Neuron 2016 89, 1331-1342DOI: (10.1016/j.neuron.2016.02.002) Copyright © 2016 Elsevier Inc. Terms and Conditions

Figure 5 No Significant NAcc Activation or Group Differences prior to, during, or following Feedback Training ERAs for ACTIVATE > COUNT during Test and Training trials. Waveforms represent percentage signal difference from baseline (shading, ± SEM). The time course for both ACTIVATE and COUNT is calculated relative to the preceding 3-s inter-trial interval. To compare the time series, we subtracted COUNT from the ACTIVATE time series. Time courses were segmented at 10 s to examine sustained activation (solid horizontal bars represent means). Pre-test: no significant corrected activations or group differences. Training: no significant activations or group differences. Post-test: no significant activations or group differences. Significant mean differences from baseline (p < 0.05) are denoted by the keys below the time courses. Center white circle, baseline; green, NAcc Feedback; blue, VC; gray, FF; black line, a significant difference. Neuron 2016 89, 1331-1342DOI: (10.1016/j.neuron.2016.02.002) Copyright © 2016 Elsevier Inc. Terms and Conditions

Figure 6 Functional Connectivity Significantly Increased in Mesolimbic Networks following VTA, but Not NAcc, Feedback In the VTA Feedback group (left), both the VTA and the NAcc ROIs exhibited significantly greater Pre-test to Post-test connectivity with the bilateral HPC (p < 0.05). There were no significant connectivity changes for the NAcc Feedback group (p > 0.1; right), resulting in a significant Run × Group interaction for these ROIs (see Table S2 in the Supplemental Information). Line thickness denotes the change in correlation strength from the Pre-test to Post-test (Z scored). Line color indicates significant/non-significant changes in connectivity (dark/light gray). The line pattern indicates the direction of change in Z-scored r values (solid lines, increased connectivity from Pre-test to Post-test; dotted lines, decreased connectivity from Pre-test to Post-test). Neuron 2016 89, 1331-1342DOI: (10.1016/j.neuron.2016.02.002) Copyright © 2016 Elsevier Inc. Terms and Conditions