1
|
Aziz-Safaie T, Müller VI, Langner R, Eickhoff SB, Cieslik EC. The effect of task complexity on the neural network for response inhibition: An ALE meta-analysis. Neurosci Biobehav Rev 2024; 158:105544. [PMID: 38220034 DOI: 10.1016/j.neubiorev.2024.105544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 12/18/2023] [Accepted: 01/09/2024] [Indexed: 01/16/2024]
Abstract
Response inhibition is classically investigated using the go/no-go (GNGT) and stop-signal task (SST), which conceptually measure different subprocesses of inhibition. Further, different task versions with varying levels of additional executive control demands exist, making it difficult to identify the core neural correlates of response inhibition independent of variations in task complexity. Using neuroimaging meta-analyses, we show that a divergent pattern of regions is consistently involved in the GNGT versus SST, arguing for different mechanisms involved when performing the two tasks. Further, for the GNGT a strong effect of task complexity was found, with regions of the multiple demand network (MDN) consistently involved particularly in the complex GNGT. In contrast, both standard and complex SST recruited the MDN to a similar degree. These results complement behavioral evidence suggesting that inhibitory control becomes automatic after some practice and is performed without input of higher control regions in the classic, standard GNGT, but continues to be implemented in a top-down controlled fashion in the SST.
Collapse
Affiliation(s)
- Taraneh Aziz-Safaie
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Germany.
| | - Veronika I Müller
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Germany
| | - Robert Langner
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Germany
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Germany
| | - Edna C Cieslik
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Germany.
| |
Collapse
|
2
|
Cieslik EC, Ullsperger M, Gell M, Eickhoff SB, Langner R. Success versus failure in cognitive control: Meta-analytic evidence from neuroimaging studies on error processing. Neurosci Biobehav Rev 2024; 156:105468. [PMID: 37979735 DOI: 10.1016/j.neubiorev.2023.105468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 10/23/2023] [Accepted: 11/13/2023] [Indexed: 11/20/2023]
Abstract
Brain mechanisms of error processing have often been investigated using response interference tasks and focusing on the posterior medial frontal cortex, which is also implicated in resolving response conflict in general. Thereby, the role other brain regions may play has remained undervalued. Here, activation likelihood estimation meta-analyses were used to synthesize the neuroimaging literature on brain activity related to committing errors versus responding successfully in interference tasks and to test for commonalities and differences. The salience network and the temporoparietal junction were commonly recruited irrespective of whether responses were correct or incorrect, pointing towards a general involvement in coping with situations that call for increased cognitive control. The dorsal posterior cingulate cortex, posterior thalamus, and left superior frontal gyrus showed error-specific convergence, which underscores their consistent involvement when performance goals are not met. In contrast, successful responding revealed stronger convergence in the dorsal attention network and lateral prefrontal regions. Underrecruiting these regions in error trials may reflect failures in activating the task-appropriate stimulus-response contingencies necessary for successful response execution.
Collapse
Affiliation(s)
- Edna C Cieslik
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany.
| | - Markus Ullsperger
- Institute of Psychology, Otto-von-Guericke University, D-39106 Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Martin Gell
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH, Aachen, Germany
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Robert Langner
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| |
Collapse
|
3
|
Heckner MK, Cieslik EC, Paas Oliveros LK, Eickhoff SB, Patil KR, Langner R. Predicting executive functioning from brain networks: modality specificity and age effects. Cereb Cortex 2023; 33:10997-11009. [PMID: 37782935 PMCID: PMC10646699 DOI: 10.1093/cercor/bhad338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 08/25/2023] [Accepted: 08/26/2023] [Indexed: 10/04/2023] Open
Abstract
Healthy aging is associated with structural and functional network changes in the brain, which have been linked to deterioration in executive functioning (EF), while their neural implementation at the individual level remains unclear. As the biomarker potential of individual resting-state functional connectivity (RSFC) patterns has been questioned, we investigated to what degree individual EF abilities can be predicted from the gray-matter volume (GMV), regional homogeneity, fractional amplitude of low-frequency fluctuations (fALFF), and RSFC within EF-related, perceptuo-motor, and whole-brain networks in young and old adults. We examined whether the differences in out-of-sample prediction accuracy were modality-specific and depended on age or task-demand levels. Both uni- and multivariate analysis frameworks revealed overall low prediction accuracies and moderate-to-weak brain-behavior associations (R2 < 0.07, r < 0.28), further challenging the idea of finding meaningful markers for individual EF performance with the metrics used. Regional GMV, well linked to overall atrophy, carried the strongest information about individual EF differences in older adults, whereas fALFF, measuring functional variability, did so for younger adults. Our study calls for future research analyzing more global properties of the brain, different task-states and applying adaptive behavioral testing to result in sensitive predictors for young and older adults, respectively.
Collapse
Affiliation(s)
- Marisa K Heckner
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40204 Düsseldorf, Germany
| | - Edna C Cieslik
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40204 Düsseldorf, Germany
| | - Lya K Paas Oliveros
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40204 Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40204 Düsseldorf, Germany
| | - Kaustubh R Patil
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40204 Düsseldorf, Germany
| | - Robert Langner
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40204 Düsseldorf, Germany
| |
Collapse
|
4
|
Boeken OJ, Cieslik EC, Langner R, Markett S. Characterizing functional modules in the human thalamus: coactivation-based parcellation and systems-level functional decoding. Brain Struct Funct 2023; 228:1811-1834. [PMID: 36547707 PMCID: PMC10516793 DOI: 10.1007/s00429-022-02603-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 12/08/2022] [Indexed: 12/24/2022]
Abstract
The human thalamus relays sensory signals to the cortex and facilitates brain-wide communication. The thalamus is also more directly involved in sensorimotor and various cognitive functions but a full characterization of its functional repertoire, particularly in regard to its internal anatomical structure, is still outstanding. As a putative hub in the human connectome, the thalamus might reveal its functional profile only in conjunction with interconnected brain areas. We therefore developed a novel systems-level Bayesian reverse inference decoding that complements the traditional neuroinformatics approach towards a network account of thalamic function. The systems-level decoding considers the functional repertoire (i.e., the terms associated with a brain region) of all regions showing co-activations with a predefined seed region in a brain-wide fashion. Here, we used task-constrained meta-analytic connectivity-based parcellation (MACM-CBP) to identify thalamic subregions as seed regions and applied the systems-level decoding to these subregions in conjunction with functionally connected cortical regions. Our results confirm thalamic structure-function relationships known from animal and clinical studies and revealed further associations with language, memory, and locomotion that have not been detailed in the cognitive neuroscience literature before. The systems-level decoding further uncovered large systems engaged in autobiographical memory and nociception. We propose this novel decoding approach as a useful tool to detect previously unknown structure-function relationships at the brain network level, and to build viable starting points for future studies.
Collapse
Affiliation(s)
- Ole J Boeken
- Faculty of Life Sciences, Department of Molecular Psychology, Humboldt-Universität Zu Berlin, Rudower Chaussee 18, 12489, Berlin, Germany.
| | - Edna C Cieslik
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Robert Langner
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Sebastian Markett
- Faculty of Life Sciences, Department of Molecular Psychology, Humboldt-Universität Zu Berlin, Rudower Chaussee 18, 12489, Berlin, Germany
| |
Collapse
|
5
|
Paas Oliveros LK, Cieslik EC, Pieczykolan A, Pläschke RN, Eickhoff SB, Langner R. Brain functional characterization of response-code conflict in dual-tasking and its modulation by age. Cereb Cortex 2023; 33:10155-10180. [PMID: 37540164 PMCID: PMC10502578 DOI: 10.1093/cercor/bhad273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 06/25/2023] [Accepted: 06/26/2023] [Indexed: 08/05/2023] Open
Abstract
Crosstalk between conflicting response codes contributes to interference in dual-tasking, an effect exacerbated in advanced age. Here, we investigated (i) brain activity correlates of such response-code conflicts, (ii) activity modulations by individual dual-task performance and related cognitive abilities, (iii) task-modulated connectivity within the task network, and (iv) age-related differences in all these aspects. Young and older adults underwent fMRI while responding to the pitch of tones through spatially mapped speeded button presses with one or two hands concurrently. Using opposing stimulus-response mappings between hands, we induced conflict between simultaneously activated response codes. These response-code conflicts elicited activation in key regions of the multiple-demand network. While thalamic and parietal areas of the conflict-related network were modulated by attentional, working-memory and task-switching abilities, efficient conflict resolution in dual-tasking mainly relied on increasing supplementary motor activity. Older adults showed non-compensatory hyperactivity in left superior frontal gyrus, and higher right premotor activity was modulated by working-memory capacity. Finally, connectivity between premotor or parietal seed regions and the conflict-sensitive network was neither conflict-specific nor age-sensitive. Overall, resolving dual-task response-code conflict recruited substantial parts of the multiple-demand network, whose activity and coupling, however, were only little affected by individual differences in task performance or age.
Collapse
Affiliation(s)
- Lya K Paas Oliveros
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Forschungszentrum Jülich, Jülich 52425, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf 40225, Germany
| | - Edna C Cieslik
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Forschungszentrum Jülich, Jülich 52425, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf 40225, Germany
| | - Aleks Pieczykolan
- Rheinische Fachhochschule – University of Applied Sciences, Cologne 50923, Germany
| | - Rachel N Pläschke
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf 40225, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Forschungszentrum Jülich, Jülich 52425, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf 40225, Germany
| | - Robert Langner
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Forschungszentrum Jülich, Jülich 52425, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf 40225, Germany
| |
Collapse
|
6
|
Heckner MK, Cieslik EC, Oliveros LKP, Eickhoff SB, Patil KR, Langner R. Predicting Executive Functioning from Brain Networks: Modality Specificity and Age Effects. bioRxiv 2023:2023.06.29.547036. [PMID: 37425780 PMCID: PMC10327061 DOI: 10.1101/2023.06.29.547036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Healthy aging is associated with structural and functional network changes in the brain, which have been linked to deterioration in executive functioning (EF), while their neural implementation at the individual level remains unclear. As the biomarker potential of individual resting-state functional connectivity (RSFC) patterns has been questioned, we investigated to what degree individual EF abilities can be predicted from gray-matter volume (GMV), regional homogeneity, fractional amplitude of low-frequency fluctuations (fALFF), and RSFC within EF-related, perceptuo-motor, and whole-brain networks in young and old adults. We examined whether differences in out-of-sample prediction accuracy were modality-specific and depended on age or task-demand levels. Both uni- and multivariate analysis frameworks revealed overall low prediction accuracies and moderate to weak brain-behavior associations (R2 < .07, r < .28), further challenging the idea of finding meaningful markers for individual EF performance with the metrics used. Regional GMV, well linked to overall atrophy, carried the strongest information about individual EF differences in older adults, whereas fALFF, measuring functional variability, did so for younger adults. Our study calls for future research analyzing more global properties of the brain, different task-states and applying adaptive behavioral testing to result in sensitive predictors for young and older adults, respectively.
Collapse
Affiliation(s)
- Marisa K. Heckner
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Edna C. Cieslik
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Lya K. Paas Oliveros
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Simon B. Eickhoff
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Kaustubh R. Patil
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Robert Langner
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| |
Collapse
|
7
|
Heckner MK, Cieslik EC, Patil KR, Gell M, Eickhoff SB, Hoffstädter F, Langner R. Predicting executive functioning from functional brain connectivity: network specificity and age effects. Cereb Cortex 2023; 33:6495-6507. [PMID: 36635227 PMCID: PMC10233269 DOI: 10.1093/cercor/bhac520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 12/07/2022] [Accepted: 12/08/2022] [Indexed: 01/14/2023] Open
Abstract
Healthy aging is associated with altered executive functioning (EF). Earlier studies found age-related differences in EF performance to be partially accounted for by changes in resting-state functional connectivity (RSFC) within brain networks associated with EF. However, it remains unclear which role RSFC in EF-associated networks plays as a marker for individual differences in EF performance. Here, we investigated to what degree individual abilities across 3 different EF tasks can be predicted from RSFC within EF-related, perceptuo-motor, whole-brain, and random networks separately in young and old adults. Specifically, we were interested if (i) young and old adults differ in predictability depending on network or EF demand level (high vs. low), (ii) an EF-related network outperforms EF-unspecific networks when predicting EF abilities, and (iii) this pattern changes with demand level. Both our uni- and multivariate analysis frameworks analyzing interactions between age × demand level × networks revealed overall low prediction accuracies and a general lack of specificity regarding neurobiological networks for predicting EF abilities. This questions the idea of finding markers for individual EF performance in RSFC patterns and calls for future research replicating the current approach in different task states, brain modalities, different, larger samples, and with more comprehensive behavioral measures.
Collapse
Affiliation(s)
- Marisa K Heckner
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Edna C Cieslik
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Kaustubh R Patil
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Martin Gell
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, 52074 Aachen, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Felix Hoffstädter
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Robert Langner
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| |
Collapse
|
8
|
Cieslik EC, Ullsperger M, Gell M, Eickhoff SB, Langner R. Success versus failure in cognitive control: meta-analytic evidence from neuroimaging studies on error processing. bioRxiv 2023:2023.05.10.540136. [PMID: 37214978 PMCID: PMC10197606 DOI: 10.1101/2023.05.10.540136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Brain mechanisms of error processing have often been investigated using response interference tasks and focusing on the posterior medial frontal cortex, which is also implicated in resolving response conflict in general. Thereby, the role other brain regions may play has remained undervalued. Here, activation likelihood estimation meta-analyses were used to synthesize the neuroimaging literature on brain activity related to committing errors versus responding successfully in interference tasks and to test for commonalities and differences. The salience network and the temporoparietal junction were commonly recruited irrespective of whether responses were correct or incorrect, pointing towards a general involvement in coping with situations that call for increased cognitive control. The dorsal posterior cingulate cortex, posterior thalamus, and left superior frontal gyrus showed error-specific convergence, which underscores their consistent involvement when performance goals are not met. In contrast, successful responding revealed stronger convergence in the dorsal attention network and lateral prefrontal regions. Underrecruiting these regions in error trials may reflect failures in activating the task-appropriate stimulus-response contingencies necessary for successful response execution.
Collapse
Affiliation(s)
- Edna C. Cieslik
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Markus Ullsperger
- Institute of Psychology, Otto-von-Guericke University, D-39106 Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Martin Gell
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Simon B. Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Robert Langner
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| |
Collapse
|
9
|
Frahm L, Cieslik EC, Hoffstaedter F, Satterthwaite TD, Fox PT, Langner R, Eickhoff SB. Evaluation of thresholding methods for activation likelihood estimation meta-analysis via large-scale simulations. Hum Brain Mapp 2022; 43:3987-3997. [PMID: 35535616 PMCID: PMC9374884 DOI: 10.1002/hbm.25898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 02/14/2022] [Accepted: 04/19/2022] [Indexed: 11/17/2022] Open
Abstract
In recent neuroimaging studies, threshold‐free cluster enhancement (TFCE) gained popularity as a sophisticated thresholding method for statistical inference. It was shown to feature higher sensitivity than the frequently used approach of controlling the cluster‐level family‐wise error (cFWE) and it does not require setting a cluster‐forming threshold at voxel level. Here, we examined the applicability of TFCE to a widely used method for coordinate‐based neuroimaging meta‐analysis, Activation Likelihood Estimation (ALE), by means of large‐scale simulations. We created over 200,000 artificial meta‐analysis datasets by independently varying the total number of experiments included and the amount of spatial convergence across experiments. Next, we applied ALE to all datasets and compared the performance of TFCE to both voxel‐level and cluster‐level FWE correction approaches. All three multiple‐comparison correction methods yielded valid results, with only about 5% of the significant clusters being based on spurious convergence, which corresponds to the nominal level the methods were controlling for. On average, TFCE's sensitivity was comparable to that of cFWE correction, but it was slightly worse for a subset of parameter combinations, even after TFCE parameter optimization. cFWE yielded the largest significant clusters, closely followed by TFCE, while voxel‐level FWE correction yielded substantially smaller clusters, showcasing its high spatial specificity. Given that TFCE does not outperform the standard cFWE correction but is computationally much more expensive, we conclude that employing TFCE for ALE cannot be recommended to the general user.
Collapse
Affiliation(s)
- Lennart Frahm
- Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, Aachen, Germany.,Institute of Neuroscience and Medicine (INM7: Brain and Behavior), Research Centre Jülich, Jülich, Germany
| | - Edna C Cieslik
- Institute of Neuroscience and Medicine (INM7: Brain and Behavior), Research Centre Jülich, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine (INM7: Brain and Behavior), Research Centre Jülich, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Theodore D Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Penn Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center, San Antonio, Texas, USA
| | - Robert Langner
- Institute of Neuroscience and Medicine (INM7: Brain and Behavior), Research Centre Jülich, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM7: Brain and Behavior), Research Centre Jülich, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| |
Collapse
|
10
|
Heckner MK, Cieslik EC, Eickhoff SB, Camilleri JA, Hoffstaedter F, Langner R. The Aging Brain and Executive Functions Revisited: Implications from Meta-analytic and Functional-Connectivity Evidence. J Cogn Neurosci 2021; 33:1716-1752. [PMID: 32762523 DOI: 10.1162/jocn_a_01616] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Healthy aging is associated with changes in cognitive performance, including executive functions (EFs) and their associated brain activation patterns. However, it has remained unclear which EF-related brain regions are affected consistently, because the results of pertinent neuroimaging studies and earlier meta-analyses vary considerably. We, therefore, conducted new rigorous meta-analyses of published age differences in EF-related brain activity. Out of a larger set of regions associated with EFs, only left inferior frontal junction and left anterior cuneus/precuneus were found to show consistent age differences. To further characterize these two age-sensitive regions, we performed seed-based resting-state functional connectivity (RS-FC) analyses using fMRI data from a large adult sample with a wide age range. We also assessed associations of the two regions' whole-brain RS-FC patterns with age and EF performance. Although our results largely point toward a domain-general role of left inferior frontal junction in EFs, the pattern of individual study contributions to the meta-analytic results suggests process-specific modulations by age. Our analyses further indicate that the left anterior cuneus/precuneus is recruited differently by older (compared with younger) adults during EF tasks, potentially reflecting inefficiencies in switching the attentional focus. Overall, our findings question earlier meta-analytic results and suggest a larger heterogeneity of age-related differences in brain activity associated with EFs. Hence, they encourage future research that pays greater attention to replicability, investigates age-related differences in deactivation, and focuses on more narrowly defined EF subprocesses, combining multiple behavioral assessments with multimodal imaging.
Collapse
Affiliation(s)
- Marisa K Heckner
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf
| | - Edna C Cieslik
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf
| | - Julia A Camilleri
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf
| | - Robert Langner
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf
| |
Collapse
|
11
|
Heckner MK, Cieslik EC, Küppers V, Fox PT, Eickhoff SB, Langner R. Delineating visual, auditory and motor regions in the human brain with functional neuroimaging: a BrainMap-based meta-analytic synthesis. Sci Rep 2021; 11:9942. [PMID: 33976234 PMCID: PMC8113600 DOI: 10.1038/s41598-021-88773-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 04/13/2021] [Indexed: 02/03/2023] Open
Abstract
Most everyday behaviors and laboratory tasks rely on visual, auditory and/or motor-related processes. Yet, to date, there has been no large-scale quantitative synthesis of functional neuroimaging studies mapping the brain regions consistently recruited during such perceptuo-motor processing. We therefore performed three coordinate-based meta-analyses, sampling the results of neuroimaging experiments on visual (n = 114), auditory (n = 122), or motor-related (n = 251) processing, respectively, from the BrainMap database. Our analyses yielded both regions known to be recruited for basic perceptual or motor processes and additional regions in posterior frontal cortex. Comparing our results with data-driven network definitions based on resting-state functional connectivity revealed good overlap in expected regions but also showed that perceptual and motor task-related activations consistently involve additional frontal, cerebellar, and subcortical areas associated with "higher-order" cognitive functions, extending beyond what is captured when the brain is at "rest." Our resulting sets of domain-typical brain regions can be used by the neuroimaging community as robust functional definitions or masks of regions of interest when investigating brain correlates of perceptual or motor processes and their interplay with other mental functions such as cognitive control or affective processing. The maps are made publicly available via the ANIMA database.
Collapse
Affiliation(s)
- Marisa K Heckner
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425, Jülich, Germany.
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
| | - Edna C Cieslik
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Vincent Küppers
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Peter T Fox
- Research Imaging Center, University of Texas Health Science Center, San Antonio, TX, USA
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Robert Langner
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425, Jülich, Germany.
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
| |
Collapse
|
12
|
Chen J, Wensing T, Hoffstaedter F, Cieslik EC, Müller VI, Patil KR, Aleman A, Derntl B, Gruber O, Jardri R, Kogler L, Sommer IE, Eickhoff SB, Nickl-Jockschat T. Neurobiological substrates of the positive formal thought disorder in schizophrenia revealed by seed connectome-based predictive modeling. Neuroimage Clin 2021; 30:102666. [PMID: 34215141 PMCID: PMC8105296 DOI: 10.1016/j.nicl.2021.102666] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 04/01/2021] [Accepted: 04/03/2021] [Indexed: 12/14/2022]
Abstract
Formal thought disorder (FTD) is a core symptom of schizophrenia, but its neurobiological substrates remain elusive. Resting-state functional connectivity (rsFC) of three meta-analytically defined seeds were correlated to positive and negative symptom dimensions of FTD. RsFC patterns allowed individual prediction of positive FTD symptom severity. These findings generalized to an independent data set. Our study has identified robust neurobiological correlates of positive FTD in schizophrenia.
Formal thought disorder (FTD) is a core symptom cluster of schizophrenia, but its neurobiological substrates remain poorly understood. Here we collected resting-state fMRI data from 276 subjects at seven sites and employed machine-learning to investigate the neurobiological correlates of FTD along positive and negative symptom dimensions in schizophrenia. Three a priori, meta-analytically defined FTD-related brain regions were used as seeds to generate whole-brain resting-state functional connectivity (rsFC) maps, which were then compared between schizophrenia patients and controls. A repeated cross-validation procedure was realized within the patient group to identify clusters whose rsFC patterns to the seeds were repeatedly observed as significantly associated with specific FTD dimensions. These repeatedly identified clusters (i.e., robust clusters) were functionally characterized and the rsFC patterns were used for predictive modeling to investigate predictive capacities for individual FTD dimensional-scores. Compared with controls, differential rsFC was found in patients in fronto-temporo-thalamic regions. Our cross-validation procedure revealed significant clusters only when assessing the seed-to-whole-brain rsFC patterns associated with positive-FTD. RsFC patterns of three fronto-temporal clusters, associated with higher-order cognitive processes (e.g., executive functions), specifically predicted individual positive-FTD scores (p = 0.005), but not other positive symptoms, and the PANSS general psychopathology subscale (p > 0.05). The prediction of positive-FTD was moreover generalized to an independent dataset (p = 0.013). Our study has identified neurobiological correlates of positive FTD in schizophrenia in a network associated with higher-order cognitive functions, suggesting a dysexecutive contribution to FTD in schizophrenia. We regard our findings as robust, as they allow a prediction of individual-level symptom severity.
Collapse
Affiliation(s)
- Ji Chen
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Tobias Wensing
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH, Aachen, Germany; JARA Translational Brain Medicine, Aachen, Germany
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Edna C Cieslik
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Veronika I Müller
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Kaustubh R Patil
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - André Aleman
- Department of Neuroscience, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Birgit Derntl
- Department of Psychiatry and Psychotherapy, Medical School, University of Tübingen, Germany
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Germany
| | - Renaud Jardri
- Univ Lille, INSERM U1172, Lille Neuroscience & Cognition Centre, Plasticity &SubjectivitY Team & CHU Lille, Fontan Hospital, CURE Platform, Lille, France
| | - Lydia Kogler
- Department of Psychiatry and Psychotherapy, Medical School, University of Tübingen, Germany
| | - Iris E Sommer
- Department of Biomedical Science of Cells and Systems, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Thomas Nickl-Jockschat
- Iowa Neuroscience Institute, Carver College of Medicine, University of Iowa, Iowa City, IA, United States; Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, United States.
| |
Collapse
|
13
|
Pläschke RN, Patil KR, Cieslik EC, Nostro AD, Varikuti DP, Plachti A, Lösche P, Hoffstaedter F, Kalenscher T, Langner R, Eickhoff SB. Age differences in predicting working memory performance from network-based functional connectivity. Cortex 2020; 132:441-459. [PMID: 33065515 PMCID: PMC7778730 DOI: 10.1016/j.cortex.2020.08.012] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 06/27/2020] [Accepted: 08/23/2020] [Indexed: 01/14/2023]
Abstract
Deterioration in working memory capacity (WMC) has been associated with normal aging, but it remains unknown how age affects the relationship between WMC and connectivity within functional brain networks. We therefore examined the predictability of WMC from fMRI-based resting-state functional connectivity (RSFC) within eight meta-analytically defined functional brain networks and the connectome in young and old adults using relevance vector machine in a robust cross-validation scheme. Particular brain networks have been associated with mental functions linked to WMC to a varying degree and are associated with age-related differences in performance. Comparing prediction performance between the young and old sample revealed age-specific effects: In young adults, we found a general unpredictability of WMC from RSFC in networks subserving WM, cognitive action control, vigilant attention, theory-of-mind cognition, and semantic memory, whereas in older adults each network significantly predicted WMC. Moreover, both WM-related and WM-unrelated networks were differently predictive in older adults with low versus high WMC. These results indicate that the within-network functional coupling during task-free states is specifically related to individual task performance in advanced age, suggesting neural-level reorganization. In particular, our findings support the notion of a decreased segregation of functional brain networks, deterioration of network integrity within different networks and/or compensation by reorganization as factors driving associations between individual WMC and within-network RSFC in older adults. Thus, using multivariate pattern regression provided novel insights into age-related brain reorganization by linking cognitive capacity to brain network integrity.
Collapse
Affiliation(s)
- Rachel N Pläschke
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
| | - Kaustubh R Patil
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Edna C Cieslik
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Alessandra D Nostro
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Deepthi P Varikuti
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Anna Plachti
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Patrick Lösche
- Leibniz Institute for International Educational Research (DIPF), Centre for Research on Human Development and Education, Frankfurt am Main, Germany
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Tobias Kalenscher
- Comparative Psychology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Robert Langner
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
| |
Collapse
|
14
|
Botvinik-Nezer R, Holzmeister F, Camerer CF, Dreber A, Huber J, Johannesson M, Kirchler M, Iwanir R, Mumford JA, Adcock RA, Avesani P, Baczkowski BM, Bajracharya A, Bakst L, Ball S, Barilari M, Bault N, Beaton D, Beitner J, Benoit RG, Berkers RMWJ, Bhanji JP, Biswal BB, Bobadilla-Suarez S, Bortolini T, Bottenhorn KL, Bowring A, Braem S, Brooks HR, Brudner EG, Calderon CB, Camilleri JA, Castrellon JJ, Cecchetti L, Cieslik EC, Cole ZJ, Collignon O, Cox RW, Cunningham WA, Czoschke S, Dadi K, Davis CP, Luca AD, Delgado MR, Demetriou L, Dennison JB, Di X, Dickie EW, Dobryakova E, Donnat CL, Dukart J, Duncan NW, Durnez J, Eed A, Eickhoff SB, Erhart A, Fontanesi L, Fricke GM, Fu S, Galván A, Gau R, Genon S, Glatard T, Glerean E, Goeman JJ, Golowin SAE, González-García C, Gorgolewski KJ, Grady CL, Green MA, Guassi Moreira JF, Guest O, Hakimi S, Hamilton JP, Hancock R, Handjaras G, Harry BB, Hawco C, Herholz P, Herman G, Heunis S, Hoffstaedter F, Hogeveen J, Holmes S, Hu CP, Huettel SA, Hughes ME, Iacovella V, Iordan AD, Isager PM, Isik AI, Jahn A, Johnson MR, Johnstone T, Joseph MJE, Juliano AC, Kable JW, Kassinopoulos M, Koba C, Kong XZ, Koscik TR, Kucukboyaci NE, Kuhl BA, Kupek S, Laird AR, Lamm C, Langner R, Lauharatanahirun N, Lee H, Lee S, Leemans A, Leo A, Lesage E, Li F, Li MYC, Lim PC, Lintz EN, Liphardt SW, Losecaat Vermeer AB, Love BC, Mack ML, Malpica N, Marins T, Maumet C, McDonald K, McGuire JT, Melero H, Méndez Leal AS, Meyer B, Meyer KN, Mihai G, Mitsis GD, Moll J, Nielson DM, Nilsonne G, Notter MP, Olivetti E, Onicas AI, Papale P, Patil KR, Peelle JE, Pérez A, Pischedda D, Poline JB, Prystauka Y, Ray S, Reuter-Lorenz PA, Reynolds RC, Ricciardi E, Rieck JR, Rodriguez-Thompson AM, Romyn A, Salo T, Samanez-Larkin GR, Sanz-Morales E, Schlichting ML, Schultz DH, Shen Q, Sheridan MA, Silvers JA, Skagerlund K, Smith A, Smith DV, Sokol-Hessner P, Steinkamp SR, Tashjian SM, Thirion B, Thorp JN, Tinghög G, Tisdall L, Tompson SH, Toro-Serey C, Torre Tresols JJ, Tozzi L, Truong V, Turella L, van 't Veer AE, Verguts T, Vettel JM, Vijayarajah S, Vo K, Wall MB, Weeda WD, Weis S, White DJ, Wisniewski D, Xifra-Porxas A, Yearling EA, Yoon S, Yuan R, Yuen KSL, Zhang L, Zhang X, Zosky JE, Nichols TE, Poldrack RA, Schonberg T. Variability in the analysis of a single neuroimaging dataset by many teams. Nature 2020; 582:84-88. [PMID: 32483374 PMCID: PMC7771346 DOI: 10.1038/s41586-020-2314-9] [Citation(s) in RCA: 423] [Impact Index Per Article: 105.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 04/07/2020] [Indexed: 01/13/2023]
Abstract
Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.
Collapse
Affiliation(s)
- Rotem Botvinik-Nezer
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Felix Holzmeister
- Department of Banking and Finance, University of Innsbruck, Innsbruck, Austria
| | - Colin F Camerer
- HSS and CNS, California Institute of Technology, Pasadena, CA, USA
| | - Anna Dreber
- Department of Economics, Stockholm School of Economics, Stockholm, Sweden
- Department of Economics, University of Innsbruck, Innsbruck, Austria
| | - Juergen Huber
- Department of Banking and Finance, University of Innsbruck, Innsbruck, Austria
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm, Sweden
| | - Michael Kirchler
- Department of Banking and Finance, University of Innsbruck, Innsbruck, Austria
| | - Roni Iwanir
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Jeanette A Mumford
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA
| | - R Alison Adcock
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Paolo Avesani
- Neuroinformatics Laboratory, Fondazione Bruno Kessler, Trento, Italy
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | - Blazej M Baczkowski
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Aahana Bajracharya
- Department of Otolaryngology, Washington University in St. Louis, St. Louis, MO, USA
| | - Leah Bakst
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | - Sheryl Ball
- Department of Economics, Virginia Tech, Blacksburg, VA, USA
- School of Neuroscience, Virginia Tech, Blacksburg, VA, USA
| | - Marco Barilari
- Crossmodal Perception and Plasticity Laboratory, Institutes for Research in Psychology (IPSY) and Neurosciences (IoNS), UCLouvain, Louvain-la-Neuve, Belgium
| | - Nadège Bault
- School of Psychology, University of Plymouth, Plymouth, UK
| | - Derek Beaton
- Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, Ontario, Canada
| | - Julia Beitner
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
- Department of Psychology, Goethe University, Frankfurt am Main, Germany
| | - Roland G Benoit
- Max Planck Research Group: Adaptive Memory, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ruud M W J Berkers
- Max Planck Research Group: Adaptive Memory, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jamil P Bhanji
- Department of Psychology, Rutgers University-Newark, Newark, NJ, USA
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | | | - Tiago Bortolini
- D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
| | | | - Alexander Bowring
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Senne Braem
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
- Department of Psychology, Vrije Universiteit Brussel, Brussels, Belgium
| | - Hayley R Brooks
- Department of Psychology, University of Denver, Denver, CO, USA
| | - Emily G Brudner
- Department of Psychology, Rutgers University-Newark, Newark, NJ, USA
| | | | - Julia A Camilleri
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Jaime J Castrellon
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Luca Cecchetti
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Edna C Cieslik
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Zachary J Cole
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Olivier Collignon
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
- Crossmodal Perception and Plasticity Laboratory, Institutes for Research in Psychology (IPSY) and Neurosciences (IoNS), UCLouvain, Louvain-la-Neuve, Belgium
| | - Robert W Cox
- National Institute of Mental Health (NIMH), National Institutes of Health, Bethesda, MD, USA
| | | | - Stefan Czoschke
- Institute of Medical Psychology, Goethe University, Frankfurt am Main, Germany
| | | | - Charles P Davis
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
- Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA
| | - Alberto De Luca
- PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Lysia Demetriou
- Section of Endocrinology and Investigative Medicine, Faculty of Medicine, Imperial College London, London, UK
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
| | | | - Xin Di
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Erin W Dickie
- Krembil Centre for Neuroinformatics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Ekaterina Dobryakova
- Center for Traumatic Brain Injury Research, Kessler Foundation, East Hanover, NJ, USA
| | - Claire L Donnat
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Niall W Duncan
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
- Brain and Consciousness Research Centre, TMU-ShuangHo Hospital, New Taipei City, Taiwan
| | - Joke Durnez
- Department of Psychology and Stanford Center for Reproducible Neuroscience, Stanford University, Stanford, CA, USA
| | - Amr Eed
- Instituto de Neurociencias, CSIC-UMH, Alicante, Spain
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Andrew Erhart
- Department of Psychology, University of Denver, Denver, CO, USA
| | - Laura Fontanesi
- Faculty of Psychology, University of Basel, Basel, Switzerland
| | - G Matthew Fricke
- Computer Science Department, University of New Mexico, Albuquerque, NM, USA
| | - Shiguang Fu
- School of Management, Zhejiang University of Technology, Hangzhou, China
- Institute of Neuromanagement, Zhejiang University of Technology, Hangzhou, China
| | - Adriana Galván
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | - Remi Gau
- Crossmodal Perception and Plasticity Laboratory, Institutes for Research in Psychology (IPSY) and Neurosciences (IoNS), UCLouvain, Louvain-la-Neuve, Belgium
| | - Sarah Genon
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Tristan Glatard
- Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada
| | - Enrico Glerean
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Jelle J Goeman
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Sergej A E Golowin
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
| | | | | | - Cheryl L Grady
- Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, Ontario, Canada
| | - Mikella A Green
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - João F Guassi Moreira
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | - Olivia Guest
- Department of Experimental Psychology, University College London, London, UK
- Research Centre on Interactive Media, Smart Systems and Emerging Technologies - RISE, Nicosia, Cyprus
| | - Shabnam Hakimi
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
| | - J Paul Hamilton
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Roeland Hancock
- Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA
| | - Giacomo Handjaras
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Bronson B Harry
- The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Sydney, New South Wales, Australia
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Peer Herholz
- McConnell Brain Imaging Centre, The Neuro (Montreal Neurological Institute-Hospital), Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Gabrielle Herman
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Stephan Heunis
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, The Netherlands
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Jeremy Hogeveen
- Department of Psychology, University of New Mexico, Albuquerque, NM, USA
- Psychology Clinical Neuroscience Center, University of New Mexico, Albuquerque, NM, USA
| | - Susan Holmes
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Chuan-Peng Hu
- Leibniz-Institut für Resilienzforschung (LIR), Mainz, Germany
| | - Scott A Huettel
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Matthew E Hughes
- School of Health Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Vittorio Iacovella
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | | | - Peder M Isager
- Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Ayse I Isik
- Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany
| | - Andrew Jahn
- fMRI Laboratory, University of Michigan, Ann Arbor, MI, USA
| | - Matthew R Johnson
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Tom Johnstone
- School of Health Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Michael J E Joseph
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Anthony C Juliano
- Center for Neuropsychology and Neuroscience Research, Kessler Foundation, East Hanover, NJ, USA
| | - Joseph W Kable
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
- MindCORE, University of Pennsylvania, Philadelphia, PA, USA
| | - Michalis Kassinopoulos
- Graduate Program in Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Cemal Koba
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Xiang-Zhen Kong
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Timothy R Koscik
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Nuri Erkut Kucukboyaci
- Center for Traumatic Brain Injury Research, Kessler Foundation, East Hanover, NJ, USA
- Department of Physical Medicine and Rehabilitation, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Brice A Kuhl
- Department of Psychology, University of Oregon, Eugene, OR, USA
| | - Sebastian Kupek
- Faculty of Economics and Statistics, University of Innsbruck, Innsbruck, Austria
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, Florida, USA
| | - Claus Lamm
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
- Vienna Cognitive Science Hub, University of Vienna, Vienna, Austria
| | - Robert Langner
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Nina Lauharatanahirun
- US CCDC Army Research Laboratory, Human Research and Engineering Directorate, Aberdeen Proving Ground, MD, USA
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA
| | - Hongmi Lee
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Sangil Lee
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - Alexander Leemans
- PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Andrea Leo
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Elise Lesage
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
| | - Flora Li
- Fralin Biomedical Research Institute, Roanoke, VA, USA
- Economics Experimental Lab, Nanjing Audit University, Nanjing, China
| | - Monica Y C Li
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
- Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA
- Haskins Laboratories, New Haven, CT, USA
| | - Phui Cheng Lim
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Evan N Lintz
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
| | | | - Annabel B Losecaat Vermeer
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Bradley C Love
- Department of Experimental Psychology, University College London, London, UK
- The Alan Turing Institute, London, UK
| | - Michael L Mack
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Norberto Malpica
- Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Madrid, Spain
| | - Theo Marins
- D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
| | - Camille Maumet
- Inria, Univ Rennes, CNRS, Inserm, IRISA UMR 6074, Empenn ERL U 1228, Rennes, France
| | - Kelsey McDonald
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Joseph T McGuire
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | - Helena Melero
- Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Madrid, Spain
- Departamento de Psicobiología, División de Psicología, CES Cardenal Cisneros, Madrid, Spain
- Northeastern University Biomedical Imaging Center, Northeastern University, Boston, MA, USA
| | - Adriana S Méndez Leal
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | - Benjamin Meyer
- Leibniz-Institut für Resilienzforschung (LIR), Mainz, Germany
- Neuroimaging Center (NIC), Focus Program Translational Neurosciences (FTN), Johannes Gutenberg University Medical Center Mainz, Mainz, Germany
| | - Kristin N Meyer
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Glad Mihai
- Max Planck Research Group: Neural Mechanisms of Human Communication, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Georgios D Mitsis
- Department of Bioengineering, McGill University, Montreal, Quebec, Canada
| | - Jorge Moll
- D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Dylan M Nielson
- Data Science and Sharing Team, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Gustav Nilsonne
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Michael P Notter
- The Laboratory for Investigative Neurophysiology (The LINE), Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland
| | - Emanuele Olivetti
- Neuroinformatics Laboratory, Fondazione Bruno Kessler, Trento, Italy
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | - Adrian I Onicas
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Paolo Papale
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Kaustubh R Patil
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Jonathan E Peelle
- Department of Otolaryngology, Washington University in St. Louis, St. Louis, MO, USA
| | - Alexandre Pérez
- McConnell Brain Imaging Centre, The Neuro (Montreal Neurological Institute-Hospital), Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Doris Pischedda
- Bernstein Center for Computational Neuroscience and Berlin Center for Advanced Neuroimaging and Clinic for Neurology, Charité Universitätsmedizin, corporate member of Freie Universität Berlin, Humboldt Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Cluster of Excellence Science of Intelligence, Technische Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
- NeuroMI - Milan Center for Neuroscience, Milan, Italy
| | - Jean-Baptiste Poline
- McConnell Brain Imaging Centre, The Neuro (Montreal Neurological Institute-Hospital), Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Henry H. Wheeler, Jr. Brain Imaging Center, Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Yanina Prystauka
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
- Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA
| | - Shruti Ray
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | | | - Richard C Reynolds
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Emiliano Ricciardi
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Jenny R Rieck
- Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, Ontario, Canada
| | - Anais M Rodriguez-Thompson
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Anthony Romyn
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Taylor Salo
- Department of Psychology, Florida International University, Miami, FL, USA
| | - Gregory R Samanez-Larkin
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Emilio Sanz-Morales
- Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Madrid, Spain
| | | | - Douglas H Schultz
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Qiang Shen
- School of Management, Zhejiang University of Technology, Hangzhou, China
- Institute of Neuromanagement, Zhejiang University of Technology, Hangzhou, China
| | - Margaret A Sheridan
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jennifer A Silvers
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | - Kenny Skagerlund
- Department of Behavioural Sciences and Learning, Linköping University, Linköping, Sweden
- Center for Social and Affective Neuroscience, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
| | - Alec Smith
- Department of Economics, Virginia Tech, Blacksburg, VA, USA
- School of Neuroscience, Virginia Tech, Blacksburg, VA, USA
| | - David V Smith
- Department of Psychology, Temple University, Philadelphia, PA, USA
| | | | - Simon R Steinkamp
- Institute of Neuroscience and Medicine, Cognitive Neuroscience (INM-3), Research Centre Jülich, Jülich, Germany
| | - Sarah M Tashjian
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | | | - John N Thorp
- Department of Psychology, Columbia University, New York, NY, USA
| | - Gustav Tinghög
- Department of Management and Engineering, Linköping University, Linköping, Sweden
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Loreen Tisdall
- Department of Psychology, Stanford University, Stanford, CA, USA
- Center for Cognitive and Decision Sciences, University of Basel, Basel, Switzerland
| | - Steven H Tompson
- US CCDC Army Research Laboratory, Human Research and Engineering Directorate, Aberdeen Proving Ground, MD, USA
| | - Claudio Toro-Serey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | | | - Leonardo Tozzi
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Vuong Truong
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
- Brain and Consciousness Research Centre, TMU-ShuangHo Hospital, New Taipei City, Taiwan
| | - Luca Turella
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | - Anna E van 't Veer
- Methodology and Statistics Unit, Institute of Psychology, Leiden University, Leiden, The Netherlands
| | - Tom Verguts
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
| | - Jean M Vettel
- US Combat Capabilities Development Command Army Research Laboratory, Aberdeen, MD, USA
- University of California Santa Barbara, Santa Barbara, CA, USA
- University of Pennsylvania, Philadelphia, PA, USA
| | - Sagana Vijayarajah
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Khoi Vo
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Matthew B Wall
- Invicro, London, UK
- Faculty of Medicine, Imperial College London, London, UK
- Clinical Psychopharmacology Unit, University College London, London, UK
| | - Wouter D Weeda
- Methodology and Statistics Unit, Institute of Psychology, Leiden University, Leiden, The Netherlands
| | - Susanne Weis
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - David J White
- Centre for Human Psychopharmacology, Swinburne University, Hawthorn, Victoria, Australia
| | - David Wisniewski
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
| | - Alba Xifra-Porxas
- Graduate Program in Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Emily A Yearling
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
- Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA
| | - Sangsuk Yoon
- Department of Management and Marketing, School of Business, University of Dayton, Dayton, OH, USA
| | - Rui Yuan
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Kenneth S L Yuen
- Leibniz-Institut für Resilienzforschung (LIR), Mainz, Germany
- Neuroimaging Center (NIC), Focus Program Translational Neurosciences (FTN), Johannes Gutenberg University Medical Center Mainz, Mainz, Germany
| | - Lei Zhang
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Xu Zhang
- Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA
- Biomedical Engineering Department, University of Connecticut, Storrs, CT, USA
| | - Joshua E Zosky
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Thomas E Nichols
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
| | | | - Tom Schonberg
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
- Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.
| |
Collapse
|
15
|
Pläschke RN, Cieslik EC, Müller VI, Hoffstaedter F, Plachti A, Varikuti DP, Goosses M, Latz A, Caspers S, Jockwitz C, Moebus S, Gruber O, Eickhoff CR, Reetz K, Heller J, Südmeyer M, Mathys C, Caspers J, Grefkes C, Kalenscher T, Langner R, Eickhoff SB. Corrigendum to "On the integrity of functional brain networks in schizophrenia, Parkinson's disease, and advanced age: Evidence from connectivity-based single-subject classification.". Hum Brain Mapp 2018; 39:4633-4635. [PMID: 30304584 DOI: 10.1002/hbm.24406] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
|
16
|
Chechko N, Cieslik EC, Müller VI, Nickl-Jockschat T, Derntl B, Kogler L, Aleman A, Jardri R, Sommer IE, Gruber O, Eickhoff SB. Differential Resting-State Connectivity Patterns of the Right Anterior and Posterior Dorsolateral Prefrontal Cortices (DLPFC) in Schizophrenia. Front Psychiatry 2018; 9:211. [PMID: 29892234 PMCID: PMC5985714 DOI: 10.3389/fpsyt.2018.00211] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Accepted: 05/03/2018] [Indexed: 01/24/2023] Open
Abstract
In schizophrenia (SCZ), dysfunction of the dorsolateral prefrontal cortex (DLPFC) has been linked to the deficits in executive functions and attention. It has been suggested that, instead of considering the right DLPFC as a cohesive functional entity, it can be divided into two parts (anterior and posterior) based on its whole-brain connectivity patterns. Given these two subregions' differential association with cognitive processes, we investigated the functional connectivity (FC) profile of both subregions through resting-state data to determine whether they are differentially affected in SCZ. Resting-state magnetic resonance imaging (MRI) scans were obtained from 120 patients and 172 healthy controls (HC) at 6 different MRI sites. The results showed differential FC patterns for the anterior and posterior parts of the right executive control-related DLPFC in SCZ with the parietal, the temporal and the cerebellar regions, along with a convergent reduction of connectivity with the striatum and the occipital cortex. An increased psychopathology level was linked to a higher difference in posterior vs. anterior FC for the left IFG/anterior insula, regions involved in higher-order cognitive processes. In sum, the current analysis demonstrated that even between two neighboring clusters connectivity could be differentially disrupted in SCZ. Lacking the necessary anatomical specificity, such notions may in fact be detrimental to a proper understanding of SCZ pathophysiology.
Collapse
Affiliation(s)
- Natalia Chechko
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
- JARA BRAIN, RWTH Aachen University, Aachen, Germany
| | - Edna C. Cieslik
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Veronika I. Müller
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Thomas Nickl-Jockschat
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
- JARA BRAIN, RWTH Aachen University, Aachen, Germany
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, United States
- Iowa Neuroscience Institute, Carver College of Medicine, University of Iowa, Iowa City, IA, United States
| | - Birgit Derntl
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
- JARA BRAIN, RWTH Aachen University, Aachen, Germany
- Department of Psychiatry and Psychotherapy, Medical School, University of Tübingen, Tübingen, Germany
- Werner Reichardt Center for Integrative Neuroscience, University of Tübingen, Tübingen, Germany
- LEAD Graduate School and Research Network, University of Tübingen, Tübingen, Germany
| | - Lydia Kogler
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
- JARA BRAIN, RWTH Aachen University, Aachen, Germany
- Department of Psychiatry and Psychotherapy, Medical School, University of Tübingen, Tübingen, Germany
| | - André Aleman
- Department of Neuroscience, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Renaud Jardri
- Univ Lille, CNRS UMR 9193, SCALab and CHU Lille, Division of Psychiatry, CURE platform, Fontan Hospital, Lille, France
| | - Iris E. Sommer
- Neuroscience Division, University Medical Centre Utrecht and Rudolf Magnus Institute for Neuroscience, Utrecht, Netherlands
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
| | - Simon B. Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| |
Collapse
|
17
|
Müller VI, Cieslik EC, Laird AR, Fox PT, Radua J, Mataix-Cols D, Tench CR, Yarkoni T, Nichols TE, Turkeltaub PE, Wager TD, Eickhoff SB. Ten simple rules for neuroimaging meta-analysis. Neurosci Biobehav Rev 2018; 84:151-161. [PMID: 29180258 PMCID: PMC5918306 DOI: 10.1016/j.neubiorev.2017.11.012] [Citation(s) in RCA: 454] [Impact Index Per Article: 75.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Revised: 11/18/2017] [Accepted: 11/20/2017] [Indexed: 01/15/2023]
Abstract
Neuroimaging has evolved into a widely used method to investigate the functional neuroanatomy, brain-behaviour relationships, and pathophysiology of brain disorders, yielding a literature of more than 30,000 papers. With such an explosion of data, it is increasingly difficult to sift through the literature and distinguish spurious from replicable findings. Furthermore, due to the large number of studies, it is challenging to keep track of the wealth of findings. A variety of meta-analytical methods (coordinate-based and image-based) have been developed to help summarise and integrate the vast amount of data arising from neuroimaging studies. However, the field lacks specific guidelines for the conduct of such meta-analyses. Based on our combined experience, we propose best-practice recommendations that researchers from multiple disciplines may find helpful. In addition, we provide specific guidelines and a checklist that will hopefully improve the transparency, traceability, replicability and reporting of meta-analytical results of neuroimaging data.
Collapse
Affiliation(s)
- Veronika I Müller
- Institute of Systems Neuroscience and Institute of Clinical Neuroscience & Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience und Medicine (INM-1, INM-7), Research Centre Jülich, Jülich, Germany.
| | - Edna C Cieslik
- Institute of Systems Neuroscience and Institute of Clinical Neuroscience & Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience und Medicine (INM-1, INM-7), Research Centre Jülich, Jülich, Germany.
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Research Service, South Texas Veterans Administration Medical Center, San Antonio, TX, USA; Shenzhen Institute of Neuroscience, Shenzhen University, Shenzhen, China
| | - Joaquim Radua
- FIDMAG Germanes Hospitalàries, CIBERSAM, Barcelona, Spain; Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden; Department of Psychosis Studies, Institute of Psychology, Psychiatry, and Neuroscience, King's College London, London, United Kingdom
| | - David Mataix-Cols
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | - Christopher R Tench
- (CRT) Division of Clinical Neurosciences, Clinical Neurology, University of Nottingham, Queen's Medical Centre, Nottingham, United Kingdom
| | - Tal Yarkoni
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
| | - Thomas E Nichols
- Department of Statistics, University of Warwick, Coventry, United Kingdom; Warwick Manufactoring Group, University of Warwick, Coventry, United Kingdom
| | - Peter E Turkeltaub
- Department of Neurology, Georgetown University Medical Center, Washington, DC, USA; Research Division, MedStar National Rehabilitation Hospital, Washington, DC, USA
| | - Tor D Wager
- Department of Psychology and Neuroscience, University of Colorado, Boulder, Colorado, USA; Institute of Cognitive Science, University of Colorado, Boulder, USA
| | - Simon B Eickhoff
- Institute of Systems Neuroscience and Institute of Clinical Neuroscience & Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience und Medicine (INM-1, INM-7), Research Centre Jülich, Jülich, Germany
| |
Collapse
|
18
|
Pläschke RN, Cieslik EC, Müller VI, Hoffstaedter F, Plachti A, Varikuti DP, Goosses M, Latz A, Caspers S, Jockwitz C, Moebus S, Gruber O, Eickhoff CR, Reetz K, Heller J, Südmeyer M, Mathys C, Caspers J, Grefkes C, Kalenscher T, Langner R, Eickhoff SB. On the integrity of functional brain networks in schizophrenia, Parkinson's disease, and advanced age: Evidence from connectivity-based single-subject classification. Hum Brain Mapp 2017; 38:5845-5858. [PMID: 28876500 DOI: 10.1002/hbm.23763] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Revised: 07/06/2017] [Accepted: 07/30/2017] [Indexed: 01/10/2023] Open
Abstract
Previous whole-brain functional connectivity studies achieved successful classifications of patients and healthy controls but only offered limited specificity as to affected brain systems. Here, we examined whether the connectivity patterns of functional systems affected in schizophrenia (SCZ), Parkinson's disease (PD), or normal aging equally translate into high classification accuracies for these conditions. We compared classification performance between pre-defined networks for each group and, for any given network, between groups. Separate support vector machine classifications of 86 SCZ patients, 80 PD patients, and 95 older adults relative to their matched healthy/young controls, respectively, were performed on functional connectivity in 12 task-based, meta-analytically defined networks using 25 replications of a nested 10-fold cross-validation scheme. Classification performance of the various networks clearly differed between conditions, as those networks that best classified one disease were usually non-informative for the other. For SCZ, but not PD, emotion-processing, empathy, and cognitive action control networks distinguished patients most accurately from controls. For PD, but not SCZ, networks subserving autobiographical or semantic memory, motor execution, and theory-of-mind cognition yielded the best classifications. In contrast, young-old classification was excellent based on all networks and outperformed both clinical classifications. Our pattern-classification approach captured associations between clinical and developmental conditions and functional network integrity with a higher level of specificity than did previous whole-brain analyses. Taken together, our results support resting-state connectivity as a marker of functional dysregulation in specific networks known to be affected by SCZ and PD, while suggesting that aging affects network integrity in a more global way. Hum Brain Mapp 38:5845-5858, 2017. © 2017 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Rachel N Pläschke
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany
| | - Edna C Cieslik
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany
| | - Veronika I Müller
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany
| | - Felix Hoffstaedter
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany
| | - Anna Plachti
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany
| | - Deepthi P Varikuti
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany
| | - Mareike Goosses
- Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany
| | - Anne Latz
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany
| | - Svenja Caspers
- Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany.,C. & O. Vogt Institute for Brain Research, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,JARA-BRAIN, Jülich-Aachen Research Alliance, Jülich, Germany
| | - Christiane Jockwitz
- Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany.,C. & O. Vogt Institute for Brain Research, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
| | - Susanne Moebus
- Center for Urban Epidemiology, University of Duisburg-Essen, Essen, Germany
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
| | - Claudia R Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany.,Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
| | - Kathrin Reetz
- JARA-BRAIN, Jülich-Aachen Research Alliance, Jülich, Germany.,JARA-BRAIN Institute of Molecular Neuroscience and Neuroimaging (INM-11), Research Centre Jülich, Jülich, Germany.,Department of Neurology, RWTH Aachen University, Aachen, Germany
| | - Julia Heller
- JARA-BRAIN, Jülich-Aachen Research Alliance, Jülich, Germany.,JARA-BRAIN Institute of Molecular Neuroscience and Neuroimaging (INM-11), Research Centre Jülich, Jülich, Germany.,Department of Neurology, RWTH Aachen University, Aachen, Germany
| | - Martin Südmeyer
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Center for Movement Disorders and Neuromodulation, Department of Neurology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Christian Mathys
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Julian Caspers
- Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany.,Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Christian Grefkes
- Department of Neurology, University Hospital Cologne, Cologne, Germany.,Institute of Neuroscience and Medicine, Cognitive Neurology Group (INM-3), Research Centre Jülich, Jülich, Germany
| | - Tobias Kalenscher
- Comparative Psychology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Robert Langner
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, (INM-1), Research Centre Jülich, Jülich, Germany
| |
Collapse
|
19
|
Wensing T, Cieslik EC, Müller VI, Hoffstaedter F, Eickhoff SB, Nickl-Jockschat T. Neural correlates of formal thought disorder: An activation likelihood estimation meta-analysis. Hum Brain Mapp 2017; 38:4946-4965. [PMID: 28653797 DOI: 10.1002/hbm.23706] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 05/24/2017] [Accepted: 06/16/2017] [Indexed: 11/10/2022] Open
Abstract
Formal thought disorder (FTD) refers to a psychopathological dimension characterized by disorganized and incoherent speech. Whether symptoms of FTD arise from aberrant processing in language-related regions or more general cognitive networks, however, remains debated. Here, we addressed this question by a quantitative meta-analysis of published functional neuroimaging studies on FTD. The revised Activation Likelihood Estimation (ALE) algorithm was used to test for convergent aberrant activation changes in 18 studies (30 experiments) investigating FTD, of which 17 studies comprised schizophrenia patients and one study healthy subjects administered to S-ketamine. Additionally, we analyzed task-dependent and task-independent (resting-state) functional connectivity (FC) of brain regions showing convergence in activation changes. Subsequent functional characterization was performed for the initial clusters and the delineated connectivity networks by reference to the BrainMap database. Consistent activation changes were found in the left superior temporal gyrus (STG) and two regions within the left posterior middle temporal gyrus (p-MTG), ventrally (vp-MTG) and dorsally (dp-MTG). Functional characterization revealed a prominent functional association of ensuing clusters from our ALE meta-analysis with language and speech processing, as well as auditory perception in STG and with social cognition in dp-MTG. FC analysis identified task-dependent and task-independent networks for all three seed regions, which were mainly related to language and speech processing, but showed additional involvement in higher order cognitive functions. Our findings suggest that FTD is mainly characterized by abnormal activation in brain regions of the left hemisphere that are associated with language and speech processing, but also extend to higher order cognitive functions. Hum Brain Mapp 38:4946-4965, 2017. © 2017 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Tobias Wensing
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Germany.,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Germany.,JARA Translational Brain Medicine, Aachen, Germany
| | - Edna C Cieslik
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Germany.,Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany
| | - Veronika I Müller
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Germany.,Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Germany.,Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Germany.,Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany
| | - Thomas Nickl-Jockschat
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Germany.,JARA Translational Brain Medicine, Aachen, Germany
| |
Collapse
|
20
|
Caspers J, Mathys C, Hoffstaedter F, Südmeyer M, Cieslik EC, Rubbert C, Hartmann CJ, Eickhoff CR, Reetz K, Grefkes C, Michely J, Turowski B, Schnitzler A, Eickhoff SB. Differential Functional Connectivity Alterations of Two Subdivisions within the Right dlPFC in Parkinson's Disease. Front Hum Neurosci 2017; 11:288. [PMID: 28611616 PMCID: PMC5447710 DOI: 10.3389/fnhum.2017.00288] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2016] [Accepted: 05/16/2017] [Indexed: 02/02/2023] Open
Abstract
Patients suffering from Parkinson's disease (PD) often show impairments in executive function (EF) like decision-making and action control. The right dorsolateral prefrontal cortex (dlPFC) has been strongly implicated in EF in healthy subjects and has repeatedly been reported to show alterations related to EF impairment in PD. Recently, two key regions for cognitive action control have been identified within the right dlPFC by co-activation based parcellation. While the posterior region is engaged in rather basal EF like stimulus integration and working memory, the anterior region has a more abstract, supervisory function. To investigate whether these functionally distinct subdivisions of right dlPFC are differentially affected in PD, we analyzed resting-state functional connectivity (FC) in 39 PD patients and 44 age- and gender-matched healthy controls. Patients were examined both after at least 12 h withdrawal of dopaminergic drugs (OFF) and under their regular dopaminergic medication (ON). We found that only the posterior right dlPFC subdivision shows FC alterations in PD, while the anterior part remains unaffected. PD-related decreased FC with posterior right dlPFC was found in the bilateral medial posterior parietal cortex (mPPC) and left dorsal premotor region (PMd) in the OFF state. In the medical ON, FC with left PMd normalized, while decoupling with bilateral mPPC remained. Furthermore, we observed increased FC between posterior right dlPFC and the bilateral dorsomedial prefrontal cortex (dmPFC) in PD in the ON state. Our findings point to differential disturbances of right dlPFC connectivity in PD, which relate to its hierarchical organization of EF processing by stronger affecting the functionally basal posterior aspect than the hierarchically higher anterior part.
Collapse
Affiliation(s)
- Julian Caspers
- Department of Diagnostic and Interventional Radiology, Medical Faculty, University DüsseldorfDüsseldorf, Germany.,Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-3, INM-11)Jülich, Germany
| | - Christian Mathys
- Department of Diagnostic and Interventional Radiology, Medical Faculty, University DüsseldorfDüsseldorf, Germany
| | - Felix Hoffstaedter
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-3, INM-11)Jülich, Germany.,Medical Faculty, Institute of Clinical Neuroscience and Medical Psychology, Heinrich-Heine-UniversityDüsseldorf, Germany
| | - Martin Südmeyer
- Medical Faculty, Institute of Clinical Neuroscience and Medical Psychology, Heinrich-Heine-UniversityDüsseldorf, Germany.,Department of Neurology, Medical Faculty, Center for Movement Disorders and Neuromodulation, Heinrich-Heine-UniversityDüsseldorf, Germany
| | - Edna C Cieslik
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-3, INM-11)Jülich, Germany.,Medical Faculty, Institute of Clinical Neuroscience and Medical Psychology, Heinrich-Heine-UniversityDüsseldorf, Germany
| | - Christian Rubbert
- Department of Diagnostic and Interventional Radiology, Medical Faculty, University DüsseldorfDüsseldorf, Germany
| | - Christian J Hartmann
- Medical Faculty, Institute of Clinical Neuroscience and Medical Psychology, Heinrich-Heine-UniversityDüsseldorf, Germany.,Department of Neurology, Medical Faculty, Center for Movement Disorders and Neuromodulation, Heinrich-Heine-UniversityDüsseldorf, Germany
| | - Claudia R Eickhoff
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-3, INM-11)Jülich, Germany.,Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen UniversityAachen, Germany
| | - Kathrin Reetz
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-3, INM-11)Jülich, Germany.,JARA BRAIN and Department of Neurology, RWTH Aachen UniversityAachen, Germany
| | - Christian Grefkes
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-3, INM-11)Jülich, Germany.,Department of Neurology, University of CologneCologne, Germany
| | - Jochen Michely
- Department of Neurology, University of CologneCologne, Germany
| | - Bernd Turowski
- Department of Diagnostic and Interventional Radiology, Medical Faculty, University DüsseldorfDüsseldorf, Germany
| | - Alfons Schnitzler
- Medical Faculty, Institute of Clinical Neuroscience and Medical Psychology, Heinrich-Heine-UniversityDüsseldorf, Germany.,Department of Neurology, Medical Faculty, Center for Movement Disorders and Neuromodulation, Heinrich-Heine-UniversityDüsseldorf, Germany
| | - Simon B Eickhoff
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-3, INM-11)Jülich, Germany.,Medical Faculty, Institute of Clinical Neuroscience and Medical Psychology, Heinrich-Heine-UniversityDüsseldorf, Germany
| |
Collapse
|
21
|
Genon S, Li H, Fan L, Müller VI, Cieslik EC, Hoffstaedter F, Reid AT, Langner R, Grefkes C, Fox PT, Moebus S, Caspers S, Amunts K, Jiang T, Eickhoff SB. The Right Dorsal Premotor Mosaic: Organization, Functions, and Connectivity. Cereb Cortex 2017; 27:2095-2110. [PMID: 26965906 DOI: 10.1093/cercor/bhw065] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
The right dorsal premotor cortex (PMd) of humans has been reported to be involved in a broad range of motor and cognitive functions. We explored the basis of this behavioral heterogeneity by performing a connectivity-based parcellation using meta-analytic approach applied to PMd coactivations. We compared our connectivity-based parcellation results with parcellations obtained through resting-state functional connectivity and probabilistic diffusion tractography. Functional connectivity profiles and behavioral decoding of the resulting PMd subregions allowed characterizing their respective behavior profile. These procedures divided the right PMd into 5 distinct subregions that formed a cognitive-motor gradient along a rostro-caudal axis. In particular, we found 1) a rostral subregion functionally connected with prefrontal cortex, which likely supports high-level cognitive processes, such as working memory, 2) a central subregion showing a mixed behavioral profile and functional connectivity to parietal regions of the dorsal attention network, and 3) a caudal subregion closely integrated with the motor system. Additionally, we found 4) a dorsal subregion, preferentially related to hand movements and connected to both cognitive and motor regions, and 5) a ventral subregion, whose functional profile fits the concept of an eye movement-related field. In conclusion, right PMd may be considered as a functional mosaic formed by 5 subregions.
Collapse
Affiliation(s)
- Sarah Genon
- Institute of Neuroscience and Medicine (INM-1, INM-3), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Düsseldorf, Germany
| | - Hai Li
- Brainnetome Center, Institute of Automation and.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation and.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Veronika I Müller
- Institute of Neuroscience and Medicine (INM-1, INM-3), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Düsseldorf, Germany
| | - Edna C Cieslik
- Institute of Neuroscience and Medicine (INM-1, INM-3), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Düsseldorf, Germany
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine (INM-1, INM-3), Research Centre Jülich, Jülich, Germany
| | - Andrew T Reid
- Institute of Neuroscience and Medicine (INM-1, INM-3), Research Centre Jülich, Jülich, Germany
| | - Robert Langner
- Institute of Neuroscience and Medicine (INM-1, INM-3), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Düsseldorf, Germany
| | - Christian Grefkes
- Institute of Neuroscience and Medicine (INM-1, INM-3), Research Centre Jülich, Jülich, Germany.,Department of Neurology, Cologne University Hospital, Cologne, Germany
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, TX, USA
| | - Susanne Moebus
- Centre for Urban Epidemiology (CUE), Universitätsklinikum Essen, University of Duisburg-Essen, Essen, Germany
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1, INM-3), Research Centre Jülich, Jülich, Germany
| | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1, INM-3), Research Centre Jülich, Jülich, Germany
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation and.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-1, INM-3), Research Centre Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Düsseldorf, Germany
| |
Collapse
|
22
|
Abstract
IMPORTANCE During the past 20 years, numerous neuroimaging experiments have investigated aberrant brain activation during cognitive and emotional processing in patients with unipolar depression (UD). The results of those investigations, however, vary considerably; moreover, previous meta-analyses also yielded inconsistent findings. OBJECTIVE To readdress aberrant brain activation in UD as evidenced by neuroimaging experiments on cognitive and/or emotional processing. DATA SOURCES Neuroimaging experiments published from January 1, 1997, to October 1, 2015, were identified by a literature search of PubMed, Web of Science, and Google Scholar using different combinations of the terms fMRI (functional magnetic resonance imaging), PET (positron emission tomography), neural, major depression, depression, major depressive disorder, unipolar depression, dysthymia, emotion, emotional, affective, cognitive, task, memory, working memory, inhibition, control, n-back, and Stroop. STUDY SELECTION Neuroimaging experiments (using fMRI or PET) reporting whole-brain results of group comparisons between adults with UD and healthy control individuals as coordinates in a standard anatomic reference space and using an emotional or/and cognitive challenging task were selected. DATA EXTRACTION AND SYNTHESIS Coordinates reported to show significant activation differences between UD and healthy controls during emotional or cognitive processing were extracted. By using the revised activation likelihood estimation algorithm, different meta-analyses were calculated. MAIN OUTCOMES AND MEASURES Meta-analyses tested for brain regions consistently found to show aberrant brain activation in UD compared with controls. Analyses were calculated across all emotional processing experiments, all cognitive processing experiments, positive emotion processing, negative emotion processing, experiments using emotional face stimuli, experiments with a sex discrimination task, and memory processing. All meta-analyses were calculated across experiments independent of reporting an increase or decrease of activity in major depressive disorder. For meta-analyses with a minimum of 17 experiments available, separate analyses were performed for increases and decreases. RESULTS In total, 57 studies with 99 individual neuroimaging experiments comprising in total 1058 patients were included; 34 of them tested cognitive and 65 emotional processing. Overall analyses across cognitive processing experiments (P > .29) and across emotional processing experiments (P > .47) revealed no significant results. Similarly, no convergence was found in analyses investigating positive (all P > .15), negative (all P > .76), or memory (all P > .48) processes. Analyses that restricted inclusion of confounds (eg, medication, comorbidity, age) did not change the results. CONCLUSIONS AND RELEVANCE Inconsistencies exist across individual experiments investigating aberrant brain activity in UD and replication problems across previous neuroimaging meta-analyses. For individual experiments, these inconsistencies may relate to use of uncorrected inference procedures, differences in experimental design and contrasts, or heterogeneous clinical populations; meta-analytically, differences may be attributable to varying inclusion and exclusion criteria or rather liberal statistical inference approaches.
Collapse
Affiliation(s)
- Veronika I. Müller
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany2Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Edna C. Cieslik
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany2Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Ilinca Serbanescu
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany
| | - Angela R. Laird
- Department of Physics, Florida International University, Miami
| | - Peter T. Fox
- Research Imaging Institute, University of Texas Health Science Center, San Antonio5Research Service, South Texas Veterans Administration Medical Center, San Antonio6State Key Laboratory for Brain and Cognitive Sciences, University of Hong Kong, Hong Kong, China
| | - Simon B. Eickhoff
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany2Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| |
Collapse
|
23
|
Schilbach L, Derntl B, Aleman A, Caspers S, Clos M, Diederen KMJ, Gruber O, Kogler L, Liemburg EJ, Sommer IE, Müller VI, Cieslik EC, Eickhoff SB. Differential Patterns of Dysconnectivity in Mirror Neuron and Mentalizing Networks in Schizophrenia. Schizophr Bull 2016; 42:1135-48. [PMID: 26940699 PMCID: PMC4988733 DOI: 10.1093/schbul/sbw015] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Impairments of social cognition are well documented in patients with schizophrenia (SCZ), but the neural basis remains poorly understood. In light of evidence that suggests that the "mirror neuron system" (MNS) and the "mentalizing network" (MENT) are key substrates of intersubjectivity and joint action, it has been suggested that dysfunction of these neural networks may underlie social difficulties in SCZ patients. Additionally, MNS and MENT might be associated differently with positive vs negative symptoms, given prior social cognitive and symptom associations. We assessed resting state functional connectivity (RSFC) in meta-analytically defined MNS and MENT networks in this patient group. Magnetic resonance imaging (MRI) scans were obtained from 116 patients and 133 age-, gender- and movement-matched healthy controls (HC) at 5 different MRI sites. Network connectivity was analyzed for group differences and correlations with clinical symptoms. Results demonstrated decreased connectivity within the MNS and also the MENT in patients compared to controls. Notably, dysconnectivity of the MNS was related to symptom severity, while no such relationship was observed for the MENT. In sum, these findings demonstrate that differential patterns of dysconnectivity exist in SCZ patients, which may contribute differently to the interpersonal difficulties commonly observed in the disorder.
Collapse
Affiliation(s)
- Leonhard Schilbach
- Max Planck Institute of Psychiatry, Munich, Germany;,Department of Psychiatry, University Hospital Cologne, Cologne, Germany;,These authors contributed equally
| | - Birgit Derntl
- Department of Psychiatry, Psychotherapy & Psychosomatics, RWTH University Aachen, Aachen, Germany; Jülich Aachen Research Alliance, JARA-BRAIN, Translational Brain Medicine, Jülich-Aachen, Germany; Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich, Germany; Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany;
| | - Andre Aleman
- BCN Neuroimaging Center, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich, Germany
| | - Mareike Clos
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich, Germany
| | - Kelly M. J. Diederen
- Neuroscience Division, University Medical Center Utrecht & Rudolf Magnus Institute for Neuroscience, Utrecht, Netherlands
| | - Oliver Gruber
- Department of Psychiatry and Psychotherapy, University of Göttingen, Göttingen, Germany;,Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University Hospital, Heidelberg, Germany
| | - Lydia Kogler
- Department of Psychiatry, Psychotherapy & Psychosomatics, RWTH University Aachen, Aachen, Germany;,Jülich Aachen Research Alliance, JARA-BRAIN, Translational Brain Medicine, Jülich-Aachen, Germany;,Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Edith J. Liemburg
- BCN Neuroimaging Center, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Iris E. Sommer
- Neuroscience Division, University Medical Center Utrecht & Rudolf Magnus Institute for Neuroscience, Utrecht, Netherlands
| | - Veronika I. Müller
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich, Germany;,Institute of Clinical Neuroscience and Medical Psychology, HHU Duesseldorf, Duesseldorf, Germany
| | - Edna C. Cieslik
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich, Germany;,Institute of Clinical Neuroscience and Medical Psychology, HHU Duesseldorf, Duesseldorf, Germany
| | - Simon B. Eickhoff
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich, Germany;,Institute of Clinical Neuroscience and Medical Psychology, HHU Duesseldorf, Duesseldorf, Germany
| |
Collapse
|
24
|
Cieslik EC, Seidler I, Laird AR, Fox PT, Eickhoff SB. Different involvement of subregions within dorsal premotor and medial frontal cortex for pro- and antisaccades. Neurosci Biobehav Rev 2016; 68:256-269. [PMID: 27211526 DOI: 10.1016/j.neubiorev.2016.05.012] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2015] [Revised: 04/01/2016] [Accepted: 05/17/2016] [Indexed: 01/22/2023]
Abstract
The antisaccade task has been widely used to investigate cognitive action control. While the general network for saccadic eye movements is well defined, the exact location of eye fields within the frontal cortex strongly varies between studies. It is unknown whether this inconsistency reflects spatial uncertainty or is the result of different involvement of subregions for specific aspects of eye movement control. The aim of the present study was to examine functional differentiations within the frontal cortex by integrating results from neuroimaging studies analyzing pro- and antisaccade behavior using meta-analyses. The results provide evidence for a differential functional specialization of neighboring oculomotor frontal regions, with lateral frontal eye fields (FEF) and supplementary eye field (SEF) more often involved in prosaccades while medial FEF and anterior midcingulate cortex (aMCC) revealed consistent stronger involvement for antisaccades. This dissociation was furthermore mirrored by functional connectivity analyses showing that the lateral FEF and SEF are embedded in a motor output network, while medial FEF and aMCC are integrated in a multiple demand network.
Collapse
Affiliation(s)
- Edna C Cieslik
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-1) Research Centre Jülich, Jülich, Germany.
| | - Isabelle Seidler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, USA; Department of Psychology, Florida International University, Miami, FL, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center San Antonio, TX, USA; Research Service, South Texas Veterans Administration Medical Center, San Antonio, TX, USA; State Key Laboratory for Brain and Cognitive Sciences, University of Hong Kong, Hong Kong
| | - Simon B Eickhoff
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-1) Research Centre Jülich, Jülich, Germany
| |
Collapse
|
25
|
Cieslik EC, Mueller VI, Eickhoff CR, Langner R, Eickhoff SB. Three key regions for supervisory attentional control: evidence from neuroimaging meta-analyses. Neurosci Biobehav Rev 2014; 48:22-34. [PMID: 25446951 DOI: 10.1016/j.neubiorev.2014.11.003] [Citation(s) in RCA: 207] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Revised: 10/08/2014] [Accepted: 11/02/2014] [Indexed: 12/20/2022]
Abstract
The supervisory attentional system has been proposed to mediate non-routine, goal-oriented behaviour by guiding the selection and maintenance of the goal-relevant task schema. Here, we aimed to delineate the brain regions that mediate these high-level control processes via neuroimaging meta-analysis. In particular, we investigated the core neural correlates of a wide range of tasks requiring supervisory control for the suppression of a routine action in favour of another, non-routine one. Our sample comprised n=173 experiments employing go/no-go, stop-signal, Stroop or spatial interference tasks. Consistent convergence across all four paradigm classes was restricted to right anterior insula and inferior frontal junction, with anterior midcingulate cortex and pre-supplementary motor area being consistently involved in all but the go/no-go task. Taken together with lesion studies in patients, our findings suggest that the controlled activation and maintenance of adequate task schemata relies, across paradigms, on a right-dominant midcingulo-insular-inferior frontal core network. This also implies that the role of other prefrontal and parietal regions may be less domain-general than previously thought.
Collapse
Affiliation(s)
- Edna C Cieslik
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Universitätsstraße 1, 40225 Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-1) Research Centre Jülich, Leo-Brandt-Straße, 52428 Jülich, Germany.
| | - Veronika I Mueller
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Universitätsstraße 1, 40225 Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-1) Research Centre Jülich, Leo-Brandt-Straße, 52428 Jülich, Germany
| | - Claudia R Eickhoff
- Institute of Neuroscience and Medicine (INM-1) Research Centre Jülich, Leo-Brandt-Straße, 52428 Jülich, Germany; Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen, University, Pauwelsstraße 30, 52074 Aachen, Germany
| | - Robert Langner
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Universitätsstraße 1, 40225 Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-1) Research Centre Jülich, Leo-Brandt-Straße, 52428 Jülich, Germany
| | - Simon B Eickhoff
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Universitätsstraße 1, 40225 Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-1) Research Centre Jülich, Leo-Brandt-Straße, 52428 Jülich, Germany
| |
Collapse
|
26
|
Müller VI, Cieslik EC, Kellermann TS, Eickhoff SB. Crossmodal emotional integration in major depression. Soc Cogn Affect Neurosci 2014; 9:839-48. [PMID: 23576809 PMCID: PMC4040101 DOI: 10.1093/scan/nst057] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2012] [Accepted: 04/09/2013] [Indexed: 11/13/2022] Open
Abstract
Major depression goes along with affective and social-cognitive deficits. Most research on affective deficits in depression has, however, only focused on unimodal emotion processing, whereas in daily life, emotional perception is often highly dependent on the evaluation of multimodal inputs. We thus investigated emotional audiovisual integration in patients with depression and healthy subjects. Subjects rated the expression of happy, neutral and fearful faces while concurrently being exposed to emotional or neutral sounds. Results demonstrated group differences in left inferior frontal gyrus and inferior parietal cortex when comparing incongruent to congruent happy facial conditions, mainly due to a failure of patients to deactivate these regions in response to congruent stimulus pairs. Moreover, healthy subjects decreased activation in right posterior superior temporal gyrus/sulcus and midcingulate cortex when an emotional stimulus was paired with a neutral rather than another emotional one. In contrast, patients did not show such deactivation when neutral stimuli were integrated. These results demonstrate aberrant neural response in audiovisual processing in depression, indicated by failure to deactivate regions involved in inhibition and salience processing when congruent and neutral audiovisual stimuli pairs are integrated, providing a possible mechanism of constant arousal and readiness to act in this patient group.
Collapse
Affiliation(s)
- Veronika I Müller
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty Heinrich Heine University, D-40225 Düsseldorf, Germany, Department of Neuroscience und Medicine, INM-1, Research Center Jülich, D-52428 Jülich, Germany, Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, D-52074 Aachen, Germany, and JARA-Brain, Translational Brain Medicine, Jülich/Aachen, GermanyInstitute of Clinical Neuroscience and Medical Psychology, Medical Faculty Heinrich Heine University, D-40225 Düsseldorf, Germany, Department of Neuroscience und Medicine, INM-1, Research Center Jülich, D-52428 Jülich, Germany, Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, D-52074 Aachen, Germany, and JARA-Brain, Translational Brain Medicine, Jülich/Aachen, GermanyInstitute of Clinical Neuroscience and Medical Psychology, Medical Faculty Heinrich Heine University, D-40225 Düsseldorf, Germany, Department of Neuroscience und Medicine, INM-1, Research Center Jülich, D-52428 Jülich, Germany, Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, D-52074 Aachen, Germany, and JARA-Brain, Translational Brain Medicine, Jülich/Aachen, Germany
| | - Edna C Cieslik
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty Heinrich Heine University, D-40225 Düsseldorf, Germany, Department of Neuroscience und Medicine, INM-1, Research Center Jülich, D-52428 Jülich, Germany, Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, D-52074 Aachen, Germany, and JARA-Brain, Translational Brain Medicine, Jülich/Aachen, GermanyInstitute of Clinical Neuroscience and Medical Psychology, Medical Faculty Heinrich Heine University, D-40225 Düsseldorf, Germany, Department of Neuroscience und Medicine, INM-1, Research Center Jülich, D-52428 Jülich, Germany, Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, D-52074 Aachen, Germany, and JARA-Brain, Translational Brain Medicine, Jülich/Aachen, GermanyInstitute of Clinical Neuroscience and Medical Psychology, Medical Faculty Heinrich Heine University, D-40225 Düsseldorf, Germany, Department of Neuroscience und Medicine, INM-1, Research Center Jülich, D-52428 Jülich, Germany, Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, D-52074 Aachen, Germany, and JARA-Brain, Translational Brain Medicine, Jülich/Aachen, Germany
| | - Tanja S Kellermann
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty Heinrich Heine University, D-40225 Düsseldorf, Germany, Department of Neuroscience und Medicine, INM-1, Research Center Jülich, D-52428 Jülich, Germany, Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, D-52074 Aachen, Germany, and JARA-Brain, Translational Brain Medicine, Jülich/Aachen, GermanyInstitute of Clinical Neuroscience and Medical Psychology, Medical Faculty Heinrich Heine University, D-40225 Düsseldorf, Germany, Department of Neuroscience und Medicine, INM-1, Research Center Jülich, D-52428 Jülich, Germany, Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, D-52074 Aachen, Germany, and JARA-Brain, Translational Brain Medicine, Jülich/Aachen, GermanyInstitute of Clinical Neuroscience and Medical Psychology, Medical Faculty Heinrich Heine University, D-40225 Düsseldorf, Germany, Department of Neuroscience und Medicine, INM-1, Research Center Jülich, D-52428 Jülich, Germany, Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, D-52074 Aachen, Germany, and JARA-Brain, Translational Brain Medicine, Jülich/Aachen, Germany
| | - Simon B Eickhoff
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty Heinrich Heine University, D-40225 Düsseldorf, Germany, Department of Neuroscience und Medicine, INM-1, Research Center Jülich, D-52428 Jülich, Germany, Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, D-52074 Aachen, Germany, and JARA-Brain, Translational Brain Medicine, Jülich/Aachen, GermanyInstitute of Clinical Neuroscience and Medical Psychology, Medical Faculty Heinrich Heine University, D-40225 Düsseldorf, Germany, Department of Neuroscience und Medicine, INM-1, Research Center Jülich, D-52428 Jülich, Germany, Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, D-52074 Aachen, Germany, and JARA-Brain, Translational Brain Medicine, Jülich/Aachen, Germany
| |
Collapse
|
27
|
Müller VI, Langner R, Cieslik EC, Rottschy C, Eickhoff SB. Interindividual differences in cognitive flexibility: influence of gray matter volume, functional connectivity and trait impulsivity. Brain Struct Funct 2014; 220:2401-14. [PMID: 24878823 DOI: 10.1007/s00429-014-0797-6] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2013] [Accepted: 05/11/2014] [Indexed: 01/08/2023]
Abstract
Cognitive flexibility, a core aspect of executive functioning, is required for the speeded shifting between different tasks and sets. Using an interindividual differences approach, we examined whether cognitive flexibility, as assessed by the Delis-Kaplan card-sorting test, is associated with gray matter volume (GMV) and functional connectivity (FC) of regions of a core network of multiple cognitive demands as well as with different facets of trait impulsivity. The core multiple-demand network was derived from three large-scale neuroimaging meta-analyses and only included regions that showed consistent associations with sustained attention, working memory as well as inhibitory control. We tested to what extent self-reported impulsivity as well as GMV and resting-state FC in this core network predicted cognitive flexibility independently and incrementally. Our analyses revealed that card-sorting performance correlated positively with GMV of the right anterior insula, FC between bilateral anterior insula and midcingulate cortex/supplementary motor area as well as the impulsivity dimension "Premeditation." Importantly, GMV, FC and impulsivity together accounted for more variance of card-sorting performance than every parameter alone. Our results therefore indicate that various factors contribute individually to cognitive flexibility, underlining the need to search across multiple modalities when aiming to unveil the mechanisms behind executive functioning.
Collapse
Affiliation(s)
- Veronika I Müller
- Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Düsseldorf, Germany,
| | | | | | | | | |
Collapse
|
28
|
Müller V, Langner R, Cieslik EC, Rottschy C, Eickhoff S. Interindividual differences in cognitive flexibility: Influence of gray-matter volume, functional connectivity and trait impulsivity. KLIN NEUROPHYSIOL 2014. [DOI: 10.1055/s-0034-1371299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
|
29
|
Cieslik EC, Müller V, Kellermann T, Halfter S, Grefkes C, Eickhoff S. Shifted neuronal balance during stimulus-response integration in schizophrenia – an fMRI study. KLIN NEUROPHYSIOL 2014. [DOI: 10.1055/s-0034-1371300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
|
30
|
Müller VI, Cieslik EC, Laird AR, Fox PT, Eickhoff SB. Dysregulated left inferior parietal activity in schizophrenia and depression: functional connectivity and characterization. Front Hum Neurosci 2013; 7:268. [PMID: 23781190 PMCID: PMC3679482 DOI: 10.3389/fnhum.2013.00268] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2013] [Accepted: 05/24/2013] [Indexed: 11/23/2022] Open
Abstract
The inferior parietal cortex (IPC) is a heterogeneous region that is known to be involved in a multitude of diverse different tasks and processes, though its contribution to these often-complex functions is yet poorly understood. In a previous study we demonstrated that patients with depression failed to deactivate the left IPC during processing of congruent audiovisual information. We now found the same dysregulation (same region and condition) in schizophrenia. By using task-independent (resting state) and task-dependent meta-analytic connectivity modeling (MACM) analyses we aimed at characterizing this particular region with regard to its connectivity and function. Across both approaches, results revealed functional connectivity of the left inferior parietal seed region with bilateral IPC, precuneus and posterior cingulate cortex (PrC/PCC), medial orbitofrontal cortex (mOFC), left middle frontal (MFG) as well as inferior frontal (IFG) gyrus. Network-level functional characterization further revealed that on the one hand, all interconnected regions are part of a network involved in memory processes. On the other hand, sub-networks are formed when emotion, language, social cognition and reasoning processes are required. Thus, the IPC-region that is dysregulated in both depression and schizophrenia is functionally connected to a network of regions which, depending on task demands may form sub-networks. These results therefore indicate that dysregulation of left IPC in depression and schizophrenia might not only be connected to deficits in audiovisual integration, but is possibly also associated to impaired memory and deficits in emotion processing in these patient groups.
Collapse
Affiliation(s)
- Veronika I Müller
- Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University Düsseldorf, Germany ; Department of Neuroscience and Medicine, Research Center Jülich, INM-1 Jülich, Germany ; Department of Psychiatry, Psychotherapy, and Psychosomatics, Medical School, RWTH Aachen University Aachen, Germany
| | | | | | | | | |
Collapse
|
31
|
Cieslik EC, Bamberger K, Rottschy C, Eickhoff SB. Unterschiedliche neuronale Netzwerkes für die Verarbeitung kognitiver Interferenz – eine ALE-Meta-Analyse. KLIN NEUROPHYSIOL 2013. [DOI: 10.1055/s-0033-1337213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
|
32
|
Langner R, Cieslik EC, Behrwind SD, Roski C, Caspers S, Zilles K, Eickhoff SB. Altern und kognitive Handlungskontrolle: Veränderungen der Performanz und funktionellen Konnektivität. KLIN NEUROPHYSIOL 2013. [DOI: 10.1055/s-0033-1337211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
|
33
|
Müller VI, Cieslik EC, Laird AR, Fox PT, Eickhoff SB. Dysregulation des linken inferioren parietalen Kortex in Depression und Schizophrenie: funktionelle Konnektivität und Charakterisierung. KLIN NEUROPHYSIOL 2013. [DOI: 10.1055/s-0033-1337212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
|
34
|
Wollenweber FA, Halfter S, Brügmann E, Weinberg C, Cieslik EC, Müller VI, Hardwick RM, Eickhoff SB. Subtle cognitive deficits in severe alcohol addicts--do they show a specific profile? J Neuropsychol 2012; 8:147-53. [PMID: 23107392 DOI: 10.1111/jnp.12001] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2012] [Accepted: 09/19/2012] [Indexed: 11/29/2022]
Abstract
Although alcohol dependency is a burden to society, data on cognitive performance in therapy-resistant patients after multiple withdrawals are poor. In this study, 22 patients without reported cognitive deficits and 20 control subjects performed extensive cognitive testing and a motor task assessing short-term memory. Patients displayed subtle deficits (mainly in executive function), while memory functions were relatively unimpaired. Our results suggest that subtle frontal-executive deficits may contribute to a poor prognosis, but could be missed by routine clinical tests.
Collapse
Affiliation(s)
- Frank A Wollenweber
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University, Munich, Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital Aachen, Germany
| | | | | | | | | | | | | | | |
Collapse
|
35
|
Cieslik EC, Zilles K, Caspers S, Roski C, Kellermann TS, Jakobs O, Langner R, Laird AR, Fox PT, Eickhoff SB. Is there "one" DLPFC in cognitive action control? Evidence for heterogeneity from co-activation-based parcellation. ACTA ACUST UNITED AC 2012; 23:2677-89. [PMID: 22918987 PMCID: PMC3792742 DOI: 10.1093/cercor/bhs256] [Citation(s) in RCA: 277] [Impact Index Per Article: 23.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
The dorsolateral prefrontal cortex (DLPFC) has consistently been implicated in cognitive control of motor behavior. There is, however, considerable variability in the exact location and extension of these activations across functional magnetic resonance imaging (fMRI) experiments. This poses the question of whether this variability reflects sampling error and spatial uncertainty in fMRI experiments or structural and functional heterogeneity of this region. This study shows that the right DLPFC as observed in 4 different experiments tapping executive action control may be subdivided into 2 distinct subregions-an anterior-ventral and a posterior-dorsal one -based on their whole-brain co-activation patterns across neuroimaging studies. Investigation of task-dependent and task-independent connectivity revealed both clusters to be involved in distinct neural networks. The posterior subregion showed increased connectivity with bilateral intraparietal sulci, whereas the anterior subregion showed increased connectivity with the anterior cingulate cortex. Functional characterization with quantitative forward and reverse inferences revealed the anterior network to be more strongly associated with attention and action inhibition processes, whereas the posterior network was more strongly related to action execution and working memory. The present data provide evidence that cognitive action control in the right DLPFC may rely on differentiable neural networks and cognitive functions.
Collapse
Affiliation(s)
- Edna C Cieslik
- Institute of Neuroscience and Medicine, INM-1, Research Centre Jülich, Germany
| | | | | | | | | | | | | | | | | | | |
Collapse
|
36
|
|
37
|
Cieslik EC, Zilles K, Caspers S, Roski C, Kellermann T, Jakobs O, Langner R, Laird A, Fox P, Eickhoff S. Co-activation based parcellation of right dorsolateral prefrontal cortex. KLIN NEUROPHYSIOL 2012. [DOI: 10.1055/s-0032-1301468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
|
38
|
Müller VI, Cieslik EC, Turetsky BI, Eickhoff SB. Crossmodal interactions in audiovisual emotion processing. Neuroimage 2011; 60:553-61. [PMID: 22182770 DOI: 10.1016/j.neuroimage.2011.12.007] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2011] [Revised: 11/16/2011] [Accepted: 12/03/2011] [Indexed: 10/14/2022] Open
Abstract
Emotion in daily life is often expressed in a multimodal fashion. Consequently emotional information from one modality can influence processing in another. In a previous fMRI study we assessed the neural correlates of audio-visual integration and found that activity in the left amygdala is significantly attenuated when a neutral stimulus is paired with an emotional one compared to conditions where emotional stimuli were present in both channels. Here we used dynamic causal modelling to investigate the effective connectivity in the neuronal network underlying this emotion presence congruence effect. Our results provided strong evidence in favor of a model family, differing only in the interhemispheric interactions. All winning models share a connection from the bilateral fusiform gyrus (FFG) into the left amygdala and a non-linear modulatory influence of bilateral posterior superior temporal sulcus (pSTS) on these connections. This result indicates that the pSTS not only integrates multi-modal information from visual and auditory regions (as reflected in our model by significant feed-forward connections) but also gates the influence of the sensory information on the left amygdala, leading to attenuation of amygdala activity when a neutral stimulus is integrated. Moreover, we found a significant lateralization of the FFG due to stronger driving input by the stimuli (faces) into the right hemisphere, whereas such lateralization was not present for sound-driven input into the superior temporal gyrus. In summary, our data provides further evidence for a rightward lateralization of the FFG and in particular for a key role of the pSTS in the integration and gating of audio-visual emotional information.
Collapse
Affiliation(s)
- Veronika I Müller
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany.
| | | | | | | |
Collapse
|
39
|
Behrwind SD, Dafotakis M, Halfter S, Hobusch K, Berthold-Losleben M, Cieslik EC, Eickhoff SB. Executive control in chronic schizophrenia: A perspective from manual stimulus-response compatibility task performance. Behav Brain Res 2011; 223:24-9. [PMID: 21515312 PMCID: PMC3111937 DOI: 10.1016/j.bbr.2011.04.009] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2011] [Revised: 04/01/2011] [Accepted: 04/07/2011] [Indexed: 11/27/2022]
Abstract
BACKGROUND Antisaccade deficits are a well-documented pathophysiological characteristic in schizophrenia. However, it is yet unclear whether these findings reflect a specific oculomotor deficit, general psychomotor impairment or disturbance in executive control mechanisms. METHODS Performance in a manual stimulus-response compatibility (SRC) task and a neuropsychological test-battery covering different cognitive and motor domains were obtained in 28 patients with chronic schizophrenia. It was compared with a normative cohort of healthy subjects and validated by comparison with a sub-sample of that cohort consisting of 28 age, gender and education matched controls. RESULTS Patients showed significantly worse performance than controls in tests requiring maintenance or manipulating of multiple components but were unimpaired in simple motor, memory or executive tasks. In the SRC task patients had a significantly worse performance in the congruent condition and also a significantly higher increase in error rate from the congruent to the incongruent condition. There were, however, neither a group difference nor a group-by-condition interaction with respect to reaction times. INTERPRETATION : Our results provide evidence against an isolated oculomotor deficit but also against an undifferentiated psychomotor dysfunction in chronic schizophrenia. Rather, in synopsis with previous reports on antisaccade performance, it becomes evident that the degree of impairment follows closely the amount of executive control required in a task, which in turn may relate to dysfunctional top-down bias of the prefrontal cortex arising from unstable task instructions.
Collapse
Affiliation(s)
- Simone D Behrwind
- Department of Psychiatry & Psychotherapy, RWTH Aachen University, Aachen, Germany.
| | | | | | | | | | | | | |
Collapse
|
40
|
Schilbach L, Eickhoff SB, Cieslik EC, Kuzmanovic B, Vogeley K. Shall we do this together? Social gaze influences action control in a comparison group, but not in individuals with high-functioning autism. Autism 2011; 16:151-62. [PMID: 21810910 DOI: 10.1177/1362361311409258] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Perceiving someone else's gaze shift toward an object can influence how this object will be manipulated by the observer, suggesting a modulatory effect of a gaze-based social context on action control. High-functioning autism (HFA) is characterized by impairments of social interaction, which may be associated with an inability to automatically integrate socially relevant nonverbal cues when generating actions. To explore these hypotheses, we made use of a stimulus-response compatibility paradigm in which a comparison group and patients with HFA were asked to generate spatially congruent or incongruent motor responses to changes in a face, a face-like and an object stimulus. Results demonstrate that while in the comparison group being looked at by a virtual other leads to a reduction of reaction time costs associated with generating a spatially incongruent response, this effect is not present in the HFA group. We suggest that this modulatory effect of social gaze on action control might play an important role in direct social interactions by helping to coordinate one's actions with those of someone else. Future research should focus on these implicit mechanisms of interpersonal alignment ('online' social cognition), which might be at the very heart of the difficulties individuals with autism experience in everyday social encounters.
Collapse
|
41
|
Cieslik EC, Zilles K, Grefkes C, Eickhoff SB. Dynamic interactions in the fronto-parietal network during a manual stimulus-response compatibility task. Neuroimage 2011; 58:860-9. [PMID: 21708271 DOI: 10.1016/j.neuroimage.2011.05.089] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2011] [Revised: 04/15/2011] [Accepted: 05/20/2011] [Indexed: 11/18/2022] Open
Abstract
Attentional orienting can be modulated by stimulus-driven bottom-up as well as task-dependent top-down processes. In a recent study we investigated the interaction of both processes in a manual stimulus-response compatibility task. Whereas the intraparietal sulcus (IPS) and the dorsal premotor cortex (dPMC) were involved in orienting towards the stimulus side facilitating congruent motor responses, the right temporoparietal junction (TPJ), right dorsolateral prefrontal cortex (DLPFC) as well as the preSMA sustained top-down control processes involved in voluntary reorienting. Here we used dynamic causal modelling to investigate the contributions and task-dependent interactions between these regions. Thirty-six models were tested, all of which included bilateral IPS, dPMC and primary motor cortex (M1) as a network transforming visual input into motor output as well as the right TPJ, right DLPFC and the preSMA as task-dependent top-down regions influencing the coupling within the dorsal network. Our data showed the right temporoparietal junction to play a mediating role during attentional reorienting processes by modulating the inter-hemispheric balance between both IPS. Analysis of connection strength supported the proposed role of the preSMA in controlling motor responses promoting or suppressing activity in primary motor cortex. As the results did not show a clear tendency towards a role of the right DLPFC, we propose this region, against the usual interpretation of an inhibitory influence in stimulus-response compatibility tasks, to subserve generic monitoring processes. Our DCM study hence provides evidence for context-dependent top-down control of right TPJ and DLPFC as well as the preSMA in stimulus-response compatibility.
Collapse
Affiliation(s)
- Edna C Cieslik
- Institute of Neuroscience and Medicine, INM-2, Research Centre Jülich, Jülich, Germany.
| | | | | | | |
Collapse
|
42
|
Cieslik EC, Zilles K, Kurth F, Eickhoff SB. Dissociating bottom-up and top-down processes in a manual stimulus-response compatibility task. J Neurophysiol 2010; 104:1472-83. [PMID: 20573974 DOI: 10.1152/jn.00261.2010] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Speed and accuracy of motor responses to lateralized stimuli are influenced by the spatial overlap between stimulus location and required response. Responses showing high spatial overlap with peripheral cues benefit from a bottom-up driven enhancement of attention to the respective location, whereas low overlap requires top-down modulated reorienting of resources. Here we investigated the interaction between these two processes using a spatial stimulus-response compatibility task. Subjects had to react to lateralized visual stimuli with a button press using either the ipsilateral (congruent condition) or the contralateral (incongruent condition) index finger. Stimulus-driven bottom-up processes were associated with significant contralateral activation in V5, the intraparietal sulcus (IPS) and the premotor cortex (PMC). Incongruent versus congruent responses evoked significant activation in bilateral IPS and PMC, highly overlapping with the activations found for stimulus-driven bottom-up processes, as well as additional activation in bilateral anterior insula and right dorsolateral prefrontal cortex (DLPFC) and temporoparietal junction (TPJ). Moreover, a region anterior to the bottom-up driven activation in the IPS was associated with top-down modulated directionality-specific reorienting of motor attention during incongruent motor responses. Based on these results, we propose that stimulus-driven activation of contralateral IPS and PMC represent key neuronal substrates for the behavioral advantage observed when reacting toward a congruently lateralized stimulus. Additional activation in bilateral insula and right DLPFC and TPJ during incongruent responses should reflect top-down control mechanisms mediating contextual (i.e., task) demands. Furthermore, this study provides evidence for both overlapping and disparate substrates of bottom-up and top-down modulated attentional processes in the IPS.
Collapse
Affiliation(s)
- Edna C Cieslik
- Institut für Neurowissenschaften und Medizin, INM-2, Forschungszentrum Jülich GmbH, D- 52425 Jülich, Germany.
| | | | | | | |
Collapse
|