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Pratt DN, Luther L, Kinney KS, Osborne KJ, Corlett PR, Powers AR, Woods SW, Gold JM, Schiffman J, Ellman LM, Strauss GP, Walker EF, Zinbarg R, Waltz JA, Silverstein SM, Mittal VA. Comparing a Computerized Digit Symbol Test to a Pen-and-Paper Classic. SCHIZOPHRENIA BULLETIN OPEN 2023; 4:sgad027. [PMID: 37868160 PMCID: PMC10590153 DOI: 10.1093/schizbullopen/sgad027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/24/2023]
Abstract
Background and Hypothesis Processing speed dysfunction is a core feature of psychosis and predictive of conversion in individuals at clinical high risk (CHR) for psychosis. Although traditionally measured with pen-and-paper tasks, computerized digit symbol tasks are needed to meet the increasing demand for remote assessments. Therefore we: (1) assessed the relationship between traditional and computerized processing speed measurements; (2) compared effect sizes of impairment for progressive and persistent subgroups of CHR individuals on these tasks; and (3) explored causes contributing to task performance differences. Study Design Participants included 92 CHR individuals and 60 healthy controls who completed clinical interviews, the Brief Assessment of Cognition in Schizophrenia Symbol Coding test, the computerized TestMyBrain Digit Symbol Matching Test, a finger-tapping task, and a self-reported motor abilities measure. Correlations, Hedges' g, and linear models were utilized, respectively, to achieve the above aims. Study Results Task performance was strongly correlated (r = 0.505). A similar degree of impairment was seen between progressive (g = -0.541) and persistent (g = -0.417) groups on the paper version. The computerized task uniquely identified impairment for progressive individuals (g = -477), as the persistent group performed similarly to controls (g = -0.184). Motor abilities were related to the computerized version, but the paper version was more related to symptoms and psychosis risk level. Conclusions The paper symbol coding task measures impairment throughout the CHR state, while the computerized version only identifies impairment in those with worsening symptomatology. These results may be reflective of sensitivity differences, an artifact of existing subgroups, or evidence of mechanistic differences.
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Affiliation(s)
- Danielle N Pratt
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Lauren Luther
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Kyle S Kinney
- Department of Psychology & Neuroscience, Temple University, Philadelphia, PA, USA
| | | | | | - Albert R Powers
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Scott W Woods
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - James M Gold
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jason Schiffman
- Department of Psychological Science, University of California, Irvine, Irvine, CA, USA
| | - Lauren M Ellman
- Department of Psychology & Neuroscience, Temple University, Philadelphia, PA, USA
| | - Gregory P Strauss
- Department of Psychology, University of Georgia, Athens, GA, USA
- Department of Neuroscience, University of Georgia, Athens, GA, USA
| | - Elaine F Walker
- Department of Psychology and Program in Neuroscience, Emory University, Atlanta, GA, USA
| | - Richard Zinbarg
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - James A Waltz
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Steven M Silverstein
- Departments of Psychiatry, Neuroscience and Ophthalmology, University of Rochester Medical Center, Rochester, NY, USA
| | - Vijay A Mittal
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Institutes for Policy Research (IPR) and Innovations in Developmental Sciences (DevSci), Psychiatry, Medical Social Sciences, Northwestern University, Evanston, IL, USA
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Chi X, Wan C, Wang C, Zhang Y, Chen X, Cui H. A Novel Hybrid Brain-Computer Interface Combining Motor Imagery and Intermodulation Steady-State Visual Evoked Potential. IEEE Trans Neural Syst Rehabil Eng 2022; 30:1525-1535. [PMID: 35657833 DOI: 10.1109/tnsre.2022.3179971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The hybrid brain-computer interface (hBCI) combining motor imagery (MI) and steady-state visual evoked potential (SSVEP) has been proven to have better performance than a pure MI- or SSVEP-based brain-computer interface (BCI). In most studies on hBCIs, subjects have been required to focus their attention on flickering light-emitting diodes (LEDs) or blocks while imagining body movements. However, these two classical tasks performed concurrently have a poor correlation. Therefore, it is necessary to reduce the task complexity of such a system and improve its user-friendliness. Aiming to achieve this goal, this study proposes a novel hybrid BCI that combines MI and intermodulation SSVEPs. In the proposed system, images of both hands flicker at the same frequency (i.e., 30 Hz) but at different grasp frequencies (i.e., 1 Hz for the left hand, and 1.5 Hz for the right hand), resulting in different intermodulation frequencies for encoding targets. Additionally, movement observation for subjects can help to perform the MI task better. In this study, two types of brain signals are classified independently and then fused by a scoring mechanism based on the probability distribution of relevant parameters. The online verification results showed that the average accuracies of 12 healthy subjects and 11 stroke patients were 92.40 ± 7.45% and 73.07 ± 9.07%, respectively. The average accuracies of 10 healthy subjects in the MI, SSVEP, and hybrid tasks were 84.00 ± 12.81%, 80.75 ± 8.08%, and 89.00 ± 9.94%, respectively. The high recognition accuracy verifies the feasibility and robustness of the proposed system. This study provides a novel and natural paradigm for a hybrid BCI based on MI and SSVEP.
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Chen X, Hu N, Gao X. Development of a Brain-Computer Interface-Based Symbol Digit Modalities Test and Validation in Healthy Elderly Volunteers and Stroke Patients. IEEE Trans Neural Syst Rehabil Eng 2022; 30:1433-1440. [PMID: 35594216 DOI: 10.1109/tnsre.2022.3176615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Standard cognitive assessment tools often involve motor or verbal responses, making them impossible for severely motor-disabled individuals. Brain-computer interfaces (BCIs) are expected to help severely motor-impaired individuals to perform cognitive assessment because BCIs can circumvent motor and verbal requirements. Currently, the field of research to develop cognitive tasks based on BCI is still in its nascent stage and needs further development. This study explored the possibility of developing a BCI version of symbol digit modalities test (BCI-SDMT). Steady-state visual evoked potential (SSVEP) was adopted to build the BCI and a 9-target SSVEP-BCI was realized to send examinees' responses. A training-free algorithm (i.e., filter bank canonical correlation analysis) was used for SSVEP identification. Thus, examinees are able to start the proposed BCI-SDMT immediately. Eighty-nine healthy elderly volunteers and 9 stroke patients were enrolled to validate the technical feasibility of the developed BCI-SDMT. For all participants, the average recognition accuracies of the developed BCI and BCI-SDMT were 93.89 ± 8.48% and 92.58 ± 10.52%, respectively, were considerably above the chance level (i.e., 11.11%). These results indicated that both healthy elderly volunteers and stroke patients could elicit sufficient SSVEPs to control the BCI. Furthermore, patient use of the developed BCI-SDMT was unaffected by the presence of motor impairment. They could understand instructions, pair numbers with specific symbols, and send commands using the BCI. The proposed BCI-SDMT can be used as a complement to the existing versions of the SDMT and has the potential to evaluate cognitive abilities in individuals with severe motor disabilities.
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Chinda B, Tran KH, Doesburg S, Siu W, Medvedev G, Liang SS, Brooks-Wilson A, Song X. Functional MRI evaluation of cognitive effects of carotid stenosis revascularization. Brain Behav 2022; 12:e2512. [PMID: 35233977 PMCID: PMC9014987 DOI: 10.1002/brb3.2512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 12/10/2021] [Accepted: 01/07/2022] [Indexed: 11/12/2022] Open
Abstract
INTRODUCTION Severe internal carotid stenosis, if left untreated, can pose serious risks for ischemic stroke and cognitive impairments. The effects of revascularization on any aspects of cognition, however, are not well understood, as conflicting results are reported, which have mainly been centered on paper-based cognitive analyses. Here, we summarized and evaluated the publications to date of functional MRI (fMRI) studies that examined the mechanisms of functional brain activation and connectivity as a way to reflect cognitive effects of revascularization on patients with carotid stenosis. METHODS A PubMed and Google Scholar (covering the relevant literature until November 1, 2021) search yielded eight original studies of the research line, including seven resting-state and one task-based fMRI reports. RESULTS Findings demonstrated treatment-related alterations in fMRI signal intensity and symmetry level, regional fMRI activation pattern, and functional brain network connectivity. The functional brain changes were associated largely with improvement in cognitive function assessed using standard cognitive test scores. CONCLUSIONS These findings support the contribution of fMRI to the understanding of brain functional activation and connectivity changes revealing cognitive effects of revascularization in the management of severe carotid stenosis. The review also highlighted the importance of reproducibility through enhancing experimental designs and cognitive task applications with future research for potential clinical translation.
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Affiliation(s)
- Betty Chinda
- Department of Biomedical Physiology & Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada.,Clinical Research and Evaluation, Surrey Memorial Hospital, Fraser Health Authority, Surrey, British Columbia, Canada
| | - Kim H Tran
- Department of Biomedical Physiology & Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada.,Clinical Research and Evaluation, Surrey Memorial Hospital, Fraser Health Authority, Surrey, British Columbia, Canada
| | - Sam Doesburg
- Department of Biomedical Physiology & Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada
| | - William Siu
- Department of Radiology, Fraser Health Authority, Royal Columbian Hospital, New Westminster, British Columbia, Canada
| | - George Medvedev
- Department of Neurology, Fraser Health Authority, Royal Columbian Hospital, New Westminster, British Columbia, Canada
| | - S Simon Liang
- Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Angela Brooks-Wilson
- Department of Biomedical Physiology & Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada.,Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, British Columbia, Canada
| | - Xiaowei Song
- Department of Biomedical Physiology & Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada.,Clinical Research and Evaluation, Surrey Memorial Hospital, Fraser Health Authority, Surrey, British Columbia, Canada
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Leng X, Qin C, Lin H, Li M, Zhao K, Wang H, Duan F, An J, Wu D, Liu Q, Qiu S. Altered Topological Properties of Static/Dynamic Functional Networks and Cognitive Function After Radiotherapy for Nasopharyngeal Carcinoma Using Resting-State fMRI. Front Neurosci 2021; 15:690743. [PMID: 34335167 PMCID: PMC8316765 DOI: 10.3389/fnins.2021.690743] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Accepted: 06/21/2021] [Indexed: 12/17/2022] Open
Abstract
Objectives The purpose of this study was to (1) explore the changes in topological properties of static and dynamic brain functional networks after nasopharyngeal carcinoma (NPC) radiotherapy (RT) using rs-fMRI and graph theoretical analysis, (2) explore the correlation between cognitive function and changes in brain function, and (3) add to the understanding of the pathogenesis of radiation brain injury (RBI). Methods Fifty-four patients were divided into 3 groups according to time after RT: PT1 (0–6 months); PT2 (>6 to ≤12 months); and PT3 (>12 months). 29 normal controls (NCs) were included. The subjects’ topological properties were evaluated by graph-theoretic network analysis, the functional connectivity of static functional networks was calculated using network-based statistics, and the dynamic functional network matrix was subjected to cluster analysis. Finally, correlation analyses were conducted to explore the relationship between the altered network parameters and cognitive function. Results Assortativity, hierarchy, and network efficiency were significantly abnormal in the PT1 group compared with the NC or PT3 group. The small-world variance in the PT3 group was smaller than that in NCs. The Nodal ClustCoeff of Postcentral_R in the PT2 group was significantly smaller than that in PT3 and NC groups. Functional connectivities were significantly reduced in the patient groups. Most of the functional connectivities of the middle temporal gyrus (MTG) were shown to be significantly reduced in all three patient groups. Most of the functional connectivities of the insula showed significantly reduced in the PT1 and PT3 groups, and most of the functional connectivities in brain regions such as frontal and parietal lobes showed significantly reduced in the PT2 and PT3 groups. These abnormal functional connectivities were correlated with scores on multiple scales that primarily assessed memory, executive ability, and overall cognitive function. The frequency F of occurrence of various states in each subject differed significantly, and the interaction effect of group and state was significant. Conclusion The disruption of static and dynamic functional network stability, reduced network efficiency and reduced functional connectivity may be potential biomarkers of RBI. Our findings may provide new insights into the pathogenesis of RBI from the perspective of functional networks.
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Affiliation(s)
- Xi Leng
- Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Chunhong Qin
- Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Huan Lin
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Mingrui Li
- Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Kui Zhao
- Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Hongzhuo Wang
- Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Fuhong Duan
- Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Jie An
- Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Donglin Wu
- Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Qihui Liu
- Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shijun Qiu
- Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
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