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Bastos G, Holmes JT, Ross JM, Rader AM, Gallimore CG, Wargo JA, Peterka DS, Hamm JP. Top-down input modulates visual context processing through an interneuron-specific circuit. Cell Rep 2023; 42:113133. [PMID: 37708021 PMCID: PMC10591868 DOI: 10.1016/j.celrep.2023.113133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 07/17/2023] [Accepted: 08/30/2023] [Indexed: 09/16/2023] Open
Abstract
Visual stimuli that deviate from the current context elicit augmented responses in the primary visual cortex (V1). These heightened responses, known as "deviance detection," require local inhibition in the V1 and top-down input from the anterior cingulate area (ACa). Here, we investigated the mechanisms by which the ACa and V1 interact to support deviance detection. Local field potential recordings in mice during an oddball paradigm showed that ACa-V1 synchrony peaks in the theta/alpha band (≈10 Hz). Two-photon imaging in the V1 revealed that mainly pyramidal neurons exhibited deviance detection, while contextually redundant stimuli increased vasoactive intestinal peptide (VIP)-positive interneuron (VIP) activity and decreased somatostatin-positive interneuron (SST) activity. Optogenetic drive of ACa-V1 inputs at 10 Hz activated V1-VIPs but inhibited V1-SSTs, mirroring the dynamics present during the oddball paradigm. Chemogenetic inhibition of V1-VIPs disrupted Aca-V1 synchrony and deviance detection in the V1. These results outline temporal and interneuron-specific mechanisms of top-down modulation that support visual context processing.
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Affiliation(s)
- Georgia Bastos
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA; Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA
| | - Jacob T Holmes
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA
| | - Jordan M Ross
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA; Center for Behavioral Neuroscience, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA
| | - Anna M Rader
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA; Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA
| | - Connor G Gallimore
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA
| | - Joseph A Wargo
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA
| | - Darcy S Peterka
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Jordan P Hamm
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA; Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA; Center for Behavioral Neuroscience, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA.
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Park J, Lee S, Choi D, Im CH. Enhancement of dynamic visual acuity using transcranial alternating current stimulation with gamma burst entrained on alpha wave troughs. BEHAVIORAL AND BRAIN FUNCTIONS : BBF 2023; 19:13. [PMID: 37620941 PMCID: PMC10463531 DOI: 10.1186/s12993-023-00215-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 08/11/2023] [Indexed: 08/26/2023]
Abstract
BACKGROUND Cross-frequency phase-amplitude coupling (PAC) of cortical oscillations is observed within and across cortical regions during higher-order cognitive processes. Particularly, the PAC of alpha and gamma waves in the occipital cortex is closely associated with visual perception. In theory, gamma oscillation is a neuronal representation of visual stimuli, which drives the duty cycle of visual perception together with alpha oscillation. Therefore, it is believed that the timing of entrainment in alpha-gamma PAC may play a critical role in the performance of visual perception. We hypothesized that transcranial alternating current stimulation (tACS) with gamma waves entrained at the troughs of alpha waves would enhance the dynamic visual acuity (DVA). METHOD We attempted to modulate the performance of DVA by using tACS. The waveforms of the tACS were tailored to target PAC over the occipital cortex. The waveforms contained gamma (80 Hz) waves oscillating at either the peaks or troughs of alpha (10 Hz) waves. Participants performed computerized DVA task before, immediately after, and 10 min after each stimulation sessions. EEG and EOG were recorded during the DVA task to assess inter-trial phase coherence (ITPC), the alpha-gamma PAC at occipital site and the eye movements. RESULTS tACS with gamma waves entrained at alpha troughs effectively enhanced DVA, while the tACS with gamma waves entrained at alpha peaks did not affect DVA performance. Importantly, analyses of EEG and EOG showed that the enhancement of DVA performance originated solely from the neuromodulatory effects, and was not related to the modulation of saccadic eye movements. Consequently, DVA, one of the higher-order cognitive abilities, was successfully modulated using tACS with a tailored waveform. CONCLUSIONS Our experimental results demonstrated that DVA performances were enhanced when tACS with gamma bursts entrained on alpha wave troughs were applied over the occipital cortex. Our findings suggest that using tACS with tailored waveforms, modulation of complex neuronal features could effectively enhance higher-order cognitive abilities such as DVA, which has never been modulated with conventional noninvasive brain stimulation methods.
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Affiliation(s)
- Jimin Park
- Department of Electronic Engineering, Hanyang University, Seoul, Republic of Korea
| | - Sangjun Lee
- Department of Electronic Engineering, Hanyang University, Seoul, Republic of Korea
| | - Dasom Choi
- Department of Electronic Engineering, Hanyang University, Seoul, Republic of Korea
| | - Chang-Hwan Im
- Department of Electronic Engineering, Hanyang University, Seoul, Republic of Korea
- Department of Biomedical Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, 133-791 Seoul, Republic of Korea
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Bastos G, Holmes JT, Ross JM, Rader AM, Gallimore CG, Peterka DS, Hamm JP. A frontosensory circuit for visual context processing is synchronous in the theta/alpha band. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.25.530044. [PMID: 36865311 PMCID: PMC9980180 DOI: 10.1101/2023.02.25.530044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2023]
Abstract
Visual processing is strongly influenced by context. Stimuli that deviate from contextual regularities elicit augmented responses in primary visual cortex (V1). These heightened responses, known as "deviance detection," require both inhibition local to V1 and top-down modulation from higher areas of cortex. Here we investigated the spatiotemporal mechanisms by which these circuit elements interact to support deviance detection. Local field potential recordings in mice in anterior cingulate area (ACa) and V1 during a visual oddball paradigm showed that interregional synchrony peaks in the theta/alpha band (6-12 Hz). Two-photon imaging in V1 revealed that mainly pyramidal neurons exhibited deviance detection, while vasointestinal peptide-positive interneurons (VIPs) increased activity and somatostatin-positive interneurons (SSTs) decreased activity (adapted) to redundant stimuli (prior to deviants). Optogenetic drive of ACa-V1 inputs at 6-12 Hz activated V1-VIPs but inhibited V1-SSTs, mirroring the dynamics present during the oddball paradigm. Chemogenetic inhibition of VIP interneurons disrupted ACa-V1 synchrony and deviance detection responses in V1. These results outline spatiotemporal and interneuron-specific mechanisms of top-down modulation that support visual context processing.
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Affiliation(s)
- Georgia Bastos
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303
- Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303
| | - Jacob T Holmes
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303
| | - Jordan M Ross
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303
- Center for Behavioral Neuroscience, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303
| | - Anna M Rader
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303
- Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303
| | - Connor G Gallimore
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303
| | - Darcy S Peterka
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Jordan P Hamm
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303
- Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303
- Center for Behavioral Neuroscience, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303
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Zhu P, Liu S, Tian Y, Chen Y, Chen W, Wang P, Du L, Wu C. Odor-induced modification of oscillations and related theta-higher gamma coupling in olfactory bulb neurons of awake and anesthetized rats. Front Chem 2022; 10:865006. [PMID: 35978860 PMCID: PMC9376862 DOI: 10.3389/fchem.2022.865006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
Olfactory gamma oscillations (40–100 Hz) are generated spontaneously in animals and represent the activity of local olfactory bulb (OB) networks, which play important roles in cognitive mechanisms. In addition, high-frequency oscillations (HFO, 130–180 Hz) have attracted widespread attention and are novel neuronal oscillations with a frequency range closer to high gamma oscillations (60–100 Hz, HGOs). Both HGOs and HFOs are distinctly regulated by θ rhythm in the hippocampus. To understand their mediation mechanisms in the OB, we investigated whether local field potential (LFP) oscillations including HGOs and HFOs and even their coupling with theta rhythm are modified by odor stimulation in both freely moving and anesthetized rats. Therefore, we combined electrophysiological technology and cross-frequency coupling analysis approaches to determine the difference in the odor-modulated LFP oscillations between awake and anesthetized rats. The obtained results indicate that LFP oscillations including HGOs and HFOs were differently modified by odor stimulation in animals of both states. However, θ-HGO and θ-HFO coupling were modified in only awake animals. It is suggested that these oscillations and their interactions with theta oscillations may play crucial roles in olfactory network activity. This could pave the way for further understanding the underlying mechanisms of oscillations in OB neurons towards odor sensation.
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Affiliation(s)
- Ping Zhu
- Department of Biophysics, Health Science Center, Institute of Medical Engineering, School of Basic Medical Sciences, Xi’an Jiaotong University, Xi’an, China
- Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education of China, Xi’an Jiaotong University, Xi’an, China
| | - Shuge Liu
- Department of Biophysics, Health Science Center, Institute of Medical Engineering, School of Basic Medical Sciences, Xi’an Jiaotong University, Xi’an, China
- Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education of China, Xi’an Jiaotong University, Xi’an, China
| | - Yulan Tian
- Department of Biophysics, Health Science Center, Institute of Medical Engineering, School of Basic Medical Sciences, Xi’an Jiaotong University, Xi’an, China
- Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education of China, Xi’an Jiaotong University, Xi’an, China
| | - Yating Chen
- Department of Biophysics, Health Science Center, Institute of Medical Engineering, School of Basic Medical Sciences, Xi’an Jiaotong University, Xi’an, China
- Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education of China, Xi’an Jiaotong University, Xi’an, China
| | - Wei Chen
- Department of Biophysics, Health Science Center, Institute of Medical Engineering, School of Basic Medical Sciences, Xi’an Jiaotong University, Xi’an, China
- Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education of China, Xi’an Jiaotong University, Xi’an, China
| | - Ping Wang
- Biosensor National Special Laboratory, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Liping Du
- Department of Biophysics, Health Science Center, Institute of Medical Engineering, School of Basic Medical Sciences, Xi’an Jiaotong University, Xi’an, China
- Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education of China, Xi’an Jiaotong University, Xi’an, China
- Biosensor National Special Laboratory, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
- *Correspondence: Liping Du, ; Chunsheng Wu,
| | - Chunsheng Wu
- Department of Biophysics, Health Science Center, Institute of Medical Engineering, School of Basic Medical Sciences, Xi’an Jiaotong University, Xi’an, China
- Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education of China, Xi’an Jiaotong University, Xi’an, China
- *Correspondence: Liping Du, ; Chunsheng Wu,
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Tabarelli D, Brancaccio A, Zrenner C, Belardinelli P. Functional Connectivity States of Alpha Rhythm Sources in the Human Cortex at Rest: Implications for Real-Time Brain State Dependent EEG-TMS. Brain Sci 2022; 12:348. [PMID: 35326304 PMCID: PMC8946162 DOI: 10.3390/brainsci12030348] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 02/13/2022] [Accepted: 02/24/2022] [Indexed: 02/04/2023] Open
Abstract
Alpha is the predominant rhythm of the human electroencephalogram, but its function, multiple generators and functional coupling patterns are still relatively unknown. In this regard, alpha connectivity patterns can change between different cortical generators depending on the status of the brain. Therefore, in the light of the communication through coherence framework, an alpha functional network depends on the functional coupling patterns in a determined state. This notion has a relevance for brain-state dependent EEG-TMS because, beyond the local state, a network connectivity overview at rest could provide further and more comprehensive information for the definition of 'instantaneous state' at the stimulation moment, rather than just the local state around the stimulation site. For this reason, we studied functional coupling at rest in 203 healthy subjects with MEG data. Sensor signals were source localized and connectivity was studied at the Individual Alpha Frequency (IAF) between three different cortical areas (occipital, parietal and prefrontal). Two different and complementary phase-coherence metrices were used. Our results show a consistent connectivity between parietal and prefrontal regions whereas occipito-prefrontal connectivity is less marked and occipito-parietal connectivity is extremely low, despite physical closeness. We consider our results a relevant add-on for informed, individualized real-time brain state dependent stimulation, with possible contributions to novel, personalized non-invasive therapeutic approaches.
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Affiliation(s)
- Davide Tabarelli
- Center for Mind/Brain Sciences—CIMeC, University of Trento, I-38123 Trento, Italy; (D.T.); (A.B.)
| | - Arianna Brancaccio
- Center for Mind/Brain Sciences—CIMeC, University of Trento, I-38123 Trento, Italy; (D.T.); (A.B.)
| | - Christoph Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Toronto, ON M6J 1H4, Canada;
| | - Paolo Belardinelli
- Center for Mind/Brain Sciences—CIMeC, University of Trento, I-38123 Trento, Italy; (D.T.); (A.B.)
- Department of Neurology & Stroke, University of Tübingen, D-72070 Tübingen, Germany
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Sadaghiani S, Brookes MJ, Baillet S. Connectomics of human electrophysiology. Neuroimage 2022; 247:118788. [PMID: 34906715 PMCID: PMC8943906 DOI: 10.1016/j.neuroimage.2021.118788] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 11/03/2021] [Accepted: 12/06/2021] [Indexed: 12/15/2022] Open
Abstract
We present both a scientific overview and conceptual positions concerning the challenges and assets of electrophysiological measurements in the search for the nature and functions of the human connectome. We discuss how the field has been inspired by findings and approaches from functional magnetic resonance imaging (fMRI) and informed by a small number of significant multimodal empirical studies, which show that the canonical networks that are commonplace in fMRI are in fact rooted in electrophysiological processes. This review is also an opportunity to produce a brief, up-to-date critical survey of current data modalities and analytical methods available for deriving both static and dynamic connectomes from electrophysiology. We review hurdles that challenge the significance and impact of current electrophysiology connectome research. We then encourage the field to take a leap of faith and embrace the wealth of electrophysiological signals, despite their apparent, disconcerting complexity. Our position is that electrophysiology connectomics is poised to inform testable mechanistic models of information integration in hierarchical brain networks, constructed from observable oscillatory and aperiodic signal components and their polyrhythmic interactions.
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Affiliation(s)
- Sepideh Sadaghiani
- Department of Psychology, University of Illinois, Urbana-Champaign, IL, United States; Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana-Champaign, IL, United States
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG72RD, United Kingdom
| | - Sylvain Baillet
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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OUP accepted manuscript. Cereb Cortex 2022; 32:4284-4292. [DOI: 10.1093/cercor/bhab482] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 11/14/2021] [Accepted: 11/15/2021] [Indexed: 11/13/2022] Open
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Cowley BU, Juurmaa K, Palomäki J. Reduced Power in Fronto-Parietal Theta EEG Linked to Impaired Attention-Sampling in Adult ADHD. eNeuro 2022; 9:ENEURO.0028-21.2021. [PMID: 34893505 PMCID: PMC8741145 DOI: 10.1523/eneuro.0028-21.2021] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 10/06/2021] [Accepted: 10/26/2021] [Indexed: 11/21/2022] Open
Abstract
Attention-deficit/hyperactivity disorder (ADHD) in adults is understudied, especially regarding neural mechanisms such as oscillatory control of attention sampling. We report an electroencephalography (EEG) study of such cortical mechanisms, in ADHD-diagnosed adults during administration of Test of Variables of Attention (TOVA), a gold-standard continuous performance test for ADHD that measures the ability to sustain attention and inhibit impulsivity. We recorded 53 adults (28 female, 25 male, aged 18-60), and 18 matched healthy controls, using 128-channel EEG. We analyzed sensor-space features established as neural correlates of attention: timing-sensitivity and phase-synchrony of response activations, and event-related (de)synchronization (ERS/D) of α and θ frequency band activity; in frontal and parietal scalp regions. TOVA test performance significantly distinguished ADHD adults from neurotypical controls, in commission errors, response time variability (RTV) and d' (response sensitivity). The ADHD group showed significantly weaker target-locked and response-locked amplitudes, that were strongly right-lateralized at the N2 wave, and weaker phase synchrony (longer reset poststimulus). They also manifested significantly less parietal prestimulus 8-Hz θ ERS, less frontal and parietal poststimulus 4-Hz θ ERS, and more frontal and parietal prestimulus α ERS during correct trials. These differences may reflect excessive modulation of endogenous activity by strong entrainment to stimulus (α), combined with deficient modulation by neural entrainment to task (θ), which in TOVA involves monitoring stimulus spatial location (not predicted occurrence onset which is regular and task-irrelevant). Building on the hypotheses of θ coding for relational structure and rhythmic attention sampling, our results suggest that ADHD adults have impaired attention sampling in relational categorization tasks.
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Affiliation(s)
- Benjamin Ultan Cowley
- Faculty of Educational Sciences, University of Helsinki, Helsinki 00014, Finland
- Cognitive Science, Department of Digital Humanities, Faculty of Arts, University of Helsinki, Helsinki 00014, Finland
| | - Kristiina Juurmaa
- Cognitive Science, Department of Digital Humanities, Faculty of Arts, University of Helsinki, Helsinki 00014, Finland
| | - Jussi Palomäki
- Cognitive Science, Department of Digital Humanities, Faculty of Arts, University of Helsinki, Helsinki 00014, Finland
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Parker DA, Trotti RL, McDowell JE, Keedy SK, Hill SK, Gershon ES, Ivleva EI, Pearlson GD, Keshavan MS, Tamminga CA, Clementz BA. Auditory Oddball Responses Across the Schizophrenia-Bipolar Spectrum and Their Relationship to Cognitive and Clinical Features. Am J Psychiatry 2021; 178:952-964. [PMID: 34407624 DOI: 10.1176/appi.ajp.2021.20071043] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Neural activations during auditory oddball tasks may be endophenotypes for psychosis and bipolar disorder. The authors investigated oddball neural deviations that discriminate multiple diagnostic groups across the schizophrenia-bipolar spectrum (schizophrenia, schizoaffective disorder, psychotic bipolar disorder, and nonpsychotic bipolar disorder) and clarified their relationship to clinical and cognitive features. METHODS Auditory oddball responses to standard and target tones from 64 sensor EEG recordings were compared across patients with psychosis (total N=597; schizophrenia, N=225; schizoaffective disorder, N=201; bipolar disorder with psychosis, N=171), patients with bipolar disorder without psychosis (N=66), and healthy comparison subjects (N=415) from the second iteration of the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP2) study. EEG activity was analyzed in voltage and in the time-frequency domain (low, beta, and gamma bands). Event-related potentials (ERPs) were compared with those from an independent sample collected during the first iteration of B-SNIP (B-SNIP1; healthy subjects, N=211; psychosis group, N=526) to establish the repeatability of complex oddball ERPs across multiple psychosis syndromes (r values >0.94 between B-SNIP1 and B-SNIP2). RESULTS Twenty-six EEG features differentiated the groups; they were used in discriminant and correlational analyses. EEG variables from the N100, P300, and low-frequency ranges separated the groups along a diagnostic continuum from healthy to bipolar disorder with psychosis/bipolar disorder without psychosis to schizoaffective disorder/schizophrenia and were strongly related to general cognitive function (r=0.91). P50 responses to standard trials and early beta/gamma frequency responses separated the bipolar disorder without psychosis group from the bipolar disorder with psychosis group. P200, N200, and late beta/gamma frequency responses separated the two bipolar disorder groups from the other groups. CONCLUSIONS Neural deviations during auditory processing are related to psychosis history and bipolar disorder. There is a powerful transdiagnostic relationship between severity of these neural deviations and general cognitive performance. These results have implications for understanding the neurobiology of clinical syndromes across the schizophrenia-bipolar spectrum that may have an impact on future biomarker research.
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Affiliation(s)
- David A Parker
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Rebekah L Trotti
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Jennifer E McDowell
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Sarah K Keedy
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - S Kristian Hill
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Elliot S Gershon
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Elena I Ivleva
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Godfrey D Pearlson
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Matcheri S Keshavan
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Carol A Tamminga
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Brett A Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
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10
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Wolpert N, Tallon-Baudry C. Coupling between the phase of a neural oscillation or bodily rhythm with behavior: Evaluation of different statistical procedures. Neuroimage 2021; 236:118050. [PMID: 33848619 PMCID: PMC8270889 DOI: 10.1016/j.neuroimage.2021.118050] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 02/12/2021] [Accepted: 04/06/2021] [Indexed: 11/24/2022] Open
Abstract
Circular tests are differentially sensitive to different coupling modes. The Watson test is a good all-rounder method. Phase Opposition Sum is robust to imbalances in relative trial number. Modulation Index detects more complex phase-behavior relationships.
Growing experimental evidence points at relationships between the phase of a cortical or bodily oscillation and behavior, using various circular statistical tests. Here, we systematically compare the performance (sensitivity, False Positive rate) of four circular statistical tests (some commonly used, i.e. Phase Opposition Sum, Circular Logistic Regression, others less common, i.e., Watson test, Modulation Index). We created semi-artificial datasets mimicking real two-alternative forced choice experiments with 30 participants, where we imposed a link between a simulated binary behavioral outcome with the phase of a physiological oscillation. We systematically varied the strength of phase-outcome coupling, the coupling mode (1:1 to 4:1), the overall number of trials and the relative number of trials in the two outcome conditions. We evaluated different strategies to estimate phase-outcome coupling chance level, as well as significance at the individual or group level. The results show that the Watson test, although seldom used in the experimental literature, is an excellent first intention test, with a good sensitivity and low False Positive rate, some sensitivity to 2:1 coupling mode and low computational load. Modulation Index, initially designed for continuous variables but that we find useful to estimate coupling between phase and a binary outcome, should be preferred if coupling mode is higher than 2:1. Phase Opposition Sum, coupled with a resampling procedure, is the only test retaining a good sensitivity in the case of a large unbalance in the number of occurrences of the two behavioral outcomes.
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Affiliation(s)
- Nicolai Wolpert
- Laboratoire de Neurosciences Cognitives et Computationnelles, Ecole Normale Supérieure, Inserm u960, PSL University, 24 rue Lhomond, Paris 75005, France.
| | - Catherine Tallon-Baudry
- Laboratoire de Neurosciences Cognitives et Computationnelles, Ecole Normale Supérieure, Inserm u960, PSL University, 24 rue Lhomond, Paris 75005, France
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11
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Parker DA, Trotti RL, McDowell JE, Keedy SK, Gershon ES, Ivleva EI, Pearlson GD, Keshavan MS, Tamminga CA, Sweeney JA, Clementz BA. Auditory paired-stimuli responses across the psychosis and bipolar spectrum and their relationship to clinical features. Biomark Neuropsychiatry 2020; 3:100014. [PMID: 36644018 PMCID: PMC9837793 DOI: 10.1016/j.bionps.2020.100014] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Background EEG responses during auditory paired-stimuli paradigms are putative biomarkers of psychosis syndromes. The initial iteration of the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP1) showed unique and common patterns of abnormalities across schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar disorder with psychosis (BDP). This study replicates those findings in new and large samples of psychosis cases and extends them to an important comparison group, bipolar disorder without psychosis (BDNP). Methods Paired stimuli responses from 64-sensor EEG recording were compared across psychosis (n = 597; SZ = 225, SAD = 201, BDP = 171), BDNP (n = 66), and healthy (n = 415) subjects from the second iteration of B-SNIP. EEG activity was analyzed in voltage and in the time-frequency domain. Principal component analysis (PCA) over sensors (sPCA) was used to efficiently capture EEG voltage responses to the paired stimuli. Evoked power was calculated via a Morlet wavelet procedure. A frequency PCA divided evoked power data into three frequency bands: Low (4-17 Hz), Beta (18-32 Hz), and Gamma (33-55 Hz). Each time-course (ERP Voltage, Low, Beta, and Gamma) were then segmented into 20 ms bins and analyzed for group differences. To efficiently summarize the multiple EEG components that best captured group differences we used multivariate discriminant and correlational analyses. This approach yields a reduced set of measures that may be useful in subsequent biomarker investigations. Results Group ANOVAs identified 17 time-ranges that showed significant group differences (p < .05 after FDR correction), constructively replicating B-SNIP1 findings. Multivariate linear discriminant analysis parsimoniously selected variables that best accounted for group differences: The P50 response to S1 and S2 uniquely separated BDNP from healthy and psychosis subjects (BDNP > all other groups); the S1 N100 response separated groups along an axis of psychopathology severity (HC > BDNP > BDP > SAD > SZ); the S1 P200 response indexed psychosis psychopathology (HC/BDNP > SAD/SZ/BDP); and the preparatory period to the S2 stimulus separated SZ from other groups (SZ > SAD/BDP>HC/BDNP).Canonical correlation identified an association between the neural responses during the S1 N100, S1 N200 and S2 preparatory period and PANSS positive symptoms and social functioning. The neural responses during the S1 P50 and S1 N100 were associated with PANSS Negative/General, MADRS and Young Mania symptoms. Conclusions This study constructively replicated prior B-SNIP1 research on auditory deviations observed during the paired stimuli task in SZ, SAD and BDP. Inclusion of a group of BDNP allows for the identification of biomarkers more closely related to affective versus nonaffective clinical phenotypes and neural distinctions between BDP and BDNP. Findings have implications for nosology and future translational work given that some biomarkers are shared across all psychosis and some are unique to affective syndromes.
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Affiliation(s)
| | | | - Jennifer E. McDowell
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Georgia
| | - Sarah K. Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States of America
| | - Elliot S. Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States of America
| | - Elena I. Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, United States of America
| | - Godfrey D. Pearlson
- Neuroscience, Yale School of Medicine, Institute of Living, Hartford Hospital, United States of America
| | - Matcheri S. Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, United States of America
| | - Carol A. Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, United States of America
| | - John A. Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States of America
| | - Brett A. Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Georgia, Corresponding author at: Psychology Department, 125 Jackson Street, Athens GA, 30601, Greece. (B.A. Clementz)
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12
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Hamm JP, Shymkiv Y, Mukai J, Gogos JA, Yuste R. Aberrant Cortical Ensembles and Schizophrenia-like Sensory Phenotypes in Setd1a +/- Mice. Biol Psychiatry 2020; 88:215-223. [PMID: 32143831 PMCID: PMC7363535 DOI: 10.1016/j.biopsych.2020.01.004] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 11/28/2019] [Accepted: 01/07/2020] [Indexed: 12/20/2022]
Abstract
BACKGROUND A breakdown of synchrony within neuronal ensembles leading to destabilization of network "attractors" could be a defining aspect of neuropsychiatric diseases such as schizophrenia, representing a common downstream convergence point for the diverse etiological pathways associated with the disease. Using a mouse genetic model, we demonstrated that altered ensembles are associated with pathological sensory cortical processing phenotypes resulting from loss of function mutations in the Setd1a gene, a recently identified rare risk genotype with very high penetrance for schizophrenia. METHODS We used fast two-photon calcium imaging of neuronal populations (calcium indicator GCaMP6s, 10 Hz, 100-250 cells, layer 2/3 of primary visual cortex, i.e., V1) in awake head-fixed mice (Setd1a+/- vs. wild-type littermate control) during rest and visual stimulation with moving full-field square-wave gratings (0.04 cycles per degree, 2.0 cycles per second, 100% contrast, 12 directions). Multielectrode recordings were analyzed in the time-frequency domain to assess stimulus-induced oscillations and cross-layer phase synchrony. RESULTS Neuronal activity and orientation/direction selectivity were unaffected in Setd1a+/- mice, but correlations between cell pairs in V1 showed altered distributions compared with wild-type mice, in both ongoing and visually evoked activity. Furthermore, population-wide "ensemble activations" in Setd1a+/- mice were markedly less reliable over time during rest and visual stimulation, resulting in unstable encoding of basic visual information. This alteration of ensembles coincided with reductions in alpha and high-gamma band phase synchrony within and between cortical layers. CONCLUSIONS These results provide new evidence for an ensemble hypothesis of schizophrenia and highlight the utility of Setd1a+/- mice for modeling sensory-processing phenotypes.
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Affiliation(s)
- Jordan P. Hamm
- Neurotechnology Center, Columbia University, New York, New York,Neuroscience Institute, Georgia State University, Atlanta, Georgia
| | - Yuriy Shymkiv
- Neurotechnology Center, Columbia University, New York, New York
| | - Jun Mukai
- College of Physicians and Surgeons; Mortimer B. Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, New York,Laboratory of Molecular Psychiatry and Neuroscience, Research and Development Center for Precision Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Joseph A. Gogos
- Department of Biological Sciences; Department of Physiology and Cellular Biophysics, Columbia University, New York, New York,College of Physicians and Surgeons; Mortimer B. Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, New York,Department of Neuroscience, Columbia University, New York, New York
| | - Rafael Yuste
- Neurotechnology Center, Columbia University, New York, New York
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13
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Agetsuma M, Hamm JP, Tao K, Fujisawa S, Yuste R. Parvalbumin-Positive Interneurons Regulate Neuronal Ensembles in Visual Cortex. Cereb Cortex 2019; 28:1831-1845. [PMID: 29106504 DOI: 10.1093/cercor/bhx169] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Accepted: 06/16/2017] [Indexed: 01/20/2023] Open
Abstract
For efficient cortical processing, neural circuit dynamics must be spatially and temporally regulated with great precision. Although parvalbumin-positive (PV) interneurons can control network synchrony, it remains unclear how they contribute to spatio-temporal patterning of activity. We investigated this by optogenetic inactivation of PV cells with simultaneous two-photon Ca2+ imaging from populations of neurons in mouse visual cortex in vivo. For both spontaneous and visually evoked activity, PV interneuron inactivation decreased network synchrony. But, interestingly, the response reliability and spatial extent of coactive neuronal ensembles during visual stimulation were also disrupted by PV-cell suppression, which reduced the functional repertoire of ensembles. Thus, PV interneurons can control the spatio-temporal dynamics of multineuronal activity by functionally sculpting neuronal ensembles and making them more different from each other. In doing so, inhibitory circuits could help to orthogonalize multicellular patterns of activity, enabling neural circuits to more efficiently occupy a higher dimensional space of potential dynamics.
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Affiliation(s)
- Masakazu Agetsuma
- Neurotechnology Center, Department of Biological Sciences, Columbia University, 550 West 120 Street, Box 4822, New York, NY 10027, USA.,Japan Science and Technology Agency, PRESTO, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan.,The Institute of Scientific and Industrial Research, Osaka University, Mihogaoka 8-1, Ibaraki, Osaka 567-0047, Japan.,National Institute for Physiological Sciences, Division of Homeostatic Development, 38 Nishigohnaka Myodaiji-cho, Okazaki, Aichi 444-8585, Japan
| | - Jordan P Hamm
- Neurotechnology Center, Department of Biological Sciences, Columbia University, 550 West 120 Street, Box 4822, New York, NY 10027, USA
| | - Kentaro Tao
- RIKEN Brain Science Institute, 2-1 Hirosawa, Wako, Saitama351-0106, Japan
| | | | - Rafael Yuste
- Neurotechnology Center, Department of Biological Sciences, Columbia University, 550 West 120 Street, Box 4822, New York, NY 10027, USA
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14
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Alpha Oscillations Modulate Preparatory Activity in Marmoset Area 8Ad. J Neurosci 2019; 39:1855-1866. [PMID: 30651331 DOI: 10.1523/jneurosci.2703-18.2019] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 01/03/2019] [Accepted: 01/04/2019] [Indexed: 11/21/2022] Open
Abstract
Cognitive control often requires suppression of prepotent stimulus-driven responses in favor of less potent alternatives. Suppression of prepotent saccades has been shown to require proactive inhibition in the frontoparietal saccade network. Electrophysiological evidence in macaque monkeys has revealed neural correlates of such inhibition in this network; however, the interlaminar instantiation of inhibitory processes remains poorly understood because these areas lie deep within sulci in macaques, rendering them inaccessible to laminar recordings. Here, we addressed this gap by exploiting the mostly lissencephalic cortex of the common marmoset (Callithrix jacchus). We inserted linear electrode arrays into areas 8Ad-the putative marmoset frontal eye field-and the lateral intraparietal area of two male marmosets and recorded neural activity during performance of a task comprised of alternating blocks of trials requiring a saccade either toward a large, high-luminance stimulus or the inhibition of this prepotent response in favor of a saccade toward a small, low-luminance stimulus. We observed prominent task-dependent activity in both alpha/gamma bands of the LFP and discharge rates of single neurons in area 8Ad during a prestimulus task epoch in which the animals had been instructed which of these two tasks to perform but before peripheral stimulus onset. These data are consistent with a model in which rhythmic alpha-band activity in deeper layers inhibits spiking in upper layers to support proactive inhibitory saccade control.SIGNIFICANCE STATEMENT Failures to inhibit automatic saccadic responses are a hallmark of many neuropsychiatric disorders, but how this process is implemented across the cortical layers in the frontoparietal saccade network remains unknown because many of the areas are inaccessible to laminar recordings in macaques. Here, we investigated laminar neural activity in marmoset monkeys, which have a smooth cortex. Monkeys were required either to generate or inhibit a prepotent saccade response. In area 8Ad, the putative frontal eye field in marmosets, rhythmic alpha-band activity (9-14 Hz) was higher in deeper layers and spiking activity was lower in upper layers when the animals were instructed to suppress a saccade toward a peripheral stimulus. Reduced alpha power during task preparation may be the underlying common neural basis of a saccade suppression deficit.
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15
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Schaeffer DJ, Rodrigue AL, Burton CR, Pierce JE, Murphy MN, Clementz BA, McDowell JE. White matter fiber integrity of the saccadic eye movement network differs between schizophrenia and healthy groups. Psychophysiology 2017; 54:1967-1977. [DOI: 10.1111/psyp.12969] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2016] [Revised: 06/26/2017] [Accepted: 06/28/2017] [Indexed: 11/28/2022]
Affiliation(s)
| | | | | | - Jordan E. Pierce
- Department of Psychology; University of Georgia; Athens Georgia USA
| | - Megan N. Murphy
- Department of Psychology; University of Georgia; Athens Georgia USA
| | - Brett A. Clementz
- Department of Neuroscience; University of Georgia; Athens Georgia USA
- Department of Psychology; University of Georgia; Athens Georgia USA
| | - Jennifer E. McDowell
- Department of Neuroscience; University of Georgia; Athens Georgia USA
- Department of Psychology; University of Georgia; Athens Georgia USA
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16
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Altered Cortical Ensembles in Mouse Models of Schizophrenia. Neuron 2017; 94:153-167.e8. [PMID: 28384469 DOI: 10.1016/j.neuron.2017.03.019] [Citation(s) in RCA: 130] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2015] [Revised: 10/07/2016] [Accepted: 03/10/2017] [Indexed: 01/26/2023]
Abstract
In schizophrenia, brain-wide alterations have been identified at the molecular and cellular levels, yet how these phenomena affect cortical circuit activity remains unclear. We studied two mouse models of schizophrenia-relevant disease processes: chronic ketamine (KET) administration and Df(16)A+/-, modeling 22q11.2 microdeletions, a genetic variant highly penetrant for schizophrenia. Local field potential recordings in visual cortex confirmed gamma-band abnormalities similar to patient studies. Two-photon calcium imaging of local cortical populations revealed in both models a deficit in the reliability of neuronal coactivity patterns (ensembles), which was not a simple consequence of altered single-neuron activity. This effect was present in ongoing and sensory-evoked activity and was not replicated by acute ketamine administration or pharmacogenetic parvalbumin-interneuron suppression. These results are consistent with the hypothesis that schizophrenia is an "attractor" disease and demonstrate that degraded neuronal ensembles are a common consequence of diverse genetic, cellular, and synaptic alterations seen in chronic schizophrenia.
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17
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Hudgens-Haney ME, Ethridge LE, Knight JB, McDowell JE, Keedy SK, Pearlson GD, Tamminga CA, Keshavan MS, Sweeney JA, Clementz BA. Intrinsic neural activity differences among psychotic illnesses. Psychophysiology 2017; 54:1223-1238. [PMID: 28419491 DOI: 10.1111/psyp.12875] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Revised: 03/03/2017] [Accepted: 03/11/2017] [Indexed: 12/13/2022]
Abstract
Individuals with psychosis have been reported to show either reduced or augmented brain responses under seemingly similar conditions. It is likely that inconsistent baseline-adjustment methods are partly responsible for this discrepancy. Using steady-state stimuli during a pro/antisaccade task, this study addressed the relationship between nonspecific and stimulus-related neural activity, and how these activities are modulated as a function of cognitive demands. In 98 psychosis probands (schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis), neural activity was assessed during baseline and during a 5-s period in preparation for the pro/antisaccade task. To maximize the ability to identify meaningful differences between psychosis subtypes, analyses were conducted as a function of subgrouping probands by standard clinical diagnoses and neurobiological features. These psychosis "biotypes" were created using brain-based biomarkers, independent of symptomatology (Clementz et al., ). Psychosis probands as a whole showed poor antisaccade performance and diminished baseline oscillatory phase synchrony. Psychosis biotypes differed on both behavioral and brain measures, in ways predicted from Clementz et al. (). Two biotype groups showed similarly deficient behavior and baseline synchrony, despite diametrically opposed neural activity amplitudes. Another biotype subgroup was more similar to healthy individuals on behavioral and brain measures, despite the presence of psychosis. This study provides evidence that (a) consideration of baseline levels of activation and synchrony will be essential for a comprehensive understanding of neural response differences in psychosis, and (b) distinct psychosis subgroups exhibit reduced versus augmented intrinsic neural activity, despite cognitive performance and clinical similarities.
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Affiliation(s)
- Matthew E Hudgens-Haney
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, Georgia
| | - Lauren E Ethridge
- Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma.,Department of Psychology, University of Oklahoma, Norman, Oklahoma
| | - Justin B Knight
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, Georgia
| | - Jennifer E McDowell
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, Georgia
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, Connecticut.,Institute of Living, Hartford Hospital, Hartford, Connecticut
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern, Dallas, Texas
| | | | - John A Sweeney
- Department of Psychiatry, University of Texas Southwestern, Dallas, Texas.,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio
| | - Brett A Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, Georgia
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18
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Cognitive control in the eye of the beholder: Electrocortical theta and alpha modulation during response preparation in a cued saccade task. Neuroimage 2017; 145:82-95. [DOI: 10.1016/j.neuroimage.2016.09.054] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2016] [Revised: 09/14/2016] [Accepted: 09/21/2016] [Indexed: 12/26/2022] Open
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19
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Perceptual Cycles. Trends Cogn Sci 2016; 20:723-735. [DOI: 10.1016/j.tics.2016.07.006] [Citation(s) in RCA: 396] [Impact Index Per Article: 49.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Revised: 07/22/2016] [Accepted: 07/29/2016] [Indexed: 11/21/2022]
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20
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VanRullen R. How to Evaluate Phase Differences between Trial Groups in Ongoing Electrophysiological Signals. Front Neurosci 2016; 10:426. [PMID: 27683543 PMCID: PMC5021700 DOI: 10.3389/fnins.2016.00426] [Citation(s) in RCA: 66] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2016] [Accepted: 08/31/2016] [Indexed: 11/13/2022] Open
Abstract
A growing number of studies endeavor to reveal periodicities in sensory and cognitive functions, by comparing the distribution of ongoing (pre-stimulus) oscillatory phases between two (or more) trial groups reflecting distinct experimental outcomes. A systematic relation between the phase of spontaneous electrophysiological signals, before a stimulus is even presented, and the eventual result of sensory or cognitive processing for that stimulus, would be indicative of an intrinsic periodicity in the underlying neural process. Prior studies of phase-dependent perception have used a variety of analytical methods to measure and evaluate phase differences, and there is currently no established standard practice in this field. The present report intends to remediate this need, by systematically comparing the statistical power of various measures of "phase opposition" between two trial groups, in a number of real and simulated experimental situations. Seven measures were evaluated: one parametric test (circular Watson-Williams test), and three distinct measures of phase opposition (phase bifurcation index, phase opposition sum, and phase opposition product) combined with two procedures for non-parametric statistical testing (permutation, or a combination of z-score and permutation). While these are obviously not the only existing or conceivable measures, they have all been used in recent studies. All tested methods performed adequately on a previously published dataset (Busch et al., 2009). On a variety of artificially constructed datasets, no single measure was found to surpass all others, but instead the suitability of each measure was contingent on several experimental factors: the time, frequency, and depth of oscillatory phase modulation; the absolute and relative amplitudes of post-stimulus event-related potentials for the two trial groups; the absolute and relative trial numbers for the two groups; and the number of permutations used for non-parametric testing. The concurrent use of two phase opposition measures, the parametric Watson-Williams test and a non-parametric test based on summing inter-trial coherence values for the two trial groups, appears to provide the most satisfactory outcome in all situations tested. Matlab code is provided to automatically compute these phase opposition measures.
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Affiliation(s)
- Rufin VanRullen
- Centre National de la Recherche Scientifique, UMR 5549, Faculté de Médecine PurpanToulouse, France; Université de Toulouse, Centre de Recherche Cerveau et Cognition, Université Paul SabatierToulouse, France
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21
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Meijer D, te Woerd E, Praamstra P. Timing of beta oscillatory synchronization and temporal prediction of upcoming stimuli. Neuroimage 2016; 138:233-241. [DOI: 10.1016/j.neuroimage.2016.05.071] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2015] [Revised: 05/25/2016] [Accepted: 05/27/2016] [Indexed: 11/15/2022] Open
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22
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Limbach K, Corballis PM. Prestimulus alpha power influences response criterion in a detection task. Psychophysiology 2016; 53:1154-64. [PMID: 27144476 DOI: 10.1111/psyp.12666] [Citation(s) in RCA: 92] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2015] [Accepted: 04/04/2016] [Indexed: 11/30/2022]
Abstract
Recent studies have linked variability in near-threshold stimulus detection to fluctuations in the prestimulus EEG alpha power (α, ∼8-12 Hz). Typically, these studies rely on hit rate as a measure of detection performance and show that detection is enhanced when α power is low compared to when it is high. However, hit rates are determined by both sensitivity to the stimulus and the placement of the response criterion. Here, we investigated the relationships between prestimulus α power and variability in these two measures on a single-trial basis. We confirm earlier reports that detection is inversely related to power in the individual α-frequency band. However, our results show a stronger relationship between α power and response criterion than with sensitivity. Higher α power was related to a more conservative response criterion (i.e., more "no" responses). A response criterion that varies depending on α power might help to optimize performance in an excited state and protect against false positives in a relatively disengaged state.
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Affiliation(s)
- Katharina Limbach
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand.,Institute of Psychology, Friedrich-Schiller-Universität Jena, Jena, Germany
| | - Paul M Corballis
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand
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23
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Wang C, Rajagovindan R, Han SM, Ding M. Top-Down Control of Visual Alpha Oscillations: Sources of Control Signals and Their Mechanisms of Action. Front Hum Neurosci 2016; 10:15. [PMID: 26834601 PMCID: PMC4718979 DOI: 10.3389/fnhum.2016.00015] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2015] [Accepted: 01/11/2016] [Indexed: 11/13/2022] Open
Abstract
Alpha oscillations (8-12 Hz) are thought to inversely correlate with cortical excitability. Goal-oriented modulation of alpha has been studied extensively. In visual spatial attention, alpha over the region of visual cortex corresponding to the attended location decreases, signifying increased excitability to facilitate the processing of impending stimuli. In contrast, in retention of verbal working memory, alpha over visual cortex increases, signifying decreased excitability to gate out stimulus input to protect the information held online from sensory interference. According to the prevailing model, this goal-oriented biasing of sensory cortex is effected by top-down control signals from frontal and parietal cortices. The present study tests and substantiates this hypothesis by (a) identifying the signals that mediate the top-down biasing influence, (b) examining whether the cortical areas issuing these signals are task-specific or task-independent, and (c) establishing the possible mechanism of the biasing action. High-density human EEG data were recorded in two experimental paradigms: a trial-by-trial cued visual spatial attention task and a modified Sternberg working memory task. Applying Granger causality to both sensor-level and source-level data we report the following findings. In covert visual spatial attention, the regions exerting top-down control over visual activity are lateralized to the right hemisphere, with the dipoles located at the right frontal eye field (FEF) and the right inferior frontal gyrus (IFG) being the main sources of top-down influences. During retention of verbal working memory, the regions exerting top-down control over visual activity are lateralized to the left hemisphere, with the dipoles located at the left middle frontal gyrus (MFG) being the main source of top-down influences. In both experiments, top-down influences are mediated by alpha oscillations, and the biasing effect is likely achieved via an inhibition-disinhibition mechanism.
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Affiliation(s)
- Chao Wang
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida Gainesville, FL, USA
| | - Rajasimhan Rajagovindan
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida Gainesville, FL, USA
| | - Sahng-Min Han
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida Gainesville, FL, USA
| | - Mingzhou Ding
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida Gainesville, FL, USA
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Pre-stimulus alpha and post-stimulus N2 foreshadow imminent errors in a single task. Neuropsychologia 2015; 77:346-58. [PMID: 26362494 DOI: 10.1016/j.neuropsychologia.2015.09.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2015] [Revised: 08/11/2015] [Accepted: 09/02/2015] [Indexed: 11/23/2022]
Abstract
Performance errors have been attributed to distinct neural mechanisms in different tasks. Two temporally and physiologically dissociable neural patterns prior to errors, i.e., pre-stimulus alpha (8-13 Hz) power indicative of sustained attention and post-stimulus N2 amplitude indicative of cognitive control, have been widely (but independently) reported in many studies. However, it is still largely unknown whether these two neural mechanisms for error commission exist in a single task at the same time and, if so, whether they can be probed simultaneously and how they lead to response accuracy (collectively or separately). To this end, we measured high-density electroencephalography (EEG) signals in a color-word matching Stroop task. We quantified both patterns on EEG data from individual stimulus condition (congruent or incongruent), as well as on pooled data from both conditions. Enhanced pre-stimulus alpha power for errors was identified over the parieto-occipital area in the congruent condition and the pooled data. Reduced post-stimulus N2 amplitude was only revealed in the incongruent condition. More importantly, for the first time, a balanced interaction between these two EEG patterns was revealed in correct trials, but not in error trials. These findings suggest that errors in one task could occur due to distinct neural mechanisms, e.g., poor sustained attention, poor cognitive control, or missed balance between these two. The present results further suggest that the detection of neural patterns related to different neural mechanisms could be complicated by other modulation factors, such as stimulus condition. Therefore, more than one neural marker should be simultaneously monitored to effectively predict imminent errors.
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Bompas A, Sumner P, Muthumumaraswamy SD, Singh KD, Gilchrist ID. The contribution of pre-stimulus neural oscillatory activity to spontaneous response time variability. Neuroimage 2015; 107:34-45. [PMID: 25482267 PMCID: PMC4306532 DOI: 10.1016/j.neuroimage.2014.11.057] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2014] [Revised: 11/14/2014] [Accepted: 11/30/2014] [Indexed: 11/17/2022] Open
Abstract
Large variability between individual response times, even in identical conditions, is a ubiquitous property of animal behavior. However, the origins of this stochasticity and its relation to action decisions remain unclear. Here we focus on the state of the perception-action network in the pre-stimulus period and its influence on subsequent saccadic response time and choice in humans. We employ magnetoencephalography (MEG) and a correlational source reconstruction approach to identify the brain areas where pre-stimulus oscillatory activity predicted saccadic response time to visual targets. We find a relationship between future response time and pre-stimulus power, but not phase, in occipital (including V1), parietal, posterior cingulate and superior frontal cortices, consistently across alpha, beta and low gamma frequencies, each accounting for between 1 and 4% of the RT variance. Importantly, these correlations were not explained by deterministic sources of variance, such as experimental factors and trial history. Our results further suggest that occipital areas mainly reflect short-term (trial to trial) stochastic fluctuations, while the frontal contribution largely reflects longer-term effects such as fatigue or practice. Parietal areas reflect fluctuations at both time scales. We found no evidence of lateralization: these effects were indistinguishable in both hemispheres and for both saccade directions, and non-predictive of choice - a finding with fundamental consequences for models of action decision, where independent, not coupled, noise is normally assumed.
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Affiliation(s)
- Aline Bompas
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Tower Building, Park Place, Cardiff CF10 3AT, UK; INSERM, U1028, CNRS, UMR5292, Lyon Neuroscience Research Center, Brain Dynamics and Cognition Team, Hopital du Vinatier, 95 Boulevard Pinel, Bron, 69500, France.
| | - Petroc Sumner
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Tower Building, Park Place, Cardiff CF10 3AT, UK
| | - Suresh D Muthumumaraswamy
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Tower Building, Park Place, Cardiff CF10 3AT, UK; School of Pharmacy and Psychology, Auckland University, Private Bag 92019, Auckland, New Zealand
| | - Krish D Singh
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Tower Building, Park Place, Cardiff CF10 3AT, UK
| | - Iain D Gilchrist
- School of Experimental Psychology, University of Bristol, 12A Priory Road, Bristol BS7 8SW, UK
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Shou G, Ding L. Detection of EEG spatial-spectral-temporal signatures of errors: a comparative study of ICA-based and channel-based methods. Brain Topogr 2014; 28:47-61. [PMID: 25228153 DOI: 10.1007/s10548-014-0397-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2013] [Accepted: 09/04/2014] [Indexed: 11/30/2022]
Abstract
The present study aimed to investigate the sensitivity of independent component analysis (ICA)- and channel-based methods in detecting electroencephalography (EEG) spatial-spectral-temporal signatures of performance errors. 128-channel EEG signals recorded from 18 subjects, who performed a color-word matching Stroop task, were analyzed. The spatial-spectral-temporal patterns in event-related potentials (ERPs) and oscillatory activities (i.e., power and phase) were measured at four selected channels, i.e., FCz, Pz, O1 and O2, from original EEG data after preprocessing, EEG data after additional current source density (CSD) transform, and back-projected EEG data from individual ICs after additional ICA analysis. Pair-wise correlation coefficient (CC) and mutual information (MI), calculated from three EEG data at four selected channels, were compared to examine mutual correlations in EEG signals obtained through three different means. Thereafter, EEG signatures of errors from these three means were statistically compared at multiple time windows in the contrast of error and correct responses. Significantly decreased CC and MI values were observed in CSD- and ICA-processed EEGs as compared with original EEG, with the smallest CC and MI in ICA EEG. Similar error patterns in ERPs and peri-response oscillatory activities were detected in all three EEGs, whereas the pre-stimulus and post-stimulus error-related oscillatory patterns identified in ICA EEG were either not or only partially detected in both original EEG and CSD EEGs in general. Both CSD and ICA processes can largely reduce signal correlations due to the volume conduction effect in original EEG, and EEG signatures of errors are better detected by ICA-based method than channel-based method (i.e., original and CSD EEGs). ICA provides the best sensitivity to detect EEG signatures linked to specific neural processes via disentangling superimposed channel-level EEG signals into distinct neurocognitive process-related component signals.
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Affiliation(s)
- Guofa Shou
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA
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Abstract
The ability to inhibit prepotent responses is critical for successful goal-directed behaviors. To investigate the neural basis of inhibitory control, we conducted a magnetoencephalography study where human participants performed the antisaccade task. Results indicated that neural oscillations in the prefrontal cortex (PFC) showed significant task modulations in preparation to suppress saccades. Before successfully inhibiting a saccade, beta-band power (18-38 Hz) in the lateral PFC and alpha-band power (10-18 Hz) in the frontal eye field (FEF) increased. Trial-by-trial prestimulus FEF alpha-band power predicted successful saccadic inhibition. Further, inhibitory control enhanced cross-frequency amplitude coupling between PFC beta-band (18-38 Hz) activity and FEF alpha-band activity, and the coupling appeared to be initiated by the PFC. Our results suggest a generalized mechanism for top-down inhibitory control: prefrontal beta-band activity initiates alpha-band activity for functional inhibition of the effector and/or sensory system.
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Hege MA, Preissl H, Stingl KT. Magnetoencephalographic signatures of right prefrontal cortex involvement in response inhibition. Hum Brain Mapp 2014; 35:5236-48. [PMID: 24845057 DOI: 10.1002/hbm.22546] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2013] [Revised: 04/30/2014] [Accepted: 05/02/2014] [Indexed: 11/08/2022] Open
Abstract
The prefrontal cortex has a pivotal role in top-down control of cognitive and sensory functions. In complex go-nogo tasks, the right dorsolateral prefrontal cortex is considered to be important for guiding the response inhibition. However, little is known about the temporal dynamics and neurophysiological nature of this activity. To address this issue, we recorded magnetoencephalographic brain activity in 20 women during a visual go-nogo task. The right dorsolateral prefrontal cortex showed an increase for the amplitude of the event-related fields and an increase in induced alpha frequency band activity for nogo in comparison to go trials. The peak of this prefrontal activity preceded the mean reaction time of around 360 ms for go trials, and thus supports the proposed role of right dorsolateral prefrontal cortex in gating the response inhibition and further suggests that right prefrontal alpha band activity might be involved in this gating. However, the results in right dorsolateral prefrontal cortex were similar for both successful and unsuccessful response inhibition. In these conditions, we instead observed pre- and poststimulus differences in alpha band activity in occipital and central areas. Thus, successful response inhibition seemed to additionally depend on prestimulus anticipatory alpha desynchronization in sensory areas as it was reduced prior to unsuccessful response inhibition. In conclusion, we suggest a role for functional inhibition by alpha synchronization not only in sensory, but also in prefrontal areas.
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Affiliation(s)
- Maike A Hege
- Institute of Medical Psychology and Behavioural Neurobiology, fMEG Center, University of Tübingen, 72076, Tübingen, Germany; Graduate School of Neural and Behavioural Sciences, International Max Planck Research School, University of Tübingen, 72074, Tübingen, Germany
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Kleberg FI, Kitajo K, Kawasaki M, Yamaguchi Y. Ongoing theta oscillations predict encoding of subjective memory type. Neurosci Res 2014; 83:69-80. [PMID: 24602686 DOI: 10.1016/j.neures.2014.02.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2013] [Revised: 01/20/2014] [Accepted: 02/09/2014] [Indexed: 11/26/2022]
Abstract
Recent human electro-encephalography (EEG) studies show that ongoing brain states support successful encoding of human memory, including recognition. However it is not known whether ongoing cortical activity qualitatively determines different memory types at encoding. In this study, using a remember/know procedure, we measured the EEG oscillations that emerge before and during the encoding of abstract visual stimuli in episodic and non-episodic memory, focusing on the theta (2-8Hz) and alpha (9-12Hz) oscillation range. We found that enhanced prestimulus theta oscillations precede episodic memory encoding, compared to non-episodic encoding. The prestimulus difference appeared at frontal and temporal sites. Furthermore, the theta enhancement reappeared after stimulus onset. Enhanced upper alpha oscillations suggested increased working memory processing in the case of episodic memory. Finally, the pre- and post-stimulus theta and alpha amplitudes showed different correlation patterns for episodic and non-episodic encoding. Our results are the first to suggest that encoding of episodic memory depends on preparatory processing in the form of frontal and temporal theta oscillations.
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Affiliation(s)
| | - Keiichi Kitajo
- RIKEN Brain Science Institute, 2-1 Hirosawa, Wako, Saitama, Japan; RIKEN BSI-Toyota Collaboration Center, 2-1 Hirosawa, Wako, Saitama, Japan.
| | - Masahiro Kawasaki
- RIKEN BSI-Toyota Collaboration Center, 2-1 Hirosawa, Wako, Saitama, Japan; Graduate School of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, Japan.
| | - Yoko Yamaguchi
- RIKEN Brain Science Institute, 2-1 Hirosawa, Wako, Saitama, Japan.
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Hamm JP, Ethridge LE, Boutros NN, Keshavan MS, Sweeney JA, Pearlson GD, Tamminga CA, Clementz BA. Diagnostic specificity and familiality of early versus late evoked potentials to auditory paired stimuli across the schizophrenia-bipolar psychosis spectrum. Psychophysiology 2014; 51:348-57. [PMID: 24660885 DOI: 10.1111/psyp.12185] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2013] [Accepted: 11/15/2013] [Indexed: 01/26/2023]
Abstract
Disrupted sensory processing is a core feature of psychotic disorders. Auditory paired stimuli (PS) evoke a complex neural response, but it is uncertain which aspects reflect shared and/or distinct liability for the most common severe psychoses, schizophrenia (SZ) and psychotic bipolar disorder (BDP). Evoked time-voltage/time-frequency domain responses quantified with EEG during a typical PS paradigm (S1-S2) were compared among proband groups (SZ [n = 232], BDP [181]), their relatives (SZrel [259], BDPrel [220]), and healthy participants (H [228]). Early S1-evoked responses were reduced in SZ and BDP, while later/S2 abnormalities showed SZ/SZrel and BDP/BDPrel specificity. Relatives' effects were absent/small despite significant familiality of the entire auditorineural response. This pattern suggests general and divergent biological pathways associated with psychosis, yet may reflect complications with conditioning solely on clinical phenomenology.
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Affiliation(s)
- Jordan P Hamm
- Department of Psychology, BioImaging Research Center, University of Georgia, Athens, Georgia, USA; Department of Neuroscience, BioImaging Research Center, University of Georgia, Athens, Georgia, USA
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Identifying electrode bridging from electrical distance distributions: a survey of publicly-available EEG data using a new method. Clin Neurophysiol 2013; 125:484-90. [PMID: 24095153 DOI: 10.1016/j.clinph.2013.08.024] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2013] [Revised: 07/23/2013] [Accepted: 08/25/2013] [Indexed: 11/22/2022]
Abstract
OBJECTIVE EEG topographies may be distorted by electrode bridges, typically caused by electrolyte spreading between adjacent electrodes. We therefore sought to determine the prevalence of electrode bridging and its potential impact on the EEG literature. METHODS Five publicly-available EEG datasets were evaluated for evidence of bridging using a new screening method that employs the temporal variance of pairwise difference waveforms (electrical distance). Distinctive characteristics of electrical distance frequency distributions were used to develop an algorithm to identify electrode bridges in datasets with different montages (22-64 channels) and noise properties. RESULTS The extent of bridging varied substantially across datasets: 54% of EEG recording sessions contained an electrode bridge, and the mean percentage of bridged electrodes in a montage was as high as 18% in one of the datasets. Furthermore, over 40% of the recording channels were bridged in 9 of 203 sessions. These findings were independently validated by visual inspection. CONCLUSIONS The new algorithm conveniently, efficiently, and reliably identified electrode bridges across different datasets and recording conditions. Electrode bridging may constitute a substantial problem for some datasets. SIGNIFICANCE Given the extent of the electrode bridging across datasets, this problem may be more widespread than commonly thought. However, when used as an automatic screening routine, the new algorithm will prevent pitfalls stemming from unrecognized electrode bridges.
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32
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Everling S, Johnston K. Control of the superior colliculus by the lateral prefrontal cortex. Philos Trans R Soc Lond B Biol Sci 2013; 368:20130068. [PMID: 24018729 DOI: 10.1098/rstb.2013.0068] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Several decades of patient, functional imaging and neurophysiological studies have supported a model in which the lateral prefrontal cortex (PFC) acts to suppress unwanted saccades by inhibiting activity in the oculomotor system. However, recent results from combined PFC deactivation and neural recordings of the superior colliculus in monkeys demonstrate that the primary influence of the PFC on the oculomotor system is excitatory, and stands in direct contradiction to the inhibitory model of PFC function. Although erroneous saccades towards a visual stimulus are commonly labelled reflexive in patients with PFC damage or dysfunction, the latencies of most of these saccades are outside of the range of express saccades, which are triggered directly by the visual stimulus. Deactivation and pharmacological manipulation studies in monkeys suggest that response errors following PFC damage or dysfunction are not the result of a failure in response suppression but can best be understood in the context of a failure to maintain and implement the proper task set.
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Affiliation(s)
- Stefan Everling
- Department of Physiology and Pharmacology, University of Western Ontario, , London, Ontario, Canada
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Abstract
Theta and gamma frequency oscillations occur in the same brain regions and interact with each other, a process called cross-frequency coupling. Here, we review evidence for the following hypothesis: that the dual oscillations form a code for representing multiple items in an ordered way. This form of coding has been most clearly demonstrated in the hippocampus, where different spatial information is represented in different gamma subcycles of a theta cycle. Other experiments have tested the functional importance of oscillations and their coupling. These involve correlation of oscillatory properties with memory states, correlation with memory performance, and effects of disrupting oscillations on memory. Recent work suggests that this coding scheme coordinates communication between brain regions and is involved in sensory as well as memory processes.
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Affiliation(s)
- John E. Lisman
- Brandeis University, Biology Department & Volen Center for Complex Systems, 415 South Street-MS 008, Waltham, MA 02454-9110, 781-736-3145
| | - Ole Jensen
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Kapittelweg 29, 6525 EN Nijmegen, The Netherlands
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34
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Vanrullen R, McLelland D. What goes up must come down: EEG phase modulates auditory perception in both directions. Front Psychol 2013; 4:16. [PMID: 23372558 PMCID: PMC3556584 DOI: 10.3389/fpsyg.2013.00016] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2012] [Accepted: 01/08/2013] [Indexed: 11/13/2022] Open
Affiliation(s)
- Rufin Vanrullen
- Centre de Recherche Cerveau et Cognition, Université Paul Sabatier, Université de Toulouse Toulouse, France ; CNRS, CerCo Toulouse, France
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Abstract
Fifty years ago Gazzaniga and coworkers published a seminal article that discussed the separate roles of the cerebral hemispheres in humans. Today, the study of interhemispheric communication is facilitated by a battery of novel data analysis techniques drawn from across disciplinary boundaries, including dynamic systems theory and network theory. These techniques enable the characterization of dynamic changes in the brain's functional connectivity, thereby providing an unprecedented means of decoding interhemispheric communication. Here, we illustrate the use of these techniques to examine interhemispheric coordination in healthy human participants performing a split visual field experiment in which they process lexical stimuli. We find that interhemispheric coordination is greater when lexical information is introduced to the right hemisphere and must subsequently be transferred to the left hemisphere for language processing than when it is directly introduced to the language-dominant (left) hemisphere. Further, we find that putative functional modules defined by coherent interhemispheric coordination come online in a transient manner, highlighting the underlying dynamic nature of brain communication. Our work illustrates that recently developed dynamic, network-based analysis techniques can provide novel and previously unapproachable insights into the role of interhemispheric coordination in cognition.
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36
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Hamm JP, Sabatinelli D, Clementz BA. Alpha oscillations and the control of voluntary saccadic behavior. Exp Brain Res 2012; 221:123-8. [PMID: 22782481 PMCID: PMC3601791 DOI: 10.1007/s00221-012-3167-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2011] [Accepted: 06/24/2012] [Indexed: 12/13/2022]
Abstract
The purpose of this review is to explore the dynamic properties of alpha oscillations as biological covariates of intra- and inter-individual variance in saccadic behavior. A preponderance of research suggests that oscillatory dynamics in the alpha band co-vary with performance on a number of visuo-spatial cognitive tasks. Here we discuss a growing body of research relating these measures to saccadic behavior, focusing also on how task related and spontaneous measures of alpha oscillations may serve as potential biomarkers for ocular motor dysfunction in clinical populations.
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Affiliation(s)
- Jordan P. Hamm
- Department of Psychology, BioImaging Research Center, University of Georgia, Psychology Building, Athens, GA 30602-3013, USA. Department of Neuroscience, BioImaging Research Center, University of Georgia, Psychology Building, Athens, GA 30602-3013, USA
| | - Dean Sabatinelli
- Department of Psychology, BioImaging Research Center, University of Georgia, Psychology Building, Athens, GA 30602-3013, USA. Department of Neuroscience, BioImaging Research Center, University of Georgia, Psychology Building, Athens, GA 30602-3013, USA
| | - Brett A. Clementz
- Department of Psychology, BioImaging Research Center, University of Georgia, Psychology Building, Athens, GA 30602-3013, USA. Department of Neuroscience, BioImaging Research Center, University of Georgia, Psychology Building, Athens, GA 30602-3013, USA
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