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Bates KE, Smith ML, Farran EK, Machizawa MG. Behavioral and Neural Correlates of Visual Working Memory Reveal Metacognitive Aspects of Mental Imagery. J Cogn Neurosci 2024; 36:272-289. [PMID: 38010290 DOI: 10.1162/jocn_a_02085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Mental imagery (MI) is the ability to generate visual phenomena in the absence of sensory input. MI is often likened to visual working memory (VWM): the ability to maintain and manipulate visual representations. How MI is recruited during VWM is yet to be established. In a modified orientation change-discrimination task, we examined how behavioral (proportion correct) and neural (contralateral delay activity [CDA]) correlates of precision and capacity map onto subjective ratings of vividness and number of items in MI within a VWM task. During the maintenance period, 17 participants estimated the vividness of their MI or the number of items held in MI while they were instructed to focus on either precision or capacity of their representation and to retain stimuli at varying set sizes (1, 2, and 4). Vividness and number ratings varied over set sizes; however, subjective ratings and behavioral performance correlated only for vividness rating at set size 1. Although CDA responded to set size as was expected, CDA did not reflect subjective reports on high and low vividness and on nondivergent (reported the probed number of items in mind) or divergent (reported number of items diverged from probed) rating trials. Participants were more accurate in low set sizes compared with higher set sizes and in coarse (45°) orientation changes compared with fine (15°) orientation changes. We failed to find evidence for a relationship between the subjective sensory experience of precision and capacity of MI and the precision and capacity of VWM.
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Siebner HR, Funke K, Aberra AS, Antal A, Bestmann S, Chen R, Classen J, Davare M, Di Lazzaro V, Fox PT, Hallett M, Karabanov AN, Kesselheim J, Beck MM, Koch G, Liebetanz D, Meunier S, Miniussi C, Paulus W, Peterchev AV, Popa T, Ridding MC, Thielscher A, Ziemann U, Rothwell JC, Ugawa Y. Transcranial magnetic stimulation of the brain: What is stimulated? - A consensus and critical position paper. Clin Neurophysiol 2022; 140:59-97. [PMID: 35738037 PMCID: PMC9753778 DOI: 10.1016/j.clinph.2022.04.022] [Citation(s) in RCA: 119] [Impact Index Per Article: 59.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 03/14/2022] [Accepted: 04/15/2022] [Indexed: 12/11/2022]
Abstract
Transcranial (electro)magnetic stimulation (TMS) is currently the method of choice to non-invasively induce neural activity in the human brain. A single transcranial stimulus induces a time-varying electric field in the brain that may evoke action potentials in cortical neurons. The spatial relationship between the locally induced electric field and the stimulated neurons determines axonal depolarization. The induced electric field is influenced by the conductive properties of the tissue compartments and is strongest in the superficial parts of the targeted cortical gyri and underlying white matter. TMS likely targets axons of both excitatory and inhibitory neurons. The propensity of individual axons to fire an action potential in response to TMS depends on their geometry, myelination and spatial relation to the imposed electric field and the physiological state of the neuron. The latter is determined by its transsynaptic dendritic and somatic inputs, intrinsic membrane potential and firing rate. Modeling work suggests that the primary target of TMS is axonal terminals in the crown top and lip regions of cortical gyri. The induced electric field may additionally excite bends of myelinated axons in the juxtacortical white matter below the gyral crown. Neuronal excitation spreads ortho- and antidromically along the stimulated axons and causes secondary excitation of connected neuronal populations within local intracortical microcircuits in the target area. Axonal and transsynaptic spread of excitation also occurs along cortico-cortical and cortico-subcortical connections, impacting on neuronal activity in the targeted network. Both local and remote neural excitation depend critically on the functional state of the stimulated target area and network. TMS also causes substantial direct co-stimulation of the peripheral nervous system. Peripheral co-excitation propagates centrally in auditory and somatosensory networks, but also produces brain responses in other networks subserving multisensory integration, orienting or arousal. The complexity of the response to TMS warrants cautious interpretation of its physiological and behavioural consequences, and a deeper understanding of the mechanistic underpinnings of TMS will be critical for advancing it as a scientific and therapeutic tool.
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Affiliation(s)
- Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark; Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.
| | - Klaus Funke
- Department of Neurophysiology, Medical Faculty, Ruhr-University Bochum, Bochum, Germany
| | - Aman S Aberra
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Andrea Antal
- Department of Clinical Neurophysiology, University Medical Center, Georg-August-University, Göttingen, Germany
| | - Sven Bestmann
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Robert Chen
- Krembil Brain Institute, University Health Network and Division of Neurology, University of Toronto, Toronto, Ontario, Canada
| | - Joseph Classen
- Department of Neurology, University of Leipzig, Leipzig, Germany
| | - Marco Davare
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Vincenzo Di Lazzaro
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, Università Campus Bio-Medico di Roma, via Álvaro del Portillo 21, 00128 Rome, Italy
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, United States
| | - Mark Hallett
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Anke N Karabanov
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Department of Nutrition and Exercise, University of Copenhagen, Copenhagen, Denmark
| | - Janine Kesselheim
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Mikkel M Beck
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Giacomo Koch
- Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy; Non-invasive Brain Stimulation Unit, Laboratorio di NeurologiaClinica e Comportamentale, Fondazione Santa Lucia IRCCS, Rome, Italy
| | - David Liebetanz
- Department of Clinical Neurophysiology, University Medical Center, Georg-August-University, Göttingen, Germany
| | - Sabine Meunier
- Sorbonne Université, Faculté de Médecine, INSERM U 1127, CNRS 4 UMR 7225, Institut du Cerveau, F-75013, Paris, France
| | - Carlo Miniussi
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Italy; Cognitive Neuroscience Section, IRCCS Centro San Giovanni di DioFatebenefratelli, Brescia, Italy
| | - Walter Paulus
- Department of Clinical Neurophysiology, University Medical Center, Georg-August-University, Göttingen, Germany
| | - Angel V Peterchev
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; Department of Psychiatry & Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA; Department of Electrical & Computer Engineering, Duke University, Durham, NC, USA; Department of Neurosurgery, School of Medicine, Duke University, Durham, NC, USA
| | - Traian Popa
- Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland; Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Michael C Ridding
- University of South Australia, IIMPACT in Health, Adelaide, Australia
| | - Axel Thielscher
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Ulf Ziemann
- Department of Neurology & Stroke, University Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University Tübingen, Tübingen, Germany
| | - John C Rothwell
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Yoshikazu Ugawa
- Department of Neurology, Fukushima Medical University, Fukushima, Japan; Fukushima Global Medical Science Centre, Advanced Clinical Research Centre, Fukushima Medical University, Fukushima, Japan
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3
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Sensory recruitment in visual short-term memory: A systematic review and meta-analysis of sensory visual cortex interference using transcranial magnetic stimulation. Psychon Bull Rev 2022; 29:1594-1624. [PMID: 35606595 DOI: 10.3758/s13423-022-02107-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/13/2022] [Indexed: 11/08/2022]
Abstract
Sensory visual areas are involved in encoding information in visual short-term memory (VSTM). Yet it remains unclear whether sensory visual cortex is a necessary component of the brain network for maintenance of information in VSTM. Here, we aimed to systematically review studies that have investigated the role of the sensory visual cortex in VSTM using transcranial magnetic stimulation (TMS) and to quantitatively explore these effects using meta-analyses. Fourteen studies were identified and reviewed. Eight studies provided sufficient data for meta-analysis. Two meta-analyses, one regarding the VSTM encoding phase (17 effect sizes) and one regarding the VSTM maintenance phase (15 effect sizes), two meta-regressions (32 effect sizes in each), and one exploratory meta-analysis were conducted. Our results indicate that the sensory visual cortex is similarly involved in both the encoding and maintenance VSTM phase. We suggest that some cases where evidence did not show significant TMS effects was due to low memory or perceptual task demands. Overall, these findings support the idea that sensory visual areas are part of the brain network responsible for successfully maintaining information in VSTM.
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Rezayat E, Clark K, Dehaqani MRA, Noudoost B. Dependence of Working Memory on Coordinated Activity Across Brain Areas. Front Syst Neurosci 2022; 15:787316. [PMID: 35095433 PMCID: PMC8792503 DOI: 10.3389/fnsys.2021.787316] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 12/06/2021] [Indexed: 11/15/2022] Open
Abstract
Neural signatures of working memory (WM) have been reported in numerous brain areas, suggesting a distributed neural substrate for memory maintenance. In the current manuscript we provide an updated review of the literature focusing on intracranial neurophysiological recordings during WM in primates. Such signatures of WM include changes in firing rate or local oscillatory power within an area, along with measures of coordinated activity between areas based on synchronization between oscillations. In comparing the ability of various neural signatures in any brain area to predict behavioral performance, we observe that synchrony between areas is more frequently and robustly correlated with WM performance than any of the within-area neural signatures. We further review the evidence for alteration of inter-areal synchrony in brain disorders, consistent with an important role for such synchrony during behavior. Additionally, results of causal studies indicate that manipulating synchrony across areas is especially effective at influencing WM task performance. Each of these lines of research supports the critical role of inter-areal synchrony in WM. Finally, we propose a framework for interactions between prefrontal and sensory areas during WM, incorporating a range of experimental findings and offering an explanation for the observed link between intra-areal measures and WM performance.
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Affiliation(s)
- Ehsan Rezayat
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Kelsey Clark
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, United States
| | - Mohammad-Reza A. Dehaqani
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Cognitive Systems Laboratory, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Behrad Noudoost
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, United States
- *Correspondence: Behrad Noudoost,
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Gann MA, King BR, Dolfen N, Veldman MP, Davare M, Swinnen SP, Mantini D, Robertson EM, Albouy G. Prefrontal stimulation prior to motor sequence learning alters multivoxel patterns in the striatum and the hippocampus. Sci Rep 2021; 11:20572. [PMID: 34663890 PMCID: PMC8523553 DOI: 10.1038/s41598-021-99926-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 09/24/2021] [Indexed: 11/09/2022] Open
Abstract
Motor sequence learning (MSL) is supported by dynamical interactions between hippocampal and striatal networks that are thought to be orchestrated by the prefrontal cortex. In the present study, we tested whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex (DLPFC) prior to MSL can modulate multivoxel response patterns in the stimulated cortical area, the hippocampus and the striatum. Response patterns were assessed with multivoxel correlation structure analyses of functional magnetic resonance imaging data acquired during task practice and during resting-state scans before and after learning/stimulation. Results revealed that, across stimulation conditions, MSL induced greater modulation of task-related DLPFC multivoxel patterns than random practice. A similar learning-related modulatory effect was observed on sensorimotor putamen patterns under inhibitory stimulation. Furthermore, MSL as well as inhibitory stimulation affected (posterior) hippocampal multivoxel patterns at post-intervention rest. Exploratory analyses showed that MSL-related brain patterns in the posterior hippocampus persisted into post-learning rest preferentially after inhibitory stimulation. These results collectively show that prefrontal stimulation can alter multivoxel brain patterns in deep brain regions that are critical for the MSL process. They also suggest that stimulation influenced early offline consolidation processes as evidenced by a stimulation-induced modulation of the reinstatement of task pattern into post-learning wakeful rest.
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Affiliation(s)
- Mareike A Gann
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium
- LBI - KU Leuven Brain Institute, KU Leuven, 3001, Leuven, Belgium
| | - Bradley R King
- Department of Health and Kinesiology, College of Health, University of Utah, Salt Lake City, UT, 84112, USA
| | - Nina Dolfen
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium
- LBI - KU Leuven Brain Institute, KU Leuven, 3001, Leuven, Belgium
| | - Menno P Veldman
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium
- LBI - KU Leuven Brain Institute, KU Leuven, 3001, Leuven, Belgium
| | - Marco Davare
- Department of Clinical Sciences, College of Health and Life Sciences, Brunel University London, Uxbridge, UB8 3PN, UK
| | - Stephan P Swinnen
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium
- LBI - KU Leuven Brain Institute, KU Leuven, 3001, Leuven, Belgium
| | - Dante Mantini
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium
- Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, 30126, Venice, Italy
| | - Edwin M Robertson
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, G12 8QB, UK
| | - Geneviève Albouy
- Department of Movement Sciences, Movement Control and Neuroplasticity Research Group, KU Leuven, 3001, Leuven, Belgium.
- LBI - KU Leuven Brain Institute, KU Leuven, 3001, Leuven, Belgium.
- Department of Health and Kinesiology, College of Health, University of Utah, Salt Lake City, UT, 84112, USA.
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Furman DJ, Zhang Z, Chatham CH, Good M, Badre D, Hsu M, Kayser AS. Augmenting Frontal Dopamine Tone Enhances Maintenance over Gating Processes in Working Memory. J Cogn Neurosci 2021; 33:1753-1765. [PMID: 33054556 DOI: 10.1162/jocn_a_01641] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
The contents of working memory must be maintained in the face of distraction, but updated when appropriate. To manage these competing demands of stability and flexibility, maintained representations in working memory are complemented by distinct gating mechanisms that selectively transmit information into and out of memory stores. The operations of such dopamine-dependent gating systems in the midbrain and striatum and their complementary dopamine-dependent memory maintenance operations in the cortex may therefore be dissociable. If true, selective increases in cortical dopamine tone should preferentially enhance maintenance over gating mechanisms. To test this hypothesis, tolcapone, a catechol-O-methyltransferase inhibitor that preferentially increases cortical dopamine tone, was administered in a randomized, double-blind, placebo-controlled, within-subject fashion to 49 participants who completed a hierarchical working memory task that varied maintenance and gating demands. Tolcapone improved performance in a condition with higher maintenance requirements and reduced gating demands, reflected in a reduction in the slope of RTs across the distribution. Resting-state fMRI data demonstrated that the degree to which tolcapone improved performance in individual participants correlated with increased connectivity between a region important for stimulus response mappings (left dorsal premotor cortex) and cortical areas implicated in visual working memory, including the intraparietal sulcus and fusiform gyrus. Together, these results provide evidence that augmenting cortical dopamine tone preferentially improves working memory maintenance.
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Affiliation(s)
- Daniella J Furman
- University of California, San Francisco.,University of California, Berkeley
| | | | | | | | | | - Ming Hsu
- University of California, Berkeley
| | - Andrew S Kayser
- University of California, San Francisco.,University of California, Berkeley.,VA Northern California Health Care System
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7
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Turner GR, Novakovic-Agopian T, Kornblith E, Adnan A, Madore M, Chen AJW, D'Esposito M. Goal-Oriented Attention Self-Regulation (GOALS) training in older adults. Aging Ment Health 2020; 24:464-473. [PMID: 30724574 DOI: 10.1080/13607863.2018.1534080] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Objectives: A common cognitive complaint of older adulthood is distractibility, or decline in ability to concentrate and maintain focus, yet few evidence-based interventions exist to address these deficits. We implemented s pilot trial of an evidence-based executive function training program, to investigate whether training in applied goal-directed attention regulation and problem solving would enhance executive control abilities in a sample of cognitively normal older adults with self-reported complaints of concentration problems.Method: Consecutively recruited participants were placed into small groups and randomized to either Goal-Oriented Attentional Self-Regulation training (GOALS; N = 15) or a closely matched Brain Health Education program (BHE; N = 15).Results: GOALS participants significantly improved on: neurocognitive measures of mental flexibility (p = 0.03, partial eta squared = 0.23); real-world setting functional performance measures of: task failures (p = 0.02, Cohen's d = 0.88), task rule breaks (p = 0.02, Cohen's d = 1.06), and execution (p = 0.04, Cohen's d = 0.76); and in-lab functional assessment of goal-directed behaviour divergent thinking scale (p = 0.03, Cohen's d = 0.95). All participants improved on a neurocognitive measure of planning (p = 0.01, partial eta squared = 0.031). BHE participants' improvement over and above GOALS participants was limited to: rule adherence on the real world task (p = 0.04, Cohen's d = 0.99), and evaluator rating (p = 0.03, Cohen's d = 0.56), and average score (p = 0.02, Cohen's d = 0.71) on the in-lab functional task.Conclusion: Participation in GOALS training can enhance executive control, and lead to real-world functional improvements, for cognitively normal older adults with self-reported attention difficulties.
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Affiliation(s)
| | | | | | | | | | - Anthony J W Chen
- University of California, Berkeley, USA.,Veteran's Administration Northern California Health Care System, Martinez, USA
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8
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Villalba-Diez J, Zheng X, Schmidt D, Molina M. Characterization of Industry 4.0 Lean Management Problem-Solving Behavioral Patterns Using EEG Sensors and Deep Learning. SENSORS (BASEL, SWITZERLAND) 2019; 19:E2841. [PMID: 31247966 PMCID: PMC6651207 DOI: 10.3390/s19132841] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Revised: 06/09/2019] [Accepted: 06/21/2019] [Indexed: 01/04/2023]
Abstract
Industry 4.0 leaders solve problems all of the time. Successful problem-solving behavioral pattern choice determines organizational and personal success, therefore a proper understanding of the problem-solving-related neurological dynamics is sure to help increase business performance. The purpose of this paper is two-fold: first, to discover relevant neurological characteristics of problem-solving behavioral patterns, and second, to conduct a characterization of two problem-solving behavioral patterns with the aid of deep-learning architectures. This is done by combining electroencephalographic non-invasive sensors that capture process owners' brain activity signals and a deep-learning soft sensor that performs an accurate characterization of such signals with an accuracy rate of over 99% in the presented case-study dataset. As a result, the deep-learning characterization of lean management (LM) problem-solving behavioral patterns is expected to help Industry 4.0 leaders in their choice of adequate manufacturing systems and their related problem-solving methods in their future pursuit of strategic organizational goals.
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Affiliation(s)
- Javier Villalba-Diez
- Fakultät Management und Vertrieb, Hochschule Heilbronn Campus Schwäbisch Hall, 74523 Schwäbisch Hall, Germany.
- Departament of Artificial Intelligence, Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, 28660 Madrid, Spain.
| | - Xiaochen Zheng
- Departament of Business Intelligence, Escuela Técnica Superior de Ingenieros Industriales, Universidad Politécnica de Madrid, 2006 Madrid, Spain
| | - Daniel Schmidt
- Saueressig GmbH + Co. KG, Gutenbergstr. 1-3, 48691 Vreden, Germany
| | - Martin Molina
- Departament of Artificial Intelligence, Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, 28660 Madrid, Spain
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Hippmann B, Kuhlemann I, Bäumer T, Bahlmann J, Münte TF, Jessen S. Boosting the effect of reward on cognitive control using TMS over the left IFJ. Neuropsychologia 2019; 125:109-115. [PMID: 30721740 DOI: 10.1016/j.neuropsychologia.2019.01.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Revised: 01/22/2019] [Accepted: 01/27/2019] [Indexed: 11/24/2022]
Abstract
Although an enhancing effect of reward on cognitive performance has been observed consistently, its neural underpinnings remain elusive. Recent evidence suggests that the inferior frontal junction (IFJ) may be a key player underlying such an enhancement by integrating motivational processes and cognitive control. However, its exact role and in particular a potential causality of IFJ activation is still unclear. In the present study, we therefore investigated the causal contributions of the left IFJ in motivated task switching by temporarily disrupting its activity using continuous theta burst stimulation (cTBS, Exp.1) or 1 Hz repetitive transcranial magnetic stimulation (rTMS, Exp.2). After TMS application over the left IFJ or a control site (vertex), participants performed a switch task in which numbers had to be judged by magnitude or parity. Different amounts of monetary rewards (high vs low) were used to manipulate the participants' motivational states. We measured reaction times and error rates. Irrespective of TMS stimulation, participants exhibited slower responses following task switches compared to task repeats. This effect was reduced in high reward trials. Importantly, we found that disrupting the IFJ improved participants' behavioral performance in the high reward condition. For high reward trials exclusively, error rates decreased when the IFJ was modulated with cTBS or 1 Hz rTMS but not after vertex stimulation. Our results suggest that the left IFJ is causally related to the increase in cognitive performance through reward.
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Affiliation(s)
| | - Ivo Kuhlemann
- Institute for Robotics and Cognitive Systems, University of Lübeck, D-23538 Lübeck, Germany
| | - Tobias Bäumer
- Institute of Neurogenetics, University of Lübeck, D-23538 Lübeck, Germany
| | - Jörg Bahlmann
- Department of Neurology, University of Lübeck, D-23538 Lübeck, Germany
| | - Thomas F Münte
- Department of Neurology, University of Lübeck, D-23538 Lübeck, Germany
| | - Sarah Jessen
- Department of Neurology, University of Lübeck, D-23538 Lübeck, Germany
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10
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Hwang K, Shine JM, D’Esposito M. Frontoparietal Activity Interacts With Task-Evoked Changes in Functional Connectivity. Cereb Cortex 2019; 29:802-813. [PMID: 29415156 PMCID: PMC7199886 DOI: 10.1093/cercor/bhy011] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Revised: 12/14/2017] [Indexed: 12/25/2022] Open
Abstract
Flexible interactions between brain regions enable neural systems to adaptively transfer and process information. However, the neural substrates that regulate adaptive communications between brain regions are understudied. In this human fMRI study, we investigated this issue by tracking time-varying, task-evoked changes in functional connectivity between localized occipitotemporal regions while participants performed different tasks on the same visually presented stimuli. We found that functional connectivity between ventral temporal and the primary visual regions selectively increased during the processing of task-relevant information. Further, additional task demands selectively strengthen these targeted connectivity patterns. To identify candidate regions that contribute to this increase in inter-regional coupling, we regressed the task-specific time-varying connectivity strength between primary visual and occipitotemporal regions against voxel-wise activity patterns elsewhere in the brain. This allowed us to identify a set of frontal and parietal regions whose activity increased as a function of task-evoked functional connectivity. These results suggest that frontoparietal regions may provide top-down biasing signals to influence task-specific interactions between brain regions.
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Affiliation(s)
- Kai Hwang
- Helen Wills Neuroscience Institute and Department of Psychology, University of California Berkeley, Berkeley, CA, USA
| | - James M Shine
- Department of Psychology, Stanford University, Palo Alto, CA, USA
- Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Mark D’Esposito
- Helen Wills Neuroscience Institute and Department of Psychology, University of California Berkeley, Berkeley, CA, USA
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11
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Working memory capacity and the functional connectome - insights from resting-state fMRI and voxelwise centrality mapping. Brain Imaging Behav 2018; 12:238-246. [PMID: 28247158 DOI: 10.1007/s11682-017-9688-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The functional connectome represents a comprehensive network map of functional connectivity throughout the human brain. To date, the relationship between the organization of functional connectivity and cognitive performance measures is still poorly understood. In the present study we use resting-state functional magnetic resonance imaging (fMRI) data to explore the link between the functional connectome and working memory capacity in an individual differences design. Working memory capacity, which refers to the maximum amount of context information that an individual can retain in the absence of external stimulation, was assessed outside the MRI scanner and estimated based on behavioral data from a change detection task. Resting-state time series were analyzed by means of voxelwise degree and eigenvector centrality mapping, which are data-driven network analytic approaches for the characterization of functional connectivity. We found working memory capacity to be inversely correlated with both centrality in the right intraparietal sulcus. Exploratory analyses revealed that this relationship was putatively driven by an increase in negative connectivity strength of the structure. This resting-state connectivity finding fits previous task based activation studies that have shown that this area responds to manipulations of working memory load.
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12
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Prefrontal θ-Burst Stimulation Disrupts the Organizing Influence of Active Short-Term Retrieval on Episodic Memory. eNeuro 2018; 5:eN-NWR-0347-17. [PMID: 29445769 PMCID: PMC5810043 DOI: 10.1523/eneuro.0347-17.2018] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Revised: 01/22/2018] [Accepted: 01/26/2018] [Indexed: 11/26/2022] Open
Abstract
Dorsolateral prefrontal cortex (DLPFC) is thought to organize items in working memory and this organizational role may also influence long-term memory. To causally test this hypothesized role of DLPFC in long-term memory formation, we used θ-burst noninvasive stimulation (TBS) to modulate DLPFC involvement in a memory task that assessed the influence of active short-term retrieval on later memory. Human subjects viewed three objects on a grid and then either actively retrieved or passively restudied one object’s location after a brief delay. Long-term memory for the other objects was assessed after a delay to evaluate the beneficial role of active short-term retrieval on subsequent memory for the entire set of object locations. We found that DLPFC TBS had no significant effects on short-term memory. In contrast, DLPFC TBS impaired long-term memory selectively in the active-retrieval condition but not in the passive-restudy condition. These findings are consistent with the hypothesized contribution of DLPFC to the organizational processes operative during active short-term retrieval that influence long-term memory, although other regions that were not stimulated could provide similar contributions. Notably, active-retrieval and passive-restudy conditions were intermixed, and therefore nonspecific influences of stimulation were well controlled. These results suggest that DLPFC is causally involved in organizing event information during active retrieval to support coherent long-term memory formation.
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Adnan A, Chen AJ, Novakovic-Agopian T, D'Esposito M, Turner GR. Brain Changes Following Executive Control Training in Older Adults. Neurorehabil Neural Repair 2017; 31:910-922. [PMID: 28868974 PMCID: PMC5729113 DOI: 10.1177/1545968317728580] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND While older adults are able to attend to goal-relevant information, the capacity to ignore irrelevant or distracting information declines with advancing age. This decline in selective attention has been associated with poor modulation of brain activity in sensory cortices by anterior brain regions implicated in cognitive control. OBJECTIVE Here we investigated whether participation in an executive control training program would result in improved selective attention and associated functional brain changes in a sample of healthy older adults (N = 24, age 60-85 years). METHODS Participants were enrolled in a goal-oriented attentional self-regulation (GOALS) program (n = 11) or a brain health education workshop as an active control condition (n = 13). All participants performed a working memory task requiring attention to or suppression of visual stimuli based on goal-relevance during functional magnetic resonance imaging. RESULTS We observed a pattern of enhanced activity in right frontal, parietal and temporal brain regions from pre- to posttraining in the GOALS intervention group, which predicted the selectivity of subsequent memory for goal-relevant stimuli. CONCLUSIONS Executive control training in older adults alters functional activity in brain regions associated with attentional control, and selectively predicts behavioral outcome.
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Affiliation(s)
| | - Anthony J.W. Chen
- Veteran's Administration Northern California Health Care System
- University of California, Berkeley
| | - Tatjana Novakovic-Agopian
- Veteran's Administration Northern California Health Care System
- University of California, San Francisco
- California Pacific Medical Centre
| | - Mark D'Esposito
- Veteran's Administration Northern California Health Care System
- University of California, Berkeley
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Hallett M, Di Iorio R, Rossini PM, Park JE, Chen R, Celnik P, Strafella AP, Matsumoto H, Ugawa Y. Contribution of transcranial magnetic stimulation to assessment of brain connectivity and networks. Clin Neurophysiol 2017; 128:2125-2139. [PMID: 28938143 DOI: 10.1016/j.clinph.2017.08.007] [Citation(s) in RCA: 96] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Revised: 07/31/2017] [Accepted: 08/12/2017] [Indexed: 01/01/2023]
Abstract
The goal of this review is to show how transcranial magnetic stimulation (TMS) techniques can make a contribution to the study of brain networks. Brain networks are fundamental in understanding how the brain operates. Effects on remote areas can be directly observed or identified after a period of stimulation, and each section of this review will discuss one method. EEG analyzed following TMS is called TMS-evoked potentials (TEPs). A conditioning TMS can influence the effect of a test TMS given over the motor cortex. A disynaptic connection can be tested also by assessing the effect of a pre-conditioning stimulus on the conditioning-test pair. Basal ganglia-cortical relationships can be assessed using electrodes placed in the process of deep brain stimulation therapy. Cerebellar-cortical relationships can be determined using TMS over the cerebellum. Remote effects of TMS on the brain can be found as well using neuroimaging, including both positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). The methods complement each other since they give different views of brain networks, and it is often valuable to use more than one technique to achieve converging evidence. The final product of this type of work is to show how information is processed and transmitted in the brain.
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Affiliation(s)
- Mark Hallett
- National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA.
| | - Riccardo Di Iorio
- Department of Geriatrics, Institute of Neurology, Neuroscience and Orthopedics, Catholic University, Policlinic A. Gemelli Foundation, Rome, Italy
| | - Paolo Maria Rossini
- Department of Geriatrics, Institute of Neurology, Neuroscience and Orthopedics, Catholic University, Policlinic A. Gemelli Foundation, Rome, Italy; Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy
| | - Jung E Park
- National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA; Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Republic of Korea
| | - Robert Chen
- Krembil Research Institute, University of Toronto, Toronto, Canada; Department of Medicine (Neurology), University of Toronto, Toronto, Canada
| | - Pablo Celnik
- Department of Physical Medicine and Rehabilitation, Johns Hopkins School of Medicine, USA
| | - Antonio P Strafella
- Krembil Research Institute, University of Toronto, Toronto, Canada; Morton and Gloria Shulman Movement Disorder Unit & E.J. Safra Parkinson Disease Program, Toronto Western Hospital, UHN, Canada; Research Imaging Centre, Campbell Family Mental Health Research Institute, CAMH, University of Toronto, Ontario, Canada
| | | | - Yoshikazu Ugawa
- Department of Neurology, School of Medicine, Fukushima Medical University, Japan; Fukushima Global Medical Science Center, Advanced Clinical Research Center, Fukushima Medical University, Japan
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Kiyonaga A, Dowd EW, Egner T. Neural Representation of Working Memory Content Is Modulated by Visual Attentional Demand. J Cogn Neurosci 2017; 29:2011-2024. [PMID: 28777056 DOI: 10.1162/jocn_a_01174] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Recent theories assert that visual working memory (WM) relies on the same attentional resources and sensory substrates as visual attention to external stimuli. Behavioral studies have observed competitive tradeoffs between internal (i.e., WM) and external (i.e., visual) attentional demands, and neuroimaging studies have revealed representations of WM content as distributed patterns of activity within the same cortical regions engaged by perception of that content. Although a key function of WM is to protect memoranda from competing input, it remains unknown how neural representations of WM content are impacted by incoming sensory stimuli and concurrent attentional demands. Here, we investigated how neural evidence for WM information is affected when attention is occupied by visual search-at varying levels of difficulty-during the delay interval of a WM match-to-sample task. Behavioral and fMRI analyses suggested that WM maintenance was impacted by the difficulty of a concurrent visual task. Critically, multivariate classification analyses of category-specific ventral visual areas revealed a reduction in decodable WM-related information when attention was diverted to a visual search task, especially when the search was more difficult. This study suggests that the amount of available attention during WM maintenance influences the detection of sensory WM representations.
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