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Uemura M, Katagiri Y, Imai E, Kawahara Y, Otani Y, Ichinose T, Kondo K, Kowa H. Dorsal Anterior Cingulate Cortex Coordinates Contextual Mental Imagery for Single-Beat Manipulation during Rhythmic Sensorimotor Synchronization. Brain Sci 2024; 14:757. [PMID: 39199452 PMCID: PMC11352649 DOI: 10.3390/brainsci14080757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2024] [Revised: 07/17/2024] [Accepted: 07/23/2024] [Indexed: 09/01/2024] Open
Abstract
Flexible pulse-by-pulse regulation of sensorimotor synchronization is crucial for voluntarily showing rhythmic behaviors synchronously with external cueing; however, the underpinning neurophysiological mechanisms remain unclear. We hypothesized that the dorsal anterior cingulate cortex (dACC) plays a key role by coordinating both proactive and reactive motor outcomes based on contextual mental imagery. To test our hypothesis, a missing-oddball task in finger-tapping paradigms was conducted in 33 healthy young volunteers. The dynamic properties of the dACC were evaluated by event-related deep-brain activity (ER-DBA), supported by event-related potential (ERP) analysis and behavioral evaluation based on signal detection theory. We found that ER-DBA activation/deactivation reflected a strategic choice of motor control modality in accordance with mental imagery. Reverse ERP traces, as omission responses, confirmed that the imagery was contextual. We found that mental imagery was updated only by environmental changes via perceptual evidence and response-based abductive reasoning. Moreover, stable on-pulse tapping was achievable by maintaining proactive control while creating an imagery of syncopated rhythms from simple beat trains, whereas accuracy was degraded with frequent erroneous tapping for missing pulses. We conclude that the dACC voluntarily regulates rhythmic sensorimotor synchronization by utilizing contextual mental imagery based on experience and by creating novel rhythms.
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Affiliation(s)
- Maho Uemura
- Department of Rehabilitation Science, Kobe University Graduate School of Health Sciences, Kobe 654-0142, Japan; (Y.O.); (H.K.)
- School of Music, Mukogawa Women’s University, Nishinomiya 663-8558, Japan;
| | - Yoshitada Katagiri
- Department of Bioengineering, School of Engineering, The University of Tokyo, Tokyo 113-8655, Japan;
| | - Emiko Imai
- Department of Biophysics, Kobe University Graduate School of Health Sciences, Kobe 654-0142, Japan;
| | - Yasuhiro Kawahara
- Department of Human life and Health Sciences, Division of Arts and Sciences, The Open University of Japan, Chiba 261-8586, Japan;
| | - Yoshitaka Otani
- Department of Rehabilitation Science, Kobe University Graduate School of Health Sciences, Kobe 654-0142, Japan; (Y.O.); (H.K.)
- Faculty of Rehabilitation, Kobe International University, Kobe 658-0032, Japan
| | - Tomoko Ichinose
- School of Music, Mukogawa Women’s University, Nishinomiya 663-8558, Japan;
| | | | - Hisatomo Kowa
- Department of Rehabilitation Science, Kobe University Graduate School of Health Sciences, Kobe 654-0142, Japan; (Y.O.); (H.K.)
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2
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Hage G, Buisseret F, Brismée JM, Dierick F, Detrembleur C, Hage R. Evaluating the additive diagnostic value of DidRen LaserTest: Correlating temporal and kinematic predictors and patient-reported outcome measures in acute-subacute non-specific neck pain. J Bodyw Mov Ther 2024; 39:201-208. [PMID: 38876626 DOI: 10.1016/j.jbmt.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 02/28/2024] [Accepted: 03/03/2024] [Indexed: 06/16/2024]
Affiliation(s)
- Guillaume Hage
- Laboratoire de Neuro Musculo Squelettique (NMSK), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, 1200 Brussels, Belgium
| | - Fabien Buisseret
- Centre de Recherche et de Formation de la HELHa (CeREF), Chaussée de Binche 159, 7000 Mons, Belgium; Service de Physique Nucléaire et Subnucléaire, UMONS, Research Institute for Complex Systems, Place Du Parc 20, 7000 Mons, Belgium
| | - Jean-Michel Brismée
- Center for Rehabilitation Research, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Frédéric Dierick
- Centre de Recherche et de Formation de la HELHa (CeREF), Chaussée de Binche 159, 7000 Mons, Belgium; Laboratoire d'Analyse du Mouvement et de la Posture (LAMP), Centre National de Rééducation Fonctionnelle et de Réadaptation (Rehazenter), Rue André Vésale 1, 2674 Luxembourg, Luxembourg; Faculté des Sciences de La Motricité, UCLouvain, Place Pierre de Coubertin 1-2, 1348 Louvain-la-Neuve, Belgium
| | - Christine Detrembleur
- Laboratoire de Neuro Musculo Squelettique (NMSK), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, 1200 Brussels, Belgium
| | - Renaud Hage
- Centre de Recherche et de Formation de la HELHa (CeREF), Chaussée de Binche 159, 7000 Mons, Belgium; Faculté des Sciences de La Motricité, UCLouvain, Place Pierre de Coubertin 1-2, 1348 Louvain-la-Neuve, Belgium; Traitement Formation Thérapie Manuelle (TFTM), Private Physiotherapy/Manual Therapy Center, Avenue des Cerisiers 211A, 1200 Brussels, Belgium; Haute école Libre de Bruxelles Ilya Prigogine, Section Kinésithérapie, 808, Route de Lennik, Bâtiment P, 1070 Brussels, Belgium.
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3
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Ivanov V, Manenti GL, Plewe SS, Kagan I, Schwiedrzik CM. Decision-making processes in perceptual learning depend on effectors. Sci Rep 2024; 14:5644. [PMID: 38453977 PMCID: PMC10920771 DOI: 10.1038/s41598-024-55508-5] [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: 07/11/2023] [Accepted: 02/24/2024] [Indexed: 03/09/2024] Open
Abstract
Visual perceptual learning is traditionally thought to arise in visual cortex. However, typical perceptual learning tasks also involve systematic mapping of visual information onto motor actions. Because the motor system contains both effector-specific and effector-unspecific representations, the question arises whether visual perceptual learning is effector-specific itself, or not. Here, we study this question in an orientation discrimination task. Subjects learn to indicate their choices either with joystick movements or with manual reaches. After training, we challenge them to perform the same task with eye movements. We dissect the decision-making process using the drift diffusion model. We find that learning effects on the rate of evidence accumulation depend on effectors, albeit not fully. This suggests that during perceptual learning, visual information is mapped onto effector-specific integrators. Overlap of the populations of neurons encoding motor plans for these effectors may explain partial generalization. Taken together, visual perceptual learning is not limited to visual cortex, but also affects sensorimotor mapping at the interface of visual processing and decision making.
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Affiliation(s)
- Vladyslav Ivanov
- Neural Circuits and Cognition Lab, European Neuroscience Institute Göttingen - A Joint Initiative of the University Medical Center Göttingen and the Max Planck Society, Grisebachstraße 5, 37077, Göttingen, Germany
- Sensorimotor Group, German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077, Göttingen, Germany
| | - Giorgio L Manenti
- Neural Circuits and Cognition Lab, European Neuroscience Institute Göttingen - A Joint Initiative of the University Medical Center Göttingen and the Max Planck Society, Grisebachstraße 5, 37077, Göttingen, Germany
- Perception and Plasticity Group, German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077, Göttingen, Germany
- Leibniz ScienceCampus Primate Cognition, Göttingen, Germany
- Systems Neuroscience Program, Graduate School for Neurosciences, Biophysics and Molecular Biosciences (GGNB), 37077, Göttingen, Germany
| | - Sandrin S Plewe
- Neural Circuits and Cognition Lab, European Neuroscience Institute Göttingen - A Joint Initiative of the University Medical Center Göttingen and the Max Planck Society, Grisebachstraße 5, 37077, Göttingen, Germany
- Perception and Plasticity Group, German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077, Göttingen, Germany
- Leibniz ScienceCampus Primate Cognition, Göttingen, Germany
| | - Igor Kagan
- Leibniz ScienceCampus Primate Cognition, Göttingen, Germany
- Decision and Awareness Group, German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077, Göttingen, Germany
| | - Caspar M Schwiedrzik
- Neural Circuits and Cognition Lab, European Neuroscience Institute Göttingen - A Joint Initiative of the University Medical Center Göttingen and the Max Planck Society, Grisebachstraße 5, 37077, Göttingen, Germany.
- Perception and Plasticity Group, German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077, Göttingen, Germany.
- Leibniz ScienceCampus Primate Cognition, Göttingen, Germany.
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4
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Reinhartz A, Strobach T, Jacobsen T, von Bastian CC. Mechanisms of Training-Related Change in Processing Speed: A Drift-Diffusion Model Approach. J Cogn 2023; 6:46. [PMID: 37600217 PMCID: PMC10437139 DOI: 10.5334/joc.310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 07/17/2023] [Indexed: 08/22/2023] Open
Abstract
Processing speed is a crucial ability that changes over the course of the lifespan. Training interventions on processing speed have shown promising effects and have been associated with improved cognitive functioning. While training-related changes in processing speed are often studied using reaction times (RTs) and error rates, these measures provide limited insight into the mechanisms underlying changes during training. The drift-diffusion model provides estimates of the cognitive processes underlying speeded decision tasks, such as the rate of evidence accumulation (drift rate), response strategies (boundary separation), as well as time for other processes such as stimulus encoding and motor response (non-decision time). In the current study, we analyzed existing data of an extensive multi-session training intervention (von Bastian & Oberauer, 2013) to disentangle changes in drift rate, boundary separation, and non-decision time during training of different speeded choice-RT tasks. During this training intervention, 30 participants performed 20 training sessions over the course of four weeks, completing three tasks each session: a face-matching, a pattern-matching, and a digit-matching task. Our results show that processing speed training increased drift rates throughout training. Boundary separation and non-decision time decreased mostly during the initial parts of training. This pattern of prolonged training-related changes in rate of evidence accumulation as well as early changes in response strategy and non-decision processes was observed across all three tasks. Future research should investigate how these training-related changes relate to improvements in cognitive functioning more broadly.
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Affiliation(s)
- Alice Reinhartz
- Department of Psychology, Medical School Hamburg, Hamburg, Germany
- Experimental Psychology Unit, Helmut Schmidt University/University of the Federal Armed Forces Hamburg, Hamburg, Germany
| | - Tilo Strobach
- Department of Psychology, Medical School Hamburg, Hamburg, Germany
| | - Thomas Jacobsen
- Experimental Psychology Unit, Helmut Schmidt University/University of the Federal Armed Forces Hamburg, Hamburg, Germany
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5
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Cochrane A, Sims CR, Bejjanki VR, Green CS, Bavelier D. Multiple timescales of learning indicated by changes in evidence-accumulation processes during perceptual decision-making. NPJ SCIENCE OF LEARNING 2023; 8:19. [PMID: 37291102 DOI: 10.1038/s41539-023-00168-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 05/15/2023] [Indexed: 06/10/2023]
Abstract
Evidence accumulation models have enabled strong advances in our understanding of decision-making, yet their application to examining learning has not been common. Using data from participants completing a dynamic random dot-motion direction discrimination task across four days, we characterized alterations in two components of perceptual decision-making (Drift Diffusion Model drift rate and response boundary). Continuous-time learning models were applied to characterize trajectories of performance change, with different models allowing for varying dynamics. The best-fitting model included drift rate changing as a continuous, exponential function of cumulative trial number. In contrast, response boundary changed within each daily session, but in an independent manner across daily sessions. Our results highlight two different processes underlying the pattern of behavior observed across the entire learning trajectory, one involving a continuous tuning of perceptual sensitivity, and another more variable process describing participants' threshold of when enough evidence is present to act.
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Affiliation(s)
- Aaron Cochrane
- University of Geneva, Geneva, Switzerland.
- Campus Biotech, Geneva, Switzerland.
- Brown University, Providence, RI, USA.
| | | | | | | | - Daphne Bavelier
- University of Geneva, Geneva, Switzerland
- Campus Biotech, Geneva, Switzerland
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6
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Masís J, Chapman T, Rhee JY, Cox DD, Saxe AM. Strategically managing learning during perceptual decision making. eLife 2023; 12:64978. [PMID: 36786427 PMCID: PMC9928425 DOI: 10.7554/elife.64978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 01/15/2023] [Indexed: 02/15/2023] Open
Abstract
Making optimal decisions in the face of noise requires balancing short-term speed and accuracy. But a theory of optimality should account for the fact that short-term speed can influence long-term accuracy through learning. Here, we demonstrate that long-term learning is an important dynamical dimension of the speed-accuracy trade-off. We study learning trajectories in rats and formally characterize these dynamics in a theory expressed as both a recurrent neural network and an analytical extension of the drift-diffusion model that learns over time. The model reveals that choosing suboptimal response times to learn faster sacrifices immediate reward, but can lead to greater total reward. We empirically verify predictions of the theory, including a relationship between stimulus exposure and learning speed, and a modulation of reaction time by future learning prospects. We find that rats' strategies approximately maximize total reward over the full learning epoch, suggesting cognitive control over the learning process.
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Affiliation(s)
- Javier Masís
- Department of Molecular and Cellular Biology, Harvard UniversityCambridgeUnited States,Center for Brain Science, Harvard UniversityCambridgeUnited States
| | - Travis Chapman
- Center for Brain Science, Harvard UniversityCambridgeUnited States
| | - Juliana Y Rhee
- Department of Molecular and Cellular Biology, Harvard UniversityCambridgeUnited States,Center for Brain Science, Harvard UniversityCambridgeUnited States
| | - David D Cox
- Department of Molecular and Cellular Biology, Harvard UniversityCambridgeUnited States,Center for Brain Science, Harvard UniversityCambridgeUnited States
| | - Andrew M Saxe
- Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
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7
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Rizvi MS. Effect of detachment of motor protein from track on its transport. J Biol Phys 2022; 48:369-381. [PMID: 36190620 PMCID: PMC9727045 DOI: 10.1007/s10867-022-09613-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 09/05/2022] [Indexed: 01/14/2023] Open
Abstract
The transportation of the cargoes in biological cells is primarily driven by the motor proteins on filamentous protein tracks. The stochastic nature of the motion of motor protein often leads to its spontaneous detachment from the track. We formulate a mathematical model to study the effect of the detachment of motor protein on its track bound transport. We calculate two quantities: the distance traveled by the motor protein in given time, and the average time taken by a single motor protein to reach a target distance. Expectedly, both of these quantities decrease with the increasing detachment rate if the motor velocity is kept fixed. However, the existing experimental data suggest that a change in the detachment rate also affects the velocity of the motor protein. This relation between motor protein speed and its detachment rate results in a non-monotonic dependence on the distance traveled in fixed time and transport rate to a fixed distance. Therefore, we demonstrate that optimal motor speeds can be identified for the time and distance controlled conditions.
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Affiliation(s)
- Mohd Suhail Rizvi
- Department of Biomedical Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, 502284, Telangana, India.
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8
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Imperfect integration: Congruency between multiple sensory sources modulates decision-making processes. Atten Percept Psychophys 2022; 84:1566-1582. [PMID: 35460027 PMCID: PMC9232470 DOI: 10.3758/s13414-021-02434-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/23/2021] [Indexed: 11/18/2022]
Abstract
Decision-making on the basis of multiple information sources is common. However, to what extent such decisions differ from those with a single source remains unclear. We combined cognitive modelling and neural-mass modelling to characterise the neurocognitive process underlying perceptual decision-making with single or double information sources. Ninety-four human participants performed binary decisions to discriminate the coherent motion direction averaged across two independent apertures. Regardless of the angular distance of the apertures, separating motion information into two apertures resulted in a reduction in accuracy. Our cognitive and neural-mass modelling results are consistent with the hypotheses that the addition of the second information source led to a lower signal-to-noise ratio of evidence accumulation with two congruent information sources, and a change in the decision strategy of speed–accuracy trade-off with two incongruent sources. Thus, our findings support a robust behavioural change in relation to multiple information sources, which have congruency-dependent impacts on selective decision-making subcomponents.
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9
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Jia K, Frangou P, Karlaftis VM, Ziminski JJ, Giorgio J, Rideaux R, Zamboni E, Hodgson V, Emir U, Kourtzi Z. Neurochemical and functional interactions for improved perceptual decisions through training. J Neurophysiol 2022; 127:900-912. [PMID: 35235415 PMCID: PMC8977131 DOI: 10.1152/jn.00308.2021] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 02/11/2022] [Accepted: 02/28/2022] [Indexed: 11/22/2022] Open
Abstract
Learning and experience are known to improve our ability to make perceptual decisions. Yet, our understanding of the brain mechanisms that support improved perceptual decisions through training remains limited. Here, we test the neurochemical and functional interactions that support learning for perceptual decisions in the context of an orientation identification task. Using magnetic resonance spectroscopy (MRS), we measure neurotransmitters (i.e., glutamate, GABA) that are known to be involved in visual processing and learning in sensory [early visual cortex (EV)] and decision-related [dorsolateral prefrontal cortex (DLPFC)] brain regions. Using resting-state functional magnetic resonance imaging (rs-fMRI), we test for functional interactions between these regions that relate to decision processes. We demonstrate that training improves perceptual judgments (i.e., orientation identification), as indicated by faster rates of evidence accumulation after training. These learning-dependent changes in decision processes relate to lower EV glutamate levels and EV-DLPFC connectivity, suggesting that glutamatergic excitation and functional interactions between visual and dorsolateral prefrontal cortex facilitate perceptual decisions. Further, anodal transcranial direct current stimulation (tDCS) in EV impairs learning, suggesting a direct link between visual cortex excitation and perceptual decisions. Our findings advance our understanding of the role of learning in perceptual decision making, suggesting that glutamatergic excitation for efficient sensory processing and functional interactions between sensory and decision-related regions support improved perceptual decisions.NEW & NOTEWORTHY Combining multimodal brain imaging [magnetic resonance spectroscopy (MRS), functional connectivity] with interventions [transcranial direct current stimulation (tDCS)], we demonstrate that glutamatergic excitation and functional interactions between sensory (visual) and decision-related (dorsolateral prefrontal cortex) areas support our ability to optimize perceptual decisions through training.
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Affiliation(s)
- Ke Jia
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Polytimi Frangou
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Vasilis M Karlaftis
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Joseph J Ziminski
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Joseph Giorgio
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Reuben Rideaux
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Elisa Zamboni
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Victoria Hodgson
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Uzay Emir
- Purdue University School of Health Sciences, West Lafayette, Indiana
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
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10
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Event-related potentials reveal early visual-tactile integration in the deaf. PSIHOLOGIJA 2022. [DOI: 10.2298/psi210407003l] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
This study examined visual-tactile perceptual integration in deaf and normal hearing individuals. Participants were presented with photos of faces or pictures of an oval in either a visual mode or a visual-tactile mode in a recognition learning task. Event-related potentials (ERPs) were recorded when participants recognized real faces and pictures of ovals in learning stage. Results from the parietal-occipital region showed that photos of faces accompanied with vibration elicited more positive-going ERP responses than photos of faces without vibration as indicated in the components of P1 and N170 in both deaf and hearing individuals. However, pictures of ovals accompanied with vibration produced more positive-going ERP responses than pictures of ovals without vibration in N170, which was only found in deaf individuals. A reversed pattern was shown in the temporal region indicating that real faces with vibration elicited less positive ERPs than photos of faces without vibration in both N170 and N300 for deaf, but such pattern did not appear in N170 and N300 for normal hearing. The results suggest that multisensory integration across the visual and tactile modality involves more fundamental perceptual regions than auditory regions. Moreover, auditory deprivation played an essential role at the perceptual encoding stage of the multisensory integration.
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11
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Vu AT, Feinberg DA. The Role of Cerebral Metabolism in Improving Time Pressured Decisions. Front Psychol 2021; 12:690198. [PMID: 34354635 PMCID: PMC8329240 DOI: 10.3389/fpsyg.2021.690198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 06/14/2021] [Indexed: 11/13/2022] Open
Abstract
Speed-accuracy tradeoff (SAT) theory dictates that decisions can be made more quickly by sacrificing accuracy. Here we investigate whether the human brain can operate in a brief metabolic overdrive to overcome SAT and successfully make decisions requiring both high levels of speed and accuracy. In the context of BOLD fMRI we expect “a brief metabolic overdrive” to involve an increase in cerebral oxygen metabolism prior to increased cerebral blood flow–a phenomenon known as the “initial dip” which results from a sudden drop in oxyhemoglobin in perfusing blood. Human subjects performed a motion discrimination task consisting of different difficulties while emphasizing either accuracy (i.e., without time pressure) or both speed and accuracy (i.e., with time pressure). Using simultaneous multi-slice fMRI, for very fast (333 ms) measurement of whole brain BOLD activity, revealed two modes of physiological overdrive responses when subjects emphasized both speed and accuracy. The majority of subjects exhibited the hypothesized enhancement of initial dip amplitude in posterior visual cortex (PVC) with the size of the enhancement significantly correlated with improvement in behavioral performance. For these subjects, the traditionally analyzed post-stimulus overshoot was not affected by task emphasis. These results demonstrate the complexity and variability of the BOLD hemodynamic response. The discovered relationships between BOLD response and behavior were only observed when subjects emphasized both speed and accuracy in more difficult trials suggesting that the brain can perform in a state of metabolic overdrive with enhanced neural processing of sensory information specifically in challenging situations.
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Affiliation(s)
- An Thanh Vu
- San Francisco VA Health Care System, San Francisco, CA, United States.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - David A Feinberg
- Advanced Magnetic Resonance Imaging (MRI) Technologies, Sebastopol, CA, United States.,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
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12
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Huberdeau DM, Turk-Browne NB. Visuomotor associations facilitate movement preparation. J Exp Psychol Hum Percept Perform 2021; 47:372-386. [PMID: 33475417 DOI: 10.1037/xhp0000895] [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: 11/08/2022]
Abstract
Many motor skills require rapidly choosing a movement goal and preparing a movement to that goal, such as in sports where circumstances often change quickly and many actions are possible. Humans can benefit from learning the perceptual cues that predict the requirements of movement so that the choice of a movement goal and movement preparation can occur earlier. However, there remains uncertainty about how these perceptual cues are learned. Here we investigate the use and learning of these perceptual-motor associations. First, we ask if episodic memory for associations can support learning. In Experiment 1, participants first memorized associations between symbols and movement goals. When these symbols were subsequently presented as cues, reaching movements were prepared as efficiently as if the goals themselves were previewed, without the need for additional practice. Next, we ask whether statistical learning can be used to learn the associations. In Experiment 2, participants had to learn the associations during the movement task itself. This learning enabled efficient movement preparation, and the rate of improvement scaled with the number and complexity of associations. These findings suggest that movement preparation can be facilitated by perceptual cues via statistical learning and memory recall, highlighting a potential role for learning and memory systems not conventionally implicated in motor behavior. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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13
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Nardone N, Shahid M, Strasser AA, Dempsey DA, Benowitz NL. The influence of nicotine metabolic rate on working memory over 6 hours of abstinence from nicotine. Pharmacol Biochem Behav 2020; 188:172836. [PMID: 31812759 PMCID: PMC7009742 DOI: 10.1016/j.pbb.2019.172836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 10/11/2019] [Accepted: 12/04/2019] [Indexed: 11/18/2022]
Abstract
BACKGROUND A faster rate of nicotine metabolism has been associated with smoking more cigarettes, greater nicotine withdrawal symptoms, and lower smoking quit rates. However, the association between nicotine metabolic rate (NMR) and cognitive functioning during withdrawal has not been determined. METHODS We compared cognitive function in 121 fast or slow nicotine metabolizers after smoking, and at 3 and 6 h of nicotine abstinence. Cognitive functioning was assessed using N-back working memory tests with outcomes of accuracy and processing speed. Participants smoked two cigarettes and then abstained from smoking for 6 h. N-back tests were administered after smoking (0 h) and at 3 and 6 h of nicotine abstinence. RESULTS An effect of processing speed was found over time on the 2-back, in that participants had significantly longer average reaction times when the stimuli presented did not match the target letter. NMR was not significantly associated with the processing speed change over time. Within-race differences in working memory were evident in that Caucasian fast metabolizers had significantly poorer accuracy and processing speed. CONCLUSIONS Minimal change in working memory over 6 h of nicotine abstinence was observed. Overall, NMR was not significantly associated with the change in processing speed, however Caucasian fast metabolizers displayed poorer accuracy and processing speed at discrete time points.
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Affiliation(s)
- Natalie Nardone
- Clinical Pharmacology Research Program, Division of Cardiology, Department of Medicine, University of California, San Francisco, 3130 20(th) Street Suite 308, San Francisco, CA 94110, USA.
| | - Marian Shahid
- Department of Neurology, Stanford University, 300 Pasteur Dr. Room H3144, MC 5235, Stanford, CA 94305, USA.
| | - Andrew A Strasser
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 3535 Market Street Suite 4100, Philadelphia, PA 19104, USA.
| | - Delia A Dempsey
- Clinical Pharmacology Research Program, Division of Cardiology, Department of Medicine, University of California, San Francisco, 3130 20(th) Street Suite 308, San Francisco, CA 94110, USA; Department of Pediatrics, University of California, San Francisco, 550 16(th) Street, Box 0110, San Francisco, CA 94143, USA.
| | - Neal L Benowitz
- Center for Tobacco Control Research and Education, University of California, San Francisco, 530 Parnassus Avenue, San Francisco, CA 94143, USA; Division of Clinical Pharmacology and Experiment Therapeutics, Departments of Medicine and Biopharmaceutical Sciences, University of California, San Francisco, 1001 Potrero Avenue, San Francisco, CA 94110, USA.
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14
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Miletić S, Boag RJ, Forstmann BU. Mutual benefits: Combining reinforcement learning with sequential sampling models. Neuropsychologia 2019; 136:107261. [PMID: 31733237 DOI: 10.1016/j.neuropsychologia.2019.107261] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 10/21/2019] [Accepted: 11/10/2019] [Indexed: 12/21/2022]
Abstract
Reinforcement learning models of error-driven learning and sequential-sampling models of decision making have provided significant insight into the neural basis of a variety of cognitive processes. Until recently, model-based cognitive neuroscience research using both frameworks has evolved separately and independently. Recent efforts have illustrated the complementary nature of both modelling traditions and showed how they can be integrated into a unified theoretical framework, explaining trial-by-trial dependencies in choice behavior as well as response time distributions. Here, we review a theoretical background of integrating the two classes of models, and review recent empirical efforts towards this goal. We furthermore argue that the integration of both modelling traditions provides mutual benefits for both fields, and highlight promises of this approach for cognitive modelling and model-based cognitive neuroscience.
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Affiliation(s)
- Steven Miletić
- University of Amsterdam, Department of Psychology, Amsterdam, the Netherlands.
| | - Russell J Boag
- University of Amsterdam, Department of Psychology, Amsterdam, the Netherlands
| | - Birte U Forstmann
- University of Amsterdam, Department of Psychology, Amsterdam, the Netherlands
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15
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Combining error-driven models of associative learning with evidence accumulation models of decision-making. Psychon Bull Rev 2019; 26:868-893. [PMID: 30719625 DOI: 10.3758/s13423-019-01570-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
As people learn a new skill, performance changes along two fundamental dimensions: Responses become progressively faster and more accurate. In cognitive psychology, these facets of improvement have typically been addressed by separate classes of theories. Reductions in response time (RT) have usually been addressed by theories of skill acquisition, whereas increases in accuracy have been explained by associative learning theories. To date, relatively little work has examined how changes in RT relate to changes in response accuracy, and whether these changes can be accounted for quantitatively within a single theoretical framework. The current work examines joint changes in accuracy and RT in a probabilistic category learning task. We report a model-based analysis of changes in the shapes of RT distributions for different category responses at the level of individual stimuli over the course of learning. We show that changes in performance are determined solely by changes in the quality of information entering the decision process. We then develop a new model that combines an associative learning front end with a sequential sampling model of the decision process, showing that the model provides a good account of all aspects of the learning data. We conclude by discussing potential extensions of the model and future directions for theoretical development that are opened up by our findings.
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16
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Amin MN, Rushdi MA, Marzaban RN, Yosry A, Kim K, Mahmoud AM. Wavelet-based Computationally-Efficient Computer-Aided Characterization of Liver Steatosis using Conventional B-mode Ultrasound Images. Biomed Signal Process Control 2019; 52:84-96. [PMID: 31983924 PMCID: PMC6980471 DOI: 10.1016/j.bspc.2019.03.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Hepatic steatosis occurs when lipids accumulate in the liver leading to steatohepatitis, which can evolve into cirrhosis and consequently may end with hepatocellular carcinoma. Several automatic classification algorithms have been proposed to detect liver diseases. However, some algorithms are manufacturer-dependent, while others require extensive calculations and consequently prolonged computational time. This may limit the development of real-time and manufacturer-independent computer-aided detection of liver steatosis. This work demonstrates the feasibility of a computationally-efficient and manufacturer-independent wavelet-based computer-aided liver steatosis detection system using conventional B-mode ultrasound (US) imaging. Seven features were extracted from the approximation part of the second-level wavelet packet transform (WPT) of US images. The proposed technique was tested on two datasets of ex-vivo mice livers with and without gelatin embedding, in addition to a third dataset of in-vivo human livers acquired using two different US machines. Using the gelatin-embedded mice liver dataset, the technique exhibited 98.8% accuracy, 97.8% sensitivity, and 100% specificity, and the frame classification time was reduced from 0.4814 s using original US images to 0.1444 s after WPT preprocessing. When the other mice liver dataset was used, the technique showed 85.74% accuracy, 84.4% sensitivity, and 88.5% specificity, and the frame classification time was reduced from 0.5612s to 0.2903 s. Using human liver image data, the best classifier exhibited 92.5% accuracy, 93.0% sensitivity, 91.0% specificity, and the classification time was reduced from 0.660 s to 0.146 s. This technique can be useful for developing computationally-efficient and manufacturer-independent noninvasive CAD systems for fatty liver detection.
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Affiliation(s)
- Manar N Amin
- Department of Biomedical Engineering and Systems, Cairo University, Giza 12613, Egypt
| | - Muhammad A Rushdi
- Department of Biomedical Engineering and Systems, Cairo University, Giza 12613, Egypt
| | - Raghda N Marzaban
- Endemic Medicine Department and Liver Unit, Faculty of Medicine, Cairo University, Giza 11652, Egypt
| | - Ayman Yosry
- Endemic Medicine Department and Liver Unit, Faculty of Medicine, Cairo University, Giza 11652, Egypt
| | - Kang Kim
- Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA
- McGowan Institute for Regenerative Medicine, University of Pittsburgh and UPMC, Pittsburgh, Pennsylvania 15219, USA
| | - Ahmed M Mahmoud
- Department of Biomedical Engineering and Systems, Cairo University, Giza 12613, Egypt
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17
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Hage R, Dierick F, Roussel N, Pitance L, Detrembleur C. Age-related kinematic performance should be considered during fast head-neck rotation target task in individuals aged from 8 to 85 years old. PeerJ 2019; 7:e7095. [PMID: 31218133 PMCID: PMC6563793 DOI: 10.7717/peerj.7095] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Accepted: 05/08/2019] [Indexed: 02/04/2023] Open
Abstract
Kinematic behavior during fast cervical rotations is a useful parameter for assessing sensorimotor control performances in neck-pain patients. However, the influence of age in asymptomatic individuals from children to older people still needs to be explored. Our aim was to assess the impact of age on sensorimotor control performance of the head-neck with execution time and kinematic variables (time of task, mean speed/acceleration/deceleration, overshoots (OSs), minimum/maximum speed) during standardized fast rotation target task using the DidRen Laser test. A total of 80 volunteers were stratified in four different age-groups: Children (8–14 years): n = 16; Young Adults (18–35 years): n = 29; Old Adults (36–64 years): n = 18; Seniors (65–85 years): n = 17. Results showed that to perform the test, Children were slower (69.0 (60.6–87.3)s) compared to Young Adults (49.6 (45.6–55.6)s) with p < 0.001, and Old Adults (51.7 (48.4–55.8)s) with p < 0.001. It was also slower in Seniors (57 (52.3–67.6)s) compared to Young Adults with p < 0.013. Mean speed was slower in Children (9.4 ± 2.3 °s−1) and Seniors (10.6 ± 2.4 °s−1) compared to Young Adults (13.7 ± 1.9 °s−1) with p < 0.001 and Old Adults (13.3 ± 2.4 °s−1) with p < 0.001. Mean acceleration was slower for Children (8.4(7.6–10.2) °s−2) compared to Young Adults (11.1 (8.8–15.3) °s−2) with p < 0.016, and Old Adults (12.0(8.4–15.3) °s−2) with p < 0.015. Mean deceleration was slower for Children (−1.9(−2.6–1.4) °s−2) compared to Young Adults (−2.9(−3.7–2.5) °s−2) with p < 0.001 and Old Adults (−3.2(−3.7–2.3) °s−2) with p < 0.003. The DidRen Laser test allows us to discriminate age-specific performances for mean speed, acceleration and deceleration. Seniors and Children needed to be slower to become as precise as Young Adults and Old Adults. No difference was observed for OSs which assesses accuracy of movement. Age should therefore be considered as a key parameter when analyzing execution time and kinematic results during DidRen Laser test. These normative data can therefore guide clinicians in the assessment of subjects with neck pain.
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Affiliation(s)
- Renaud Hage
- Institut de Recherche Expérimentale et Clinique, Laboratoire NMSK, Université Catholique de Louvain, Brussels, Belgium
| | - Frédéric Dierick
- Forme et Fonctionnement Humain Lab, Department of Physical Therapy, CERISIC, CeREF, Haute Ecole Louvain en Hainaut, Charleroi, Hainaut, Belgium
| | - Nathalie Roussel
- Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Laurent Pitance
- Clinique Universitaire Saint-Luc, Stomatologie et Chirurgie Maxillo-Faciale, Université Catholique de Louvain, Brussels, Belgium
| | - Christine Detrembleur
- Institut de Recherche Expérimentale et Clinique, Laboratoire NMSK, Université Catholique de Louvain, Brussels, Belgium
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18
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Boag RJ, Strickland L, Loft S, Heathcote A. Strategic attention and decision control support prospective memory in a complex dual-task environment. Cognition 2019; 191:103974. [PMID: 31234118 DOI: 10.1016/j.cognition.2019.05.011] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Revised: 04/03/2019] [Accepted: 05/15/2019] [Indexed: 10/26/2022]
Abstract
Human performance in complex multiple-task environments depends critically on the interplay between cognitive control and cognitive capacity. In this paper we propose a tractable computational model of how cognitive control and capacity influence the speed and accuracy of decisions made in the event-based prospective memory (PM) paradigm, and in doing so test a new quantitative formulation that measures two distinct components of cognitive capacity (gain and focus) that apply generally to choices among two or more options. Consistent with prior work, individuals used proactive control (increased ongoing task thresholds under PM load) and reactive control (inhibited ongoing task accumulation rates to PM items) to support PM performance. Individuals used cognitive gain to increase the amount of resources allocated to the ongoing task under time pressure and PM load. However, when demands exceeded the capacity limit, resources were reallocated (shared) between ongoing task and PM processes. Extending previous work, individuals used cognitive focus to control the quality of processing for the ongoing and PM tasks based on the particular demand and payoff structure of the environment (e.g., higher focus for higher priority tasks; lower focus under high time pressure and with PM load). Our model provides the first detailed quantitative understanding of cognitive gain and focus as they apply to evidence accumulation models, which - along with cognitive control mechanisms - support decision-making in complex multiple-task environments.
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Affiliation(s)
| | | | - Shayne Loft
- The University of Western Australia, Australia
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19
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Jia K, Xue X, Lee JH, Fang F, Zhang J, Li S. Visual perceptual learning modulates decision network in the human brain: The evidence from psychophysics, modeling, and functional magnetic resonance imaging. J Vis 2019; 18:9. [PMID: 30452587 DOI: 10.1167/18.12.9] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Perceptual learning refers to improved perceptual performance after intensive training and was initially suggested to reflect long-term plasticity in early visual cortex. Recent behavioral and neurophysiological evidence further suggested that the plasticity in brain regions related to decision making could also contribute to the observed training effects. However, how perceptual learning modulates the responses of decision-related regions in the human brain remains largely unknown. In the present study, we combined psychophysics and functional magnetic resonance imaging (fMRI), and adopted a model-based approach to investigate this issue. We trained participants on a motion direction discrimination task and fitted their behavioral data using the linear ballistic accumulator model. The results from model fitting showed that behavioral improvement could be well explained by a specific improvement in sensory information accumulation. A critical model parameter, the drift rate of the information accumulation, was correlated with the fMRI responses derived from three spatial independent components: ventral premotor cortex (PMv), supplementary eye field (SEF), and the fronto-parietal network, including intraparietal sulcus (IPS) and frontal eye field (FEF). In this decision network, we found that the behavioral training effects were accompanied by signal enhancement specific to trained direction in PMv and FEF. Further, we also found direction-specific signal reduction in sensory areas (V3A and MT+), as well as the strengthened effective connectivity from V3A to PMv and from IPS to FEF. These findings provide evidence for the learning-induced decision refinement after perceptual learning and the brain regions that are involved in this process.
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Affiliation(s)
- Ke Jia
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China.,PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.,Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China
| | - Xin Xue
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China.,PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.,Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China.,Department of Health Industry Management, Beijing International Studies University, Beijing, China
| | - Jong-Hwan Lee
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
| | - Fang Fang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China.,PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.,Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | | | - Sheng Li
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China.,PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.,Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China
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20
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van der Groen O, Tang MF, Wenderoth N, Mattingley JB. Stochastic resonance enhances the rate of evidence accumulation during combined brain stimulation and perceptual decision-making. PLoS Comput Biol 2018; 14:e1006301. [PMID: 30020922 PMCID: PMC6066257 DOI: 10.1371/journal.pcbi.1006301] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Revised: 07/30/2018] [Accepted: 06/14/2018] [Indexed: 12/11/2022] Open
Abstract
Perceptual decision-making relies on the gradual accumulation of noisy sensory evidence. It is often assumed that such decisions are degraded by adding noise to a stimulus, or to the neural systems involved in the decision making process itself. But it has been suggested that adding an optimal amount of noise can, under appropriate conditions, enhance the quality of subthreshold signals in nonlinear systems, a phenomenon known as stochastic resonance. Here we asked whether perceptual decisions made by human observers obey these stochastic resonance principles, by adding noise directly to the visual cortex using transcranial random noise stimulation (tRNS) while participants judged the direction of coherent motion in random-dot kinematograms presented at the fovea. We found that adding tRNS bilaterally to visual cortex enhanced decision-making when stimuli were just below perceptual threshold, but not when they were well below or above threshold. We modelled the data under a drift diffusion framework, and showed that bilateral tRNS selectively increased the drift rate parameter, which indexes the rate of evidence accumulation. Our study is the first to provide causal evidence that perceptual decision-making is susceptible to a stochastic resonance effect induced by tRNS, and to show that this effect arises from selective enhancement of the rate of evidence accumulation for sub-threshold sensory events.
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Affiliation(s)
- Onno van der Groen
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- * E-mail:
| | - Matthew F. Tang
- Queensland Brain Institute, The University of Queensland, St Lucia, Queensland, Australia
| | - Nicole Wenderoth
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Jason B. Mattingley
- Queensland Brain Institute, The University of Queensland, St Lucia, Queensland, Australia
- School of Psychology, The University of Queensland, St Lucia, Queensland, Australia
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21
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Peleg-Adler R, Lanir J, Korman M. The effects of aging on the use of handheld augmented reality in a route planning task. COMPUTERS IN HUMAN BEHAVIOR 2018. [DOI: 10.1016/j.chb.2017.12.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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22
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Cohen Hoffing R, Karvelis P, Rupprechter S, Seriès P, Seitz AR. The Influence of Feedback on Task-Switching Performance: A Drift Diffusion Modeling Account. Front Integr Neurosci 2018; 12:1. [PMID: 29456494 PMCID: PMC5801306 DOI: 10.3389/fnint.2018.00001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Accepted: 01/11/2018] [Indexed: 11/28/2022] Open
Abstract
Task-switching is an important cognitive skill that facilitates our ability to choose appropriate behavior in a varied and changing environment. Task-switching training studies have sought to improve this ability by practicing switching between multiple tasks. However, an efficacious training paradigm has been difficult to develop in part due to findings that small differences in task parameters influence switching behavior in a non-trivial manner. Here, for the first time we employ the Drift Diffusion Model (DDM) to understand the influence of feedback on task-switching and investigate how drift diffusion parameters change over the course of task switch training. We trained 316 participants on a simple task where they alternated sorting stimuli by color or by shape. Feedback differed in six different ways between subjects groups, ranging from No Feedback (NFB) to a variety of manipulations addressing trial-wise vs. Block Feedback (BFB), rewards vs. punishments, payment bonuses and different payouts depending upon the trial type (switch/non-switch). While overall performance was found to be affected by feedback, no effect of feedback was found on task-switching learning. Drift Diffusion Modeling revealed that the reductions in reaction time (RT) switch cost over the course of training were driven by a continually decreasing decision boundary. Furthermore, feedback effects on RT switch cost were also driven by differences in decision boundary, but not in drift rate. These results reveal that participants systematically modified their task-switching performance without yielding an overall gain in performance.
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Affiliation(s)
- Russell Cohen Hoffing
- UCR Brain Game Center, Department of Cognitive Psychology, University of California, Riverside, Riverside, CA, United States
| | - Povilas Karvelis
- School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Samuel Rupprechter
- School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Peggy Seriès
- School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Aaron R Seitz
- UCR Brain Game Center, Department of Cognitive Psychology, University of California, Riverside, Riverside, CA, United States
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23
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Engle-Friedman M, Mathew GM, Martinova A, Armstrong F, Konstantinov V. The role of sleep deprivation and fatigue in the perception of task difficulty and use of heuristics. ACTA ACUST UNITED AC 2018; 11:74-84. [PMID: 30083294 PMCID: PMC6056069 DOI: 10.5935/1984-0063.20180016] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
This study investigated the effects of sleep deprivation on perception of task
difficulty and use of heuristics (mental shortcuts) compared to
naturally-experienced sleep at home. Methods: Undergraduate
students were screened and assigned through block-random assignment to
Naturally-Experienced Sleep (NES; n=19) or Total Sleep
Deprivation (TSD; n=20). The next morning, reported fatigue,
perception of task difficulty, and use of “what-is-beautiful-is-good,” “greedy
algorithm,” and “speed-accuracy trade-off” heuristics were assessed.
Results: NES slept for an average of 354.74 minutes
(SD=72.84), or 5.91 hours. TSD rated a reading task as
significantly more difficult and requiring more time than NES. TSD was
significantly more likely to use the greedy algorithm heuristic by skipping
instructions and the what-is-beautiful-is-good heuristic by rating an
unattractive consumer item with a favorable review as poor quality. Those in
Total Sleep Deprivation who chose more difficult math problems made this
selection to finish the task more quickly in findings approaching significance,
indicating use of the speed-accuracy trade-off heuristic. Collapsed across
conditions, self-reported fatigue predicted greater perceived difficulty in both
the reading task and a visuo-motor task, higher quality rating for the
attractive consumer item, and lower quality rating for the unattractive consumer
item. Conclusions: Findings indicate sleep deprivation and fatigue
increase perceptions of task difficulty, promote skipping instructions, and
impair systematic evaluation of unappealing stimuli compared to
naturally-experienced sleep.
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Affiliation(s)
| | - Gina Marie Mathew
- Baruch College, City University of New York, Psychology - New York - NY - USA
| | - Anastasia Martinova
- Baruch College, City University of New York, Psychology - New York - NY - USA
| | - Forrest Armstrong
- Baruch College, City University of New York, Psychology - New York - NY - USA
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24
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Foley BR, Marjoram P. Sure enough: efficient Bayesian learning and choice. Anim Cogn 2017; 20:867-880. [PMID: 28669114 DOI: 10.1007/s10071-017-1107-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Revised: 06/16/2017] [Accepted: 06/20/2017] [Indexed: 12/31/2022]
Abstract
Probabilistic decision-making is a general phenomenon in animal behavior, and has often been interpreted to reflect the relative certainty of animals' beliefs. Extensive neurological and behavioral results increasingly suggest that animal beliefs may be represented as probability distributions, with explicit accounting of uncertainty. Accordingly, we develop a model that describes decision-making in a manner consistent with this understanding of neuronal function in learning and conditioning. This first-order Markov, recursive Bayesian algorithm is as parsimonious as its minimalist point-estimate, Rescorla-Wagner analogue. We show that the Bayesian algorithm can reproduce naturalistic patterns of probabilistic foraging, in simulations of an experiment in bumblebees. We go on to show that the Bayesian algorithm can efficiently describe the behavior of several heuristic models of decision-making, and is consistent with the ubiquitous variation in choice that we observe within and between individuals in implementing heuristic decision-making. By describing learning and decision-making in a single Bayesian framework, we believe we can realistically unify descriptions of behavior across contexts and organisms. A unified cognitive model of this kind may facilitate descriptions of behavioral evolution.
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Affiliation(s)
- Brad R Foley
- The Department of Molecular and Computational Biology, The University of Southern California, 1050 Childs Way, Los Angeles, CA, 90089, USA.
| | - Paul Marjoram
- Preventative Medicine, Keck School of Medicine, The University of Southern California, 2001 N. Soto Street, Los Angeles, CA, 90032, USA
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25
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Kelly S, Bailey A, Hirata Y. Metaphoric Gestures Facilitate Perception of Intonation More than Length in Auditory Judgments of Non-Native Phonemic Contrasts. COLLABRA: PSYCHOLOGY 2017. [DOI: 10.1525/collabra.76] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
It is well established that hand gestures affect comprehension and learning of semantic aspects of a foreign language (FL). However, much less is known about the role of hand gestures in lower-level language processes, such as perception of phonemes. To address this gap, we explored the role that metaphoric gestures play in perceiving FL speech sounds that varied on two dimensions: length and intonation. English speaking adults listened to Japanese length contrasts and sentence-final intonational distinctions in the context of congruent, incongruent and no gestures. For intonational contrasts, identification was more accurate for congruent gestures and less accurate for incongruent gestures relative to the baseline no gesture condition. However, for the length contrasts, there was no such clear and consistent pattern, and in fact, congruent gestures made speech processing more effortful. We conclude that metaphoric gestures help with some—but not all—novel speech sounds in a FL, suggesting that gesture and speech are phonemically integrated to differing extents depending on the nature of the gesture and/or speech sound.
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Affiliation(s)
- Spencer Kelly
- Department of Psychology, Center for Language and Brain, Colgate University, US
| | | | - Yukari Hirata
- Department of East Asian Languages and Literatures, Center for Language and Brain, Colgate University, US
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26
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Leyva A, Balachandran A, Britton JC, Eltoukhy M, Kuenze C, Myers ND, Signorile JF. The development and examination of a new walking executive function test for people over 50 years of age. Physiol Behav 2017; 171:100-109. [DOI: 10.1016/j.physbeh.2017.01.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Revised: 12/01/2016] [Accepted: 01/03/2017] [Indexed: 10/20/2022]
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27
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Barack DL, Gold JI. Temporal trade-offs in psychophysics. Curr Opin Neurobiol 2016; 37:121-125. [PMID: 26921829 PMCID: PMC4860089 DOI: 10.1016/j.conb.2016.01.015] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2015] [Revised: 01/22/2016] [Accepted: 01/28/2016] [Indexed: 11/21/2022]
Abstract
Psychophysical techniques typically assume straightforward relationships between manipulations of real-world events, their effects on the brain, and behavioral reports of those effects. However, these relationships can be influenced by many complex, strategic factors that contribute to task performance. Here we discuss several of these factors that share two key features. First, they involve subjects making flexible use of time to process information. Second, this flexibility can reflect the rational regulation of information-processing trade-offs that can play prominent roles in particular temporal epochs: sensitivity to stability versus change for past information, speed versus accuracy for current information, and exploitation versus exploration for future goals. Understanding how subjects manage these trade-offs can be used to help design and interpret psychophysical studies.
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Affiliation(s)
- David L Barack
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, United States; Department of Philosophy, University of Pennsylvania, Philadelphia, PA 19104, United States; The Center for Science and Society and Departments of Philosophy, Neuroscience, and Economics, Columbia University, New York, NY 10027, United States
| | - Joshua I Gold
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, United States.
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28
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Harris H, Israeli D, Minshew N, Bonneh Y, Heeger DJ, Behrmann M, Sagi D. Perceptual learning in autism: over-specificity and possible remedies. Nat Neurosci 2015; 18:1574-6. [PMID: 26436903 DOI: 10.1038/nn.4129] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 09/08/2015] [Indexed: 11/09/2022]
Abstract
Inflexible behavior is a core characteristic of autism spectrum disorder (ASD), but its underlying cause is unknown. Using a perceptual learning protocol, we observed initially efficient learning in ASD that was followed by anomalously poor learning when the location of the target was changed (over-specificity). Reducing stimulus repetition eliminated over-specificity. Our results indicate that inflexible behavior may be evident ubiquitously in ASD, even in sensory learning, but can be circumvented by specifically designed stimulation protocols.
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Affiliation(s)
- Hila Harris
- Department of Neurobiology/Brain Research, Weizmann Institute of Science, Rehovot, Israel
| | - David Israeli
- Jerusalem Center for Mental Health, Hebrew University, Jerusalem, Israel
| | - Nancy Minshew
- Center for Excellence in Autism Research, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Yoram Bonneh
- Department of Neurobiology/Brain Research, Weizmann Institute of Science, Rehovot, Israel.,Department of Human Biology, University of Haifa, Haifa, Israel
| | - David J Heeger
- Department of Psychology and Center for Neural Science, New York University, New York, New York, USA
| | - Marlene Behrmann
- Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Dov Sagi
- Department of Neurobiology/Brain Research, Weizmann Institute of Science, Rehovot, Israel
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Arnold NR, Bröder A, Bayen UJ. Empirical validation of the diffusion model for recognition memory and a comparison of parameter-estimation methods. PSYCHOLOGICAL RESEARCH 2014; 79:882-98. [PMID: 25281426 PMCID: PMC4534506 DOI: 10.1007/s00426-014-0608-y] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2014] [Accepted: 09/02/2014] [Indexed: 12/02/2022]
Abstract
The diffusion model introduced by Ratcliff (Psychol Rev 85:59–108, 1978) has been applied to many binary decision tasks including recognition memory. It describes dynamic evidence accumulation unfolding over time and models choice accuracy as well as response-time distributions. Various parameters describe aspects of decision quality and response bias. In three recognition-memory experiments, the validity of the model was tested experimentally and analyzed with three different programs: fast-dm, EZ, and DMAT. Each of three central model parameters was targeted via specific experimental manipulations. All manipulations affected mainly the corresponding parameters, thus supporting the convergent validity of the measures. There were, however, smaller effects on other parameters, showing some limitations in discriminant validity.
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Affiliation(s)
- Nina R Arnold
- Institute for Experimental Psychology, Heinrich-Heine-Universität Düsseldorf, Universitätsstr. 1, 40225, Düsseldorf, Germany,
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Goldhacker M, Rosengarth K, Plank T, Greenlee MW. The effect of feedback on performance and brain activation during perceptual learning. Vision Res 2014; 99:99-110. [DOI: 10.1016/j.visres.2013.11.010] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2013] [Revised: 11/14/2013] [Accepted: 11/30/2013] [Indexed: 01/22/2023]
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Zhang J, Rowe JB. Dissociable mechanisms of speed-accuracy tradeoff during visual perceptual learning are revealed by a hierarchical drift-diffusion model. Front Neurosci 2014; 8:69. [PMID: 24782701 PMCID: PMC3988401 DOI: 10.3389/fnins.2014.00069] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2014] [Accepted: 03/24/2014] [Indexed: 02/02/2023] Open
Abstract
Two phenomena are commonly observed in decision-making. First, there is a speed-accuracy tradeoff (SAT) such that decisions are slower and more accurate when instructions emphasize accuracy over speed, and vice versa. Second, decision performance improves with practice, as a task is learnt. The SAT and learning effects have been explained under a well-established evidence-accumulation framework for decision-making, which suggests that evidence supporting each choice is accumulated over time, and a decision is committed to when the accumulated evidence reaches a decision boundary. This framework suggests that changing the decision boundary creates the tradeoff between decision speed and accuracy, while increasing the rate of accumulation leads to more accurate and faster decisions after learning. However, recent studies challenged the view that SAT and learning are associated with changes in distinct, single decision parameters. Further, the influence of speed-accuracy instructions over the course of learning remains largely unknown. Here, we used a hierarchical drift-diffusion model to examine the SAT during learning of a coherent motion discrimination task across multiple training sessions, and a transfer test session. The influence of speed-accuracy instructions was robust over training and generalized across untrained stimulus features. Emphasizing decision accuracy rather than speed was associated with increased boundary separation, drift rate and non-decision time at the beginning of training. However, after training, an emphasis on decision accuracy was only associated with increased boundary separation. In addition, faster and more accurate decisions after learning were due to a gradual decrease in boundary separation and an increase in drift rate. The results suggest that speed-accuracy instructions and learning differentially shape decision-making processes at different time scales.
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Affiliation(s)
- Jiaxiang Zhang
- Cognition and Brain Sciences Unit, Medical Research CouncilCambridge, UK,*Correspondence: Jiaxiang Zhang, Cognition and Brain Sciences Unit, Medical Research Council, 15 Chaucer Road, Cambridge CB2 7EF, UK e-mail:
| | - James B. Rowe
- Cognition and Brain Sciences Unit, Medical Research CouncilCambridge, UK,Department of Clinical Neurosciences, University of CambridgeCambridge, UK,Behavioural and Clinical Neuroscience Institute, University of CambridgeCambridge, UK
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Gold JI, Ding L. How mechanisms of perceptual decision-making affect the psychometric function. Prog Neurobiol 2013; 103:98-114. [PMID: 22609483 PMCID: PMC3445702 DOI: 10.1016/j.pneurobio.2012.05.008] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2011] [Revised: 05/02/2012] [Accepted: 05/09/2012] [Indexed: 11/24/2022]
Abstract
Psychometric functions are often interpreted in the context of Signal Detection Theory, which emphasizes a distinction between sensory processing and non-sensory decision rules in the brain. This framework has helped to relate perceptual sensitivity to the "neurometric" sensitivity of sensory-driven neural activity. However, perceptual sensitivity, as interpreted via Signal Detection Theory, is based on not just how the brain represents relevant sensory information, but also how that information is read out to form the decision variable to which the decision rule is applied. Here we discuss recent advances in our understanding of this readout process and describe its effects on the psychometric function. In particular, we show that particular aspects of the readout process can have specific, identifiable effects on the threshold, slope, upper asymptote, time dependence, and choice dependence of psychometric functions. To illustrate these points, we emphasize studies of perceptual learning that have identified changes in the readout process that can lead to changes in these aspects of the psychometric function. We also discuss methods that have been used to distinguish contributions of the sensory representation versus its readout to psychophysical performance.
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Affiliation(s)
- Joshua I Gold
- 116 Johnson Pavilion, Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104-6074, United States.
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Zhang J. The effects of evidence bounds on decision-making: theoretical and empirical developments. Front Psychol 2012; 3:263. [PMID: 22870070 PMCID: PMC3409448 DOI: 10.3389/fpsyg.2012.00263] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2012] [Accepted: 07/08/2012] [Indexed: 11/23/2022] Open
Abstract
Converging findings from behavioral, neurophysiological, and neuroimaging studies suggest an integration-to-boundary mechanism governing decision formation and choice selection. This mechanism is supported by sequential sampling models of choice decisions, which can implement statistically optimal decision strategies for selecting between multiple alternative options on the basis of sensory evidence. This review focuses on recent developments in understanding the evidence boundary, an important component of decision-making raised by experimental findings and models. The article starts by reviewing the neurobiology of perceptual decisions and several influential sequential sampling models, in particular the drift-diffusion model, the Ornstein–Uhlenbeck model and the leaky-competing-accumulator model. In the second part, the article examines how the boundary may affect a model’s dynamics and performance and to what extent it may improve a model’s fits to experimental data. In the third part, the article examines recent findings that support the presence and site of boundaries in the brain. The article considers two questions: (1) whether the boundary is a spontaneous property of neural integrators, or is controlled by dedicated neural circuits; (2) if the boundary is variable, what could be the driving factors behind boundary changes? The review brings together studies using different experimental methods in seeking answers to these questions, highlights psychological and physiological factors that may be associated with the boundary and its changes, and further considers the evidence boundary as a generic mechanism to guide complex behavior.
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Affiliation(s)
- Jiaxiang Zhang
- Cognition and Brain Sciences Unit, Medical Research Council Cambridge, UK
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34
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Ahissar M. Perceptual Learning 2012. Vision Res 2012; 61:1-3. [DOI: 10.1016/j.visres.2012.04.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Sterkin A, Yehezkel O, Polat U. Learning to be fast: gain accuracy with speed. Vision Res 2011; 61:115-24. [PMID: 22037306 DOI: 10.1016/j.visres.2011.09.015] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2011] [Revised: 09/02/2011] [Accepted: 09/05/2011] [Indexed: 01/07/2023]
Abstract
Our recent neurophysiological findings provided evidence for collinear facilitation in detecting low-contrast Gabor patches (GPs) and for the abolishment of these collinear interactions by backward masking (BM) (Sterkin et al., 2008; Sterkin, Yehezkel, Bonneh, et al., 2009). We suggested that the suppression induced by the BM eliminates the collinear facilitation. Moreover, our recent study showed that training on a BM task overcomes the BM effect, hence, improves the processing speed (Polat, 2009). Here we applied training on detecting a target that is followed by BM in order to study whether reinforced facilitatory interactions can overcome the suppressive effects induced by BM. Event-Related Potentials (ERPs) were recorded before and after ten training sessions performed on different days. Low-contrast, foveal target GP was simultaneously flanked by two collinear high-contrast GPs. In the BM task, another identical mask was presented at different time-intervals (ISIs). Before training, BM induced suppression of target detection, at the ISI of 50 ms, in agreement with earlier behavioral findings. This ISI coincides with the active time-window of lateral interactions. After training, our results show a remarkable improvement in all behavioral measurements, including percent of correct responses, sensitivity (d'), reaction time (RT) and the decision criterion for this ISI. The ERP results show that before training,BM attenuated the physiological markers of facilitation at the same ISI of 50 ms, measured as the amplitude of the negative N1 peak (latency of 260 ms). After the training, the sensory representation, reflected by P1 peak, has not changed, consistent with the unchanged physical parameters of the stimulus. Instead, the shorter latency (by 20 ms, latency of 240 ms) and the increased amplitude of N1 represent the development of faster and stronger facilitatory lateral interactions between the target and the collinear flankers. Thus, previously effective backward masking became ineffective in disrupting the collinear facilitation. Moreover, a high-amplitude late peak (P4, latency of 610-630 ms) was not affected by training, however its high correlation with RT (95%) before training was significantly decreased (to 76%), consistent with a lower-level representation of a trained skill. We suggest that perceptual learning that strengthens collinear facilitation results in a faster processing speed.
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Affiliation(s)
- Anna Sterkin
- Goldschleger Eye Research Institute, Tel Aviv University, Tel Hashomer, Israel.
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