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Ruikes TR, Fiorilli J, Lim J, Huis In 't Veld G, Bosman C, Pennartz CMA. Theta Phase Entrainment of Single-Cell Spiking in Rat Somatosensory Barrel Cortex and Secondary Visual Cortex Is Enhanced during Multisensory Discrimination Behavior. eNeuro 2024; 11:ENEURO.0180-23.2024. [PMID: 38621992 PMCID: PMC11055653 DOI: 10.1523/eneuro.0180-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 02/16/2024] [Accepted: 02/16/2024] [Indexed: 04/17/2024] Open
Abstract
Phase entrainment of cells by theta oscillations is thought to globally coordinate the activity of cell assemblies across different structures, such as the hippocampus and neocortex. This coordination is likely required for optimal processing of sensory input during recognition and decision-making processes. In quadruple-area ensemble recordings from male rats engaged in a multisensory discrimination task, we investigated phase entrainment of cells by theta oscillations in areas along the corticohippocampal hierarchy: somatosensory barrel cortex (S1BF), secondary visual cortex (V2L), perirhinal cortex (PER), and dorsal hippocampus (dHC). Rats discriminated between two 3D objects presented in tactile-only, visual-only, or both tactile and visual modalities. During task engagement, S1BF, V2L, PER, and dHC LFP signals showed coherent theta-band activity. We found phase entrainment of single-cell spiking activity to locally recorded as well as hippocampal theta activity in S1BF, V2L, PER, and dHC. While phase entrainment of hippocampal spikes to local theta oscillations occurred during sustained epochs of task trials and was nonselective for behavior and modality, somatosensory and visual cortical cells were only phase entrained during stimulus presentation, mainly in their preferred modality (S1BF, tactile; V2L, visual), with subsets of cells selectively phase-entrained during cross-modal stimulus presentation (S1BF: visual; V2L: tactile). This effect could not be explained by modulations of firing rate or theta amplitude. Thus, hippocampal cells are phase entrained during prolonged epochs, while sensory and perirhinal neurons are selectively entrained during sensory stimulus presentation, providing a brief time window for coordination of activity.
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Affiliation(s)
- Thijs R Ruikes
- Center for Neuroscience, Faculty of Science, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam 1098 XH, The Netherlands
| | - Julien Fiorilli
- Center for Neuroscience, Faculty of Science, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam 1098 XH, The Netherlands
| | - Judith Lim
- Center for Neuroscience, Faculty of Science, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam 1098 XH, The Netherlands
| | - Gerjan Huis In 't Veld
- Center for Neuroscience, Faculty of Science, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam 1098 XH, The Netherlands
| | - Conrado Bosman
- Center for Neuroscience, Faculty of Science, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam 1098 XH, The Netherlands
| | - Cyriel M A Pennartz
- Center for Neuroscience, Faculty of Science, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam 1098 XH, The Netherlands
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2
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Oude Lohuis MN, Marchesi P, Olcese U, Pennartz CMA. Triple dissociation of visual, auditory and motor processing in mouse primary visual cortex. Nat Neurosci 2024; 27:758-771. [PMID: 38307971 DOI: 10.1038/s41593-023-01564-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 12/19/2023] [Indexed: 02/04/2024]
Abstract
Primary sensory cortices respond to crossmodal stimuli-for example, auditory responses are found in primary visual cortex (V1). However, it remains unclear whether these responses reflect sensory inputs or behavioral modulation through sound-evoked body movement. We address this controversy by showing that sound-evoked activity in V1 of awake mice can be dissociated into auditory and behavioral components with distinct spatiotemporal profiles. The auditory component began at approximately 27 ms, was found in superficial and deep layers and originated from auditory cortex. Sound-evoked orofacial movements correlated with V1 neural activity starting at approximately 80-100 ms and explained auditory frequency tuning. Visual, auditory and motor activity were expressed by different laminar profiles and largely segregated subsets of neuronal populations. During simultaneous audiovisual stimulation, visual representations remained dissociable from auditory-related and motor-related activity. This three-fold dissociability of auditory, motor and visual processing is central to understanding how distinct inputs to visual cortex interact to support vision.
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Affiliation(s)
- Matthijs N Oude Lohuis
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | - Pietro Marchesi
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Umberto Olcese
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands.
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands.
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3
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Evers K, Farisco M, Pennartz CMA. Assessing the commensurability of theories of consciousness: On the usefulness of common denominators in differentiating, integrating and testing hypotheses. Conscious Cogn 2024; 119:103668. [PMID: 38417198 DOI: 10.1016/j.concog.2024.103668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 02/07/2024] [Accepted: 02/12/2024] [Indexed: 03/01/2024]
Abstract
How deep is the current diversity in the panoply of theories to define consciousness, and to what extent do these theories share common denominators? Here we first examine to what extent different theories are commensurable (or comparable) along particular dimensions. We posit logical (and, when applicable, empirical) commensurability as a necessary condition for identifying common denominators among different theories. By consequence, dimensions for inclusion in a set of logically and empirically commensurable theories of consciousness can be proposed. Next, we compare a limited subset of neuroscience-based theories in terms of commensurability. This analysis does not yield a denominator that might serve to define a minimally unifying model of consciousness. Theories that seem to be akin by one denominator can be remote by another. We suggest a methodology of comparing different theories via multiple probing questions, allowing to discern overall (dis)similarities between theories. Despite very different background definitions of consciousness, we conclude that, if attention is paid to the search for a common methological approach to brain-consciousness relationships, it should be possible in principle to overcome the current Babylonian confusion of tongues and eventually integrate and merge different theories.
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Affiliation(s)
- K Evers
- Centre for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden.
| | - M Farisco
- Centre for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden; Bioethics Unit, Biogem, Molecular Biology and Molecular Genetics Research Institute, Ariano Irpino (AV), Italy
| | - C M A Pennartz
- Department of Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherland; Research Priority Area, Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
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4
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Storm JF, Klink PC, Aru J, Senn W, Goebel R, Pigorini A, Avanzini P, Vanduffel W, Roelfsema PR, Massimini M, Larkum ME, Pennartz CMA. An integrative, multiscale view on neural theories of consciousness. Neuron 2024:S0896-6273(24)00088-6. [PMID: 38447578 DOI: 10.1016/j.neuron.2024.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 12/20/2023] [Accepted: 02/05/2024] [Indexed: 03/08/2024]
Abstract
How is conscious experience related to material brain processes? A variety of theories aiming to answer this age-old question have emerged from the recent surge in consciousness research, and some are now hotly debated. Although most researchers have so far focused on the development and validation of their preferred theory in relative isolation, this article, written by a group of scientists representing different theories, takes an alternative approach. Noting that various theories often try to explain different aspects or mechanistic levels of consciousness, we argue that the theories do not necessarily contradict each other. Instead, several of them may converge on fundamental neuronal mechanisms and be partly compatible and complementary, so that multiple theories can simultaneously contribute to our understanding. Here, we consider unifying, integration-oriented approaches that have so far been largely neglected, seeking to combine valuable elements from various theories.
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Affiliation(s)
- Johan F Storm
- The Brain Signaling Group, Division of Physiology, IMB, Faculty of Medicine, University of Oslo, Domus Medica, Sognsvannsveien 9, Blindern, 0317 Oslo, Norway.
| | - P Christiaan Klink
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands; Experimental Psychology, Helmholtz Institute, Utrecht University, 3584 CS Utrecht, the Netherlands; Laboratory of Visual Brain Therapy, Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Institut de la Vision, Paris 75012, France
| | - Jaan Aru
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Walter Senn
- Department of Physiology, University of Bern, Bern, Switzerland
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands
| | - Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan 20122, Italy
| | - Pietro Avanzini
- Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche, 43125 Parma, Italy
| | - Wim Vanduffel
- Department of Neurosciences, Laboratory of Neuro and Psychophysiology, KU Leuven Medical School, 3000 Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Department of Radiology, Harvard Medical School, Boston, MA 02144, USA
| | - Pieter R Roelfsema
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands; Laboratory of Visual Brain Therapy, Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Institut de la Vision, Paris 75012, France; Department of Integrative Neurophysiology, VU University, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands; Department of Neurosurgery, Academisch Medisch Centrum, Postbus 22660, 1100 DD Amsterdam, the Netherlands
| | - Marcello Massimini
- Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Milan 20157, Italy; Istituto di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan 20122, Italy; Azrieli Program in Brain, Mind and Consciousness, Canadian Institute for Advanced Research (CIFAR), Toronto, ON M5G 1M1, Canada
| | - Matthew E Larkum
- Institute of Biology, Humboldt University Berlin, Berlin, Germany; Neurocure Center for Excellence, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Sciencepark 904, Amsterdam 1098 XH, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands
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5
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Arnts H, Tewarie P, van Erp W, Schuurman R, Boon LI, Pennartz CMA, Stam CJ, Hillebrand A, van den Munckhof P. Deep brain stimulation of the central thalamus restores arousal and motivation in a zolpidem-responsive patient with akinetic mutism after severe brain injury. Sci Rep 2024; 14:2950. [PMID: 38316863 PMCID: PMC10844373 DOI: 10.1038/s41598-024-52267-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 01/16/2024] [Indexed: 02/07/2024] Open
Abstract
After severe brain injury, zolpidem is known to cause spectacular, often short-lived, restorations of brain functions in a small subgroup of patients. Previously, we showed that these zolpidem-induced neurological recoveries can be paralleled by significant changes in functional connectivity throughout the brain. Deep brain stimulation (DBS) is a neurosurgical intervention known to modulate functional connectivity in a wide variety of neurological disorders. In this study, we used DBS to restore arousal and motivation in a zolpidem-responsive patient with severe brain injury and a concomitant disorder of diminished motivation, more than 10 years after surviving hypoxic ischemia. We found that DBS of the central thalamus, targeted at the centromedian-parafascicular complex, immediately restored arousal and was able to transition the patient from a state of deep sleep to full wakefulness. Moreover, DBS was associated with temporary restoration of communication and ability to walk and eat in an otherwise wheelchair-bound and mute patient. With the use of magnetoencephalography (MEG), we revealed that DBS was generally associated with a marked decrease in aberrantly high levels of functional connectivity throughout the brain, mimicking the effects of zolpidem. These results imply that 'pathological hyperconnectivity' after severe brain injury can be associated with reduced arousal and behavioral performance and that DBS is able to modulate connectivity towards a 'healthier baseline' with lower synchronization, and, can restore functional brain networks long after severe brain injury. The presence of hyperconnectivity after brain injury may be a possible future marker for a patient's responsiveness for restorative interventions, such as DBS, and suggests that lower degrees of overall brain synchronization may be conducive to cognition and behavioral responsiveness.
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Affiliation(s)
- Hisse Arnts
- Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
- Department of Neurosurgery, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Prejaas Tewarie
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Willemijn van Erp
- Department of Primary and Community Care, Centre for Family Medicine, Geriatric Care and Public Health, Radboud University Medical Centre, Nijmegen, The Netherlands
- Accolade Zorg, Bosch en Duin, The Netherlands
- Libra Rehabilitation & Audiology, Tilburg, The Netherlands
| | - Rick Schuurman
- Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Lennard I Boon
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute, Center for Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Pepijn van den Munckhof
- Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.
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6
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Fiorilli J, Marchesi P, Ruikes T, Huis in ‘t Veld G, Buckton R, Quintero MD, Reiten I, Bjaalie JG, Pennartz CMA. Neural correlates of object identity and reward outcome in the sensory cortical-hippocampal hierarchy: coding of motivational information in perirhinal cortex. Cereb Cortex 2024; 34:bhae002. [PMID: 38314581 PMCID: PMC10847907 DOI: 10.1093/cercor/bhae002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 12/21/2023] [Accepted: 12/24/2023] [Indexed: 02/06/2024] Open
Abstract
Neural circuits support behavioral adaptations by integrating sensory and motor information with reward and error-driven learning signals, but it remains poorly understood how these signals are distributed across different levels of the corticohippocampal hierarchy. We trained rats on a multisensory object-recognition task and compared visual and tactile responses of simultaneously recorded neuronal ensembles in somatosensory cortex, secondary visual cortex, perirhinal cortex, and hippocampus. The sensory regions primarily represented unisensory information, whereas hippocampus was modulated by both vision and touch. Surprisingly, the sensory cortices and the hippocampus coded object-specific information, whereas the perirhinal cortex did not. Instead, perirhinal cortical neurons signaled trial outcome upon reward-based feedback. A majority of outcome-related perirhinal cells responded to a negative outcome (reward omission), whereas a minority of other cells coded positive outcome (reward delivery). Our results highlight a distributed neural coding of multisensory variables in the cortico-hippocampal hierarchy. Notably, the perirhinal cortex emerges as a crucial region for conveying motivational outcomes, whereas distinct functions related to object identity are observed in the sensory cortices and hippocampus.
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Affiliation(s)
- Julien Fiorilli
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Pietro Marchesi
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Thijs Ruikes
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Gerjan Huis in ‘t Veld
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Rhys Buckton
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Mariana D Quintero
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Ingrid Reiten
- Institute of Basic Medical Sciences, University of Oslo, NO-0316 Oslo, Norway
| | - Jan G Bjaalie
- Institute of Basic Medical Sciences, University of Oslo, NO-0316 Oslo, Norway
| | - Cyriel M A Pennartz
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
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7
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Abstract
Deep learning and predictive coding architectures commonly assume that inference in neural networks is hierarchical. However, largely neglected in deep learning and predictive coding architectures is the neurobiological evidence that all hierarchical cortical areas, higher or lower, project to and receive signals directly from subcortical areas. Given these neuroanatomical facts, today's dominance of cortico-centric, hierarchical architectures in deep learning and predictive coding networks is highly questionable; such architectures are likely to be missing essential computational principles the brain uses. In this Perspective, we present the shallow brain hypothesis: hierarchical cortical processing is integrated with a massively parallel process to which subcortical areas substantially contribute. This shallow architecture exploits the computational capacity of cortical microcircuits and thalamo-cortical loops that are not included in typical hierarchical deep learning and predictive coding networks. We argue that the shallow brain architecture provides several critical benefits over deep hierarchical structures and a more complete depiction of how mammalian brains achieve fast and flexible computational capabilities.
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Affiliation(s)
- Mototaka Suzuki
- Department of Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.
| | - Cyriel M A Pennartz
- Department of Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Jaan Aru
- Institute of Computer Science, University of Tartu, Tartu, Estonia.
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8
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Pennartz CMA, Oude Lohuis MN, Olcese U. How 'visual' is the visual cortex? The interactions between the visual cortex and other sensory, motivational and motor systems as enabling factors for visual perception. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220336. [PMID: 37545313 PMCID: PMC10404929 DOI: 10.1098/rstb.2022.0336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 06/13/2023] [Indexed: 08/08/2023] Open
Abstract
The definition of the visual cortex is primarily based on the evidence that lesions of this area impair visual perception. However, this does not exclude that the visual cortex may process more information than of retinal origin alone, or that other brain structures contribute to vision. Indeed, research across the past decades has shown that non-visual information, such as neural activity related to reward expectation and value, locomotion, working memory and other sensory modalities, can modulate primary visual cortical responses to retinal inputs. Nevertheless, the function of this non-visual information is poorly understood. Here we review recent evidence, coming primarily from studies in rodents, arguing that non-visual and motor effects in visual cortex play a role in visual processing itself, for instance disentangling direct auditory effects on visual cortex from effects of sound-evoked orofacial movement. These findings are placed in a broader framework casting vision in terms of predictive processing under control of frontal, reward- and motor-related systems. In contrast to the prevalent notion that vision is exclusively constructed by the visual cortical system, we propose that visual percepts are generated by a larger network-the extended visual system-spanning other sensory cortices, supramodal areas and frontal systems. This article is part of the theme issue 'Decision and control processes in multisensory perception'.
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Affiliation(s)
- Cyriel M. A. Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
| | - Matthijs N. Oude Lohuis
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
- Champalimaud Research, Champalimaud Foundation, 1400-038 Lisbon, Portugal
| | - Umberto Olcese
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands
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9
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Brucklacher M, Bohté SM, Mejias JF, Pennartz CMA. Local minimization of prediction errors drives learning of invariant object representations in a generative network model of visual perception. Front Comput Neurosci 2023; 17:1207361. [PMID: 37818157 PMCID: PMC10561268 DOI: 10.3389/fncom.2023.1207361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 08/31/2023] [Indexed: 10/12/2023] Open
Abstract
The ventral visual processing hierarchy of the cortex needs to fulfill at least two key functions: perceived objects must be mapped to high-level representations invariantly of the precise viewing conditions, and a generative model must be learned that allows, for instance, to fill in occluded information guided by visual experience. Here, we show how a multilayered predictive coding network can learn to recognize objects from the bottom up and to generate specific representations via a top-down pathway through a single learning rule: the local minimization of prediction errors. Trained on sequences of continuously transformed objects, neurons in the highest network area become tuned to object identity invariant of precise position, comparable to inferotemporal neurons in macaques. Drawing on this, the dynamic properties of invariant object representations reproduce experimentally observed hierarchies of timescales from low to high levels of the ventral processing stream. The predicted faster decorrelation of error-neuron activity compared to representation neurons is of relevance for the experimental search for neural correlates of prediction errors. Lastly, the generative capacity of the network is confirmed by reconstructing specific object images, robust to partial occlusion of the inputs. By learning invariance from temporal continuity within a generative model, the approach generalizes the predictive coding framework to dynamic inputs in a more biologically plausible way than self-supervised networks with non-local error-backpropagation. This was achieved simply by shifting the training paradigm to dynamic inputs, with little change in architecture and learning rule from static input-reconstructing Hebbian predictive coding networks.
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Affiliation(s)
- Matthias Brucklacher
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Sander M Bohté
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
- Machine Learning Group, Centrum Wiskunde & Informatica, Amsterdam, Netherlands
| | - Jorge F Mejias
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
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10
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Dorman R, Bos JJ, Vinck MA, Marchesi P, Fiorilli J, Lorteije JAM, Reiten I, Bjaalie JG, Okun M, Pennartz CMA. Spike-based coupling between single neurons and populations across rat sensory cortices, perirhinal cortex, and hippocampus. Cereb Cortex 2023; 33:8247-8264. [PMID: 37118890 PMCID: PMC10425201 DOI: 10.1093/cercor/bhad111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 04/30/2023] Open
Abstract
Cortical computations require coordination of neuronal activity within and across multiple areas. We characterized spiking relationships within and between areas by quantifying coupling of single neurons to population firing patterns. Single-neuron population coupling (SNPC) was investigated using ensemble recordings from hippocampal CA1 region and somatosensory, visual, and perirhinal cortices. Within-area coupling was heterogeneous across structures, with area CA1 showing higher levels than neocortical regions. In contrast to known anatomical connectivity, between-area coupling showed strong firing coherence of sensory neocortices with CA1, but less with perirhinal cortex. Cells in sensory neocortices and CA1 showed positive correlations between within- and between-area coupling; these were weaker for perirhinal cortex. All four areas harbored broadcasting cells, connecting to multiple external areas, which was uncorrelated to within-area coupling strength. When examining correlations between SNPC and spatial coding, we found that, if such correlations were significant, they were negative. This result was consistent with an overall preservation of SNPC across different brain states, suggesting a strong dependence on intrinsic network connectivity. Overall, SNPC offers an important window on cell-to-population synchronization in multi-area networks. Instead of pointing to specific information-coding functions, our results indicate a primary function of SNPC in dynamically organizing communication in systems composed of multiple, interconnected areas.
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Affiliation(s)
- Reinder Dorman
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Jeroen J Bos
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, 6500 HC Nijmegen, The Netherlands
| | - Martin A Vinck
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Plank Society, 60528 Frankfurt, Germany
| | - Pietro Marchesi
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Julien Fiorilli
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Jeanette A M Lorteije
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Ingrid Reiten
- Institute of Basic Medical Sciences, University of Oslo, NO-0316 Oslo, Norway
| | - Jan G Bjaalie
- Institute of Basic Medical Sciences, University of Oslo, NO-0316 Oslo, Norway
| | - Michael Okun
- Department of Psychology and Neuroscience Institute, University of Sheffield, Sheffield S10 2TN, UK
| | - Cyriel M A Pennartz
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
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11
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Klaver LMF, Brinkhof LP, Sikkens T, Casado-Román L, Williams AG, van Mourik-Donga L, Mejías JF, Pennartz CMA, Bosman CA. Spontaneous variations in arousal modulate subsequent visual processing and local field potential dynamics in the ferret during quiet wakefulness. Cereb Cortex 2023; 33:7564-7581. [PMID: 36935096 PMCID: PMC10267643 DOI: 10.1093/cercor/bhad061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 02/11/2023] [Accepted: 02/14/2023] [Indexed: 03/21/2023] Open
Abstract
Behavioral states affect neuronal responses throughout the cortex and influence visual processing. Quiet wakefulness (QW) is a behavioral state during which subjects are quiescent but awake and connected to the environment. Here, we examined the effects of pre-stimulus arousal variability on post-stimulus neural activity in the primary visual cortex and posterior parietal cortex in awake ferrets, using pupil diameter as an indicator of arousal. We observed that the power of stimuli-induced alpha (8-12 Hz) decreases when the arousal level increases. The peak of alpha power shifts depending on arousal. High arousal increases inter- and intra-areal coherence. Using a simplified model of laminar circuits, we show that this connectivity pattern is compatible with feedback signals targeting infragranular layers in area posterior parietal cortex and supragranular layers in V1. During high arousal, neurons in V1 displayed higher firing rates at their preferred orientations. Broad-spiking cells in V1 are entrained to high-frequency oscillations (>80 Hz), whereas narrow-spiking neurons are phase-locked to low- (12-18 Hz) and high-frequency (>80 Hz) rhythms. These results indicate that the variability and sensitivity of post-stimulus cortical responses and coherence depend on the pre-stimulus behavioral state and account for the neuronal response variability observed during repeated stimulation.
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Affiliation(s)
- Lianne M F Klaver
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Lotte P Brinkhof
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Tom Sikkens
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Lorena Casado-Román
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Alex G Williams
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Laura van Mourik-Donga
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Jorge F Mejías
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Conrado A Bosman
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
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12
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Mertens PEC, Marchesi P, Ruikes TR, Oude Lohuis M, Krijger Q, Pennartz CMA, Lansink CS. Coherent mapping of position and head direction across auditory and visual cortex. Cereb Cortex 2023:7086054. [DOI: 10.1093/cercor/bhad045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 01/31/2023] [Accepted: 02/01/2023] [Indexed: 03/28/2023] Open
Abstract
Abstract
Neurons in primary visual cortex (V1) may not only signal current visual input but also relevant contextual information such as reward expectancy and the subject’s spatial position. Such contextual representations need not be restricted to V1 but could participate in a coherent mapping throughout sensory cortices. Here, we show that spiking activity coherently represents a location-specific mapping across auditory cortex (AC) and lateral, secondary visual cortex (V2L) of freely moving rats engaged in a sensory detection task on a figure-8 maze. Single-unit activity of both areas showed extensive similarities in terms of spatial distribution, reliability, and position coding. Importantly, reconstructions of subject position based on spiking activity displayed decoding errors that were correlated between areas. Additionally, we found that head direction, but not locomotor speed or head angular velocity, was an important determinant of activity in AC and V2L. By contrast, variables related to the sensory task cues or to trial correctness and reward were not markedly encoded in AC and V2L. We conclude that sensory cortices participate in coherent, multimodal representations of the subject’s sensory-specific location. These may provide a common reference frame for distributed cortical sensory and motor processes and may support crossmodal predictive processing.
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13
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Muller M, Pennartz CMA, Bosman CA, Olcese U. A novel task to investigate vibrotactile detection in mice. PLoS One 2023; 18:e0284735. [PMID: 37079581 PMCID: PMC10118142 DOI: 10.1371/journal.pone.0284735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 04/06/2023] [Indexed: 04/21/2023] Open
Abstract
Throughout the last decades, understanding the neural mechanisms of sensory processing has been a key objective for neuroscientists. Many studies focused on uncovering the microcircuit-level architecture of somatosensation using the rodent whisker system as a model. Although these studies have significantly advanced our understanding of tactile processing, the question remains to what extent the whisker system can provide results translatable to the human somatosensory system. To address this, we developed a restrained vibrotactile detection task involving the limb system in mice. A vibrotactile stimulus was delivered to the hindlimb of head-fixed mice, who were trained to perform a Go/No-go detection task. Mice were able to learn this task with satisfactory performance and with reasonably short training times. In addition, the task we developed is versatile, as it can be combined with diverse neuroscience methods. Thus, this study introduces a novel task to study the neuron-level mechanisms of tactile processing in a system other than the more commonly studied whisker system.
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Affiliation(s)
- Mariel Muller
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Conrado A Bosman
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Umberto Olcese
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
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14
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Lohuis MNO, Pie JL, Marchesi P, Montijn JS, de Kock CPJ, Pennartz CMA, Olcese U. Author Correction: Multisensory task demands temporally extend the causal requirement for visual cortex in perception. Nat Commun 2022; 13:4088. [PMID: 35835734 PMCID: PMC9283481 DOI: 10.1038/s41467-022-31518-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Affiliation(s)
- Matthijs N Oude Lohuis
- Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Jean L Pie
- Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands.,Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, VU Amsterdam, Amsterdam, The Netherlands
| | - Pietro Marchesi
- Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Jorrit S Montijn
- Cortical Structure and Function, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Christiaan P J de Kock
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, VU Amsterdam, Amsterdam, The Netherlands
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Umberto Olcese
- Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands. .,Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands.
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15
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Oude Lohuis MN, Marchesi P, Pennartz CMA, Olcese U. Functional (ir)Relevance of Posterior Parietal Cortex during Audiovisual Change Detection. J Neurosci 2022; 42:5229-5245. [PMID: 35641187 PMCID: PMC9236290 DOI: 10.1523/jneurosci.2150-21.2022] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 03/24/2022] [Accepted: 03/25/2022] [Indexed: 12/31/2022] Open
Abstract
The posterior parietal cortex (PPC) plays a key role in integrating sensory inputs from different modalities to support adaptive behavior. Neuronal activity in PPC reflects perceptual decision-making across behavioral tasks, but the mechanistic involvement of PPC is unclear. In an audiovisual change detection task, we tested the hypothesis that PPC is required to arbitrate between the noisy inputs from the two different modalities and help decide in which modality a sensory change occurred. In trained male mice, we found extensive single-neuron and population-level encoding of task-relevant visual and auditory stimuli, trial history, as well as upcoming behavioral responses. However, despite these rich neural correlates, which would theoretically be sufficient to solve the task, optogenetic inactivation of PPC did not affect visual or auditory performance. Thus, despite neural correlates faithfully tracking sensory variables and predicting behavioral responses, PPC was not relevant for audiovisual change detection. This functional dissociation questions the role of sensory- and task-related activity in parietal associative circuits during audiovisual change detection. Furthermore, our results highlight the necessity to dissociate functional correlates from mechanistic involvement when exploring the neural basis of perception and behavior.SIGNIFICANCE STATEMENT The posterior parietal cortex (PPC) is active during many daily tasks, but capturing its function has remained challenging. Specifically, it is proposed to function as an integration hub for multisensory inputs. Here, we tested the hypothesis that, rather than classical cue integration, mouse PPC is involved in the segregation and discrimination of sensory modalities. Surprisingly, although neural activity tracked current and past sensory stimuli and reflected the ongoing decision-making process, optogenetic inactivation did not affect task performance. Thus, we show an apparent redundancy of sensory and task-related activity in mouse PPC. These results narrow down the function of parietal circuits, as well as direct the search for those neural dynamics that causally drive perceptual decision-making.
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Affiliation(s)
- Matthijs N Oude Lohuis
- Cognitive and Systems Neuroscience Group, SILS, University of Amsterdam, Amsterdam 1098XH, The Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam 1018WS, The Netherlands
| | - Pietro Marchesi
- Cognitive and Systems Neuroscience Group, SILS, University of Amsterdam, Amsterdam 1098XH, The Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam 1018WS, The Netherlands
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, SILS, University of Amsterdam, Amsterdam 1098XH, The Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam 1018WS, The Netherlands
| | - Umberto Olcese
- Cognitive and Systems Neuroscience Group, SILS, University of Amsterdam, Amsterdam 1098XH, The Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam 1018WS, The Netherlands
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16
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Pennartz CMA. What is neurorepresentationalism? From neural activity and predictive processing to multi-level representations and consciousness. Behav Brain Res 2022; 432:113969. [PMID: 35718232 DOI: 10.1016/j.bbr.2022.113969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 05/18/2022] [Accepted: 05/20/2022] [Indexed: 11/02/2022]
Abstract
This review provides an update on Neurorepresentationalism, a theoretical framework that defines conscious experience as multimodal, situational survey and explains its neural basis from brain systems constructing best-guess representations of sensations originating in our environment and body [1]. It posits that conscious experience is characterized by five essential hallmarks: (i) multimodal richness, (ii) situatedness and immersion, (iii) unity and integration, (iv) dynamics and stability, and (v) intentionality. Consciousness is furthermore proposed to have a biological function, framed by the contrast between reflexes and habits (not requiring consciousness) versus goal-directed, planned behavior (requiring multimodal, situational survey). Conscious experience is therefore understood as a sensorily rich, spatially encompassing representation of body and environment, while we nevertheless have the impression of experiencing external reality directly. Contributions to understanding neural mechanisms underlying consciousness are derived from models for predictive processing, which are trained in an unsupervised manner, do not necessarily require overt action, and have been extended to deep neural networks. Even with predictive processing in place, however, the question remains why this type of neural network activity would give rise to phenomenal experience. Here, I propose to tackle the Hard Problem with the concept of multi-level representations which emergently give rise to multimodal, spatially wide superinferences corresponding to phenomenal experiences. Finally, Neurorepresentationalism is compared to other neural theories of consciousness, and its implications for defining indicators of consciousness in animals, artificial intelligence devices and immobile or unresponsive patients with disorders of consciousness are discussed.
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Affiliation(s)
- Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, the Netherlands.
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17
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Oude Lohuis MN, Pie JL, Marchesi P, Montijn JS, de Kock CPJ, Pennartz CMA, Olcese U. Multisensory task demands temporally extend the causal requirement for visual cortex in perception. Nat Commun 2022; 13:2864. [PMID: 35606448 PMCID: PMC9126973 DOI: 10.1038/s41467-022-30600-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 05/09/2022] [Indexed: 01/02/2023] Open
Abstract
Primary sensory areas constitute crucial nodes during perceptual decision making. However, it remains unclear to what extent they mainly constitute a feedforward processing step, or rather are continuously involved in a recurrent network together with higher-order areas. We found that the temporal window in which primary visual cortex is required for the detection of identical visual stimuli was extended when task demands were increased via an additional sensory modality that had to be monitored. Late-onset optogenetic inactivation preserved bottom-up, early-onset responses which faithfully encoded stimulus features, and was effective in impairing detection only if it preceded a late, report-related phase of the cortical response. Increasing task demands were marked by longer reaction times and the effect of late optogenetic inactivation scaled with reaction time. Thus, independently of visual stimulus complexity, multisensory task demands determine the temporal requirement for ongoing sensory-related activity in V1, which overlaps with report-related activity. How primary sensory cortices contribute to decision making remains poorly understood. Here the authors report that increasing task demands extend the temporal window in which the primary visual cortex is required for detecting identical stimuli.
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18
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Pearson MJ, Dora S, Struckmeier O, Knowles TC, Mitchinson B, Tiwari K, Kyrki V, Bohte S, Pennartz CMA. Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding. Front Robot AI 2021; 8:732023. [PMID: 34966789 PMCID: PMC8710724 DOI: 10.3389/frobt.2021.732023] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 11/19/2021] [Indexed: 11/13/2022] Open
Abstract
Recognising familiar places is a competence required in many engineering applications that interact with the real world such as robot navigation. Combining information from different sensory sources promotes robustness and accuracy of place recognition. However, mismatch in data registration, dimensionality, and timing between modalities remain challenging problems in multisensory place recognition. Spurious data generated by sensor drop-out in multisensory environments is particularly problematic and often resolved through adhoc and brittle solutions. An effective approach to these problems is demonstrated by animals as they gracefully move through the world. Therefore, we take a neuro-ethological approach by adopting self-supervised representation learning based on a neuroscientific model of visual cortex known as predictive coding. We demonstrate how this parsimonious network algorithm which is trained using a local learning rule can be extended to combine visual and tactile sensory cues from a biomimetic robot as it naturally explores a visually aliased environment. The place recognition performance obtained using joint latent representations generated by the network is significantly better than contemporary representation learning techniques. Further, we see evidence of improved robustness at place recognition in face of unimodal sensor drop-out. The proposed multimodal deep predictive coding algorithm presented is also linearly extensible to accommodate more than two sensory modalities, thereby providing an intriguing example of the value of neuro-biologically plausible representation learning for multimodal navigation.
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Affiliation(s)
- Martin J Pearson
- Bristol Robotics Laboratory, University of The West England Bristol, Bristol, United Kingdom
| | - Shirin Dora
- Department of Computer Science, Loughborough University, Loughborough, United Kingdom.,Center for Mathematics and Informatics, Amsterdam, Netherlands
| | | | - Thomas C Knowles
- Bristol Robotics Laboratory, University of The West England Bristol, Bristol, United Kingdom
| | - Ben Mitchinson
- Department of Computer Science, University of Sheffield, Sheffield, United Kingdom
| | - Kshitij Tiwari
- Intelligent Robotics Group, Aalto University, Helsinki, Finland
| | - Ville Kyrki
- Intelligent Robotics Group, Aalto University, Helsinki, Finland
| | - Sander Bohte
- Center for Mathematics and Informatics, Amsterdam, Netherlands.,Department of Cognitive and Systems Neuroscience, University of Amsterdam, Amsterdam, Netherlands
| | - Cyriel M A Pennartz
- Department of Cognitive and Systems Neuroscience, University of Amsterdam, Amsterdam, Netherlands
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19
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Oude Lohuis MN, Canton AC, Pennartz CMA, Olcese U. Higher Order Visual Areas Enhance Stimulus Responsiveness in Mouse Primary Visual Cortex. Cereb Cortex 2021; 32:3269-3288. [PMID: 34849636 PMCID: PMC9340391 DOI: 10.1093/cercor/bhab414] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 10/19/2021] [Accepted: 10/20/2021] [Indexed: 01/14/2023] Open
Abstract
Over the past few years, the various areas that surround the primary visual cortex (V1) in the mouse have been associated with many functions, ranging from higher order visual processing to decision-making. Recently, some studies have shown that higher order visual areas influence the activity of the primary visual cortex, refining its processing capabilities. Here, we studied how in vivo optogenetic inactivation of two higher order visual areas with different functional properties affects responses evoked by moving bars in the primary visual cortex. In contrast with the prevailing view, our results demonstrate that distinct higher order visual areas similarly modulate early visual processing. In particular, these areas enhance stimulus responsiveness in the primary visual cortex, by more strongly amplifying weaker compared with stronger sensory-evoked responses (for instance specifically amplifying responses to stimuli not moving along the direction preferred by individual neurons) and by facilitating responses to stimuli entering the receptive field of single neurons. Such enhancement, however, comes at the expense of orientation and direction selectivity, which increased when the selected higher order visual areas were inactivated. Thus, feedback from higher order visual areas selectively amplifies weak sensory-evoked V1 responses, which may enable more robust processing of visual stimuli.
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Affiliation(s)
- Matthijs N Oude Lohuis
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098XH Amsterdam, The Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, 1098XH Amsterdam, The Netherlands
| | - Alexis Cervan Canton
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098XH Amsterdam, The Netherlands.,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098XH Amsterdam, The Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, 1098XH Amsterdam, The Netherlands
| | - Umberto Olcese
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098XH Amsterdam, The Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, 1098XH Amsterdam, The Netherlands
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20
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Homberg JR, Adan RAH, Alenina N, Asiminas A, Bader M, Beckers T, Begg DP, Blokland A, Burger ME, van Dijk G, Eisel ULM, Elgersma Y, Englitz B, Fernandez-Ruiz A, Fitzsimons CP, van Dam AM, Gass P, Grandjean J, Havekes R, Henckens MJAG, Herden C, Hut RA, Jarrett W, Jeffrey K, Jezova D, Kalsbeek A, Kamermans M, Kas MJ, Kasri NN, Kiliaan AJ, Kolk SM, Korosi A, Korte SM, Kozicz T, Kushner SA, Leech K, Lesch KP, Lesscher H, Lucassen PJ, Luthi A, Ma L, Mallien AS, Meerlo P, Mejias JF, Meye FJ, Mitchell AS, Mul JD, Olcese U, González AO, Olivier JDA, Pasqualetti M, Pennartz CMA, Popik P, Prickaerts J, de la Prida LM, Ribeiro S, Roozendaal B, Rossato JI, Salari AA, Schoemaker RG, Smit AB, Vanderschuren LJMJ, Takeuchi T, van der Veen R, Smidt MP, Vyazovskiy VV, Wiesmann M, Wierenga CJ, Williams B, Willuhn I, Wöhr M, Wolvekamp M, van der Zee EA, Genzel L. The continued need for animals to advance brain research. Neuron 2021; 109:2374-2379. [PMID: 34352213 DOI: 10.1016/j.neuron.2021.07.015] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Policymakers aim to move toward animal-free alternatives for scientific research and have introduced very strict regulations for animal research. We argue that, for neuroscience research, until viable and translational alternatives become available and the value of these alternatives has been proven, the use of animals should not be compromised.
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Affiliation(s)
| | - Roger A H Adan
- University Medical Center Utrecht, Utrecht, the Netherlands
| | - Natalia Alenina
- The Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Antonis Asiminas
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh EH8 9XD, UK; Center for Translational Neuromedicine, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Michael Bader
- The Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Tom Beckers
- KU Leuven, Leuven Brain Institute and Faculty of Psychology and Educational Sciences, Leuven, Belgium
| | - Denovan P Begg
- School of Psychology, UNSW Sydney, Sydney, NSW, Australia
| | | | | | - Gertjan van Dijk
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, the Netherlands
| | - Ulrich L M Eisel
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, the Netherlands
| | - Ype Elgersma
- Erasmus Medical Center, Rotterdam, the Netherlands
| | | | | | - Carlos P Fitzsimons
- Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands
| | - Anne-Marie van Dam
- Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands; Amsterdam University Medical Center, Free University, Amsterdam, the Netherlands
| | - Peter Gass
- Central Institute of Mental Health, University of Heidelberg, Mannheim Faculty, Mannheim, Germany
| | | | - Robbert Havekes
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, the Netherlands
| | | | - Christiane Herden
- Institute of Veterinary Pathology, Gießen, Gießen, Germany; Center of Mind Brain and Behavior (CMBB), Philipps-University of Marburg and Justus-Liebig-University Gießen, Marburg, Germany
| | - Roelof A Hut
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, the Netherlands
| | | | - Kate Jeffrey
- Institute of Behavioural Neuroscience, University College London, London WC1H 0AP, UK
| | - Daniela Jezova
- Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Andries Kalsbeek
- Netherlands Institute for Neuroscience (NIN), Amsterdam, the Netherlands; Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Maarten Kamermans
- Netherlands Institute for Neuroscience (NIN), Amsterdam, the Netherlands; Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Martien J Kas
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, the Netherlands
| | | | | | | | - Aniko Korosi
- Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands
| | - S Mechiel Korte
- Faculty of Science, Utrecht University, Utrecht, the Netherlands
| | | | | | - Kirk Leech
- European Animal Research Association, London, UK
| | - Klaus-Peter Lesch
- Division of Molecular Psychiatry, Center of Mental Health, University of Würzburg, Würzburg, Germany; Laboratory of Psychiatric Neurobiology, Institute of Molecular Medicine, Sechenov First Moscow State Medical University, Moscow, Russia; Department of Neuropsychology and Psychiatry, School for Mental Health and Neuroscience (MHeNS), Maastricht University, Maastricht, the Netherlands
| | - Heidi Lesscher
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands
| | - Paul J Lucassen
- Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands
| | - Anita Luthi
- Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Liya Ma
- Radboud University, Nijmegen, the Netherlands
| | - Anne S Mallien
- Central Institute of Mental Health, University of Heidelberg, Mannheim Faculty, Mannheim, Germany
| | - Peter Meerlo
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, the Netherlands
| | - Jorge F Mejias
- Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands
| | - Frank J Meye
- University Medical Center Utrecht, Utrecht, the Netherlands
| | | | - Joram D Mul
- Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands
| | - Umberto Olcese
- Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands
| | | | - Jocelien D A Olivier
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, the Netherlands
| | | | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands
| | - Piotr Popik
- Maj Institute of Pharmacology, Polish Academy of Sciences, Kraków 31-343, Poland
| | | | - Liset M de la Prida
- Instituto Cajal, Consejo Superior de Investigaciones Científicas, Madrid, Spain
| | - Sidarta Ribeiro
- Brain Institute, Federal University of Rio Grande do Norte, Natal, Brazil
| | | | - Janine I Rossato
- Department of Physiology, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Ali-Akbar Salari
- Salari Institute of Cognitive and Behavioral Disorders (SICBD), Karaj, Alborz, Iran
| | - Regien G Schoemaker
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, the Netherlands
| | - August B Smit
- Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | | | - Tomonori Takeuchi
- Danish Research Institute of Translational Neuroscience - DANDRITE, Nordic-EMBL Partnership for Molecular Medicine, Aarhus University, Aarhus C, Denmark
| | - Rixt van der Veen
- Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands
| | - Marten P Smidt
- Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands
| | | | | | - Corette J Wierenga
- Biology Department, Faculty of Science, Utrecht University, Utrecht, the Netherlands
| | | | - Ingo Willuhn
- Netherlands Institute for Neuroscience (NIN), Amsterdam, the Netherlands; Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Markus Wöhr
- Center of Mind Brain and Behavior (CMBB), Philipps-University of Marburg and Justus-Liebig-University Gießen, Marburg, Germany; Philipps-University of Marburg, Faculty of Psychology, Experimental and Biological Psychology, Behavioral Neuroscience, Marburg, Germany; KU Leuven, Leuven Brain Institute and Faculty of Psychology and Educational Sciences, Leuven, Belgium
| | | | - Eddy A van der Zee
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, the Netherlands
| | - Lisa Genzel
- Radboud University, Nijmegen, the Netherlands.
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21
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Dora S, Bohte SM, Pennartz CMA. Deep Gated Hebbian Predictive Coding Accounts for Emergence of Complex Neural Response Properties Along the Visual Cortical Hierarchy. Front Comput Neurosci 2021; 15:666131. [PMID: 34393744 PMCID: PMC8355371 DOI: 10.3389/fncom.2021.666131] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 06/28/2021] [Indexed: 11/13/2022] Open
Abstract
Predictive coding provides a computational paradigm for modeling perceptual processing as the construction of representations accounting for causes of sensory inputs. Here, we developed a scalable, deep network architecture for predictive coding that is trained using a gated Hebbian learning rule and mimics the feedforward and feedback connectivity of the cortex. After training on image datasets, the models formed latent representations in higher areas that allowed reconstruction of the original images. We analyzed low- and high-level properties such as orientation selectivity, object selectivity and sparseness of neuronal populations in the model. As reported experimentally, image selectivity increased systematically across ascending areas in the model hierarchy. Depending on the strength of regularization factors, sparseness also increased from lower to higher areas. The results suggest a rationale as to why experimental results on sparseness across the cortical hierarchy have been inconsistent. Finally, representations for different object classes became more distinguishable from lower to higher areas. Thus, deep neural networks trained using a gated Hebbian formulation of predictive coding can reproduce several properties associated with neuronal responses along the visual cortical hierarchy.
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Affiliation(s)
- Shirin Dora
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands.,Intelligent Systems Research Centre, Ulster University, Londonderry, United Kingdom
| | - Sander M Bohte
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands.,Machine Learning Group, Centre of Mathematics and Computer Science, Amsterdam, Netherlands
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
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22
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Fiorilli J, Bos JJ, Grande X, Lim J, Düzel E, Pennartz CMA. Reconciling the object and spatial processing views of the perirhinal cortex through task-relevant unitization. Hippocampus 2021; 31:737-755. [PMID: 33523577 PMCID: PMC8359385 DOI: 10.1002/hipo.23304] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 11/27/2020] [Accepted: 01/02/2021] [Indexed: 12/21/2022]
Abstract
The perirhinal cortex is situated on the border between sensory association cortex and the hippocampal formation. It serves an important function as a transition area between the sensory neocortex and the medial temporal lobe. While the perirhinal cortex has traditionally been associated with object coding and the "what" pathway of the temporal lobe, current evidence suggests a broader function of the perirhinal cortex in solving feature ambiguity and processing complex stimuli. Besides fulfilling functions in object coding, recent neurophysiological findings in freely moving rodents indicate that the perirhinal cortex also contributes to spatial and contextual processing beyond individual sensory modalities. Here, we address how these two opposing views on perirhinal cortex-the object-centered and spatial-contextual processing hypotheses-may be reconciled. The perirhinal cortex is consistently recruited when different features can be merged perceptually or conceptually into a single entity. Features that are unitized in these entities include object information from multiple sensory domains, reward associations, semantic features and spatial/contextual associations. We propose that the same perirhinal network circuits can be flexibly deployed for multiple cognitive functions, such that the perirhinal cortex performs similar unitization operations on different types of information, depending on behavioral demands and ranging from the object-related domain to spatial, contextual and semantic information.
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Affiliation(s)
- Julien Fiorilli
- Cognitive and Systems Neuroscience Group, SILS Center for NeuroscienceUniversity of AmsterdamAmsterdamThe Netherlands
- Research Priority Area Brain and CognitionUniversity of AmsterdamAmsterdamThe Netherlands
| | - Jeroen J. Bos
- Cognitive and Systems Neuroscience Group, SILS Center for NeuroscienceUniversity of AmsterdamAmsterdamThe Netherlands
- Research Priority Area Brain and CognitionUniversity of AmsterdamAmsterdamThe Netherlands
- Donders Institute for Brain, Cognition and BehaviorRadboud University and Radboud University Medical CentreNijmegenThe Netherlands
| | - Xenia Grande
- Institute of Cognitive Neurology and Dementia ResearchOtto‐von‐Guericke University MagdeburgMagdeburgGermany
- German Center for Neurodegenerative DiseasesMagdeburgGermany
| | - Judith Lim
- Cognitive and Systems Neuroscience Group, SILS Center for NeuroscienceUniversity of AmsterdamAmsterdamThe Netherlands
- Research Priority Area Brain and CognitionUniversity of AmsterdamAmsterdamThe Netherlands
| | - Emrah Düzel
- Institute of Cognitive Neurology and Dementia ResearchOtto‐von‐Guericke University MagdeburgMagdeburgGermany
- German Center for Neurodegenerative DiseasesMagdeburgGermany
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
| | - Cyriel M. A. Pennartz
- Cognitive and Systems Neuroscience Group, SILS Center for NeuroscienceUniversity of AmsterdamAmsterdamThe Netherlands
- Research Priority Area Brain and CognitionUniversity of AmsterdamAmsterdamThe Netherlands
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23
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Meijer GT, Marchesi P, Mejias JF, Montijn JS, Lansink CS, Pennartz CMA. Neural Correlates of Multisensory Detection Behavior: Comparison of Primary and Higher-Order Visual Cortex. Cell Rep 2021; 31:107636. [PMID: 32402272 DOI: 10.1016/j.celrep.2020.107636] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 01/10/2020] [Accepted: 04/21/2020] [Indexed: 01/16/2023] Open
Abstract
We act upon stimuli in our surrounding environment by gathering the multisensory information they convey and by integrating this information to decide on a behavioral action. We hypothesized that the anterolateral secondary visual cortex (area AL) of the mouse brain may serve as a hub for sensorimotor transformation of audiovisual information. We imaged neuronal activity in primary visual cortex (V1) and AL of the mouse during a detection task using visual, auditory, and audiovisual stimuli. We found that AL neurons were more sensitive to weak uni- and multisensory stimuli compared to V1. Depending on contrast, different subsets of AL and V1 neurons showed cross-modal modulation of visual responses. During audiovisual stimulation, AL neurons showed stronger differentiation of behaviorally reported versus unreported stimuli compared to V1, whereas V1 showed this distinction during unisensory visual stimulation. Thus, neural population activity in area AL correlates more closely with multisensory detection behavior than V1.
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Affiliation(s)
- Guido T Meijer
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands
| | - Pietro Marchesi
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands
| | - Jorge F Mejias
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands
| | - Jorrit S Montijn
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands
| | - Carien S Lansink
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, 1098 XH Amsterdam, the Netherlands.
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, 1098 XH Amsterdam, the Netherlands.
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24
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Arnts H, van Erp WS, Boon LI, Bosman CA, Admiraal MM, Schrantee A, Pennartz CMA, Schuurman R, Stam CJ, van Rootselaar AF, Hillebrand A, van den Munckhof P. Awakening after a sleeping pill: Restoring functional brain networks after severe brain injury. Cortex 2020; 132:135-146. [PMID: 32979847 DOI: 10.1016/j.cortex.2020.08.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 02/09/2020] [Accepted: 08/11/2020] [Indexed: 12/11/2022]
Abstract
Some patients with severe brain injury show short-term neurological improvements, such as recovery of consciousness, motor function, or speech after administering zolpidem, a GABA receptor agonist. The working mechanism of this paradoxical phenomenon remains unknown. In this study, we used electroencephalography and magnetoencephalography to investigate a spectacular zolpidem-induced awakening, including the recovery of functional communication and the ability to walk in a patient with severe hypoxic-ischemic brain injury. We show that cognitive deficits, speech loss, and motor impairments after severe brain injury are associated with stronger beta band connectivity throughout the brain and suggest that neurological recovery after zolpidem occurs with the restoration of beta band connectivity. This exploratory work proposes an essential role for beta rhythms in goal-directed behavior and cognition. It advocates further fundamental and clinical research on the role of increased beta band connectivity in the development of neurological deficits after severe brain injury.
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Affiliation(s)
- Hisse Arnts
- Amsterdam UMC, University of Amsterdam, Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - Willemijn S van Erp
- Department of Primary and Community Care, Centre for Family Medicine, Geriatric Care and Public Health, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Lennard I Boon
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Conrado A Bosman
- Cognitive and Systems Neuroscience Group, Swammerdam Institute, Center for Neuroscience, University of Amsterdam, Amsterdam, the Netherlands
| | - Marjolein M Admiraal
- Amsterdam UMC, University of Amsterdam, Department of Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Anouk Schrantee
- Amsterdam UMC, University of Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute, Center for Neuroscience, University of Amsterdam, Amsterdam, the Netherlands
| | - Rick Schuurman
- Amsterdam UMC, University of Amsterdam, Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Anne-Fleur van Rootselaar
- Amsterdam UMC, University of Amsterdam, Department of Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Arjan Hillebrand
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Pepijn van den Munckhof
- Amsterdam UMC, University of Amsterdam, Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam, the Netherlands
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25
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Bos JJ, Vinck M, Marchesi P, Keestra A, van Mourik-Donga LA, Jackson JC, Verschure PFMJ, Pennartz CMA. Multiplexing of Information about Self and Others in Hippocampal Ensembles. Cell Rep 2019; 29:3859-3871.e6. [PMID: 31851919 DOI: 10.1016/j.celrep.2019.11.057] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 10/03/2019] [Accepted: 11/13/2019] [Indexed: 10/25/2022] Open
Abstract
In addition to coding a subject's location in space, the hippocampus has been suggested to code social information, including the spatial position of conspecifics. "Social place cells" have been reported for tasks in which an observer mimics the behavior of a demonstrator. We examine whether rat hippocampal neurons may encode the behavior of a minirobot, but without requiring the animal to mimic it. Rather than finding social place cells, we observe that robot behavioral patterns modulate place fields coding animal position. This modulation may be confounded by correlations between robot movement and changes in the animal's position. Although rat position indeed significantly predicts robot behavior, we find that hippocampal ensembles code additional information about robot movement patterns. Fast-spiking interneurons are particularly informative about robot position and global behavior. In conclusion, when the animal's own behavior is conditional on external agents, the hippocampus multiplexes information about self and others.
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Affiliation(s)
- Jeroen J Bos
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands
| | - Martin Vinck
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands; Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society, Deutschordenstraße 46, 60528 Frankfurt, Germany
| | - Pietro Marchesi
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands
| | - Amos Keestra
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands
| | - Laura A van Mourik-Donga
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands
| | - Jadin C Jackson
- Medtronic, 7000 Central Avenue NE, Minneapolis, MN 55432, USA
| | - Paul F M J Verschure
- Institute for Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands.
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26
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Rusu SI, Pennartz CMA. Learning, memory and consolidation mechanisms for behavioral control in hierarchically organized cortico-basal ganglia systems. Hippocampus 2019; 30:73-98. [PMID: 31617622 PMCID: PMC6972576 DOI: 10.1002/hipo.23167] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Revised: 09/09/2019] [Accepted: 09/11/2019] [Indexed: 01/05/2023]
Abstract
This article aims to provide a synthesis on the question how brain structures cooperate to accomplish hierarchically organized behaviors, characterized by low‐level, habitual routines nested in larger sequences of planned, goal‐directed behavior. The functioning of a connected set of brain structures—prefrontal cortex, hippocampus, striatum, and dopaminergic mesencephalon—is reviewed in relation to two important distinctions: (a) goal‐directed as opposed to habitual behavior and (b) model‐based and model‐free learning. Recent evidence indicates that the orbitomedial prefrontal cortices not only subserve goal‐directed behavior and model‐based learning, but also code the “landscape” (task space) of behaviorally relevant variables. While the hippocampus stands out for its role in coding and memorizing world state representations, it is argued to function in model‐based learning but is not required for coding of action–outcome contingencies, illustrating that goal‐directed behavior is not congruent with model‐based learning. While the dorsolateral and dorsomedial striatum largely conform to the dichotomy between habitual versus goal‐directed behavior, ventral striatal functions go beyond this distinction. Next, we contextualize findings on coding of reward‐prediction errors by ventral tegmental dopamine neurons to suggest a broader role of mesencephalic dopamine cells, viz. in behavioral reactivity and signaling unexpected sensory changes. We hypothesize that goal‐directed behavior is hierarchically organized in interconnected cortico‐basal ganglia loops, where a limbic‐affective prefrontal‐ventral striatal loop controls action selection in a dorsomedial prefrontal–striatal loop, which in turn regulates activity in sensorimotor‐dorsolateral striatal circuits. This structure for behavioral organization requires alignment with mechanisms for memory formation and consolidation. We propose that frontal corticothalamic circuits form a high‐level loop for memory processing that initiates and temporally organizes nested activities in lower‐level loops, including the hippocampus and the ripple‐associated replay it generates. The evidence on hierarchically organized behavior converges with that on consolidation mechanisms in suggesting a frontal‐to‐caudal directionality in processing control.
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Affiliation(s)
- Silviu I Rusu
- Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
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27
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Olcese U, Bos JJ, Vinck M, Pennartz CMA. Functional determinants of enhanced and depressed interareal information flow in nonrapid eye movement sleep between neuronal ensembles in rat cortex and hippocampus. Sleep 2019; 41:5078618. [PMID: 30423179 DOI: 10.1093/sleep/zsy167] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Indexed: 11/12/2022] Open
Abstract
Compared with wakefulness, neuronal activity during nonrapid eye movement (NREM) sleep is characterized by a decreased ability to integrate information, but also by the reemergence of task-related information patterns. To investigate the mechanisms underlying these seemingly opposing phenomena, we measured directed information flow by computing transfer entropy between neuronal spiking activity in three cortical regions and the hippocampus of rats across brain states. State-dependent information flow was jointly determined by the anatomical distance between neurons and by their functional specialization. We distinguished two regimes, operating at short and long time scales, respectively. From wakefulness to NREM sleep, transfer entropy at short time scales increased for interareal connections between neurons showing behavioral task correlates. Conversely, transfer entropy at long time scales became stronger between nontask modulated neurons and weaker between task-modulated neurons. These results may explain how, during NREM sleep, a global interareal disconnection is compatible with highly specific task-related information transfer.
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Affiliation(s)
- Umberto Olcese
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Jeroen J Bos
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Martin Vinck
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Ernst Strungmann Institute for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
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28
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Pennartz CMA, Farisco M, Evers K. Indicators and Criteria of Consciousness in Animals and Intelligent Machines: An Inside-Out Approach. Front Syst Neurosci 2019; 13:25. [PMID: 31379521 PMCID: PMC6660257 DOI: 10.3389/fnsys.2019.00025] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Accepted: 06/24/2019] [Indexed: 01/02/2023] Open
Abstract
In today's society, it becomes increasingly important to assess which non-human and non-verbal beings possess consciousness. This review article aims to delineate criteria for consciousness especially in animals, while also taking into account intelligent artifacts. First, we circumscribe what we mean with "consciousness" and describe key features of subjective experience: qualitative richness, situatedness, intentionality and interpretation, integration and the combination of dynamic and stabilizing properties. We argue that consciousness has a biological function, which is to present the subject with a multimodal, situational survey of the surrounding world and body, subserving complex decision-making and goal-directed behavior. This survey reflects the brain's capacity for internal modeling of external events underlying changes in sensory state. Next, we follow an inside-out approach: how can the features of conscious experience, correlating to mechanisms inside the brain, be logically coupled to externally observable ("outside") properties? Instead of proposing criteria that would each define a "hard" threshold for consciousness, we outline six indicators: (i) goal-directed behavior and model-based learning; (ii) anatomic and physiological substrates for generating integrative multimodal representations; (iii) psychometrics and meta-cognition; (iv) episodic memory; (v) susceptibility to illusions and multistable perception; and (vi) specific visuospatial behaviors. Rather than emphasizing a particular indicator as being decisive, we propose that the consistency amongst these indicators can serve to assess consciousness in particular species. The integration of scores on the various indicators yields an overall, graded criterion for consciousness, somewhat comparable to the Glasgow Coma Scale for unresponsive patients. When considering theoretically derived measures of consciousness, it is argued that their validity should not be assessed on the basis of a single quantifiable measure, but requires cross-examination across multiple pieces of evidence, including the indicators proposed here. Current intelligent machines, including deep learning neural networks (DLNNs) and agile robots, are not indicated to be conscious yet. Instead of assessing machine consciousness by a brief Turing-type of test, evidence for it may gradually accumulate when we study machines ethologically and across time, considering multiple behaviors that require flexibility, improvisation, spontaneous problem-solving and the situational conspectus typically associated with conscious experience.
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Affiliation(s)
- Cyriel M. A. Pennartz
- Department of Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
- Research Priority Area, Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Michele Farisco
- Centre for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden
- Biogem, Biology and Molecular Genetics Institute, Ariano Irpino, Italy
| | - Kathinka Evers
- Centre for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden
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29
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Amunts K, Knoll AC, Lippert T, Pennartz CMA, Ryvlin P, Destexhe A, Jirsa VK, D’Angelo E, Bjaalie JG. The Human Brain Project-Synergy between neuroscience, computing, informatics, and brain-inspired technologies. PLoS Biol 2019; 17:e3000344. [PMID: 31260438 PMCID: PMC6625714 DOI: 10.1371/journal.pbio.3000344] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Revised: 07/12/2019] [Indexed: 02/03/2023] Open
Abstract
The Human Brain Project (HBP) is a European flagship project with a 10-year horizon aiming to understand the human brain and to translate neuroscience knowledge into medicine and technology. To achieve such aims, the HBP explores the multilevel complexity of the brain in space and time; transfers the acquired knowledge to brain-derived applications in health, computing, and technology; and provides shared and open computing tools and data through the HBP European brain research infrastructure. We discuss how the HBP creates a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating perspectives on societal benefits. This Community Page article presents the Human Brain Project; a European Flagship project with a ten-year horizon aiming to understand the human brain and translate neuroscience knowledge into medicine and technology.
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Affiliation(s)
- Katrin Amunts
- Institute for Neuroscience and Medicine (INM-1), Forschungszentrum Jülich, Germany
- C. and O. Vogt Institute for Brain Research, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- * E-mail:
| | - Alois C. Knoll
- Institut für Informatik VI, Technische Universität München, Garching bei München, Germany
| | - Thomas Lippert
- Jülich Supercomputing Centre, Institute for Advanced Simulation, Forschungszentrum Jülich, Germany
| | - Cyriel M. A. Pennartz
- Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, the Netherlands
| | - Philippe Ryvlin
- Department of Clinical Neurosciences, Centre Hospitalo-Universitaire Vaudois (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Alain Destexhe
- Unité de Neurosciences, Information & Complexité (UNIC), Centre National de la Recherche Scientifique (CNRS), Gif-sur-Yvette, France
| | - Viktor K. Jirsa
- Institut de Neurosciences des Systèmes, Inserm UMR1106, Aix-Marseille Université, Faculté de Médecine, Marseille, France
| | - Egidio D’Angelo
- Department of Brain and Behavioral Science, Unit of Neurophysiology, University of Pavia, Pavia, Italy
| | - Jan G. Bjaalie
- Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
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30
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Meijer GT, Mertens PEC, Pennartz CMA, Olcese U, Lansink CS. The circuit architecture of cortical multisensory processing: Distinct functions jointly operating within a common anatomical network. Prog Neurobiol 2019; 174:1-15. [PMID: 30677428 DOI: 10.1016/j.pneurobio.2019.01.004] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 12/21/2018] [Accepted: 01/21/2019] [Indexed: 12/16/2022]
Abstract
Our perceptual systems continuously process sensory inputs from different modalities and organize these streams of information such that our subjective representation of the outside world is a unified experience. By doing so, they also enable further cognitive processing and behavioral action. While cortical multisensory processing has been extensively investigated in terms of psychophysics and mesoscale neural correlates, an in depth understanding of the underlying circuit-level mechanisms is lacking. Previous studies on circuit-level mechanisms of multisensory processing have predominantly focused on cue integration, i.e. the mechanism by which sensory features from different modalities are combined to yield more reliable stimulus estimates than those obtained by using single sensory modalities. In this review, we expand the framework on the circuit-level mechanisms of cortical multisensory processing by highlighting that multisensory processing is a family of functions - rather than a single operation - which involves not only the integration but also the segregation of modalities. In addition, multisensory processing not only depends on stimulus features, but also on cognitive resources, such as attention and memory, as well as behavioral context, to determine the behavioral outcome. We focus on rodent models as a powerful instrument to study the circuit-level bases of multisensory processes, because they enable combining cell-type-specific recording and interventional techniques with complex behavioral paradigms. We conclude that distinct multisensory processes share overlapping anatomical substrates, are implemented by diverse neuronal micro-circuitries that operate in parallel, and are flexibly recruited based on factors such as stimulus features and behavioral constraints.
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Affiliation(s)
- Guido T Meijer
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, the Netherlands.
| | - Paul E C Mertens
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, the Netherlands.
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Science Park 904, 1098XH Amsterdam, the Netherlands.
| | - Umberto Olcese
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Science Park 904, 1098XH Amsterdam, the Netherlands.
| | - Carien S Lansink
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098XH Amsterdam, the Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Science Park 904, 1098XH Amsterdam, the Netherlands.
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Olcese U, Oude Lohuis MN, Pennartz CMA. Sensory Processing Across Conscious and Nonconscious Brain States: From Single Neurons to Distributed Networks for Inferential Representation. Front Syst Neurosci 2018; 12:49. [PMID: 30364373 PMCID: PMC6193318 DOI: 10.3389/fnsys.2018.00049] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2018] [Accepted: 09/25/2018] [Indexed: 11/29/2022] Open
Abstract
Neuronal activity is markedly different across brain states: it varies from desynchronized activity during wakefulness to the synchronous alternation between active and silent states characteristic of deep sleep. Surprisingly, limited attention has been paid to investigating how brain states affect sensory processing. While it was long assumed that the brain was mostly disconnected from external stimuli during sleep, an increasing number of studies indicates that sensory stimuli continue to be processed across all brain states-albeit differently. In this review article, we first discuss what constitutes a brain state. We argue that-next to global, behavioral states such as wakefulness and sleep-there is a concomitant need to distinguish bouts of oscillatory dynamics with specific global/local activity patterns and lasting for a few hundreds of milliseconds, as these can lead to the same sensory stimulus being either perceived or not. We define these short-lasting bouts as micro-states. We proceed to characterize how sensory-evoked neural responses vary between conscious and nonconscious states. We focus on two complementary aspects: neuronal ensembles and inter-areal communication. First, we review which features of ensemble activity are conducive to perception, and how these features vary across brain states. Properties such as heterogeneity, sparsity and synchronicity in neuronal ensembles will especially be considered as essential correlates of conscious processing. Second, we discuss how inter-areal communication varies across brain states and how this may affect brain operations and sensory processing. Finally, we discuss predictive coding (PC) and the concept of multi-level representations as a key framework for understanding conscious sensory processing. In this framework the brain implements conscious representations as inferences about world states across multiple representational levels. In this representational hierarchy, low-level inference may be carried out nonconsciously, whereas high levels integrate across different sensory modalities and larger spatial scales, correlating with conscious processing. This inferential framework is used to interpret several cellular and population-level findings in the context of brain states, and we briefly compare its implications to two other theories of consciousness. In conclusion, this review article, provides foundations to guide future studies aiming to uncover the mechanisms of sensory processing and perception across brain states.
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Affiliation(s)
- Umberto Olcese
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Matthijs N. Oude Lohuis
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Cyriel M. A. Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
- Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
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Meijer GT, Pie JL, Dolman TL, Pennartz CMA, Lansink CS. Audiovisual Integration Enhances Stimulus Detection Performance in Mice. Front Behav Neurosci 2018; 12:231. [PMID: 30337861 PMCID: PMC6180166 DOI: 10.3389/fnbeh.2018.00231] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Accepted: 09/14/2018] [Indexed: 11/13/2022] Open
Abstract
The detection of objects in the external world improves when humans and animals integrate object features of multiple sensory modalities. Behavioral and neuronal mechanisms underlying multisensory stimulus detection are poorly understood, mainly because they have not been investigated with suitable behavioral paradigms. Such behavioral paradigms should (i) elicit a robust multisensory gain, (ii) incorporate systematic calibration of stimulus amplitude to the sensory capacities of the individual subject, (iii) yield a high trial count, and (iv) be easily compatible with a large variety of neurophysiological recording techniques. We developed an audiovisual stimulus detection task for head-fixed mice which meets all of these critical behavioral constraints. Behavioral data obtained with this task indicated a robust increase in detection performance of multisensory stimuli compared with unisensory cues, which was maximal when both stimulus constituents were presented at threshold intensity. The multisensory behavioral effect was associated with a change in the perceptual performance which consisted of two components. First, the visual and auditory perceptual systems increased their sensitivity meaning that low intensity stimuli were more often detected. Second, enhanced acuity enabled the systems to better classify whether there was a stimulus or not. Fitting our data to signal detection models revealed that the multisensory gain was more likely to be achieved by integration of sensory signals rather than by stimulus redundancy or competition. This validated behavioral paradigm can be exploited to reliably investigate the neuronal correlates of multisensory stimulus detection at the level of single neurons, microcircuits, and larger perceptual systems.
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Affiliation(s)
- Guido T. Meijer
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
| | - Jean L. Pie
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
| | - Thomas L. Dolman
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
| | - Cyriel M. A. Pennartz
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Carien S. Lansink
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
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Stoianov IP, Pennartz CMA, Lansink CS, Pezzulo G. Model-based spatial navigation in the hippocampus-ventral striatum circuit: A computational analysis. PLoS Comput Biol 2018; 14:e1006316. [PMID: 30222746 PMCID: PMC6160242 DOI: 10.1371/journal.pcbi.1006316] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Revised: 09/27/2018] [Accepted: 06/20/2018] [Indexed: 12/26/2022] Open
Abstract
While the neurobiology of simple and habitual choices is relatively well known, our current understanding of goal-directed choices and planning in the brain is still limited. Theoretical work suggests that goal-directed computations can be productively associated to model-based (reinforcement learning) computations, yet a detailed mapping between computational processes and neuronal circuits remains to be fully established. Here we report a computational analysis that aligns Bayesian nonparametrics and model-based reinforcement learning (MB-RL) to the functioning of the hippocampus (HC) and the ventral striatum (vStr)-a neuronal circuit that increasingly recognized to be an appropriate model system to understand goal-directed (spatial) decisions and planning mechanisms in the brain. We test the MB-RL agent in a contextual conditioning task that depends on intact hippocampus and ventral striatal (shell) function and show that it solves the task while showing key behavioral and neuronal signatures of the HC-vStr circuit. Our simulations also explore the benefits of biological forms of look-ahead prediction (forward sweeps) during both learning and control. This article thus contributes to fill the gap between our current understanding of computational algorithms and biological realizations of (model-based) reinforcement learning.
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Affiliation(s)
- Ivilin Peev Stoianov
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Cyriel M. A. Pennartz
- University of Amsterdam, Swammerdam Institute for Life Sciences–Center for Neuroscience Amsterdam, The Netherlands
| | - Carien S. Lansink
- University of Amsterdam, Swammerdam Institute for Life Sciences–Center for Neuroscience Amsterdam, The Netherlands
| | - Giovani Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
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Arbab T, Pennartz CMA, Battaglia FP. Impaired hippocampal representation of place in the Fmr1-knockout mouse model of fragile X syndrome. Sci Rep 2018; 8:8889. [PMID: 29892074 PMCID: PMC5995880 DOI: 10.1038/s41598-018-26853-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Accepted: 04/19/2018] [Indexed: 12/26/2022] Open
Abstract
Fragile X syndrome (FXS) is an X-chromosome linked intellectual disability and the most common known inherited single gene cause of autism spectrum disorder (ASD). Building upon demonstrated deficits in neuronal plasticity and spatial memory in FXS, we investigated how spatial information processing is affected in vivo in an FXS mouse model (Fmr1-KO). Healthy hippocampal neurons (so-called place cells) exhibit place-related activity during spatial exploration, and their firing fields tend to remain stable over time. In contrast, we find impaired stability and reduced specificity of Fmr1-KO spatial representations. This is a potential biomarker for the cognitive dysfunction observed in FXS, informative on the ability to integrate sensory information into an abstract representation and successfully retain this conceptual memory. Our results provide key insight into the biological mechanisms underlying cognitive disabilities in FXS and ASD, paving the way for a targeted approach to remedy these.
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Affiliation(s)
- Tara Arbab
- Cognitive and Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, Faculty of Science, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands. .,Netherlands Institute for Neuroscience, Institute of the Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105 BA, Amsterdam, The Netherlands. .,Department of Psychiatry, Academic Medical Center, University of Amsterdam, Postal Box 22660, 1100 DD, Amsterdam, The Netherlands.
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, Faculty of Science, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands.,Research Priority Program Brain and Cognition, University of Amsterdam, Postal Box 94216, 1090 GE, Amsterdam, The Netherlands
| | - Francesco P Battaglia
- Cognitive and Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, Faculty of Science, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands.,Donders Institute for Brain, Cognition, and Behaviour, Radboud Universiteit Nijmegen, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands
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Bjerke IE, Øvsthus M, Papp EA, Yates SC, Silvestri L, Fiorilli J, Pennartz CMA, Pavone FS, Puchades MA, Leergaard TB, Bjaalie JG. Data integration through brain atlasing: Human Brain Project tools and strategies. Eur Psychiatry 2018. [PMID: 29519589 DOI: 10.1016/j.eurpsy.2018.02.004] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
The Human Brain Project (HBP), an EU Flagship Initiative, is currently building an infrastructure that will allow integration of large amounts of heterogeneous neuroscience data. The ultimate goal of the project is to develop a unified multi-level understanding of the brain and its diseases, and beyond this to emulate the computational capabilities of the brain. Reference atlases of the brain are one of the key components in this infrastructure. Based on a new generation of three-dimensional (3D) reference atlases, new solutions for analyzing and integrating brain data are being developed. HBP will build services for spatial query and analysis of brain data comparable to current online services for geospatial data. The services will provide interactive access to a wide range of data types that have information about anatomical location tied to them. The 3D volumetric nature of the brain, however, introduces a new level of complexity that requires a range of tools for making use of and interacting with the atlases. With such new tools, neuroscience research groups will be able to connect their data to atlas space, share their data through online data systems, and search and find other relevant data through the same systems. This new approach partly replaces earlier attempts to organize research data based only on a set of semantic terminologies describing the brain and its subdivisions.
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Affiliation(s)
- Ingvild E Bjerke
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Norway
| | - Martin Øvsthus
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Norway
| | - Eszter A Papp
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Norway
| | - Sharon C Yates
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Norway
| | - Ludovico Silvestri
- European Laboratory for Non-linear Spectroscopy, Sesto Fiorentino, Italy
| | - Julien Fiorilli
- Cognitive and Systems Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, The Netherlands
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, The Netherlands
| | - Francesco S Pavone
- European Laboratory for Non-linear Spectroscopy, Sesto Fiorentino, Italy
| | - Maja A Puchades
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Norway
| | - Trygve B Leergaard
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Norway
| | - Jan G Bjaalie
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Norway.
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Arbab T, Battaglia FP, Pennartz CMA, Bosman CA. Abnormal hippocampal theta and gamma hypersynchrony produces network and spike timing disturbances in the Fmr1-KO mouse model of Fragile X syndrome. Neurobiol Dis 2018; 114:65-73. [PMID: 29486296 DOI: 10.1016/j.nbd.2018.02.011] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Revised: 02/12/2018] [Accepted: 02/21/2018] [Indexed: 01/02/2023] Open
Abstract
Neuronal networks can synchronize their activity through excitatory and inhibitory connections, which is conducive to synaptic plasticity. This synchronization is reflected in rhythmic fluctuations of the extracellular field. In the hippocampus, theta and gamma band LFP oscillations are a hallmark of the processing of spatial information and memory. Fragile X syndrome (FXS) is an intellectual disability and the most common genetic cause of autism spectrum disorder (Belmonte and Bourgeron, 2006). Here, we investigated how neuronal network synchronization in the mouse hippocampus is compromised by the Fmr1 mutation that causes FXS (Santos et al., 2014), relating recently observed single-cell level impairments (Arbab et al., 2017) to neuronal network aberrations. We implanted tetrodes in hippocampus of freely moving Fmr1-KO and littermate wildtype (WT) mice (Mientjes et al., 2006), to record spike trains from multiple, isolated neurons as well as LFPs in a spatial exploration paradigm. Compared to wild type mice, Fmr1-KO mice displayed greater power of hippocampal theta oscillations, and higher coherence in the slow gamma band. Additionally, spike trains of Fmr1-KO interneurons show decreased spike-count correlations and they are hypersynchronized with theta and slow gamma oscillations. The hypersynchronization of Fmr1-KO oscillations and spike timing reflects functional deficits in local networks. This network hypersynchronization pathologically decreases the heterogeneity of spike-LFP phase coupling, compromising information processing within the hippocampal circuit. These findings may reflect a pathophysiological mechanism explaining cognitive impairments in FXS and autism, in which there is anomalous processing of social and environmental cues and associated deficits in memory and cognition.
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Affiliation(s)
- Tara Arbab
- Cognitive & Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, Faculty of Science, University of Amsterdam, Sciencepark 904, 1098 XH Amsterdam, The Netherlands; Netherlands Institute for Neuroscience, Institute of the Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105 BA Amsterdam, The Netherlands; Department of Psychiatry, Academic Medical Center, University of Amsterdam, Postal Box 22660, 1100 DD Amsterdam, The Netherlands.
| | - Francesco P Battaglia
- Cognitive & Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, Faculty of Science, University of Amsterdam, Sciencepark 904, 1098 XH Amsterdam, The Netherlands; Donders Institute for Brain, Cognition, and Behaviour, Radboud Universiteit Nijmegen, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands
| | - Cyriel M A Pennartz
- Cognitive & Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, Faculty of Science, University of Amsterdam, Sciencepark 904, 1098 XH Amsterdam, The Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Postal Box 94216, 1090 GE Amsterdam, The Netherlands
| | - Conrado A Bosman
- Cognitive & Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, Faculty of Science, University of Amsterdam, Sciencepark 904, 1098 XH Amsterdam, The Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Postal Box 94216, 1090 GE Amsterdam, The Netherlands.
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Pennartz CMA. Consciousness, Representation, Action: The Importance of Being Goal-Directed. Trends Cogn Sci 2017; 22:137-153. [PMID: 29233478 DOI: 10.1016/j.tics.2017.10.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Revised: 10/26/2017] [Accepted: 10/30/2017] [Indexed: 12/14/2022]
Abstract
Recent years have witnessed fierce debates on the dependence of consciousness on interactions between a subject and the environment. Reviewing neuroscientific, computational, and clinical evidence, I will address three questions. First, does conscious experience necessarily depend on acute interactions between a subject and the environment? Second, does it depend on specific perception-action loops in the longer run? Third, which types of action does consciousness cohere with, if not with all of them? I argue that conscious contents do not necessarily depend on acute or long-term brain-environment interactions. Instead, consciousness is proposed to be specifically associated with, and subserve, deliberate, goal-directed behavior (GDB). Brain systems implied in conscious representation are highly connected to, but distinct from, neural substrates mediating GDB and declarative memory.
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Affiliation(s)
- Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, The Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, The Netherlands.
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Bos JJ, Vinck M, van Mourik-Donga LA, Jackson JC, Witter MP, Pennartz CMA. Perirhinal firing patterns are sustained across large spatial segments of the task environment. Nat Commun 2017; 8:15602. [PMID: 28548084 PMCID: PMC5458559 DOI: 10.1038/ncomms15602] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Accepted: 03/27/2017] [Indexed: 11/16/2022] Open
Abstract
Spatial navigation and memory depend on the neural coding of an organism's location. Fine-grained coding of location is thought to depend on the hippocampus. Likewise, animals benefit from knowledge parsing their environment into larger spatial segments, which are relevant for task performance. Here we investigate how such knowledge may be coded, and whether this occurs in structures in the temporal lobe, supplying cortical inputs to the hippocampus. We found that neurons in the perirhinal cortex of rats generate sustained firing patterns that discriminate large segments of the task environment. This contrasted to transient firing in hippocampus and sensory neocortex. These spatially extended patterns were not explained by task variables or temporally discrete sensory stimuli. Previously it has been suggested that the perirhinal cortex is part of a pathway processing object, but not spatial information. Our results indicate a greater complexity of neural coding than captured by this dichotomy.
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Affiliation(s)
- Jeroen J. Bos
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Martin Vinck
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society, Deutschordenstraße 46, 60528 Frankfurt, Germany
| | - Laura A. van Mourik-Donga
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Jadin C. Jackson
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- Medtronic, 7000 Central Avenue NE, Minneapolis, Minnesota 55432, USA
| | - Menno P. Witter
- Kavli Institute for Systems Neuroscience, Centre for Neural Computation, Norwegian University of Science and Technology, DMF, NTNU PO Box 8905, NO-7491 Trondheim, Norway
| | - Cyriel M. A. Pennartz
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
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Malkki HAI, Mertens PEC, Lankelma JV, Vinck M, van Schalkwijk FJ, van Mourik-Donga LB, Battaglia FP, Mahlke C, Kuhl D, Pennartz CMA. Effects of Arc/Arg3.1 gene deletion on rhythmic synchronization of hippocampal CA1 neurons during locomotor activity and sleep. Neurobiol Learn Mem 2016; 131:155-65. [PMID: 27038743 DOI: 10.1016/j.nlm.2016.03.021] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Revised: 02/23/2016] [Accepted: 03/28/2016] [Indexed: 02/07/2023]
Abstract
The activity-regulated cytoskeletal-associated protein/activity regulated gene (Arc/Arg3.1) is crucial for long-term synaptic plasticity and memory formation. However, the neurophysiological substrates of memory deficits occurring in the absence of Arc/Arg3.1 are unknown. We compared hippocampal CA1 single-unit and local field potential (LFP) activity in Arc/Arg3.1 knockout and wild-type mice during track running and flanking sleep periods. Locomotor activity, basic firing and spatial coding properties of CA1 cells in knockout mice were not different from wild-type mice. During active behavior, however, knockout animals showed a significantly shifted balance in LFP power, with a relative loss in high-frequency (beta-2 and gamma) bands compared to low-frequency bands. Moreover, during track-running, knockout mice showed a decrease in phase locking of spiking activity to LFP oscillations in theta, beta and gamma bands. Sleep architecture in knockout mice was not grossly abnormal. Sharp-wave ripples, which have been associated with memory consolidation and replay, showed only minor differences in dynamics and amplitude. Altogether, these findings suggest that Arc/Arg3.1 effects on memory formation are not only manifested at the level of molecular pathways regulating synaptic plasticity, but also at the systems level. The disrupted power balance in theta, beta and gamma rhythmicity and concomitant loss of spike-field phase locking may affect memory encoding during initial storage and memory consolidation stages.
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Affiliation(s)
- Hemi A I Malkki
- Cognitive & Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, University of Amsterdam, The Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Postal Box 94216, 1090 GE Amsterdam, The Netherlands
| | - Paul E C Mertens
- Cognitive & Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, University of Amsterdam, The Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Postal Box 94216, 1090 GE Amsterdam, The Netherlands
| | - Jan V Lankelma
- Cognitive & Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, University of Amsterdam, The Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Postal Box 94216, 1090 GE Amsterdam, The Netherlands
| | - Martin Vinck
- Cognitive & Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, University of Amsterdam, The Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Postal Box 94216, 1090 GE Amsterdam, The Netherlands
| | - Frank J van Schalkwijk
- Cognitive & Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, University of Amsterdam, The Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Postal Box 94216, 1090 GE Amsterdam, The Netherlands
| | - Laura B van Mourik-Donga
- Cognitive & Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, University of Amsterdam, The Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Postal Box 94216, 1090 GE Amsterdam, The Netherlands
| | - Francesco P Battaglia
- Cognitive & Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, University of Amsterdam, The Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Postal Box 94216, 1090 GE Amsterdam, The Netherlands
| | - Claudia Mahlke
- Institute for Molecular and Cellular Cognition Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Falkenried 94, 20251 Hamburg, Germany
| | - Dietmar Kuhl
- Institute for Molecular and Cellular Cognition Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Falkenried 94, 20251 Hamburg, Germany
| | - Cyriel M A Pennartz
- Cognitive & Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, University of Amsterdam, The Netherlands; Research Priority Program Brain and Cognition, University of Amsterdam, Postal Box 94216, 1090 GE Amsterdam, The Netherlands.
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Perrenoud Q, Pennartz CMA, Gentet LJ. Membrane Potential Dynamics of Spontaneous and Visually Evoked Gamma Activity in V1 of Awake Mice. PLoS Biol 2016; 14:e1002383. [PMID: 26890123 PMCID: PMC4758619 DOI: 10.1371/journal.pbio.1002383] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Accepted: 01/15/2016] [Indexed: 11/19/2022] Open
Abstract
Cortical gamma activity (30–80 Hz) is believed to play important functions in neural computation and arises from the interplay of parvalbumin-expressing interneurons (PV) and pyramidal cells (PYRs). However, the subthreshold dynamics underlying its emergence in the cortex of awake animals remain unclear. Here, we characterized the intracellular dynamics of PVs and PYRs during spontaneous and visually evoked gamma activity in layers 2/3 of V1 of awake mice using targeted patch-clamp recordings and synchronous local field potentials (LFPs). Strong gamma activity patterned in short bouts (one to three cycles), occurred when PVs and PYRs were depolarizing and entrained their membrane potential dynamics regardless of the presence of visual stimulation. PV firing phase locked unconditionally to gamma activity. However, PYRs only phase locked to visually evoked gamma bouts. Taken together, our results indicate that gamma activity corresponds to short pulses of correlated background synaptic activity synchronizing the output of cortical neurons depending on external sensory drive. Gamma activity, an important component of brain dynamics, is driven by synaptic background activity and synchronizes distinct cortical cell types differently depending on visual input. The neocortex is the main substrate of cognitive activity of the mammalian brain. During active wakefulness, it exhibits an oscillatory activity in the gamma range (30–80Hz), which is believed to play an important functional role and is altered in schizophrenic patients. Experimental studies have shown that gamma activity arises from the interaction of excitatory pyramidal neurons, the main neuronal type of the cortex, and local inhibitory neurons expressing the protein parvalbumin (PV). However, how these neuronal types behave during gamma activity remains largely unknown. Here, we recorded the intracellular activity of pyramidal and PV-expressing neurons in the visual cortex of awake mice while acquiring Local Field Potentials (LFPs)—extracellular voltage fluctuations within a small volume of the cortex—to monitor gamma activity. We found that gamma activity arises when PV-expressing neurons synchronize their output in response to a correlated input, reflecting the general activation of the local cortical network. This happens even in the absence of visual input. On the other hand, the output of pyramidal neurons only becomes entrained to gamma activity when the mice are exposed to visual stimulation. Thus, our results suggest that gamma activity synchronizes pyramidal neurons specifically when the cortex is engaged in processing external inputs.
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Affiliation(s)
- Quentin Perrenoud
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, the Netherlands
- Department of Neurobiology, Yale University School of Medicine, New Haven, Connecticut, United States of America
- * E-mail: (QP); (LJG)
| | - Cyriel M. A. Pennartz
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, the Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands
| | - Luc J. Gentet
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, the Netherlands
- Team Waking, Lyon Neuroscience Research Center, INSERM U1028 – CNRS UMR5292 F-69008, Lyon, France
- University Lyon 1, F-69000, Lyon, France
- * E-mail: (QP); (LJG)
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Vinck M, Bos JJ, Van Mourik-Donga LA, Oplaat KT, Klein GA, Jackson JC, Gentet LJ, Pennartz CMA. Cell-Type and State-Dependent Synchronization among Rodent Somatosensory, Visual, Perirhinal Cortex, and Hippocampus CA1. Front Syst Neurosci 2016; 9:187. [PMID: 26834582 PMCID: PMC4722130 DOI: 10.3389/fnsys.2015.00187] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2015] [Accepted: 12/21/2015] [Indexed: 01/01/2023] Open
Abstract
Beta and gamma rhythms have been hypothesized to be involved in global and local coordination of neuronal activity, respectively. Here, we investigated how cells in rodent area S1BF are entrained by rhythmic fluctuations at various frequencies within the local area and in connected areas, and how this depends on behavioral state and cell type. We performed simultaneous extracellular field and unit recordings in four connected areas of the freely moving rat (S1BF, V1M, perirhinal cortex, CA1). S1BF spiking activity was strongly entrained by both beta and gamma S1BF oscillations, which were associated with deactivations and activations, respectively. We identified multiple classes of fast spiking and excitatory cells in S1BF, which showed prominent differences in rhythmic entrainment and in the extent to which phase locking was modulated by behavioral state. Using an additional dataset acquired by whole-cell recordings in head-fixed mice, these cell classes could be compared with identified phenotypes showing gamma rhythmicity in their membrane potential. We next examined how S1BF cells were entrained by rhythmic fluctuations in connected brain areas. Gamma-synchronization was detected in all four areas, however we did not detect significant gamma coherence among these areas. Instead, we only found long-range coherence in the theta-beta range among these areas. In contrast to local S1BF synchronization, we found long-range S1BF-spike to CA1–LFP synchronization to be homogeneous across inhibitory and excitatory cell types. These findings suggest distinct, cell-type contributions of low and high-frequency synchronization to intra- and inter-areal neuronal interactions.
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Affiliation(s)
- Martin Vinck
- Cognitive and Systems Neuroscience Group, SILS Center for Neuroscience, University of AmsterdamAmsterdam, Netherlands; Research Priority Program Brain and Cognition, University of AmsterdamAmsterdam, Netherlands; Department of Neurobiology, Yale UniversityNew Haven, CT, USA
| | - Jeroen J Bos
- Cognitive and Systems Neuroscience Group, SILS Center for Neuroscience, University of AmsterdamAmsterdam, Netherlands; Research Priority Program Brain and Cognition, University of AmsterdamAmsterdam, Netherlands
| | - Laura A Van Mourik-Donga
- Cognitive and Systems Neuroscience Group, SILS Center for Neuroscience, University of AmsterdamAmsterdam, Netherlands; Research Priority Program Brain and Cognition, University of AmsterdamAmsterdam, Netherlands
| | - Krista T Oplaat
- Cognitive and Systems Neuroscience Group, SILS Center for Neuroscience, University of AmsterdamAmsterdam, Netherlands; Research Priority Program Brain and Cognition, University of AmsterdamAmsterdam, Netherlands
| | - Gerbrand A Klein
- Cognitive and Systems Neuroscience Group, SILS Center for Neuroscience, University of AmsterdamAmsterdam, Netherlands; Research Priority Program Brain and Cognition, University of AmsterdamAmsterdam, Netherlands
| | - Jadin C Jackson
- Cognitive and Systems Neuroscience Group, SILS Center for Neuroscience, University of AmsterdamAmsterdam, Netherlands; Research Priority Program Brain and Cognition, University of AmsterdamAmsterdam, Netherlands
| | - Luc J Gentet
- Cognitive and Systems Neuroscience Group, SILS Center for Neuroscience, University of AmsterdamAmsterdam, Netherlands; Research Priority Program Brain and Cognition, University of AmsterdamAmsterdam, Netherlands; Team Waking, Lyon Neuroscience Research Center, Institut National de la Santé et de La Recherche Médicale U1028 - Centre National de la Recherche Scientifique UMR 5292Lyon, France
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, SILS Center for Neuroscience, University of AmsterdamAmsterdam, Netherlands; Research Priority Program Brain and Cognition, University of AmsterdamAmsterdam, Netherlands
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Montijn JS, Goltstein PM, Pennartz CMA. Mouse V1 population correlates of visual detection rely on heterogeneity within neuronal response patterns. eLife 2015; 4:e10163. [PMID: 26646184 PMCID: PMC4739777 DOI: 10.7554/elife.10163] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2015] [Accepted: 12/06/2015] [Indexed: 01/23/2023] Open
Abstract
Previous studies have demonstrated the importance of the primary sensory cortex for the detection, discrimination, and awareness of visual stimuli, but it is unknown how neuronal populations in this area process detected and undetected stimuli differently. Critical differences may reside in the mean strength of responses to visual stimuli, as reflected in bulk signals detectable in functional magnetic resonance imaging, electro-encephalogram, or magnetoencephalography studies, or may be more subtly composed of differentiated activity of individual sensory neurons. Quantifying single-cell Ca2+ responses to visual stimuli recorded with in vivo two-photon imaging, we found that visual detection correlates more strongly with population response heterogeneity rather than overall response strength. Moreover, neuronal populations showed consistencies in activation patterns across temporally spaced trials in association with hit responses, but not during nondetections. Contrary to models relying on temporally stable networks or bulk signaling, these results suggest that detection depends on transient differentiation in neuronal activity within cortical populations. DOI:http://dx.doi.org/10.7554/eLife.10163.001 Seeing is not the same as perceiving, where an object is recognized and information about it is interpreted by the brain. Things might be in your field of view, but not actively perceived; for example, when daydreaming with your eyes open. Many researchers have investigated how the brain responds differently to a perceived object compared with something that is seen but not perceived. However, using relatively coarse techniques, only small differences in brain activity have been found. Many of the techniques used to investigate brain activity only look at the average activity of a group of neurons – the cells in the brain that process information. This raises the possibility that the perception of an object relies on more subtle or complex interactions in brain activity. To investigate this, Montijn et al. trained mice to lick a reward spout that gave out sugar water when they perceived a particular image. A technique called two-photon calcium imaging was then used to simultaneously record the activity of tens to hundreds of neurons in part of the brain called the visual cortex as the mice performed the perception task. This revealed that the average activation of a group of neurons was only weakly related to whether a mouse had perceived the image. However, differences in the strength of the responses of the individual neurons in the group reflected perception more strongly: when a mouse perceived the image and licked in response, a heterogeneous (non-uniform) set of neuronal responses occurred. The diversity of the neuronal responses could also be used to predict how quickly a mouse would respond to an image. These activity differences would not be picked up by techniques that detect the average activity of many neurons, explaining why these effects had not previously been seen. These findings shed light on which patterns of activity in the visual region of the brain lead to objects being perceived or not. Whether similar mechanisms operate in different regions of the brain remains to be investigated. DOI:http://dx.doi.org/10.7554/eLife.10163.002
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Affiliation(s)
- Jorrit S Montijn
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands
| | - Pieter M Goltstein
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands.,Max Planck Institute of Neurobiology, Martinsried, Germany
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands.,Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
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43
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Pezzulo G, Verschure PFMJ, Balkenius C, Pennartz CMA. The principles of goal-directed decision-making: from neural mechanisms to computation and robotics. Philos Trans R Soc Lond B Biol Sci 2015; 369:rstb.2013.0470. [PMID: 25267813 DOI: 10.1098/rstb.2013.0470] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Paul F M J Verschure
- University Pompeu Fabra and Catalan Institute of Advanced Studies (ICREA), Barcelona, Spain
| | | | - Cyriel M A Pennartz
- Faculty of Science, Department Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
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Goltstein PM, Montijn JS, Pennartz CMA. Effects of isoflurane anesthesia on ensemble patterns of Ca2+ activity in mouse v1: reduced direction selectivity independent of increased correlations in cellular activity. PLoS One 2015; 10:e0118277. [PMID: 25706867 PMCID: PMC4338011 DOI: 10.1371/journal.pone.0118277] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2014] [Accepted: 01/04/2015] [Indexed: 01/22/2023] Open
Abstract
Anesthesia affects brain activity at the molecular, neuronal and network level, but it is not well-understood how tuning properties of sensory neurons and network connectivity change under its influence. Using in vivo two-photon calcium imaging we matched neuron identity across episodes of wakefulness and anesthesia in the same mouse and recorded spontaneous and visually evoked activity patterns of neuronal ensembles in these two states. Correlations in spontaneous patterns of calcium activity between pairs of neurons were increased under anesthesia. While orientation selectivity remained unaffected by anesthesia, this treatment reduced direction selectivity, which was attributable to an increased response to the null-direction. As compared to anesthesia, populations of V1 neurons coded more mutual information on opposite stimulus directions during wakefulness, whereas information on stimulus orientation differences was lower. Increases in correlations of calcium activity during visual stimulation were correlated with poorer population coding, which raised the hypothesis that the anesthesia-induced increase in correlations may be causal to degrading directional coding. Visual stimulation under anesthesia, however, decorrelated ongoing activity patterns to a level comparable to wakefulness. Because visual stimulation thus appears to 'break' the strength of pairwise correlations normally found in spontaneous activity under anesthesia, the changes in correlational structure cannot explain the awake-anesthesia difference in direction coding. The population-wide decrease in coding for stimulus direction thus occurs independently of anesthesia-induced increments in correlations of spontaneous activity.
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Affiliation(s)
- Pieter M. Goltstein
- Center for Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Jorrit S. Montijn
- Center for Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Cyriel M. A. Pennartz
- Center for Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
- * E-mail:
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45
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Verschure PFMJ, Pennartz CMA, Pezzulo G. The why, what, where, when and how of goal-directed choice: neuronal and computational principles. Philos Trans R Soc Lond B Biol Sci 2014; 369:20130483. [PMID: 25267825 PMCID: PMC4186236 DOI: 10.1098/rstb.2013.0483] [Citation(s) in RCA: 90] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
The central problems that goal-directed animals must solve are: 'What do I need and Why, Where and When can this be obtained, and How do I get it?' or the H4W problem. Here, we elucidate the principles underlying the neuronal solutions to H4W using a combination of neurobiological and neurorobotic approaches. First, we analyse H4W from a system-level perspective by mapping its objectives onto the Distributed Adaptive Control embodied cognitive architecture which sees the generation of adaptive action in the real world as the primary task of the brain rather than optimally solving abstract problems. We next map this functional decomposition to the architecture of the rodent brain to test its consistency. Following this approach, we propose that the mammalian brain solves the H4W problem on the basis of multiple kinds of outcome predictions, integrating central representations of needs and drives (e.g. hypothalamus), valence (e.g. amygdala), world, self and task state spaces (e.g. neocortex, hippocampus and prefrontal cortex, respectively) combined with multi-modal selection (e.g. basal ganglia). In our analysis, goal-directed behaviour results from a well-structured architecture in which goals are bootstrapped on the basis of predefined needs, valence and multiple learning, memory and planning mechanisms rather than being generated by a singular computation.
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Affiliation(s)
- Paul F M J Verschure
- Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Center of Autonomous Systems and Neurorobotics, Universitat Pompeu Fabra (UPF), Barcelona, Spain Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | | | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
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Pezzulo G, van der Meer MAA, Lansink CS, Pennartz CMA. Internally generated sequences in learning and executing goal-directed behavior. Trends Cogn Sci 2014; 18:647-57. [PMID: 25156191 DOI: 10.1016/j.tics.2014.06.011] [Citation(s) in RCA: 150] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2014] [Revised: 06/25/2014] [Accepted: 06/26/2014] [Indexed: 12/29/2022]
Abstract
A network of brain structures including hippocampus (HC), prefrontal cortex, and striatum controls goal-directed behavior and decision making. However, the neural mechanisms underlying these functions are unknown. Here, we review the role of 'internally generated sequences': structured, multi-neuron firing patterns in the network that are not confined to signaling the current state or location of an agent, but are generated on the basis of internal brain dynamics. Neurophysiological studies suggest that such sequences fulfill functions in memory consolidation, augmentation of representations, internal simulation, and recombination of acquired information. Using computational modeling, we propose that internally generated sequences may be productively considered a component of goal-directed decision systems, implementing a sampling-based inference engine that optimizes goal acquisition at multiple timescales of on-line choice, action control, and learning.
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Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Via San Martino della Battaglia 44, 00185 Roma, Italy
| | - Matthijs A A van der Meer
- Department of Biology and Centre for Theoretical Neuroscience, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
| | - Carien S Lansink
- Swammerdam Institute for Life Sciences - Center for Neuroscience, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands; Amsterdam Brain and Cognition, Research Priority Program Brain and Cognition, Nieuwe Achtergracht 129, 1018 WS Amsterdam, The Netherlands
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences - Center for Neuroscience, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands; Amsterdam Brain and Cognition, Research Priority Program Brain and Cognition, Nieuwe Achtergracht 129, 1018 WS Amsterdam, The Netherlands.
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47
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Montijn JS, Vinck M, Pennartz CMA. Population coding in mouse visual cortex: response reliability and dissociability of stimulus tuning and noise correlation. Front Comput Neurosci 2014; 8:58. [PMID: 24917812 PMCID: PMC4040453 DOI: 10.3389/fncom.2014.00058] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2014] [Accepted: 05/14/2014] [Indexed: 11/13/2022] Open
Abstract
The primary visual cortex is an excellent model system for investigating how neuronal populations encode information, because of well-documented relationships between stimulus characteristics and neuronal activation patterns. We used two-photon calcium imaging data to relate the performance of different methods for studying population coding (population vectors, template matching, and Bayesian decoding algorithms) to their underlying assumptions. We show that the variability of neuronal responses may hamper the decoding of population activity, and that a normalization to correct for this variability may be of critical importance for correct decoding of population activity. Second, by comparing noise correlations and stimulus tuning we find that these properties have dissociated anatomical correlates, even though noise correlations have been previously hypothesized to reflect common synaptic input. We hypothesize that noise correlations arise from large non-specific increases in spiking activity acting on many weak synapses simultaneously, while neuronal stimulus response properties are dependent on more reliable connections. Finally, this paper provides practical guidelines for further research on population coding and shows that population coding cannot be approximated by a simple summation of inputs, but is heavily influenced by factors such as input reliability and noise correlation structure.
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Affiliation(s)
- Jorrit S Montijn
- Cognitive and Systems Neuroscience, Faculty of Science, Center for Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam Amsterdam, Netherlands
| | - Martin Vinck
- Cognitive and Systems Neuroscience, Faculty of Science, Center for Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam Amsterdam, Netherlands
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience, Faculty of Science, Center for Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam Amsterdam, Netherlands ; Research Priority Program Brain and Cognition, University of Amsterdam Amsterdam, Netherlands
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48
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Bosman CA, Lansink CS, Pennartz CMA. Functions of gamma-band synchronization in cognition: from single circuits to functional diversity across cortical and subcortical systems. Eur J Neurosci 2014; 39:1982-99. [PMID: 24809619 DOI: 10.1111/ejn.12606] [Citation(s) in RCA: 129] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2014] [Revised: 03/18/2014] [Accepted: 04/03/2014] [Indexed: 12/19/2022]
Abstract
Gamma-band activity (30-90 Hz) and the synchronization of neural activity in the gamma-frequency range have been observed in different cortical and subcortical structures and have been associated with different cognitive functions. However, it is still unknown whether gamma-band synchronization subserves a single universal function or a diversity of functions across the full spectrum of cognitive processes. Here, we address this question reviewing the mechanisms of gamma-band oscillation generation and the functions associated with gamma-band activity across several cortical and subcortical structures. Additionally, we raise a plausible explanation of why gamma rhythms are found so ubiquitously across brain structures. Gamma band activity originates from the interplay between inhibition and excitation. We stress that gamma oscillations, associated with this interplay, originate from basic functional motifs that conferred advantages for low-level system processing and multiple cognitive functions throughout evolution. We illustrate the multifunctionality of gamma-band activity by considering its role in neural systems for perception, selective attention, memory, motivation and behavioral control. We conclude that gamma-band oscillations support multiple cognitive processes, rather than a single one, which, however, can be traced back to a limited set of circuit motifs which are found universally across species and brain structures.
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Affiliation(s)
- Conrado A Bosman
- Cognitive and Systems Neuroscience Group, Center for Neuroscience, Faculty of Science, Swammerdam Institute for Life Sciences, University of Amsterdam, Postal Box 94216, 1090, GE Amsterdam, The Netherlands; Research Priority Program Brain & Cognition, University of Amsterdam, Amsterdam, The Netherlands
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49
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Huijbers W, Pennartz CMA, Beldzik E, Domagalik A, Vinck M, Hofman WF, Cabeza R, Daselaar SM. Respiration phase-locks to fast stimulus presentations: implications for the interpretation of posterior midline "deactivations". Hum Brain Mapp 2014; 35:4932-43. [PMID: 24737724 DOI: 10.1002/hbm.22523] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2013] [Revised: 02/21/2014] [Accepted: 03/24/2014] [Indexed: 01/20/2023] Open
Abstract
The posterior midline region (PMR)-considered a core of the default mode network-is deactivated during successful performance in different cognitive tasks. The extent of PMR-deactivations is correlated with task-demands and associated with successful performance in various cognitive domains. In the domain of episodic memory, functional MRI (fMRI) studies found that PMR-deactivations reliably predict learning (successful encoding). Yet it is unclear what explains this relation. One intriguing possibility is that PMR-deactivations are partially mediated by respiratory artifacts. There is evidence that the fMRI signal in PMR is particularly prone to respiratory artifacts, because of its large surrounding blood vessels. As respiratory fluctuations have been shown to track changes in attention, it is critical for the general interpretation of fMRI results to clarify the relation between respiratory fluctuations, cognitive performance, and fMRI signal. Here, we investigated this issue by measuring respiration during word encoding, together with a breath-holding condition during fMRI-scanning. Stimulus-locked respiratory analyses showed that respiratory fluctuations predicted successful encoding via a respiratory phase-locking mechanism. At the same time, the fMRI analyses showed that PMR-deactivations associated with learning were reduced during breath-holding and correlated with individual differences in the respiratory phase-locking effect during normal breathing. A left frontal region--used as a control region--did not show these effects. These findings indicate that respiration is a critical factor in explaining the link between PMR-deactivation and successful cognitive performance. Further research is necessary to demonstrate whether our findings are restricted to episodic memory encoding, or also extend to other cognitive domains.
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Affiliation(s)
- Willem Huijbers
- Harvard Medical School, Martinos Center for Biomedical Imaging, Brigham and Women's Hospital, Boston, Massachusetts; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
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50
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Cabral HO, Vinck M, Fouquet C, Pennartz CMA, Rondi-Reig L, Battaglia FP. Oscillatory dynamics and place field maps reflect hippocampal ensemble processing of sequence and place memory under NMDA receptor control. Neuron 2014; 81:402-15. [PMID: 24462101 DOI: 10.1016/j.neuron.2013.11.010] [Citation(s) in RCA: 92] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/24/2013] [Indexed: 12/22/2022]
Abstract
Place coding in the hippocampus requires flexible combination of sensory inputs (e.g., environmental and self-motion information) with memory of past events. We show that mouse CA1 hippocampal spatial representations may either be anchored to external landmarks (place memory) or reflect memorized sequences of cell assemblies depending on the behavioral strategy spontaneously selected. These computational modalities correspond to different CA1 dynamical states, as expressed by theta and low- and high-frequency gamma oscillations, when switching from place to sequence memory-based processing. These changes are consistent with a shift from entorhinal to CA3 input dominance on CA1. In mice with a deletion of forebrain NMDA receptors, the ability of place cells to maintain a map based on sequence memory is selectively impaired and oscillatory dynamics are correspondingly altered, suggesting that oscillations contribute to selecting behaviorally appropriate computations in the hippocampus and that NMDA receptors are crucial for this function.
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Affiliation(s)
- Henrique O Cabral
- SILS - Center for Neuroscience, Universiteit van Amsterdam, 1090GE Amsterdam, the Netherlands; Cognitive Sciences Center Amsterdam, Research Priority Program "Brain and Cognition," 1018WS Amsterdam, the Netherlands; NERF, 3001 Leuven, Belgium; Donders Institute for Brain Cognition and Behavior, Radboud Universiteit Nijmegen, 6500GL Nijmegen, the Netherlands.
| | - Martin Vinck
- SILS - Center for Neuroscience, Universiteit van Amsterdam, 1090GE Amsterdam, the Netherlands; Cognitive Sciences Center Amsterdam, Research Priority Program "Brain and Cognition," 1018WS Amsterdam, the Netherlands
| | - Celine Fouquet
- Sorbonne Universités, UPMC Univ Paris 06, UMR-S 8246, Neuroscience Paris Seine, Navigation Memory and Aging Team, F-75005 Paris, France; INSERM, UMR-S 1130, Neuroscience Paris Seine, Navigation Memory and Aging Team, F-75005 Paris, France; CNRS, UMR 8246, Neuroscience Paris Seine, Navigation Memory and Aging Team, F-75005 Paris, France
| | - Cyriel M A Pennartz
- SILS - Center for Neuroscience, Universiteit van Amsterdam, 1090GE Amsterdam, the Netherlands; Cognitive Sciences Center Amsterdam, Research Priority Program "Brain and Cognition," 1018WS Amsterdam, the Netherlands
| | - Laure Rondi-Reig
- Sorbonne Universités, UPMC Univ Paris 06, UMR-S 8246, Neuroscience Paris Seine, Navigation Memory and Aging Team, F-75005 Paris, France; INSERM, UMR-S 1130, Neuroscience Paris Seine, Navigation Memory and Aging Team, F-75005 Paris, France; CNRS, UMR 8246, Neuroscience Paris Seine, Navigation Memory and Aging Team, F-75005 Paris, France
| | - Francesco P Battaglia
- SILS - Center for Neuroscience, Universiteit van Amsterdam, 1090GE Amsterdam, the Netherlands; Cognitive Sciences Center Amsterdam, Research Priority Program "Brain and Cognition," 1018WS Amsterdam, the Netherlands; NERF, 3001 Leuven, Belgium; Donders Institute for Brain Cognition and Behavior, Radboud Universiteit Nijmegen, 6500GL Nijmegen, the Netherlands; VIB, 3000 Leuven, Belgium.
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