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Ceccarelli F, Ferrucci L, Londei F, Ramawat S, Brunamonti E, Genovesio A. Static and dynamic coding in distinct cell types during associative learning in the prefrontal cortex. Nat Commun 2023; 14:8325. [PMID: 38097560 PMCID: PMC10721651 DOI: 10.1038/s41467-023-43712-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 11/17/2023] [Indexed: 12/17/2023] Open
Abstract
The prefrontal cortex maintains information in memory through static or dynamic population codes depending on task demands, but whether the population coding schemes used are learning-dependent and differ between cell types is currently unknown. We investigate the population coding properties and temporal stability of neurons recorded from male macaques in two mapping tasks during and after stimulus-response associative learning, and then we use a Strategy task with the same stimuli and responses as control. We identify a heterogeneous population coding for stimuli, responses, and novel associations: static for putative pyramidal cells and dynamic for putative interneurons that show the strongest selectivity for all the variables. The population coding of learned associations shows overall the highest stability driven by cell types, with interneurons changing from dynamic to static coding after successful learning. The results support that prefrontal microcircuitry expresses mixed population coding governed by cell types and changes its stability during associative learning.
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Affiliation(s)
- Francesco Ceccarelli
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy
| | - Lorenzo Ferrucci
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy
| | - Fabrizio Londei
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy
- PhD program in Behavioral Neuroscience, Sapienza University, Rome, Italy
| | - Surabhi Ramawat
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy
| | - Emiliano Brunamonti
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy
| | - Aldo Genovesio
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy.
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2
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Banaie Boroujeni K, Womelsdorf T. Routing states transition during oscillatory bursts and attentional selection. Neuron 2023; 111:2929-2944.e11. [PMID: 37463578 PMCID: PMC10529654 DOI: 10.1016/j.neuron.2023.06.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 05/22/2023] [Accepted: 06/20/2023] [Indexed: 07/20/2023]
Abstract
Brain-wide information routing relies on the spatio-temporal dynamics of neural activity, but it remains unclear how routing states emerge at fast spiking timescales and relate to slower activity dynamics during cognitive processes. Here, we show that localized spiking events participate in directional routing states with spiking activity in distant brain areas that dynamically switch or amplify states during oscillatory bursts, attentional selection, and decision-making. Modeling and neural recordings from lateral prefrontal cortex (LPFC), anterior cingulate cortex (ACC), and striatum of nonhuman primates revealed that cross-regional routing states arise within 20 ms following individual neuron spikes, with LPFC spikes leading the activity in ACC and striatum. The baseline routing state amplified during LPFC beta bursts between LPFC and striatum and switched direction during ACC theta/alpha bursts between ACC and LPFC. Selective attention amplified theta-/alpha-band-specific lead ensembles in ACC, while decision-making increased the lead of ACC and LPFC spikes to the striatum.
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Affiliation(s)
- Kianoush Banaie Boroujeni
- Department of Psychology, Vanderbilt University, Nashville, TN 37240, USA; Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA.
| | - Thilo Womelsdorf
- Department of Psychology, Vanderbilt University, Nashville, TN 37240, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, USA
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3
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Recanatesi S. Untangling network information flow. NATURE COMPUTATIONAL SCIENCE 2022; 2:475-476. [PMID: 38177793 DOI: 10.1038/s43588-022-00284-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
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4
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Gokcen E, Jasper AI, Semedo JD, Zandvakili A, Kohn A, Machens CK, Yu BM. Disentangling the flow of signals between populations of neurons. NATURE COMPUTATIONAL SCIENCE 2022; 2:512-525. [PMID: 38177794 DOI: 10.1038/s43588-022-00282-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 06/21/2022] [Indexed: 01/06/2024]
Abstract
Technological advances now allow us to record from large populations of neurons across multiple brain areas. These recordings may illuminate how communication between areas contributes to brain function, yet a substantial barrier remains: how do we disentangle the concurrent, bidirectional flow of signals between populations of neurons? We propose here a dimensionality reduction framework, delayed latents across groups (DLAG), that disentangles signals relayed in each direction, identifies how these signals are represented by each population and characterizes how they evolve within and across trials. We demonstrate that DLAG performs well on synthetic datasets similar in scale to current neurophysiological recordings. Then we study simultaneously recorded populations in primate visual areas V1 and V2, where DLAG reveals signatures of bidirectional yet selective communication. Our framework lays a foundation for dissecting the intricate flow of signals across populations of neurons, and how this signalling contributes to cortical computation.
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Affiliation(s)
- Evren Gokcen
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Anna I Jasper
- Dominick Purpura Department of Neuroscience, Albert Einstein College of Medicine, New York, NY, USA
| | - João D Semedo
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Amin Zandvakili
- Dominick Purpura Department of Neuroscience, Albert Einstein College of Medicine, New York, NY, USA
| | - Adam Kohn
- Dominick Purpura Department of Neuroscience, Albert Einstein College of Medicine, New York, NY, USA
- Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, New York, NY, USA
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, New York, NY, USA
| | - Christian K Machens
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | - Byron M Yu
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
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5
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6
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Srinath R, Ruff DA, Cohen MR. Attention improves information flow between neuronal populations without changing the communication subspace. Curr Biol 2021; 31:5299-5313.e4. [PMID: 34699782 PMCID: PMC8665027 DOI: 10.1016/j.cub.2021.09.076] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 09/22/2021] [Accepted: 09/28/2021] [Indexed: 10/20/2022]
Abstract
Visual attention allows observers to change the influence of different parts of a visual scene on their behavior, suggesting that information can be flexibly shared between visual cortex and neurons involved in decision making. We investigated the neural substrate of flexible information routing by analyzing the activity of populations of visual neurons in the medial temporal area (MT) and oculo-motor neurons in the superior colliculus (SC) while rhesus monkeys switched spatial attention. We demonstrated that attention increases the efficacy of visuomotor communication: trial-to-trial variability in SC population activity could be better predicted by the activity of the MT population (and vice versa) when attention was directed toward their joint receptive fields. Surprisingly, this improvement in prediction was not explained by changes in the dimensionality of the shared subspace or in the magnitude of local or shared pairwise noise correlations. These results lay a foundation for future theoretical and experimental studies into how visual attention can flexibly change information flow between sensory and decision neurons.
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Affiliation(s)
- Ramanujan Srinath
- Department of Neuroscience and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Douglas A Ruff
- Department of Neuroscience and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
| | - Marlene R Cohen
- Department of Neuroscience and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
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7
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Umakantha A, Morina R, Cowley BR, Snyder AC, Smith MA, Yu BM. Bridging neuronal correlations and dimensionality reduction. Neuron 2021; 109:2740-2754.e12. [PMID: 34293295 PMCID: PMC8505167 DOI: 10.1016/j.neuron.2021.06.028] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Revised: 05/05/2021] [Accepted: 06/25/2021] [Indexed: 01/01/2023]
Abstract
Two commonly used approaches to study interactions among neurons are spike count correlation, which describes pairs of neurons, and dimensionality reduction, applied to a population of neurons. Although both approaches have been used to study trial-to-trial neuronal variability correlated among neurons, they are often used in isolation and have not been directly related. We first established concrete mathematical and empirical relationships between pairwise correlation and metrics of population-wide covariability based on dimensionality reduction. Applying these insights to macaque V4 population recordings, we found that the previously reported decrease in mean pairwise correlation associated with attention stemmed from three distinct changes in population-wide covariability. Overall, our work builds the intuition and formalism to bridge between pairwise correlation and population-wide covariability and presents a cautionary tale about the inferences one can make about population activity by using a single statistic, whether it be mean pairwise correlation or dimensionality.
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Affiliation(s)
- Akash Umakantha
- Carnegie Mellon Neuroscience Institute, Pittsburgh, PA 15213, USA; Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Rudina Morina
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Benjamin R Cowley
- Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | - Adam C Snyder
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14642, USA; Department of Neuroscience, University of Rochester, Rochester, NY 14642, USA; Center for Visual Science, University of Rochester, Rochester, NY 14642, USA
| | - Matthew A Smith
- Carnegie Mellon Neuroscience Institute, Pittsburgh, PA 15213, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
| | - Byron M Yu
- Carnegie Mellon Neuroscience Institute, Pittsburgh, PA 15213, USA; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
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8
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Salamanca-Giron RF, Raffin E, Zandvliet SB, Seeber M, Michel CM, Sauseng P, Huxlin KR, Hummel FC. Enhancing visual motion discrimination by desynchronizing bifocal oscillatory activity. Neuroimage 2021; 240:118299. [PMID: 34171500 DOI: 10.1016/j.neuroimage.2021.118299] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 06/11/2021] [Accepted: 06/20/2021] [Indexed: 11/17/2022] Open
Abstract
Visual motion discrimination involves reciprocal interactions in the alpha band between the primary visual cortex (V1) and mediotemporal areas (V5/MT). We investigated whether modulating alpha phase synchronization using individualized multisite transcranial alternating current stimulation (tACS) over V5 and V1 regions would improve motion discrimination. We tested 3 groups of healthy subjects with the following conditions: (1) individualized In-Phase V1alpha-V5alpha tACS (0° lag), (2) individualized Anti-Phase V1alpha-V5alpha tACS (180° lag) and (3) sham tACS. Motion discrimination and EEG activity were recorded before, during and after tACS. Performance significantly improved in the Anti-Phase group compared to the In-Phase group 10 and 30 min after stimulation. This result was explained by decreases in bottom-up alpha-V1 gamma-V5 phase-amplitude coupling. One possible explanation of these results is that Anti-Phase V1alpha-V5alpha tACS might impose an optimal phase lag between stimulation sites due to the inherent speed of wave propagation, hereby supporting optimized neuronal communication.
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Affiliation(s)
- Roberto F Salamanca-Giron
- Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Swiss Federal Institute of Technology (EPFL), Campus Biotech, Room H4.3.132.084, Chemin des Mines 9, Geneva, Switzerland; Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Clinique Romande de Readaptation (CRR), EPFL Valais, Sion, Switzerland
| | - Estelle Raffin
- Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Swiss Federal Institute of Technology (EPFL), Campus Biotech, Room H4.3.132.084, Chemin des Mines 9, Geneva, Switzerland; Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Clinique Romande de Readaptation (CRR), EPFL Valais, Sion, Switzerland
| | - Sarah B Zandvliet
- Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Swiss Federal Institute of Technology (EPFL), Campus Biotech, Room H4.3.132.084, Chemin des Mines 9, Geneva, Switzerland; Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Clinique Romande de Readaptation (CRR), EPFL Valais, Sion, Switzerland
| | - Martin Seeber
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202, Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202, Geneva, Switzerland; Lemanic Biomedical Imaging Centre (CIBM), Lausanne, Geneva, Switzerland
| | - Paul Sauseng
- Department of Psychology, LMU Munich, Leopoldstr. 13, Munich 80802, Germany
| | - Krystel R Huxlin
- The Flaum Eye Institute and Center for Visual Science, University of Rochester, Rochester, NY, USA
| | - Friedhelm C Hummel
- Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Swiss Federal Institute of Technology (EPFL), Campus Biotech, Room H4.3.132.084, Chemin des Mines 9, Geneva, Switzerland; Defitech Chair in Clinical Neuroengineering, Center for Neuroprosthetics and Brain Mind Institute, Clinique Romande de Readaptation (CRR), EPFL Valais, Sion, Switzerland; Clinical Neuroscience, University of Geneva Medical School, Geneva, Switzerland.
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9
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Banaie Boroujeni K, Tiesinga P, Womelsdorf T. Interneuron-specific gamma synchronization indexes cue uncertainty and prediction errors in lateral prefrontal and anterior cingulate cortex. eLife 2021; 10:69111. [PMID: 34142661 PMCID: PMC8248985 DOI: 10.7554/elife.69111] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 06/17/2021] [Indexed: 12/27/2022] Open
Abstract
Inhibitory interneurons are believed to realize critical gating functions in cortical circuits, but it has been difficult to ascertain the content of gated information for well-characterized interneurons in primate cortex. Here, we address this question by characterizing putative interneurons in primate prefrontal and anterior cingulate cortex while monkeys engaged in attention demanding reversal learning. We find that subclasses of narrow spiking neurons have a relative suppressive effect on the local circuit indicating they are inhibitory interneurons. One of these interneuron subclasses showed prominent firing rate modulations and (35–45 Hz) gamma synchronous spiking during periods of uncertainty in both, lateral prefrontal cortex (LPFC) and anterior cingulate cortex (ACC). In LPFC, this interneuron subclass activated when the uncertainty of attention cues was resolved during flexible learning, whereas in ACC it fired and gamma-synchronized when outcomes were uncertain and prediction errors were high during learning. Computational modeling of this interneuron-specific gamma band activity in simple circuit motifs suggests it could reflect a soft winner-take-all gating of information having high degree of uncertainty. Together, these findings elucidate an electrophysiologically characterized interneuron subclass in the primate, that forms gamma synchronous networks in two different areas when resolving uncertainty during adaptive goal-directed behavior.
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Affiliation(s)
| | - Paul Tiesinga
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - Thilo Womelsdorf
- Department of Psychology, Vanderbilt University, Nashville, United States.,Department of Biology, Centre for Vision Research, York University, Toronto, Canada
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10
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Kadohisa M, Watanabe K, Kusunoki M, Buckley MJ, Duncan J. Focused Representation of Successive Task Episodes in Frontal and Parietal Cortex. Cereb Cortex 2021; 30:1779-1796. [PMID: 31690931 DOI: 10.1093/cercor/bhz202] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Complex cognition is dynamic, with each stage of a task requiring new cognitive processes appropriately linked to stimulus or other content. To investigate control over successive task stages, we recorded neural activity in lateral frontal and parietal cortex as monkeys carried out a complex object selection task, with each trial separated into phases of visual selection and learning from feedback. To study capacity limitation, complexity was manipulated by varying the number of object targets to be learned in each problem. Different task phases were associated with quasi-independent patterns of activity and information coding, with no suggestion of sustained activity linked to a current target. Object and location coding were largely parallel in frontal and inferior parietal cortex, though frontal cortex showed somewhat stronger object representation at feedback, and more sustained location coding at choice. At both feedback and choice, coding precision diminished as task complexity increased, matching a decline in performance. We suggest that, across successive task steps, there is radical but capacity-limited reorganization of frontoparietal activity, selecting different cognitive operations linked to their current targets.
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Affiliation(s)
- Mikiko Kadohisa
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - Kei Watanabe
- Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK.,Graduate School of Frontier Biosciences, Osaka University, Osaka 565-0871, Japan
| | - Makoto Kusunoki
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - Mark J Buckley
- Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK
| | - John Duncan
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK.,Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK
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11
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Mosher CP, Wei Y, Kamiński J, Nandi A, Mamelak AN, Anastassiou CA, Rutishauser U. Cellular Classes in the Human Brain Revealed In Vivo by Heartbeat-Related Modulation of the Extracellular Action Potential Waveform. Cell Rep 2021; 30:3536-3551.e6. [PMID: 32160555 DOI: 10.1016/j.celrep.2020.02.027] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 12/23/2019] [Accepted: 02/05/2020] [Indexed: 01/01/2023] Open
Abstract
Determining cell types is critical for understanding neural circuits but remains elusive in the living human brain. Current approaches discriminate units into putative cell classes using features of the extracellular action potential (EAP); in absence of ground truth data, this remains a problematic procedure. We find that EAPs in deep structures of the brain exhibit robust and systematic variability during the cardiac cycle. These cardiac-related features refine neural classification. We use these features to link bio-realistic models generated from in vitro human whole-cell recordings of morphologically classified neurons to in vivo recordings. We differentiate aspiny inhibitory and spiny excitatory human hippocampal neurons and, in a second stage, demonstrate that cardiac-motion features reveal two types of spiny neurons with distinct intrinsic electrophysiological properties and phase-locking characteristics to endogenous oscillations. This multi-modal approach markedly improves cell classification in humans, offers interpretable cell classes, and is applicable to other brain areas and species.
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Affiliation(s)
- Clayton P Mosher
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Yina Wei
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jan Kamiński
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Division of Biology and Biological Engineering, Caltech, Pasadena, CA 91125, USA
| | - Anirban Nandi
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Adam N Mamelak
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Costas A Anastassiou
- Allen Institute for Brain Science, Seattle, WA 98109, USA; Division of Neurology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
| | - Ueli Rutishauser
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Center for Neural Science and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Division of Biology and Biological Engineering, Caltech, Pasadena, CA 91125, USA.
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12
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Caballero A, Orozco A, Tseng KY. Developmental regulation of excitatory-inhibitory synaptic balance in the prefrontal cortex during adolescence. Semin Cell Dev Biol 2021; 118:60-63. [PMID: 33714681 DOI: 10.1016/j.semcdb.2021.02.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 02/26/2021] [Indexed: 02/06/2023]
Abstract
The prefrontal cortex (PFC) is a cortical structure involved in a variety of complex functions in the cognitive and affective domains. The intrinsic function of the PFC is defined by the interaction of local glutamatergic and GABAergic neurons and their modulation by long-range inputs. The ensuing interactions generate a ratio of excitation and inhibition (E-I) in each output neuron, a balance which is refined during the adolescent to adult transition. In this short review, we aim to describe how an increase in GABAergic transmission during adolescence modifies the E-I ratio in adults. We further discuss how this new setpoint may change the dynamics of PFC networks observed during the transition to adulthood.
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Affiliation(s)
- Adriana Caballero
- Department of Anatomy and Cell Biology, College of Medicine, University of Illinois at Chicago, 808 S Wood St, Chicago, IL 60612, USA
| | - Amanda Orozco
- Department of Anatomy and Cell Biology, College of Medicine, University of Illinois at Chicago, 808 S Wood St, Chicago, IL 60612, USA
| | - Kuei Y Tseng
- Department of Anatomy and Cell Biology, College of Medicine, University of Illinois at Chicago, 808 S Wood St, Chicago, IL 60612, USA.
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13
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van Kempen J, Gieselmann MA, Boyd M, Steinmetz NA, Moore T, Engel TA, Thiele A. Top-down coordination of local cortical state during selective attention. Neuron 2021; 109:894-904.e8. [PMID: 33406410 PMCID: PMC7927916 DOI: 10.1016/j.neuron.2020.12.013] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 11/20/2020] [Accepted: 12/16/2020] [Indexed: 11/30/2022]
Abstract
Spontaneous fluctuations in cortical excitability influence sensory processing and behavior. These fluctuations, long thought to reflect global changes in cortical state, were recently found to be modulated locally within a retinotopic map during spatially selective attention. We report that periods of vigorous (On) and faint (Off) spiking activity, the signature of cortical state fluctuations, are coordinated across brain areas with retinotopic precision. Top-down attention enhanced interareal local state coordination, traversing along the reverse cortical hierarchy. The extent of local state coordination between areas was predictive of behavioral performance. Our results show that cortical state dynamics are shared across brain regions, modulated by cognitive demands and relevant for behavior.
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Affiliation(s)
- Jochem van Kempen
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
| | - Marc A Gieselmann
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Michael Boyd
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Nicholas A Steinmetz
- Department of Biological Structure, University of Washington, Seattle, WA 98195, USA
| | - Tirin Moore
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Tatiana A Engel
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Alexander Thiele
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
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14
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Semedo JD, Gokcen E, Machens CK, Kohn A, Yu BM. Statistical methods for dissecting interactions between brain areas. Curr Opin Neurobiol 2020; 65:59-69. [PMID: 33142111 PMCID: PMC7935404 DOI: 10.1016/j.conb.2020.09.009] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 09/23/2020] [Accepted: 09/24/2020] [Indexed: 12/12/2022]
Abstract
The brain is composed of many functionally distinct areas. This organization supports distributed processing, and requires the coordination of signals across areas. Our understanding of how populations of neurons in different areas interact with each other is still in its infancy. As the availability of recordings from large populations of neurons across multiple brain areas increases, so does the need for statistical methods that are well suited for dissecting and interrogating these recordings. Here we review multivariate statistical methods that have been, or could be, applied to this class of recordings. By leveraging population responses, these methods can provide a rich description of inter-areal interactions. At the same time, these methods can introduce interpretational challenges. We thus conclude by discussing how to interpret the outputs of these methods to further our understanding of inter-areal interactions.
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Affiliation(s)
- João D Semedo
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
| | - Evren Gokcen
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
| | - Christian K Machens
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Adam Kohn
- Dominick Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA; Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, USA; Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Byron M Yu
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
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15
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Duncan J, Assem M, Shashidhara S. Integrated Intelligence from Distributed Brain Activity. Trends Cogn Sci 2020; 24:838-852. [PMID: 32771330 PMCID: PMC7116395 DOI: 10.1016/j.tics.2020.06.012] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 06/29/2020] [Accepted: 06/30/2020] [Indexed: 01/21/2023]
Abstract
How does organized cognition arise from distributed brain activity? Recent analyses of fluid intelligence suggest a core process of cognitive focus and integration, organizing the components of a cognitive operation into the required computational structure. A cortical 'multiple-demand' (MD) system is closely linked to fluid intelligence, and recent imaging data define nine specific MD patches distributed across frontal, parietal, and occipitotemporal cortex. Wide cortical distribution, relative functional specialization, and strong connectivity suggest a basis for cognitive integration, matching electrophysiological evidence for binding of cognitive operations to their contents. Though still only in broad outline, these data suggest how distributed brain activity can build complex, organized cognition.
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Affiliation(s)
- John Duncan
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK; Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK.
| | - Moataz Assem
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - Sneha Shashidhara
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
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16
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Biologically plausible mechanisms underlying motor response correction during reward-based decision-making. Neurocomputing 2020. [DOI: 10.1016/j.neucom.2020.06.103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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17
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Zang Y, Hong S, De Schutter E. Firing rate-dependent phase responses of Purkinje cells support transient oscillations. eLife 2020; 9:e60692. [PMID: 32895121 PMCID: PMC7478895 DOI: 10.7554/elife.60692] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 08/20/2020] [Indexed: 01/09/2023] Open
Abstract
Both spike rate and timing can transmit information in the brain. Phase response curves (PRCs) quantify how a neuron transforms input to output by spike timing. PRCs exhibit strong firing-rate adaptation, but its mechanism and relevance for network output are poorly understood. Using our Purkinje cell (PC) model, we demonstrate that the rate adaptation is caused by rate-dependent subthreshold membrane potentials efficiently regulating the activation of Na+ channels. Then, we use a realistic PC network model to examine how rate-dependent responses synchronize spikes in the scenario of reciprocal inhibition-caused high-frequency oscillations. The changes in PRC cause oscillations and spike correlations only at high firing rates. The causal role of the PRC is confirmed using a simpler coupled oscillator network model. This mechanism enables transient oscillations between fast-spiking neurons that thereby form PC assemblies. Our work demonstrates that rate adaptation of PRCs can spatio-temporally organize the PC input to cerebellar nuclei.
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Affiliation(s)
- Yunliang Zang
- Computational Neuroscience Unit, Okinawa Institute of Science and Technology Graduate UniversityOkinawaJapan
| | - Sungho Hong
- Computational Neuroscience Unit, Okinawa Institute of Science and Technology Graduate UniversityOkinawaJapan
| | - Erik De Schutter
- Computational Neuroscience Unit, Okinawa Institute of Science and Technology Graduate UniversityOkinawaJapan
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18
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Ibañez S, Luebke JI, Chang W, Draguljić D, Weaver CM. Network Models Predict That Pyramidal Neuron Hyperexcitability and Synapse Loss in the dlPFC Lead to Age-Related Spatial Working Memory Impairment in Rhesus Monkeys. Front Comput Neurosci 2020; 13:89. [PMID: 32009920 PMCID: PMC6979278 DOI: 10.3389/fncom.2019.00089] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 12/18/2019] [Indexed: 01/04/2023] Open
Abstract
Behavioral studies have shown spatial working memory impairment with aging in several animal species, including humans. Persistent activity of layer 3 pyramidal dorsolateral prefrontal cortex (dlPFC) neurons during delay periods of working memory tasks is important for encoding memory of the stimulus. In vitro studies have shown that these neurons undergo significant age-related structural and functional changes, but the extent to which these changes affect neural mechanisms underlying spatial working memory is not understood fully. Here, we confirm previous studies showing impairment on the Delayed Recognition Span Task in the spatial condition (DRSTsp), and increased in vitro action potential firing rates (hyperexcitability), across the adult life span of the rhesus monkey. We use a bump attractor model to predict how empirically observed changes in the aging dlPFC affect performance on the Delayed Response Task (DRT), and introduce a model of memory retention in the DRSTsp. Persistent activity-and, in turn, cognitive performance-in both models was affected much more by hyperexcitability of pyramidal neurons than by a loss of synapses. Our DRT simulations predict that additional changes to the network, such as increased firing of inhibitory interneurons, are needed to account for lower firing rates during the DRT with aging reported in vivo. Synaptic facilitation was an essential feature of the DRSTsp model, but it did not compensate fully for the effects of the other age-related changes on DRT performance. Modeling pyramidal neuron hyperexcitability and synapse loss simultaneously led to a partial recovery of function in both tasks, with the simulated level of DRSTsp impairment similar to that observed in aging monkeys. This modeling work integrates empirical data across multiple scales, from synapse counts to cognitive testing, to further our understanding of aging in non-human primates.
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Affiliation(s)
- Sara Ibañez
- Department of Mathematics, Franklin and Marshall College, Lancaster, PA, United States
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
| | - Jennifer I. Luebke
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
| | - Wayne Chang
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
| | - Danel Draguljić
- Department of Mathematics, Franklin and Marshall College, Lancaster, PA, United States
| | - Christina M. Weaver
- Department of Mathematics, Franklin and Marshall College, Lancaster, PA, United States
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19
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Voloh B, Womelsdorf T. Cell-Type Specific Burst Firing Interacts with Theta and Beta Activity in Prefrontal Cortex During Attention States. Cereb Cortex 2019; 28:4348-4364. [PMID: 29136106 DOI: 10.1093/cercor/bhx287] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2017] [Indexed: 12/25/2022] Open
Abstract
Population-level theta and beta band activity in anterior cingulate and prefrontal cortices (ACC/PFC) are prominent signatures of self-controlled, adaptive behaviors. But how these rhythmic activities are linked to cell-type specific activity has remained unclear. Here, we suggest such a cell-to-systems level linkage. We found that the rate of burst spiking events is enhanced particularly during attention states and that attention-specific burst spikes have a unique temporal relationship to local theta and beta band population-level activities. For the 5-10 Hz theta frequency range, bursts coincided with transient increases of local theta power relative to nonbursts, particularly for bursts of putative interneurons. For the 16-30 Hz beta frequency, bursts of putative interneurons phase synchronized stronger than nonbursts, and were associated with larger beta power modulation. In contrast, burst of putative pyramidal cells showed similar beta power modulation as nonbursts, but were accompanied by stronger beta power only when they occurred early in the beta cycle. These findings suggest that in the ACC/PFC during attention states, mechanisms underlying burst firing are intimately linked to narrow band population-level activities, providing a cell-type specific window into rhythmic inhibitory gating and the emergence of rhythmically coherent network states during goal directed behavior.
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Affiliation(s)
- B Voloh
- Department of Biology, Centre for Vision Research, York University, Toronto, Ontario, Canada.,Department of Psychology, Vanderbilt University, PMB 407817, 2301 Vanderbilt Place, Nashville, TN, USA
| | - T Womelsdorf
- Department of Biology, Centre for Vision Research, York University, Toronto, Ontario, Canada.,Department of Psychology, Vanderbilt University, PMB 407817, 2301 Vanderbilt Place, Nashville, TN, USA
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20
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Trainito C, von Nicolai C, Miller EK, Siegel M. Extracellular Spike Waveform Dissociates Four Functionally Distinct Cell Classes in Primate Cortex. Curr Biol 2019; 29:2973-2982.e5. [PMID: 31447374 DOI: 10.1016/j.cub.2019.07.051] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 06/21/2019] [Accepted: 07/17/2019] [Indexed: 11/19/2022]
Abstract
Understanding the function of different neuronal cell types is key to understanding brain function. However, cell-type diversity is typically overlooked in electrophysiological studies in awake behaving animals. Here, we show that four functionally distinct cell classes can be robustly identified from extracellular recordings in several cortical regions of awake behaving monkeys. We recorded extracellular spiking activity from dorsolateral prefrontal cortex (dlPFC), the frontal eye field (FEF), and the lateral intraparietal area of macaque monkeys during a visuomotor decision-making task. We employed unsupervised clustering of spike waveforms, which robustly dissociated four distinct cell classes across all three brain regions. The four cell classes were functionally distinct. They showed different baseline firing statistics, visual response dynamics, and coding of visual information. Although cell-class-specific baseline statistics were consistent across brain regions, response dynamics and information coding were regionally specific. Our results identify four functionally distinct spike-waveform-based cell classes in primate cortex. This opens a new window to dissect and study the cell-type-specific function of cortical circuits.
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Affiliation(s)
- Caterina Trainito
- Centre for Integrative Neuroscience, University of Tübingen, Otfried-Müller-Strasse 25, 72076 Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Otfried-Müller-Strasse 27, 72076 Tübingen, Germany; MEG Center, University of Tübingen, Otfried-Müller-Strasse 47, 72076 Tübingen, Germany; IMPRS for Cognitive and Systems Neuroscience, University of Tübingen, Österbergstrasse 3, 72074 Tübingen, Germany
| | - Constantin von Nicolai
- Centre for Integrative Neuroscience, University of Tübingen, Otfried-Müller-Strasse 25, 72076 Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Otfried-Müller-Strasse 27, 72076 Tübingen, Germany; MEG Center, University of Tübingen, Otfried-Müller-Strasse 47, 72076 Tübingen, Germany
| | - Earl K Miller
- The Picower Institute for Learning and Memory and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Markus Siegel
- Centre for Integrative Neuroscience, University of Tübingen, Otfried-Müller-Strasse 25, 72076 Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Otfried-Müller-Strasse 27, 72076 Tübingen, Germany; MEG Center, University of Tübingen, Otfried-Müller-Strasse 47, 72076 Tübingen, Germany.
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21
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Hassani SA, Lendor S, Boyaci E, Pawliszyn J, Womelsdorf T. Multineuromodulator measurements across fronto-striatal network areas of the behaving macaque using solid-phase microextraction. J Neurophysiol 2019; 122:1649-1660. [PMID: 31433731 DOI: 10.1152/jn.00321.2019] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Different neuromodulators rarely act independent from each other to modify neural processes but are instead coreleased, gated, or modulated. To understand this interdependence of neuromodulators and their collective influence on local circuits during different brain states, it is necessary to reliably extract local concentrations of multiple neuromodulators in vivo. Here we describe results using solid-phase microextraction (SPME), a method providing sensitive, multineuromodulator measurements. SPME is a sampling method that is coupled with mass spectrometry to quantify collected analytes. Reliable measurements of glutamate, dopamine, acetylcholine, and choline were made simultaneously within frontal cortex and striatum of two macaque monkeys (Macaca mulatta) during goal-directed behavior. We find glutamate concentrations several orders of magnitude higher than acetylcholine and dopamine in all brain regions. Dopamine was reliably detected in the striatum at tenfold higher concentrations than acetylcholine. Acetylcholine and choline concentrations were detected with high consistency across brain areas within monkeys and between monkeys. These findings illustrate that SPME microprobes provide a versatile novel tool to characterize multiple neuromodulators across different brain areas in vivo to understand the interdependence and covariation of neuromodulators during goal-directed behavior. Such data would be important to better distinguish between different behavioral states and characterize dysfunctional brain states that may be evident in psychiatric disorders.NEW & NOTEWORTHY Our paper reports a reliable and sensitive novel method for measuring the absolute concentrations of glutamate, acetylcholine, choline, dopamine, and serotonin in brain circuits in vivo. We show that this method reliably samples multiple neurochemicals in three brain areas simultaneously while nonhuman primates are engaged in goal-directed behavior. We further describe how the methodology we describe here may be used by electrophysiologists as a low-barrier-to-entry tool for measuring multiple neurochemicals.
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Affiliation(s)
- Seyed-Alireza Hassani
- Department of Psychology, Vanderbilt University, Nashville, Tennessee.,Department of Biology, Centre for Vision Research, York University, Toronto, Ontario, Canada
| | - Sofia Lendor
- Department of Chemistry, University of Waterloo, Waterloo, Ontario, Canada
| | - Ezel Boyaci
- Department of Chemistry, University of Waterloo, Waterloo, Ontario, Canada
| | - Janusz Pawliszyn
- Department of Chemistry, University of Waterloo, Waterloo, Ontario, Canada
| | - Thilo Womelsdorf
- Department of Psychology, Vanderbilt University, Nashville, Tennessee.,Department of Biology, Centre for Vision Research, York University, Toronto, Ontario, Canada
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22
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Lendor S, Hassani SA, Boyaci E, Singh V, Womelsdorf T, Pawliszyn J. Solid Phase Microextraction-Based Miniaturized Probe and Protocol for Extraction of Neurotransmitters from Brains in Vivo. Anal Chem 2019; 91:4896-4905. [DOI: 10.1021/acs.analchem.9b00995] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Sofia Lendor
- Department of Chemistry, University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1, Canada
| | - Seyed-Alireza Hassani
- Department of Psychology, Vanderbilt University, PMB 407817, 2301 Vanderbilt Place, Nashville, Tennessee 37240, United States
- Department of Biology, Centre for Vision Research, York University, Toronto, Ontario M6J 1P3, Canada
| | - Ezel Boyaci
- Department of Chemistry, University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1, Canada
| | - Varoon Singh
- Department of Chemistry, University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1, Canada
| | - Thilo Womelsdorf
- Department of Psychology, Vanderbilt University, PMB 407817, 2301 Vanderbilt Place, Nashville, Tennessee 37240, United States
- Department of Biology, Centre for Vision Research, York University, Toronto, Ontario M6J 1P3, Canada
| | - Janusz Pawliszyn
- Department of Chemistry, University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1, Canada
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23
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Semedo JD, Zandvakili A, Machens CK, Yu BM, Kohn A. Cortical Areas Interact through a Communication Subspace. Neuron 2019; 102:249-259.e4. [PMID: 30770252 DOI: 10.1016/j.neuron.2019.01.026] [Citation(s) in RCA: 163] [Impact Index Per Article: 32.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Revised: 10/12/2018] [Accepted: 01/14/2019] [Indexed: 01/03/2023]
Abstract
Most brain functions involve interactions among multiple, distinct areas or nuclei. For instance, visual processing in primates requires the appropriate relaying of signals across many distinct cortical areas. Yet our understanding of how populations of neurons in interconnected brain areas communicate is in its infancy. Here we investigate how trial-to-trial fluctuations of population responses in primary visual cortex (V1) are related to simultaneously recorded population responses in area V2. Using dimensionality reduction methods, we find that V1-V2 interactions occur through a communication subspace: V2 fluctuations are related to a small subset of V1 population activity patterns, distinct from the largest fluctuations shared among neurons within V1. In contrast, interactions between subpopulations within V1 are less selective. We propose that the communication subspace may be a general, population-level mechanism by which activity can be selectively routed across brain areas.
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Affiliation(s)
- João D Semedo
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA; Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal; Department of Electrical and Computer Engineering, Instituto Superior Técnico, Lisbon, Portugal.
| | - Amin Zandvakili
- Dominick Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Christian K Machens
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Byron M Yu
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Adam Kohn
- Dominick Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA; Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, USA; Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, USA
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24
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Oemisch M, Westendorff S, Azimi M, Hassani SA, Ardid S, Tiesinga P, Womelsdorf T. Feature-specific prediction errors and surprise across macaque fronto-striatal circuits. Nat Commun 2019; 10:176. [PMID: 30635579 PMCID: PMC6329800 DOI: 10.1038/s41467-018-08184-9] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 12/20/2018] [Indexed: 01/23/2023] Open
Abstract
To adjust expectations efficiently, prediction errors need to be associated with the precise features that gave rise to the unexpected outcome, but this credit assignment may be problematic if stimuli differ on multiple dimensions and it is ambiguous which feature dimension caused the outcome. Here, we report a potential solution: neurons in four recorded areas of the anterior fronto-striatal networks encode prediction errors that are specific to feature values of different dimensions of attended multidimensional stimuli. The most ubiquitous prediction error occurred for the reward-relevant dimension. Feature-specific prediction error signals a) emerge on average shortly after non-specific prediction error signals, b) arise earliest in the anterior cingulate cortex and later in dorsolateral prefrontal cortex, caudate and ventral striatum, and c) contribute to feature-based stimulus selection after learning. Thus, a widely-distributed feature-specific eligibility trace may be used to update synaptic weights for improved feature-based attention. In order to adjust expectations efficiently, prediction errors need to be associated with the features that gave rise to the unexpected outcome. Here, the authors show that neurons in anterior fronto-striatal networks encode prediction errors that are specific to feature values of different stimulus dimensions.
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Affiliation(s)
- Mariann Oemisch
- Department of Biology, Centre for Vision Research, York University, 4700 Keele Street, Toronto, ON, M6J 1P3, Canada. .,Department of Neuroscience, Yale University School of Medicine, New Haven, CT, 06510, USA.
| | - Stephanie Westendorff
- Department of Biology, Centre for Vision Research, York University, 4700 Keele Street, Toronto, ON, M6J 1P3, Canada.,Institute of Neurobiology, University of Tübingen, Tübingen, 72076, Germany
| | - Marzyeh Azimi
- Department of Biology, Centre for Vision Research, York University, 4700 Keele Street, Toronto, ON, M6J 1P3, Canada
| | - Seyed Alireza Hassani
- Department of Biology, Centre for Vision Research, York University, 4700 Keele Street, Toronto, ON, M6J 1P3, Canada.,Department of Psychology, Vanderbilt University, Nashville, TN, 37240, USA
| | - Salva Ardid
- Department of Mathematics and Statistics, Boston University, Boston, MA, 02215, USA
| | - Paul Tiesinga
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, 6525 EN, Netherlands
| | - Thilo Womelsdorf
- Department of Biology, Centre for Vision Research, York University, 4700 Keele Street, Toronto, ON, M6J 1P3, Canada. .,Department of Psychology, Vanderbilt University, Nashville, TN, 37240, USA.
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25
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Asymmetric effective connectivity between primate anterior cingulate and lateral prefrontal cortex revealed by electrical microstimulation. Brain Struct Funct 2018; 224:779-793. [DOI: 10.1007/s00429-018-1806-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Accepted: 11/27/2018] [Indexed: 10/27/2022]
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26
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Kolling N, Scholl J, Chekroud A, Trier HA, Rushworth MFS. Prospection, Perseverance, and Insight in Sequential Behavior. Neuron 2018; 99:1069-1082.e7. [PMID: 30189202 PMCID: PMC6127030 DOI: 10.1016/j.neuron.2018.08.018] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 06/14/2018] [Accepted: 08/16/2018] [Indexed: 12/29/2022]
Abstract
Real-world decisions have benefits occurring only later and dependent on additional decisions taken in the interim. We investigated this in a novel decision-making task in humans (n = 76) while measuring brain activity with fMRI (n = 24). Modeling revealed that participants computed the prospective value of decisions: they planned their future behavior taking into account how their decisions might affect which states they would encounter and how they themselves might respond in these states. They considered their own likely future behavioral biases (e.g., failure to adapt to changes in prospective value) and avoided situations in which they might be prone to such biases. Three neural networks in adjacent medial frontal regions were linked to distinct components of prospective decision making: activity in dorsal anterior cingulate cortex, area 8 m/9, and perigenual anterior cingulate cortex reflected prospective value, anticipated changes in prospective value, and the degree to which prospective value influenced decisions.
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Affiliation(s)
- Nils Kolling
- Department of Experimental Psychology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Oxford Centre of Human Brain Activity, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Jacqueline Scholl
- Department of Experimental Psychology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Adam Chekroud
- Department of Experimental Psychology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
| | - Hailey A Trier
- Department of Experimental Psychology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Matthew F S Rushworth
- Department of Experimental Psychology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Centre for Functional MRI of the Brain (MRI), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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27
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Abstract
Understanding how cognitive processes affect the responses of sensory neurons may clarify the relationship between neuronal population activity and behavior. However, tools for analyzing neuronal activity have not kept up with technological advances in recording from large neuronal populations. Here, we describe prevalent hypotheses of how cognitive processes affect sensory neurons, driven largely by a model based on the activity of single neurons or pools of neurons as the units of computation. We then use simple simulations to expand this model to a new conceptual framework that focuses on subspaces of population activity as the relevant units of computation, uses comparisons between brain areas or to behavior to guide analyses of these subspaces, and suggests that population activity is optimized to decode the large variety of stimuli and tasks that animals encounter in natural behavior. This framework provides new ways of understanding the ever-growing quantity of recorded population activity data.
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Affiliation(s)
- Douglas A Ruff
- Department of Neuroscience and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA;
| | - Amy M Ni
- Department of Neuroscience and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA;
| | - Marlene R Cohen
- Department of Neuroscience and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA;
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28
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Stolyarova A. Solving the Credit Assignment Problem With the Prefrontal Cortex. Front Neurosci 2018; 12:182. [PMID: 29636659 PMCID: PMC5881225 DOI: 10.3389/fnins.2018.00182] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Accepted: 03/06/2018] [Indexed: 12/13/2022] Open
Abstract
In naturalistic multi-cue and multi-step learning tasks, where outcomes of behavior are delayed in time, discovering which choices are responsible for rewards can present a challenge, known as the credit assignment problem. In this review, I summarize recent work that highlighted a critical role for the prefrontal cortex (PFC) in assigning credit where it is due in tasks where only a few of the multitude of cues or choices are relevant to the final outcome of behavior. Collectively, these investigations have provided compelling support for specialized roles of the orbitofrontal (OFC), anterior cingulate (ACC), and dorsolateral prefrontal (dlPFC) cortices in contingent learning. However, recent work has similarly revealed shared contributions and emphasized rich and heterogeneous response properties of neurons in these brain regions. Such functional overlap is not surprising given the complexity of reciprocal projections spanning the PFC. In the concluding section, I overview the evidence suggesting that the OFC, ACC and dlPFC communicate extensively, sharing the information about presented options, executed decisions and received rewards, which enables them to assign credit for outcomes to choices on which they are contingent. This account suggests that lesion or inactivation/inhibition experiments targeting a localized PFC subregion will be insufficient to gain a fine-grained understanding of credit assignment during learning and instead poses refined questions for future research, shifting the focus from focal manipulations to experimental techniques targeting cortico-cortical projections.
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Affiliation(s)
- Alexandra Stolyarova
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States
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29
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Abstract
PURPOSE OF REVIEW The computational power of the brain arises from the complex interactions between neurons. One straightforward method to quantify the strength of neuronal interactions is by measuring correlation and coherence. Efforts to measure correlation have been advancing rapidly of late, spurred by the development of advanced recording technologies enabling recording from many neurons and brain areas simultaneously. This review highlights recent results that provide clues into the principles of neural coordination, connections to cognitive and neurological phenomena, and key directions for future research. RECENT FINDINGS The correlation structure of neural activity in the brain has important consequences for the encoding properties of neural populations. Recent studies have shown that this correlation structure is not fixed, but adapts in a variety of contexts in ways that appear beneficial to task performance. By studying these changes in biological neural networks and computational models, researchers have improved our understanding of the principles guiding neural communication. SUMMARY Correlation and coherence are highly informative metrics for studying coding and communication in the brain. Recent findings have emphasized how the brain modifies correlation structure dynamically in order to improve information-processing in a goal-directed fashion. One key direction for future research concerns how to leverage these dynamic changes for therapeutic purposes.
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30
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Neuronal Encoding of Self and Others' Head Rotation in the Macaque Dorsal Prefrontal Cortex. Sci Rep 2017; 7:8571. [PMID: 28819117 PMCID: PMC5561028 DOI: 10.1038/s41598-017-08936-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Accepted: 07/17/2017] [Indexed: 12/25/2022] Open
Abstract
Following gaze is a crucial skill, in primates, for understanding where and at what others are looking, and often requires head rotation. The neural basis underlying head rotation are deemed to overlap with the parieto-frontal attention/gaze-shift network. Here, we show that a set of neurons in monkey’s Brodmann area 9/46dr (BA 9/46dr), which is involved in orienting processes and joint attention, becomes active during self head rotation and that the activity of these neurons cannot be accounted for by saccade-related activity (head-rotation neurons). Another set of BA 9/46dr neurons encodes head rotation performed by an observed agent facing the monkey (visually triggered neurons). Among these latter neurons, almost half exhibit the intriguing property of encoding both execution and observation of head rotation (mirror-like neurons). Finally, by means of neuronal tracing techniques, we showed that BA 9/46dr takes part into two distinct networks: a dorso/mesial network, playing a role in spatial head/gaze orientation, and a ventrolateral network, likely involved in processing social stimuli and mirroring others’ head. The overall results of this study provide a new, comprehensive picture of the role of BA 9/46dr in encoding self and others’ head rotation, likely playing a role in head-following behaviors.
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31
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Attention Increases Spike Count Correlations between Visual Cortical Areas. J Neurosci 2017; 36:7523-34. [PMID: 27413161 DOI: 10.1523/jneurosci.0610-16.2016] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2016] [Accepted: 06/04/2016] [Indexed: 11/21/2022] Open
Abstract
UNLABELLED Visual attention, which improves perception of attended locations or objects, has long been known to affect many aspects of the responses of neuronal populations in visual cortex. There are two nonmutually exclusive hypotheses concerning the neuronal mechanisms that underlie these perceptual improvements. The first hypothesis, that attention improves the information encoded by a population of neurons in a particular cortical area, has considerable physiological support. The second hypothesis is that attention improves perception by selectively communicating relevant visual information. This idea has been tested primarily by measuring interactions between neurons on very short timescales, which are mathematically nearly independent of neuronal interactions on longer timescales. We tested the hypothesis that attention changes the way visual information is communicated between cortical areas on longer timescales by recording simultaneously from neurons in primary visual cortex (V1) and the middle temporal area (MT) in rhesus monkeys. We used two independent and complementary approaches. Our correlative experiment showed that attention increases the trial-to-trial response variability that is shared between the two areas. In our causal experiment, we electrically microstimulated V1 and found that attention increased the effect of stimulation on MT responses. Together, our results suggest that attention affects both the way visual stimuli are encoded within a cortical area and the extent to which visual information is communicated between areas on behaviorally relevant timescales. SIGNIFICANCE STATEMENT Visual attention dramatically improves the perception of attended stimuli. Attention has long been thought to act by selecting relevant visual information for further processing. It has been hypothesized that this selection is accomplished by increasing communication between neurons that encode attended information in different cortical areas. We recorded simultaneously from neurons in primary visual cortex and the middle temporal area while rhesus monkeys performed an attention task. We found that attention increased shared variability between neurons in the two areas and that attention increased the effect of microstimulation in V1 on the firing rates of MT neurons. Our results provide support for the hypothesis that attention increases communication between neurons in different brain areas on behaviorally relevant timescales.
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Cued Memory Retrieval Exhibits Reinstatement of High Gamma Power on a Faster Timescale in the Left Temporal Lobe and Prefrontal Cortex. J Neurosci 2017; 37:4472-4480. [PMID: 28336569 DOI: 10.1523/jneurosci.3810-16.2017] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Revised: 02/27/2017] [Accepted: 03/02/2017] [Indexed: 01/12/2023] Open
Abstract
Converging evidence suggests that reinstatement of neural activity underlies our ability to successfully retrieve memories. However, the temporal dynamics of reinstatement in the human cortex remain poorly understood. One possibility is that neural activity during memory retrieval, like replay of spiking neurons in the hippocampus, occurs at a faster timescale than during encoding. We tested this hypothesis in 34 participants who performed a verbal episodic memory task while we recorded high gamma (62-100 Hz) activity from subdural electrodes implanted for seizure monitoring. We show that reinstatement of distributed patterns of high gamma activity occurs faster than during encoding. Using a time-warping algorithm, we quantify the timescale of the reinstatement and identify brain regions that show significant timescale differences between encoding and retrieval. Our data suggest that temporally compressed reinstatement of cortical activity is a feature of cued memory retrieval.SIGNIFICANCE STATEMENT We show that cued memory retrieval reinstates neural activity on a faster timescale than was present during encoding. Our data therefore provide a link between reinstatement of neural activity in the cortex and spontaneous replay of cortical and hippocampal spiking activity, which also exhibits temporal compression, and suggest that temporal compression may be a universal feature of memory retrieval.
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Attenuated contact heat-evoked potentials associated with sensory and social-emotional symptoms in individuals with autism spectrum disorder. Sci Rep 2017; 7:36887. [PMID: 28139664 PMCID: PMC5282530 DOI: 10.1038/srep36887] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2016] [Accepted: 07/26/2016] [Indexed: 02/06/2023] Open
Abstract
Sensory disturbance is associated with socio-emotional problems in individuals with autism spectrum disorder (ASD). Most studies assess sensory symptoms by self-reports, which are largely limited by the language ability and self-awareness of the individuals. This study aims to investigate sensory disturbance by contact heat-evoked potentials (CHEP) in ASD individuals, and to examine the clinical correlates of CHEP parameters. We compared the CHEP parameters and reported pain between 31 ASD individuals (aged 20.5 ± 5.2 years) and and 22 typically-developing controls (TD, aged 21.4 ± 2.6), and correlated the CHEP parameters with self-reported sensory symptoms and attention/socio-emotional symptoms. We found that ASD individuals showed smaller P2-wave amplitudes than TD, even though they reported a similar level of pain. In TD individuals, a smaller P2-wave amplitude was related to higher scores on ‘low registration,’ ‘attention to detail,’ and ‘attention switching difficulties.’ In ASD individuals, longer N2-wave latency was related to higher scores on ‘sensory sensitivity’ and socio-emotional problems; while higher reported pain was associated with higher scores on ‘low registration,’ overall autistic severity, and longer N2-wave latency. Our findings of attenuated CHEP response in ASD, which was associated with sensory symptoms and socio-emotional problems, suggest a potential role for CHEP in studying sensory disturbances in ASD.
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Kolling N, Behrens T, Wittmann MK, Rushworth M. Multiple signals in anterior cingulate cortex. Curr Opin Neurobiol 2016; 37:36-43. [PMID: 26774693 PMCID: PMC4863523 DOI: 10.1016/j.conb.2015.12.007] [Citation(s) in RCA: 144] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Revised: 12/15/2015] [Accepted: 12/17/2015] [Indexed: 12/23/2022]
Abstract
There are multiple signals in anterior cingulate cortex (ACC). ACC activity reflects value of behavioural change even after controlling for difficulty. ACC activity reflects updating of internal models even after controlling for difficulty.
Activity in anterior cingulate cortex (ACC) has been linked both to commitment to a course of action, even when it is associated with costs, and to exploring or searching for alternative courses of action. Here we review evidence that this is due to the presence of multiple signals in ACC reflecting the updating of beliefs and internal models of the environment and encoding aspects of choice value, including the average value of choices afforded by the environment (‘search value’). We contrast this evidence with the influential view that ACC activity is better described as reflecting task difficulty. A consideration of cortical neural network properties explains why ACC may carry such signals and also exhibit sensitivity to task difficulty.
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Affiliation(s)
- N Kolling
- Department of Experimental Psychology, University of Oxford, Oxford, UK.
| | - Tej Behrens
- Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, UK
| | - M K Wittmann
- Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Mfs Rushworth
- Department of Experimental Psychology, University of Oxford, Oxford, UK; Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, UK
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