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Klug S, Murgaš M, Godbersen GM, Hacker M, Lanzenberger R, Hahn A. Synaptic signaling modeled by functional connectivity predicts metabolic demands of the human brain. Neuroimage 2024; 295:120658. [PMID: 38810891 DOI: 10.1016/j.neuroimage.2024.120658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 04/22/2024] [Accepted: 05/27/2024] [Indexed: 05/31/2024] Open
Abstract
PURPOSE The human brain is characterized by interacting large-scale functional networks fueled by glucose metabolism. Since former studies could not sufficiently clarify how these functional connections shape glucose metabolism, we aimed to provide a neurophysiologically-based approach. METHODS 51 healthy volunteers underwent simultaneous PET/MRI to obtain BOLD functional connectivity and [18F]FDG glucose metabolism. These multimodal imaging proxies of fMRI and PET were combined in a whole-brain extension of metabolic connectivity mapping. Specifically, functional connectivity of all brain regions were used as input to explain glucose metabolism of a given target region. This enabled the modeling of postsynaptic energy demands by incoming signals from distinct brain regions. RESULTS Functional connectivity input explained a substantial part of metabolic demands but with pronounced regional variations (34 - 76%). During cognitive task performance this multimodal association revealed a shift to higher network integration compared to resting state. In healthy aging, a dedifferentiation (decreased segregated/modular structure of the brain) of brain networks during rest was observed. Furthermore, by including data from mRNA maps, [11C]UCB-J synaptic density and aerobic glycolysis (oxygen-to-glucose index from PET data), we show that whole-brain functional input reflects non-oxidative, on-demand metabolism of synaptic signaling. The metabolically-derived directionality of functional inputs further marked them as top-down predictions. In addition, the approach uncovered formerly hidden networks with superior efficiency through metabolically informed network partitioning. CONCLUSIONS Applying multimodal imaging, we decipher a crucial part of the metabolic and neurophysiological basis of functional connections in the brain as interregional on-demand synaptic signaling fueled by anaerobic metabolism. The observed task- and age-related effects indicate promising future applications to characterize human brain function and clinical alterations.
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Affiliation(s)
- Sebastian Klug
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Matej Murgaš
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Godber M Godbersen
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Marcus Hacker
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Andreas Hahn
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria.
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2
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DiNuzzo M, Dienel GA, Behar KL, Petroff OA, Benveniste H, Hyder F, Giove F, Michaeli S, Mangia S, Herculano-Houzel S, Rothman DL. Neurovascular coupling is optimized to compensate for the increase in proton production from nonoxidative glycolysis and glycogenolysis during brain activation and maintain homeostasis of pH, pCO 2, and pO 2. J Neurochem 2024; 168:632-662. [PMID: 37150946 PMCID: PMC10628336 DOI: 10.1111/jnc.15839] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 04/22/2023] [Accepted: 05/02/2023] [Indexed: 05/09/2023]
Abstract
During transient brain activation cerebral blood flow (CBF) increases substantially more than cerebral metabolic rate of oxygen consumption (CMRO2) resulting in blood hyperoxygenation, the basis of BOLD-fMRI contrast. Explanations for the high CBF versus CMRO2 slope, termed neurovascular coupling (NVC) constant, focused on maintenance of tissue oxygenation to support mitochondrial ATP production. However, paradoxically the brain has a 3-fold lower oxygen extraction fraction (OEF) than other organs with high energy requirements, like heart and muscle during exercise. Here, we hypothesize that the NVC constant and the capillary oxygen mass transfer coefficient (which in combination determine OEF) are co-regulated during activation to maintain simultaneous homeostasis of pH and partial pressure of CO2 and O2 (pCO2 and pO2). To test our hypothesis, we developed an arteriovenous flux balance model for calculating blood and brain pH, pCO2, and pO2 as a function of baseline OEF (OEF0), CBF, CMRO2, and proton production by nonoxidative metabolism coupled to ATP hydrolysis. Our model was validated against published brain arteriovenous difference studies and then used to calculate pH, pCO2, and pO2 in activated human cortex from published calibrated fMRI and PET measurements. In agreement with our hypothesis, calculated pH, pCO2, and pO2 remained close to constant independently of CMRO2 in correspondence to experimental measurements of NVC and OEF0. We also found that the optimum values of the NVC constant and OEF0 that ensure simultaneous homeostasis of pH, pCO2, and pO2 were remarkably similar to their experimental values. Thus, the high NVC constant is overall determined by proton removal by CBF due to increases in nonoxidative glycolysis and glycogenolysis. These findings resolve the paradox of the brain's high CBF yet low OEF during activation, and may contribute to explaining the vulnerability of brain function to reductions in blood flow and capillary density with aging and neurovascular disease.
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Affiliation(s)
| | - Gerald A Dienel
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR, 72205 USA
- Department of Cell Biology and Physiology, University of New Mexico School of Medicine, Albuquerque, NM, 87131 USA
| | - Kevin L Behar
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06511 USA
| | - Ognen A Petroff
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06511 USA
| | - Helene Benveniste
- Department of Anesthesiology, Yale University, New Haven, CT, 06520 USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520 USA
| | - Fahmeed Hyder
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520 USA
- Department of Radiology, Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, 06520 USA
| | - Federico Giove
- Centro Ricerche Enrico Fermi, Rome, RM, 00184 Italy
- Fondazione Santa Lucia IRCCS, Rome, RM, 00179 Italy
| | - Shalom Michaeli
- Department of Radiology, Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, 55455 USA
| | - Silvia Mangia
- Department of Radiology, Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, 55455 USA
| | - Suzana Herculano-Houzel
- Department of Psychology, Vanderbilt University, Nashville, TN
- Department of Biological Sciences, Vanderbilt University, Nashville, TN
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN
| | - Douglas L Rothman
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520 USA
- Department of Radiology, Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, 06520 USA
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3
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Theriault JE, Shaffer C, Dienel GA, Sander CY, Hooker JM, Dickerson BC, Barrett LF, Quigley KS. A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments. Neurosci Biobehav Rev 2023; 153:105373. [PMID: 37634556 PMCID: PMC10591873 DOI: 10.1016/j.neubiorev.2023.105373] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/28/2023] [Accepted: 08/23/2023] [Indexed: 08/29/2023]
Abstract
In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.
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Affiliation(s)
- Jordan E Theriault
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
| | - Clare Shaffer
- Northeastern University, Department of Psychology, Boston, MA, USA
| | - Gerald A Dienel
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Department of Cell Biology and Physiology, University of New Mexico, Albuquerque, NM, USA
| | - Christin Y Sander
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Jacob M Hooker
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Bradford C Dickerson
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Lisa Feldman Barrett
- Northeastern University, Department of Psychology, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Karen S Quigley
- Northeastern University, Department of Psychology, Boston, MA, USA; VA Bedford Healthcare System, Bedford, MA, USA
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Yoo JH, Park YW, Kim D, Park H, Jeong B. Effects of Parental Verbal Abuse Experience on the Glutamate Response to Swear Words in the Ventromedial Prefrontal Cortex: A Functional 1H-magnetic Resonance Spectroscopy Study. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE : THE OFFICIAL SCIENTIFIC JOURNAL OF THE KOREAN COLLEGE OF NEUROPSYCHOPHARMACOLOGY 2023; 21:559-571. [PMID: 37424423 PMCID: PMC10335905 DOI: 10.9758/cpn.22.1019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/12/2022] [Accepted: 10/17/2022] [Indexed: 07/11/2023]
Abstract
Objective Several lines of evidence indicate verbal abuse (VA) critically impacts the developing brain; however, whether VA results in changes in brain neurochemistry has not been established. Here, we hypothesized that exposure to recurrent parental VA elicits heightened glutamate (Glu) responses during the presentation of swear words, which can be measured with functional magnetic resonance spectroscopy (fMRS). Methods During an emotional Stroop task consisting of blocks of color and swear words, metabolite concentration changes were measured in the ventromedial prefrontal cortex (vmPFC) and the left amygdalohippocampal region (AMHC) of healthy adults (14 F/27 M, 23 ± 4 years old) using fMRS. The dynamic changes in Glu and their associations with the emotional state of the participants were finally evaluated based on 36 datasets from the vmPFC and 30 from the AMHC. Results A repeated-measures analysis of covariance revealed a modest effect of parental VA severity on Glu changes in the vmPFC. The total score on the Verbal Abuse Questionnaire by parents (pVAQ) was associated with the Glu response to swear words (ΔGluSwe). The interaction term of ΔGluSwe and baseline N-acetyl aspartate (NAA) level in the vmPFC could be used to predict state-trait anxiety level and depressive mood. We could not find any significant associations between ΔGluSwe in the AMHC and either pVAQ or emotional states. Conclusion Parental VA exposure in individuals is associated with a greater Glu response towards VA-related stimuli in the vmPFC and that the accompanying low NAA level may be associated with anxiety level or depressive mood.
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Affiliation(s)
- Jae Hyun Yoo
- Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
| | - Young Woo Park
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Dohyun Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
- Department of Psychiatry, Dankook University College of Medicine, Cheonan, Korea
| | - HyunWook Park
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
| | - Bumseok Jeong
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
- KAIST Institute for Health Science and Technology and KI for Artificial Intelligence, KAIST, Daejeon, Korea
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5
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Bednarik P, Goranovic D, Svatkova A, Niess F, Hingerl L, Strasser B, Deelchand DK, Spurny-Dworak B, Krssak M, Trattnig S, Hangel G, Scherer T, Lanzenberger R, Bogner W. 1H magnetic resonance spectroscopic imaging of deuterated glucose and of neurotransmitter metabolism at 7 T in the human brain. Nat Biomed Eng 2023; 7:1001-1013. [PMID: 37106154 PMCID: PMC10861140 DOI: 10.1038/s41551-023-01035-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 03/30/2023] [Indexed: 04/29/2023]
Abstract
Impaired glucose metabolism in the brain has been linked to several neurological disorders. Positron emission tomography and carbon-13 magnetic resonance spectroscopic imaging (MRSI) can be used to quantify the metabolism of glucose, but these methods involve exposure to radiation, cannot quantify downstream metabolism, or have poor spatial resolution. Deuterium MRSI (2H-MRSI) is a non-invasive and safe alternative for the quantification of the metabolism of 2H-labelled substrates such as glucose and their downstream metabolic products, yet it can only measure a limited number of deuterated compounds and requires specialized hardware. Here we show that proton MRSI (1H-MRSI) at 7 T has higher sensitivity, chemical specificity and spatiotemporal resolution than 2H-MRSI. We used 1H-MRSI in five volunteers to differentiate glutamate, glutamine, γ-aminobutyric acid and glucose deuterated at specific molecular positions, and to simultaneously map deuterated and non-deuterated metabolites. 1H-MRSI, which is amenable to clinically available magnetic-resonance hardware, may facilitate the study of glucose metabolism in the brain and its potential roles in neurological disorders.
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Affiliation(s)
- Petr Bednarik
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark.
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark.
| | - Dario Goranovic
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Alena Svatkova
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna, Vienna, Austria
| | - Fabian Niess
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lukas Hingerl
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Dinesh K Deelchand
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Benjamin Spurny-Dworak
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Martin Krssak
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Gilbert Hangel
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
| | - Thomas Scherer
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
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6
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Koolschijn RS, Clarke WT, Ip IB, Emir UE, Barron HC. Event-related functional magnetic resonance spectroscopy. Neuroimage 2023; 276:120194. [PMID: 37244321 PMCID: PMC7614684 DOI: 10.1016/j.neuroimage.2023.120194] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 05/24/2023] [Indexed: 05/29/2023] Open
Abstract
Proton-Magnetic Resonance Spectroscopy (MRS) is a non-invasive brain imaging technique used to measure the concentration of different neurochemicals. "Single-voxel" MRS data is typically acquired across several minutes, before individual transients are averaged through time to give a measurement of neurochemical concentrations. However, this approach is not sensitive to more rapid temporal dynamics of neurochemicals, including those that reflect functional changes in neural computation relevant to perception, cognition, motor control and ultimately behaviour. In this review we discuss recent advances in functional MRS (fMRS) that now allow us to obtain event-related measures of neurochemicals. Event-related fMRS involves presenting different experimental conditions as a series of trials that are intermixed. Critically, this approach allows spectra to be acquired at a time resolution in the order of seconds. Here we provide a comprehensive user guide for event-related task designs, choice of MRS sequence, analysis pipelines, and appropriate interpretation of event-related fMRS data. We raise various technical considerations by examining protocols used to quantify dynamic changes in GABA, the primary inhibitory neurotransmitter in the brain. Overall, we propose that although more data is needed, event-related fMRS can be used to measure dynamic changes in neurochemicals at a temporal resolution relevant to computations that support human cognition and behaviour.
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Affiliation(s)
- Renée S Koolschijn
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, United Kingdom; Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands.
| | - William T Clarke
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, United Kingdom; Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - I Betina Ip
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, United Kingdom
| | - Uzay E Emir
- School of Health Sciences, Purdue University, West Lafayette, United States
| | - Helen C Barron
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, United Kingdom; Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom.
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7
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Vella O, Bagshaw AP, Wilson M. SLIPMAT: a pipeline for extracting tissue-specific spectral profiles from 1H MR spectroscopic imaging data. Neuroimage 2023:120235. [PMID: 37331644 DOI: 10.1016/j.neuroimage.2023.120235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 06/15/2023] [Indexed: 06/20/2023] Open
Abstract
1H Magnetic Resonance Spectroscopy (MRS) is an important non-invasive tool for measuring brain metabolism, with numerous applications in the neuroscientific and clinical domains. In this work we present a new analysis pipeline (SLIPMAT), designed to extract high-quality, tissue-specific, spectral profiles from MR spectroscopic imaging data (MRSI). Spectral decomposition is combined with spatially dependant frequency and phase correction to yield high SNR white and grey matter spectra without partial-volume contamination. A subsequent series of spectral processing steps are applied to reduce unwanted spectral variation, such as baseline correction and linewidth matching, before direct spectral analysis with machine learning and traditional statistical methods. The method is validated using a 2D semi-LASER MRSI sequence, with a 5-minute duration, from data acquired in triplicate across 8 healthy participants. Reliable spectral profiles are confirmed with principal component analysis, revealing the importance of total-choline and scyllo-inositol levels in distinguishing between individuals - in good agreement with our previous work. Furthermore, since the method allows the simultaneous measurement of metabolites in grey and white matter, we show the strong discriminative value of these metabolites in both tissue types for the first time. In conclusion, we present a novel and time efficient MRSI acquisition and processing pipeline, capable of detecting reliable neuro-metabolic differences between healthy individuals, and suitable for the sensitive neurometabolic profiling of in-vivo brain tissue.
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Affiliation(s)
- Olivia Vella
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, UK
| | - Andrew P Bagshaw
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, UK
| | - Martin Wilson
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, UK.
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8
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Ciobanu MM, Manoliu DR, Ciobotaru MC, Anchidin BG, Matei M, Munteanu M, Frunză G, Murariu OC, Flocea EI, Boișteanu PC. The Influence of Sensory Characteristics of Game Meat on Consumer Neuroperception: A Narrative Review. Foods 2023; 12:foods12061341. [PMID: 36981266 PMCID: PMC10048761 DOI: 10.3390/foods12061341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 03/11/2023] [Accepted: 03/20/2023] [Indexed: 03/30/2023] Open
Abstract
Game meat contains bioactive compounds that directly influence the formation of a rich reservoir of flavor precursors that produce specific sensory properties. Quality is considered one of the most influential determinants of consumer behavior, but the interpretation of this concept differs between consumers. Although recognized for its quality, its unique sensory characteristics (smell, taste, aroma) may have a major impact on consumer perception. The aim of this review is to describe the consumer behavior regarding game meat through elements of neuroperception, using methods of analysis, observation, and interpretation of scientific information from the literature. Following the analysis of published papers on this topic, it was shown that external factors influencing the biological basis of behavior could provide explanations for the acceptance or rejection of this type of meat and solutions. Neuroperception can explain the mechanism behind consumer decision-making. The influence of extrinsic factors (environment, mood, emotions, stress) shapes the perception of the quality attributes of game meat, the unique sensory characteristics of game meat passing through a primary filter of sensory receptors (eyes, nose, tongue, etc). Game meat is darker and tougher (compared to meat from domestic animals), and the taste and smell have the power to trigger memories and change the mood, influencing consumer behavior. Understanding consumer attitudes towards game meat in relation to quality attributes and the physiology of sensory perception can provide important insights for food industry professionals, processors, sensory evaluators, and researchers.
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Affiliation(s)
- Marius-Mihai Ciobanu
- Faculty of Agriculture, "Ion Ionescu de la Brad" University of Life Sciences, M. Sadoveanu Alley, No. 3, 700490 Iasi, Romania
| | - Diana-Remina Manoliu
- Faculty of Animal and Food Resources Engineering, "Ion Ionescu de la Brad" University of Life Sciences, M. Sadoveanu Alley, No. 8, 700490 Iasi, Romania
| | - Mihai-Cătălin Ciobotaru
- Faculty of Agriculture, "Ion Ionescu de la Brad" University of Life Sciences, M. Sadoveanu Alley, No. 3, 700490 Iasi, Romania
| | - Bianca-Georgiana Anchidin
- Faculty of Animal and Food Resources Engineering, "Ion Ionescu de la Brad" University of Life Sciences, M. Sadoveanu Alley, No. 8, 700490 Iasi, Romania
| | - Mădălina Matei
- Faculty of Animal and Food Resources Engineering, "Ion Ionescu de la Brad" University of Life Sciences, M. Sadoveanu Alley, No. 8, 700490 Iasi, Romania
| | - Mugurel Munteanu
- Faculty of Animal and Food Resources Engineering, "Ion Ionescu de la Brad" University of Life Sciences, M. Sadoveanu Alley, No. 8, 700490 Iasi, Romania
| | - Gabriela Frunză
- Faculty of Agriculture, "Ion Ionescu de la Brad" University of Life Sciences, M. Sadoveanu Alley, No. 3, 700490 Iasi, Romania
| | - Otilia Cristina Murariu
- Faculty of Agriculture, "Ion Ionescu de la Brad" University of Life Sciences, M. Sadoveanu Alley, No. 3, 700490 Iasi, Romania
| | - Elena-Iuliana Flocea
- Faculty of Agriculture, "Ion Ionescu de la Brad" University of Life Sciences, M. Sadoveanu Alley, No. 3, 700490 Iasi, Romania
| | - Paul-Corneliu Boișteanu
- Faculty of Animal and Food Resources Engineering, "Ion Ionescu de la Brad" University of Life Sciences, M. Sadoveanu Alley, No. 8, 700490 Iasi, Romania
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9
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Frangou P, Clarke WT. Where functional MRI stops, metabolism starts. eLife 2022; 11:78327. [PMID: 35467531 PMCID: PMC9038188 DOI: 10.7554/elife.78327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Combining techniques that track blood oxygenation and biochemicals during neuronal activity reveals how the brain computes perceived and unperceived stimuli.
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Affiliation(s)
- Polytimi Frangou
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - William T Clarke
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
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