Perception is associated with the brain’s metabolic response to sensory stimulation

  1. Mauro DiNuzzo
  2. Silvia Mangia
  3. Marta Moraschi
  4. Daniele Mascali
  5. Gisela E Hagberg
  6. Federico Giove

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    Evaluation Summary:

    Giove and colleagues demonstrate an intriguing dissociation of neurovascular (as measured with BOLD-fMRI) and neurometabolic (measured with fMRS) responses during perception. This is a thought-provoking study that makes one wonder about the signals we measure with human neuroimaging, especially fMRI. It will therefore be of great interest to the broad community of neuroimagers, as well as perception researchers.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1, Reviewer #2 and Reviewer #3 agreed to share their name with the authors.)

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Abstract

Processing of incoming sensory stimulation triggers an increase of cerebral perfusion and blood oxygenation (neurovascular response) as well as an alteration of the metabolic neurochemical profile (neurometabolic response). Here, we show in human primary visual cortex (V1) that perceived and unperceived isoluminant chromatic flickering stimuli designed to have similar neurovascular responses as measured by blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) have markedly different neurometabolic responses as measured by proton functional magnetic resonance spectroscopy (1H-fMRS). In particular, a significant regional buildup of lactate, an index of aerobic glycolysis, and glutamate, an index of malate–aspartate shuttle, occurred in V1 only when the flickering was perceived, without any relation with other behavioral or physiological variables. Whereas the BOLD-fMRI signal in V1, a proxy for input to V1, was insensitive to flickering perception by design, the BOLD-fMRI signal in secondary visual areas was larger during perceived than unperceived flickering, indicating increased output from V1. These results demonstrate that the upregulation of energy metabolism induced by visual stimulation depends on the type of information processing taking place in V1, and that 1H-fMRS provides unique information about local input/output balance that is not measured by BOLD-fMRI.

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  1. Version published to 10.7554/elife.71016 on eLife
  2. eLife

    Author Response

    Reviewer #1 (Public Review):

    Giove and colleagues find that a perceptual effect, namely whether a flicker is perceived or unperceived, is reflected in metabolic signals measured with functional MRS, but not in BOLDfMRI. Specifically, perceived but not unperceived flicker led to an increase in lactate and glutamate in early visual cortex (a combination of V1, V2 and V3). BOLD-fMRI did not increase in this same region, suggesting that we are missing important neural signals by focusing on BOLD-fMRI only. The authors also provide a thorough discussion of the potential physiological mechanisms underlying these metabolic effects. I should note that I have no expertise in fMRS, and my assessment is based on knowledge of BOLD-fMRI and perception.

    Whether or not the flicker was visible was manipulated by changing the frequency of the flicker. Specific, a low frequency flicker (7.5 Hz) was perceived, but a high frequency flicker (30 Hz) was not. Of course, this means that it is difficult to assess whether the fMRS effects are related to perception itself (visible vs. invisible) or due to the low-level features of the stimulus, e.g. the temporal filtering properties of the visual system. This limitation does not however hinder the main conclusion of the paper, which is that certain neural signals are missed by BOLD-fMRI but can be picked up by fMRS.

    We thank the referee for these constructive comments. In this revision we further stress the importance of the argument suggested by the referee that MRS but not BOLDfMRI better reflects differences in information processing related to perception. In other words, the metabolic response of V1 can predict whether a visual stimulus is perceived or not. This of course does not necessarily involve causality. We argue that stimulus perception is inextricably linked with low-level features of the stimulus, i.e., perception is equivalent to the filtering of the stimulus, which in turn depends on stimulus characteristics.

    In Figure 2B, it looks like BOLD dynamics may differ between the slow and fast flicker blocks, even if the mean amplitude did not. So perhaps there are some more subtle BOLD differences between conditions that the authors do not explore.

    In this revision, we test for statistical differences in the BOLD time-course, as suggested by the referee. Please see our response in the “Essential Revisions” above.

    The authors themselves also raise a potential partial voluming issue in the fMRS measurement that seems important to consider, given the differential BOLD signal in nearby regions (V2 and V3). Specifically, the volume in which fMRS is measured consists of parts of V1, V2, and V3. There are no significant differences between perceived and unperceived BOLD-fMRI in this volume as a whole, but there are in V2 and V3 in isolation. This raises the possibility that the null effect of BOLD-fMRI in the fMRS volume as a whole is due to it washing out in this larger volume. Could it be that the fMRS effects are also driven by V2 and V3, but are for some reason stronger/more robust, and therefore survive in the larger volume? In other words, I wonder if the BOLD and fMRS effects may actually co-localise, but differ in effect size.

    This is an interesting possibility to consider, but unfortunately, it cannot be really addressed without the help of a tailored study. To attempt a minimally meaningful analysis we would need (at least) to know the partial volume of each individual subject for assessing whether and to what extent the partial volume correlates with the spectroscopic results. As stated above, we did not acquire single-subject retinotopic maps. Even with this piece of information, a reliable identification of multiple and spatially distinct components summing up to the single MRS signal would be problematic. A qualitative reply to the issue raised by the referee is that the metabolic response to visual stimulation measured with FDG-PET (an index of glucose utilization, and by extension, of lactate production) has been proposed to peak in V1 (e.g., Chen et al., HBM 2018 PMID: 30076750). Therefore, it is unlikely that V2/V3 contribute much more than V1 to the stimulation-induced increase in lactate and glutamate concentration. Furthermore, to the best of our knowledge all previously reported increases in lactate concentration during photic stimulation have been assigned to V1.

    In conclusion, the authors demonstrate an intriguing dissociation between BOLD-fMRI and fMRS, which should prompt further research into this topic, and may ultimately change the way we interpret neuroimaging signals.

    The referee has wonderfully summarized our study. Thank you.

    Reviewer #2 (Public Review):

    In this paper the authors investigate differences in metabolic response in primary visual cortex (V1) to perceptible and imperceptible stimuli using proton magnetic resonance spectroscopy (1h-MRS) and fMRI.

    The main strength of this paper is it shows that perceptible stimuli trigger a different metabolic response in V1 than imperceptible stimuli, namely that lactate and glutamate levels both increase for perceptible stimuli but are unchanged for imperceptible stimuli. Weaknesses of the study are that no retinotopic mapping was performed on the subjects so the spectroscopic voxel may contain contributions from early visual cortex outside V1; the assumption that increased BOLD response in V2 is caused by perception is not convincing.
    The differences in concentration of lactate and glutamate are striking, and the only plausible explanation is differences in metabolic response in V1.

    This is the clear and main result of the paper. The argument that an increased activation in V2 is caused by perception is less interesting. More sophisticated experimentation and analysis including connectivity analysis would be required to investigate the interaction between V1 and the rest of the brain.

    This could considerably increase the importance of MRS in cognitive neuroscience. It would be fascinating to use dynamic causal modelling or a similar technique to explore connectivity between regions for perceptible/imperceptible stimuli and to combine this with proton spectroscopic imaging.

    We agree with the referee that our work cannot help in establishing a relationship between perception and activation of visual areas, and that more sophisticated investigations would be necessary for that purpose. We also acknowledge that our study suffers of the limitations mentioned by the referee. In the present revision we include, as limitations, the absence of retinotopic mapping and the lack of causality between perception and BOLD/MRS, as suggested by the referee. The idea of correlating brain connectivity with metabolic imaging (CSI or even FDG-PET) during different stimulation paradigms (or resting-state) is appealing, as recent combined PET/fMRI experiments showed that BOLD and glucose consumption (CMRglc) are dissociated in a region- and task-dependent manner (e.g., Stiernman et al, PNAS 2021).

    Reviewer #3 (Public Review):

    Di Nuzzo et al demonstrate here that perception of visual stimulation is reflected in dissociable neurometabolic -but not neurovascular- responses in human visual cortex. This work uses human neuroimaging to show the effects of perception on neuronal energy demands and is of great importance for the neuroscience community. The authors carefully designed a task that would elicit similar BOLD response in primary visual cortex (V1) for perceived or unperceived visual flickering. They combined fMRI BOLD measurements with functional MRS, to quantify the functional (BOLD) and metabolic (concentration of lactate and glutamate) responses during visual stimulation. While they found no differences in the BOLD response within V1 for perceived vs. unperceived visual flicker, the authors show increased levels of glutamate and lactate in V1 when the flicker is perceived, suggesting increased energy metabolism during perceived visual stimulation.

    We thank the referee for the careful and constructive reviews of our manuscript.

    While BOLD response within V1 does not differ between perceived and unperceived flicker (Figures 3B, 2C, 3C), the authors find enhanced BOLD in the lateral occipital cortex when the flicker is perceived (Figures 3B, 3D).

    The authors consider BOLD in secondary visual areas to be a surrogate measure of V1 output, indicating that stimulus processing during perceived stimulation results in enhanced V1 output. The spatial and temporal resolution more commonly used in human neuroimaging do not facilitate building relationships of input-output neuronal activity in a way analogous to animal neurophysiology. The assumption that BOLD activity in secondary visual areas reflects V1 output is very tightly linked to the unique architecture of the visual system; however, the paper would benefit from including the uncertainty of this assumption in the discussion.

    We agree with the referee, and we now mention the uncertainty of the assumption that the BOLD signal increase we observe in secondary visual areas does reflect a rise in the output from V1. We also mention the lack of direct measurement to support such assumption as a limitation of the study.

    The paper would further benefit from following a more standardised way of reporting preprocessing steps of the fMRI data, as well as a more detailed description of the statistical analyses on the fMRI data.

    We have carefully checked the methods section related to the fMRI data analysis (prepreprocessing and statistics) and modified the text where appropriate. Thank you for pointing this out.

    Finally, the authors have provided a series of well-chosen controls to ensure that their findings are not driven by differences in levels of attention between perceived and unperceived stimulation (Figure 1). The authors are commended on the quality of their figures, their choice of detailed graphs and the constructive use of additional media.

    We would like to thank the referee for the complimentary comment.

  3. eLife

    Evaluation Summary:

    Giove and colleagues demonstrate an intriguing dissociation of neurovascular (as measured with BOLD-fMRI) and neurometabolic (measured with fMRS) responses during perception. This is a thought-provoking study that makes one wonder about the signals we measure with human neuroimaging, especially fMRI. It will therefore be of great interest to the broad community of neuroimagers, as well as perception researchers.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1, Reviewer #2 and Reviewer #3 agreed to share their name with the authors.)

  4. eLife

    Reviewer #1 (Public Review):

    Giove and colleagues find that a perceptual effect, namely whether a flicker is perceived or unperceived, is reflected in metabolic signals measured with functional MRS, but not in BOLD-fMRI. Specifically, perceived but not unperceived flicker led to an increase in lactate and glutamate in early visual cortex (a combination of V1, V2 and V3). BOLD-fMRI did not increase in this same region, suggesting that we are missing important neural signals by focusing on BOLD-fMRI only. The authors also provide a thorough discussion of the potential physiological mechanisms underlying these metabolic effects. I should note that I have no expertise in fMRS, and my assessment is based on knowledge of BOLD-fMRI and perception.

    Whether or not the flicker was visible was manipulated by changing the frequency of the flicker. Specific, a low frequency flicker (7.5 Hz) was perceived, but a high frequency flicker (30 Hz) was not. Of course, this means that it is difficult to assess whether the fMRS effects are related to perception itself (visible vs. invisible) or due to the low-level features of the stimulus, e.g. the temporal filtering properties of the visual system. This limitation does not however hinder the main conclusion of the paper, which is that certain neural signals are missed by BOLD-fMRI but can be picked up by fMRS.

    In Figure 2B, it looks like BOLD dynamics may differ between the slow and fast flicker blocks, even if the mean amplitude did not. So perhaps there are some more subtle BOLD differences between conditions that the authors do not explore.

    The authors themselves also raise a potential partial voluming issue in the fMRS measurement that seems important to consider, given the differential BOLD signal in nearby regions (V2 and V3). Specifically, the volume in which fMRS is measured consists of parts of V1, V2, and V3. There are no significant differences between perceived and unperceived BOLD-fMRI in this volume as a whole, but there are in V2 and V3 in isolation. This raises the possibility that the null effect of BOLD-fMRI in the fMRS volume as a whole is due to it washing out in this larger volume. Could it be that the fMRS effects are also driven by V2 and V3, but are for some reason stronger/more robust, and therefore survive in the larger volume? In other words, I wonder if the BOLD and fMRS effects may actually co-localise, but differ in effect size.

    In conclusion, the authors demonstrate an intriguing dissociation between BOLD-fMRI and fMRS, which should prompt further research into this topic, and may ultimately change the way we interpret neuroimaging signals.

  5. eLife

    Reviewer #2 (Public Review):

    In this paper the authors investigate differences in metabolic response in primary visual cortex (V1) to perceptible and imperceptible stimuli using proton magnetic resonance spectroscopy (1h-MRS) and fMRI.

    The main strength of this paper is it shows that perceptible stimuli trigger a different metabolic response in V1 than imperceptible stimuli, namely that lactate and glutamate levels both increase for perceptible stimuli but are unchanged for imperceptible stimuli. Weaknesses of the study are that no retinotopic mapping was performed on the subjects so the spectroscopic voxel may contain contributions from early visual cortex outside V1; the assumption that increased BOLD response in V2 is caused by perception is not convincing.

    The differences in concentration of lactate and glutamate are striking, and the only plausible explanation is differences in metabolic response in V1. This is the clear and main result of the paper. The argument that an increased activation in V2 is caused by perception is less interesting. More sophisticated experimentation and analysis including connectivity analysis would be required to investigate the interaction between V1 and the rest of the brain.

    This could considerably increase the importance of MRS in cognitive neuroscience. It would be fascinating to use dynamic causal modelling or a similar technique to explore connectivity between regions for perceptible/imperceptible stimuli and to combine this with proton spectroscopic imaging.

  6. eLife

    Reviewer #3 (Public Review):

    Di Nuzzo et al demonstrate here that perception of visual stimulation is reflected in dissociable neurometabolic -but not neurovascular- responses in human visual cortex. This work uses human neuroimaging to show the effects of perception on neuronal energy demands and is of great importance for the neuroscience community. The authors carefully designed a task that would elicit similar BOLD response in primary visual cortex (V1) for perceived or unperceived visual flickering. They combined fMRI BOLD measurements with functional MRS, to quantify the functional (BOLD) and metabolic (concentration of lactate and glutamate) responses during visual stimulation. While they found no differences in the BOLD response within V1 for perceived vs. unperceived visual flicker, the authors show increased levels of glutamate and lactate in V1 when the flicker is perceived, suggesting increased energy metabolism during perceived visual stimulation.

    While BOLD response within V1 does not differ between perceived and unperceived flicker (Figures 3B, 2C, 3C), the authors find enhanced BOLD in the lateral occipital cortex when the flicker is perceived (Figures 3B, 3D). The authors consider BOLD in secondary visual areas to be a surrogate measure of V1 output, indicating that stimulus processing during perceived stimulation results in enhanced V1 output. The spatial and temporal resolution more commonly used in human neuroimaging do not facilitate building relationships of input-output neuronal activity in a way analogous to animal neurophysiology. The assumption that BOLD activity in secondary visual areas reflects V1 output is very tightly linked to the unique architecture of the visual system; however, the paper would benefit from including the uncertainty of this assumption in the discussion.

    The paper would further benefit from following a more standardised way of reporting pre-processing steps of the fMRI data, as well as a more detailed description of the statistical analyses on the fMRI data.

    Finally, the authors have provided a series of well-chosen controls to ensure that their findings are not driven by differences in levels of attention between perceived and unperceived stimulation (Figure 1). The authors are commended on the quality of their figures, their choice of detailed graphs and the constructive use of additional media.

  7. Version published to 10.1101/2021.09.17.460759v1 on bioRxiv