1
|
Ross G, Radtke-Schuller S, Frohlich F. Ferret as a model system for studying the anatomy and function of the prefrontal cortex: A systematic review. Neurosci Biobehav Rev 2024; 162:105701. [PMID: 38718987 PMCID: PMC11162921 DOI: 10.1016/j.neubiorev.2024.105701] [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: 10/30/2023] [Revised: 04/12/2024] [Accepted: 05/01/2024] [Indexed: 05/19/2024]
Abstract
There is a lack of consensus on anatomical nomenclature, standards of documentation, and functional equivalence of the frontal cortex between species. There remains a major gap between human prefrontal function and interpretation of findings in the mouse brain that appears to lack several key prefrontal areas involved in cognition and psychiatric illnesses. The ferret is an emerging model organism that has gained traction as an intermediate model species for the study of top-down cognitive control and other higher-order brain functions. However, this research has yet to benefit from synthesis. Here, we provide a summary of all published research pertaining to the frontal and/or prefrontal cortex of the ferret across research scales. The targeted location within the ferret brain is summarized visually for each experiment, and the anatomical terminology used at time of publishing is compared to what would be the appropriate term to use presently. By doing so, we hope to improve clarity in the interpretation of both previous and future publications on the comparative study of frontal cortex.
Collapse
Affiliation(s)
- Grace Ross
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA
| | - Susanne Radtke-Schuller
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Flavio Frohlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA; Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC, USA; Department of Biomedical Engineering, University of North Carolina, Chapel Hill, NC, USA; Department of Neurology, University of North Carolina, Chapel Hill, NC, USA.
| |
Collapse
|
2
|
Chang AS, Wirak GS, Li D, Gabel CV, Connor CW. Measures of Information Content during Anesthesia and Emergence in the Caenorhabditis elegans Nervous System. Anesthesiology 2023; 139:49-62. [PMID: 37027802 PMCID: PMC10266588 DOI: 10.1097/aln.0000000000004579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2023]
Abstract
BACKGROUND Suppression of behavioral and physical responses defines the anesthetized state. This is accompanied, in humans, by characteristic changes in electroencephalogram patterns. However, these measures reveal little about the neuron or circuit-level physiologic action of anesthetics nor how information is trafficked between neurons. This study assessed whether entropy-based metrics can differentiate between the awake and anesthetized state in Caenorhabditis elegans and characterize emergence from anesthesia at the level of interneuronal communication. METHODS Volumetric fluorescence imaging measured neuronal activity across a large portion of the C. elegans nervous system at cellular resolution during distinct states of isoflurane anesthesia, as well as during emergence from the anesthetized state. Using a generalized model of interneuronal communication, new entropy metrics were empirically derived that can distinguish the awake and anesthetized states. RESULTS This study derived three new entropy-based metrics that distinguish between stable awake and anesthetized states (isoflurane, n = 10) while possessing plausible physiologic interpretations. State decoupling is elevated in the anesthetized state (0%: 48.8 ± 3.50%; 4%: 66.9 ± 6.08%; 8%: 65.1 ± 5.16%; 0% vs. 4%, P < 0.001; 0% vs. 8%, P < 0.001), while internal predictability (0%: 46.0 ± 2.94%; 4%: 27.7 ± 5.13%; 8%: 30.5 ± 4.56%; 0% vs. 4%, P < 0.001; 0% vs. 8%, P < 0.001), and system consistency (0%: 2.64 ± 1.27%; 4%: 0.97 ± 1.38%; 8%: 1.14 ± 0.47%; 0% vs. 4%, P = 0.006; 0% vs. 8%, P = 0.015) are suppressed. These new metrics also resolve to baseline during gradual emergence of C. elegans from moderate levels of anesthesia to the awake state (n = 8). The results of this study show that early emergence from isoflurane anesthesia in C. elegans is characterized by the rapid resolution of an elevation in high frequency activity (n = 8, P = 0.032). The entropy-based metrics mutual information and transfer entropy, however, did not differentiate well between the awake and anesthetized states. CONCLUSIONS Novel empirically derived entropy metrics better distinguish the awake and anesthetized states compared to extant metrics and reveal meaningful differences in information transfer characteristics between states. EDITOR’S PERSPECTIVE
Collapse
Affiliation(s)
- Andrew S Chang
- Department of Physiology and Biophysics, Boston University School of Medicine, Boston University, Boston, Massachusetts
| | - Gregory S Wirak
- Department of Physiology and Biophysics, Boston University, Boston, Massachusetts
| | - Duan Li
- Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Christopher V Gabel
- Department of Physiology and Biophysics, Boston University, Boston, Massachusetts
| | - Christopher W Connor
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, Massachusetts; Department of Biomedical Engineering, Physiology and Biophysics, Boston University, Boston, Massachusetts
| |
Collapse
|
3
|
Puche Sarmiento AC, Bocanegra García Y, Ochoa Gómez JF. Active information storage in Parkinson's disease: a resting state fMRI study over the sensorimotor cortex. Brain Imaging Behav 2019; 14:1143-1153. [PMID: 30684153 DOI: 10.1007/s11682-019-00037-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Parkinson's disease (PD), the second most frequent neurodegenerative disease, affects significantly life quality by a combination of motor and cognitive disturbances. Although it is traditionally associated with basal ganglia dysfunction, cortical alterations are also involved in disease symptoms. Our objective is to evaluate the alterations in brain dynamics in de novo and recently treated PD subjects using a nonlinear method known as Active Information Storage. In the current research, Active Information Storage (AIS) was used to study the complex dynamics in motor cortex spontaneous activity captured using resting state functional Magnetic Resonance Imaging (rs-fMRI) at early-stage in non-medicated and recently medicated PD subjects. Supplementary to AIS, the fractional Amplitude of Low Frequency Fluctuation (fALFF), which is a better-established technique of analysis of rs-fMRI signals, was also evaluated. Compared to healthy subjects, the AIS values were significantly reduced in PD patients over the analyzed motor cortex regions; differences were also found at less extent using the fALFF measure. Correlations between AIS and fALFF values showed that the measures seem to capture similar neuronal phenomena in rs-fMRI data. The highest sensitivity when detecting group differences revealed by AIS, and not captured by traditional linear approaches, suggests that this measure is a promising tool for the analysis of rs-fMRI neural data in PD.
Collapse
Affiliation(s)
- Aura Cristina Puche Sarmiento
- Grupo de Investigación en Bioinstrumentación e Ingeniería Clínica, Facultad de Ingeniería, Universidad de Antioquia UdeA, Calle 70 No 52-11, 050010, Medellín, Colombia.
| | - Yamile Bocanegra García
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia UdeA, Calle 70 No 52-11, Medellín, Colombia.,Grupo Neuropsicología y Conducta, Facultad de Medicina, Universidad de Antioquia UdeA, Calle 70 No 52-11, Medellín, Colombia
| | - John Fredy Ochoa Gómez
- Grupo de Investigación en Bioinstrumentación e Ingeniería Clínica, Facultad de Ingeniería, Universidad de Antioquia UdeA, Calle 70 No 52-11, 050010, Medellín, Colombia
| |
Collapse
|
4
|
Baria AT, Centeno MV, Ghantous ME, Chang PC, Procissi D, Apkarian AV. BOLD temporal variability differentiates wakefulness from anesthesia-induced unconsciousness. J Neurophysiol 2017; 119:834-848. [PMID: 29212921 DOI: 10.1152/jn.00714.2017] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Even though a number of findings, based on information content or information integration, are shown to define neural underpinnings characteristic of a conscious experience, the neurophysiological mechanism of consciousness is still poorly understood. Here, we investigated the brain activity and functional connectivity changes that occur in the isoflurane-anesthetized unconscious state in contrast to the awake state in rats (awake and/or anesthetized, n = 68 rats). We examined nine information measures previously shown to distinguish between conscious states: blood oxygen level-dependent (BOLD) variability, functional connectivity strength, modularity, weighted modularity, efficiency, clustering coefficient, small-worldness, and spatial and temporal Lempel-Ziv complexity measure. We also identified modular membership, seed-based network connectivity, and absolute and normalized power spectrums to assess the integrity of the BOLD functional networks between awake and anesthesia. fMRI BOLD variability and related absolute power were the only information measures significantly higher during the awake state compared with isoflurane anesthesia across animals, and with varying levels of anesthesia, after correcting for motion and respiration confounds. Thus, we conclude that, at least under the specific conditions examined here, global measures of information integration/sharing do not properly distinguish the anesthetized state from wakefulness, and heightened overall, global and local, BOLD variability is the most reliable determinant of conscious brain activity relative to isoflurane anesthesia. NEW & NOTEWORTHY Multiple metrics previously suggested to be able to distinguish between states of consciousness were compared, within and across rats in awake and isoflurane anesthesia-induced unconsciousness. All measures tested showed sensitivity to confounds, correcting for motion and for respiration changes due to anesthesia. Resting state local BOLD variability and the related absolute power were the only information measures that robustly differentiated wakefulness states. These results caution against the general applicability of global information measures in identifying levels of consciousness, thus challenging the popular concept that these measures reflect states of consciousness, and also pointing to local signal variability as a more reliable indicator of states of wakefulness.
Collapse
Affiliation(s)
- Alexis T Baria
- Department of Physiology, Northwestern University Feinberg School of Medicine , Chicago, Illinois
| | - Maria V Centeno
- Department of Physiology, Northwestern University Feinberg School of Medicine , Chicago, Illinois
| | - Mariam E Ghantous
- Department of Physiology, Northwestern University Feinberg School of Medicine , Chicago, Illinois
| | - Pei C Chang
- Department of Physiology, Northwestern University Feinberg School of Medicine , Chicago, Illinois
| | - Daniele Procissi
- Department of Radiology, Northwestern University Feinberg School of Medicine , Chicago, Illinois
| | - A Vania Apkarian
- Department of Physiology, Northwestern University Feinberg School of Medicine , Chicago, Illinois.,Physical Medicine and Rehabilitation, Northwestern University Feinberg School of Medicine , Chicago, Illinois.,Department of Anesthesia, Northwestern University Feinberg School of Medicine , Chicago, Illinois
| |
Collapse
|
5
|
Neural Correlates of Wakefulness, Sleep, and General Anesthesia: An Experimental Study in Rat. Anesthesiology 2017; 125:929-942. [PMID: 27617688 DOI: 10.1097/aln.0000000000001342] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Significant advances have been made in our understanding of subcortical processes related to anesthetic- and sleep-induced unconsciousness, but the associated changes in cortical connectivity and cortical neurochemistry have yet to be fully clarified. METHODS Male Sprague-Dawley rats were instrumented for simultaneous measurement of cortical acetylcholine and electroencephalographic indices of corticocortical connectivity-coherence and symbolic transfer entropy-before, during, and after general anesthesia (propofol, n = 11; sevoflurane, n = 13). In another group of rats (n = 7), these electroencephalographic indices were analyzed during wakefulness, slow wave sleep (SWS), and rapid eye movement (REM) sleep. RESULTS Compared to wakefulness, anesthetic-induced unconsciousness was characterized by a significant decrease in cortical acetylcholine that recovered to preanesthesia levels during recovery wakefulness. Corticocortical coherence and frontal-parietal symbolic transfer entropy in high γ band (85 to 155 Hz) were decreased during anesthetic-induced unconsciousness and returned to preanesthesia levels during recovery wakefulness. Sleep-wake states showed a state-dependent change in coherence and transfer entropy in high γ bandwidth, which correlated with behavioral arousal: high during wakefulness, low during SWS, and lowest during REM sleep. By contrast, frontal-parietal θ connectivity during sleep-wake states was not correlated with behavioral arousal but showed an association with well-established changes in cortical acetylcholine: high during wakefulness and REM sleep and low during SWS. CONCLUSIONS Corticocortical coherence and frontal-parietal connectivity in high γ bandwidth correlates with behavioral arousal and is not mediated by cholinergic mechanisms, while θ connectivity correlates with cortical acetylcholine levels.
Collapse
|
6
|
Wollstadt P, Sellers KK, Rudelt L, Priesemann V, Hutt A, Fröhlich F, Wibral M. Breakdown of local information processing may underlie isoflurane anesthesia effects. PLoS Comput Biol 2017; 13:e1005511. [PMID: 28570661 PMCID: PMC5453425 DOI: 10.1371/journal.pcbi.1005511] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 04/11/2017] [Indexed: 02/07/2023] Open
Abstract
The disruption of coupling between brain areas has been suggested as the mechanism underlying loss of consciousness in anesthesia. This hypothesis has been tested previously by measuring the information transfer between brain areas, and by taking reduced information transfer as a proxy for decoupling. Yet, information transfer is a function of the amount of information available in the information source—such that transfer decreases even for unchanged coupling when less source information is available. Therefore, we reconsidered past interpretations of reduced information transfer as a sign of decoupling, and asked whether impaired local information processing leads to a loss of information transfer. An important prediction of this alternative hypothesis is that changes in locally available information (signal entropy) should be at least as pronounced as changes in information transfer. We tested this prediction by recording local field potentials in two ferrets after administration of isoflurane in concentrations of 0.0%, 0.5%, and 1.0%. We found strong decreases in the source entropy under isoflurane in area V1 and the prefrontal cortex (PFC)—as predicted by our alternative hypothesis. The decrease in source entropy was stronger in PFC compared to V1. Information transfer between V1 and PFC was reduced bidirectionally, but with a stronger decrease from PFC to V1. This links the stronger decrease in information transfer to the stronger decrease in source entropy—suggesting reduced source entropy reduces information transfer. This conclusion fits the observation that the synaptic targets of isoflurane are located in local cortical circuits rather than on the synapses formed by interareal axonal projections. Thus, changes in information transfer under isoflurane seem to be a consequence of changes in local processing more than of decoupling between brain areas. We suggest that source entropy changes must be considered whenever interpreting changes in information transfer as decoupling. Currently we do not understand how anesthesia leads to loss of consciousness (LOC). One popular idea is that we loose consciousness when brain areas lose their ability to communicate with each other–as anesthetics might interrupt transmission on nerve fibers coupling them. This idea has been tested by measuring the amount of information transferred between brain areas, and taking this transfer to reflect the coupling itself. Yet, information that isn’t available in the source area can’t be transferred to a target. Hence, the decreases in information transfer could be related to less information being available in the source, rather than to a decoupling. We tested this possibility measuring the information available in source brain areas and found that it decreased under isoflurane anesthesia. In addition, a stronger decrease in source information lead to a stronger decrease of the information transfered. Thus, the input to the connection between brain areas determined the communicated information, not the strength of the coupling (which would result in a stronger decrease in the target). We suggest that interrupted information processing within brain areas has an important contribution to LOC, and should be focused on more in attempts to understand loss of consciousness under anesthesia.
Collapse
Affiliation(s)
- Patricia Wollstadt
- MEG Unit, Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
- * E-mail: (PW); (VP)
| | - Kristin K. Sellers
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Lucas Rudelt
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
| | - Viola Priesemann
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Bernstein Center for Computational Neuroscience, BCCN, Göttingen, Germany
- * E-mail: (PW); (VP)
| | - Axel Hutt
- Deutscher Wetterdienst, Section FE 12 - Data Assimilation, Offenbach/Main, Germany
- Department of Mathematics and Statistics, University of Reading, Reading, United Kingdom
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neurobiology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Michael Wibral
- MEG Unit, Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| |
Collapse
|