Cerebral perturbations during exercise in hypoxia.: The brain during hypoxic exercise

International audienceReduction of aerobic exercise performance observed under hypoxic conditions is mainly attributed to altered muscle metabolism due to impaired O(2) delivery. It has been recently proposed that hypoxia-induced cerebral perturbations may also contribute to exercise performance limitation. A significant reduction in cerebral oxygenation during whole body exercise has been reported in hypoxia compared with normoxia, while changes in cerebral perfusion may depend on the brain region, the level of arterial oxygenation and hyperventilation induced alterations in arterial CO(2). With the use of transcranial magnetic stimulation, inconsistent changes in cortical excitability have been reported in hypoxia, whereas a greater impairment in maximal voluntary activation following a fatiguing exercise has been suggested when arterial O(2) content is reduced. Electromyographic recordings during exercise showed an accelerated rise in central motor drive in hypoxia, probably to compensate for greater muscle contractile fatigue. This accelerated development of muscle fatigue in moderate hypoxia may be responsible for increased inhibitory afferent signals to the central nervous system leading to impaired central drive. In severe hypoxia (arterial O(2) saturation <70-75%), cerebral hypoxia per se may become an important contributor to impaired performance and reduced motor drive during prolonged exercise. This review examines the effects of acute and chronic reduction in arterial O(2) (and CO(2)) on cerebral blood flow and cerebral oxygenation, neuronal function, and central drive to the muscles. Direct and indirect influences of arterial deoxygenation on central command are separated. Methodological concerns as well as future research avenues are also considered

Effects of normobaric hypoxia on the activation of motor and visual cortex areas in functional magnetic resonance imaging (fMRI)

Aims: Hypoxia due to high altitude or otherwise altered fraction of inspired O2 affects cerebral mechanisms. Human brain function can be assessed indirectly via examination of local changes in haemodynamics in fMRI. The aim of this study was to examine if adaptation to normobaric hypoxia determines divergent activation in the brain regions supplied by the main cerebral arterial vessels. Methods: Visual and motor paradigms were used to shed light on the activation of different brain regions in fMRI under normobaric hypoxic conditions in 16 healthy male subjects. Hypoxia was produced by reducing the percentage of O2 in an inhaled gas mixture resulting in normobaric hypoxia with an FiO2 of 13 %. Participants had to complete a total of 3 MRI sessions to study different oxygen conditions: normoxia (FiO2 = 0.21, normal pressure), short-time (7 ± 1 min, FiO2 = 0.13, normal pressure), longtime hypoxia (8 h and 29 ± 24 min, FiO2 = 0.13, normal pressure). Each session lasted approximately 30 min, consisting of two fMRI runs (1 visual task, 1 motor task) which were pseudo-randomized between participants, followed by the structural sequence. Cerebral symptoms of AMS were assessed by means of the LLS and it was examined if symptomatic AMS has consequences on brain activation patterns measured as ∆S values. Results: Mean ∆S during normoxia was 2.43 ± 0.80 % due to motor stimulation, and 3.49 ± 1.41 % due to visual stimulation. During motor stimulation, the mean signal change due to short-time hypoxia was 0.55 ± 0.30 % and 0.82 ± 0,62 % due to longtime hypoxia. During visual stimulation, the mean signal change due to short-time hypoxia was 1.79 ± 0.69 %. Long-time hypoxia led to a mean signal change of 2.02 ± 1.18 %. Repeated ANOVA measures with factors task (motor, visual) and the hypoxic conditions (short-time hypoxia, long-time hypoxia) showed a main effect of task (F (1,15) = 52.10, p < 0.001), but no main effect of the hypoxic condition (F (1, 15) = 1.79, p = ns). Conclusions: Hypoxia led to diminished cerebral activation during motor and visual stimulation in spite of a preserved cerebral function. The oxygenation changes associated with brain activation seem more influential on the motor area, rather than the visual cortex. Therefore, the capability of the human brain to acclimatise to chronic hypoxic conditions may vary in the motor and the visual system.Ziele: Hypoxie aufgrund großer Höhe oder eines anderweitig veränderten Anteils von eingeatmetem O2-Gehalts beeinflusst zerebrale Mechanismen. Die menschliche Gehirnfunktion kann indirekt über den Nachweis lokaler hämodynamischer Veränderungen im fMRT bestimmt werden. Das Ziel dieser Studie war es, zu untersuchen, ob die Anpassung an normobare Hypoxie eine unterschiedliche Aktivierung in von den drei Hauptgefäßen versorgten Gehirnregionen erzeugt. Methoden: Bei 16 gesunden, männlichen Probanden wurden visuelle und motorische Testparadigmen angewendet, um die Aktivierung verschiedener Hirnregionen im fMRT unter normobaren, hypoxischen Bedingungen aufzuklären. Hypoxie wurde mit Hilfe eines sauerstoffreduzierten Gasgemischs (O2-Anteil 13%) erzeugt. Die Probanden mussten insgesamt 3 MRT-Sitzungen absolvieren, um verschiedene Sauerstoffzustände zu untersuchen: Normoxie (FiO2 = 0,21), Kurzzeithypoxie (7 ± 1 min Hypoxie, FiO2 = 0,13), Langzeithypoxie (8 h und 29 ± 24 min Hypoxie, FiO2 = 0,13). Jede Sitzung dauerte ca. 30 min und bestand aus je zwei fMRI-Durchgängen (1 visuelle Aufgabe, 1 motorische Aufgabe). Die zerebralen Symptome einer Höhenkrankheit wurden mittels des LLS bewertet und der Einfluss einer Höhenkrankheit auf die Gehirnaktivierungsmuster im fMRT untersucht. Resultate: Die mittlere BOLD-Signalveränderung während Normoxie betrug bei motorischer Stimulation 2,43 ± 0,80% und bei visueller Stimulation 3,49 ± 1,41%. Bei motorischer Stimulation betrug sie nach Kurzzeithypoxie 0,55 ± 0,30% und 0,82 ± 0,62% nach Langzeithypoxie. Bei visueller Stimulation betrug die mittlere Signaländerung aufgrund von Kurzzeithypoxie 1,79 ± 0,69 und aufgrund Langzeithypoxie 2,02 ± 1,18%. ANOVA-Messungen mit den Faktoren Aufgabe (motorisch, visuell) und hypoxische Bedingungen (Kurzzeithypoxie, Langzeithypoxie) zeigten einen Effekt der Aufgabe (F (1, 15) = 52.10, p <0.001), aber keinen Effekt der hypoxischen Bedingung (F (1, 15) = 1,79, p = ns) auf die BOLD Signalwertänderungen. Schlussfolgerungen: Hypoxie führte zu einer verminderten Hirnaktivität im fMRT bei motorischer und visueller Stimulation trotz erhaltener Hirnfunktion. Die mit der Gehirnaktivierung verbundenen Veränderungen der Oxygenierung scheinen eher Einfluss auf den motorischen Bereich als den visuellen Kortex zu haben. Die Adaptationsfähigkeit an chronische hypoxische Zustände scheint sich demzufolge zwischen dem motorischen und dem visuellen System zu unterscheiden

Effects of normobaric hypoxia on the activation of motor and visual cortex areas in functional magnetic resonance imaging (fMRI)

Aims: Hypoxia due to high altitude or otherwise altered fraction of inspired O2 affects cerebral mechanisms. Human brain function can be assessed indirectly via examination of local changes in haemodynamics in fMRI. The aim of this study was to examine if adaptation to normobaric hypoxia determines divergent activation in the brain regions supplied by the main cerebral arterial vessels. Methods: Visual and motor paradigms were used to shed light on the activation of different brain regions in fMRI under normobaric hypoxic conditions in 16 healthy male subjects. Hypoxia was produced by reducing the percentage of O2 in an inhaled gas mixture resulting in normobaric hypoxia with an FiO2 of 13 %. Participants had to complete a total of 3 MRI sessions to study different oxygen conditions: normoxia (FiO2 = 0.21, normal pressure), short-time (7 ± 1 min, FiO2 = 0.13, normal pressure), longtime hypoxia (8 h and 29 ± 24 min, FiO2 = 0.13, normal pressure). Each session lasted approximately 30 min, consisting of two fMRI runs (1 visual task, 1 motor task) which were pseudo-randomized between participants, followed by the structural sequence. Cerebral symptoms of AMS were assessed by means of the LLS and it was examined if symptomatic AMS has consequences on brain activation patterns measured as ∆S values. Results: Mean ∆S during normoxia was 2.43 ± 0.80 % due to motor stimulation, and 3.49 ± 1.41 % due to visual stimulation. During motor stimulation, the mean signal change due to short-time hypoxia was 0.55 ± 0.30 % and 0.82 ± 0,62 % due to longtime hypoxia. During visual stimulation, the mean signal change due to short-time hypoxia was 1.79 ± 0.69 %. Long-time hypoxia led to a mean signal change of 2.02 ± 1.18 %. Repeated ANOVA measures with factors task (motor, visual) and the hypoxic conditions (short-time hypoxia, long-time hypoxia) showed a main effect of task (F (1,15) = 52.10, p < 0.001), but no main effect of the hypoxic condition (F (1, 15) = 1.79, p = ns). Conclusions: Hypoxia led to diminished cerebral activation during motor and visual stimulation in spite of a preserved cerebral function. The oxygenation changes associated with brain activation seem more influential on the motor area, rather than the visual cortex. Therefore, the capability of the human brain to acclimatise to chronic hypoxic conditions may vary in the motor and the visual system.Ziele: Hypoxie aufgrund großer Höhe oder eines anderweitig veränderten Anteils von eingeatmetem O2-Gehalts beeinflusst zerebrale Mechanismen. Die menschliche Gehirnfunktion kann indirekt über den Nachweis lokaler hämodynamischer Veränderungen im fMRT bestimmt werden. Das Ziel dieser Studie war es, zu untersuchen, ob die Anpassung an normobare Hypoxie eine unterschiedliche Aktivierung in von den drei Hauptgefäßen versorgten Gehirnregionen erzeugt. Methoden: Bei 16 gesunden, männlichen Probanden wurden visuelle und motorische Testparadigmen angewendet, um die Aktivierung verschiedener Hirnregionen im fMRT unter normobaren, hypoxischen Bedingungen aufzuklären. Hypoxie wurde mit Hilfe eines sauerstoffreduzierten Gasgemischs (O2-Anteil 13%) erzeugt. Die Probanden mussten insgesamt 3 MRT-Sitzungen absolvieren, um verschiedene Sauerstoffzustände zu untersuchen: Normoxie (FiO2 = 0,21), Kurzzeithypoxie (7 ± 1 min Hypoxie, FiO2 = 0,13), Langzeithypoxie (8 h und 29 ± 24 min Hypoxie, FiO2 = 0,13). Jede Sitzung dauerte ca. 30 min und bestand aus je zwei fMRI-Durchgängen (1 visuelle Aufgabe, 1 motorische Aufgabe). Die zerebralen Symptome einer Höhenkrankheit wurden mittels des LLS bewertet und der Einfluss einer Höhenkrankheit auf die Gehirnaktivierungsmuster im fMRT untersucht. Resultate: Die mittlere BOLD-Signalveränderung während Normoxie betrug bei motorischer Stimulation 2,43 ± 0,80% und bei visueller Stimulation 3,49 ± 1,41%. Bei motorischer Stimulation betrug sie nach Kurzzeithypoxie 0,55 ± 0,30% und 0,82 ± 0,62% nach Langzeithypoxie. Bei visueller Stimulation betrug die mittlere Signaländerung aufgrund von Kurzzeithypoxie 1,79 ± 0,69 und aufgrund Langzeithypoxie 2,02 ± 1,18%. ANOVA-Messungen mit den Faktoren Aufgabe (motorisch, visuell) und hypoxische Bedingungen (Kurzzeithypoxie, Langzeithypoxie) zeigten einen Effekt der Aufgabe (F (1, 15) = 52.10, p <0.001), aber keinen Effekt der hypoxischen Bedingung (F (1, 15) = 1,79, p = ns) auf die BOLD Signalwertänderungen. Schlussfolgerungen: Hypoxie führte zu einer verminderten Hirnaktivität im fMRT bei motorischer und visueller Stimulation trotz erhaltener Hirnfunktion. Die mit der Gehirnaktivierung verbundenen Veränderungen der Oxygenierung scheinen eher Einfluss auf den motorischen Bereich als den visuellen Kortex zu haben. Die Adaptationsfähigkeit an chronische hypoxische Zustände scheint sich demzufolge zwischen dem motorischen und dem visuellen System zu unterscheiden

Magnetoenkefalografian ja toiminnallisen magneettikuvauksen vertailu ja yhdistäminen tunto- ja liikejärjestelmän tutkimuksessa

MEG directly measures the neuronal events and has greater temporal resolution than fMRI, which has limited temporal resolution mainly due to the larger timescale of the hemodynamic response. On the other hand fMRI has advantages in spatial resolution, while the localization results with MEG can be ambiguous due to the non-uniqueness of the electromagnetic inverse problem. Thus, these methods could provide complementary information and could be used to create both spatially and temporally accurate models of brain function. We investigated the degree of overlap, revealed by the two imaging methods, in areas involved in sensory or motor processing in healthy subjects and neurosurgical patients. Furthermore, we used the spatial information from fMRI to construct a spatiotemporal model of the MEG data in order to investigate the sensorimotor system and to create a spatiotemporal model of its function. We compared the localization results from the MEG and fMRI with invasive electrophysiological cortical mapping. We used a recently introduced method, contextual clustering, for hypothesis testing of fMRI data and assessed the the effect of neighbourhood information use on the reproducibility of fMRI results. Using MEG, we identified the ipsilateral primary sensorimotor cortex (SMI) as a novel source area contributing to the somatosensory evoked fields (SEF) to median nerve stimulation. Using combined MEG and fMRI measurements we found that two separate areas in the lateral fissure may be the generators for the SEF responses from the secondary somatosensory cortex region. The two imaging methods indicated activation in corresponding locations. By using complementary information from MEG and fMRI we established a spatiotemporal model of somatosensory cortical processing. This spatiotemporal model of cerebral activity was in good agreement with results from several studies using invasive electrophysiological measurements and with anatomical studies in monkey and man concerning the connections between somatosensory areas. In neurosurgical patients, the MEG dipole model turned out to be more reliable than fMRI in the identification of the central sulcus. This was due to prominent activation in non-primary areas in fMRI, which in some cases led to erroneous or ambiguous localization of the central sulcus.Magnetoenkefalografia (MEG) mittaa suoraan aivojen hermosolujen sähköistä toimintaa ja sillä on parempi ajallinen erotuskyky kuin aivojen aktivaation aiheuttamia paikallisen verenkierron muutoksia kuvaava toiminnallinen magneettikuvaus (TMK). TMK:lla on toisaalta etuja paikannuksessa MEG:hen nähden ja MEG:llä saadut paikannustulokset ovat monikäsitteisiä. Nämä menetelmät voivat täydentää toisiaan ja yhdessä niillä voidaan saada tarkempi ajallinen ja paikallinen kuva aivojen toiminnasta. Käytimme näitä kahta menetelmää aivojen tunto- ja liikejärjestelmän toiminnan kuvantamisessa terveillä koehenkilöillä ja neurokirurgisilla potilailla. Tutkimme menetelmillä saatavan paikannustuloksen yhteneväisyyttä ja käytimme TMK:sta saatavaa paikannustietoa MEG:llä mitattujen aivojen magneetisten vasteiden mallinuksessa luoden mallin aivojen tuntojärjestelmän toiminnasta. Neurokirurgisilla potilailla vertasimme kuvantamismenetelmien tuloksia leikkauksenaikaiseen sähköiseen liikeaivokuoren paikannukseen. Tutkimuksessa testattiin ja sovellettin kehittämiämme uusia kuva-analyysimenetelmiä. MEG:llä ja TMK:lla havaitsimme viitteitä aktivaatiosta tuntoärsykkeen kanssa samanpuoleisella primäärillä tuntoaivokuorella. Tuloksemme viittaavat lisäksi siihen että aivojen lateraalisessa fissuurassa on ainakin kaksi erillistä lähdealuetta jotka tuottavat magneettisia tuntoherätevasteita. Mallimme aivojen toiminnasta tuntoarsykkeen käsittelyn aikana vastasi hyvin kirjallisuudessa raportoituja suoraan aivoista mitattuja eri alueiden aktivaatioaikoja. TMK-analyysimenetelmiä vertailtaessa todettiin kuva-alkion naapurustoinformaatiota käyttävien menetelmien tuottavan paremmin toistettavia tuloksia. Kehittämämme menetelmä rajasi tarkemmin aivojen aktivaatioalueen ja oli muita menetelmiä herkempi havaitsemaan heikkoja aktivaatioita. Paikannettaessa aivojen keskusuurretta leikkauksen suunnittelua ja riskien arviointia varten MEG tuotti luotettavamman tuloksen kuin TMK jossa osalla potilaista aktivaatiot muilla kuin primäärillä liikeaivokuorella olivat voimakkaimpia vaikeuttaen tulosten tulkintaa

Investigating cerebrovascular health and functional plasticity using quantitative FMRI

A healthy cerebrovasculature is necessary to maintain optimal levels of blood flow and oxygen metabolism required for overall brain health. Cerebrovascular health also promotes functional plasticity which facilitates lifelong adaptation with experience and recovery following injury. In diseases such as Multiple Sclerosis (MS), there is known vascular and metabolic dysfunction, however, patients retain variable levels of functional plasticity which aids recovery following acute bouts of inflammation. Physical exercise interventions, aimed at improving cerebral blood flow and oxygen metabolism, present a potential avenue for improving patient outcomes and slowing the progression of disability. However, there is a lack of mechanistic understanding of i) brain energetic processes underlying plasticity and ii) how aerobic fitness (AF), which is linked to increased brain plasticity, benefits brain vascular and metabolic function. The work presented in this thesis uses arterial spin labelling (ASL) functional magnetic resonance imaging (fMRI) to quantitatively characterise the vascular and metabolic processes associated with functional brain plasticity, and the effects of AF on the brain’s functional capacity in healthy adults. This thesis begins with an overview of the neurobiological processes of interest and fMRI techniques that can quantify these processes. Next, a comparison of common ASL acquisition and analysis procedures is made to establish the most appropriate methods for subsequent experimental work. Chapters 4 and 5 investigate the effects of AF on cerebrovascular function in healthy adults. Chapter 6 then gives an overview of existing functional motor plasticity work, before Chapters 7 and 8 which quantify vascular and metabolic adaptations following motor training in the healthy brain. Chapter 9, presents preliminary work in an MS cohort, applying methods from previous chapters to quantify vascular and metabolic differences between patients and controls. The general discussion in Chapter 10 summarises the main findings and contributions of this work and key areas for future research are outlined