Ringraziamo il Dr. D. Chen e il Dr. C. Yen per aver condiviso lo script AFNI per impostare la fMRI in tempo reale per PV 5 e il team AFNI per il supporto software. Questa ricerca è stata supportata dal finanziamento NIH Brain Initiative (RF1NS113278-01, R01 MH111438-01), e dalla sovvenzione dello strumento S10 (S10 RR023009-01) al Martinos Center, German Research Foundation (DFG) Yu215 / 3-1, BMBF 01GQ1702 e dal finanziamento interno della Max Planck Society.

Questo studio è stato condotto in conformità con la legge tedesca sul benessere degli animali (TierSchG) e l'ordinanza sugli animali da laboratorio per il benessere degli animali (TierSchVersV). Il protocollo sperimentale qui descritto è stato esaminato dalla commissione etica (§15 TierSchG) e approvato dall'autorità statale (Regierungspräsidium, Tübingen, Baden-Württemberg, Germania).
1. Preparazione del set-up sperimentale BOLD-fMRI per lo studio su piccoli animali
<ol><li>Accendere il software della console per controllare i parametri di imaging e acquisire i dati MRI. NOTA: La configurazione fMRI in tempo reale proposta viene implementata utilizzando le macro-funzioni del software della console (versione 6) in parallelo con le funzioni di elaborazione delle immagini di AFNI.</li>
	<li>Trovare le sequenze MR (ad esempio, Posizione, Localizzatore, Acquisizione rapida con miglioramento del rilassamento (RARE) e imaging ecoplanare 3D (EPI) con Esplora area di lavoro, quindi trascinarle e aggiungerle nell'elenco di scansione. NOTA: le sequenze Posizione e Localizzatore vengono utilizzate per identificare una regione di interesse (ROI) in un cervello. Una sequenza RARE viene utilizzata per una scansione anatomica. Una sequenza EPI 3D viene utilizzata per misurare le risposte BOLD dinamiche.</li>
	<li>Posizionare gli script macro predefiniti, "Setup_rt3DEPI" e "Feed2AFNI_rt3DEPI" nel percorso dello script macro (ad esempio, "/opt/(PV version)/prog/curdir/(nome utente)/ParaVision/macros"). Attivare le opzioni di ricostruzione EPI 3D, "Attività serie pre-immagine" e "Esegui macro" nel menu dell'interfaccia utente "Ricostruzione dati", quindi collegare lo script macro predefinito, "Setup_rt3DEPI", prima di fare clic sul pulsante "Scansione". Nota : gli script macro sono inclusi nei file supplementari.</li>
	<li>Installare il software AFNI per l'analisi e la visualizzazione BOLD-fMRI in tempo reale.</li>
</ol>2. Cateterismo e chirurgia di ventilazione
<ol><li>Impostare un ventilatore e sistemi di monitoraggio dello stato fisiologico come termometro, pressione sanguigna e registrazione della respirazione, come mostrato nella Figura 1. Impostare una frequenza costante di 60 ± 1 respiro/min con il ventilatore e una temperatura di 37 °C utilizzando una piastra riscaldante compatibile con MR con un set di controllo di feedback.</li>
	<li>Anestetizzare un ratto Sprague-Dawley maschio adulto (300-600 g) in una camera con isoflurano al 5% per induzione e fornire isoflurano al 2-2,5% per l'intervento chirurgico da un vaporizzatore. Controlla la profondità dell'anestesia pizzicando la zampa posteriore e confermando la mancanza di una risposta di ritiro.</li>
	<li>Intubare l'animale con una cannula di plastica da 14 G per la ventilazione (60 ± 1 respiro/min con una miscela di 70% di aria e 30% di ossigeno). Regolare l'anidride carbonica di fine marea (CO2) nell'intervallo 25 ± 5 mmHg29. NOTA: L'intubazione è fondamentale per mantenere adeguati livelli di CO2 attraverso esperimenti fMRI.</li>
	<li>Metti l'animale in posizione supina su un lettino chirurgico e raditi una coscia con un rasoio elettrico. E poi, fai un'incisione sulla pelle rasata con le forbici chirurgiche. NOTA: La lunghezza dell'incisione è di circa 1-2 cm in direzione longitudinale.</li>
	<li>Trova un'arteria femorale e una vena sotto la regione incisa per il cateterismo e separa l'arteria femorale individuale e la vena dai tessuti circostanti.</li>
	<li>Fissare un lato dell'arteria femorale separata con una sutura chirurgica e tenere l'altro lato con una pinza micro bulldog. Quindi, fare una piccola incisione tra le regioni legate sull'arteria femorale.</li>
	<li>Inserire un catetere nell'arteria femorale attraverso la piccola incisione e legare il catetere e l'arteria insieme con suture chirurgiche. Monitorare costantemente la pressione arteriosa con il sistema di monitoraggio fisiologico nell'intervallo 80-120 mmHg e misurare regolarmente il gas arterioso per mantenere pO 2 di minimo 90 mmHg e pCO2 di 30-45 mmHg durante la scansione. NOTA: Questo cateterismo è fondamentale per il monitoraggio della pressione arteriosa durante gli esperimenti fMRI.</li>
	<li>Fissare entrambe le estremità della vena femorale con suture chirurgiche intrecciate di seta. Quindi, fare una piccola incisione tra le regioni legate sulla vena femorale. Utilizzare una pinza per eseguire la sutura. NOTA: La dimensione della sutura è di circa 1-2 cm.</li>
	<li>Inserire un catetere nella vena femorale. Legare il catetere e la vena insieme con suture chirurgiche. NOTA: Questo cateterismo è fondamentale per la somministrazione di alfa-cloralosio attraverso la vena e la regolazione dei livelli di anestetico durante gli esperimenti fMRI. Se l'animale non è ben anestetizzato, inizierà a respirare spontaneamente. In questo caso, deve essere somministrato più alfa-cloralosio per evitare artefatti di movimento respiratorio.</li>
	<li>Suturare l'incisione chirurgica sulla pelle rasata. Una volta completate le procedure chirurgiche, mantenere l'animale anestetizzato infondendo un bolo di alfa-cloralosio con il dosaggio di ~ 80 mg / kg attraverso il catetere collegato alla vena femorale e interrompere la somministrazione di isoflurano allo stesso tempo.</li>
</ol>3. Posizionamento dell'animale all'interno dello scanner MRI
<ol><li>Trasferire l'animale anestetizzato allo scanner MRI non appena viene eseguito il passaggio 2.10 e fissarlo su una culla personalizzata.</li>
	<li>Inserire un termometro rettale a feedback in tempo reale sull'animale per monitorare la temperatura dell'animale. Posizionare una piastra elettrica sotto il busto dell'animale per controllare la temperatura. Mantenere la temperatura corporea a 37,0 ± 0,5 °C durante le scansioni MRI.</li>
	<li>Fornire alfa-cloralosio con ~ 25 mg / kg / h di soluzione in una miscela di pancuronio (~ 2 mg / kg / h), un rilassante muscolare, mantenendo l'animale anestetizzato e riducendo gli artefatti di movimento nelle immagini fMRI. Monitorare la pressione sanguigna e la respirazione regolando la quantità di farmaco e la velocità di ventilazione in base allo stato fisiologico.</li>
	<li>Somministrare unguento oftalmico sugli occhi dell'animale per prevenire la secchezza durante gli esperimenti fMRI. Fissare la testa dell'animale in modo sicuro con due barre auricolari per evitare artefatti di movimento della testa.</li>
	<li>Fissare una bobina di superficie del ricetrasmettitore sulla testa. Sintonizzare e abbinare la bobina alla frequenza di Larmor (ad esempio, 599 MHz su 14,1 T) sulla testa prima delle misurazioni MRI. NOTA: Qui, la bobina di 22 mm di diametro viene utilizzata per coprire l'intero cervello di un ratto.</li>
	<li>Inserire un paio di elettrodi ad ago nella pelle della zampa anteriore tra le dita 1 e 4 e fissarli con nastro chirurgico. Quindi, verificare che la stimolazione funzioni correttamente dopo aver collegato un cavo di ingresso di stimolazione a questi elettrodi30.</li>
	<li>Inserire l'animale nel foro della risonanza magnetica e posizionarlo approssimativamente nell'isocentro.</li>
</ol>4. Misurazione delle immagini anatomiche RM
<ol><li>Fare clic sul pulsante del menu di calibrazione nell'interfaccia utente principale. Eseguire le calibrazioni del sistema MRI facendo clic sulle seguenti voci nell'interfaccia utente della piattaforma di regolazione (vedere il menu Aiuto nel software della console): Trovare la frequenza di risonanza di base, Calibrare la potenza dell'impulso RF, Impostare il guadagno ottimale del ricevitore, Misurare la mappa B0 nell'animale per lo shimming, Eseguire spessori lineari globali basati sull'integrale del decadimento libero (FID) non localizzato. NOTA: questo passaggio richiede meno di 2 minuti.</li>
	<li>Esegui una sequenza di posizione facendo clic sul pulsante "Scansione" per trovare la posizione della testa dell'animale all'interno del foro della risonanza magnetica. Se la testa non si trova nell'isocentro, regolate la posizione della testina mentre spostate la culla avanti e indietro fino a quando la testa non si trova nell'isocentro.</li>
	<li>Esegui una sequenza di localizzatori facendo clic sul pulsante "Scansione" per identificare un ROI nella testa. Selezionare Map Shim e definire il ROI del volume dello shim per coprire l'intero cervello nell'immagine del localizzatore, quindi eseguire uno shimming di ordine elevato (ad esempio, 2 ° o 3° ordine) utilizzando l'opzione "Shim fino a" per ridurre le disomogeneità del campo magnetico principale (B0) al ROI. NOTA: Lo shimming di ordine elevato è un passaggio fondamentale per migliorare la qualità dei dati BOLD-fMRI quando vengono utilizzate sequenze EPI.</li>
	<li>Eseguire una sequenza RARE pesata in T2 facendo clic sul pulsante "Scan" per acquisire immagini anatomiche che coprono l'intero cervello in una vista coronale (ad esempio, vengono utilizzati i seguenti parametri di sequenza: tempo di ripetizione (TR) 4000 ms, tempo di eco effettivo (TE) 36,1 ms, matrice 128 x 128, campo visivo (FOV) 19,2x19,2 mm2, numero di fette 32, spessore della fetta 0,3 mm, Fattore RARE 8). NOTA: nella seguente fase di visualizzazione fMRI in tempo reale, le immagini anatomiche vengono utilizzate per registrare le immagini EPI 3D come modello.</li>
</ol>5. Configurazione del software fMRI in tempo reale e visualizzazione della risposta fMRI
<ol><li>Apri una finestra di terminale e vai al percorso del plugin AFNI in tempo reale usando il seguente comando: cd /home/(nome utente)/rt_afni NOTA: lo script del plugin AFNI, "afni_rt" è incluso nei file supplementari.</li>
	<li>Esegui il software AFNI con il plugin in tempo reale utilizzando il comando e le opzioni seguenti. AFNI -RT -yestplugouts -DAFNI_REALTIME_MP_HOST_PORT=localhost:(numero porta) -DAFNI_REALTIME_Graph=Tempo reale -DAFNI_FIM_IDEAL=(paradigma) NOTA: Nel primo caso, il codice consente ai programmi esterni di scambiare dati con AFNI mentre nel secondo caso il plug-in in tempo reale tenterà di aprire un socket TCP al localhost e alla porta definiti dall'utente. Nel terzo e quarto caso, i codici tracceranno il corso temporale dei dati fMRI in tempo reale e tracceranno il corso temporale del paradigma definito dall'utente nel corso temporale fMRI rispettivamente quando vengono acquisiti i dati fMRI in tempo reale. Per ulteriori dettagli, consultare https://afni.nimh.nih.gov/pub/dist/doc/program_help/README.environment.html.</li>
	<li>Monitorare i prossimi file AFNI BRIK definiti utilizzando il comando "Dimon" come illustrato nella Figura 2 con le seguenti opzioni: Dimon -tr (TR di EPI) -nt (NRepetizioni di EPI) -rt -quit -infile_pattern in tempo reale*. BRIK · -file_type AFNI NOTA: "Dimon" è un comando per monitorare l'acquisizione in tempo reale di file di immagine AFNI utilizzando le seguenti opzioni: "-rt" che esegue il plugin in tempo reale e "-infile_pattern (nome dati). BRIK -file_type AFNI" che consente al plugin di leggere i file BRIK specifici e di inviarli in AFNI per la visualizzazione e la formattazione. Per ulteriori dettagli, consultare https://afni.nimh.nih.gov/pub/dist/doc/program_help/Dimon.html.</li>
	<li>Utilizzare il comando "pvcmd" con le seguenti opzioni: pvcmd -a JMacroManager JMMExecuteMacro -categoria $USER -macro Feed2AFNI_rt3DEPI NOTA: questo codice esiste nello script macro, "Setup_rt3DEPI", per eseguire lo script macro di sfondo, "Feed2AFNI_rt3DEPI", subito dopo aver fatto clic sul pulsante "Scansione" per l'acquisizione EPI.</li>
	<li>Utilizzare il comando "exec pvcmd" con le seguenti opzioni per ottenere i parametri di acquisizione EPI. exec pvcmd -a ParxServer -r ParamGetValue -psid $ParSpaceId -param (parametri PVM di EPI) -id 10 -args $AcqKey $ParSpaceId $ProcnoPath</li>
	<li>Utilizzare il comando "exec to3d" con le seguenti opzioni per convertire i dati grezzi EPI in file AFNI in tempo reale nello script macro di sfondo, "Feed2AFNI_rt3DEPI". exec to3d -omri -xFOV $FOV_X -yFOV $FOV_Y -zFOV $FOV_Z -prefisso $LastVolName $ImgFormat$Path2dseq</li>
	<li>Assicurarsi che le informazioni geometriche EPI siano coerenti con l'orientamento anatomico. NOTA: Il comando AFNI "to3d" verrà eseguito automaticamente con le informazioni geometriche come il campo visivo (FOV) e la dimensione della matrice per convertire i dati grezzi fMRI in un unico dato AFNI BRIK ogni volta che ogni dato del volume 3D viene memorizzato dopo ogni singolo TR come mostrato nella Figura 2. L'orientamento dell'immagine può essere modificato con i parametri geometrici di "to3d". Per ulteriori dettagli, consulta https://afni.nimh.nih.gov/pub/dist/doc/program_help/to3d.html.</li>
	<li>Accendere un isolatore di stimolo elettrico ed eseguire la stimolazione elettrica della zampa anteriore per uno studio fMRI evocato (ad esempio, 3Hz, larghezza di impulso 4s 300us, 2,5mA) utilizzando blocchi di stimolazione. NOTA: Qui, il paradigma di progettazione dei blocchi consiste in 10 scansioni di pre-stimolazione, 3 scansioni di stimolazione e 12 scansioni di inter-stimolazione (15 scansioni per epoca).</li>
	<li>Eseguire una sequenza EPI 3D pesata in T2* facendo clic sul pulsante "Scan" per lo studio BOLD-fMRI (ad esempio, vengono utilizzati i seguenti parametri: TR/TE 1500/14 ms, matrice 64 x 64 x 32, FOV 19,2 x 19,2 x 9,6 mm 3 e risoluzione 300 x 300 x 300 μm3). NOTA: non appena si fa clic sul pulsante "Scansione", il monitoraggio e l'elaborazione dei dati grezzi verranno eseguiti utilizzando gli script macro predefiniti in tempo reale. Una volta convertito un set di dati AFNI BRIK, i grafici del percorso temporale voxel-wise per le immagini EPI 3D vengono visualizzati nel software AFNI e aggiornati automaticamente per ogni singolo TR.</li>
	<li>Per sovrapporre le immagini EPI alle immagini anatomiche RARE, convertire le immagini RARE in un set di dati AFNI BRIK utilizzando il comando "to3d" come nel passaggio 5.6, quindi registrare le immagini EPI nelle immagini anatomiche utilizzando lo script AFNI "align_epi_anat.py" con le seguenti opzioni: align_epi_anat.py -anat anatomy_template_al+orig -epi epi.$(epi data number)+orig -epi_base 1 -suffisso _volreg -rat_align -cost LPA -epi2anat NOTA: per ulteriori dettagli, consultare https://afni.nimh.nih.gov/pub/dist/doc/program_help/ align_epi_anat.py.html.</li>
	<li>Per elaborare mappe funzionali delle risposte BOLD, calcolare la deconvoluzione del set di dati 3D+tempo con una serie temporale di stimolo specifica utilizzando il comando "3dDeconvolve" con le seguenti opzioni: 3dDeconvolve -input (nome file di input)+orig. -nfirst 0 -polort 3 -num_stimts 1 -stim_times 1 (nome del file del paradigma di stimolazione) 'BLOCK(4,1)' -stim_label 1 zampa anteriore -tout -fout -rout NOTA: le fasi di elaborazione delle immagini come l'attenuazione spaziale o il filtraggio temporale sono state incorporate in uno script di elaborazione dati AFNI personalizzato. Per ulteriori dettagli, consulta https://afni.nimh.nih.gov/afni/doc/help/3dDeconvolve.html.</li>
	<li>Per visualizzare le mappe funzionali dei segnali BOLD, utilizzare un clustering interattivo nel software AFNI. Aprire l'opzione "Define Overlay" e utilizzare la funzione "Clusters" dal menu dell'interfaccia utente AFNI.</li>
	<li>Dopo l'ultima scansione fMRI, estrarre l'animale dallo scanner MRI e eutanasia secondo i protocolli approvati. NOTA: le funzioni di elaborazione delle immagini di AFNI e le macro-funzioni nel più recente software della console sono state utilizzate per elaborare i dati fMRI in tempo reale. Informazioni dettagliate e descrizioni delle macrofunzioni sono disponibili dal menu di aiuto nel software della console. Il software AFNI è un freeware, che può essere scaricato direttamente attraverso il sito web NIMH-AFNI. Gli script correlati per creare il collegamento tra AFNI e il sistema di console sono allegati.</li>
</ol>

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B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+animal+functional+magnetic+resonance+imaging+and+its+application+to+neurophamacological+studies.">Real-time animal functional magnetic resonance imaging and its application to neurophamacological studies.</a> Magnetic Resonance Imaging. 26 (9), 1266-1272 (2008).</li><li>Cox, R. W., Jesmanowicz, A., Hyde, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+functional+magnetic+resonance+imaging.">Real-time functional magnetic resonance imaging.</a> Magnetic Resonance Medicine. 33 (2), 230-236 (1995).</li><li>Lee, C. C., Jack, C. R., Rossman, P. J., Riederer, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+reconstruction+and+high-speed+processing+in+functional+MR+imaging.">Real-time reconstruction and high-speed processing in functional MR imaging.</a> American Journal of Neuroradiology. 19 (7), 1297-1300 (1998).</li><li>Voyvodic, J. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+fMRI+paradigm+control,+physiology,+and+behavior+combined+with+near+real-time+statistical+analysis.">Real-time fMRI paradigm control, physiology, and behavior combined with near real-time statistical analysis.</a> Neuroimage. 10 (2), 91-106 (1999).</li><li>Cohen, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+functional+magnetic+resonance+imaging.">Real-time functional magnetic resonance imaging.</a> Methods. 25 (2), 201-220 (2001).</li><li>Posse, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+new+approach+to+measure+single-event+related+brain+activity+using+real-time+fMRI:+Feasibility+of+sensory,+motor,+and+higher+cognitive+tasks.">A new approach to measure single-event related brain activity using real-time fMRI: Feasibility of sensory, motor, and higher cognitive tasks.</a> Human Brain Mapping. 12 (1), 25-41 (2001).</li><li>Decharms, R. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reading+and+controlling+human+brain+activation+using+real-time+functional+magnetic+resonance+imaging.">Reading and controlling human brain activation using real-time functional magnetic resonance imaging.</a> Trends in Cognitive Sciences. 11 (11), 473-481 (2007).</li><li>Bruhl, A. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Making+Sense+of+Real-Time+Functional+Magnetic+Resonance+Imaging+(rtfMRI)+and+rtfMRI+Neurofeedback.">Making Sense of Real-Time Functional Magnetic Resonance Imaging (rtfMRI) and rtfMRI Neurofeedback.</a> International Journal of Neuropsychopharmacology. 18 (6), (2015).</li><li>Cox, R. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=AFNI:+Software+for+analysis+and+visualization+of+functional+magnetic+resonance+neuroimages.">AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages.</a> Computers and Biomedical Research. 29 (3), 162-173 (1996).</li><li>Liou, W. W., Goshgarian, H. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+assessment+of+the+effect+of+chronic+phrenicotomy+on+the+induction+of+the+crossed+phrenic+phenomenon.">Quantitative assessment of the effect of chronic phrenicotomy on the induction of the crossed phrenic phenomenon.</a> Experimental Neurology. 127 (1), 145-153 (1994).</li><li>Shih, Y. Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultra+high-resolution+fMRI+and+electrophysiology+of+the+rat+primary+somatosensory+cortex.">Ultra high-resolution fMRI and electrophysiology of the rat primary somatosensory cortex.</a> Neuroimage. 73, 113-120 (2013).</li><li>Masamoto, K., Kim, T., Fukuda, M., Wang, P., Kim, S. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Relationship+between+neural,+vascular,+and+BOLD+signals+in+isoflurane-anesthetized+rat+somatosensory+cortex.">Relationship between neural, vascular, and BOLD signals in isoflurane-anesthetized rat somatosensory cortex.</a> Cerebral Cortex. 17 (4), 942-950 (2007).</li><li>van Alst, T. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Anesthesia+differentially+modulates+neuronal+and+vascular+contributions+to+the+BOLD+signal.">Anesthesia differentially modulates neuronal and vascular contributions to the BOLD signal.</a> Neuroimage. 195, 89-103 (2019).</li><li>Wu, T. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+isoflurane+anesthesia+on+resting-state+fMRI+signals+and+functional+connectivity+within+primary+somatosensory+cortex+of+monkeys.">Effects of isoflurane anesthesia on resting-state fMRI signals and functional connectivity within primary somatosensory cortex of monkeys.</a> Brain and Behavior. 6 (12), 00591 (2016).</li><li>Liu, X., Zhu, X. H., Zhang, Y., Chen, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+change+of+functional+connectivity+specificity+in+rats+under+various+anesthesia+levels+and+its+neural+origin.">The change of functional connectivity specificity in rats under various anesthesia levels and its neural origin.</a> Brain Topography. 26 (3), 363-377 (2013).</li><li>Liu, X. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiphasic+modification+of+intrinsic+functional+connectivity+of+the+rat+brain+during+increasing+levels+of+propofol.">Multiphasic modification of intrinsic functional connectivity of the rat brain during increasing levels of propofol.</a> Neuroimage. 83, 581-592 (2013).</li><li>Hutchison, R. M., Hutchison, M., Manning, K. Y., Menon, R. S., Everling, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isoflurane+induces+dose-dependent+alterations+in+the+cortical+connectivity+profiles+and+dynamic+properties+of+the+brain's+functional+architecture.">Isoflurane induces dose-dependent alterations in the cortical connectivity profiles and dynamic properties of the brain's functional architecture.</a> Human Brain Mapping. 35 (12), 5754-5775 (2014).</li><li>He, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultra-Slow+Single-Vessel+BOLD+and+CBV-Based+fMRI+Spatiotemporal+Dynamics+and+Their+Correlation+with+Neuronal+Intracellular+Calcium+Signals.">Ultra-Slow Single-Vessel BOLD and CBV-Based fMRI Spatiotemporal Dynamics and Their Correlation with Neuronal Intracellular Calcium Signals.</a> Neuron. 97 (4), 925-939 (2018).</li><li>Yoshida, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Physiological+effects+of+a+habituation+procedure+for+functional+MRI+in+awake+mice+using+a+cryogenic+radiofrequency+probe.">Physiological effects of a habituation procedure for functional MRI in awake mice using a cryogenic radiofrequency probe.</a> Journal of Neuroscience Methods. 274, 38-48 (2016).</li></ol>

Sascha Köhler è un dipendente di Bruker BioSpin MRI GmbH.

Il monitoraggio in tempo reale del segnale fMRI aiuta gli sperimentatori a regolare la fisiologia degli animali per ottimizzare la mappatura funzionale. Gli artefatti di movimento negli animali svegli, così come l'effetto anestetico, sono i principali fattori che mediano la variabilità dei segnali fMRI, confondendo l'interpretazione biologica del segnale da solo 31,32,33,34,35,36,37,38</...

La risonanza magnetica funzionale (fMRI) è un metodo non invasivo per misurare le risposte emodinamiche 1,2,3,4,5,6,7,8,9, ad esempio, il volume del sangue cerebrale dipendente dal livello di ossigeno nel sangue (BOLD), il volume del sangue cerebrale e il segnale di flusso, associati all'attività neurale nel cervello. Negli studi sugli animali, i segnali emodinamici possono essere influenzati dall'anestesia10, dal livello di stress degli animali svegli 11, nonché dai potenziali artefatti non fisiologici, ad esempio pulsazioni cardiache e movimenti respiratori12,13,14,15. Sebbene siano stati sviluppati molti metodi di post-elaborazione per fornire un'analisi retrospettiva del segnale fMRI per la dinamica funzionale correlata al compito e allo stato di riposo e la mappatura della connettività16,17,18,19, ci sono poche tecniche per fornire una soluzione di mappatura delle funzioni cerebrali in tempo reale e letture istantanee nel cervello animale 20 (la maggior parte delle quali sono utilizzate principalmente per la mappatura del cervello umano21, 22,23,24,25,26,27). In particolare, questo tipo di metodo di mappatura fMRI in tempo reale è carente negli studi sugli animali. È necessario istituire una piattaforma fMRI per consentire l'indagine degli stadi fisiologici dipendenti dallo stato cerebrale in tempo reale e fornire un paradigma di stimolazione biofeedback in tempo reale per studi funzionali del cervello animale.
Nel presente lavoro, illustriamo un set-up sperimentale fMRI in tempo reale con le macro-funzioni personalizzate del software della console MRI, dimostrando il monitoraggio in tempo reale delle risposte BOLD-fMRI evocate nella corteccia somatosensoriale primaria della zampa anteriore (FP-S1) dei ratti anestetizzati. Questa configurazione in tempo reale consente la visualizzazione dell'attivazione cerebrale in corso in mappe funzionali, nonché singoli corsi temporali in modo voxel-wise, utilizzando il software di analisi delle neuroimmagini esistente, Analysis of Functional NeuroImages (AFNI)28. La preparazione del set-up sperimentale fMRI in tempo reale per lo studio sugli animali è descritta nel protocollo. Oltre alla configurazione degli animali, forniamo procedure dettagliate per impostare la visualizzazione e l'analisi dei segnali fMRI in tempo reale utilizzando il più recente software della console in parallelo con gli script di elaborazione delle immagini. In sintesi, la configurazione fMRI in tempo reale proposta per gli studi sugli animali è un potente strumento per monitorare i segnali dinamici fMRI nel cervello animale utilizzando il sistema di console MRI.

<table>
	<tbody>
		<tr>
			<td>14.1T Bruker MRI system</td>
			<td>Bruker BioSpin MRI GmbH</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>A365 Stimulus Isolator</td>
			<td>World Precision Instruments</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>AcqKnowledge Software</td>
			<td>Biopac</td>
			<td>RRID:SCR_014279, http://www.biopac.com/product/acqknowledge-software/</td>
			<td></td>
		</tr>
		<tr>
			<td>AFNI</td>
			<td>Cox, 1996</td>
			<td>RRID:SCR_005927, http://afni.nimh.nih.gov</td>
			<td></td>
		</tr>
		<tr>
			<td>CO2SMO (ETCO2/SpO2 Monitor), Model 7100</td>
			<td>Novametrix Medical Systems Inc</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>Isoflurane</td>
			<td>CP-Pharma</td>
			<td>Cat# 1214</td>
			<td></td>
		</tr>
		<tr>
			<td>Master-9</td>
			<td>A.M.P.I</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>Nanoliter Injector</td>
			<td>World Precision Instruments</td>
			<td>Cat# NANOFIL</td>
			<td></td>
		</tr>
		<tr>
			<td>Pancuronium Bromide</td>
			<td>Inresa Arzneimittel</td>
			<td>Cat# 34409.00.00</td>
			<td></td>
		</tr>
		<tr>
			<td>ParaVision 6</td>
			<td>Bruker BioSpin MRI GmbH</td>
			<td>RRID:SCR_001964</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate Buffered Saline (PBS)</td>
			<td>Gibco</td>
			<td>Cat# 10010-023</td>
			<td></td>
		</tr>
		<tr>
			<td>Rat: Sprague Dawley rat</td>
			<td>Charles River Laboratories</td>
			<td>Crl:CD(SD)</td>
			<td></td>
		</tr>
		<tr>
			<td>SAR-830/AP Ventilator</td>
			<td>CWE</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>&#945;-chloralose</td>
			<td>Sigma-Aldrich</td>
			<td>Cat# C0128-25G;RRID</td>
			<td></td>
		</tr>
	</tbody>
</table>

real-time fmri brain mapping in animals

Le risposte fMRI dinamiche variano in gran parte in base alle condizioni fisiologiche degli animali sia in anestesia che in stato di veglia. Abbiamo sviluppato una piattaforma fMRI in tempo reale per guidare gli sperimentatori a monitorare istantaneamente le risposte fMRI durante l'acquisizione, che può essere utilizzata per modificare la fisiologia degli animali per ottenere le risposte emodinamiche desiderate nel cervello animale. La configurazione fMRI in tempo reale si basa su un sistema di risonanza magnetica preclinica 14.1T, che consente la mappatura in tempo reale delle risposte fMRI dinamiche nella corteccia somatosensoriale primaria della zampa anteriore (FP-S1) di ratti anestetizzati. Invece di un'analisi retrospettiva per indagare le fonti confondenti che portano alla variabilità dei segnali fMRI, la piattaforma fMRI in tempo reale fornisce uno schema più efficace per identificare le risposte fMRI dinamiche utilizzando macro-funzioni personalizzate e un software di analisi delle neuroimmagini comune nel sistema MRI. Inoltre, fornisce una fattibilità immediata per la risoluzione dei problemi e un paradigma di stimolazione del biofeedback in tempo reale per gli studi funzionali del cervello negli animali.

La Figura 3 e la Figura 4 mostrano un percorso temporale BOLD-fMRI rappresentativo in tempo reale e mappe funzionali con stimolazione elettrica della zampa anteriore (3 Hz, 4 s, larghezza dell'impulso 300 us, 2,5 mA). Il paradigma di progettazione fMRI comprende 10 scansioni di pre-stimolazione, 3 scansioni di stimolazione e 12 scansioni di inter-stimolazione con un totale di 8 epoche (130 scansioni). Il tempo di scansione totale è di 3 min 15 sec (195 sec). <s...

Watch this Scientific Journal Video about Real-Time fMRI Brain Mapping in Animals at JoVE.com

Real-Time fMRI Brain Mapping in Animals

La mappatura funzionale del cervello animale può trarre vantaggio dalla configurazione sperimentale di risonanza magnetica funzionale in tempo reale (fMRI). Utilizzando il più recente software implementato nel sistema di risonanza magnetica animale, abbiamo creato una piattaforma di monitoraggio in tempo reale per la fMRI dei piccoli animali.

Mappatura cerebrale fMRI in tempo reale negli animali

Dynamic fMRI responses vary largely according to the physiological conditions of animals either under anesthesia or in awake states. We developed a ...

Research

JoVE Journal

Neuroscience

3.4K Views.  Max Planck Institute for Biological Cybernetics. La mappatura funzionale del cervello animale può trarre vantaggio dalla configurazione sperimentale di risonanza magnetica funzionale in tempo reale (fMRI). Utilizzando il più recente software implementato nel sistema di risonanza magnetica animale, abbiamo creato una piattaforma di monitoraggio in tempo reale per la fMRI dei piccoli animali.

Video: Real-Time fMRI Brain Mapping in Animals

Simultaneous fMRI and Electrophysiology in the Rodent Brain

To examine the neural basis of the blood oxygenation level dependent (BOLD) magnetic resonance imaging (MRI) signal, we have developed a rodent model in which functional MRI data and in vivo intracortical recording can be performed simultaneously. The combination of MRI and electrical recording is technically challenging because the electrodes used for recording distort the MRI images and the MRI acquisition induces noise in the electrical recording. To minimize the mutual interference of the two modalities, glass microelectrodes were used rather than metal and a noise removal algorithm was implemented for the electrophysiology data. In our studies, two microelectrodes were separately implanted in bilateral primary somatosensory cortices (SI) of the rat and fixed in place. One coronal slice covering the electrode tips was selected for functional MRI. Electrode shafts and fixation positions were not included in the image slice to avoid imaging artifacts. The removed scalp was replaced with toothpaste to reduce susceptibility mismatch and prevent Gibbs ringing artifacts in the images. The artifact structure induced in the electrical recordings by the rapidly-switching magnetic fields during image acquisition was characterized by averaging all cycles of scans for each run. The noise structure during imaging was then subtracted from original recordings. The denoised time courses were then used for further analysis in combination with the fMRI data. As an example, the simultaneous acquisition was used to determine the relationship between spontaneous fMRI BOLD signals and band-limited intracortical electrical activity. Simultaneous fMRI and electrophysiological recording in the rodent will provide a platform for many exciting applications in neuroscience in addition to elucidating the relationship between the fMRI BOLD signal and neuronal activity.

We have developed a method for simultaneous functional magnetic resonance imaging and electrophysiological recording in the rodent brain, providing a platform for the investigation of the relationship between neural activity and the blood oxygenation level dependent (BOLD) MRI signal.

FMRI simultanea ed Elettrofisiologia nel cervello roditori

To examine the neural basis of the blood oxygenation level dependent (BOLD) magnetic resonance imaging (MRI) signal, we have developed a rodent model in ...

Ricerca

Neuroscienze

Combining Transcranial Magnetic Stimulation and fMRI to Examine the Default Mode Network

The default mode network is a group of brain regions that are active when an individual is not focused on the outside world and the brain is at "wakeful rest."1,2,3 It is thought the default mode network corresponds to self-referential or "internal mentation".2,3
It has been hypothesized that, in humans, activity within the default mode network is correlated with certain pathologies (for instance, hyper-activation has been linked to schizophrenia 4,5,6 and autism spectrum disorders 7 whilst hypo-activation of the network has been linked to Alzheimer's and other neurodegenerative diseases 8). As such, noninvasive modulation of this network may represent a potential therapeutic intervention for a number of neurological and psychiatric pathologies linked to abnormal network activation. One possible tool to effect this modulation is Transcranial Magnetic Stimulation: a non-invasive neurostimulatory and neuromodulatory technique that can transiently or lastingly modulate cortical excitability (either increasing or decreasing it) via the application of localized magnetic field pulses.9
In order to explore the default mode network's propensity towards and tolerance of modulation, we will be combining TMS (to the left inferior parietal lobe) with functional magnetic resonance imaging (fMRI). Through this article, we will examine the protocol and considerations necessary to successfully combine these two neuroscientific tools.

In this article, we examine the methodology and considerations relevant to the combination of TMS and fMRI to examine the effects of brain stimulation on the default network.

La combinazione di stimolazione magnetica transcranica e fMRI per esaminare il modo predefinito della rete

The default mode network is a group of brain regions that are active when an individual is not focused on the outside world and the brain is at "wakeful ...

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Neuroimaging studies of human cognitive, sensory, and motor processes are usually based on noninvasive techniques such as electroencephalography (EEG), magnetoencephalography or functional magnetic-resonance imaging. These techniques have either inherently low temporal or low spatial resolution, and suffer from low signal-to-noise ratio and/or poor high-frequency sensitivity. Thus, they are suboptimal for exploring the short-lived spatio-temporal dynamics of many of the underlying brain processes. In contrast, the invasive technique of electrocorticography (ECoG) provides brain signals that have an exceptionally high signal-to-noise ratio, less susceptibility to artifacts than EEG, and a high spatial and temporal resolution (i.e., &lt;1 cm/&lt;1 millisecond, respectively). ECoG involves measurement of electrical brain signals using electrodes that are implanted subdurally on the surface of the brain. Recent studies have shown that ECoG amplitudes in certain frequency bands carry substantial information about task-related activity, such as motor execution and planning1, auditory processing2 and visual-spatial attention3. Most of this information is captured in the high gamma range (around 70-110 Hz). Thus, gamma activity has been proposed as a robust and general indicator of local cortical function1-5. ECoG can also reveal functional connectivity and resolve finer task-related spatial-temporal dynamics, thereby advancing our understanding of large-scale cortical processes. It has especially proven useful for advancing brain-computer interfacing (BCI) technology for decoding a user's intentions to enhance or improve communication6 and control7. Nevertheless, human ECoG data are often hard to obtain because of the risks and limitations of the invasive procedures involved, and the need to record within the constraints of clinical settings. Still, clinical monitoring to localize epileptic foci offers a unique and valuable opportunity to collect human ECoG data. We describe our methods for collecting recording ECoG, and demonstrate how to use these signals for important real-time applications such as clinical mapping and brain-computer interfacing. Our example uses the BCI2000 software platform8,9 and the SIGFRIED10 method, an application for real-time mapping of brain functions. This procedure yields information that clinicians can subsequently use to guide the complex and laborious process of functional mapping by electrical stimulation.
Prerequisites and Planning:
Patients with drug-resistant partial epilepsy may be candidates for resective surgery of an epileptic focus to minimize the frequency of seizures. Prior to resection, the patients undergo monitoring using subdural electrodes for two purposes: first, to localize the epileptic focus, and second, to identify nearby critical brain areas (i.e., eloquent cortex) where resection could result in long-term functional deficits. To implant electrodes, a craniotomy is performed to open the skull. Then, electrode grids and/or strips are placed on the cortex, usually beneath the dura. A typical grid has a set of 8 x 8 platinum-iridium electrodes of 4 mm diameter (2.3 mm exposed surface) embedded in silicon with an inter-electrode distance of 1cm. A strip typically contains 4 or 6 such electrodes in a single line. The locations for these grids/strips are planned by a team of neurologists and neurosurgeons, and are based on previous EEG monitoring, on a structural MRI of the patient's brain, and on relevant factors of the patient's history. Continuous recording over a period of 5-12 days serves to localize epileptic foci, and electrical stimulation via the implanted electrodes allows clinicians to map eloquent cortex. At the end of the monitoring period, explantation of the electrodes and therapeutic resection are performed together in one procedure.
In addition to its primary clinical purpose, invasive monitoring also provides a unique opportunity to acquire human ECoG data for neuroscientific research. The decision to include a prospective patient in the research is based on the planned location of their electrodes, on the patient's performance scores on neuropsychological assessments, and on their informed consent, which is predicated on their understanding that participation in research is optional and is not related to their treatment. As with all research involving human subjects, the research protocol must be approved by the hospital's institutional review board. The decision to perform individual experimental tasks is made day-by-day, and is contingent on the patient's endurance and willingness to participate. Some or all of the experiments may be prevented by problems with the clinical state of the patient, such as post-operative facial swelling, temporary aphasia, frequent seizures, post-ictal fatigue and confusion, and more general pain or discomfort.
At the Epilepsy Monitoring Unit at Albany Medical Center in Albany, New York, clinical monitoring is implemented around the clock using a 192-channel Nihon-Kohden Neurofax monitoring system. Research recordings are made in collaboration with the Wadsworth Center of the New York State Department of Health in Albany. Signals from the ECoG electrodes are fed simultaneously to the research and the clinical systems via splitter connectors. To ensure that the clinical and research systems do not interfere with each other, the two systems typically use separate grounds. In fact, an epidural strip of electrodes is sometimes implanted to provide a ground for the clinical system. Whether research or clinical recording system, the grounding electrode is chosen to be distant from the predicted epileptic focus and from cortical areas of interest for the research. Our research system consists of eight synchronized 16-channel g.USBamp amplifier/digitizer units (g.tec, Graz, Austria). These were chosen because they are safety-rated and FDA-approved for invasive recordings, they have a very low noise-floor in the high-frequency range in which the signals of interest are found, and they come with an SDK that allows them to be integrated with custom-written research software. In order to capture the high-gamma signal accurately, we acquire signals at 1200Hz sampling rate-considerably higher than that of the typical EEG experiment or that of many clinical monitoring systems. A built-in low-pass filter automatically prevents aliasing of signals higher than the digitizer can capture. The patient's eye gaze is tracked using a monitor with a built-in Tobii T-60 eye-tracking system (Tobii Tech., Stockholm, Sweden). Additional accessories such as joystick, bluetooth Wiimote (Nintendo Co.), data-glove (5th Dimension Technologies), keyboard, microphone, headphones, or video camera are connected depending on the requirements of the particular experiment.
Data collection, stimulus presentation, synchronization with the different input/output accessories, and real-time analysis and visualization are accomplished using our BCI2000 software8,9. BCI2000 is a freely available general-purpose software system for real-time biosignal data acquisition, processing and feedback. It includes an array of pre-built modules that can be flexibly configured for many different purposes, and that can be extended by researchers' own code in C++, MATLAB or Python. BCI2000 consists of four modules that communicate with each other via a network-capable protocol: a Source module that handles the acquisition of brain signals from one of 19 different hardware systems from different manufacturers; a Signal Processing module that extracts relevant ECoG features and translates them into output signals; an Application module that delivers stimuli and feedback to the subject; and the Operator module that provides a graphical interface to the investigator.
A number of different experiments may be conducted with any given patient. The priority of experiments will be determined by the location of the particular patient's electrodes. However, we usually begin our experimentation using the SIGFRIED (SIGnal modeling For Realtime Identification and Event Detection) mapping method, which detects and displays significant task-related activity in real time. The resulting functional map allows us to further tailor subsequent experimental protocols and may also prove as a useful starting point for traditional mapping by electrocortical stimulation (ECS).
Although ECS mapping remains the gold standard for predicting the clinical outcome of resection, the process of ECS mapping is time consuming and also has other problems, such as after-discharges or seizures. Thus, a passive functional mapping technique may prove valuable in providing an initial estimate of the locus of eloquent cortex, which may then be confirmed and refined by ECS. The results from our passive SIGFRIED mapping technique have been shown to exhibit substantial concurrence with the results derived using ECS mapping10.
The protocol described in this paper establishes a general methodology for gathering human ECoG data, before proceeding to illustrate how experiments can be initiated using the BCI2000 software platform. Finally, as a specific example, we describe how to perform passive functional mapping using the BCI2000-based SIGFRIED system.

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

We present a method for collecting electrocorticographic signals for research purposes from humans who are undergoing invasive epilepsy monitoring. We show how to use the BCI2000 software platform for data collection, signal processing and stimulus presentation. Specifically, we demonstrate SIGFRIED, a BCI2000-based tool for real-time functional brain mapping.

Registrazione umani Electrocorticographic (ECOG) Segnali per la ricerca neuroscientifica e in tempo reale la mappatura funzionale corticale

Neuroimaging studies of human cognitive, sensory, and motor processes are usually based on noninvasive techniques such as electroencephalography (EEG), ...

Design and Assembly of an Ultra-light Motorized Microdrive for Chronic Neural Recordings in Small Animals

The ability to chronically record from populations of neurons in freely behaving animals has proven an invaluable tool for dissecting the function of neural circuits underlying a variety of natural behaviors, including navigation1 , decision making 2,3, and the generation of complex motor sequences4,5,6. Advances in precision machining has allowed for the fabrication of light-weight devices suitable for chronic recordings in small animals, such as mice and songbirds. The ability to adjust the electrode position with small remotely controlled motors has further increased the recording yield in various behavioral contexts by reducing animal handling.6,7
 Here we describe a protocol to build an ultra-light motorized microdrive for long-term chronic recordings in small animals. Our design evolved from an earlier published version7, and has been adapted for ease-of use and cost-effectiveness to be more practical and accessible to a wide array of researchers. This proven design 8,9,10,11 allows for fine, remote positioning of electrodes over a range of ~ 5 mm and weighs less than 750 mg when fully assembled. We present the complete protocol for how to build and assemble these drives, including 3D CAD drawings for all custom microdrive components.

The design, fabrication and assembly of an ultra-light motorized microdrive is described. The device provides a cost-effective and easy-to-use solution for chronic recordings of single units in small behaving animals.

Progettazione e assemblaggio di un ultraleggero motorizzato per Microdrive croniche Recordings neurali in animali di piccola taglia

The ability to chronically record from populations of neurons in freely behaving animals has proven an invaluable tool for dissecting the function of ...

Functional Imaging of Auditory Cortex in Adult Cats using High-field fMRI

Current knowledge of sensory processing in the mammalian auditory system is mainly derived from electrophysiological studies in a variety of animal models, including monkeys, ferrets, bats, rodents, and cats. In order to draw suitable parallels between human and animal models of auditory function, it is important to establish a bridge between human functional imaging studies and animal electrophysiological studies. Functional magnetic resonance imaging (fMRI) is an established, minimally invasive method of measuring broad patterns of hemodynamic activity across different regions of the cerebral cortex. This technique is widely used to probe sensory function in the human brain, is a useful tool in linking studies of auditory processing in both humans and animals and has been successfully used to investigate auditory function in monkeys and rodents. The following protocol describes an experimental procedure for investigating auditory function in anesthetized adult cats by measuring stimulus-evoked hemodynamic changes in auditory cortex using fMRI. This method facilitates comparison of the hemodynamic responses across different models of auditory function thus leading to a better understanding of species-independent features of the mammalian auditory cortex.

Functional studies of the auditory system in mammals have traditionally been conducted using spatially-focused techniques such as electrophysiological recordings. The following protocol describes a method of visualizing large-scale patterns of evoked hemodynamic activity in the cat auditory cortex using functional magnetic resonance imaging.

Imaging funzionale di Auditory Cortex in gatti adulti utilizzando ad alto campo fMRI

Current knowledge of sensory processing in the mammalian auditory system is mainly derived from electrophysiological studies in a variety of animal ...

Deep Brain Stimulation with Simultaneous fMRI in Rodents

In order to visualize the global and downstream neuronal responses to deep brain stimulation (DBS) at various targets, we have developed a protocol for using blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) to image rodents with simultaneous DBS. DBS fMRI presents a number of technical challenges, including accuracy of electrode implantation, MR artifacts created by the electrode, choice of anesthesia and paralytic to minimize any neuronal effects while simultaneously eliminating animal motion, and maintenance of physiological parameters, deviation from which can confound the BOLD signal.&#160;Our laboratory has developed a set of procedures that are capable of overcoming most of these possible issues. For electrical stimulation, a homemade tungsten bipolar microelectrode is used, inserted stereotactically at the stimulation site in the anesthetized subject. In preparation for imaging, rodents are fixed on a plastic headpiece and transferred to the magnet bore. For sedation and paralysis during scanning, a cocktail of dexmedetomidine and pancuronium is continuously infused, along with a minimal dose of isoflurane; this preparation minimizes the BOLD ceiling effect of volatile anesthetics. In this example experiment, stimulation of the subthalamic nucleus (STN) produces BOLD responses which are observed primarily in ipsilateral cortical regions, centered in motor cortex. Simultaneous DBS and fMRI allows the unambiguous modulation of neural circuits dependent on stimulation location and stimulation parameters, and permits observation of neuronal modulations free of regional bias. This technique may be used to explore the downstream effects of modulating neural circuitry at nearly any brain region, with implications for both experimental and clinical DBS.

This protocol describes a standard method for simultaneous functional magnetic resonance imaging and deep brain stimulation in the rodent. The combined use of these experimental tools allows for the exploration of global downstream activity in response to electrical stimulation at virtually any brain target.

La stimolazione cerebrale profonda con simultanea fMRI in Roditori

In order to visualize the global and downstream neuronal responses to deep brain stimulation (DBS) at various targets, we have developed a protocol for ...

An Ex Vivo Laser-induced Spinal Cord Injury Model to Assess Mechanisms of Axonal Degeneration in Real-time

Injured CNS axons fail to regenerate and often retract away from the injury site. Axons spared from the initial injury may later undergo secondary axonal degeneration. Lack of growth cone formation, regeneration, and loss of additional myelinated axonal projections within the spinal cord greatly limits neurological recovery following injury. To assess how central myelinated axons of the spinal cord respond to injury, we developed an ex vivo living spinal cord model utilizing transgenic mice that express yellow fluorescent protein in axons and a focal and highly reproducible laser-induced spinal cord injury to document the fate of axons and myelin (lipophilic fluorescent dye Nile Red) over time using two-photon excitation time-lapse microscopy. Dynamic processes such as acute axonal injury, axonal retraction, and myelin degeneration are best studied in real-time. However, the non-focal nature of contusion-based injuries and movement artifacts encountered during in vivo spinal cord imaging make differentiating primary and secondary axonal injury responses using high resolution microscopy challenging. The ex vivo spinal cord model described here mimics several aspects of clinically relevant contusion/compression-induced axonal pathologies including axonal swelling, spheroid formation, axonal transection, and peri-axonal swelling providing a useful model to study these dynamic processes in real-time. Major advantages of this model are excellent spatiotemporal resolution that allows differentiation between the primary insult that directly injures axons and secondary injury mechanisms; controlled infusion of reagents directly to the perfusate bathing the cord; precise alterations of the environmental milieu (e.g., calcium, sodium ions, known contributors to axonal injury, but near impossible to manipulate in vivo); and murine models also offer an advantage as they provide an opportunity to visualize and manipulate genetically identified cell populations and subcellular structures. Here, we describe how to isolate and image the living spinal cord from mice to capture dynamics of acute axonal injury.

An Ex Vivo Laser-induced Spinal Cord Injury Model to Assess Mechanisms of Axonal Degeneration in Real-time

We present a protocol utilizing two-photon excitation time-lapse microscopy to simultaneously visualize the dynamics of axon and myelin injuries in real time. This proposed protocol permits studies of both intrinsic and extrinsic factors which can influence central myelinated axon fate after injury and contribute to permanent clinical disability.

Un<em&gt; Ex Vivo</em&gt; Laser-indotta Spinal Cord Injury modello per valutare i meccanismi di degenerazione assonale in tempo reale

Injured CNS axons fail to regenerate and often retract away from the injury site. Axons spared from the initial injury may later undergo secondary axonal ...

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control neuroplastic processes and correct abnormal function, or even shift functions from damaged tissue to physiologically healthy brain regions, hold the potential to dramatically improve overall health. Of the current neuroplastic interventions in development, neurofeedback training (NFT) from functional Magnetic Resonance Imaging (fMRI) has the advantages of being completely non-invasive, non-pharmacologic, and spatially localized to target brain regions, as well as having no known side effects. Furthermore, NFT techniques, initially developed using fMRI, can often be translated to exercises that can be performed outside of the scanner without the aid of medical professionals or sophisticated medical equipment. In fMRI NFT, the fMRI signal is measured from specific regions of the brain, processed, and presented to the participant in real-time. Through training, self-directed mental processing techniques, that regulate this signal and its underlying neurophysiologic correlates, are developed. FMRI NFT has been used to train volitional control over a wide range of brain regions with implications for several different cognitive, behavioral, and motor systems. Additionally, fMRI NFT has shown promise in a broad range of applications such as the treatment of neurologic disorders and the augmentation of baseline human performance. In this article, we present an fMRI NFT protocol developed at our institution for modulation of both healthy and abnormal brain function, as well as examples of using the method to target both cognitive and auditory regions of the brain.

The ability to induce and/or control neural plasticity may be critical in future treatments for neurologic disorders and the recovery from brain injury. In this paper, we present a protocol on the use of neurofeedback training with functional magnetic resonance imaging to modulate human brain function.

Un protocollo per l'amministrazione di Real-Time fMRI Neurofeedback Training

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control ...

Real-time Iontophoresis with Tetramethylammonium to Quantify Volume Fraction and Tortuosity of Brain Extracellular Space

This review describes the basic concepts and protocol to perform the real-time iontophoresis (RTI) method, the gold-standard to explore and quantify the extracellular space (ECS) of the living brain. The ECS surrounds all brain cells and contains both interstitial fluid and extracellular matrix. The transport of many substances required for brain activity, including neurotransmitters, hormones, and nutrients, occurs by diffusion through the ECS. Changes in the volume and geometry of this space occur during normal brain processes, like sleep, and pathological conditions, like ischemia. However, the structure and regulation of brain ECS, particularly in diseased states, remains largely unexplored. The RTI method measures two physical parameters of living brain: volume fraction and tortuosity. Volume fraction is the proportion of tissue volume occupied by ECS. Tortuosity is a measure of the relative hindrance a substance encounters when diffusing through a brain region as compared to a medium with no obstructions. In RTI, an inert molecule is pulsed from a source microelectrode into the brain ECS. As molecules diffuse away from this source, the changing concentration of the ion is measured over time using an ion-selective microelectrode positioned roughly 100 &#181;m away. From the resulting diffusion curve, both volume fraction and tortuosity can be calculated. This technique has been used in brain slices from multiple species (including humans) and in vivo to study acute and chronic changes to ECS. Unlike other methods, RTI can be used to examine both reversible and irreversible changes to the brain ECS in real time.

This protocol describes real-time iontophoresis, a method that measures physical parameters of the extracellular space (ECS) of living brains. The diffusion of an inert molecule released into the ECS is used to calculate the ECS volume fraction and tortuosity. It is ideal for studying acute reversible changes to brain ECS.

Iontoforesi in tempo reale con tetrametilammonio per quantificare la frazione del volume e la tortuosità dello spazio extracellulare del cervello

This review describes the basic concepts and protocol to perform the real-time iontophoresis (RTI) method, the gold-standard to explore and quantify the ...

Live-cell Measurement of Odorant Receptor Activation Using a Real-time cAMP Assay

The enormous sizes of the mammalian odorant receptor (OR) families present difficulties to find their cognate ligands among numerous volatile chemicals. To efficiently and accurately deorphanize ORs, we combine the use of a heterologous cell line to express mammalian ORs and a genetically modified biosensor plasmid to measure cAMP production downstream of OR activation in real time. This assay can be used to screen odorants against ORs and vice versa. Positive odorant-receptor interactions from the screens can be subsequently confirmed by testing against various odor concentrations, generating concentration-response curves. Here we used this method to perform a high-throughput screening of an odorous compound against a human OR library expressed in Hana3A cells and confirmed that the positively-responding receptor is the cognate receptor for the compound of interest. We found this high-throughput detection method to be efficient and reliable in assessing OR activation and our data provide an example of its potential use in OR functional studies.

Characterizing the function of odorant receptors serves an indispensable part in the deorphanization process. We describe a method to measure the activation of odorant receptors in real time using a cAMP assay.

Vivere-cella misura di Odorant recettore attivazione mediante un'analisi di campo in tempo reale

The enormous sizes of the mammalian odorant receptor (OR) families present difficulties to find their cognate ligands among numerous volatile chemicals. ...