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YNIMG-09254; No. of pages: 10; 4C: NeuroImage xxx (2012) xxx–xxx Contents lists available at SciVerse ScienceDirect NeuroImage journal homepage: www.elsevier.com/locate/ynimg 1 Review Q1 4 Matthew Colonnese a, b, c,⁎, Rustem Khazipov a, b, d O a INSERM, U29, INMED, Marseille 13009, France Aix Marseille Université, Faculté des Sciences, Marseille, F-13000, France Department of Pharmacology and Physiology, Institute for Neuroscience, George Washington University, Washington DC 20037, USA d Kazan Federal University, Kazan, Russia b c R O 5 6 Q2 7 8 F Q3 3 Spontaneous activity in developing sensory circuits: Implications for resting state fMRI 2 9 i n f o a b s t r a c t P a r t i c l e Article history: Accepted 13 February 2012 Available online xxxx D The immature brain spontaneously expresses unique patterns of electrical activity that are believed to contribute to the development of neuronal networks. Certain electrographic features of this activity, particularly modulation on an infraslow time scale, resemble activity patterns observed in the mature brain at ‘rest’, loosely defined as the absence of an investigator imposed task. However, it is not clear whether the immature activity patterns observed at rest are precursors of the spontaneous neuronal activity that forms resting state networks in the adult. Here, we review recent studies that have explored the generative mechanisms of resting state activity during development in the primary sensory systems of premature human neonates and neonatal rodents. The remarkable hypothesis suggested by this work is that while resting state activity during the pre- and possibly near-term period can bear superficial resemblance to adult activity it is fundamentally different in terms of function and origin. During early development spontaneous thalamocortical activity in primary sensory regions is determined largely by transitory generators in the sensory periphery. This is in contrast to the adult, where spontaneous activity generated within thalamocortex, particularly by corticocortical connections, dominates. We therefore suggest a conservative interpretation of developmental mapping studies which are based on indirect measurement of activity (e.g. fMRI), or on the partitioning of EEG frequency using bands derived from adult studies. The generative mechanisms for brain activity at early ages are likely different from those of adults, and may play very different roles; for example in circuit formation as opposed to attention. © 2012 Published by Elsevier Inc. T E Keywords: Development Resting state Preterm Neonatal Spindle burst Spontaneous activity R E C 10 11 12 13 15 14 16 17 18 19 20 21 22 23 N C O 48 49 50 51 52 53 54 55 56 57 58 Q1459 60 Contents Resting state activity in neonates and adults . . . . . . . . . . . Discontinuous temporal organization of early activity . . . . . . . Unique activity patterns in preterm infants . . . . . . . . . . . . Appearance . . . . . . . . . . . . . . . . . . . . . . . . Modulation . . . . . . . . . . . . . . . . . . . . . . . . Developmental separation . . . . . . . . . . . . . . . . . Generative mechanisms . . . . . . . . . . . . . . . . . . Peripheral dominance of resting activity during early development Development of intrinsic thalamocortical activities . . . . . . . . Early cortical function and implications for resting state fMRI . . . Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . Uncited references . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . U 44 47 46 43 42 R 45 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 ⁎ Corresponding author at: INSERM, U29, INMED, Marseille 13009, France. E-mail address: [email protected] (M. Colonnese). 1053-8119/$ – see front matter © 2012 Published by Elsevier Inc. doi:10.1016/j.neuroimage.2012.02.046 Please cite this article as: Colonnese, M., Khazipov, R., Spontaneous activity in developing sensory circuits: Implications for resting state fMRI, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.02.046 0 0 0 0 0 0 0 0 0 0 0 0 0 M. Colonnese, R. Khazipov / NeuroImage xxx (2012) xxx–xxx 80 81 Q4 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 Q5 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 C F O 78 79 E 76 77 R 74 75 R 72 73 O 70 71 C 68 69 N 67 U 65 66 R O The cerebral cortex is never quiet (Fox and Raichle, 2007). Even primary sensory regions are consistently active in the absence of sensory input, including during states of unconsciousness such as non-REM sleep and anesthesia (Bianciardi et al., 2009; Hasenstaub et al., 2007; Leopold and Logothetis, 2003). Neurophysiologists have a tradition of labeling such non-task related activity ‘spontaneous’ or even ‘background’, while similar fluctuations have been categorized as ‘resting state’ by the human fMRI community. The origins and functions of this activity are a mystery, but are thought to include replay of sensory information in cortical circuits during sleep and attention, visual learning and ongoing cogitation during waking (Berkes et al., 2011; Haider and McCormick, 2009; Ji and Wilson, 2007). And, resting state activity fluctuations have themselves become a powerful tool in defining the functional connections between cortical and sub-cortical regions. Measuring the co-modulation of activity in multiple regions with fMRI or EEG during ‘rest’, i.e. in the absence of directed goals, has revealed multiple independent networks linked to sensory processing, movement, and higher functions such as attention. Perhaps most striking is the discovery of ‘default-mode’ networks inversely correlated with directed behavior and perceptual tasks (Raichle and Snyder, 2007). Understanding when these networks form is an important goal, because their disruption during development is predicted to be causally linked to the onset of neurological disorders. The question has two components: when do the anatomical connections that link brain regions together form, and when are the network properties sufficiently mature to allow for mature function? This latter question is critically important because network properties change constantly during development. Animal models have shown that during the initial formation of neural circuits a number of transitory properties exist to generate spontaneous activity in the local circuits, despite a poverty of local interconnectivity and adult functional connectivity (Blankenship and Feller, 2010). For example, isolated slices of rodent cortex and hippocampus exhibit multiple stages of network activity during the first postnatal weeks (Allene et al., 2008; Moody and Bosma, 2005). In addition, both the retina and cochlea generate transitory activity bursts that synchronize firing in local neuronal populations on an infraslow timescale (Demas et al., 2003; Tritsch et al., 2007; Wong, 1999). This process has been studied extensively in the visual system, where genetic and pharmacological manipulation of spontaneous retinal activity has been shown to be critical for visual map formation in central visual structures including the cortex (Huberman et al., 2008). Sensorimotor systems also engage in a similar process, but instead of generating activity spontaneously in the sense organ, spontaneous bursts of activity in the spinal cord cause myclonic jerks in the various muscles, resulting in ‘spontaneous’ sensory input that is carried to the cortex (Khazipov et al., 2004; Kreider and Blumberg, 2000). In short, data from animal models predict significant ‘resting-state’ activity during early developmental time periods equivalent to the fetal stage in humans. This review examines the evidence that this activity is not equivalent to resting-state modulations in adults, either in terms of generative mechanisms or function. This is important because understanding the development of resting state networks requires not just a demonstration of co-modulation of various brain regions, but also an understanding of the generative mechanisms of these modulations, which are likely to change dramatically during development. Humans are born in the midst of a surge of cortical synaptogenesis that will continue throughout the first year after birth (Huttenlocher and Dabholkar, 1997). This synaptic burst is coincident with a rapid increase in the continuity of cortical activity and a maturation of activity patterns, as many EEG grapho-elements disappear in the first couple of months, and adult patterns of activity including sleep spindles, delta waves and strong gamma-band modulations emerge within the first year (Andre et al., 2010; Curzi-Dascalova, 1977; Ellingson and Peters, 1980). As might be expected, these rapid changes in synaptic density, P 63 64 connectivity and electrical activity are accompanied by rearrangements in resting state cortical networks as assayed by fMRI. Resting state networks, organized locally around hubs in sensory and motor cortex, have been demonstrated in term infants (Fransson et al., 2011), as well as preterm infants (Doria et al., 2010; Smyser et al., 2010). By contrast, resting state networks involving distant regions, particularly frontal and associative regions such as the default state and attention networks, develop later than local networks. One study identified the adult complement of resting state networks by term (Doria et al., 2010), while other studies observed an incomplete default state network at term (Fransson et al., 2007, 2011; Gao et al., 2009; Smyser et al., 2010). These data suggest that some important property of sensory networks forms in utero, while the development of associational networks is likely part of the rapid synaptogenesis and maturation of cortical activity patterns observed postnatally. Thus a close examination of activity in primary sensory cortex during the fetal period will be necessary to determine to what extent the resting state fMRI detects adult-like functional networks or immature activity patterns, and what this would mean for the processing capacity of the infant brain. Determining the patterns of activity expressed in the fetal brain is a challenging task. Due to the technical difficulty of performing EEG and MEG through the uterine wall, the main approach consists of scalp EEG recordings from premature neonates. One should question whether cortical activity in premature neonates is the same as in the fetus. Certainly, the extra-uterine environment is very different, and the function of many systems (cardiovascular, respiratory, and digestive) undergo significant development after birth regardless of gestational age. However, the major characteristics of preterm EEG, such as those used for clinical monitoring, are primarily determined by gestational, and not postnatal, age (Andre et al., 2010); the length of time ex utero does not exert a large effect on the gross patterns of brain activity maturation. Moreover, the temporal organization of spontaneous activity as shown by fetal MEG studies is remarkably consistent with data obtained from gestational age matched premature neonates (Eswaran et al., 2004, 2007). A number of caveats apply, however. The development of a number of neurological markers is accelerated by preterm birth, while others are delayed or unaffected (Ellingson and Peters, 1980; Smyser et al., 2010) and these can vary depending on the extrauterine experience (Guzzetta et al., 2009). Furthermore, the fetus, under the influence of maternal hormones and lack of stimuli, is maintained in a sleep-promoting environment. Therefore, scalp EEG from healthy premature neonates should be considered as an approximation of fetal brain activity, and hopefully further technical developments will provide further verification for this model. A mechanistic understanding of resting state network development requires appropriate animal models. Pioneering studies describing the phenomenology of EEG development were performed in fetal and neonatal pigs, sheep, guinea pigs, cats, rabbits, rats and dogs (Bergstrom et al., 1962; Bernhard et al., 1959; Charles and Fuller, 1956; Crain, 1952; Deza and Eidelberg, 1967; Fox, 1967; Jouvet-Mounier et al., 1970; Marty and Thomas, 1963; Pampiglione, 1977; Petersen et al., 1964; Rose and Ellingson, 1968; Scherrer and Oeconomos, 1954; Tuge et al., 1960; Yoshii and Tsukiyama, 1951). These studies led to conclusion that EEG pattern maturation is similar between species and determined more by relative maturation than by time of birth. In all species, at first appearance EEG activity consists of bursts of activity lasting around 1 s with intervening periods of electrical silence that can last up to 10 s. Interhemispheric synchrony is lacking. No changes associated with the sleep-wake cycle can be detected. As described by Ellingson (1970) EEG patterns then undergo a series of universal developmental trends in the postnatal EEG: (1) low frequency activity becomes less abundant with increasing age; (2) frequency of rhythmic (alpha- or alpha-like) activity during wakefulness increases with age; (3) interhemispheric synchrony improves with age; (4) overall amplitude increases during infancy and then declines somewhat to maturity; and (5) complexity of sleep patterns increases with age (Ellingson, 1970). D Resting state activity in neonates and adults T 62 E 2 Please cite this article as: Colonnese, M., Khazipov, R., Spontaneous activity in developing sensory circuits: Implications for resting state fMRI, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.02.046 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 M. Colonnese, R. Khazipov / NeuroImage xxx (2012) xxx–xxx 214 215 216 217 218 219 220 Q6 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 246 247 248 249 250 251 252 253 254 255 256 C 212 213 E 316 We have considered the differences in the nature of the infraslow oscillations observed at rest during early development and in adults, namely the alternation between network silence and activity that characterizes the immature brain, as opposed to waxing and waning of 317 F Unique activity patterns in preterm infants O 210 211 R 208 209 R 206 207 N C O 204 205 U 202 203 R O The adult brain is constantly active, though the patterns and amount of this activity are modulated differentially between brain networks by a number of factors including vigilance state, mental task and sensory input (Steriade and McCarley, 2005). The basis of functional connectivity mapping appears to be the waxing and waning of ongoing activity on an ‘infraslow’ timescale (0.01–0.2 Hz), rather than the cessation and reinduction of activity itself (Baria et al., 2011; Jann et al., 2010; Laufs et al., 2003; Sadaghiani et al., 2010; Vincent et al., 2007; Zuo et al., 2010). Since the first recordings of human neonates using scalp electrographic recordings by Dreyfus-Brisac and Monod (1965) and DreyfusBrisac et al., (1956), a pronounced infraslow modulation of activity in preterm infants has also been noted. However, close examination of this oscillation reveals that it is of a fundamentally different character 200 201 P 244 245 199 257 258 D Discontinuous temporal organization of early activity 197 198 from adult: it arises not from the modulation of ongoing activity or brain states as in adults, but from alternating periods of complete network silence and activity. This temporal organization in preterms was named tracé discontinu, and is most prominent during the second half of gestation, particularly during quiet sleep. During tracé discontinu, the cortical EEG is organized in intermittent bursts separated by periods of isoelectric EEG that could last for tens of seconds (Dreyfus-Brisac and Larroche, 1971). With maturation, the flat periods between bursts become progressively shorter, first during active (pre-REM) sleep and then during quiet sleep. By 30 weeks post-conception periods of tracé discontinu become interleaved with periods of low-voltage activity (indicative of continuous activity) observed between the bursts. These periods, so called tracé alternant, become more common, resulting in longer periods of continuous activity. Continuous cortical activity is observed from 1 to 2 months after birth (Andre et al., 2010). Thus infraslow modulation in preterm infants results from the apparent cessation of activity, while in adults it results from more modest increases and decreases in ongoing activity. Recent rodent studies have examined whether these isoelectric ‘silent’ periods result from true network silence, or from asynchronous neuronal activity that poorly registers at the scalp. Extracellular recordings of multiple unit activity in somatosensory and visual cortex of rats showed that neurons fire virtually no action potentials during these isoelectric EEG epochs (Fig. 1). In agreement with this result, patch-clamp recordings revealed that neurons stay relaxed at their resting membrane potential and receive very few synaptic inputs during the isoelectric EEG periods (Colonnese and Khazipov, 2010; Khazipov et al., 2004; Rochefort et al., 2009). This means that isoelectric EEG epochs reflect a synchronous neuronal silence which is never observed in a healthy adult. The closest the adult cortex comes to such collective silence is during so called ‘down states’, observed during unconsciousness brought on by slowwave sleep or anesthesia. In adults, natural down states observed during sleep last only on the order of hundreds of milliseconds (Steriade and McCarley, 2005), whereas they can last for tens of seconds in neonatal rats and preterm humans. Oscillations between periods of neuronal depolarization associated with synaptic barrages (called UP-states) and the DOWN state generates slow waves on EEG (Steriade et al., 1993), giving name to the state of sleep when they are most commonly observed. In adults this so-called ‘slow’ oscillation between up and down states is too rapid to account for resting state connectivity (though the number or power of such transitions over a 10 s period could in theory (Jann et al., 2010)). In contrast, in preterm infants and neonatal rats a singular burst of activity against a background of network silence could conceivably contribute to infraslow modulations and resting state connectivity. Why do immature networks produce such long-lasting periods of network silence? Intracellular studies in adults indicate that down states result when the level of mutual excitation in the cortical network falls below the critical level necessary to maintain the UP-state, allowing neurons to return to their resting membrane potential (Contreras et al., 1996; Sanchez-Vives and McCormick, 2000; Shu et al., 2003). Immature networks, which are much less densely connected, likely require much greater network activation before generating an up-state, and thus spend much longer periods of time in network silence. Combined with the evidence outlined below that the majority of activity that does occur in immature sensory cortex is related to thalamic input, it appears that the default state of cortical networks during the fetal period is network silence, rather than the continuous ‘spontaneous’ activity characteristic of healthy mature cortex. E 243 195 196 T 241 242 Pampiglione (1977) also pointed out that “from the evolution of E.E.G. features it seems that the underlying mechanisms during maturation do not evolve according to a uniformly continuous process but proceed, like the main E.E.G. features, in irregular steps, with plateaus lasting days or weeks, followed by a more rapid change over a period of a very few days before reaching the next plateau which then may last several weeks or months before changing again into a final adult phase. The evolution process therefore seems to be much more like a series of changes of uneven duration rather than a smooth curve.” To move beyond these phenomenological observations and construct a mechanistic understanding of the early activity patterns and their physiological roles in brain development, recent efforts have focused on neonatal rodents, and to a lesser extent ferrets, as a model system for human EEG development. In rodents invasive recordings of brain activity, including intra-cellular recordings, can be combined with pharmacological and genetic manipulations to identify network mechanisms of early activity generation (Khazipov and Luhmann, 2006). Rats and mice are altricial; that is, they are born in an immature state. Although it is difficult to provide exact comparisons between human and rodents, the degree of rat cortical development on the day of birth (P0) can be roughly compared to the stage of human cortex at mid-gestation (Clancy et al., 2001). Multi-factor estimates based primarily on neurogenetic times (Clancy et al., 2007), and direct comparisons of neural activity patterns in humans and rats (Colonnese et al., 2010) disagree on the rat equivalent of term in humans. This is in part because there is likely no single age equivalent useful for all brain regions, as even primates exhibit profound heterogeneity between cortical and sub-cortical developmental times (Clancy et al., 2000). For hippocampus, term in human was suggested to correspond to postnatal day P5–7 in the rat (Avishai-Eliner et al., 2002). For cortex however, both the timing of the surge in synaptogenesis in primary sensory regions, and changes in neural activity appear to develop on a time course that diverges from other developmental markers. Such heterochrony may have implications for resting state network development, as networks may become ‘functional’ at different developmental points in different species. For visual cortex, in terms of function, we suggest that term in humans roughly corresponds to postnatal day P12-14 (roughly the time of eye opening) in the rat or mouse. The invasive animal studies completed so far suggest that in primary sensory systems neuronal activity during the preterm period is categorically different from adult activity, even when there are superficial similarities in terms of temporal modulation and frequencies. In particular, while adult resting activity appears generated by the dense corticocortical interconnectivity modulated by the neuromodulatory systems (Destexhe et al., 2003; Haider and McCormick, 2009), early sensory networks are driven largely by spontaneous activity in the periphery, interacting with thalamocortical network properties unique to the time period. We will review this evidence below, focusing on two features: the lack of continuous cortical–cortical activity, which causes a discontinuous pattern of resting activity, and the generation of unique activity patterns in cortex during early development. 193 194 3 Please cite this article as: Colonnese, M., Khazipov, R., Spontaneous activity in developing sensory circuits: Implications for resting state fMRI, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.02.046 259 260 Q7 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 Q8 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 318 319 320 4 M. Colonnese, R. Khazipov / NeuroImage xxx (2012) xxx–xxx P6 ∗ ∗ ∗ ∗ Quiet Inter-SAT ∗ unique rhythmic, oscillations and intermittent, fast events that are expressed during restricted ages. These immature patterns are notable for their poor modulation by specific behaviors or vigilance states. Because they are clearly different in structure and occurrence from adult patterns, these events have been given unique names, which include temporal theta bursts, encoches frontales, and delta brush (Andre et al., 2010; Mizrahi et al., 2003). The earliest activity, detected at 24–25 post-menstrual weeks (the earliest age that reliable recordings are made), appears in clinical EEG as intermittent ‘delta’ waves, either smooth or with more rapid rhythms superimposed. By the seventh month, these slow oscillations are reliably intermixed with rapid rhythms, and are abundant in central, temporal and occipital regions, fading first in central regions and lastly on occipital electrodes around term. Our understanding of the organization and development of early activity patterns is still evolving. Recent observations using direct-current (DC) recordings to reveal activity modulation on long timescales show that delta brushes and other rapid oscillations often occur sequentially, contained within a negative potential of unusually large amplitude (up to 800 μV; (Vanhatalo et al., 2002)). During standard EEG such ‘DC shifts’ are not observed due to the use of conventional high-pass (>0.5–1 Hz) filters. These studies suggest that the subdivision of various oscillations into discrete events such as individual delta brushes should be questioned, and that they would be better considered a singular class of unique developmental events termed ‘spontaneous activity transients’ (SATs), which consist of slow and infraslow waves that group rapid oscillations of various frequencies (Vanhatalo and Kaila, 2006). Evidence from animal studies, reviewed below, supports this classification. Wide Band EEG 500μV 40 s 200 μV 2s P10 Bursting Inter-SAT ∗ ∗ ∗ 500μV O F 40 s 200 μV R O 1s Constant retinal Activity No retinal activity ∗ Continuous Inter-SAT ∗ ∗ ∗ D P13 P 500μV 40 s E 500μV Modulation T 40 s 321 C O R R E C Fig. 1. Development of resting state activity in the rat visual cortex. Spontaneous depth EEG recorded from layer 4 from three different ages of rat, roughly equivalent to midgestation (P6), third trimester (P10) and term (P13) in human. Direct current recordings of the field potential reveal infraslow activity dynamics. During the first postnatal week all activity consists of recurrent infraslow waves that contain rapid (alpha-beta) oscillations and delta waves, together called a delta brush or spindle burst (P6). These events are often linked together to form spontaneous activity transients (SATs). Between SATs, cortical networks are largely silent (‘inter-SAT’). SATs continue during the second postnatal week (P10), but short bursts of activity are now present between SATs. Elimination of retinal activity eliminates SATs, but short activity bursts remain (P10 lower left). Conversely, pharmacological initiation of constant retinal activity causes constant SAT activity in cortex (P10 lower right). Thus SATs (and therefore 90% of spiking) are not generated spontaneously in cortex but driven by the retina, while the short activity bursts result from true intrinsic spontaneous activity in thalamocortical circuits. Continuous inter-SAT activity begins at the end of the second postnatal week (P13), and the size of the now infrequent SATs is reduced. Figure modified from Colonnese and Khazipov (2010). 330 Appearance 331 332 In adults, cortical activity patterns are notable for their diversity and modulation by vigilance state. Some examples are the production of delta waves of increasing amplitude as the depth of non-REM sleep increases, spindle oscillations during light sleep, alpha oscillations during eye closure, and gamma-band oscillations during sensory vigilance (Buzsáki, 2006). Homologues of none of these patterns have been identified in preterm infants. Preterm activity is instead dominated by a few 324 325 326 327 333 334 335 336 337 U 322 323 N 328 329 continuous activity in the adult. The next question is whether the activity bursts that interrupt network silences are fragments of the corticocortical activity that composes the adult resting state, or are of a qualitatively different sort. Along with Pampiglione's ideas quoted above, a number of facts argue for the latter. In particular (1) the appearance of the activity is different, (2) the modulation of the cortical activities by sleep, ‘rest’, and vigilance is poorly developed, (3) adult resting activity does not emerge from immature bursts, and (4) studies in sensory cortex show that the generative mechanisms are different. 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 Cortical activity in preterm infants is weakly modulated by vigilance state. Until approximately 32 weeks post-conception both quiet and active sleep (thought to be equivalent to non-REM and REM sleep respectively) are poorly differentiated in EEG and display prominent delta waves, brushes and SATs as described above. By 32 weeks delta activity becomes more restricted to quiet sleep and active sleep becomes defined by low amplitude rapid activity, yet as much as 30% of sleep at these ages is characterized as indeterminate, or containing characteristics of each (Andre et al., 2010). This developmental pattern is matched in neonatal rats, which display little modulation of cortical activity. Cortical EEG in rats starts to exhibit some sleep/awake state-dependent differentiation of delta activity beginning approximately at P10–11, becoming robust at the end of the second postnatal week (Frank and Heller, 1997; Gramsbergen, 1976; Jouvet-Mounier et al., 1970; Seelke and Blumberg, 2008). 368 369 Developmental separation 383 Simple difference in appearance between the immature and adult EEG is not sufficient evidence to declare them to be independent phenomena. Functionally similar activity patterns could appear superficially different as a result of changing circuitry or even current source relationships. In this case we expect that early activity patterns, if followed through development, would transform into adult patterns. However, in every case examined so far the opposite occurs. The first studies to identify delta brushes in preterm infants noted their structural similarity to sleep spindles (Dreyfus-Brisac, 1962; Ellingson, 1958; Watanabe and Iwase, 1972) However, it became rapidly apparent that delta brushes do not develop into sleep spindles, because sleep spindles appear a full two months after delta brushes have ceased (Ellingson, 1982). In keeping with these clinical findings, sleep spindles in thalamic slices from ferrets and mice also appear after the disappearance of delta brushes (McCormick et al., 1995; Warren and Jones, 1997). A second example is gamma oscillations, which have been proposed to be a 384 Please cite this article as: Colonnese, M., Khazipov, R., Spontaneous activity in developing sensory circuits: Implications for resting state fMRI, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.02.046 370 371 372 373 374 375 376 377 378 379 380 381 382 385 386 387 388 389 390 391 392 Q9 Q10 393 394 395 Q11 396 397 398 399 M. Colonnese, R. Khazipov / NeuroImage xxx (2012) xxx–xxx 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 C 424 425 E 417 418 R F 415 416 R 413 414 Peripheral dominance of resting activity during early development N C O 411 412 Investigators have used the somatosensory and visual cortex of rats and ferrets to ask the following question: Is resting activity in neonates driven by cortico-cortical connections as it is in adults, or is it driven by other mechanisms such as spontaneous activity in the sense organ? These studies have revealed that the large majority of cortical activity during the period of discontinuity results from input generated spontaneously at the sensory periphery, not within cortex. Examination of electrographic signatures of sensory stimulation in both neonatal rats and human preterm infants has provided evidence that a similar peripheral generation of resting activity may occur in the neonates and fetuses. This conserved peripheral dominance was first identified in rat primary somatosensory cortex where spontaneous muscle twitches are associated with local, transient bursts of rhythmic, 5–25 Hz activity, originally termed ‘spindle burst’(Khazipov et al., 2004)(Fig. 2A). Use of wide-band recording techniques revealed a very large (up to 1 mV) negative slow potential associated with rapid oscillations (MarcanoReik and Blumberg, 2008; Minlebaev et al., 2009), thus electrographically resembling delta brushes in human preterms. This was confirmed in a follow up study in preterm infants that showed delta brushes were triggered in the somatotopically appropriate region at GW28–32 U 409 410 O The final evidence that early and late resting activities are different is that they have fundamentally different pacemakers and generators. One clear example in cortex is gamma oscillations. In young rodents gamma oscillations take the form of EGOs, and are primarily determined by gamma-rhythmic excitatory input from thalamus. In the adult, gamma oscillations depend on perisomatic inhibition within the cortex. (Minlebaev et al., 2011). This difference in generation leads to significant differences in the physiological roles of EGOs and adult gamma oscillations. Whereas EGOs enable the vertical synchronization of the topographically aligned thalamic and cortical neurons necessary for the development of thalamocortical units, adult gamma oscillations synchronize larger areas of the cortex horizontally. A detailed understanding of the thalamic and cortical pacemakers of other early resting activity patterns is not complete. However, as reviewed in the next section, it is clear that the production of the great majority of activity in the early sensory cortex is dependent on external drive of thalamus; a fact that stands in contrast to adult resting activity. 407 408 R O 422 423 406 P Generative mechanisms 404 405 (Fig. 2B) (Milh et al., 2007; see also Hrbek et al. (1973) for earlier demonstration of similar phenomenon). Thus in both species direct stimulation of the same body regions induces delta brushes in somatic cortex, suggesting that it is the sensory feedback produced by the twitch which triggers delta brushes. In rats spindle bursts do persist after sensory deafferentation (e.g., spinal cord transection), although at a much reduced frequency (Khazipov et al., 2004). These results suggest that some component of spindle bursts is endogenous to the thalamocortical circuit. However, under normal, intact circumstances, they are controlled by the external stimuli brought about by the thalamocortical afferents that trigger these oscillations in the somatosensory cortex in a somatotopic manner. Spindle bursts are also the dominant pattern in early postnatal rat visual cortex (Fig. 1). However, spindle bursts in visual cortex are longer and less frequent than those in somatosensory cortex. This difference is due largely to the influence of the retina, not differences intrinsic to the cortical region. Following enucleation, visual cortex strongly resembles somatosensory cortex after spinal cord transections, producing shortduration network bursts with long inter-burst periods (Colonnese and Khazipov, 2010; Hanganu et al., 2006; Khazipov et al., 2004). Retinal involvement in spindle bursts is also indicated by evoked responses. Spindle bursts can be evoked by visual stimulation in preterm infants and neonatal rats once photoreceptor mediated light responses occur in the retina (Figs. 2C and D) (Colonnese et al., 2010; Ellingson, 1960; Hrbek and Mares, 1964), or in rats by electrical stimulation of the eye before this point (Hanganu et al., 2006). The importance of visual induction of human delta brushes (the homolog of spindle bursts) under normal circumstances is unknown, but is likely to be minimal because the fetus is relatively visually isolated and spindle occurrence does not depend on the presence of fluctuations of environmental illumination or movement that might change luminance on the retina. Furthermore, in rats, the retina is insensitive to light during the first postnatal week, while spindle bursts are prevalent. Rather than ambient illumination, spontaneous retinal activity, which propagates as wave fronts and synchronizes retinal activity within local domains (Wong, 1999) provides the primary drive for spindle bursts, at least in rats. A role for these retinal waves in driving visual cortex spindle bursts was demonstrated by simultaneous recordings from the retina and V1 cortex (Hanganu et al., 2006), which revealed a strong correlation between the occurrence of spindle bursts in visual cortex and spontaneous retinal waves. Furthermore, pharmacological manipulations to increase retinal wave generation increased spindle-burst activity (Colonnese and Khazipov, 2010; Hanganu et al., 2006). Perhaps most tellingly, the temporal structure of spindle bursts in visual cortex is not constant during development, but undergoes a profound change during the second postnatal week, as spindle bursts begin to occur in groups that together form long-lasting (5–10 s) events associated with large amplitude DC shifts, highly reminiscent of SATs observed in human preterm neonates. The occurrence of V1 SATs at this time is highly regular, repeating approximately every 60 s. This change exactly parallels changes in the structure of spontaneous retinal activity (Blankenship et al., 2009; Demas et al., 2003; Kerschensteiner and Wong, 2008). Multiunit recordings made from the cortex and thalamus of freely moving ferrets during the same developmental period revealed similar long-lasting macro-burst behavior eliminated by enucleation (Chiu and Weliky, 2001; Weliky and Katz, 1999). Thus the differences in the initiation, duration, and intra-burst structure of activity between visual and somatosensory cortex, as well as between visual cortex at different ages, appears to result from differences inherent in the sense organ input. In total, activity in immature cortex appears to have a two-tiered generative mechanism: short-duration inputs such as muscle twitches, light flashes, electrical stimulation, and perhaps even endogenous cortical activity in the absence of peripheral input, trigger spindle bursts/delta brushes. However, elongated activity such as retinal waves drives similarly elongated spindle bursts or even their agglomeration into SATs. D 421 402 403 T 419 420 mechanism for horizontal synchronization and large scale binding necessary for perception and thought in adults (Buzsáki, 2006). Traditionally thought to emerge relatively late in development, recent observations in the neonatal rats revealed robust local oscillations at gamma frequency (Minlebaev et al., 2011). However, despite a similar frequency and potential to be evoked by sensory stimuli as those of the adult, the early gamma oscillations (EGOs) are transiently expressed. They abruptly disappear at the end of the first postnatal week, while the earliest adult gamma oscillations cannot be observed until days later, thus arguing against their identity as the same class of activity. A final example is SATs, introduced above. SATs become elongated in duration but reduced in amplitude with gestational age (Colonnese and Khazipov, 2010; Tolonen et al., 2007), suggesting that the continuous activity of maturity may emerge due to elongated SATs becoming linked during development. However, close examination of activity using DC recordings in both humans and rats showed that continuous resting activity actually emerges from the quiet periods between SATs, and not from their elongation (Fig. 1). We are not aware of any evidence demonstrating transformation of an identified early activity pattern into a mature network activity. The activities of immaturity studied in detail so far are clearly temporally independent from adult activity. E 400 401 5 Please cite this article as: Colonnese, M., Khazipov, R., Spontaneous activity in developing sensory circuits: Implications for resting state fMRI, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.02.046 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 Q12 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 6 M. Colonnese, R. Khazipov / NeuroImage xxx (2012) xxx–xxx A P5Rat Somatosensory Cortex Hindlimb S1 EEG + + - - 0.1 mV 0.2 s Hindlimb S1 MUA 0.1 mV Hindlimb Movement 4s Right Hand Stimulation Somatosensory Cortex - F B GW 30 Twitch - evoked delta-brush + 100 µV T3 FP1 FP2 C3 Cz C4 O 0.5 s T4 Depth EEG + - * Sleep C + - T4 40 µV Evoked 200 ms delta-brush Electrode O2 + > 2Hz T3 O1 Cz 500 mV Evoked delta-brush 100 mV 500 ms 5s O R O1 O2 MUA EEG (0.05-40 Hz) R FP1 FP2 C3 Cz C4 FP2 C4 T4 O2 FP1 C3 + 400 µV E GW 30 Visual Cortex T light flash T3 Depth EEG D 400 µV 200 ms light flash D Awake Evoked delta-brush P P10Rat Visual Cortex E C R O O1 O2 + 528 529 530 531 532 533 534 535 536 537 538 539 540 U N C Fig. 2. Conserved drive of early network oscillations by sensory periphery. In the human and rat somatosensory and visual systems, spontaneous early network oscillations can also be reliably evoked in a topographically restricted manner by sensory input. A. Simultaneous recording in hindlimb S1 while monitoring hindlimb motion. Spontaneous delta brushes in rats are associated with spontaneous myclonic jerks, which precede the delta brush. Expanded time scale (right) shows rapid oscillations of delta brushes and associated unit activity following movements. Direct stimulation of the hind-paw also elicits delta brushes (not shown). B. Direct stimulation of the hand in a preterm infant produces delta brushes in contralateral central cortex (center panel). Expanded time scale (right) shows delta brush (negative is up) restricted to single electrode. C. Visual stimulation produces delta brushes in visual cortex. Responses to 6 light flashes in layer 4 of V1 from the same animal during different vigilance states (central traces). A spontaneous delta brush occurs before one of the stimulus trials (asterisk). Note the similarity of spontaneous and evoked patterns. Expanded time scale (right) shows field potential and evoked unit activity. D. Visual stimulation produces delta brushes in occipital electrodes of preterm infants (center panel). Expanded time scale (right) shows evoked potentials similar to the rodent visual response. Modified from Khazipov et al. (2004); Milh et al. (2007); and Colonnese et al. (2010). Recent studies suggest that regions outside of the primary sensory regions follow similar developmental patterns. Prefrontal cortex demonstrates alternating periods of silence and rapid oscillation that are driven by the hippocampus and become continuous around the same time as sensory cortex (Brockmann et al., 2011). Similar activity patterns have also been described in dysgranular and temporal cortex (Adelsberger et al., 2005; Seelke and Blumberg, 2010), though their generative mechanisms are still unclear. In summary, recent rodent work, partially confirmed in human preterm infants, shows that the resting state neural events (SATs/spindle bursts/delta brushes) which constitute the majority of early neural activity (>90% in rat visual cortex) have as their primary driver input from the peripheral sense organ (Fig. 3). In adults the proportion of resting activity contributed by sensory input to primary sensory cortex is likely to be small, as sensory input is specifically kept minimal during testing and ongoing activity in visual cortex is only minimally modulated by visual inputs (Fiser et al., 2004). 541 Development of intrinsic thalamocortical activities 545 If the basis of resting state activity modulations in sensory cortex during early development is spontaneous activation at the periphery, then they result from different functional circuits from those generating resting activity in the adult. The activity patterns most closely associated with resting state modulations in sensory cortex are delta waves (Jann et al., 2010; Lu et al., 2007), which result from spontaneous activation 546 Please cite this article as: Colonnese, M., Khazipov, R., Spontaneous activity in developing sensory circuits: Implications for resting state fMRI, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.02.046 542 543 544 547 548 549 550 551 M. Colonnese, R. Khazipov / NeuroImage xxx (2012) xxx–xxx Immature Pre-resting state 7 Adult Resting state Higher SC and other Ctx Higher VC and other Ctx Higher SC and other Ctx Visual Cortex Somatosensory Cortex Visual Cortex SC Thalamus Thalamus Thalamus Thalamus Retina (spontaneous waves) Somatic Receptors (spontaneous twitches) Retina F HigherVC and other Ctx O Somatic Receptors 564 565 566 567 568 569 570 Q13571 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 D in rodents (Gramsbergen, 1976). This rapid increase in spontaneous activity does not emerge simultaneously in entire cortex, but instead occurs first in somatosensory and then in visual cortex in both the rat and human. In both species it coincides with the elimination of delta brushes and spindle bursts in these areas (Andre et al., 2010). At least two developmental factors relevant to the generation of resting state connectivity are likely involved in the emergence of the activated cortical state: the development of arousal systems and intra-cortical connections. Isolating the forebrain from ascending neuromodulatory arousal inputs at P13–15 rats reverses the developmental increase in spontaneous cortical activity, reinstating the immature discontinuity (Colonnese et al., 2010). The mature activity state is re–instated by application of norepinephrine, a key initiator of the activated cortical state (Constantinople and Bruno, 2011). This is consistent with the critical role for noradrenergic systems for the development of sleep-wake transitions (Gall et al., 2009) and the maturation of cholinergic (Mechawar and Descarries, 2001; Robertson et al., 1985) and noradrenergic afferents and receptor distributions (Latsari et al., 2002; Venkatesan et al., 1996) around this time. However, arousal system activity alone is incapable of inducing a continuous active state in the immature cortex (Hanganu et al., 2007). Thus the acquisition of brainstem control of cortical rest states likely requires thalamocortical inputs as well. A prominent candidate is the strengthening of the long and short range intra-cortical connectivity, required for maintenance of the activated cortical state (Sanchez-Vives and McCormick, 2000; Steriade and McCarley, 2005; Timofeev et al., 2000). The network of horizontal connections between cortical columns emerges shortly before eye opening in cats and ferrets (Durack and Katz, 1996; Ruthazer and Stryker, 1996) independently of visual input (Callaway and Katz, 1990; Durack and Katz, 1996; Ruthazer and Stryker, 1996). In mice feedback connections to V1 are observed just before eye opening (Berezovskii et al., 2011). In humans, dense horizontal connections are also first observed at GW37 (Burkhalter et al., 1993). Emergence of the continuous mode of cortical activity thus likely results from a coincidence of two developmentally regulated factors: (i) maturation of the brainstem arousal input to thalamus and cortex, which provides tonic neuronal depolarization and (ii) formation of excitatory synaptic connections among local and distant cortical neurons, required for initiation and maintenance of the activated cortical state, and for resting state modulations. E T C 562 563 E 560 561 R 558 559 R 556 557 N C O 554 555 of thalamocortical circuits during sleep or periods of low vigilance (Steriade and McCarley, 2005). Not surprisingly, the development of delta activity induced by non-REM sleep parallels the loss of early activity patterns in rats and humans (Andre et al., 2010; Gramsbergen, 1976; Seelke and Blumberg, 2008). Thus, the question of when adult resting state develops a question of when intrinsic activity generated within cortical circuits develops (Fig. 3). In adults, intrinsically generated activity in thalamocortical circuits is characterized by the presence of activated cortical states (aka desynchronized- or up-state) (Destexhe et al., 2003, 2007). This intrinsic activity is generated via recurrent cortical connectivity, which drives balanced excitatory and inhibitory input to neurons, and is regulated by neuromodulatory input, particularly acetylcholine and norephinephrine (Steriade and McCarley, 2005). The active state occurs during waking, REM sleep and even slow wave sleep, when it is broken up by very short periods of network silence, or down states. Intracellular recordings show little difference between continuous cortical activity during awake, REM sleep and UP-states during slow wave sleep. As described in Sections Discontinuous temporal organization of early activity, Unique activity patterns in preterm infants, and Peripheral dominance of resting activity during early development, the current evidence suggests that the activated cortical state is not present in neonatal rats and young premature neonates, as the majority of activity is driven directly by the periphery, not intra-cortical circuits. Furthermore, the early sensory driven SAT and delta brushes do not develop into activated cortical states. Instead it appears that primitive active states, which resemble those observed in isolated cortical slabs, develop independently during the second postnatal week in the rat, which show increased delta activity during quiet sleep (Seelke and Blumberg, 2008), calcium bursts under anesthesia (Golshani et al., 2009; Rochefort et al., 2009) and short 200–500 ms bursts of cortical activity that are insensitive to eye-removal (Colonnese and Khazipov, 2010). This may correspond to the increase in delta activity observed during quiet sleep during third trimester preterm infants, or the tracé alternant pattern which becomes increasingly prevalent during active sleep toward the end of gestation. Interestingly, rat cortical slices begin to produce spontaneous synaptic activity around the same time (Allene et al., 2008; Rheims et al., 2008), demonstrating a basic change in the ability of isolated cortex to generate activity. In visual cortex these early delta/slow waves become rapidly more frequent around eye opening (Colonnese and Khazipov, 2010; Colonnese et al., 2010; Rochefort et al., 2009), coinciding with the emergence of clearly differentiable EEG sleep states U 552 553 P R O Fig. 3. Changing drive of resting state activity during development of sensory systems. Diagram shows hypothesized circuits influencing cortical activity during preterm and adult resting states in primary sensory systems. During early development in the absence of visual input spontaneous waves cause the retina to be synchronously active. Spontaneous jerks serve a similar purpose in the somatosensory system. During this period spontaneous intra-cortical activity (both local and feedback) is minimal. The majority of resting activity thus results from the transmission of spontaneous retinal activity. This is in contrast to adults, whose resting activity is largely independent of retinal or somatic input and is instead generated via recurrent interactions between and within cortex and thalamus. Because of these substantial differences in drive and function between the immature and adult systems, we propose that the preterm infant and neonatal rat be considered to be in a pre-resting state. Please cite this article as: Colonnese, M., Khazipov, R., Spontaneous activity in developing sensory circuits: Implications for resting state fMRI, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.02.046 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 C 660 661 E 658 659 R 656 657 R 654 655 O 652 653 C 650 651 N 648 649 U 646 647 Summary 744 Electrophysiological evidence in human preterm infants and animal models reviewed here is consistent with the hypothesis that early circuit development is characterized by a unique state of cortical network dynamics, in which adult-like thalamocortical resting state activity is minimal, allowing inputs from the periphery to be amplified by cortical oscillatory bursts (Fig. 3). This period appears tightly regulated to coincide with the sensory deprivation experienced in the womb (or maintained by eye or ear canal closure in rodents), and to end when active sensory processing is initiated. It is only when this early period ends that many of the gross characteristics of adult resting state activity can be discerned, including clear regulation of cortical EEG by sleep state and the reduction and eventual elimination of SATs in counterpoint to continuous activity (Gramsbergen, 1976; Seelke and Blumberg, 2008; Vanhatalo et al., 2005), and perhaps not surprisingly, elements of complex cortico-cortical resting state networks (Doria et al., 2010; Fransson et al., 2011; Gao et al., 2009). Of course, the development of cortical activity is by no means complete by this point; in essence it has only just 745 746 F We have presented evidence that ‘resting state’ modulations of activity in sensory cortex during early ages are not the same infraslow modulation present in the adult. This is supported by two characteristics of neocortical activity during the fetal and early neonatal period (1) unique early network activities driven by the sensory periphery and (2) the lack of intrinsic activity generated in thalamocortical circuits. The young resting state activities represent a unique network state that is limited to early development. We propose this state is optimized to drive synaptic plasticity in thalamocortical networks in response to spontaneous activity generated in the sense organs. To support this function, ‘resting’ activity at these ages largely reflects activity generated in the sensory periphery, despite its independence from changes in the external environment. As a result, cortical activity at these early ages is poorly modulated by vigilance state or the environment; in effect the cortex is always ‘at rest’ in the sense that there are no task or attention based modulations of the cortex. Unlike adults, however, rest is a singular condition, at least during early development. A key implication of this hypothesis for imaging studies is that while powerful activity modulations are present during early development, they are incapable of conveying graded and high-frequency information transfer as in adults. Two examples support this assertion. Using two-photon calcium imaging of the superficial layers of visual cortex in anesthetized mice Rochefort et al. (2009) and Golshani et al. (2009) traced the development of cortical slow waves. They observed a rapid developmental decrease in neuronal synchrony during individual slow waves by the end of the second postnatal week. Why is this important? Generation of active states is proposed to be a primary mode of intra-cortical communication, by activation of particular circuits and not others during waking and by driving replay of memories during sleep (Destexhe et al., 2003; Ji and Wilson, 2007), both of which require differential firing of neurons based on behavioral or sensory experience. Thus synchronous firing by all neurons is poorly adapted for information processing, though it is well adapted for the stabilization of grossly refined connectivity during early development. Such all or none responses are found during early sensory processing. Colonnese et al. (2010) examined the role of early thalamocortical networks properties in determining visual responses in preterm humans and rat. Despite weak or absent retinal visual responses in vitro, robust light responses could be evoked as early as P8 in rats. As discussed previously, cortical light responses consisted of a complex group of network oscillations including delta brushes (Fig. 2C). These visual responses were ‘all-or-none’ bursts, effectively registering the presence of an even minimal stimulation, but not its intensity. Measurement of the spiking responses of retinal ganglion cells in acutely excised retina allowed further quantification of the input-output relationships, which showed that these early bursting responses massively amplified retinal activity within the cortical circuit. Only with the development of continuous activity in cortex were graded responses to light observed. Thus we suggest that the primary role of early activity patterns, in addition to precisely synchronizing activity, is to amplify weak, tentative inputs. Such amplification is incompatible with visual processing. These changes in bursting and amplification observed in the visual system 641 642 O 645 640 R O Early cortical function and implications for resting state fMRI 638 639 698 699 P 644 636 637 (where they can be quantified) are likely also to occur in other, nonsensory, cortical areas, where we would predict that early activity might be similarly ’non-coding’, but instead serve more limited synapse stabilization goals at these early ages. In short these data strongly argue that while correlated activity within and between various brain regions is undoubtedly present during the fetal period, they are much more likely to reflect the presence of anatomical connections rather than a functional transfer of information. In fact two pieces of evidence suggest that early connectivity studies may ‘over-estimate’ connectivity in preterm infants relative to adult. First, the lack of continuous activity should increase signal to noise, leading to detection of connectivity levels below those apparent in adults. Second, the amplification of weak inputs should result in activity levels with much lower anatomical connectivity indexes. By contrast, fMRI has a potential to underestimate connectivity in young brains relative to electrophysiological measurements because neurovascular coupling is still immature. While relatively tight coupling of neuronal activity and the Blood Oxygen Level Dependent (BOLD) signal in adults has been established in animal models (Logothetis and Wandell, 2004), the developmental timing of this coupling is poorly explored. In rat somatosensory cortex, evoked BOLD signal in anesthetized rats could not be observed before the 13th postnatal day (Colonnese et al., 2008). Even after the development of functional coupling, the time course of hemodynamic responses evolved over an extended time period, which should change the relevant frequencies of resting state modulations. Combined studies of spontaneous cortical EEG and blood flow measured with near infrared spectroscopy in preterm infants show that SATs are accompanied by increased oxygen extraction leading to a large and extended decrease in oxy-hemoglobin which is followed by a delayed hyperfusion of oxygenated blood relative to the adult value (Roche-Labarbe et al., 2007), somewhat resembling early BOLD signals in rats. fMRI studies in term infants have suggested a changing developmental relationship between evoked neural activity and the BOLD signal. Pattern vision evoked BOLD signals undergo an inversion, moving from positive to negative around 8 weeks (Muramoto et al., 2002). The authors suggest this is a result of rapid synaptogenesis out-pacing vascular development at these ages, causing oxygen extraction to exceed reactive blood flow. This effect has seen mixed support in other studies (Anderson et al., 2001; Dehaene-Lambertz et al., 2002; Erberich et al., 2003). Thus until the development of the neurovascular unit is better understood in humans and animal models, methods relying on neurovascular dynamics in the infant, particularly preterm infants, do not have the same experimental support as currently exists for adults, and have the potential to underestimate connectivity, while the activity and electrical characteristics of young tissue may provide a counter balancing amplification. T 643 In summary, spontaneous activity generated within thalamocortical circuits, i.e. the true ‘resting state’, is developmentally delayed relative to cortical responses to spontaneous activity in the periphery, which generate transient excitatory waves on an infraslow timescale during early development. Only after the establishment of basic cortical circuits, such as topographic mapping of thalamic inputs, does significant intra-cortical connectivity and modulation by vigilance state emerge. It is perhaps then not surprising that resting state networks involving multiple, distant cortical regions emerge after local, primarily sensory, networks (Doria et al., 2010; Power et al., 2010). D 634 635 M. Colonnese, R. Khazipov / NeuroImage xxx (2012) xxx–xxx E 8 Please cite this article as: Colonnese, M., Khazipov, R., Spontaneous activity in developing sensory circuits: Implications for resting state fMRI, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.02.046 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 M. Colonnese, R. Khazipov / NeuroImage xxx (2012) xxx–xxx 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 Q15799 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 F O R O Q14780 Uncited references Minlebaev et al., 2007 Yang et al., 2009 P 779 References Adelsberger, H., Garaschuk, O., Konnerth, A., 2005. Cortical calcium waves in resting newborn mice. Nat. Neurosci. 8, 988–990. 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Khazipov / NeuroImage xxx (2012) xxx–xxx E 10 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 Please cite this article as: Colonnese, M., Khazipov, R., Spontaneous activity in developing sensory circuits: Implications for resting state fMRI, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.02.046