Using Continuous Glucose Monitoring Values for Bolus Size Calculation in Smart Multiple Daily Injection Systems: No Negative Impact on Post-bolus Glycemic Outcomes Found in Real-World Data.

BACKGROUND: Recent evidence shows that it may be safe to estimate bolus sizes based on continuous glucose monitoring (CGM) rather than blood glucose (BG) values using glycemic trend-adjusted bolus calculators. Users may already be doing this in the real world, though it is unclear whether this is safe or effective for calculators not employing trend adjustment. METHODS: We assessed real-world data from a smart multiple daily injections (MDIs) device users with a CGM system, hypothesizing that four-hour post-bolus outcomes using CGM values are not inferior to those using BG values. Our data set included 184 users and spanned 18 months with 79 000 bolus observations. We tested differences using logistic regression predicting CGM or BG value usage based on outcomes and confirmed initial results using a mixed model regression accounting for within-subject correlations. RESULTS: Comparing four-hour outcomes for bolus events using CGM and BG values revealed no differences using our initial approach (P > .183). This finding was confirmed by our mixed model regression approach in all cases (P > .199), except for times below range outcomes. Higher times below range were predictive of lower odds of CGM-based bolus calculations (OR = 0.987, P < .0001 and OR = 0.987, P = .0276, for time below 70 and 54 mg/dL, respectively). CONCLUSIONS: We found no differences in four-hour post-bolus glycemic outcomes when using CGM or BG except for time below range, which showed evidence of being lower for CGM. Though preliminary, our results confirm prior findings showing non-inferiority of using CGM values for bolus calculation compared with BG usage in the real world.

Effects of arousal and movement on secondary somatosensory and visual thalamus.

Neocortical sensory areas have associated primary and secondary thalamic nuclei. While primary nuclei transmit sensory information to cortex, secondary nuclei remain poorly understood. We recorded juxtasomally from secondary somatosensory (POm) and visual (LP) nuclei of awake mice while tracking whisking and pupil size. POm activity correlated with whisking, but not precise whisker kinematics. This coarse movement modulation persisted after facial paralysis and thus was not due to sensory reafference. This phenomenon also continued during optogenetic silencing of somatosensory and motor cortex and after lesion of superior colliculus, ruling out a motor efference copy mechanism. Whisking and pupil dilation were strongly correlated, possibly reflecting arousal. Indeed LP, which is not part of the whisker system, tracked whisking equally well, further indicating that POm activity does not encode whisker movement per se. The semblance of movement-related activity is likely instead a global effect of arousal on both nuclei. We conclude that secondary thalamus monitors behavioral state, rather than movement, and may exist to alter cortical activity accordingly.

Target-specific M1 inputs to infragranular S1 pyramidal neurons.

The functional role of input from the primary motor cortex (M1) to primary somatosensory cortex (S1) is unclear; one key to understanding this pathway may lie in elucidating the cell-type specific microcircuits that connect S1 and M1. Recently, we discovered that a subset of pyramidal neurons in the infragranular layers of S1 receive especially strong input from M1 (Kinnischtzke AK, Simons DJ, Fanselow EE. Cereb Cortex 24: 2237-2248, 2014), suggesting that M1 may affect specific classes of pyramidal neurons differently. Here, using combined optogenetic and retrograde labeling approaches in the mouse, we examined the strengths of M1 inputs to five classes of infragranular S1 neurons categorized by their projections to particular cortical and subcortical targets. We found that the magnitude of M1 synaptic input to S1 pyramidal neurons varies greatly depending on the projection target of the postsynaptic neuron. Of the populations examined, M1-projecting corticocortical neurons in L6 received the strongest M1 inputs, whereas ventral posterior medial nucleus-projecting corticothalamic neurons, also located in L6, received the weakest. Each population also possessed distinct intrinsic properties. The results suggest that M1 differentially engages specific classes of S1 projection neurons, thereby regulating the motor-related influence S1 exerts over subcortical structures.

Motor cortex broadly engages excitatory and inhibitory neurons in somatosensory barrel cortex.

Anatomical studies have shown that primary somatosensory (S1) and primary motor (M1) cortices are reciprocally connected. The M1 to S1 projection is thought to represent a modulatory signal that conveys motor-related information to S1. Here, we investigated M1 synaptic inputs to S1 by injecting an AAV virus containing channelrhodopsin-2 and a fluorescent tag into M1. Consistent with previous results, we found labeling of M1 axons within S1 that was most robust in the deep layers and in L1. Labeling was sparse in L4 and was concentrated in the interbarrel septa, largely avoiding barrel centers. In S1, we recorded in vitro from regular-spiking excitatory neurons and fast-spiking and somatostatin-expressing inhibitory interneurons. All 3 cell types had a high probability of receiving direct excitatory M1 input. Both excitatory and inhibitory cells within L4 were the least likely to receive such input from M1. Disynaptic inhibition was observed frequently, indicating that M1 recruits substantial inhibition within S1. Additionally, a subpopulation of L6 regular-spiking excitatory neurons received exceptionally strong M1 input. Overall, our results suggest that activation of M1 evokes within S1 a bombardment of excitatory and inhibitory synaptic activity that could contribute in a layer-specific manner to state-dependent changes in S1.

Postnatal maturation of somatostatin-expressing inhibitory cells in the somatosensory cortex of GIN mice.

Postnatal inhibitory neuron development affects mammalian brain function, and failure of this maturation process may underlie pathological conditions such as epilepsy, schizophrenia, and depression. Furthermore, understanding how physiological properties of inhibitory neurons change throughout development is critical to understanding the role(s) these cells play in cortical processing. One subset of inhibitory neurons that may be affected during postnatal development is somatostatin-expressing (SOM) cells. A subset of these cells is labeled with green-fluorescent protein (GFP) in a line of mice known as the GFP-positive inhibitory neurons (GIN) line. Here, we studied how intrinsic electrophysiological properties of these cells changed in the somatosensory cortex of GIN mice between postnatal ages P11 and P32+. GIN cells were targeted for whole-cell current-clamp recordings and ranges of positive and negative current steps were presented to each cell. The results showed that as the neocortical circuitry matured during this critical time period multiple intrinsic and firing properties of GIN inhibitory neurons, as well as those of excitatory (regular-spiking [RS]) cells, were altered. Furthermore, these changes were such that the output of GIN cells, but not RS cells, increased over this developmental period. We quantified changes in excitability by examining the input-output relationship of both GIN and RS cells. We found that the firing frequency of GIN cells increased with age, while the rheobase current remained constant across development. This created a multiplicative increase in the input-output relationship of the GIN cells, leading to increases in gain with age. The input-output relationship of the RS cells, on the other hand, showed primarily a subtractive shift with age, but no substantial change in gain. These results suggest that as the neocortex matures, inhibition coming from GIN cells may become more influential in the circuit and play a greater role in the modulation of neocortical activity.

Effects of thalamic high-frequency electrical stimulation on whisker-evoked cortical adaptation.

Activity in thalamocortical circuits depends strongly on immediate past experience. When the successive activity is attenuated on short timescales, this phenomenon is known as adaptation. Adaptive processes may be effectively initiated by ongoing exposure to sensory stimuli and/or direct electrical stimulation of neural tissue. Ongoing high-frequency electrical stimulation is increasingly employed as a treatment for a variety of neurological disorders. Neural stimulation with similar parameters to therapeutic electrical stimulation may modulate the way in which cortical neurons respond and adapt to sensory stimuli. Here, we studied the effects of high-frequency stimulation of the somatosensory thalamus on the transmission of sensory signals in thalamocortical circuits. We examined how whisker-evoked sensory inputs in layer IV cortical barrels are affected by concurrent 100 Hz thalamic electrical stimulation and how the latter modulates sensory-evoked adaptation. Even in the presence of ongoing thalamic stimulation, sensory transmission in thalamocortical circuits is maintained. However, cortical responses to whisker deflections are reduced in an intensity-dependent fashion and can be nearly abolished with high intensity currents. The electrical stimulation-induced reduction in cortical responsiveness likely reflects engagement of circuit mechanisms that normally produce sensory adaptation.

Daily and developmental modulation of "premotor" activity in the birdsong system.

Human speech and birdsong are shaped during a sensorimotor sensitive period in which auditory feedback guides vocal learning. To study brain activity as song learning occurred, we recorded longitudinally from developing zebra finches during the sensorimotor phase. Learned sequences of vocalizations (motifs) were examined along with contemporaneous neural population activity in the song nucleus HVC, which is necessary for the production of learned song (Nottebohm et al. 1976: J Comp Neurol 165:457-486; Simpson and Vicario 1990: J Neurosci 10:1541-1556). During singing, HVC activity levels increased as the day progressed and decreased after a night of sleep in juveniles and adults. In contrast, the pattern of HVC activity changed on a daily basis only in juveniles: activity bursts became more pronounced during the day. The HVC of adults was significantly burstier than that of juveniles. HVC bursting was relevant to song behavior because the degree of burstiness inversely correlated with the variance of song features in juveniles. The song of juveniles degrades overnight (Deregnaucourt et al. 2005: Nature 433:710-716). Consistent with a relationship between HVC activity and song plasticity (Day et al. 2008: J Neurophys 100:2956-2965), HVC burstiness degraded overnight in young juveniles and the amount of overnight degradation declined with developmental song learning. Nocturnal changes in HVC activity strongly and inversely correlated with the next day's change, suggesting that sleep-dependent degradation of HVC activity may facilitate or enable subsequent diurnal changes. Collectively, these data show that HVC activity levels exhibit daily cycles in adults and juveniles, whereas HVC burstiness and song stereotypy change daily in juveniles only. In addition, the data indicate that HVC burstiness increases with development and inversely correlates with song variability, which is necessary for trial and error vocal learning.

Top-down regulation of plasticity in the birdsong system: "premotor" activity in the nucleus HVC predicts song variability better than it predicts song features.

We studied real-time changes in brain activity during active vocal learning in the zebra finch songbird. The song nucleus HVC is required for the production of learned song. To quantify the relationship of HVC activity and behavior, HVC population activity during repeated vocal sequences (motifs) was recorded and temporally aligned relative to the motif, millisecond by millisecond. Somewhat surprisingly, HVC activity did not reliably predict any vocal feature except amplitude and, to a lesser extent, entropy and pitch goodness (sound periodicity). Variance in "premotor" HVC activity did not reliably predict variance in behavior. In contrast, HVC activity inversely predicted the variance of amplitude, entropy, frequency, pitch, and FM. We reasoned that, if HVC was involved in song learning, the relationship of HVC activity to learned features would be developmentally regulated. To test this hypothesis, we compared the HVC song feature relationships in adults and juveniles in the sensorimotor "babbling" period. We found that the relationship of HVC activity to variance in FM was developmentally regulated, with the greatest difference at an HVC vocalization lag of 50 ms. Collectively, these data show that, millisecond by millisecond, bursts in HVC activity predict song stability on-line during singing, whereas decrements in HVC activity predict plasticity. These relationships between neural activity and plasticity may play a role in vocal learning in songbirds by enabling the selective stabilization of parts of the song that match a learned tutor model.

HVC neural sleep activity increases with development and parallels nightly changes in song behavior.

Sleep abnormalities are coexpressed with human communication disorders. Recent data from the birdsong system, the best model for human speech, indicate that sleep has a critical role in vocal learning. To understand the neural mechanisms that underlie behavioral changes during sleep, we recorded sleep activity in the song control area HVC longitudinally during song development in zebra finches. We focused on the sensorimotor phase of song learning, when the finch shapes his song behavior toward a learned tutor song model. Direct comparison of sleep activity in adults and juveniles revealed that the juvenile HVC has a lower spike rate and longer silent periods than the adult. Within individual finches, sleep silent periods decreased and spike rate increased with age. We next systematically compared neural sleep activity and song behavior. We now report that spike rate during sleep was significantly correlated with overnight changes in song behavior. Collectively, these data indicate that sleep activity in the vocal control area HVC increases with age and may affect song behavior.