Faculty Bibliography

Patients with hereditary sensory and autonomic neuropathy type III(HSAN III) exhibit marked gait disturbances. The cause of the gaitataxia is not known, but we recently showed that functional musclespindle afferents in the leg, recorded via intraneural microelectrodesinserted into the peroneal nerve, are absent in HSAN III, althoughlarge-diameter cutaneous afferents are intact. Moreover, there is atight correlation between loss of proprioceptive acuity at the knee andthe severity of gait impairment. Here we tested the hypothesis thatmanual motor performance is also compromised in HSAN III,attributed to the predicted absence of muscle spindles in the intrinsicmuscles of the hand. Manual performance in the Purdue pegboardtask was assessed in 12 individuals with HSAN III and 12 age-matched healthy controls. The mean (+/- SD) pegboard score (number ofpins inserted in 30 s) was 8.1 +/- 1.9 and 8.6 +/- 1.8 for the left andright hand respectively, significantly lower than the scores for thecontrols (14.3 +/- 2.9 and 15.5 +/- 2.0; P <0.0001). In five patients weinserted a tungsten microelectrode into the ulnar nerve at the wrist.No spontaneous or stretch-evoked muscle afferent activity could beidentified in any of the 11 fascicles supplying intrinsic muscles of thehand, whereas rich tactile afferent activity could be recorded from 4cutaneous fascicles. We conclude that functional muscle spindles areabsent in the hand, and likely absent in the long finger flexors andextensors, and that this largely accounts for the poor manual motorperformance in HSAN III

In a near-threshold sensory detection task, an animal sometimes detects and sometimes misses the same physical stimulus. A simple hypothesis is that perceptual variability is linked to variability in sensory-evoked responses in the brain as early as primary cortex. Response variability arises in part from the interaction of sensory (Figure presented) inputs with ongoing activity and is partially predictable based on the pre-stimulus cortical state. If variability in evoked responses is linked to perception, and if that variability is predictable, we would expect that it would be possible to predict based on ongoing activity whether sensory cortex is primed to detect a sensory input. Here, we determine the pre-stimulus features that are predictive of variability in the evoked response in the awake animal. We then ask what implications these observations have for the detectability of a stimulus. Using data obtained from multi-electrode recordings across the cortical depth in S1 of awake mice, we systematically quantify how much variability in the sensory-evoked LFP response is predictable from ongoing LFP activity (Fig. 1AB). This interaction has been studied extensively in the anesthetized animal [e.g., 1, 2], where the major predictors of response variability are the degree of cortical synchronization, quantified by the amount of low-frequency power, and the phase of low-frequency oscillations at which sensory input occurred. Similarly, we found that the degree of synchronization was predictive, but instead of oscillation phase, the instantaneous level of activation of the LFP in layer 4 was a useful predictor. Specifically, positive excursions in the LFP and more low-frequency (1-5 Hz) power in the LFP in the pre-stimulus period predicted larger sensory-evoked responses ("high-response state"). Using a regularized estimator of current-source density (CSD) [3] on single trials, we localized the most predictive ongoing signal to a current source location near layer 4. Finally, we found that no significant predictive power was gained by increasing the complexity of the decoder or by utilizing the full array of channels. Thus, the most predictive signatures of ongoing activity are remarkably simple and could be accessible to downstream areas. Next, we examined the impact of predictable variability on an ideal observer analysis of the detectability of sensory events (Fig. 1C). We built a detection model, in which the detection threshold is either fixed, or adaptive and based on the pre-stimulus features that are predictive of evoked variability. We quantified the accuracy of the model in terms of the simulated hit rate and the false alarm rate. Detection was more accurate in the adaptive threshold model. In the fixed-threshold model, pre-stimulus features predicted hit and miss trials. This relationship was weaker in the adaptive- threshold model, where hits as well as false alarms were nearly equally as likely to occur in low- or high-response state. In summary, if sensory perception is built on the cortical response and variability in this response is completely unpredictable, then perceptual variability would to some extent be determined by cortical variability. However, if cortical variability is predictable and downstream circuits in the brain make this prediction, then the perceptual variability could be decoupled from cortical variability

Aggression is a fundamental social behavior that is essential for competing for resources and protecting oneself and families in both males and females. As a result of natural selection, aggression is often displayed differentially between the sexes, typically at a higher level in males than females. Here, we highlight the behavioral differences between male and female aggression in rodents. We further outline the aggression circuits in males and females, and compare their differences at each circuit node. Lastly, we summarize our current understanding regarding the generation of sexually dimorphic aggression circuits during development and their maintenance during adulthood. In both cases, gonadal steroid hormones appear to play crucial roles in differentiating the circuits by impacting on the survival, morphology, and intrinsic properties of relevant cells. Many other factors, such as environment and experience, may also contribute to sex differences in aggression and remain to be investigated in future studies.

Neural computations are often compared to instrument-measured distance or duration, and such relationships are interpreted by a human observer. However, neural circuits do not depend on human-made instruments but perform computations relative to an internally defined rate-of-change. While neuronal correlations with external measures, such as distance or duration, can be observed in spike rates or other measures of neuronal activity, what matters for the brain is how such activity patterns are utilized by downstream neural observers. We suggest that hippocampal operations can be described by the sequential activity of neuronal assemblies and their internally defined rate of change without resorting to the concept of space or time.

INTRODUCTION/BACKGROUND:-weighted DCE-MRI. MATERIALS AND METHODS/METHODS:) and arterial input function (AIF). In addition, the effect of the conversion method on the diagnostic accuracy was evaluated with 36 breast lesions (19 benign and 17 malignant). RESULTS:. CONCLUSION/CONCLUSIONS:measurement is not available and a low FA is used for DCE-MRI, the uncertainty in the contrast kinetic parameter estimation can be reduced by using the LC method with pAIF, without compromising the diagnostic accuracy.

The nervous system represents the most complex tissue in animals. How this complexity evolved has been a challenging question to address. The explosion in single cell sequencing techniques, the development of new algorithms to cluster single cells into cell types, along with powerful tools for drawing developmental trajectories offer a unique opportunity to compare homologous cell types between species. They further permit the identification of key developmental points and transcription factors that can lead to the evolution of new cell types. At the same time, the ease of use and efficiency of CRISPR genome editing technology allow validation of predicted regulators. This promises exciting developments in the next few years in the field of neuronal evolution and development.

OBJECTIVE: Children with NF1 display multiple structural and functional changes in the central nervous system, such as white matter alterations, and a unique profile of neuropsy-chological cognitive abnormalities. Assessment of resting state networks (RSNs) can reveal differences in the functional architecture of the developing brain in response to neurofibromin deficiency resulting from NF1 mutation. Here, we focused on resting-state functional connectivity between the subcortical striatum and cortical networks differentiated as primary (e.g., visual, somatomotor) versus association (e.g., ventral attention, default). MATERIAL-METHODS: Eighteen children with NF1 who had resting-state fMRI scans were group-matched (age, gender and head movement) with 18 typically developing children (TDC) from the ABIDE repository. Coherent slow fluctuations in the fMRI signal across the entire brain were used to interrogate the pattern of functional connectivity of cortical-subcortical structures. Assessment of RSNs was done using a previously established automated clustering algorithm. RESULTS: NF1 children demonstrated abnormal organization of association networks, particularly, deficient long-distance functional connectivity. Examining the contribution of the striatum revealed that corticostriatal functional connectivity was altered, with NF1 children demonstrating diminished functional connectivity between striatum and the ventral attention network, as well as the posterior cingulate area, which is associated with the default network. By contrast, somatomotor functional connectivity with the striatum was increased. Functional connectivity of the visual network with the striatum did not differ in the NF1 group. CONCLUSION: These findings suggest that, much like in animal studies, the striatum plays a major role in NF1 cognitive pathogenesis. In addition, the "immature" pattern of deficient long distance functional connectivity suggests that NF1-associated myelin abnormalities may also play a significant role in the disrupted formation of RSNs

The types of errors during speech production can vary across individuals with chronic post-stroke aphasia, possibly due to the location and extent of brain damage. In this study, we evaluated the relationship between semantic vs. phonemic errors during confrontational naming, and their relationship with the degree of damage to ventral and dorsal white matter pathways extending beyond the necrotic stroke lesion. Based on the dual stream model of language processing, we tested the hypothesis that semantic errors would be associated with ventral stream damage, whereas phonemic errors would be associated with dorsal stream damage, but not vice-versa. Multi-shell diffusion MRI was used to obtain kurtosis-based white matter tractography from 32 chronic stroke survivors. Using diffusion microstructural tissue modeling, we estimated axonal loss along the length of the inferior and superior longitudinal fasciculi (ILF and SLF), representing the main pathways in the ventral and dorsal streams, respectively. The frequency of semantic paraphasias was strongly associated with ILF axonal loss, whereas phonemic paraphasias were strongly associated with SLF axonal loss, but not vice versa. This dissociation between semantic and phonological processing is in agreement with the dual stream model of language processing and corroborates the concept that, during speech production, knowledge association (semantics) depends on the integrity of ventral, whereas form encoding (phonological encoding) is more localized to dorsal pathways. These findings also demonstrate the importance of the residual integrity of specific white matter pathways beyond regional gray matter damage for speech production.

G protein-coupled receptors (GPCRs) mediate the transduction of extracellular signals into complex intracellular responses. Despite their ubiquitous roles in physiological processes and as drug targets for a wide range of disorders, the precise mechanisms of GPCR function at the molecular, cellular, and systems levels remain partially understood. To dissect the function of individual receptor subtypes with high spatiotemporal precision, various optogenetic and photopharmacological approaches have been reported that use the power of light for receptor activation and deactivation. Here, we introduce a novel and, to date, most remote way of applying photoswitchable orthogonally remotely tethered ligands by using a SNAP-tag fused nanobody. Our nanobody-photoswitch conjugates can be used to target a green fluorescent protein-fused metabotropic glutamate receptor by either gene-free application of purified complexes or coexpression of genetically encoded nanobodies to yield robust, reversible control of agonist binding and subsequent downstream activation. By harboring and combining the selectivity and flexibility of both nanobodies and self-labeling proteins (or suicide enzymes), we set the stage for targeting endogenous receptors in vivo.

The contributions of areas downstream of retinal ganglion cells involved in the processing and regulation of mood remain largely unspecified. In this issue of Cell, Fernandez et al. (2018) identify a thalamic circuit within the perihabenular region (pHb) linking daily changes of light pattern to mood regulation.