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 many studies of attention-deficit hyperactivity disorder (ADHD), stimulus encoding and processing (perceptual function) and response selection (executive function) have been intertwined. To dissociate deficits in these functions, we introduced a task that parametrically varied low-level stimulus features (orientation and color) for fine-grained analysis of perceptual function. It also required participants to switch their attention between feature dimensions on a trial-by-trial basis, thus taxing executive processes. Furthermore, we used a response paradigm that captured task-irrelevant motor output (TIMO), reflecting failures to use the correct stimulus-response rule. ADHD participants had substantially higher perceptual variability than controls, especially for orientation, as well as higher TIMO. In both ADHD and controls, TIMO was strongly affected by the switch manipulation. Across participants, the perceptual variability parameter was correlated with TIMO, suggesting that perceptual deficits are associated with executive function deficits. Based on perceptual variability alone, we were able to classify participants into ADHD and controls with a mean accuracy of about 77%. Participants' self-reported General Executive Composite score correlated not only with TIMO but also with the perceptual variability parameter. Our results highlight the role of perceptual deficits in ADHD and the usefulness of computational modeling of behavior in dissociating perceptual from executive processes.

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.

Nervous systems control locomotion using rhythmically active networks that orchestrate motor neuron firing patterns. Whether animals use common or distinct genetic programs to encode motor rhythmicity remains unclear. Cross-species comparisons have revealed remarkably conserved neural patterning systems but have also unveiled divergent circuit architectures that can generate similar locomotor behaviors.

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

Hereditary sensory and autonomic neuropathy type III (HSAN III)features a marked ataxic gait that progressively worsens over time.We recently assessed whether proprioceptive disturbances can explainthe ataxia. Proprioception at the knee joint was assessed using passivejoint angle matching in 18 patients and 14 age-matched controls; fivepatients with cerebellar ataxia were also studied. Ataxia was quantified using the Brief Ataxia Rating Score, which ranged from 7 to26/30. Patients with HSAN III performed poorly in judging jointposition at the knee: mean (+/- SE) absolute error was 8.7 +/- 1.0 andthe range was very wide (2.8-18.1); conversely, absolute error wasonly 2.7 +/- 0.3 (1.6-5.5) in the controls and 3.0 +/- 0.2 (2.1-3.4) in the cerebellar patients. This error was positively correlated tothe degree of ataxia in patients with HSAN III but not in patients withcerebellar ataxia. However, using the same approach at the elbowrevealed no significant differences in mean error in 12 patients withHSAN III (4.8 +/- 1.2; 3.0-7.2) and 12 age-matched controls(4.1 +/- 1.1; 2.1-5.5). Interestingly, microelectrode recordingsfrom the peroneal nerve showed a complete absence of spontaneousor stretch-evoked muscle afferent activity, confirmed in the ulnarnerve. Clearly, the lack of muscle spindles compromised proprioception at the knee but not at the elbow, and we suggest that patientswith HSAN III have learned to rely more on proprioceptive signalsfrom the skin around the elbow. Indeed, applying longitudinal stripsof elastic tape around the joint to increase tensile strain in the skinimproved proprioception at the knee but not the elbow

Myelin breakdown and neural fiber loss occur in aging. This study used white matter tract integrity metrics derived from biophysical modeling using Diffusional Kurtosis Imaging to assess loss of myelin (i.e., extraaxonal diffusivity, radial direction, D_e,⊥) and axonal density (i.e., axonal water fraction) in cognitively unimpaired older adults. Tract-based spatial statistics and region of interest analyses sought to identify ontogenic differences and age-related changes in white matter tracts using cross-sectional and longitudinal data analyzed with general linear and mixed-effects models. In addition to pure diffusion parameters (i.e., fractional anisotropy, mean diffusivity, mean kurtosis), we found that white matter tract integrity metrics significantly differentiated early- from late-myelinating tracts, correlated with age in spatially distinct regions, and identified primarily extraaxonal changes over time. Percent metric changes were |0.3-0.9|% and |0.0-1.9|% per year using cross-sectional data and longitudinal data, respectively. There was accelerated decline in some late- versus early-myelinating tracts in older age. These results demonstrate that these metrics may inform further study of the transition from age-related changes to neurodegenerative decline.

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 local field potential (LFP) is an aggregate measure of group neuronal activity and is often correlated with the action potentials of single neurons. In recent years, investigators have found that action potential firing rates increase during elevations in power high-frequency band oscillations (50-200 Hz range). However, action potentials also contribute to the LFP signal itself, making the spike-LFP relationship complex. Here, we examine the relationship between spike rates and LFP in varying frequency bands in rat neocortical recordings. We find that 50-180 Hz oscillations correlate most consistently with high firing rates, but that other LFP bands also carry information relating to spiking, including in some cases anti-correlations. Relatedly, we find that spiking itself and electromyographic activity contribute to LFP power in these bands. The relationship between spike rates and LFP power varies between brain states and between individual cells. Finally, we create an improved oscillation-based predictor of action potential activity by specifically utilizing information from across the entire recorded frequency spectrum of LFP. The findings illustrate both caveats and improvements to be taken into account in attempts to infer spiking activity from LFP.