Faculty Bibliography

Despite intense recent research, the neural correlates of conscious visual perception remain elusive. The most established paradigm for studying brain mechanisms underlying conscious perception is to keep the physical sensory inputs constant and identify brain activities that correlate with the changing content of conscious awareness. However, such a contrast based on conscious content alone would not only reveal brain activities directly contributing to conscious perception, but also include brain activities that precede or follow it. To address this issue, we devised a paradigm whereby we collected, trial-by-trial, measures of objective performance, subjective awareness, and the confidence level of subjective awareness. Using magnetoencephalography recordings in healthy human volunteers, we dissociated brain activities underlying these different cognitive phenomena. Our results provide strong evidence that widely distributed slow cortical potentials (SCPs) correlate with subjective awareness, even after the effects of objective performance and confidence were both removed. The SCP correlate of conscious perception manifests strongly in its waveform, phase, and power. In contrast, objective performance and confidence were both contributed by relatively transient brain activity. These results shed new light on the brain mechanisms of conscious, unconscious, and metacognitive processing.

Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra - a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework - a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and while performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately - resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well.

Brain activity observed at many spatiotemporal scales exhibits a 1/f-like power spectrum, including neuronal membrane potentials, neural field potentials, noninvasive electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) signals. A 1/f-like power spectrum is indicative of arrhythmic brain activity that does not contain a predominant temporal scale (hence, 'scale-free'). This characteristic of scale-free brain activity distinguishes it from brain oscillations. Although scale-free brain activity and brain oscillations coexist, our understanding of the former remains limited. Recent research has shed light on the spatiotemporal organization, functional significance, and potential generative mechanisms of scale-free brain activity, as well as its developmental and clinical relevance. A deeper understanding of this prevalent brain signal should provide new insights into, and analytical tools for, cognitive neuroscience.

Brain-machine interfaces (BMIs) open new horizons for the treatment of paralyzed persons, giving hope for the artificial restoration of lost physiological functions. Whereas BMI development has mainly focused on motor rehabilitation, recent studies have suggested that higher cognitive functions can also be deciphered from brain activity, bypassing low level planning and execution functions, and replacing them by computer-controlled effectors. This review describes the new generation of cognitive-motor BMIs, focusing on three BMI types: By outlining recent progress in developing these BMI types, we aim to provide a unified view of contemporary research towards the replacement of behavioral outputs of cognitive processes by direct interaction with the brain.

Planar neural networks and interfaces serve as versatile in vitro models of central nervous system physiology, but adaptations of related methods to three dimensions (3D) have met with limited success. Here, we demonstrate for the first time volumetric functional imaging in a bioengineered neural tissue growing in a transparent hydrogel with cortical cellular and synaptic densities, by introducing complementary new developments in nonlinear microscopy and neural tissue engineering. Our system uses a novel hybrid multiphoton microscope design combining a 3D scanning-line temporal-focusing subsystem and a conventional laser-scanning multiphoton microscope to provide functional and structural volumetric imaging capabilities: dense microscopic 3D sampling at tens of volumes per second of structures with mm-scale dimensions containing a network of over 1,000 developing cells with complex spontaneous activity patterns. These developments open new opportunities for large-scale neuronal interfacing and for applications of 3D engineered networks ranging from basic neuroscience to the screening of neuroactive substances.

Sensory systems use stochastic mechanisms to diversify neuronal subtypes. In the Drosophila eye, stochastic expression of the PAS-bHLH transcription factor Spineless (Ss) determines a random binary subtype choice in R7 photoreceptors. Here, we show that a stochastic, cell-autonomous decision to express ss is made intrinsically by each ss locus. Stochastic on or off expression of each ss allele is determined by combinatorial inputs from one enhancer and two silencers acting at long range. However, the two ss alleles also average their frequency of expression through up-regulatory and down-regulatory interallelic cross-talk. This inter- or intrachromosomal long-range regulation does not require endogenous ss chromosomal positioning or pairing. Therefore, although individual ss alleles make independent stochastic choices, interchromosomal communication coordinates expression state between alleles, ensuring that they are both expressed in the same random subset of R7s.

The elbow/no ocelli (elb/noc) complex of Drosophila melanogaster encodes two paralogs of the evolutionarily conserved NET family of zinc finger proteins. These transcriptional repressors share a conserved domain structure, including a single atypical C2H2 zinc finger. In flies, Elb and Noc are important for the development of legs, eyes and tracheae. Vertebrate NET proteins play an important role in the developing nervous system, and mutations in the homolog ZNF703 human promote luminal breast cancer. However, their interaction with transcriptional regulators is incompletely understood. Here we show that loss of both Elb and Noc causes mis-specification of polarization-sensitive photoreceptors in the 'dorsal rim area' (DRA) of the fly retina. This phenotype is identical to the loss of the homeodomain transcription factor Homothorax (Hth)/dMeis. Development of DRA ommatidia and expression of Hth are induced by the Wingless/Wnt pathway. Our data suggest that Elb/Noc genetically interact with Hth, and we identify two conserved domains crucial for this function. Furthermore, we show that Elb/Noc specifically interact with the transcription factor Orthodenticle (Otd)/Otx, a crucial regulator of rhodopsin gene transcription. Interestingly, different Elb/Noc domains are required to antagonize Otd functions in transcriptional activation, versus transcriptional repression. We propose that similar interactions between vertebrate NET proteins and Meis and Otx factors might play a role in development and disease.

Embryonic anterior-posterior patterning is well understood in Drosophila, which uses 'long germ' embryogenesis, in which all segments are patterned before cellularization. In contrast, most insects use 'short germ' embryogenesis, wherein only head and thorax are patterned in a syncytial environment while the remainder of the embryo is generated after cellularization. We use the wasp Nasonia (Nv) to address how the transition from short to long germ embryogenesis occurred. Maternal and gap gene expression in Nasonia suggest long germ embryogenesis. However, the Nasonia pair-rule genes even-skipped, odd-skipped, runt and hairy are all expressed as early blastoderm pair-rule stripes and late-forming posterior stripes. Knockdown of Nv eve, odd or h causes loss of alternate segments at the anterior and complete loss of abdominal segments. We propose that Nasonia uses a mixed mode of segmentation wherein pair-rule genes pattern the embryo in a manner resembling Drosophila at the anterior and ancestral Tribolium at the posterior. DOI: http://dx.doi.org/10.7554/eLife.01440.001.

Combining genome-wide analyses of binding sites and expression profiles generates a model for the functional evolution of two SOXB paralogous proteins in neurogenesis.