Past events

Gamma oscillations are fast (30-80 Hz) rhythmic patterns of neural activity that have been proposed to support information processing in the brain. Gamma rhythms are altered in diseases such as schizophrenia and autism and are therefore of both basic and clinical interest. I have been developing optogenetic tools for light-based control over the activity of genetically defined neuronal populations. A new set of such tools, step function opsins (SFOs), are optimized for modulating the activity of neural circuits and ideal for observing emergent network properties. I will present the molecular engineering approach we used for developing these opsins and show new data on application of these tools to study the mechanisms underlying gamma oscillations in the prefrontal cortex. Some technological aspects will be discussed, with emphasis on the array of available optogenetic tools and how they might be improved to further extend the range of experiments feasible with these new techniques.

Many natural sounds, such as those produced by rainstorms, fires, and swarms of insects, result from large numbers of rapidly occurring acoustic events. Such “sound textures” are often temporally homogeneous, and in many cases do not depend much on the precise arrangement of the component events, suggesting that they might be represented statistically. To test this idea and explore the statistics that might characterize natural sound textures, we designed an algorithm to synthesize sound textures from statistics extracted from real sounds. The algorithm is inspired by those used to synthesize visual textures, in which a set of statistical measurements from a real sound are imposed on a sample of noise. This process is iterated, and converges over time to a sound that obeys the chosen constraints. If the statistics capture the perceptually important properties of the texture in question, the synthesized result ought to sound like the original sound. We tested whether rudimentary statistics computed from the responses of a bank of bandpass filters could produce compelling synthetic textures. Simply matching the marginal statistics (variance, kurtosis) of individual filter responses was generally insufficient to yield good results, but imposing various joint envelope statistics (correlations between bands, and autocorrelations within each band) greatly improved the results, frequently producing synthetic textures that sounded natural and that subjects could reliably recognize. The results suggest that statistical representations could underlie sound texture perception, and that in many cases the auditory system may rely on fairly simple statistics to recognize real world sound textures. Joint work with Andrew Oxenham and Eero Simoncelli.

The human ventral stream consists of regions in the lateral and ventral aspects of the occipital and temporal lobes and is involved in visual recognition. One robust characteristic of selectivity in the adult human ventral stream is category selectivity. Category selectivity is manifested by both a regional preference to particular object categories, such as faces, places and bodyparts, as well as in specific (and reproducible) distributed response patterns across the ventral stream for different object categories. However, it is not well understood how these representations come about throughout development and how experience modifies these representations and how do. I will describe two sets of experiments in which we addressed these important questions. First, I will describe experiments in which we examined changes in category selectivity throughout development from middle childhood (7-11 years), through adolescence (12-16) into adulthood. Surprisingly, we find that it takes more than a decade for the development of adult-like face and place-selective regions. In contrast, the lateral occipital object-selective region showed an adult-like profile by age 7. Further, recent findings from our research indicate that face-selective regions have a particularly prolonged development as they continue develop through adolescence in correlation with improved face, but not object or scene recognition memory. Development manifests as increases in the size of face-selective regions, increases in face-selectivity as well as increases in the distinctiveness of distributed response patterns to faces compared to nonfaces. Second, I will describe experiments in adults in which we examined the effect of repetition on categorical responses in the ventral stream. Repeating objects decreases responses in the human ventral stream. Repetition in lateral ventral regions manifests as a proportional effects in which responses to repeated objects are a constant fraction of nonrepeating stimuli with no change in selectivity. In contrast in medial ventral temporal cortex, we find differential effects across time scales whereby immediate repetitions produce proportional effects, but long-lagged repetitions sharpen responses, increasing category selectivity. Finally, I will discuss the implications of these results on plasticity in the ventral stream and our theoretical models linking between fMRI measurements and the underlying neural mechanisms.