Faculty Bibliography

One of the fundamental questions in system neuroscience is how the brain encodes external stimuli in the early sensory cortex. It has been found in experiments that even some simple sensory stimuli can activate large populations of neurons. It is believed that information can be encoded in the spatiotemporal profile of these collective neuronal responses. Here, we use a large-scale computational model of the primary visual cortex (V1) to study the population responses in V1 as observed in experiments in which monkeys performed visual detection tasks. We show that our model can capture very well spatiotemporal activities measured by voltage-sensitive-dye-based optical imaging in V1 of the awake state. In our model, the properties of horizontal long-range connections with NMDA conductance play an important role in the correlated population responses and have strong implications for spatiotemporal coding of neuronal populations. Our computational modeling approach allows us to reveal intrinsic cortical dynamics, separating them from those statistical effects arising from averaging procedures in experiment. For example, in experiments, it was shown that there was a spatially antagonistic center-surround structure in optimal weights in signal detection theory, which was believed to underlie the efficiency of population coding. However, our study shows that this feature is an artifact of data processing.

BACKGROUND: Clinical and epidemiological studies suggest an association between cannabis use and psychosis but this relationship remains controversial. METHOD: Clinical high-risk (CHR) subjects (age 12-22 years) with attenuated positive symptoms of psychosis (CHR+, n=101) were compared to healthy controls (HC, n=59) on rates of substance use, including cannabis. CHR+ subjects with and without lifetime cannabis use (and abuse) were compared on prodromal symptoms and social/role functioning at baseline. Participants were followed an average of 2.97 years to determine psychosis conversion status and functional outcome. RESULTS: At baseline, CHR+ subjects had significantly higher rates of lifetime cannabis use than HC. CHR+ lifetime cannabis users (n=35) were older (p=0.015, trend), more likely to be Caucasian (p=0.002), less socially anhedonic (p<0.001) and had higher Global Functioning: Social (GF:Social) scores (p<0.001) than non-users (n=61). CHR+ cannabis users continued to have higher social functioning than non-users at follow-up (p<0.001) but showed no differences in role functioning. A small sample of CHR+ cannabis abusers (n=10) showed similar results in that abusers were older (p=0.008), less socially anhedonic (p=0.017, trend) and had higher baseline GF:Social scores (p=0.006) than non-abusers. Logistic regression analyses revealed that conversion to psychosis in CHR+ subjects (n=15) was not related to lifetime cannabis use or abuse. CONCLUSIONS: The current data do not indicate that low to moderate lifetime cannabis use is a major contributor to psychosis or poor social and role functioning in clinical high-risk youth with attenuated positive symptoms of psychosis.

This paper reviews our recent work addressing the role of both synaptic-input and connectivity-architecture fluctuations in coarse-grained descriptions of integrate-and-fire (I&F) point-neuron network models. Beginning with the most basic coarse-grained description, the all-to-all coupled, mean-field model, which ignores all fluctuations, we add the effects of the two types of fluctuations one at a time. To study the effects of synaptic-input fluctuations, we derive a kinetic-theoretic description, first in the form of a Boltzmann equation in (2+1) dimensions, simplifying that to an advection-diffusion equation, and finally reducing the dimension to a system of two (1+1)-dimensional kinetic equations via the maximum entropy principle. In the limit of an infinitely-fast conductance relaxation time, we derive a Fokker-Planck equation which captures the bifurcation between a bistable, hysteretic operating regime of the network when the amount of synaptic-input fluctuations is small, and a stable regime when the amount of fluctuations increases. To study the effects of complex neuronal-network architecture, we incorporate the network connectivity statistics in the mean-field description, and investigate the dependence of these statistics on the statistical properties of the neuronal firing rates for three network examples with increasingly complex connectivity architecture

BACKGROUND: Stress sensitivity and HPA axis activity may be relevant to the development and expression of psychotic disorders. Cortisol secretion has been associated with positive symptoms both in patients with psychotic disorders and in young people at clinical risk for psychosis. Herein, we aimed to replicate these findings, to determine which positive symptoms may be associated with cortisol levels, and to explore any associations with affective symptoms and impaired stress tolerance. METHODS: Thirty-one clinical high risk patients were evaluated in cross-section for associations between salivary cortisol levels upon clinic entry at 11 am, demographic variables, and clinical symptoms. RESULTS: Salivary cortisol levels were unrelated to medication exposure or demographics, except for higher levels in the ten females studied. Salivary cortisol bore no relationship to overall positive symptom severity but was associated with anxiety, as well as with suspiciousness and impaired stress tolerance, which were themselves highly intercorrelated. CONCLUSIONS: Cortisol secretion in the context of a putative novel social situation (i.e. clinic entry) may be a biological correlate of suspiciousness, impaired stress tolerance and affective symptoms in individuals vulnerable to developing psychosis. These associations are consistent with findings from experience sampling studies in individuals at risk for psychosis as well as basic studies of animal models of schizophrenia.