Person:

Kreiman, Gabriel

We investigated the variability of P-receptor afferent spike trains in the weakly electric fish, Eigenmannia, to repeated presentations of random electric field AMs (RAMs) and quantified its impact on the encoding of time-varying stimuli. A new measure of spike timing jitter was developed using the notion of spike train distances recently introduced by Victor and Purpura. This measure of variability is widely applicable to neuronal responses, irrespective of the type of stimuli used (deterministic vs. random) or the reliability of the recorded spike trains. In our data, the mean spike count and its variance measured in short time windows were poorly correlated with the reliability of P-receptor afferent spike trains, implying that such measures provide unreliable indices of trial-to-trial variability. P-receptor afferent spike trains were considerably less variable than those of Poisson model neurons. The average timing jitter of spikes lay within 1–2 cycles of the electric organ discharge (EOD). At low, but not at high firing rates, the timing jitter was dependent on the cutoff frequency of the stimulus and, to a lesser extent, on its contrast. When spikes were artificially manipulated to increase jitter, information conveyed by P-receptor afferents was degraded only for average jitters considerably larger than those observed experimentally. This suggests that the intrinsic variability of single spike trains lies outside of the range where it might degrade the information conveyed, yet still allows for improvement in coding by averaging across multiple afferent fibers. Our results were summarized in a phenomenological model of P-receptor afferents, incorporating both their linear transfer properties and the variability of their spike trains. This model complements an earlier one proposed by Nelson et al. for P-receptor afferents of Apteronotus. Because of their relatively high precision with respect to the EOD cycle frequency, P-receptor afferent spike trains possess the temporal resolution necessary to support coincidence detection operations at the next stage in the amplitude-coding pathway.

Microarray technology represents a potentially powerful method for identifying cell type- and regionally restricted genes expressed in the brain. Here we have combined a microarray analysis of differential gene expression among five selected brain regions, including the amygdala, cerebellum, hippocampus, olfactory bulb, and periaqueductal gray, with in situ hybridization. On average, 0.3% of the 34,000 genes interrogated were highly enriched in each of the five regions, relative to the others. In situ hybridization performed on a subset of amygdala-enriched genes confirmed in most cases the overall region-specificity predicted by the microarray data and identified additional sites of brain expression not examined on the microarrays. Strikingly, the majority of these genes exhibited boundaries of expression within the amygdala corresponding to cytoarchitectonically defined subnuclei. These results define a unique set of molecular markers for amygdaloid subnuclei and provide tools to genetically dissect their functional roles in different emotional behaviors.

Adult neocortical areas are characterized by marked differences in cytoarchitecture and connectivity that underlie their functional roles. The molecular determinants of these differences are largely unknown. We performed a microarray analysis to identify molecules that define the somatosensory and visual areas during the time when afferent and efferent projections are forming. We identified 122 molecules that are differentially expressed between the regions and confirmed by quantitative polymerase chain reaction 95% of the 20 genes tested. Two genes were chosen for further investigation: Bcl6 and Ten_m3. Bcl6 was highly expressed in the superficial cortical plate corresponding to developing layer IV of somatosensory cortex at postnatal day (P) 0. This had diminished by P3, but strong expression was found in layer V pyramidal cells by P7 and was maintained until adulthood. Retrograde tracing showed that Bcl6 is expressed in corticospinal neurons. Ten_m3 was expressed in a graded pattern within layer V of caudal cortex that corresponds well with visual cortex. Retrograde tracing and immunostaining showed that Ten_m3 is highly expressed along axonal tracts of projection neurons of the developing visual pathway. Overexpression demonstrated that Ten_m3 promotes homophilic adhesion and neurite outgrowth in vivo. This suggests an important role for Ten_m3 in the development of the visual pathway.

Primary sensory nuclei of the thalamus process and relay parallel channels of sensory input into the cortex. The developmental processes by which these nuclei acquire distinct functional roles are not well understood. To identify novel groups of genes with a potential role in differentiating two adjacent sensory nuclei, we performed a microarray screen comparing perinatal gene expression in the principal auditory relay nucleus, the medial geniculate nucleus (MGN), and principal visual relay nucleus, the lateral geniculate nucleus (LGN). We discovered and confirmed groups of highly ranked, differentially expressed genes with qRT-PCR and in situ hybridization. A functional role for Zic4, a transcription factor highly enriched in the LGN, was investigated using Zic4-null mice, which were found to have changes in topographic patterning of retinogeniculate projections. Foxp2, a transcriptional repressor expressed strongly in the MGN, was found to be positively regulated by activity in the MGN. These findings identify roles for two differentially expressed genes, Zic4 and Foxp2, in visual and auditory pathway development. Finally, to test whether modality-specific patterns of gene expression are influenced by extrinsic patterns of input, we performed an additional microarray screen comparing the normal MGN to “rewired” MGN, in which normal auditory afferents are ablated and novel retinal inputs innervate the MGN. Data from this screen indicate that rewired MGN acquires some patterns of gene expression that are present in the developing LGN, including an upregulation of Zic4 expression, as well as novel patterns of expression which may represent unique processes of cross-modal plasticity.

Human and non-human primates excel at visual recognition tasks. The primate visual system exhibits a strong degree of selectivity while at the same time being robust to changes in the input image. We have developed a quantitative theory to account for the computations performed by the feedforward path in the ventral stream of the primate visual cortex. Here we review recent predictions by a model instantiating the theory about physiological observations in higher visual areas. We also show that the model can perform recognition tasks on datasets of complex natural images at a level comparable to psychophysical measurements on human observers during rapid categorization tasks. In sum, the evidence suggests that the theory may provide a framework to explain the first 100–150 ms of visual object recognition. The model also constitutes a vivid example of how computational models can interact with experimental observations in order to advance our understanding of a complex phenomenon. We conclude by suggesting a number of open questions, predictions, and specific experiments for visual physiology and psychophysics.

Visual information from the environment is transformed into perceptual sensations through several stages of neuronal processing. Flash suppression constitutes a striking example in which the same retinal input can give rise to two different conscious visual percepts. We directly recorded the responses of individual neurons during flash suppression in the human amygdala, entorhinal cortex, hippocampus, and parahippocampal gyrus, allowing us to explore the neuronal responses in untrained subjects at a high spatial and temporal resolution in the medial temporal lobe. Subjects were patients with pharmacologically intractable epilepsy implanted with depth electrodes to localize the seizure onset focus. We observed that the activity of two thirds of all visually selective neurons followed the perceptual alternations rather than the retinal input. None of the selective neurons responded to a perceptually suppressed stimulus. Therefore, the activity of most individual neurons in the medial temporal lobe of naive human subjects directly correlates with the phenomenal visual experience.

Background: Alternative pre-mRNA splicing (AS) is widely used by higher eukaryotes to generate different protein isoforms in specific cell or tissue types. To compare AS events across human tissues, we analyzed the splicing patterns of genomically aligned expressed sequence tags (ESTs) derived from libraries of cDNAs from different tissues. Results: Controlling for differences in EST coverage among tissues, we found that the brain and testis had the highest levels of exon skipping. The most pronounced differences between tissues were seen for the frequencies of alternative 3' splice site and alternative 5' splice site usage, which were about 50 to 100% higher in the liver than in any other human tissue studied. Quantifying differences in splice junction usage, the brain, pancreas, liver and the peripheral nervous system had the most distinctive patterns of AS. Analysis of available microarray expression data showed that the liver had the most divergent pattern of expression of serine-arginine protein and heterogeneous ribonucleoprotein genes compared to the other human tissues studied, possibly contributing to the unusually high frequency of alternative splice site usage seen in liver. Sequence motifs enriched in alternative exons in genes expressed in the brain, testis and liver suggest specific splicing factors that may be important in AS regulation in these tissues. Conclusions: This study distinguishes the human brain, testis and liver as having unusually high levels of AS, highlights differences in the types of AS occurring commonly in different tissues, and identifies candidate cis-regulatory elements and trans-acting factors likely to have important roles in tissue-specific AS in human cells.

The difficulty of visual recognition stems from the need to achieve high selectivity while maintaining robustness to object transformations within hundreds of milliseconds. Theories of visual recognition differ in whether the neuronal circuits invoke recurrent feedback connections or not. The timing of neurophysiological responses in visual cortex plays a key role in distinguishing between bottom-up and top-down theories. Here, we quantified at millisecond resolution the amount of visual information conveyed by intracranial field potentials from 912 electrodes in 11 human subjects. We could decode object category information from human visual cortex in single trials as early as 100 ms poststimulus. Decoding performance was robust to depth rotation and scale changes. The results suggest that physiological activity in the temporal lobe can account for key properties of visual recognition. The fast decoding in single trials is compatible with feedforward theories and provides strong constraints for computational models of human vision.

Neighboring cells in topographical sensory maps may transmit similar information to the next higher level of processing. How information transmission by groups of nearby neurons compares with the performance of single cells is a very important question for understanding the functioning of the nervous system. To tackle this problem, we quantified stimulus-encoding and feature extraction performance by pairs of simultaneously recorded electrosensory pyramidal cells in the hindbrain of weakly electric fish. These cells constitute the output neurons of the first central nervous stage of electrosensory processing. Using random amplitude modulations (RAMs) of a mimic of the fish's own electric field within behaviorally relevant frequency bands, we found that pyramidal cells with overlapping receptive fields exhibit strong stimulus-induced correlations. To quantify the encoding of the RAM time course, we estimated the stimuli from simultaneously recorded spike trains and found significant improvements over single spike trains. The quality of stimulus reconstruction, however, was still inferior to the one measured for single primary sensory afferents. In an analysis of feature extraction, we found that spikes of pyramidal cell pairs coinciding within a time window of a few milliseconds performed significantly better at detecting upstrokes and downstrokes of the stimulus compared with isolated spikes and even spike bursts of single cells. Coincident spikes can thus be considered “distributed bursts.” Our results suggest that stimulus encoding by primary sensory afferents is transformed into feature extraction at the next processing stage. There, stimulus-induced coincident activity can improve the extraction of behaviorally relevant features from the stimulus.