Summary Natural vision often involves recognizing objects from partial information. Recognition of objects from parts presents a significant challenge for theories of vision because it requires spatial integration and extrapolation from prior knowledge. Here we recorded intracranial field potentials of 113 visually selective electrodes from epilepsy patients in response to whole and partial objects. Responses along the ventral visual stream, particularly the Inferior Occipital and Fusiform Gyri, remained selective despite showing only 9–25% of the object areas. However, these visually selective signals emerged ~100 ms later for partial versus whole objects. These processing delays were particularly pronounced in higher visual areas within the ventral stream. This latency difference persisted when controlling for changes in contrast, signal amplitude, and the strength of selectivity. These results argue against a purely feed-forward explanation of recognition from partial information, and provide spatiotemporal constraints on theories of object recognition that involve recurrent processing.

The response of a neuron in the visual cortex to stimuli of different contrast placed in its receptive field is commonly characterized using the contrast response curve. When attention is directed into the receptive field of a V4 neuron, its contrast response curve is shifted to lower contrast values (Reynolds et al., 2000). The neuron will thus be able to respond to weaker stimuli than it responded to without attention. Attention also increases the coherence between neurons responding to the same stimulus (Fries et al., 2001). We studied how the firing rate and synchrony of a densely interconnected cortical network varied with contrast and how they were modulated by attention. The changes in contrast and attention were modeled as changes in driving current to the network neurons. We found that an increased driving current to the excitatory neurons increased the overall firing rate of the network, whereas variation of the driving current to inhibitory neurons modulated the synchrony of the network. We explain the synchrony modulation in terms of a locking phenomenon during which the ratio of excitatory to inhibitory firing rates is approximately constant for a range of driving current values. We explored the hypothesis that contrast is represented primarily as a drive to the excitatory neurons, whereas attention corresponds to a reduction in driving current to the inhibitory neurons. Using this hypothesis, the model reproduces the following experimental observations: (1) the firing rate of the excitatory neurons increases with contrast; (2) for high contrast stimuli, the firing rate saturates and the network synchronizes; (3) attention shifts the contrast response curve to lower contrast values; (4) attention leads to stronger synchronization that starts at a lower value of the contrast compared with the attend-away condition. In addition, it predicts that attention increases the delay between the inhibitory and excitatory synchronous volleys produced by the network, allowing the stimulus to recruit more downstream neurons.

Receptive fields of neurons in cortical area V4 are large enough to fit multiple stimuli, making V4 the ideal place to study the effects of selective attention at the single-neuron level. Experiments have revealed evidence for stimulus competition and have characterized the effect thereon of spatial and feature-based attention. We developed a biophysical model with spiking neurons and conductance-based synapses. To account for the comprehensive set of experimental results, it was necessary to include in the model, in addition to regular spiking excitatory (E) cells, two types of interneurons: feedforward interneurons (FFI) and top-down interneurons (TDI). Feature-based attention was mediated by a projection of the TDI to the FFI, stimulus competition was mediated by a cross-columnar excitatory connection to the FFI, whereas spatial attention was mediated by an increase in activity of the feedforward inputs from cortical area V2. The model predicts that spatial attention increases the FFI firing rate, whereas feature-based attention decreases the FFI firing rate and increases the TDI firing rate. During strong stimulus competition, the E cells were synchronous in the beta frequency range (15-35 Hz), but with feature-based attention, they became synchronous in the gamma frequency range (35-50 Hz). We propose that the FFI correspond to fast-spiking, parvalbumin-positive basket cells and that the TDI correspond to cells with a double-bouquet morphology that are immunoreactive to calbindin or calretinin. Taken together, the model results provide an experimentally testable hypothesis for the behavior of two interneuron types under attentional modulation.

The quantum transport properties of the ultrathin silver nanowires are investigated. For a perfect crystalline nanowire with four atoms per unit cell, three conduction channels are found, corresponding to three s bands crossing the Fermi level. One conductance channel is disrupted by a single-atom defect, either adding or removing one atom. Quantum interference effect leads to oscillation of conductance versus the inter-defect distance. In the presence of multiple-atom defect, one conduction channel remains robust at Fermi level regardless the details of defect configuration. The histogram of conductance calculated for a finite nanowire (seven atoms per cross section) with a large number of random defect configurations agrees well with recent experiment.PACS: 73.63. Nm, 61.46.+w In recent years, metallic nanowires are of great interest as building blocks for nanoelectronic devices. Since the dimension of the metallic nanowires is comparable to the electron Fermi wavelength, the conductance is quantized in units ofThe number of conductance channels is determined by the number of electronic bands crossing the Fermi level (E F ) and sensitively depends on the nanowire geometry. The effect of conductance quantization and the related high sensitivity lead to potential applications such as single-atom switch [4], conductor [5,6], and chemical sensor [7].Most earlier works on the quantum conductance of metallic nanowires are based on the point contacts formed between metal electrodes [1]. With mechanically controllable break junctions [8,9] or tip-surface contact [10,11,12,13] techniques, the statistical histograms of the conductance value for large number of contacts have been recorded. However, the metallic nanowires obtained from nanoscale contact are limited by the short length and structural instability for practical applications. Other fabricating methods, such as reduction of metal compounds [14], ions irradiation [15], carbon nanotubes capillary growth [16,17,18], and template-aid synthesis [19,20] have been introduced to generate much longer nanowires with well-defined structures. Understanding the transport properties of these long and nearly freestanding metallic nanowires are important for their future applications in nanoelectronics. Recently, Kim's group has successfully obtained ultrathin single-crystalline silver nanowire arrays [20]. The silver nanowires with 0.4 nm width (only four atoms on the cross section) and µm-scale length are grown inside the pores of organic templates. In this letter, we investigate the transport properties of the ultrathin silver nanowires and discussed the effect of defects on the conductances.The geometry optimization for the silver nanowires are performed by using ab initio plane-wave ultrasoft pseudopotential method [21]. Both atomic positions and cell parameters for the nanowires (perfect crystalline or with structural defects) were fully relaxed at level of local density approximation (LDA). We adopt the initial configurations proposed in Ref. [20], that is, fcc-like...