Neural Resolution of Formant Frequencies in the Primary Auditory Cortex of Rats.

Pulse-resonance sounds play an important role in animal communication and auditory object recognition, yet very little is known about the cortical representation of this class of sounds. In this study we shine light on one simple aspect: how well does the firing rate of cortical neurons resolve resonant ("formant") frequencies of vowel-like pulse-resonance sounds. We recorded neural responses in the primary auditory cortex (A1) of anesthetized rats to two-formant pulse-resonance sounds, and estimated their formant resolving power using a statistical kernel smoothing method which takes into account the natural variability of cortical responses. While formant-tuning functions were diverse in structure across different penetrations, most were sensitive to changes in formant frequency, with a frequency resolution comparable to that reported for rat cochlear filters.

Sound sensitivity of neurons in rat hippocampus during performance of a sound-guided task.

To investigate how hippocampal neurons encode sound stimuli, and the conjunction of sound stimuli with the animal's position in space, we recorded from neurons in the CA1 region of hippocampus in rats while they performed a sound discrimination task. Four different sounds were used, two associated with water reward on the right side of the animal and the other two with water reward on the left side. This allowed us to separate neuronal activity related to sound identity from activity related to response direction. To test the effect of spatial context on sound coding, we trained rats to carry out the task on two identical testing platforms at different locations in the same room. Twenty-one percent of the recorded neurons exhibited sensitivity to sound identity, as quantified by the difference in firing rate for the two sounds associated with the same response direction. Sensitivity to sound identity was often observed on only one of the two testing platforms, indicating an effect of spatial context on sensory responses. Forty-three percent of the neurons were sensitive to response direction, and the probability that any one neuron was sensitive to response direction was statistically independent from its sensitivity to sound identity. There was no significant coding for sound identity when the rats heard the same sounds outside the behavioral task. These results suggest that CA1 neurons encode sound stimuli, but only when those sounds are associated with actions.

Faces in the cloud: Fourier power spectrum biases ultrarapid face detection.

Recent results show that humans can respond with a saccadic eye movement toward faces much faster and with less error than toward other objects. What feature information does your visual cortex need to distinguish between different objects so rapidly? In a first step, we replicated the "fast saccadic bias" toward faces. We simultaneously presented one vehicle and one face image with different contrasts and asked our subjects to saccade as fast as possible to the image with higher contrast. This was considerably easier when the target was the face. In a second step, we scrambled both images to the same extent. For one subject group, we scrambled the orientations of wavelet components (local orientations) while preserving their location. This manipulation completely abolished the face bias for the fastest saccades. For a second group, we scrambled the phases (i.e., the location) of Fourier components while preserving their orientation (i.e., the 2-D amplitude spectrum). Even when no face was visible (100% scrambling), the fastest saccades were still strongly biased toward the scrambled face image! These results suggest that the ability to rapidly saccade to faces in natural scenes depends, at least in part, on low-level information contained in the Fourier 2-D amplitude spectrum.

What's color got to do with it? The influence of color on visual attention in different categories.

Certain locations attract human gaze in natural visual scenes. Are there measurable features, which distinguish these locations from others? While there has been extensive research on luminance-defined features, only few studies have examined the influence of color on overt attention. In this study, we addressed this question by presenting color-calibrated stimuli and analyzing color features that are known to be relevant for the responses of LGN neurons. We recorded eye movements of 15 human subjects freely viewing colored and grayscale images of seven different categories. All images were also analyzed by the saliency map model (L. Itti, C. Koch, & E. Niebur, 1998). We find that human fixation locations differ between colored and grayscale versions of the same image much more than predicted by the saliency map. Examining the influence of various color features on overt attention, we find two extreme categories: while in rainforest images all color features are salient, none is salient in fractals. In all other categories, color features are selectively salient. This shows that the influence of color on overt attention depends on the type of image. Also, it is crucial to analyze neurophysiologically relevant color features for quantifying the influence of color on attention.