Biomedical subjects
Publications and source records attributed to Gregor Rainer.
Faces convey a great variety of information, for example about the species, gender, age, identity and even mood or intentions. A recent study sheds light on the neural mechanisms for encoding a face's gaze direction.
Neurons in the inferior temporal (IT) cortex respond selectively to complex objects, and maintain their selectivity despite partial occlusion. However, relatively little is known about how the occlusion of different shape parts influences responses in the IT cortex. Here, we determine experimentally which parts of complex objects monkeys are relying on in a discrimination task. We then study the effect of occlusion of parts with different behavioral relevance on neural responses in the IT cortex at the level of spiking activity and local field potentials (LFPs). For both spiking activity and LFPs, we found that the diagnostic object parts, which were important for behavioral judgments, were preferentially represented in the IT cortex. Our data show that the effects of diagnosticity grew systematically stronger along a posterior-anterior axis for LFPs, but were evenly distributed for single units, suggesting that diagnosticity is first encoded in the posterior IT cortex. Our findings highlight the power of combined analysis of field potentials and spiking activity for mapping structure to computational function in the brain.
By learning to discriminate among visual stimuli, human observers can become experts at specific visual tasks. The same is true for Rhesus monkeys, the major animal model of human visual perception. Here, we systematically compare how humans and monkeys solve a simple visual task. We trained humans and monkeys to discriminate between the members of small natural-image sets. We employed the "Bubbles" procedure to determine the stimulus features used by the observers. On average, monkeys used image features drawn from a diagnostic region covering about 7% +/- 2% of the images. Humans were able to use image features drawn from a much larger diagnostic region covering on average 51% +/- 4% of the images. Similarly for the two species, however, about 2% of the image needed to be visible within the diagnostic region on any individual trial for correct performance. We characterize the low-level image properties of the diagnostic regions and discuss individual differences among the monkeys. Our results reveal that monkeys base their behavior on confined image patches and essentially ignore a large fraction of the visual input, whereas humans are able to gather visual information with greater flexibility from large image regions.
Working memory has been linked to elevated single neuron discharge in monkeys and to oscillatory changes in the human EEG, but the relation between these effects has remained largely unexplored. We addressed this question by measuring local field potentials and single unit activity simultaneously from multiple electrodes placed in extrastriate visual cortex while monkeys were performing a working memory task. We describe a significant enhancement in theta band energy during the delay period. Theta oscillations had a systematic effect on single neuron activity, with neurons emitting more action potentials near their preferred angle of each theta cycle. Sample-selective delay activity was enhanced if only action potentials emitted near the preferred theta angle were considered. Our results suggest that extrastriate visual cortex is involved in short-term maintenance of information and that theta oscillations provide a mechanism for structuring the recurrent interaction between neurons in different brain regions that underlie working memory.
One of the most remarkable capabilities of the adult brain is its ability to learn and continuously adapt to an ever-changing environment. While many studies have documented how learning improves the perception and identification of visual stimuli, relatively little is known about how it modifies the underlying neural mechanisms. We trained monkeys to identify natural images that were degraded by interpolation with visual noise. We found that learning led to an improvement in monkeys' ability to identify these indeterminate visual stimuli. We link this behavioral improvement to a learning-dependent increase in the amount of information communicated by V4 neurons. This increase was mediated by a specific enhancement in neural activity. Our results reveal a mechanism by which learning increases the amount of information that V4 neurons are able to extract from the visual environment. This suggests that V4 plays a key role in resolving indeterminate visual inputs by coordinated interaction between bottom-up and top-down processing streams.
The ability to detect and respond to novel events is crucial for survival in a rapidly changing environment. Four decades of neuroscientific research has begun to delineate the neural mechanisms by which the brain detects and responds to novelty. Here, we review this research and suggest how changes in neural processing at the cellular, synaptic and network levels allow us to detect, attend to and subsequently remember the occurrence of a novel event.
We have investigated BOLD signal changes associated with scrambling natural images into different numbers of segments in visually modulated regions of the macaque monkey (macacca mulatta) brain. For 10 degrees x 10 degrees images, we observed that BOLD activity in primary visual cortex (V1) increased with scrambling, and then dramatically dropped for very highly scrambled images (128 x 128 segments). In extrastriate visual areas, BOLD signal levels did not distinguish between natural images and scrambled images, except that as in V1 very highly scrambled images led to a drop in BOLD activity. Finally in the superior temporal sulcus region and inferior temporal cortex, BOLD activity decreased systematically with scrambling. Our results are consistent with the view that the BOLD signal might reflect average activation of local orienation detectors in V1, and sensitivity to more global object representations in higher visual areas. In addition, we quantify the effects of scrambling on the Fourier amplitude spectrum of the images. This analysis shows that scrambling causes substantial changes to the spatial frequency content of images. This suggests that low-level accounts for reduced BOLD activation in higher visual areas cannot be completely ruled out based on scrambling data.
We studied the timecourse of neural activity in the primate (Macacca mulatta) prefrontal (PF) cortex during an object delayed-matching-to-sample (DMS) task. To assess the effects of experience on this timecourse, we conducted the task using both novel and highly familiar objects. In addition, noise patterns containing no task-relevant information were used as samples on some trials. Comparison of average PF ensemble activity relative to baseline activity generated by objects and noise patterns revealed three distinct activity periods. (i) Sample onset elicited a transient sensory visual response. In this sensory period, novel objects elicited stronger average ensemble activity than both familiar objects and noise patterns. (ii) An intermediate period of elevated activity followed, which began before sample offset, and continued well into the delay period. In the intermediate period, activity was elevated for noise patterns and novel objects, but near baseline for familiar objects. (iii) Finally, after average ensemble activity reached baseline activity at the end of the intermediate period, a reactivation period occurred late in the delay. Experience had little effect during reactivation, where activity was elevated for both novel and familiar objects compared to noise patterns. We show that the ensemble average resembles the activity timecourse of many single prefrontal neurons. These results suggest that PF delay activity does not merely maintain recent sensory input, but is subject to more complex experience-dependent dynamics. This has implications for how delay activity is generated and maintained.
The prefrontal cortex is an area of high-level association cortex that plays an important part in the processing of visual objects. In this update, we summarize recent experimental findings that have investigated object processing in the frontal cortex in monkeys and humans. We highlight several common themes that have emerged from the study of these different systems, including the short-term maintenance of object information in working memory and the processing of novel information. Together, these findings suggest that regions of the prefrontal cortex participate in the selection, maintenance, and evaluation of task-relevant attributes. At a larger level, the convergence of findings from monkey and human studies demonstrates that concurrent investigation of scientific questions in both species can be a fruitful approach and promises to lead to future advances.