1. The role of subcortical brain structures in the control of spatial attention and visual selection in non-human primates Recent findings demonstrate that the control of attention is not limited to the cortex but also includes the SC. We have found that reversible inactivation of the primate SC causes major deficits in performance on selective attention tasks. The effects resemble visual extinction: monkeys mostly ignored cued signals in the inactivated region when they competed with misinformative foil signals placed elsewhere, but discrimination ability was largely intact when stimuli appeared alone in the affected region. These findings demonstrate that SC activity can play a major causal role in the control of covert selective attention, but the detailed circuits and neural algorithms involved are not yet understood. We are investigating the mechanisms underlying the deficits in visual attention caused by SC inactivation. Our central hypothesis is that activity in the SC acts to weight the priority of stimuli at different locations. This weighting could be achieved by altering neuronal activity in cortical areas for instance, by enhancing sensory processing of the corresponding visual signals or regulating how these signals are pooled during the formation of perceptual judgments. During the past year, we have made progress on two fronts: Identifying the impact of SC inactivation on visual sensory responses in cortex The deficits in visual selection caused by SC inactivation could be associated with changes in signal processing in several different brain regions visual cortical areas, prefrontal cortex, parietal lobe, thalamus, and basal ganglia are among the reasonable candidates. Of these, we thought that investigating the middle temporal area (MT) and medial superior temporal area (MST) would be the most informative to investigate first, because these areas are crucial for processing the visual motion signals whose discrimination is affected in our task, and they both show robust modulation with selective attention. The strategy of these experiments was to record from neurons in cortical areas MT and MST before and after SC inactivation and characterize any changes in their response properties. We systematically tested whether there were changes in any of the key features of neural activity that have been associated with selective attention. Because these neural measurements will be made as the monkey performs a selective attention task, before and after SC inactivation, the deficits in performance served as positive controls, allowing us to draw strong conclusions whether or not particular changes occur. We found that during SC inactivation, the enhanced responses of neurons in MT and MST to attended stimuli were preserved despite large behavioral impairments in a covert attention task. Moreover, the attention deficit induced by SC inactivation not only preserved the cue-related changes in visual responses, it also left intact the other known correlates of attention in visual cortex: the ability of neurons to discriminate cued from uncued spatial locations, the reliability of neuronal discharge (i.e. Fano factor), and cue-related changes in noise correlations between neurons. These effects cannot be explained by a sensory impairment, because previous studies have shown that attention deficits during SC inactivation are not caused by changes in local motion perception4. The effects also cannot be explained by a motor deficit, because the single-button response in our task was unimpaired for stimuli outside the affected region of the visual field. These results are currently in press for Nature. Identifying the impact of SC inactivation on activity in cortical salience maps Now that we have found that SC inactivation has little or no effect on the cue-related changes of activity in motion processing areas of cortex, it is logical to test whether the effects take place at stages downstream of MT and MST. Among the candidate areas, we think that the frontal eye fields (FEF) is the next logical area to investigate, because of its well-established roles as possible salience maps for the control of attention, its role in representing decision variables during decision-making, and its anatomical connections with the SC and sensory areas involved in motion processing. The physiology phase of these experiments has not yet begun, but during the past year we have prepared one non-human primate subject for the experiments, with most of the time taken up with behavioral training on the task. The strategy of these experiments will be to record from neurons in cortical area FEF and characterize any changes in their activity caused by SC inactivation. By using the same experimental approach and task design as in our other experiments, our results from FEF will be directly comparable to what we found in MT/MST, and will provide new insights into the underlying mechanisms. 2. Sensory-motor decision-making in mice Current studies of sensory-motor functions are most often conducted in non-human primates, in which it is relatively difficult to apply targeted genetic, cellular and molecular manipulations. Consequently, another major effort in the lab is to study sensory decision-making in normal and genetically altered mice, using a combination of psychophysical, physiological, molecular and computational approaches. The basic design is to have mice lick or not lick, based on the properties of visual motion stimuli presented. Mice will be head-fixed and positioned beside a pair of flat-panel display screens, and will extend their tongues to reach the spout (detected by a lickometer sensor). Mice will be trained to lick for some visual stimuli and to avoid licking for others. Although the visual acuity of mice is much poorer than primates, they can detect visual motion readily when the stimulus is scaled appropriately. The mouses response will be detected by the lickometer and determine whether or not they receive a small fluid reinforcement. Because the head of the mouse is fixed in place, neuronal activity can be recorded or manipulated, either electrically or optically. During the past year, we have designed and built the experimental apparatus. There were several major problems that had to be solved, including: providing a secure and reproducible method for positioning the mouse with respect to the visual displays, adding sound-proofing so that the mice will not be distracted by irrelevant ambient noises, including a ventilation system so that the heat from the displays and the animal can be drawn off to prevent over-heating. Now that the apparatus is ready, we will begin to quantify how well mice learn and perform the decision task. If successful, we will be able to characterize the performance of mice using the same computational models of decision-making used with human and non-human primates, before moving on to using electrophysiological and optogenetic techniques to probe neuronal activity in the SC as mice perform the task, similar to what we have done in non-human primates, but taking advantage of the more precise cellular targeting that is possible in mice.
| Wang, Lupeng; Krauzlis, Richard J (2018) Visual Selective Attention in Mice. Curr Biol 28:676-685.e4 |
| Krauzlis, Richard J; Bogadhi, Amarender R; Herman, James P et al. (2018) Selective attention without a neocortex. Cortex 102:161-175 |
| Bollimunta, Anil; Bogadhi, Amarender R; Krauzlis, Richard J (2018) Comparing frontal eye field and superior colliculus contributions to covert spatial attention. Nat Commun 9:3553 |
| Wang, Lupeng; Rangarajan, Krsna V; Gerfen, Charles R et al. (2018) Activation of Striatal Neurons Causes a Perceptual Decision Bias during Visual Change Detection in Mice. Neuron 97:1369-1381.e5 |
| Krauzlis, Richard J; Goffart, Laurent; Hafed, Ziad M (2017) Neuronal control of fixation and fixational eye movements. Philos Trans R Soc Lond B Biol Sci 372: |
| Lovejoy, Lee P; Krauzlis, Richard J (2017) Changes in perceptual sensitivity related to spatial cues depends on subcortical activity. Proc Natl Acad Sci U S A 114:6122-6126 |
| Herman, James P; Krauzlis, Richard J (2017) Color-Change Detection Activity in the Primate Superior Colliculus. eNeuro 4: |
| Rucci, Michele; McGraw, Paul V; Krauzlis, Richard J (2016) Fixational eye movements and perception. Vision Res 118:1-4 |
| Herman, James P; Bogadhi, Amarender R; Krauzlis, Richard J (2015) Effects of spatial cues on color-change detection in humans. J Vis 15:3 |
| Perrone, John A; Krauzlis, Richard J (2014) Simulating component-to-pattern dynamic effects with a computer model of middle temporal pattern neurons. J Vis 14: |
Showing the most recent 10 out of 24 publications
