Jungah Lee

How the brain preserves information about multiple simultaneous items is poorly understood. We report that single neurons can represent multiple stimuli by interleaving signals across time. We record single units in an auditory region, the inferior colliculus, while monkeys localize 1 or 2 simultaneous sounds. During dual-sound trials, we find that some neurons fluctuate between firing rates observed for each single sound, either on a whole-trial or on a sub-trial timescale. These fluctuations are correlated in pairs of neurons, can be predicted by the state of local field potentials prior to sound onset, and, in one monkey, can predict which sound will be reported first. We find corroborating evidence of fluctuating activity patterns in a separate dataset involving responses of inferotemporal cortex neurons to multiple visual stimuli. Alternation between activity patterns corresponding to each of multiple items may therefore be a general strategy to enhance the brain processing capacity, potentially linking such disparate phenomena as variable neural firing, neural oscillations, and limits in attentional/memory capacity.

How the brain preserves information about multiple simultaneous items is poorly understood. We report that single neurons can represent multiple different stimuli by interleaving different signals across time. We record single units in an auditory region, the inferior colliculus, while monkeys localize 1 or 2 simultaneous sounds. During dual-sound trials, we find that some neurons fluctuate between firing rates observed for each single sound, either on a whole-trial or on a sub-trial timescale. These fluctuations are correlated in pairs of neurons, can be predicted by the state of local field potentials prior to sound onset, and, in one monkey, can predict which sound will be reported first. We find corroborating evidence of fluctuating activity patterns in a separate data set involving responses of inferotemporal cortex neurons to multiple visual stimuli. Alternation between activity patterns corresponding to each of multiple items may therefore be a general strategy to enhance the brain processing capacity, potentially linking such disparate phenomena as variable neural firing, neural oscillations, and limits in attentional/memory capacity.

Maps are a mainstay of visual, somatosensory, and motor coding in many species. However, auditory maps of space have not been reported in the primate brain. Instead, recent studies have suggested that sound location may be encoded via broadly responsive neurons whose firing rates vary roughly proportionately with sound azimuth. Within frontal space, maps and such rate codes involve different response patterns at the level of individual neurons. Maps consist of neurons exhibiting circumscribed receptive fields, whereas rate codes involve open-ended response patterns that peak in the periphery. This coding format discrepancy therefore poses a potential problem for brain regions responsible for representing both visual and auditory information. Here, we investigated the coding of auditory space in the primate superior colliculus(SC), a structure known to contain visual and oculomotor maps for guiding saccades. We report that, for visual stimuli, neurons showed circumscribed receptive fields consistent with a map, but for auditory stimuli, they had open-ended response patterns consistent with a rate or level-of-activity code for location. The discrepant response patterns were not segregated into different neural populations but occurred in the same neurons. We show that a read-out algorithm in which the site and level of SC activity both contribute to the computation of stimulus location is successful at evaluating the discrepant visual and auditory codes, and can account for subtle but systematic differences in the accuracy of auditory compared to visual saccades. This suggests that a given population of neurons can use different codes to support appropriate multimodal behavior.

A computational hurdle in multisensory integration is that visual and auditory signals potentially have different representational formats. In the early visual pathway, neurons have receptive fields that tile the visual scene and produce a "place code" for stimulus location. In contrast, the binaural computation performed in the auditory pathway has been suggested to produce a "rate code" for sound location. In this latter format, neurons in the IC and auditory cortex respond to a broad range of locations with activity levels that scale proportionate with sound position, exhibiting maximum responses to sounds at extreme contralateral positions (Groh JM et al., 2003; Werner-Reiss U and Groh JM, 2008), The superior colliculus (SC) has been thought to employ a place code for sensory and saccade-related activity, with the same neurons controlling auditory as well as visual saccades. However, there is little quantitative information addressing the coding of sound location in monkey SC. Here, we examined individual auditory neuron in the primate SC to determine whether they have receptive field (place code) or monotonic spatial pattern (rate code). A monotonic code for sound location would mean a discrepancy between visual and auditory processing in the SC. We recorded sensory and saccade-related activity from 180 neurons in the intermediate and deep SC of two rhesus monkeys. Noise bursts or LED came from one of 9 locations between +/- 24 degrees in the horizontal dimension. The monkeys made saccades from different initial eye positions to these visual or auditory targets in an overlap saccade task. To quantify the representational format, we fit each neuron’s response functions to gaussian and sigmoid curves. The idea was that gaussian functions would be substantially better than sigmoids at fitting the tuned response patterns characteristic of a place code, but that both sigmoid and broad half-gaussians would be equally successful at fitting the monotonic tuning patterns characteristic of a rate code. We found that most neurons had monotonic response patterns for auditory stimuli along the axis of the contralateral ear, even though the same neurons had non-monotonic response patterns to visual stimuli. For the auditory trials, the sigmoid functions were as good as gaussians at capturing the response patterns. For visual trials, the gaussian functions showed significantly better performance than sigmoids in fitting the tuning curves. This pattern was true for both sensory and saccade-related activity. Our findings imply that a read-out algorithm is required to reconcile the discrepancy. The algorithm should be able to convert the visual and auditory signals into a motor command to work on either place or rate code to produce the same accurate saccade for both types of signals. In line with this, we have developed several models that involve transformation of signals from a place code to a rate or vice-versa (Groh and Sparks, 1992; Groh, 2001; Porter and Groh, 2006). Acknowledgements: This work was supported by CRCNS grants [R01 NS50942]. JAL was also supported by the Korea Research Foundation Grant funded by the Korean Government [KRF-2008-356-H00003].