Modeling Multisensory Enhancement with Self-organizing Maps

Self-organization, a process by which the internal organization of a system changes without supervision, has been proposed as a possible basis for multisensory enhancement (MSE) in the superior colliculus (Anastasio and Patton, 2003). We simplify and extend these results by presenting a simulation using traditional self-organizing maps, intended to understand and simulate MSE as it may generally occur throughout the central nervous system. This simulation of MSE: (1) uses a standard unsupervised competitive learning algorithm, (2) learns from artificially generated activation levels corresponding to driven and spontaneous stimuli from separate and combined input channels, (3) uses a sigmoidal transfer function to generate quantifiable responses to separate inputs, (4) enhances the responses when those same inputs are combined, (5) obeys the inverse effectiveness principle of multisensory integration, and (6) can topographically congregate MSE in a manner similar to that seen in cortex. Thus, the model provides a useful method for evaluating and simulating the development of enhanced interactions between responses to different sensory modalities

Asymmetric multisensory interactions of visual and somatosensory responses in a region of the rat parietal cortex

Perception greatly benefits from integrating multiple sensory cues into a unified percept. To study the neural mechanisms of sensory integration, model systems are required that allow the simultaneous assessment of activity and the use of techniques to affect individual neural processes in behaving animals. While rodents qualify for these requirements, little is known about multisensory integration and areas involved for this purpose in the rodent. Using optical imaging combined with laminar electrophysiological recordings, the rat parietal cortex was identified as an area where visual and somatosensory inputs converge and interact. Our results reveal similar response patterns to visual and somatosensory stimuli at the level of current source density (CSD) responses and multi-unit responses within a strip in parietal cortex. Surprisingly, a selective asymmetry was observed in multisensory interactions: when the somatosensory response preceded the visual response, supra-linear summation of CSD was observed, but the reverse stimulus order resulted in sub-linear effects in the CSD. This asymmetry was not present in multi-unit activity however, which showed consistently sub-linear interactions. These interactions were restricted to a specific temporal window, and pharmacological tests revealed significant local intra-cortical contributions to this phenomenon. Our results highlight the rodent parietal cortex as a system to model the neural underpinnings of multisensory processing in behaving animals and at the cellular level

Cortical And Subcortical Mechanisms For Sound Processing

The auditory cortex is essential for encoding complex and behaviorally relevant sounds. Many questions remain concerning whether and how distinct cortical neuronal subtypes shape and encode both simple and complex sound properties. In chapter 2, we tested how neurons in the auditory cortex encode water-like sounds perceived as natural by human listeners, but that we could precisely parametrize. The stimuli exhibit scale-invariant statistics, specifically temporal modulation within spectral bands scaled with the center frequency of the band. We used chronically implanted tetrodes to record neuronal spiking in rat primary auditory cortex during exposure to our custom stimuli at different rates and cycle-decay constants. We found that, although neurons exhibited selectivity for subsets of stimuli with specific statistics, over the population responses were stable. These results contribute to our understanding of how auditory cortex processes natural sound statistics. In chapter 3, we review studies examining the role of different cortical inhibitory interneurons in shaping sound responses in auditory cortex. We identify the findings that support each other and the mechanisms that remain unexplored. In chapter 4, we tested how direct feedback from auditory cortex to the inferior colliculus modulated sound responses in the inferior colliculus. We optogenetically activated or suppressed cortico-collicular feedback while recording neuronal spiking in the mouse inferior colliculus in response to pure tones and dynamic random chords. We found that feedback modulated sound responses by reducing sound selectivity by decreasing responsiveness to preferred frequencies and increasing responsiveness to less preferred frequencies. Furthermore, we tested the effects of perturbing intra-cortical inhibitory-excitatory networks on sound responses in the inferior colliculus. We optogenetically activated or suppressed parvalbumin-positive (PV) and somatostatin-positive (SOM) interneurons while recording neuronal spiking in mouse auditory cortex and inferior colliculus. We found that modulation of neither PV- nor SOM-interneurons affected sound-evoked responses in the inferior colliculus, despite significant modulation of cortical responses. Our findings imply that cortico-collicular feedback can modulate responses to simple and complex auditory stimuli independently of cortical inhibitory interneurons. These experiments elucidate the role of descending auditory feedback in shaping sound responses. Together these results implicate the importance of the auditory cortex in sound processing

Identifying functional roles of neural circuits in two primary auditory cortices

During sound perception, auditory signals have to travel a long way from the cochlea, through the subcortical areas, up to the auditory cortex. How each nucleus on this pathway - especially in the central auditory system - contributes to making sense of the acoustic world is far from understood. In the rodent auditory system, the primary cortex is subdivided into two regions, both receiving direct inputs from the auditory thalamus: the primary auditory cortex (A1) and the anterior auditory field (AAF). To deepen our general knowledge of auditory cortical processing, we studied what sound features are preferentially represented by primary auditory cortices, the spatial organization of these preferences, and their possible perceptual role. Using in vivo electrophysiological recordings in the mouse auditory cortex, we found that AAF neurons have significantly stronger responses to tone offset than A1 neurons. These results emphasize the potentially critical role of AAF for temporal processing. By combining electrophysiological recordings in AAF and auditory thalamus with antidromic stimulation, we revealed that cortical offset responses are inherited from the periphery, amplified, and generated de novo. Preventing offset responses in animals performing sound termination detection task decreased their ability to detect that the sound stopped, confirming the relevance of cortical auditory offset responses at the behavioral level. Additionally, by studying responses in A1 and AAF evoked by sounds with different spectral complexity, we found that responses in A1, but not in AAF, are influenced by the spectral complexity of the sound, suggesting that A1 is predominantly enrolled in the spectral processing. Our findings open new vistas into understanding the functional roles of A1 and AAF and more general auditory cortex in sound processing and perception. Identifying the specific functions of auditory cortical circuits paves the way for future understanding of the mechanisms behind impairments in spectral or temporal processing arising from both aging and disease

Cortical Mechanisms Of Adaptation In Auditory Processing

Adaptation is computational strategy that underlies sensory nervous systems’ ability to accurately encode stimuli in various and dynamic contexts and shapes how animals perceive their environment. Many questions remain concerning how adaptation adjusts to particular stimulus features and its underlying mechanisms. In Chapter 2, we tested how neurons in the primary auditory cortex adapt to changes in stimulus temporal correlation. We used chronically implanted tetrodes to record neuronal spiking in rat primary auditory cortex during exposure to custom made dynamic random chord stimuli exhibiting different levels of temporal correlation. We estimated linear non-linear model for each neuron at each temporal correlation level, finding that neurons compensate for temporal correlation changes through gain-control adaptation. This experiment extends our understanding of how complex stimulus statistics are encoded in the auditory nervous system. In Chapter 3 and 4, we tested how interneurons are involved in adaptation by optogenetically suppressing parvalbumin-positive (PV) and somatostatin-positive (SOM) interneurons during tone train stimuli and using silicon probes to record neuronal spiking in mouse primary auditory cortex. In Chapter 3, we found that inhibition from both PVs and SOMs contributes to stimulus-specific adaptation (SSA) through different mechanisms. SOM inhibition was stimulus-specific, suppressing responses to standard tones more strongly than responses to deviant tones, and increasing with standard tone repetition. PVs amplified SSA because inhibition was similar for standard and deviant tones and PV mediated inhibition was insensitive to tone repetition. PVs and SOMs themselves exhibit SSA, and a Wilson-Cowan dynamic model identified that PVs and SOMs can directly contribute to SSA in pyramidal neurons. In Chapter 4, we tested how SOMs and PVs inhibition is modulated with the dynamics of adaptation and across frequency tuning, during exposure to single frequency tone trains across the neuron’s tuning curve. We found that the magnitude of SOM inhibition correlated with the magnitude of adaptive suppression, while PVs inhibition was largely insensitive to stimulus conditions. Together Chapters 3 and 4 implicate SOM inhibition in actively suppressing responses in a stimulus-specific manner while PV inhibition may passively enhance stimulus-specific suppression. These experiments inform the underlying principles and mechanisms of cortical sensory adaptation

Functional role of the Oc2M cortical area in the processing of multimodal sensory inputs in rats

Tese de mestrado, Neurociências, Universidade de Lisboa, Faculdade de Medicina, 2020Quase todos os organismos dotados de um sistema nervoso são confrontados, diariamente, com uma grande variedade de estímulos sensoriais. A forma como os animais (humanos e não-humanos) interagem com o mundo externo, está dependente da capacidade de integração das várias informações sensoriais em seu redor. Esta integração permite formar uma percepção coesa do ambiente envolta, como também possibilita a extração de informação relevante para tomar decisões comportamentais adequadas. Por outro lado, os sistemas sensoriais não processam informação isoladamente, e o conteúdo multissensorial presente nas nossas memórias episódicas sugere que, de alguma forma, o processamento de estímulos sensoriais está intrinsecamente relacionado com a formação e armazenamento de memórias. O registo electrofisiológico in vivo da atividade neuronal em cérebros de modelos animais oferece a possibilidade de correlacionar a atividade cerebral detectada em específicas regiões do cérebro, com determinados outputs comportamentais. Este tipo experiências levaram à descoberta de células presentes no hipocampo, chamadas de ‘place cells’ (O’Keefe & Dostrovsky, 1971), que se acredita serem responsáveis pela formação de um mapa cognitivo que orienta a navegação no espaço (Keefe, 1976). Estas células podem representar não só a localização atual do animal, assim como localizações anteriores e futuras (Ferbinteanu & Shapiro, 2003; Frank, Brown, & Wilson, 2000). Mais tarde, a descoberta de neurónios com outras propriedades espaciais, tais como as ‘células- grelha’ (grid-cells, Hafting et al., 2005) células ‘head-direction’ (Sargolini et al., 2006) ou as células ‘border’ (Solstad, 2008), contribuíram para um maior entendimento acerca de como o cérebro codifica e organiza informação sensorial à sua volta, na forma de um mapa cognitivo espacial. Contudo, as regiões e os mecanismos subjacentes que levam à formação destes mapas cognitivos, com base na integração de estímulos sensoriais primários, ainda não são conhecidos. Este projeto explora a região anatómica no cérebro do rato, designada como Oc2M, como um possível local de convergência na integração de informação multimodal, crucial para a formação de memórias num contexto sensorial. Estudos anteriores mostraram que a região Oc2M, tradicionalmente considerada como uma região visual secundária, está de facto envolvida no processamento de estímulos visuais e auditivos, assim como na sua localização espacial. Para além disso, estudos recentes do nosso laboratório, revelaram que neurónios em Oc2M recebem projeções de todos os córtices sensoriais primários, alguns córtices sensoriais secundários, alguns núcleos do tálamo, e do hipocampo. Com base na utilização de ferramentas de optogenética para a estimulação in vitro dos inputs sinápticos em Oc2M, verificou-se que os córtices primários visual e auditivo estabelecem sinapses funcionais com a região Oc2M (Quintino & Remondes, 2017 não-publicado). Evidências preliminares do nosso laboratório de registos extracelulares in vivo da região Oc2M, mostraram que esta região responde a estímulos de som e luz, com uma distinta organização temporal (Cardoso & Remondes, 2017, não-publicado). Neste projeto começámos por desenvolver uma tarefa comportamental com o objectivo de captar – in vivo - a dependência funcional entre Oc2M e Hipocampo. Nestas tarefa os animais são colocados num labirinto, e são treinados para associar um determinado estímulo (componente sensorial) com uma específica trajetória (componente de memória). Os resultados comportamentais mostraram que dois, dos seis animais treinados, conseguiram aprender a tarefa. Estes mostraram uma progressão de aprendizagem linear ao longo do tempo, e conseguiram manter de forma consistente uma taxa de acerto acima de ‘chance level’ (probabilidade de acerto atribuída ao acaso) para cada uma das modalidades sensoriais. Estes animais foram depois sujeitos a um período de interrupção de 33 dias, para serem novamente treinados na tarefa, desta vez com a duração da pista sensorial reduzida para metade (500 milissegundos em vez de 1 segundo). Os ratos conseguiram não só reaprender a tarefa com um nível de dificuldade mais acentuado, assim como ambos precisaram de menos sessões para atingir as performances esperadas. Os registos eletrofisiológicos foram obtidos através de um dispositivo chamado ‘hyperdrive’. A ‘hyperdrive’ é uma estrutura com 30 tétrodos movíveis, construída no laboratório, e implantada no cérebro do rato através de uma cirurgia estereotáxica, com os vários tétrodos colocados nas regiões de interesse (neste caso, Oc2M e Hipocampo). Cada tétrodo é composto por quatro canais que registam de forma independente a atividade neuronal da região cerebral onde se encontram inseridos. Desta forma, para além de registarmos os valores correspondentes à voltagem extracelular de determinado local (sinal chamado de ‘local field potential’, LFP), conseguimos também identificar e isolar a atividade proveniente de diversos neurónios representativos do local de interesse, e correlacionar essa atividade com variáveis comportamentais. No presente trabalho apresentamos dados de eletrofisiologia in vivo de 2 ratos implantados, com registo da atividade em Oc2M e Hipocampo, em resposta a estímulos sensoriais num protocolo passivo de estimulação chamado de ‘Stimbox’. Neste paradigma experimental, os animais são colocados numa caixa (50 x 30 x 60 cm) onde são sujeitos a 3 condições diferentes de estimulação sensorial: som, luz, e som + luz em simultâneo. Análises realizadas ao LFP revelaram que, após a apresentação do estímulo, apenas as condições de luz e som + luz provocaram uma resposta evidente em ambas as áreas, Oc2M e Hipocampo. O facto de estas duas condições não terem apresentado respostas estatisticamente significativas entre si, sugere que apenas a estimulação visual foi responsável pelos transientes observados na atividade do LFP. Contudo, a identificação de subpopulações de neurónios em Oc2M, e a posterior análise aos potenciais de ação gerados com base na sua frequência de disparos, revelou a existência de células em Oc2M que respondem de forma distinta aos mesmos estímulos sensoriais. Ademais, as respostas observadas por neurónios em Oc2M em resposta à luz e à luz + som em simultâneo, mostraram-se significativamente diferentes, sugerindo assim um efeito modulatório do som na atividade de Oc2M, quando apresentado em combinação com um estímulo visual. Estes resultados suportam a hipótese de Oc2M como uma área de associação multissensorial, possível homólogo do córtex parietal posterior nos seres humanos. Embora não tenha sido possível realizar, planeamos como futuras experiências o registo simultâneo da atividade neuronal em Oc2M e Hipocampo com ratos a desempenhar a SCTAT. Tal irá ajudar-nos a perceber as computações subjacentes à integração de inputs sensoriais por parte do Oc2M, e como é que essa informação é transferida e utilizada pelo hipocampo numa tarefa de tomada- de-decisão perceptual. Outro objectivo futuro será a supressão seletiva da atividade celular em Oc2M durante sessões da SCTAT, recorrendo a técnicas da engenharia genética tais como chemogenetics (Armbruster et al., 2007) ou optogenética (Boyden et al., 2005). Estas experiências permitir-nos-ia testar, de forma causal, a hipótese de Oc2M como um local de convergência no processamento de informação sensorial relevante.The hippocampal system has long been associated with episodic memory. The discovery of place cells (O’Keefe & Dostrovsky, 1971) and entorhinal grid cells (Hafting et al., 2005) led to a major insight on how the brain encodes and organizes sensory information in the form of a spatial contextual map. However, little is known concerning the mechanisms underlying the integration of primary sensory stimuli in such a way as to convert it into the hippocampal spatial maps. Previous studies and preliminary data from our lab suggest that the cortical region of the rat’s brain Oc2M might play a critical role in the integration of multimodal sensory information in the service of spatial navigation. We established a behavioral task aimed to test the functional inter- dependency between Oc2M and Hippocampus. In the sensory-cue trajectory association task (SCTAT), rats are required to associate a particular sensory stimulus, sound or light, with a specific trajectory on a modified T-maze. Our results showed that 2 out of 6 animals were able to learn the SCTAT, having reached performance levels of above 80% for both sensory modalities. Additionally, after an interruption period of 33 days, we observed that these two rats were not only able to relearn the task with a shortened stimulus duration (500 milliseconds), but they also needed fewer sessions to achieve performances above chance level. An ‘hyperdrive’ array of 30 independently movable tetrodes was built and chronically implanted in the rat’s brain, targeted to Oc2M and Hippocampus. Each tetrode comprises four independent channels that record intra-cerebrally the extracellular electrical potential, which allow us to identify single neurons’ activity and correlate it with behavior. In the current work, we present in-vivo electrophysiological data from two implanted rats, regarding Oc2M and Hippocampus activity, in response to sensory cues in a passive-stimulation protocol called ‘Stimbox’. This protocol is composed by 3 sensory conditions: light stimulation, sound stimulation, and light and sound combined stimulation. Analyses of the local field potential (LFP) activity showed that, after stimulus onset, only light and sound + light conditions elicited a clear response in both Oc2M and Hippocampus. The fact the light and sound + light conditions were not significantly different, suggests that only light itself was responsible for the observed changes in LFP activity. However, we found neuronal ensembles in Oc2M that exhibited significantly different responses, in terms of firing rate, to the same sensory cues. Importantly, Oc2M neurons’ responses to light and sound + light cues were found to be different, thus suggesting a modulatory effect of the sound stimulus once paired with a light cue. Such supports the hypothesis of Oc2M as a multimodal association area, comparable to the human posterior parietal cortex. As future experiments, neuronal recordings of Oc2M and Hippocampus while rats perform the SCTAT would shed light on how Oc2M integrates sensory inputs, and how it conveys information to hippocampus in a perceptual decision- making task. Furthermore, the use of genetic tools to selectively suppress Oc2M’s cellular activity during the SCTAT, such as chemogenetic (Ambruster et al., 2007) or optogenetic (Boyden et al., 2005), would further lead to causally test our long-term hypothesis of Oc2M as a site of convergence to process sensory- relevant information

System Level Assessment of Motor Control through Patterned Microstimulation in the Superior Colliculus

We are immersed in an environment full of sensory information, and without much thought or effort we can produce orienting responses to appropriately react to different stimuli. This seemingly simple and reflexive behavior is accomplished by a very complicated set of neural operations, in which motor systems in the brain must control behavior based on populations of sensory information. The oculomotor or saccadic system is particularly well studied in this regard. Within a visual environment consisting of many potential stimuli, we control our gaze with rapid eye movements, or saccades, in order to foveate visual targets of interest. A key sub-cortical structure involved in this process is the superior colliculus (SC). The SC is a structure in the midbrain which receives visual input and in turn projects to lower-level areas in the brainstem that produce saccades. Interestingly, microstimulation of the SC produces eye movements that match the metrics and kinematics of naturally-evoked saccades. As a result, we explore the role of the SC in saccadic motor control by manually introducing distributions of activity through neural stimulation. Systematic manipulation of microstimulation patterns were used to characterize how ensemble activity in the SC is decoded to generate eye movements. Specifically, we focused on three different facets of saccadic motor control. In the first study, we examine the effective influence of microstimulation parameters on behavior to reveal characteristics of the neural mechanisms underlying saccade generation. In the second study, we experimentally verify the predictions of computational algorithms that are used to describe neural mechanisms for saccade generation. And in the third study, we assess where neural mechanisms for decoding occur within the oculomotor network in order to establish the order of operations necessary for saccade generation. The experiments assess different aspects of saccadic motor control, which collectively, reveal properties and mechanisms that contribute to the comprehensive understanding of signal processing in the oculomotor system

Genetic dissection of circuits underlying the modular structure of the Superior Colliculus

In order to successfully interact with the environment, animals need to produce accurate movements towards specific positions in space. A crucial region of the brain that guides such goal-oriented movements is the superior colliculus (SC), an evolutionary conserved structure of the midbrain. While several lines of research in different model organisms have confirmed that the SC contributes to the initiation of orienting movements, how functionally distinct neuronal groups within the SC are organized to support the production of such motor outputs is poorly understood. One of the reasons why the intrinsic circuit organization of the SC remains elusive is the lack of genetic characterization of the neuronal populations of the motor SC. Here, we performed RNAseq to screen for genetic markers for neuronal subpopulations in the motor SC. We identified a transcription factor, Pitx2, which is exclusively expressed in a subpopulation of glutamatergic neurons in the motor domain of the SC. Strikingly, this population of neurons displays a non-homogenous distribution within the motor layer of the SC, being organised in clusters along the mediolateral and anteroposterior axis. We mapped the pre-synaptic network and the post-synaptic targets of Pitx2ON neurons, unveiling that this modular population receives direct inputs from motor and sensory cortical regions, as well as several midbrain nuclei involved in movement control, and sends projection along the cephalomotor pathway. We then asked whether these modules may act as functional units, each integrating multimodal sensory information and encoding a specific feature of head movement, the main ethologically relevant orienting behaviour in rodents. Optogenetic activation of this modular population in freely moving animals produced a stereotyped, robust head motion characterised by a pronounced quantal nature; furthermore, the amplitude of the elicited head movement varied based on the modular unit activated. Our results suggest that distinct clusters of genetically defined neurons produce head displacement along a characteristic vector. In conclusion, we found that a population of premotor neurons in the SC is organised in a modular conformation and we suggest that such modularity may represent a physical implementation of a discontinuous motor map for orienting movements encoded in the mouse SC. Our work complements previous observations of periodicity in SC circuitry, as well as its afferent and efferent systems. Exploiting the genetic toolkit available in the mouse, our work begins to address the functional relevance of this modularity and paves the way for future experiments to investigate principles of sensorimotor integration in SC circuits.MR

Sensory integration model inspired by the superior colliculus for multimodal stimuli localization

Sensory information processing is an important feature of robotic agents that must interact with humans or the environment. For example, numerous attempts have been made to develop robots that have the capability of performing interactive communication. In most cases, individual sensory information is processed and based on this, an output action is performed. In many robotic applications, visual and audio sensors are used to emulate human-like communication. The Superior Colliculus, located in the mid-brain region of the nervous system, carries out similar functionality of audio and visual stimuli integration in both humans and animals. In recent years numerous researchers have attempted integration of sensory information using biological inspiration. A common focus lies in generating a single output state (i.e. a multimodal output) that can localize the source of the audio and visual stimuli. This research addresses the problem and attempts to find an effective solution by investigating various computational and biological mechanisms involved in the generation of multimodal output. A primary goal is to develop a biologically inspired computational architecture using artificial neural networks. The advantage of this approach is that it mimics the behaviour of the Superior Colliculus, which has the potential of enabling more effective human-like communication with robotic agents. The thesis describes the design and development of the architecture, which is constructed from artificial neural networks using radial basis functions. The primary inspiration for the architecture came from emulating the function top and deep layers of the Superior Colliculus, due to their visual and audio stimuli localization mechanisms, respectively. The integration experimental results have successfully demonstrated the key issues, including low-level multimodal stimuli localization, dimensionality reduction of audio and visual input-space without affecting stimuli strength, and stimuli localization with enhancement and depression phenomena. Comparisons have been made between computational and neural network based methods, and unimodal verses multimodal integrated outputs in order to determine the effectiveness of the approach.EThOS - Electronic Theses Online ServiceGBUnited Kingdo