Neural and Behavioral Consequences of Perceptual Organization using Proto-Objects

The human visual system utilizes attention to direct processing towards areas of interest. In particular, certain objects in a visual scene can be salient, meaning they attract attention rather than being the targets of some search process. Visual salience appears to be driven by the formation of visual proto-objects, which have been hypothesized to cause an increase in synchronous firing between neurons encoding parts of an object. This thesis approaches proto-objects both from a behavioral level and at a low level of analyzing synchrony. At the behavioral level, existing studies of visual salience rely on many repetitive trials or task instructions to tell study participants what to do, which can influence attentive behavior in a top-down manner, confounding the measurement of salience. I introduce an experimental paradigm that records attentional selections from subjects without any such information, and used this paradigm to analyze whether proto-objects interact in the determination of salience. The results show that uniqueness of an object does indeed attract attention, and I develop a model that normalizes among proto-objects to explain the measured data. At the neuronal level, I develop a more rapid method to perform jitter hypothesis tests regarding detecting the presence of synchronous spiking between pairs of neurons. While the detection of synchrony does imply some connection between neurons, I also show that the inference of a change in common input from changes in synchrony is not possible

Oscillatory Network Activity in Brain Functions and Dysfunctions

Recent experimental studies point to the notion that the brain is a complex dynamical system whose behaviors relating to brain functions and dysfunctions can be described by the physics of network phenomena. The brain consists of anatomical axonal connections among neurons and neuronal populations in various spatial scales. Neuronal interactions and synchrony of neuronal oscillations are central to normal brain functions. Breakdowns in interactions and modifications in synchronization behaviors are usual hallmarks of brain dysfunctions. Here, in this dissertation for PhD degree in physics, we report discoveries of brain oscillatory network activity from two separate studies. These studies investigated the large-scale brain activity during tactile perceptual decision-making and epileptic seizures. In the perceptual decision-making study, using scalp electroencephalography (EEG) recordings of brain potentials, we investigated how oscillatory activity functionally organizes different neocortical regions as a network during a tactile discrimination task. While undergoing EEG recordings, blindfolded healthy participants felt a linear three-dot array presented electromechanically, under computer control, and reported whether the central dot was offset to the left or right. Based on the current dipole modeling in the brain, we found that the source-level peak activity appeared in the left primary somatosensory cortex (SI), right lateral occipital complex (LOC), right posterior intraparietal sulcus (pIPS) and finally left dorsolateral prefrontal cortex (dlPFC) at 45, 130, 160 and 175 ms respectively. Spectral interdependency analysis showed that fine tactile discrimination is mediated by distinct but overlapping ~15 Hz beta and ~80 Hz gamma band large-scale oscillatory networks. The beta-network that included all four nodes was dominantly feedforward, similar to the propagation of peak cortical activity, implying its role in accumulating and maintaining relevant sensory information and mapping to action. The gamma-network activity, occurring in a recurrent loop linked SI, pIPS and dlPFC, likely carrying out attentional selection of task-relevant sensory signals. Behavioral measure of task performance was correlated with the network activity in both bands. In the study of epileptic seizures, we investigated high-frequency (\u3e 50 Hz) oscillatory network activity from intracranial EEG (IEEG) recordings of patients who were the candidates for epilepsy surgery. The traditional approach of identifying brain regions for epilepsy surgery usually referred as seizure onset zones (SOZs) has not always produced clarity on SOZs. Here, we investigated directed network activity in the frequency domain and found that the high frequency (\u3e80 Hz) network activities occur before the onset of any visible ictal activity, andcausal relationships involve the recording electrodes where clinically identifiable seizures later develop. These findings suggest that high-frequency network activities and their causal relationships can assist in precise delineation of SOZs for surgical resection

A Combinatorial Premotor Neural Code: Transformation Of Sensory Information Into Meaningful Rhythmic Motor Output By A Network Of Heterogeneous Modulatory Neurons

The goal of the following research was to investigate the contributions of neural networks in selecting distinct variants of rhythmic motor activity. We used the premotor commissural ganglion (CoG) in the stomatogastric nervous system of the Jonah crab to understand how this network effectively controls the rhythms produced in downstream motor circuits. Prior research determined that individual CoG neurons are necessary to mediate sensory-induced variation in the effected motor patterns. However, single premotor neuron inputs to the STG are not sufficient to recreate the patterns induced by the selective activation of sensory pathways. Thus, it was hypothesized that the CoG-mediated effects on these sensorimotor transformations must be explained at the level of CoG population activity. We embraced the exploratory nature of this study by approaching it in three phases. First, we established voltage-sensitive dye imaging in the stomatogastric nervous system, as a technique that reports the simultaneous activity of many neurons with single-neuron resolution. In short, this form of imaging was effective at reporting both slow and fast changes in membrane potential, and provided an effective means of staining fine neural structures through neural sheaths, structures that often act as barriers to many substances. Then, we characterized the distribution of somata in the CoG, and found that soma location was not fixed in its location from animal to animal, but that clustering of CoG somata did occur near their different nerve pathway origins. Finally, we used the voltage-sensitive dye-imaging technique to investigate the CoG population under many different sensory conditions, and found that two different sensory modalities, one chemosensory and one mechanosensory pathway, differentially affected the balance of excited and inhibited (network activation) neurons found in the CoGs. Moreover, differences in the composition of CoG participants between modalities was not extremely robust. However, it differed enough so that both CoG participation and activation were drivers of the observed changes in the downstream pyloric motor network, providing support for a premotor combinatorial code for motor pattern selection

Oscillatory and epileptiform activity in human and rodent cortical regions in vitro

Epilepsy is a chronic neurological disorder in which patients have spontaneous recurrent seizures. Approximately 50 million people worldwide live with epilepsy and of those ~30% fail to adequately respond to anti-epileptic drugs (AEDs), indicating a need for further research. In this study oscillatory and epileptiform activity was explored in the rodent piriform cortex (PC) in vitro, an underexplored brain region implicated in the development of epilepsy. PC gamma oscillations have been studied in both anaesthetised and awake rodents in vivo; however, to date they have not been reported in vitro. Extracellular field potential recordings were made in rodent PC brain slices prepared from 70-100g male Wistar rats in vitro. Application of kainic acid and carbachol reliably induced persistent gamma oscillations (30 – 40 Hz) in layer II of the PC. These oscillations were found to be pharmacologically similar to gamma oscillations previously found in other rodent brain regions in vitro, as they were dependent on GABAA receptors, AMPA receptors and gap junctions. Persistent oscillations were also induced and characterised for the first time in human neuronal tissue in vitro. Human brain slices were prepared from excised tissue from various brain regions (primarily temporal) from paediatric patients undergoing surgery to alleviate the symptoms of drug resistant epilepsy. As in the rodent PC, oscillations were induced by application of kainic acid and carbachol, however, these oscillations were found to be within the beta frequency range (12 – 30 Hz). Despite this difference in frequency band, these beta oscillations were pharmacologically similar to gamma oscillations found in the rodent PC. Seizure-like events (SLEs) were induced in brain slices prepared from 70-100g male Wistar rats via application of zero Mg2+ artificial cerebral spinal fluid (0[Mg]2+ aCSF). The properties of these SLEs were found to be similar between brain regions when recordings were performed in layer II of the anterior and posterior PC and lateral entorhinal cortex (LEC) and the stratum pyramidale of CA1. In the majority of recordings SLEs occurred in the PC before the LEC or CA1 and SLEs were displayed in the PC in a higher proportion of slices than the LEC. The sensitivity of these PC slices to 0[Mg]2+ aCSF was assessed at several stages (24 hours and 1 week (early latent), 4 weeks (mid latent) and 3 months+ (chronic period)) following the reduced intensity status epilepticus (SE) protocol for epilepsy induction compared to age-matched controls (AMCs). A decrease in excitability of the slices was observed in slices prepared from AMC animals with age, as the inter-event interval and latency to first SLE was observed to be longer in slices prepared from aged compared to young AMC animals. Slices prepared from SE animals maintained their youthful hyperexcitability with no difference in IEI or latency to first SLE observed in the early latent period compared to the chronic period. The pharmacoresistance (or sensitivity) of these SLEs to single and double AED challenge was evaluated. Differences in efficacy of the AEDs were found between SE and AMC in the mid-latent period; increased efficacy of Na+ channel modulating AEDs were found in slices prepared from SE compared to AMC animals. The proportion of slices that displayed pharmacoresistance of these SLEs to AEDs was found to be higher in slices prepared from young animals (early latent period and AMCs), and was similar to that found clinically in human patients. The pharmacoresistance of the SLEs to AEDs was lower in slices prepared from older animals (mid latent, chronic and AMCs) compared to young animals (early latent and AMCs). This age-dependent reduction in resistance likely reflects normal alterations in neuronal networks with ageing. SLEs induced in young control PC slices could be exploited as a new in vitro model of drug resistant epilepsy. Overall, oscillatory and epileptiform activity in the PC and human cortex in vitro could be further explored as tools to evaluate the efficacy and mechanism of action of newly developed AEDs, as well as to explore the networks involved in drug resistant epilepsy

Data assimilation for conductance-based neuronal models

This dissertation illustrates the use of data assimilation algorithms to estimate unobserved variables and unknown parameters of conductance-based neuronal models. Modern data assimilation (DA) techniques are widely used in climate science and weather prediction, but have only recently begun to be applied in neuroscience. The two main classes of DA techniques are sequential methods and variational methods. Throughout this work, twin experiments, where the data is synthetically generated from output of the model, are used to validate use of these techniques for conductance-based models observing only the voltage trace. In Chapter 1, these techniques are described in detail and the estimation problem for conductance-based neuron models is derived. In Chapter 2, these techniques are applied to a minimal conductance-based model, the Morris-Lecar model. This model exhibits qualitatively different types of neuronal excitability due to changes in the underlying bifurcation structure and it is shown that the DA methods can identify parameter sets that produce the correct bifurcation structure even with initial parameter guesses that correspond to a different excitability regime. This demonstrates the ability of DA techniques to perform nonlinear state and parameter estimation, and introduces the geometric structure of inferred models as a novel qualitative measure of estimation success. Chapter 3 extends the ideas of variational data assimilation to include a control term to relax the problem further in a process that is referred to as nudging from the geoscience community. The nudged 4D-Var is applied to twin experiments from a more complex, Hodgkin-Huxley-type two-compartment model for various time-sampling strategies. This controlled 4D-Var with nonuniform time-samplings is then applied to voltage traces from current-clamp recordings of suprachiasmatic nucleus neurons in diurnal rodents to improve upon our understanding of the driving forces in circadian (~24) rhythms of electrical activity. In Chapter 4 the complementary strengths of 4D-Var and UKF are leveraged to create a two-stage algorithm that uses 4D-Var to estimate fast timescale parameters and UKF for slow timescale parameters. This coupled approach is applied to data from a conductance-based model of neuronal bursting with distinctive slow and fast time-scales present in the dynamics. In Chapter 5, the ideas of identifiability and sensitivity are introduced. The Morris-Lecar model and a subset of its parameters are shown to be identifiable through the use of numerical techniques. Chapter 6 frames the selection of stimulus waveforms to inject into neurons during patch-clamp recordings as an optimal experimental design problem. Results on the optimal stimulus waveforms for improving the identifiability of parameters for a Hodgkin-Huxley-type model are presented. Chapter 7 shows the preliminary application of data assimilation for voltage-clamp, rather than current-clamp, data and expands on voltage-clamp principles to formulate a reduced assimilation problem driven by the observed voltage. Concluding thoughts are given in Chapter 8

TO INFEROTEMPORAL NEURONS THE WHOLE IS NOT THE SUM OF THE PARTS

Vision seems to occur effortlessly and without mistakes. As a result, it is easy to lose sight of the complex representational mechanisms going on under the hood. In macaque monkeys, the brain region thought to be the ultimate mediator of object recognition is the inferotemporal cortex (IT). The purpose of this dissertation was to investigate how IT neurons handle parts of objects, both in a context wherein parts interfere with one another as well as a context in which certain parts aren’t readily perceived. We broke this down into three distinct projects, outlined below. The first project was concerned with the behavioral phenomenon known as crowding, in which clutter causes peripheral objects to devolve into an unintelligible jumble. We are the first to develop a task that was conducive to concurrent behavior and neuronal recordings in monkeys. To demonstrate relevance of our task, we turned to a hallmark of crowding: that what matters is the eccentricity and spacing between objects, not object size. Having demonstrated this, we were set to proceed to neuronal recordings. Our primary question was whether crowding quantitatively reduced the strength of IT neuronal selectivity or alternatively whether crowding induced a qualitative change to the neuronal code. Our results support the latter hypothesis. We then asked additional follow-up questions regarding size-sensitivity and adjacency of part-part interactions. Overall, our results were incompatible with a pooling model of crowding and consistent with models based on attention, texture, or source confusion. The final experiment was concerned with whether certain parts of compound objects were preferentially represented over others. To do this we recorded IT spiking activity while monkeys viewed composite shapes made up of overlapping outlines, as well as all the possible constituent closed parts created by the overlap. Humans tend to only perceive the simpler shapes originally used to create the composite, but the same was not true of IT neurons. Instead, they represented the composite more like its external contour than any other part, especially in the initial phase of the response

Methods for Detecting High-Frequency Oscillations in Ongoing Brain Signals: Application to the Determination of Epileptic Seizure Onset Zones

Epilepsy is a neurological disorder with varied expression. Patients with focal onset seizures that are resistant to medications can benefit from ablative surgery. However, localization of the seizure onset zone (SOZ) and characterization of propagation to secondary areas can be challenging. The present study aimed at developing the appropriate signal processing methodology to detect bursts of interictal high-frequency oscillations (HFOs), as a possible signature of the SOZ, in patients with drug-resistant partial epilepsy. Additionally, invasive interictal and ictal intracranial electroencephalography (iEEG) data and non-invasive electromagnetic source imaging with magnetoencephalography (MEG) data from three subjects were analyzed. We developed a novel algorithm that extracts HFO bursts from the envelope of iEEG and MEG traces in the [80-300] Hz range. Clusters of HFO events across multichannel iEEG traces were subsequently analyzed to investigate their relative time delays and to infer possible propagation patterns during the interictal period and episodes of ictal onset (iEEG only). The location of iEEG electrodes sustaining the HFO bursts were labeled with respect to the chronometry of the local HFOs. The recording site bearing the smallest rank was labeled as the lead generator of HFO discharges. The aim of using MEG traces was essentially to determine probable SOZ locations non-invasively by extending the results obtained with iEEG. We proposed a new metric referred to as `spiking index\u27 that was computed at each cortical site in the vicinity of iEEG electrode locations (iEEG and MEG data were obtained for the same patients: iEEG was considered as the standard of reference for MEG results). The sensitivity and specificity of the HFO detector operating from ongoing brain traces were evaluated. Our results indicate that higher values of spiking index and higher rates of HFOs corresponded to brain regions that were identified independently as the SOZ by an expert clinician and as determined by the location and extent of the cortical resection that freed the patients from the seizures. Interictal and ictal iEEG HFO localization showed good concordance with the location of resected areas. The use of interictal data only, if used for surgical planning, would reduce the time required for making decisions regarding the resection of cortex and improve the chances of success of surgery in making patients become seizure-free. Obtaining iEEG data is invasive, with possible risks to the patients, and requires an expensive procedure. Another fundamental disadvantage of iEEG is that the implanted electrode grids and strips needed to cover the supposed abnormal cortical areas for proper determination of the SOZ. Our results indicate that the spiking index and rate map obtained from MEG source maps may provide a non-invasive alternative for determination of the SOZ and may provide greater accuracy to the placement of the implantable electrodes, and eventually avoid an invasive exploratory procedure before surgery

The effects of DMT and associated psychedelics on the human mind and brain

This work presents seven investigations conducted with the aim to determine the effects of DMT (a compound which is able to cause remarkable effects in consciousness) and associated psychedelic drugs on the human brain and mind. Including a variety of neuroimaging (EEG, MEG and fMRI), phenomenological, psychometric and naturalistic research methods, these are the first controlled investigations of the impact of DMT in the human resting brain. Results revealed that DMT disrupted several brain mechanisms associated with top-down control (alpha power, integrity of high-level networks, modularity), increased measures related to entropy, or disorder (Lempel-Ziv complexity, novel pairwise connectivity) and immersive states of consciousness (delta/theta power), with some of these effects following the experiential trajectories of the DMT state. We also observed a significant temporal correlation between some of these effects (alpha power and default-mode network integrity fluctuations), which were supported by LSD effects of reduced feedback connectivity and neural adaption mechanisms. suggesting that the psychedelic brain state is one of reduced modularity, increased integration and functional plasticity. These findings were complemented by psychological studies showing that the DMT state is one of immersive visual imagery, intense somatic experiences and partial disconnection from the environment, which we found shared significant overlap with near- death experiences. DMT administration also resulted in positive mental health outcomes in healthy volunteers providing evidence for the first time that DMT may provide a useful alternative to currently- investigated psychedelic treatments. Finally, results from our last study performed in naturalistic environments revealed that psychedelics are able to have a transformative potential on core beliefs concerning the fundamental nature of reality and consciousness for up to 6 months, with important social and bioethical implications. Collectively these results attest to the strong impact that psychedelics have on varied human domains, which range experience, brain activity, mental health, intersubjectivity and beliefs.Open Acces