IST Austria Thesis

The solving of complex tasks requires the functions of more than one brain area and their interaction. Whilst spatial navigation and memory is dependent on the hippocampus, flexible behavior relies on the medial prefrontal cortex (mPFC). To further examine the roles of the hippocampus and mPFC, we recorded their neural activity during a task that depends on both of these brain regions. With tetrodes, we recorded the extracellular activity of dorsal hippocampal CA1 (HPC) and mPFC neurons in Long-Evans rats performing a rule-switching task on the plus-maze. The plus-maze task had a spatial component since it required navigation along one of the two start arms and at the maze center a choice between one of the two goal arms. Which goal contained a reward depended on the rule currently in place. After an uncued rule change the animal had to abandon the old strategy and switch to the new rule, testing cognitive flexibility. Investigating the coordination of activity between the HPC and mPFC allows determination during which task stages their interaction is required. Additionally, comparing neural activity patterns in these two brain regions allows delineation of the specialized functions of the HPC and mPFC in this task. We analyzed neural activity in the HPC and mPFC in terms of oscillatory interactions, rule coding and replay. We found that theta coherence between the HPC and mPFC is increased at the center and goals of the maze, both when the rule was stable or has changed. Similar results were found for locking of HPC and mPFC neurons to HPC theta oscillations. However, no differences in HPC-mPFC theta coordination were observed between the spatially- and cue-guided rule. Phase locking of HPC and mPFC neurons to HPC gamma oscillations was not modulated by maze position or rule type. We found that the HPC coded for the two different rules with cofiring relationships between cell pairs. However, we could not find conclusive evidence for rule coding in the mPFC. Spatially-selective firing in the mPFC generalized between the two start and two goal arms. With Bayesian positional decoding, we found that the mPFC reactivated non-local positions during awake immobility periods. Replay of these non-local positions could represent entire behavioral trajectories resembling trajectory replay of the HPC. Furthermore, mPFC trajectory-replay at the goal positively correlated with rule-switching performance. Finally, HPC and mPFC trajectory replay occurred independently of each other. These results show that the mPFC can replay ordered patterns of activity during awake immobility, possibly underlying its role in flexible behavior

The hippocampus and entorhinal cortex map events across space and time

The medial temporal lobe supports the encoding of new facts and experiences, and organizes them so that we can infer relationships and make unique associations during new encounters. Evidence from studies on humans and animals suggest that the hippocampus is specifically required for our ability to form these internal representations of the world. The mechanism by which the hippocampus performs this function remains unclear, but electrophysiological recordings in the hippocampus support a general model. One component of this model suggests that the cortex represents places, times, and events separately, and then the hippocampus generates conjunctive representations that connect the three. According to this hypothesis, the hippocampus binds places and events to an existing relational structure. This dissertation explores how item and place associations develop within cortex, and then examines the relational structure that organizes these events within the hippocampus. The first study suggests that contrary to previous models, events and places are bound together outside of the hippocampus in the entorhinal cortex and perirhinal cortex. The second study shows that this relational scaffold may be embodied by a continually changing code that permits both the association and separation of information across the continuum of time. The final study suggests that the hippocampus and entorhinal cortex contain qualitatively different time codes that may act in a complementary fashion to bind events and places and relate them across time. Overall, these studies support a theory wherein time is encoded in a range of brain regions that also contain conjunctive item and position information. In these regions, conjunctive representations of items, places, and times are organized not only by their perceptual similarity but also their temporal proximity

Concurrent neuroimaging and neurostimulation reveals a causal role for dlPFC in coding of task-relevant information.

Dorsolateral prefrontal cortex (dlPFC) is proposed to drive brain-wide focus by biasing processing in favour of task-relevant information. A longstanding debate concerns whether this is achieved through enhancing processing of relevant information and/or by inhibiting irrelevant information. To address this, we applied transcranial magnetic stimulation (TMS) during fMRI, and tested for causal changes in information coding. Participants attended to one feature, whilst ignoring another feature, of a visual object. If dlPFC is necessary for facilitation, disruptive TMS should decrease coding of attended features. Conversely, if dlPFC is crucial for inhibition, TMS should increase coding of ignored features. Here, we show that TMS decreases coding of relevant information across frontoparietal cortex, and the impact is significantly stronger than any effect on irrelevant information, which is not statistically detectable. This provides causal evidence for a specific role of dlPFC in enhancing task-relevant representations and demonstrates the cognitive-neural insights possible with concurrent TMS-fMRI-MVPA

LMPIT-inspired Tests for Detecting a Cyclostationary Signal in Noise with Spatio-Temporal Structure

In spectrum sensing for cognitive radio, the presence of a primary user can be detected by making use of the cyclostationarity property of digital communication signals. For the general scenario of a cyclostationary signal in temporally colored and spatially correlated noise, it has previously been shown that an asymptotic generalized likelihood ratio test (GLRT) and locally most powerful invariant test (LMPIT) exist. In this paper, we derive detectors for the presence of a cyclostationary signal in various scenarios with structured noise. In particular, we consider noise that is temporally white and/or spatially uncorrelated. Detectors that make use of this additional information about the noise process have enhanced performance. We have previously derived GLRTs for these specific scenarios; here, we examine the existence of LMPITs. We show that these exist only for detecting the presence of a cyclostationary signal in spatially uncorrelated noise. For white noise, an LMPIT does not exist. Instead, we propose tests that approximate the LMPIT, and they are shown to perform well in simulations. Finally, if the noise structure is not known in advance, we also present hypothesis tests using our framework

Distributed Activity Patterns for Objects and Their Features: Decoding Perceptual and Conceptual Object Processing in Information Networks of the Human Brain

How are object features and knowledge-fragments represented and bound together in the human brain? Distributed patterns of activity within brain regions can encode distinctions between perceptual and cognitive phenomena with impressive specificity. The research reported here investigated how the information within regions\u27 multi-voxel patterns is combined in object-concept networks. Chapter 2 investigated how memory-driven activity patterns for an object\u27s specific shape, color, and identity become active at different stages of the visual hierarchy. Brain activity patterns were recorded with functional magnetic resonance imaging (fMRI) as participants searched for specific fruits or vegetables within visual noise. During time-points in which participants were searching for an object, but viewing pure noise, the targeted object\u27s identity could be decoded in the left anterior temporal lobe (ATL). In contrast, top-down generated patterns for the object\u27s specific shape and color were decoded in early visual regions. The emergence of object-identity information in the left ATL was predicted by concurrent shape and color information in their respective featural regions. These findings are consistent with theories proposing that feature-fragments in sensory cortices converge to higher-level identity representations in convergence zones. Chapter 3 investigated whether brain regions share fluctuations in multi-voxel information across time. A new analysis method was first developed, to measure dynamic changes in distributed pattern information. This method, termed informational connectivity (IC), was then applied to data collected as participants viewed different types of man-made objects. IC identified connectivity between object-processing regions that was not apparent from existing functional connectivity measures, which track fluctuating univariate signals. Collectively, this work suggests that networks of regions support perceptual and conceptual object processing through the convergence and synchrony of distributed pattern information

Decoupled maximum likelihood channel estimator for space-time block coded system

Master'sMASTER OF ENGINEERIN

Dynamic Oscillatory Interactions Between Neural Attention and Sensorimotor Systems

The adaptive and flexible ability of the human brain to preference the processing of salient environmental features in the visual space is essential to normative cognitive function, and various neurologically afflicted patient groups report negative impacts on visual attention. While the brain-bases of human attentional processing have begun to be unraveled, very little is known regarding the interactions between attention systems and systems supporting sensory and motor processing. This is essential, as these interactions are dynamic; evolving rapidly in time and across a wide range of functionally defined rhythmic frequencies. Using magnetoencephalography (MEG) and a range of novel cognitive paradigms and analytical techniques, this work attempts to fill critical gaps in this knowledge. Specifically, we unravel the role of dynamic oscillatory interactions between attention and three sensorimotor systems. First, we establish the importance of sub-second occipital alpha (8 – 14 Hz) oscillatory responses in visual distractor suppression during selective attention (Chapter 1) and their essential role in fronto-parietal attention networks during visual orienting (Chapter 2). Next, we examine the divergent effects of directed attention on multi-frequency primary somatosensory neural oscillations in the theta (4 – 8 Hz), alpha, and beta (18 – 26 Hz) bands (Chapter 3). Finally, we extend these findings to the motor system (Chapter 4), and find that the frontal and parietal beta-frequency oscillations known to support motor planning and execution are modulated equivalently by differing subtypes of attentional interference, whereas frontal gamma (64 – 84 Hz) oscillations specifically index the superadditive effect of this interference. These findings provide new insight into the dynamic nature of attention-sensorimotor interactions in the human brain, and will be the foundation for groundbreaking new studies of attentional deficits in patients with common neurological disorders (e.g., Alzheimer’s disease, HIV-associated neurocognitive disorders, Parkinson’s disease). With an enhanced knowledge of the temporal and spectral definitions of these impairments, new therapeutic interventions utilizing frequency-targeted neural stimulation can be developed

Concurrent neuroimaging and neurostimulation reveals a causal role for dlPFC in coding of task-relevant information.

Dorsolateral prefrontal cortex (dlPFC) is proposed to drive brain-wide focus by biasing processing in favour of task-relevant information. A longstanding debate concerns whether this is achieved through enhancing processing of relevant information and/or by inhibiting irrelevant information. To address this, we applied transcranial magnetic stimulation (TMS) during fMRI, and tested for causal changes in information coding. Participants attended to one feature, whilst ignoring another feature, of a visual object. If dlPFC is necessary for facilitation, disruptive TMS should decrease coding of attended features. Conversely, if dlPFC is crucial for inhibition, TMS should increase coding of ignored features. Here, we show that TMS decreases coding of relevant information across frontoparietal cortex, and the impact is significantly stronger than any effect on irrelevant information, which is not statistically detectable. This provides causal evidence for a specific role of dlPFC in enhancing task-relevant representations and demonstrates the cognitive-neural insights possible with concurrent TMS-fMRI-MVPA

Object-specific semantic coding in human perirhinal cortex.

Category-specificity has been demonstrated in the human posterior ventral temporal cortex for a variety of object categories. Although object representations within the ventral visual pathway must be sufficiently rich and complex to support the recognition of individual objects, little is known about how specific objects are represented. Here, we used representational similarity analysis to determine what different kinds of object information are reflected in fMRI activation patterns and uncover the relationship between categorical and object-specific semantic representations. Our results show a gradient of informational specificity along the ventral stream from representations of image-based visual properties in early visual cortex, to categorical representations in the posterior ventral stream. A key finding showed that object-specific semantic information is uniquely represented in the perirhinal cortex, which was also increasingly engaged for objects that are more semantically confusable. These findings suggest a key role for the perirhinal cortex in representing and processing object-specific semantic information that is more critical for highly confusable objects. Our findings extend current distributed models by showing coarse dissociations between objects in posterior ventral cortex, and fine-grained distinctions between objects supported by the anterior medial temporal lobes, including the perirhinal cortex, which serve to integrate complex object information.This work was supported by funding from the European Research Council under the European Community's Seventh Framework Programme (FP7/2007--2013)/ ERC Grant agreement no. 249640 to L.K.T