257 research outputs found

    The hearing hippocampus

    Get PDF
    The hippocampus has a well-established role in spatial and episodic memory but a broader function has been proposed including aspects of perception and relational processing. Neural bases of sound analysis have been described in the pathway to auditory cortex, but wider networks supporting auditory cognition are still being established. We review what is known about the role of the hippocampus in processing auditory information, and how the hippocampus itself is shaped by sound. In examining imaging, recording, and lesion studies in species from rodents to humans, we uncover a hierarchy of hippocampal responses to sound including during passive exposure, active listening, and the learning of associations between sounds and other stimuli. We describe how the hippocampus' connectivity and computational architecture allow it to track and manipulate auditory information ā€“ whether in the form of speech, music, or environmental, emotional, or phantom sounds. Functional and structural correlates of auditory experience are also identified. The extent of auditory-hippocampal interactions is consistent with the view that the hippocampus makes broad contributions to perception and cognition, beyond spatial and episodic memory. More deeply understanding these interactions may unlock applications including entraining hippocampal rhythms to support cognition, and intervening in links between hearing loss and dementia

    Non-destructive whole-brain monitoring using nanorobots : neural electrical data rate requirements

    Get PDF
    Neuronanorobotics, a promising future medical technology, may provide the ultimate tool for achieving comprehensive non-destructive real-time in vivo monitoring of the many information channels in the human brain. This paper focuses on the electrical information channel and employs a novel electrophysiological approach to estimate the data rate requirements, calculated to be (5.52 Ā± 1.13) x 1016 bits/sec in an entire living human brain, for acquiring, transmitting, and storing singleneuron electrical information using medical nanorobots, corresponding to an estimated synapticprocessed spike rate of (4.31 Ā± 0.86) x 1015 spikes/sec.Centro de MatemĆ”tica da Universidade do Minho (CMAT). The principal author (NRBM) thanks the FundaĆ§Ć£o para a CiĆŖncia e Tecnologia (FCT) for their financial support of this work (grant SFRH/BD/69660/2010)

    Dynamics and network structure in neuroimaging data

    Get PDF

    High Frequency Oscillations are Phase-Amplitude Coupled in Stress Induced Seizures Following Traumatic Brain Injury

    Get PDF
    Traumatic Brain Injury (TBI) often leads to the development of epilepsy, especially with the occurrence of stressful events. Stressors increase the levels of corticotropin-releasing factor (CRF) in the amygdala, which can be damaged by the secondary effects of TBI. It is hypothesized that the activity of CRF receptor type 1 (CRFR1) in the amygdala is altered post-TBI and supports the generation of epileptiform waves, namely high-frequency oscillations (HFOs). Sprague-Dawley rats were given a moderate TBI and in vivo recordings of the amygdala were taken during the administration of an acute tail pinch stressor. The stressor increased broadband activity which included the occurrence of HFOs. Moreover, HFO amplitudes were found to be coupled to the phase of a simultaneous theta wave (4 ā€“ 8Hz). Furthermore, application of a CRFR1 antagonist disrupted the generation of HFOs and their phase-amplitude coupling with theta, and these effects were reverted after washout of the antagonist

    Cross-Frequency Coupling Based Neuromodulation for Treating Neurological Disorders

    Get PDF
    Synchronous, rhythmic changes in the membrane polarization of neurons form oscillations in local field potentials. It is hypothesized that high-frequency brain oscillations reflect local cortical information processing, and low-frequency brain oscillations project information flow across larger cortical networks. This provides complex forms of information transmission due to interactions between oscillations at different frequency bands, which can be rendered with cross-frequency coupling (CFC) metrics. Phase-amplitude coupling (PAC) is one of the most common representations of the CFC. PAC reflects the coupling of the phase of oscillations in a specific frequency band to the amplitude of oscillations in another frequency band. In a normal brain, PAC accompanies multi-item working memory in the hippocampus, and changes in PAC have been associated with diseases such as schizophrenia, obsessive-compulsive disorder (OCD), Alzheimer disease (AD), epilepsy, and Parkinsonā€™s disease (PD). The purpose of this article is to explore CFC across the central nervous system and demonstrate its correlation to neurological disorders. Results from previously published studies are reviewed to explore the significant role of CFC in large neuronal network communication and its abnormal behavior in neurological disease. Specifically, the association of effective treatment in PD such as dopaminergic medication and deep brain stimulation with PAC changes is described. Lastly, CFC analysis of the electrocorticographic (ECoG) signals recorded from the motor cortex of a Parkinsonā€™s disease patient and the parahippocampal gyrus of an epilepsy patient are demonstrated. This information taken together illuminates possible roles of CFC in the nervous system and its potential as a therapeutic target in disease states. This will require new neural interface technologies such as phase-dependent stimulation triggered by PAC changes, for the accurate recording, monitoring, and modulation of the CFC signal

    Neuronal network dynamics during epileptogenesis in the medial temporal lobe

    Get PDF
    Epilepsy is one of the most common neurological disorders, a large fraction of which is resistant to pharmacotherapy. In this light, understanding the mechanisms of epilepsy and its intractable forms in particular could create new targets for pharmacotherapeutic intervention. The current project explores the dynamic changes in neuronal network function in the chronic temporal lobe epilepsy (TLE) in rat and human brain in vitro. I focused on the process of establishment of epilepsy (epileptogenesis) in the temporal lobe. Rhythmic behaviour of the hippocampal neuronal networks in healthy animals was explored using spontaneous oscillations in the gamma frequency band (SĪ³O). The use of an improved brain slice preparation technique resulted in the natural occurence (in the absence of pharmacological stimulation) of rhythmic activity, which was then pharmacologically characterised and compared to other models of gamma oscillations (KA- and CCh-induced oscillations) using local field potential recording technique. The results showed that SĪ³O differed from pharmacologically driven models, suggesting higher physiological relevance of SĪ³O. Network activity was also explored in the medial entorhinal cortex (mEC), where spontaneous slow wave oscillations (SWO) were detected. To investigate the course of chronic TLE establishment, a refined Li-pilocarpine-based model of epilepsy (RISE) was developed. The model significantly reduced animal mortality and demonstrated reduced intensity, yet high morbidy with almost 70% mean success rate of developing spontaneous recurrent seizures. We used SĪ³O to characterize changes in the hippocampal neuronal networks throughout the epileptogenesis. The results showed that the network remained largely intact, demonstrating the subtle nature of the RISE model. Despite this, a reduction in network activity was detected during the so-called latent (no seizure) period, which was hypothesized to occur due to network fragmentation and an abnormal function of kainate receptors (KAr). We therefore explored the function of KAr by challenging SĪ³O with kainic acid (KA). The results demonstrated a remarkable decrease in KAr response during the latent period, suggesting KAr dysfunction or altered expression, which will be further investigated using a variety of electrophysiological and immunocytochemical methods. The entorhinal cortex, together with the hippocampus, is known to play an important role in the TLE. Considering this, we investigated neuronal network function of the mEC during epileptogenesis using SWO. The results demonstrated a striking difference in AMPAr function, with possible receptor upregulation or abnormal composition in the early development of epilepsy. Alterations in receptor function inevitably lead to changes in the network function, which may play an important role in the development of epilepsy. Preliminary investigations were made using slices of human brain tissue taken following surgery for intratctable epilepsy. Initial results showed that oscillogenesis could be induced in human brain slices and that such network activity was pharmacologically similar to that observed in rodent brain. Overall, our findings suggest that excitatory glutamatergic transmission is heavily involved in the process of epileptogenesis. Together with other types of receptors, KAr and AMPAr contribute to epilepsy establishment and may be the key to uncovering its mechanism

    Electrophysiological evidence for memory schemas in the rat hippocampus

    Full text link
    According to Piaget and Bartlett, learning involves both assimilation of new memories into networks of preexisting knowledge and alteration of existing networks to accommodate new information into existing schemas. Recent evidence suggests that the hippocampus integrates related memories into schemas that link representations of separately acquired experiences. In this thesis, I first review models for how memories of individual experiences become consolidated into the structure of world knowledge. Disruption of consolidated memories can occur during related learning, which suggests that consolidation of new information is the reconsolidation of related memories. The accepted role of the hippocampus during memory consolidation and reconsolidation suggests that it is also involved in modifying appropriate schemas during learning. To study schema development, I trained rats to retrieve rewards at different loci on a maze while recording hippocampal calls. About a quarter of cells were active at multiple goal sites, though the ensemble as a whole distinguished goal loci from one another. When new goals were introduced, cells that had been active at old goal locations began firing at the new locations. This initial generalization decreased in the days after learning. Learning also caused changes in firing patterns at well-learned goal locations. These results suggest that learning was supported by modification of an active schema of spatially related reward loci. In another experiment, I extended these findings to explore a schema of object and place associations. Ensemble activity was influenced by a hierarchy of task dimensions which included: experimental context, rat's spatial location, the reward potential and the identity of sampled objects. As rats learned about new objects, the cells that had previously fired for particular object-place conjunctions generalized their firing patterns to new conjunctions that similarly predicted reward. In both experiments, I observed highly structured representations for a set of related experiences. This organization of hippocampal activity counters key assumptions in standard models of hippocampal function that predict relative independence between memory traces. Instead, these findings reveal neural mechanisms for how the hippocampus develops a relational organization of memories that could support novel, inferential judgments between indirectly related events

    Development and application of an optogenetic platform for controlling and imaging a large number of individual neurons

    Full text link
    The understanding and treatment of brain disorders as well as the development of intelligent machines is hampered by the lack of knowledge of how the brain fundamentally functions. Over the past century, we have learned much about how individual neurons and neural networks behave, however new tools are critically needed to interrogate how neural networks give rise to complex brain processes and disease conditions. Recent innovations in molecular techniques, such as optogenetics, have enabled neuroscientists unprecedented precision to excite, inhibit and record defined neurons. The impressive sensitivity of currently available optogenetic sensors and actuators has now enabled the possibility of analyzing a large number of individual neurons in the brains of behaving animals. To promote the use of these optogenetic tools, this thesis integrates cutting edge optogenetic molecular sensors which is ultrasensitive for imaging neuronal activity with custom wide field optical microscope to analyze a large number of individual neurons in living brains. Wide-field microscopy provides a large field of view and better spatial resolution approaching the Abbe diffraction limit of fluorescent microscope. To demonstrate the advantages of this optical platform, we imaged a deep brain structure, the Hippocampus, and tracked hundreds of neurons over time while mouse was performing a memory task to investigate how those individual neurons related to behavior. In addition, we tested our optical platform in investigating transient neural network changes upon mechanical perturbation related to blast injuries. In this experiment, all blasted mice show a consistent change in neural network. A small portion of neurons showed a sustained calcium increase for an extended period of time, whereas the majority lost their activities. Finally, using optogenetic silencer to control selective motor cortex neurons, we examined their contributions to the network pathology of basal ganglia related to Parkinsonā€™s disease. We found that inhibition of motor cortex does not alter exaggerated beta oscillations in the striatum that are associated with parkinsonianism. Together, these results demonstrate the potential of developing integrated optogenetic system to advance our understanding of the principles underlying neural network computation, which would have broad applications from advancing artificial intelligence to disease diagnosis and treatment
    • ā€¦
    corecore