Project description:Frequency-specific oscillations and phase-coupling of neuronal populations are essential mechanisms for the coordination of activity between brain areas during cognitive tasks. Therefore, the ongoing activity ascribed to the different functional brain networks should also be able to reorganise and coordinate via similar mechanisms. We develop a novel method for identifying large-scale phase-coupled network dynamics and show that resting networks in magnetoencephalography are well characterised by visits to short-lived transient brain states, with spatially distinct patterns of oscillatory power and coherence in specific frequency bands. Brain states are identified for sensory, motor networks and higher-order cognitive networks. The cognitive networks include a posterior alpha (8-12?Hz) and an anterior delta/theta range (1-7?Hz) network, both exhibiting high power and coherence in areas that correspond to posterior and anterior subdivisions of the default mode network. Our results show that large-scale cortical phase-coupling networks have characteristic signatures in very specific frequency bands, possibly reflecting functional specialisation at different intrinsic timescales.
Project description:Despite numerous studies of auditory cortical processing in the ferret (Mustela putorius), very little is known about the connections between the different regions of the auditory cortex that have been characterized cytoarchitectonically and physiologically. We examined the distribution of retrograde and anterograde labeling after injecting tracers into one or more regions of ferret auditory cortex. Injections of different tracers at frequency-matched locations in the core areas, the primary auditory cortex (A1) and anterior auditory field (AAF), of the same animal revealed the presence of reciprocal connections with overlapping projections to and from discrete regions within the posterior pseudosylvian and suprasylvian fields (PPF and PSF), suggesting that these connections are frequency specific. In contrast, projections from the primary areas to the anterior dorsal field (ADF) on the anterior ectosylvian gyrus were scattered and non-overlapping, consistent with the non-tonotopic organization of this field. The relative strength of the projections originating in each of the primary fields differed, with A1 predominantly targeting the posterior bank fields PPF and PSF, which in turn project to the ventral posterior field, whereas AAF projects more heavily to the ADF, which then projects to the anteroventral field and the pseudosylvian sulcal cortex. These findings suggest that parallel anterior and posterior processing networks may exist, although the connections between different areas often overlap and interactions were present at all levels.
Project description:Deep brain stimulation (DBS) is increasingly applied for the treatment of brain disorders, but its mechanism of action remains unknown. Here we evaluate the effect of basal ganglia DBS on cortical function using invasive cortical recordings in Parkinson's disease (PD) patients undergoing DBS implantation surgery. In the primary motor cortex of PD patients, neuronal population spiking is excessively synchronized to the phase of network oscillations. This manifests in brain surface recordings as exaggerated coupling between the phase of the beta rhythm and the amplitude of broadband activity. We show that acute therapeutic DBS reversibly reduces phase-amplitude interactions over a similar time course as that of the reduction in parkinsonian motor signs. We propose that DBS of the basal ganglia improves cortical function by alleviating excessive beta phase locking of motor cortex neurons.
Project description:Fluid intelligence (gf) represents a crucial component of human cognition, as it correlates with academic achievement, successful aging, and longevity. However, it has strong resilience against enhancement interventions, making the identification of gf enhancement approaches a key unmet goal of cognitive neuroscience. Here, we applied a spike-timing-dependent plasticity (STDP)-inducing brain stimulation protocol, named cortico-cortical paired associative stimulation (cc-PAS), to modulate gf in 29 healthy young subjects (13 females-mean?± standard deviation, 25.43 years?±?3.69), based on dual-coil transcranial magnetic stimulation (TMS). Pairs of neuronavigated TMS pulses (10-ms interval) were delivered over two frontoparietal nodes of the gf network, based on individual functional magnetic resonance imaging data and in accordance with cognitive models of information processing across the prefrontal and parietal lobe. cc-PAS enhanced accuracy at gf tasks, with parieto-frontal and fronto-parietal stimulation significantly increasing logical and relational reasoning, respectively. Results suggest the possibility of using SPTD-inducing TMS protocols to causally validate cognitive models by selectively engaging relevant networks and manipulating inter-regional temporal dynamics supporting specific cognitive functions.
Project description:The cerebellum plays an important role in motor learning as part of a cortico-striato-cerebellar network. Patients with cerebellar degeneration typically show impairments in different aspects of motor learning, including implicit motor sequence learning. How cerebellar dysfunction affects interactions in this cortico-striato-cerebellar network is poorly understood. The present study investigated the effect of cerebellar degeneration on activity in causal interactions between cortical and subcortical regions involved in motor learning. We found that cerebellar patients showed learning-related increase in activity in two regions known to be involved in learning and memory, namely parahippocampal cortex and cerebellar Crus I. The cerebellar activity increase was observed in non-learners of the patient group whereas learners showed an activity decrease. Dynamic causal modeling analysis revealed that modulation of M1 to cerebellum and putamen to cerebellum connections were significantly more negative for sequence compared to random blocks in controls, replicating our previous results, and did not differ in patients. In addition, a separate analysis revealed a similar effect in connections from SMA and PMC to M1 bilaterally. Again, neural network changes were associated with learning performance in patients. Specifically, learners showed a negative modulation from right SMA to right M1 that was similar to controls, whereas this effect was close to zero in non-learners. These results highlight the role of cerebellum in motor learning and demonstrate the functional role cerebellum plays as part of the cortico-striato-cerebellar network.
Project description:In the absence of sensory stimulation or motor output, the brain exhibits complex spatiotemporal patterns of intrinsically generated neural activity. Analysis of ongoing brain dynamics has identified the prevailing modes of cortico-cortical interaction; however, little is known about how such patterns of intrinsically generated activity are correlated between cortical and subcortical brain areas. We investigate the correlation structure of ongoing cortical and superior colliculus (SC) activity across multiple spatial and temporal scales. Ongoing cortico-tectal interaction was characterized by correlated fluctuations in the amplitude of delta, spindle, low gamma, and high-frequency oscillations (>100 Hz). Of these identified coupling modes, topographical patterns of high-frequency coupling were the most consistent with patterns of anatomical connectivity, reflecting synchronized spiking within cortico-tectal networks. Cortico-tectal coupling at high frequencies was temporally parcellated by the phase of slow cortical oscillations and was strongest for SC-cortex channel pairs that displayed overlapping visual spatial receptive fields. Despite displaying a high degree of spatial specificity, cortico-tectal coupling in lower-frequency bands did not match patterns of cortex-to-SC anatomical connectivity. Collectively, our findings demonstrate that neural activity is spontaneously coupled between cortex and SC, with high- and low-frequency modes of coupling reflecting direct and indirect cortico-tectal interactions, respectively.
Project description:Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique that has been shown to alter cortical excitability and activity via application of weak direct currents. Beyond intracortical effects, functional imaging as well as behavioral studies are suggesting additional tDCS-driven alterations of subcortical areas, however, direct evidence for such effects is scarce. We aimed to investigate the impact of tDCS on cortico-subcortical functional networks by seed functional connectivity analysis of different striatal and thalamic regions to prove tDCS-induced alterations of the cortico-striato-thalamic circuit. fMRI resting state data sets were acquired immediately before and after 10 min of bipolar tDCS during rest, with the anode/cathode placed over the left primary motor cortex (M1) and the cathode/anode over the contralateral frontopolar cortex. To control for possible placebo effects, an additional sham stimulation session was carried out. Functional coupling between the left thalamus and the ipsilateral primary motor cortex (M1) significantly increased following anodal stimulation over M1. Additionally, functional connectivity between the left caudate nucleus and parietal association cortices was significantly strengthened. In contrast, cathodal tDCS over M1 decreased functional coupling between left M1 and contralateral putamen. In summary, in this study, we show for the first time that tDCS modulates functional connectivity of cortico-striatal and thalamo-cortical circuits. Here we highlight that anodal tDCS over M1 is capable of modulating elements of the cortico-striato-thalamo-cortical functional motor circuit.
Project description:ObjectiveThe aim of the present study was to investigate the optimal stimulation parameters for eliciting cortico-cortical evoked potentials (CCEPs) for mapping functional and epileptogenic networks.MethodsWe studied 13 patients with refractory epilepsy undergoing intracranial EEG monitoring. We systematically titrated the intensity of single-pulse electrical stimulation at multiple sites to assess the effect of increasing current on salient features of CCEPs such as N1 potential magnitude, signal to noise ratio, waveform similarity, and spatial distribution of responses. Responses at each incremental stimulation setting were compared to each other and to a final set of responses at the maximum intensity used in each patient (3.5-10 mA, median 6 mA).ResultsWe found that with a biphasic 0.15 ms/phase pulse at least 2-4 mA is needed to differentiate between non-responsive and responsive sites, and that stimulation currents of 6-7 mA are needed to maximize amplitude and spatial distribution of N1 responses and stabilize waveform morphology.ConclusionsWe determined a minimum stimulation threshold necessary for eliciting CCEPs, as well as a point at which the current-dependent relationship of several response metrics all saturate.SignificanceThis titration study provides practical, immediate guidance on optimal stimulation parameters to study specific features of CCEPs, which have been increasingly used to map both functional and epileptic brain networks in humans.
Project description:The level of activity of many animals including humans rises and falls with a period of ~ 24 hours. The intrinsic biological oscillator that gives rise to this circadian oscillation is driven by a molecular feedback loop with an approximately 24 hour cycle period and is influenced by the environment, most notably the light:dark cycle. In addition to the circadian oscillations, behavior of many animals is influenced by multiple oscillations occurring at faster-ultradian-time scales. These ultradian oscillations are also thought to be driven by feedback loops. While many studies have focused on identifying such ultradian oscillations, less is known about how the ultradian behavioral oscillations interact with each other and with the circadian oscillation. Decoding the coupling among the various physiological oscillators may be important for understanding how they conspire together to regulate the normal activity levels, as well in disease states in which such rhythmic fluctuations in behavior may be disrupted. Here, we use a wavelet-based cross-frequency analysis to show that different oscillations identified in spontaneous mouse behavior are coupled such that the amplitude of oscillations occurring at higher frequencies are modulated by the phase of the slower oscillations. The patterns of these interactions are different among different individuals. Yet this variability is not random. Differences in the pattern of interactions are confined to a low dimensional subspace where different patterns of interactions form clusters. These clusters expose the differences among individuals-males and females are preferentially segregated into different clusters. These sex-specific features of spontaneous behavior were not apparent in the spectra. Thus, our methodology reveals novel aspects of the structure of spontaneous animal behavior that are not observable using conventional methodology.
Project description:While functional imaging is widely used in studies of the brain, how well the hemodynamic signal represents the underlying neural activity is still unclear. And there is a debate on whether hemodynamic signal is more tightly related to synaptic activity or action potentials. This study intends to address these questions by examining neurovascular coupling driven by pyramidal cells in the motor cortex of rats. Pyramidal cells in the motor cortex of rats were selectively transduced with the light sensitive cation channel channelrhodopsin-2 (ChR2). Electrophysiological recordings and optical intrinsic signal imaging were performed simultaneously and synchronously to capture the neural activity and hemodynamics induced by optical stimulation of ChR2-expressing pyramidal cells. Our results indicate that both synaptic activity (local field potential, LFP) and action potentials (multi-unit activity, MUA) are tightly related to hemodynamic signals. While LFPs in γ band are better in predicting hemodynamic signals elicited by short stimuli, MUA has better predictions to hemodynamic signals elicited by long stimuli. Our results also indicate that strong nonlinearity exists in neurovascular coupling.