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M-A Tagamets

Publications and source records attributed to M-A Tagamets.

3 recordsLinked to original sources

Investigating the neural basis for functional and effective connectivity. Application to fMRI.

Viewing cognitive functions as mediated by networks has begun to play a central role in interpreting neuroscientific data, and studies evaluating interregional functional and effective connectivity have become staples of the neuroimaging literature. The neurobiological substrates of functional and effective connectivity are, however, uncertain. We have constructed neurobiologically realistic models for visual and auditory object processing with multiple interconnected brain regions that perform delayed match-to-sample (DMS) tasks. We used these models to investigate how neurobiological parameters affect the interregional functional connectivity between functional magnetic resonance imaging (fMRI) time-series. Variability is included in the models as subject-to-subject differences in the strengths of anatomical connections, scan-to-scan changes in the level of attention, and trial-to-trial interactions with non-specific neurons processing noise stimuli. We find that time-series correlations between integrated synaptic activities between the anterior temporal and the prefrontal cortex were larger during the DMS task than during a control task. These results were less clear when the integrated synaptic activity was haemodynamically convolved to generate simulated fMRI activity. As the strength of the model anatomical connectivity between temporal and frontal cortex was weakened, so too was the strength of the corresponding functional connectivity. These results provide a partial validation for using fMRI functional connectivity to assess brain interregional relations.

Auditory Perception↗

Relating neuronal dynamics for auditory object processing to neuroimaging activity: a computational modeling and an fMRI study.

We investigated the neural basis of auditory object processing in the cerebral cortex by combining neural modeling and functional neuroimaging. We developed a large-scale, neurobiologically realistic network model of auditory pattern recognition that relates the neuronal dynamics of cortical auditory processing of frequency modulated (FM) sweeps to functional neuroimaging data of the type obtained using PET and fMRI. Areas included in the model extend from primary auditory to prefrontal cortex. The electrical activities of the neuronal units of the model were constrained to agree with data from the neurophysiological literature regarding the perception of FM sweeps. We also conducted an fMRI experiment using stimuli and tasks similar to those used in our simulations. The integrated synaptic activity of the neuronal units in each region of the model, convolved with a hemodynamic response function, was used as a correlate of the simulated fMRI activity, and generally agreed with the experimentally observed fMRI data in the brain areas corresponding to the regions of the model. Our results demonstrate that the model is capable of exhibiting the salient features of both electrophysiological neuronal activities and fMRI values that are in agreement with empirically observed data. These findings provide support for our hypotheses concerning how auditory objects are processed by primate neocortex.

Adult↗

Simulating transcranial magnetic stimulation during PET with a large-scale neural network model of the prefrontal cortex and the visual system.

Transcranial magnetic stimulation (TMS) exerts both excitatory and inhibitory effects on the stimulated neural tissue, although little is known about the neurobiological mechanisms by which it influences neuronal function. TMS has been used in conjunction with PET to examine interregional connectivity of human cerebral cortex. To help understand how TMS affects neuronal function, and how these effects are manifested during functional brain imaging, we simulated the effects of TMS on a large-scale neurobiologically realistic computational model consisting of multiple, interconnected regions that performs a visual delayed-match-to-sample task. The simulated electrical activities in each region of the model are similar to those found in single-cell monkey data, and the simulated integrated summed synaptic activities match regional cerebral blood flow (rCBF) data obtained in human PET studies. In the present simulations, the excitatory and inhibitory effects of TMS on both locally stimulated and distal sites were studied using simulated behavioral measures and simulated PET rCBF results. The application of TMS to either excitatory or inhibitory units of the model, or both, resulted in an increased number of errors in the task performed by the model. In experimental studies, both increases and decreases in rCBF following TMS have been observed. In the model, increasing TMS intensity caused an increase in rCBF when TMS exerted a predominantly excitatory effect, whereas decreased rCBF following TMS occurred if TMS exerted a predominantly inhibitory effect. We also found that regions both directly and indirectly connected to the stimulating site were affected by TMS.

Brain Mapping↗