Our laboratory studies the relationship between what is observed in functional neuroimaging studies and the underlying neural dynamics (Horwitz & Banerjee, 2012). To do this, we use large-scale computer models of neuronal dynamics that perform either a visual or auditory object-matching task similar to those designed for PET/fMRI/MEG studies. A review of both models can be found in Horwitz & Husain (2007). We also develop computational methods for fMRI and MEG data that allow us to investigate functional brain networks in normal human subjects and in patients with sensory and cognitive processing disorders. Our auditory processing neural modeling has been used for trying to understand the neural basis of tinnitus, which is the perception of sound in the absence of an external source (see Husain, 2007). Tinnitus is often accompanied by hearing loss but not everyone with hearing loss experiences tinnitus. Models make it possible to evaluate the contribution of different neural mechanisms affecting tinnitus in a principled manner. To obtain experimental data that could be compared to our neural model, we first examined neuroanatomical alterations associated with hearing loss and tinnitus in three groups of subjects: those with hearing loss with tinnitus, those with hearing loss without tinnitus and normal hearing controls without tinnitus. To examine changes in gray matter, we (Husain et al., 2011) used structural MRI scans and voxel-based morphometry (VBM), and to identify changes in white matter tract integrity we used diffusion tensor imaging (DTI). A major finding of our study was that there were both gray and white matter changes in the vicinity of the auditory cortex for subjects with hearing loss alone relative to those with tinnitus and those with normal hearing. We did not find significant changes in gray or white matter in subjects with tinnitus and hearing loss compared to normal hearing controls. Thus, in attempting to dissociate the effect of tinnitus from hearing loss, we observed that hearing loss rather than tinnitus had the greatest influence on gray and white matter alterations. To see if functional neural imaging was more sensitive than structural neural imaging with respect to tinnitus, we used fMRI to investigate differences among the three groups in auditory perception and cognitive processing. We employed pure tones and frequency-modulated sweeps as stimuli in two tasks: passive listening and active discrimination. Results suggest that a differential engagement of a putative auditory network, comprising regions in the frontal, parietal and temporal cortices and the anterior cingulate, may represent a key difference in the neural bases of chronic tinnitus accompanied by hearing loss relative to hearing loss alone (Husain et al., 2011). Our laboratory also has performed studies to elucidate the neural basis of speech production and its disorders. Central brain structures include the laryngeal motor cortex, which is indispensable for the vocal motor control of speech and song production, premotor cortex and left inferior frontal gyrus. We reviewed two fields of investigations of dopamine action on voice control in humans and songbirds, who share similar behavioral and neural mechanisms for speech and song production (Simonyan et al., 2012). An important disorder associated with aberrant speech production is stuttering. We used MRI to examine functional and structural connectivity within cortico-cortical loops in adults who stutter and compared the findings with those obtained individuals who do not stutter (Chang et al., 2011). Psychophysiological interaction (PPI) was used to find brain regions with heightened functional connectivity with the left and right inferior frontal gyri during speech and nonspeech tasks. Probabilistic tractography was used to track white matter tracts in each hemisphere using the same seed regions. Both PPI and tractography supported connectivity deficits between the left inferior frontal gyrus and the left premotor regions, while connectivity among homologous right hemisphere structures was significantly increased in the stuttering group, providing support for deficient left hemisphere inferior frontal to premotor connectivity as a neural correlate of stuttering. Functional neuroimaging has shown that multiple brain regions are active during volitional swallowing. Although unilateral brain lesions in either hemisphere can produce swallowing deficits, some functional neuroimaging studies indicate that the left hemisphere has greater activation in certain sensory and motor-related swallowing regions. In our fMRI study (Lowell et al., 2012), correlation coefficients were computed for five seed regions during volitional saliva swallowing to determine the functional relationships of these regions with the rest of the brain: the anterior and posterior insula, inferior frontal gyrus, primary sensory cortex, and primary motor cortex. A laterality index was derived that accounts for relative differences in total, positive connected voxels for the left/right hemisphere seeds. Clusters of significantly connected voxels were greater from the anterior and posterior insula than from the other three seed regions. There was greater connectivity from the left hemisphere insula to brain regions within and across hemispheres, suggesting that the insula is a primary integrative region for volitional swallowing in humans. Our laboratory has also continued to develop new methods for employing brain fMRI and MEG data to evaluate how different brain regions interact with one another during the performance of sensory, motor and cognitive tasks (i.e., brain network methods to calculate functional and effective connectivity). One potentially important application of these methods is for use as biomarkers for neurological and psychiatric disorders (Horwitz & Horovitz, 2012; Horovitz & Horwitz, 2012). An overview of the employment of such neuroimaging biomarkers for neurodegenerative disorders (Horwitz and Rowe, 2011) discussed the various uses that functional neuroimaging biomarkers can play in detecting, diagnosing, assessing treatment response and investigating neurodegenerative disorders. We went on to explain why the emphasis of much recent work has shifted to network-based biomarkers, as opposed to those that examine individual brain regions. Analysis of directionally specific interactions (effective connectivity) between brain regions in fMRI data has proliferated. We (Smith et al., 2012) identified six unresolved issues with existing effective connectivity methods. These included, for example, the correct identification of the network itself including the number and anatomical origin of the network nodes, and the locus of the signal used as a node in a network. We introduced potential solutions to these issues within the framework of linear dynamic systems. Unlike fMRI data, MEG provides data with high temporal resolution. We reviewed some functional connectivity methods used with such data to investigate large-scale neuronal assemblies mediating complex cognitive tasks (Banerjee et al., 2012a). We also developed a method (TMCN temporal microstructure of cortical networks) for use with MEG for determining how such neurocognitive networks reorganize spatiotemporally on the order of a few milliseconds to process specific aspects of a task (Banerjee et al., 2012b). We applied TMCN using a paired associated task applied to long term memory recall comparing visual-auditory and visual-visual pairs. We found that visualvisual and visual auditory memory recollection involves equivalent network components without any additional recruitment during an initial period of sensory processing, but is then followed by recruitment of additional network components for modality specific memory recollection.