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Simulating TMS during PET using a large-scale neural network of the visual system
NemoImage
11, Number
5, 2000,
Part 2 of 2 Parts 1 DE
METHODS
a[@
- ACQUISITION
Simulating TMS During PET Using a Large-Scale Neural Network of the Visual System G. Nandipati”,
F.T. Husain*, A.R. Braun*, M.-A. Tagametsi, B. Horwitz*
*Language Section, National Institute on Deafiess and other Communication Disorders, NIH, Bethesda, MD, USA iMaryland
Psychiatric Research Center, Univ. of Maryland, Baltimore, MD, USA
Introduction During transcranial magnetic stimulation (TMS), a strong, changing magnetic field applied to a region on the scalp induces intracranial electrical currents that can alter regional neuronal function. TMS exerts both excitatory and inhibitory effects on stimulated neural tissue, although little is known about the exact neurobiological mechanisms by which TMS alters neuronal function. TMS has been used in conjunction with positron emission tomography (PET) to examine interregional connectivity of human cerebral cortex [2]. In this study, we simulated the effect of TMS using a large-scale, neurobiologically realistic model [3] with multiple, interconnected brain regions that performs a visual delayed match-to-sample (DMS) task. In the model, simulated electrical activities in each region are similar to those found in single-cell monkey data, and the simulated integrated summed synaptic activities matches regional cerebral blood flow (rCBF) data obtained in human PET studies. In the present simulations, TMS was applied to this model to investigate its effects on DMS task performance, and on rCBF in regions connected to the stimulated area. Methods The simulated experimental condition is a visual shape-matching task with a delay period. The regions comprising the model represent the “right” hemisphere of the ventral visual processing stream: VlN2, V4, IT (inferior-temporal cortex), PFC (prefrontal cortex), and a frontal response module. The model’s basic element is an excitatory-inhibitory interacting pair of units representing a cortical column (whose basic time unit is 5 msec), with intra- and inter-regional connections based on primate neuroanatomical data. Visual stimuli are presented to the model’s lateral geniculate nucleus. The PET response is simulated by temporally and spatially integrating the absolute value of the synaptic activity in each region over the time course of the study. The task was to match a delayed (second) stimulus to a sample (first) stimulus and was simulated via an attentional unit that had diffuse synapses onto PFC units, which in turn, had feedback connections to IT and V4; if a match occurred, units in the frontal response module increased their electrical activity. TMS was simulated as a 5 Hz pulse train of different current intensities delivered during the delay period to the PFC units. Results When TMS of sufficient intensity was applied to both the excitatory and inhibitory units of the PFC, the number of errors made by the system increased: response units did not differentiate between a match and a non-match stimulus. This result is similar to that found by Pascual-Leone and Hallett [1], who found that applying TMS during the delay period of a DMS task impaired performance by increasing response errors. Applying TMS to the inhibitory units alone also led to impaired performance by the model. Using PET, Paus et al. [2] reported that TMS stimulation of sensory cortex resulted in a reduction in lCBF that covaried with the number of TMS pulse trains in regions functionally connected to the site of stimulation. This was reflected in our simulations, but only when TMS was applied just to the inhibitory units in PFC: there were reductions in rCBF in anatomically connected brain regions (e.g., IT and V4) that correlated with the intensity of the applied TMS. However, when both the excitatory and inhibitory units of PFC were stimulated, there was a slight increase in blood flow in PFC, IT and V4. Discussion In this simulation study, we used a neurobiologically realistic, large-scale neural model to investigate the biological correlates of TMS, and the relation between TMS and changes in rCBF, as measured by PET. We demonstrated that our manner of simulating TMS led to performance errors on the DMS task, which was the case when TMS was applied to both excitatory and inhibitory units, and only to inhibitory units. We also showed that we could reproduce the experimental finding of decreased rCBF following TMS in brain regions functionally connected to the stimulation site. However, this occurred only if TMS was applied to the inhibitory neuronal population. References [I] Pascual-Leone, A. and Hallett, [2] Paus, T., et al., J. Neurophysiol., [3] Tagamets, M.-A. and Horwitz,
M., NeuroReport, 1994, 5: 2517-2520. 1998, 79:1102-1107. B., Cerebral Cortex, 1998, 8310-320.
S492
11, Number
5, 2000,
Part 2 of 2 Parts 1 DE
METHODS
a[@
- ACQUISITION
Simulating TMS During PET Using a Large-Scale Neural Network of the Visual System G. Nandipati”,
F.T. Husain*, A.R. Braun*, M.-A. Tagametsi, B. Horwitz*
*Language Section, National Institute on Deafiess and other Communication Disorders, NIH, Bethesda, MD, USA iMaryland
Psychiatric Research Center, Univ. of Maryland, Baltimore, MD, USA
Introduction During transcranial magnetic stimulation (TMS), a strong, changing magnetic field applied to a region on the scalp induces intracranial electrical currents that can alter regional neuronal function. TMS exerts both excitatory and inhibitory effects on stimulated neural tissue, although little is known about the exact neurobiological mechanisms by which TMS alters neuronal function. TMS has been used in conjunction with positron emission tomography (PET) to examine interregional connectivity of human cerebral cortex [2]. In this study, we simulated the effect of TMS using a large-scale, neurobiologically realistic model [3] with multiple, interconnected brain regions that performs a visual delayed match-to-sample (DMS) task. In the model, simulated electrical activities in each region are similar to those found in single-cell monkey data, and the simulated integrated summed synaptic activities matches regional cerebral blood flow (rCBF) data obtained in human PET studies. In the present simulations, TMS was applied to this model to investigate its effects on DMS task performance, and on rCBF in regions connected to the stimulated area. Methods The simulated experimental condition is a visual shape-matching task with a delay period. The regions comprising the model represent the “right” hemisphere of the ventral visual processing stream: VlN2, V4, IT (inferior-temporal cortex), PFC (prefrontal cortex), and a frontal response module. The model’s basic element is an excitatory-inhibitory interacting pair of units representing a cortical column (whose basic time unit is 5 msec), with intra- and inter-regional connections based on primate neuroanatomical data. Visual stimuli are presented to the model’s lateral geniculate nucleus. The PET response is simulated by temporally and spatially integrating the absolute value of the synaptic activity in each region over the time course of the study. The task was to match a delayed (second) stimulus to a sample (first) stimulus and was simulated via an attentional unit that had diffuse synapses onto PFC units, which in turn, had feedback connections to IT and V4; if a match occurred, units in the frontal response module increased their electrical activity. TMS was simulated as a 5 Hz pulse train of different current intensities delivered during the delay period to the PFC units. Results When TMS of sufficient intensity was applied to both the excitatory and inhibitory units of the PFC, the number of errors made by the system increased: response units did not differentiate between a match and a non-match stimulus. This result is similar to that found by Pascual-Leone and Hallett [1], who found that applying TMS during the delay period of a DMS task impaired performance by increasing response errors. Applying TMS to the inhibitory units alone also led to impaired performance by the model. Using PET, Paus et al. [2] reported that TMS stimulation of sensory cortex resulted in a reduction in lCBF that covaried with the number of TMS pulse trains in regions functionally connected to the site of stimulation. This was reflected in our simulations, but only when TMS was applied just to the inhibitory units in PFC: there were reductions in rCBF in anatomically connected brain regions (e.g., IT and V4) that correlated with the intensity of the applied TMS. However, when both the excitatory and inhibitory units of PFC were stimulated, there was a slight increase in blood flow in PFC, IT and V4. Discussion In this simulation study, we used a neurobiologically realistic, large-scale neural model to investigate the biological correlates of TMS, and the relation between TMS and changes in rCBF, as measured by PET. We demonstrated that our manner of simulating TMS led to performance errors on the DMS task, which was the case when TMS was applied to both excitatory and inhibitory units, and only to inhibitory units. We also showed that we could reproduce the experimental finding of decreased rCBF following TMS in brain regions functionally connected to the stimulation site. However, this occurred only if TMS was applied to the inhibitory neuronal population. References [I] Pascual-Leone, A. and Hallett, [2] Paus, T., et al., J. Neurophysiol., [3] Tagamets, M.-A. and Horwitz,
M., NeuroReport, 1994, 5: 2517-2520. 1998, 79:1102-1107. B., Cerebral Cortex, 1998, 8310-320.
S492