- Email: [email protected]
Neural correlates of response inhibition for behavioral regulation in humans assessed by functional magnetic resonance imaging
Neuroscience Letters 309 (2001) 109±112
www.elsevier.com/locate/neulet
Neural correlates of response inhibition for behavioral regulation in humans assessed by functional magnetic resonance imaging Tatia M.C. Lee a,*, Ho-Ling Liu b, Ching-Mei Feng c, Jinwen Hou c, Srikanth Mahankali c, Peter T. Fox c, Jia-Hong Gao c a
Neuropsychology Laboratory, Department of Psychology, The University of Hong Kong, Pokfulam Road, Hong Kong Department of Medical Technology, Chang Gung University, Department of Diagnostic Radiology, Chang Gung Medical Center, Taoyuan, Taiwan c Research Imaging Center, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
b
Received 21 March 2001; received in revised form 22 June 2001; accepted 22 June 2001
Abstract To identify the speci®c frontal and cingulate regions involved in response inhibition, ®ve Chinese right-handed male volunteers with an attention span reaching or exceeding a 7-digit level participated in this blocked design functional magnetic resonance imaging study. Each block represented one of the two experimental conditions, the Correct Matching or the Incorrect Matching condition. In the Correct Matching condition, the subjects were required to make correct judgement of whether the two 3-digit numbers presented in succession were the same or not; whereas in the Incorrect Matching condition, the participants were instructed to inhibit the correct responses. Bilateral activations of the prefrontal and anterior cingulate as well as the left posterior cingulated cortex were observed while the subjects were exercising response inhibition. The roles of these activations in response inhibition were discussed. q 2001 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Disinhibition; Inhibition; Prefrontal; Cingulate; Dorsolateral-prefrontal; Orbitofrontal
Inhibition refers to the cognitive regulation of habitual responses to meet target behaviors. Ef®cient inhibitory processes are essential for controlled cognitive processing leading to co-ordinated behavioral output. Indeed, it has been suggested that the development of inhibitory mechanisms accounts for age-related differences in cognitive behavior [5], and age-related impaired performance on a number of tasks is the result of the weakening of inhibitory processes accompanying the normal ageing process [8]. Evidence of the role of the prefrontal cortex in inhibitory mechanisms comes from a number of animal and human studies (e.g. [2,15]). A cortico-subcortical circuit involving the dorsolateral prefrontal, orbitofrontal, mediofrontal and/ or anterior cingulate circuits has been proposed as possible neural correlates of the cognitive control of behavioral disinhibition [7]. Konishi et al. [10] proposed that the right prefrontal cortex may be a key structure for response inhibition for behavioral regulation. It has been suggested * Corresponding author. Tel.: 1852-2857-8394; fax: 1852-28583518. E-mail address: [email protected] (T.M.C. Lee).
that inhibitory processes are typically associated with more ventral/orbital frontal regions [6]. Casey et al. [4], however, revealed activation that was distributed across both the dorsolateral and orbitofrontal cortices. In addition to the frontal circuit, Posner and Dahaene [16] have proposed that the anterior cingulate cortex (ACC) plays a prominent role in the executive control of cognition. To integrate the data, MacDonald et al. [13] have recently suggested that cognitive control is a dynamic process implemented in the brain by a distributed network that involves closely interacting, but nevertheless anatomically dissociable, components. Within this system, the dorsolateral prefrontal cortex (DLPFC) provides top-down support of task-appropriate behaviors, whereas other components, such as the ACC, are likely to be involved in evaluative processes indicating when control needs to be more strongly engaged. To identify the speci®c frontal and cingulate regions involved in response inhibition, we employed functional magnetic resonance imaging (fMRI) technology and used a blocked design format. Next we had to decide on the experimental tasks. It is well recognized that clinical dif®culties in inhibiting habitual responses can be examined by
0304-3940/01/$ - see front matter q 2001 Elsevier Science Ireland Ltd. All rights reserved. PII: S03 04 - 394 0( 0 1) 02 04 3- 2
110
T.M.C. Lee et al. / Neuroscience Letters 309 (2001) 109±112
tests in which the patient must make converse responses to the examiner's signals [12]. For example, if the examiner taps once, the patient must tap twice and vice versa. Patients with self-regulation problems may irresistibly follow the examiner's response pattern. In order to use neuroimaging to understand clinical neuropsychological phenomenon of response inhibition, we decided to adapt the above stated commonly use clinical method for assessment of response inhibition for use in our fMRI study. Two 3-digit numbers, same or different, were presented in succession. The subjects were to decide if the pair was the same or not. They were then required to inhibit their correct responses and give the opposite answers. The data of our study were expected to inform us about the speci®c prefrontal and cingulate activations when inhibition of habitual responses was exercised while performing on this simulated clinical assessment procedure for response inhibition. Our study was conducted at the Research Imaging Center, the University of Texas Health Science Center at San Antonio (UTHSCSA). Five male volunteers participated in this fMRI study. They gave informed consent in accordance with guidelines set by the UTHSCSA. All subjects were native Chinese (Mandarin) speakers from Mainland China, ranging in age from 31.6 to 37.2 years. All subjects were strongly right-handed, as judged by the Lateral Dominance Test [12]. Inclusion criteria were: (1) subjects' attention span reached or exceeded a 7-digit level as measured by the Digit Span Test; and (2) subjects obtained full scores on the digit task to be administered during scanning. Experiments were performed on a 1.9T GE/Elscint Prestige whole-body magnetic resonance imaging (MRI) scanner (GE/Elscint Ltd., Haifa, Israel). We performed a blocked design fMRI study employing a digit task of a forced-choice format. The subject was presented with a 3digit number presented for 0.75 s followed by visual ®xation on a cross hair for 2.25 s and another 3-digit number for 0.75 s. After presenting the pair of digits a cross hair was shown for 3.25 s. With four questions in each experimental condition, the total duration per condition is 28 s. Each experimental condition was repeated three times and the order of presentation was counter-balanced. All stimuli were shown through a LED projector system. The participant was to decide if the two stimuli were the same. Pressing an air pump connected to a bell in the MRI console room indicated a `yes' response. Each block represented one of the two experimental conditions, the Correct Matching or the Incorrect Matching condition. In the Correct Matching condition, the participants were to press the pump for a correct answer. However, in the Incorrect Matching condition, the participants were instructed to inhibit the correct responses and answered incorrectly. Furthermore, it was made very clear to them that they should make a correct recall ®rst, and then inhibit their usual response and answer incorrectly. A T2*-weighted gradient-echo EPI sequence was used for the fMRI scans, with the slice thickness was 6 mm, in-plane resolution 2.9 mm £ 2.9 mm, and TR=TE=FA 2000
ms/45 ms/908. Twenty axial slices were acquired to cover the whole brain. For the anatomical detail, a T1-weighted image was obtained with a resolution of 1 mm 3. Brain activation during both the Correct Matching and the Incorrect Matching conditions was measured. By subtracting the cerebral activity of the former from the latter, a clear picture about the pattern of brain activation underlying inhibition was provided. We used Matlab (The Math Works, Inc., Natick, MA, USA) and in-house software for image data processing [20], including corrections for head motion and global MRI signal shift. Altogether 14 images were acquired in each task block, and each condition was repeated three times. After excluding the ®rst four images of each condition from further functional data processing to minimize the transit effects of hemodynamic responses, a total of 30 images were obtained for each experimental condition. Activation maps were calculated by comparing images acquired during the Incorrect Matching and Correct Matching task states, using a t-test. Both of the activation maps and the T1 images were spatially normalized to the Talairach brain atlas [19] using a Convex Hull algorithm [11]. The averaged activation maps across subjects with a tvalue threshold of 2.4 (P , 0:01, uncorrected) were then overlaid on the corresponding T1 images. Clusters with an activation volume smaller than 120 mm 3 were excluded from the functional map [20]. For each comparison, the Talairach co-ordinates of the center-of-mass and volume of the activation clusters were determined based on the averaged activation maps. The ®ve subjects did not commit any errors in the two experimental conditions. Brain activation fMRI images averaged across the ®ve subjects for Incorrect Matching minus Correctly Matching are shown in Fig. 1. The results indicate that activations of the bilateral fronto-polar prefrontal (BA 10), dorsolateral prefrontal (DLPFC) (BA 9/46 on the right and BA 9 on the left side) and orbitofrontal (BA 11/ 47 on the right and BA 11/25/47 on the left side) cortices were observed while subjects were exercising response inhibition. Activations of the anterior cingulate cortices bilaterally and left posterior cingulate cortex were also observed. Other activations that were considered not directly related to response inhibition under study included that in the BA 6, 8, 45, and temporal-occipital regions. These activations are excluded from further discussion in this report. Nevertheless, we speculated that activation of motor speech region on the left side (BA 45) may relate to subvocalization and conforms to the expectation of a left hemispheric dominance pattern of our participants. Residual activations of BA 6 and 8 and that in the temporal and occipital regions may relate to increased task demand in the Incorrect Matching condition. Our ®ndings concur with Casey et al.'s [4] observations that both dorsolateral and orbitofrontal cortices are involved when habitual responses are inhibited. Furthermore, cingulate activations were observed, which in general is consistent with MacDonald et al.'s [13] speculation that both
T.M.C. Lee et al. / Neuroscience Letters 309 (2001) 109±112
111
Fig. 1. Functional maps. Normalized activation brain maps averaged across ®ve subjects demonstrate the statistically signi®cant activations (P , 0:01 uncorrected) in response inhibition activation for correct matching with the activation for incorrect matching removed) when performing on the digit task. Planes are axial sections, labeled with the height (mm) relative to the bicommissural line. L, the left hemisphere; R, the right hemisphere.
prefrontal and cingulate cortices are required for response inhibition. However, generalization of our ®ndings should be done with caution given the small sample size. It is well-known that prefrontal activation is contingent upon task speci®c working memory representation for goal directed information manipulation and integration and programming strategies, rather than a simple re¯ection of working memory load [17]. Speci®cally, activation of the fronto-polar prefrontal region (BA 10) was responsible for holding in place primary goals while still processing secondary goals simultaneously [9]. This matches with the demand of response inhibition studied here because the subjects had to make a correct judgement ®rst as their primary goal while they were required to inhibit the correct judgement and presented the opposite answer as their secondary goal. Activation of the dorsolateral prefrontal region (BA 9 & 46), on the other hand, represented anticipation of performance [18] and cognitive control [13]. The orbitofrontal activation observed may re¯ect an emotional response to the `reward' of task accomplishment [14]. All these functions are essential for ef®cient response inhibition. Activation of the anterior cingulate cortex (ACC) (BA 24/ 32) is likely due to performance [13] as well as con¯ict monitoring by detecting response competition [3]. Indeed, previous studies did show that the ACC was activated not only during erroneous responses but also during correct responses when there was increased response competition. This implies that the ACC detects conditions under which errors are likely to occur rather than errors themselves. In other words, the ACC is involved in monitoring and compensating for errors [3], which is an integral part of response inhibition studied here. Activation of the posterior cingulate (BA 23) regions, on the other hand, is most likely related to the inhibition of previously learned rules and selfmonitoring of random errors [1], which is essential for inhibition of habitual responses.
Previous studies on response inhibition have suggested that the locus of inhibition is in the right prefrontal cortex (see for example ref. [10]). Our observation is more in line with the ®ndings and speculations of Casey et al. [4] and MacDonald et al. [13]. Bilateral activations of prefrontal and cingulated regions tend to support the speculation of a neural network rather than a locus of control for the execution and monitoring of response inhibition. We further speculated that the prefrontal activation may be involved in representing and maintaining the attention for task performance, and the cingulate activation may be involved in evaluative processes, such as monitoring the occurrence of errors or the presence of response con¯ict, which occurs when two incompatible responses are both compelling. This speculation is awaiting veri®cation in future research. [1] Amos, A., A computational model of information processing in the frontal cortex and basal ganglia, J. Cogn. Neurosci., 12 (2000) 505±519. [2] Buchkremer-Ratzmann, I. and Witte, O.W., Extended brain disinhibition following small photothrombotic lesions in rat frontal cortex, NeuroReport, 8 (1996) 519±522. [3] Carter, C.S., Braver, T.S., Barch, D.M., Botvinick, M.M., Noll, D. and Cohen, J.D., Anterior cingulate cortex, error detection, and the online monitoring of performance, Science, 280 (1998) 747±749. [4] Casey, B.J., Trainor, R.J., Orendi, J.L., Schubert, A.B., Nystrom, L.E., Giedd, J.N., Castellanos, X., Haxby, J.V., Noll, D.C., Cohen, J.D., Forman, S.D., Dahl, R.E. and Rapoport, J.L., A developmental functional MRI study of prefrontal activation during performance of a Go-No-Go task, J. Cogn. Neurosci., 9 (1997) 835±847. [5] Dempster, F.N., The rise and fall of the inhibitory mechanism: Toward a uni®ed theory of cognitive development and aging, Dev. Rev., 12 (1992) 45±75. [6] Fuster, J.M., The Prefrontal Cortex: Anatomy, Physiology and Neuropsychology of the Frontal Lobe, Raven Press, New York, 1989, 110pp. [7] Harnishfeger, K.K. and Bjorklund, D.F., The ontogeny of inhibition mechanisms: A renewed approach to cognitive
112
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[11]
[12] [13]
T.M.C. Lee et al. / Neuroscience Letters 309 (2001) 109±112 development, In M.L. Howe and R. Pasnak (Eds.), Emerging Themes in Cognitive Development, Springer-Verlag, New York, 1993, pp. 28±49. Kane, M.L., Hasher, L., Stoltzfus, E.R., Zacks, R.T. and Connelly, S.L., Inhibitory attentional mechanisms and ageing, Psychol. Aging., 9 (1994) 103±112. Koechlin, E., Basso, G., Pietrini, P., Panzer, S. and Grafman, J., The role of the anterior prefrontal cortex in human cognition, Nature, 399 (1999) 48±151. Konishi, S., Nakajima, K., Uchida, I., Kikyo, H., Kameyama, M. and Miyashita, Y., Common inhibitory mechanism in human inferior prefrontal cortex revealed by event-related functional MRI, Brain, 122 (1999) 981±991. Lancaster, J.L., Fox, P.T., Downs, H., Nickerson, D.S., Hander, T.A., Mallah, M.E., Kochunov, P.V. and Zamarripa, B., Global spatial normalization of human brain using convex halls, J. Nucl. Med., 40 (1999) 942±955. Lezak, M.D., Neuropsychological Assessment, 3rd ed., Oxford University Press, New York, 1995, 671pp. MacDonald, A.W., Cohen, J.D., Stenger, V.A. and Carter, C.S., Dissociating the role of the dorsolateral prefrontal
[14] [15] [16] [17]
[18] [19] [20]
and anterior cingulate cortex in cognitive control, Science, 288 (2000) 1835±1838. Maguire, E.A., Frith, C.D. and Morris, R.G.M., The functional neuroanatomy of comprehension and memory: the importance of prior knowledge, Brain, 122 (1999) 1839±1850. Malloy, P., Bihrlr, A. and Duffy, J., The orbitomedial frontal syndrome, Arch. Clin. Neuropsychol., 8 (1993) 185±201. Posner, M.I. and Dahaene, S., Attentional networks, Trends. Neurosci., 17 (1994) 75±79. Prabhakaran, V., Narayanan, Z., Zhao, Z. and Gabrieli, J.D.E., Integration of diverse information in working memory within the frontal lobe, Nat. Neurosci., 3 (2000) 85±90. Schacter, D.L., Buckner, R.L. and Koutstaal, W., Memory, consciousness, and neuroimaging, Philos. Trans. R. Soc. Lond., B353 (1998) 1861±1878. Talairach, J. and Tournoux, P., Co-planar Stereostatic Atlas of the Human brain, Theme Medical, New York, 1998, 1pp. Xiong, J., Gao, J.H., Lancaster, J.L. and Fox, P.T., Cluster pixels analysis for functional MRI activation studies in the human brain, Hum. Brain Mapp., 3 (1995) 209±223.
www.elsevier.com/locate/neulet
Neural correlates of response inhibition for behavioral regulation in humans assessed by functional magnetic resonance imaging Tatia M.C. Lee a,*, Ho-Ling Liu b, Ching-Mei Feng c, Jinwen Hou c, Srikanth Mahankali c, Peter T. Fox c, Jia-Hong Gao c a
Neuropsychology Laboratory, Department of Psychology, The University of Hong Kong, Pokfulam Road, Hong Kong Department of Medical Technology, Chang Gung University, Department of Diagnostic Radiology, Chang Gung Medical Center, Taoyuan, Taiwan c Research Imaging Center, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
b
Received 21 March 2001; received in revised form 22 June 2001; accepted 22 June 2001
Abstract To identify the speci®c frontal and cingulate regions involved in response inhibition, ®ve Chinese right-handed male volunteers with an attention span reaching or exceeding a 7-digit level participated in this blocked design functional magnetic resonance imaging study. Each block represented one of the two experimental conditions, the Correct Matching or the Incorrect Matching condition. In the Correct Matching condition, the subjects were required to make correct judgement of whether the two 3-digit numbers presented in succession were the same or not; whereas in the Incorrect Matching condition, the participants were instructed to inhibit the correct responses. Bilateral activations of the prefrontal and anterior cingulate as well as the left posterior cingulated cortex were observed while the subjects were exercising response inhibition. The roles of these activations in response inhibition were discussed. q 2001 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Disinhibition; Inhibition; Prefrontal; Cingulate; Dorsolateral-prefrontal; Orbitofrontal
Inhibition refers to the cognitive regulation of habitual responses to meet target behaviors. Ef®cient inhibitory processes are essential for controlled cognitive processing leading to co-ordinated behavioral output. Indeed, it has been suggested that the development of inhibitory mechanisms accounts for age-related differences in cognitive behavior [5], and age-related impaired performance on a number of tasks is the result of the weakening of inhibitory processes accompanying the normal ageing process [8]. Evidence of the role of the prefrontal cortex in inhibitory mechanisms comes from a number of animal and human studies (e.g. [2,15]). A cortico-subcortical circuit involving the dorsolateral prefrontal, orbitofrontal, mediofrontal and/ or anterior cingulate circuits has been proposed as possible neural correlates of the cognitive control of behavioral disinhibition [7]. Konishi et al. [10] proposed that the right prefrontal cortex may be a key structure for response inhibition for behavioral regulation. It has been suggested * Corresponding author. Tel.: 1852-2857-8394; fax: 1852-28583518. E-mail address: [email protected] (T.M.C. Lee).
that inhibitory processes are typically associated with more ventral/orbital frontal regions [6]. Casey et al. [4], however, revealed activation that was distributed across both the dorsolateral and orbitofrontal cortices. In addition to the frontal circuit, Posner and Dahaene [16] have proposed that the anterior cingulate cortex (ACC) plays a prominent role in the executive control of cognition. To integrate the data, MacDonald et al. [13] have recently suggested that cognitive control is a dynamic process implemented in the brain by a distributed network that involves closely interacting, but nevertheless anatomically dissociable, components. Within this system, the dorsolateral prefrontal cortex (DLPFC) provides top-down support of task-appropriate behaviors, whereas other components, such as the ACC, are likely to be involved in evaluative processes indicating when control needs to be more strongly engaged. To identify the speci®c frontal and cingulate regions involved in response inhibition, we employed functional magnetic resonance imaging (fMRI) technology and used a blocked design format. Next we had to decide on the experimental tasks. It is well recognized that clinical dif®culties in inhibiting habitual responses can be examined by
0304-3940/01/$ - see front matter q 2001 Elsevier Science Ireland Ltd. All rights reserved. PII: S03 04 - 394 0( 0 1) 02 04 3- 2
110
T.M.C. Lee et al. / Neuroscience Letters 309 (2001) 109±112
tests in which the patient must make converse responses to the examiner's signals [12]. For example, if the examiner taps once, the patient must tap twice and vice versa. Patients with self-regulation problems may irresistibly follow the examiner's response pattern. In order to use neuroimaging to understand clinical neuropsychological phenomenon of response inhibition, we decided to adapt the above stated commonly use clinical method for assessment of response inhibition for use in our fMRI study. Two 3-digit numbers, same or different, were presented in succession. The subjects were to decide if the pair was the same or not. They were then required to inhibit their correct responses and give the opposite answers. The data of our study were expected to inform us about the speci®c prefrontal and cingulate activations when inhibition of habitual responses was exercised while performing on this simulated clinical assessment procedure for response inhibition. Our study was conducted at the Research Imaging Center, the University of Texas Health Science Center at San Antonio (UTHSCSA). Five male volunteers participated in this fMRI study. They gave informed consent in accordance with guidelines set by the UTHSCSA. All subjects were native Chinese (Mandarin) speakers from Mainland China, ranging in age from 31.6 to 37.2 years. All subjects were strongly right-handed, as judged by the Lateral Dominance Test [12]. Inclusion criteria were: (1) subjects' attention span reached or exceeded a 7-digit level as measured by the Digit Span Test; and (2) subjects obtained full scores on the digit task to be administered during scanning. Experiments were performed on a 1.9T GE/Elscint Prestige whole-body magnetic resonance imaging (MRI) scanner (GE/Elscint Ltd., Haifa, Israel). We performed a blocked design fMRI study employing a digit task of a forced-choice format. The subject was presented with a 3digit number presented for 0.75 s followed by visual ®xation on a cross hair for 2.25 s and another 3-digit number for 0.75 s. After presenting the pair of digits a cross hair was shown for 3.25 s. With four questions in each experimental condition, the total duration per condition is 28 s. Each experimental condition was repeated three times and the order of presentation was counter-balanced. All stimuli were shown through a LED projector system. The participant was to decide if the two stimuli were the same. Pressing an air pump connected to a bell in the MRI console room indicated a `yes' response. Each block represented one of the two experimental conditions, the Correct Matching or the Incorrect Matching condition. In the Correct Matching condition, the participants were to press the pump for a correct answer. However, in the Incorrect Matching condition, the participants were instructed to inhibit the correct responses and answered incorrectly. Furthermore, it was made very clear to them that they should make a correct recall ®rst, and then inhibit their usual response and answer incorrectly. A T2*-weighted gradient-echo EPI sequence was used for the fMRI scans, with the slice thickness was 6 mm, in-plane resolution 2.9 mm £ 2.9 mm, and TR=TE=FA 2000
ms/45 ms/908. Twenty axial slices were acquired to cover the whole brain. For the anatomical detail, a T1-weighted image was obtained with a resolution of 1 mm 3. Brain activation during both the Correct Matching and the Incorrect Matching conditions was measured. By subtracting the cerebral activity of the former from the latter, a clear picture about the pattern of brain activation underlying inhibition was provided. We used Matlab (The Math Works, Inc., Natick, MA, USA) and in-house software for image data processing [20], including corrections for head motion and global MRI signal shift. Altogether 14 images were acquired in each task block, and each condition was repeated three times. After excluding the ®rst four images of each condition from further functional data processing to minimize the transit effects of hemodynamic responses, a total of 30 images were obtained for each experimental condition. Activation maps were calculated by comparing images acquired during the Incorrect Matching and Correct Matching task states, using a t-test. Both of the activation maps and the T1 images were spatially normalized to the Talairach brain atlas [19] using a Convex Hull algorithm [11]. The averaged activation maps across subjects with a tvalue threshold of 2.4 (P , 0:01, uncorrected) were then overlaid on the corresponding T1 images. Clusters with an activation volume smaller than 120 mm 3 were excluded from the functional map [20]. For each comparison, the Talairach co-ordinates of the center-of-mass and volume of the activation clusters were determined based on the averaged activation maps. The ®ve subjects did not commit any errors in the two experimental conditions. Brain activation fMRI images averaged across the ®ve subjects for Incorrect Matching minus Correctly Matching are shown in Fig. 1. The results indicate that activations of the bilateral fronto-polar prefrontal (BA 10), dorsolateral prefrontal (DLPFC) (BA 9/46 on the right and BA 9 on the left side) and orbitofrontal (BA 11/ 47 on the right and BA 11/25/47 on the left side) cortices were observed while subjects were exercising response inhibition. Activations of the anterior cingulate cortices bilaterally and left posterior cingulate cortex were also observed. Other activations that were considered not directly related to response inhibition under study included that in the BA 6, 8, 45, and temporal-occipital regions. These activations are excluded from further discussion in this report. Nevertheless, we speculated that activation of motor speech region on the left side (BA 45) may relate to subvocalization and conforms to the expectation of a left hemispheric dominance pattern of our participants. Residual activations of BA 6 and 8 and that in the temporal and occipital regions may relate to increased task demand in the Incorrect Matching condition. Our ®ndings concur with Casey et al.'s [4] observations that both dorsolateral and orbitofrontal cortices are involved when habitual responses are inhibited. Furthermore, cingulate activations were observed, which in general is consistent with MacDonald et al.'s [13] speculation that both
T.M.C. Lee et al. / Neuroscience Letters 309 (2001) 109±112
111
Fig. 1. Functional maps. Normalized activation brain maps averaged across ®ve subjects demonstrate the statistically signi®cant activations (P , 0:01 uncorrected) in response inhibition activation for correct matching with the activation for incorrect matching removed) when performing on the digit task. Planes are axial sections, labeled with the height (mm) relative to the bicommissural line. L, the left hemisphere; R, the right hemisphere.
prefrontal and cingulate cortices are required for response inhibition. However, generalization of our ®ndings should be done with caution given the small sample size. It is well-known that prefrontal activation is contingent upon task speci®c working memory representation for goal directed information manipulation and integration and programming strategies, rather than a simple re¯ection of working memory load [17]. Speci®cally, activation of the fronto-polar prefrontal region (BA 10) was responsible for holding in place primary goals while still processing secondary goals simultaneously [9]. This matches with the demand of response inhibition studied here because the subjects had to make a correct judgement ®rst as their primary goal while they were required to inhibit the correct judgement and presented the opposite answer as their secondary goal. Activation of the dorsolateral prefrontal region (BA 9 & 46), on the other hand, represented anticipation of performance [18] and cognitive control [13]. The orbitofrontal activation observed may re¯ect an emotional response to the `reward' of task accomplishment [14]. All these functions are essential for ef®cient response inhibition. Activation of the anterior cingulate cortex (ACC) (BA 24/ 32) is likely due to performance [13] as well as con¯ict monitoring by detecting response competition [3]. Indeed, previous studies did show that the ACC was activated not only during erroneous responses but also during correct responses when there was increased response competition. This implies that the ACC detects conditions under which errors are likely to occur rather than errors themselves. In other words, the ACC is involved in monitoring and compensating for errors [3], which is an integral part of response inhibition studied here. Activation of the posterior cingulate (BA 23) regions, on the other hand, is most likely related to the inhibition of previously learned rules and selfmonitoring of random errors [1], which is essential for inhibition of habitual responses.
Previous studies on response inhibition have suggested that the locus of inhibition is in the right prefrontal cortex (see for example ref. [10]). Our observation is more in line with the ®ndings and speculations of Casey et al. [4] and MacDonald et al. [13]. Bilateral activations of prefrontal and cingulated regions tend to support the speculation of a neural network rather than a locus of control for the execution and monitoring of response inhibition. We further speculated that the prefrontal activation may be involved in representing and maintaining the attention for task performance, and the cingulate activation may be involved in evaluative processes, such as monitoring the occurrence of errors or the presence of response con¯ict, which occurs when two incompatible responses are both compelling. This speculation is awaiting veri®cation in future research. [1] Amos, A., A computational model of information processing in the frontal cortex and basal ganglia, J. Cogn. Neurosci., 12 (2000) 505±519. [2] Buchkremer-Ratzmann, I. and Witte, O.W., Extended brain disinhibition following small photothrombotic lesions in rat frontal cortex, NeuroReport, 8 (1996) 519±522. [3] Carter, C.S., Braver, T.S., Barch, D.M., Botvinick, M.M., Noll, D. and Cohen, J.D., Anterior cingulate cortex, error detection, and the online monitoring of performance, Science, 280 (1998) 747±749. [4] Casey, B.J., Trainor, R.J., Orendi, J.L., Schubert, A.B., Nystrom, L.E., Giedd, J.N., Castellanos, X., Haxby, J.V., Noll, D.C., Cohen, J.D., Forman, S.D., Dahl, R.E. and Rapoport, J.L., A developmental functional MRI study of prefrontal activation during performance of a Go-No-Go task, J. Cogn. Neurosci., 9 (1997) 835±847. [5] Dempster, F.N., The rise and fall of the inhibitory mechanism: Toward a uni®ed theory of cognitive development and aging, Dev. Rev., 12 (1992) 45±75. [6] Fuster, J.M., The Prefrontal Cortex: Anatomy, Physiology and Neuropsychology of the Frontal Lobe, Raven Press, New York, 1989, 110pp. [7] Harnishfeger, K.K. and Bjorklund, D.F., The ontogeny of inhibition mechanisms: A renewed approach to cognitive
112
[8] [9] [10]
[11]
[12] [13]
T.M.C. Lee et al. / Neuroscience Letters 309 (2001) 109±112 development, In M.L. Howe and R. Pasnak (Eds.), Emerging Themes in Cognitive Development, Springer-Verlag, New York, 1993, pp. 28±49. Kane, M.L., Hasher, L., Stoltzfus, E.R., Zacks, R.T. and Connelly, S.L., Inhibitory attentional mechanisms and ageing, Psychol. Aging., 9 (1994) 103±112. Koechlin, E., Basso, G., Pietrini, P., Panzer, S. and Grafman, J., The role of the anterior prefrontal cortex in human cognition, Nature, 399 (1999) 48±151. Konishi, S., Nakajima, K., Uchida, I., Kikyo, H., Kameyama, M. and Miyashita, Y., Common inhibitory mechanism in human inferior prefrontal cortex revealed by event-related functional MRI, Brain, 122 (1999) 981±991. Lancaster, J.L., Fox, P.T., Downs, H., Nickerson, D.S., Hander, T.A., Mallah, M.E., Kochunov, P.V. and Zamarripa, B., Global spatial normalization of human brain using convex halls, J. Nucl. Med., 40 (1999) 942±955. Lezak, M.D., Neuropsychological Assessment, 3rd ed., Oxford University Press, New York, 1995, 671pp. MacDonald, A.W., Cohen, J.D., Stenger, V.A. and Carter, C.S., Dissociating the role of the dorsolateral prefrontal
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