Cerebellar contributions to skilled operations in verbal working memory

1. Cerebellar contributions to skilled operations in verbal working memory A.L. Hayter, D.W. Langdon and N. Ramnani Department of Psychology, Royal Holloway University of London, U.K. Introduction Analysis Methods • Scans were analyzed in SPM2. • Preprocessing: • Scans were realigned and normalized to the reference space of the MNI template brain, and then smoothed with a Gaussian kernel (8 mm). • Statistical Analysis: • First-level single-subject analysis: • Four event types were modeled in each subject-specific GLM: 1. Instruction cue (modeled as transient HRF); 2. ADD block; 3. REPEAT block; 4. ERROR block (8 % of all ADD blocks that were excluded from 2 in which participants made errors). At the first level, events were convolved with the canonical HRF and the resulting regressors were incorporated into a subject-specific GLM. Head motion parameters estimated during realignment were incorporated as confounding covariates. The following SPM{t} contrasts were applied: Reciprocal Cortico-Cerebellar Connections The cortico-cerebellar system is composed of multiple, parallel loops. Evidence from non-human primates shows dense projections between the cerebellum and the cortical motor system1, as well as additional projections between the cerebellum and the prefrontal cortex (Walker’s area 462). The latter suggests a role for this system in processing information that may not be directly related to motor control. The motor cortex (area 4) is reciprocally connected with lobules HV, HVI, HVIIB and HVIII of the cerebellar cortex. Prefrontal area 46 is reciprocally connected to vermal and hemispheral parts of lobule VII (see figure 1). In humans, evidence from Diffusion Tractography shows that prefrontal inputs from the prefrontal cortex have selectively evolved3. • 1. ADD > REPEAT • 2. ADD only • 3. REPEAT only • Second-level random effects analysis: • ADD>REPEAT: Group level analyses were conducted by incorporating single-subject contrast images into a one-sample t-test (FWE corrected, p<0.05) • Conjunction: a one-way ANOVA was applied to contrast images 2 and 3 determined at the first level (FWE corrected). Figure 1 Results Information processing in the cerebellar-prefrontal loop Information processing within the cerebellar-prefrontal loop is poorly understood4. Cerebellar theory suggests that cerebellar components of the “motor” loop acquire forward models of cerebral cortical information processing. These aid the automatic execution of processes required for motor control4. This information processing account can be extended to the “prefrontal loop”, such that prefrontal-projecting areas of the cerebellar cortex may acquire forward models of prefrontal information processing. These may play an important role in the rapid and efficient processing of routine cognitive operations. Such processes should therefore activate the cerebellar components of the prefrontal loop4, just as skilled motor control activates cerebellar components of the motor loop5. During scanning, participants scored an average of 97% correct for ADD. There were no errors in the REPEAT condition. Conjunction: Areas commonly activated by ADD and REPEAT included ventral regions of sensorimotor cortex (BA 3, BA 4; see figure 3A) and superior temporal sulcus. These reflect the common auditory processing and speech production demands of both conditions. We additionally report common activity in cerebellar areas known to be interconnected with the primary motor cortex (figure 3B). Working memory related activations in the cerebellum? In this study a demanding verbal working memory task (the Paced Auditory Serial Addition Task; PASAT6), was utilized to isolate activity related to skilled cognitive operations. On the basis of previous work we predicted activity localized to the human homologue of macaque prefrontal area 46 (human area 9/46 of Petrides & Pandya, 19997). Importantly, we also predicted such activity in hemispheral and vermal components Lobule VII of the cerebellar cortex. Figure 3 ADD > REPEAT: Consistent with out prediction, activity was found in areas of the prefrontal cortex, 9/46 (figure 4, A2) and also areas of the cerebellum known to be interconnected with this area in non-human primates (lobule VII; figure 4, B3). Table 1: ADD>REPEAT, 1 sample t-test, FWE Experimental Design The experiment consisted of two phases: Preparation phase: participants practiced a traditional version of the PASAT outside the scanner (they heard 60 numbers consecutively). They performed mental calculations in the manner specified below. Then the participants practiced our variant of the PASAT (see below) within the scanner (2 blocks of experimental and 2 blocks of control trials). Experimental phase: Participants presented with 35 experimental blocks, 35 control blocks and 10 null block, pseudorandomly intermixed. Figure 4 Experimental Timings Experimental Block Instruction Cue Period 5 4 2 6 3 Auditory stimuli “9” “6” “8” “9” Verbal responses 2s 1s 3sTR Conclusions Visual instruction cue Scanner noise (volume acquisition) 1s visual instruction cue jittered over first 9 seconds 5 numbers presented through MRI compatible headphones Two conditions ADD (experimental condition): On presentation of every number (n), that number must be added to the preceding number heard in the sequence (n-1) REPEAT (control condition): Repeat last number heard In ADD and REPEAT, participants were required to speak their answer aloud. Verbal responses were recorded with an MRI compatible microphone. 1s • Activity in the ‘motor loop’: The conjunction across conditions revealed activity related to the common motor demands of both conditions. Such activity was found in ventral regions of the precentral gyrus known to contain representations of facial musculature. This area was co-activated with cerebellar cortical lobule HVI which is known to be interconnected with the motor cortex in non-human primates. • Activity in the ‘prefrontal loop’: • Differential activity between ADD and REPEAT reflected information processing related to the maintenance and manipulation of information in verbal working memory, while controlling for non-specific sensory and motor factors common to both conditions. Such activity was found in prefrontal area 9/46 as reported in several previous studies. • Consistent with our hypothesis, such activity was also found in lobule VII of the cerebellar cortex. • The co-activation of prefrontal interconnected lobule VII of the cerebellum with these areas imply that they act as a functional network involved in abstract cognitive information processing – the ‘prefrontal’ cortico-cerebellar loop. • We propose that circuits in cerebellar cortical lobule VII acquire internal models of prefrontal information processing related to verbal working memory. These may be used in a feed-forward manner during the execution of routine and automatic cognitive operations. • (see Hayter, A.L., Langdon, D.W., & Ramnani, N., “Cerebellar contributions to working memory”. NeuroImage (In press). Jitter 9s15s Figure 2 Data Acquisition 644 EPI images were acquired using a 3T Siemens Trio MRI. 27 transversal slices were collected, TE = 32 s, TR = 3 s, voxel size 3 mm³ + 1mm gap, FoV = 192 x 192, image matrix = 64 x 64 pixels. The scanning sequence lasted 32.5 minutes. T1 structurals were also acquired. Sparse Sampling The requirement to produce an overt verbal response is an important feature of the PASAT that ensures the imposition of relatively high cognitive demands. We used sparse sampling in order to avoid artifacts caused by speech-related head motion (see figure 2). EPI images were acquired rapidly in the first 2 seconds of each TR. Since no data were acquired during the remaining 1s interval, participants could speak without risk of head motion-related artifact. • References • 1. Brodal, P., (1978), Brain: 101,251-283 5. Ito, M., (2005), Progress in Brain Research: 148, 95-109 • Middleton, F.A. & Strick, P.L., (2001), Journal of Neuroscience: 21, 700-712 6. Gronwall, D.M., (1977), Perceptual and Motor Skills: 44, 367-373 • Ramnani, N., et al.., (2006), Cerebral Cortex: 16, 811-818 7. Petrides, M. & Pandya, D.N., (1999), European Journal of Neuroscience: 11, 1011-1036 • Ramnani, N., (2006), Nature Reviews Neuroscience: 7, 511-522