Projection of the digit and wrist area of precentral gyrus to the putamen: Relation between topography and physiological properties of neurons in the putamen

Liles, Samuel L.; Updyke, B. V.

doi:10.1016/0006-8993(85)90089-7

Cited by 96 publications

(49 citation statements)

References 23 publications

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“…The superio-inferior gradient, with the face lying inferiorly, foot superiorly, and hand in between, is in good agreement with recent fMRI studies in humans (Gerardin et al, 2003;Lehericy et al, 1998;Scholz et al, 2000) and studies in non-human primates (Alexander and DeLong, 1985;Graybiel, 1991, 1993;Kunzle, 1975;Liles and Updyke, 1985). The anterio-posterior gradient, with the face lying anteriorly, foot posteriorly, and hand in between, is contradictorily reported in literature (Gerardin et al, 2003;Kunzle, 1975;Maillard et al, 2000).…”

Section: Discussionsupporting

confidence: 87%

Combining fMRI and DTI: A framework for exploring the limits of fMRI-guided DTI fiber tracking and for verifying DTI-based fiber tractography results

et al. 2008

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Combining fMRI and DTI: a framework for exploring the limits of fMRI-guided DTI fiber tracking and for verifying DTI-based fiber tractography resultsStaempfli, P; Reischauer, C; Jaermann, T; Valavanis, A; Kollias, S; Boesiger, P Staempfli, P; Reischauer, C; Jaermann, T; Valavanis, A; Kollias, S; Boesiger, P (2008 Combining fMRI and DTI: a framework for exploring the limits of fMRI-guided DTI fiber tracking and for verifying DTI-based fiber tractography results AbstractA powerful, non-invasive technique for estimating and visualizing white matter tracts in the human brain in vivo is white matter fiber tractography that uses magnetic resonance diffusion tensor imaging. The success of this method depends strongly on the capability of the applied tracking algorithm and the quality of the underlying data set. However, DTI-based fiber tractography still lacks standardized validation. In the present work, a combined fMRI/DTI study was performed, both to develop a setup for verifying fiber tracking results using fMRI-derived functional connections and to explore the limitations of fMRI based DTI fiber tracking. Therefore, a minor fiber bundle that features several fiber crossings and intersections was examined: The striatum and its connections to the primary motor cortex were examined by using two approaches to derive the somatotopic organization of the striatum. First, an fMRI-based somatotopic map of the striatum was reconstructed, based on fMRI activations that were provoked by unilateral motor tasks. Second, fMRI-guided DTI fiber tracking was performed to generate DTI-based somatotopic maps, using a standard line propagation and an advanced fast marching algorithm. The results show that the fiber connections reconstructed by the advanced fast marching algorithm are in good agreement with known anatomy, and that the DTI-revealed somatotopy is similar to the fMRI somatotopy. Furthermore, the study illustrates that the combination of fMRI with DTI can supply additional information in order to choose reasonable seed regions for generating functionally relevant networks and to validate reconstructed fibers. A powerful, non-invasive technique for estimating and visualizing white matter tracts in the human brain in vivo is white matter fiber tractography that uses magnetic resonance diffusion tensor imaging. The success of this method depends strongly on the capability of the applied tracking algorithm and the quality of the underlying data set. However, DTI-based fiber tractography still lacks standardized validation. In the present work, a combined fMRI/DTI study was performed, both to develop a setup for verifying fiber tracking results using fMRI-derived functional connections and to explore the limitations of fMRI based DTI fiber tracking. Therefore, a minor fiber bundle that features several fiber crossings and intersections was examined: The striatum and its connections to the primary motor cortex were examined by using two approaches to derive the somatotopic organization of the striatum. First, an fMRI-based somat...

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Section: Discussionsupporting

confidence: 87%

Combining fMRI and DTI: A framework for exploring the limits of fMRI-guided DTI fiber tracking and for verifying DTI-based fiber tractography results

et al. 2008

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“…The excitatory responses followed well the double-cortical stimulation with short intervals (20 -50 ms), suggesting that they are monosynaptic responses. The distribution of the orthodromically activated putaminal neurons corresponds well to that of MI proximal -, MI distal -, and SMAderived corticostriatal terminals reported previously (Künzle 1975;Liles and Updyke 1985;Takada et al 1998a, b;Tokuno et al 1999). The latency of MI-evoked orthodromic responses of putaminal neurons in this study was within the same range as that of corticostriatal-evoked responses in the monkey (Liles 1975; and putamen-evoked antidromic activation of MI neurons (Bauswein et al 1989;Turner and DeLong 2000).…”

Section: Discussionsupporting

confidence: 66%

“…On the other hand, the interneurons are classified into several groups, including parvalbumin (PV)-containing GABAergic neurons and large cholinergic neurons (Bennett and Wilson 2000). The PV-containing GABAergic interneurons especially receive inputs from the cerebral cortex and innervate the projection neurons (Koós and Tepper 1999;Mallet et al 2005;Tepper et al 2008). Thus GABAergic networks in the striatum, comprising feedback inhibition through the axon collaterals of the projection neurons and feedforward inhibition through the GABAergic interneurons (Gage et al 2010), are thought to control the activity of striatal projection neurons.…”

Section: Discussionmentioning

confidence: 99%

“…In the present study, only PANs were studied (see MATERIALS AND METHODS). PANs are originally considered medium, spiny, GABAergic-projection neurons; however, recent studies reported electrophysiologically distinct subtypes of PANs in the striatum (Gittis et al 2010;Mallet et al 2005;Sharott et al 2009). Actually, based on the recent juxtacellular-labeling study of rats, the majority of PANs are medium-sized, spiny GABAergic-projection neurons, whereas a smaller number are GABAergic interneurons, including fastspiking interneurons.…”

Section: Discussionmentioning

confidence: 99%

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Differential activity patterns of putaminal neurons with inputs from the primary motor cortex and supplementary motor area in behaving monkeys

Takara

Hatanaka

Nambu

2011

Journal of Neurophysiology

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Takara S, Hatanaka N, Takada M, Nambu A. Differential activity patterns of putaminal neurons with inputs from the primary motor cortex and supplementary motor area in behaving monkeys. J Neurophysiol 106: 1203-1217, 2011. First published June 8, 2011 doi:10.1152/jn.00768.2010.-Activity patterns of projection neurons in the putamen were investigated in behaving monkeys. Stimulating electrodes were implanted chronically into the proximal (MI proximal ) and distal (MI distal ) forelimb regions of the primary motor cortex (MI) and the forelimb region of the supplementary motor area (SMA). Cortical inputs to putaminal neurons were identified by excitatory orthodromic responses to stimulation of these motor cortices. Then, neuronal activity was recorded during the performance of a goaldirected reaching task with delay. Putaminal neurons with inputs from the MI and SMA showed different activity patterns, i.e., movementand delay-related activity, during task performance. MI-recipient neurons increased activity in response to arm-reach movements, whereas SMA-recipient neurons increased activity during delay periods, as well as during movements. The activity pattern of MI ϩ SMA-recipient neurons was of an intermediate type between those of MI-and SMA-recipient neurons. Approximately one-half of MI proximal -, SMA-, and MI ϩ SMA-recipient neurons changed activities before the onset of movements, whereas a smaller number of MI distal -and MI proximal ϩ distal -recipient neurons did. Movementrelated activity of MI-recipient neurons was modulated by target directions, whereas SMA-and MI ϩ SMA-recipient neurons had a lower directional selectivity. MI-recipient neurons were located mainly in the ventrolateral part of the caudal aspect of the putamen, whereas SMA-recipient neurons were located in the dorsomedial part. MI ϩ SMA-recipient neurons were found in between. The present results suggest that a subpopulation of putaminal neurons displays specific activity patterns depending on motor cortical inputs. Each subpopulation receives convergent or nonconvergent inputs from the MI and SMA, retains specific motor information, and sends it to the globus pallidus and the substantia nigra through the direct and indirect pathways of the basal ganglia. basal ganglia; striatum; motor control; single-unit recording THE PRIMATE STRIATUM, composed of the putamen, the caudate nucleus, and the ventral striatum, is a main input station of the basal ganglia and receives neural signals from wide areas of the cerebral cortex. Every single striatal projection neuron is estimated to receive diverse inputs from ϳ750 to 7,500 cortical neurons (Bennet and Wilson 2000), and thus cortical information is massively integrated within the striatum. The activity of striatal projection neurons is strongly modulated by local interneurons that also receive cortical inputs (Tepper et al. 2008). The projection neurons finally send processed signals to the external and internal segments of the globus pallidus and the substantia nigra pars reticulata through the ...

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“…Anatomical tract-tracing cases were adapted for conformity as described in Fig. 4 from the following with permission: motor (Liles and Updyke 1985), SMA (Inase et al 1999), PFC lp (Selemon and Goldman-Rakic 1985), scg25 (Haber et al 2006), and PFC md (Ferry et al 2000). Original tracings from Ferry et al (2000;PFC md and Fig.…”

mentioning

confidence: 99%

The organization of the human striatum estimated by intrinsic functional connectivity

Choi

Yeo

Buckner

2012

Journal of Neurophysiology

687

658

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Choi EY, Yeo BT, Buckner RL. The organization of the human striatum estimated by intrinsic functional connectivity. J Neurophysiol 108: 2242-2263, 2012. First published July 25, 2012 doi:10.1152/jn.00270.2012.-The striatum is connected to the cerebral cortex through multiple anatomical loops that process sensory, limbic, and heteromodal information. Tract-tracing studies in the monkey reveal that these corticostriatal connections form stereotyped patterns in the striatum. Here the organization of the striatum was explored in the human with resting-state functional connectivity MRI (fcMRI). Data from 1,000 subjects were registered with nonlinear deformation of the striatum in combination with surface-based alignment of the cerebral cortex. fcMRI maps derived from seed regions placed in the foot and tongue representations of the motor cortex yielded the expected inverted somatotopy in the putamen. fcMRI maps derived from the supplementary motor area were located medially to the primary motor representation, also consistent with anatomical studies. The topography of the complete striatum was estimated and replicated by assigning each voxel in the striatum to its most strongly correlated cortical network in two independent groups of 500 subjects. The results revealed at least five cortical zones in the striatum linked to sensorimotor, premotor, limbic, and two association networks with a topography globally consistent with monkey anatomical studies. The majority of the human striatum was coupled to cortical association networks. Examining these association networks further revealed details that fractionated the five major networks. The resulting estimates of striatal organization provide a reference for exploring how the striatum contributes to processing motor, limbic, and heteromodal information through multiple large-scale corticostriatal circuits. somatotopy; limbic network; prefrontal cortex; association cortex; fMRI; functional connectivity; default network ANIMAL STUDIES and human patient cases demonstrate that the basal ganglia are involved in diverse functional domains including movement, cognition, and reward (Alexander et al. 1986;DeLong and Georgopoulos 1981;Haber and Gdowski 2004;MacLean 1972). Providing an anatomical basis for functional diversity, tract-tracing studies show that the basal ganglia are connected to distributed regions of the cerebral cortex through multiple, partially parallel anatomical loops (Alexander et al. 1986(Alexander et al. , 1990. Each loop includes projections from the cerebral cortex, through the basal ganglia, to the thalamus, and back to the cerebral cortex. Cortical efferents to the striatum (the main input nucleus of the basal ganglia) form distinct patterns depending on their cortical origin. The posterior putamen and the dorsolateral anterior putamen receive projections from motor and motor association cortex, the central anterior striatum from cognitive regions including prefrontal cortex, and the ventral anterior striatum from regions associated with the limbic syste...

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Projection of the digit and wrist area of precentral gyrus to the putamen: Relation between topography and physiological properties of neurons in the putamen

Cited by 96 publications

References 23 publications

Combining fMRI and DTI: A framework for exploring the limits of fMRI-guided DTI fiber tracking and for verifying DTI-based fiber tractography results

Combining fMRI and DTI: A framework for exploring the limits of fMRI-guided DTI fiber tracking and for verifying DTI-based fiber tractography results

Differential activity patterns of putaminal neurons with inputs from the primary motor cortex and supplementary motor area in behaving monkeys

The organization of the human striatum estimated by intrinsic functional connectivity

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